Recommendations for Accurate Resolution of Gene and Isoform Allele-Specific Expression in RNA-Seq Data

Wood, David L. A., Nones, Katia, Steptoe, Anita, Christ, Angelika, Harliwong, Ivon, Newell, Felicity, Bruxner, Timothy J. C., Miller, David, Cloonan, Nicole and Grimmond, Sean M. (2015) Recommendations for Accurate Resolution of Gene and Isoform Allele-Specific Expression in RNA-Seq Data. PLoS One, 10 5: e0126911-e0126911. doi:10.1371/journal.pone.0126911

Author Wood, David L. A.
Nones, Katia
Steptoe, Anita
Christ, Angelika
Harliwong, Ivon
Newell, Felicity
Bruxner, Timothy J. C.
Miller, David
Cloonan, Nicole
Grimmond, Sean M.
Title Recommendations for Accurate Resolution of Gene and Isoform Allele-Specific Expression in RNA-Seq Data
Journal name PLoS One   Check publisher's open access policy
ISSN 1932-6203
Publication date 2015-05-12
Year available 2015
Sub-type Article (original research)
DOI 10.1371/journal.pone.0126911
Open Access Status DOI
Volume 10
Issue 5
Start page e0126911
End page e0126911
Total pages 27
Place of publication San Francisco, CA United States
Publisher Public Library of Science
Collection year 2016
Language eng
Formatted abstract
Genetic variation modulates gene expression transcriptionally or post-transcriptionally, and can profoundly alter an individual's phenotype. Measuring allelic differential expression at heterozygous loci within an individual, a phenomenon called allele-specific expression (ASE), can assist in identifying such factors. Massively parallel DNA and RNA sequencing and advances in bioinformatic methodologies provide an outstanding opportunity to measure ASE genome-wide. In this study, matched DNA and RNA sequencing, genotyping arrays and computationally phased haplotypes were integrated to comprehensively and conservatively quantify ASE in a single human brain and liver tissue sample. We describe a methodological evaluation and assessment of common bioinformatic steps for ASE quantification, and recommend a robust approach to accurately measure SNP, gene and isoform ASE through the use of personalized haplotype genome alignment, strict alignment quality control and intragenic SNP aggregation. Our results indicate that accurate ASE quantification requires careful bioinformatic analyses and is adversely affected by sample specific alignment confounders and random sampling even at moderate sequence depths. We identified multiple known and several novel ASE genes in liver, including WDR72, DSP and UBD, as well as genes that contained ASE SNPs with imbalance direction discordant with haplotype phase, explainable by annotated transcript structure, suggesting isoform derived ASE. The methods evaluated in this study will be of use to researchers performing highly conservative quantification of ASE, and the genes and isoforms identified as ASE of interest to researchers studying those loci.
Keyword Human Genomes
Q-Index Code C1
Q-Index Status Confirmed Code
Institutional Status UQ

Document type: Journal Article
Sub-type: Article (original research)
Collections: Official 2016 Collection
School of Medicine Publications
Institute for Molecular Bioscience - Publications
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Citation counts: TR Web of Science Citation Count  Cited 2 times in Thomson Reuters Web of Science Article | Citations
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Created: Mon, 18 May 2015, 15:49:33 EST by Susan Allen on behalf of Institute for Molecular Bioscience