Affymetrix 6.0 SNP arrays interrogated to detect allele-specific DNA modification in the brain
Ontology highlight
ABSTRACT:
ORGANISM(S): Homo sapiens
PROVIDER: GSE71443 | GEO | 2015/07/29
SECONDARY ACCESSION(S): PRJNA291241
REPOSITORIES: GEO
Similar Datasets
Project description:It has long been hypothesized that knowledge of allele-specific modification (ASM; "modification" is used to denote various types of epigenetic cytosine marks, not only methylation) can supplement and inform GWAS of complex diseases and traits. To explore the relationship between GWAS subthreshold SNPs and ASM, we identified brain ASM-SNPs from Caucasian control individuals (n=76) and Caucasian patients affected by schizophrenia (n=65) or bipolar (n=67) using the Affymetrix SNP 6.0 microarray, one of the most common GWAS platforms which has also been thoroughlyt validated for ASM mapping. The brain samples (N=230, all ethnicities) were interrogated twice on Affymetrix SNP 6.0 microarrays. First, regular SNP genotyping was performed following the manufacturer's protocol. Second, we investigated allelic differences in DNA methylation by enriching the unmodified DNA fraction using DNA methylation-sensitive restriction enzymes.
2015-07-29 | E-GEOD-71443 | biostudies-arrayexpress
Project description:Background: Mapping of allele-specific DNA methylation (ASM) can be a post-GWAS strategy for localizing regulatory sequence polymorphisms (rSNPs). However, the advantages of this approach, and the mechanisms underlying ASM in normal and neoplastic cells, remain to be clarified. Results: We performed whole genome methyl-seq on diverse normal cells and tissues and three types of cancers (multiple myeloma, lymphoma, glioblastoma multiforme). After excluding imprinting, the data pinpointed 15,114 high-confidence ASM differentially methylated regions (DMRs), of which 1,842 contained SNPs in strong linkage disequilibrium or coinciding with GWAS peaks. ASM frequencies were increased 5 to 9-fold in cancers vs. matched normal tissues, due to widespread allele-specific hypomethylation and focal allele-specific hypermethylation in poised chromatin. Cancers showed increased allele switching at ASM loci, but destructive SNPs in specific classes of CTCF and transcription factor (TF) binding motifs were similarly correlated with ASM in cancer and non-cancer. Rare somatic mutations in these same motif classes tracked with de novo ASM in the cancers. Allele-specific TF binding from ChIP-seq was enriched among ASM loci, but most ASM DMRs lacked such annotations, and some were found in otherwise uninformative “chromatin deserts”. Conclusions: ASM is increased in cancers but occurs by a shared mechanism involving rSNPs in CTCF and TF binding sites in normal and neoplastic cells. Dense ASM mapping in normal plus cancer samples reveals candidate rSNPs that are difficult to find by other approaches. Together with GWAS data, these rSNPs can nominate specific transcriptional pathways in susceptibility to autoimmune, neuropsychiatric, and neoplastic diseases.
2020-03-18 | GSE137879 | GEO
Project description:Background: Mapping of allele-specific methylation (ASM) can be a post-GWAS strategy for localizing functional regulatory sequence polymorphisms (rSNPs). However, the unique advantages of this approach, and the mechanisms underlying ASM in normal and neoplastic cells, remain to be clarified. Results: We performed sequence capture-based (25 samples, including 14 newly sequenced samples) and whole genome bisulfite sequencing (81 samples) on diverse normal human cells and tissues from multiple individuals, plus a group of cancers (multiple myeloma, lymphoma, and glioblastoma multiforme). After excluding imprinting, the data pinpointed 15,114 high-confidence ASM differentially methylated regions (DMRs), of which 1,842 contained SNPs in strong linkage disequilibrium or coinciding with GWAS peaks. ASM frequencies were increased 5 to 9-fold in cancers vs. matched normal tissues, due to widespread allele-specific hypomethylation and focal allele-specific hypermethylation in poised chromatin. Cancers showed increased allele switching at ASM loci, but destructive SNPs in specific classes of CTCF and transcription factor (TF) binding motifs were similarly correlated with ASM in cancer and non-cancer. Rare somatic mutations in these same motif classes tracked with de novo ASM in the cancers. Allele-specific TF binding from ChIP-seq was enriched among ASM loci, but most ASM DMRs lacked such annotations, and some were found in otherwise uninformative “chromatin deserts”. Conclusions: ASM is increased in cancers but occurs by a shared mechanism involving rSNPs in CTCF and TF binding sites in normal and neoplastic cells. Dense ASM mapping in normal plus cancer samples reveals candidate rSNPs that are difficult to find by other approaches. Together with GWAS data, these rSNPs can nominate specific transcriptional pathways in susceptibility to autoimmune, neuropsychiatric, and neoplastic diseases.
