Phenotypic and Genetic Aspects of Fertility in Beef Heifers
Type of DegreePhD Dissertation
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Reproductive success of a heifer’s first breeding season is highly critical to the sustainability of beef cattle production systems. Therefore, multiple management practices exist to ensure heifers are properly developed for a successful first breeding season. However, first breeding season pregnancy rates might not exceed 85-90%. Increased understanding of the nature of beef heifer fertility is essential to further improve heifer pregnancy rates. Therefore, we sought to further characterize phenotypes and genetic characteristics of replacement heifers with varied fertility potential. We performed 2 studies to test the hypothesis that production records and bloodborne RNA profiles would differ among beef heifers that conceived to first service artificial insemination (AI-pregnant), conceived to natural breeding (NB-pregnant), or failed to become pregnant (Not-pregnant) in the first breeding season. In our first study, we curated records for age, weaning weight, reproductive tract score (RTS; scale of 1-5 where 1=prepubertal and 5=pubertal, luteal phase), and body condition score (BCS; scale of 1-9 where 1=emaciated and 9=obese) on 259 heifers that were pre-selected at BCS≥4 and RTS≥3 at the start of their first breeding season. None of the parameters tested displayed predictive ability to discriminate among AI-pregnant, NB-pregnant, and Not-pregnant heifers (P>0.05). The results highlight the need for additional methods to identify heifers of different reproductive potential before the start of the first breeding season. Therefore, in study 2 we generated RNA-sequencing data from peripheral white blood cells (PWBC) collected at the time of AI from 23 heifers and determined differential gene expression profiles for 12,538 genes. We detected 18 differentially expressed genes (DEGs) between AI-pregnant and NB-pregnant heifers and 6 DEGs between AI-pregnant and Not-pregnant heifers. Then, we utilized to top scoring pair technique to classify heifers of different pregnancy outcomes based upon the expression ratios of all possible gene pairs. There were 88 and 1,520 pairs of genes whose expression ratios categorized AI-pregnant heifers separately from Not-pregnant and NB-pregnant heifers, respectively. Additionally, relative expression levels from 2 gene pairs correctly classified 10 of 12 AI-pregnant heifers separately from NB-pregnant and Not-pregnant heifers. Therefore, we conclude that differential expression of specific genes in PWBC at the time of AI is associated with beef heifer fertility. Circulating transcript profiles have potential to classify beef heifers according to first breeding season pregnancy outcome.