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Abstract Background Standard ChIP-seq and RNA-seq processing pipelines typically disregard sequencing reads whose origin is ambiguous (“multimappers”). This usual practice has potentially important consequences for the functional interpretation of the data: genomic elements belonging to clusters composed of highly similar members are left unexplored. Results In particular, disregarding multimappers leads to the underrepresentation in epigenetic studies of recently active transposable elements, such as AluYa5, L1HS and SVAs. Furthermore, this common strategy also has implications for transcriptomic analysis: members of repetitive gene families, such the ones including major histocompatibility complex (MHC) class I and II genes, are under-quantified. Conclusion Revealing inherent biases that permeate routine tasks such as functional enrichment analysis, our results underscore the urgency of broadly adopting multimapper-aware bioinformatic pipelines –currently restricted to specific contexts or communities– to ensure the reliability of genomic and transcriptomic studies.

Abstract Background Fatty liver hemorrhagic syndrome (FLHS) in the modern poultry industry is primarily caused by nutrition. Despite encouraging progress on FLHS, the mechanism through which nutrition influences susceptibility to FLHS is still lacking in terms of epigenetics. Results In this study, we analyzed the genome-wide patterns of trimethylated lysine residue 27 of histone H3 (H3K27me3) enrichment by chromatin immunoprecipitation-sequencing (ChIP-seq), and examined its association with transcriptomes in healthy and FLHS hens. The study results indicated that H3K27me3 levels were increased in the FLHS hens on a genome-wide scale. Additionally, H3K27me3 was found to occupy the entire gene and the distant intergenic region, which may function as silencer-like regulatory elements. The analysis of transcription factor (TF) motifs in hypermethylated peaks has demonstrated that 23 TFs are involved in the regulation of liver metabolism and development. Transcriptomic analysis indicated that differentially expressed genes (DEGs) were enriched in fatty acid metabolism, amino acid, and carbohydrate metabolism. The hub gene identified from PPI network is fatty acid synthase (FASN). Combined ChIP-seq and transcriptome analysis revealed that the increased H3K27me3 and down-regulated genes have significant enrichment in the ECM-receptor interaction, tight junction, cell adhesion molecules, adherens junction, and TGF-beta signaling pathways. Conclusions Overall, the trimethylation modification of H3K27 has been shown to have significant regulatory function in FLHS, mediating the expression of crucial genes associated with the ECM-receptor interaction pathway. This highlights the epigenetic mechanisms of H3K27me3 and provides insights into exploring core regulatory targets and nutritional regulation strategies in FLHS.

Background: Standard ChIP-seq and RNA-seq processing pipelines typically disregard sequencing reads whose origin is ambiguous ("multimappers"). This usual practice has potentially important consequences for the functional interpretation of the data: genomic elements belonging to clusters composed of highly similar members are left unexplored. Results: In particular, disregarding multimappers leads to the underrepresentation in epigenetic studies of recently active transposable elements, such as AluYa5, L1HS and SVAs. Furthermore, this common strategy also has implications for transcriptomic analysis: members of repetitive gene families, such the ones including major histocompatibility complex (MHC) class I and II genes, are under-quantified. Conclusion: Revealing inherent biases that permeate routine tasks such as functional enrichment analysis, our results underscore the urgency of broadly adopting multimapper-aware bioinformatic pipelines –currently restricted to specific contexts or communities– to ensure the reliability of genomic and transcriptomic studies. [ABSTRACT FROM AUTHOR]

Background: Fatty liver hemorrhagic syndrome (FLHS) in the modern poultry industry is primarily caused by nutrition. Despite encouraging progress on FLHS, the mechanism through which nutrition influences susceptibility to FLHS is still lacking in terms of epigenetics. Results: In this study, we analyzed the genome-wide patterns of trimethylated lysine residue 27 of histone H3 (H3K27me3) enrichment by chromatin immunoprecipitation-sequencing (ChIP-seq), and examined its association with transcriptomes in healthy and FLHS hens. The study results indicated that H3K27me3 levels were increased in the FLHS hens on a genome-wide scale. Additionally, H3K27me3 was found to occupy the entire gene and the distant intergenic region, which may function as silencer-like regulatory elements. The analysis of transcription factor (TF) motifs in hypermethylated peaks has demonstrated that 23 TFs are involved in the regulation of liver metabolism and development. Transcriptomic analysis indicated that differentially expressed genes (DEGs) were enriched in fatty acid metabolism, amino acid, and carbohydrate metabolism. The hub gene identified from PPI network is fatty acid synthase (FASN). Combined ChIP-seq and transcriptome analysis revealed that the increased H3K27me3 and down-regulated genes have significant enrichment in the ECM-receptor interaction, tight junction, cell adhesion molecules, adherens junction, and TGF-beta signaling pathways. Conclusions: Overall, the trimethylation modification of H3K27 has been shown to have significant regulatory function in FLHS, mediating the expression of crucial genes associated with the ECM-receptor interaction pathway. This highlights the epigenetic mechanisms of H3K27me3 and provides insights into exploring core regulatory targets and nutritional regulation strategies in FLHS. [ABSTRACT FROM AUTHOR]

Abstract Background There are two major genetic types of Epstein-Barr Virus (EBV): type 1 (EBV-1) and type 2 (EBV-2). EBV functions by manipulating gene expression in host B cells, using virus-encoded gene regulatory proteins including Epstein-Barr Nuclear Antigen 2 (EBNA2). While type 1 EBNA2 is known to interact with human transcription factors (hTFs) such as RBPJ, EBF1, and SPI1 (PU.1), type 2 EBNA2 shares only ~ 50% amino acid identity with type 1 and thus may have distinct binding partners, human genome binding locations, and functions. Results In this study, we examined genome-wide EBNA2 binding in EBV-1 and EBV-2 transformed human B cells to identify shared and unique EBNA2 interactions with the human genome, revealing thousands of type-specific EBNA2 ChIP-seq peaks. Computational predictions based on hTF motifs and subsequent ChIP-seq experiments revealed that both type 1 and 2 EBNA2 co-occupy the genome with SPI1 and AP-1 (BATF and JUNB) hTFs. However, type 1 EBNA2 showed preferential co-occupancy with EBF1, and type 2 EBNA2 preferred RBPJ. These differences in hTF co-occupancy revealed possible mechanisms underlying type-specific gene expression of known EBNA2 human target genes: MYC (shared), CXCR7 (type 1 specific), and CD21 (type 2 specific). Both type 1 and 2 EBNA2 binding events were enriched at systemic lupus erythematosus (SLE) and multiple sclerosis (MS) risk loci, while primary biliary cholangitis (PBC) risk loci were specifically enriched for type 2 peaks. Conclusions This study reveals extensive type-specific EBNA2 interactions with the human genome, possible differences in EBNA2 interaction partners, and a possible new role for type 2 EBNA2 in autoimmune disorders. Our results highlight the importance of considering EBV type in the control of human gene expression and disease-related investigations.

Abstract Background Switchgrass (Panicum virgatum L.) is a warm-season perennial (C4) grass identified as an important biofuel crop in the United States. It is well adapted to the marginal environment where heat and moisture stresses predominantly affect crop growth. However, the underlying molecular mechanisms associated with heat and drought stress tolerance still need to be fully understood in switchgrass. The methylation of H3K4 is often associated with transcriptional activation of genes, including stress-responsive. Therefore, this study aimed to analyze genome-wide histone H3K4-tri-methylation in switchgrass under heat, drought, and combined stress. Results In total, ~ 1.3 million H3K4me3 peaks were identified in this study using SICER. Among them, 7,342; 6,510; and 8,536 peaks responded under drought (DT), drought and heat (DTHT), and heat (HT) stresses, respectively. Most DT and DTHT peaks spanned 0 to + 2000 bases from the transcription start site [TSS]. By comparing differentially marked peaks with RNA-Seq data, we identified peaks associated with genes: 155 DT-responsive peaks with 118 DT-responsive genes, 121 DTHT-responsive peaks with 110 DTHT-responsive genes, and 175 HT-responsive peaks with 136 HT-responsive genes. We have identified various transcription factors involved in DT, DTHT, and HT stresses. Gene Ontology analysis using the AgriGO revealed that most genes belonged to biological processes. Most annotated peaks belonged to metabolite interconversion, RNA metabolism, transporter, protein modifying, defense/immunity, membrane traffic protein, transmembrane signal receptor, and transcriptional regulator protein families. Further, we identified significant peaks associated with TFs, hormones, signaling, fatty acid and carbohydrate metabolism, and secondary metabolites. qRT-PCR analysis revealed the relative expressions of six abiotic stress-responsive genes (transketolase, chromatin remodeling factor-CDH3, fatty-acid desaturase A, transmembrane protein 14C, beta-amylase 1, and integrase-type DNA binding protein genes) that were significantly (P

