Genome-wide transcription factor binding: beyond direct target regulation

TExCNN: Leveraging Pre-Trained Models to Predict Gene Expression from Genomic Sequences

BACKGROUND/OBJECTIVES

Understanding the relationship between DNA sequences and gene expression levels is of significant biological importance. Recent advancements have demonstrated the ability of deep learning to predict gene expression levels directly from genomic data. However, traditional methods are limited by basic word encoding techniques, which fail to capture the inherent features and patterns of DNA sequences.

METHODS

We introduce TExCNN, a novel framework that integrates the pre-trained models DNABERT and DNABERT-2 to generate word embeddings for DNA sequences. We partitioned the DNA sequences into manageable segments and computed their respective embeddings using the pre-trained models. These embeddings were then utilized as inputs to our deep learning framework, which was based on convolutional neural network.

RESULTS

TExCNN outperformed current state-of-the-art models, achieving an average R2 score of 0.622, compared to the 0.596 score achieved by the DeepLncLoc model, which is based on the Word2Vec model and a text convolutional neural network. Furthermore, when the sequence length was extended from 10,500 bp to 50,000 bp, TExCNN achieved an even higher average R2 score of 0.639. The prediction accuracy improved further when additional biological features were incorporated.

CONCLUSIONS

Our experimental results demonstrate that the use of pre-trained models for word embedding generation significantly improves the accuracy of predicting gene expression. The proposed TExCNN pipeline performes optimally with longer DNA sequences and is adaptable for both cell-type-independent and cell-type-dependent predictions.

Correlating gene expression levels with transcription factor binding sites facilitates identification of key transcription factors from transcriptome data

Identification of key transcription factors from transcriptome data by correlating gene expression levels with transcription factor binding sites is important for transcriptome data analysis. In a typical scenario, we always set a threshold to filter the top ranked differentially expressed genes and top ranked transcription factor binding sites. However, correlation analysis of filtered data can often result in spurious correlations. In this study, we tested four methods for creating the gene expression inputs (ranked gene list) in the correlation analysis: star coordinate map transformation (START), expression differential score (ED), preferential expression measure (PEM), and the specificity measure (SPM). Then, Kendall's tau correlation statistical algorithms implementing the standard (STD), LINEAR, MIX-LINEAR, DENSITY-CURVE, and MIXED-DENSITY-CURVE weighting methods were used to identify key transcription factors. ED was identified as the optimal method for creating a ranked gene list from filtered expression data, which can address the "unable to detect negative correlation" fallacy presented by other methods. The MIXED-DENSITY-CURVE was the most sensitive for identifying transcription factors from the gene set and list in which only the top proportion was correlated. Ultimately, 644 transcription factor candidates were identified from the transcriptome data of 1,206 cell lines, six of which were validated by wet lab experiments. The Jinzer and Flaver software implementing these methods can be obtained from http://www.thua45/cn/flaver under a free academic license.

Dynamic activity changes in transcription factors: Unlocking the mechanisms regulating physiological changes in the brain

Transcription factors (TFs) regulate the establishment and modulation of the transcriptome within cells, thereby playing a crucial role in various aspects of cellular physiology throughout the body. Quantitative measurement of TF activity during the development, function, and dysfunction of the brain is essential for gaining a deeper understanding of the regulatory mechanisms governing gene expression during these processes. Due to their role as regulators of gene expression, assessing and modulating detailed TF activity contributes to the development of practical methods to intervene in these processes, potentially offering more efficient treatments for diseases. Recent methodologies have revealed that TF activity is dynamically regulated within cells and organisms, including the adult brain. This review summarizes the regulatory mechanisms of TF activities and the methodologies used to assess them, emphasizing their importance in both fundamental research and clinical applications.

A MOZ-TIF2 leukemia mouse model displays KAT6-dependent H3K23 propionylation and overexpression of a set of active developmental genes

