The RNA landscape of the human placenta in health and disease

Sungsam Gong, Francesca Gaccioli, Justyna Dopierala, Ulla Sovio, Emma Cook, Pieter-Jan Volders, Lennart Martens, Paul D. W. Kirk, Sylvia Richardson, Gordon C. S. Smith and D. Stephen Charnock-Jones ()
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Sungsam Gong: NIHR Cambridge Biomedical Research Centre
Francesca Gaccioli: NIHR Cambridge Biomedical Research Centre
Justyna Dopierala: NIHR Cambridge Biomedical Research Centre
Ulla Sovio: NIHR Cambridge Biomedical Research Centre
Emma Cook: NIHR Cambridge Biomedical Research Centre
Pieter-Jan Volders: Ghent University
Lennart Martens: Ghent University
Paul D. W. Kirk: University of Cambridge
Sylvia Richardson: University of Cambridge
Gordon C. S. Smith: NIHR Cambridge Biomedical Research Centre
D. Stephen Charnock-Jones: NIHR Cambridge Biomedical Research Centre

Nature Communications, 2021, vol. 12, issue 1, 1-17

Abstract: Abstract The placenta is the interface between mother and fetus and inadequate function contributes to short and long-term ill-health. The placenta is absent from most large-scale RNA-Seq datasets. We therefore analyze long and small RNAs (~101 and 20 million reads per sample respectively) from 302 human placentas, including 94 cases of preeclampsia (PE) and 56 cases of fetal growth restriction (FGR). The placental transcriptome has the seventh lowest complexity of 50 human tissues: 271 genes account for 50% of all reads. We identify multiple circular RNAs and validate 6 of these by Sanger sequencing across the back-splice junction. Using large-scale mass spectrometry datasets, we find strong evidence of peptides produced by translation of two circular RNAs. We also identify novel piRNAs which are clustered on Chr1 and Chr14. PE and FGR are associated with multiple and overlapping differences in mRNA, lincRNA and circRNA but fewer consistent differences in small RNAs. Of the three protein coding genes differentially expressed in both PE and FGR, one encodes a secreted protein FSTL3 (follistatin-like 3). Elevated serum levels of FSTL3 in pregnant women are predictive of subsequent PE and FGR. To aid visualization of our placenta transcriptome data, we develop a web application ( https://www.obgyn.cam.ac.uk/placentome/ ).

Date: 2021
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DOI: 10.1038/s41467-021-22695-y

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