Tiling array data analysis: a multiscale approach using wavelets

<p>Abstract</p> <p>Background</p> <p>Tiling array data is hard to interpret due to noise. The wavelet transformation is a widely used technique in signal processing for elucidating the true signal from noisy data. Consequently, we attempted to denoise representative tiling array datasets for ChIP-chip experiments using wavelets. In doing this, we used specific wavelet basis functions, <it>Coiflets</it>, since their triangular shape closely resembles the expected profiles of true ChIP-chip peaks.</p> <p>Results</p> <p>In our wavelet-transformed data, we observed that noise tends to be confined to small scales while the useful signal-of-interest spans multiple large scales. We were also able to show that wavelet coefficients due to non-specific cross-hybridization follow a log-normal distribution, and we used this fact in developing a thresholding procedure. In particular, wavelets allow one to set an unambiguous, absolute threshold, which has been hard to define in ChIP-chip experiments. One can set this threshold by requiring a similar confidence level at different length-scales of the transformed signal. We applied our algorithm to a number of representative ChIP-chip data sets, including those of Pol II and histone modifications, which have a diverse distribution of length-scales of biochemical activity, including some broad peaks.</p> <p>Conclusions</p> <p>Finally, we benchmarked our method in comparison to other approaches for scoring ChIP-chip data using spike-ins on the ENCODE Nimblegen tiling array. This comparison demonstrated excellent performance, with wavelets getting the best overall score.</p

Coordinated Regulation of ATF2 by miR-26b in γ-Irradiated Lung Cancer Cells

MicroRNA regulates cellular responses to ionizing radiation (IR) through translational control of target genes. We analyzed time-series changes in microRNA expression following γ-irradiation in H1299 lung cancer cells using microarray analysis. Significantly changed IR-responsive microRNAs were selected based on analysis of variance analysis, and predicted target mRNAs were enriched in mitogen-activated protein kinase (MAPK) signaling. Concurrent analysis of time-series mRNA and microRNA profiles uncovered that expression of miR-26b was down regulated, and its target activating transcription factor 2 (ATF2) mRNA was up regulated in γ-irradiated H1299 cells. IR in miR-26b overexpressed H1299 cells could not induce expression of ATF2. When c-Jun N-terminal kinase activity was inhibited using SP600125, expression of miR-26b was induced following γ-irradiation in H1299 cells. From these results, we concluded that IR-induced up-regulation of ATF2 was coordinately enhanced by suppression of miR-26b in lung cancer cells, which may enhance the effect of IR in the MAPK signaling pathway

Genome-Scale Validation of Deep-Sequencing Libraries

Chromatin immunoprecipitation followed by high-throughput (HTP) sequencing (ChIP-seq) is a powerful tool to establish protein-DNA interactions genome-wide. The primary limitation of its broad application at present is the often-limited access to sequencers. Here we report a protocol, Mab-seq, that generates genome-scale quality evaluations for nucleic acid libraries intended for deep-sequencing. We show how commercially available genomic microarrays can be used to maximize the efficiency of library creation and quickly generate reliable preliminary data on a chromosomal scale in advance of deep sequencing. We also exploit this technique to compare enriched regions identified using microarrays with those identified by sequencing, demonstrating that they agree on a core set of clearly identified enriched regions, while characterizing the additional enriched regions identifiable using HTP sequencing

Global analysis of DNA methylation in early-stage liver fibrosis

<p>Abstract</p> <p>Background</p> <p>Liver fibrosis is caused by chemicals or viral infection. The progression of liver fibrosis results in hepatocellular carcinogenesis in later stages. Recent studies have revealed the importance of DNA hypermethylation in the progression of liver fibrosis to hepatocellular carcinoma (HCC). However, the importance of DNA methylation in the early-stage liver fibrosis remains unclear.</p> <p>Methods</p> <p>To address this issue, we used a pathological mouse model of early-stage liver fibrosis that was induced by treatment with carbon tetrachloride (CCl₄) for 2 weeks and performed a genome-wide analysis of DNA methylation status. This global analysis of DNA methylation was performed using a combination of methyl-binding protein (MBP)-based high throughput sequencing (MBP-seq) and bioinformatic tools, IPA and Oncomine. To confirm functional aspect of MBP-seq data, we complementary used biochemical methods, such as bisulfite modification and <it>in-vitro</it>-methylation assays.</p> <p>Results</p> <p>The genome-wide analysis revealed that DNA methylation status was reduced throughout the genome because of CCl₄treatment in the early-stage liver fibrosis. Bioinformatic and biochemical analyses revealed that a gene associated with fibrosis, <it>secreted phosphoprotein 1 </it>(<it>Spp1</it>), which induces inflammation, was hypomethylated and its expression was up-regulated. These results suggest that DNA hypomethylation of the genes responsible for fibrosis may precede the onset of liver fibrosis. Moreover, <it>Spp1 </it>is also known to enhance tumor development. Using the web-based database, we revealed that <it>Spp1 </it>expression is increased in HCC.</p> <p>Conclusions</p> <p>Our study suggests that hypomethylation is crucial for the onset of and in the progression of liver fibrosis to HCC. The elucidation of this change in methylation status from the onset of fibrosis and subsequent progression to HCC may lead to a new clinical diagnosis.</p

