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Chromatin structure is distinct between coding and non-coding single nucleotide polymorphisms.

ABSTRACT: BACKGROUND: Previous studies suggested that nucleosomes are enriched with single nucleotide polymorphisms (SNPs) in humans and that the occurrence of mutations is closely associated with CpG dinucleotides. We aimed to determine if the chromatin organization is genomic locus specific around SNPs, and if newly occurring mutations are associated with SNPs. RESULTS: Here, we classified SNPs according their loci and investigated chromatin organization in both CD4+ T cell and lymphoblastoid cell in humans. We calculated the SNP frequency around somatic mutations. The results indicated that nucleosome occupancy is different around SNPs sites in different genomic loci. Coding SNPs are mainly enriched at nucleosomes and associated with repressed histone modifications (HMs) and DNA methylation. Contrastingly, intron SNPs occur in nucleosome-depleted regions and lack HMs. Interestingly, risk-associated non-coding SNPs are also enriched at nucleosomes with HMs but associated with low GC-content and low DNA methylation level. The base-transversion allele frequency is significantly low in coding-synonymous SNPs (P?

SUBMITTER: Liu H

PROVIDER: S-EPMC4193957 | biostudies-literature | 2014

REPOSITORIES: biostudies-literature

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Chromatin structure is distinct between coding and non-coding single nucleotide polymorphisms.

Liu Hongde H Zhai Jinchen J Luo Kun K Liu Lingjie L

BMC molecular biology 20141005

<h4>Background</h4>Previous studies suggested that nucleosomes are enriched with single nucleotide polymorphisms (SNPs) in humans and that the occurrence of mutations is closely associated with CpG dinucleotides. We aimed to determine if the chromatin organization is genomic locus specific around SNPs, and if newly occurring mutations are associated with SNPs.<h4>Results</h4>Here, we classified SNPs according their loci and investigated chromatin organization in both CD4+ T cell and lymphoblasto ...[more]

PMID: 25282079

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Project description:BACKGROUND:Although our microbial community and genomes (the human microbiome) outnumber our genome by several orders of magnitude, to what extent the human host genetic complement informs the microbiota composition is not clear. The Human Microbiome Project (HMP) Consortium established a unique population-scale framework with which to characterize the relationship of microbial community structure with their human hosts. A wide variety of taxa and metabolic pathways have been shown to be differentially distributed by virtue of race/ethnicity in the HMP. Given that mtDNA haplogroups are the maternally derived ancestral genomic markers and mitochondria's role as the generator for cellular ATP, characterizing the relationship between human mtDNA genomic variants and microbiome profiles becomes of potential marked biologic and clinical interest. RESULTS:We leveraged sequencing data from the HMP to investigate the association between microbiome community structures with its own host mtDNA variants. 15 haplogroups and 631 mtDNA nucleotide polymorphisms (mean sequencing depth of 280X on the mitochondria genome) from 89 individuals participating in the HMP were accurately identified. 16S rRNA (V3-V5 region) sequencing generated microbiome taxonomy profiles and whole genome shotgun sequencing generated metabolic profiles from various body sites were treated as traits to conduct association analysis between haplogroups and host clinical metadata through linear regression. The mtSNPs of individuals with European haplogroups were associated with microbiome profiles using PLINK quantitative trait associations with permutation and adjusted for multiple comparisons. We observe that among 139 stool and 59 vaginal posterior fornix samples, several haplogroups show significant association with specific microbiota (q-value < 0.05) as well as their aggregate community structure (Chi-square with Monte Carlo, p < 0.005), which confirmed and expanded previous research on the association of race and ethnicity with microbiome profile. Our results further indicate that mtDNA variations may render different microbiome profiles, possibly through an inflammatory response to different levels of reactive oxygen species activity. CONCLUSIONS:These data provide initial evidence for the association between host ancestral genome with the structure of its microbiome.

Project description:Estrogen receptor (ER) activity is critical for the development and progression of the majority of breast cancers. It is known that ER is differentially bound to DNA leading to transcriptomic and phenotypic changes in different breast cancer models. We investigated whether single nucleotide variants (SNVs) in ER binding sites (regSNVs) contribute to ER action through changes in the ER cistrome, thereby affecting disease progression. Here we developed a computational pipeline to identify SNVs in ER binding sites using chromatin immunoprecipitation sequencing (ChIP-seq) data from ER+ breast cancer models.ER ChIP-seq data were downloaded from the Gene Expression Omnibus (GEO). GATK pipeline was used to identify SNVs and the MACS algorithm was employed to call DNA-binding sites. Determination of the potential effect of a given SNV in a binding site was inferred using reimplementation of the is-rSNP algorithm. The Cancer Genome Atlas (TCGA) data were integrated to correlate the regSNVs and gene expression in breast tumors. ChIP and luciferase assays were used to assess the allele-specific binding.Analysis of ER ChIP-seq data from MCF7 cells identified an intronic SNV in the IGF1R gene, rs62022087, predicted to increase ER binding. Functional studies confirmed that ER binds preferentially to rs62022087 versus the wild-type allele. By integrating 43 ER ChIP-seq datasets, multi-omics, and clinical data, we identified 17 regSNVs associated with altered expression of adjacent genes in ER+ disease. Of these, the top candidate was in the promoter of the GSTM1 gene and was associated with higher expression of GSTM1 in breast tumors. Survival analysis of patients with ER+ tumors revealed that higher expression of GSTM1, responsible for detoxifying carcinogens, was correlated with better outcome.In conclusion, we have developed a computational approach that is capable of identifying putative regSNVs in ER ChIP-binding sites. These non-coding variants could potentially regulate target genes and may contribute to clinical prognosis in breast cancer.

Dataset Information

Chromatin structure is distinct between coding and non-coding single nucleotide polymorphisms.

Publications

Chromatin structure is distinct between coding and non-coding single nucleotide polymorphisms.

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