Genome-wide association study for endocrine fertility traits using single nucleotide polymorphism arrays and sequence variants in dairy cattle

Abstract

Endocrine fertility traits, which are defined from progesterone concentration levels in milk, are interesting indicators of dairy cow fertility because they more directly reflect the cows own reproductive physiology than classical fertility traits, which are more biased by farm management decisions. The aim of this study was to detect quantitative trait loci (QTL) for 7 endocrine fertility traits in dairy cows by performing a genome-wide association study with 85k single nucleotide polymorphisms (SNP), and then fine-map targeted QTL regions, using imputed sequence variants. Two classical fertility traits were also analyzed for QTL with 85k SNP. The association between a SNP and a phenotype was assessed by single-locus regression for each SNP, using a linear mixed model that included a random polygenic effect. A total of 2,447 Holstein Friesian cows with 5,339 lactations with both phenotypes and genotypes were used for association analysis. Heritability estimates ranged from 0.09 to 0.15 for endocrine fertility traits and 0.03 to 0.10 for classical fertility traits. The genome-wide association study identified 17 QTL regions for endocrine fertility traits on Bos taurus autosomes (BTA) 2, 3, 8, 12, 15, 17, 23, and 25. The highest number (5) of QTL regions from the genome-wide association study was identified for the endocrine trait "proportion of samples with luteal activity." Overlapping QTL regions were found between endocrine traits on BTA 2, 3, and 17. For the classical trait calving to first service, 3 QTL regions were identified on BTA 3, 15, and 23, and an overlapping region was identified on BTA 23 with endocrine traits. Fine-mapping target regions for the endocrine traits on BTA 2 and 3 using imputed sequence variants confirmed the QTL from the genome-wide association study, and identified several associated variants that can contribute to an index of markers for genetic improvement of fertility. Several potential candidate genes underlying endocrine fertility traits were also identified in the target regions and are discussed. However, due to high linkage disequilibrium, it was not possible to specify genes or polymorphisms as causal factors for any of the regions.

A Genome-Wide Association Study for Calving Interval in Holstein Dairy Cows Using Weighted Single-Step Genomic BLUP Approach

“…The estimated additive, permanent environmental effect, and residual variances in multiparous cows were 198.3 (67.8), 71.4 (100.4), and 2953.7 (103.15), respectively. The heritability estimates for the length of the CI in primi-and multiparous cows were 0.05 (0.01) and 0.06 (0.01), respectively, which are consistent with findings from other studies on dairy cattle [17,[30][31][32][33]. Generally, the large unexplained residual variation observed for the length of the CI is attributable not only to the large effect of the environmental factors on this trait but also to the low quality of the data [34].…”

Genome-wide association study of normal and atypical progesterone profiles in Holstein-Friesian dairy cows

“…Berry et al (2012) also found significant SNP associated with CFH on BTA8, but this was not at the same position as in the present study. Tenghe et al (2016) reported significant SNP associated with LPL on BTA3 and BTA17, whereas in the present study we found interesting regions for IOI on the same chromosomes. As IOI combines information from LPL and ILI, this may suggest that the same genes influence both IOI and LPL.…”

“…To date, no QTL region has been reported for C-LA on BTA8, BTA17, and BTA23. Earlier studies have reported significant associations with C-LA on other chromosomes; for example, Berry et al (2012) and Tenghe et al (2016) detected a QTL region associated with C-LA on BTA2. Although we used different methods, we found the same significant SNP on BTA2 in this study as was found by Berry et al (2012).…”

“…Berry et al (2012) found clear associations with C-LA on BTA2 and on BTA21. Furthermore, Tenghe et al (2016) reported regions on BTA2 and BTA3 (among others) that are likely to include mutations associated with C-LA, interval from C-LA to first insemination, luteal phase length (LPL), inter-ovulatory interval (IOI), and CFS (among other traits). One challenge when working with low heritability traits is that GWAS requires a large number of individuals with phenotype and genotype information (Olsen et al, 2011).…”

Meta-analysis of sequence-based association studies across three cattle breeds reveals 25 QTL for fat and protein percentages in milk at nucleotide resolution

“…Although sequence-based association studies uncovered many QTL (e.g., [9][10][11]), little is known regarding their molecular-genetic underpinnings because the characterization of putatively causal variants was rarely attempted (e.g., [5,12,13]).…”