Dataset Information

Genome-wide pathogenesis interpretation using a heat diffusion-based systems genetics method and implications for gene function annotation.

ABSTRACT: BACKGROUND:Genetics is best dedicated to interpreting pathogenesis and revealing gene functions. The past decade has witnessed unprecedented progress in genetics, particularly in genome-wide identification of disorder variants through Genome-Wide Association Studies (GWAS) and Phenome-Wide Association Studies (PheWAS). However, it is still a great challenge to use GWAS/PheWAS-derived data to elucidate pathogenesis. METHODS:In this study, we used HotNet2, a heat diffusion-based systems genetics algorithm, to calculate the networks for disease genes obtained from GWAS and PheWAS, with an attempt to get deeper insights into disease pathogenesis at a molecular level. RESULTS:Through HotNet2 calculation, significant networks for 202 (for GWAS) and 167 (for PheWAS) types of diseases were identified and evaluated, respectively. The GWAS-derived disease networks exhibit a stronger biomedical relevance than PheWAS counterparts. Therefore, the GWAS-derived networks were used for pathogenesis interpretation by integrating the accumulated biomedical information. As a result, the pathogenesis for 64 diseases was elucidated in terms of mutation-caused abnormal transcriptional regulation, and 47 diseases were preliminarily interpreted in terms of mutation-caused varied protein-protein interactions. In addition, 3,802 genes (including 46 function-unknown genes) were assigned with new functions by disease network information, some of which were validated through mice gene knockout experiments. CONCLUSIONS:Systems genetics algorithm HotNet2 can efficiently establish genotype-phenotype links at the level of biological networks. Compared with original GWAS/PheWAS results, HotNet2-calculated disease-gene associations have stronger biomedical significance, hence provide better interpretations for the pathogenesis of genome-wide variants, and offer new insights into gene functions as well. These results are also helpful in drug development.

SUBMITTER: Quan Y

PROVIDER: S-EPMC7549611 | biostudies-literature | 2020 Sep

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Genome-wide pathogenesis interpretation using a heat diffusion-based systems genetics method and implications for gene function annotation.

Quan Yuan Y Zhang Qing-Ye QY Lv Bo-Min BM Xu Rui-Feng RF Zhang Hong-Yu HY

Molecular genetics & genomic medicine 20200901 10

<h4>Background</h4>Genetics is best dedicated to interpreting pathogenesis and revealing gene functions. The past decade has witnessed unprecedented progress in genetics, particularly in genome-wide identification of disorder variants through Genome-Wide Association Studies (GWAS) and Phenome-Wide Association Studies (PheWAS). However, it is still a great challenge to use GWAS/PheWAS-derived data to elucidate pathogenesis.<h4>Methods</h4>In this study, we used HotNet2, a heat diffusion-based sys ...[more]

PMID: 32869547

Similar Datasets

Project description:The acceleration of DNA sequencing in samples from patients and population studies has resulted in extensive catalogues of human genetic variation, but the interpretation of rare genetic variants remains problematic. A notable example of this challenge is the existence of disruptive variants in dosage-sensitive disease genes, even in apparently healthy individuals. Here, by manual curation of putative loss-of-function (pLoF) variants in haploinsufficient disease genes in the Genome Aggregation Database (gnomAD)1, we show that one explanation for this paradox involves alternative splicing of mRNA, which allows exons of a gene to be expressed at varying levels across different cell types. Currently, no existing annotation tool systematically incorporates information about exon expression into the interpretation of variants. We develop a transcript-level annotation metric known as the 'proportion expressed across transcripts', which quantifies isoform expression for variants. We calculate this metric using 11,706 tissue samples from the Genotype Tissue Expression (GTEx) project2 and show that it can differentiate between weakly and highly evolutionarily conserved exons, a proxy for functional importance. We demonstrate that expression-based annotation selectively filters 22.8% of falsely annotated pLoF variants found in haploinsufficient disease genes in gnomAD, while removing less than 4% of high-confidence pathogenic variants in the same genes. Finally, we apply our expression filter to the analysis of de novo variants in patients with autism spectrum disorder and intellectual disability or developmental disorders to show that pLoF variants in weakly expressed regions have similar effect sizes to those of synonymous variants, whereas pLoF variants in highly expressed exons are most strongly enriched among cases. Our annotation is fast, flexible and generalizable, making it possible for any variant file to be annotated with any isoform expression dataset, and will be valuable for the genetic diagnosis of rare diseases, the analysis of rare variant burden in complex disorders, and the curation and prioritization of variants in recall-by-genotype studies.

Dataset Information

Genome-wide pathogenesis interpretation using a heat diffusion-based systems genetics method and implications for gene function annotation.

Publications

Genome-wide pathogenesis interpretation using a heat diffusion-based systems genetics method and implications for gene function annotation.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets