Endometrial gene expression profile of pregnant sows with extreme phenotypes for reproductive efficiency

Sci Rep. 2015 Oct 5;5:14416. doi: 10.1038/srep14416.


Prolificacy can directly impact porcine profitability, but large genetic variation and low heritability have been found regarding litter size among porcine breeds. To identify key differences in gene expression associated to swine reproductive efficiency, we performed a transcriptome analysis of sows' endometrium from an Iberian x Meishan F2 population at day 30-32 of gestation, classified according to their estimated breeding value (EBV) as high (H, EBV > 0) and low (L, EBV < 0) prolificacy phenotypes. For each sample, mRNA and small RNA libraries were RNA-sequenced, identifying 141 genes and 10 miRNAs differentially expressed between H and L groups. We selected four miRNAs based on their role in reproduction, and five genes displaying the highest differences and a positive mapping into known reproductive QTLs for RT-qPCR validation on the whole extreme population. Significant differences were validated for genes: PTGS2 (p = 0.03; H/L ratio = 3.50), PTHLH (p = 0.03; H/L ratio = 3.69), MMP8 (p = 0.01; H/L ratio =4.41) and SCNN1G (p = 0.04; H/L ratio = 3.42). Although selected miRNAs showed similar expression levels between H and L groups, significant correlation was found between the expression level of ssc-miR-133a (p < 0.01) and ssc-miR-92a (p < 0.01) and validated genes. These results provide a better understanding of the genetic architecture of prolificacy-related traits and embryo implantation failure in pigs.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Animals
  • Breeding
  • Endometrium / metabolism*
  • Female
  • Gene Ontology
  • Gene Regulatory Networks
  • Genetic Association Studies
  • MicroRNAs / genetics
  • MicroRNAs / metabolism
  • Molecular Sequence Annotation
  • Phenotype
  • Pregnancy
  • Quantitative Trait Loci
  • RNA Interference
  • Sus scrofa / genetics*
  • Sus scrofa / metabolism
  • Transcriptome


  • MicroRNAs