Transcriptome analysis in switchgrass discloses ecotype difference in photosynthetic efficiency

Serba, Desalegn D.; Uppalapati, Srinivasa Rao; Krom, Nick; Mukherjee, Shreyartha; Tang, Yuhong; Mysore, Kirankumar S.; Saha, Malay C.

doi:10.1186/s12864-016-3377-8

Transcriptome analysis in switchgrass discloses ecotype difference in photosynthetic efficiency

Journal Article · Thu Dec 01 00:00:00 EST 2016 · BMC Genomics

DOI:https://doi.org/10.1186/s12864-016-3377-8· OSTI ID:1626801

Serba, Desalegn D. ^[1]; Uppalapati, Srinivasa Rao ^[2]; Krom, Nick ^[3]; Mukherjee, Shreyartha ^[3]; Tang, Yuhong ^[4]; Mysore, Kirankumar S. ^[4]; Saha, Malay C. ^[5]

The Samuel Roberts Noble Foundation, Ardmore, OK (United States). Forage Improvement Division; Kansas State Univ., Hays, KS (United States). Agricultural Research Center-Hays; DOE/OSTI
The Samuel Roberts Noble Foundation, Ardmore, OK (United States). Plant Biology Division; DuPont Crop Protection, Newark, DE (United States). Stine-Haskell Research Center
The Samuel Roberts Noble Foundation, Ardmore, OK (United States). Computing Services
The Samuel Roberts Noble Foundation, Ardmore, OK (United States). Plant Biology Division
The Samuel Roberts Noble Foundation, Ardmore, OK (United States). Forage Improvement Division

Background: Switchgrass, a warm-season perennial grass studied as a potential dedicated biofuel feedstock, is classified into two main taxa – lowland and upland ecotypes – that differ in morphology and habitat of adaptation. But there is limited information on their inherent molecular variations. Results: Transcriptome analysis by RNA-sequencing (RNA-Seq) was conducted for lowland and upland ecotypes to document their gene expression variations. Mapping of transcriptome to the reference genome (Panicum virgatum v1. 1) revealed that the lowland and upland ecotypes differ substantially in sets of genes transcribed as well as levels of expression. Differential gene expression analysis exhibited that transcripts related to photosynthesis efficiency and development and photosystem reaction center subunits were upregulated in lowlands compared to upland genotype. On the other hand, catalase isozymes, helix-loop-helix, late embryogenesis abundant group I, photosulfokinases, and S-adenosyl methionine synthase gene transcripts were upregulated in the upland compared to the lowlands. At ≥100x coverage and ≥5% minor allele frequency, a total of 25,894 and 16,979 single nucleotide polymorphism (SNP) markers were discovered for VS16 (upland ecotype) and K5 (lowland ecotype) against the reference genome. The allele combination of the SNPs revealed that the transition mutations are more prevalent than the transversion mutations. Conclusions: The gene ontology (GO) analysis of the transcriptome indicated lowland ecotype had significantly higher representation for cellular components associated with photosynthesis machinery controlling carbon fixation. In addition, using the transcriptome data, SNP markers were detected, which were distributed throughout the genome. The differentially expressed genes and SNP markers detected in this study would be useful resources for traits mapping and gene transfer across ecotypes in switchgrass breeding for increased biomass yield for biofuel conversion.

View Accepted Manuscript (DOE)

Research Organization:: The Samuel Roberts Noble Foundation, Ardmore, OK (United States)

Sponsoring Organization:: USDOE Office of Science (SC), Biological and Environmental Research (BER). Biological Systems Science Division

Grant/Contract Number:: FG02-00ER41132

OSTI ID:: 1626801

Journal Information:: BMC Genomics, Journal Name: BMC Genomics Journal Issue: 1 Vol. 17; ISSN 1471-2164

Publisher:: SpringerCopyright Statement

Country of Publication:: United States

Language:: English

References (71)

Exploiting EST databases for the development and characterization of gene-derived SSR-markers in barley (Hordeum vulgare L.) Thiel, T.; Michalek, W.; Varshney, R. Theoretical and Applied Genetics, Vol. 106, Issue 3 https://doi.org/10.1007/s00122-002-1031-0	journal	February 2003
Bridging the genotyping gap: using genotyping by sequencing (GBS) to add high-density SNP markers and new value to traditional bi-parental mapping and breeding populations Spindel, Jennifer; Wright, Mark; Chen, Charles Theoretical and Applied Genetics, Vol. 126, Issue 11 https://doi.org/10.1007/s00122-013-2166-x	journal	August 2013
Switchgrass (Panicum virgatum L) flag leaf transcriptomes reveal molecular signatures of leaf development, senescence, and mineral dynamics Palmer, Nathan A.; Donze-Reiner, Teresa; Horvath, David Functional & Integrative Genomics, Vol. 15, Issue 1 https://doi.org/10.1007/s10142-014-0393-0	journal	August 2014
Molecular Markers for the Classification of Switchgrass (Panicum virgatum L.) Germplasm and to Assess Genetic Diversity in Three Synthetic Switchgrass Populations Missaoui, Ali M.; Paterson, Andrew H.; Bouton, Joseph H. Genetic Resources and Crop Evolution, Vol. 53, Issue 6 https://doi.org/10.1007/s10722-005-3878-9	journal	March 2006
Development and integration of EST–SSR markers into an established linkage map in switchgrass Liu, Linglong; Huang, Yalin; Punnuri, Somashekhar Molecular Breeding, Vol. 32, Issue 4 https://doi.org/10.1007/s11032-013-9921-1	journal	July 2013
Algal biofuels Razeghifard, Reza Photosynthesis Research, Vol. 117, Issue 1-3 https://doi.org/10.1007/s11120-013-9828-z	journal	April 2013
Photosynthetic gene expression in higher plants Berry, James O.; Yerramsetty, Pradeep; Zielinski, Amy M. Photosynthesis Research, Vol. 117, Issue 1-3 https://doi.org/10.1007/s11120-013-9880-8	journal	July 2013
Standardization of Switchgrass Sample Collection for Cell Wall and Biomass Trait Analysis Hardin, C. Frank; Fu, Chunxiang; Hisano, Hiroshi BioEnergy Research, Vol. 6, Issue 2 https://doi.org/10.1007/s12155-012-9292-1	journal	January 2013
Linkage Maps of Lowland and Upland Tetraploid Switchgrass Ecotypes Serba, Desalegn; Wu, Limin; Daverdin, Guillaume BioEnergy Research, Vol. 6, Issue 3 https://doi.org/10.1007/s12155-013-9315-6	journal	March 2013
Dedicated Herbaceous Biomass Feedstock Genetics and Development Anderson, W. F.; Sarath, G.; Edme, S. BioEnergy Research, Vol. 9, Issue 2 https://doi.org/10.1007/s12155-015-9709-8	journal	June 2016
Biofuels Somerville, Chris Current Biology, Vol. 17, Issue 4, p. R115-R119 https://doi.org/10.1016/j.cub.2007.01.010	journal	February 2007
Genomics of cellulosic biofuels Rubin, Edward M. Nature, Vol. 454, Issue 7206 https://doi.org/10.1038/nature07190	journal	August 2008
Comparative population genomics in animals uncovers the determinants of genetic diversity Romiguier, J.; Gayral, P.; Ballenghien, M. Nature, Vol. 515, Issue 7526 https://doi.org/10.1038/nature13685	journal	August 2014
CCL5 derived from tumor-associated macrophages promotes prostate cancer stem cells and metastasis via activating β-catenin/STAT3 signaling Huang, Renlun; Wang, Shengqi; Wang, Neng Cell Death & Disease, Vol. 11, Issue 4 https://doi.org/10.1038/s41419-020-2435-y	journal	April 2020
