Correlation between DNase I hypersensitive site distribution and gene expression in HeLa S3 cells

Genetic variants of NEUROD1 target genes are associated with clinical outcomes of small-cell lung cancer patients

BACKGROUND

Neurogenic differentiation factor 1 (NEUROD1) is frequently overexpressed in small-cell lung cancer (SCLC). NEUROD1 plays an important role in promoting malignant behavior and survival.

METHODS

In this study, we evaluated the association between putative functional polymorphisms in 45 NEUROD1 target genes and chemotherapy response and survival outcomes in 261 patients with SCLC. Among the 100 single nucleotide polymorphisms (SNPs) studied, two were significantly associated with both chemotherapy response and overall survival (OS) of patients with SCLC.

RESULTS

The SNP rs3806915C⟩A in semaphorin 6A (SEMA6A) gene was significantly associated with better chemotherapy response and OS (p = 0.04 and p = 0.04, respectively). The SNP rs11265375C⟩T in nescient helix-loop helix 1 (NHLH1) gene was also associated with better chemotherapy response and OS (p = 0.04 and p = 0.02, respectively). Luciferase assay showed a significantly higher promoter activity of SEMA6A with the rs3806915 A allele than C allele in H446 lung cancer cells (p = 4 × 10^-6 ). The promoter activity of NHLH1 showed a significantly higher with the rs11265375 T allele than C allele (p = 0.001).

CONCLUSION

These results suggest that SEMA6A rs3806915C>A and NHLH1 rs11265375C>T polymorphisms affect the promoter activity and expression of the genes, which may affect the survival outcome of patients with SCLC.

CALN1 hypomethylation as a biomarker for high-risk bladder cancer

Background

DNA methylation in cancer is considered a diagnostic and predictive biomarker. We investigated the usefulness of the methylation status of CALN1 as a biomarker for bladder cancer using methylation-sensitive restriction enzyme (MSRE)-quantitative polymerase chain reaction (qPCR).

Methods

Eighty-two bladder cancer fresh samples were collected via transurethral resection of bladder tumors. Genomic DNA was extracted from the samples, and MSRE-qPCR was performed to determine the CALN1 methylation percentage. Reverse transcription-qPCR was performed to assess the correlation between CALN1 methylation and mRNA expression. The association between CALN1 methylation percentage and clinicopathological variables of all cases and intravesical recurrence of non-muscle-invasive bladder cancer (non-MIBC) cases were analyzed.

Results

Of the 82 patients, nine had MIBC and 71 had non-MIBC who had not undergone total cystectomy. The median CALN1 methylation percentage was 79.5% (interquartile range: 51.1–92.6%). The CALN1 methylation percentage had a negative relationship with CALN1 mRNA expression (Spearman’s ρ = − 0.563 and P = 0.012). Hypomethylation of CALN1 was associated with advanced tumor stage (P = 0.0007) and histologically high grade (P = 0.018). Furthermore, multivariate analysis revealed that CALN1 hypomethylation was an independent risk factor for intravesical recurrence in non-MIBC patients (hazard ratio 3.83, 95% confidence interval; 1.14–13.0, P = 0.031).

Conclusion

Our findings suggest that CALN1 methylation percentage could be a useful molecular biomarker for bladder cancer.

Genome-Wide Study of Colocalization between Genomic Stretches: A Method and Applications to the Regulation of Gene Expression

In this paper, we describe a method for the study of colocalization effects between stretch-stretch and stretch-point genome tracks based on a set of indices varying within the (-1, +1) interval. The indices combine the distances between the centers of neighboring stretches and their lengths. The extreme boundaries of the interval correspond to the complete colocalization of the genome tracks or its complete absence. We also obtained the relevant criteria of statistical significance for such indices using the complete permutation test. The method is robust with respect to strongly inhomogeneous positioning and length distribution of the genome tracks. On the basis of this approach, we created command-line software, the Genome Track Colocalization Analyzer. The software was tested, compared with other available packages, and applied to particular problems related to gene expression. The package, Genome Track Colocalization Analyzer (GTCA), is freely available to the users. GTCA complements our previous software, the Genome Track Analyzer, intended for the search for pairwise correlations between point-like genome tracks (also freely available). The corresponding details are provided in Data Availability Statement at the end of the text.

