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Abstract Background Reproducibility is a major concern in biomedical studies, and existing publication guidelines do not solve the problem. Batch effects and quality imbalances between groups of biological samples are major factors hampering reproducibility. Yet, the latter is rarely considered in the scientific literature. Results Our analysis uses 40 clinically relevant RNA-seq datasets to quantify the impact of quality imbalance between groups of samples on the reproducibility of gene expression studies. High-quality imbalance is frequent (14 datasets; 35%), and hundreds of quality markers are present in more than 50% of the datasets. Enrichment analysis suggests common stress-driven effects among the low-quality samples and highlights a complementary role of transcription factors and miRNAs to regulate stress response. Preliminary ChIP-seq results show similar trends. Quality imbalance has an impact on the number of differential genes derived by comparing control to disease samples (the higher the imbalance, the higher the number of genes), on the proportion of quality markers in top differential genes (the higher the imbalance, the higher the proportion; up to 22%) and on the proportion of known disease genes in top differential genes (the higher the imbalance, the lower the proportion). We show that removing outliers based on their quality score improves the resulting downstream analysis. Conclusions Thanks to a stringent selection of well-designed datasets, we demonstrate that quality imbalance between groups of samples can significantly reduce the relevance of differential genes, consequently reducing reproducibility between studies. Appropriate experimental design and analysis methods can substantially reduce the problem.

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.

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

Wood-decaying fungi of the class Agaricomycetes (phylum Basidiomycota) are saprotrophs that break down lignocellulose and play an important role in nutrient recycling. They secrete a wide range of extracellular plant cell wall degrading enzymes that break down cellulose, hemicellulose, and lignin, the main building blocks of plant biomass. Although the production of these enzymes is regulated mainly at the transcriptional level, no activating regulators have been identified in any wood-decaying fungus in the class Agaricomycetes. We studied the regulation of cellulase expression in the wood-decaying fungus Schizophyllum commune. Comparative genomics and transcriptomics on two wild isolates revealed a Zn2Cys6-type transcription factor gene (roc1) that was highly upregulated during growth on cellulose, compared to glucose. It is only conserved in the class Agaricomycetes. A roc1 knockout strain showed an inability to grow on medium with cellulose as sole carbon source, and growth on cellobiose and xylan (other components of wood) was inhibited. Growth on non-wood-related carbon sources was not inhibited. Cellulase gene expression and enzyme activity were reduced in the Δroc1 strain. ChIP-Seq identified 1474 binding sites of the Roc1 transcription factor. Promoters of genes involved in lignocellulose degradation were enriched with these binding sites, especially those of LPMO (lytic polysaccharide monooxygenase) CAZymes, indicating that Roc1 directly regulates these genes. A conserved motif was identified as the binding site of Roc1, which was confirmed by a functional promoter analysis. Together, Roc1 is a key regulator of cellulose degradation and the first identified in wood-decaying fungi in the phylum Basidiomycota. IMPORTANCE Wood-degrading fungi in the phylum Basidiomycota play a crucial role in nutrient recycling by breaking down all components of wood. Fungi have evolved transcriptional networks that regulate expression of wood-degrading enzymes, allowing them to prioritize one nutrient source over another. However, to date all these transcription factors have been identified in the phylum Ascomycota, which is only distantly related to the phylum Basidiomycota. Here, we identified the transcription factor Roc1 as a key regulator of cellulose degradation in the mushroom-forming and wood-degrading fungus Schizophyllum commune. Roc1 is highly conserved in the phylum Basidiomycota. Using comparative genomics, transcriptomics, ChIP-Seq and promoter analysis we have identified direct targets of Roc1, as well as other aspects of the transcriptional response to cellulose.

DNA-binding transcription factors (TFs) remain challenging to target with molecular probes. Many TFs function in part through interaction with Mediator, a 26-subunit complex that controls RNA polymerase II activity genome-wide. We sought to block p53 function by disrupting the p53-Mediator interaction. Through rational design and activity-based screening, we characterize a stapled peptide, with functional mimics of both p53 activation domains, that blocks p53-Mediator binding and selectively inhibits p53-dependent transcription in human cells; importantly, this "bivalent" peptide has negligible impact, genome-wide, on non-p53 target genes. Our proof-of-concept strategy circumvents the TF entirely and targets the TF-Mediator interface instead, with desired functional outcomes (i.e., selective inhibition of p53 activation). Furthermore, these results demonstrate that TF activation domains represent viable starting points for Mediator-targeting molecular probes, as an alternative to large compound libraries. Different TFs bind Mediator through different subunits, suggesting this strategy could be broadly applied to selectively alter gene expression programs.

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.

Mesendodermal specification is one of the earliest events in embryogenesis, where cells first acquire distinct identities. Cell differentiation is a highly regulated process that involves the function of numerous transcription factors (TFs) and signaling molecules, which can be described with gene regulatory networks (GRNs). Cell differentiation GRNs are difficult to build because existing mechanistic methods are low throughput, and high-throughput methods tend to be non-mechanistic. Additionally, integrating highly dimensional data composed of more than two data types is challenging. Here, we use linked self-organizing maps to combine chromatin immunoprecipitation sequencing (ChIP-seq)/ATAC-seq with temporal, spatial, and perturbation RNA sequencing (RNA-seq) data from Xenopus tropicalis mesendoderm development to build a high-resolution genome scale mechanistic GRN. We recover both known and previously unsuspected TF-DNA/TF-TF interactions validated through reporter assays. Our analysis provides insights into transcriptional regulation of early cell fate decisions and provides a general approach to building GRNs using highly dimensional multi-omic datasets.

