P301_Biofuel poster V3

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Association Mapping of Saccharification Yield
in Sorghum Using a Mini Core Collecti
Aniruddha Acharya1*, Yi-Hong Wang1
1 Department of Biology, University of Louisiana at Lafayette
Abstract
Result and Discussion
Increasing world population and limited resources is necessarily synonymous with energy crisis. Fossil
fuel has been exploited since industrial revolution and have contributed to polluting the earth to near
lethal limits. In this situation fuel from biological organisms (biofuel) is very promising in meeting the
global energy demands and also restoring balance in the ecosystem. Biofuel is a renewable and clean
source of energy. Biofuels produced from non-edible plant biomass are not yet commercially viable due to its
high production cost. This study focuses on identifying genes responsible for cellulosic biofuel yield from
sorghum stalks. Sorghum is a very promising energy crop as it can grow in relatively hostile conditions with
low fertilizer and water input but produces high biomass nonetheless. High biomass along with high
saccharification yield (conversion of cellulosic biomass to fermentable sugars like xylose and glucose)
will ensure a more cost effective biofuel. To improve saccharification yield, our lab is trying to identify
candidate genes involved in cell wall synthesis that affects saccharification yield.
Introduction
Biomass is a carbon neutral source of energy and consists of 76% of all renewable energy. Fuel produced
from biomass is called biofuel and has the potential to deliver 25% of world projected energy need by 2035.
The countries like Sweden , Austria , Brazil , China and USA has made progress in this technology but still
biofuel is at its infancy and much research needs to be done. But critics are skeptic about its impact on land
use, water and nutrient cycling, and emission of nitrous oxide.
Cellulose forms largest amount of organic matter but cellulosic biofuel production faces severe bottleneck
due to recalcitrant nature of cell wall where cellulose is trapped. Cell wall especially secondary cell wall is a
rich source of carbohydrate mainly composed of cellulose [a glucose polymer], xylose and lignin [phenyl
propanoid polymer]. However, lignin is the main recalcitrant factor to cellulose digestion by forming crosslinks
across the cell wall and shields enzyme from sugar polymers. Also lignin is found to absorb enzymes thus
resulting in low saccharification yield. This can be altered by identifying and expressing genes that can alter
cell wall structure or can produce more efficient cell wall degrading enzyme. The brown –midrib mutation
depicts how a defect in lignin structure can improve cell wall digestibility. Rapid gene identification can be
done by association mapping.
Materials and Methods
Sorghum accessions from the mini core collection [ Upadhyaya et al. 2009 ] were grown in the field,
harvested, air dried for 2 weeks and cut into 20 cm pieces. They were dried again at 80°C for 2 days and
milled to 2 mm with a Wiley Model 4 Laboratory Mill. The stalk powder was dried again and 0.5 g were
weighed in tubes in two replicates and labeled. They were autoclaved with 5 ml of 2% sulfuric acid. The
samples were immediately washed for 6 to 7 times using double distilled sterile water. Finally they were
digested at 50°C shaken at 240 rpm for 24 hours. Digestion solution consisted of 5 ml citrate buffer, 50 µl
Cellic CTec cellulase enzyme from Novozyme and 10 µl of 20 µg/ml tetracycline. For each sample, 100 µl of
supernatant was transferred to 1.5 ml tube containing 900 µl double distilled water and mixed. 10 µl of mixed
solution was used to measure glucose. Glucose content was measured using OneTouch UltraSmart®
glucose meter (Figure 1; Saballos et al. 2008). Association mapping was conducted using TASSEL 3.0
(Bradbury et al. 2007; available from http://www.maizegenetics.net/) with the mixed linear model (Yu et al. 2006). 14,739
SNP markers (mostly from Wang et al. 2013) were used for the association mapping.
Sorghum stalk
powder
Pretreated with
2% H2SO4
Washed and
digested with
CTec cellulase
Measure
glucose content
Figure 1. Measuring saccharification yield in sorghum.
References
Bradbury PJ, Zhang Z, Kroon DE, Casstevens TM, Ramdoss Y, Buckler ES 2007. Bioinformatics 23:2633-2635.
Murray SC, Rooney WL, Mitchell SE, Kresovich S 2009. Plant Genome, 2:48-62.
Saballos A, Vermerris W, Rivera L, Ejeta G 2008. BioEnerg Res 1: 193-204.
Spokevicius AV, Southerton SG, MacMillan CP, Qiu D, Gan S, Tibbits JFG, Moran GF, Bossinger G 2007. Plant J 51: 717–726.
Vandenbrink JP, MP Delgado, JR Frederick, FA Feltus 2010. Industrial Crops and Products 31:444–448.