Aberrant regulation of chromatin modifiers is a common occurrence across many cancer types, and a key priority is to determine how specific alterations of these proteins, often enzymes, can be targeted therapeutically. MOZ, a histone acyltransferase, is recurrently fused to coactivators CBP, p300, and TIF2 in cases of acute myeloid leukemia (AML). Using either pharmacological inhibition or targeted protein degradation in a mouse model for MOZ-TIF2-driven leukemia, we show that KAT6 (MOZ/MORF) enzymatic activity and the MOZ-TIF2 protein are necessary for indefinite proliferation in cell culture. MOZ-TIF2 directly regulates a small subset of genes encoding developmental transcription factors, augmenting their high expression. Furthermore, transcription levels in MOZ-TIF2 cells positively correlate with enrichment of histone H3 propionylation at lysine 23 (H3K23pr), a recently appreciated histone acylation associated with gene activation. Unexpectedly, we also show that MOZ-TIF2 and MLL-AF9 regulate transcription of unique gene sets, and their cellular models exhibit distinct sensitivities to multiple small-molecule inhibitors directed against AML pathways. This is despite the shared genetic pathways of wild-type MOZ and MLL. Overall, our data provide insight into how aberrant regulation of MOZ contributes to leukemogenesis. We anticipate that these experiments will inform future work identifying targeted therapies in the treatment of AML and other diseases involving MOZ-induced transcriptional dysregulation.

The ENCODE mouse postnatal developmental time course identifies regulatory programs of cell types and cell states

Postnatal genomic regulation significantly influences tissue and organ maturation but is under-studied relative to existing genomic catalogs of adult tissues or prenatal development in mouse. The ENCODE4 consortium generated the first comprehensive single-nucleus resource of postnatal regulatory events across a diverse set of mouse tissues. The collection spans seven postnatal time points, mirroring human development from childhood to adulthood, and encompasses five core tissues. We identified 30 cell types, further subdivided into 69 subtypes and cell states across adrenal gland, left cerebral cortex, hippocampus, heart, and gastrocnemius muscle. Our annotations cover both known and novel cell differentiation dynamics ranging from early hippocampal neurogenesis to a new sex-specific adrenal gland population during puberty. We used an ensemble Latent Dirichlet Allocation strategy with a curated vocabulary of 2,701 regulatory genes to identify regulatory "topics," each of which is a gene vector, linked to cell type differentiation, subtype specialization, and transitions between cell states. We find recurrent regulatory topics in tissue-resident macrophages, neural cell types, endothelial cells across multiple tissues, and cycling cells of the adrenal gland and heart. Cell-type-specific topics are enriched in transcription factors and microRNA host genes, while chromatin regulators dominate mitosis topics. Corresponding chromatin accessibility data reveal dynamic and sex-specific regulatory elements, with enriched motifs matching transcription factors in regulatory topics. Together, these analyses identify both tissue-specific and common regulatory programs in postnatal development across multiple tissues through the lens of the factors regulating transcription.

PML::RARA and GATA2 proteins interact via DNA templates to induce aberrant self-renewal in mouse and human hematopoietic cells

The underlying mechanism(s) by which the PML::RARA fusion protein initiates acute promyelocytic leukemia is not yet clear. We defined the genomic binding sites of PML::RARA in primary mouse and human hematopoietic progenitor cells with V5-tagged PML::RARA, using anti-V5-PML::RARA chromatin immunoprecipitation sequencing and CUT&RUN approaches. Most genomic PML::RARA binding sites were found in regions that were already chromatin-accessible (defined by ATAC-seq) in unmanipulated, wild-type promyelocytes, suggesting that these regions are "open" prior to PML::RARA expression. We found that GATA binding motifs, and the direct binding of the chromatin "pioneering factor" GATA2, were significantly enriched near PML::RARA binding sites. Proximity labeling studies revealed that PML::RARA interacts with ~250 proteins in primary mouse hematopoietic cells; GATA2 and 33 others require PML::RARA binding to DNA for the interaction to occur, suggesting that binding to their cognate DNA target motifs may stabilize their interactions. In the absence of PML::RARA, Gata2 overexpression induces many of the same epigenetic and transcriptional changes as PML::RARA. These findings suggested that PML::RARA may indirectly initiate its transcriptional program by activating Gata2 expression: Indeed, we demonstrated that inactivation of Gata2 prior to PML::RARA expression prevented its ability to induce self-renewal. These data suggested that GATA2 binding creates accessible chromatin regions enriched for both GATA and Retinoic Acid Receptor Element motifs, where GATA2 and PML::RARA can potentially bind and interact with each other. In turn, PML::RARA binding to DNA promotes a feed-forward transcriptional program by positively regulating Gata2 expression. Gata2 may therefore be required for PML::RARA to establish its transcriptional program.