SMAD4 regulates gene expression in response to BMP and TGFβ signal transduction, and is required for diverse morphogenetic processes, but its target genes have remained largely elusive. Here, we identify the SMAD4 target genes in mouse limb buds using an epitope-tagged Smad4 allele for ChIP-seq analysis in combination with transcription profiling. This analysis shows that SMAD4 predominantly mediates BMP signal transduction during early limb bud development. Unexpectedly, the expression of cholesterol biosynthesis enzymes is precociously downregulated and intracellular cholesterol levels are reduced in Smad4-deficient limb bud mesenchymal progenitors. Most importantly, our analysis reveals a predominant function of SMAD4 in upregulating target genes in the anterior limb bud mesenchyme. Analysis of differentially expressed genes shared between Smad4- and Shh-deficient limb buds corroborates this function of SMAD4 and also reveals the repressive effect of SMAD4 on posterior genes that are upregulated in response to SHH signaling. This analysis uncovers opposing trans-regulatory inputs from SHH- and SMAD4-mediated BMP signal transduction on anterior and posterior gene expression during the digit patterning and outgrowth in early limb buds.

A common mechanism in inherited ataxia is a vulnerability of DNA damage. Spinocerebellar ataxia type 7 (SCA7) is a CAG-polyglutamine-repeat disorder characterized by cerebellar and retinal degeneration. Polyglutamine-expanded ataxin-7 protein incorporates into STAGA co-activator complex and interferes with transcription by altering histone acetylation. We performed chromatic immunoprecipitation sequencing ChIP-seq on cerebellum from SCA7 mice and observed increased H3K9-promoter acetylation in DNA repair genes, resulting in increased expression. After detecting increased DNA damage in SCA7 cells, mouse primary cerebellar neurons, and patient stem-cell-derived neurons, we documented reduced homology-directed repair (HDR) and single-strand annealing (SSA). To evaluate repair at endogenous DNA in native chromosome context, we modified linear amplification-mediated high-throughput genome-wide translocation sequencing and found that DNA translocations are less frequent in SCA7 models, consistent with decreased HDR and SSA. Altered DNA repair function in SCA7 may predispose the subject to excessive DNA damage, leading to neuron demise and highlights DNA repair as a therapy target.

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

Abstract Background Cells orchestrate histone biogenesis with strict temporal and quantitative control. To efficiently regulate histone biogenesis, the repetitive Drosophila melanogaster replication-dependent histone genes are arrayed and clustered at a single locus. Regulatory factors concentrate in a nuclear body known as the histone locus body (HLB), which forms around the locus. Historically, HLB factors are largely discovered by chance, and few are known to interact directly with DNA. It is therefore unclear how the histone genes are specifically targeted for unique and coordinated regulation. Results To expand the list of known HLB factors, we performed a candidate-based screen by mapping 30 publicly available ChIP datasets of 27 unique factors to the Drosophila histone gene array. We identified novel transcription factor candidates, including the Drosophila Hox proteins Ultrabithorax (Ubx), Abdominal-A (Abd-A), and Abdominal-B (Abd-B), suggesting a new pathway for these factors in influencing body plan morphogenesis. Additionally, we identified six other factors that target the histone gene array: JIL-1, hormone-like receptor 78 (Hr78), the long isoform of female sterile homeotic (1) (fs(1)h) as well as the general transcription factors TBP associated factor 1 (TAF-1), Transcription Factor IIB (TFIIB), and Transcription Factor IIF (TFIIF). Conclusions Our foundational screen provides several candidates for future studies into factors that may influence histone biogenesis. Further, our study emphasizes the powerful reservoir of publicly available datasets, which can be mined as a primary screening technique.

Abstract Background The largest group of patients with breast cancer are estrogen receptor-positive (ER+) type. The estrogen receptor acts as a transcription factor and triggers cell proliferation and differentiation. Hence, investigating ER-DNA interaction genomic regions can help identify genes directly regulated by ER and understand the mechanism of ER action in cancer progression. Methods In the present study, we employed a workflow to do a meta-analysis of ChIP-seq data of ER+ cell lines stimulated with 10 nM and 100 nM of E2. All publicly available data sets were re-analyzed with the same platform. Then, the known and unknown batch effects were removed. Finally, the meta-analysis was performed to obtain meta-differentially bound sites in estrogen-treated MCF7 cell lines compared to vehicles (as control). Also, the meta-analysis results were compared with the results of T47D cell lines for more precision. Enrichment analyses were also employed to find the functional importance of common meta-differentially bound sites and associated genes among both cell lines. Results Remarkably, POU5F1B, ZNF662, ZNF442, KIN, ZNF410, and SGSM2 transcription factors were recognized in the meta-analysis but not in individual studies. Enrichment of the meta-differentially bound sites resulted in the candidacy of pathways not previously reported in breast cancer. PCGF2, HNF1B, and ZBED6 transcription factors were also predicted through the enrichment analysis of associated genes. In addition, comparing the meta-analysis results of both ChIP-seq and RNA-seq data showed that many transcription factors affected by ER were up-regulated. Conclusion The meta-analysis of ChIP-seq data of estrogen-treated MCF7 cell line leads to the identification of new binding sites of ER that have not been previously reported. Also, enrichment of the meta-differentially bound sites and their associated genes revealed new terms and pathways involved in the development of breast cancer which should be examined in future in vitro and in vivo studies.

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.

Summary: Cleavage under targets & release using nuclease (CUT&RUN) is a technique for identifying genomic sites where proteins or histone modifications are present in chromatin in permeabilized cells. Here, we present a fluorescence-based protocol to quantitatively titrate CUT&RUN buffer components, for efficient cell permeabilization and retention of target epitopes on chromatin. We describe steps for capturing cells on concanavalin A beads and using a fluorescently labeled secondary antibody to titrate concentrations of digitonin and NaCl in CUT&RUN buffers. We then detail procedures for fluorescence imaging to identify optimal conditions.For complete details on the use and execution of this protocol, please refer to Lerner et al.1 : Publisher’s note: Undertaking any experimental protocol requires adherence to local institutional guidelines for laboratory safety and ethics.

Abstract Prediction of transcription factor binding sites (TFBS) is an example of application of Bioinformatics where DNA molecules are represented as sequences of A, C, G and T symbols. The most used model in this problem is Position Weight Matrix (PWM). Notwithstanding the advantage of being simple, PWMs cannot capture dependency between nucleotide positions, which may affect prediction performance. Acyclic Probabilistic Finite Automata (APFA) is an alternative model able to accommodate position dependencies. However, APFA is a more complex model, which means more parameters have to be learned. In this paper, we propose an innovative method to identify when position dependencies influence preference for PWMs or APFAs. This implied using position dependency features extracted from 1106 sets of TFBS to infer a decision tree able to predict which is the best model - PWM or APFA - for a given set of TFBSs. According to our results, as few as three pinpointed features are able to choose the best model, providing a balance of performance (average precision) and model simplicity.

Abstract Background Genetic variation in regulatory sequences that alter transcription factor (TF) binding is a major cause of phenotypic diversity. Brassinosteroid is a growth hormone that has major effects on plant phenotypes. Genetic variation in brassinosteroid-responsive cis-elements likely contributes to trait variation. Pinpointing such regulatory variations and quantitative genomic analysis of the variation in TF-target binding, however, remains challenging. How variation in transcriptional targets of signaling pathways such as the brassinosteroid pathway contributes to phenotypic variation is an important question to be investigated with innovative approaches. Results Here, we use a hybrid allele-specific chromatin binding sequencing (HASCh-seq) approach and identify variations in target binding of the brassinosteroid-responsive TF ZmBZR1 in maize. HASCh-seq in the B73xMo17 F1s identifies thousands of target genes of ZmBZR1. Allele-specific ZmBZR1 binding (ASB) has been observed for 18.3% of target genes and is enriched in promoter and enhancer regions. About a quarter of the ASB sites correlate with sequence variation in BZR1-binding motifs and another quarter correlate with haplotype-specific DNA methylation, suggesting that both genetic and epigenetic variations contribute to the high level of variation in ZmBZR1 occupancy. Comparison with GWAS data shows linkage of hundreds of ASB loci to important yield and disease-related traits. Conclusion Our study provides a robust method for analyzing genome-wide variations of TF occupancy and identifies genetic and epigenetic variations of the brassinosteroid response transcription network in maize.

Significant advancements in understanding disease mechanisms can occur through combined analysis of next-generation sequencing datasets generated using purified cell populations. Here, we detail our optimized protocol for purification of mouse hepatic macrophages (or other liver non-parenchymal populations) suitable for use in various next-generation sequencing protocols. An alternative framework is described for sorting pre-fixed hepatic nuclei populations. This strategy has the advantage of rapidly preserving the nuclei and can facilitate success with ChIP-seq for more challenging molecules. For complete details on the use and execution of these protocols, please refer to Muse et al. (2018), Sakai et al. (2019), and Seidman et al. (2020).

An important question is what genes govern the differentiation of plant embryos into suspensor and embryo proper regions following fertilization and division of the zygote. We compared embryo proper and suspensor transcriptomes of four plants that vary in embryo morphology within the suspensor region. We determined that genes encoding enzymes in several metabolic pathways leading to the formation of hormones, such as gibberellic acid, and other metabolites are up-regulated in giant scarlet runner bean and common bean suspensors. Genes involved in transport and Golgi body organization are up-regulated within the suspensors of these plants as well, strengthening the view that giant specialized suspensors serve as a hormone factory and a conduit for transferring substances to the developing embryo proper. By contrast, genes controlling transcriptional regulation, development, and cell division are up-regulated primarily within the embryo proper. Transcriptomes from less specialized soybean and Arabidopsis suspensors demonstrated that fewer genes encoding metabolic enzymes and hormones are up-regulated. Genes active in the embryo proper, however, are functionally similar to those active in scarlet runner bean and common bean embryo proper regions. We uncovered a set of suspensor- and embryo proper-specific transcription factors (TFs) that are shared by all embryos irrespective of morphology, suggesting that they are involved in early differentiation processes common to all plants. Chromatin immunoprecipitation sequencing (ChIP-Seq) experiments with scarlet runner bean and soybean WOX9, an up-regulated suspensor TF, gained entry into a regulatory network important for suspensor development irrespective of morphology.

