AN ABSTRACT OF THE DISSERTATION OF
Vidyasagar R. Sathuvalli for the degree of Doctor of Philosophy in Horticulture presented on December 16, 2010
Title: Eastern Filbert Blight in Hazelnut ( Corylus avellana ): Identification of New
Resistance Sources and High Resolution Genetic and Physical Mapping of a
Resistance Gene
Abstract approved: _____________________________________________________
Shawn A. Mehlenbacher
European hazelnut, Corylus avellana L., is the only economically important nut crop in the family Betulaceae. One of the threats to the hazelnut industry in the Pacific
Northwest is the fungal disease eastern filbert blight (EFB) caused by the pyrenomycete Anisogramma anomala . Host genetic resistance to EFB identified in the obsolete pollinizer 'Gasaway' has been extensively used in the hazelnut breeding program at Oregon State University. Concern over deployment of a single resistance gene prompted a search for new sources of resistance. Eighty six accessions from ten countries were evaluated for their response to greenhouse inoculation with the pathogen. Nine accessions showed complete resistance. These new sources of EFB resistance have geographically diverse origins and will broaden the genetic base of our
EFB-resistant hazelnut germplasm.
Map-based cloning of the EFB resistance gene from 'Gasaway' hazelnut was initiated by constructing a BAC library for 'Jefferson' which is heterozygous for resistance. The BAC library was constructed using the cloning enzyme MboI and the vector pECBAC1 ( BamH I site). The library consists of 39,936 clones arrayed in 104
384-well microtiter plates with an average insert size of 117 kb and estimated coverage of 12 genome-equivalents.
Chromosome walking initiated with eight RAPD markers closely linked to resistance, and extended with two further rounds of walking identified a total of 93
BACs in the resistance region. A high resolution genetic map of the resistance region was created with 51 markers in a mapping population of 1488 seedlings. In parallel, a physical map was constructed. Analysis indicated that the resistance gene is located in a single contig of three BACs (43F13, 66C22 and 85B7).
Whole BACs identified in the resistance region (< 1cM) were sequenced using an Illumina II x genome analyzer, with multiplexing and barcoded adapters to reduce the cost, and paired-end reads to facilitate de novo sequence assembly. De novo sequence assembly was carried out using the programs Velvet and SOPRA, and the resulting contigs were further aligned using CodonCode software, and generated contig length ranged from 356 bp to 99632 bp. Estimated coverage of the BACs ranged from 64 to 100%. The gene prediction program AUGUSTUS identified 233 genes from these sequences using Arabidopsis as the model. Of these, RNA-Seq data supported 73 genes at a 60% cutoff and 32 at 100% support. The predicted gene sequences were compared with sequences in GenBank using a BLASTP search
(NCBI) and identified two putative genes encoding a p-loop NTPase and F-box super family. Genes in these two superfamilies have defense response properties. Future complementation and mapping studies are essential to confirm which gene confers resistance.
©Copyright by Vidyasagar R. Sathuvalli
December 16, 2010
All Rights Reserved
Eastern Filbert Blight in Hazelnut ( Corylus avellana ): Identification of New
Resistance Sources and High Resolution Genetic and Physical Mapping of a
Resistance Gene by
Vidyasagar R. Sathuvalli
A DISSERTATION submitted to
Oregon State University in partial fulfillment of the requirements for the degree of
Doctor of Philosophy
Presented December 16, 2010
Commencement June 2011
Doctor of Philosophy dissertation of Vidyasagar R. Sathuvalli presented on December
16, 2010.
APPROVED:
Major Professor, representing Horticulture
Head of the Department of Horticulture
Dean of the Graduate School
I understand that my dissertation will become part of the permanent collection of
Oregon State University libraries. My signature below authorizes release of my dissertation to any reader upon request.
Vidyasagar R. Sathuvalli, Author
ACKNOWLEDGEMENTS
I am heartily thankful to my major professor, Dr. Shawn Mehlenbacher for his invaluable mentoring and support throughout this study. His enthusiasm for my research and openness to different technologies facilitated a favorable environment during my study. He is also my best Squash mate and I enjoyed playing Squash with him all the time. My sincere thanks to all my committee members: Dr.Todd C
Mockler, Dr. Nahla V.Bassil, Dr. Ruth C. Martin and Dr. Sabry Elias for their timely suggestions and contributions for my research. Without the guidance and support of my committee members I couldn’t have finished my research on time.
Thanks are in due for Dr. Anita Azarenko, Dr. Tony Chen, Dr. Jim Myers, Dr.
Ryan Contreras and Dr. Sushma Naithani for allowing me to use their equipment. My special thanks to Dr. Mary Slabaugh and Dr. Rich Cronn for teaching me various protocols for my study. Extended thanks are due for Dr. Brian Knaus who is instrumental for my bioinformatics research.
My Sincere thanks to David C. Smith, Cristino Montes, Becky McCluskey, and former lab mate Dr. Kahraman Gurcan for being part of my hazelnut family. Their support throughout my study is priceless. Further, I would like to thanks Dr. Ramesh
Sagili, Wayne Wood, Lee Ann Julson, Gina Hashagen, Viki Meink and all other faculty members in the department of horticulture for their support in various forms.
Finally, I would like to thank all my present and past graduate student colleagues, my friends, Ravindranath Tagore Eluri, Balaji Saireddy, Rajesh Inti, Ravi
Challa and all my family members for making my academic and social life joyful.
CONTRIBUTION OF AUTHORS
Dr. Shawn A. Mehlenbacher was the main designer of the experiments. Dr.
Mehlenbacher also provided facilities and funding.
David C. Smith grafted all the plant materials in the greenhouse for disease evaluation and was involved in field data collection.
Dr. Todd C. Mockler provided RNA-Seq data from ‘Jefferson’ hazelnut in
Chapter 6.
TABLE OF CONTENTS
Page
Chapter 1 INTRODUCTION ………………………………………………………….1
European Hazelnut
…………………………………………………………1
Eastern Filbert Blight of Hazelnut
………………………………………….2
Host Genetic Resistance to Eastern Filbert Blight …………………………5
Hazelnut Breeding at Oregon State University …………………………….6
RAPD Markers in Hazelnut Breeding
……………………………………...7
Plant Disease Resistance Genes ……………………………………………9
Genetic Fine Mapping
…………………………………………………….16
Map-based Cloning
……………………………………………………….18
Development of Molecular Markers from BAC Sequences ………………24
Contig Assembly and High Information Content Fingerprinting ………...30
High-throughput Sequencing Technologies ………………………………31
Genome Sequence Annotation ……………………………………………32
Research Objectives ………………………………………………………38
References ………………………………………………………………...39
Chapter 2 RESPONSE OF HAZELNUT ACCESSIONS TO GREENHOUSE
INOCULATON WITH Anisogramma anomala ………………………….58
Abstract
…………………………………………………………………...59
Introduction ……………………………………………………………….59
TABLE OF CONTENTS (Continued)
Page
Materials and Methods
……………………………………………………61
Plant materials ……………………………………………………...61
Disease inoculation
...………………………………………………61
Disease susceptibility evaluation
...………………………………...63
Description of resistant accessions
...………………………………63
Results and Discussion
……………………………………………………63
References ……………………….………………………………………..73
Chapter 3 A BACTERIAL ARTIFICIAL CHROMOSOME LIBRARY OF
‘JEFFERSON’ HAZELNUT: A RESOURCE FOR FINE-MAPPING
AND MAP-BASED CLONING ….………….………….………….…….75
Abstract
…………………………………………………………………...76
Introduction ……………………………………………………………….76
Materials and Methods ……………………………………………………78
Plant materials
……………………………………………………..78
BAC library construction
…………………………………………..79
Identification of recombinant seedling …………………………….79
Disease Inoculations ……………………………………………….80
Disease Susceptibility evaluation ………………………………….80
Fine mapping with RAPD markers
………………………………...80
Screening of BAC library ………………………………………….81
Results and Discussion
……………………………………………………81
Construction of BAC library ………………………………………81
Fine mapping
………………………………………………………82
Library screening
…………………………………………………..83
Conclusion ………………………………………………………………...83
References ………………………………………………………………...85
TABLE OF CONTENTS (Continued)
Page
Chapter 4 DE NOVO SEQUENCING OF HAZELNUT BACTERIA ARTIFICIAL
CHROMOSOMES (BACs) IN A DISEASE RESISTANCE REGION
USING MULTIPLEX ILLUMINA II x SEQUENCING
…………………87
Abstract
…………………………………………………………………...88
Introduction
……………………………………………………………….88
Materials and Methods ……………………………………………………90
BAC screening and selection ………………………………………90
Preparation of BAC libraries for Illumina sequencing
…………….91
Data analysis and bioinformatics …………………………………..92
Estimating size of BAC inserts …………………………………….93
Results and Discussion ……………………………………………………94
Screening of BAC library ………………………………………….94
Library preparation
………………………………………………...94
Analysis of Illumina reads and barcodes
…………………………..94
BAC sequence assembly …………………………………………...95
Analysis of BAC sequences
………………………………………..96
References
………………………………………………………………...99
Chapter 5 HIGH RESOLUTION GENETIC AND PHYSICAL MAPPING OF THE
EASTERN FILBERT BLIGHT RESISTANCE REGION IN
‘JEFFERSON’ HAZELNUT ( Corylus avellana L.) …………………….102
Abstract
…………………………………………………………………..103
Introduction
……………………………………………………………...104
Materials and Methods
…………………………………………………..106
Plant materials …………………………………………………….106
Disease inoculation and phenotypic assays
………………………107
Pooling and screening of BAC library by PCR
…………………..108
Chromosome walking ………………….…………………………109
BAC end sequencing
……………………………………………...109
High resolution genetic mapping …………………………………109
Fine genetic mapping of the resistance region ……………………112
BAC fingerprinting and contig assembly
…………………………112
TABLE OF CONTENTS (Continued)
Page
Determination of homolog origin
………………………………...113
Results
…………………………………………………………………...113
Chromosome walking and high resolution mapping
……………..113
Fine mapping of EFB resistance region
…………………………..115
Homolog determination and physical map construction
…………116
Discussion
……………………………………………………………….118
References
……………………………………………………………….130
Chapter 6 ANNOTATION OF WHOLE BAC SEQUENCES IN THE EASTERN
FILBERT RESISTANCE REGION FROM ‘JEFFERSON’
HAZELNUT ( Corylus avellana L.) ………………..……………………135
Abstract ………………………………………………………………….136
Introduction ……………………………………………………………...136
Materials and Methods …………………………………………………..138
Plant material ……………………………………………………..138
BAC sequencing and data analysis
……………………………….138
Results
…………………………………………………………………...139
Discussion ……………………………………………………………….140
References ……………………………………………………………….148
Chapter 7 SUMMARY
……………………………………………………………..150
Bibliography
………………………………………………………………………..154
Appendices
………………………………………………………………………….185
LIST OF FIGURES
Figure Page
1.1 Strategy to isolate a gene of interest using map-based cloning
………………….23
1.2 A generalized flow chart of genome annotation
…………………………………34
3.1 DNA of 28 randomly selected BAC clones digested with NotI . Lanes 1 to 14 are from the first ligation and lanes 15-28 are from the second
…………………84
3.2 A genetic linkage map for the eastern filbert blight resistance locus (R-locus) and eight RAPD markers constructed from 1488 seedlings from a cross of hazelnut selections OSU252.146 x OSU414.062
………………………………..84
5.1 Pedigree of hazelnut progeny 07001 used in fine-mapping and disease inoculations ……………………………………………………………………..107
5.2 Map of EFB resistance locus, seven RAPD, two HRM, and one SCAR marker in the hazelnut progeny OSU252.146 x OSU414.062 and its reciprocal ………123
5.3 High-resolution genetic map of the EFB resistance locus, including new markers developed from BAC end sequences, in the hazelnut progeny OSU252.142 x
OSU414.062 and its reciprocal
…………………………………………………124
5.4 Physical map of eastern filbert blight resistance region in ‘Jefferson’ hazelnut
..125
LIST OF TABLES
Table Page
1.1
Objectives of the OSU hazelnut breeding program ……………………………….8
1.2
Cultivars released by the OSU hazelnut breeding program
……………………….8
1.3
Pollinizers released by the OSU hazelnut breeding program
….…………………9
1.4 Cloned plant disease resistance genes
……………………………………………13
1.5 Comparison of next-generation sequencing platforms …………………………..35
1.6 Computational tools for analysis of next generation sequencing data
…………..36
2.1 Response of 52 hazelnut accessions to greenhouse inoculation with
Anisogramma anomala
…………………………………………………………..68
2.2 Response of 34 hazelnut accessions from the Russian Research Institute of
Forestry and Mechanization to greenhouse inoculation with Anisogramma anomala
…………………………………………………………………………..71
2.3 Description of nine hazelnut accessions with complete resistance to eastern filbert blight, and four cultivars from a trial planted in Corvallis, Ore, in 1998
……………………………………………………………………………72
4.1 Primer pairs designed from RAPD markers linked to EFB resistance in hazelnut
…………………………………………………………………………..97
4.2 Barcoded adapters used for multiplex sequencing of 17 hazelnut BACs
……….97
4.3 Analysis of BAC sequencing data from Illumina sequencing …………………...97
4.4 Results of sequencing and assembling 17 BACs identified by probing the BAC library with primer pairs from linked RAPD markers …………………………...98
5.1 Description of new DNA markers for hazelnut in the eastern filbert blight resistance region
………………………………………………………………..126
6.1 Genes in the eastern filbert blight resistance region predicted by
AUGUSTUS
……………………………………………………………………144
6.2 Gene products identified by a BLASTP search
…………...……………………145
LIST OF TABLES (Continued)
Table Page
6.3 Five highest likelihood hits for four predicted genes in Contig 4 ………………147
LIST OF APPENDICES
Appendix Page
A Protocols
………………………………………………………………………….186
B Predicted gene sequences
………………………………………………………...205
C Marker scoring for recombinant seedlings of progenies 07001 and 07002
…..….218
D Images of SCAR markers developed from BAC ends
…………………………...233
E Images of SSCP markers developed from BAC ends ……………………………238
F Images of HRM markers developed from BAC ends ……………….……………240
DEDICATION
EASTERN FILBERT BLIGHT IN HAZELNUT (
):
IDENTIFICATION OF NEW RESISTANCE SOURCES AND
HIGH RESOLUTION GENETIC AND PHYSICAL MAPPING OF
A RESISTANCE GENE
CHAPTER 1
INTRODUCTION
European Hazelnut
The European hazelnut, Corylus avellana L., is one of the world's important nut crops. Also known as filbert, it belongs to the family Betulaceae and the order
Fagales. Turkey is the leading producer with 70% of the world’s production, followed by Italy, Azerbaijan, USA, Georgia, Spain, France and Russia. The United States produces 3-5% of the world hazelnut crop (FAOSTAT, faostat.fao.org) on 12,181 ha in the United States, nearly all in Oregon’s Willamette Valley. The U.S. annual production is 32,000 MT (Oregon Agripedia, 2009). In 2007, FAO listed 30 countries as hazelnut producers, with a total of 567,265 hectares and 776,890 tons produced
(FAOSTAT, faostat.fao.org).
European hazelnuts are deciduous shrubs or small trees native to Europe, the
Caucasus Mountains and Asia Minor. The distribution of European hazelnut is wide, extending from Ireland to Norway to Moscow to the Ural Mountains, through the
Caucasus to northwestern Iran, to Lebanon, and across the Mediterranean Sea to the
Iberian Peninsula (Mehlenbacher, 2009). The cultivated European hazelnut is a shrub of temperate climates (Tombesi, 1991) with most of the commercial production
2 located near large bodies of water with moderate temperatures in winter and summer, and high humidity during mid-winter bloom (Mehlenbacher, 2009). Cold-hardiness is rarely a concern in the major production areas as some cultivars can resist temperatures down to -15 o
C to -18 o
C without considerable damage (Krpina et al.,
1992; Fideghelli and De Salvador, 2009). World European hazelnut production is based primarily on selections from the wild (Mehlenbacher, 2009).
Eastern Filbert Blight of Hazelnut
The first hazelnut tree was planted in Oregon sometime between 1854 and
1857 by a retired sailor in Scottsburg, Douglas County, and the first commercial hazelnut orchard in Oregon was planted in 1905 by George Dorris on five acres near
Springfield, Ore. The area under cultivation increased until eastern filbert blight
(EFB) caused by the pyrenomycete Anisogramma anomala (Peck) E. Müller was discovered in Clackamas County in 1986.
Eastern filbert blight was first diagnosed in the Pacific Northwest in 1970 after being noticed in 1968 by a grower in western Washington (Davison & Davidson,
1973). EFB was first found in Oregon’s Willamette Valley in 1986 (Pinkerton et al.,
1992); the epidemic continued to spread southward at an average rate of 2 to 3 km per year (Johnson et al., 1996) and is now firmly established in the Willamette Valley.
Currently, more than 60-75% of Oregon’s hazelnut orchards are affected or in close proximity to diseased orchards (Pscheidt, Pers. Comm.). In September 2004, EFB was
3 discovered near Corvallis, Ore. It now poses problems for genetic conservation of hazelnuts at the USDA-ARS National Clonal Germplasm Repository (NCGR).
The pathogen was first described by Peck in 1875, and given the name
Diatrype anomala , later renamed as Anisogramma anomala (Peck) by Müller and von
Arx in 1962. The fungus is an obligate biotrophic parasite of the wild American hazelnut, Corylus americana Marsh., on which it produces very small cankers. It infects several other species of Corylus including the commercially grown European hazelnut where it can produce very large stem cankers. Taxonomically, A. anomala is in the class Ascomycetes, subclass Pyrenomycetes, order Diaporthales and family
Gnomoniaceae (Barr, 1978; Barss, 1921).
The life cycle of A. anomala is well-documented and the details have been posted on the web at http://oregonstate.edu/dept/botany/epp/EFB/. The fungus has a two-year life cycle (Pinkerton et al., 1995) which begins in the spring with the release of ascospores, the infectious propagules, from the perithecia. The ascospores are forcibly ejected from the swollen, hydrated perithecia within stromata and are carried away by wind-driven rain or are splash-dispersed (Pinkerton et al., 1998a), infecting young tissues from spring to mid-summer. Although new infections can occur from spring through summer, most infections occur in the spring after budbreak and during shoot elongation, as the germinating hyphae can only penetrate newly developing tissue (Stone et al., 1992; Johnson et al., 1994). Following infection, the hyphae of A. anomala colonize the vascular tissue, especially the phloem, cambium, and the outermost layer of xylem (Stone et al., 1992; Johnson et al., 1994, 1996). Mycelial
4 growth in the vascular tissue continues through the summer without showing obvious symptoms of disease (Gottwald and Cameron, 1980; Pinkerton et al., 1998a, 1998b). If the infected tree goes dormant and undergoes a period of chilling, fungal stroma appear 13 to 16 months after initial infection in sunken perennial cankers on infected limbs (Gottwald and Cameron, 1980). The stroma contain the ascospores. The maturation of two-celled ascospores begins in perithecia in August and the life cycle continues with new infections following rain and budbreak. Most cankers appear 13-
16 months after infection, although occasionally an additional year is required (25-28 months) (Pinkerton et al., 1993).
Control measures for EFB include vigorous scouting and pruning of the infected trees below the cankers, usually several inches below the last cankered area
(Pscheidt, 2006) and routine fungicide applications especially at budbreak and during growth of new shoots (Johnson et al., 1993; Johnson et al., 1994). Various kinds of fungicides have been registered for use. Most common are chlorothalonil and strobilurin fungicides, and copper hydroxide. None of these protective chemicals are completely effective (Pscheidt, 2006). Present recommendations include four spray applications at two-week intervals starting at budbreak. This is the eight-week window during which young shoots should be covered with fungicide (Pscheidt,
2006). Because of environmental concern over using fungicides and the high cost incurred, host genetic resistance is the most desirable and economical means of controlling EFB (Mehlenbacher, 1994).
5
Host Genetic Resistance to Eastern Filbert Blight
Complete resistance to eastern filbert blight was first discovered in 1975 in
‘Gasaway’, an obsolete pollinizer that was found free of symptoms in a heavily infected ‘DuChilly’ orchard (Cameron, 1976). The resistance from ‘Gasaway’ is controlled by a dominant allele at a single locus (Mehlenbacher et al., 1991). This resistance has been extensively used in the hazelnut breeding program at Oregon State
University (OSU). The resistance of new cultivars 'Jefferson', 'Santiam' and 'Yamhill' is from ‘Gasaway’. Concern over the breakdown of a single resistance gene
(Osterbauer et al., 1997) offers an incentive to explore for new sources of resistance to eastern filbert blight.
Greenhouse inoculation studies have identified several sources of resistance, both qualitative and quantitative. The EFB resistance sources include accessions within Corylus avellana , representatives of other Corylus species and interspecific hybrids (Sathuvalli, 2007; Lunde, 1999; Lunde et al., 2000; Chen et al., 2007).
Greenhouse inoculation studies with various isolates of Anisogramma anomala at Rutgers University (New Jersey) showed infection of 'Gasaway' by an isolate from
Michigan (Molnar, 2006; 2010). This emphasizes the importance of using more than one source of resistance in breeding. Efforts are underway in the OSU hazelnut breeding program to identify additional sources of resistance, study their genetic control and use them in breeding either singly or through pyramiding of resistance genes. Marker-assisted selection is used to identify seedlings likely to carry 'Gasaway' resistance, and would play a prominent role in pyramiding.
6
Hazelnut Breeding at Oregon State University
The OSU hazelnut breeding program was established in 1969 to develop cultivars for the Oregon hazelnut industry. The breeding program has two major thrusts: suitability to the blanched kernel market and resistance to EFB
(Mehlenbacher, 2009). A complementary hybridization approach is used for this clonally propagated species. The objectives of the program are listed in Table 1.1.
For kernel quality, the Italian cultivars 'Tonda Gentile delle Langhe' and 'Tonda di
Giffoni' set the standard (Mehlenbacher, 2009). Since the start of the breeding program, many improved cultivars and pollinizers resistant to EFB have been developed (Tables 1.2 and 1.3).
In addition to applied breeding, genetic studies are conducted. Many of these studies involve DNA markers. A genetic linkage map was constructed using RAPD and SSR markers (Mehlenbacher et al., 2006), and DNA markers linked to various sources of EFB resistance have been identified (Davis et al., 1998; Mehlenbacher et al., 2004; Sathuvalli, 2007). Some 230 microsatellite markers have been developed for hazelnut (Boccacci et al., 2005; Bassil et al., 2005a, 2005b; Gurcan et al., 2010a,
2010b) and most have been placed on the linkage map. Molecular markers linked to the sporophytic incompatibility locus have been identified (Bassil and Azarenko.,
2001; Pomper et al., 1998) and new alleles have been identified using florescence microscopy (Mehlenbacher, 2009).
7
RAPD Markers in Hazelnut Breeding
In hazelnuts, RAPD markers linked to EFB resistance were identified, and are suitable for use in marker-assisted selection (MAS) (Davis and Mehlenbacher, 1997;
Mehlenbacher et al., 2004). Davis and Mehlenbacher (1997) identified five RAPD markers linked to the 'Gasaway' resistance gene in the cross 'Willamette' x VR 6-28.
One of these markers (UBC 152-800) was found to be robust under different amplification conditions and has been extensively used for MAS. Mehlenbacher et al.
(2004) identified 21 additional RAPD markers linked to the ‘Gasaway’ resistance.
These markers supplement and add precision to other methods for testing eastern filbert blight susceptibility and have potential application for MAS. In addition to
UBC 152-800, marker UBC 268-580, which flanks the resistance locus on the opposite side, is being used in MAS. Additionally, marker AA12-850, which cosegregates with resistance, is used to confirm the presence of resistance in advanced selections. Other RAPD markers identified are less suitable for MAS because of their sensitivity to changes in primer or MgCl
2
concentration, the long time required for electrophoresis to separate bands of similar size, deviation from the expected 1:1 ratio in some segregating populations, or difficulty in scoring (Mehlenbacher et al., 2004).
Sathuvalli (2007) identified RAPD markers linked to EFB resistance from three different sources: 'Ratoli' from Spain, OSU 408.040 from Minnesota (USA), and OSU
759.010 from the Republic of Georgia. Of these, OPG17-800 for 'Ratoli' resistance,
UBC 538-780R and OPAJ01-290 for OSU 408.040 resistance, and UBC 695-1800,
UBC 373-700, UBC 349-450 for OSU 759.010 resistance are currently used for MAS.
Table 1.1
Objectives of the OSU hazelnut breeding program.
Blanched kernel market (for chocolate, pastries)
1. Bud mite resistance
2. Round nut shape
3. High percent kernel
4. Precocity
5. High yield
6. Easy pellicle removal
7. Few defects
8. Early maturity
9. Free-falling nuts
Resistance to eastern filbert blight (EFB)
1. Simply inherited resistance (e.g. ‘Gasaway’)
2. Quantitative resistance (e.g. ‘Tonda di Giffoni’)
1
2
3
4
Table 1.2
. Cultivars released by the OSU hazelnut breeding program
S.No Cultivar Name Year of
Release
Resistance to
EFB
5
6
7
Willamette
Lewis
Clark
Rosita*
Santiam
Sacajawea
Yamhill
1990
1997
1999
1999
2005
2006
2008
Quantitative
Quantitative
Quantitative
Quantitative
Complete
Quantitative
Complete
8
9
Jefferson
Red Dragon*
2009
2009
10 Tonda Pacifica 2010
* Ornamental red leaf hazelnut cultivar
Complete
Complete
Susceptible
8
9
2
3
4
5
Table 1.3
. Pollinizers released through hazelnut breeding program at OSU
S.No Cultivar Name Year of Resistance to
1 VR4-31
Release
1990
EFB
Complete
VR11-27
VR20-11
VR23-18
Gamma
1990
1990
1990
2002
Complete
Complete
Complete
Complete
6
7
8
9
Delta
Epsilon
Zeta
Eta
10 Theta
2002
2002
2002
2009
2009
Complete
Complete
Complete
Complete
Complete
Plant Disease Resistance Genes
Plants utilize various defense mechanisms (both passive and active) to counter pathogen attack. Often these mechanisms are controlled by resistance genes ( R genes) that confer high levels of resistance but sometimes only to specific pathogen genotypes. These genes are frequently used in disease resistance breeding. More than
55 R genes have been cloned from different monocot and dicot plant species (van
Ooijen et al., 2007; Martin et al., 2003). These R genes confer resistance to different pathogens and have been assigned to groups based on similarity in their DNA sequences. Many R genes have nucleotide binding site (NBS) or kinase domains.