Epigenetic alterations of CXCL5 in Cr(VI)-induced carcinogenesis

Chronic exposure to hexavalent chromium compounds [Cr(VI)] is associated with an increased risk of cancers, but the molecular mechanisms remain to be elucidated. In this study, we found that CXCL5 levels in peripheral blood monocytes (PBMCs) and plasma from workers with occupational exposure to Cr(VI) were dramatically upregulated compared to non-exposure healthy subjects, and plasma C-X-C Motif Chemokine Ligand 5 (CXCL5) CXCL5 levels were positively correlated with Cr concentrations in subjects' toenails. Zinc chromate exposed mice showed higher levels of CXCL5 and its receptor CXCR2 in lung tissues, and in PBMCs. Similar CXCL5 upregulation was evident in Cr(VI)-induced transformed (Cr-T) cells with long-term Cr(VI) treatment. Mechanistic studies showed that elevated CXCL5 expression levels were regulated by Cr(VI)-induced histone modifications and DNA hypomethylation, and that the c-Myc/p300 complex was a key upstream regulator of histone H3 acetylation. CXCL5 overexpression promoted Cr(VI)-induced the epithelial to mesenchyme transition (EMT) by upregulating zinc finger E-box binding homeobox 1 (ZEB1) to promote tumor development. Our findings identify a novel mechanism by which CXCL5 is upregulated and promotes EMT and carcinogenesis upon chronic Cr(VI) exposure. Our work also implies that CXCL5 mRNA and protein levels will elevate in PBMCs and serum after occupational Cr(VI) exposure, which may be a potential target and biomarker for cancer prevention and health surveillance among populations exposed to Cr(VI).

CORE GREML for estimating covariance between random effects in linear mixed models for complex trait analyses

As a key variance partitioning tool, linear mixed models (LMMs) using genome-based restricted maximum likelihood (GREML) allow both fixed and random effects. Classic LMMs assume independence between random effects, which can be violated, causing bias. Here we introduce a generalized GREML, named CORE GREML, that explicitly estimates the covariance between random effects. Using extensive simulations, we show that CORE GREML outperforms the conventional GREML, providing variance and covariance estimates free from bias due to correlated random effects. Applying CORE GREML to UK Biobank data, we find, for example, that the transcriptome, imputed using genotype data, explains a significant proportion of phenotypic variance for height (0.15, p-value = 1.5e-283), and that these transcriptomic effects correlate with the genomic effects (genome-transcriptome correlation = 0.35, p-value = 1.2e-14). We conclude that the covariance between random effects is a key parameter for estimation, especially when partitioning phenotypic variance by multi-omics layers.

Linear mixed models have bias due to the assumed independence between random effects. Here, the authors describe a genome-based restricted maximum likelihood, CORE GREML, which estimates covariance between random effects. Application to UK Biobank data highlights this as an important parameter for multi-omics analyses of phenotypic variance.

Harnessing targeted DNA methylation and demethylation using dCas9

DNA methylation is an essential DNA modification that plays a crucial role in genome regulation during differentiation and development, and is disrupted in a range of disease states. The recent development of CRISPR/catalytically dead CRISPR/Cas9 (dCas9)-based targeted DNA methylation editing tools has enabled new insights into the roles and functional relevance of this modification, including its importance at regulatory regions and the role of aberrant methylation in various diseases. However, while these tools are advancing our ability to understand and manipulate this regulatory layer of the genome, they still possess a variety of limitations in efficacy, implementation, and targeting specificity. Effective targeted DNA methylation editing will continue to advance our fundamental understanding of the role of this modification in different genomic and cellular contexts, and further improvements may enable more accurate disease modeling and possible future treatments. In this review, we discuss strategies, considerations, and future directions for targeted DNA methylation editing.