A novel OsHB5-OsAPL-OsMADS27/OsWRKY102 regulatory module regulates grain size in rice

Grain size, a crucial trait that determines rice yield and quality, is typically regulated by multiple genes. Although numerous genes controlling grain size have been identified, the precise and dynamic regulatory network governing grain size is still not fully understood. In this study, we unveiled a novel regulatory module composed of OsHB5, OsAPL and OsMADS27/OsWRKY102, which plays a crucial role in modulating grain size in rice. As a positive regulator of grain size, OsAPL has been found to interact with OsHB5 both in vitro and in vivo. Through chromatin immunoprecipitation-sequencing, we successfully mapped two potential targets of OsAPL, namely OsMADS27, a positive regulator in grain size and OsWRKY102, a negative regulator in lignification that is also associated with grain size control. Further evidence from EMSA and chromatin immunoprecipitation-quantitative PCR experiments has shown that OsAPL acts as an upstream transcription factor that directly binds to the promoters of OsMADS27 and OsWRKY102. Moreover, EMSA and dual-luciferase reporter assays have indicated that the interaction between OsAPL and OsHB5 enhances the repressive effect of OsAPL on OsMADS27 and OsWRKY102. Collectively, our findings discovered a novel regulatory module, OsHB5-OsAPL-OsMADS27/OsWRKY102, which plays a significant role in controlling grain size in rice. These discoveries provide potential targets for breeding high-yield and high-quality rice varieties.

Unsupervised AI reveals insect species-specific genome signatures

Insects are a highly diverse phylogeny and possess a wide variety of traits, including the presence or absence of wings and metamorphosis. These diverse traits are of great interest for studying genome evolution, and numerous comparative genomic studies have examined a wide phylogenetic range of insects. Here, we analyzed 22 insects belonging to a wide phylogenetic range (Endopterygota, Paraneoptera, Polyneoptera, Palaeoptera, and other insects) by using a batch-learning self-organizing map (BLSOM) for oligonucleotide compositions in their genomic fragments (100-kb or 1-Mb sequences), which is an unsupervised machine learning algorithm that can extract species-specific characteristics of the oligonucleotide compositions (genome signatures). The genome signature is of particular interest in terms of the mechanisms and biological significance that have caused the species-specific difference, and can be used as a powerful search needle to explore the various roles of genome sequences other than protein coding, and can be used to unveil mysteries hidden in the genome sequence. Since BLSOM is an unsupervised clustering method, the clustering of sequences was performed based on the oligonucleotide composition alone, without providing information about the species from which each fragment sequence was derived. Therefore, not only the interspecies separation, but also the intraspecies separation can be achieved. Here, we have revealed the specific genomic regions with oligonucleotide compositions distinct from the usual sequences of each insect genome, e.g., Mb-level structures found for a grasshopper Schistocerca americana. One aim of this study was to compare the genome characteristics of insects with those of vertebrates, especially humans, which are phylogenetically distant from insects. Recently, humans seem to be the "model organism" for which a large amount of information has been accumulated using a variety of cutting-edge and high-throughput technologies. Therefore, it is reasonable to use the abundant information from humans to study insect lineages. The specific regions of Mb length with distinct oligonucleotide compositions have also been previously observed in the human genome. These regions were enriched by transcription factor binding motifs (TFBSs) and hypothesized to be involved in the three-dimensional arrangement of chromosomal DNA in interphase nuclei. The present study characterized the species-specific oligonucleotide compositions (i.e., genome signatures) in insect genomes and identified specific genomic regions with distinct oligonucleotide compositions.

KaScape: a sequencing-based method for global characterization of protein‒DNA binding affinity

It is difficult to exhaustively screen all possible DNA binding sequences for a given transcription factor (TF). Here, we developed the KaScape method, in which TFs bind to all possible DNA sequences in the same DNA pool where DNA sequences are prepared by randomized oligo synthesis and the random length can be adjusted to a length such as 4, 5, 6, or 7. After separating bound from unbound double-stranded DNAs (dsDNAs), their sequences are determined by next-generation sequencing. To demonstrate the relative binding affinities of all possible DNA sequences determined by KaScape, we developed three-dimensional KaScape viewing software based on a K-mer graph. We applied KaScape to 12 plant TF family AtWRKY proteins and found that all AtWRKY proteins bound to the core sequence GAC with similar profiles. KaScape can detect not only binding sequences consistent with the consensus W-box "TTGAC(C/T)" but also other sequences with weak affinity. KaScape provides a high-throughput, easy-to-operate, sensitive, and exhaustive method for quantitatively characterizing the relative binding strength of a TF with all possible binding sequences, allowing us to comprehensively characterize the specificity and affinity landscape of transcription factors, particularly for moderate- and low-affinity binding sites.