ABSTRACTResearch experiences provide diverse benefits for undergraduates. Many academic institutions have adopted course-based undergraduate research experiences (CUREs) to improve student access to research opportunities. However, potential instructors of a CURE might still face financial or practical hurdles that prevent implementation. Bioinformatics research offers an alternative that is free, safe, compatible with remote learning, and may be more accessible for students with disabilities. Here, we describe a bioinformatics CURE that leverages publicly available datasets to discover novel proteins that target an instructor-determined genomic locus of interest. We use the free, user-friendly bioinformatics platform Galaxy to map ChIP-seq datasets to a genome, which removes the computing burden from students. Both faculty and students directly benefit from this CURE, as faculty can perform candidate screens and publish CURE results. Students gain not only basic bioinformatics knowledge, but also transferable skills, including scientific communication, database navigation, and primary literature experience. The CURE is flexible and can be expanded to analyze different types of high-throughput data or to investigate different genomic loci in any species.

BackgroundMotif enrichment analysis (MEA) identifies over-represented transcription factor binding (TF) motifs in the DNA sequence of regulatory regions, enabling researchers to infer which transcription factors can regulate transcriptional response to a stimulus, or identify sequence features found near a target protein in a ChIP-seq experiment. Score-based MEA determines motifs enriched in regions exhibiting extreme differences in regulatory activity, but existing methods do not control for biases in GC content or dinucleotide composition. This lack of control for sequence bias, such as those often found in CpG islands, can obscure the enrichment of biologically relevant motifs.ResultsWe developed Motif Enrichment In Ranked Lists of Peaks (MEIRLOP), a novel MEA method that determines enrichment of TF binding motifs in a list of scored regulatory regions, while controlling for sequence bias. In this study, we compare MEIRLOP against other MEA methods in identifying binding motifs found enriched in differentially active regulatory regions after interferon-beta stimulus, finding that using logistic regression and covariates improves the ability to call enrichment of ISGF3 binding motifs from differential acetylation ChIP-seq data compared to other methods. Our method achieves similar or better performance compared to other methods when quantifying the enrichment of TF binding motifs from ENCODE TF ChIP-seq datasets. We also demonstrate how MEIRLOP is broadly applicable to the analysis of numerous types of NGS assays and experimental designs.ConclusionsOur results demonstrate the importance of controlling for sequence bias when accurately identifying enriched DNA sequence motifs using score-based MEA. MEIRLOP is available for download from https://github.com/npdeloss/meirlop under the MIT license.

Pioneer factors such as Zelda (Zld) help initiate zygotic transcription in Drosophila early embryos, but whether other factors support this dynamic process is unclear. Odd-paired (Opa), a zinc-finger transcription factor expressed at cellularization, controls the transition of genes from pair-rule to segmental patterns along the anterior-posterior axis. Finding that Opa also regulates expression through enhancer sog_Distal along the dorso-ventral axis, we hypothesized Opas role is more general. Chromatin-immunoprecipitation (ChIP-seq) confirmed its in vivo binding to sog_Distal but also identified widespread binding throughout the genome, comparable to Zld. Furthermore, chromatin assays (ATAC-seq) demonstrate that Opa, like Zld, influences chromatin accessibility genome-wide at cellularization, suggesting both are pioneer factors with common as well as distinct targets. Lastly, embryos lacking opa exhibit widespread, late patterning defects spanning both axes. Collectively, these data suggest Opa is a general timing factor and likely late-acting pioneer factor that drives a secondary wave of zygotic gene expression.

Tissue-resident and recruited macrophages contribute to both host defense and pathology. Multiple macrophage phenotypes are represented in diseased tissues, but we lack deep understanding of mechanisms controlling diversification. Here, we investigate origins and epigenetic trajectories of hepatic macrophages during diet-induced non-alcoholic steatohepatitis (NASH). The NASH diet induced significant changes in Kupffer cell enhancers and gene expression, resulting in partial loss of Kupffer cell identity, induction of Trem2 and Cd9 expression, and cell death. Kupffer cell loss was compensated by gain of adjacent monocyte-derived macrophages that exhibited convergent epigenomes, transcriptomes, and functions. NASH-induced changes in Kupffer cell enhancers were driven by AP-1 and EGR that reprogrammed LXR functions required for Kupffer cell identity and survival to instead drive a scar-associated macrophage phenotype. These findings reveal mechanisms by which disease-associated environmental signals instruct resident and recruited macrophages to acquire distinct gene expression programs and corresponding functions.