Dietary palmitic acid promotes a prometastatic memory via Schwann cells Pascual, Gloria; Domínguez, Diana; Elosúa-Bayes, Marc Nature, Vol. 599, Issue 7885 https://doi.org/10.1038/s41586-021-04075-0	journal	November 2021
Characterizing the molecular regulation of inhibitory immune checkpoints with multimodal single-cell screens Papalexi, Efthymia; Mimitou, Eleni P.; Butler, Andrew W. Nature Genetics, Vol. 53, Issue 3 https://doi.org/10.1038/s41588-021-00778-2	journal	March 2021
Salinity tolerance mechanisms of an Arctic Pelagophyte using comparative transcriptomic and gene expression analysis Freyria, Nastasia J.; Kuo, Alan; Chovatia, Mansi Communications Biology, Vol. 5, Issue 1 https://doi.org/10.1038/s42003-022-03461-2	journal	May 2022
CP12 provides a new mode of light regulation of Calvin cycle activity in higher plants Wedel, N.; Soll, J.; Paap, B. K. Proceedings of the National Academy of Sciences, Vol. 94, Issue 19 https://doi.org/10.1073/pnas.94.19.10479	journal	September 1997
Peroxiredoxin Functions as a Peroxidase and a Regulator and Sensor of Local Peroxides Rhee, Sue Goo; Woo, Hyun Ae; Kil, In Sup Journal of Biological Chemistry, Vol. 287, Issue 7 https://doi.org/10.1074/jbc.r111.283432	journal	December 2011
The Biology and Agronomy of Switchgrass for Biofuels Parrish, David J.; Fike, John H. Critical Reviews in Plant Sciences, Vol. 24, Issue 5-6 https://doi.org/10.1080/07352680500316433	journal	September 2005
The Sequence Alignment/Map format and SAMtools Li, H.; Handsaker, B.; Wysoker, A. Bioinformatics, Vol. 25, Issue 16 https://doi.org/10.1093/bioinformatics/btp352	journal	June 2009
Identification of novel transcripts in annotated genomes using RNA-Seq Roberts, A.; Pimentel, H.; Trapnell, C. Bioinformatics, Vol. 27, Issue 17 https://doi.org/10.1093/bioinformatics/btr355	journal	June 2011
The Gene Ontology (GO) database and informatics resource No authors listed Nucleic Acids Research, Vol. 32, Issue 90001 https://doi.org/10.1093/nar/gkh036	journal	January 2004
Detection of single nucleotide variations in expressed exons of the human genome using RNA-Seq Chepelev, Iouri; Wei, Gang; Tang, Qingsong Nucleic Acids Research, Vol. 37, Issue 16 https://doi.org/10.1093/nar/gkp507	journal	June 2009
agriGO: a GO analysis toolkit for the agricultural community Du, Zhou; Zhou, Xin; Ling, Yi Nucleic Acids Research, Vol. 38, Issue suppl_2 https://doi.org/10.1093/nar/gkq310	journal	April 2010
Combining RT-PCR-seq and RNA-seq to catalog all genic elements encoded in the human genome Howald, C.; Tanzer, A.; Chrast, J. Genome Research, Vol. 22, Issue 9 https://doi.org/10.1101/gr.134478.111	journal	September 2012
Evidence of neutral transcriptome evolution in plants Broadley, M. R.; White, P. J.; Hammond, J. P. New Phytologist, Vol. 180, Issue 3 https://doi.org/10.1111/j.1469-8137.2008.02640.x	journal	November 2008
Genic microsatellite markers derived from EST sequences of switchgrass (Panicum virgatum L.) Tobias, Christian M.; Hayden, Daniel M.; Twigg, Paul Molecular Ecology Notes, Vol. 6, Issue 1 https://doi.org/10.1111/j.1471-8286.2006.01187.x	journal	March 2006
High-throughput genomics in sorghum: from whole-genome resequencing to a SNP screening array Bekele, Wubishet A.; Wieckhorst, Silke; Friedt, Wolfgang Plant Biotechnology Journal, Vol. 11, Issue 9 https://doi.org/10.1111/pbi.12106	journal	August 2013