Systematic identification of silencers in human cells

The majority of the human genome does not encode proteins. Many of these noncoding regions contain important regulatory sequences that control gene expression. To date, most studies have focused on activators such as enhancers, but regions that repress gene expression-silencers-have not been systematically studied. We have developed a system that identifies silencer regions in a genome-wide fashion on the basis of silencer-mediated transcriptional repression of caspase 9. We found that silencers are widely distributed and may function in a tissue-specific fashion. These silencers harbor unique epigenetic signatures and are associated with specific transcription factors. Silencers also act at multiple genes, and at the level of chromosomal domains and long-range interactions. Deletion of silencer regions linked to the drug transporter genes ABCC2 and ABCG2 caused chemo-resistance. Overall, our study demonstrates that tissue-specific silencing is widespread throughout the human genome and probably contributes substantially to the regulation of gene expression and human biology.

Complex Relationships between Chromatin Accessibility, Sequence Divergence, and Gene Expression in Arabidopsis thaliana

Variation in regulatory DNA is thought to drive phenotypic variation, evolution, and disease. Prior studies of regulatory DNA and transcription factors across animal species highlighted a fundamental conundrum: Transcription factor binding domains and cognate binding sites are conserved, while regulatory DNA sequences are not. It remains unclear how conserved transcription factors and dynamic regulatory sites produce conserved expression patterns across species. Here, we explore regulatory DNA variation and its functional consequences within Arabidopsis thaliana, using chromatin accessibility to delineate regulatory DNA genome-wide. Unlike in previous cross-species comparisons, the positional homology of regulatory DNA is maintained among A. thaliana ecotypes and less nucleotide divergence has occurred. Of the ∼50,000 regulatory sites in A. thaliana, we found that 15% varied in accessibility among ecotypes. Some of these accessibility differences were associated with extensive, previously unannotated sequence variation, encompassing many deletions and ancient hypervariable alleles. Unexpectedly, for the majority of such regulatory sites, nearby gene expression was unaffected. Nevertheless, regulatory sites with high levels of sequence variation and differential chromatin accessibility were the most likely to be associated with differential gene expression. Finally, and most surprising, we found that the vast majority of differentially accessible sites show no underlying sequence variation. We argue that these surprising results highlight the necessity to consider higher-order regulatory context in evaluating regulatory variation and predicting its phenotypic consequences.

EnhancerDB: a resource of transcriptional regulation in the context of enhancers

Enhancers can act as cis-regulatory elements to control transcriptional regulation by recruiting DNA-binding transcription factors (TFs) in a tissue-specific manner. Recent studies show that enhancers regulate not only protein-coding genes but also microRNAs (miRNAs), and mutations within the TF binding sites (TFBSs) located on enhancers will cause a variety of diseases such as cancer. However, a comprehensive resource to integrate these regulation elements for revealing transcriptional regulations in the context of enhancers is not currently available. Here, we introduce EnhancerDB, a web-accessible database to provide a resource to browse and search regulatory relationships identified in this study, including 131 054 581 TF–enhancer, 17 059 enhancer–miRNAs, 318 993 enhancer–genes, 4 639 558 TF–miRNAs, 1 059 695 TF–genes, 11 439 394 enhancer–single-nucleotide polymorphisms (SNPs) and 23 334 genes associated with expression quantitative trait loci (eQTL) SNP and expression profile of TF/gene/miRNA across multiple human tissues/cell lines. We also developed a tool that further allows users to define tissue-specific enhancers by setting the threshold score of tissue specificity of enhancers. In addition, links to external resources are also available at EnhancerDB.

