Identification of pig reproductive QTL genes based on gene set enrichment analysis of mouse microarray dataset

Abstract


Kan He, Fan Yang, Minghui Wang, Qishan Wang, Yuchun Pan and Yufang Ma

Nowadays, abundantly different transcripts related to reproductive traits using mouse model have been identified by microarray analysis with the robustness, which were needed of re-evaluation with quantitive real time PCR (qPCR). Meanwhile, pig QTL databases were established but with large spans in the confidence interval for QTL location. Therefore, a genome-wide comparative and functional analysis of the association between mouse microarrays analysis results and reported pig QTLs is needed to better elucidate the genetic and physiological background of pig enhanced reproductive performance in genomics. Here, we employed a microarray dataset of a high fertility mouse line and applied gene set enrichment analysis method to identify significant mouse genes in a pathway level. Next we used a comparative genomic approach to find the homologous pig genes and locate them to the interval of the reported QTL for pigs’ traits based on AnimalQTLdb. Finally, we identified some pathways participating in pig high fertility, and some pig genes were further identified within the reported QTL location related to reproductive performance. Combining microarray analysis of mouse high fertility dataset by GSEA with pigQTLdb will substantially help us to identify candidate genes in reported QTL regions related to pig reproduction that are eventually responsible for increased fertility performance in pig and are also helpful for understanding the genetic information of pig reproduction in genomics. Furthermore, we can also provide some novel pig genes in identified pathways with relationship of reproduction.

Share this article

Awards Nomination

Select your language of interest to view the total content in your interested language

Indexed In
  • Index Copernicus
  • Google Scholar
  • Sherpa Romeo
  • Open J Gate
  • Academic Keys
  • ResearchBible
  • CiteFactor
  • Electronic Journals Library
  • Centre for Agriculture and Biosciences International (CABI)
  • OCLC- WorldCat
  • Universitat Vechta Library
  • GEOMAR Library Ocean Research Information Access
  • OPAC
  • WZB
  • ZB MED
  • German National Library of Science and Technology
  • Paperpile
  • Universitat Hamburg Library