4.6 Article

Myometrial Transcriptional Signatures of Human Parturition

Journal

FRONTIERS IN GENETICS
Volume 10, Issue -, Pages -

Publisher

FRONTIERS MEDIA SA
DOI: 10.3389/fgene.2019.00185

Keywords

parturition; myometrium; gene expression networks; classification; inflammation

Funding

  1. March of Dimes Ohio Prematurity Research Collaborative
  2. Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Institutes of Health [HD069818]
  3. National Institutes of Health [U01-CA198941]
  4. EUNICE KENNEDY SHRIVER NATIONAL INSTITUTE OF CHILD HEALTH & HUMAN DEVELOPMENT [ZIAHD002400] Funding Source: NIH RePORTER

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The process of parturition involves the transformation of the quiescent myometrium (uterine smooth muscle) to the highly contractile laboring state. This is thought to be driven by changes in gene expression in myometrial cells. Despite the existence of multiple myometrial gene expression studies, the transcriptional programs that initiate labor are not known. Here, we integrated three transcriptome datasets, one novel (NCBI Gene Expression Ominibus: GSE80172) and two existing, to characterize the gene expression changes in myometrium associated with the onset of labor at term. Computational analyses including classification, singular value decomposition, pathway enrichment, and network inference were applied to individual and combined datasets. Outcomes across studies were integrated with multiple protein and pathway databases to build a myometrial parturition signaling network. A high-confidence (significant across all studies) set of 126 labor genes were identified and machine learning models exhibited high reproducibility between studies. Labor signatures included both known (interleukins, cytokines) and unknown (apoptosis, MYC, cell proliferation/differentiation) pathways while cyclic AMP signaling and muscle relaxation were associated with nonlabor. These signatures accurately classified and characterized the stages of labor. The data-derived parturition signaling networks provide new genes/signaling interactions to understand phenotype-specific processes and aid in future studies of parturition.

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