Abstract
Interactions among genomic loci have often been overlooked in genome-wide association studies, revealing the combinatorial effects of variants on phenotype or disease manifestation. Unexplained genetic variance, interactions among causal genes of small effects, and biological pathways could be identified using a network biology approach. The main objective of this study was to determine the genome-wide epistatic variants affecting feed efficiency traits [feed conversion ratio (FCR) and residual feed intake (RFI)] based on weighted interaction SNP hub (WISH-R) method. Herein, we detected highly interconnected epistatic SNP modules, pathways, and potential biomarkers for the FCR and RFI in Duroc and Landrace purebreds considering the whole population, and separately for low and high feed efficient groups. Highly interacting SNP modules in Duroc (1,247 SNPs) and Landrace (1,215 SNPs) across the population and for low feed efficient (Duroc—80 SNPs, Landrace—146 SNPs) and high feed efficient group (Duroc—198 SNPs, Landrace—232 SNPs) for FCR and RFI were identified. Gene and pathway analyses identified ABL1, MAP3K4, MAP3K5, SEMA6A, KITLG, and KAT2B from chromosomes 1, 2, 5, and 13 underlying ErbB, Ras, Rap1, thyroid hormone, axon guidance pathways in Duroc. GABBR2, GNA12, and PRKCG genes from chromosomes 1, 3, and 6 pointed towards thyroid hormone, cGMP-PKG and cAMP pathways in Landrace. From Duroc low feed efficient group, the TPK1 gene was found involved with thiamine metabolism, whereas PARD6G, DLG2, CRB1 were involved with the hippo signaling pathway in high feed efficient group. PLOD1 and SETD7 genes were involved with lysine degradation in low feed efficient group in Landrace, while high feed efficient group pointed to genes underpinning valine, leucine, isoleucine degradation, and fatty acid elongation. Some SNPs and genes identified are known for their association with feed efficiency, others are novel and potentially provide new avenues for further research. Further validation of epistatic SNPs and genes identified here in a larger cohort would help to establish a framework for modelling epistatic variance in future methods of genomic prediction, increasing the accuracy of estimated genetic merit for FE and helping the pig breeding industry.
Highlights
Genetic or epistatic interactions between single nucleotide polymorphism (SNP), genes or QTLs is a topic of interest in molecular and quantitative genetics (Cordell, 2002) as it occurs when the phenotypic effect of a mutation is affected by the presence of other mutations in the genome (Papp and Pál, 2011)
After quality control (QC), 48,444 and 49,876 loci in Duroc and Landrace on 18 porcine autosomes were available for association analysis with feed conversion ratio (FCR)
The top 7,000 SNPs were selected, and based on Weighted Interaction SNP hub (WISH)-R package (Carmelo et al, 2018), we calculated the epistatic interactions based on FCR in both the breeds and within the breed groups (Figure 2)
Summary
Genetic or epistatic interactions between SNPs, genes or QTLs is a topic of interest in molecular and quantitative genetics (Cordell, 2002) as it occurs when the phenotypic effect of a mutation is affected by the presence of other mutations in the genome (Papp and Pál, 2011). Epistatic interactions between genes for some quantitative traits, such as meat quality (Ovilo et al, 2002; Duthie et al, 2011a), carcass (Duthie et al, 2010), reproductive traits (Bidanel, 1993; Rodríguez et al, 2005; Noguera et al, 2009), growth (Crooks and Guo, 2017), and muscle fiber traits (Estellé et al, 2008) have been reported for pigs These findings shed light on the different interactions underlying the genomic regulation in several traits. To the best of our knowledge, there are no studies on genome-wide epistatic interactions using high throughput genomic data (HTG) and in the context of genetic (SNP) networks underlying feed efficiency related traits in pigs
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