1. Utilizing the Illumina deep sequencing technique to define
the plant transcriptome
Pinghua Li
Institute of Tropical Biosciences & Biotechnology (ITBB)
Chinese Academy of Tropical Agriculture Sciences (CATAS)
GCP21-II, Kampala, Uganda
June 19, 2012

2. Acknowledgments Brutnell Lab (Danforth)
Xiang Lab (Weill Cornell Medical College)
Jenny Xiang
Diana Shao
Wang Lab (ITBB, CATAS)
Wenquan Wang
Zhiqiang Xia
Xin Chen
Kun Pan
Yang Zhang
Giovannoni Lab (Cornell)
Jim Giovannoni
Silin Zhong
Wang Lab (CAS)
Ying Wang
Gong Xiao
Brutnell Lab (Danforth)
Tom Brutnell
Lin Wang
Tesfamichael Kebrom
Nelson Lab (Yale University)
Tim Nelson (Yale)
Neeru Gandotra
Lori Tausta
Turgeon Lab (Cornell University)
Bob Turgeon
Edwin Reidel
Sun Lab (Cornell University)
Qi Sun
Lalit Ponnala
Liu Lab (Iowa State University)
Peng Liu
Yaqing Si

3. High throughput sequencing – a new paradigm
Illumina (Solexa)
SOLiD
454/Roche Genome Sequencer
Single Molecule Sequencing/Pacific Biosciences
Applications
Genome sequencing
microRNA screening
Gene expression (RNA-seq)
ChIP-seq
RNA-seq profiles vs. microarray
• Less dependent on gene annotation
• Resolves closely related members of a gene family
• Identifies alternative splicing patterns
• Capture low abundant expression

4. Outline
RNA-seq library construction
What to expect from RNA-seq (an example from Maize leaf transcriptome)
Application in wild type vs. cultivar comparison of Cassava

5. What is your purpose? Consider the RNA input
RNA-seq library construction
What is your purpose?
mRNA profile? Nocoding RNA? Small RNA? Chloroplast genes?
Consider the RNA input
Lin Wang

6. RNA-seq library construction
Wang et al. PLoS One. 2011

7. RNA-seq library construction
UDG Uracil DNA Glycosylase
Barcode
Wang et al. PLoS One. 2011

8. PCR amplification with Bar-coded primers
RNA-seq library construction
PCR amplification with Bar-coded primers
Pool libraries
Illumina Hiseq 2000
Sequence how deep?
(Tomato)
ZhangJun Fei, Cornell

9. Aconitase RNA-seq application From maize leaf transcriptome
Genome annotation correction
Differential expressed genes discovery (Biological stories)
Aconitase
Exon skipping

10. RNA-seq application-- Gene annotation correction
Wang et al. PLoS One. 2011

11. RNA-seq application-Differential expressed (DE)gene-biological stories
RNA-seq raw read
Align to the reference genome
Quantitative gene expression
Determine the DE gene
Clustering and pathway analysis
Biological stories-paper writing
Base -1cm +4cm Tip
Li et al, Nature Genetics, 2010

12. RNA-seq application-Cassava transcriptome
Lines: Arg 7 vs. W14
Tissue: Roots, leaves and stems
Platform: Illumina Hiseq 2000
KU50 & Arg7 (cultivar) vs. W14 (wild type)
Starch biosynthesis
Root
1480
390
345
378
Leaf
2234
Stem
2381
1545
DE genes in root, leaf and stem
Leaf
Root

13. Thank you for your attention!

14. Maize leaf developmental gradient for 9 day Leaf 3
RNA-seq application
Leaf 1
Maize leaf developmental gradient for 9 day Leaf 3
Base cm cm Tip
Source
Sink
Transition
Base cm cm Tip
Li et al, Nature Genetics, 2010