Genome-wide Identification and Characterization of Enhancers Across 10 Human Tissues

Background: Enhancers can act as cis-regulatory elements (CREs) to control development and cellular function by regulating gene expression in a tissue-specific and ubiquitous manner. However, the regulatory network and characteristic of different types of enhancers (e.g., transcribed/non-transcribed enhancers, tissue-specific/ubiquitous enhancers) across multiple tissues are still unclear. Results: Here, a total of 53,924 active enhancers and 10,307 enhancer-associated RNAs (eRNAs) in 10 tissues (adrenal, brain, breast, heart, liver, lung, ovary, placenta, skeletal muscle and kidney) were identified through the integration of histone modifications (H3K4me1, H3K27ac and H3K4me3) and DNase I hypersensitive sites (DHSs) data. Moreover, 40,101 tissue-specific enhancers (TS-Enh), 1,241 ubiquitously expressed enhancers (UE-Enh) as well as transcribed enhancers (T-Enh), including 7,727 unidirectionally transcribed enhancers (1D-Enh) and 1,215 bidirectionally transcribed enhancers (2D-Enh) were defined in 10 tissues. The results show that enhancers exhibited high GC content, genomic variants and transcription factor binding sites (TFBS) enrichment in all tissues. These characteristics were significantly different between TS-Enh and UE-Enh, T-Enh and NT-Enh, 2D-Enh and 1D-Enh. Furt hermore, the results showed that enhancers obviously upregulate the expression of adjacent target genes which were remarkably correlated with the functions of corresponding tissues. Finally, a free user-friendly tissue-specific enhancer database, TiED (http://lcbb.swjtu.edu.cn/TiED), has been built to store, visualize, and confer these results. Conclusion: Genome-wide analysis of the regulatory network and characteristic of various types of enhancers showed that enhancers associated with TFs, eRNAs and target genes appeared in tissue specificity and function across different tissues.

Computational Methods for Assessing Chromatin Hierarchy

The hierarchical organization of chromatin is known to associate with diverse cellular functions; however, the precise mechanisms and the 3D structure remain to be determined. With recent advances in high-throughput next generation sequencing (NGS) techniques, genome-wide profiling of chromatin structures is made possible. Here, we provide a comprehensive overview of NGS-based methods for profiling "higher-order" and "primary-order" chromatin structures from both experimental and computational aspects. Experimental requirements and considerations specific for each method were highlighted. For computational analysis, we summarized a common analysis strategy for both levels of chromatin assessment, focusing on the characteristic computing steps and the tools. The recently developed single-cell level techniques based on Hi-C and ATAC-seq present great potential to reveal cell-to-cell variability in chromosome architecture. A brief discussion on these methods in terms of experimental and data analysis features is included. We also touch upon the biological relevance of chromatin organization and how the combination with other techniques uncovers the underlying mechanisms. We conclude with a summary and our prospects on necessary improvements of currently available methods in order to advance understanding of chromatin hierarchy. Our review brings together the analyses of both higher- and primary-order chromatin structures, and serves as a roadmap when choosing appropriate experimental and computational methods for assessing chromatin hierarchy.

Chromatin accessibility dynamics reveal novel functional enhancers in C. elegans

Chromatin accessibility, a crucial component of genome regulation, has primarily been studied in homogeneous and simple systems, such as isolated cell populations or early-development models. Whether chromatin accessibility can be assessed in complex, dynamic systems in vivo with high sensitivity remains largely unexplored. In this study, we use ATAC-seq to identify chromatin accessibility changes in a whole animal, the model organism Caenorhabditis elegans, from embryogenesis to adulthood. Chromatin accessibility changes between developmental stages are highly reproducible, recapitulate histone modification changes, and reveal key regulatory aspects of the epigenomic landscape throughout organismal development. We find that over 5000 distal noncoding regions exhibit dynamic changes in chromatin accessibility between developmental stages and could thereby represent putative enhancers. When tested in vivo, several of these putative enhancers indeed drive novel cell-type- and temporal-specific patterns of expression. Finally, by integrating transcription factor binding motifs in a machine learning framework, we identify EOR-1 as a unique transcription factor that may regulate chromatin dynamics during development. Our study provides a unique resource for C. elegans, a system in which the prevalence and importance of enhancers remains poorly characterized, and demonstrates the power of using whole organism chromatin accessibility to identify novel regulatory regions in complex systems.

