Genetic variants influence on the placenta regulatory landscape

• Published in: PLoS genetics 2018-11, Vol.14 (11), p.e1007785
• Main Authors: Delahaye, Fabien, Do, Catherine, Kong, Yu, Ashkar, Remi, Salas, Martha, Tycko, Ben, Wapner, Ronald, Hughes, Francine
• Format: Article
• Language: English
• Subjects: Adolescent; Adult; Base sequence; Binding Sites - genetics; Biochemistry; Bioinformatics; Biology and life sciences; Biomedical research; CpG Islands; Deoxyribonucleic acid; Diabetes; Disease; Disease susceptibility; DNA; DNA methylation; DNA Methylation - genetics; DNA sequencing; Epigenesis, Genetic; Epigenetic inheritance; Epigenetics; Female; Gene expression; Gene Expression Profiling; Gene Expression Regulation; Gene mapping; Genes; Genetic analysis; Genetic aspects; Genetic diversity; Genetic regulation; Genetic research; Genetic Variation; Genetics; Genome, Human; Genome-Wide Association Study; Genomes; Genomics; Genotype; Genotypes; Gynecology; Humans; Medical research; Messenger RNA; Methylation; Nucleotide sequence; Obstetrics; Physical Sciences; Placenta; Placenta - metabolism; Polymorphism, Single Nucleotide; Pregnancy; Quantitative genetics; Quantitative Trait Loci; RNA; Sequence Analysis, DNA; Studies; Supervision; Transcription (Genetics); Transcription Factors - genetics; Transcription Factors - metabolism; Type 2 diabetes; Women's health; Young Adult
• ISSN: 1553-7404; 1553-7390; 1553-7404
• DOI: 10.1371/journal.pgen.1007785

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.