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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...

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Autores principales: Delahaye, Fabien, Do, Catherine, Kong, Yu, Ashkar, Remi, Salas, Martha, Tycko, Ben, Wapner, Ronald, Hughes, Francine
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2018
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.
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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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