Genome Wide Scan to Identify Potential Genomic Regions Associated With Milk Protein and Minerals in Vrindavani Cattle

Abstract

In this study, genome-wide association study (GWAS) was conducted for identifying significantly associated genomic regions/SNPs with milk protein and minerals in the 96 taurine-indicine crossbred (Vrindavani) cows using 50K SNP Chip. After quality control, a total of 41,427 SNPs were retained and were further analyzed using a single-SNP additive linear model. Lactation stage, parity, test day milk yield and proportion of exotic inheritance were included as fixed effects in GWAS model. Across all traits, 13 genome-wide significant (p < 1.20 x 10−06) and 49 suggestive significant (p < 2.41 x 10−05) SNPs were identified which were located on 18 different autosomes. The strongest association for protein percentage, calcium (Ca), phosphorus (P), copper (Cu), zinc (Zn), and iron (Fe) were found on BTA 18, 7, 2, 3, 14, and 2, respectively. No significant SNP was detected for manganese (Mn). Several significant SNPs identified were within or close proximity to CDH13, BHLHE40, EDIL3, HAPLN1, INHBB, USP24, ZFAT, and IKZF2 gene, respectively. Enrichment analysis of the identified candidate genes elucidated biological processes, cellular components, and molecular functions involved in metal ion binding, ion transportation, transmembrane protein, and signaling pathways. This study provided a groundwork to characterize the molecular mechanism for the phenotypic variation in milk protein percentage and minerals in crossbred cattle. Further work is required on a larger sample size with fine mapping of identified QTL to validate potential candidate regions.

Unraveling the Genomic Association for Milk Production Traits and Signatures of Selection of Cattle in a Harsh Tropical Environment

“…FBRSL1 was significantly associated with milk yield in Chinese Holstein cows based on a GWAS for haplotypes [7]. In another genome-wide scan conducted on a tropically adapted Indian composite crossbred dairy cattle breed (Vrindavani cattle), the CACN gene was significantly associated with milk copper content [8].…”

“…Furthermore, GWASs also contribute to identifying potential candidate genes associated with economic and resilience traits. Several researchers adopted such methodologies to identify potential candidate genes and signatures of selection [7,8].…”

Genome-Wide Association Studies, Runs of Homozygosity Analysis, and Copy Number Variation Detection to Identify Reproduction-Related Genes in Bama Xiang Pigs

“…where y is an n -vector of reproduction traits, W is a matrix of fixed effects including three principal constituents and the parity effect, x is the SNP genotype, α and β are the corresponding coefficients, u is the random effect, ε is the random error, τ −1 is the variance of residual errors, λ is the ratio between the two variance components, K is the kinship matrix, In is the n × n identity matrix, and MVN n denotes the n -dimensional multivariate normal distribution. Thresholds for Bonferroni-adjusted genome-wide significance and suggestive significance were defined as –log 10 ( p ) = 5.68 (0.05/24,123) and –log 10 ( p ) = 4.38 (1/24,123), respectively ( 27 – 29 ). We defined the 200 kb regions upstream and downstream of the saliency marker as significant for identifying genes in the Biomart program ( Sus scrofa 10.2 ).…”

“…The Q and K matrices were calculated by SNP array data using Tassel software. According to the Bonferroni thresholds of GWAS, we defined p = 0.001 (0.05/50) and p = 0.02 (1/50) as the significance thresholds and suggestive significance thresholds, respectively ( 27 – 29 ). The significance and suggestive significance HCNVRs were annotated using the BioMart program.…”