Two environmental factors, Newcastle disease and heat stress, are concurrently negatively impacting poultry worldwide and warrant greater attention into developing genetic resistance within chickens. Using two genetically distinct and highly inbred layer lines, Fayoumi and Leghorn, we explored how different genetic backgrounds affect the bursal response to a treatment of simultaneous Newcastle disease virus (NDV) infection at 6 days postinfection (dpi) while under chronic heat stress. The bursa is a primary lymphoid organ within birds and is crucial for the development of B cells. We performed RNA-seq and ChIP-seq targeting histone modifications on bursa tissue. Differential gene expression revealed that Leghorn, compared to Fayoumi, had significant down-regulation in genes involved in cell proliferation, cell cycle, and cell division. Interestingly, we also found greater differences in histone modification levels in response to treatment in Leghorns than Fayoumis, and biological processes enriched in associated target genes of H3K27ac and H3K4me1 were similarly associated with cell cycle and receptor signaling of lymphocytes. Lastly, we found candidate variants between the two genetic lines within exons of differentially expressed genes and regulatory elements with differential histone modification enrichment between the lines, which provides a strong foundation for understanding the effects of genetic variation on NDV resistance under heat stress. This study provides further understanding of the cellular mechanisms affected by NDV infection under heat stress in chicken bursa and identified potential genes and regulatory regions that may be targets for developing genetic resistance within chickens.

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.

Abstract Background JUNB transcription factor contributes to the formation of the ubiquitous transcriptional complex AP-1 involved in the control of many physiological and disease-associated functions. The roles of JUNB in the control of cell division and tumorigenic processes are acknowledged but still unclear. Results Here, we report the results of combined transcriptomic, genomic, and functional studies showing that JUNB promotes cell cycle progression via induction of cyclin E1 and repression of transforming growth factor (TGF)-β2 genes. We also show that high levels of JUNB switch the response of TGF-β2 stimulation from an antiproliferative to a pro-invasive one, induce endogenous TGF-β2 production by promoting TGF-β2 mRNA translation, and enhance tumor growth and metastasis in mice. Moreover, tumor genomic data indicate that JUNB amplification associates with poor prognosis in breast and ovarian cancer patients. Conclusions Our results reveal novel functions for JUNB in cell proliferation and tumor aggressiveness through regulation of cyclin E1 and TGF-β2 expression, which might be exploited for cancer prognosis and therapy.

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

Epigenomic regulation and lineage-specific gene expression act in concert to drive cellular differentiation, but the temporal interplay between these processes is largely unknown. Using neural induction from human pluripotent stem cells (hPSCs) as a paradigm, we interrogated these dynamics by performing RNA sequencing (RNA-seq), chromatin immunoprecipitation sequencing (ChIP-seq), and assay for transposase accessible chromatin using sequencing (ATAC-seq) at seven time points during early neural differentiation. We found that changes in DNA accessibility precede H3K27ac, which is followed by gene expression changes. Using massively parallel reporter assays (MPRAs) to test the activity of 2,464 candidate regulatory sequences at all seven time points, we show that many of these sequences have temporal activity patterns that correlate with their respective cell-endogenous gene expression and chromatin changes. A prioritization method incorporating all genomic and MPRA data further identified key transcription factors involved in driving neural fate. These results provide a comprehensive resource of genes and regulatory elements that orchestrate neural induction and illuminate temporal frameworks during differentiation.

DLX transcription factors (TFs) are master regulators of the developing vertebrate brain, driving forebrain GABAergic neuronal differentiation. Ablation of Dlx1&2 alters expression of genes that are critical for forebrain GABAergic development. We integrated epigenomic and transcriptomic analyses, complemented with in situ hybridization (ISH), and in vivo and in vitro studies of regulatory element (RE) function. This revealed the DLX-organized gene regulatory network at genomic, cellular, and spatial levels in mouse embryonic basal ganglia. DLX TFs perform dual activating and repressing functions; the consequences of their binding were determined by the sequence and genomic context of target loci. Our results reveal and, in part, explain the paradox of widespread DLX binding contrasted with a limited subset of target loci that are sensitive at the epigenomic and transcriptomic level to Dlx1&2 ablation. The regulatory properties identified here for DLX TFs suggest general mechanisms by which TFs orchestrate dynamic expression programs underlying neurodevelopment.

Ectopic expression of combinations of transcription factors (TFs) can drive direct lineage conversion, thereby reprogramming a somatic cell's identity. To determine the molecular mechanisms by which Gata4, Mef2c, and Tbx5 (GMT) induce conversion from a cardiac fibroblast toward an induced cardiomyocyte, we performed comprehensive transcriptomic, DNA-occupancy, and epigenomic interrogation throughout the reprogramming process. Integration of these datasets identified new TFs involved in cardiac reprogramming and revealed context-specific roles for GMT, including the ability of Mef2c and Tbx5 to independently promote chromatin remodeling at previously inaccessible sites. We also find evidence for cooperative facilitation and refinement of each TF's binding profile in a combinatorial setting. A reporter assay employing newly defined regulatory elements confirmed that binding of a single TF can be sufficient for gene activation, suggesting that co-binding events do not necessarily reflect synergy. These results shed light on fundamental mechanisms by which combinations of TFs direct lineage conversion.

