Submitted by ja607 on
Title | Genetic regulatory variation in populations informs transcriptome analysis in rare disease. |
Publication Type | Journal Article |
Year of Publication | 2019 |
Authors | Mohammadi, P, Castel, SE, Cummings, BB, Einson, J, Sousa, C, Hoffman, P, Donkervoort, S, Jiang, Z, Mohassel, P, A Foley, R, Wheeler, HE, Im, HKyung, Bonnemann, CG, MacArthur, DG, Lappalainen, T |
Journal | Science |
Volume | 366 |
Issue | 6463 |
Pagination | 351-356 |
Date Published | 2019 10 18 |
ISSN | 1095-9203 |
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. |
DOI | 10.1126/science.aay0256 |
Alternate Journal | Science |
PubMed ID | 31601707 |
PubMed Central ID | PMC6814274 |
Grant List | UM1 HG008900 / HG / NHGRI NIH HHS / United States UL1 TR001114 / TR / NCATS NIH HHS / United States R01 MH107666 / MH / NIMH NIH HHS / United States R01 MH106842 / MH / NIMH NIH HHS / United States UM1 HG008901 / HG / NHGRI NIH HHS / United States R15 HG009569 / HG / NHGRI NIH HHS / United States K99 HG009916 / HG / NHGRI NIH HHS / United States UL1 TR002550 / TR / NCATS NIH HHS / United States R01 GM122924 / GM / NIGMS NIH HHS / United States P30 DK020595 / DK / NIDDK NIH HHS / United States |