Genetic regulatory variation in populations informs transcriptome analysis in rare disease

Pejman Mohammadi, Stephane E Castel, Beryl B Cummings, Jonah Einson, Christina Sousa, Paul Hoffman, Sandra Donkervoort, Zhuoxun Jiang, Payam Mohassel, A. Reghan Foley, Heather E. Wheeler, Hae Kyung Im, Carsten G Bonnemann, Daniel G MacArthur, Tuuli Lappalainen

Research output: Contribution to journalArticlepeer-review

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.

Original languageAmerican English
JournalHistory: Faculty Publications and Other Works
Volume366
Issue number6463
DOIs
StatePublished - Oct 18 2019

Disciplines

  • Biology

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