Bioinformatics and gene network analyses of the swine mammary gland transcriptome during late gestation

Wangsheng Zhao, Khuram Shahzad, Mingfeng Jiang, Daniel E. Graugnard, Sandra L. Rodriguez-Zas, Jun Luo, Juan J. Loor, Walter L. Hurley

Research output: Contribution to journalArticle

Abstract

We used the newly-developed Dynamic Impact Approach (DIA) and gene network analysis to study the sow mammary transcriptome at 80, 100, and 110 days of pregnancy. A swine oligoarray with 13,290 inserts was used for transcriptome profiling. An ANOVA with false discovery rate (FDR < 0.15) correction resulted in 1,409 genes with a significant time effect across time comparisons. The DIA uncovered that Fatty acid biosynthesis, Interleukin-4 receptor binding, Galactose metabolism, and mTOR signaling were among the most-impacted pathways. IL-4 receptor binding, ABC transporters, cytokine-cytokine receptor interaction, and Jak-STAT signaling were markedly activated at 110 days compared with 80 and 100 days. Epigenetic and transcription factor regulatory mechanisms appear important in coordinating the final stages of mammary development during pregnancy. Network analysis revealed a crucial role for TP53, ARNT2, E2F4, and PPARG. The bioinformatics analyses revealed a number of pathways and functions that perform an irreplaceable role during late gestation to farrowing.

Original languageEnglish (US)
Pages (from-to)193-216
Number of pages24
JournalBioinformatics and Biology Insights
Volume7
DOIs
StatePublished - Jul 19 2013

Keywords

  • Dynamic impact approach
  • Mammary gland
  • Sow
  • Systems biology
  • Transcriptomics

ASJC Scopus subject areas

  • Biochemistry
  • Molecular Biology
  • Computer Science Applications
  • Computational Mathematics
  • Applied Mathematics

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