Whole-transcriptome analysis delineates the human placenta gene network and its associations with fetal growth

• Authors: Maya A. Deyssenroth, Icahn School of Medicine at Mount Sinai; Shouneng Peng, Icahn School of Medicine at Mount Sinai; Ke Hao, Icahn School of Medicine at Mount Sinai; Luca Lambertini, Icahn School of Medicine at Mount Sinai; Carmen Marsit, Emory University; Jia Chen, Icahn School of Medicine at Mount Sinai
• Journal Title: BMC Genomics
• Volume: Volume 18, Number 1
• Publisher: BioMed Central | 2017-07-10, Pages 520-520
• Type of Work: Article | Final Publisher PDF
• Publisher DOI: http://doi.org/10.1186/s12864-017-3878-0
• Subjects: Health Sciences, Oncology; Health Sciences, Obstetrics and Gynecology
• Keywords: Birth weight; Placenta; RNA-Seq; WGCNA

Abstract

Background: The placenta is the principal organ regulating intrauterine growth and development, performing critical functions on behalf of the developing fetus. The delineation of functional networks and pathways driving placental processes has the potential to provide key insight into intrauterine perturbations that result in adverse birth as well as later life health outcomes. Results: We generated the transcriptome-wide profile of 200 term human placenta using the Illumina HiSeq 2500 platform and characterized the functional placental gene network using weighted gene coexpression network analysis (WGCNA). We identified 17 placental coexpression network modules that were dominated by functional processes including growth, organ development, gas exchange and immune response. Five network modules, enriched for processes including cellular respiration, amino acid transport, hormone signaling, histone modifications and gene expression, were associated with birth weight; hub genes of all five modules (CREB3, DDX3X, DNAJC14, GRHL1 and C21orf91) were significantly associated with fetal growth restriction, and one hub gene (CREB3) was additionally associated with fetal overgrowth. Conclusions: In this largest RNA-Seq based transcriptome-wide profiling study of human term placenta conducted to date, we delineated a placental gene network with functional relevance to fetal growth using a network-based approach with superior scale reduction capacity. Our study findings not only implicate potential molecular mechanisms underlying fetal growth but also provide a reference placenta gene network to inform future studies investigating placental dysfunction as a route to future disease endpoints.