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Integration of whole-genome DNA methylation data with RNA sequencing data to identify markers for bull fertility.

Nicole GrossFrancisco PeñagaricanoHasan Khatib
Published in: Animal genetics (2020)
Predicting bull fertility prior to breeding is a current challenge for the dairy industry. The use of molecular biomarkers has been previously assessed. However, the integration of this information has not been performed to extract biologically relevant markers. The goal of this study was to integrate DNA methylation data with previously published RNA-sequencing results in order to identify candidate markers for sire fertility. A total of 1765 differentially methylated cytosines were found between high- and low-fertility sires. Ten genes associated with 11 differentially methylated cytosines were found in a previous study of gene expression between high- and low-fertility sires. Additionally, two of these genes code for proteins found exclusively in bull seminal plasma. Collectively, our results reveal 10 genes that could be used in the future as a panel for predicting bull fertility.
Keyphrases
  • dna methylation
  • genome wide
  • gene expression
  • childhood cancer
  • single cell
  • electronic health record
  • big data
  • randomized controlled trial
  • oxidative stress
  • machine learning
  • single molecule
  • anti inflammatory