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Genetic regulatory variation in populations informs transcriptome analysis in rare disease.

Citation
Mohammadi, P., et al. “Genetic Regulatory Variation In Populations Informs Transcriptome Analysis In Rare Disease.”. Science (New York, N.y.), pp. 351-356.
Center University of Chicago
Author Pejman Mohammadi, Stephane E Castel, Beryl B Cummings, Jonah Einson, Christina Sousa, Paul Hoffman, Sandra Donkervoort, Zhuoxun Jiang, Payam Mohassel, Reghan Foley, Heather E Wheeler, Hae Kyung Im, Carsten G Bonnemann, Daniel G MacArthur, Tuuli Lappalainen
Abstract

Transcriptome data can facilitate the interpretation of the effects of rare genetic variants. Here, we introduce ANEVA (analysis of expression variation) to quantify genetic variation in gene dosage from allelic expression (AE) data in a population. Application of ANEVA to the Genotype-Tissues Expression (GTEx) data showed that this variance estimate is robust and correlated with selective constraint in a gene. Using these variance estimates in a dosage outlier test (ANEVA-DOT) applied to AE data from 70 Mendelian muscular disease patients showed accuracy in detecting genes with pathogenic variants in previously resolved cases and led to one confirmed and several potential new diagnoses. Using our reference estimates from GTEx data, ANEVA-DOT can be incorporated in rare disease diagnostic pipelines to use RNA-sequencing data more effectively.

Year of Publication
2019
Journal
Science (New York, N.Y.)
Volume
366
Issue
6463
Number of Pages
351-356
Date Published
12/2019
ISSN Number
1095-9203
DOI
10.1126/science.aay0256
Alternate Journal
Science
PMID
31601707
PMCID
PMC6814274
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