Department of Animal Science, University of São Paulo, Piracicaba, SP, 13418-900, Brazil.
Department of Animal Science, Iowa State University, Ames, IA, 50011, USA.
BMC Genomics. 2018 Jun 27;19(1):499. doi: 10.1186/s12864-018-4871-y.
Integration of high throughput DNA genotyping and RNA-sequencing data allows for the identification of genomic regions that control gene expression, known as expression quantitative trait loci (eQTL), on a whole genome scale. Intramuscular fat (IMF) content and carcass composition play important roles in metabolic and physiological processes in mammals because they influence insulin sensitivity and consequently prevalence of metabolic diseases such as obesity and type 2 diabetes. However, limited information is available on the genetic variants and mechanisms associated with IMF deposition in mammals. Thus, our hypothesis was that eQTL analyses could identify putative regulatory regions and transcription factors (TFs) associated with intramuscular fat (IMF) content traits.
We performed an integrative eQTL study in skeletal muscle to identify putative regulatory regions and factors associated with intramuscular fat content traits. Data obtained from skeletal muscle samples of 192 animals was used for association analysis between 461,466 SNPs and the transcription level of 11,808 genes. This yielded 1268 cis- and 10,334 trans-eQTLs, among which we identified nine hotspot regions that each affected the expression of > 119 genes. These putative regulatory regions overlapped with previously identified QTLs for IMF content. Three of the hotspots respectively harbored the transcription factors USF1, EGR4 and RUNX1T1, which are known to play important roles in lipid metabolism. From co-expression network analysis, we further identified modules significantly correlated with IMF content and associated with relevant processes such as fatty acid metabolism, carbohydrate metabolism and lipid metabolism.
This study provides novel insights into the link between genotype and IMF content as evident from the expression level. It thereby identifies genomic regions of particular importance and associated regulatory factors. These new findings provide new knowledge about the biological processes associated with genetic variants and mechanisms associated with IMF deposition in mammals.
高通量 DNA 基因分型和 RNA 测序数据的整合允许鉴定控制基因表达的基因组区域,这些区域称为表达数量性状基因座 (eQTL),这是在全基因组范围内进行的。肌肉内脂肪 (IMF) 含量和胴体组成在哺乳动物的代谢和生理过程中起着重要作用,因为它们影响胰岛素敏感性,进而影响肥胖和 2 型糖尿病等代谢疾病的流行。然而,关于与哺乳动物 IMF 沉积相关的遗传变异和机制的信息有限。因此,我们的假设是,eQTL 分析可以鉴定与肌肉内脂肪 (IMF) 含量特征相关的潜在调节区域和转录因子 (TF)。
我们在骨骼肌中进行了综合 eQTL 研究,以鉴定与肌肉内脂肪含量特征相关的潜在调节区域和因素。从 192 个动物的骨骼肌样本中获得的数据用于在 461,466 个 SNP 和 11,808 个基因的转录水平之间进行关联分析。这产生了 1268 个顺式和 10,334 个反式 eQTL,其中我们鉴定了 9 个热点区域,每个区域都影响了 >119 个基因的表达。这些潜在的调节区域与之前鉴定的 IMF 含量 QTL 重叠。三个热点区域分别含有转录因子 USF1、EGR4 和 RUNX1T1,它们已知在脂质代谢中起着重要作用。从共表达网络分析中,我们进一步鉴定了与 IMF 含量显著相关的模块,并与相关过程如脂肪酸代谢、碳水化合物代谢和脂质代谢相关联。
这项研究提供了关于基因型与 IMF 含量之间联系的新见解,从表达水平上可以明显看出。它因此确定了特别重要的基因组区域和相关的调节因子。这些新发现提供了关于与哺乳动物 IMF 沉积相关的遗传变异和机制相关的生物过程的新知识。