Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

  • Article
  • Published:

Alternative expression analysis by RNA sequencing

Nature Methods volume 7, pages 843–847 (2010)Cite this article

Subjects

Abstract

In alternative expression analysis by sequencing (ALEXA-seq), we developed a method to analyze massively parallel RNA sequence data to catalog transcripts and assess differential and alternative expression of known and predicted mRNA isoforms in cells and tissues. As proof of principle, we used the approach to compare fluorouracil-resistant and -nonresistant human colorectal cancer cell lines. We assessed the sensitivity and specificity of the approach by comparison to exon tiling and splicing microarrays and validated the results with reverse transcription–PCR, quantitative PCR and Sanger sequencing. We observed global disruption of splicing in fluorouracil-resistant cells characterized by expression of new mRNA isoforms resulting from exon skipping, alternative splice site usage and intron retention. Alternative expression annotation databases, source code, a data viewer and other resources to facilitate analysis are available at http://www.alexaplatform.org/alexa_seq/.

This is a preview of subscription content, access via your institution

Access options

Buy this article

  • Purchase on Springer Link
  • Instant access to full article PDF
Buy now

Prices may be subject to local taxes which are calculated during checkout

Figure 1: Overview of ALEXA-seq analysis.
Figure 2: Quantitative RT-PCR validation of 192 alternatively expressed exons.
Figure 3: Alternative expression in 5-FU–sensitive versus 5-FU–resistant cells.

Similar content being viewed by others

Accession codes

Accessions

Gene Expression Omnibus

References

  1. Griffith, M. & Marra, M.A. Alternative expression analysis: experimental and bioinformatic approaches for the analysis of transcript diversity. in Genes, Genomes & Genomics. (eds., Thangadurai, D., Tang, W. & Pullaiah, T.) 201–242 (Regency Publications, New Delhi, 2007).

  2. Griffith, M. et al. ALEXA: a microarray design platform for alternative expression analysis. Nat. Methods 5, 118 (2008).

    Article  CAS  Google Scholar 

  3. Johnson, J.M. et al. Genome-wide survey of human alternative pre-mRNA splicing with exon junction microarrays. Science 302, 2141–2144 (2003).

    Article  CAS  Google Scholar 

  4. Pan, Q. et al. Revealing global regulatory features of Mammalian alternative splicing using a quantitative microarray platform. Mol. Cell 16, 929–941 (2004).

    Article  CAS  Google Scholar 

  5. Mortazavi, A., Williams, B.A., McCue, K., Schaeffer, L. & Wold, B. Mapping and quantifying mammalian transcriptomes by RNA-seq. Nat. Methods 5, 621–628 (2008).

    Article  CAS  Google Scholar 

  6. Morin, R. et al. Profiling the HeLa S3 transcriptome using randomly primed cDNA and massively parallel short-read sequencing. Biotechniques 45, 81–94 (2008).

    Article  CAS  Google Scholar 

  7. Yassour, M. et al. Ab initio construction of a eukaryotic transcriptome by massively parallel mRNA sequencing. Proc. Natl. Acad. Sci. USA 106, 3264–3269 (2009).

    Article  CAS  Google Scholar 

  8. Jiang, H. & Wong, W.H. Statistical inferences for isoform expression in RNA-seq. Bioinformatics 25, 1026–1032 (2009).

    Article  CAS  Google Scholar 

  9. Tang, F. et al. mRNA-seq whole-transcriptome analysis of a single cell. Nat. Methods 6, 377–382 (2009).

    Article  CAS  Google Scholar 

  10. Cloonan, N. et al. Stem cell transcriptome profiling via massive-scale mRNA sequencing. Nat. Methods 5, 613–619 (2008).

    Article  CAS  Google Scholar 

  11. Li, H. et al. Determination of tag density required for digital transcriptome analysis: application to an androgen-sensitive prostate cancer model. Proc. Natl. Acad. Sci. USA 105, 20179–20184 (2008).

    Article  CAS  Google Scholar 

  12. Sultan, M. et al. A global view of gene activity and alternative splicing by deep sequencing of the human transcriptome. Science 321, 956–960 (2008).

    Article  CAS  Google Scholar 

  13. Pan, Q., Shai, O., Lee, L.J., Frey, B.J. & Blencowe, B.J. Deep surveying of alternative splicing complexity in the human transcriptome by high-throughput sequencing. Nat. Genet. 40, 1413–1415 (2008).

    Article  CAS  Google Scholar 

  14. Wang, E.T. et al. Alternative isoform regulation in human tissue transcriptomes. Nature 456, 470–476 (2008).

    Article  CAS  Google Scholar 

  15. Trapnell, C., Pachter, L. & Salzberg, S.L. TopHat: discovering splice junctions with RNA-seq. Bioinformatics 25, 1105–1111 (2009).

