Interrogation of allelic chromatin states in human cells by high-density ChIP-genotyping

Light, Nicholas; Adoue, Véronique; Ge, Bing; Chen, Shu-Huang; Kwan, Tony; Pastinen, Tomi

doi:10.4161/epi.29920

Cited by 11 publications

(12 citation statements)

References 43 publications

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“…In order to validate the binding of a repressor factor, we examined allelic ChIP‐seq signals for H3K4me3 at rs780100 across all individuals that are heterozygous for this variant. We observed a significantly higher signal (~twofold, chi‐squared test, P < 0.001 for all individuals except for MNC491 with P < 0.05) for active chromatin on the same haplotype as the less expressed allele, reinforcing our hypothesis of a repressor binding NRBP1 promoter region (Fig E) (Light et al , ). It is also interesting to note that the risk allele is associated to the repression of this gene.…”

Section: Resultssupporting

confidence: 83%

Allelic expression mapping across cellular lineages to establish impact of non‐coding SNPs

Adoue

Schiavi

Light

et al. 2014

Molecular Systems Biology

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Most complex disease-associated genetic variants are located in non-coding regions and are therefore thought to be regulatory in nature. Association mapping of differential allelic expression (AE) is a powerful method to identify SNPs with direct cis-regulatory impact (cis-rSNPs). We used AE mapping to identify cis-rSNPs regulating gene expression in 55 and 63 HapMap lymphoblastoid cell lines from a Caucasian and an African population, respectively, 70 fibroblast cell lines, and 188 purified monocyte samples and found 40–60% of these cis-rSNPs to be shared across cell types. We uncover a new class of cis-rSNPs, which disrupt footprint-derived de novo motifs that are predominantly bound by repressive factors and are implicated in disease susceptibility through overlaps with GWAS SNPs. Finally, we provide the proof-of-principle for a new approach for genome-wide functional validation of transcription factor–SNP interactions. By perturbing NFκB action in lymphoblasts, we identified 489 cis-regulated transcripts with altered AE after NFκB perturbation. Altogether, we perform a comprehensive analysis of cis-variation in four cell populations and provide new tools for the identification of functional variants associated to complex diseases.

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Section: Resultssupporting

confidence: 83%

Allelic expression mapping across cellular lineages to establish impact of non‐coding SNPs

Adoue

Schiavi

Light

et al. 2014

Molecular Systems Biology

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“…Genome-wide association studies (GWAS) revealed that the majority of the associated single nucleotide polymorphisms (SNPs) lie in non-coding regulatory regions [ 1 , 2 ]. To understand the functional impact of these SNPs, various studies have linked these to cellular traits, including gene expression (expression quantitative trait loci (eQTLs) or allele-specific expression (ASE) and splicing QTLs) [ 3 – 6 ], DNA methylation (mQTLs) [ 7 , 8 ], histone marks (hQTLs), or allele specific chromatin immunoprecipitation (AS-ChIP)) [ 9 , 10 ] effects, especially when cell types relevant to the disease of interest are used. Many of these studies have confirmed early efforts [ 1 ] showing that in fact a majority of GWAS hits are enriched for these different QTLs.…”

Section: Introductionmentioning

confidence: 99%

“…Allele-specific histone (ASH) has also been linked to allelically biased gene expression. Allele-specific enhancers are found close to genes showing ASE, with high concordance of ASH signal to the corresponding ASE of the same allele [ 9 , 17 ]. Allele-specific independent events (methylation, gene expression and histone) have been shown to have genome-wide, autosomal associations for complex traits, and particularly for complex disease [ 18 , 19 ].…”

