Abstract
MotivationGene prioritization at human GWAS loci is challenging due to linkage-disequilibrium and long-range gene regulatory mechanisms. However, identifying the causal gene is crucial to enable identification of potential drug targets and better understanding of molecular mechanisms. Mapping GWAS traits to known phenotypically relevant Mendelian disease genes near a locus is a promising approach to gene prioritization.ResultsWe present MendelVar, a comprehensive tool that integrates knowledge from four databases on Mendelian disease genes with enrichment testing for a range of associated functional annotations such as Human Phenotype Ontology, Disease Ontology and variants from ClinVar. This open web-based platform enables users to strengthen the case for causal importance of phenotypically matched candidate genes at GWAS loci. We demonstrate the use of MendelVar in post-GWAS gene annotation for type 1 diabetes, type 2 diabetes, blood lipids and atopic dermatitis.Availability and implementationMendelVar is freely available at https://mendelvar.mrcieu.ac.ukSupplementary information Supplementary data are available at Bioinformatics online.
Highlights
The last decade has delivered a bounty of genetic data due to advances in high-throughput DNA sequencing and genotyping
We demonstrate the use of MendelVar in post-GWAS gene annotation for type 1 diabetes, type 2 diabetes, blood lipids and atopic dermatitis
MendelVar uses all the confirmed gene-disease relationships featured in OMIM and complements it with three more specialist data sources for Mendelian disease: Orphanet (Rath et al, 2012), expertly curated gene panels used for diagnostics from Genomics England PanelApp (Martin et al, 2019) and results from the on-going Deciphering Developmental Disorders Study (DECIPHER)—whose aim is to identify de novo microgenomic rearrangements responsible for undiagnosed developmental delay disorders (Firth et al, 2009)
Summary
The last decade has delivered a bounty of genetic data due to advances in high-throughput DNA sequencing and genotyping. This has led to dramatic advances in investigation of the genetic basis of complex, polygenic disease and traits with 9407 studies featured in the GWAS Catalog as of October 2020 (Buniello et al, 2019). At the other end of the spectrum, Mendelian monogenic disease research has benefitted tremendously from recent sequencing methods, which helped to detect the causal genes in >1000 Mendelian conditions (Bamshad et al, 2019). In contrast to complex trait loci, large-effect sizes and typically missense consequences of Mendelian perturbations mean the causal gene is more detected using statistical methods alone, resulting in a direct link between phenotype and gene. In MendelVar, we utilize these direct links between phenotypes and genes from Mendelian traits to aid in identifying causal genes and pathways implicated in GWAS of complex traits
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