@SNPSTER3:1:1:58:972#0/1 run=090820_SNPSTER3_0438_42FFTAAXX_PE TCAGTCCGGTGCCGGAACTGTCCCCTGAGAATCTCAGTACCCTCTTGATGGAGA
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+SNPSTER3:1:1:58:972#0/1 a^YQ[``UOU\a_TUYV\^V^`a`a`YY]ZV^a`a^^W\`\]_`_aXQ[]YU_^ @SNPSTER3:1:1:58:916#0/1 run=090820_SNPSTER3_0438_42FFTAAXX_PE ATTCCTATCCTGTGACATCCCAACCCTATCCAGAAACCCTGTCACCCTTTCCCT +SNPSTER3:1:1:58:916#0/1 ]HY^``PaaaaMa_Ya[aaaaaaa``_UJ[aa_[X`aaa`Q_aba`a__``a_a @SNPSTER3:1:1:58:1806#0/1 run=090820_SNPSTER3_0438_42FFTAAXX_PE ATGCACCGGCGTCGGAGTTTCAACTTCGCCGGAGGAAAATTGGGGATGCGGGTT +SNPSTER3:1:1:58:1806#0/1 a_\aYaa^Ya]\a^XNXU_`a````]`^aa\\T^[[UMT_`^[^Y[^]a^YYU[ @SNPSTER3:1:1:58:1896#0/1 run=090820_SNPSTER3_0438_42FFTAAXX_PE AGTCCGATCCCTGTTGCACACCCTGCCCACACCTATGGGGCATAGCATACCTCC +SNPSTER3:1:1:58:1896#0/1 aOX``UQ]aa`]KX\XaS```a`]U[``X`V^`\XTNNRR]\X[P`ZQW`\X^` @SNPSTER3:1:1:58:1554#0/1 Eric Johnson run=090820_SNPSTER3_0438_42FFTAAXX_PE University of Oregon AGTCCGATCCAAGCAATGAACCCATATAGCTGCATTCCAAAGACCTATGCCCAG +SNPSTER3:1:1:58:1554#0/1 `Z[aa^X_aa[TWaZWZYUZ^a`U]Z`_^`VS_]XN__TYZY]\a]TUN]aBBB @SNPSTER3:1:1:58:926#0/1 Seq, and ye shall find: next-generation sequencing tools for genetics and genomics Sequencing costs are dropping $3,000,000,000 NIH Cost (US dollars) $300,000,000 Venter WGS $2,000,000 454 $100,000 Illumina 1995 2000 2006 Year 2008 There is still a “genome center” mentality that treats DNA as a large-scale resource and not a means for small-scale discovery Threespine stickleback populations have varied armor plating Oceanic Lake with Bill Cresko splicing changes were seen in the lowfish. e also generated probes to examine the l pattern of expression of Eda in ebacks, but we were unable to detect cant Eda expression in any samples whole-mount in situ hybridization, even phenotype of fish from Salmon River, British Columbia (SRST) (2), a population that does share the characteristic Eda sequence changes seen in PAXB and most other low-plated populations. These data suggest that the lowplated phenotype in NAKA is due to an independently derived allele of Eda. multiple origins, we amplified sequences from 25 random nuclear genes and scored singlenucleotide polymorphisms (SNPs) at 193 sites from 20 different completely and low-plated populations. Trees built from the nuclear sequences showed no evidence for a single origin of low-plated populations (Fig. 3C). The Previous studies mapped the lateral plate locus to a single gene . Genetic, physical, and linkage disequilibrium map of the plate interval. (A) Complete and low-morph phenotypes in alizarin red– d specimens (4) of Japanese Marine (JAMA, left) and benthic n Lake (PAXB, right) sticklebacks, the parent populations of a large pping cross. Other skeletal changes evident in PAXB fish, such as ion of pelvis and spines, map to different chromosomes (5). Scale 1 cm. (B) High-resolution genetic and physical mapping. Newly d markers Stn345 and Stn346 rarely recombine with the plate (C) Linkage disequilibrium screening. Two sequenced BAC clones were used to develop new microsatellite markers (Stn348–Stn379) located 15 39, 48, 63, 96, 103, 118, 120, 135, 137, 142, 145, 145, 163, 165, 177 179, 182, 195, 198, 203, 250, 267, 282, 284, 293, 315, 319, 339, 353 354, and 374 kilobases from Stn345 (black dots). Stn365, located in the stickleback Eda locus, showed large differences in allele frequency in completely and low-plated fish from Friant, CA. Positions of other genes from Colosimo al, 2005 in the sequenced interval are shown, with human genome et nomenclature We decided to try something a bit different Restriction-site Associated DNA (RAD) markers Mike Miller, Tressa Atwood, Nate Baird, Paul Etter Bill Cresko, Joe Dunham RAD markers sequence a subset of the genome RAD WGS Sample tracking with barcoded adapters A typical run involves several experiments of many samples each Mapping with RAD markers Low plate X Complete plate A. F1 fish from the mapping cross RAD1 RAD2 RAD3 RAD1 F1 x F1 mx x v x wv v x v B. F2 Pool of lowplate F2s F2 RAD2 mx wv v x x mx v x mx x v x mx v x v mx v v wv wv x mx x x mx v x mx x x wv x v C. Pool and make tags No completeD. Mix and hybridize to array plate alleles RAD1 RAD2 RAD3 wv wv RAD3 v x x x Pool of completeplate F2s Mapping traits by genotyping F2 mapping populations Bear Paw Lake Rabbit Slough with Mark Currey & Bill Cresko Mapping the genetic basis of lateral plate armor loss in threespine stickleback Linkage group I II III IV V VI VII Eda 41,000 SbfI RAD tags 1,890 markers I II III IV Bulk segregant analysis of RAD markers identifies two regions with the lateral plate phenotype. Sixteen RAD markers (small ) with large hybridization differences in the bulk experiments of lete plate pool versus low plate pool were sequenced and linkage group IV. (A) Six markers clustered in a 3-Mb region g Eda, the previously identified lateral plate locus. Seven mark- Linkage group We typ cro app poi hyb den arra for a su ing RA tide be or s kar are wit the repr mo add hig Downloaded from www.genome.org Regions of linkage match our previous study with a different lake Increased marker density with different enzyme choice Linkage group I II III IV V VI VII 148,390 EcoRI RAD tags 6,841 markers Tracking recombination breakpoints in individuals Linkage group I II III IV V VI VII in silico mapping of pelvic structure formation Bing Maps Mapping traits by examining genetic variation between natural populations Unsaved collection 1. 2. 3. 4. 5. Bear Paw Lake, AK Mud Lake, AK Boot Lake, AK Rabbit Slough, AK Resurrection Bay, AK 3 freshwater populations 2 14 5 3 2 marine populations 20 individuals x 5 populations ~45,000 polymorphisms Hohenlohe, Bassham et al (Bill Cresko) © 2009 Microsoft Corporation © 2009 NAVTEQ Image courtesy of NASA Signatures of genetic differentiation found comparing lake and marine populations 0.6 FST 0.5 0.4 0.3 0.2 0.1 0 -0.1 0 5000 10000 15000 20000 LG IV 25000 30000 35000 Bear Paw Lake Boot Lake Mud Lake 0.6 0.4 0.3 0.2 0.1 0 -0.1 0 5000 10000 15000 20000 LG IV 25000 30000 35000 Bear Paw Lake Boot Lake Mud Lake 5. FST 0.5 Bulk segregant analysis of RAD markers ident Regions match previous mapped regions REPEATED SELECTION OF GENETIC COMPLEXITY Mapping induced mutations in zebrafish - with Julie Kuhlman and Judith Eisen lacks dorsal root ganglion neurons wild type b938 Pooled 60 F2 wildtype embryos and 60 mutant embryos Chr # linked 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 24 33 25 0 This chromosome has 32.7 fold higher RAD markers than expected, P<0.001 