Abstract Background Transcription factors (TFs) exhibit heterogeneous DNA-binding specificities in individual cells and whole organisms under natural conditions, and de novo motif discovery usually provides multiple motifs, even from a single chromatin immunoprecipitation-sequencing (ChIP-seq) sample. Despite the accumulation of ChIP-seq data and ChIP-seq-derived motifs, the diversity of DNA-binding specificities across different TFs and cell types remains largely unexplored. Results Here, we applied MOCCS2, our k-mer-based motif discovery method, to a collection of human TF ChIP-seq samples across diverse TFs and cell types, and systematically computed profiles of TF-binding specificity scores for all k-mers. After quality control, we compiled a set of TF-binding specificity score profiles for 2,976 high-quality ChIP-seq samples, comprising 473 TFs and 398 cell types. Using these high-quality samples, we confirmed that the k-mer-based TF-binding specificity profiles reflected TF- or TF-family dependent DNA-binding specificities. We then compared the binding specificity scores of ChIP-seq samples with the same TFs but with different cell type classes and found that half of the analyzed TFs exhibited differences in DNA-binding specificities across cell type classes. Additionally, we devised a method to detect differentially bound k-mers between two ChIP-seq samples and detected k-mers exhibiting statistically significant differences in binding specificity scores. Moreover, we demonstrated that differences in the binding specificity scores between k-mers on the reference and alternative alleles could be used to predict the effect of variants on TF binding, as validated by in vitro and in vivo assay datasets. Finally, we demonstrated that binding specificity score differences can be used to interpret disease-associated non-coding single-nucleotide polymorphisms (SNPs) as TF-affecting SNPs and provide candidates responsible for TFs and cell types. Conclusions Our study provides a basis for investigating the regulation of gene expression in a TF-, TF family-, or cell-type-dependent manner. Furthermore, our differential analysis of binding-specificity scores highlights noncoding disease-associated variants in humans.

Abstract Background Genomics data is available to the scientific community after publication of research projects and can be investigated for a multitude of research questions. However, in many cases deposited data is only assessed and used for the initial publication, resulting in valuable resources not being exploited to their full depth. Main A likely reason for this is that many wetlab-based researchers are not formally trained to apply bioinformatic tools and may therefore assume that they lack the necessary experience to do so themselves. In this article, we present a series of freely available, predominantly web-based platforms and bioinformatic tools that can be combined in analysis pipelines to interrogate different types of next-generation sequencing data. Additionally to the presented exemplary route, we also list a number of alternative tools that can be combined in a mix-and-match fashion. We place special emphasis on tools that can be followed and used correctly without extensive prior knowledge in programming. Such analysis pipelines can be applied to existing data downloaded from the public domain or be compared to the results of own experiments. Conclusion Integrating transcription factor binding to chromatin (ChIP-seq) with transcriptional output (RNA-seq) and chromatin accessibility (ATAC-seq) can not only assist to form a deeper understanding of the molecular interactions underlying transcriptional regulation but will also help establishing new hypotheses and pre-testing them in silico.

Background: Transcription factors (TFs) exhibit heterogeneous DNA-binding specificities in individual cells and whole organisms under natural conditions, and de novo motif discovery usually provides multiple motifs, even from a single chromatin immunoprecipitation-sequencing (ChIP-seq) sample. Despite the accumulation of ChIP-seq data and ChIP-seq-derived motifs, the diversity of DNA-binding specificities across different TFs and cell types remains largely unexplored. Results: Here, we applied MOCCS2, our k-mer-based motif discovery method, to a collection of human TF ChIP-seq samples across diverse TFs and cell types, and systematically computed profiles of TF-binding specificity scores for all k-mers. After quality control, we compiled a set of TF-binding specificity score profiles for 2,976 high-quality ChIP-seq samples, comprising 473 TFs and 398 cell types. Using these high-quality samples, we confirmed that the k-mer-based TF-binding specificity profiles reflected TF- or TF-family dependent DNA-binding specificities. We then compared the binding specificity scores of ChIP-seq samples with the same TFs but with different cell type classes and found that half of the analyzed TFs exhibited differences in DNA-binding specificities across cell type classes. Additionally, we devised a method to detect differentially bound k-mers between two ChIP-seq samples and detected k-mers exhibiting statistically significant differences in binding specificity scores. Moreover, we demonstrated that differences in the binding specificity scores between k-mers on the reference and alternative alleles could be used to predict the effect of variants on TF binding, as validated by in vitro and in vivo assay datasets. Finally, we demonstrated that binding specificity score differences can be used to interpret disease-associated non-coding single-nucleotide polymorphisms (SNPs) as TF-affecting SNPs and provide candidates responsible for TFs and cell types. Conclusions: Our study provides a basis for investigating the regulation of gene expression in a TF-, TF family-, or cell-type-dependent manner. Furthermore, our differential analysis of binding-specificity scores highlights noncoding disease-associated variants in humans. [ABSTRACT FROM AUTHOR]

Background: Genomics data is available to the scientific community after publication of research projects and can be investigated for a multitude of research questions. However, in many cases deposited data is only assessed and used for the initial publication, resulting in valuable resources not being exploited to their full depth. Main: A likely reason for this is that many wetlab-based researchers are not formally trained to apply bioinformatic tools and may therefore assume that they lack the necessary experience to do so themselves. In this article, we present a series of freely available, predominantly web-based platforms and bioinformatic tools that can be combined in analysis pipelines to interrogate different types of next-generation sequencing data. Additionally to the presented exemplary route, we also list a number of alternative tools that can be combined in a mix-and-match fashion. We place special emphasis on tools that can be followed and used correctly without extensive prior knowledge in programming. Such analysis pipelines can be applied to existing data downloaded from the public domain or be compared to the results of own experiments. Conclusion: Integrating transcription factor binding to chromatin (ChIP-seq) with transcriptional output (RNA-seq) and chromatin accessibility (ATAC-seq) can not only assist to form a deeper understanding of the molecular interactions underlying transcriptional regulation but will also help establishing new hypotheses and pre-testing them in silico. [ABSTRACT FROM AUTHOR]

Abstract Background Epigenomic profiling assays such as ChIP-seq have been widely used to map the genome-wide enrichment profiles of chromatin-associated proteins and posttranslational histone modifications. Sequencing depth is a key parameter in experimental design and quality control. However, due to variable sequencing depth requirements across experimental conditions, it can be challenging to determine optimal sequencing depth, particularly for projects involving multiple targets or cell types. Results We developed the peaksat R package to provide target read depth estimates for epigenomic experiments based on the analysis of peak saturation curves. We applied peaksat to establish the distinctive read depth requirements for ChIP-seq studies of histone modifications in different cell lines. Using peaksat, we were able to estimate the target read depth required per library to obtain high-quality peak calls for downstream analysis. In addition, peaksat was applied to other sequence-enrichment methods including CUT&RUN and ATAC-seq. Conclusion peaksat addresses a need for researchers to make informed decisions about whether their sequencing data has been generated to an adequate depth and subsequently sufficient meaningful peaks, and failing that, how many more reads would be required per library. peaksat is applicable to other sequence-based methods that include calling peaks in their analysis.

Abstract Background The cis-regulatory element became increasingly important for resistance breeding. There were many DNA variations identified by resequencing. To investigate the links between the DNA variations and cis-regulatory element was the fundamental work. DNA variations in cis-regulatory elements caused phenotype variations in general. Results We used WGBS, ChIP-seq and RNA-seq technology to decipher the regulatory element landscape from eight hulless barley varieties under four kinds of abiotic stresses. We discovered 231,440 lowly methylated regions (LMRs) from the methylome data of eight varieties. The LMRs mainly distributed in the intergenic regions. A total of 97,909 enhancer-gene pairs were identified from the correlation analysis between methylation degree and expression level. A lot of enriched motifs were recognized from the tolerant-specific LMRs. The key transcription factors were screened out and the transcription factor regulatory network was inferred from the enhancer-gene pairs data for drought stress. The NAC transcription factor was predicted to target to TCP, bHLH, bZIP transcription factor genes. We concluded that the H3K27me3 modification regions overlapped with the LMRs more than the H3K4me3. The variation of single nucleotide polymorphism was more abundant in LMRs than the remain regions of the genome. Conclusions Epigenetic regulation is an important mechanism for organisms to adapt to complex environments. Through the study of DNA methylation and histone modification, we found that many changes had taken place in enhancers and transcription factors in the abiotic stress of hulless barley. For example, transcription factors including NAC may play an important role. This enriched the molecular basis of highland barley stress response.