    Article  CAS  Google Scholar 

  16. Wang, L. et al. A statistical method for the detection of alternative splicing using RNA-seq. PLoS ONE 5, e8529 (2010).

    Article  Google Scholar 

  17. Denoeud, F. et al. Annotating genomes with massive-scale RNA sequencing. Genome Biol. 9, R175 (2008).

    Article  Google Scholar 

  18. Ameur, A., Wetterbom, A., Feuk, L. & Gyllensten, U. Global and unbiased detection of splice junctions from RNA-seq data. Genome Biol. 11, R34 (2010).

    Article  Google Scholar 

  19. Au, K.F., Jiang, H., Lin, L., Xing, Y. & Wong, W.H. Detection of splice junctions from paired-end RNA-seq data by SpliceMap. Nucleic Acids Res. 38, 4570–4578 (2010).

    Article  CAS  Google Scholar 

  20. Wu, T.D. & Nacu, S. Fast and SNP-tolerant detection of complex variants and splicing in short reads. Bioinformatics 26, 873–881 (2010).

    Article  CAS  Google Scholar 

  21. Guttman, M. et al. Ab initio reconstruction of cell type-specific transcriptomes in mouse reveals the conserved multi-exonic structure of lincRNAs. Nat. Biotechnol. 28, 503–510 (2010).

    Article  CAS  Google Scholar 

  22. Trapnell, C. et al. Transcript assembly and quantification by RNA-seq reveals unannotated transcripts and isoform switching during cell differentiation. Nat. Biotechnol. 28, 511–515 (2010).

    Article  CAS  Google Scholar 

  23. Niles, R.M. et al. Isolation and characterization of an undifferentiated human colon carcinoma cell line (MIP-101). Cancer Invest. 5, 545–552 (1987).

    Article  CAS  Google Scholar 

  24. Tai, I.T., Dai, M., Owen, D.A. & Chen, L.B. Genome-wide expression analysis of therapy-resistant tumors reveals SPARC as a novel target for cancer therapy. J. Clin. Invest. 115, 1492–1502 (2005).

    Article  CAS  Google Scholar 

  25. Jurka, J. et al. Repbase update, a database of eukaryotic repetitive elements. Cytogenet. Genome Res. 110, 462–467 (2005).

    Article  CAS  Google Scholar 

  26. Venables, J.P. et al. Cancer-associated regulation of alternative splicing. Nat. Struct. Mol. Biol. 16, 670–676 (2009).

    Article  CAS  Google Scholar 

  27. Birol, I. et al. De novo transcriptome assembly with ABySS. Bioinformatics 25, 2872–2877 (2009).

    Article  CAS  Google Scholar 

  28. Klinck, R. et al. Multiple alternative splicing markers for ovarian cancer. Cancer Res. 68, 657–663 (2008).

    Article  CAS  Google Scholar 

  29. Venables, J.P. et al. Identification of alternative splicing markers for breast cancer. Cancer Res. 68, 9525–9531 (2008).

    Article  CAS  Google Scholar 

  30. Hancock, J.M. & Armstrong, J.S. SIMPLE34: an improved and enhanced implementation for VAX and Sun computers of the SIMPLE algorithm for analysis of clustered repetitive motifs in nucleotide sequences. Comput. Appl. Biosci. 10, 67–70 (1994).

    CAS  PubMed  Google Scholar 

  31. Hubbard, T.J. et al. Ensembl 2009. Nucleic Acids Res. 37, D690–D697 (2009).

    Article  CAS  Google Scholar 

  32. Gentleman, R.C. et al. Bioconductor: open software development for computational biology and bioinformatics. Genome Biol. 5, R80 (2004).

    Article  Google Scholar 

  33. Benjamini, Y. & Hochberg, Y. Controlling the false discovery rate: a practical and powerful approach to multiple testing. J. R. Stat. Soc. Ser. A Stat. Soc. 57, 289–300 (1995).

    Google Scholar 

Download references

Acknowledgements

We are grateful for funding provided by the University of British Columbia, the Michael Smith Foundation for Health Research, the Natural Sciences and Engineering Research Council, Genome British Columbia, the Terry Fox Foundation, the Canadian Institutes of Health Research, the National Cancer Institute of Canada and the British Columbia Cancer Foundation.