Chromatin accessibility dynamics reveal novel functional enhancers in C. elegans

Chromatin accessibility, a crucial component of genome regulation, has primarily been studied in homogeneous and simple systems, such as isolated cell populations or early-development models. Whether chromatin accessibility can be assessed in complex, dynamic systems in vivo with high sensitivity remains largely unexplored. In this study, we use ATAC-seq to identify chromatin accessibility changes in a whole animal, the model organism Caenorhabditis elegans, from embryogenesis to adulthood. Chromatin accessibility changes between developmental stages are highly reproducible, recapitulate histone modification changes, and reveal key regulatory aspects of the epigenomic landscape throughout organismal development. We find that over 5000 distal noncoding regions exhibit dynamic changes in chromatin accessibility between developmental stages and could thereby represent putative enhancers. When tested in vivo, several of these putative enhancers indeed drive novel cell-type- and temporal-specific patterns of expression. Finally, by integrating transcription factor binding motifs in a machine learning framework, we identify EOR-1 as a unique transcription factor that may regulate chromatin dynamics during development. Our study provides a unique resource for C. elegans, a system in which the prevalence and importance of enhancers remains poorly characterized, and demonstrates the power of using whole organism chromatin accessibility to identify novel regulatory regions in complex systems.

Recognition but no repair of abasic site in single-stranded DNA by human ribosomal uS3 protein residing within intact 40S subunit

Isolated human ribosomal protein uS3 has extra-ribosomal functions including those related to base excision DNA repair, e.g. AP lyase activity that nicks double-stranded (ds) DNA 3΄ to the abasic (AP) site. However, the ability of uS3 residing within ribosome to recognize and cleave damaged DNA has never been addressed. Here, we compare interactions of single-stranded (ss) DNA and dsDNA bearing AP site with human ribosome-bound uS3 and with the isolated protein, whose interactions with ssDNA were not yet studied. The AP lyase activity of free uS3 was much higher with ssDNA than with dsDNA, whereas ribosome-bound uS3 was completely deprived of this activity. Nevertheless, an exposed peptide of ribosome-bound uS3 located far away from the putative catalytic center previously suggested for isolated uS3 cross-linked to full-length uncleaved ssDNA, but not to dsDNA. In contrast, free uS3 cross-linked mainly to the 5΄-part of the damaged DNA strand after its cleavage at the AP site. ChIP-seq analysis showed preferential uS3 binding to nucleolus-associated chromatin domains. We conclude that free and ribosome-bound uS3 proteins interact with AP sites differently, exhibiting their non-translational functions in DNA repair in and around the nucleolus and in regulation of DNA damage response in looped DNA structures, respectively.

RGmatch: matching genomic regions to proximal genes in omics data integration

Background

The integrative analysis of multiple genomics data often requires that genome coordinates-based signals have to be associated with proximal genes. The relative location of a genomic region with respect to the gene (gene area) is important for functional data interpretation; hence algorithms that match regions to genes should be able to deliver insight into this information.

Results

In this work we review the tools that are publicly available for making region-to-gene associations. We also present a novel method, RGmatch, a flexible and easy-to-use Python tool that computes associations either at the gene, transcript, or exon level, applying a set of rules to annotate each region-gene association with the region location within the gene. RGmatch can be applied to any organism as long as genome annotation is available. Furthermore, we qualitatively and quantitatively compare RGmatch to other tools.

Conclusions

RGmatch simplifies the association of a genomic region with its closest gene. At the same time, it is a powerful tool because the rules used to annotate these associations are very easy to modify according to the researcher’s specific interests. Some important differences between RGmatch and other similar tools already in existence are RGmatch’s flexibility, its wide range of user options, compatibility with any annotatable organism, and its comprehensive and user-friendly output.

Electronic supplementary material

The online version of this article (doi:10.1186/s12859-016-1293-1) contains supplementary material, which is available to authorized users.

Effects of RNAs on chromatin accessibility and gene expression suggest RNA-mediated activation

The study of the interaction between RNA and DNA sequences in activating genes has important significance for understanding the mechanisms of RNA-mediated activation. Here, we used in vitro chromatin reconstitution approach to observe whether RNAs increase DNase I digestion, plasmid transfection to observe whether RNAs promote gene expression, and bioinformatics analysis to predict the binding ability of RNAs to centromere DNA (constitutive heterochromatin). Synthetic RNAs (23nt) that were complementary to mouse albumin gene and total liver RNA increased DNase I digestion sensitivity of mouse albumin gene, suggesting that RNAs can increase chromatin accessibility. Transcribed sense-antisense tandem Alu elements activated an enhanced green fluorescent protein reporter gene after stable transfection. Bioinformatics analysis showed that the binding strength of RNA population to centromere DNAs is significantly lower than that of their flanking sequences, which suggests that the centromere is not easily affected by RNAs produced from other transcribed regions and may be the reason why centromeres consist of constitutive heterochromatin. The results in this paper illustrate that RNAs complementary to DNA sequences play roles in activating genes. Since RNA is mainly produced from the cell's own DNA, the work presented in this paper suggests that RNAs transcribed from DNA create feedback that activates DNA transcription.

iDHS-EL: identifying DNase I hypersensitive sites by fusing three different modes of pseudo nucleotide composition into an ensemble learning framework

MOTIVATION

Regulatory DNA elements are associated with DNase I hypersensitive sites (DHSs). Accordingly, identification of DHSs will provide useful insights for in-depth investigation into the function of noncoding genomic regions.

RESULTS

In this study, using the strategy of ensemble learning framework, we proposed a new predictor called iDHS-EL for identifying the location of DHS in human genome. It was formed by fusing three individual Random Forest (RF) classifiers into an ensemble predictor. The three RF operators were respectively based on the three special modes of the general pseudo nucleotide composition (PseKNC): (i) kmer, (ii) reverse complement kmer and (iii) pseudo dinucleotide composition. It has been demonstrated that the new predictor remarkably outperforms the relevant state-of-the-art methods in both accuracy and stability.

AVAILABILITY AND IMPLEMENTATION

For the convenience of most experimental scientists, a web server for iDHS-EL is established at http://bioinformatics.hitsz.edu.cn/iDHS-EL, which is the first web-server predictor ever established for identifying DHSs, and by which users can easily get their desired results without the need to go through the mathematical details. We anticipate that IDHS-EL: will become a very useful high throughput tool for genome analysis.

CONTACT

bliu@gordonlifescience.org or bliu@insun.hit.edu.cn

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

The histone deacetylase inhibitor Entinostat enhances polymer-mediated transgene expression in cancer cell lines

Eukaryotic cells maintain an immense amount of genetic information by tightly wrapping their DNA around positively charged histones. While this strategy allows human cells to maintain more than 25,000 genes, histone binding can also block gene expression. Consequently, cells express histone acetyl transferases (HATs) to acetylate histone lysines and release DNA for transcription. Conversely, histone deacetylases (HDACs) are employed for restoring the positive charge on the histones, thereby silencing gene expression by increasing histone-DNA binding. It has previously been shown that histones bind and silence viral DNA, while hyperacetylation of histones via HDAC inhibition restores viral gene expression. In this study, we demonstrate that treatment with Entinostat, an HDAC inhibitor, enhances transgene (luciferase) expression by up to 25-fold in human prostate and murine bladder cancer cell lines when used with cationic polymers for plasmid DNA delivery. Entinostat treatment altered cell cycle progression, resulting in a significant increase in the fraction of cells present in the G0/G1 phase at low micromolar concentrations. While this moderate G0/G1 arrest disappeared at higher concentrations, a modest increase in the fraction of apoptotic cells and a decrease in cell proliferation were observed, consistent with the known anticancer effects of the drug. DNase accessibility studies revealed no significant change in plasmid transcriptional availability with Entinostat treatment. However, quantitative PCR studies indicated that Entinostat treatment, at the optimal dose for enhancing transgene expression, led to an increase in the amount of plasmid present in the nucleus in two cancer cell lines. Taken together, our results show that Entinostat enhances polymer- mediated transgene expression and can be useful in applications related to transient protein expression in mammalian cells. Biotechnol. Bioeng. 2016;113: 1345-1356. © 2015 Wiley Periodicals, Inc.

