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Type: Journal article
Title: Placental transcriptome co-expression analysis reveals conserved regulatory programs across gestation
Author: Buckberry, S.
Bianco-Miotto, T.
Bent, S.
Clifton, V.
Shoubridge, C.
Shankar, K.
Roberts, C.
Citation: BMC Genomics, 2017; 18(1):10-1-10-13
Publisher: BioMed Central Ltd
Issue Date: 2017
ISSN: 1471-2164
Statement of
Sam Buckberry, Tina Bianco-Miotto, Stephen J. Bent, Vicki Clifton, Cheryl Shoubridge, Kartik Shankar and Claire T. Roberts
Abstract: Background: Mammalian development in utero is absolutely dependent on proper placental development, which is ultimately regulated by the placental genome. The regulation of the placental genome can be directly studied by exploring the underlying organisation of the placental transcriptome through a systematic analysis of gene-wise co-expression relationships. Results: In this study, we performed a comprehensive analysis of human placental co-expression using RNA sequencing and intergrated multiple transcriptome datasets spanning human gestation. We identified modules of co-expressed genes that are preserved across human gestation, and also identifed modules conserved in the mouse indicating conserved molecular networks involved in placental development and gene expression patterns more specific to late gestation. Analysis of co-expressed gene flanking sequences indicated that conserved co-expression modules in the placenta are regulated by a core set of transcription factors, including ZNF423 and EBF1. Additionally, we identified a gene co-expression module enriched for genes implicated in the pregnancy pathology preeclampsia. By using an independnet transcriptome dataset, we show that these co-expressed genes are differentially expressed in preeclampsia. Conclusions: This study represents a comprehensive characterisation of placental co-expression and provides insight into potential transcriptional regulators that govern conserved molecular programs fundamental to placental development.
Keywords: RNA-seq; placenta; preeclampsia; co-expression; gene expression; microarray
Rights: © The Author(s). 2017 Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (, which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver ( applies to the data made available in this article, unless otherwise stated.
DOI: 10.1186/s12864-016-3384-9
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