Wang Y-H, DD Poudel, KH Hasenstein 2011. Genome 54:883-889.
Wang Y-H, Upadhyaya HD, Burrell AM, Sahraeian SME, Klein RR, Klein PE 2013. GenesGenomes  Genetics doi: 10.1534/g3.112.004861.
Yu JM, Pressoir G, Briggs WH, Bi IV, Yamasaki M, Doebley JF, McMullen MD, Gaut BS, Nielsen DM, Holland JB, Kresovich S, Buckler ES 2006. Nat Genet 38:203-208.
Zhong R, Lee C, McCarthy RL, Reeves CK, Jones EG, Ye ZH 2011. Plant Cell Physiol 52:1856-1871.
Kopetz H 2013. Nature 494: 29-31.
Bahl K B 2013. Nature 493: 483-485.
Caprita N C, McCann M 2008. Trends in Plant Sciences 13: 415-420.
Lorenzana RE, Lewis MF, Jung H-JG, Bernardo R 2010. Crop Science 50 : 541-555.
Glucose meter calibration
Calibration for the OneTouch UltraSmart® glucose
meter using a set of D-glucose solutions in 18 MΩ
water. Each standard was measured three times with
similar readings (from Wang et al. 2011). Linear
relationship between glucose concentration and the
readings is evident. 
Variation of saccharification
yield
Genetic variation in saccharification
yield in sorghum---the lowest and the
highest yield among evaluated
varieties. A. From an evaluation of
the mini core varieties (Wang et al.
2011). B. From an evaluation of 426
conversion varieties
(Vandenbrink et al. 2010). Name of
the variety is on top of each bar. 
SNP markers strongly associated with saccharification yield in sorghum
To find genes potentially related to saccharification yield, we examined the genomic regions
surrounding SNP loci associated with the trait. The gene closest to the locus on chromosome 4
codes for β-tubulin (table below). β-tubulin has been found to determine the orientation of cellulose
microfibrils in plant secondary fiber cell walls and different orientation can influence the strength
and flexibility of secondary plant cell walls (Spokevicius et al. 2007). The gene closest to the two
SNP loci on chromosome 10 encodes a No Apical Meriatem ( NAM) transcription factor SbNAM1 (
Table below ). In Arabidopsis several closely related NAM transcription factors have been shown to
be master switches of secondary wall biosynthesis ( Wang H et al. 2011 ; Zong et al. 2011). SbNAM
1 is most homologous ( 71 % identity and 74% similarity) to the maize secondary wall NAC
transcription factor 1 ( ZmSWN1 ; accession number AEO53053). Overexpression of ZmSWN1
results in ectopic deposition of all three major secondary cell wall components – cellulose, xylan
(hemicellulose) and lignin in the mesophyll cells which are not normally lignified ( Zhong et al
2011)..
SNP marker
chr4_4361515
chr4_4361522
chr4_4361523
chr4_4361525
chr4_4361527
chr4_4361534
chr10_1801700
chr10_1801720
chr10_1801722
chr10_1801726
chr10_1801760 and
chr10_1806523
chr10_1806529
Association p value range
All 7.18  10-7 except
chr4_4361534 which has a
p value of 2.57  10-6.
SNP location (in bp)
4361515 – 4361534 bp
on chromosome 4
Closest gene and function
Sb04g004520 (β-tubulin)
Cell wall cellulose microfibril
orientation
Reference
Spokevicius et al.
2007
See Figure 2
1801700 – 1801760 bp
on chromosome 10
Sb10g002120 (SbNAM1)
Secondary cell wall thickening
Zhong et al. 2011
Figure 2. SNP markers associated with SbNAM1 on sorghum chromosome 10. X-axis
displays the physical location and distance in bp; y-axis is the –log10(p value) as used in
Figure 3---higher values indicate stronger associations. Threshold p value is 3.3910-6, the
Bonferroni-corrected threshold probability at α = 0.05 as described by Murray et al. (2009) for
14,739 SNP markers. In blue are the SNP markers between 1790 kb and 1828 kb. Two
annotated genes are indicated. Scale and positions of the two genes are based on
information from www.phytozome.net/sorghum.
Summary
We have mapped genes responsible for saccharification yield in sorghum using the mini core collection as
the mapping panel and 14,739 SNP markers. The identified candidate genes have been shown to play roles
in plant secondary cell wall synthesis.
Acknowledgements
We Dr. Susan Mopper and Andre Daugereaux for allowing the use of UL’s Center for Ecology and Environmental Technology facility.
The study is supported in part by LA EPSCoR (LEQSF-EPS(2012)-PFUND-298) and the University of Louisiana at Lafayette.
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