Building High-Confidence Gene Regulatory Networks by Integrating Validated TF-Target Gene Interactions Using ConnecTF

Many methods are now available to identify or predict the target genes of transcription factors (TFs) in plants. These include experimental approaches such as in vivo or in vitro TF-target gene-binding assays and various methods for identifying regulated targets in mutants, transgenics, or isolated plant cells. In addition, computational approaches are used to infer TF-target gene interactions from the regulatory elements or gene expression changes across treatments. While each of these approaches has now been applied to a large number of TFs from many species, each method has its own limitations which necessitates that multiple data types are integrated to build the most accurate representation of the gene regulatory networks operating in plants. To make the analyses of TF-target interaction datasets available to the broader research community, we have developed the ConnecTF web platform ( https://connectf.org/ ). In this chapter, we describe how ConnecTF can be used to integrate validated and predicted TF-target gene interactions in order to dissect the regulatory role of TFs in developmental and stress response pathways. Using as our examples KN1 and RA1, two well-characterized maize TFs involved in developing floral tissue, we demonstrate how ConnecTF can be used to (1) compare the target genes between TFs, (2) identify direct vs. indirect targets by combining TF-binding and TF-regulation datasets, (3) chart and visualize network paths between TFs and their downstream targets, and (4) prune inferred user networks for high-confidence predicted interactions using validated TF-target gene data. Finally, we provide instructions for setting up a private version of ConnecTF that enables research groups to store and analyze their own TF-target gene interaction datasets.

Multi-Layered Regulations on the Chromatin Architectures: Establishing the Tight and Specific Responses of Fission Yeast fbp1 Gene Transcription

Transcriptional regulation is pivotal for all living organisms and is required for adequate response to environmental fluctuations and intercellular signaling molecules. For precise regulation of transcription, cells have evolved regulatory systems on the genome architecture, including the chromosome higher-order structure (e.g., chromatin loops), location of transcription factor (TF)-binding sequences, non-coding RNA (ncRNA) transcription, chromatin configuration (e.g., nucleosome positioning and histone modifications), and the topological state of the DNA double helix. To understand how these genome-chromatin architectures and their regulators establish tight and specific responses at the transcription stage, the fission yeast fbp1 gene has been analyzed as a model system for decades. The fission yeast fbp1 gene is tightly repressed in the presence of glucose, and this gene is induced by over three orders of magnitude upon glucose starvation with a cascade of multi-layered regulations on various levels of genome and chromatin architecture. In this review article, we summarize the multi-layered transcriptional regulatory systems revealed by the analysis of the fission yeast fbp1 gene as a model system.

DNA and coding/non-coding RNA methylation analysis provide insights into tomato fruit ripening

Ripening is the last, irreversible developmental stage during which fruit become palatable, thus promoting seed dispersal by frugivory. In Alisa Craig fruit, mRNAs with increasing m5C levels, such as STPK and WRKY 40, were identified as being involved in response to biotic and abiotic stresses. Furthermore, two mRNAs involved in cell wall metabolism, PG and EXP-B1, also presented increased m5C levels. In the Nr mutant, several m5C-modified mRNAs involved in fruit ripening, including those encoding WRKY and MADS-box proteins, were found. Targets of long non-coding RNAs and circular RNAs with different m5C sites were also found; these targets included 2-alkenal reductase, soluble starch synthase 1, WRKY, MADS-box, and F-box/ketch-repeat protein SKIP11. A combined analysis of changes in 5mC methylation and mRNA revealed many differentially expressed genes with differentially methylated regions encoding transcription factors and key enzymes related to ethylene biosynthesis and signal transduction; these included ERF084, EIN3, AP2/ERF, ACO5, ACS7, EIN3/4, EBF1, MADS-box, AP2/ERF, and ETR1. Taken together, our findings contribute to the global understanding of the mechanisms underlying fruit ripening, thereby providing new information for both fruit and post-harvest behavior.

Transcription factor-nucleosome dynamics from plasma cfDNA identifies ER-driven states in breast cancer

Genome-wide binding profiles of estrogen receptor (ER) and FOXA1 reflect cancer state in ER+ breast cancer. However, routine profiling of tumor transcription factor (TF) binding is impractical in the clinic. Here, we show that plasma cell-free DNA (cfDNA) contains high-resolution ER and FOXA1 tumor binding profiles for breast cancer. Enrichment of TF footprints in plasma reflects the binding strength of the TF in originating tissue. We defined pure in vivo tumor TF signatures in plasma using ER+ breast cancer xenografts, which can distinguish xenografts with distinct ER states. Furthermore, state-specific ER-binding signatures can partition human breast tumors into groups with significantly different ER expression and mortality. Last, TF footprints in human plasma samples can identify the presence of ER+ breast cancer. Thus, plasma TF footprints enable minimally invasive mapping of the regulatory landscape of breast cancer in humans and open vast possibilities for clinical applications across multiple tumor types.

