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遗传变异对胎盘调控景观的影响。

Genetic variants influence on the placenta regulatory landscape.

机构信息

Department of Genetics, Albert Einstein College of Medicine, Bronx, New York, United States of America.

Department of Biomedical Research, Division of Genetics & Epigenetics, Hackensack-Meridian Health Center for Discovery and Innovation, Nutley, New Jersey, United States of America.

出版信息

PLoS Genet. 2018 Nov 19;14(11):e1007785. doi: 10.1371/journal.pgen.1007785. eCollection 2018 Nov.

DOI:10.1371/journal.pgen.1007785
PMID:30452450
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC6277118/
Abstract

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.

摘要

从基因组关联研究、数量性状位点分析和表观基因组图谱分析中可以明显看出,有必要进行大量努力来定义遗传-表观遗传相互作用,并了解其在疾病易感性和进展中的作用。出于这个原因,对人类胎盘的基因表达和 DNA 甲基化进行高分辨率和全基因组覆盖的遗传变异影响分析将具有多种机制和实际意义。通过对来自健康女性胎盘的 DNA 序列变异(n = 303)、DNA 甲基化(n = 303)和 mRNA 表达数据(n = 80)进行产生和分析,我们研究了人类胎盘的调控景观,并提供了分析方法来整合不同类型的基因组数据,并解决当前平台的一些潜在局限性。我们区分了表达和 DNA 甲基化之间相互作用的两种模式,揭示了线性或双峰效应,反映了基因组背景、转录因子募集以及可能的细胞亚群的差异。这些发现有助于阐明正常人类胎盘遗传、表观遗传和转录调控机制之间的相互作用。它们还为正常胎盘中转录和 DNA 甲基化的基因型驱动修饰提供了有力证据。除了这些机制方面的意义外,这里提出的数据和分析方法将提高与涉及胎盘功能的人类特征和疾病相关的全基因组和全表观基因组关联研究的可解释性。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d58a/6277118/133d8fb75cb5/pgen.1007785.g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d58a/6277118/c13fbdcf8c23/pgen.1007785.g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d58a/6277118/e22152f39121/pgen.1007785.g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d58a/6277118/cc8179783b96/pgen.1007785.g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d58a/6277118/cc4202a6c9f4/pgen.1007785.g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d58a/6277118/2e3cb0a717ad/pgen.1007785.g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d58a/6277118/190546b5c729/pgen.1007785.g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d58a/6277118/133d8fb75cb5/pgen.1007785.g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d58a/6277118/c13fbdcf8c23/pgen.1007785.g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d58a/6277118/e22152f39121/pgen.1007785.g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d58a/6277118/cc8179783b96/pgen.1007785.g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d58a/6277118/cc4202a6c9f4/pgen.1007785.g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d58a/6277118/2e3cb0a717ad/pgen.1007785.g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d58a/6277118/190546b5c729/pgen.1007785.g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d58a/6277118/133d8fb75cb5/pgen.1007785.g007.jpg

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