These conserved elements encode cell receptors that detect and/or interact with products of specific avirulence ( Avr ) genes in the pathogen. Recognition activates a signal transduction pathway that leads to resistance. The avirulence proteins and elicitors are generally not conserved between the species or even between two isolates of the same pathogen (van Ooijen et al., 2007). Thus the interaction between the
10 specific plant R gene and specific Avr gene is one-to-one, and thus it is called genefor-gene resistance. Once the R gene recognizes the Avr proteins from the pathogen, defense responses are triggered which are often associated with the death of the first cell or cells infected and the local accumulation of antimicrobial compounds. This is called a hypersensitive response (HR) and it restricts proliferation of the pathogen.
Based on the encoded conserved elements, R genes have been assigned to different classes (Hulbert et al., 2001; Martin et al., 2003; van Ooijen et al., 2007;
Kozjak et al., 2009). The vast majority of cloned R genes encode NBS-LRR proteins.
These proteins have a central nucleotide-binding (NB) subdomain as part of a larger entity called the NB-ARC domain which is similar to the domain present in the human apoptotic protease-activating factor 1 (APAF-1), R proteins, and the CED-4 protein of
Caenorhabditus elegans (van Ooijen et al., 2007, van der Biezen., 1998). A second domain, a leucine-rich repeat (LRR) domain, lies C-terminal to the NB-ARC domain.
The LRR domain is sometimes followed by an extension of variable length. These
NBS-LRR R genes are abundant in plant genomes, comprising an estimated 1% of the genes in the Arabidopsis genome (Meyers et al., 1999). NBS-LRR R proteins can be further divided based on the domain present in their N-termini. The N-terminal domain can be either a TIR domain which shows homology to a protein found in the
Drosophila Toll and human Interleukin-1(IL-1R) receptor domains (Whitham et al.,
1994) or a non-TIR protein containing predicted coiled coil structures or an extended coiled-coil domain. The former R genes are referred to as TIR-NBS-LRR or TNL proteins (TNL class) and the later are referred to as non-TIR-NBS-LRR proteins or
11
CC-NBS-LRR or CNL proteins (CNL class), respectively (van Ooijen et al., 2007).
Although both TNL and CNL classes of NBS-LRR R genes are involved in pathogen recognition, the two subfamilies are distinct in sequence and in signaling pathways and further phylogenetic analyses of these two classes using their NB-ARC domain revealed separate clustering of these classes (McHale et al., 2006). The separate clustering of TNL and CNL classes of NBS-LRR R proteins is further evidenced from the complete absence of TNL class R proteins in cereal species suggesting that the early angiosperm ancestors had few TNLs and that these were lost in the cereal lineage (McHale et al., 2006). Other major classes of R genes are the Receptor-like protein (RLP) class and the Receptor-like kinase (RLK) class. These RLP and RLK classes of R proteins span the plasma membrane and contain an extracellular leucine rich repeat (LRR) domain. In addition to RLP and RLK, other classes of R genes include protein kinases, toxin reductases, membrane proteins and unique classes.
Cloned plant disease resistance genes are listed in Table 1.4.
Resistance gene analogs (RGAs), identified by sequence similarity of certain functional R domains (e.g. NB domains, LRR domains, etc) through PCR and cloning approaches, tend to occur in clusters and often map to major resistance genes or QTLs.
Specific RGAs can be identified and used as molecular markers to investigate plants with different levels of disease resistance. RGA markers associated with resistance may be used in marker-assisted selection and help locate the genes or genomic regions responsible for this resistance. Baldo et al. (2009) used an RGA approach in the
12
Rosaceae to tag resistance regions and also to identify potential parents in the germplasm collection.
In plant breeding, genetic markers can increase the efficiency of selection for disease resistance, especially when resistance has a low heritability as for Fusarium head blight and cereal cyst nematode resistance in wheat. Markers are also useful for pyramiding genes, and to supplement disease screening methods that are slow or laborious. For eastern filbert blight in hazelnut, the time from the initial inoculation to expression of disease symptoms is > 16 months. MAS also allows selection for resistance in the absence of the pathogen, and thus avoids its spread. In self-pollinated crops, markers allow accelerated recovery of the recurrent parent in backcrossing
(Anderson, 2003).
The hazelnut-EFB pathosystem involves a perennial tree and a canker disease, for which a gene-for-gene relationship has not been demonstrated and typical hypersensitive responses are not seen. The cloning and sequencing of the most commonly used EFB resistance gene could provide new insights into the mechanism of resistance to this perennial canker disease.
13
14
15
16
Genetic Fine Mapping
Genetic linkage maps are useful in gene identification, study, utilization and isolation, and provide markers for use in MAS and whole genome selection in breeding programs. Genetic mapping involves the identification of markers that are linked to the trait of interest. With the advent of recombinant DNA technology and the availability of different kinds of molecular markers, fine mapping has become possible in any plant that can be crossed. Isozymes are limited in number, seldom tightly linked to the locus of interest and often difficult to score. In contrast, DNAbased molecular markers have several advantages which depend on the type of marker
(SSR, SNP, SSCP, RAPD, RFLP, etc.). According to Falconer and Mackey (1996), the ideal type of genetic marker should be abundant, neutral with respect to the trait of interest and to reproductive fitness, and they should be co-dominant. Further the markers should be highly polymorphic, easy to score, and amenable to highthroughput technologies. In addition to the above characters the markers should lack issues with penetrance and or epistasis so that they can be scored easily across different progenies.
A genetic fine map involves identification of tightly linked markers that flank the gene of interest usually at less than one centiMorgan. The availability of a fine genetic map is the basis for the successful isolation of a desired gene through a mapbased gene isolation strategy. Fine mapping requires a large population (usually thousands) that has been accurately phenotyped and genotyped, so that every recombination event can be scored and eventually mapped. The first step in fine
17 mapping involves construction of a low-resolution map for the region (usually 5-10 cM) that contains the locus of interest using a small number (100-200) of plants. The second step involves screening thousands of plants with the closest flanking markers identified in the low-resolution population. The screening of thousands of plants with the flanking markers allows identification of plants that show recombination between them. Only these recombinants are retained for phenotyping and further molecular marker development (Krattinger et al., 2009). In rice, Joen et al. (2003) used recombinant seedlings to finely map the Pi5 ( t ) locus for blast resistance. Also in rice,
Yang et al. (2004) developed a high-resolution genetic map at the BPh15 locus for brown planthopper resistance using 9472 F
2
individuals. In barley, the gene responsible for six-row spikes was mapped to a 0.07 cM target interval using more than 4900 plants (Komatsuda et al., 2007). In apple, Patocchi et al. (1999a) used 758 plants in many progenies segregating for the Vf gene that confers resistance to apple scab to construct a fine map of the region.
Several problems are encountered when attempting to finely map the region around a plant gene of interest. According to Bennetzen (2000), the most common problems associated with fine mapping are (i) plants have relatively large genomes and hence most linked markers may be many cM away from the targeted gene, (ii) recombination is relatively rare in plants and thus requires investigation of hundreds to a few thousand sexual progeny to map markers to a resolution of 0.1 to 1.0 cM, (iii) low levels of polymorphism in the mapping population will not allow placement of the most tightly linked markers. To avoid these problems, it is essential to have a large,
18 polymorphic mapping population from crosses of unrelated or distantly-related parents, and to utilize various types of markers to identify those polymorphisms at the single nucleotide level.
In hazelnut, Mehlenbacher et al. (2004, 2006) created a low-resolution genetic map for eastern filbert blight resistance from 'Gasaway' using RAPD markers. The mapping population of 144 seedlings was from a cross of OSU 252.146 (susceptible) x
OSU 414.062 (resistant). A total of 36 markers linked to resistance were identified
(Mehlenbacher et al., 2004, 2006). These markers provided a starting point for construction of a high-resolution genetic map of the region, and can eventually lead to cloning and sequencing of the gene of interest using chromosome walking techniques.
The development of additional markers tightly linked to resistance will increase the precision of MAS.
Map-based Cloning
Map-based cloning is a strategy to clone genes of interest without prior knowledge of the gene product (Krattinger et al., 2009). An overview of the mapbased cloning procedure for the isolation of a gene is presented in Figure 1.1.
According to Tanksley et al. (1995), map-based cloning has only two requirements: (i) that individuals within the population have genetically based differences in the trait of interest; and (ii) that the gene responsible for this difference can be mapped to a chromosomal position adjacent to segments of DNA that have already been sequenced
(e.g. DNA markers). Additional requirements for successful map-based cloning are a
19 suitable fine-mapping population that segregates for the trait of interest and a combination of phenotypic scores and molecular marker data that leads to a precise genetic map (Krattinger et al., 2009). Chromosome walking and chromosome landing are the two procedures that are used as part of map-based cloning strategy. For chromosome walking and chromosome-walking strategies, large insert libraries such as Bacterial Artificial Chromosome (BAC), Yeast Artificial Chromosome (YAC), and
Fosmid libraries are essential. Chromosome walking involves utilization of the most closely linked markers in the initial probing of the library, and identification of a set of overlapping fragments (BACs, YACs, etc.). The ends of these fragments are sequenced. This continues until one arrives at another molecular marker known to be situated on the opposite side of the target gene, or until there is an indication that the walk has actually passed over the target gene (Tanksley et al., 1995). Chromosome walking is tedious and time-consuming, with most of the time spent probing and identifying positive clones.
The chromosome landing procedure is slightly different from chromosome walking. Chromosome landing involves screening of the initial segregating population with a huge number of molecular markers and identifying markers that are very close physically to the target gene. Tightly linked markers may identify a single clone or group of clones that contains the gene of interest.
With the recent surge in sequencing technologies, other methods are being used in map-based cloning:
20
(i) Microarray-based rapid cloning: Gong et al. (2004) used this technology to effectively clone an ion accumulation deletion mutant in Arabidopsis thaliana.
This strategy uses masking bulked segregant analysis
(Michelmore et al., 1991) to mask unrelated deletions, thus allowing identification of target deletions by microarray hybridization of pooled genomic DNA from both wild type (WT) and mutant F
2
populations.
(ii) GoldenGate assay based cloning: In soybean, Hyten et al. (2009) used bulked segregant analysis and the GoldenGate high throughput SNP detection assay to locate the RPP3 locus that confers resistance to soybean rust.
These two technologies require having a whole genome sequence and are currently efficient only for the model species or crops with a sequenced genome. With nextgeneration sequencing technologies, genome sequences of many crops are becoming available, and draft genome sequences will become available for additional species in the near future. Thus the two strategies listed above could become more common in map-based gene cloning.
Though map-based cloning is a conceptually straightforward approach, the procedure is burdened with a number of difficulties such as large genome size and the resulting need for many chromosomes walks, the inability to perfectly relate the genetic distance to the physical distance, a high frequency of repetitive DNA, and large-insert libraries whose inserts contain chimeric clones or clones in which the fragments have been rearranged (Tanksley et al., 1995). In spite of difficulties associated with map-based cloning; many genes have been isolated using this
21 procedure. Nearly half of the genes cloned using a map-based strategy confer resistance to biotrophic pathogens (Table 1.4).
The map-based cloning approach in clonally propagated crops is slightly different from that in self-pollinated crops, as in the former case the library is constructed from a heterozygous individual rather than a homozygous line. A heterozygous plant has two homologous chromosomes that differ significantly in their
DNA sequence and often have similar non-polymorphic sequences in the region of interest. In clonally propagated crops, map-based gene cloning of a disease resistance gene involves two simultaneous chromosome walks and the construction of two separate contigs. One contig is for the region that contains the allele for resistance, and the other contains the allele for susceptibility. In spite of the pitfalls associated with the map-based cloning approach, the strategy has been successfully employed in many clonally propagated crops. In citrus, Yang et al. (2001) finely mapped the region around the Ctv locus that confers resistance to citrus tristeza virus using a total of 554 seedlings from 10 populations segregating at the Ctv locus. Chromosome walking was carried out and a 1.2 Mb contig of 61 BAC clones was constructed. The fine map spanned from 1.2 cM to the left and 0.6 cM to the right of the Ctv locus. The
Ctv locus was later assigned to a 300 kb contig composed of four BACs. In apple,
Patocchi et al. (1999a, 1999b) initiated a chromosome walk at the apple scab resistance gene ( V f
) using flanking RAPD markers M18 and AL07. More than 2000 seedlings from different progenies segregating for scab resistance were phenotyped for disease response and used in the walk. After nine chromosome walking steps, the V f
22 locus was assigned to a contig of five clones spanning 350 kb. Vinatzer et al. (2001) found four sequences in this 350 kb that were similar to the Cf gene in tomato, and confirmed that one of them ( HcrVf2) conferred scab resistance in transgenic apples
(Belfanti et al., 2004). Other examples of successful map-based cloning in clonally propagated crops include, the RB gene from Solanum bulbocastanum that confers resistance to late blight resistance in potato (Bradeen et al., 2003; Song et al., 2003), and the Ma locus for resistance to root knot nematode in Myrobalan plum ( Prunus cerasifera L.) (Claverie et al., 2004). In rose, three markers derived from BAC end sequences about 100 kb apart co-segregated with Rdr 1 that confers resistance to blackspot (Kaufmann et al., 2003).
23
Fig. 1.1. Strategy to isolate a gene of interest using map-based cloning (adapted from
Krattinger et al., 2009).
24
Development of Molecular Markers from BAC Sequences
C hromosome walking is initiated by using markers that flank the gene of interest to probe the BAC library, and then sequencing the ends of the identified
BACs. The markers developed from the BAC end sequences are most commonly are
Sequence Characterized Amplified Region (SCAR) and Simple Sequence Repeat
(SSR) markers. While these markers may reveal polymorphisms between the resistant and susceptible parents, a lack (or apparent lack) of polymorphism at newly developed marker loci can be encountered. In the latter situation, additional marker technologies that may be useful include: Cleaved Amplified Polymorphic Sequence (CAPS),
Single Strand Conformational Polymorphism (SSCP), Thermal Gradient Gel
Electrophoresis (TGGE), Denaturing Gradient Gel Electrophoresis (DGGE), Cleavase
Fragment Length Polymorphism (CFLP) and High Resolution Melting (HRM) markers. These marker types depend on Single Nucleotide Polymorphisms (SNPs) but can generally be investigated without sequence information. Once the sequence is known and a SNP identified, new markers that target the SNP can be developed.
SNPs in plant genomes are useful for marker development if different sequence alternatives (alleles) exist in the population, and the least frequent allele is present at a frequency ≥ 1% (Brooks, 1999). Several types of markers that can be developed from
BAC end sequences are described in detail below.
Microsatellite or Simple Sequence Repeat (SSR) markers are ubiquitous sets of tandemly repeated DNA motifs that are generally composed of di-, tri-, tetra- and sometimes greater perfectly repeated nucleotide sequences (Tautz and Renz, 1984).
25
SSRs are highly polymorphic (Zane et al., 2002), highly abundant and randomly dispersed throughout the genome. SSRs are co-dominant, locus-specific and often have many alleles per locus. Additionally, SSRs are highly reproducible (Kelly et al.,
1998), amenable to automation and are easily shared among labs as primer sequences, providing common markers for collaborative research (Powell et al., 1996).
Development of SSR markers de novo involves high cost and labor-intensive methods. Unlike arbitrary markers, each SSR must be cloned and sequenced before a useful marker can be generated (Reiter, 2001). A microsatellite-enriched genomic
DNA library is prepared by hybridizing genomic DNA with microsatellite probes and then cloning and sequencing individual clones. With the advances in next-generation sequencing technologies, it is possible to sequence fragmented microsatellite libraries, prepared by hybridizing the genomic DNA libraries to specific microsatellite probes, by 454 or Illumina paired-end technologies. The sequences obtained by this method provide many microsatellite loci that can be effectively used as markers after designing the appropriate primers (Cronn et al., Pers. Comm.). SSRs are becoming the markers of choice for genetic analysis.
SSRs can also be identified through BAC end sequencing. Some BAC end sequences will contain nucleotide repeats that can be converted into SSR markers.
SSRs have been identified from BAC ends in many plants, including soybean, Glycine max (L.) Merr. 'Williams 82' (Shoemaker et al., 2008), Musa acuminata (Cheung and
Town, 2007), tomato, Solanum lycopersicum , formerly Lycopersicon esculentum
26
(Ohyama et al., 2009), apple, Malus × domestica Borkh (Han and Korban, 2008), and carrot, Daucus carota (Cavagnaro et al., 2009
In hazelnut, SSRs have been developed (Bassil et al., 2005a, 2005b; Boccacci et al., 2005; Gürcan et al., 2009, 2010a, 2010b), placed on the linkage map of
Mehlenbacher et al. (2006), and used to fingerprint cultivars (Boccacci et al., 2006;
Gökirmak, 2006). SSR markers developed in hazelnuts were also transferable across genera in the Betulaceae (Gürcan and Mehlenbacher, 2010). SSR markers can be used to probe the BAC library and obtain the sequence of the adjacent region.
Sequence Characterized Amplified Region (SCAR) markers are PCR-based and commonly developed from Random Amplified Polymorphic DNA (RAPD) or
Amplified Fragment Length Polymorphism (AFLP) markers. Marker termini are sequenced and longer primers (22-34 bases) are designed for specific amplification of a particular locus (Paran and Michelmore, 1993). SCAR markers are similar to
Sequence Tagged Site (STS) markers (Olson et al., 1989) in construction and application. SCAR markers are usually dominant (occasionally co-dominant) and are highly reproducible compared to RAPD and AFLP markers. The polymorphism is usually scored as present or absent, but differences in PCR product length are also possible. Once we have the sequence information, the development of SCAR markers is relatively easy. Unfortunately, a high percentage of the SCAR markers developed from polymorphic RAPD or AFLP markers are monomorphic. Other techniques, including CAPS and SSCP markers, allow visualization of polymorphism based on single nucleotide differences.
27
For Cleaved Amplified Polymorphic Sequence (CAPS) markers, polymorphism is due to the presence of a restriction site in one of the two sequences
(Konieczny and Ausubel, 1993). The PCR products are digested with a restriction enzyme and then separated by electrophoresis (Jarvis et al., 1994). Often a battery of restriction enzymes is used to individually digest the PCR products, and polymorphic combinations are scored as markers. CAPS markers are co-dominant.
Single Strand Conformation Polymorphism (SSCP) markers, also called single strand chain polymorphism markers, result from conformational differences of single-stranded nucleotide sequences of identical length but differening sequences, as revealed under certain experimental conditions. The SSCP technique is easy and inexpensive compared to other SNP detection methods. SSCPs have been used for gene mapping, using EST-derived SNP markers, in various plant species such as barley ( Hordeum vulgare L.) (Tondelli et al., 2006), wheat ( Triticum aestivum L.) (Yu et al., 2008; Chao et al., 2009), pearl millet ( Pennisetum glaucum (L.) R.Br.) (Bertin et al., 2005), common bean ( Phaseolus vulgaris L.) (Galeano et al., 2009), Cuphea
(Slabaugh et al., 1997), cassava ( Manihot esculenta Crantz) (Castelblanco and
Fregene, 2006), grapevine ( Vitis vinifera L.) (Salmaso et al., 2004) and Pinus species
(Plomion et al., 1999).
Denaturing Gradient Gel Electrophoresis (DGGE) markers are due to SNPs that result in differential denaturing characteristics of the DNA and are visualized by separating PCR products (Myers et al., 1987). During DGGE, PCR products encounter increasingly higher concentrations of a chemical denaturant (usually urea)
28 as they migrate through a polyacrylamide gel. Upon reaching a threshold denaturant concentration, the weaker melting domains of the double-stranded PCR product begin to denature at which time migration slows dramatically (Ercolini, 2004). Sequences of
DNA with SNPs will denature at different denaturant concentrations resulting in a pattern of bands that can be visualized and scored for polymorphism.
Thermal Gradient Gel Electrophoresis (TGGE) is similar to DGGE but the polymorphism is visualized on a non-gradient gel by applying a temporal temperature gradient during the course of electrophoresis (Riesner et al., 1990). PCR products have different melting behavior due to sequence variations (SNPs). The PCR products will stop migrating at different positions in the gel, and the polymorphism is visualized accordingly.
Both DGGE and TGGE are based on differences in the stability of the DNA under specific gel conditions and are technically quite demanding, thus requiring highly controlled conditions. Both DGGE and TGGE are extensively used in microbial ecology as part of genetic fingerprinting and phylogenetic studies (Muyzer and Smalla, 1998; Marzorati et al., 2008).
Cleavase Fragment Length Polymorphism (CFLP) involves detection of sequence variation (usually SNPs) based on cleavage patterns generated by the structure-specific thermostable endonuclease Cleavase
®
I. (Brown et al., 1996). The
PCR products are differentially labeled with biotin, fluorescein or JOE at their 5' ends, heat-denatured, and then cooled to a preoptimized temperature. The labeled PCR products are cleaved using Cleavase I enzyme and the cleavage products are separated
29 on a denaturing polyacrylamide gel. In this method not only are the sequence differences between the two DNA fragments revealed but the patterns also reflect the location of the sequence differences identified.
High-Resolution Melting (HRM) is a post-PCR technique that can be used for high-throughput mutation scanning and genotyping (Gundry et al., 2003). HRM detects the melting behavior of PCR amplicons in the presence of a saturating fluorescent dye and discriminates between genotypes on the basis of SNPs, INDELs
(insertions or deletions) or SSR variation (Wu et al., 2010; Studer et al., 2009). The shape of the resulting melting curve depends on the reaction specificity and the thermal stability of a PCR amplicon, which is determined by its length, GC content and base sequence (Studer et al., 2009). In the HRM analysis, the differences between homozygous samples can be distinguished by a simple shift in the melting temperatures ( T m
), whereas heterozygous samples can be distinguished by changes in the shape of the melting curve (Gundry et al., 2003: Wittwer et al., 2003; Reed and
Wittwer 2004; Lehmensiek et al., 2008). HRM of PCR products has been used in clinical studies for many years (Kennerson et al., 2009; Tindall et al., 2009), but has only recently been applied to plant improvement. HRM has been used to map SNP markers linked to a covered smut resistance gene in barley (Lehmensiek et al., 2008); for genotyping and variant scanning of diploid and autotetraploid potato (Koeyer et al., 2010); for development of new SNP markers from ESTs and their mapping in almond (Wu et al., 2008; 2009; 2010) and blind mapping of genic DNA sequence polymorphisms in Lolium perenne L. (Studer et al., 2009).
30
Contig Assembly and High Information Content Fingerprinting
Once the screening of BAC library is carried out and new BAC-end markers are identified, the BACs can be assigned to a specific location based on co-segregation with the desired trait. As BAC libraries are constructed with a minimum of 4x coverage, theoretically we should get more than one hit from each probe and hence it is essential to merge the overlapping BACs obtained from a single screen into a contig. BAC fingerprinting (Coulson et al., 1986) involves digestion of BAC DNA with one or more restriction enzymes and assembling of the generated fragments according to their sizes either manually or by using specific software programs. The
BAC fingerprinting technique can be divided into three groups based on (i) agarose gels, (ii) acrylamide gels and (iii) capillary electrophoresis (Scalabrin et al., 2010).
Chromosome walking requires efficient analysis of the overlap between the
BAC clones identified in each walking step for correct assembly and identification of new BAC-ends for the next walking step. Further, it will be easier to evaluate the overlaps of numerous positive BAC-clones. To assemble contigs and to select BACends for the next chromosome walking step (Deng et al., 2001), High Information
Content Fingerprinting (HICF) is effective for contig construction. HICF uses digestion of BAC DNA with two to five restriction enzymes followed by SNaPshot flourescent labeling and sizing of the fragments using automated capillary DNA sequencing instruments. FingerPrinted Contigs (FPC) software (Soderlund et al.,
1997) can be used to assemble contigs from the BAC fragments (Soderlund et al.,
2000). Additionally, BAC sequences can be incorporated if available (Nelson and
31
Soderlund, 2009). HICF has been extensively used in BAC based construction of physical maps in Vitis vinefera (Scalabrin et al., 2010), Oryza sativa (Zhang and
Wing, 1997), Cucumis melo (González et al., 2010), Arabidopsis thaliana (Mozo et al., 1999; Marra et al., 1999; Chang et al., 2001), Malus x domestica Borkh, (Han et al., 2007) and many other crops.
High-throughput Sequencing Technologies
Over the past few years, there has been a fundamental shift away from the application of automated Sanger sequencing for genome analysis (Metzkher, 2010).