2020-03-18 | GSE137287 | GEO
Project description:Juvenile idiopathic arthritis (JIA) is the most common chronic childhood rheumatic disease in the Western world. To identify novel JIA predisposing loci, a genome-wide association study (GWAS) in 814 Caucasian JIA cases and 3058 Caucasian controls was completed. After adjusting for the most significant HLA associations, the strongest novel associations included rs6479891 (10q21, odds ratio (OR)=1.59, P=1.3x10-8) and rs10761747 (OR=1.34, P=4.0x10-5) within JMJD1C; rs12719740 (15q26, OR=1.47, P=3.3x10-7) near FAM169B; rs4688011 (3q13, OR=1.33, P=1.1x10-4) within C3orf1 and rs4254850 (4q31, OR=0.85, P=7.8x10-3) near IL15. Eleven SNPs were genotyped in Caucasian replication cohorts (1744 cases, 7010 controls) and meta-analysis continued to provide evidence for association with three of the SNPs (rs6479891, P=4.3x10-5; rs12719740, P=5.2x10-4; rs4688011, P=3.6x10-7). Analysis of expression data from 68 JIA cases and 23 controls overlapping in the GWAS cohort1 and published lymphoblastoid cell lines (LCL)2 showed cis eQTL associations for JMJD1C SNPs (P=0.01 and P=1.6x10-6, respectively), and the C3orf1 SNP (P=5.7x10-6).
2012-03-23 | GSE26554 | GEO
Project description:Juvenile idiopathic arthritis (JIA) is the most common chronic childhood rheumatic disease in the Western world. To identify novel JIA predisposing loci, a genome-wide association study (GWAS) in 814 Caucasian JIA cases and 3058 Caucasian controls was completed. After adjusting for the most significant HLA associations, the strongest novel associations included rs6479891 (10q21, odds ratio (OR)=1.59, P=1.3x10-8) and rs10761747 (OR=1.34, P=4.0x10-5) within JMJD1C; rs12719740 (15q26, OR=1.47, P=3.3x10-7) near FAM169B; rs4688011 (3q13, OR=1.33, P=1.1x10-4) within C3orf1 and rs4254850 (4q31, OR=0.85, P=7.8x10-3) near IL15. Eleven SNPs were genotyped in Caucasian replication cohorts (1744 cases, 7010 controls) and meta-analysis continued to provide evidence for association with three of the SNPs (rs6479891, P=4.3x10-5; rs12719740, P=5.2x10-4; rs4688011, P=3.6x10-7). Analysis of expression data from 68 JIA cases and 23 controls overlapping in the GWAS cohort1 and published lymphoblastoid cell lines (LCL)2 showed cis eQTL associations for JMJD1C SNPs (P=0.01 and P=1.6x10-6, respectively), and the C3orf1 SNP (P=5.7x10-6). Peripheral blood samples were obtained from 23 healthy children and 68 children with JIA. RNA was purified from Ficoll-isolated mononuclear cells, fluorescently labeled and then hybridized to Affymetrix U133 Plus 2.0 GeneChips. Data were imported using Robust Multi-Array Average pre-processing and Distance Weighted Discrimination normalization. eQTL analysis were performed using genomewide association data.
2012-03-23 | E-GEOD-26554 | biostudies-arrayexpress
Project description:Six affected individuals were profiled on Affymetrix Genome-Wide SNP array 6.0.
2014-12-26 | E-MTAB-2821 | biostudies-arrayexpress
Project description:Reports on common mutations in neuroendocrine tumors (NET) are rare and clonality of NET metastases has not been investigated in this tumor entity yet. We selected a NET and a the corresponding lymph node and liver metastases as well as the derivative cell lines to screen for somatic mutations in the primary NET and to track the fate of genetic changes (by Affymetrix SNP 6.0 micorarray and targeted resequencing by 454 GS FLX) and during metastasis and in vitro progression. using Affymetrix SNP 6.0 Arrays.