Comparative genomic analysis of the human genome and six bat genomes using unsupervised machine learning: Mb-level CpG and TFBS islands

BACKGROUND

Emerging infectious disease-causing RNA viruses, such as the SARS-CoV-2 and Ebola viruses, are thought to rely on bats as natural reservoir hosts. Since these zoonotic viruses pose a great threat to humans, it is important to characterize the bat genome from multiple perspectives. Unsupervised machine learning methods for extracting novel information from big sequence data without prior knowledge or particular models are highly desirable for obtaining unexpected insights. We previously established a batch-learning self-organizing map (BLSOM) of the oligonucleotide composition that reveals novel genome characteristics from big sequence data.

RESULTS

In this study, using the oligonucleotide BLSOM, we conducted a comparative genomic study of humans and six bat species. BLSOM is an explainable-type machine learning algorithm that reveals the diagnostic oligonucleotides contributing to sequence clustering (self-organization). When unsupervised machine learning reveals unexpected and/or characteristic features, these features can be studied in more detail via the much simpler and more direct standard distribution map method. Based on this combined strategy, we identified the Mb-level enrichment of CG dinucleotide (Mb-level CpG islands) around the termini of bat long-scaffold sequences. In addition, a class of CG-containing oligonucleotides were enriched in the centromeric and pericentromeric regions of human chromosomes. Oligonucleotides longer than tetranucleotides often represent binding motifs for a wide variety of proteins (e.g., transcription factor binding sequences (TFBSs)). By analyzing the penta- and hexanucleotide composition, we observed the evident enrichment of a wide range of hexanucleotide TFBSs in centromeric and pericentromeric heterochromatin regions on all human chromosomes.

CONCLUSION

Function of transcription factors (TFs) beyond their known regulation of gene expression (e.g., TF-mediated looping interactions between two different genomic regions) has received wide attention. The Mb-level TFBS and CpG islands are thought to be involved in the large-scale nuclear organization, such as centromere and telomere clustering. TFBSs, which are enriched in centromeric and pericentromeric heterochromatin regions, are thought to play an important role in the formation of nuclear 3D structures. Our machine learning-based analysis will help us to understand the differential features of nuclear 3D structures in the human and bat genomes.

Identification and functional characterization of transcriptional activators in human cells

Transcription is orchestrated by thousands of transcription factors (TFs) and chromatin-associated proteins, but how these are causally connected to transcriptional activation is poorly understood. Here, we conduct an unbiased proteome-scale screen to systematically uncover human proteins that activate transcription in a natural chromatin context. By combining interaction proteomics and chemical inhibitors, we delineate the preference of these transcriptional activators for specific co-activators, highlighting how even closely related TFs can function via distinct cofactors. We also identify potent transactivation domains among the hits and use AlphaFold2 to predict and experimentally validate interaction interfaces of two activation domains with BRD4. Finally, we show that many novel activators are partners in fusion events in tumors and functionally characterize a myofibroma-associated fusion between SRF and C3orf62, a potent p300-dependent activator. Our work provides a functional catalog of potent transactivators in the human proteome and a platform for discovering transcriptional regulators at genome scale.

Lupus Susceptibility Region Containing CDKN1B rs34330 Mechanistically Influences Expression and Function of Multiple Target Genes, Also Linked to Proliferation and Apoptosis

OBJECTIVE

In a recent genome-wide association study, a significant genetic association between rs34330 of CDKN1B and risk of systemic lupus erythematosus (SLE) in Han Chinese was identified. This study was undertaken to validate the reported association and elucidate the biochemical mechanisms underlying the effect of the variant.

METHODS

We performed an allelic association analysis in patients with SLE, followed by a meta-analysis assessing genome-wide association data across 11 independent cohorts (n = 28,872). In silico bioinformatics analysis and experimental validation in SLE-relevant cell lines were applied to determine the functional consequences of rs34330.