Automated Sanger sequencing is considered a 'first-generation' sequencing technology that initiated the genomics era (Metzkher, 2010). Sanger sequencing involves a mixture of techniques: bacterial cloning or PCR, template purification, labeling of
DNA fragments using the chain termination method with energy transfer, dye-labeled dideoxynucleotides and a DNA polymerase, capillary electrophoresis, and fluorescence detection that provides four-color plots to reveal the DNA sequence
(Olsvik, 1993). The newer high-throughput technologies, known as massively parallel sequencing (MPS) or next-generation sequencing (NGS), rely on a combination of template preparation, sequencing and imaging, and genome alignment and assembly methods. NGS collectively refers to sequencing technologies other than Sanger. With
NGS technologies, it may soon be possible to sequence a human's genome for US$
1000 (Service, 2006). Many NGS technologies are either already commercially available or in the process of development and release to users. The commercially
32 available NGS technologies include Roche/454, Illumina/Solexa, Life/APG’s SOLiD,
Helicos Biosciences, and the Polonator G.007. Additional methods are being developed by Pacific Biosciences, Oxford Nanopore Technology and Ion Torrent
Technology. NGS technologies and their applications have been reviewed recently
(Metzker, 2010; Fox et al., 2009; Gupta, 2008; Madris, 2008; Morozova and Marra,
2008; Lister et al., 2009; Varshney et al., 2009). A detailed comparison of different
NGS platforms is presented in Table 1.5. The efficiency of NGS platforms increases day by day. Huge amounts of data are generated in a short time, and must be stored in a cost-effective way. Special bioinformatics tools are needed for assembly and analysis. The available tools include reference-guided assembly, de novo assembly, and visualization tools. Table 1.6 lists the available computational tools for analysis of NGS data.
Genome Sequence Annotation
Genome sequence annotation involves extraction, definition, and interpretation of features on the genome sequence derived by integrating computational tools and biological knowledge. Genome sequencing technology advances and cost reductions have been dramatic, but getting useful information from the sequence data remains a challenge. In order to benefit from the huge amounts of sequence data, annotation tools must be reliable and the databases must be consistent (Bakke et al., 2009). To date, more than 40 gene annotation tools are available for both prokaryotes and eukaryotes (geneprediction.org) for analysis of sequence data. Most of these programs
33 are trained for model organisms for which well-defined expressed sequence information is available. For other organisms, ab initio gene finder programs are available which use information from the already-established gene annotation programs. Though there are more than 40 gene finder programs available, all of them make one or more of the common assumptions: the sequences have no overlapping genes, no nested genes, no frameshifts or sequencing errors, no split start or split stop codons, no alternative splicing, no selenocysteine codons, and no ambiguity codes.
Furthermore, these programs are based on statistical models such as Hidden Markov
Model (HMM), Generalized Hidden Markov Model (GHMM), Hidden Semi-Markov
Supported Vector Machines (HSVM), and Interpolated Markov Models along with evolutionary and phylogenetic information.
Once the set of predicted genes has been identified using a particular program, a generalized database search can be carried out to find similar sequences, to identify conserved domains, and to refine functional predictions (Fig 1.2). Genome annotation was recently reviewed in detail by Siezen and van Hijum (2010).
In order to confirm the gene(s) responsible for the desirable trait from the predicted genes, complementation tests through transgenic approaches need to be carried out.
34
Fig. 2.2. A generalized flow chart of genome annotation (adapted from Siezen and van Hijum, 2010)
35
36
37
38
Research Objectives
Since the discovery of eastern filbert blight in Clackamas County in 1986, the area under cultivation remained stable for 22 years at approximately 29,000 acres, but has increased in the past two years with the release of resistant cultivars. 'Yamhill' and
'Jefferson' have EFB resistance from 'Gasaway', and there is a need for additional new sources of resistance. Therefore, this research involves the survey of different hazelnut genotypes for their response to EFB. The new sources of resistance can be used in breeding programs and eventually pyramiding two or more sources of resistance in a single cultivar. An understanding of the underlying molecular aspects of EFB resistance from 'Gasaway' will help us to intelligently deploy available resistance alleles. Our goal is to construct a high-resolution map of the EFB resistance region using a BAC library of 'Jefferson', to clone and sequence the region, and to identify candidate R genes. This study will extend our knowledge of disease resistance genes in plants, using a host and a pathogen with long life cycles. This will be the first cloned disease resistance gene in the Order Fagales.
39
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58
Chapter 2
RESPONSE OF HAZELNUT ACCESSIONS TO GREENHOUSE
INOCULATION WITH
Vidyasagar R. Sathuvalli, Shawn A. Mehlenbacher and David C. Smith
Published in HortScience 2010, Vol. 45, No. 7, pp.1116-1119.
59
Abstract
Eastern filbert blight (EFB), caused by the pyrenomycete Anisogramma anomala , is a devastating disease in the hazelnut orchards of the Pacific Northwest.
Host genetic resistance from 'Gasaway' has been used extensively for breeding hazelnuts at Oregon State University. Concern over the durability of this single-gene resistance prompted a search for new sources of resistance. In this study, 86 accessions from ten countries were evaluated for their response to greenhouse inoculation with the pathogen. Nine accessions showed complete resistance, including one from Chile ('Amarillo Tardio'), two from Serbia ('Crvenje' and 'Uebov'), one from southern Russia (OSU 495.072) and five from Moscow, Russia (N01, N02, N26, N27 and N37). These new sources of EFB resistance have geographically diverse origins and will broaden the genetic base of our EFB-resistant hazelnut germplasm. The previously reported resistance of 'Grand Traverse' from Michigan and the susceptibility of 'Closca Molla' from Spain were confirmed.
Introduction
European hazelnut ( Corylus avellana L.) is an important crop in Oregon. In the U.S., hazelnuts are produced primarily in the Willamette Valley of Oregon. The
Oregon crop represents 99% of the U.S. crop and 4-5% of world production (FAOStat,
2009). However, the Oregon hazelnut industry is threatened by the disease eastern filbert blight (EFB) caused by the pyrenomycete Anisogramma anomala (Peck) E.
Muller .
The fungus, an obligate biotroph with a two-year life cycle (Pinkerton et al.,
60
1995), causes severe stem cankers on commercially important European hazelnuts.
Ascospores are released from perithecia during periods of branch wetness in winter and spring, and dispersed by splashing rain and air currents. The spores germinate and produce hyphae that directly penetrate young growing shoots in the spring. The hyphae permeate and destroy the cambial layer, and cankers bearing stromata become visible 16-18 months after initial infection (Stone et al., 1992; Johnson et al., 1994;
Pinkerton et al., 1998). Control measures include scouting and pruning out infected branches below the cankers, plus four fungicide treatments at two-week intervals starting at budbreak (Pscheidt, 2006).
Host genetic resistance is a desirable way to avoid the expense and time involved in scouting, pruning, and spraying to control this disease (Mehlenbacher,
1995). The resistance from 'Gasaway', an obsolete pollinizer, has been extensively used in the hazelnut breeding program at Oregon State University (OSU). Concern over the durability of this single resistance gene prompted this search for new sources of resistance to EFB. Inoculations by Molnar (2006) with different isolates of A. anomala showed that an isolate from Michigan produced a few cankers on 'Gasaway' and suggested genetic diversity among isolates of the pathogen. A series of studies
(Coyne et al., 1998; Lunde et al., 2000; Chen et al., 2007) has identified several new sources of resistance. Molecular markers linked to resistance have been identified for some of these (Chen et al., 2005; Sathuvalli, 2007). In this study, we evaluated the response of 86 hazelnut accessions recently introduced from several countries to greenhouse inoculation with the EFB pathogen.
61
Materials and Methods
Plant materials
The tested accessions were obtained from 11 countries (Tables 2.1 and 2.2), and included 35 from Russia, 21 from Azerbaijan, 7 from Georgia, and 6 each from
Ukraine and Serbia. One was a selection from imported seeds, and 85 were received as scions. Scions were grafted to rooted layers of C . avellana , and held in post-entry quarantine in the greenhouse for two growing seasons. The trees were then planted in the field at OSU's Smith Horticultural Research Farm in Corvallis, Ore. For disease inoculations, scions were collected in the field or the lathhouse in December-January and grafted to rooted layers in May-June. Scions were collected annually in January over a five-year period (2004-08) and stored at -1
o
C until grafted the following spring.
Three scions per accession were grafted to C .
avellana rooted layers. The grafted plants were potted in 5-L pots containing a mixture of equal volumes of peat, pumice and fine bark dust, to which 9 g of Sierra 3-4 month release fertilizer (18N-6P-12K)
(Peters Professional, Allentown, PA) was added. The grafted trees were grown in a greenhouse under optimal conditions (24 o
C day/18 o
C night) for a few weeks until they were ready for inoculation.
Disease inoculation
Inoculations were carried out in a greenhouse, and the inoculated trees later planted in the field at the Smith Horticultural Research Farm. Cankered shoots with mature stromata were collected in December annually from diseased trees from various orchards in the Willamette Valley over five years (2003-07). They were
62 stored at – 20 o
C until used as a source of inoculum. Inoculation chambers were set up in the greenhouse, using polyvinyl chloride tubing (1.27 cm diam.) placed on top of benches (2.44 m x 0.88 m) and covered with white 4 mm polythene sheeting. In the first three years (2003-05), the chamber's roof was closed and high humidity was maintained using humidifiers as described by Chen et al. (2007). In the next two years
(2006-07) the roof was open and humidifiers were replaced with mist nozzles. Three misters (7.57 L•h -1
) per bench were placed 0.3 m apart, 0.9 m above the bench top and set to operate for 10 sec every 30 min during the day time (8:00 am to 7:00 pm) and 10 sec every hour during the night (7:00 pm to 8:00 am) using an automated misting unit
(Model No. DE 8 PR2, Davis Engineering, Canoga Park, CA). Grafted plants were inoculated when the shoots had four to five nodes (Coyne et al., 1998) and actively growing shoot tips. Perithecia from the diseased twigs were dissected, ground with a mortar and pestle to release ascospores, and diluted in water to a concentration of 1 x
10
6
spores•mL
-1
. Two inoculations at a three-day interval were carried out either in the evening (8:00 pm - 10:00 pm) or early morning (5:00 am - 7:00 am) to reduce the risk of escapes. The spore suspension was sprayed on shoot tips until they were visibly damp but not dripping wet. The inoculated trees were moved out of the inoculation chamber three days after the second inoculation and grown in the greenhouse at optimal temperatures (24 o
C day/18 o
C night). In October, the trees were planted in a nursery row at the Smith Farm. 'Gasaway' was included as the resistant control, and 'Ennis', 'Daviana' and 'Tonda di Giffoni' were the susceptible
63 controls. 'Ennis' and 'Daviana' are highly susceptible to EFB while 'Tonda di Giffoni' has a high level of quantitative resistance.
Disease susceptibility evaluation
The inoculated plants were visually evaluated for the presence of cankers 16-
20 months after inoculation. A genotype was scored as susceptible if cankers with pustules were observed on one or more of the three trees, and scored as resistant if all three trees remained free of infection. Tests were repeated a second year for nine of the accessions scored as resistant, but only once for 'Amarillo Tardio'.
Description of resistant accessions
The newly identified resistant accessions were described using standard descriptors (Table 2.3). Most of these descriptions are based on a single tree and 1-6 years of observation. Data from a replicated yield trial planted in Spring, 1998 are presented for comparison.
Results and Discussion
Over the 5-year period, we assessed the disease response of 86 hazelnut accessions. Of these, 76 were susceptible and ten were resistant (Tables 2.1 and 2.2).
The resistant check 'Gasaway' remained free of EFB in all tests. The highly susceptible controls 'Ennis' and 'Daviana' became infected in all years and the moderately susceptible control ‘Tonda di Giffoni’ produced few cankers with pustules.
Inoculations were performed twice, once in the early morning and once in the late evening, to minimize the number of escapes. We reduced the number of inoculations
64 from three to two to minimize shoot tip abortion. The use of misters rather than humidifiers resulted in improved plant growth.
Twenty-one accessions from Azerbaijan, seven from the Republic of Georgia and six from Kharkiv, Ukraine were tested and all were susceptible. Sathuvalli (2007) described Georgian selection (OSU 759.010) with complete resistance. This accession was received in 1994 under two cultivar names, 'Tshkenis Dzudzu' and 'Gulshishvela', but neither name was correct. 'Tshkenis Dzudzu' and 'Gulshishvela' were received as scions in 2002 and the identities of the resulting trees confirmed. Both cultivars are susceptible, in contrast to OSU 759.010, which is resistant. In an earlier test in which potted trees were exposed under a structure topped with diseased wood, 'Lozovkoi
Sharovidnii' from Ukraine developed a few small cankers with very few stromata (data not shown) indicating possible resistance. However, 'Lozovskoi Sharovidnii' was susceptible in our greenhouse inoculations. Of seven accessions from Čačak, Serbia, two ('Crvenje' and 'Uebov') showed complete resistance to EFB. Four selections from
Dalian, China were susceptible to EFB; all are hybrids between C . heterophylla Fisch. and C . avellana .
Lunde et al. (2000) reported that 'Grand Traverse' from Michigan and 'Closca
Molla' from Spain were resistant, but Chen et al. (2007) later observed cankers on
'Closca Molla' exposed under a structure topped with diseased wood. Our greenhouse inoculations of 'Closca Molla' confirmed its susceptibility. Molnar (2006) inoculated
'Closca Molla’ with several isolates of
A. anomala and also reported it to be susceptible. Our studies, and those of Molnar (2006), confirmed the resistance of
65
'Grand Traverse'. 'Grand Traverse' has nearly round nuts with a high kernel percentage (51%) and kernels have little fiber. It was introduced for the in-shell trade
(The Brooks and Olmo Register of Fruit and Nut Varieties, 1997). The tree is vigorous, productive, winter hardy, and resistant to bud mites but not precocious.
'Amarillo Tardio' is a late-shedding pollenizer received from the Institituto
Nacional de Investigaciones Agropecuarias - Quilamapu Research Station in Chillan,
Chile. It is believed to be a seedling from nuts imported from Europe. Its nuts are small, round with a slight point, borne in clusters of three, and mature with
'Barcelona'. The husks are slightly shorter than the nuts, and most fall free at maturity.
Of the nuts harvested in 2007, 32% were poorly filled. 'Amarillo Tardio' pollen expresses incompatibility allele S
2
; the second S-allele has not been identified. The disease response of 'Amarillo Tardio' was tested only once.
'Crvenje' is a local selection received from the Agricultural Research Institute's
Fruit and Grape Research Centre in Čačak, Serbia. The nuts are small and long-oval, and the husks are slightly longer than the nuts. Most are borne as single nuts. The nuts fall free of the husk at maturity, about one week later than Barcelona. Nut yields are low, but bud mite resistance is very good. The brittle kernels are covered with fiber, blanch poorly, and often break when the nuts are cracked. It has incompatibility alleles S
6
and S
23
.
OSU 495.072
was selected from seedlings grown from seed sent by the All-
Union Institute of Plant Industry (VIR) headquarters in St. Petersburg, Russia. We do not know the collection site, but assume that the seeds were collected at a VIR station
66 near Krasnodar or elsewhere in the North Caucasus. A total of 91 seedlings were planted. They were vigorous with upright growth, a striking lack of precocity, and late-maturing nuts that fell free of short, open husks. In contrast, Russian cultivars from Sochi on the Black Sea coast are similar to those grown in Turkey in that they have small trees that are spreading and low in vigor, and the nuts are enclosed in long, clasping husks. The nuts of OSU 495.072 are small, round with a slight point oblong, and borne in husks about 50% longer than the nuts. The nuts are in clusters of three and fall free of the husk slightly earlier than 'Barcelona'. The kernels are covered with fiber, but pellicle removal scores are good. Resistance to bud mite (primarily
Phytoptus avellanae Nal.) is good and similar to 'Lewis'. It has incompatibility alleles
S
6
and S
30
.
'Uebov' is a local selection received from the ARI Fruit and Grape Research
Centre in Cacak, Serbia. The nuts are large, attractive and round, and are borne in clusters of one or two. The husk is slightly longer than the nut and slit on the side.
Nuts are well-filled for their size, but shells are thick and show a high incidence of split sutures, which results in many kernels having black tips. The nuts mature slightly later than 'Barcelona'. Nut yields are low, but the kernels are attractive and blanch well. Bud mite resistance is very good. It has incompatibility alleles S
12
and
S
16
.
Of the 34 selections from the Russian Research Institute of Forestry and
Mechanization, five (N01, N02, N26, N27 and N37) remained free of EFB in two tests, while 29 others were susceptible. N01, N26 and N37 have small nuts, N27 has
67 medium-sized nuts and N02 has large nuts. The large nuts of N02 are well-filled for their size. All produce long nuts, and kernel percentage ranges from 41 to 50%. Husk length is roughly equal to nut length. Nut maturity is more than a week earlier than
'Barcelona' for N01, N26, N27 and N37. The incompatibility alleles of these five selections have not yet been identified.
The geographic origins of the nine newly identified resistant accessions (six from Russia, two from Serbia, and one from Chile) suggest diversity in their resistance genes. These nine accessions should be useful in breeding hazelnuts for areas where
EFB is present.
68
69
70
71
Table 2.2. Response of 34 hazelnut accessions from the Russian Research z
Institute of Forestry and Mechanization to greenhouse inoculation with
Anisogramma anomala.
Selection
N01
N02
N26
N27
N37
N01-08
N01-13
N05
N06
N07
N08
N09
N10
N11
N12
Year of inoculation
2005, 2007
2005, 2007
2005, 2007
2005, 2007
2005, 2007
2005, 2007
2005
2005
2005
2005, 2007
2005
2005, 2007
2005, 2007
2005
2005
N33
N34
N35
N36
N38
N39
N40
N43
N44
N13
N14
N15
N21
N22
N24
N28
N30
N31
2005
2005, 2007
2005
2005, 2007
2005
2005
2005
2005
2005
2005, 2007
2005, 2007
2005, 2007
2005
2005, 2007
2005
2005
2005
2005, 2007
"
"
"
"
"
"
"
"
"
N45 2005 " z
15 Institutskaya St., Pushkino, Moscow Province 141202 Russian Federation.
"
"
"
"
"
"
"
"
"
Disease response
Resistant
"
"
"
"
Susceptible
"
"
"
"
"
"
"
"
"
72
73
References
Chen, H., S.A. Mehlenbacher, and D.C. Smith. 2005. AFLP markers linked to eastern filbert blight resistance from OSU 408.040 hazelnut. J. Amer. Soc.
Hort. Sci. 130:412-417.
Chen, H., S.A. Mehlenbacher, and D.C. Smith. 2007. Hazelnut accessions provide new sources of resistance to eastern filbert blight. HortScience 42:429-748.
Coyne, C.J., S.A. Mehlenbacher, and D.C. Smith. 1998. Sources of resistance to eastern filbert blight in hazelnut. J. Amer. Soc. Hort. Sci. 123:253-257.
FAOStat 2009. http://faostat.fao.org/site/567/default.aspx#ancor Accessed Dec 24,
2009.
Johnson, K.B., J.N. Pinkerton, S.M. Gaudreault, and J.K. Stone. 1994. Infection of
European hazelnut by Anisogramma anomala : Site of infection and effect of host development stage. Phytopathology 84:1465-1470.
Lunde, C.F., S.A. Mehlenbacher, and D.C. Smith. 2000. Survey of hazelnut cultivars for response to eastern filbert blight inoculation. HortScience 35:729-731.
Mehlenbacher, S.A. 1995. Classical and molecular approaches to breeding fruit and nut crops for disease resistance. HortScience 30:466-477.
Molnar, T.J. 2006. Genetic resistance to eastern filbert blight in hazelnut ( Corylus ).
Ph.D. dissertation. Department of Plant Biology. Rutgers, the State University of New Jersey. New Brunswick, NJ.
Pinkerton, J.N., J.K. Stone, S.J. Nelson, and K.B. Johnson. 1995. Infection of
European hazelnut by Anisogramma anomala : ascospore adhesion, mode of penetration of immature shoots, and host response. Phytopathology 88:1260-
1268.
Pinkerton, J.N., K.B. Johnson, J.K. Stone, and K.L. Ivors. 1998. Factors affecting the release of ascospores of Anisogramma anomala.
Phytopathology 88:122-128.
Pscheidt, J.W. 2006. Potential EFB control programs. Proceedings of the Nut
Growers Society of Oregon, Washington and British Columbia 91:72-78.
Sathuvalli, V.R. 2007. DNA Markers linked to novel sources of resistance to eastern filbert blight in European hazelnut ( Corylus avellana L). M.S. thesis.
Department of Horticulture, Oregon State University, Corvallis, Oregon.
74
Stone, J.K., K.B. Johnson, J.N. Pinkerton, and J.W. Pscheidt. 1992. Natural infection period and susceptibility of vegetative seedlings of European hazelnut to
Anisogramma anomala . Plant Disease 76:348-352.
The Brooks and Olmo Register of fruit and nut varieties. 1997. Third edition. ASHS
Press, Alexandria, VA. p.307.
75
Chapter 3
A BACTERIAL ARTIFICIAL CHROMOSOME LIBRARY OF
‘JEFFERSON’ HAZELNUT: A RESOURCE FOR FINE-MAPPING
AND MAP-BASED CLONING
Vidyasagar R. Sathuvalli and Shawn A. Mehlenbacher
76
Abstract
European hazelnut, Corylus avellana L., is the only economically important nut crop in the family Betulaceae. Because of its small genome size (1C ~385 Mb), relatively short life cycle, availability of a dense linkage map, and amenability to transformation by Agrobacterium , the European hazelnut could serve as a model plant for the Betulaceae. Here we report the construction of a bacterial artificial chromosome (BAC) library of ‘Jefferson’ hazelnut using the cloning enzyme MboI and the vector pECBAC1 (BamHI site). The library consists of 39,936 clones arrayed in 104 384-well microtiter plates with an average insert size of 117 kb. The genomic coverage of the library is estimated to be about 12 genome-equivalents. This BAC library provides a valuable resource for map-based cloning of genes, including the
'Gasaway' gene which confers resistance to eastern filbert blight caused by the fungus
Anisogramma anomala . Fine-resolution mapping of eight RAPD markers closely linked to resistance showed that markers W07-375 and X01-825 flanked the resistance locus at distances of 0.06 and 0.05 cM, respectively. A preliminary screening of the library with primers derived from AA12-850 gave 11 hits. Assuming that 1 cM corresponds to a physical distance of 430 kb, it will take approximately 1-2 chromosome walks to cover the resistance locus.
Introduction
The Betulaceae family contains more than 130 species (Chen, 1994) including alder ( Alnus sp.
), beech ( Nothofagus sp.
), birch ( Betula sp.
) and hazelnut ( Corylus
77 sp.
). The European hazelnut ( Corylus avellana ) is the most economically important nut crop species in the Betulaceae with more than 750,000 MT of in-shell kernels produced worldwide (data for 2007; http://faostat.fao.org) on more than 560,000 hectares. Hazelnut consumption has increased recently and has been associated with various health benefits, including heart health (Richardson, 1997). Yücesan et al.
(2010) showed that a hazelnut-enriched diet may play an important role in decreasing the susceptibility of low-density lipoprotein (LDL) to oxidation. The European hazelnut is a diploid with 11 pairs of chromosomes and a haploid genome size of 0.48 pg/1C nucleus (http://www.kew.org/cvalues/ homepage.html
).
The estimated genome size is 385 MB, which is about 3.5 times that of Arabidopsis and slightly smaller than that of rice. A high-density linkage map with an average of 2.6 cM between adjacent markers was constructed using random amplified polymorphic DNA (RAPD) and simple sequence repeat (SSR) markers (Mehlenbacher et al., 2006). Gürcan et al.
(2010a, 2010b) recently placed more than 150 SSR markers on the map. The small genome size, relatively short life cycle (~ 5 years to first flowering), a dense linkage map, suitability for micropropagation and amenity to Agrobacterium
–mediated transformation makes hazelnut a suitable model for the Betulaceae.
Eastern filbert blight (EFB), caused by the pyrenomycete Anisogramma anomala is a major disease on European hazelnut in the Pacific Northwest (USA).
Host genetic resistance is a desirable alternative to the expense and time commitment for scouting, pruning, and spraying to control this disease (Mehlenbacher, 1995).
Resistance from ‘Gasaway’, an obsolete pollinizer, has been extensively used in the
78 hazelnut breeding program at Oregon State University (OSU). Marker-assisted selection has used RAPD markers UBC 152-800 and UBC 268-580 which flank the resistance allele (Mehlenbacher et al., 2004).
Though there are many important plant species in the family Betulaceae, the genomic resources available are relatively few compared to other nut, woody ornamental and forest tree crops. In an effort to increase the genomic resources for hazelnut and to better understand the genetic control of host-pathogen interactions and other important traits, a bacterial artificial chromosome (BAC) library was constructed for the cultivar ‘Jefferson’ (OSU 703.007) which is heterozygous for resistance from
‘Gasaway’. In this study, we report the construction of a BAC library for hazelnut and fine-resolution mapping of the eastern filbert blight resistance locus with RAPD markers closely linked to resistance. This is a first step towards map-based cloning of the resistance allele.
Materials and Methods
Plant materials
The cultivar ‘Jefferson’ (OSU 703.007) was the source of DNA for BAC library construction and fine mapping. ‘Jefferson’ is from the cross OSU 252.146 x
OSU 414.062. Young leaves of ‘Jefferson’ were collected from trees growing in the field at OSU’s Smith Horticulture Research Farm in Corvallis, OR in spring 2007, snap frozen in liquid nitrogen and shipped immediately on dry ice to Amplicon
Express (Pullman, WA).
79
BAC library construction
The BAC library was constructed at Amplicon Express. High molecular weight DNA was embedded in agar plugs. Partial digestion of the agar plugs was carried out using Mbo I to generate the insert DNA. The inserts were ligated into the
BamH I site of the vector pECBAC1 carrying chloramphenicol resistance and transformed into DH10 b E .coli
cells. Putative transformants were robotically picked and arrayed onto 384-well plates.
