Chair of Genetics, Animal Biotechnology and Immunology, Department of Animal Science, Biotechnical Faculty, University of Ljubljana, Domžale, 1230, Slovenia.
Faculty of Medicine, Department of Metabolism, Digestion and Reproduction, Imperial College London, London, SW7 2AZ, UK.
Genes Genomics. 2024 May;46(5):557-575. doi: 10.1007/s13258-024-01507-9. Epub 2024 Mar 14.
Analysing 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.
To 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.
Genetic 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.
WGS 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.
WGS 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.
分析动物模型生物的基因组被广泛用于理解肥胖等复杂性状和疾病的遗传基础,尽管存在少数肥胖小鼠模型,但缺乏它们的瘦型对照。
分析源自同一基础群体并通过超过 60 代分歧选择建立的多基因肥胖(Fat 系)和瘦型(Lean 系)独特小鼠模型的遗传差异。
使用 WGS 分析遗传变异性。使用 GATK 识别变体,并使用 Ensembl VEP 进行注释。使用 g.Profiler、WebGestalt 和 KEGG 进行 GO 和通路富集分析。使用 miRPathDB 2.0 获取 miRNA 种子区域,使用 LncRRIsearch 预测鉴定的 lncRNA 的靶基因,并使用 IMPC 数据库搜索影响脂肪组织量的基因。
WGS 分析揭示了 630 万个 SNPs,其中 130 万个是新的。鉴定出数千个潜在有影响的 SNPs,包括与脂肪组织量相关的 24 个基因内的 SNPs。SNP 密度在假基因和调控 RNA 中最高。Lean 系在 mmu-miR-3086-3p 的种子区域携带 SNP rs248726381,可能影响脂肪酸代谢。KEGG 分析显示免疫反应和糖尿病基因中有害错义变异,食物感知途径最富集。考虑 SNP GERP 评分、变体后果以及与其他小鼠系的等位基因比较进行基因优先级排序,确定了七个新的肥胖候选基因:4930441H08Rik、Aff3、Fam237b、Gm36633、Pced1a、Tecrl 和 Zfp536。
WGS 揭示了在选择期间积累的品系之间的许多遗传差异,包括对基因功能具有潜在负面影响的变体。鉴于越来越多的小鼠品系和遗传多态性目录的可用性,该研究为研究肥胖提供了有价值的资源。