Revealing the transcriptomic complexity of switchgrass by PacBio long-read sequencing

Zuo, Chunman; Blow, Matthew; Sreedasyam, Avinash; Kuo, Rita C.; Ramamoorthy, Govindarajan Kunde; Torres-Jerez, Ivone; Li, Guifen; Wang, Mei; Dilworth, David; Barry, Kerrie; Udvardi, Michael; Schmutz, Jeremy; Tang, Yuhong; Xu, Ying

doi:10.1186/s13068-018-1167-z

Title: Revealing the transcriptomic complexity of switchgrass by PacBio long-read sequencing

Journal Article · Wed Jun 20 00:00:00 EDT 2018 · Biotechnology for Biofuels

DOI:https://doi.org/10.1186/s13068-018-1167-z· OSTI ID:1477307

Zuo, Chunman ^[1]; Blow, Matthew ^[2]; Sreedasyam, Avinash ^[3]; Kuo, Rita C. ^[2]; Ramamoorthy, Govindarajan Kunde ^[2]; Torres-Jerez, Ivone ^[4]; Li, Guifen ^[4]; Wang, Mei ^[2]; Dilworth, David ^[2]; Barry, Kerrie ^[2]; Udvardi, Michael ^[4]; Schmutz, Jeremy ^[5]; Tang, Yuhong ^[6]; Xu, Ying ^[1]

Jilin Univ., Changchun (China); Univ. of Georgia, Athens, GA (United States); Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)
USDOE Joint Genome Institute (JGI), Walnut Creek, CA (United States)
HudsonAlpha Institute for Biotechnology, Huntsville, AL (United States)
Noble Research Institute, LLC, Ardmore, OK (United States)
USDOE Joint Genome Institute (JGI), Walnut Creek, CA (United States); HudsonAlpha Institute for Biotechnology, Huntsville, AL (United States)
Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Noble Research Institute, LLC, Ardmore, OK (United States)

Switchgrass (Panicum virgatum L.) is an important bioenergy crop widely used for lignocellulosic research. While extensive transcriptomic analyses have been conducted on this species using short read-based sequencing techniques, very little has been reliably derived regarding alternatively spliced (AS) transcripts. Here, we present an analysis of transcriptomes of six switchgrass tissue types pooled together, sequenced using Pacific Biosciences (PacBio) single-molecular long-read technology. Our analysis identified 105,419 unique transcripts covering 43,570 known genes and 8795 previously unknown genes. 45,168 are novel transcripts of known genes. A total of 60,096 AS transcripts are identified, 45,628 being novel. We have also predicted 1549 transcripts of genes involved in cell wall construction and remodeling, 639 being novel transcripts of known cell wall genes. Most of the predicted transcripts are validated against Illumina-based short reads. Specifically, 96% of the splice junction sites in all the unique transcripts are validated by at least five Illumina reads. Comparisons between genes derived from our identified transcripts and the current genome annotation revealed that among the gene set predicted by both analyses, 16,640 have different exon-intron structures. Overall, substantial amount of new information is derived from the PacBio RNA data regarding both the transcriptome and the genome of switchgrass.

View Accepted Manuscript (DOE)

Cite

Export

Save

Research Organization:: Lawrence Berkeley National Laboratory (LBNL), Berkeley, CA (United States)

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

Grant/Contract Number:: AC02-05CH11231

OSTI ID:: 1477307

Journal Information:: Biotechnology for Biofuels, Vol. 11, Issue 1; ISSN 1754-6834

Publisher:: BioMed CentralCopyright Statement

Country of Publication:: United States

Language:: English

Citation Metrics:

Cited by: 27 works

Citation information provided by
Web of Science

References (70)

Experimental validation of the regulated expression of large numbers of non-coding RNAs from the mouse genome Ravasi, T. Genome Research, Vol. 16, Issue 1 https://doi.org/10.1101/gr.4200206	journal	December 2005
Transcriptome survey reveals increased complexity of the alternative splicing landscape in Arabidopsis Marquez, Yamile; Brown, John W. S.; Simpson, Craig Genome Research, Vol. 22, Issue 6 https://doi.org/10.1101/gr.134106.111	journal	March 2012
Long noncoding RNAs in development and disease of the central nervous system Ng, Shi-Yan; Lin, Lin; Soh, Boon Seng Trends in Genetics, Vol. 29, Issue 8 https://doi.org/10.1016/j.tig.2013.03.002	journal	August 2013
Gene clustering in plant specialized metabolism Nützmann, Hans-Wilhelm; Osbourn, Anne Current Opinion in Biotechnology, Vol. 26 https://doi.org/10.1016/j.copbio.2013.10.009	journal	April 2014
SpliceGrapher: detecting patterns of alternative splicing from RNA-Seq data in the context of gene models and EST data Rogers, Mark F.; Thomas, Julie; Reddy, Anireddy SN Genome Biology, Vol. 13, Issue 1 https://doi.org/10.1186/gb-2012-13-1-r4	journal	January 2012
PNRD: a plant non-coding RNA database Yi, Xin; Zhang, Zhenhai; Ling, Yi Nucleic Acids Research, Vol. 43, Issue D1 https://doi.org/10.1093/nar/gku1162	journal	November 2014
Widespread Polycistronic Transcripts in Fungi Revealed by Single-Molecule mRNA Sequencing Gordon, Sean P.; Tseng, Elizabeth; Salamov, Asaf PLOS ONE, Vol. 10, Issue 7 https://doi.org/10.1371/journal.pone.0132628	journal	July 2015
Managing and enhancing switchgrass as a bioenergy feedstock Mitchell, Rob; Vogel, Kenneth P.; Sarath, Gautam Biofuels, Bioproducts and Biorefining, Vol. 2, Issue 6 https://doi.org/10.1002/bbb.106	journal	November 2008
An optimized protocol for forensic application of the PreCR™ Repair Mix to multiplex STR amplification of UV-damaged DNA Diegoli, Toni M.; Farr, Matthew; Cromartie, Carter Forensic Science International: Genetics, Vol. 6, Issue 4 https://doi.org/10.1016/j.fsigen.2011.09.003	journal	July 2012
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
The rise of operon-like gene clusters in plants Boycheva, Svetlana; Daviet, Laurent; Wolfender, Jean-Luc Trends in Plant Science, Vol. 19, Issue 7 https://doi.org/10.1016/j.tplants.2014.01.013	journal	July 2014
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
Unveiling the complexity of the maize transcriptome by single-molecule long-read sequencing Wang, Bo; Tseng, Elizabeth; Regulski, Michael Nature Communications, Vol. 7, Issue 1 https://doi.org/10.1038/ncomms11708	journal	June 2016
Assessment of transcript reconstruction methods for RNA-seq Steijger, Tamara; Abril, Josep F.; Engström, Pär G. Nature Methods, Vol. 10, Issue 12 https://doi.org/10.1038/nmeth.2714	journal	November 2013
A survey of the sorghum transcriptome using single-molecule long reads Abdel-Ghany, Salah E.; Hamilton, Michael; Jacobi, Jennifer L. Nature Communications, Vol. 7, Issue 1 https://doi.org/10.1038/ncomms11706	journal	June 2016
Biomass Recalcitrance: Engineering Plants and Enzymes for Biofuels Production Himmel, M. E.; Ding, S.-Y.; Johnson, D. K. Science, Vol. 315, Issue 5813, p. 804-807 https://doi.org/10.1126/science.1137016	journal	February 2007
The Switchgrass Genome: Tools and Strategies Casler, Michael D.; Tobias, Christian M.; Kaeppler, Shawn M. The Plant Genome Journal, Vol. 4, Issue 3 https://doi.org/10.3835/plantgenome2011.10.0026	journal	January 2011
A field guide to whole-genome sequencing, assembly and annotation Ekblom, Robert; Wolf, Jochen B. W. Evolutionary Applications, Vol. 7, Issue 9 https://doi.org/10.1111/eva.12178	journal	June 2014
