ORF Capture-Seq as a versatile method for targeted identification of full-length isoforms

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, David E. Hill () and Marc Vidal
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Gloria M. Sheynkman: Dana-Farber Cancer Institute
Katharine S. Tuttle: Dana-Farber Cancer Institute
Florent Laval: Dana-Farber Cancer Institute
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
Robert Sebra: Icahn School of Medicine at Mount Sinai
Luc Willems: University of Liège
Tong Hao: Dana-Farber Cancer Institute
Michael A. Calderwood: Dana-Farber Cancer Institute
David E. Hill: Dana-Farber Cancer Institute
Marc Vidal: Dana-Farber Cancer Institute

Nature Communications, 2020, vol. 11, issue 1, 1-12

Abstract: 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.

Date: 2020
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DOI: 10.1038/s41467-020-16174-z

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