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The RNA landscape of the human placenta in health and disease

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 pla...

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Autores principales: Gong, Sungsam, Gaccioli, Francesca, Dopierala, Justyna, Sovio, Ulla, Cook, Emma, Volders, Pieter-Jan, Martens, Lennart, Kirk, Paul D. W., Richardson, Sylvia, Smith, Gordon C. S., Charnock-Jones, D. Stephen
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8113443/
https://www.ncbi.nlm.nih.gov/pubmed/33976128
http://dx.doi.org/10.1038/s41467-021-22695-y
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author Gong, Sungsam
Gaccioli, Francesca
Dopierala, Justyna
Sovio, Ulla
Cook, Emma
Volders, Pieter-Jan
Martens, Lennart
Kirk, Paul D. W.
Richardson, Sylvia
Smith, Gordon C. S.
Charnock-Jones, D. Stephen
author_facet Gong, Sungsam
Gaccioli, Francesca
Dopierala, Justyna
Sovio, Ulla
Cook, Emma
Volders, Pieter-Jan
Martens, Lennart
Kirk, Paul D. W.
Richardson, Sylvia
Smith, Gordon C. S.
Charnock-Jones, D. Stephen
author_sort Gong, Sungsam
collection PubMed
description 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/).
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spelling pubmed-81134432021-05-14 The RNA landscape of the human placenta in health and disease Gong, Sungsam Gaccioli, Francesca Dopierala, Justyna Sovio, Ulla Cook, Emma Volders, Pieter-Jan Martens, Lennart Kirk, Paul D. W. Richardson, Sylvia Smith, Gordon C. S. Charnock-Jones, D. Stephen Nat Commun Article 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/). Nature Publishing Group UK 2021-05-11 /pmc/articles/PMC8113443/ /pubmed/33976128 http://dx.doi.org/10.1038/s41467-021-22695-y Text en © The Author(s) 2021 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as 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 images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle Article
Gong, Sungsam
Gaccioli, Francesca
Dopierala, Justyna
Sovio, Ulla
Cook, Emma
Volders, Pieter-Jan
Martens, Lennart
Kirk, Paul D. W.
Richardson, Sylvia
Smith, Gordon C. S.
Charnock-Jones, D. Stephen
The RNA landscape of the human placenta in health and disease
title The RNA landscape of the human placenta in health and disease
title_full The RNA landscape of the human placenta in health and disease
title_fullStr The RNA landscape of the human placenta in health and disease
title_full_unstemmed The RNA landscape of the human placenta in health and disease
title_short The RNA landscape of the human placenta in health and disease
title_sort rna landscape of the human placenta in health and disease
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8113443/
https://www.ncbi.nlm.nih.gov/pubmed/33976128
http://dx.doi.org/10.1038/s41467-021-22695-y
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