Identification of recombinant seedlings
A total of 1488 seedlings from the cross OSU 252.146 × OSU 414.062, including the reciprocal cross, was generated in the year 2007. DNA was extracted from leaves of seedlings from this mapping population in the spring of 2008 as described by Lunde et al. (2000) and amplified by PCR using two RAPD primers,
UBC 152 and UBC 268 (Mehlenbacher et al., 2004). Amplifications were performed separately in a 15 µl volume containing 0.4 µM of primer, 10-25 ng of template DNA,
0.4 U of Biolase DNA polymerase (Biolase USA, Randolph, MA), 1.5 mM MgCl
2 ,
120 µM each of dATP, dCTP, dGTP and dTTP and the 1X ammonium-based buffer supplied by the manufacturer (Mehlenbacher et al., 2004). Ninety-six reactions were run simultaneously using Geneamp® PCR System 9600 and 9700 thermal cyclers.
The thermal cycler program consisted of an initial 94 o
C for 1 min, followed by 45 cycles of 1 min at 94 o
C, 1 min 30s at 37 o
C, 30s at 54 o
C , 2 min at 72 o
C; then 14:45 min at 72 o
C, ending with an indefinite hold at 4 o
C until retrieved from the thermal cycler. Amplification products were separated by electrophoresis on 2% w/v agarose,
80 stained with ethidium bromide, and photographed using an ultraviolet imaging system.
The gel images were scored for presence of markers 152-800 and 268-580. Seedlings that showed only one of the two markers were retained for further study.
Disease inoculations
Recombinant and potentially recombinant seedlings were grown in the greenhouse until they were one meter tall and inoculated with Anisogramma anomala spores as described by Sathuvalli et al. (2010a). The inoculated plants were planted at
OSU’s Smith Horticulture Research Farm. ‘Jefferson’, ‘Gasaway’ and parent OSU
414.062 were used as resistant controls; ‘Ennis’ and parent OSU 252.146 were used as susceptible controls. ‘Tonda di Giffoni’, which has high degree of quantitative EFB resistance, was used as an additional susceptible control.
Disease susceptibility evaluation
The inoculated seedlings were evaluated for the presence of cankers 16-20 months after inoculation. The seedlings were scored as susceptible if cankers with stromata (pustules) were observed, and scored as resistant if they were free of infection. The plants that are free from infection were reevaluated 28-32 months after inoculation. Seedlings that died after inoculation and before the onset of symptoms were excluded from the analysis as we could not determine if death was due to EFB or another reason.
Fine mapping with RAPD markers
Seedlings that showed recombination between markers 152-800 and 268-580 were scored for the presence of six other RAPD markers linked to resistance (173-500,
81
AA12-850, W07-375, X01-825, H04-850 and 726-665) (Mehlenbacher et al., 2004).
PCRs were performed as described above. A linkage map was constructed for the eight RAPD markers and disease phenotype using JoinMap 4.0 (van Ooijen, 2006) as described by Sathuvalli et al. (2010b).
Screening of BAC library
Because of our intention to isolate the ‘Gasaway’ resistance gene, the library was screened with primers derived from the closely linked RAPD marker AA12-850.
The primer sequences used for AA12-850 screening were F:
GGACCTCTTCTACACGGTTATC and R: GACCTCTTGCCTTGGACTCT
Results and Discussion
Construction of BAC library
A BAC library was successfully constructed from two ligations for ‘Jefferson’
(OSU 703.007), which is resistant to eastern filbert blight. The average insert size was
115 kb in the first ligation and 120 kb in the second (Fig. 3.1). The library consists of
39,936 clones arrayed in 104 384-well microtiter plates and is stored at -80 o
C. The average insert size for the whole library is estimated to be 117 kb with 1% of clones missing inserts and 0.14% missed wells. The percentage of empty clones (1.0%) is on a par with other BAC libraries including Vitis vinifera (0.5-2.2%) (Adam-Blondon et al., 2005), Daucus carota L. (4%) (Cavagnaro et al., 2009), and Coffea canephora
(0%) (Leroy et al., 2005). For successful map-based cloning, physical mapping and genome sequencing, the library should have coverage of 5-10X across the genome
82
(Ammiraju et al. 2006). Assuming a genome size of 385 Mb, the library should give
12X haploid equivalents and >99.9% probability of finding any gene in the library
(Clarke and Carbon, 1976).
Fine mapping
As a step forward in the map-based cloning approach, a population of 1488 seedlings was screened for two RAPD markers that flank the ‘Gasaway’ resistance locus, 152-800 and 268-580 (Mehlenbacher et al., 2004). Of the seedlings, 87 showed recombination between the markers. These seedlings were inoculated with the pathogen, and disease phenotypes scored 16-20 months later. These seedlings were scored for presence of six other RAPD markers (Mehlenbacher et al. 2004) closely linked to resistance.
The map of Mehlenbacher et al. (2004) shows markers 152-800 and 268-580 flanking the resistance locus and 7.5 cM apart. The present map (Fig 3.2) constructed using 1488 seedling, the distance between these two markers is 4.37 cM. RAPD markers W07-375 and X01-825 closely flank the resistance locus at distances of 0.06 cM and 0.05 cM, respectively. Mehlenbacher et al. (2006) constructed separate genetic linkage maps for OSU 252.146 (susceptible maternal parent) and OSU
414.062 (resistant paternal parent). The maps covered total distances of 661 cM and
812 cM, respectively. Assuming an average genetic distance of 900 cM of the whole hazelnut map, the physical distance corresponding to 1 cM will be equal to ~ 430 kb.
As average insert size of BAC library is 117 kb it will take around 3 to 4 chromosome walks to cover a distance of 1 cM. As the closest RAPD markers are 0.06 and 0.05
83 cM, we presume that it will take 1 to 2 chromosome walks to cover the region that contains the resistance locus. Thus a map-based cloning approach seems to be feasible for isolation of the eastern filbert blight resistance locus. PCR-based screening using pooling and sub-pooling strategy as described by Wang et al. (2004) is being used for map-based cloning.
Library screening
Screening of the library with primers derived from RAPD marker AA12-850 identified eleven positive clones. Comparisons of sequences in this region revealed that six of them contain the marker associated with the resistance allele, and thus we believe that the other five BAC clones are associated with the allele for susceptibility
(data not shown). If this is true, it would indicate that the library contains roughly equal representation of the resistant and susceptible homologs.
Conclusion
A BAC library for ‘Jefferson’ hazelnut was constructed. Mapping of recombinant seedlings showed that RAPD marker W07-375 and X01-825 closely flank the resistance locus. Preliminary screening of the BAC library with primers designed from RAPD marker AA12-850 indicate that it is feasible to isolate the resistance locus using a map-based cloning approach.
84
Fig.3.1.
DNA of 28 randomly selected BAC clones digested with NotI . Lanes 1 to 14 are from the first ligation and lanes 15-28 are from the second. (Photo courtesy of
Robert Bogden, Amplicon Express).
Fig. 3.2.
A genetic linkage map for the eastern filbert blight resistance locus (R-locus) and eight RAPD markers constructed from 1488 seedlings from a cross of hazelnut selections OSU 252.146 × OSU414.062.
85
References
Adam-Blondon, A.F., A. Bernole, G. Faes, D. Lamoureux, S. Pateyron, M.S. Grando,
M. Caboche, R. Velasco, B. Chalhoub. 2005. Construction and characterization of BAC libraries from major grapevine cultivars. Theor Appl
Genet 110:1363–1371.
Ammiraju, J.S.S., M. Lwo, J.L. Goicochea, W. Wang, D. Kudrna, C. Mueller, J.
Talag, H-R. Kim, N.B. Sisneros, B. Blackmon, E. Fang, J.B. Tomkins, D.
Brar, D. MacKill, S. McCouch, N. Kurata, G. Lambert, D.W. Galbraith, K.
Arumuganathan, K. Rao, J.G. Walling, N. Gill, Y. Yu, P. SanMiguel, C.
Soderlund, S. Jackson, R.A. Wing. 2006. The Oryra bacterial artificial chromosome library resource: construction and analysis of 12 deep-coverage large-insert BAC libraries that represent the 10 genome types of the genus
Oryza . Genome Res 16:140–147.
Cavagnaro, P.F., S-M. Chung, M. Szklarczyk, D. Grzebelus, D. Senalik, A.E. Atkins,
P.W. Simon. 2009. Characterization of a deep-coverage carrot ( Daucus carota L.) BAC library and initial analysis of BAC-end sequences. Mol Genet
Genomics 281:273-288.
Chen, Z.-D. 1994. Phylogeny and phytogeography of the Betulaceae. Acta
Phytotaxonomica Sinica 32: 1-32, 101-153 (in Chinese with English summary)
Clarke, L. and J. Carbon. 1976. A colony bank containing synthetic ColE1 hybrid plasmids representative of the entire E. coli genome. Cell 9:91-100.
Gürcan, K. and S.A. Mehlenbacher. 2010a. Development of microsatellite marker loci for European hazelnut ( Corylus avellana L.) from ISSR fragments.
Molecular Breeding
DOI
10.1007/s11032-010-9464-7.
Gürcan, K., S.A. Mehlenbacher, N.V. Bassil, P. Boccacci, A. Akkak, R. Botta. 2010b.
Development, characterization, segregation, and mapping of microsatellite markers for European hazelnut (Corylusavellana L.) from enriched genomic libraries and usefulness in genetic diversity studies. Tree Genetics and
Genomes 6:513-531.
Leroy, T., P. Marraccini, M. Dufour, C. Montagnon, C. Lashermes, X. Sabau, L.P.
Ferreira, I. Jourdan, D. Pot, A.C. Andrade, J.C. Glaszmann, L.G.E. Vieira, P.
Piffanelli. 2005. Construction and characterization of a Coffea canephora
BAC library to study the organization of sucrose biosynthesis genes. Theor
Appl Genet 111:1032–1041.
86
Lunde, C.F., S.A. Mehlenbacher, and D.C. Smith. 2000. Survey of hazelnut cultivars for response to eastern filbert blight inoculation. HortScience 35:729-731.
Mehlenbacher, S.A. 1995. Classical and molecular approaches to breeding fruit and nut crops for disease resistance. HortScience 30:466-477.
Mehlenbacher, S.A., R.N. Brown, J.W. Davis, H. Chen, N.V. Bassil, and D.C. Smith.
2004. RAPD markers linked to eastern filbert blight resistance in Corylus avellana . Theor. Appl. Genet. 108:651-656.
Mehlenbacher, S.A., R.N. Brown, E.R. Nouhra, T. Gökirmak, N.V. Bassil, and T.L.
Kubisiak. 2006. A genetic linkage map for hazelnut ( Corylus avellana L.) based on RAPD and SSR markers. Genome 49:122-133.
Richardson, D.G. 1997. The health benefits of eating hazelnuts: Implications for blood lipid profiles, coronary heart disease, and cancer risks. Acta Hort.
445:295-300.
Sathuvalli, V.R., S.A. Mehlenbacher, and D.C. Smith. 2010a. Response of hazelnut accessions to greenhouse inoculation with Anisogramma anomala .
HortScience 45:1116-1119.
Sathuvalli, V.R., H. Chen, S.A. Mehlenbacher, and D.C. Smith. 2010b. DNA markers linked to eastern filbert blight resistance in ‘Ratoli’ hazelnut (
Corylus avellana L.). Tree Genetics and Genomes Doi 10.1007/s11295-010-0335-5 .
Van Ooijen, J.W., and R.E Voorrips. 2006. JoinMap 4.0, Software for the calculation of genetic linkage maps. Kyazama B.V., Wageningen, Netherlands.
Wang, Y., T. Tsukamoto, K. Yi, S. Huang, A.G. McCubbin, and T. Kao. 2004.
Chromosome walking in the Petunia inflata self-incompatibility ( S) locus and gene identification in an 881-kb contig containing S
2
-RNase.
Plant Molecular
Biology 54:727-742.
Yücesan, F.B., A. Orem, B.V. Kural, C. Orem, and I. Turan. 2010. Hazelnut consumption decreases the susceptibility of LDL to oxidation, plasma oxidized
LDL level and increases the ratio of large/small LDL in normolipidemic healthy subjects. Anadolu Kardiyol Derg. 10:28-35.
Chapter 4
SEQUENCING OF HAZELNUT BACTERIAL
ARTIFICIAL CHROMOSOMES (BACS) IN A DISEASE
RESISTANCE REGION USING MULTIPLEX ILLUMINA IIx
SEQUENCING
Vidyasagar R. Sathuvalli and Shawn A. Mehlenbacher
87
88
Abstract
Bacterial artificial chromosomes (BACs) are widely used in the map based cloning of plant genes. Eastern filbert blight (EFB), caused by the pyrenomycete
Anisogramma anomala , (Peck) E. Müller is a devastating disease of European hazelnut ( Corylus avellana L.) in the Pacific Northwest. A dominant allele at a single locus from the obsolete pollenizer 'Gasaway' confers complete resistance to EFB. Our map-based cloning efforts use a BAC library for 'Jefferson' hazelnut, which is heterozygous for resistance. Screening the library with primer pairs designed from
RAPD markers closely linked to EFB resistance identified 17 BACs. We sequenced these BACs using an Illumina IIx genome analyzer, with multiplexing with barcoded adapters to reduce the cost, and paired-end reads to facilitate de novo sequence assembly. De novo sequence assembly was carried out using the programs Velvet and
SOPRA, and the resulting contigs were further aligned using CodonCode software and generated contig length ranged from 356 bp to 99632 bp. Estimated coverage of assembled BACs ranged from 64 to 100 % of the BAC sequences.
Introduction
The hazelnut industry in the Pacific Northwest (USA) is threatened by eastern filbert blight (EFB) caused by the pyrenomycete, Anisogramma anomala (Peck) E.
Müller. Host genetic resistance is a desirable way to avoid the expense and time commitment involved in scouting, pruning, and spraying to control this disease
(Mehlenbacher, 1995). Complete resistance was first discovered in ‘Gasaway’, an
89 obsolete pollinizer that was found free of symptoms in a heavily infected ‘DuChilly’ orchard (Cameron, 1976). The resistance from ‘Gasaway’, controlled by a dominant allele at a single locus (Mehlenbacher et al., 1991), has been extensively used in the hazelnut breeding program at Oregon State University. Marker-assisted selection has used RAPD markers UBC152-800 and UBC268-580 which flank the resistance locus
(Mehlenbacher et al., 2004). A map-based approach is being used to clone the resistance gene.
Physical mapping, chromosome walking and map-based cloning in plant genomes require large insert DNA libraries (Woo et al., 1994). Bacterial artificial chromosome libraries permit the cloning and stable maintenance of large inserts, usually 100 to 300 kb, in E. coli (Shizuya et al., 1992). BAC libraries have been used in map-based cloning in many plants (Patocchi et al., 1999; Sandal et al., 2005,
Krattinger et al., 2009; Shinozuka et al., 2010; Kaufmann et al., 2003, Claverie et al.,
2004). For map-based cloning of the 'Gasaway' EFB resistance gene, a BAC library was constructed for the heterozygous resistant cultivar ‘Jefferson’ (Sathuvalli and
Mehlenbacher, 2009). The BAC library consists of 39,936 clones arrayed in 104 384well microtiter plates. The average insert size is estimated to be 117 kb, with 1% of clones lacking inserts. The genomic coverage is estimated to be about 12 genomeequivalents.
Over the past few years there has been tremendous improvement in next generation sequencing (NGS) technologies. Commercially available NGS platforms are Illumina/Solexa, Roche/454, Life/APG SOLiD and Helicos BioSciences. The
90 chemistry, technology and applications of NGS, and the associated bioinformatics have been reviewed (Metzker, 2010; Hawkins et al., 2010; Varshney et al., 2009).
Chromosome landing is a procedure that involves screening a segregating mapping population with a very large number of molecular markers to identify those very closely linked to the target gene. Those markers are then used to probe a BAC library to identify a single clone or group of clones that contains the gene of interest
(Tanksley et al., 1995). Four RAPD markers closely linked to EFB resistance from
‘Gasaway’ had been previously identified (Mehlenbacher et al., 2004). In this study, we screened a ‘Jefferson’ BAC library with primer pairs designed from the four closely linked RAPD markers. We identified 17 BACs and sequenced them using
Illumina IIG sequencing-by-synthesis.
Materials and Methods
BAC screening and selection
Primer pairs, two each, were designed from RAPD marker sequences (Table
4.1). The designed Sequence Characterized Amplified Region (SCAR) primers were tested for their polymorphism by amplifying the resistant parent, susceptible parent, two resistant seedlings and two susceptible seedlings. These primers were used to probe the ‘Jefferson’ BAC library. BACs were identified in two steps using the polymerase chain reaction (PCR) and the pooling and sub-pooling strategy described by Wang et al. (2004). In the first step, the plate pools were screened and positive plates were identified. In the second step row and column pools were screened for
91 each positive plate and positive BACs were identified. PCR amplifications were carried out in 10 µl volume containing 0.5 µM of primer, 25 ng of template DNA, 0.2
U of Biolase DNA polymerase (Biolase USA, Randolph, MA), 1.5 mM MgCl
2 ,
120
µM each of dATP, dCTP, dGTP and dTTP and the 1× ammonium-based buffer supplied by the manufacturer. The thermal cycler program consists of an initial 4 min at 95 o
C followed by 40 cycles of 30s at 95 o
C, 30 s at 60 o
C, 30s at 72 o
C; then 7 min at 72 o
C, ending with an indefinite hold at 4 o
C until retrieved from the thermal cycler.
‘Jefferson’ DNA was used as controls and the amplification products were run at 120
V for two hours on 2% w/v agarose (ISC Bioexpress, Kaysville, UT) in 1X Sodium
Borate (SB) buffer. The gels were then stained with ethidium bromide (Sigma-Aldrich
Co. St. Louis, MO), and the amplification products were visualized and photographed using an ultra-violet imaging system (UVP, Upland, CA).
Preparation of BAC libraries for Illumina sequencing
BAC DNA was extracted from 30 ml overnight liquid cultures in 2xYT media containing the antibiotic chloramphenicol (12 µg/ml) using the PhasePrep
™
BAC
DNA Kit (Sigma-Aldrich) as described in the kit's instruction manual. The Illumina fragment libraries were prepared as described by Cronn et al. (2008) with slight modifications. Briefly, 5 µg of BAC DNA dissolved in 100 µl TE buffer was sheared using a Bioruptor
TM
(Diagenode, Inc.) for 15 min with 30 sec sonication and 30 sec cooling. Sheared fragments were then purified and concentrated using a QIAquick
PCR purification spin column (QIAgen Inc, Valencia, CA, USA).
92
The ends of sheared fragments were repaired using a NEB Quick Blunting kit and 5U of Klenow fragment DNA polymerase (New England Biolabs Inc, Ipswich,
MA, USA). Following the end repair, terminal (3') A-residues were added by incubation at 37 o
C for 30 min with dATP, NEB Klenow buffer and Klenow exo (3’-
5’ exo-). Custom-made adapters with unique 3bp tags were ligated to the A-overhang
DNA fragments using the NEB Quick ligation kit. The adapter-ligated DNA fragments were separated using electrophoresis on low melt agarose (UltraPure™
Low Melting Point Agarose, Life technologies, CA, USA) gels in low-EDTA TAE buffer, and 300-400 bp fragments were selected. The size-selected libraries were amplified using 18 cycle PCR amplification and standard Illumina paired-end primers and Phusion® Flash High-Fidelity PCR Master Mix (Finnzymes Oy, Espoo, Finland).
At the end of each step and before the start of the next, the DNA was purified using an
Agencourt AMPure XP PCR purification kit (Agencourt Bioscience Corp, MA, USA).
After purification of amplification products, libraries were quantified using a
Nanodrop. DNA of the 18 BACs (17 identified BACs and 1 control BAC) was pooled at equimolar ratios to yield two multiplex mixtures 15 nM each. A 10 pmol aliquot of each multiplex library was submitted for paired-end 80 cycle sequencing in two lanes on an Illumina IIG genome analyzer at the Core Labs of the Center for Genome
Research and Biocomputing at Oregon State University.
Data analysis and bioinformatics
The 80 bp paired-end reads from the Illumina pipeline were sorted according to the adapter barcodes using the perl script bcsort_pe.pl (http://brianknaus.com). To
93 assemble the BAC sequences from the IIumina short reads, we used a three step process. The first de novo assembly used the Velvet de novo short read assembler
(Zerbino and Birney, 2008). Assembly was performed several times using various values for expected coverage and mean insert length. The options that generated the fewest contigs and the highest coverage were chosen. The second de novo assembly used the SOPRA de novo assembler (Dayarian et al., 2010). The contigs assembled by
Velvet and SOPRA were then aligned, trimmed and corrected using CodonCode
Aligner software (CodonCode Corporation, Dedham, MA, USA; http://www.codoncode.com). A BLAST search of the contigs against the sequence of the cloning vector and the E. coli genome database identified contaminant sequences which were then removed.
Estimating size of BAC inserts
Pulsed field gel electrophoresis was carried out to estimate the approximate sizes of the BACs. Overnight cultures of 1.5 ml were minipreped using a modified alkaline lysis protocol from QIAGEN (Large Construct Kit). Ten µl of DNA was cut for sizing using Not I enzyme (Fermentas, Inc, Maryland, USA). Four µl of 5x loading buffer was added to the 20 µl digest and 15 µl were loaded onto a 1% agarose gel. The gel was run on BioRad Chef with an initial switch time of 5s and final of 15s at 5.5v/cm. The gel was run for 16 hours and then stained with ethidium bromide visualized and photographed using an ultra-violet imaging system (UVP, Upland,
CA).
94
Results and Discussion
Screening of BAC library
We employed a chromosome landing approach to identify the BACs in the eastern filbert blight resistance region. The use of two primer pairs for each RAPD marker increases the likelihood of identifying all potential hits and minimizes the number of false positive. When used to amplify the resistant and susceptible parents of our mapping population, all primer pairs produced PCR products, but none revealed length polymorphism on 2% agarose gels. This indicates that our approach identified
BACs from both resistant and susceptible homologs. The total number of hits from screening ranged from one for 173-500 to eight for AA12-850. The library screening identified a total of 17 BACs which were then sequenced.
Library preparation
The 17 BACs were sequenced using Illumina technology, with multiplexing to reduce cost. Eight and nine BACs, each tagged with a different barcoded adapter
(Table 3.2), were multiplexed and sequenced in each of two lanes. In preparing the
BAC DNA for sequencing, we used mechanical shearing rather than nebulization or fragmentase shearing. In our experience, mechanical shearing of BAC DNA produces better results than nebulization or the fragmentase method (data not shown).
Analysis of Illumina reads and barcodes
We obtained 16.95 million reads of 80 bp paired-end data from the two lanes.
Lane 1 produced three times more data than lane 2 (Table 4.3). The difference might be due to an error in quantifying the DNA prior to submission. Also possible are
95 different numbers of clusters formed during the cluster generation step in the illumina sequencing pipeline. Although the amount of data differed, it had very little effect on the sequence assembly (Table 4.4).
Correctly identified barcodes were 98.64 and 95.13% for lanes 1 and 2, respectively. Cronn et al. (2008) attributed less-than-perfect sorting by barcodes to the presence of a small number of sequences that correspond to adapters, and a failure to correctly assign sequences due to presence of an ‘N’ at one of the three tag positions.
Additionally, Hillier et al. (2008) noted that it might be attributable to mutational bias towards incorporating ‘A’.
BAC sequence assembly
The total number of reads per BAC obtained from the Illumina pipeline ranged from 0.20 million for 70N1 to 3.4 million for 54O7. The difference indicates that the
BACs are not equally represented in the pooled multiplexed library. The reads were initially assembled using the Velvet de novo assembler (Zerbino and Birney, 2008) as paired end data. The program was performed several times using various values for expected coverage and mean insert length. The set of options that produced the fewest contigs but the highest sequence coverage was a hash length of 55, insert length of
350, minimum contig length of 200 bp, coverage cutoff of 5x, expected coverage as auto, and short paired-end data . The second de novo assembly used the program
SOPRA (Dayarian et al., 2010), and the contigs from Velvet and SOPRA were further aligned using CodonCode version 3.6.1. A BLAST search of the resulting contigs identified sequences from the E. coli cloning vector which were then removed.
96
The number of resulting contigs ranged from one for 65G23 to 13 43F13, for which mean lengths were 99632 bp and 6598 bp, respectively. Over all 17 BACs, contig lengths ranged from 356 to 99632 pb. Based on the average insert size determined by PFGE, we estimate that sequence coverage ranges from 64 to 100%
(Table 4.4.) with an average of 92.5%. In 9 of 17 cases, the total length of the contig exceeds the average size estimate, which indicates that almost all of the sequence is captured and also the effectiveness of sequencing.
To verify the accuracy of our assembly, we used the cloning vector sequence as a reference. In all cases, BLAST alignment of the cloning vector sequences in the assembled contigs perfectly matched the cloning vector sequence, indicating high level of accuracy of our assembly.
Analysis of BAC sequences
A BLAST search of the assembled BAC sequences against the genome database (http://blast.ncbi.nlm.nih.gov/Blast.cgi) identified three BACs (43F13,
66C22, and 85B7) having NBS-containing resistance-like protein genes of hazelnut
( Corylus avellana ). All three BACs were identified from the RAPD marker OPW07-
350. The HICF data merged all three NBS-containing contigs to a single contig of length ~150 kb. A candidate gene approach (Collins, 1992) is essential to isolate resistance gene like sequences located in these BACs. Additionally, mapping and complementation experiments should be performed to determine if the identified sequences are part of the ‘Gasaway’ resistance gene.
97
Table 4.1
. Primer pairs designed from RAPD markers linked to EFB resistance in hazelnut.
