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

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.

SUBMITTER: Mohammadi P

PROVIDER: S-EPMC6814274 | biostudies-literature | 2019 Oct

REPOSITORIES: biostudies-literature

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

Mohammadi Pejman P Castel Stephane E SE Cummings Beryl B BB Einson Jonah J Sousa Christina C Hoffman Paul P Donkervoort Sandra S Jiang Zhuoxun Z Mohassel Payam P Foley A Reghan AR Wheeler Heather E HE Im Hae Kyung HK Bonnemann Carsten G CG MacArthur Daniel G DG Lappalainen Tuuli T

Science (New York, N.Y.) 20191010 6463

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 dat ...[more]

PMID: 31601707

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Project description:BackgroundMitochondrial dysfunction plays a key role in PD, but the underlying molecular mechanisms remain unresolved. We hypothesized that the disruption of mitochondrial function in PD is primed by rare, protein-altering variation in nuclear genes controlling mitochondrial structure and function.ObjectiveThe objective of this study was to assess whether genetic variation in genes associated with mitochondrial function influences the risk of idiopathic PD.MethodsWe employed whole-exome sequencing data from 2 independent cohorts of clinically validated idiopathic PD and controls, the Norwegian ParkWest cohort (n = 411) and the North American Parkinson's Progression Markers Initiative (n = 640). We applied burden-based and variance-based collapsing methods to assess the enrichment of rare, nonsynonymous, and damaging genetic variants on genes, exome-wide, and on a comprehensive set of mitochondrial pathways, defined as groups of genes controlling specific mitochondrial functions.ResultsUsing the sequence kernel association test, we detected a significant polygenic enrichment of rare, nonsynonymous variants in the gene-set encoding the pathway of mitochondrial DNA maintenance. Notably, this was the strongest association in both cohorts and survived multiple testing correction (ParkWest P = 6.3 × 10-3 , Parkinson's Progression Markers Initiative P = 6.9 × 10-5 , metaanalysis P = 3.2 × 10-6 ).ConclusionsOur results show that the enrichment of rare inherited variation in the pathway controlling mitochondrial DNA replication and repair influences the risk of PD. We propose that this polygenic enrichment contributes to the impairment of mitochondrial DNA homeostasis, thought to be a key mechanism in the pathogenesis of PD, and explains part of the disorder's "missing heritability." © 2018 The Authors. Movement Disorders published by Wiley Periodicals, Inc. on behalf of International Parkinson and Movement Disorder Society.

Dataset Information

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

Publications

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

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