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QuickIsoSeq for Isoform Quantification in Large-Scale RNA Sequencing

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RNA Bioinformatics

Part of the book series: Methods in Molecular Biology ((MIMB,volume 2284))

Abstract

RNA-sequencing (RNA-seq) is a powerful technology for transcriptome profiling. While most RNA-seq projects focus on gene-level quantification and analysis, there is growing evidence that most mammalian genes are alternatively spliced to generate different isoforms that can be subsequently translated to protein molecules with diverse or even opposing biological functions. Quantifying the expression levels of these isoforms is key to understanding the genes biological functions in healthy tissues and the progression of diseases. Among open source tools developed for isoform quantification, Salmon, Kallisto, and RSEM are recommended based upon previous systematic evaluation of these tools using both experimental and simulated RNA-seq datasets. However, isoform quantification in practical RNA-seq data analysis needs to deal with many QC issues, such as the abundance of rRNAs in mRNA-seq, the efficiency of globin RNA depletion in whole blood samples, and potential sample swapping. To overcome these practical challenges, QuickIsoSeq was developed for large-scale RNA-seq isoform quantification along with QC. In this chapter, we describe the pipeline and detailed the steps required to deploy and use it to analyze RNA-seq datasets in practice. The QuickIsoSeq package can be downloaded from https://github.com/shanrongzhao/QuickIsoSeq.

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Change history

  • 03 August 2021

    In the original version of this book, chapter 8 was published with incomplete list of authors. This has now been rectified in this revised version of the book.

References

  1. Mortazavi A et al (2008) Mapping and quantifying mammalian transcriptomes by RNA-Seq. Nat Methods 5(7):621–628

    Article  CAS  Google Scholar 

  2. Stark R, Grzelak M, Hadfield J (2019) RNA sequencing: the teenage years. Nat Rev Genet 20(11):631–656

    Article  CAS  Google Scholar 

  3. Wang ET et al (2008) Alternative isoform regulation in human tissue transcriptomes. Nature 456:470–476

    Article  CAS  Google Scholar 

  4. Harrow J et al (2012) GENCODE: the reference human genome annotation for the ENCODE project. Genome Res 22:1760–1774

    Article  CAS  Google Scholar 

  5. Aoubala M et al (2011) p53 directly transactivates Delta133p53alpha, regulating cell fate outcome in response to DNA damage. Cell Death Differ 18:248–258

    Article  CAS  Google Scholar 

  6. Kim S, An SS (2016) Role of p53 isoforms and aggregations in cancer. Medicine (Baltimore) 95:e3993

    Article  CAS  Google Scholar 

  7. Mondal AM et al (2013) p53 isoforms regulate aging- and tumor-associated replicative senescence in T lymphocytes. J Clin Invest 123:5247–5257

    Article  CAS  Google Scholar 

  8. He W et al (2018) QuickRNASeq: guide for pipeline implementation and for interactive results visualization. Methods Mol Biol 1751:57–70

    Article  CAS  Google Scholar 

  9. Zhao S et al (2016) QuickRNASeq lifts large-scale RNA-seq data analyses to the next level of automation and interactive visualization. BMC Genomics 17:39

    Article  CAS  Google Scholar 

  10. Liao Y, Smyth GK, Shi W (2014) featureCounts: an efficient general purpose program for assigning sequence reads to genomic features. Bioinformatics 30:923–930

    Article  CAS  Google Scholar 

  11. Zhang C et al (2018) Computational identification and validation of alternative splicing in ZSF1 rat RNA-seq data, a preclinical model for type 2 diabetic nephropathy. Sci Rep 8(1):7624

    Article  Google Scholar 

  12. Zhao S, Xi L, Zhang B (2015) Union exon based approach for RNA-Seq gene quantification: to be or not to be? PLoS One 10(11):e0141910

    Article  Google Scholar 

  13. Zhang C et al (2017) Evaluation and comparison of computational tools for RNA-seq isoform quantification. BMC Genomics 18(1):583

    Article  Google Scholar 

  14. Zhang C et al (2016) Bioinformatics tools for RNA-seq gene and Isoform quantification. Next Gen Sequence Appl 3:3

    Google Scholar 

  15. Li B, Dewey CN (2011) RSEM: accurate transcript quantification from RNA-Seq data with or without a reference genome. BMC Bioinformatics 12:323

    Article  CAS  Google Scholar 

  16. Roberts A, Pachter L (2013) Streaming fragment assignment for real-time analysis of sequencing experiments. Nat Methods 10:71–73

    Article  CAS  Google Scholar 

  17. Nariai N et al (2014) TIGAR2: sensitive and accurate estimation of transcript isoform expression with longer RNA-Seq reads. BMC Genomics 15:S5

    Article  Google Scholar 

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

    Article  CAS  Google Scholar 

  19. Patro R, Mount SM, Kingsford C (2014) Sailfish enables alignment-free isoform quantification from RNA-seq reads using lightweight algorithms. Nat Biotechnol 32:462–464

    Article  CAS  Google Scholar 

  20. Patro R et al (2017) Salmon provides fast and bias-aware quantification of transcript expression. Nat Methods 14:417–419

    Article  CAS  Google Scholar 

  21. Bray NL et al (2016) Near-optimal probabilistic RNA-seq quantification. Nat Biotechnol 34:525–527

    Article  CAS  Google Scholar 

  22. Carithers LJ, Moore HM (2015) The Genotype-Tissue Expression (GTEx) Project. Biopreserv Biobank 13(5):307–308

    Article  Google Scholar 

Download references

Acknowledgments

The authors would like to thank Robert Stanton for his critical reading of the draft manuscript.

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Correspondence to Shanrong Zhao .

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Gamini, R. et al. (2021). QuickIsoSeq for Isoform Quantification in Large-Scale RNA Sequencing. In: Picardi, E. (eds) RNA Bioinformatics. Methods in Molecular Biology, vol 2284. Humana, New York, NY. https://doi.org/10.1007/978-1-0716-1307-8_8

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  • DOI: https://doi.org/10.1007/978-1-0716-1307-8_8

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  • Publisher Name: Humana, New York, NY

  • Print ISBN: 978-1-0716-1306-1

  • Online ISBN: 978-1-0716-1307-8

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