RAPD marker Primer sequences
UBC173-500 1F: GCGTAGGCAGCTACTCATACC
1R: TTGAGGTATTGAACCTCTGAAGC
2F: GCGTAGGCAGCTACTCATACCT
2R: AGGCGGCGTCACAAAAGT
OPAA12-850 1F: GGACCTCTTCTACACGGTTATC
1R: GACCTCTTGCCTTGGACTCT
2F: ACATGCATTCTCCAACCACA
2R: GTTGCTTTGGGCTCTGTCTC
OPW07-350 1F: GAGAGAGAGGGAGGGAGCATAC
1R: CGTCAACATAGGGCAATTTATG
2F: ATGCCATCCTGTTGTGGTTT
2R: CACCCAGAAACAAACACGTC
OPX01-800 1F: TTTTGCACAGGCTCGACAC
1R: TCTTGAGTCAACCCGAGCTT
2F: CACGAGGTTGGACATATGGTT
2R: GGCACGATGATTTGTGTCAT
Table 4.2.
Barcoded adapters used for multiplex sequencing of 18 hazelnut BACs
S.No Barcode in adapter Lane 1 BACs Lane 2 BACs
6
7
8
9
1
2
3
4
5
GGG
CGT
AGC
CCC
TGC
CTG
GCT
ACG
CAC
18L4
43F13
72F19
85B7
54O21 (Control) 96K15
54O7
65G23
66C22
67L9
68G11
69B19
85B18
67B17
87L10
60F8
25P3
70N1
Table 4.3.
Analysis of BAC sequencing data from Illumina sequencing.
Reads Lane 1 Lane 2
Total number 12.953951 million 3.996458 million
Number with barcodes
Number lacking barcodes
Percentage with Barcodes reads
12.777926 million
0.176025 million
98.64
3.801909 million
0.194549 million
95.13
98
98
99
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Chapter 5
HIGH-RESOLUTION GENETIC AND PHYSICAL MAPPING OF
THE EASTERN FILBERT BLIGHT RESISTANCE REGION IN
‘JEFFERSON’ HAZELNUT (
L.)
Vidyasagar R. Sathuvalli and Shawn A. Mehlenbacher
103
Abstract
Eastern filbert blight (EFB), caused by the pyrenomycete Anisogramma anomala (Peck) E. Müller is a devastating disease of European hazelnut ( Corylus avellana L .) in the Pacific Northwest where it is a serious threat to the industry's existence. A dominant allele at a single locus from the obsolete pollenizer 'Gasaway' confers complete resistance, for which several linked random amplified polymorphic
DNA (RAPD) markers have been identified. A mapping population of 1488 seedlings, which segregate for resistance, was developed and scored for flanking
RAPD markers 152-800 and 268-580 to identify potential recombinants.
Chromosome walking was initiated using primers designed from eight RAPD markers linked to resistance. The BAC library was screened using these primer pairs and a
PCR pooling and subpooling strategy. In this study, we report a high resolution genetic map and a physical map, and identify the BAC(s) most likely to carry the resistance gene. A total of 51 markers where placed on the high resolution genetic map, including markers newly developed from the BACs. In parallel to the genetic map, a physical map was constructed. Analysis of 1488 mapping seedlings indicates that the resistance gene is located in a single contig of three BACs (43F13, 66C22 and
85B7). Further mapping and complementation tests of the genes in these BACs is essential to confirm which confers resistance to eastern filbert blight.
104
Introduction
The United States produces ~5% of the world’s hazelnuts ( Corylus avellana
L.) with cultivation centered in Willamette Valley of Oregon. One of the threats to the hazelnut industry in the Pacific Northwest (Oregon and Washington) is eastern filbert blight (EFB) caused by an obligate biotrophic fungus, Anisogramma anomala (Peck)
E. Műller, a pyrenomycete first reported by Peck (1876) as a pathogen of the
American hazelnut, Corylus americana Marsh. (Cameron, 1976). The fungus causes occasional small lesions on the American hazelnut, but large stem cankers on the commercially important European hazelnut. The disease has been well-studied
(Pinkerton et al., 1992, 1993, 1995, 1998a, 1998b; Stone et al., 1992; Johnson et al.,
1994, 1996). The fungus has a two-year life cycle that includes a latent period of 16-
20 months between inoculation and the appearance of cankers. Current control measures include surveying and pruning of the infected trees below the cankers and four fungicide treatments at two-week intervals starting at budbreak (Pscheidt, 2006).
Because of environmental concerns and the high cost of fungicide applications, host genetic resistance remains the most desirable and economical approach for the longterm control of this disease.
Complete resistance to EFB was first discovered in ‘Gasaway’, an obsolete pollenizer that was found free of symptoms in a heavily infected ‘DuChilly’ orchard
(Cameron, 1976). Resistance from ‘Gasaway’ is controlled by a dominant allele at a single locus (Mehlenbacher et al., 1991) and has been extensively used in the hazelnut breeding program at Oregon State University (OSU). Random amplified polymorphic
105
DNA (RAPD) markers closely linked to ‘Gasaway’ resistance have been identified
(Davis and Mehlenbacher, 1997; Mehlenbacher et al., 2004, 2006) and two robust flanking markers, 152-800 and 268-580, are used for marker-assisted selection (MAS).
Concern over the durability of a single resistance has stimulated a search for other sources of resistance and their use in breeding. New sources of resistance have been identified by Lunde et al. (2000), Chen et al. (2007), Molnar et al. (2007) and
Sathuvalli et al. (2010a).
Plant disease resistance ( R ) genes represent a large number of the cloned genes in plant species. More than 55 R genes have been cloned from different monocot and dicot species (van Ooijen et al., 2007; Martin et al., 2003). The structure and function of these R genes have been studied. Their sequences contain common motifs that are widely conserved across different taxa. These conserved regions allow primer design and amplification, and the PCR products are called resistance gene analogs (RGAs).
RGAs tend to occur in clusters and often map to the same regions as major resistance genes or QTLs. The identification of specific RGAs, and their use as molecular markers in studies of plants with different levels of disease resistance, may help identify the genes or genomic regions responsible for resistance. It may also be possible to use RGAs for the development of markers for marker-assisted selection.
Baldo et al. (2009) used an RGA approach in the Rosaceae, using the identified RGAs as tags for resistance regions and identification of potential parents in the germplasm collection.
106
'Jefferson' (OSU 703.007) is a new hazelnut cultivar released by the Oregon
Agricultural Experiment Station in January 2009 with complete resistance derived from ‘Gasaway’. A bacterial artificial chromosome (BAC) genomic library of
'Jefferson' composed of 39,936 clones arrayed in 104 384-well microtiter plates was constructed to support contig assembly and map-based cloning of the EFB resistance locus (Sathuvalli and Mehlenbacher, 2009). The BAC library is estimated to have 12× genome coverage. The aims of this study were to use the BAC library and chromosome walking to construct a high-density map of the region that contains the
EFB resistance gene, and to construct a physical map of the region. Our ultimate goal is to clone the resistance gene.
Materials and Methods
Plant materials
The hazelnut genotypes used in this study were generated by the hazelnut breeding project at Oregon State University. 'Jefferson' is from a cross of OSU
252.146 × OSU 414.062 (Mehlenbacher et al., 2006). For fine mapping, controlled crosses were made in 2007 to generate two progenies. Progeny 07001 is from a cross of OSU 252.146 x OSU 414.062, and is a repeat of the cross that gave 'Jefferson'.
Progeny 07002 is the reciprocal cross, OSU 414.062 x OSU 252.146. The crosses generated 1080 and 408 seedlings, respectively. All 1488 seedlings in the two progenies were screened for presence of RAPD markers UBC 152-800 and UBC 268-
580, and recombinants between the two markers were used for disease inoculations.
107
07001
OSU 252.146
OSU 41.083
Montebello
Compton
Barcelona
OSU 17.028
Tombul Ghiaghli
OSU 23.017
Barcelona
Extra Ghiaghli
OSU 414.062
Montebello
VR 11-27
Gasaway
Fig. 5.1
. Pedigree of hazelnut progeny 07001 used in fine-mapping and disease inoculations. Genotypes heterozygous resistant to eastern filbert blight are underlined.
Progeny 07002 is from the reciprocal cross, OSU 414.062 x OSU 252.146.
Disease inoculation and phenotypic assays
Recombinant seedlings were inoculated in a greenhouse in August 2008, as described by Sathuvalli et al. (2010a, 2010b), and later planted in the field at the OSU
Smith Horticulture Research Farm in Corvallis, Ore. The resistant controls were
'Gasaway' and 'Jefferson', and the susceptible controls were 'Ennis', 'Daviana' and
'Tonda di Giffoni'. The inoculated plants were scored for the presence of cankers in
Dec. 2009, and again in Sep. 2010 to confirm the disease scores. The seedlings were scored as resistant if there was no sign of cankers and scored as susceptible if cankers with stromata were present on either evaluation date.
108
Pooling and screening of the BAC library by PCR
The BAC library is composed of 104 plates corresponding to a total of 39,936 clones, with each plate containing 384 BACs. The clones from each plate were mixed to create 104 "plate pools". The pool was cultured overnight in 30 ml liquid LB media containing 12 µg/ml of the antibiotic chloramphenicol. DNA was extracted from the pooled culture using the PhasePrep
™
BAC DNA kit from Sigma-Aldrich, Inc., according to the manufacturer's instructions. Similarly, row and column pools were created for each plate. For each plate there are 16 row pools (24 clones each) and 24 column pools (16 clones each). The BAC library was screened in two steps using
PCR, primer pairs designed from marker sequences, and the DNA pools. In the first step, the plate pools were screened and positive plates identified. In the second step, row and column pools were screened for plates identified as positive in the first step and the clones were confirmed by amplifying the individual BACs.
PCR amplifications were carried out in 10 µl volumes containing 0.5 µM of primer, 25 ng of template DNA, 0.25 U of Biolase DNA polymerase (Biolase USA, Randolph, MA),
1.0 mM MgCl
2 ,
80 µM each of dATP, dCTP, dGTP and dTTP and the 1× ammoniumbased buffer supplied by the manufacturer. The thermal cycler program consisted of an initial 4 min at 95 o
C followed by 40 cycles of 30s at 95 o
C, 40 s at 60 o
C, 40s at 72 o
C; then 7 min at 72 o
C, ending with an indefinite hold at 4 o
C until retrieved from the thermal cycler. When necessary, annealing temperatures were adjusted for precise amplification to reduced noise during PCR amplification. 'Jefferson' DNA and empty plasmid vector were used as controls, and the amplification products were separated
109 on 2% w/v agarose (ISC Bioexpress, Kaysville, UT) in 1x sodium borate (SB) buffer at 120 V for 2.0 hrs. The gels were stained with ethidium bromide (Sigma-Aldrich
Inc., St. Louis, MO), and the amplification products visualized and photographed using an ultra-violet imaging system (UVP, Upland, CA).
Chromosome walking
The first screening of the BAC library used primers designed from the sequences of RAPD markers linked to EFB resistance. Subsequent screenings were conducted in stepwise manner using primers designed from the end sequences of
BACs identified in the previous step.
BAC end sequencing
Positive BAC clones were cultured overnight in liquid 2x YT media and DNA extracted as described above. BAC ends were sequenced enzymatically using ABI's
Big Dye Terminator chemistry at the core lab of the Center for Genome Research and
Biocomputing (CGRB) at Oregon State University. A total of 2.2 µg of BAC DNA was submitted along with 100 pmol of each of two primers, T7 and SP6. Both ends of the BAC were sequenced.
High resolution genetic mapping
Mehlenbacher et al. (2004, 2006) identified a total of 9 RAPD markers linked to the disease resistance locus at a distance of < 6 cM .
New markers developed from
BAC end sequences were of four types: Sequence Characterized Amplified Region
(SCAR), Single Strand Conformational Polymorphism (SSCP), Cleaved Amplified
Polymorphic Sequence (CAPS) and High Resolution Melting (HRM) markers. For
110 the first three types, PCR primers were selected manually or designed using Primer 3 software (http://frodo.wi.mit.edu/primer3/) to produce an amplicon of 400-600 bp.
For HRM, the primers were selected using Lightscanner primer design software
(Idaho Technology, Inc., Salt Lake City, UT) to amplify a product of 80 - 250 bp.
PCR amplifications as described above were carried out on recombinant seedlings. A total of 87 recombinant seedlings (70 from progeny 07001 and 17 from 07002) were used for high-resolution mapping. Initial BAC end primer screening was carried out on six templates: resistant parent (OSU 414.062), susceptible parent (OSU 252.146), two resistant seedlings (one of which was 'Jefferson') and two susceptible seedlings.
PCR products were separated on 2% agarose gels, stained, and photographed.
Markers that were clearly polymorphic between the parents and in the seedlings were amplified and scored using all recombinants. For PCR products that appeared to be monomorphic on agarose gels, attempts were made to develop polymorphic SSCP,
CAPS, or HRM markers from them.
For SSCP markers, 2-4 µl of PCR product was mixed with 9 µl of loading buffer containing 95% Formamide, 0.05% bromophenol blue, 0.05% xylene cyanol and 10 mM NaOH. The samples were denatured at 94
o
C for 2 min and then immediately placed in ice to stabilize single strands and avoid heteroduplex formation.
Four µl of the denatured product was separated by electrophoresis on a 50 cm x 20 cm x 1mm mega gel (C.B.S. Scientific Company, Inc., Del Mar, CA) using a 0.5X MDE
® gel (Lonza Rockland, Inc., Rockland, ME). Electrophoresis was in 0.6X TBE buffer
111 at room temperature and constant 4W for 14-18 h. After electrophoresis, the gels were silver stained to visualize the bands (Slabaugh et al., 1997) .
To develop CAPS markers, PCR products were digested individually with a set of 15 restriction enzymes and the digestion products separated by electrophoresis on
2% agarose gels in TBE buffer at 90 volts for 3.5 hr. The gels were stained with ethidium bromide and the bands visualized and photographed using an ultra-violet imaging system (UVP, Upland, CA).
For HRM analysis, PCR was performed in a total volume of 10 µl using 1X
LightScanner high sensitivity master mix (Idaho Technology) containing LC Green
®
PLUS, 0.20 mM each of forward and reverse primer, and 25 ng of template DNA. In order to avoid evaporation during PCR amplification and HRM, each reaction was covered with 25 µl of mineral oil. Initial melt curve analysis was carried out in duplicate, with each set including the resistant parent, susceptible parent, two resistant seedlings and two susceptible seedlings. The PCR program was initial denaturation of
4 min at 95 o
C, followed by 40 cycles of 40 s at 94 o
C, 40 s at the optimal annealing temperature for the primer pair and 40 s at 72 o
C, and a final elongation step at 72 o
C for 10 min. To promote heteroduplex formation, two final steps were added: 30 s at
94 o
C and 30 s at 25 o
C. Following PCR amplification, high-resolution melting was carried out in 96-well plates (twin.tec real-time PCR Plates 96, semi-skirted black,
Eppendorf, USA; catalog no. 951022067) at temperatures from 60 o
C to 94 o
C in steps of 0.05 o
C, with a 1 s hold at each step, in a LightScanner Instrument (Idaho
112
Technology, Salt Lake City, UT). Analysis was with LightScanner
®
with Call-IT
®
2.0 software modules (Idaho Technology).
Fine genetic mapping of the resistance region
RAPD markers, newly-developed markers from BAC end sequences (SCAR,
SSCP, CAPS and HRM markers), and disease phenotype scores were used for fine mapping with JoinMap v 4.0 (van Ooijen and Voorrips, 2006) and the two-way pseudo-testcross progeny strategy (Grattapaglia and Sederoff, 1994) as described by
Sathuvalli et al. (2010b). Recombinant seedlings were scored for all new markers
(Table 5.1). For seedlings in which flanking RAPD markers 152-800 and 268-580 were present, all new markers were also scored as present. For seedlings in which the two flanking markers were absent, all new markers were scored as absent.
BAC fingerprinting and contig assembly
High Information Content Fingerprinting (HICF) of 91 BACs was carried out at the Clemson University Genomics Institute (CUGI)
( http://www.genome.clemson.edu/ services/genomics/physical_mapping).
At CUGI, the BAC clones were subjected to miniprep and restriction enzyme digestion, and labeled with a SNaPSHOT kit (Applied Biosystems). Fluorescently-labeled fragments were then separated by capillary electrophoresis on an ABI3730 or 3730xl DNA
Analyzer. The BAC clones in wells E7 and H12 of the 96-well plates were used as controls to assess data uniformity. BACs were fingerprinted and assembled into contigs at a threshold of 1×e
-35
using the program FPC v9.3 (Nelson and Soderlund,
113
2009). Using the HICF information, two separate contigs were developed, one for the resistant and one for the susceptible homolog.
Determination of homolog origin
As 'Jefferson' is heterozygous at the resistance locus, it inherited resistance and linked markers from OSU 414.062. The second chromosome is from susceptible parent OSU 252.146. Therefore, some of the identified BACs may be from the resistant homolog and others from the susceptible homolog.
SCAR, SSCP, CAPS and
HRM markers were used to determine the homolog origin of the identified BACs.
Each BAC-derived marker was generated using PCR and four templates: the resistant parent, susceptible parent, 'Jefferson' and the BAC from which the marker was developed. The BACs were assigned to a homolog based on the origin of the allele as revealed by the pattern of polymorphism determined by amplifing the primer pair in the resistant parent, susceptible parent, ‘Jefferson’ and the identified BAC clone . If a
BAC had been assigned to a single contig by HICF, the whole contig was assigned to a homolog based on one or more polymorphic markers from BACs in the contig.
Results
Chromosome walking and high resolution mapping
Previous mapping of the ‘Gasaway’ resistance locus (Mehlenbacher et al.,
2004; 2006) used a full-sib progeny of 144 seedlings, and placed the locus between
RAPD markers 152-800 and 268-580 at a distance of 1.4 cM and 6.1 cM, respectively.
No recombination was observed between resistance and the RAPD markers X01-825,
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AA12-850 and W07-375. 173-500 was placed on the 152-800 side at a distance of 0.7 cM from the resistance locus. H04-850 and V20-800 were placed on the 268-580 side at distances of 0.7 and 2.2 cM, respectively, from the resistance locus. Amplification of 1488 seedlings from progenies 07001 and 07002 with RAPD primers identified 87 seedlings that showed recombination between flanking markers 152-800 and 268-580.
These recombinants were the focus of the fine-mapping. Four RAPD markers (AA12-
850, 173-500, X01-825 and W07-375), one SCAR marker derived from the sequence of RAPD marker H04-850, one HRM marker derived from the sequence of X01-825, and another HRM marker derived from the sequence of W07-375 were mapped to the region between 152-800 and 268-580. We were not able to score RAPD marker H04-
850 with confidence, as it is sensitive to primer and Mg concentration, and so excluded the scores in map construction. We purchased a new tube of primer V20, but were not able to duplicate the banding pattern of the original primer, and so do not present data for this marker.
Scores for RAPD marker 726-665 were included to confirm the scoring of 268-580. The initial map (Fig. 5.2) includes disease scores,
RAPD markers, and the SCAR and HRM markers developed from RAPD marker sequences. It spans a distance of 4.43 cM, with resistance flanked by RAPD markers
W07-375 and X01-825 at distances of 0.05 and 0.06 cM, respectively. Two primer pairs for each of 8 RAPD markers were designed and used to probe the BAC library using a PCR-based pooling and subpooling approach. After the initial step, two further rounds of chromosome walking were carried out. In the second and third steps, the BAC library was probed with primers designed from BAC end sequences.
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Only markers from the ends of BACs identified by the four RAPD markers closest to the resistance locus (173-500, AA12-850, W07-375 and X01-825) were used in the second and third screening. The number of hits from probing the library ranged from a maximum of 8 to a minimum of no hits. In most cases, the PCR products (primer pairs designed from either RAPD or BAC end sequences) showed no polymorphism between the parents, and presumably the identified BACs include both the resistant and susceptible homologs.
After two rounds of chromosome walking, 93 BACs had been identified. They were subjected to HICF and then assembled into contigs. A total of 91 BACs were fingerprinted, and assembled into 22 contigs and 23 singletons. The number of contigs exceeds the number of probes, as would be expected if some primer pairs amplified sequences from resistant and susceptible homologs. It is also possible that some are false positives .
Fine mapping with markers derived from BAC sequences allowed us to identify the contigs in the resistance region.
Fine mapping of the EFB resistance region
All primer pairs derived from BAC end sequences were initially tested for polymorphism using six templates: the resistant parent, susceptible parent,
‘Jefferson’, one other resistant seedling, and two susceptible seedlings. Markers that showed polymorphism on agarose gels were amplified in all recombinant seedlings and mapped. For PCR products that appeared to be monomorphic on agarose gels, we attempted to develop other types of markers (SSCP, CAPS or HRM) from them, and map those that showed polymorphism. From each BAC end sequence, we designed
116 two primer pairs. One pair generated a product of 400-600 bp, and the second pair generated a shorter fragment (80-200 bp) suitable for HRM analysis. With two forward and two reverse primers, it is possible to generate four different amplicons per
BAC end. For few BAC ends we designed only one set of primers. Amplification of hazelnut template DNA with 629 primer combinations resulted in identification of 63 polymorphic markers. Of these, 41 markers mapped to the resistance region, while 22 others did not. These 22 markers may have been developed from BACs that are from sequences from the susceptible homolog in 'Jefferson' or are from false negatives.
A high-density genetic map constructed with 51 markers (Fig. 5.3), including previously-identified RAPD markers, spans a distance of 4.45 cM. The map averages
0.03 cM between the markers, and includes 24 SCAR, 7 SSCP and 9 HRM, 4 SSR
(simple sequence repeat) and 7 RAPD markers, and the disease resistance locus, but no CAPS markers. The map from 173-500 to X01-825 spans 0.95 cM and includes the resistance locus and 34 markers (Fig 5.3). This high-resolution map enabled us to construct a physical map of the region.
Homolog determination and physical map construction
'Jefferson' is heterozygous at the EFB resistance locus, and thus the library contains BACs from the resistant and susceptible homologs. The homologs would have similar but not identical sequences. Some primer pairs designed from sequences linked to resistance might amplify only sequences from the resistant homolog, while other primer pairs might amplify sequences from both homologs. It was necessary to assign all BACs to either the resistant or susceptible homolog. The co-dominant
117
SCAR, SSCP and HRM markers used for fine mapping were invaluable for homolog determination. We were able to successfully assign all contigs as resistant or susceptible, except for the contig for RAPD marker 268-580 for which no markers were polymorphic.
The high resolution genetic map allowed us to align the markers and the BACs, and thus create a physical map of the resistance region (Fig. 5.4). The physical map of the resistant homolog consists of four contigs of at least two BACs each, and three individual BACs. BACs in the susceptible homolog were identified for all RAPD markers except 152-800 and 173-500 for which all identified BACs were from the resistant homolog. The physical map (Fig. 5.4) shows that 50 markers were assigned to the resistant homolog. Further work is essential with the unmapped markers to place them on the linkage map, assign some of them to the susceptible homolog origin, and identify false positives.
The fine map shows a single recombination event (seedling UY44) between the resistance locus and markers W07-SSR-HRM and BAC43F13-T7 and on the other side a single recombination event (seedling VC55) between the resistance locus and markers BAC 43F13-SP6 and BAC96K15-T7. The two different recombination events within BAC43F13 confirm that this BAC contains the resistance gene. The size of BAC43F13, estimated by pulsed field gel electrophoresis, is 135 kb.
BAC43F13 overlaps two other BAC clones, 85B7 and 66C22.
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Discussion
Genetic linkage maps are useful for the identification, isolation and study of genes, and provide markers for use in marker-assisted selection in the breeding programs. A fine- or high-resolution map that identifies tightly linked markers that flank the gene of interest (usually < one cM) is a prelude to map-based cloning efforts.
Many studies have stressed the importance of high-resolution maps for map-based cloning approaches (Meksem et al., 1995; Krattinger et al., 2009; Yang et al., 2001;
Bradeen et al., 2003). According to Bennetzen (2000), the most common problems associated with fine mapping are (i) plants have relatively large genomes and hence most linked markers may be many cM away from the targeted gene (ii) recombination is relatively rare in plants and thus requires investigation of hundreds to a few thousand sexual progeny to map markers to a resolution of 0.1 to 1 cM, (iii) tightly linked markers lack polymorphism in the mapping population and thus cannot be mapped. Hazelnut has a small genome (385mb). We observed many recombinants near the EFB resistance locus, and 34 of the 72 new marker loci were polymorphic
(Fig 5.3; Fig 5.4). Thus we encountered none of these limitations in our work with hazelnut.
For identification of rare recombinants and fine mapping of the EFB resistance region, we created a population of 1488 seedlings, screened for flanking RAPD markers 152-800 and 268-580, and identified 87 recombinants. Mehlenbacher et al.
(2004; 2006) placed five RAPD markers within this region and identified an additional
RAPD marker that co-segregated with 268-580. The previously identified RAPD
119 marker H04-800 was difficult to score, so we developed a SCAR marker from the sequence. We were unable to map V20-800 as new primer did not generate the same banding pattern. HRM markers were developed from the sequences of RAPD markers X01-825 and W07-375. The primers for W07_HRM flank a microsatellite repeat. Eight markers (5 RAPDs, 1 SCAR and 2 HRM markers) and disease resistance scores for the recombinant seedlings allowed construction of the genetic map (Fig. 5.2) that was the start of our efforts at map-based cloning of the EFB resistance locus from 'Gasaway'.
We used PCR with a pooling and sub-pooling strategy to probe the BAC library. Similar strategies have been described previously (Bouzidi et al., 2002;
Ozdemir et al., 2004; Asakawa et al., 1997; Klein et al., 2000). Our two-step approach used plate pools in the first step, and row and column pools in the second step. We designed two primer pairs from the RAPD marker sequence for screening the BAC library. With two primer pairs, we screened the BAC library twice for each region.
The expectation was that all hits detected with one primer pair would also be detected with the second primer pair. However, if a primer pair detects a hit and the other does not, it may be an actual hit and an escape (false negative), possibly due to PCR failure.