Defining a personal, allele-specific, and single-molecule long-read transcriptome Tilgner, Hagen; Grubert, Fabian; Sharon, Donald Proceedings of the National Academy of Sciences, Vol. 111, Issue 27 https://doi.org/10.1073/pnas.1400447111	journal	June 2014
The WRKY transcription factor family and senescence in switchgrass Rinerson, Charles I.; Scully, Erin D.; Palmer, Nathan A. BMC Genomics, Vol. 16, Issue 1 https://doi.org/10.1186/s12864-015-2057-4	journal	November 2015
Differential gene and transcript expression analysis of RNA-seq experiments with TopHat and Cufflinks Trapnell, Cole; Roberts, Adam; Goff, Loyal Nature Protocols, Vol. 7, Issue 3 https://doi.org/10.1038/nprot.2012.016	journal	March 2012
RNA Maps Reveal New RNA Classes and a Possible Function for Pervasive Transcription Kapranov, P.; Cheng, J.; Dike, S. Science, Vol. 316, Issue 5830 https://doi.org/10.1126/science.1138341	journal	June 2007
PlantTFDB 4.0: toward a central hub for transcription factors and regulatory interactions in plants Jin, Jinpu; Tian, Feng; Yang, De-Chang Nucleic Acids Research, Vol. 45, Issue D1 https://doi.org/10.1093/nar/gkw982	journal	October 2016
How biotech can transform biofuels Lynd, Lee R.; Laser, Mark S.; Bransby, David Nature Biotechnology, Vol. 26, Issue 2, p. 169-172 https://doi.org/10.1038/nbt0208-169	journal	February 2008
Development of an integrated transcript sequence database and a gene expression atlas for gene discovery and analysis in switchgrass ( Panicum virgatum L.) Zhang, Ji-Yi; Lee, Yi-Ching; Torres-Jerez, Ivone The Plant Journal, Vol. 74, Issue 1 https://doi.org/10.1111/tpj.12104	journal	February 2013
GenBank Clark, Karen; Karsch-Mizrachi, Ilene; Lipman, David J. Nucleic Acids Research, Vol. 44, Issue D1 https://doi.org/10.1093/nar/gkv1276	journal	November 2015
An Introduction to Sequence Similarity (“Homology”) Searching Pearson, William R. Current Protocols in Bioinformatics, Vol. 42, Issue 1 https://doi.org/10.1002/0471250953.bi0301s42	journal	June 2013
Switchgrass SBP-box transcription factors PvSPL1 and 2 function redundantly to initiate side tillers and affect biomass yield of energy crop Wu, Zhenying; Cao, Yingping; Yang, Ruijuan Biotechnology for Biofuels, Vol. 9, Issue 1 https://doi.org/10.1186/s13068-016-0516-z	journal	May 2016
Genetic variants regulating ORMDL3 expression contribute to the risk of childhood asthma Moffatt, Miriam F.; Kabesch, Michael; Liang, Liming Nature, Vol. 448, Issue 7152 https://doi.org/10.1038/nature06014	journal	July 2007
Identification and Molecular Characterization of the Switchgrass AP2/ERF Transcription Factor Superfamily, and Overexpression of PvERF001 for Improvement of Biomass Characteristics for Biofuel Wuddineh, Wegi A.; Mazarei, Mitra; Turner, Geoffrey B. Frontiers in Bioengineering and Biotechnology, Vol. 3 https://doi.org/10.3389/fbioe.2015.00101	journal	July 2015
Switchgrass for bioethanol and other value-added applications: A review Keshwani, Deepak R.; Cheng, Jay J. Bioresource Technology, Vol. 100, Issue 4 https://doi.org/10.1016/j.biortech.2008.09.035	journal	February 2009
A survey of best practices for RNA-seq data analysis Conesa, Ana; Madrigal, Pedro; Tarazona, Sonia Genome Biology, Vol. 17, Issue 1 https://doi.org/10.1186/s13059-016-0881-8	journal	January 2016
The feasibility of switchgrass for biofuel production Mitchell, Rob; Vogel, Kenneth P.; Uden, Daniel R. Biofuels, Vol. 3, Issue 1 https://doi.org/10.4155/bfs.11.153	journal	January 2012
Biosolutions to the energy problem Demain, Arnold L. Journal of Industrial Microbiology & Biotechnology, Vol. 36, Issue 3 https://doi.org/10.1007/s10295-008-0521-8	journal	January 2009
