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Comparative Methylome Analyses Identify Epigenetic Regulatory Loci of Human Brain Evolution

ABSTRACT: This SuperSeries is composed of the SubSeries listed below.

ORGANISM(S): Hoolock leuconedys Pan troglodytes Homo sapiens Macaca Macaca fascicularis Macaca mulatta

PROVIDER: GSE85868 | GEO | 2016/08/20

SECONDARY ACCESSION(S): PRJNA339582

REPOSITORIES: GEO

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Comparative Methylome Analyses Identify Epigenetic Regulatory Loci of Human Brain Evolution.

Project description:How do epigenetic modifications change across species and how do these modifications affect evolution? These are fundamental questions at the forefront of our evolutionary epigenomic understanding. Our previous work investigated human and chimpanzee brain methylomes, but it was limited by the lack of outgroup data which is critical for comparative (epi)genomic studies. Here, we compared whole genome DNA methylation maps from brains of humans, chimpanzees and also rhesus macaques (outgroup) to elucidate DNA methylation changes during human brain evolution. Moreover, we validated that our approach is highly robust by further examining 38 human-specific DMRs using targeted deep genomic and bisulfite sequencing in an independent panel of 37 individuals from five primate species. Our unbiased genome-scan identified human brain differentially methylated regions (DMRs), irrespective of their associations with annotated genes. Remarkably, over half of the newly identified DMRs locate in intergenic regions or gene bodies. Nevertheless, their regulatory potential is on par with those of promoter DMRs. An intriguing observation is that DMRs are enriched in active chromatin loops, suggesting human-specific evolutionary remodeling at a higher-order chromatin structure. These findings indicate that there is substantial reprogramming of epigenomic landscapes during human brain evolution involving noncoding regions.

| S-EPMC5062329 | biostudies-literature

Comparative Methylome Analyses Identify Epigenetic Regulatory Loci of Human Brain Evolution

Project description:This SuperSeries is composed of the SubSeries listed below. Refer to individual Series

2016-08-20 | E-GEOD-85868 | biostudies-arrayexpress

Comparative Methylome Analyses Identify Epigenetic Regulatory Loci of Human Brain Evolution

Project description:We report the application of DNA sequencing technology for high-throughput sequencing of mix bis-PCR products totally 38 based on bisulfate treated DNA from human, chimpanzee, gibbon, macaque and crab eating macaque profrontal cortex tissues. Mix bisulfate PCR products from 1 tissues, 23 individula humans, 2 individual chimpanzees, 1 individual gibbons, 7 individual rhesus macaques and 5 crab eating macaques were sequenced by using MiSeq

2016-08-16 | E-GEOD-76788 | biostudies-arrayexpress

Comparative Methylome Analyses Identify Epigenetic Regulatory Loci of Human Brain Evolution [SNP]

Project description:We report the application of DNA sequencing technology for high-throughput sequencing of mix candidate genes' PCR products totally 38 based on DNA from human, chimpanzee, gibbon, macaque and crab eating macaque profrontal cortex tissues. Mix candidate genes PCR products from 1 tissues, 22 individual humans, 2 individual chimpanzees, 1 individual gibbons,15 individual rhesus macaques and 5 crab eating macaques were sequenced by using MiSeq

2016-08-20 | E-GEOD-85867 | biostudies-arrayexpress

Comparative Methylome Analyses Identify Epigenetic Regulatory Loci of Human Brain Evolution [methylation]

2016-08-16 | GSE76788 | GEO

Comparative Methylome Analyses Identify Epigenetic Regulatory Loci of Human Brain Evolution [SNP]

2016-08-20 | GSE85867 | GEO

Comparative Methylome Analyses Identify Epigenetic Regulatory Loci of Human Brain Evolution

Project description:Comparative Methylome Analyses Identify Epigenetic Regulatory Loci of Human Brain Evolution

| PRJNA339582 | ENA

Comparative Methylome Analyses Identify Epigenetic Regulatory Loci of Human Brain Evolution [SNP]

Project description:Comparative Methylome Analyses Identify Epigenetic Regulatory Loci of Human Brain Evolution [SNP]

| PRJNA339583 | ENA

Comparative Methylome Analyses Identify Epigenetic Regulatory Loci of Human Brain Evolution [methylation]

Project description:Comparative Methylome Analyses Identify Epigenetic Regulatory Loci of Human Brain Evolution [methylation]

| PRJNA308588 | ENA

Recursive Motif Analyses Identify Brain Epigenetic Transcription Regulatory Modules.

Project description:DNA methylation is an epigenetic modification modulating the structure of DNA molecule and the interactions with its binding proteins. Accumulating large-scale methylation data motivates the development of analytic tools to facilitate methylome data mining. One critical phenomenon associated with dynamic DNA methylation is the altered DNA binding affinity of transcription factors, which plays key roles in gene expression regulation. In this study, we conceived an algorithm to predict epigenetic regulatory modules through recursive motif analyses on differentially methylated loci. A two-step procedure was implemented to first group differentially methylated loci into clusters according to their correlations in methylation profiles and then to repeatedly identify the transcription factor binding motifs significantly enriched in each cluster. We applied this tool on methylome datasets generated for mouse brains which have a lack of DNA demethylation enzymes TET1 or TET2. Compared with wild type control, the differentially methylated CpG sites identified in TET1 knockout mouse brains differed significantly from those determined for TET2 knockout. Transcription factors with zinc finger DNA binding domains including Egr1, Zic3, and Zeb1 were predicted to be associated with TET1 mediated brain methylome programming, while Lhx family members with Homeobox domains were predicted to be associated with TET2 function. Interestingly, genomic loci from a co-methylated cluster often host motifs for transcription factors sharing the same DNA binding domains. Altogether, our study provided a systematic approach for epigenetic regulatory module identification and will help throw light on the interplay of DNA methylation and transcription factors.

| S-EPMC6462766 | biostudies-literature

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