The disadvantage of screening with two primer pairs per sequence is that it increases the time spent on screening, and increases the chance of identifying false positives.
We chose to design and use two primer pairs per marker sequence, as we wanted to obtain the maximum number of hits.
120
Efficient fine-scale mapping and positional cloning largely depends on the relationship between the physical and genetic distances (Ballvora et al., 2001).
Accurate phenotyping is also essential to position the resistance locus. With EFB, inoculation and appearance of symptoms are separated by 18-20 months. As a result, the chromosome walk was initiated before disease scores were available. Two rounds of chromosome walking had been completed before the disease scores became available. These two rounds resulted in identification of 93 BACs that were fingerprinted with HICF, but were able to place only 36 BAC clones in the region between 152-800 and 268-580 (Fig. 5.4).
A challenge in mapping is the lack of polymorphism between the parents at new marker loci developed from BAC end sequences. With the use of SSCP and
HRM techniques, we were able to visualize polymorphism in many cases where bands on agarose gels were monomorphic. We were not able to develop any CAPS markers in the region using a set of 15 restriction enzymes, which is a trial-and-error approach.
SSCP and HRM are promising techniques in detecting polymorphism based on singlenucleotide polymorphisms (SNPs). A constraint of SSCP markers is the long gel running time (14-18 hrs). HRM avoids the use of gels, but scoring is challenging if the sequences contain several SNPs and thus multiple melting domains. We found
SSCP and HRM markers to be more efficient than the CAPS markers for genetic mapping.
Hazelnut is highly heterozygous throughout its genome, and 'Jefferson' is heterozygous at the resistance locus. Thus, probes of the 'Jefferson' BAC library
121 would likely identify hits from both resistant and susceptible homologs. For physical map construction, it is essential to assign BACs to a homolog. SCAR, HRM and
SSCP markers are very useful for homolog assignment. For BACs in a contig, assignment of one marker in one BAC is sufficient for assignment of the contig to a homolog.
The high-resolution genetic map enabled us to construct a physical map of the
EFB resistance region. The combined maps identified a single contig that spans the
EFB resistance locus. The 1488 seedlings showed two recombination breakpoints within a physical distance of 135 kb. This region is the target for future whole BAC sequencing and a search for disease resistance genes.
Plants utilize various defense mechanisms (both passive and active) to counter pathogen attack. Often these mechanisms are controlled by resistance genes ( R genes) that confer high levels of resistance but sometimes only to specific pathogen genotypes. More than 55 R genes have been cloned from different monocot and dicot plant species (van Ooijen et al., 2007; Martin et al., 2003). These R genes confer resistance to different pathogens and have been assigned to groups based on similarity in their DNA sequences. Many R genes have nucleotide binding site (NBS), kinase, or leucine-rich repeat (LRR) domains. Based on the encoded conserved elements, R genes have been assigned to different classes (Hulbert et al., 2001; Martin et al., 2003; van Ooijen et al., 2007; Kozjak et al., 2009). The vast majority of cloned R genes encode NBS-LRR proteins. These NBS-LRR R genes are abundant in plant genomes, comprising an estimated 1% of the genes in the Arabidopsis genome (Meyers et al.,
122
1999). Degenerate primers have been developed in and around the conserved amino acid motifs for PCR-based amplification of R -gene like sequences commonly called resistance gene analogs (RGAs) (Ballvora et al., 2002; Leister et al., 1996; Bradeen et al., 2003). The homology-based identification of genes in conjunction with positional cloning was successfully employed to isolate R genes at the maize Rp1-D locus
(Collins et al., 1999) and Bs4 locus in tomato (Schornack et al., 2004).
To conclude, we successfully identified BACs in the region of the EFB resistance gene from 'Gasaway'. By sequencing these BACs and using a candidate gene approach (Collins, 1992), we aim to identify resistance gene-like sequences.
Additional complementation experiments will then be needed to confirm which of the identified genes confers resistance to the pathogen.
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Fig. 5.2
. Map of the EFB resistance locus, seven RAPD, two HRM, and one SCAR marker in the hazelnut progeny OSU 252.146 x OSU 414.062 and its reciprocal.
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Fig. 5.3.
High-resolution genetic map of the EFB resistance locus, including new markers developed from BAC end sequences, in the hazelnut progeny OSU 252.146 x
OSU 414.062 and its reciprocal. New markers developed from BAC ends are described in Table 5.1.
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Chapter 6
ANNOTATION OF WHOLE BAC SEQUENCES IN THE
EASTERN FILBERT BLIGHT RESISTANCE REGION FROM
‘JEFFERSON’ HAZELNUT (
)
Vidyasagar R. Sathuvalli, Shawn A. Mehlenbacher and Todd C. Mockler
136
Abstract
Eastern filbert blight (EFB) is a devastating disease in European hazelnut
( Corylus avellana L.) in Oregon. Complete resistance in the obsolete pollinizer
‘Gasaway’ is conferred by a dominant allele at a single locus. A bacterial artificial chromosome (BAC) library for 'Jefferson', which carries resistance from 'Gasaway', was probed using RAPD markers tightly linked to resistance to initiate a chromosome walk. The identified BACs were sequenced using Illumina technology. In this study, we identified and annotated the coding sequences in these BACs using the gene prediction program AUGUSTUS with Arabidopsis as the model. RNA-seq data
(Mockler 2010 unpublished
) for ‘Jefferson’ was used to support the gene predictions.
In seven contigs from the region <1 cM from the EFB resistance locus, AUGUSTUS predicted 233 genes. RNA-seq data supported 73 of these at a 60% cutoff and 43 at an
80% cutoff. The putative genes were compared with sequences in GenBank using a
BLASTP search (NCBI). Two of the putative genes in the resistant contig 4 encode genes in the p-loop NTPase and F-box super-families. Future complementation and mapping studies are essential to confirm which gene confers resistance.
Introduction
Eastern filbert blight (EFB), caused by Anisogramma anomala , is a devastating disease on European hazelnut ( Corylus avellana L.). Host genetic resistance is a desirable way to avoid the expense and time commitment involved in scouting, pruning, and spraying to control the disease (Mehlenbacher, 1995). Resistance from
137
'Gasaway', an obsolete pollinizer, has been extensively used in the hazelnut breeding program at Oregon State University (OSU). Disease resistance is a major objective of the breeding program. Our goal in this study was to isolate the 'Gasaway' EFB resistance gene(s).
Plants utilize various defense mechanisms (both passive and active) to counter pathogen attack. Often these mechanisms are controlled by resistance genes ( R genes) that confer high levels of resistance but sometimes only to specific pathogen genotypes. R genes are frequently used in breeding, and >55 have been cloned from different plant species (van Ooijen et al., 2007; Martin et al., 2003). Based on the encoded conserved elements, R genes have been assigned to different classes (Hulbert et al., 2001; Martin et al., 2003; van Ooijen et al., 2007; Kozjak et al., 2009). The vast majority of cloned R genes encode putatively cytoplasmic proteins with nucleotidebinding site and leucine-rich repeat (NBS-LRR) domains (Dangl and Jones, 2001;
Ellis et al., 2000). Other classes of R genes include receptor-like protein (RLP), receptor-like kinase (RLK), protein kinase, toxin reductase, and membrane protein.
While genome sequencing technology advances and cost reductions have been dramatic, the mining of useful information from the sequence data remains a challenge. In order to benefit from the huge amounts of sequence data, annotation tools must be reliable and the databases must be consistent (Bakke et al., 2009). More than 40 gene annotation tools are now available for both prokaryotes and eukaryotes
(geneprediction.org) for effective analysis of sequence data. Most of these programs are trained for model organisms which have well-defined expressed sequence
138 information available. For other organisms, ab initio gene finder programs are available which use information from the already-established gene annotation programs.
Our recent map-based cloning efforts constructed a high resolution genetic and physical map around the EFB resistance region using a bacterial artificial chromosome
(BAC) library for ‘Jefferson’ hazelnut and the mapping population from which it was selected (Chapter 5). 'Jefferson' is heterozygous at the resistance locus. The physical map covering <1 cM of the resistance region has seven contigs, four of which are from the resistant homolog. Here we report using the ab initio gene annotation program
AUGUSTUS (Stanke et al., 2008) and RNA-seq data from 'Jefferson' hazelnut to predict the genes in these seven contigs.
Materials and Methods
Plant material
DNA of 'Jefferson' hazelnut was used to construct a BAC library (Sathuvalli and Mehlenbacher, 2009). RNA extracted from leaves, bark and catkins of ‘Jefferson’ and roots of several different seedlings was the source of the RNA-seq data.
BAC sequencing and data analysis
A previous study (Chapter 5) identified 22 BACs within 1 cM of the EFB resistance locus, and assembled them into 7 contigs. Twenty of the 22 BACs were sequenced using an Illumina IIx Genome analyzer and assembled de novo using the programs Velvet (Zerbino and Birney, 2008) and SOPRA (Dayarian et al., 2010). The
139 sequences were further aligned using CodonCode Aligner software (CodonCode
Corporation, Dedham, MA, USA; http://www.codoncode.com) as described by
Sathuvalli (Chapter 4) .
RNA was extracted from the various tissues, and the cDNA was sequenced using an Illumina IIx genome analyzer. The RNA-seq data was provided by the Mockler lab at Oregon State University.
Gene prediction was carried out using the assembled BAC contig sequences and the program AUGUSTUS (Stanke et al., 2008) as described in the program manual using Arabidopsis as the reference. The AUGUSTUS program requires that interspersed repeats and low complexity DNA sequences from the genome sequences are removed to compare with RNA-seq data to obtain hints data for the transcript predictions. For this, the assembled BAC sequences were masked using the software
Censor (Kohany et al., 2006).
With gene predictions from AUGUSTUS and hints supported by the RNA-seq data, attention was focused on sequences with >60% support. A BLAST search using the amino acid sequences of the predicted genes was carried out against the nonredundant protein sequence database (http://blast.ncbi.nlm.nih.gov/Blast.cgi) with a cutoff of 1 × e
-05
.
Results
The AUGUSTUS program predicted a total of 233 genes in the seven contigs.
For these, the transcript support from the RNA-Seq hints ranged from 0 to 100%. The number of predicted genes in each contig ranged from a minimum of 15 for contig5 to
140 a maximum of 62 for contig3 (Table 6.1.). Using the RNA-Seq data and 60% as the cutoff for transcript support, the predicted number of genes is 73, of which 32 have
100% support.
A BLAST search of the protein sequences of the 73 predicted genes identified
35 putative genes with at least one hit (Table 6.2). In most cases the predicted genes were similar to hypothetical proteins in Vitis vinifera .
A previous study (Chapter 5) placed the EFB resistance gene in contig4. A
BLASTP search of the putative gene sequences with >60% transcript support from
RNA-Seq hints in contig4 identified five gene with certain protein homology (Table
6.2). Three of the five putative genes belong to protein super-families; a resistance gene analog P-loop NTPase super-family, an F-box super-family and a pollen allerg-1 super-family with RNA-Seq support of 75, 100 and 100%, respectively. Of these three super-families, the P-loop NTPase super-family (Contig4_g19) and F-box superfamily (Contig4_g25) have disease resistance properties. Analysis of the susceptible contig in the same region identified one putative gene of the resistance gene analog Ploop NTPase super-family, with 60% transcript support.
Discussion
We used the AUGUSTUS gene prediction program to identify putative genes in seven contigs within one cM of the EFB resistance locus. Although there are many programs available to predict genes in DNA sequences, we chose AUGUSTUS because of its ability to incorporate RNA-Seq data. AUGUSTUS predicted 233 genes
141 in the DNA sequences. Utilization of RNA-Seq data reduced the number of predicted genes to 73 at a 60% cutoff (see Appendix for predicted protein sequences), 43 at an
80% cutoff, and 32 at a 100% cutoff. We used Arabidopsis as the model to train the program. Although AUGUSTUS can be trained with tomato ( Solanum lycopersicum ) and maize ( Zea mays ), we chose Arabidopsis as our model for gene prediction because
Arabidopsis and Corylus are distantly related and belong to the same clade, the
Rosids. Furthermore, Arabidopsis is well-annotated compared to tomato and maize.
The RNA-Seq data was an invaluable resource for ab initio gene prediction.
Hints from the RNA-Seq data supported the gene predictions from 0 to 100%. We chose a 60% cutoff prior to the BLAST search, and this reduced the number of predicted genes from 233 to 73. Use of the 60% cutoff also reduced the risk of false positive gene predictions.
A previous study (Chapter 5) identified contig 4 as containing the EFB resistance gene. The search for homology of the predicted genes in contig 4 showed two interesting conserved domains related to plant defense. The predicted gene
Contig4_g19 is related to the P-loop NTPase super-family which includes NBS-LRR type R proteins and other signal transduction ATPases, numerous STAND (signal transduction ATPases with numerous domains) class proteins that include the AP-
ATPases (animal apoptosis regulators CED4/Apaf-1, plant disease resistance proteins, and bacterial AfsR-like transcription regulators) and NACHT NTPases (e.g. NAIP,
TLP1, Het-E-1) (Leipe et al., 2004; Takken et al., 2006). As most of the R genes identified to date have the p-loop NTPase domain that is primarily responsible for
142 disease resistance, this putative gene might play an important role in EFB resistance.
Analysis of the susceptible contig from the same region identified a similar gene
(Contig5_g4) encoding the p-loop NTPase family. However, the percentage of transcript support from the RNA-Seq data is rather low (60%) compared to the sequence in the resistant contig (75%). Further study in this region is essential to find whether the putative p-loop NTPase gene is expressed in both the resistant and susceptible plants.
The predicted gene Contig4_g25 belongs to the F-box super-family with
100% transcript support from the RNA-Seq hints. F-box proteins are substraterecognition components of the skp-1-Rbx1-Cul1-F-box protein 9SCF ubiquitin ligases
(Xu et al., 2009). Plant F-box genes form one of the largest multi-gene super-families that have been found to control many important biological functions such as plant disease resistance, senescence, embryogenesis, hormonal responses, seedling development and floral organogenesis (Lechner et al., 2006; Xu et al., 2009). Defense related F-box proteins include the COI1 (CORONATINE INSENSITIVE) protein in
Arabidopsis and its homolog in tomato, JA1 (Li et al., 2004); and the SON1
(SUPPRESSOR OF NIM1-1), a negative regulator of Hordeum parasitica in
Arabidopsis (Kim and Delaney, 2002). Further, Cao et al. (2008) showed that overexpression of the rice defense-related F-box protein gene OsDRF1 in transgenic tobacco resulted in enhanced disease resistance against tomato mosaic virus (ToMV) and Pseudomonas syringae pv. tabaci and Dagdas et al. (2009) showed that a new
ZTL-type F-box functions as a positive regulator in powdery mildew disease
143 mechanism in barley. Thus, this predicted gene, which is absent in the susceptible contig sequence, might play an important role in EFB resistance.
Apart from these two gene families, the BLAST search revealed many other protein families like the Pollen allerg1 super-family which might play a role in resistance (Table 6.2). Further study including fine mapping is essential to understand these and other putative genes, with complementation studies to confirm which gene is responsible for resistance.
98
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98
146
98
147
148
References
Bakke, P., N. Carney, W. DeLoache, M. Gearing, K. Ingvorsen, M. Lotz, J. McNair,
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Cao, Y., Y. Yang, H. Zhang, D. Li, Z. Zheng, and F. Song. 2008. Overexpression of a rice defense-related F-box protein gene OsDRF1 in tobacco improves disease resistance through potentiation of defense gene expression. Physiologia
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150
Chapter 7
SUMMARY
European hazelnut, Corylus avellana L., is the only economically important nut crop in the family Betulaceae. Because of its small genome size (1C ~385 Mb), relatively short life cycle, availability of a dense linkage map, and amenability to transformation by Agrobacterium , the European hazelnut could serve as a model plant for the Betulaceae. One of the threats to the hazelnut industry in the Pacific Northwest is the fungal disease eastern filbert blight (EFB), caused by the pyrenomycete
Anisogramma anomala (Peck) E. Müller. A dominant allele at a single locus from the obsolete pollinizer 'Gasaway' confers complete resistance to EFB and has been extensively used in the disease resistance breeding. Concern over the durability of this single-gene resistance prompted a search for new sources of resistance. Eighty-six accessions from ten countries were evaluated for their response to greenhouse inoculation with the pathogen. Nine accessions showed complete resistance, including one from Chile ('Amarillo Tardio'), two from Serbia ('Crvenje' and 'Uebov'), one from southern Russia (OSU 495.072) and five from Moscow, Russia. These new sources of
EFB resistance have geographically diverse origins and will broaden the genetic base of our EFB-resistant hazelnut germplasm. Further we confirmed the previously reported resistance of 'Grand Traverse' from Michigan and the susceptibility of 'Closca
Molla' from Spain.
In order to understand the genetic nature and to isolate the gene responsible for the 'Gasaway' resistance, we constructed a bacterial artificial chromosome (BAC)
151 library for 'Jefferson' hazelnut, which is heterozygous resistant. The BAC library was constructed using the cloning enzyme MboI and the vector pECBAC1 (BamHI site).
The library consists of 39,936 clones arrayed in 104 384-well microtiter plates with an average insert size of 117 kb. The genomic coverage of the library is estimated to be about 12 genome-equivalents.
Previous studies identified several RAPD markers closely linked to EFB resistance. A mapping population of 1488 seedlings, which segregates for 'Gasaway' resistance, was developed and scored for flanking RAPD markers 152-800 and 268-
580 to identify recombinants. The recombinants were greenhouse-inoculated and scored for disease phenotype. To understand the feasibility of map-based cloning, fine-resolution mapping of eight RAPD markers closely linked to resistance was carried out. The initial fine map showed that markers W07-375 and X01-825 flanked the resistance locus at distances of 0.05 and 0.06 cM, respectively. Assuming that 1 cM corresponds to a physical distance of 430 kb, we estimated that 2-3 chromosome walks would be needed to cover the resistance locus.
Chromosome walking was initiated using primers designed from eight RAPD markers linked to resistance. The BAC library was screened using these primer pairs and a PCR pooling and subpooling strategy. Two rounds of chromosome walking identified 93 BAC clones in the resistance region. A high-resolution genetic map for the resistance region was created with 51 markers that include seven RAPD markers, three SCAR markers, and markers newly developed from the BACs. In parallel to the genetic map, a physical map was constructed. Analysis of 1488 seedlings indicates
152 that the resistance gene is located in a single contig of three BACs (43F13, 66C22 and
85B7).
We sequenced whole BACs close to the resistance (< 1cM) using an Illumina
II x genome analyzer, with multiplexing and barcoded adapters to reduce the cost, and paired-end reads to facilitate de novo sequence assembly. De novo sequence assembly was carried out using the programs Velvet and SOPRA, and the resulting contigs were further aligned using CodonCode software and generated contig length ranged from
356 bp to 99632 bp. Estimated coverage of assembled BACs ranged from 64 to 100
%.
In order to obtain useful information from the whole BAC sequences, we identified and annotated the coding sequences using the gene prediction program
AUGUSTUS with Arabidopsis as the model. RNA-seq data (Mockler 2010 unpublished ) for 'Jefferson' was used to support the gene predictions. In seven contigs for the region < 1 cM from the EFB resistance locus, AUGUSTUS predicted 233 genes. RNA-seq data supported 73 of these at a 60% cutoff and 43 at an 80% cutoff.
The putative genes were compared with sequences in GenBank using a BLASTP search (NCBI). One of the putative genes encodes a p-loop NTPase and the other encodes an F-box super family.
To conclude, we identified new sources of resistance and used map-based cloning to identify one contig that putatively carries the resistance allele. Sequencing and annotation of this contig identified two potential genes associated with disease
resistance. Future complementation and mapping studies are essential to confirm which gene confers resistance.
153
154
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Appendices
185
186
Appendix A. Protocols
A) POLYMERASE CHAIN REACTION (10µl)
: 1.0µl 10x NH
4
Reaction Buffer
50mM MgCl
2
Solution dNTPs 2.5mM Solution
: 0.44µl
: 0.66µl
Sterilized deionized water
Forward Primer
: 6.0µl
: 0.5µl
Reverse Primer
DNA (15-25µg/µl)
*
: 0.5µl
: 1.0µl
BIOLASE Taq Polymerase : 0.15 units
Total : 10.0µl
*
For colony PCR, 0.1mm of colony is diluted with 100 µl of water and 1µl is used for
PCR amplification
B) HIGH RESOLUTION MELTING
LightScanner
®
Mastermix - 10µl reaction
5x Master Mix : 2.0µl
Sterilized deionized water
Forward primer
: 6.0µl
: 0.5µl
Reverse primer
DNA (25µg/µl)
Total
: 0.5µl
: 1.0µl
: 10.0µl
187
LCGreen
® PLUS+
Dye - 10µl reaction
LCGreen
® PLUS+
Solution
10x NH
4
Reaction Buffer
50mM MgCl
2
Solution dNTPs 2.5mM Solution
Sterilized deionized water
Forward primer
Reverse primer
DNA (25µg/µl)
BIOLASE Taq Polymerase
Total
: 1.0µl
: 1.0µl
: 0.44µl
: 0.66µl
: 5.0µl
: 0.5µl
: 0.5µl
: 1.0µl
: 0.15 units
: 10.0µl
The PCR mix is overlaid with 25µl of mineral oil and the PCR is carried out for at least 40 cycles as per the recommended protocol. At the end of the run, two additional steps, 30sec at 95
o
C and 30sec at 25 o
C are added to promote heteroduplex formation.
The amplified product is run on a LightScanner High Resolution Melting instrument, using melting temperatures from 60 o
C to 98 o
C and exposure to auto.
188
C) CLEAVED AMPLIFIED POLYMORPHIC SEQUENCES
Amplified PCR Product : 10.0µl
Restriction enzyme 10x Buffer
Sterilized deionized water
: 2.0µl
: 8.0µl
Restriction enzyme
Total
: 10 units
: 20.0µl
For certain restriction enzymes, BSA is added at a 1x concentration
The reaction product is incubated at the desired temperature for 3 hrs and the digested products are run on a gel to visualize the restriction patterns.
189
D) ILLUMINA SEQUENCING LIBRARY PREPARATION
Illumina library preps are carried out with 5µg of BAC DNA extracted from 30ml overnight cultures using a Sigma PhasePrep kit.
1. Fragmentation of BAC DNA a.
Place 100 µl of DNA sample (in a 1.5 ml conical tube) in the Bioruptor
(sonicator) and sonicate a total of 15 minutes per set of samples. (30 seconds sonication and 30 seconds cooling). b.
5 µl of sonicated sample is run an 1.5 % agarose gel to ensure that shearing is successful and that fragments are within the expected size ranges. c.
Clean the DNA after sonication using the Qiaquick PCR purification
Kit (Qiagen, Valencia, CA) as per the manufacturer’s instructions. At the final step elute the DNA in 20 µl of Elution Buffer.
2. Perform end repair
This protocol converts the overhangs resulting from fragmentation into blunt ends using T4 DNA polymerase and E. coli DNA polymerase I Klenow fragment. The 3’ to 5’ exonuclease activity of these enzymes removes 3’ overhangs and the polymerase activity fills in the 5’ overhangs.
Procedure:
1.
Prepare the following reaction mix:
DNA sample (18µl)
Water (0µl)
10X Blunting Buffer (2.5µl)
1mM dNTPs mix (2.5µl)
Blunting Enzyme T4 DNA Polymerase (1 µl)
190
Klenow DNA polymerase (1 µl)
The total volume should be 25 µl.
2. Incubate in the thermal cycler at 20 ºC for 30 minutes
3. Use the Agencourt AMPure Kit (refer to AMPure Notes below) to purify the
25 µl sample and elute in 20 µl.
3. Add A’ Bases to the 3’ End of the DNA Fragments
This protocol adds an A’ base to the 3’ end of the blunt phosphorylated DNA fragments, using the polymerase activity of the Klenow fragment (3’-5’ exo minus). This prepares the DNA fragments for ligation to the adapters, which have a single ‘T’ base overhang at their 3’ end.
Procedure:
1. Prepare the following reaction mix:
DNA sample (20 µl)
Klenow (NEB Buffer 2) buffer (2.5 µl) dATP, 5mM (1 µl)
Klenow exo (3’ to 5’ exo-) (1.5 µl)
The total volume should be 25 µl.
2. Incubate for 30 minutes at 37 ºC
Follow the instructions in the AMPure Kit to purify samples and elute in 9 µl of elution buffer + 13 µl of ligase buffer.
4. Ligate Adapters to DNA Fragments
This protocol ligates adapters to the ends of the DNA fragments preparing them for hybridization to a flow cell.
191
Procedure
If a sample is not being bar-coded use the PE Non-index Adapter Oligos, if a sample is being bar-coded use the PE Index Adapter Oligos mix in the following procedure.
1. Prepare the following reaction mix:
DNA sample (eluted with 9µl EB+13µl of NEB Quick Ligation buffer)
21µl
PE Index Adapter oligo mix (25mM)* (2.5 µl)
Quick Ligase (1.5 µl)
The total volume should be 25 µl.
2. Incubate for 15 minutes at room temperature.
3. Use the AMPure PCR purification Kit (*45 µl beads) to purify the samples.
Elute in 30µl of elution buffer, and then dry for 20 min or to completion in a
SpinVac until the DNA dries.
4. The samples are re-suspended in eluted in 8 µl of EB. The 8 µl is used directly for the next step.
5. Purification of ligation products
This protocol purifies the products of the ligation reaction on a gel to remove all un-ligated adapters, remove any adapters that may have ligated to one another, and select a size-range of templates to go on the cluster generation platform.
192
Procedure
Caution 1 : Illumina does not recommend purifying multiple samples on a single gel due to the risk of cross-contamination between libraries—so use a mini gel.
Caution 2 : It is important to perform this procedure exactly as described to ensure reproducibility.