Abstract Background Causal variants for complex traits, such as eQTL are often found in non-coding regions of the genome, where they are hypothesised to influence phenotypes by regulating gene expression. Many regulatory regions are marked by histone modifications, which can be assayed by chromatin immunoprecipitation followed by sequencing (ChIP-seq). Sequence reads from ChIP-seq form peaks at putative regulatory regions, which may reflect the amount of regulatory activity at this region. Therefore, eQTL which are also associated with differences in histone modifications are excellent candidate causal variants. Results We assayed the histone modifications H3K4Me3, H3K4Me1 and H3K27ac and mRNA in the mammary gland of up to 400 animals. We identified QTL for peak height (histone QTL), exon expression (eeQTL), allele specific expression (aseQTL) and allele specific binding (asbQTL). By intersecting these results, we identify variants which may influence gene expression by altering regulatory regions of the genome, and may be causal variants for other traits. Lastly, we find that these variants are found in putative transcription factor binding sites, identifying a mechanism for the effect of many eQTL. Conclusions We find that allele specific and traditional QTL analysis often identify the same genetic variants and provide evidence that many eQTL are regulatory variants which alter activity at regulatory regions of the bovine genome. Our work provides methodological and biological updates on how regulatory mechanisms interplay at multi-omics levels.

Background: Epigenomic profiling assays such as ChIP-seq have been widely used to map the genome-wide enrichment profiles of chromatin-associated proteins and posttranslational histone modifications. Sequencing depth is a key parameter in experimental design and quality control. However, due to variable sequencing depth requirements across experimental conditions, it can be challenging to determine optimal sequencing depth, particularly for projects involving multiple targets or cell types. Results: We developed the peaksat R package to provide target read depth estimates for epigenomic experiments based on the analysis of peak saturation curves. We applied peaksat to establish the distinctive read depth requirements for ChIP-seq studies of histone modifications in different cell lines. Using peaksat, we were able to estimate the target read depth required per library to obtain high-quality peak calls for downstream analysis. In addition, peaksat was applied to other sequence-enrichment methods including CUT&RUN and ATAC-seq. Conclusion: peaksat addresses a need for researchers to make informed decisions about whether their sequencing data has been generated to an adequate depth and subsequently sufficient meaningful peaks, and failing that, how many more reads would be required per library. peaksat is applicable to other sequence-based methods that include calling peaks in their analysis. [ABSTRACT FROM AUTHOR]

Abstract Background Transcription factors (TFs) play central roles in regulating gene expression. With the rapid growth in the use of high-throughput sequencing methods, there is a need to develop a comprehensive data processing and analyzing framework for inferring influential TFs based on ChIP-seq/ATAC-seq datasets. Results Here, we introduce FindIT2 (Find Influential TFs and Targets), an R/Bioconductor package for annotating and processing high-throughput multi-omics data. FindIT2 supports a complete framework for annotating ChIP-seq/ATAC-seq peaks, identifying TF targets by the combination of ChIP-seq and RNA-seq datasets, and inferring influential TFs based on different types of data input. Moreover, benefited from the annotation framework based on Bioconductor, FindIT2 can be applied to any species with genomic annotations, which is particularly useful for the non-model species that are less well-studied. Conclusion FindIT2 provides a user-friendly and flexible framework to generate results at different levels according to the richness of the annotation information of user’s species. FindIT2 is compatible with all the operating systems and is released under Artistic-2.0 License. The source code and documents are freely available through Bioconductor ( https://bioconductor.org/packages/devel/bioc/html/FindIT2.html ).

Abstract Background Toxoplasma gondii is a protozoan parasite that differentiates from acute tachyzoite stages to latent bradyzoite forms in response to environmental cues that modify the epigenome. We studied the distribution of the histone variants CenH3, H3.3, H2A.X, H2A.Z and H2B.Z, by genome-wide chromatin immunoprecipitation to understand the role of variant histones in developmental transitions of T. gondii parasites. Results H3.3 and H2A.X were detected in telomere and telomere associated sequences, whereas H3.3, H2A.X and CenH3 were enriched in centromeres. Histones H2A.Z and H2B.Z colocalize with the transcriptional activation mark H3K4me3 in promoter regions surrounding the nucleosome-free region upstream of the transcription start site. The H2B.Z/H2A.Z histone pair also localizes to the gene bodies of genes that are silent but poised for activation, including bradyzoite stage-specific genes. The majority of H2A.X and H2A.Z/H2B.Z loci do not overlap, consistent with variant histones demarcating specific functional regions of chromatin. The extent of enrichment of H2A.Z/H2B.Z (and H3.3 and H2A.X) within the entire gene (5’UTR and gene body) reflects the timing of gene expression during the cell cycle, suggesting that dynamic turnover of H2B.Z/H2A.Z occurs during the tachyzoite cell cycle. Thus, the distribution of the variant histone H2A.Z/H2B.Z dimer defines active and developmentally silenced regions of the T. gondii epigenome including genes that are poised for expression. Conclusions Histone variants mark functional regions of parasite genomes with the dynamic placement of the H2A.Z/H2B.Z dimer implicated as an evolutionarily conserved regulator of parasite and eukaryotic differentiation.

Background: The cis-regulatory element became increasingly important for resistance breeding. There were many DNA variations identified by resequencing. To investigate the links between the DNA variations and cis-regulatory element was the fundamental work. DNA variations in cis-regulatory elements caused phenotype variations in general. Results: We used WGBS, ChIP-seq and RNA-seq technology to decipher the regulatory element landscape from eight hulless barley varieties under four kinds of abiotic stresses. We discovered 231,440 lowly methylated regions (LMRs) from the methylome data of eight varieties. The LMRs mainly distributed in the intergenic regions. A total of 97,909 enhancer-gene pairs were identified from the correlation analysis between methylation degree and expression level. A lot of enriched motifs were recognized from the tolerant-specific LMRs. The key transcription factors were screened out and the transcription factor regulatory network was inferred from the enhancer-gene pairs data for drought stress. The NAC transcription factor was predicted to target to TCP, bHLH, bZIP transcription factor genes. We concluded that the H3K27me3 modification regions overlapped with the LMRs more than the H3K4me3. The variation of single nucleotide polymorphism was more abundant in LMRs than the remain regions of the genome. Conclusions: Epigenetic regulation is an important mechanism for organisms to adapt to complex environments. Through the study of DNA methylation and histone modification, we found that many changes had taken place in enhancers and transcription factors in the abiotic stress of hulless barley. For example, transcription factors including NAC may play an important role. This enriched the molecular basis of highland barley stress response. [ABSTRACT FROM AUTHOR]

Background: Causal variants for complex traits, such as eQTL are often found in non-coding regions of the genome, where they are hypothesised to influence phenotypes by regulating gene expression. Many regulatory regions are marked by histone modifications, which can be assayed by chromatin immunoprecipitation followed by sequencing (ChIP-seq). Sequence reads from ChIP-seq form peaks at putative regulatory regions, which may reflect the amount of regulatory activity at this region. Therefore, eQTL which are also associated with differences in histone modifications are excellent candidate causal variants. Results: We assayed the histone modifications H3K4Me3, H3K4Me1 and H3K27ac and mRNA in the mammary gland of up to 400 animals. We identified QTL for peak height (histone QTL), exon expression (eeQTL), allele specific expression (aseQTL) and allele specific binding (asbQTL). By intersecting these results, we identify variants which may influence gene expression by altering regulatory regions of the genome, and may be causal variants for other traits. Lastly, we find that these variants are found in putative transcription factor binding sites, identifying a mechanism for the effect of many eQTL. Conclusions: We find that allele specific and traditional QTL analysis often identify the same genetic variants and provide evidence that many eQTL are regulatory variants which alter activity at regulatory regions of the bovine genome. Our work provides methodological and biological updates on how regulatory mechanisms interplay at multi-omics levels. [ABSTRACT FROM AUTHOR]

BackgroundThe transcriptional corepressor Groucho (Gro) is required for the function of many developmentally regulated DNA binding repressors, thus helping to define the gene expression profile of each cell during development. The ability of Gro to repress transcription at a distance together with its ability to oligomerize and bind to histones has led to the suggestion that Gro may spread along chromatin. However, much is unknown about the mechanism of Gro-mediated repression and about the dynamics of Gro targeting.ResultsOur chromatin immunoprecipitation sequencing analysis of temporally staged Drosophila embryos shows that Gro binds in a highly dynamic manner primarily to clusters of discrete (

