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Genetic variants influence on the placenta regulatory landscape
From genomic association studies, quantitative trait loci analysis, and epigenomic mapping, it is evident that significant efforts are necessary to define genetic-epigenetic interactions and understand their role in disease susceptibility and progression. For this reason, an analysis of the effects...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6277118/ https://www.ncbi.nlm.nih.gov/pubmed/30452450 http://dx.doi.org/10.1371/journal.pgen.1007785 |
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author | Delahaye, Fabien Do, Catherine Kong, Yu Ashkar, Remi Salas, Martha Tycko, Ben Wapner, Ronald Hughes, Francine |
author_facet | Delahaye, Fabien Do, Catherine Kong, Yu Ashkar, Remi Salas, Martha Tycko, Ben Wapner, Ronald Hughes, Francine |
author_sort | Delahaye, Fabien |
collection | PubMed |
description | From genomic association studies, quantitative trait loci analysis, and epigenomic mapping, it is evident that significant efforts are necessary to define genetic-epigenetic interactions and understand their role in disease susceptibility and progression. For this reason, an analysis of the effects of genetic variation on gene expression and DNA methylation in human placentas at high resolution and whole-genome coverage will have multiple mechanistic and practical implications. By producing and analyzing DNA sequence variation (n = 303), DNA methylation (n = 303) and mRNA expression data (n = 80) from placentas from healthy women, we investigate the regulatory landscape of the human placenta and offer analytical approaches to integrate different types of genomic data and address some potential limitations of current platforms. We distinguish two profiles of interaction between expression and DNA methylation, revealing linear or bimodal effects, reflecting differences in genomic context, transcription factor recruitment, and possibly cell subpopulations. These findings help to clarify the interactions of genetic, epigenetic, and transcriptional regulatory mechanisms in normal human placentas. They also provide strong evidence for genotype-driven modifications of transcription and DNA methylation in normal placentas. In addition to these mechanistic implications, the data and analytical methods presented here will improve the interpretability of genome-wide and epigenome-wide association studies for human traits and diseases that involve placental functions. |
format | Online Article Text |
id | pubmed-6277118 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-62771182018-12-19 Genetic variants influence on the placenta regulatory landscape Delahaye, Fabien Do, Catherine Kong, Yu Ashkar, Remi Salas, Martha Tycko, Ben Wapner, Ronald Hughes, Francine PLoS Genet Research Article From genomic association studies, quantitative trait loci analysis, and epigenomic mapping, it is evident that significant efforts are necessary to define genetic-epigenetic interactions and understand their role in disease susceptibility and progression. For this reason, an analysis of the effects of genetic variation on gene expression and DNA methylation in human placentas at high resolution and whole-genome coverage will have multiple mechanistic and practical implications. By producing and analyzing DNA sequence variation (n = 303), DNA methylation (n = 303) and mRNA expression data (n = 80) from placentas from healthy women, we investigate the regulatory landscape of the human placenta and offer analytical approaches to integrate different types of genomic data and address some potential limitations of current platforms. We distinguish two profiles of interaction between expression and DNA methylation, revealing linear or bimodal effects, reflecting differences in genomic context, transcription factor recruitment, and possibly cell subpopulations. These findings help to clarify the interactions of genetic, epigenetic, and transcriptional regulatory mechanisms in normal human placentas. They also provide strong evidence for genotype-driven modifications of transcription and DNA methylation in normal placentas. In addition to these mechanistic implications, the data and analytical methods presented here will improve the interpretability of genome-wide and epigenome-wide association studies for human traits and diseases that involve placental functions. Public Library of Science 2018-11-19 /pmc/articles/PMC6277118/ /pubmed/30452450 http://dx.doi.org/10.1371/journal.pgen.1007785 Text en © 2018 Delahaye et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. |
spellingShingle | Research Article Delahaye, Fabien Do, Catherine Kong, Yu Ashkar, Remi Salas, Martha Tycko, Ben Wapner, Ronald Hughes, Francine Genetic variants influence on the placenta regulatory landscape |
title | Genetic variants influence on the placenta regulatory landscape |
title_full | Genetic variants influence on the placenta regulatory landscape |
title_fullStr | Genetic variants influence on the placenta regulatory landscape |
title_full_unstemmed | Genetic variants influence on the placenta regulatory landscape |
title_short | Genetic variants influence on the placenta regulatory landscape |
title_sort | genetic variants influence on the placenta regulatory landscape |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6277118/ https://www.ncbi.nlm.nih.gov/pubmed/30452450 http://dx.doi.org/10.1371/journal.pgen.1007785 |
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