1. Prepare 1.5% low melt agarose gel in 1X low EDTA-TAE. I used 1.5%large gels (250 ml).
2. Add GelRed after microwaving the TAE-agarose. The final concentration of GelRed should be 0.5X (2µl for mini; 10µl for large gel). If using ethidium bromide, add to a final concentration of 400 ng/ml.
3. To the 8 µl reaction sample add 4 µl of 6X loading buffer and run the 12 µl total volume on the low melt low EDTA agarose gel.
4. Load 5 µl of the 100 bp ladder solution to each marker lane of the gel.
5. Load samples. If samples are bar-coded, you may run them on the same gel, but it is best to leave a blank between each lane. Non-bar coded samples should be run on separate gels.
6. Run the gel at 100 V for ~90 minutes.
7. View the gel on a Dark UV trans-illuminator. Minimize the exposure of gel to UV light.
8. Cut at the 350 bp range and at 650 bp range using a clean SafeXtractor
(Fisher 5-Prime SafeXtractor-25). Each plug removed is placed into a labeled
193
1.7ml tube. I use the 650 bp plug as back-up, so I remove all of my 350 bp range plugs first.
9. If low-EDTA TAE running buffer was used, then the PCR step can be carried out directly, using 2 µl of the DNA/agarose mixture in the PCR reaction.
10. If the smear is very light, you can extract the DNA from the low melt agarose gel using a Qiagen gel extraction kit.
11. This plug is stored at -20 ° and used as needed.
6. Enrichment of adapter-modified DNA fragments by PCR
This protocol uses PCR to selectively enrich those DNA fragments that have adapter molecules on both ends, and to amplify the amount of DNA in the library. The PCR is performed with two primers that anneal to the ends of the adapters. The number of PCR cycles is minimized to avoid skewing the representation of the library.
Procedure
This protocol assumes 5 µg of DNA input into the library preparation. If 0.5
µg was used, the protocol should be adjusted as described as in the table below.
1. Heat 350 bp gel slices to 60 ºC for 10 minutes in heat block or water bath then vortex well (at least 10 seconds) to mix. Ensure that the gel is completely
194 melted before using it for PCR because the gel sets quickly after removing it from the heat.
2. Prepare the following PCR reaction mix; i.
DNA (2µl) ii.
Phusion DNA polymerase Mix (Finnzymes Oy) (12.5µl) iii.
PCR primer 1.1 (0.5µl) iv.
PCR primer 1.2 (0.5 µl) v.
Water (9.5 µl)
The total volume should be 25 µl.
3. Amplify using the following PCR protocol:
30 seconds at 98 °C
18 cycles of:
1.
30 seconds at 98 ºC
2.
30 seconds at 65 ºC
3.
30 seconds at 72 ºC (after first cycle hit pause button, remove samples and then vortex to mix the samples)
5 minutes at 72 ºC
Hold at 4 ºC
4. If want to submit, clean the PCR product with a QIAquick PCR Purification
Kit.
5. Run a 1.5 % agarose gel with 1.0 µl of PCR product to verify library size and to estimate the concentration using 12.5 µl & 6.25 µl of 100 bp ladder as a standard concentration.
195
6. Quantify the DNA using a Nanodrop spectrophotometer and Bio analyzer
(excellent for determining the band size) to determine the quantities to input for the multiplex pools. All three sources of information should be used to help decide how much of the sample to submit.
7. Preparing the Illumina Sample
To submit the sample you need the band size, concentration and the 260/280 absorbance ratio. CGRB needs 30 ul of a 10 nM stock solution (diluted in dH2O, with 0.1% Tween-20 for final concentration) for normal single-plex libraries. To make the multiplex, you simply need to divide the "total ng
DNA/30 ul" value by the number of samples you wish to multiplex.
Agencourt® AMPure® XP Purification of DNA
Agencourt AMPure XP Magnetic Particle Solution
Store at 4°C upon arrival, for up to 12 months.
The particles settle to the bottom so mix the reagent well before use. It should appear homogeneous and consistent in color. There should be no sediment at the bottom after mixing.
DO NOT FREEZE.
196
Procedure:
96 Well Format:
1. Determine whether or not a plate transfer is necessary.
If the PCR reaction volume multiplied by 2.8 exceeds the volume of the PCR plate, a transfer to a 300 µ L round bottom plate is required..
2. Gently shake the Agencourt AMPure XP bottle to resuspend any magnetic particles that may have settled. Add Agencourt AMPure XP according to the PCR reaction volume chart below:
PCR Reaction Volume (μL) AMPure XP Volume (μL)
10 18
20 36
50
100
90
180
The volume of Agencourt AMPure XP for a given reaction can be derived from the following equation: (Volume of Agencourt AMPure XP per reaction) = 1.8 x
(Reaction Volume)
3. Mix reagent and PCR reaction thoroughly by pipette mixing 10 times. Let the mixed samples incubate for 5 minutes at room temperature for maximum recovery.
This step binds PCR products 100bp and larger to the magnetic beads. Pipette mixing is preferable as it tends to be more reproducible. The color of the mixture should appear homogenous after mixing. The Matrix multi-channel pipette increases efficiency and quality of DNA for this protocol.
197
4. Place the reaction plate onto an Agencourt SPRIPlate 96 Super Magnet Plate for 2 minutes to separate beads from the solution.
Wait for the solution to clear before proceeding to the next step.
5. Aspirate the cleared solution from the reaction plate and discard.
This step must be performed while the reaction plate is situated on the Agencourt
SPRIPlate 96 Super Magnet Plate. Do not disturb the ring of separated magnetic beads. If beads are drawn out, leave a few microliters of supernatant behind.
6. Dispense 200 μL of 70% ethanol to each well of the reaction plate and incubate for 30 seconds at room temperature. Fresh 70% ethanol should be prepared for optimal results. Aspirate out the ethanol and discard. Repeat for a total of two washes.
It is important to perform these steps with the reaction plate situated on an Agencourt
SPRIPlate 96 Super Magnet Plate. Do not disturb the separated magnetic beads. Be sure to remove all of the ethanol from the bottom of the well as it is a known PCR inhibitor.
NOTE: A dry time of ~ 5 min at Room Temperature is optional to ensure all traces of ethanol are removed but take care not to over dry the bead ring (bead ring appears cracked) as this will significantly decrease elution efficiency.
7. Off the magnet plate, add 40 μL of elution buffer (Reagent grade water, TRIS
Acetate pH 8.0, or TE) to each well of the reaction plate and pipette mix 10 times.
The liquid level will be high enough to contact the magnetic beads at a 40 μL elution volume. A greater volume of elution buffer can be used, but using less than 40 μL will require extra mixing (to ensure the liquid comes into contact with the beads) and
198 may not be sufficient to elute the entire PCR product. Elution is quite rapid and it is not necessary for the beads to go back into solution for it to occur.
8. Place the reaction plate onto an Agencourt SPRIPlate 96 Super Magnet Plate for 1 minute to separate beads from the solution.
9. Transfer the elutant to a new plate.
For long term freezer storage, Agencourt recommends transferring Agencourt
AMPure XP purified samples into a new plate to prevent beads from shattering.
199
E) BAC SCREENING (PCR BASED)
PCR based method: Initial step for PCR based screening of BAC involves developing pools of BAC library
1.
Have 150mm x 15 mm plates ready with LB media (with antibiotic) before going for replication of BAC clones.
2.
Take out the BAC library plate from -80 o
C and allow it to thaw under laminar flow chamber.
3.
Before replicating, the 384 well replicator should be sterilized using bleach for
1 min followed by a sterile water wash for 1 min and finally dipping in 95% alcohol and flaming.
4.
Once the BAC plates are thawed, with the help of replicator, the BAC clones are replicated on the LB agar petri plates (with antibiotic) and incubated overnight at 37 o
C.
5.
Once the BAC clones are grown, all the clones in each petri dish are picked and then regrown overnight at 37 o
C in LB liquid media (with antibiotic) (25-
500ml)
6.
Once the pooled bacteria are grown the plasmid DNA is extracted using either
BAC plasmid prep kit or traditional methods (alkaline lysis).
7.
About 50 to 100 µl of the grown culture can be store for future use. This can be done by mixing equal quantities of culture and glycerol stock added together and stored at -80 o
C.
200
8.
The plate pool DNA is used as template DNA and PCR amplified using the
SCAR primers that have been developed.
9.
Once the positive BAC plate is identified, follow the procedure from step 1 but in step 5 instead of pooling the whole plate, each individual row or column is pooled to get row/column DNA and then screen with the same SCAR primers to identify the row or column of interest.
10.
Once the row or column of interest had been identified, a colony PCR is carried out for each clone either in the row or column to identify the single
BAC clone.
11.
If we have hits on several different plates, the same procedure is employed for all the plates that show hits.
12.
The identified BAC clone is picked and recultured in liquid media and the pure plasmid DNA is extracted and then snet for BAC end sequencing using the sequencing primers of the plasmid used for BAC library construction.
201
F) SINGLE STRANDED CONFIRMATION POLYMORPHISM GELS
Solutions:
6XTBE
64.8g Tris base
33g boric acid
24ml 0.5M EDTA pH8
H
2
O to 1liter
Running Buffer (0.6X TBE)
200ml 6X TBE diluted to 2 liters
Sample Load Solution, per ml
950µl Fornanude
10µl 1M NaOH
40µl 1% dyes (10mg/ml each bromophenyl blue and xylene cyanol in water)
0.5X MDE Gel Solution (120ml, for each gel using 1mm spacers and comb.)
H
2
O
MDE solution
6XTBE
78ml
30ml
12ml
10%APS
TEMED
873µl (100mg ammonium persulphate in 1ml of water)
175µl
Add TEMED just before pouring the gel, parafilm the flask, and invert a few times to mix.
Bind Silane diluent (95% ethanol, 0.5% glacial acetic acid)
49.75ml 95% ethanol
250µl glacial acetic acid
Silver Stain Fixer (10liter)
1.05liter 95% ethanol
50ml glacial acetic acid
8.9 liter H
2
O
Silver Nitrate Solution
800ml fixer
1.6g silver nitrate
202
Developer
925ml H
2
O
75ml 10N NaOH
1ml Formaldehyde (37%)
Procedure
1.
Treat unnotched plate with Bind Silane
3ml Bind Silane diluent
9µl Bind Silane
Prepare fresh binding solution and wipe onto a scrupulously cleaned unnotched plate with Kimwipe, in the hood. Be sure the plate is completely treated with solution. After 5 min, apply approximately 2ml 95% ethanol to the plate and wipe with Kimwipe in one direction and then perpendicular to the first direction using gentle pressure. Repeat this wash ~ 3 times, using a fresh
Kimwipe each time, to remove excess binding solution. This is essential to prevent the binding solution from contaminating the notched glass plate, which could result in a torn gel.
2.
Treat notched plate with RainEx (This is unnecessary if water beads on the surface of the plate and only needs to be done every 4-5 runs). Change gloves before handling the notched plate to prevent cross contamination with binding solution. Wipe a scrupulously cleaned plate using a tissue saturated with
RainEx or SigmaCote. After 5-10 minutes, remove excess by wiping with a
Kimwipe.
203
3.
Set up the plate sandwich. With the Bind Silane-treated side of the notched plate facing up, install the blue rubbery sealing strip with the bead toward the
Bind Silane-treated side. Be sure the slits in the rubbery strip are at the rounded corners and that the strip is evenly pressed all the way to the glass on the edges. Place a 1mm thick side spacer inside the strip on each side. Lower the notched plate onto the rubbery strip with glass edges even. Check to be sure the strip has not bulged out or otherwise messed up anywhere, or you will have leaks. Apply clamps along bottom and sides of glass sandwich.
4.
Pour the gel to the glass sandwich slowly. Any bubbles that get trapped can be removed by tipping the glass sandwich to the left or right. Add the gel solution almost all the way to the notch. Put the comb in slowly, checking for any little bubbles trapped under the teeth.
5.
Allow acrylamide to polymerize for 1-2hr.
6.
Remove clamps, rubber strip and combs and assemble the glass sandwich to the gel apparatus. Add buffer to top and bottom reservoirs, remove any bubbles from under the sandwich with a Pasteur pipette, and flush any bubbles out of the wells with a syringe and 18-ga needle. Pre-run the gel 20-30 min
(4W Power) to equilibrate the gel to the running temperature.
7.
Sample prep: 2-4µl PCR product + 9µl Sample load solution. Incubate at 95 o
C for 2 min, then quick-cool in ice/waterbath. Load 4µl of sample per well.
8.
Run the gel
Set values: 250 Volts
4 Watts
100 milliamps
204
Run the gels for appropriate time depending on sizes of PCR fragments
(12-16hr)
9.
At the end of the run remove the glass sandwich from the apparatus and lay on lab mat with notched plate up. Remove the side spacers and very gently pry the plates apart using the black plastic wedges along one of the short edges.
Transfer the gel on the glass plate to a plexiglass try containing 1L of Fixer.
Set tray on a shaker to oscillate very slowly. Fix for 5-10min, discard Fixer solution and add stain solution. Stain the gel with slow shaking for 5-10min, collect stain into a beaker and save for precipitating the silver. Rinse the gel two times with water before adding the Developer. Bands should appear in 15-
20 min.
205
Appendix B. Predicted gene (amino acid) sequences
Amino acid sequences of predicted genes using the program AUGUSTUS with 60 percent or more of the transcript being supported by hints generated from RNA-Seq data
Contig1 (from UBC173-500)
>Contig1_g2
MKVEGYDEFMLATAFDHLNGDEKLARGFLVKNAKLRKFWFDNFFKNHGN
>Contig1_g4
MGVAEPRGWLGHPLGLQGGWGWFRPPPRLHGVAWPPPVGTGGGFSHPVGA
QGHPQMASHPQS
>Contig1_g7
MSGDEGSGSDGLGGNTYPACWRPLLTKADEARIREECFIPKSVKLRFDDERVG
AIVRSDAHEVCLYETMFRAGFRLPFPPIIRELLSYLNLAPHQIVPNAWRLIYAC
VLLWPLALGPGHYLTAREFLWVYRLQKNPKCDGLYNFQSRRGKFVHVDGKY
SSNHAWKGKYFFATGQWEFHPTEVAQGPRVPRETSVPAGNASKEPTLTDSEQ
QHVNDVLRWTQKHESLLSYSLLMSTTLKGKGLVAVDGGVGGGKKRLAFVIT
RDPKLVISDPPAANTWGATPKKARLDKGKGKLIESPKQKNLPLAKKLNPPPRV
ARALCLVDEPVESDKPVAPQPKKRKLVKAAEMKVQDQFASLLAARRKAAPR
PVVKPVAEVEAFLANEPVPARPLNATPLASDGVEARTAIPIESLSLQPLGSNIQ
HIMDDIELVEHSDSSVEMVCERTEGPTAAVEGSRPLSPIDEAEPEAHDPISTKA
RTTTPTTVGKVAEKDSTKERESAAETSSSFVSPIRPRGVDWTVGGRLADFSGN
LKGNPFLALCIIFLFLSFFFVFVFFFFFLYIHKVANDSATKINTLQGLVTDLEAEN
ARLKEVVAKQDEELLLSGRQQSIMEAETSEAAAARARAESKATELAAEIEGLR
AEINRLQEDNSIIKEDLNQLGEAHTGVSDQLELAQAEILDQKNLVVKTNEAKV
IAEEKLKFFKGKYIQVRAQLKEAKSRAANYLSWAKDSTQKIDLDRVKIEDIPC
SDAAMAQLVNLGQEQMPDAAGIKNFSSIPSQINIAMVPSLILMTPHPRPILSSPY
LPRLPVLILLLPLRQHNVIPFDSSLYIPQVP
>Contig1_g12
MRGSSARHTFCAQVPSPSVDTRTVDTVVPDVERSYQVVLQLYKNGVILCSHL
PKLLKGLLYFFERAIPLLLPPCRRGCSISSSLVGCGGRRNRNQCGLVQEIIEAVS
SPVGDEGEAHHMKNLTDHDKIDAQVIALEVVHLETPFSLHLHPMGTFVREVL
206
NHLCASGKAINWPRITEVTHSWGLGDAADKVRSHYNQLAPKPSPEGVAVPLL
DIGRPYPQSSVGYISHVDPLLNYGPSVFVEIWIPASGLVSSEVGEVISAVGSIAIS
PATNLPRWVFGLRIAGWRGIGDDILHFVIRAFGREGSKSRRFGLKERIWEKLEF
LAVRSIARNLRSSALPEKTSSEYSHVRSCVHQKSLDCRRAIERTLVAT
>Contig1_g13
MCVSYMGLGSNGCFVNGTALTGGQYRTNITSNVGHLRSNSV
>Contig1_g16
MALGGGLATLNGQNPKINFWVLAMGGAEHPHEDVTKDIIRAEHPLQTFPPHP
SPKTKLQLQDLDELRYEANEDTKLHKKRPKAFHHKKHVKKEFYVGQKVLTY
NVSPAPAPPSALEPQSVEFKCPSPH
>Contig1_g17
MPKTRASSSRGSDAQATSPLPTFEEQKLLFETTFAIREDFQHLKATQWVIAEVK
RQGLKKLFKPITSTAYKKLVTKFYAHLSSTVHGRAINVTRADIAAALYCNNEH
PLEEVQLAEQPPRFYVAEIIQDMHQRQYLTLTIMPTAGPSYLHSFGL
>Contig1_g18
MPRVPQAPTVGVEEFEAEPMVEDEPAAEPEATEEEALVILRVAQYRFISE
>Contig1_g27
MASSMTFQGASSSSTSPRPYDVFLSFRGSDTRQNFTAYLCKTLREKGIYTYMD
DKLRMGDEIGPELLKAINESRIAIVVLSKNYASSTWCLCELEKILECMETNQQII
MPVFYKVDPADVRHQIKSFGESLAKHESRYEESIVQHWKAALQKVANLSGRH
LVKGYVFLTLYIHH
>Contig1_g28
