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A technology-agnostic long-read analysis pipeline for transcriptome discovery and quantification

Wyman, Dana and Balderrama-Gutierrez, Gabriela and Reese, Fairlie and Jiang, Shan and Rahmanian, Sorena and Zeng, Weihua and Williams, Brian and Trout, Diane and England, Whitney and Chu, Sophie and Spitale, Robert C. and Tenner, Andrea and Wold, Barbara and Mortazavi, Ali (2019) A technology-agnostic long-read analysis pipeline for transcriptome discovery and quantification. . (Unpublished) http://resolver.caltech.edu/CaltechAUTHORS:20190618-105056093

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Abstract

Alternative splicing is widely acknowledged to be a crucial regulator of gene expression and is a key contributor to both normal developmental processes and disease states. While cost-effective and accurate for quantification, short-read RNA-seq lacks the ability to resolve full-length transcript isoforms despite increasingly sophisticated computational methods. Long-read sequencing platforms such as Pacific Biosciences (PacBio) and Oxford Nanopore (ONT) bypass the transcript reconstruction challenges of short-reads. Here we describe TALON, the ENCODE4 pipeline for analyzing PacBio cDNA and ONT direct-RNA transcriptomes. We apply TALON to three human ENCODE Tier 1 cell lines and show that while both technologies perform well at full-transcript discovery and quantification, each technology has its distinct artifacts. We further apply TALON to mouse cortical and hippocampal transcriptomes and find that a substantial proportion of neuronal genes have more reads associated with novel isoforms than annotated ones. The TALON pipeline for technology-agnostic, long-read transcriptome discovery and quantification tracks both known and novel transcript models as well as expression levels across datasets for both simple studies and larger projects such as ENCODE that seek to decode transcriptional regulation in the human and mouse genomes to predict more accurate expression levels of genes and transcripts than possible with short-reads alone.


Item Type:Report or Paper (Discussion Paper)
Related URLs:
URLURL TypeDescription
https://doi.org/10.1101/672931DOIDiscussion Paper
https://www.biorxiv.org/content/10.1101/672931v1OrganizationDiscussion Paper
ORCID:
AuthorORCID
Balderrama-Gutierrez, Gabriela0000-0002-5794-4518
Reese, Fairlie0000-0002-9240-0102
Wold, Barbara0000-0003-3235-8130
Mortazavi, Ali0000-0002-4259-6362
Additional Information:The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-ND 4.0 International license. bioRxiv preprint first posted online Jun. 18, 2019. We would like to thank Melanie Oakes at UC Irvine Genomics High-Throughput Facility (GHTF) for her help with PacBio sequencing as well as the entire ENCODE DCC for help implementing the TALON pipeline at the ENCODE portal. This work was supported in part by grants from the National Institutes of Health (UM1HG009443 to A.M. and B.W. as well as R01AG060148 to A.M and A.T.).
Funders:
Funding AgencyGrant Number
NIHUM1HG009443
NIHR01AG060148
Record Number:CaltechAUTHORS:20190618-105056093
Persistent URL:http://resolver.caltech.edu/CaltechAUTHORS:20190618-105056093
Official Citation:A technology-agnostic long-read analysis pipeline for transcriptome discovery and quantification. Dana Wyman, Gabriela Balderrama-Gutierrez, Fairlie Reese, Shan Jiang, Sorena Rahmanian, Weihua Zeng, Brian A Williams, Diane Trout, Whitney England, Sophie Chu, Robert C Spitale, Andrea J Tenner, Barbara Wold, Ali Mortazavi. bioRxiv 672931; doi: https://doi.org/10.1101/672931
Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:96500
Collection:CaltechAUTHORS
Deposited By: Tony Diaz
Deposited On:18 Jun 2019 19:38
Last Modified:18 Jun 2019 19:38

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