Dataset Information

Analysis of the epigenetic status of telomeres by using ChIP-seq data.

ABSTRACT: The chromatin structure of eukaryotic telomeres plays an essential role in telomere functions. However, their study might be impaired by the presence of interstitial telomeric sequences (ITSs), which have a widespread distribution in different model systems. We have developed a simple approach to study the chromatin structure of Arabidopsis telomeres independently of ITSs by analyzing ChIP-seq data. This approach could be used to study the chromatin structure of telomeres in some other eukaryotes. The analysis of ChIP-seq experiments revealed that Arabidopsis telomeres have higher density of histone H3 than centromeres, which might reflects their short nucleosomal organization. These experiments also revealed that Arabidopsis telomeres have lower levels of heterochromatic marks than centromeres (H3K9(Me2) and H3K27(Me)), higher levels of some euchromatic marks (H3K4(Me2) and H3K9Ac) and similar or lower levels of other euchromatic marks (H3K4(Me3), H3K36(Me2), H3K36(Me3) and H3K18Ac). Interestingly, the ChIP-seq experiments also revealed that Arabidopsis telomeres exhibit high levels of H3K27(Me3), a repressive mark that associates with many euchromatic genes. The epigenetic profile of Arabidopsis telomeres is closely related to the previously defined chromatin state 2. This chromatin state is found in 23% of Arabidopsis genes, many of which are repressed or lowly expressed. At least, in part, this scenario is similar in rice.

SUBMITTER: Vaquero-Sedas MI

PROVIDER: S-EPMC3505975 | biostudies-literature | 2012 Nov

REPOSITORIES: biostudies-literature

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Analysis of the epigenetic status of telomeres by using ChIP-seq data.

Vaquero-Sedas María I MI Luo Chongyuan C Vega-Palas Miguel A MA

Nucleic acids research 20120801 21

The chromatin structure of eukaryotic telomeres plays an essential role in telomere functions. However, their study might be impaired by the presence of interstitial telomeric sequences (ITSs), which have a widespread distribution in different model systems. We have developed a simple approach to study the chromatin structure of Arabidopsis telomeres independently of ITSs by analyzing ChIP-seq data. This approach could be used to study the chromatin structure of telomeres in some other eukaryote ...[more]

PMID: 22855559

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Project description:BackgroundDespite the advent of Chromatin Immunoprecipitation Sequencing (ChIP-seq) having revolutionised our understanding of the mammalian genome's regulatory landscape, many challenges remain. In particular, because of their repetitive nature, the sequencing reads derived from transposable elements (TEs) pose a real bioinformatics challenge, to the point that standard analysis pipelines typically ignore reads whose genomic origin cannot be unambiguously ascertained.ResultsWe show that discarding ambiguously mapping reads may lead to a systematic underestimation of the number of reads associated with young TE families/subfamilies. We also provide evidence suggesting that the strategy of randomly permuting the location of the read mappings (or the TEs) that is often used to compute the background for enrichment calculations at TE families/subfamilies can result in both false positive and negative enrichments. To address these problems, we present the Transposable Element Enrichment Estimator (T3E), a tool that makes use of ChIP-seq data to characterise the epigenetic profile of associated TE families/subfamilies. T3E weights the number of read mappings assigned to the individual TE copies of a family/subfamily by the overall number of genomic loci to which the corresponding reads map, and this is done at the single nucleotide level. In addition, T3E computes ChIP-seq enrichment relative to a background estimated based on the distribution of the read mappings in the input control DNA. We demonstrated the capabilities of T3E on 23 different ChIP-seq libraries. T3E identified enrichments that were consistent with previous studies. Furthermore, T3E detected context-specific enrichments that are likely to pinpoint unexplored TE families/subfamilies with individual TE copies that have been frequently exapted as cis-regulatory elements during the evolution of mammalian regulatory networks.ConclusionsT3E is a novel open-source computational tool (available for use at: https://github.com/michelleapaz/T3E ) that overcomes some of the pitfalls associated with the analysis of ChIP-seq data arising from the repetitive mammalian genome and provides a framework to shed light on the epigenetics of entire TE families/subfamilies.

Project description:BackgroundDespite well-documented effects on human health, the action modes of environmental pollutants are incompletely understood. Although transcriptome-based approaches are widely used to predict associations between chemicals and disorders, the molecular cues regulating pollutant-derived gene expression changes remain unclear. Therefore, we developed a data-mining approach, termed "DAR-ChIPEA," to identify transcription factors (TFs) playing pivotal roles in the action modes of pollutants.MethodsLarge-scale public ChIP-Seq data (human, n = 15,155; mouse, n = 13,156) were used to predict TFs that are enriched in the pollutant-induced differentially accessible genomic regions (DARs) obtained from epigenome analyses (ATAC-Seq). The resultant pollutant-TF matrices were then cross-referenced to a repository of TF-disorder associations to account for pollutant modes of action. We subsequently evaluated the performance of the proposed method using a chemical perturbation data set to compare the outputs of the DAR-ChIPEA and our previously developed differentially expressed gene (DEG)-ChIPEA methods using pollutant-induced DEGs as input. We then adopted the proposed method to predict disease-associated mechanisms triggered by pollutants.ResultsThe proposed approach outperformed other methods using the area under the receiver operating characteristic curve score. The mean score of the proposed DAR-ChIPEA was significantly higher than that of our previously described DEG-ChIPEA (0.7287 vs. 0.7060; Q = 5.278 × 10-42; two-tailed Wilcoxon rank-sum test). The proposed approach further predicted TF-driven modes of action upon pollutant exposure, indicating that (1) TFs regulating Th1/2 cell homeostasis are integral in the pathophysiology of tributyltin-induced allergic disorders; (2) fine particulates (PM2.5) inhibit the binding of C/EBPs, Rela, and Spi1 to the genome, thereby perturbing normal blood cell differentiation and leading to immune dysfunction; and (3) lead induces fatty liver by disrupting the normal regulation of lipid metabolism by altering hepatic circadian rhythms.ConclusionsHighlighting genome-wide chromatin change upon pollutant exposure to elucidate the epigenetic landscape of pollutant responses outperformed our previously described method that focuses on gene-adjacent domains only. Our approach has the potential to reveal pivotal TFs that mediate deleterious effects of pollutants, thereby facilitating the development of strategies to mitigate damage from environmental pollution.

Dataset Information

Analysis of the epigenetic status of telomeres by using ChIP-seq data.

Publications

Analysis of the epigenetic status of telomeres by using ChIP-seq data.

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