MHTINTYMCLWCAEIAHLCTMGCRDVRSLHHGVQRW
>Contig1_g29
MNILNVVKVFMWRACHNALATKSNLRHPKITEDPLCPVCGIEVETTWHVLWS
CRVAKDIWSRCNRKIQKSSVNQEEFMLIWEELLQRLNIEDMELMAVVARQIW
FCRKAFVHGNKINSSINVVGSAVESLEAYQEANSRKNEVAKRRNSQDLRWEA
LKNDFVKVNWDAAVDLNRNKTGVGVIRRDGMREVLATLSSPRVY
IIEPDIEEAIAALRAAHFRHELRF
207
>Contig1_g31
MPGTIIDQCADIFTKGLTSSRFLELHDKLMILPPPMSLRGSVKESTATQEKSARS
HTSERSSAVPESSEVQNQLKYDRAHSLVRSIAVPENSSSKPSRVRSSAITRVLD
RSTRDLPP
>Contig1_g33
MVNPRLDRLEQQLGNLMTMVEGFMKKMKENNEIIQEKLSALIAKFDDGSAD
NNDELHCYKQPQMVLPLYPMPSLDPQPTEDINNLVKPQDPFHHVEVSPLTIKS
SCCNHLKPAKLLPWMQTKMMDQKDKTCVLRIDTHRSQFWLCLMTTILAKVE
MHQPRGRPPRKRMKGQRRKNAKMEGNIGR
Contig2 (from AA12-850)
>Contig2_g3
LIMSANSDASSGRPLCRCGVVAFVRYSWTNDNYSRKLYGCEKYKQVGDCGF
FLWVDNEMTAYEKKIMQRLKDIEEQTRAEIGRLEKLLATEQAQYRAHLENMF
QSRDEM
>Contig2_g7
MELLQSHRAEMISIAVALAAIVGGSAYYYYLTRKPKGLTFTSHFVSHFWLSSH
FQHVFFNA
>Contig2_g13
MRAHVGRSVFLAPRETREKLGINAMDGGATAERGSARRWFHHSFFFAILSAP
RVNRLAGGRGCGNSMSSQVTRTAQP
>Contig2_g14
MKTAGSLGGFFIFFPKGYCSNLLVTNDVVLLFPSKLTVLTNGVAKMQ
>Contig2_g16
MDTAKHLGSVIVVTPEMSQRPRYNNVRSNDGRGPSQLDEKTRNVLDATQAL
ETVASLLVEALVNIKGKGTPSENKDQGRVSAIDVARWDTSFEIATRPKRMVLV
CLEGNDGKTWDNMSVETKEVARANLRIMIAGSIIILAKANVVADVLSMKSTV
ELATLEISQHQLVMEFAREGIEVVDEGAPTLLSNLVVESEMLDR
IKAAQLGDPKCT
208
>Contig2_g22
MHSSLCSGATALVSPPPFATSLGGPPLLFKPLDQLSSSLLACMFLRVSSLYPGA
CTLETPSFPMLDDSTIETEPRSVLILTLKNLPHSTLSSYVSTSSTTPIEAPIWLPTA
CPILASVRLYILTQKATLLNAIYVVGINPSNSSTENRFPSNNHGRPSMTLTLSHS
CSNSKRNKFSPKTLNERLPVGLHPLIRMALIVSLLTNYSAMSFSTRQSCPLCTIP
SNTCSLISSSTLSSSINEKFPHSLVSSSAIVAILTSKVICPRVLFIA
>Contig2_g23
MLHDLGQVQSSAGKRGIDRVRAIECTRAAIERTRAQEAFQMVATMSLFPY
>Contig2_g24
MPRTCASSSRGLGAHDISPPPTFEEQELLFETTFTIREDFENNEATQWAVAEFR
QRGLKKLFKLVTSTVYRKLVVEFYAKLSHDCDNLAAISSKVRGQIVHITRADI
AVALQCNDKHPPETANLAEQPSRYYVAEIIEDMCQGDYADAHHNAGSQSKLP
RRLWFVDSVLHRNAFRLGHKTQRQDQFLQTLYAFHKDAWYSIPKIIWNQIYK
FWNGVHVRGAKSTHSWGLPFPYLITHILQKKGIKGTAADEPVTTTPLFGIHQW
SKSCSHMPQALPEAGEEVDEAEPMAEDEPELSRKLTMMMKLNLIFEPSNTEPF
VSKWKAFNETSPINEGRPKKIRST
>Contig2_g25
MADQKHVTTKTEQAIQKLEVQIGQMAKELSERKQGEFPTQTIPNPSNHQQLK
AVTVQRGPTPTRALEPNSE
>Contig2_g26
MKQAYVPTNLHQLSYIAYQPEVEGSYYISPKILNALTHFRGTATEDPNLHLKE
FFDLCKLQNVQGLTQERLRLVLFSFSLKDNAKLWYNSLPAESIHTWEELTTKF
LKRFFPAQKTKQLKRELQMFQQREGDLFFEAWDHFNFLLLKCPHHNIPQDEQ
VQIFYEGLDDTNKGMVDSACGGTLMERSSEEAVEIFETLSEH
S
>Contig2_g27
MGKLKLRGTVINRKVPAIEHNTREDAARPRPRAIESSQKQDRSRTCDRAHTGC
DRAHPCAGGIPNGGYNAPISILGFFKLQIVIGLKPCGNPRVYYFFKDF
209
Contig3 (from AA12-850, susceptible homolog origin)
>Contig3_g3
MESVFGEPPSDGPASSVRNEYKAEETQFVSHKGVKSTIGLTHIGSMGEAQMV
DVSPKESSKRTAISSCKVILGKKVFDLVLANQIAKGDVLSVAKIAGISGAKETS
SLIPLCHNITLTHVRVDLTLNPEDFSVDIEGEAASTGKTGVEMEAMTAVTIAAL
TVYDMCKAASKDIQITDIRLERKTGGKSGDWSREE
>Contig3_g9
MFPPHTLSGSRAAPPRAPPPSPNYGLAVLRLVAEPSVDEQIRQAAAVNFKNHL
RVRWSPASSSDELSAPSLVPDSEKEQIKALIVSLMLSSTPKIQSQLSEALALIGK
HDFPKLWPALLPELVASLQKASQASDYTSINGILGTANSIFKKFCYQYKTNDL
LLDLKYCLDNFAAPLLEIFLKTAALIDSAASSGAPAATLKPLFESQKLCCRIFYS
LNFQELPEFFEDHMKEWMTEFRKYLTTSYPALESGGVDGLALVDELRADVCE
NINLYMEKNEEEFQGYLNDFAFAVWSLLGNVTQSSSRDQLAVMAIKFLTTVS
MSVHHTLFAGEGVILQICQSIVIPNVRLREEDEELFEMNYIEFIRRDMEGSDLDT
RRRIACELLKGIATNYRQQVTEIVSAQIQNLLTSFVSNPVGNWKDKDCAIYLV
VALSTKRAGGASVSTDLVDVQSFFASVIVPELQSQDVNGFPMLKAGALKFFT
MFRNQIPKDVAIQIFRDLVRFLLAESNVVHSYAASCIEKLLLVKDEGGRARYT
AKDIAPFFGELMTNLFKAFKFPESEENQYIMKCIMRVLGVAEISREDAGNCVIG
LTSILMEVCKNPKNPIFNHYLFESVAILVKRACEKEPSLISAFEERLLPCLQLILA
NDVTEFFPYAFQLLAQLVELNSPPIPRNYMQIFEILLSPDLWKRTSNVPALVRL
LQAFLQKAPHELSQEGRLNMVLGIFNTLISSSGTAEQGFYVLNTIIESLEYGVIA
PYVCHIWAALFGQLQNRRTIKFVKSFLIIMSLFIVKHGPANLVDTMNAVQPNIF
SMIVKQVWIPNLKLITGVIELKLTAVASIRLICESQALLDAANVELWGKMLDSI
VTLLSQPEQDRVEEESEMPDITENVGYTATFIRLYNAGKKEEDPLKDIKDPREF
VVALLARLSSLSPGRYPQIL
>Contig3_g10
MEEEREEGGKVRALIEKATNSTAPEVDPRLLKAIKSVVRYSDRELRLAAQTLM
DLMKRDHSQVRYLTLLIIDELFMRSKLFRTILVENLDQLLSLSVGFRRNLPLPA
PPAVASVLRSKAIEFLEKWNSSFGIHYRQLRLGFDYLKNTLKFQFPNLQAHAA
RIQQERRERERRSKELLLKKFEMLKENFSSIKEEIKSTIDEIRECLDIVCAKDEF
MPLGPIDDEDFEEFRSSELLQIRLNTLREGQKVHENNDNKVVFDALRELYKLL
VTKHLVSVQEGISVLVRVEVADNRVRDSTLKELIDIRNCLQSVKKKCEESGCA
VPNTTSCDDEEEDFWEEGKIGSLENERSTVPNNQNENLSMALASIELKNRTLE
SNNRGSNDNELPSLEGGETGTNSLRNKLLADAPMMSWGYFLNNWGSNREVL
ANQRGLELESHWGRVDYDAVIPAEKIAELNVHSTLYKEEQTEIQPCHAPLRKG
GLCQRRDLRVCPFHGRIIPRDDEGKPLNHNSSKDEITLDSGTDLVEQVAKQAV
KNVRERDKEVVKKREIDKRSLKRAKLAKIREHNDVVLRDAALASTSSSAAIGE
210
DMEATNGEKLSARNKKETLSSMLRKKVTPKDRLAQRLLNTQVKDATVRELT
LGEDSNYREAFPNQW
>Contig3_g14
PAYIALRDAFRAGASNLKRGPEFSLFDTCFDLSGMTEVKVPTVVLHFRGADLS
LPATNYLIPVDTDGTFCFAFAGTLSGLSILGNIQQQGFRVVYDLAGSRIGFAPR
GCA
>Contig3_g18
MEQPPYAEDYLTSTSATQSHRKSDSQRGGTRHPVFRGVRKRRWGKWVSEIRE
PRKKTRIWLGSFPAPEMAAKAYDVAAFCLKGRKAQLNFPDEVDHLPRPSTCT
ARDIQAAASKAAHAIVLEKKKRDVDAVSGCDDFWGEIELPELRVSECYWNSC
GWSFTAGDAAGLDGEVSQPFTACL
>Contig3_g21
MVALKYDTMRGGWMALWCGCVKMYKEGVGSRFGLSWVMPSIVAGLFACW
WSGGRSWSAVVWKMVPHSLMWCLWVERNARCYENSERSLKEFTAFFFYTL
FTWTAA
>Contig3_g24
MNRRKKDFGIGDNESEFYDGKMKKSMSSASITSSVKEDMEPMQCRCGLTSPII
TSTTIKNPGRRFYGCAIKLANVVFSNGMTKKPVLEEGRSYLRCINKFIP
>Contig3_g26
MTSSHHGPYDQGYTRATMAHTKRSDLARASGPHKVRRSPDWSLQLDSMKSE
SLVIVDQNATVNTFPGLVHTARHTMGVGCKRSR
>Contig3_g32
MRAHVGRSVILAPRETREKLGIDAMDGGATAERGSAKRWFHHVPIFKTGQGV
KLLMVVDFTY
>Contig3_g39
MRVIEKIEYRLASWKRLYLSKGGRVTLIKSTLANLPTYYLSLFPIPVSVAKRIE
KLQRNFLWGGIGEEFKYHLVKWSQVCTPIKEGGLGIRNLLVFNRALLGKWLW
HYGSERDAWWRDVIDAKFGSLWGGWCSVEPGGTFGVGLWKNIRKGWETFK
GFTRFAVGDGSRISFWHDWWCGDSALKIAFPSLYSIACAKEASVADNVEMLG
GSNQWNVSFSREAHDWEVEAFASFFQVLHSTGVRRGSEDRLWWNPSKRGTF
211
KVKSLFLSLACSEGRRFPWKSVWRTQAPPRAAFFAWSAAWGKILTLDNLRKK
NVIVSGCRVASLLVVCRKGVECCSLEDGAYLLFLVSMEREK
>Contig3_g45
METRKKFAGSRKNGNNDYLEYEALKKAVESGDWKAADEFLKRHPGVAVAK
ITPFGHTALNVAVKAGHEDIVEKLVDLM
>Contig3_g50
MNTASEGRGLVAVEGGVGGGKKRLASVIIRDPKLVISDPPAANTRGATLKKA
RLDKGKGKLIESPKQKNLPLQTGGALRISGRVDPPAVSQLRTTGPLKMDMRA
KKLNLPPRAARALCLVDELVESDKPEVPQPKKRKLVKAAEVKVQDQFASLLA
ARRKAAPGPVVKPIAEVEAFLANEPIPARPLNATPLASDGVEARTAILIESLSLQ
PLGSYIQHILDDIELVEHSDSSVEMARSPTPVKKVTEKALAKEMESTAETSSSS
ASAIRPQGVDWTVGGRLADFSGDLKGMTEQMIFFQLTGVIRSLVLYCYFRKV
ANDSATKTNTLQTLGTDLEAENARLKEVVTKQDKELLLSGQQQSIMEAETSE
AAAARARAESKATELAVEIEGLRAEINRLQEDNSIIKEDLNQLGEAHTEVSNQ
LELAQAEILDQKNLVVRANEAKVIAEEKLKFFKGKYVQARAQLREAKSRAAN
YLRQLSFASWVRNSAWADGLILGFETFRAWAKDSARKIDLNRVKIEDIPCSDA
AMAQLVNLGQEQMPDAAGIKEFFFDPFSDQHRQGAESDPDDTRSEADSVESV
SAEAPDINLASAPKAK
>Contig3_g51
MSGDEGSGSDGLGGNTYPARWRPLLTKADEARIREECFIPKSMKLRFDDERV
GAIVRSDAHEVCLYETMFRAGFRLPFPPIIRELLSYLNLAPHQIVPNAWRLIHSC
VLLWPLALGPGHHLTAREFLWVYRLQKNPKCDGLYNFQSRRGKFVHVDGKY
SSNHAGKGK
>Contig3_g55
MGTWPPHGGRPPPIPTGGDFGQPHGARGWLWSREGGQATPMEPRRWPKPPP
MGIGVVLATPIRPDGGGLMAKATPKWPRGWP
>Contig3_g56
MFISKAHARSMTLHLQLTTLKKGSMSITDYFQKFTKLVDTLAAIDKPLDDDDI
MYFLLVGLNSEYDSFLTSITTRVDPISIDELYSHLLAYESRLEHNITSLDLSVSSV
HIASGDSLSRGGGHSYSSRVSYSNGNGNHSTYNGGFYSHSPNYRGRGRGRGA
PSFNRAPCPICQIYNCIGHLVTTCYQRFEHSSS
212
>Contig3_g61
MKTEAIGRLAKVAFPGKLLTVEPHLVQPSSYPPKLVLKLPKGFSGPLISKQHLH
TKGNMLNRN
Contig4 (from W07-375)
>Contig4_g1
FSGAAQPDGDADETSDEALGFLAKQSCSDGGADETSDEALGFSCISISFGRWC
RRDFRRSSRVFLHINLVRTMVHTRLQTKLSGFLHSNLVRTVLQTGLQTNLSGK
ISFFSSGRAFRRDPV
>Contig4_g2
MYGQNPLGVLDLAPIPCIGRLSIKADEMTDYLRGVHDQVKKAIEDSNVKYKA
QSDSHRHKVTFEVGDLVWVVLTRDRFPVGEYNKLRERKIGPCEILQKINENAY
RLHLPSHLKDLCCVQCEAFDSMFC
>Contig4_g13
MKTKHHIIPPTLTCRPPSPDAVAMKPLLPLSPLKVGVKPPQPPWGGRAGHPSRI
WGGLRATPWLGLLAGHPSSSPLAVLIYDLVFFFSL
>Contig4_g19
MADQLLIGTAERIIDTLSSLVAKEMGLLWGVKGELKRLKNTVSTIKAVLLDAE
EKQGARDGEAVKDWLGKLKDVIYDADDLLDDVSTEVLRREIMTQDKKAKK
VCLFFSKYNQLYSLHKTAHKIKAMRERLDAINADRESFHLVVRDAETRVGNK
LHTSRETYSFVRERSIIGREDDKKAVIDWLMDSNVEDEVSILPIVAIGGLGKTA
LAQLIFNDEQIQKRFQLKMWACVSDPFDVKNTIEKILESATNTKQQDVQKNTL
VNYLRKEINGKKYLLVLDDVWNEDHRKWSKLKEVLMGGARGSRILVTTRTE
RVARICGTVESYSLRGLKEHASWSSFMQMAFEKGQEPEENSSIAAIGREILKRC
SGVPLAIRTIGSLLLFKKSETEWLNFKNNKLSKIPQNETDILPTLKLSYDQLQSH
LKHCFAYCSLFPKDFNINRSTLIQLWIAQGFVKLSDQSQCLEDVGNEYFMDLL
WRSFFQEADTDEFGNIIQCKMHDLMHDLAISEAGSLIIALDDKEMKFDEKIRH
VSIGCDISTLSITTSLCKASGIRTLLRPTPNLRPILGGELYCEAIVSTFKLLRTLDL
HQLLTPFLPSSIGILKHLRYLDLSANFSLKKLPNSITNLQNLQTLILLSCYKLEEL
PKDMQKLVNLRYLNINRCYNLNYMPCGLGKLTNLQTLSKFVIHWDPLSNDSS
GLKELNGLNNLRGXLXITNLRHGKDVASECKAANLKEKKHLHALTLRWRPE
GGVNDSDVDVDAELLLEDLQPHPNLKELRFELNHCMSLRLPSWLSSLTNLVR
FELYRCTKCQYMPPLSQLPSLKYLFLEYMEAMEYISVGNEFSSSSSAPIPFFPSL
KEIVFVDCSNLKGWWRRRHSSVEANSDGDNSVEITTETSMTAHCLLPSFPCLS
213
TLKIINCPMLTSMPMFPHLERVLLSHASLKLLQQTLMMNMAVPQSPTPTTXGS
SSXTPLSKLKFIELXXIADLETLPEEWLKNLTSLQSLTIFGCNRLNSLSPGIQHLT
TLQDLHIDNCLELELANDEDGMQWQGLKSLFSLKFNRLPKLVTLPLGLQHVT
TLQKLTISTCENLTAIPDWIQNCTSLQVFEI
>Contig4_g23
MPVVSLGLAPICVIPARSTAHRLVHLDSCSTTSLLGSASAHHTFCTRSVSPDVV
>Contig4_g25
MACEEVLKAVFPLLEGVDLASCMAVCKQWRDIARDDYFWKCICAKRWPSIC
KQPNPPTVTYYKLYQTFYRRQQRRTLPPPKLSFDDLEFFIDIWAGDRLIFSEVV
PGLVLQTGIKVPPPGICDVLRFHLEGLEFKMRQAVKPRFTIPLSQTISVSVLVSR
KDSNMVACIINKSLFEYVDRTAYRAMAFDYLEFSPVHPFIAGARAWFSLLFNE
DGNEGVIDVFGIEMDFCDTANSKEEVLWLLDMLDWK
>Contig4_g26
MSSTERCNSWAACITATFFHSEGFPPEIRGQWCHRGVNPVRFSGFWPKPEPEP
GYPGSRFWETGTGTGTPVNRGPDSRPVPVLSGPVTRF
>Contig4_g27
MKDLAPLSLSLSQFLPPPPTHIRPPPPSTTAGHTIQWLRRQPPRSRSSADPNQFL
SLSQTVGHHLS
>Contig4_g28
MCSRKCAVPLVSSVSNLDPASIHTPTVAVRAARFDSVATRRPFGRVVTRVSGA
ERIRVRSAVAGWGDPCLRKRGSGLSSCLSLDFKASARRSYTMAVGGGGEGGG
ADDGVAISWEVEADRVAWAMYDVAALWDRRDRVRMCFIAISLSVSPSVYYG
EELLRVFSSGSED
>Contig4_g30
G
VLLYNVGGAGDVANVKIKGSRTGWTQMTRNWGQKWQTGLVLRGQSLSFQV
TTSDGKMLQFDNVVPANWQFGQNFEAKTNFF
>Contig4_g32
MQTANTGECYHGRHTAGANVRREEGNNPDRQLRCNGAKPCTEAAAATLMR
CWVGERSVSLRRCAVRHAGGIRSANADISNDKAGEKPARRKTKGSCPTLIGA
214
>Contig4_g37
NSTKLDRNNSSSHWCKLCEHGHGQVEVLERGIAPIPDTFSVVWRAEIGGRDFD
GASISNAPLWIIHAHDLEASAAAASLVE
Contig5 (from W07-375, susceptible homolog origin)
>Contig5_g3
MERTNQKWSKKCPVSDAHSNIEAKLSSVICNGDWLWRPTRSEALVGIQARLL
EVGLGICDKPVWIASKKGFMSAQILGMFIERRGRSLFAGRWSGFVLPFLSKLLS
CGLL
>Contig5_g4
MAEQLLFGTAERIIDTLTTLVGKEIGLLWGVKGELKRLMNTVSTIKDVLLDAE
EKGAAGGHAVKNWLKKLQDVIYDAEDFFDDVSTEALGRKIMTRDKKAKKV
CIFFSKSNPLVYRHKMAHKIKAIRERLDAINADRESFDLVVRNAETRVGNNLH
TSRETYSHVYEKSIIGREDDKKAVIDRLVDSNVDDDVSILPIVAIGGLGKTALT
QLIFNDEQIQKHFQLRMWVCVSDPFNVKDIVGKILESAKYPKQPDVQLTTLVN
YLKNEIDGKKYLLVLDDVWNEDHEKWSNLKDVLMGGARGSRILVTTRTERV
ATICGTVESYSLRGLKKHASWSLFMQMAFEKGQEPEENSSIAVIGREILKKCSG
VPLAIRTIGSLLRFKKSETEWLNFKNDKLSKIPQNETGILPTLKLSYDQLQSHLK
HCFAYCSLFPKDFNIDKSELIQLWIAQGFVKLSDQSRCLEDVGNEYFMDLLWR
SFFQEAETDEFDNVTHCKMHDLMHDLASLEAGSLITTLDDKEMNVDENIRHV
SIDCDIGTLSITTSLCKASRIRTFLCTTSNYFQFGDSYCEAIVSSFKLLRTLDLHG
QEMDILPSSIGMLKHLRYLDLSANYNLQKLPNSITELHNLQTLILTDCMELSEW
PEDMQKLVNLRHLDIHNCNMLTYMPRGLGKLTNLQTLSKFAIHRDPLSIDSGG
LKELNGLTNLRGKLVIENLRHGKDVASECKAANLKEKKHLHALTLHWRYER
RVNDLDVDVDAELLLEDLQPHPNLKELRFELNHCMSLRLPSWLSSLTNLVRFE
LYWCTKCQYMPPLSQLPSLKYLSLQSEAMEYISVGNEFSSSSSAPKPFFPSLKEI
EFFRCYNLKGWWRRHSSVEANSDGDNSVEITTETSMTAHCLLPSFPRLSTLEIT
KCPMLTTMPMFPHLERKLVLSHTSLKLLQQTMMMNGAAPQSPTPTTIGSSSST
PLSKLKFIELDSIADLETLPEEWLKNLTSLESLRISGCDRLKSLSPGIQHLTALQD
LNIEDCLELELSNDEDGMQWQGLKSLISLNFSGLPELVTLPLGLQHVTTLQELT
IKDCENLTAIPDWIQNCTSLQDFKISNCSSLTSLPEGMRSLTSLQRLKIYSCPVL
LQRCEKEVGEDWPNIAHIPDLVLHYYTPTHLELIQISDAEAEETEDLEHIQNSR
DLNS
>Contig5_g14
MASGEANVVENHDDAVAVELPAPQGWKKMVRSLCYLSFSLVFVLNSCSWLV
SVT
215
>Contig5_g15
MPERVSQAPSQVFPGMSTMSCSSVADFVAHGLAEADVIDKI
Contig6 (from X01-825)
>Contig6_g4
MGADVGQLFESGQHGPYALGYKPSYPKPKVSTCPFRRSKSPSWKKISEGGAQ
VDFKDGPATAKWKHRSVSTVRDFPPVPGRCNPYLSVEMKWEMHTHLTQIAN
EYAEMECEEIRLLKAGALLAGSDRQKTGFLSSIDKDYEALVKDEEDPIEESGG
EC
>Contig6_g5
MHRHRPPRATHNLCPFSHTPLKSSNCIETHTIPQICCRPSSSHPKICQHVLRVLP
RATCHCAFGIHMPPPPYTRRYQRPTRLIAAPLHISTAEDARSVNHAVIKASTCL
HASLQSPATFLHALLPDLLCCRRRPVLEKPTPFQISGFRSSSRGPHRALVRTSCH
PQEILL
>Contig6_g13
MFLSADCLLRLLCYYLIDESILHGVSGNPALRQGKPGSGIGLGYGLRFKSQFG
HFQVDYAINAFQQKTLYFGISNVAS
>Contig6_g18
MAAWAMLMVAMLVMAVGLDAANTNGVYQPCADTKIQRSDGFTFGIAFSSK
DNFYNNQSHQLSPCDRRLSLASLNSQLALFRPKVDEISLLSINTSSFFPVPFTSTP
IFRRFTVIDIQLMGFGYSANGYTTKSLIGIALGNIEFLFIEKSSAFYELKALFNFL
SKQALT
>Contig6_g25
MASIGSSYWCYRCNRFIRVRVRAQDTVICPDCSGGFVEEIRTPTRSPLHRFPAA
AMYIDPNPPNSDHNPIPRLRRSRRNGGDRSPFNPVIVLRGPADGGGNEPERGNF
ELYYDDGAGSGLRPLPASMSEFLMGSGFDRLLDQLAQLEVNGIGRLEQPPASK
AAIESMPIIKIVSSHVSTESHCAVCKEPFELDSEAREMPCKHIYHSDCILPWLSM
RNSCPVCRHELPTDVRGRNSPESDGGRDEETVGLTIWRLPGGGFAVGRFTGGI
RAAERELPVVYTEVDGGFNNGGVPRRISWETSVRSSRESGGFRRVFRNFFSFL
GRFRISTSSSSSASRLSSEPGITRRSGSSAVFSRSWRRRRGGRALDLDDNRW
216
>Contig6_g30
MLPTPTSSSLPTTTTSTTTMEPTMGSTNAWKATDTVRSASRSSTDTAPRPPAAT
PSRGQSPSVTPPSVAAPNCGKLTLRKIFSL
>Contig6_g34
MSDQSLPPFLLKNLISLWKDVSPSYVANLLAPKDLFGTMVPRTARLFAKILESL
GIKWLFETLNNWSLGFMKCLKRDCDKGVSFSTHFLVSGQI
>Contig6_g35
MNFHFNDFNASPSCRTPAPTNYPQNFFPNKPCSFCFNPYHEENNCPDLRTELN
DLWDKLDQIRAARSTFSYEQMNTSFSSPGFDSNFNCYNPDWSNQYDFSGSAQ
ATGNYAHQFDELHHSEYPQFDHQAQPPVYQSTTQVPAPQSSLEDMMKAFMQ
SMDKNIQEIKQDMKNTILSNSQDIQELKGFTNQAVQEMRNSNMANNRDIQEL
KQAMTKIEGQISHLVADFNRIEEEELQSQLMAERHYMIDEDDSKNSYHEHAQ
VTITLESEEIVDNKEEEEKEEQVEHPEQVEHHENSEPPTNPDLPSDMEVSTEAT
AYITVPLEAHQEPSYVKIFKDLCTQAHKSRNHFPKKICRSKQVYIIWRNILPEG
YEVLKKKGWKGLVGHPHDRGKRCKVSPPVYFLHFTPQILSFLFHYIAFLFICFC
F
>Contig6_g36
MFHKSGLIPTRSALEHTFSAIECTRALCSRKLVARVRSSAPRVRSSTLGRLGSA
ETLKLAYKYHSFAL
Contig7 (from X01_850, susceptible homolog origin)
>Contig7_g1
MYTLVFFCSSLVVHFLVFFCSSSISVFCSSKCQAHSKTLGMEVQATVGRTGSL
WLYLLI
>Contig7_g3
MISGYTRNGLLPESQMLLNVIYGKNVRTWTILLTVYAKSGLVNKARVLFDAM
PKRSVVSWNAMNIGYVENGDLQSARVLFNEMPERNVVSWNLMITGYCNCC
MALLVVALLAIKGLNESCLSLRTLAIKTGYEEDVVVGTAILDAYTRNGSLDNA
IG
217
>Contig7_g6
MATAAALSGTMVSTSFVRRQPVTSLRSLPSVGQALFGVKGGRGGRITAMAVH
KVKLITPEGPQEFECPDDVYILDQAEELGIDLPYSCRAGSCSSCAGKVVEGPVD
QSDGSFLDDDQLGRGWVLTCVAYPQGNVVIETHKEEALTEDS
>Contig7_g11
MCHVSTSYWSTCQSIRSINGQLTDGLTWSFIKTTGTSCDKNETPRGKKINDDL
CYHWLAITSGSPPSRNQQQSNTIPAAPSRNTGLWPPAVHRSDLASSFRSTADPP
PSGLHQLTESSPSRHQPPIHTMTPLPKSPKLRASSHIR
>Contig7_g13
MDRQDAVITFWREGRPQRVPNARRQERHAHVDDFHDNHEDKFKDDQASLN
GDGRFVPRGKRRGRGFRRDPRWQNGTNRKLGNIKMKIPSFQGKNDPEAYLE
WEKEVELIFECHNYSEEKKVKLAVIEFTNYAIIWWDQLVMNRRRDHKRLIET
WEEIKAIMRRRFVPSHYYRDLYQKLQSVIQGERSVDNYYKEMEITIIRANVEE
DREATMARFFNGLNQDIANGVELQQYMSWRTWCTWQ
>Contig7_g16
MHSSLCSGATALVSPPPFATSLGGPPLLFKPLDQLSSSLLACMFLRVSSLYPGA
CTLETPSFPMLDDSTIETEPRSVLILTLKNLPHSTLSSYVSTSSTTPIEAPIWLPTA
CPILASVRLYILTQKATLLNAIYVVGINPSNSSTENRFPSNNHGRPSMTLTLSHS
CSNSKRNKFSPKTLNERLPVGLHPLIRMALIVSLLTNYSAMSFSTRQSCPLCTIP
SNTCSLISSSTLSSSINEKFPHSLVSSSAIVAILTSKVICPRVLFIA
>Contig7_g17
MLHDLGQVQSSAGKRGIDRVRAIECTRAAIERTRAQEAFQMVATMSLFPY
>Contig7_g18
MPRTCASSSRGLGAHDISPPPTFEEQELLFETTFTIREDFENNEATQWAVAEFR
QRGLKKLFKLVTSTVYRKLVVEFYAKLSHDCDNLAAISSKVRGQIVHITRADI
AVALQCNDKHPPETANLAEQPSRYYVAEIIEDMCQGDYADAHHNAGSQSKLP
RRLWFVDSVLHRNAFRLGHKTQRQDQFLQTLYAFHKDAWYSIPKIIWNQIYK
FWNGVHVRGAKSTHSWGLPFPYLITHILQKKGIKGTAADEPVTTTPLFGIHQW
SKSCSHMPQALPEAGEEVDEAEPMAEDEPELSRKLTMMMKLNLIFEPSNTEPF
VSKWKAFNETSPINEGRPKKIRST
98
218
98
219
98
220
98
221
98
222
98
223
98
224
98
225
98
226
98
227
98
228
98
229
98
230
98
231
240
98
232
233
Appendix D . Images of SCAR markers developed from BAC ends. The arrow indicates the band associated with resistance.
BE01 BE03
R S R R S S R S R R R S S S
R S
BE22
R R S S R S
BE24
R R S S
BE25
R S R R S S R S
BE26
R R S S
R = Resistant; S = Susceptible
234
Appendix D Continued.
BE27
R S R R S S
R
R
S
BE56
BE62
S
R R S S
R R S S R
R
S
S
BE33
R R
BE61
BE68
R R R S
S
R S R R S S
S
S
S
R = Resistant; S = Susceptible
235
Appendix D Continued.
HICF12
R S S R R S S
R S S R S R
R
HICF53
H04_SCAR
S R R S S
HICF13
R S R R S S
R
R
S
S
HICF58
S
TBE14
R
R R
S
S
R
S
R = Resistant; S = Susceptible
236
Appendix D Continued.
TBE62
R S R R
TBE116
S S
R S R R S S
R
TBE129
R S S R S
R = Resistant; S = Susceptible
R
R
S
S
TBE115
R
R R
R
TBE128
S S
S S
TBE_IV_62
R S R R S S
Appendix D Continued.
SBE70
R S R R S S
SBE78
R S R R S S
R = Resistant; S = Susceptible
SBE72
R S R R S S
SBE79
R S R R S S
237
238
Appendix E.
Images of SSCP markers developed from BAC ends. The arrow indicates the band associated with resistance.
S S
BE02
R R S R R S
BE04
R R S S
R
S
S
BE05
R R
S
BE10
R R
S S
S R
S
R
S
S
BE08
R R
BE41
R R
S
S
R
S
R = Resistant; S = Susceptible
Appendix D Continued.
R S
BE54
R R S
R = Resistant; S = Susceptible
S
239
240
Appendix F . Images of HRM markers developed from BAC ends. The melting curve associated with resistance is shown in red.
BE02_HRM SBE27
TBE97 TBE123
TBE126 TBE_II_14
Appendix D Continued.
TBE_II_60
W07_SSR X01_HRM
The melting curve associated with resistance is shown in red.
241