Whole genome sequencing of mouse lines divergently selected for fatness (FLI) and leanness (FHI) revealed several genetic variants as candidates for novel obesity genes

Abstract

BackgroundAnalysing genomes of animal model organisms is widely used for understanding the genetic basis of complex traits and diseases, such as obesity, for which only a few mouse models exist, however, without their lean counterparts.ObjectiveTo analyse genetic differences in the unique mouse models of polygenic obesity (Fat line) and leanness (Lean line) originating from the same base population and established by divergent selection over more than 60 generations.MethodsGenetic variability was analysed using WGS. Variants were identified with GATK and annotated with Ensembl VEP. g.Profiler, WebGestalt, and KEGG were used for GO and pathway enrichment analysis. miRNA seed regions were obtained with miRPathDB 2.0, LncRRIsearch was used to predict targets of identified lncRNAs, and genes influencing adipose tissue amount were searched using the IMPC database.ResultsWGS analysis revealed 6.3 million SNPs, 1.3 million were new. Thousands of potentially impactful SNPs were identified, including within 24 genes related to adipose tissue amount. SNP density was highest in pseudogenes and regulatory RNAs. The Lean line carries SNP rs248726381 in the seed region of mmu-miR-3086-3p, which may affect fatty acid metabolism. KEGG analysis showed deleterious missense variants in immune response and diabetes genes, with food perception pathways being most enriched. Gene prioritisation considering SNP GERP scores, variant consequences, and allele comparison with other mouse lines identified seven novel obesity candidate genes: 4930441H08Rik, Aff3, Fam237b, Gm36633, Pced1a, Tecrl, and Zfp536.ConclusionWGS revealed many genetic differences between the lines that accumulated over the selection period, including variants with potential negative impacts on gene function. Given the increasing availability of mouse strains and genetic polymorphism catalogues, the study is a valuable resource for researchers to study obesity.