Single-nucleotide polymorphism discovery by high-throughput sequencing in sorghum Nelson, James C.; Wang, Shichen; Wu, Yuye BMC Genomics, Vol. 12, Issue 1 https://doi.org/10.1186/1471-2164-12-352	journal	July 2011
Integrating transcriptional, metabolomic, and physiological responses to drought stress and recovery in switchgrass (Panicum virgatum L.) Meyer, Eli; Aspinwall, Michael J.; Lowry, David B. BMC Genomics, Vol. 15, Issue 1 https://doi.org/10.1186/1471-2164-15-527	journal	January 2014
Visualizing genomic information across chromosomes with PhenoGram Wolfe, Daniel; Dudek, Scott; Ritchie, Marylyn D. BioData Mining, Vol. 6, Issue 1 https://doi.org/10.1186/1756-0381-6-18	journal	October 2013
Improving RNA-Seq expression estimates by correcting for fragment bias Roberts, Adam; Trapnell, Cole; Donaghey, Julie Genome Biology, Vol. 12, Issue 3 https://doi.org/10.1186/gb-2011-12-3-r22	journal	January 2011
TopHat2: accurate alignment of transcriptomes in the presence of insertions, deletions and gene fusions Kim, Daehwan; Pertea, Geo; Trapnell, Cole Genome Biology, Vol. 14, Issue 4 https://doi.org/10.1186/gb-2013-14-4-r36	journal	January 2013
Comprehensive evaluation of differential gene expression analysis methods for RNA-seq data Rapaport, Franck; Khanin, Raya; Liang, Yupu Genome Biology, Vol. 14, Issue 9 https://doi.org/10.1186/gb-2013-14-9-r95	journal	January 2013
Deep transcriptome sequencing provides new insights into the structural and functional organization of the wheat genome Pingault, Lise; Choulet, Frédéric; Alberti, Adriana Genome Biology, Vol. 16, Issue 1 https://doi.org/10.1186/s13059-015-0601-9	journal	February 2015
Revisiting an Old Riddle: What Determines Genetic Diversity Levels within Species? Leffler, Ellen M.; Bullaughey, Kevin; Matute, Daniel R. PLoS Biology, Vol. 10, Issue 9 https://doi.org/10.1371/journal.pbio.1001388	journal	September 2012
Switchgrass Genomic Diversity, Ploidy, and Evolution: Novel Insights from a Network-Based SNP Discovery Protocol Lu, Fei; Lipka, Alexander E.; Glaubitz, Jeff PLoS Genetics, Vol. 9, Issue 1 https://doi.org/10.1371/journal.pgen.1003215	journal	January 2013
An Improved Genotyping by Sequencing (GBS) Approach Offering Increased Versatility and Efficiency of SNP Discovery and Genotyping Sonah, Humira; Bastien, Maxime; Iquira, Elmer PLoS ONE, Vol. 8, Issue 1 https://doi.org/10.1371/journal.pone.0054603	journal	January 2013
A Next-Generation Sequencing Method for Genotyping-by-Sequencing of Highly Heterozygous Autotetraploid Potato Uitdewilligen, Jan G. A. M. L.; Wolters, Anne-Marie A.; D’hoop, Bjorn B. PLoS ONE, Vol. 8, Issue 5 https://doi.org/10.1371/journal.pone.0062355	journal	May 2013
Contrasting Metabolism in Perenniating Structures of Upland and Lowland Switchgrass Plants Late in the Growing Season Palmer, Nathan A.; Saathoff, Aaron J.; Tobias, Christian M. PLoS ONE, Vol. 9, Issue 8 https://doi.org/10.1371/journal.pone.0105138	journal	August 2014
A High-Density Simple Sequence Repeat-Based Genetic Linkage Map of Switchgrass Liu, Linglong; Wu, Yanqi; Wang, Yunwen G3: Genes\|Genomes\|Genetics, Vol. 2, Issue 3 https://doi.org/10.1534/g3.111.001503	journal	March 2012
The CP12 protein family: a thioredoxin-mediated metabolic switch? López-Calcagno, Patricia E.; Howard, Thomas P.; Raines, Christine A. Frontiers in Plant Science, Vol. 5 https://doi.org/10.3389/fpls.2014.00009	journal	January 2014
Linkage Map Construction and Quantitative Trait Locus Analysis of Agronomic and Fiber Quality Traits in Cotton Gore, Michael A.; Fang, David D.; Poland, Jesse A. The Plant Genome, Vol. 7, Issue 1 https://doi.org/10.3835/plantgenome2013.07.0023	journal	March 2014
Algal Biofuels Tiwari, Archana; Pandey, Anjana Natural and Artificial Photosynthesis: Solar Power as an Energy Source https://doi.org/10.1002/9781118659892.ch9	book	August 2013
Molecular breeding of switchgrass for use as a biofuel crop Bouton, Joseph H. Current Opinion in Genetics & Development, Vol. 17, Issue 6 https://doi.org/10.1016/j.gde.2007.08.012	journal	December 2007
Gene Ontology: tool for the unification of biology Ashburner, Michael; Ball, Catherine A.; Blake, Judith A. Nature Genetics, Vol. 25, Issue 1 https://doi.org/10.1038/75556	journal	May 2000
Transcript assembly and quantification by RNA-Seq reveals unannotated transcripts and isoform switching during cell differentiation Trapnell, Cole; Williams, Brian A.; Pertea, Geo Nature Biotechnology, Vol. 28, Issue 5 https://doi.org/10.1038/nbt.1621	journal	May 2010
Differential analysis of gene regulation at transcript resolution with RNA-seq Trapnell, Cole; Hendrickson, David G.; Sauvageau, Martin Nature Biotechnology, Vol. 31, Issue 1 https://doi.org/10.1038/nbt.2450	journal	December 2012
Mapping and quantifying mammalian transcriptomes by RNA-Seq Mortazavi, Ali; Williams, Brian A.; McCue, Kenneth Nature Methods, Vol. 5, Issue 7, p. 621-628 https://doi.org/10.1038/nmeth.1226	journal	May 2008
Fast gapped-read alignment with Bowtie 2 Langmead, Ben; Salzberg, Steven L. Nature Methods, Vol. 9, Issue 4 https://doi.org/10.1038/nmeth.1923	journal	March 2012
Differential expression analysis for sequence count data Anders, Simon; Huber, Wolfgang Nature Precedings https://doi.org/10.1038/npre.2010.4282.2	journal	April 2010
Transcriptomic analysis of female and male gonads in juvenile snakeskin gourami (Trichopodus pectoralis) Boonanuntanasarn, Surintorn; Jangprai, Araya; Na-Nakorn, Uthairat Scientific Reports, Vol. 10, Issue 1 https://doi.org/10.1038/s41598-020-61738-0	journal	March 2020
Peroxiredoxin Functions as a Peroxidase and a Regulator and Sensor of Local Peroxides Rhee, Sue Goo; Woo, Hyun Ae; Kil, In Sup Journal of Biological Chemistry, Vol. 287, Issue 7 https://doi.org/10.1074/jbc.R111.283432	journal	December 2011
A Comparison of Rice Chloroplast Genomes Tang, Jiabin; Xia, Hong'ai; Cao, Mengliang Plant Physiology, Vol. 135, Issue 1 https://doi.org/10.1104/pp.103.031245	journal	April 2004
Genomic diversity in switchgrass (Panicum virgatum): from the continental scale to a dune landscape: GENOMIC DIVERSITY IN SWITCHGRASS Morris, Geoffrey P.; Grabowski, Paul P.; Borevitz, Justin O. Molecular Ecology, Vol. 20, Issue 23 https://doi.org/10.1111/j.1365-294X.2011.05335.x	journal	November 2011
P LANT P EROXIREDOXINS Dietz, Karl-Josef Annual Review of Plant Biology, Vol. 54, Issue 1 https://doi.org/10.1146/annurev.arplant.54.031902.134934	journal	June 2003
Differential expression analysis for sequence count data Anders, Simon; Huber, Wolfgang Genome Biology, Vol. 11, Issue 10 https://doi.org/10.1186/gb-2010-11-10-r106	journal	October 2010
InteractiVenn: a web-based tool for the analysis of sets through Venn diagrams Heberle, Henry; Meirelles, Gabriela Vaz; da Silva, Felipe R. BMC Bioinformatics, Vol. 16, Issue 1 https://doi.org/10.1186/s12859-015-0611-3	journal	May 2015
Genomic insight into diet adaptation in the biological control agent Cryptolaemus montrouzieri Li, Hao-Sen; Huang, Yu-Hao; Chen, Mei-Lan BMC Genomics, Vol. 22, Issue 1 https://doi.org/10.1186/s12864-021-07442-3	journal	February 2021
Maize (Zea mays L.) Genome Diversity as Revealed by RNA-Sequencing Kumar, Santosh The Role of Bioinformatics in Agriculture https://doi.org/10.1201/b16568-18	book	February 2014
TopHat2: accurate alignment of transcriptomes in the presence of insertions, deletions and gene fusions Kim, Daehwan; Pertea, Geo; Trapnell, Cole Springer Nature https://doi.org/10.13016/7jyb-2sdy	text	January 2013
Correction: A High Throughput In Vivo Assay for Taste Quality and Palatability Palmer, R. Kyle; Long, Daniel; Brennan, Francis PLoS ONE, Vol. 9, Issue 1 https://doi.org/10.1371/annotation/6a76b80f-015c-4749-9b11-e3db355726e3	journal	January 2014
Chloroplast Genome Variation in Upland and Lowland Switchgrass Young, Hugh A.; Lanzatella, Christina L.; Sarath, Gautam PLoS ONE, Vol. 6, Issue 8 https://doi.org/10.1371/journal.pone.0023980	journal	August 2011
Development of High-Density Genetic Maps for Barley and Wheat Using a Novel Two-Enzyme Genotyping-by-Sequencing Approach Poland, Jesse A.; Brown, Patrick J.; Sorrells, Mark E. PLoS ONE, Vol. 7, Issue 2 https://doi.org/10.1371/journal.pone.0032253	journal	February 2012
Maize (Zea mays L.) Genome Diversity as Revealed by RNA-Sequencing Hansey, Candice N.; Vaillancourt, Brieanne; Sekhon, Rajandeep S. PLoS ONE, Vol. 7, Issue 3, Article No. e33071 https://doi.org/10.1371/journal.pone.0033071	journal	March 2012
Exploring the Switchgrass Transcriptome Using Second-Generation Sequencing Technology Wang, Yixing; Zeng, Xin; Iyer, Niranjani J. PLoS ONE, Vol. 7, Issue 3 https://doi.org/10.1371/journal.pone.0034225	journal	March 2012
Genetic Linkage Mapping and Transmission Ratio Distortion in a Three-Generation Four-Founder Population of Panicum virgatum (L.) Li, Guifen; Serba, Desalegn D.; Saha, Malay C. G3: Genes\|Genomes\|Genetics, Vol. 4, Issue 5 https://doi.org/10.1534/g3.113.010165	journal	March 2014
Complete Switchgrass Genetic Maps Reveal Subgenome Collinearity, Preferential Pairing and Multilocus Interactions Okada, Miki; Lanzatella, Christina; Saha, Malay C. Genetics, Vol. 185, Issue 3 https://doi.org/10.1534/genetics.110.113910	journal	April 2010
Chloroplast DNA and Nuclear DNA Content Variations among Cultivars of Switchgrass, Panicum virgatum L. Hultquist, Sherry J.; Vogel, K. P.; Lee, D. J. Crop Science, Vol. 36, Issue 4 https://doi.org/10.2135/cropsci1996.0011183X003600040039x	journal	January 1996
Transcriptome Profiling of Rust Resistance in Switchgrass Using RNA-Seq Analysis Serba, Desalegn D.; Uppalapati, Srinivasa Rao; Mukherjee, Shreyartha The Plant Genome, Vol. 8, Issue 2 https://doi.org/10.3835/plantgenome2014.10.0075	journal	January 2015