Abstract Background Imprinting Control Regions (ICRs) are CpG-rich sequences acquiring differential methylation in the female and male germline and maintaining it in a parental origin-specific manner in somatic cells. Despite their expected high mutation rate due to spontaneous deamination of methylated cytosines, ICRs show conservation of CpG-richness and CpG-containing transcription factor binding sites in mammalian species. However, little is known about the mechanisms contributing to the maintenance of a high density of methyl CpGs at these loci. Results To gain functional insights into the mechanisms for maintaining CpG methylation, we sought to identify the proteins binding the methylated allele of the ICRs by determining the interactors of ZFP57 that recognizes a methylated hexanucleotide motif of these DNA regions in mouse ESCs. By using a tagged approach coupled to LC–MS/MS analysis, we identified several proteins, including factors involved in mRNA processing/splicing, chromosome organization, transcription and DNA repair processes. The presence of the post-replicative mismatch-repair (MMR) complex components MSH2 and MSH6 among the identified ZFP57 interactors prompted us to investigate their DNA binding profile by chromatin immunoprecipitation and sequencing. We demonstrated that MSH2 was enriched at gene promoters overlapping unmethylated CpG islands and at repeats. We also found that both MSH2 and MSH6 interacted with the methylated allele of the ICRs, where their binding to DNA was mediated by the ZFP57/KAP1 complex. Conclusions Our findings show that the MMR complex is concentrated on gene promoters and repeats in mouse ESCs, suggesting that maintaining the integrity of these regions is a primary function of highly proliferating cells. Furthermore, the demonstration that MSH2/MSH6 are recruited to the methylated allele of the ICRs through interaction with ZFP57/KAP1 suggests a role of the MMR complex in the maintenance of the integrity of these regulatory regions and evolution of genomic imprinting in mammalian species.

Abstract Background Revealing the gene targets of distal regulatory elements is challenging yet critical for interpreting regulome data. Experiment-derived enhancer-gene links are restricted to a small set of enhancers and/or cell types, while the accuracy of genome-wide approaches remains elusive due to the lack of a systematic evaluation. We combined multiple spatial and in silico approaches for defining enhancer locations and linking them to their target genes aggregated across >500 cell types, generating 1860 human genome-wide distal enhancer-to-target gene definitions (EnTDefs). To evaluate performance, we used gene set enrichment (GSE) testing on 87 independent ENCODE ChIP-seq datasets of 34 transcription factors (TFs) and assessed concordance of results with known TF Gene Ontology annotations, and other benchmarks. Results The top ranked 741 (40%) EnTDefs significantly outperform the common, naïve approach of linking distal regions to the nearest genes, and the top 10 EnTDefs perform well when applied to ChIP-seq data of other cell types. The GSE-based ranking of EnTDefs is highly concordant with ranking based on overlap with curated benchmarks of enhancer-gene interactions. Both our top general EnTDef and cell-type-specific EnTDefs significantly outperform seven independent computational and experiment-based enhancer-gene pair datasets. We show that using our top EnTDefs for GSE with either genome-wide DNA methylation or ATAC-seq data is able to better recapitulate the biological processes changed in gene expression data performed in parallel for the same experiment than our lower-ranked EnTDefs. Conclusions Our findings illustrate the power of our approach to provide genome-wide interpretation regardless of cell type.

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.

Abstract Identifying genomic regions with hypervariable ChIP-seq or ATAC-seq signals across given samples is essential for large-scale epigenetic studies. In particular, the hypervariable regions across tumors from different patients indicate their heterogeneity and can contribute to revealing potential cancer subtypes and the associated epigenetic markers. We present HyperChIP as the first complete statistical tool for the task. HyperChIP uses scaled variances that account for the mean-variance dependence to rank genomic regions, and it increases the statistical power by diminishing the influence of true hypervariable regions on model fitting. A pan-cancer case study illustrates the practical utility of HyperChIP.

Transcription factors (TFs) and chromatin-modifying factors (CMFs) access chromatin by recognizing specific DNA motifs in their target genes. Chromatin immunoprecipitation followed by next-generation sequencing (ChIP-seq) has been widely used to discover the potential DNA-binding motifs for both TFs and CMFs. Yet, an in vivo method for verifying DNA motifs captured by ChIP-seq is lacking in plants. Here, we describe the use of clustered regularly interspaced short palindromic repeat (CRISPR)/CRISPR-associated 9 (Cas9) to verify DNA motifs in their native genomic context in Arabidopsis. Using a single-guide RNA (sgRNA) targeting the DNA motif bound by REF6, a DNA sequence-specific H3K27 demethylase in plants, we generated stable transgenic plants where the motif was disrupted in a REF6 target gene. We also deleted a cluster of multiple motifs from another REF6 target gene using a pair of sgRNAs, targeting upstream and downstream regions of the cluster, respectively. We demonstrated that endogenous genes with motifs disrupted and/or deleted become inaccessible to REF6. This strategy should be widely applicable for in vivo verification of DNA motifs identified by ChIP-seq in plants.