ChIP-chip versus ChIP-seq: Lessons for experimental design and data analysis

<p>Abstract</p> <p>Background</p> <p>Chromatin immunoprecipitation (ChIP) followed by microarray hybridization (ChIP-chip) or high-throughput sequencing (ChIP-seq) allows genome-wide discovery of protein-DNA interactions such as transcription factor bindings and histone modifications. Previous reports only compared a small number of profiles, and little has been done to compare histone modification profiles generated by the two technologies or to assess the impact of input DNA libraries in ChIP-seq analysis. Here, we performed a systematic analysis of a modENCODE dataset consisting of 31 pairs of ChIP-chip/ChIP-seq profiles of the coactivator CBP, RNA polymerase II (RNA PolII), and six histone modifications across four developmental stages of <it>Drosophila melanogaster</it>.</p> <p>Results</p> <p>Both technologies produce highly reproducible profiles within each platform, ChIP-seq generally produces profiles with a better signal-to-noise ratio, and allows detection of more peaks and narrower peaks. The set of peaks identified by the two technologies can be significantly different, but the extent to which they differ varies depending on the factor and the analysis algorithm. Importantly, we found that there is a significant variation among multiple sequencing profiles of input DNA libraries and that this variation most likely arises from both differences in experimental condition and sequencing depth. We further show that using an inappropriate input DNA profile can impact the average signal profiles around genomic features and peak calling results, highlighting the importance of having high quality input DNA data for normalization in ChIP-seq analysis.</p> <p>Conclusions</p> <p>Our findings highlight the biases present in each of the platforms, show the variability that can arise from both technology and analysis methods, and emphasize the importance of obtaining high quality and deeply sequenced input DNA libraries for ChIP-seq analysis.</p

Diverse Roles and Interactions of the SWI/SNF Chromatin Remodeling Complex Revealed Using Global Approaches

A systems understanding of nuclear organization and events is critical for determining how cells divide, differentiate, and respond to stimuli and for identifying the causes of diseases. Chromatin remodeling complexes such as SWI/SNF have been implicated in a wide variety of cellular processes including gene expression, nuclear organization, centromere function, and chromosomal stability, and mutations in SWI/SNF components have been linked to several types of cancer. To better understand the biological processes in which chromatin remodeling proteins participate, we globally mapped binding regions for several components of the SWI/SNF complex throughout the human genome using ChIP-Seq. SWI/SNF components were found to lie near regulatory elements integral to transcription (e.g. 5′ ends, RNA Polymerases II and III, and enhancers) as well as regions critical for chromosome organization (e.g. CTCF, lamins, and DNA replication origins). Interestingly we also find that certain configurations of SWI/SNF subunits are associated with transcripts that have higher levels of expression, whereas other configurations of SWI/SNF factors are associated with transcripts that have lower levels of expression. To further elucidate the association of SWI/SNF subunits with each other as well as with other nuclear proteins, we also analyzed SWI/SNF immunoprecipitated complexes by mass spectrometry. Individual SWI/SNF factors are associated with their own family members, as well as with cellular constituents such as nuclear matrix proteins, key transcription factors, and centromere components, implying a ubiquitous role in gene regulation and nuclear function. We find an overrepresentation of both SWI/SNF-associated regions and proteins in cell cycle and chromosome organization. Taken together the results from our ChIP and immunoprecipitation experiments suggest that SWI/SNF facilitates gene regulation and genome function more broadly and through a greater diversity of interactions than previously appreciated

HPV16 oncogene expression levels during early cervical carcinogenesis are determined by the balance of epigenetic chromatin modifications at the integrated virus genome.

