Abstract
With the decrease in fertility in dairy cow, the interest towards means to control this variable through genetic selection is growing. One of the most important factors controlling follicular maturity and timely ovulation is the aromatase enzyme, which is encoded by the CYP19A1 gene. The activity of this enzyme is potentially the limiting factor in postpartum fertility. In this study, we developed a methodology, based on genetical genomics, to model the aromatase expression profile from granulosa cell samples. The transcriptomic expression profiles obtained were used to identify 355 genes or isoforms potentially associated with the regulation of aromatase. From those genes, 23,388 single-nucleotide polymorphism (SNPs) in the genome of Holstein cows were identified. Results showed that some SNPs (on KRT8, LHCGR, CREB, ANXA1, and on CYP19A1 itself) were relevant to aromatase expression and the model generated could predict 44% of the observed phenotype. This study demonstrated the value of genetical genomics to generate better biomarkers for the dairy industry.
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