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09 BIOMASS FUELS
59 BASIC BIOLOGICAL SCIENCES
Biotechnology & Applied Microbiology
Ecotype
Genetics & Heredity
Photosynthesis
SNP markers
Switchgrass
Transcriptome

Additional file 4: Table S3. of Transcriptome analysis in switchgrass discloses ecotype difference in photosynthetic efficiency Serba, Desalegn; Uppalapati, Srinivasa; Krom, Nick https://doi.org/10.6084/M9.FIGSHARE.C.3647507_D1 The current record is supplemented by this dataset	dataset	January 2016
Additional file 2: Table S2. of Transcriptome analysis in switchgrass discloses ecotype difference in photosynthetic efficiency Serba, Desalegn; Uppalapati, Srinivasa; Krom, Nick https://doi.org/10.6084/M9.FIGSHARE.C.3647507_D3 The current record is supplemented by this dataset	dataset	January 2016
Additional file 1: Table S1. of Transcriptome analysis in switchgrass discloses ecotype difference in photosynthetic efficiency Serba, Desalegn; Uppalapati, Srinivasa; Krom, Nick https://doi.org/10.6084/M9.FIGSHARE.C.3647507_D5 The current record is supplemented by this dataset	dataset	January 2016
Transcriptome analysis in switchgrass discloses ecotype difference in photosynthetic efficiency Serba, Desalegn; Uppalapati, Srinivasa; Krom, Nick https://doi.org/10.6084/m9.figshare.c.3647507 The current record is supplemented by this collection	collection	January 2016
Transcriptome analysis in switchgrass discloses ecotype difference in photosynthetic efficiency Serba, Desalegn; Uppalapati, Srinivasa; Krom, Nick https://doi.org/10.6084/m9.figshare.c.3647507.v1 The current record is supplemented by this collection	collection	January 2016
Additional file 4: Table S3. of Transcriptome analysis in switchgrass discloses ecotype difference in photosynthetic efficiency Serba, Desalegn; Uppalapati, Srinivasa; Krom, Nick https://doi.org/10.6084/m9.figshare.c.3647507_d1.v1 The current record is supplemented by this dataset	dataset	January 2016
Additional file 3: Figure S1. of Transcriptome analysis in switchgrass discloses ecotype difference in photosynthetic efficiency Serba, Desalegn; Uppalapati, Srinivasa; Krom, Nick https://doi.org/10.6084/m9.figshare.c.3647507_d2 The current record is supplemented by this text	text	January 2016
Additional file 3: Figure S1. of Transcriptome analysis in switchgrass discloses ecotype difference in photosynthetic efficiency Serba, Desalegn; Uppalapati, Srinivasa; Krom, Nick https://doi.org/10.6084/m9.figshare.c.3647507_d2.v1 The current record is supplemented by this text	text	January 2016
Additional file 2: Table S2. of Transcriptome analysis in switchgrass discloses ecotype difference in photosynthetic efficiency Serba, Desalegn; Uppalapati, Srinivasa; Krom, Nick https://doi.org/10.6084/m9.figshare.c.3647507_d3.v1 The current record is supplemented by this dataset	dataset	January 2016
Additional file 5: Table S4. of Transcriptome analysis in switchgrass discloses ecotype difference in photosynthetic efficiency Serba, Desalegn; Uppalapati, Srinivasa; Krom, Nick https://doi.org/10.6084/m9.figshare.c.3647507_d4 The current record is supplemented by this text	text	January 2016
Additional file 5: Table S4. of Transcriptome analysis in switchgrass discloses ecotype difference in photosynthetic efficiency Serba, Desalegn; Uppalapati, Srinivasa; Krom, Nick https://doi.org/10.6084/m9.figshare.c.3647507_d4.v1 The current record is supplemented by this text	text	January 2016
Additional file 1: Table S1. of Transcriptome analysis in switchgrass discloses ecotype difference in photosynthetic efficiency Serba, Desalegn; Uppalapati, Srinivasa; Krom, Nick https://doi.org/10.6084/m9.figshare.c.3647507_d5.v1 The current record is supplemented by this dataset	dataset	January 2016

Transcriptome analysis in switchgrass discloses ecotype difference in photosynthetic efficiency

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