Single gene and gene interaction effects on fertilization and embryonic survival rates in cattle

Abstract

Decrease in fertility and conception rates is a major cause of economic loss and cow culling in dairy herds. Conception rate is the product of fertilization rate and embryonic survival rate. Identification of genetic factors that cause the death of embryos is the first step in eliminating this problem from the population and thereby increasing reproductive efficiency. A candidate pathway approach was used to identify candidate genes affecting fertilization and embryo survival rates using an in vitro fertilization experimental system. A total of 7,413 in vitro fertilizations were performed using oocytes from 504 ovaries and semen samples from 10 different bulls. Fertilization rate was calculated as the number of cleaved embryos 48 h postfertilization out of the total number of oocytes exposed to sperm. Survival rate of embryos was calculated as the number of blastocysts on d 7 of development out of the number of total embryos cultured. All ovaries were genotyped for 8 genes in the POU1F1 signaling pathway. Single-gene analysis revealed significant associations of GHR, PRLR, STAT5A, and UTMP with survival rate and of POU1F1, GHR, STAT5A, and OPN with fertilization rate. To further characterize the contribution of the entire integrated POU1F1 pathway to fertilization and early embryonic survival, a model selection procedure was applied. Comparisons among the different models showed that interactions between adjacent genes in the pathway revealed a significant contribution to the variation in fertility traits compared with other models that analyzed only bull information or only genes without interactions. Moreover, some genes that were not significant in the single-gene analysis showed significant effects in the interaction analysis. Thus, we propose that single genes as well as an entire pathway can be used in selection programs to improve reproduction performance in dairy cattle.

Interactions of the bovine placental lactogen and prolactin receptor genes are associated with fertility traits in cattle

“…Although single gene analysis of bPL did not reveal significant association with either trait, its interaction with PRLR showed significant association with fertilization rate and suggestive association with survival rate. This is a further support of the significant contribution of SNP-SNP interactions between biologically interacting genes to these fertility traits in cattle (Khatib et al, 2009). In addition, it could justify the use of genotypic combination of interacting genes in markerassisted selection programs to improve fertility in cattle.…”

“…Because of their biological interaction, SNP-SNP interaction between bPL and PRLR was also tested for association with fertilization and survival rates. As single SNPs, the SNP in PRLR was not associated with fertilization rate or survival rate, whereas the SNP in GHR was significantly associated with survival rate but not fertilization rate (Khatib et al, 2009). Interestingly, the genotypic effect of the bPL SNP depended on the genotype of PRLR, an indication of genetic interaction or epistasis.…”

“…Indeed, using an IVF system developed in our laboratory, single-nucleotide polymorphisms (SNPs) in several genes have been successfully shown to be associated with fertilization rate and early embryonic survival rate (Khatib et al, 2008a and2008b). Importantly, SNP-SNP interactions between biologically interacting genes in the same signaling pathway were also found to contribute significantly to fertilization and early embryonic development (Khatib et al, 2009).Placental lactogen or chorionic somatomammotropin hormone 1 (CSH1), is a polypeptide hormone found in the placenta of mammals. It is structurally and functionally related to prolactin (PRL) and growth hormone (GH), two pituitary-derived hormones.…”

“…The C allele appeared as 35-bp and 202-bp bands and the T allele was one intact band. Genotypes of PRLR (Blott et al, 2003) and GHR (Viitala et al, 2006) were obtained in an earlier study (Khatib et al, 2009) using similar PCR-RFLP approaches but different restriction enzymes.To test the association between the bPL SNP and fertilization and survival rates, the following generalized linear mixed model was used to model the binary response of successful fertilization of oocytes or survival of embryos up to the blastocyst stage with a linear combination of predictors:where b 1i is the fixed effect of genotype i for the bPL SNP, Bull j is the random effect of the jth bull and Ovary k is the random effect of the kth ovary, which is nested within genotype of bPL SNP. The response variable was coded as binary ('1' for successful fertilization; '0' otherwise and '1' for normal development to blastocyst stage; '0' otherwise, respectively).…”

“…However, the differences in fertilization rates or survival rates did not reach statistical significance (Table 1). In addition to single SNP associations, SNP-SNP interactions between genes in the same signaling pathway have also been shown to contribute significantly to the variation in fertilization rate and survival rate (Khatib et al, 2009). Because of their biological interaction, SNP-SNP interaction between bPL and PRLR was also tested for association with fertilization and survival rates.…”