PBSIM: PacBio reads simulator—toward accurate genome assembly Ono, Yukiteru; Asai, Kiyoshi; Hamada, Michiaki Bioinformatics, Vol. 29, Issue 1 https://doi.org/10.1093/bioinformatics/bts649	journal	November 2012
Describing and Quantifying Growth Stages of Perennial Forage Grasses Moore, K. J.; Moser, L. E.; Vogel, K. P. Agronomy Journal, Vol. 83, Issue 6 https://doi.org/10.2134/agronj1991.00021962008300060027x	journal	January 1991
Development of switchgrass (Panicum virgatum) as a bioenergy feedstock in the United States McLaughlin, Samuel B.; Adams Kszos, Lynn Biomass and Bioenergy, Vol. 28, Issue 6 https://doi.org/10.1016/j.biombioe.2004.05.006	journal	June 2005
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
Reference sequence (RefSeq) database at NCBI: current status, taxonomic expansion, and functional annotation O'Leary, Nuala A.; Wright, Mathew W.; Brister, J. Rodney Nucleic Acids Research, Vol. 44, Issue D1 https://doi.org/10.1093/nar/gkv1189	journal	November 2015
Genomics of plant cell wall biogenesis Yong, Weidong; Link, Bruce; O’Malley, Ronan Planta, Vol. 221, Issue 6 https://doi.org/10.1007/s00425-005-1563-z	journal	June 2005
Analysis and design of RNA sequencing experiments for identifying isoform regulation Katz, Yarden; Wang, Eric T.; Airoldi, Edoardo M. Nature Methods, Vol. 7, Issue 12 https://doi.org/10.1038/nmeth.1528	journal	November 2010
Advances in biotechnology and genomics of switchgrass Nageswara-Rao, Madhugiri; Soneji, Jaya R.; Kwit, Charles Biotechnology for Biofuels, Vol. 6, Issue 1 https://doi.org/10.1186/1754-6834-6-77	journal	January 2013
BLAST+: architecture and applications Camacho, Christiam; Coulouris, George; Avagyan, Vahram BMC Bioinformatics, Vol. 10, Issue 1 https://doi.org/10.1186/1471-2105-10-421	journal	January 2009
Long noncoding RNA transcriptome of plants Liu, Jun; Wang, Huan; Chua, Nam-Hai Plant Biotechnology Journal, Vol. 13, Issue 3 https://doi.org/10.1111/pbi.12336	journal	January 2015
Strawberry: Fast and accurate genome-guided transcript reconstruction and quantification from RNA-Seq Liu, Ruolin; Dickerson, Julie PLOS Computational Biology, Vol. 13, Issue 11 https://doi.org/10.1371/journal.pcbi.1005851	journal	November 2017
Genome-wide analyses of alternative splicing in plants: Opportunities and challenges Barbazuk, W. B.; Fu, Y.; McGinnis, K. M. Genome Research, Vol. 18, Issue 9 https://doi.org/10.1101/gr.053678.106	journal	July 2008
A window into third-generation sequencing Schadt, E. E.; Turner, S.; Kasarskis, A. Human Molecular Genetics, Vol. 19, Issue R2 https://doi.org/10.1093/hmg/ddq416	journal	September 2010
Analyses of Long Non-Coding RNA and mRNA profiling using RNA sequencing during the pre-implantation phases in pig endometrium Wang, Yueying; Xue, Songyi; Liu, Xiaoran Scientific Reports, Vol. 6, Issue 1 https://doi.org/10.1038/srep20238	journal	January 2016
Detecting alternatively spliced transcript isoforms from single-molecule long-read sequences without a reference genome Liu, Xiaoxian; Mei, Wenbin; Soltis, Pamela S. Molecular Ecology Resources, Vol. 17, Issue 6 https://doi.org/10.1111/1755-0998.12670	journal	June 2017
GREENC: a Wiki-based database of plant lncRNAs Paytuví Gallart, Andreu; Hermoso Pulido, Antonio; Anzar Martínez de Lagrán, Irantzu Nucleic Acids Research, Vol. 44, Issue D1 https://doi.org/10.1093/nar/gkv1215	journal	November 2015
StringTie enables improved reconstruction of a transcriptome from RNA-seq reads Pertea, Mihaela; Pertea, Geo M.; Antonescu, Corina M. Nature Biotechnology, Vol. 33, Issue 3 https://doi.org/10.1038/nbt.3122	journal	February 2015
Next-generation DNA sequencing Shendure, Jay; Ji, Hanlee Nature Biotechnology, Vol. 26, Issue 10 https://doi.org/10.1038/nbt1486	journal	October 2008
