Genome Wide Association Studies for Milk Production Traits in Chinese Holstein Population

Abstract

Genome-wide association studies (GWAS) based on high throughput SNP genotyping technologies open a broad avenue for exploring genes associated with milk production traits in dairy cattle. Motivated by pinpointing novel quantitative trait nucleotide (QTN) across Bos Taurus genome, the present study is to perform GWAS to identify genes affecting milk production traits using current state-of-the-art SNP genotyping technology, i.e., the Illumina BovineSNP50 BeadChip. In the analyses, the five most commonly evaluated milk production traits are involved, including milk yield (MY), milk fat yield (FY), milk protein yield (PY), milk fat percentage (FP) and milk protein percentage (PP). Estimated breeding values (EBVs) of 2,093 daughters from 14 paternal half-sib families are considered as phenotypes within the framework of a daughter design. Association tests between each trait and the 54K SNPs are achieved via two different analysis approaches, a paternal transmission disequilibrium test (TDT)-based approach (L1-TDT) and a mixed model based regression analysis (MMRA). In total, 105 SNPs were detected to be significantly associated genome-wise with one or multiple milk production traits. Of the 105 SNPs, 38 were commonly detected by both methods, while four and 63 were solely detected by L1-TDT and MMRA, respectively. The majority (86 out of 105) of the significant SNPs is located within the reported QTL regions and some are within or close to the reported candidate genes. In particular, two SNPs, ARS-BFGL-NGS-4939 and BFGL-NGS-118998, are located close to the DGAT1 gene (160bp apart) and within the GHR gene, respectively. Our findings herein not only provide confirmatory evidences for previously findings, but also explore a suite of novel SNPs associated with milk production traits, and thus form a solid basis for eventually unraveling the causal mutations for milk production traits in dairy cattle.

Maximum difference analysis: a new empirical method for genome-wide association studies

“…The MDA approach was able to detect a total of 479 significant SNPs across the entire genome. A similar number of associated SNPs was obtained in analogue studies developed by using common GWAS approaches Jiang et al 2010;Mai et al 2010). The distribution of SNPs across the 29 autosomes and their positions was generally in agreement with results reported in literature (Jiang et al 2010;Meredith et al 2012).…”

“…A similar number of associated SNPs was obtained in analogue studies developed by using common GWAS approaches Jiang et al 2010;Mai et al 2010). The distribution of SNPs across the 29 autosomes and their positions was generally in agreement with results reported in literature (Jiang et al 2010;Meredith et al 2012). The number of significant markers detected for each trait seems to reflect the known genetic architecture of traits: a higher number of significant SNPs were found for yield compared to composition traits.…”

“…Many association studies identified QTLs affecting FY and FP in the centromeric region of BTA14 Jiang et al 2010;Meredith et al 2012). The DGAT1 locus is an enzyme that catalyses the synthesis of diacylglycerols involved in several biological processes (Mai et al 2010).…”

Disentangling Prenatal and Postnatal Maternal Genetic Effects Reveals Persistent Prenatal Effects on Offspring Growth in Mice

“…Although this pleiotropic link between maternal and offspring traits must exist at some level (i.e., maternal effects must ultimately be caused by some feature of the mothers), we know very little about the connection from maternal loci to offspring trait variation through a set of known maternal traits. Maternal traits like milk quality characteristics, which may be largely responsible for maternal effects on offspring growth traits in livestock species (Meyer et al 1994), have been successfully mapped in various livestock species (e.g., Gutierrez-Gil et al 2009;Jiang et al 2010), making such loci candidates for maternal effects on offspring developmental traits. However, searches for candidate genes associated with obvious maternal traits, such as lactation, nursing, or nesting traits, in the intervals around the maternal-effect loci we identified did not yield any specific candidate genes, which is perhaps not surprising since these traits have few identified candidates in the genome (Blake et al 2011).…”

SNPs genotyping technologies and their applications in farm animals breeding programs: review

“…Australia has taken the lead in identifying the genomic regions associated with milk production (Bolormaa et al 2010;Pryce et al 2010). Several studies have also been completed in the United States and Canada (Wiggans et al 2009;Cole et al 2011) and China (Jiang et al 2010). Recently, Fulton (2012) has discussed several challenges in the application of genomic information.…”