Author
Listed:
- Gloria M. Sheynkman
(Dana-Farber Cancer Institute
Blavatnik Institute, Harvard Medical School
Dana-Farber Cancer Institute)
- Katharine S. Tuttle
(Dana-Farber Cancer Institute
Blavatnik Institute, Harvard Medical School
Dana-Farber Cancer Institute
Northeastern University)
- Florent Laval
(Dana-Farber Cancer Institute
Blavatnik Institute, Harvard Medical School
Dana-Farber Cancer Institute
University of Liège)
- Elizabeth Tseng
(Pacific Biosciences)
- Jason G. Underwood
(Pacific Biosciences)
- Liang Yu
(Xidian University)
- Da Dong
(Xidian University)
- Melissa L. Smith
(Icahn School of Medicine at Mount Sinai
Icahn Institute of Data Science and Genomic Technology)
- Robert Sebra
(Icahn School of Medicine at Mount Sinai
Icahn Institute of Data Science and Genomic Technology)
- Luc Willems
(University of Liège
University of Liège)
- Tong Hao
(Dana-Farber Cancer Institute
Blavatnik Institute, Harvard Medical School
Dana-Farber Cancer Institute)
- Michael A. Calderwood
(Dana-Farber Cancer Institute
Blavatnik Institute, Harvard Medical School
Dana-Farber Cancer Institute)
- David E. Hill
(Dana-Farber Cancer Institute
Blavatnik Institute, Harvard Medical School
Dana-Farber Cancer Institute)
- Marc Vidal
(Dana-Farber Cancer Institute
Blavatnik Institute, Harvard Medical School)
Abstract
Most human protein-coding genes are expressed as multiple isoforms, which greatly expands the functional repertoire of the encoded proteome. While at least one reliable open reading frame (ORF) model has been assigned for every coding gene, the majority of alternative isoforms remains uncharacterized due to (i) vast differences of overall levels between different isoforms expressed from common genes, and (ii) the difficulty of obtaining full-length transcript sequences. Here, we present ORF Capture-Seq (OCS), a flexible method that addresses both challenges for targeted full-length isoform sequencing applications using collections of cloned ORFs as probes. As a proof-of-concept, we show that an OCS pipeline focused on genes coding for transcription factors increases isoform detection by an order of magnitude when compared to unenriched samples. In short, OCS enables rapid discovery of isoforms from custom-selected genes and will accelerate mapping of the human transcriptome.
Suggested Citation
Gloria M. Sheynkman & Katharine S. Tuttle & Florent Laval & Elizabeth Tseng & Jason G. Underwood & Liang Yu & Da Dong & Melissa L. Smith & Robert Sebra & Luc Willems & Tong Hao & Michael A. Calderwood, 2020.
"ORF Capture-Seq as a versatile method for targeted identification of full-length isoforms,"
Nature Communications, Nature, vol. 11(1), pages 1-12, December.
Handle:
RePEc:nat:natcom:v:11:y:2020:i:1:d:10.1038_s41467-020-16174-z
DOI: 10.1038/s41467-020-16174-z
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Citations
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Cited by:
- Feng Wang & Yang Xu & Robert Wang & Beatrice Zhang & Noah Smith & Amber Notaro & Samantha Gaerlan & Eric Kutschera & Kathryn E. Kadash-Edmondson & Yi Xing & Lan Lin, 2023.
"TEQUILA-seq: a versatile and low-cost method for targeted long-read RNA sequencing,"
Nature Communications, Nature, vol. 14(1), pages 1-15, December.
- Zhiping Zhang & Bongmin Bae & Winston H. Cuddleston & Pedro Miura, 2023.
"Coordination of alternative splicing and alternative polyadenylation revealed by targeted long read sequencing,"
Nature Communications, Nature, vol. 14(1), pages 1-14, December.
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