GMAP: a genomic mapping and alignment program for mRNA and EST sequences Wu, T. D.; Watanabe, C. K. Bioinformatics, Vol. 21, Issue 9 https://doi.org/10.1093/bioinformatics/bti310	journal	February 2005
Chimeras taking shape: Potential functions of proteins encoded by chimeric RNA transcripts Frenkel-Morgenstern, M.; Lacroix, V.; Ezkurdia, I. Genome Research, Vol. 22, Issue 7 https://doi.org/10.1101/gr.130062.111	journal	May 2012
Improving the Arabidopsis genome annotation using maximal transcript alignment assemblies Haas, B. J. Nucleic Acids Research, Vol. 31, Issue 19 https://doi.org/10.1093/nar/gkg770	journal	October 2003
CPC: assess the protein-coding potential of transcripts using sequence features and support vector machine Kong, Lei; Zhang, Yong; Ye, Zhi-Qiang Nucleic Acids Research, Vol. 35, Issue suppl_2 https://doi.org/10.1093/nar/gkm391	journal	July 2007
Genome-wide screening and functional analysis identify a large number of long noncoding RNAs involved in the sexual reproduction of rice Zhang, Yu-Chan; Liao, Jian-You; Li, Ze-Yuan Genome Biology, Vol. 15, Issue 12 https://doi.org/10.1186/s13059-014-0512-1	journal	December 2014
A single-molecule long-read survey of the human transcriptome Sharon, Donald; Tilgner, Hagen; Grubert, Fabian Nature Biotechnology, Vol. 31, Issue 11 https://doi.org/10.1038/nbt.2705	journal	October 2013
Protein networks identify novel symbiogenetic genes resulting from plastid endosymbiosis Méheust, Raphaël; Zelzion, Ehud; Bhattacharya, Debashish Proceedings of the National Academy of Sciences, Vol. 113, Issue 13 https://doi.org/10.1073/pnas.1517551113	journal	March 2016
Characterization of the human ESC transcriptome by hybrid sequencing Au, K. F.; Sebastiano, V.; Afshar, P. T. Proceedings of the National Academy of Sciences, Vol. 110, Issue 50 https://doi.org/10.1073/pnas.1320101110	journal	November 2013
Tying the knot: occurrence and possible significance of gene fusions in plant metabolism and beyond Hagel, Jillian M.; Facchini, Peter J. Journal of Experimental Botany, Vol. 68, Issue 15 https://doi.org/10.1093/jxb/erx152	journal	May 2017
A window into third generation sequencing Schadt, E. E.; Turner, S.; Kasarskis, A. Human Molecular Genetics, Vol. 20, Issue 4 https://doi.org/10.1093/hmg/ddq481	journal	December 2010
Coriander Genomics Database: a genomic, transcriptomic, and metabolic database for coriander Song, Xiaoming; Nie, Fulei; Chen, Wei Horticulture Research, Vol. 7, Issue 1 https://doi.org/10.1038/s41438-020-0261-0	journal	April 2020
Androgen receptor and its splice variant, AR-V7, differentially induce mRNA splicing in prostate cancer cells Rana, Manjul; Dong, Jianrong; Robertson, Matthew J. Scientific Reports, Vol. 11, Issue 1 https://doi.org/10.1038/s41598-021-81164-0	journal	January 2021
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
Assessment of transcript reconstruction methods for RNA-seq Steijger, T.; Abril, Jf; Engström, Pg Nature Publishing Group https://doi.org/10.17863/cam.33359	journalarticle	January 2018
An Introduction to Sequence Similarity (“Homology”) Searching Stormo, Gary D. Current Protocols in Bioinformatics, Vol. 27, Issue 1 https://doi.org/10.1002/0471250953.bi0301s27	journal	September 2009
Widespread Polycistronic Transcripts In Fungi Revealed By Single-Molecule Mrna Sequencing Gordon, Sean; Tseng, Elizabeth; Salamov, Asaf Zenodo https://doi.org/10.5281/zenodo.165839	dataset	January 2016
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
A Survey Of The Sorghum Transcriptome Using Single-Molecule Long Reads Abdel-Ghany, Salah; Hamilton, Michael; Jacobi, Jennifer Zenodo https://doi.org/10.5281/zenodo.49944	dataset	January 2016

