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Science. 2019 Oct 18;366(6463):351-356. doi: 10.1126/science.aay0256. Epub 2019 Oct 10.

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

Author information

1
New York Genome Center, New York, NY, USA. pejman@scripps.edu tlappalainen@nygenome.org.
2
Department of Systems Biology, Columbia University, New York, NY, USA.
3
Scripps Research Translational Institute, La Jolla, CA, USA.
4
Department of Integrative Structural and Computational Biology, The Scripps Research Institute, La Jolla, CA, USA.
5
New York Genome Center, New York, NY, USA.
6
Analytical and Translation Genetics Unit, Massachusetts General Hospital, Boston, MA, USA.
7
Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA.
8
Neuromuscular and Neurogenetic Disorders of Childhood Section, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, USA.
9
Section of Genetic Medicine, Department of Medicine, University of Chicago, Chicago, IL, USA.
10
Department of Biology, Loyola University Chicago, Chicago, IL, USA.
11
Department of Computer Science, Loyola University Chicago, Chicago, IL, USA.

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.

PMID:
31601707
PMCID:
PMC6814274
[Available on 2020-04-18]
DOI:
10.1126/science.aay0256

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