In cervical squamous cell carcinomas, high-risk human papillomavirus (HRHPV) DNA is usually integrated into host chromosomes. Multiple integration events are thought to be present within the cells of a polyclonal premalignant lesion and the features that underpin clonal selection of one particular integrant remain poorly understood. We previously used the W12 model system to generate a panel of cervical keratinocyte clones, derived from cells of a low-grade premalignant lesion naturally infected with the major HRHPV type, HPV16. The cells were isolated regardless of their selective advantage and differed only by the site of HPV16 integration into the host genome. We used this resource to test the hypothesis that levels of HPV16 E6/E7 oncogene expression in premalignant cells are regulated epigenetically. We performed a comprehensive analysis of the epigenetic landscape of the integrated HPV16 DNA in selected clones, in which levels of virus oncogene expression per DNA template varied ~6.6-fold. Across the cells examined, higher levels of virus expression per template were associated with more open chromatin at the HPV16 long control region, together with greater loading of chromatin remodelling enzymes and lower nucleosome occupancy. There were higher levels of histone post-translational modification hallmarks of transcriptionally active chromatin and lower levels of repressive hallmarks. There was greater abundance of the active/elongating form of the RNA polymerase-II enzyme (RNAPII-Ser2P), together with CDK9, the component of positive transcription elongation factor b complex responsible for Ser2 phosphorylation. The changes observed were functionally significant, as cells with higher HPV16 expression per template showed greater sensitivity to depletion and/or inhibition of histone acetyltransferases and CDK9 and less sensitivity to histone deacetylase inhibition. We conclude that virus gene expression per template following HPV16 integration is determined through multiple layers of epigenetic regulation, which are likely to contribute to selection of individual cells during cervical carcinogenesis.This work was supported by Cancer Research UK (Programme Grant A13080); the Medical Research Council; The Pathological Society of Great Britain and Ireland (E.L.A.K.); and the Agency for Science, Technology and Research, Singapore (Q.Y.A).This is the final version of the article. It first appeared from Nature Publishing Group via http://dx.doi.org/10.1038/onc.2016.

De-Novo Identification of PPARγ/RXR Binding Sites and Direct Targets during Adipogenesis

BACKGROUND: The pathophysiology of obesity and type 2 diabetes mellitus is associated with abnormalities in endocrine signaling in adipose tissue and one of the key signaling affectors operative in these disorders is the nuclear hormone transcription factor peroxisome proliferator-activated receptor-gamma (PPARgamma). PPARgamma has pleiotropic functions affecting a wide range of fundamental biological processes including the regulation of genes that modulate insulin sensitivity, adipocyte differentiation, inflammation and atherosclerosis. To date, only a limited number of direct targets for PPARgamma have been identified through research using the well established pre-adipogenic cell line, 3T3-L1. In order to obtain a genome-wide view of PPARgamma binding sites, we applied the pair end-tagging technology (ChIP-PET) to map PPARgamma binding sites in 3T3-L1 preadipocyte cells. METHODOLOGY/PRINCIPAL FINDINGS: Coupling gene expression profile analysis with ChIP-PET, we identified in a genome-wide manner over 7700 DNA binding sites of the transcription factor PPARgamma and its heterodimeric partner RXR during the course of adipocyte differentiation. Our validation studies prove that the identified sites are bona fide binding sites for both PPARgamma and RXR and that they are functionally capable of driving PPARgamma specific transcription. Our results strongly indicate that PPARgamma is the predominant heterodimerization partner for RXR during late stages of adipocyte differentiation. Additionally, we find that PPARgamma/RXR association is enriched within the proximity of the 5' region of the transcription start site and this association is significantly associated with transcriptional up-regulation of genes involved in fatty acid and lipid metabolism confirming the role of PPARgamma as the master transcriptional regulator of adipogenesis. Evolutionary conservation analysis of these binding sites is greater when adjacent to up-regulated genes than down-regulated genes, suggesting the primordial function of PPARgamma/RXR is in the induction of genes. Our functional validations resulted in identifying novel PPARgamma direct targets that have not been previously reported to promote adipogenic differentiation. CONCLUSIONS/SIGNIFICANCE: We have identified in a genome-wide manner the binding sites of PPARgamma and RXR during the course of adipogenic differentiation in 3T3L1 cells, and provide an important resource for the study of PPARgamma function in the context of adipocyte differentiation

Identification of CIITA Regulated Genetic Module Dedicated for Antigen Presentation

The class II trans-activator CIITA is a transcriptional co-activator required for the expression of Major Histocompatibility Complex (MHC) genes. Although the latter function is well established, the global target-gene specificity of CIITA had not been defined. We therefore generated a comprehensive list of its target genes by performing genome-wide scans employing four different approaches designed to identify promoters that are occupied by CIITA in two key antigen presenting cells, B cells and dendritic cells. Surprisingly, in addition to MHC genes, only nine new targets were identified and validated by extensive functional and expression analysis. Seven of these genes are known or likely to function in processes contributing to MHC-mediated antigen presentation. The remaining two are of unknown function. CIITA is thus uniquely dedicated for genes implicated in antigen presentation. The finding that CIITA regulates such a highly focused gene expression module sets it apart from all other transcription factors, for which large-scale binding-site mapping has indicated that they exert pleiotropic functions and regulate large numbers of genes