BACKGROUND:Our understanding of the regulation of gene expression has benefited from the availability of high-throughput technologies that interrogate the whole genome for the binding of specific transcription factors and gene expression profiles. In the case of widely used model organisms, such as Escherichia coli K-12, the new knowledge gained from these approaches needs to be integrated with the legacy of accumulated knowledge from genetic and molecular biology experiments conducted in the pre-genomic era in order to attain the deepest level of understanding possible based on the available data. RESULTS:In this paper, we describe an expansion of RegulonDB, the database containing the rich legacy of decades of classic molecular biology experiments supporting what we know about gene regulation and operon organization in E. coli K-12, to include the genome-wide dataset collections from 32 ChIP and 19 gSELEX publications, in addition to around 60 genome-wide expression profiles relevant to the functional significance of these datasets and used in their curation. Three essential features for the integration of this information coming from different methodological approaches are: first, a controlled vocabulary within an ontology for precisely defining growth conditions; second, the criteria to separate elements with enough evidence to consider them involved in gene regulation from isolated transcription factor binding sites without such support; and third, an expanded computational model supporting this knowledge. Altogether, this constitutes the basis for adequately gathering and enabling the comparisons and integration needed to manage and access such wealth of knowledge. CONCLUSIONS:This version 10.0 of RegulonDB is a first step toward what should become the unifying access point for current and future knowledge on gene regulation in E. coli K-12. Furthermore, this model platform and associated methodologies and criteria can be emulated for gathering knowledge on other microbial organisms.

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 (

Genome biology approaches have made enormous contributions to our understanding of biological rhythms, particularly in identifying outputs of the clock, including RNAs, proteins, and metabolites, whose abundance oscillates throughout the day. These methods hold significant promise for future discovery, particularly when combined with computational modeling. However, genome-scale experiments are costly and laborious, yielding "big data" that are conceptually and statistically difficult to analyze. There is no obvious consensus regarding design or analysis. Here we discuss the relevant technical considerations to generate reproducible, statistically sound, and broadly useful genome-scale data. Rather than suggest a set of rigid rules, we aim to codify principles by which investigators, reviewers, and readers of the primary literature can evaluate the suitability of different experimental designs for measuring different aspects of biological rhythms. We introduce CircaInSilico, a web-based application for generating synthetic genome biology data to benchmark statistical methods for studying biological rhythms. Finally, we discuss several unmet analytical needs, including applications to clinical medicine, and suggest productive avenues to address them.

ChIP-seq has been commonly applied to identify genomic occupation of transcription factors (TFs) in a context-specific manner. It is generally assumed that a TF should have similar binding patterns in cells from the same or closely related tissues. Surprisingly, this assumption has not been carefully examined. To this end, we systematically compared the genomic binding of the cell cycle regulator FOXM1 in eight cell lines from seven different human tissues at binding signal, peaks and target genes levels. We found that FOXM1 binding in ER-positive breast cancer cell line MCF-7 are distinct comparing to those in not only other non-breast cell lines, but also MDA-MB-231, ER-negative breast cancer cell line. However, binding sites in MDA-MB-231 and non-breast cell lines were highly consistent. The recruitment of estrogen receptor alpha (ERα) caused the unique FOXM1 binding patterns in MCF-7. Moreover, the activity of FOXM1 in MCF-7 reflects the regulatory functions of ERα, while in MDA-MB-231 and non-breast cell lines, FOXM1 activities regulate cell proliferation. Our results suggest that tissue similarity, in some specific contexts, does not hold precedence over TF-cofactors interactions in determining transcriptional states and that the genomic binding of a TF can be dramatically affected by a particular co-factor under certain conditions.

The lysine demethylase 3A (KDM3A, JMJD1A or JHDM2A) controls transcriptional networks in a variety of biological processes such as spermatogenesis, metabolism, stem cell activity, and tumor progression. We matched transcriptomic and ChIP-Seq profiles to decipher a genome-wide regulatory network of epigenetic control by KDM3A in prostate cancer cells. ChIP-Seq experiments monitoring histone 3 lysine 9 (H3K9) methylation marks show global histone demethylation effects of KDM3A. Combined assessment of histone demethylation events and gene expression changes presented major transcriptional activation suggesting that distinct oncogenic regulators may synergize with the epigenetic patterns by KDM3A. Pathway enrichment analysis of cells with KDM3A knockdown prioritized androgen signaling indicating that KDM3A plays a key role in regulating androgen receptor activity. Matched ChIP-Seq and knockdown experiments of KDM3A in combination with ChIP-Seq of the androgen receptor resulted in a gain of H3K9 methylation marks around androgen receptor binding sites of selected transcriptional targets in androgen signaling including positive regulation of KRT19, NKX3-1, KLK3, NDRG1, MAF, CREB3L4, MYC, INPP4B, PTK2B, MAPK1, MAP2K1, IGF1, E2F1, HSP90AA1, HIF1A, and ACSL3. The cancer systems biology analysis of KDM3A-dependent genes identifies an epigenetic and transcriptional network in androgen response, hypoxia, glycolysis, and lipid metabolism. Genome-wide ChIP-Seq data highlights specific gene targets and the ability of epigenetic master regulators to control oncogenic pathways and cancer progression.