Abstract Background Estrogen plays an essential role in female development and reproductive function. In chickens, estrogen is critical for lipid metabolism in the liver. The regulatory molecular network of estrogen in chicken liver is poorly understood. To identify estrogen-responsive genes and estrogen functional sites on a genome-wide scale, we determined expression profiles of mRNAs, lncRNAs, and miRNAs in estrogen-treated ((17β-estradiol)) and control chicken livers using RNA-Sequencing (RNA-Seq) and studied the estrogen receptor α binding sites by ChIP-Sequencing (ChIP-Seq). Results We identified a total of 990 estrogen-responsive genes, including 962 protein-coding genes, 11 miRNAs, and 17 lncRNAs. Functional enrichment analyses showed that the estrogen-responsive genes were highly enriched in lipid metabolism and biological processes. Integrated analysis of the data of RNA-Seq and ChIP-Seq, identified 191 genes directly targeted by estrogen, including 185 protein-coding genes, 4 miRNAs, and 2 lncRNAs. In vivo and in vitro experiments showed that estrogen decreased the mRNA expression of PPARGC1B, which had been reported to be linked with lipid metabolism, by directly increasing the expression of miR-144-3p. Conclusions These results increase our understanding of the functional network of estrogen in chicken liver and also reveal aspects of the molecular mechanism of estrogen-related lipid metabolism.

Abstract Background Transcription factors (TFs) bind specifically to TF binding sites (TFBSs) at cis-regulatory regions to control transcription. It is critical to locate these TF-DNA interactions to understand transcriptional regulation. Efforts to predict bona fide TFBSs benefit from the availability of experimental data mapping DNA binding regions of TFs (chromatin immunoprecipitation followed by sequencing - ChIP-seq). Results In this study, we processed ~ 10,000 public ChIP-seq datasets from nine species to provide high-quality TFBS predictions. After quality control, it culminated with the prediction of ~ 56 million TFBSs with experimental and computational support for direct TF-DNA interactions for 644 TFs in > 1000 cell lines and tissues. These TFBSs were used to predict > 197,000 cis-regulatory modules representing clusters of binding events in the corresponding genomes. The high-quality of the TFBSs was reinforced by their evolutionary conservation, enrichment at active cis-regulatory regions, and capacity to predict combinatorial binding of TFs. Further, we confirmed that the cell type and tissue specificity of enhancer activity was correlated with the number of TFs with binding sites predicted in these regions. All the data is provided to the community through the UniBind database that can be accessed through its web-interface ( https://unibind.uio.no/ ), a dedicated RESTful API, and as genomic tracks. Finally, we provide an enrichment tool, available as a web-service and an R package, for users to find TFs with enriched TFBSs in a set of provided genomic regions. Conclusions UniBind is the first resource of its kind, providing the largest collection of high-confidence direct TF-DNA interactions in nine species.

Background: Transcription factors (TFs) play central roles in regulating gene expression. With the rapid growth in the use of high-throughput sequencing methods, there is a need to develop a comprehensive data processing and analyzing framework for inferring influential TFs based on ChIP-seq/ATAC-seq datasets. Results: Here, we introduce FindIT2 (Find Influential TFs and Targets), an R/Bioconductor package for annotating and processing high-throughput multi-omics data. FindIT2 supports a complete framework for annotating ChIP-seq/ATAC-seq peaks, identifying TF targets by the combination of ChIP-seq and RNA-seq datasets, and inferring influential TFs based on different types of data input. Moreover, benefited from the annotation framework based on Bioconductor, FindIT2 can be applied to any species with genomic annotations, which is particularly useful for the non-model species that are less well-studied. Conclusion: FindIT2 provides a user-friendly and flexible framework to generate results at different levels according to the richness of the annotation information of user's species. FindIT2 is compatible with all the operating systems and is released under Artistic-2.0 License. The source code and documents are freely available through Bioconductor (https://bioconductor.org/packages/devel/bioc/html/FindIT2.html). [ABSTRACT FROM AUTHOR]

Background: Toxoplasma gondii is a protozoan parasite that differentiates from acute tachyzoite stages to latent bradyzoite forms in response to environmental cues that modify the epigenome. We studied the distribution of the histone variants CenH3, H3.3, H2A.X, H2A.Z and H2B.Z, by genome-wide chromatin immunoprecipitation to understand the role of variant histones in developmental transitions of T. gondii parasites. Results: H3.3 and H2A.X were detected in telomere and telomere associated sequences, whereas H3.3, H2A.X and CenH3 were enriched in centromeres. Histones H2A.Z and H2B.Z colocalize with the transcriptional activation mark H3K4me3 in promoter regions surrounding the nucleosome-free region upstream of the transcription start site. The H2B.Z/H2A.Z histone pair also localizes to the gene bodies of genes that are silent but poised for activation, including bradyzoite stage-specific genes. The majority of H2A.X and H2A.Z/H2B.Z loci do not overlap, consistent with variant histones demarcating specific functional regions of chromatin. The extent of enrichment of H2A.Z/H2B.Z (and H3.3 and H2A.X) within the entire gene (5'UTR and gene body) reflects the timing of gene expression during the cell cycle, suggesting that dynamic turnover of H2B.Z/H2A.Z occurs during the tachyzoite cell cycle. Thus, the distribution of the variant histone H2A.Z/H2B.Z dimer defines active and developmentally silenced regions of the T. gondii epigenome including genes that are poised for expression. Conclusions: Histone variants mark functional regions of parasite genomes with the dynamic placement of the H2A.Z/H2B.Z dimer implicated as an evolutionarily conserved regulator of parasite and eukaryotic differentiation. [ABSTRACT FROM AUTHOR]

Abstract Background RNA-Seq, the high-throughput sequencing (HT-Seq) of mRNAs, has become an essential tool for characterizing gene expression differences between different cell types and conditions. Gene expression is regulated by several mechanisms, including epigenetically by post-translational histone modifications which can be assessed by ChIP-Seq (Chromatin Immuno-Precipitation Sequencing). As more and more biological samples are analyzed by the combination of ChIP-Seq and RNA-Seq, the integrated analysis of the corresponding data sets becomes, theoretically, a unique option to study gene regulation. However, technically such analyses are still in their infancy. Results Here we introduce intePareto, a computational tool for the integrative analysis of RNA-Seq and ChIP-Seq data. With intePareto we match RNA-Seq and ChIP-Seq data at the level of genes, perform differential expression analysis between biological conditions, and prioritize genes with consistent changes in RNA-Seq and ChIP-Seq data using Pareto optimization. Conclusion intePareto facilitates comprehensive understanding of high dimensional transcriptomic and epigenomic data. Its superiority to a naive differential gene expression analysis with RNA-Seq and available integrative approach is demonstrated by analyzing a public dataset.

BackgroundThe ZNF217 gene, encoding a C2H2 zinc finger protein, is located at 20q13 and found amplified and overexpressed in greater than 20% of breast tumors. Current studies indicate ZNF217 drives tumorigenesis, yet the regulatory mechanisms of ZNF217 are largely unknown. Because ZNF217 associates with chromatin modifying enzymes, we postulate that ZNF217 functions to regulate specific gene signaling networks. Here, we present a large-scale functional genomic analysis of ZNF217, which provides insights into the regulatory role of ZNF217 in MCF7 breast cancer cells.ResultsChIP-seq analysis reveals that the majority of ZNF217 binding sites are located at distal regulatory regions associated with the chromatin marks H3K27ac and H3K4me1. Analysis of ChIP-seq transcription factor binding sites shows clustering of ZNF217 with FOXA1, GATA3 and ERalpha binding sites, supported by the enrichment of corresponding motifs for the ERalpha-associated cis-regulatory sequences. ERalpha expression highly correlates with ZNF217 in lysates from breast tumors (n = 15), and ERalpha co-precipitates ZNF217 and its binding partner CtBP2 from nuclear extracts. Transcriptome profiling following ZNF217 depletion identifies differentially expressed genes co-bound by ZNF217 and ERalpha; gene ontology suggests a role for ZNF217-ERalpha in expression programs associated with ER+ breast cancer studies found in the Molecular Signature Database. Data-mining of expression data from breast cancer patients correlates ZNF217 with reduced overall survival.ConclusionsOur genome-wide ZNF217 data suggests a functional role for ZNF217 at ERalpha target genes. Future studies will investigate whether ZNF217 expression contributes to aberrant ERalpha regulatory events in ER+ breast cancer and hormone resistance.