Modeling co-occupancy of transcription factors using chromatin features

Regulation of gene expression requires both transcription factor (TFs) and epigenetic modifications, and interplays between the two types of factors have been discovered. However study of relationships between chromatin features and TF–TF co-occupancy remains limited. Here, we revealed the relationship by first illustrating distinct profile patterns of chromatin features related to different binding events, including single TF binding and TF–TF co-occupancy of 71 TFs from five human cell lines. We further implemented statistical analyses to demonstrate the relationship by accurately predicting co-occupancy genome-widely using chromatin features including DNase I hypersensitivity, 11 histone modifications (HMs) and GC content. Remarkably, our results showed that the combination of chromatin features enables accurate predictions across the five cells. For individual chromatin features, DNase I enables high and consistent predictions. H3K27ac, H3K4me 2, H3K4me3 and H3K9ac are more reliable predictors than other HMs. Although the combination of 11 HMs achieves accurate predictions, their predictive ability varies considerably when a model obtained from one cell is applied to others, indicating relationship between HMs and TF–TF co-occupancy is cell type dependent. GC content is not a reliable predictor, but the addition of GC content to any other features enhances their predictive ability. Together, our results elucidate a strong relationship between TF–TF co-occupancy and chromatin features.

Chromatin accessibility: a window into the genome

Transcriptional activation throughout the eukaryotic lineage has been tightly linked with disruption of nucleosome organization at promoters, enhancers, silencers, insulators and locus control regions due to transcription factor binding. Regulatory DNA thus coincides with open or accessible genomic sites of remodeled chromatin. Current chromatin accessibility assays are used to separate the genome by enzymatic or chemical means and isolate either the accessible or protected locations. The isolated DNA is then quantified using a next-generation sequencing platform. Wide application of these assays has recently focused on the identification of the instrumental epigenetic changes responsible for differential gene expression, cell proliferation, functional diversification and disease development. Here we discuss the limitations and advantages of current genome-wide chromatin accessibility assays with especial attention on experimental precautions and sequence data analysis. We conclude with our perspective on future improvements necessary for moving the field of chromatin profiling forward.

Genome-wide mapping of DNase I hypersensitive sites and association analysis with gene expression in MSB1 cells

DNase I hypersensitive sites (DHSs) mark diverse classes of cis-regulatory regions, such as promoters and enhancers. MSB-1 derived from chicken Marek's disease (MD) lymphomas is an MDV-transformed CD4+ T-cell line for MD study. Previously, DNase I HS sites were studied mainly in human cell types for mammalian. To capture the regulatory elements specific to MSB1 cells and explore the molecular mechanisms of T-cell transformation caused by MDV in MD, we generated high-quality of DHSs map and gene expression profile for functional analysis in MSB1 cell line. The total of 21,724 significant peaks of DHSs was identified from around 40 million short reads. DHSs distribution varied between chromosomes and they preferred to enrich in the gene-rich chromosomes. More interesting, DHSs enrichments appeared to be scarce on regions abundant in CpG islands. Besides, we integrated DHSs into the gene expression data and found that DHSs tended to enrich on high expressed genes throughout whole gene regions while DHSs did not show significant changes for low and silent expressed genes. Furthermore, the correlation of DHSs with lincRNAs expression was also calculated and it implied that enhancer-associated lincRNAs probably originated from enhancer-like regions of DHSs. Together, our results indicated that DNase I HS sites highly correlate with active genes expression in MSB1 cells, suggesting DHSs can be considered as markers to identify the cis-regulatory elements associated with chicken Marek's disease.

