American Association for the Advancement of Science
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.
Mohammadi, Pejman; Castel, Stephane E.; Cummings, Beryl B.; Einson, Jonah; Sousa, Christina; Hoffman, Paul; Donkervoort, Sandra; Jiang, Zhuoxun; Mohassel, Payam; Foley, A. Reghan; Wheeler, Heather E.; Im, Hae Kyung; Bonnemann, Carsten G.; MacArthur, Daniel G.; and Lappalainen, Tuuli. Genetic regulatory variation in populations informs transcriptome analysis in rare disease. Science, 366, 6463: 351-356, 2019. Retrieved from Loyola eCommons, Biology: Faculty Publications and Other Works, http://dx.doi.org/10.1126/science.aay0256
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© The Authors, 2019.