Abstract Background Knowledge of the three-dimensional structure of the genome is necessary to understand how gene expression is regulated. Recent experimental techniques such as Hi-C or ChIA-PET measure long-range chromatin interactions genome-wide but are experimentally elaborate, have limited resolution and such data is only available for a limited number of cell types and tissues. Results While ChIP-seq was not designed to detect chromatin interactions, the formaldehyde treatment in the ChIP-seq protocol cross-links proteins with each other and with DNA. Consequently, also regions that are not directly bound by the targeted TF but interact with the binding site via chromatin looping are co-immunoprecipitated and sequenced. This produces minor ChIP-seq signals at loop anchor regions close to the directly bound site. We use the position and shape of ChIP-seq signals around CTCF motif pairs to predict whether they interact or not. We implemented this approach in a prediction method, termed Computational Chromosome Conformation Capture by Correlation of ChIP-seq at CTCF motifs (7C). We applied 7C to all CTCF motif pairs within 1 Mb in the human genome and validated predicted interactions with high-resolution Hi-C and ChIA-PET. A single ChIP-seq experiment from known architectural proteins (CTCF, Rad21, Znf143) but also from other TFs (like TRIM22 or RUNX3) predicts loops accurately. Importantly, 7C predicts loops in cell types and for TF ChIP-seq datasets not used in training. Conclusion 7C predicts chromatin loops which can help to associate TF binding sites to regulated genes. Furthermore, profiling of hundreds of ChIP-seq datasets results in novel candidate factors functionally involved in chromatin looping. Our method is available as an R/Bioconductor package: http://bioconductor.org/packages/sevenC.

Abstract Background Histone modifications play a significant role in the regulation of transcription and various biological processes, such as development and regeneration. Though a few genomic (including DNA methylation patterns) and transcriptomic studies are currently available in switchgrass, the genome-wide distribution of histone modifications has not yet been studied to help elucidate gene regulation and its application to switchgrass improvement. Results This study provides a comprehensive epigenomic analyses of two contrasting switchgrass ecotypes, lowland (AP13) and upland (VS16), by employing chromatin immunoprecipitation sequencing (ChIP-Seq) with two histone marks (suppressive- H3K9me2 and active- H4K12ac). In this study, most of the histone binding was in non-genic regions, and the highest enrichment was seen between 0 and 2 kb regions from the transcriptional start site (TSS). Considering the economic importance and potential of switchgrass as a bioenergy crop, we focused on genes, transcription factors (TFs), and pathways that were associated with C4-photosynthesis, biomass, biofuel production, biotic stresses, and abiotic stresses. Using quantitative real-time PCR (qPCR) the relative expression of five genes selected from the phenylpropanoid-monolignol pathway showed preferential binding of acetylation marks in AP13 rather than in VS16. Conclusions The genome-wide histone modifications reported here can be utilized in understanding the regulation of genes important in the phenylpropanoid–monolignol biosynthesis pathway, which in turn, may help understand the recalcitrance associated with conversion of biomass to biofuel, a major roadblock in utilizing lignocellulosic feedstocks.

Abstract Background Mutations in the transcription factor, KLF1, are common within certain populations of the world. Heterozygous missense mutations in KLF1 mostly lead to benign phenotypes, but a heterozygous mutation in a DNA-binding residue (E325K in human) results in severe Congenital Dyserythropoietic Anemia type IV (CDA IV); i.e. an autosomal-dominant disorder characterized by neonatal hemolysis. Results To investigate the biochemical and genetic mechanism of CDA IV, we generated murine erythroid cell lines that harbor tamoxifen-inducible (ER™) versions of wild type and mutant KLF1 on a Klf1 −/− genetic background. Nuclear translocation of wild type KLF1 results in terminal erythroid differentiation, whereas mutant KLF1 results in hemolysis without differentiation. The E to K variant binds poorly to the canonical 9 bp recognition motif (NGG-GYG-KGG) genome-wide but binds at high affinity to a corrupted motif (NGG-GRG-KGG). We confirmed altered DNA-binding specificity by quantitative in vitro binding assays of recombinant zinc-finger domains. Our results are consistent with previously reported structural data of KLF-DNA interactions. We employed 4sU-RNA-seq to show that a corrupted transcriptome is a direct consequence of aberrant DNA binding. Conclusions Since all KLF/SP family proteins bind DNA in an identical fashion, these results are likely to be generally applicable to mutations in all family members. Importantly, they explain how certain mutations in the DNA-binding domain of transcription factors can generate neomorphic functions that result in autosomal dominant disease.

Abstract Background Epigenetic dysregulation is involved in the etiology and progression of various human diseases. Formalin-fixed paraffin-embedded (FFPE) samples represent the gold standard for archiving pathology samples, and thus FFPE samples are a major resource of samples in clinical research. However, chromatin-based epigenetic assays in the clinical settings are limited to fresh or frozen samples, and are hampered by low chromatin yield in FFPE samples due to the lack of a reliable and efficient chromatin preparation method. Here, we introduce a new chromatin extraction method from FFPE tissues (Chrom-EX PE) for chromatin-based epigenetic assays. Results During rehydration of FFPE tissues, applying a tissue-level cross-link reversal into the deparaffinized tissue at 65 °C dramatically increased chromatin yield in the soluble fraction. The resulting chromatin is compatible with targeted ChIP-qPCR and genome-wide ChIP-seq approaches. The chromatin prepared by Chrom-EX PE showed a gradual fragmentation pattern with varying incubation temperature. At temperatures below 37 °C, the majority of soluble chromatin is over 1 kb. The soluble chromatin prepared in the range of 45–60 °C showed a typical nucleosomal pattern. And the majority of chromatin prepared at 65 °C is close to mononucleosomal size. These observations indicate that chromatin preparation from FFPE samples can be controlled for downstream chromatin-based epigenetic assays. Conclusions This study provided a new method that achieves efficient extraction of high-quality chromatin suitable for chromatin-based epigenetic assays with less damage on chromatin. This approach may provide a way to circumvent the over-fixed nature of FFPE tissues for future technology development.

Abstract Background Paulownia withes’-broom (PaWB) disease caused by phytoplasma is a serious infectious disease for Paulownia. However, the underlying molecular pathogenesis is not fully understood. Recent studies have demonstrated that histone modifications could play a role in plant defense responses to pathogens. But there is still no available genome-wide histone modification data in non-model ligneous species infected with phytoplasma. Results Here, we provided the first genome-wide profiles of three histone marks (H3K4me3, H3K36me3 and H3K9ac) in Paulownia fortunei under phytoplasma stress by using chromatin immunoprecipitation sequencing (ChIP-Seq). We found that H3K4me3, H3K36me3 and H3K9ac were mainly enriched in the genic regions in P. fortunei with (PFI) and without (PF) phytoplasma infection. ChIP-Seq analysis revealed 1738, 986, and 2577 genes were differentially modified by H3K4me3, H3K36me3 and H3K9ac marks in PFI under phytoplasma infection, respectively. The functional analysis of these genes suggested that most of them were mainly involved in metabolic pathways, biosynthesis of secondary metabolites, phenylpropanoid biosynthesis, plant-pathogen interaction and plant hormone signal transduction. In addition, the combinational analysis of ChIP-Seq and RNA-Seq showed that differential histone methylation and acetylation only affected a small subset of phytoplasma-responsive genes. Conclusions Taken together, this is the first report of integrated analysis of histone modifications and gene expression involved in Paulownia-phytoplasma interaction. Our results will provide the valuable resources for the mechanism studies of gene regulation in non-model plants upon pathogens attack.

Abstract Background Chromatin immunoprecipitation coupled to sequencing (ChIP-seq) is widely used to map histone modifications and transcription factor binding on a genome-wide level. Results We present high-throughput ChIPmentation (HT-ChIPmentation) that eliminates the need for DNA purification prior to library amplification and reduces reverse-crosslinking time from hours to minutes. Conclusions The resulting workflow is easily established, extremely rapid, and compatible with requirements for very low numbers of FACS sorted cells, high-throughput applications and single day data generation.