2012-07-17 | GSE39371 | GEO
Project description:Haplotype-dependent allele-specific methylation (hap-ASM) can impact disease susceptibility, but maps of this phenomenon using stringent criteria in disease-relevant tissues remain sparse. Here we apply array-based and Methyl-seq approaches to multiple human tissues and cell types, including brain, purified neurons and glia, T lymphocytes, and placenta, and identify 795 hap-ASM differentially methylated regions (DMRs) and 3,082 strong methylation quantitative trait loci (mQTLs), most not previously reported. More than half of these DMRs have cell type-restricted ASM, and among them are 188 hap-ASM DMRs and 933 mQTLs located near GWAS signals for immune and neurological disorders. Targeted bis-seq confirmed hap-ASM in 12/13 loci tested, including CCDC155, CD69, FRMD1, IRF1, KBTBD11, and S100A*-ILF2, associated with immune phenotypes, MYT1L, PTPRN2,CMTM8 and CELF2, associated with neurological disorders, NGFR and HLA-DRB6, associated with both immunological and brain disorders, and ZFP57, a trans-acting regulator of genomic imprinting. Polymorphic CTCF and transcription factor (TF) binding sites are over-represented among hap-ASM DMRs and mQTLs, and analysis of the human data, supplemented by cross-species comparisons to Macaca mulattamacaques, indicates that CTCF and TF binding likelihood predicts the strength and direction of the allelic methylation asymmetry. These results show that hap-ASM is highly tissue-specific; an important trans-acting regulator of genomic imprinting is regulated by this phenomenon; variation in CTCF and TF binding sites is an underlying mechanism in primary tissues, and maps of hap-ASM and mQTLs reveal regulatory sequences underlying supera- and sub-threshold GWAS peaks in immunological and neurological disorders.
2016-03-21 | GSE79254 | GEO
Project description:Haplotype-dependent allele-specific methylation (hap-ASM) can impact disease susceptibility, but maps of this phenomenon using stringent criteria in disease-relevant tissues remain sparse. Here we apply array-based and Methyl-seq approaches to multiple human tissues and cell types, including brain, purified neurons and glia, T lymphocytes, and placenta, and identify 795 hap-ASM differentially methylated regions (DMRs) and 3,082 strong methylation quantitative trait loci (mQTLs), most not previously reported. More than half of these DMRs have cell type-restricted ASM, and among them are 188 hap-ASM DMRs and 933 mQTLs located near GWAS signals for immune and neurological disorders. Targeted bis-seq confirmed hap-ASM in 12/13 loci tested, including CCDC155, CD69, FRMD1, IRF1, KBTBD11, and S100A*-ILF2, associated with immune phenotypes, MYT1L, PTPRN2,CMTM8 and CELF2, associated with neurological disorders, NGFR and HLA-DRB6, associated with both immunological and brain disorders, and ZFP57, a trans-acting regulator of genomic imprinting. Polymorphic CTCF and transcription factor (TF) binding sites are over-represented among hap-ASM DMRs and mQTLs, and analysis of the human data, supplemented by cross-species comparisons to Macaca mulattamacaques, indicates that CTCF and TF binding likelihood predicts the strength and direction of the allelic methylation asymmetry. These results show that hap-ASM is highly tissue-specific; an important trans-acting regulator of genomic imprinting is regulated by this phenomenon; variation in CTCF and TF binding sites is an underlying mechanism in primary tissues, and maps of hap-ASM and mQTLs reveal regulatory sequences underlying supera- and sub-threshold GWAS peaks in immunological and neurological disorders.
2016-03-21 | GSE79148 | GEO
Project description:Haplotype-dependent allele-specific methylation (hap-ASM) can impact disease susceptibility, but maps of this phenomenon using stringent criteria in disease-relevant tissues remain sparse. Here we apply array-based and Methyl-seq approaches to multiple human tissues and cell types, including brain, purified neurons and glia, T lymphocytes, and placenta, and identify 795 hap-ASM differentially methylated regions (DMRs) and 3,082 strong methylation quantitative trait loci (mQTLs), most not previously reported. More than half of these DMRs have cell type-restricted ASM, and among them are 188 hap-ASM DMRs and 933 mQTLs located near GWAS signals for immune and neurological disorders. Targeted bis-seq confirmed hap-ASM in 12/13 loci tested, including CCDC155, CD69, FRMD1, IRF1, KBTBD11, and S100A*-ILF2, associated with immune phenotypes, MYT1L, PTPRN2,CMTM8 and CELF2, associated with neurological disorders, NGFR and HLA-DRB6, associated with both immunological and brain disorders, and ZFP57, a trans-acting regulator of genomic imprinting. Polymorphic CTCF and transcription factor (TF) binding sites are over-represented among hap-ASM DMRs and mQTLs, and analysis of the human data, supplemented by cross-species comparisons to Macaca mulattamacaques, indicates that CTCF and TF binding likelihood predicts the strength and direction of the allelic methylation asymmetry. These results show that hap-ASM is highly tissue-specific; an important trans-acting regulator of genomic imprinting is regulated by this phenomenon; variation in CTCF and TF binding sites is an underlying mechanism in primary tissues, and maps of hap-ASM and mQTLs reveal regulatory sequences underlying supera- and sub-threshold GWAS peaks in immunological and neurological disorders.
2016-03-21 | GSE79144 | GEO