Genomic Heritability and Genome-Wide Association Studies of Plasma Metabolites in Crossbred Beef Cattle

Jiyuan Li; Everestus C Akanno; Tiago S Valente; Mohammed Abo-Ismail; Brian K Karisa; Zhiquan Wang; Graham S Plastow

doi:10.3389/fgene.2020.538600

Genomic Heritability and Genome-Wide Association Studies of Plasma Metabolites in Crossbred Beef Cattle

Front Genet. 2020 Sep 24:11:538600. doi: 10.3389/fgene.2020.538600. eCollection 2020.

Authors

Jiyuan Li¹, Everestus C Akanno¹, Tiago S Valente^{1

2}, Mohammed Abo-Ismail^{1

3}, Brian K Karisa⁴, Zhiquan Wang¹, Graham S Plastow¹

Affiliations

¹ Livestock Gentec, Department of Agriculture, Food and Nutritional Science, Faculty of Agricultural, Life and Environmental Sciences, University of Alberta, Edmonton, AB, Canada.
² Department of Animal Science, Ethology and Animal Ecology Research Group, São Paulo State University, Jaboticabal, Brazil.
³ Department of Animal Science, College of Agriculture, Food and Environmental Sciences, California Polytechnic State University, San Luis Obispo, CA, United States.
⁴ Ministry of Agriculture and Forestry, Edmonton, AB, Canada.

Abstract

Metabolites, substrates or products of metabolic processes, are involved in many biological functions, such as energy metabolism, signaling, stimulatory and inhibitory effects on enzymes and immunological defense. Metabolomic phenotypes are influenced by combination of genetic and environmental effects allowing for metabolome-genome-wide association studies (mGWAS) as a powerful tool to investigate the relationship between these phenotypes and genetic variants. The objectives of this study were to estimate genomic heritability and perform mGWAS and in silico functional enrichment analyses for a set of plasma metabolites in Canadian crossbred beef cattle. Thirty-three plasma metabolites and 45,266 single nucleotide polymorphisms (SNPs) were available for 475 animals. Genomic heritability for all metabolites was estimated using genomic best linear unbiased prediction (GBLUP) including genomic breed composition as covariates in the model. A single-step GBLUP implemented in BLUPF90 programs was used to determine SNP P values and the proportion of genetic variance explained by SNP windows containing 10 consecutive SNPs. The top 10 SNP windows that explained the largest genetic variation for each metabolite were identified and mapped to detect corresponding candidate genes. Functional enrichment analyses were performed on metabolites and their candidate genes using the Ingenuity Pathway Analysis software. Eleven metabolites showed low to moderate heritability that ranged from 0.09 ± 0.15 to 0.36 ± 0.15, while heritability estimates for 22 metabolites were zero or negligible. This result indicates that while variations in 11 metabolites were due to genetic variants, the majority are largely influenced by environment. Three significant SNP associations were detected for betaine (rs109862186), L-alanine (rs81117935), and L-lactic acid (rs42009425) based on Bonferroni correction for multiple testing (family wise error rate <0.05). The SNP rs81117935 was found to be located within the Catenin Alpha 2 gene (CTNNA2) showing a possible association with the regulation of L-alanine concentration. Other candidate genes were identified based on additive genetic variance explained by SNP windows of 10 consecutive SNPs. The observed heritability estimates and the candidate genes and networks identified in this study will serve as baseline information for research into the utilization of plasma metabolites for genetic improvement of crossbred beef cattle.

Keywords: candidate genes; crossbred beef cattle; functional enrichment analyses; metabolomics; single-step GBLUP.