Abstract Background Chromatin-immunoprecipitation followed by sequencing (ChIP-seq) is the method of choice for mapping genome-wide binding of chromatin-associated factors. However, broadly applicable methods for between-sample comparisons are lacking. Results Here, we introduce SNP-ChIP, a method that leverages small-scale intra-species polymorphisms, mainly SNPs, for quantitative spike-in normalization of ChIP-seq results. Sourcing spike-in material from the same species ensures antibody cross-reactivity and physiological coherence, thereby eliminating two central limitations of traditional spike-in approaches. We show that SNP-ChIP is robust to changes in sequencing depth and spike-in proportions, and reliably identifies changes in overall protein levels, irrespective of changes in binding distribution. Application of SNP-ChIP to test cases from budding yeast meiosis allowed discovery of novel regulators of the chromosomal protein Red1 and quantitative analysis of the DNA-damage associated histone modification γ-H2AX. Conclusion SNP-ChIP is fully compatible with the intra-species diversity of humans and most model organisms and thus offers a general method for normalizing ChIP-seq results.

Background: Transcription factors (TFs) bind specifically to TF binding sites (TFBSs) at cis-regulatory regions to control transcription. It is critical to locate these TF-DNA interactions to understand transcriptional regulation. Efforts to predict bona fide TFBSs benefit from the availability of experimental data mapping DNA binding regions of TFs (chromatin immunoprecipitation followed by sequencing - ChIP-seq). Results: In this study, we processed ~ 10,000 public ChIP-seq datasets from nine species to provide high-quality TFBS predictions. After quality control, it culminated with the prediction of ~ 56 million TFBSs with experimental and computational support for direct TF-DNA interactions for 644 TFs in > 1000 cell lines and tissues. These TFBSs were used to predict > 197,000 cis-regulatory modules representing clusters of binding events in the corresponding genomes. The high-quality of the TFBSs was reinforced by their evolutionary conservation, enrichment at active cis-regulatory regions, and capacity to predict combinatorial binding of TFs. Further, we confirmed that the cell type and tissue specificity of enhancer activity was correlated with the number of TFs with binding sites predicted in these regions. All the data is provided to the community through the UniBind database that can be accessed through its web-interface (https://unibind.uio.no/), a dedicated RESTful API, and as genomic tracks. Finally, we provide an enrichment tool, available as a web-service and an R package, for users to find TFs with enriched TFBSs in a set of provided genomic regions. Conclusions: UniBind is the first resource of its kind, providing the largest collection of high-confidence direct TF-DNA interactions in nine species. [ABSTRACT FROM AUTHOR]

Background: Estrogen plays an essential role in female development and reproductive function. In chickens, estrogen is critical for lipid metabolism in the liver. The regulatory molecular network of estrogen in chicken liver is poorly understood. To identify estrogen-responsive genes and estrogen functional sites on a genome-wide scale, we determined expression profiles of mRNAs, lncRNAs, and miRNAs in estrogen-treated ((17β-estradiol)) and control chicken livers using RNA-Sequencing (RNA-Seq) and studied the estrogen receptor α binding sites by ChIP-Sequencing (ChIP-Seq). Results: We identified a total of 990 estrogen-responsive genes, including 962 protein-coding genes, 11 miRNAs, and 17 lncRNAs. Functional enrichment analyses showed that the estrogen-responsive genes were highly enriched in lipid metabolism and biological processes. Integrated analysis of the data of RNA-Seq and ChIP-Seq, identified 191 genes directly targeted by estrogen, including 185 protein-coding genes, 4 miRNAs, and 2 lncRNAs. In vivo and in vitro experiments showed that estrogen decreased the mRNA expression of PPARGC1B, which had been reported to be linked with lipid metabolism, by directly increasing the expression of miR-144-3p. Conclusions: These results increase our understanding of the functional network of estrogen in chicken liver and also reveal aspects of the molecular mechanism of estrogen-related lipid metabolism. [ABSTRACT FROM AUTHOR]

Abstract Background Maternal separation models in rodents are widely used to establish molecular mechanisms underlying prolonged effects of early life adversity on neurobiological and behavioral outcomes in adulthood. However, global epigenetic signatures following early life stress in these models remain unclear. Results In this study, we carried out a ChIP-seq analysis of H3K4 trimethylation profile in the prefrontal cortex of adult male mice with a history of early life stress. Two types of stress were used: prolonged separation of pups from their mothers (for 3 h once a day, maternal separation, MS) and brief separation (for 15 min once a day, handling, HD). Adult offspring in the MS group demonstrated reduced locomotor activity in the open field test accompanied by reduced exploratory activity, while the HD group showed decreased anxiety-like behavior only. In a group of maternal separation, we have found a small number (45) of slightly up-regulated peaks, corresponding to promoters of 70 genes, while no changes were observed in a group of handling. Among the genes whose promoters have differential enrichment of H3K4me3, the most relevant ones participate in gene expression regulation, modulation of chromatin structure and mRNA processing. For two genes, Ddias and Pip4k2a, increased H3K4me3 levels were associated with the increased mRNA expression in MS group. Conclusion The distribution of H3K4me3 in prefrontal cortex showed relatively low variability across all individuals, and only some subtle changes were revealed in mice with a history of early life stress. It is possible that the observed long-lasting behavioral alterations induced by maternal separation are mediated by other epigenetic mechanisms, or other brain structures are responsible for these effects.

Abstract Background Plant stress responses and mechanisms determining tolerance are controlled by diverse sets of genes. Transcription factors (TFs) have been implicated in conferring drought tolerance under drought stress conditions, and the identification of their target genes can elucidate molecular regulatory networks that orchestrate tolerance mechanisms. Results We generated transgenic rice plants overexpressing the 4 rice TFs, OsNAC5, 6, 9, and 10, under the control of the root-specific RCc3 promoter. We showed that they were tolerant to drought stress with reduced loss of grain yield under drought conditions compared with wild type plants. To understand the molecular mechanisms underlying this tolerance, we here performed chromatin immunoprecipitation (ChIP)-Seq and RNA-Seq analyses to identify the direct target genes of the OsNAC proteins using the RCc3:6MYC-OsNAC expressing roots. A total of 475 binding loci for the 4 OsNAC proteins were identified by cross-referencing their binding to promoter regions and the expression levels of the corresponding genes. The binding loci were distributed among the promoter regions of 391 target genes that were directly up-regulated by one of the OsNAC proteins in four RCc3:6MYC-OsNAC transgenic lines. Based on gene ontology (GO) analysis, the direct target genes were related to transmembrane/transporter activity, vesicle, plant hormones, carbohydrate metabolism, and TFs. The direct targets of each OsNAC range from 4.0–8.7% of the total number of up-regulated genes found in the RNA-Seq data sets. Thus, each OsNAC up-regulates a set of direct target genes that alter root system architecture in the RCc3:OsNAC plants to confer drought tolerance. Our results provide a valuable resource for functional dissection of the molecular mechanisms of drought tolerance. Conclusions Many of the target genes, including transmembrane/transporter, vesicle related, auxin/hormone related, carbohydrate metabolic processes, and transcription factor genes, that are up-regulated by OsNACs act as the cellular components which would alter the root architectures of RCc3:OsNACs for drought tolerance.

Background: RNA-Seq, the high-throughput sequencing (HT-Seq) of mRNAs, has become an essential tool for characterizing gene expression differences between different cell types and conditions. Gene expression is regulated by several mechanisms, including epigenetically by post-translational histone modifications which can be assessed by ChIP-Seq (Chromatin Immuno-Precipitation Sequencing). As more and more biological samples are analyzed by the combination of ChIP-Seq and RNA-Seq, the integrated analysis of the corresponding data sets becomes, theoretically, a unique option to study gene regulation. However, technically such analyses are still in their infancy. Results: Here we introduce intePareto, a computational tool for the integrative analysis of RNA-Seq and ChIP-Seq data. With intePareto we match RNA-Seq and ChIP-Seq data at the level of genes, perform differential expression analysis between biological conditions, and prioritize genes with consistent changes in RNA-Seq and ChIP-Seq data using Pareto optimization. Conclusion: intePareto facilitates comprehensive understanding of high dimensional transcriptomic and epigenomic data. Its superiority to a naive differential gene expression analysis with RNA-Seq and available integrative approach is demonstrated by analyzing a public dataset. [ABSTRACT FROM AUTHOR]