A comparison of peak callers used for DNase-Seq data

Genome-wide profiling of open chromatin regions using DNase I and high-throughput sequencing (DNase-seq) is an increasingly popular approach for finding and studying regulatory elements. A variety of algorithms have been developed to identify regions of open chromatin from raw sequence-tag data, which has motivated us to assess and compare their performance. In this study, four published, publicly available peak calling algorithms used for DNase-seq data analysis (F-seq, Hotspot, MACS and ZINBA) are assessed at a range of signal thresholds on two published DNase-seq datasets for three cell types. The results were benchmarked against an independent dataset of regulatory regions derived from ENCODE in vivo transcription factor binding data for each particular cell type. The level of overlap between peak regions reported by each algorithm and this ENCODE-derived reference set was used to assess sensitivity and specificity of the algorithms. Our study suggests that F-seq has a slightly higher sensitivity than the next best algorithms. Hotspot and the ChIP-seq oriented method, MACS, both perform competitively when used with their default parameters. However the generic peak finder ZINBA appears to be less sensitive than the other three. We also assess accuracy of each algorithm over a range of signal thresholds. In particular, we show that the accuracy of F-Seq can be considerably improved by using a threshold setting that is different from the default value.

Genome-wide analysis of the chromatin composition of histone H2A and H3 variants in mouse embryonic stem cells

Genome-wide distribution of the majority of H2A and H3 variants (H2A, H2AX, H2AZ, macroH2A, H3.1, H3.2 and H3.3) was simultaneously investigated in mouse embryonic stem cells by chromatin immunoprecipitation sequencing. Around the transcription start site, histone variant distribution differed between genes possessing promoters of high and low CpG density, regardless of their expression levels. In the intergenic regions, regulatory elements were enriched in H2A.Z and H3.3, whereas repeat elements were abundant in H2A and macroH2A, and H3.1, respectively. Analysis of H2A and H3 variant combinations composing nucleosomes revealed that the H2A.Z and H3.3 combinations were present at a higher frequency throughout the genome than the other combinations, suggesting that H2A.Z and H3.3 associate preferentially with each other to comprise the nucleosomes independently of genome region. Finally, we found that chromatin was unstable only in regions where it was enriched in both H2A.Z and H3.3, but strongly quantified stable in regions in which only H3.3 was abundant. Therefore, histone variant composition is an important determinant of chromatin structure, which is associated with specific genomic functions.

Bioinformatics analysis of the factors controlling type I IFN gene expression in autoimmune disease and virus-induced immunity

Patients with systemic lupus erythematosus (SLE) and Sjögren’s syndrome (SS) display increased levels of type I interferon (IFN)-induced genes. Plasmacytoid dendritic cells (PDCs) are natural interferon producing cells and considered to be a primary source of IFN-α in these two diseases. Differential expression patterns of type I IFN-inducible transcripts can be found in different immune cell subsets and in patients with both active and inactive autoimmune disease. A type I IFN gene signature generally consists of three groups of IFN-induced genes – those regulated in response to virus-induced type I IFN, those regulated by the IFN-induced mitogen-activated protein kinase/extracellular-regulated kinase (MAPK/ERK) pathway, and those by the IFN-induced phosphoinositide-3 kinase (PI-3K) pathway. These three groups of type I IFN-regulated genes control important cellular processes such as apoptosis, survival, adhesion, and chemotaxis, that when dysregulated, contribute to autoimmunity. With the recent generation of large datasets in the public domain from next-generation sequencing and DNA microarray experiments, one can perform detailed analyses of cell-type specific gene signatures as well as identify distinct transcription factors (TFs) that differentially regulate these gene signatures. We have performed bioinformatics analysis of data in the public domain and experimental data from our lab to gain insight into the regulation of type I IFN gene expression. We have found that the genetic landscape of the IFNA and IFNB genes are occupied by TFs, such as insulators CTCF and cohesin, that negatively regulate transcription, as well as interferon regulatory factor (IRF)5 and IRF7, that positively and distinctly regulate IFNA subtypes. A detailed understanding of the factors controlling type I IFN gene transcription will significantly aid in the identification and development of new therapeutic strategies targeting the IFN pathway in autoimmune disease.