Cited By (2)

PacBio single molecule long-read sequencing provides insight into the complexity and diversity of the Pinctada fucata martensii transcriptome Zhang, Hua; Xu, Hanzhi; Liu, Huiru BMC Genomics, Vol. 21, Issue 1 https://doi.org/10.1186/s12864-020-06894-3	journal	July 2020
Transcriptome Profiling Provides Insight into the Genes in Carotenoid Biosynthesis during the Mesocarp and Seed Developmental Stages of Avocado (Persea americana) Ge, Yu; Cheng, Zhihao; Si, Xiongyuan International Journal of Molecular Sciences, Vol. 20, Issue 17 https://doi.org/10.3390/ijms20174117	journal	August 2019

Linked Research (24)

Figures / Tables (7)

Similar Records

Analysis of Transcriptome and Epitranscriptome in Plants Using PacBio Iso-Seq and Nanopore-Based Direct RNA Sequencing

Journal Article · Thu Mar 21 00:00:00 EDT 2019 · Frontiers in Genetics · OSTI ID:1477307

Zhao, Liangzhen; Zhang, Hangxiao; Kohnen, Markus V.; +3 more

Decoding co-/post-transcriptional complexities of plant transcriptomes and epitranscriptome using next-generation sequencing technologies

Journal Article · Mon Nov 16 00:00:00 EST 2020 · Biochemical Society Transactions · OSTI ID:1477307

Reddy, Anireddy S. N.; Huang, Jie; Syed, Naeem H.; +3 more

A survey of the sorghum transcriptome using single-molecule long reads

Journal Article · Fri Jun 24 00:00:00 EDT 2016 · Nature Communications · OSTI ID:1477307