Abstract Background Chromatin immunoprecipitation-sequencing (ChIP-seq) is a widely used epigenetic approach for investigating genome-wide protein-DNA interactions in cells and tissues. The approach has been relatively well established but several key steps still require further improvement. As a part of the procedure, immnoprecipitated DNA must undergo purification and library preparation for subsequent high-throughput sequencing. Current ChIP protocols typically yield nanogram quantities of immunoprecipitated DNA mainly depending on the target of interest and starting chromatin input amount. However, little information exists on the performance of reagents used for the purification of such minute amounts of immunoprecipitated DNA in ChIP elution buffer and their effects on ChIP-seq data. Here, we compared DNA recovery, library preparation efficiency, and ChIP-seq results obtained with several commercial DNA purification reagents applied to 1 ng ChIP DNA and also investigated the impact of conditions under which ChIP DNA is stored. Results We compared DNA recovery of ten commercial DNA purification reagents and phenol/chloroform extraction from 1 to 50 ng of immunopreciptated DNA in ChIP elution buffer. The recovery yield was significantly different with 1 ng of DNA while similar in higher DNA amounts. We also observed that the low nanogram range of purified DNA is prone to loss during storage depending on the type of polypropylene tube used. The immunoprecipitated DNA equivalent to 1 ng of purified DNA was subject to DNA purification and library preparation to evaluate the performance of four better performing purification reagents in ChIP-seq applications. Quantification of library DNAs indicated the selected purification kits have a negligible impact on the efficiency of library preparation. The resulting ChIP-seq data were comparable with the dataset generated by ENCODE consortium and were highly correlated between the data from different purification reagents. Conclusions This study provides comparative data on commercial DNA purification reagents applied to nanogram-range immunopreciptated ChIP DNA and evidence for the importance of storage conditions of low nanogram-range purified DNA. We verified consistent high performance of a subset of the tested reagents. These results will facilitate the improvement of ChIP-seq methodology for low-input applications.

Background: Optimal glucose metabolism is central to the growth and development of cells. In microbial eukaryotes, carbon catabolite repression (CCR) mediates the preferential utilization of glucose, primarily by repressing alternate carbon source utilization. In fission yeast, CCR is mediated by transcriptional repressors Scr1 and the Tup/Ssn6 complex, with the Rst2 transcription factor important for activation of gluconeogenesis and sexual differentiation genes upon derepression. Through genetic and genome-wide methods, this study aimed to comprehensively characterize CCR in fission yeast by identifying the genes and biological processes that are regulated by Scr1, Tup/Ssn6 and Rst2, the core CCR machinery. Results: The transcriptional response of fission yeast to glucose-sufficient or glucose-deficient growth conditions in wild type and CCR mutant cells was determined by RNA-seq and ChIP-seq. Scr1 was found to regulate genes involved in carbon metabolism, hexose uptake, gluconeogenesis and the TCA cycle. Surprisingly, a role for Scr1 in the suppression of sexual differentiation was also identified, as homothallic scr1 deletion mutants showed ectopic meiosis in carbon and nitrogen rich conditions. ChIP-seq characterised the targets of Tup/Ssn6 and Rst2 identifying regulatory roles within and independent of CCR. Finally, a subset of genes bound by all three factors was identified, implying that regulation of certain loci may be modulated in a competitive fashion between the Scr1, Tup/Ssn6 repressors and the Rst2 activator. Conclusions: By identifying the genes directly and indirectly regulated by Scr1, Tup/Ssn6 and Rst2, this study comprehensively defined the gene regulatory networks of CCR in fission yeast and revealed the transcriptional complexities governing this system. [ABSTRACT FROM AUTHOR]

Background: Chromatin immunoprecipitation coupled to sequencing (ChIP-seq) is widely used to map histone modifications and transcription factor binding on a genome-wide level. Results: We present high-throughput ChIPmentation (HT-ChIPmentation) that eliminates the need for DNA purification prior to library amplification and reduces reverse-crosslinking time from hours to minutes. Conclusions: The resulting workflow is easily established, extremely rapid, and compatible with requirements for very low numbers of FACS sorted cells, high-throughput applications and single day data generation. [ABSTRACT FROM AUTHOR]

Background: Chromatin-immunoprecipitation followed by sequencing (ChIP-seq) is the method of choice for mapping genome-wide binding of chromatin-associated factors. However, broadly applicable methods for between-sample comparisons are lacking. Results: Here, we introduce SNP-ChIP, a method that leverages small-scale intra-species polymorphisms, mainly SNPs, for quantitative spike-in normalization of ChIP-seq results. Sourcing spike-in material from the same species ensures antibody cross-reactivity and physiological coherence, thereby eliminating two central limitations of traditional spike-in approaches. We show that SNP-ChIP is robust to changes in sequencing depth and spike-in proportions, and reliably identifies changes in overall protein levels, irrespective of changes in binding distribution. Application of SNP-ChIP to test cases from budding yeast meiosis allowed discovery of novel regulators of the chromosomal protein Red1 and quantitative analysis of the DNA-damage associated histone modification γ-H2AX. Conclusion: SNP-ChIP is fully compatible with the intra-species diversity of humans and most model organisms and thus offers a general method for normalizing ChIP-seq results. [ABSTRACT FROM AUTHOR]

Background: Allele-specific transcriptional regulation, including of imprinted genes, is essential for normal mammalian development. While the regulatory regions controlling imprinted genes are associated with DNA methylation (DNAme) and specific histone modifications, the interplay between transcription and these epigenetic marks at allelic resolution is typically not investigated genome-wide due to a lack of bioinformatic packages that can process and integrate multiple epigenomic datasets with allelic resolution. In addition, existing ad-hoc software only consider SNVs for allele-specific read discovery. This limitation omits potentially informative INDELs, which constitute about one fifth of the number of SNVs in mice, and introduces a systematic reference bias in allele-specific analyses. Results: Here, we describe MEA, an INDEL-aware Methylomic and Epigenomic Allele-specific analysis pipeline which enables user-friendly data exploration, visualization and interpretation of allelic imbalance. Applying MEA to mouse embryonic datasets yields robust allele-specific DNAme maps and low reference bias. We validate allele-specific DNAme at known differentially methylated regions and show that automated integration of such methylation data with RNA- and ChIP-seq datasets yields an intuitive, multidimensional view of allelic gene regulation. MEA uncovers numerous novel dynamically methylated loci, highlighting the sensitivity of our pipeline. Furthermore, processing and visualization of epigenomic datasets from human brain reveals the expected allele-specific enrichment of H3K27ac and DNAme at imprinted as well as novel monoallelically expressed genes, highlighting MEA’s utility for integrating human datasets of distinct provenance for genome-wide analysis of allelic phenomena. Conclusions: Our novel pipeline for standardized allele-specific processing and visualization of disparate epigenomic and methylomic datasets enables rapid analysis and navigation with allelic resolution. MEA is freely available as a Docker container at https://github.com/julienrichardalbert/MEA. [ABSTRACT FROM AUTHOR]

Background: Transcriptional target genes show functional enrichment of genes. However, how many and how significantly transcriptional target genes include functional enrichments are still unclear. To address these issues, I predicted human transcriptional target genes using open chromatin regions, ChIP-seq data and DNA binding sequences of transcription factors in databases, and examined functional enrichment and gene expression level of putative transcriptional target genes. Results: Gene Ontology annotations showed four times larger numbers of functional enrichments in putative transcriptional target genes than gene expression information alone, independent of transcriptional target genes. To compare the number of functional enrichments of putative transcriptional target genes between cells or search conditions, I normalized the number of functional enrichment by calculating its ratios in the total number of transcriptional target genes. With this analysis, native putative transcriptional target genes showed the largest normalized number of functional enrichments, compared with target genes including 5-60% of randomly selected genes. The normalized number of functional enrichments was changed according to the criteria of enhancer-promoter interactions such as distance from transcriptional start sites and orientation of CTCF-binding sites. Forward-reverse orientation of CTCF-binding sites showed significantly higher normalized number of functional enrichments than the other orientations. Journal papers showed that the top five frequent functional enrichments were related to the cellular functions in the three cell types. The median expression level of transcriptional target genes changed according to the criteria of enhancer-promoter assignments (i.e. interactions) and was correlated with the changes of the normalized number of functional enrichments of transcriptional target genes. Conclusions: Human putative transcriptional target genes showed significant functional enrichments. Functional enrichments were related to the cellular functions. The normalized number of functional enrichments of human putative transcriptional target genes changed according to the criteria of enhancer-promoter assignments and correlated with the median expression level of the target genes. These analyses and characters of human putative transcriptional target genes would be useful to examine the criteria of enhancer-promoter assignments and to predict the novel mechanisms and factors such as DNA binding proteins and DNA sequences of enhancer-promoter interactions. [ABSTRACT FROM AUTHOR]