Author information

Authors and Affiliations

  1. Genome Sciences Centre, British Columbia Cancer Agency, Vancouver, Canada

    Malachi Griffith, Obi L Griffith, Jill Mwenifumbo, Rodrigo Goya, A Sorana Morrissy, Ryan D Morin, Richard Corbett, Michelle J Tang, Ying-Chen Hou, Trevor J Pugh, Gordon Robertson, Suganthi Chittaranjan, Adrian Ally, Jennifer K Asano, Susanna Y Chan, Haiyan I Li, Helen McDonald, Kevin Teague, Yongjun Zhao, Thomas Zeng, Allen Delaney, Martin Hirst, Gregg B Morin, Steven J M Jones, Isabella T Tai & Marco A Marra

  2. Department of Medical Genetics, University of British Columbia, Vancouver, Canada

    Malachi Griffith, Obi L Griffith, A Sorana Morrissy, Trevor J Pugh, Gregg B Morin, Steven J M Jones & Marco A Marra

  3. Department of Medicine, University of British Columbia, Vancouver, Canada

    Isabella T Tai

Authors
  1. Malachi Griffith
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Obi L Griffith
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Jill Mwenifumbo
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Rodrigo Goya
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. A Sorana Morrissy
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Ryan D Morin
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Richard Corbett
    View author publications

    You can also search for this author in PubMed Google Scholar

  8. Michelle J Tang
    View author publications

    You can also search for this author in PubMed Google Scholar

  9. Ying-Chen Hou
    View author publications

    You can also search for this author in PubMed Google Scholar

  10. Trevor J Pugh
    View author publications

    You can also search for this author in PubMed Google Scholar

  11. Gordon Robertson
    View author publications

    You can also search for this author in PubMed Google Scholar

  12. Suganthi Chittaranjan
    View author publications

    You can also search for this author in PubMed Google Scholar

  13. Adrian Ally
    View author publications

    You can also search for this author in PubMed Google Scholar

  14. Jennifer K Asano
    View author publications

    You can also search for this author in PubMed Google Scholar

  15. Susanna Y Chan
    View author publications

    You can also search for this author in PubMed Google Scholar

  16. Haiyan I Li
    View author publications

    You can also search for this author in PubMed Google Scholar

  17. Helen McDonald
    View author publications

    You can also search for this author in PubMed Google Scholar

  18. Kevin Teague
    View author publications

    You can also search for this author in PubMed Google Scholar

  19. Yongjun Zhao
    View author publications

    You can also search for this author in PubMed Google Scholar

  20. Thomas Zeng
    View author publications

    You can also search for this author in PubMed Google Scholar

  21. Allen Delaney
    View author publications

    You can also search for this author in PubMed Google Scholar

  22. Martin Hirst
    View author publications

    You can also search for this author in PubMed Google Scholar

  23. Gregg B Morin
    View author publications

    You can also search for this author in PubMed Google Scholar

  24. Steven J M Jones
    View author publications

    You can also search for this author in PubMed Google Scholar

  25. Isabella T Tai
    View author publications

    You can also search for this author in PubMed Google Scholar

  26. Marco A Marra
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

M.G. and M.A.M. wrote the manuscript. M.G. conducted the analysis, created the figures and participated in all experimental design, laboratory work, programming, and database and website design. O.L.G., R.G., G.R. and R.D.M. contributed to analysis concepts and assisted with programming and code testing. A.S.M., R.G and R.C. assisted with comparisons to other alternative expression tools. M.J.T. provided cell lines and assisted with tissue culture. T.J.P. and Y.-C.H. contributed to laboratory experiments. H.I.L. and A.D. performed the mitochondrial cross species contamination and other quality control analyses. K.T. assisted in the implementation of website hosting and indexing. S.Y.C., J.K.A. and A.A. performed microarray hybridizations and scanning. Y.Z., H.M., T.Z. and M.H. performed Illumina library construction and sequencing. S.C. and J.M. assisted with experimental validations. S.J.M.J. and G.B.M. contributed concepts and experimental designs. I.T.T. provided cell lines and contributed concepts and experimental designs. M.A.M. supported the project and contributed concepts and experimental designs.

Corresponding author

Correspondence to Marco A Marra.

Ethics declarations

Competing interests

The authors declare no competing financial interests.

Supplementary information

Supplementary Text and Figures

Supplementary Figures 1–11, Supplementary Tables 1–8, Supplementary Results, Supplementary Methods, Supplementary Equations 1–5 (PDF 13812 kb)

Rights and permissions

Reprints and permissions

About this article

Cite this article

Griffith, M., Griffith, O., Mwenifumbo, J. et al. Alternative expression analysis by RNA sequencing. Nat Methods 7, 843–847 (2010). https://doi.org/10.1038/nmeth.1503

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1038/nmeth.1503

This article is cited by

Search

Advanced search

Quick links

Nature Briefing

Sign up for the Nature Briefing newsletter — what matters in science, free to your inbox daily.

Get the most important science stories of the day, free in your inbox. Sign up for Nature Briefing