b938 is located in a 2 Mb region of Chr 24 18 # of completely linked markers 15 12 9 6 3 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 Position (Mb) Advantages of RAD markers Project Design Choose sampling density Avoid repetitive (methylated) areas of genome Marker development Identify SNPs in samples of interest High depth of coverage Genotyping Multiplexed sample prep saves labor Analysis Limited sequence space - rapid and sensitive alignment Next step: Identify the causative genetic variation Target region Genomic DNA Fosmids or BACs Sheared genomic Biotinylated fosmid Purification B B B B B B B B B B B B B B B B Doug Turnbull SNP calling * Meredith Price Sean O’Rourke Bruce Bowerman Ryan Anderson Chris Doe BAC capture enriches for the region of interest coverage 400 300 200 100 4.0M 4.1M 4.2M 4.3M 4.4M Nucleotide position on chromosome 3R Ryan Andersen & Chris Doe BAC capture enriches for the region of interest coverage 400 300 200 100 4.0M 4.1M 4.2M 4.3M 4.4M Nucleotide position on chromosome 3R Ryan Andersen & Chris Doe Complex changes can be identified D. melanogaster ChrIII 4.1M 4.3M Ryan Andersen & Chris Doe BAC capture can enrich for large regions 3.6M C. elegans ChrIII 5.4M Average of 91x coverage across region 53% of reads map to region Meredith Price, Sean O’Rourke & Bruce Bowerman Mutations can be distinguished from sequencing errors Although the goal was to create a technology appropriate for an individual investigator, the approaches developed have use in ‘genome center’ style projects. Where are all the genomes? Sequencing a genome is still not routine Genome assembly is difficult 650 Mb genome Read Length 46 90 # of Reads 217,298,974 204,777,872 # of Bases 9,995,752,804 18,430,008,480 Read Type Paired-End Paired-End num_contigs 248,108 426,975 total assembly length 15,659,960 72,911,435 2.5% 11.2% % genome assembled red End Sequencing for LongRead Local assembly from genome-wide data Floragenex Long Read (LR) sequencing is a cutting edge application of RAD technology. Using only Illumina sequence reads, a composite sequence contig is developed which can rival the the length of 454 GS-FLX Titanium reads but at half the cost of pyrosequencing. Below we describe an overview of the process: 1) RAD Fragment 2) Paired end sequence anchored by common restriction site (blue) and single end sequence TGCAGGATTGCGCTAAAAGCAT TGCGAATTTGGCGCGATGATCGTAGCTG 3) Size selection of overlapping fragments 4) Assembly of short read sequences TGCGAATTTGGCGCGATGATCGTAGCTG AATTTGGCGCGATGATCGTAGCTGATCT CGCGATGATCGTAGCTGATCTTCATCTATTA CGTAGCTGATCTTCATCTATTATCGTGCTGC GATCTTCATCTATTATCGTGCTGCGCGCGC ATCTATTATCGTGCTGCGCGCGCTATGGC Paul Etter 5) Development of local DNA contig Nick Stiffler RAD paired-end contig in stickleback Thousands of contigs are developed simultaneously 1500 # of contigs 1125 750 375 0 100 200 300 400 500 600 Contig length (bp) 700 800 900 RAD paired-end sequencing can assay haplotypes SNP in RAD site SNPs in paired-end contig Whole genome de novo assembly by RAD paired-end contigs Partially digest DNA with frequent cutter. RAD paired-end sequencing of an Aeromonas bacterial genome TGACCGGTGCCGATGCCAAGAAAGAGAAAGAGGCGGCCAAGCTGACCATCGAACTGCTCTCCCCGGAACAGGGCCGCACCCGGGGGGGAAACACAGGCAACATCGTCTG