Background: Plant stress responses and mechanisms determining tolerance are controlled by diverse sets of genes. Transcription factors (TFs) have been implicated in conferring drought tolerance under drought stress conditions, and the identification of their target genes can elucidate molecular regulatory networks that orchestrate tolerance mechanisms. Results: We generated transgenic rice plants overexpressing the 4 rice TFs, OsNAC5, 6, 9, and 10, under the control of the root-specific RCc3 promoter. We showed that they were tolerant to drought stress with reduced loss of grain yield under drought conditions compared with wild type plants. To understand the molecular mechanisms underlying this tolerance, we here performed chromatin immunoprecipitation (ChIP)-Seq and RNA-Seq analyses to identify the direct target genes of the OsNAC proteins using the RCc3:6MYC-OsNAC expressing roots. A total of 475 binding loci for the 4 OsNAC proteins were identified by cross-referencing their binding to promoter regions and the expression levels of the corresponding genes. The binding loci were distributed among the promoter regions of 391 target genes that were directly up-regulated by one of the OsNAC proteins in four RCc3:6MYC-OsNAC transgenic lines. Based on gene ontology (GO) analysis, the direct target genes were related to transmembrane/transporter activity, vesicle, plant hormones, carbohydrate metabolism, and TFs. The direct targets of each OsNAC range from 4.0-8.7% of the total number of up-regulated genes found in the RNA-Seq data sets. Thus, each OsNAC up-regulates a set of direct target genes that alter root system architecture in the RCc3:OsNAC plants to confer drought tolerance. Our results provide a valuable resource for functional dissection of the molecular mechanisms of drought tolerance. Conclusions: Many of the target genes, including transmembrane/transporter, vesicle related, auxin/hormone related, carbohydrate metabolic processes, and transcription factor genes, that are up-regulated by OsNACs act as the cellular components which would alter the root architectures of RCc3:OsNACs for drought tolerance. [ABSTRACT FROM AUTHOR]

Background: The Hepatitis B Virus (HBV) HBx regulatory protein is required for HBV replication and involved in HBV-related carcinogenesis. HBx interacts with chromatin modifying enzymes and transcription factors to modulate histone post-translational modifications and to regulate viral cccDNA transcription and cellular gene expression. Aiming to identify genes and non-coding RNAs (ncRNAs) directly targeted by HBx, we performed a chromatin immunoprecipitation sequencing (ChIP-Seq) to analyse HBV recruitment on host cell chromatin in cells replicating HBV. Results: ChIP-Seq high throughput sequencing of HBx-bound fragments was used to obtain a high-resolution, unbiased, mapping of HBx binding sites across the genome in HBV replicating cells. Protein-coding genes and ncRNAs involved in cell metabolism, chromatin dynamics and cancer were enriched among HBx targets together with genes/ ncRNAs known to modulate HBV replication. The direct transcriptional activation of genes/miRNAs that potentiate endocytosis (Ras-related in brain (RAB) GTPase family) and autophagy (autophagy related (ATG) genes, beclin-1, miR- 33a) and the transcriptional repression of microRNAs (miR-138, miR-224, miR-576, miR-596) that directly target the HBV pgRNA and would inhibit HBV replication, contribute to HBx-mediated increase of HBV replication. Conclusions: Our ChIP-Seq analysis of HBx genome wide chromatin recruitment defined the repertoire of genes and ncRNAs directly targeted by HBx and led to the identification of new mechanisms by which HBx positively regulates cccDNA transcription and HBV replication. [ABSTRACT FROM AUTHOR]

Background: Biomedical applications of high-throughput sequencing methods generate a vast amount of data in which numerous chromatin features are mapped along the genome. The results are frequently analysed by creating binary data sets that link the presence/absence of a given feature to specific genomic loci. However, the nucleosome occupancy or chromatin accessibility landscape is essentially continuous. It is currently a challenge in the field to cope with continuous distributions of deep sequencing chromatin readouts and to integrate the different types of discrete chromatin features to reveal linkages between them. Results: Here we introduce the NucTools suite of Perl scripts as well as MATLAB- and R-based visualization programs for a nucleosome-centred downstream analysis of deep sequencing data. NucTools accounts for the continuous distribution of nucleosome occupancy. It allows calculations of nucleosome occupancy profiles averaged over several replicates, comparisons of nucleosome occupancy landscapes between different experimental conditions, and the estimation of the changes of integral chromatin properties such as the nucleosome repeat length. Furthermore, NucTools facilitates the annotation of nucleosome occupancy with other chromatin features like binding of transcription factors or architectural proteins, and epigenetic marks like histone modifications or DNA methylation. The applications of NucTools are demonstrated for the comparison of several datasets for nucleosome occupancy in mouse embryonic stem cells (ESCs) and mouse embryonic fibroblasts (MEFs). Conclusions: The typical workflows of data processing and integrative analysis with NucTools reveal information on the interplay of nucleosome positioning with other features such as for example binding of a transcription factor CTCF, regions with stable and unstable nucleosomes, and domains of large organized chromatin K9me2 modifications (LOCKs). As potential limitations and problems we discuss how inter-replicate variability of MNase-seq experiments can be addressed. [ABSTRACT FROM AUTHOR]

Background: The nuclear hormone receptor superfamily acts as a genomic sensor of diverse signals. Their actions are often intertwined with other transcription factors. Nuclear hormone receptors are targets for many therapeutic drugs, and include the vitamin D receptor (VDR). VDR signaling is pleotropic, being implicated in calcaemic function, antibacterial actions, growth control, immunomodulation and anti-cancer actions. Specifically, we hypothesized that the biologically significant relationships between the VDR transcriptome and phenotype-associated biology could be discovered by integrating the known VDR transcription factor binding sites and all published trait- and disease-associated SNPs. By integrating VDR genome-wide binding data (ChIP-seq) with the National Human Genome Research Institute (NHGRI) GWAS catalog of SNPs we would see where and which target gene interactions and pathways are impacted by inherited genetic variation in VDR binding sites, indicating which of VDR's multiple functions are most biologically significant. Results: To examine how genetic variation impacts VDR function we overlapped 23,409 VDR genomic binding peaks from six VDR ChIP-seq datasets with 191,482 SNPs, derived from GWAS-significant SNPs (Lead SNPs) and their correlated variants (r2 > 0.8) from HapMap3 and the 1000 genomes project. In total, 574 SNPs (71 Lead and 503 SNPs in linkage disequilibrium with Lead SNPs) were present at VDR binding loci and associated with 211 phenotypes. For each phenotype a hypergeometric test was used to determine if SNPs were enriched at VDR binding sites. Bonferroni correction for multiple testing across the 211 phenotypes yielded 42 SNPs that were either disease- or phenotype-associated with seven predominately immune related including self-reported allergy; esophageal cancer was the only cancer phenotype. Motif analyses revealed that only two of these 42 SNPs reside within a canonical VDR binding site (DR3 motif), and that 1/3 of the 42 SNPs significantly impacted binding and gene regulation by other transcription factors, including NF-κB. This suggests a plausible link for the potential cross-talk between VDR and NF-κB. Conclusions: These analyses showed that VDR peaks are enriched for SNPs associated with immune phenotypes suggesting that VDR immunomodulatory functions are amongst its most important actions. The enrichment of genetic variation in non-DR3 motifs suggests a significant role for the VDR to bind in multimeric complexes containing other transcription factors that are the primary DNA binding component. Our work provides a framework for the combination of ChIP-seq and GWAS findings to provide insight into the underlying phenotype-associated biology of a given transcription factor. [ABSTRACT FROM AUTHOR]

Background: Transcription factors (TFs) often interact with one another to form TF complexes that bind DNA and regulate gene expression. Many databases are created to describe known TF complexes identified by either mammalian two-hybrid experiments or data mining. Lately, a wealth of ChIP-seq data on human TFs under different experiment conditions are available, making it possible to investigate condition-specific (cell type and/or physiologic state) TF complexes and their target genes. Results: Here, we developed a systematic pipeline to infer Condition-Specific Targets of human TF-TF complexes (called the CST pipeline) by integrating ChIP-seq data and TF motifs. In total, we predicted 2,392 TF complexes and 13,504 high-confidence or 127,994 low-confidence regulatory interactions amongst TF complexes and their target genes. We validated our predictions by (i) comparing predicted TF complexes to external TF complex databases, (ii) validating selected target genes of TF complexes using ChIP-qPCR and RT-PCR experiments, and (iii) analysing target genes of select TF complexes using gene ontology enrichment to demonstrate the accuracy of our work. Finally, the predicted results above were integrated and employed to construct a CST database. Conclusions: We built up a methodology to construct the CST database, which contributes to the analysis of transcriptional regulation and the identification of novel TF-TF complex formation in a certain condition. This database also allows users to visualize condition-specific TF regulatory networks through a user-friendly web interface. [ABSTRACT FROM AUTHOR]