Abdel-Ghany, Salah E.; Hamilton, Michael; Jacobi, Jennifer L.; +5 more

Related Subjects

09 BIOMASS FUELS
Switchgrass
PacBio sequencing
Transcriptomic analysis
Alternative splicing
Plant cell wall

MOESM10 of Revealing the transcriptomic complexity of switchgrass by PacBio long-read sequencing Blow, Matthew; Sreedasyam, Avinash; Kuo, Rita https://doi.org/10.6084/m9.figshare.6627329 The current record is supplemented by this figure	figure	June 2018
MOESM11 of Revealing the transcriptomic complexity of switchgrass by PacBio long-read sequencing Blow, Matthew; Sreedasyam, Avinash; Kuo, Rita https://doi.org/10.6084/m9.figshare.6627353 The current record is supplemented by this figure	figure	June 2018
MOESM1 of Revealing the transcriptomic complexity of switchgrass by PacBio long-read sequencing Blow, Matthew; Sreedasyam, Avinash; Kuo, Rita https://doi.org/10.6084/m9.figshare.6627365 The current record is supplemented by this dataset	dataset	June 2018
MOESM1 of Revealing the transcriptomic complexity of switchgrass by PacBio long-read sequencing Blow, Matthew; Sreedasyam, Avinash; Kuo, Rita https://doi.org/10.6084/m9.figshare.6627365.v1 The current record is supplemented by this dataset	dataset	June 2018
MOESM2 of Revealing the transcriptomic complexity of switchgrass by PacBio long-read sequencing Blow, Matthew; Sreedasyam, Avinash; Kuo, Rita https://doi.org/10.6084/M9.FIGSHARE.6627380 The current record is supplemented by this dataset	dataset	June 2018
MOESM2 of Revealing the transcriptomic complexity of switchgrass by PacBio long-read sequencing Blow, Matthew; Sreedasyam, Avinash; Kuo, Rita https://doi.org/10.6084/m9.figshare.6627380.v1 The current record is supplemented by this dataset	dataset	June 2018
MOESM3 of Revealing the transcriptomic complexity of switchgrass by PacBio long-read sequencing Blow, Matthew; Sreedasyam, Avinash; Kuo, Rita https://doi.org/10.6084/M9.FIGSHARE.6627398 The current record is supplemented by this dataset	dataset	June 2018
MOESM3 of Revealing the transcriptomic complexity of switchgrass by PacBio long-read sequencing Blow, Matthew; Sreedasyam, Avinash; Kuo, Rita https://doi.org/10.6084/m9.figshare.6627398.v1 The current record is supplemented by this dataset	dataset	June 2018
MOESM4 of Revealing the transcriptomic complexity of switchgrass by PacBio long-read sequencing Blow, Matthew; Sreedasyam, Avinash; Kuo, Rita https://doi.org/10.6084/M9.FIGSHARE.6627422 The current record is supplemented by this dataset	dataset	June 2018
MOESM4 of Revealing the transcriptomic complexity of switchgrass by PacBio long-read sequencing Blow, Matthew; Sreedasyam, Avinash; Kuo, Rita https://doi.org/10.6084/m9.figshare.6627422.v1 The current record is supplemented by this dataset	dataset	June 2018
MOESM5 of Revealing the transcriptomic complexity of switchgrass by PacBio long-read sequencing Blow, Matthew; Sreedasyam, Avinash; Kuo, Rita https://doi.org/10.6084/m9.figshare.6627443 The current record is supplemented by this dataset	dataset	June 2018
MOESM5 of Revealing the transcriptomic complexity of switchgrass by PacBio long-read sequencing Blow, Matthew; Sreedasyam, Avinash; Kuo, Rita https://doi.org/10.6084/m9.figshare.6627443.v1 The current record is supplemented by this dataset	dataset	June 2018
MOESM6 of Revealing the transcriptomic complexity of switchgrass by PacBio long-read sequencing Blow, Matthew; Sreedasyam, Avinash; Kuo, Rita https://doi.org/10.6084/m9.figshare.6627461 The current record is supplemented by this dataset	dataset	June 2018
MOESM6 of Revealing the transcriptomic complexity of switchgrass by PacBio long-read sequencing Blow, Matthew; Sreedasyam, Avinash; Kuo, Rita https://doi.org/10.6084/m9.figshare.6627461.v1 The current record is supplemented by this dataset	dataset	June 2018
MOESM7 of Revealing the transcriptomic complexity of switchgrass by PacBio long-read sequencing Blow, Matthew; Sreedasyam, Avinash; Kuo, Rita https://doi.org/10.6084/m9.figshare.6627479 The current record is supplemented by this dataset	dataset	June 2018
MOESM7 of Revealing the transcriptomic complexity of switchgrass by PacBio long-read sequencing Blow, Matthew; Sreedasyam, Avinash; Kuo, Rita https://doi.org/10.6084/m9.figshare.6627479.v1 The current record is supplemented by this dataset	dataset	June 2018
MOESM8 of Revealing the transcriptomic complexity of switchgrass by PacBio long-read sequencing Blow, Matthew; Sreedasyam, Avinash; Kuo, Rita https://doi.org/10.6084/m9.figshare.6627506 The current record is supplemented by this dataset	dataset	June 2018
MOESM8 of Revealing the transcriptomic complexity of switchgrass by PacBio long-read sequencing Blow, Matthew; Sreedasyam, Avinash; Kuo, Rita https://doi.org/10.6084/m9.figshare.6627506.v1 The current record is supplemented by this dataset	dataset	June 2018
MOESM9 of Revealing the transcriptomic complexity of switchgrass by PacBio long-read sequencing Blow, Matthew; Sreedasyam, Avinash; Kuo, Rita https://doi.org/10.6084/m9.figshare.6627530 The current record is supplemented by this dataset	dataset	June 2018
MOESM9 of Revealing the transcriptomic complexity of switchgrass by PacBio long-read sequencing Blow, Matthew; Sreedasyam, Avinash; Kuo, Rita https://doi.org/10.6084/m9.figshare.6627530.v1 The current record is supplemented by this dataset	dataset	June 2018
Revealing the transcriptomic complexity of switchgrass by PacBio long-read sequencing [Supplemental Data] Blow, Matthew; Sreedasyam, Avinash; Kuo, Rita https://doi.org/10.6084/m9.figshare.c.4140089 The current record is supplemented by this collection	collection	June 2018
Revealing the transcriptomic complexity of switchgrass by PacBio long-read sequencing [Supplemental Data] Blow, Matthew; Sreedasyam, Avinash; Kuo, Rita https://doi.org/10.6084/m9.figshare.c.4140089.v1 The current record is supplemented by this collection	collection	June 2018
MOESM10 of Revealing the transcriptomic complexity of switchgrass by PacBio long-read sequencing Blow, Matthew; Sreedasyam, Avinash; Kuo, Rita https://doi.org/10.6084/m9.figshare.6627329.v1 The current record is supplemented by this figure	figure	June 2018
MOESM11 of Revealing the transcriptomic complexity of switchgrass by PacBio long-read sequencing Blow, Matthew; Sreedasyam, Avinash; Kuo, Rita https://doi.org/10.6084/m9.figshare.6627353.v1 The current record is supplemented by this figure	figure	June 2018