Dataset Information

ProGeM: a framework for the prioritization of candidate causal genes at molecular quantitative trait loci.

ABSTRACT: Quantitative trait locus (QTL) mapping of molecular phenotypes such as metabolites, lipids and proteins through genome-wide association studies represents a powerful means of highlighting molecular mechanisms relevant to human diseases. However, a major challenge of this approach is to identify the causal gene(s) at the observed QTLs. Here, we present a framework for the 'Prioritization of candidate causal Genes at Molecular QTLs' (ProGeM), which incorporates biological domain-specific annotation data alongside genome annotation data from multiple repositories. We assessed the performance of ProGeM using a reference set of 227 previously reported and extensively curated metabolite QTLs. For 98% of these loci, the expert-curated gene was one of the candidate causal genes prioritized by ProGeM. Benchmarking analyses revealed that 69% of the causal candidates were nearest to the sentinel variant at the investigated molecular QTLs, indicating that genomic proximity is the most reliable indicator of 'true positive' causal genes. In contrast, cis-gene expression QTL data led to three false positive candidate causal gene assignments for every one true positive assignment. We provide evidence that these conclusions also apply to other molecular phenotypes, suggesting that ProGeM is a powerful and versatile tool for annotating molecular QTLs. ProGeM is freely available via GitHub.

SUBMITTER: Stacey D

PROVIDER: S-EPMC6326795 | biostudies-literature | 2019 Jan

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

ProGeM: a framework for the prioritization of candidate causal genes at molecular quantitative trait loci.

Stacey David D Fauman Eric B EB Ziemek Daniel D Sun Benjamin B BB Harshfield Eric L EL Wood Angela M AM Butterworth Adam S AS Suhre Karsten K Paul Dirk S DS

Nucleic acids research 20190101 1

Quantitative trait locus (QTL) mapping of molecular phenotypes such as metabolites, lipids and proteins through genome-wide association studies represents a powerful means of highlighting molecular mechanisms relevant to human diseases. However, a major challenge of this approach is to identify the causal gene(s) at the observed QTLs. Here, we present a framework for the 'Prioritization of candidate causal Genes at Molecular QTLs' (ProGeM), which incorporates biological domain-specific annotatio ...[more]

PMID: 30239796

Similar Datasets

Project description:Trauma- and stress-related disorders are clinically heterogeneous and associated with substantial genetic risk. Understanding the biological origins of heterogeneity of key intermediate phenotypes such as cognition and emotion can provide novel mechanistic insights into disorder pathogenesis. Performing quantitative genetics in animal models is a tractable strategy for examining both the genetic basis of intermediate phenotypes and functional testing of candidate quantitative traits genes (QTGs). Here, existing and newly collected data were used for collaborative genome-wide mapping of cued fear acquisition and expression in 65 mouse strains from the BXD genetic reference panel. For fear acquisition, we identified a significant locus on chromosome (Chr) 10 and eight suggestive loci on Chr 2, 4, 5, 11, 13, and 15. For fear expression, we identified one significant and another highly suggestive locus on Chr 13, as well as four suggestive loci on Chr 10, 11, and X. Across these loci, 60 putative QTGs were identified. The quantitative trait locus on distal Chr 13 contained a single, highly promising gene at the location of the peak likelihood ratio statistic score. The gene, hyperpolarization-activated cyclic nucleotide-gated channel 1 (Hcn1), regulates neuronal excitability. Validation experiments using behavioral pharmacology revealed that functional Hcn channels in the basolateral amygdala are necessary for conditioned fear acquisition and expression. Hcn1, together with the other candidate QTGs, thus provide new targets for neurobiological and treatment studies of fear learning and trauma- and stress-related disorders.There is a knowledge gap in understanding the genetic contributions to behavioral heterogeneity in typical and atypical populations. Mouse genetic reference panels (GRPs) provide one approach for identifying genetic sources of variation. Here, we identified three loci for conditioned fear acquisition and expression in a mouse GRP. Each locus contained candidate quantitative trait genes (QTGs). One locus had a single QTG, Hcn1 (hyperpolarization-activated cyclic nucleotide-gated channel 1), which has been implicated in neuronal excitability and learning. This discovery was validated using behavioral pharmacology, revealing that Hcn channels in the basolateral amygdala are required for fear acquisition and expression. The study thus identifies novel candidate QTGs that may contribute to variation in emotional learning and highlight the utility of mouse GRPs for the identification of genes underlying complex traits.

Dataset Information

ProGeM: a framework for the prioritization of candidate causal genes at molecular quantitative trait loci.

Publications

ProGeM: a framework for the prioritization of candidate causal genes at molecular quantitative trait loci.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets