Genome-wide association studies of fertility and calving traits in Brown Swiss cattle using imputed whole-genome sequences

Abstract

Background: The detection of quantitative trait loci has accelerated with recent developments in genomics. The introduction of genomic selection in combination with sequencing efforts has made a large amount of genotypic data available. Functional traits such as fertility and calving traits have been included in routine genomic estimation of breeding values making large quantities of phenotypic data available for these traits. This data was used to investigate the genetics underlying fertility and calving traits and to identify potentially causative genomic regions and variants. We performed genome-wide association studies for 13 functional traits related to female fertility as well as for direct and maternal calving ease based on imputed whole-genome sequences. Deregressed breeding values from~1000-5000 bulls per trait were used to test for associations with approximately 10 million imputed sequence SNPs. Results: We identified a QTL on BTA17 associated with non-return rate at 56 days and with interval from first to last insemination. We found two significantly associated non-synonymous SNPs within this QTL region. Two more QTL for fertility traits were identified on BTA25 and 29. A single QTL was identified for maternal calving traits on BTA13 whereas three QTL on BTA19, 21 and 25 were identified for direct calving traits. The QTL on BTA19 co-localizes with the reported BH2 haplotype. The QTL on BTA25 is concordant for fertility and calving traits and co-localizes with a QTL previously reported to influence stature and related traits in Brown Swiss dairy cattle. Conclusion: The detection of QTL and their causative variants remains challenging. Combining comprehensive phenotypic data with imputed whole genome sequences seems promising. We present a QTL on BTA17 for female fertility in dairy cattle with two significantly associated non-synonymous SNPs, along with five additional QTL for fertility traits and calving traits. For all of these we fine mapped the regions and suggest candidate genes and candidate variants.

Genetic architecture of quantitative traits in beef cattle revealed by genome wide association studies of imputed whole genome sequence variants: I: feed efficiency and component traits

“…Therefore, an alternative way is to impute genotypes of individuals from low density DNA markers to whole genome sequence (WGS) variants. The improved power of GWAS based on imputed WGS variants was reported in studies on milk protein composition in dairy cattle [22], lumbar number in Sutai pigs [23], fertility and calving traits in Brown Swiss cattle [24], and milk fat percentage in Fleckvieh and Holstein cattle [25]. In this study, we imputed 50 K SNP genotypes to whole genome sequence variants and investigated the effect for each of imputed 7,853,211 DNA variants (SNPs and INDELs) based on a sample of 7573 Canadian beef cattle, with an aim to elucidate genetic architectures of RFI and its component traits DMI, ADG, and MWT.…”

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

“…Genomic information can be used to improve the accuracy of breeding values and to perform genome-wide association studies (GWAS) with the aim of identifying genomic region(s) explaining genetic variance of traits. Although, genome-wide association studies carried out within a variety of cattle breeds identified many single nucleotide polymorphisms (SNPs) associated with the length of the calving interval (CI), as an indicator for reproductive performance, they are mainly based on the polygenic estimated breeding value (EBV), daughter yield deviation (DYD), or deregressed proof for CI [4,[17][18][19]. The single-step genomic best linear unbiased prediction (ssGBLUP) approach [20,21], a quite common procedure in GWAS, has the advantage of simultaneously using the phenotypes of genotyped and nongenotyped animals, pedigrees, and genotypes; therefore, there is no need to calculate pseudo-phenotypes.…”

Association of lipid-related genes implicated in conceptus elongation with female fertility traits in dairy cattle

“…During elongation of the preimplantation conceptus, the rapid proliferation and intense metabolism of conceptus cells might generate a high level of reactive oxygen species in the uterine lumen, which need to be controlled by enzymes such as catalase. A SNP close to this region was previously identified on BTA15 at 64.1 Mb for days to first service in Brown Swiss cattle (Frischknecht et al, 2017). In addition, Peñagaricano et al (2012) reported the presence of a SNP 251 kb from the 65.8 Mb region on BTA15 that was significantly associated with sire conception rate in Holstein dairy cattle.…”

“…On BTA25, our study detected a synonymous SNP at 3.65 Mb near HMOX2; this marker was associated with all 3 fertility traits evaluated in Holstein bulls (DPR, CCR, and HCR) and with SF in lactating cows. Frischknecht et al (2017) also reported a SNP on BTA25 at 1.5 Mb, associated with days to first service and interval between first and last insemination in Brown Swiss cattle. Heme oxygenase 2 is 1 of 2 heme oxygenases (HMOX1 and HMOX2) responsible for the degradation of heme into biliverdin, iron, and carbon monoxide, and it is involved in sensing of oxygen levels and regulation of oxidative stress in multiple tissues (Muñoz-Sánchez and Chánez-Cárdenas, 2014).…”

“…Sahana et al (2010) identified a genomic region on BTA29 at position 46.9-51.9 Mb, close to CHKA, that had significant associations with number of inseminations, interval from first to last insemination, and fertility index in Holstein dairy cattle. Moreover, Frischknecht et al (2017) detected a significant SNP on BTA29, approximately 1 Mb downstream of CHKA, that was associated with days to first service in Brown Swiss cattle. These studies corroborate our results, in which the 2 validated SNP in CHKA were highly associated with DPR and CCR in the bull population and with SF and FertC in the lactating cow population.…”