Section: Introductionmentioning

confidence: 99%

Functional variation in allelic methylomes underscores a strong genetic contribution and reveals novel epigenetic alterations in the human epigenome

et al. 2017

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BackgroundThe functional impact of genetic variation has been extensively surveyed, revealing that genetic changes correlated to phenotypes lie mostly in non-coding genomic regions. Studies have linked allele-specific genetic changes to gene expression, DNA methylation, and histone marks but these investigations have only been carried out in a limited set of samples.ResultsWe describe a large-scale coordinated study of allelic and non-allelic effects on DNA methylation, histone mark deposition, and gene expression, detecting the interrelations between epigenetic and functional features at unprecedented resolution. We use information from whole genome and targeted bisulfite sequencing from 910 samples to perform genotype-dependent analyses of allele-specific methylation (ASM) and non-allelic methylation (mQTL). In addition, we introduce a novel genotype-independent test to detect methylation imbalance between chromosomes. Of the ~2.2 million CpGs tested for ASM, mQTL, and genotype-independent effects, we identify ~32% as being genetically regulated (ASM or mQTL) and ~14% as being putatively epigenetically regulated. We also show that epigenetically driven effects are strongly enriched in repressed regions and near transcription start sites, whereas the genetically regulated CpGs are enriched in enhancers. Known imprinted regions are enriched among epigenetically regulated loci, but we also observe several novel genomic regions (e.g., HOX genes) as being epigenetically regulated. Finally, we use our ASM datasets for functional interpretation of disease-associated loci and show the advantage of utilizing naïve T cells for understanding autoimmune diseases.ConclusionsOur rich catalogue of haploid methylomes across multiple tissues will allow validation of epigenome association studies and exploration of new biological models for allelic exclusion in the human genome.Electronic supplementary materialThe online version of this article (doi:10.1186/s13059-017-1173-7) contains supplementary material, which is available to authorized users.

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“…Now if we want to know the variants previously associated with autoimmune disease, as used by Light et al (2014), we need to retrieve statistical association information on these variants, and then apply a filter using the same level of significance P < 1 × 10 −6 [9]. A quick inspection at the gwasrapidd cheatsheet (Additional file 2: gwasrapidd cheatsheet) hints that statitiscal information, such as p-values and odds ratios can be found in the associations table of the associations S4 class object.…”

Section: Resultsmentioning

confidence: 99%

gwasrapidd: an R package to query, download and wrangle GWAS Catalog data

Magno

Ana

2019

Preprint

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Motivation:The NHGRI Catalog of Published Genome-Wide Association Studies (GWAS) Catalog has collected, curated, and made available data from over 3 900 studies. The recently developed GWAS Catalog REST API is the only method allowing programmatic access to this resource. Results: Here, we describe gwasrapidd, an R package that provides a client interface to the GWAS Catalog REST API, representing an important software counterpart to the server-side component. gwasrapidd enables users to quickly retrieve, filter and integrate data with comprehensive bioinformatics analysis tools, which is particularly critical for those looking into functional characterisation of risk loci. Availability: gwasrapidd is freely available under an MIT License, and can be accessed from https://github.com/ramiromagno/gwasrapidd. 130 possibility in gwasrapidd, we map EFO identifiers (efo id) to EFO traits with 131 get traits() using the former as a search parameter. The table traits of the S4 132 object traits contains the trait column, providing a one-to-one mapping between each 133 EFO identifier and its trait description (trait). Then, we use internally 134 get variants() to search by EFO trait description (efo trait). 135 Finally, gwasrapidd also provides a set of helper functions to easily browse linked 136 web resources, such as PubMed [11] , dbSNP [12],and GTEx project [13]. 137 Limitations 138The most popular method of access to the Catalog is still the web graphical user 139 interface (GUI), and is therefore still the one that gets more attention and dedication 140 from the GWAS Catalog team. Thus, compared to the web GUI, the REST API is still 141 lagging behind in functionality. Here we discuss some of the limitations of the REST 142 API compared to the web GUI. 143When searching by publication related information, with the REST API, we can 144 only use the PubMed identifier as a query. Thus, to search using other publication 145 related criteria, such as words in the title or date of publication, one needs to download 146 6/9

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Interrogation of allelic chromatin states in human cells by high-density ChIP-genotyping

Cited by 11 publications

References 43 publications

Allelic expression mapping across cellular lineages to establish impact of non‐coding SNPs

Allelic expression mapping across cellular lineages to establish impact of non‐coding SNPs

Functional variation in allelic methylomes underscores a strong genetic contribution and reveals novel epigenetic alterations in the human epigenome

gwasrapidd: an R package to query, download and wrangle GWAS Catalog data

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