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Genetic regulatory variation in populations informs transcriptome analysis in rare disease
Science
  • Pejman Mohammadi, Columbia University
  • Stephane E Castel, Columbia University
  • Beryl B Cummings, Broad Institute of MIT and Harvard
  • Jonah Einson, Columbia University
  • Christina Sousa, The Scripps Research Institute
  • Paul Hoffman, Columbia University
  • Sandra Donkervoort, National Institute of Neurological Disorders and Stroke
  • Zhuoxun Jiang, University of Chicago
  • Payam Mohassel, National Institute of Neurological Disorders and Stroke
  • A. Reghan Foley, National Institute of Neurological Disorders and Stroke
  • Heather E. Wheeler, Loyola University Chicago
  • Hae Kyung Im, Loyola University Chicago
  • Carsten G Bonnemann, National Institute of Neurological Disorders and Stroke
  • Daniel G MacArthur, Broad Institute of MIT and Harvard
  • Tuuli Lappalainen, Columbia University
Document Type
Article
Publication Date
10-18-2019
Pages
351-356
Publisher Name
American Association for the Advancement of Science
Disciplines
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.

Comments

Author Posting © The Authors, 2019. This is the author's version of the work. It is posted here by permission of The Authors for personal use, not for redistribution. The definitive version was published in Science, Volume 366, Issue 6463, July 2019. https://doi.org/10.1126/science.aay0256

Creative Commons License
Creative Commons Attribution-Noncommercial-No Derivative Works 3.0
Citation Information
Pejman Mohammadi, Stephane E Castel, Beryl B Cummings, Jonah Einson, et al.. "Genetic regulatory variation in populations informs transcriptome analysis in rare disease" Science Vol. 366 Iss. 6463 (2019)
Available at: http://works.bepress.com/heather-wheeler/59/