Genome Wide Analysis of Fertility and Production Traits in Italian Holstein Cattle

Abstract

A genome wide scan was performed on a total of 2093 Italian Holstein proven bulls genotyped with 50K single nucleotide polymorphisms (SNPs), with the objective of identifying loci associated with fertility related traits and to test their effects on milk production traits. The analysis was carried out using estimated breeding values for the aggregate fertility index and for each trait contributing to the index: angularity, calving interval, non-return rate at 56 days, days to first service, and 305 day first parity lactation. In addition, two production traits not included in the aggregate fertility index were analysed: fat yield and protein yield. Analyses were carried out using all SNPs treated separately, further the most significant marker on BTA14 associated to milk quality located in the DGAT1 region was treated as fixed effect. Genome wide association analysis identified 61 significant SNPs and 75 significant marker-trait associations. Eight additional SNP associations were detected when SNP located near DGAT1 was included as a fixed effect. As there were no obvious common SNPs between the traits analyzed independently in this study, a network analysis was carried out to identify unforeseen relationships that may link production and fertility traits.

Tissues, Metabolic Pathways and Genes of Key Importance in Lactating Dairy Cattle

“…In two other association studies in Nordic Red dairy cattle using 50 K SNP genotypes imputed into whole-genome sequencing data, several other genes including SLC6A17, SDS5, ADCY1, SLC1A4 and PPM1B associated with cow and heifer non-return rate, calving to first service interval, number of inseminations per conception and days from first to last insemination were identified [57,60]. The TGFB2, APOH and IGLL1 genes were reported as important candidate genes under significant peaks associated with nonreturn rate and days to first service in Italian Holstein cattle [107]. The genes TGFB2 and APOH are both involved in the process of the follicular development as they interact with the reproductive hormones LH and FSH [107].…”

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

“…Allele K (lysine) has a positive effect on the fat content in the milk while the allele A (alanine) on milk yield. Recently, Minozzi et al (2013) during a GWAS using GenABEL R package on Italian Holstein cattle found the same associations highlighted by MDA among markers near DGAT1 and milk traits.…”

“…In dairy cattle, for example, a common outcome is the detection of significant markers mainly located on the BTA14, in the region of the DGAT1 locus. The MDA method was able to indicate a larger number of significant markers in comparison with one of the most popular approaches used in GWAS study, the GenAbel R package (Strucken et al 2012;Minozzi et al 2013). The reliability of the MDA, based on the resampling procedure and on the use of the Chebyshev's inequality, together with the biological soundness of the detected genes, suggests that the obtained results should not be interpreted in terms of an increase of false positives, but as an evidence of the larger power of this method compared to more conservative approaches.…”

First insights in the genetics of caseous lymphadenitis in goats

“…Although the application of genomic technologies, mainly applied in dairy cattle, can decrease the generation interval and boost genetic gain compared with traditional phenotypic selection, it is still important to perform genome wide association studies for infectious diseases to pinpoint and localise the genetic variations that have an effect on health traits, in cases where no effective therapy or prophylaxis are available, as in the case of bovine tuberculosis (Allen et al 2010;Finlay et al 2012;Bermingham et al 2014;Zare et al 2014;Richardson et al 2016) and bovine paratuberculosis (Settles et al 2009;Kirkpatrick et al 2011;Minozzi et al 2012;van Hulzen et al 2012;Alpay et al 2014;Pauciullo et al 2015), allowing the possibility to include the genetic approach as a complementary aid for disease incidence reduction. Recent developments in the animal genome sequencing technologies have allowed the application of a series of methods designed to identify regions of the genome linked or that affect certain characters of economic interest in cattle (e.g., production and/or resistance to diseases in dairy cattle) (Minozzi et al 2013) and in small ruminants, suitable when pedigree information is not available or unreliable. Genome wide association (GWA) studies are now widely used to estimate the association among single nucleotide polymorphisms distributed across the whole genome and one or more traits.…”