TGACCGGTGCCGATGCCAAGAAAGAGAAAGAGGCGGCCAAGCTGACCATCGAACTGCTCTCCCCGGAACAGGGCAGCACCCTGCGCGACAACACAGGCAACATCGTCTTTCAGGGCACCATCAGCCCCAAACCTCCGACCCAGTATGATGTGCGCCTGACCCTGGATGGCAAAGCCGCCCCCATCGTCAGCAACAGCCT ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! CAACATCGTCTTTTAGGGCACCCTCAGCCCCAAACCTCCGACCCAGTATGATGTGCGCCTGACCCTGGATGGCAAAGCCGCCCCCATCGTCAGCAACAGCCTCTCTGTCCGCGTCGAAAACGTCGATCGCGGCCC ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ATCGTCAGCAACAGCCTCTCTGTCCGCGTCGAAAACGTCGATCGCGGCGCCCACGAGGCTCAGCTCGAGCTGCTCGCCAAAGACGGTACGATCCTTGCTAAATCCAGTGCAGTCACCTTTTACCTGCATAGAGCGAGCGTGACGCCGGCTCCCAAACCCACCCCCAAAGCCGACTAGGGGTGATATAGCGCACCGATGC ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! TGGCCGGGTAACACCG ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! Zac Stephens & Karen Guillemin ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! RAD paired-end sequencing For genotyping Increased marker density Compatible with high-throughput genotyping platforms Haplotype information generated For de novo assembly Assembly is local Haplotype information generated Reads with sequence errors more easily aligned Repeats localized to contig region Current technology development RAD markers for rapid physical mapping RAD sequences form a fingerprint for each BAC Digestion Sites BAC RAD Sequence A RAD-based physical map closes gaps in a whole genome assembly RAD Sequence BACs WGS Contigs Sequence-Based Genetic Markers Deconvolution of RAD sequences Pool BAC DNA into rows, columns and regions Convert each pool to RAD tags Sequence barcode and RAD tag GCAT CACCGGTGTGACAGTGACAGGGAGATTGGTG GCGT CACCGGTGCGATGCGGCTAGGCAAAGTCGAG AGAT CACCGGTGCGATGCGGCTAGGCAAAGTCGAG ATTT CACCGGTGTGACAGTGACAGGGAGATTGGTG CCTT CACCGGTGGCAGAGAGTGATATCCCGTGAGG GGTT CACCGGTGCGATGCGGCTAGGCAAAGTCGAG Identify pools with shared RAD sequence AGAT GCGT GGTT Paul Etter Floragenex TILLING - Targeted Induced Local Lesions IN Genomes Improved TILLing scheme a) Pool genomic DNA into rows and columns e) Amplify using target region primer 68 rows target-specific primer Illumina amplification sequence 96 columns b) Shear each pool to 500 bp by sonication c) Add asymmetric barcoded adaptors Amplification-Sequencing-Barcode f) Sequence barcode and part of genomic region barcode assembled reads * GCAT GCCGTAGTCGATGCGGCTAGGCAAAGTCGAG GCGT GCCGTAGTCGATGCGGCTAGGCAAAGTAGAG CCTT GCCGTAGTCGATGCGGCTAGGCAAAGTCGAG GGTT GCCGTAGTCGATGCGGCTAGGCAAAGTCGAG AGAT GCCGTAGTCGATGCGGCTAGGCAAAGTAGAG TCTT GCCGTAGTCGATGCGGCTAGGCAAAGTCGAG Amplification2 g) Identify rows and pools with shared sequence change AGAT d) Create two superpools of all rows and all columns GCGT mutation detected mutation detected Summary • • Tools for genetics • • RAD markers are a flexible system for SNP discovery and genotyping Targeted sequencing allows identification of causative change Tools for genomics • • RAD paired-end contigs help assembly at the local scale RAD physical mapping helps at the macro scale Thanks Lab members - Michael Miller, Tressa Atwood, Nate Baird, Paul Etter, Doug Turnbull Collaborators - Bill Cresko, John Postlethwait, Bruce Bowerman, Chris Doe, Eric Selker, Chuck Kimmel, Karen Guillemin, Judith Eisen, Floragenex Funding - American Cancer Society, American Heart Association, Medical Research Fund, NIH