Chromatin immunoprecipitation followed by sequencing (ChIP-seq) is an important tool for studying gene regulatory proteins, such as transcription factors and histones. Peak calling is one of the first steps in the analysis of these data. Peak calling consists of two sub-problems: identifying candidate peaks and testing candidate peaks for statistical significance. We surveyed 30 methods and identified 12 features of the two sub-problems that distinguish methods from each other. We picked six methods GEM, MACS2, MUSIC, BCP, Threshold-based method (TM) and ZINBA] that span this feature space and used a combination of 300 simulated ChIP-seq data sets, 3 real data sets and mathematical analyses to identify features of methods that allow some to perform better than the others. We prove that methods that explicitly combine the signals from ChIP and input samples are less powerful than methods that do not. Methods that use windows of different sizes are more powerful than the ones that do not. For statistical testing of candidate peaks, methods that use a Poisson test to rank their candidate peaks are more powerful than those that use a Binomial test. BCP and MACS2 have the best operating characteristics on simulated transcription factor binding data. GEM has the highest fraction of the top 500 peaks containing the binding motif of the immunoprecipitated factor, with 50% of its peaks within 10 base pairs of a motif. BCP and MUSIC perform best on histone data. These findings provide guidance and rationale for selecting the best peak caller for a given application.

The HAND2 transcriptional regulator controls cardiac development, and we uncover additional essential functions in the endothelial to mesenchymal transition (EMT) underlying cardiac cushion development in the atrioventricular canal (AVC). In Hand2-deficient mouse embryos, the EMT underlying AVC cardiac cushion formation is disrupted, and we combined ChIP-seq of embryonic hearts with transcriptome analysis of wild-type and mutants AVCs to identify the functionally relevant HAND2 target genes. The HAND2 target gene regulatory network (GRN) includes most genes with known functions in EMT processes and AVC cardiac cushion formation. One of these is Snai1, an EMT master regulator whose expression is lost from Hand2-deficient AVCs. Re-expression of Snai1 in mutant AVC explants partially restores this EMT and mesenchymal cell migration. Furthermore, the HAND2-interacting enhancers in the Snai1 genomic landscape are active in embryonic hearts and other Snai1-expressing tissues. These results show that HAND2 directly regulates the molecular cascades initiating AVC cardiac valve development.

The extent and nature of epigenomic changes associated with melanoma progression is poorly understood. Through systematic epigenomic profiling of 35 epigenetic modifications and transcriptomic analysis, we define chromatin state changes associated with melanomagenesis by using a cell phenotypic model of non-tumorigenic and tumorigenic states. Computation of specific chromatin state transitions showed loss of histone acetylations and H3K4me2/3 on regulatory regions proximal to specific cancer-regulatory genes in important melanoma-driving cell signaling pathways. Importantly, such acetylation changes were also observed between benign nevi and malignant melanoma human tissues. Intriguingly, only a small fraction of chromatin state transitions correlated with expected changes in gene expression patterns. Restoration of acetylation levels on deacetylated loci by histone deacetylase (HDAC) inhibitors selectively blocked excessive proliferation in tumorigenic cells and human melanoma cells, suggesting functional roles of observed chromatin state transitions in driving hyperproliferative phenotype. Through these results, we define functionally relevant chromatin states associated with melanoma progression.

The interplay between transcription factors and chromatin dictates gene regulatory network activity. Germ layer specification is tightly coupled with zygotic gene activation and, in most metazoans, is dependent upon maternal factors. We explore the dynamic genome-wide interactions of Foxh1, a maternal transcription factor that mediates Nodal/TGF-β signaling, with cis-regulatory modules (CRMs) during mesendodermal specification. Foxh1 marks CRMs during cleavage stages and recruits the co-repressor Tle/Groucho in the early blastula. We highlight a population of CRMs that are continuously occupied by Foxh1 and show that they are marked by H3K4me1, Ep300, and Fox/Sox/Smad motifs, suggesting interplay between these factors in gene regulation. We also propose a molecular "hand-off" between maternal Foxh1 and zygotic Foxa at these CRMs to maintain enhancer activation. Our findings suggest that Foxh1 functions at the top of a hierarchy of interactions by marking developmental genes for activation, beginning with the onset of zygotic gene expression.

Histone citrullination regulates diverse cellular processes. Here, we report that SMARCAD1 preferentially associates with H3 arginine 26 citrullination (H3R26Cit) peptides present on arrays composed of 384 histone peptides harboring distinct post-transcriptional modifications. Among ten histone modifications assayed by ChIP-seq, H3R26Cit exhibited the most extensive genomewide co-localization with SMARCAD1 binding. Increased Smarcad1 expression correlated with naive pluripotency in pre-implantation embryos. In the presence of LIF, Smarcad1 knockdown (KD) embryonic stem cells lost naive state phenotypes but remained pluripotent, as suggested by morphology, gene expression, histone modifications, alkaline phosphatase activity, energy metabolism, embryoid bodies, teratoma, and chimeras. The majority of H3R26Cit ChIP-seq peaks occupied by SMARCAD1 were associated with increased levels of H3K9me3 in Smarcad1 KD cells. Inhibition of H3Cit induced H3K9me3 at the overlapping regions of H3R26Cit peaks and SMARCAD1 peaks. These data suggest a model in which SMARCAD1 regulates naive pluripotency by interacting with H3R26Cit and suppressing heterochromatin formation.