Genome-wide association study and annotating candidate gene networks affecting age at first calving in Nellore cattle.

We performed a genome-wide mapping for the age at first calving (AFC) with the goal of annotating candidate genes that regulate fertility in Nellore cattle. Phenotypic data from 762 cows and 777k SNP genotypes from 2,992 bulls and cows were used. Single nucleotide polymorphism (SNP) effects based on the single-step GBLUP methodology were blocked into adjacent windows of 1 Megabase (Mb) to explain the genetic variance. SNP windows explaining more than 0.40% of the AFC genetic variance were identified on chromosomes 2, 8, 9, 14, 16 and 17. From these windows, we identified 123 coding protein genes that were used to build gene networks. From the association study and derived gene networks, putative candidate genes (e.g., PAPPA, PREP, FER1L6, TPR, NMNAT1, ACAD10, PCMTD1, CRH, OPKR1, NPBWR1 and NCOA2) and transcription factors (TF) (STAT1, STAT3, RELA, E2F1 and EGR1) were strongly associated with female fertility (e.g., negative regulation of luteinizing hormone secretion, folliculogenesis and establishment of uterine receptivity). Evidence suggests that AFC inheritance is complex and controlled by multiple loci across the genome. As several windows explaining higher proportion of the genetic variance were identified on chromosome 14, further studies investigating the interaction across haplotypes to better understand the molecular architecture behind AFC in Nellore cattle should be undertaken.

Gene expression in swine granulosa cells and ovarian tissue during the estrous cycle.

The components of the insulin-like growth factor (IGF) system appear to be involved in regulation of ovarian follicular growth and atresia in the pig. We investigated the expression pattern of mRNAs for IGF1 (IGF1), its binding proteins (IGFBP1, IGFBP2, IGFBP3, and IGFBP5), and epidermal growth factor in swine follicle cells and ovarian tissue throughout the estrous cycle using the real-time quantitative PCR technique. The results of gene expression were analyzed using linear regression with gene expression as a dependent variable and days of estrous cycle as an independent variable. Additionally, an analysis was made of the correlation of expression levels with plasma concentration of follicle-stimulating hormone, luteinizing hormone, estradiol-17ß, progesterone, and prolactin. Expression of mRNA of all of these genes was detected in granulosa cells and ovarian tissue. IGFBP3 mRNA showed a quadratic expression pattern (P ≤ 0.001) and was significantly and positively correlated with progesterone (r = 0.81; P ≤ 0.01) but negatively correlated with prolactin (r = -0.596; P ≤ 0.05). Expression of the other genes was unaffected by the stage of the estrous cycle. Real-time quantitative PCR effectively detected all transcripts, including the very low levels of IGFBP1 transcripts, and could be used for studies of follicle dynamics.