RESULTS

We replicated a genetic association between SLE and rs34330 (meta-analysis P = 5.29 × 10-22 , odds ratio 0.84 [95% confidence interval 0.81-0.87]). Follow-up bioinformatics and expression quantitative trait locus analysis suggested that rs34330 is located in active chromatin and potentially regulates several target genes. Using luciferase and chromatin immunoprecipitation-real-time quantitative polymerase chain reaction, we demonstrated substantial allele-specific promoter and enhancer activity, and allele-specific binding of 3 histone marks (H3K27ac, H3K4me3, and H3K4me1), RNA polymerase II (Pol II), CCCTC-binding factor, and a critical immune transcription factor (interferon regulatory factor 1 [IRF-1]). Chromosome conformation capture revealed long-range chromatin interactions between rs34330 and the promoters of neighboring genes APOLD1 and DDX47, and effects on CDKN1B and the other target genes were directly validated by clustered regularly interspaced short palindromic repeat (CRISPR)-based genome editing. Finally, CRISPR/dead CRISPR-associated protein 9-based epigenetic activation/silencing confirmed these results. Gene-edited cell lines also showed higher levels of proliferation and apoptosis.

CONCLUSION

Collectively, these findings suggest a mechanism whereby the rs34330 risk allele (C) influences the presence of histone marks, RNA Pol II, and IRF-1 transcription factor to regulate expression of several target genes linked to proliferation and apoptosis. This process could potentially underlie the association of rs34330 with SLE.

Search and Localization Dynamics of the CRISPR-Cas9 System

The CRISPR-Cas9 system acts as the prokaryotic immune system and has important applications in gene editing. The protein Cas9 is one of its crucial components. The role of Cas9 is to search for specific target sequences on the DNA and cleave them. In this Letter, we introduce a model of facilitated diffusion for Cas9 and fit its parameters to single-molecule experiments. Our model confirms that Cas9 search for targets by sliding, but shows that its sliding length is rather short. We then investigate how Cas9 explores a long stretch of DNA containing randomly placed targets. We solve this problem by mapping it into the theory of Anderson localization in condensed matter physics. Our theoretical approach rationalizes experimental evidence on the distribution of Cas9 molecules along the DNA.

Reciprocal stabilization of transcription factor binding integrates two signaling pathways to regulate fission yeast fbp1 transcription

Transcriptional regulation, a pivotal biological process by which cells adapt to environmental fluctuations, is achieved by the binding of transcription factors to target sequences in a sequence-specific manner. However, how transcription factors recognize the correct target from amongst the numerous candidates in a genome has not been fully elucidated. We here show that, in the fission-yeast fbp1 gene, when transcription factors bind to target sequences in close proximity, their binding is reciprocally stabilized, thereby integrating distinct signal transduction pathways. The fbp1 gene is massively induced upon glucose starvation by the activation of two transcription factors, Atf1 and Rst2, mediated via distinct signal transduction pathways. Atf1 and Rst2 bind to the upstream-activating sequence 1 region, carrying two binding sites located 45 bp apart. Their binding is reciprocally stabilized due to the close proximity of the two target sites, which destabilizes the independent binding of Atf1 or Rst2. Tup11/12 (Tup-family co-repressors) suppress independent binding. These data demonstrate a previously unappreciated mechanism by which two transcription-factor binding sites, in close proximity, integrate two independent-signal pathways, thereby behaving as a hub for signal integration.

RHOX10 drives mouse spermatogonial stem cell establishment through a transcription factor signaling cascade

Spermatogonial stem cells (SSCs) are essential for male fertility. Here, we report that mouse SSC generation is driven by a transcription factor (TF) cascade controlled by the homeobox protein, RHOX10, which acts by driving the differentiation of SSC precursors called pro-spermatogonia (ProSG). We identify genes regulated by RHOX10 in ProSG in vivo and define direct RHOX10-target genes using several approaches, including a rapid temporal induction assay: iSLAMseq. Together, these approaches identify temporal waves of RHOX10 direct targets, as well as RHOX10 secondary-target genes. Many of the RHOX10-regulated genes encode proteins with known roles in SSCs. Using an in vitro ProSG differentiation assay, we find that RHOX10 promotes mouse ProSG differentiation through a conserved transcriptional cascade involving the key germ-cell TFs DMRT1 and ZBTB16. Our study gives important insights into germ cell development and provides a blueprint for how to define TF cascades.

Time-Based Systems Biology Approaches to Capture and Model Dynamic Gene Regulatory Networks

All aspects of transcription and its regulation involve dynamic events. However, capturing these dynamic events in gene regulatory networks (GRNs) offers both a promise and a challenge. The promise is that capturing and modeling the dynamic changes in GRNs will allow us to understand how organisms adapt to a changing environment. The ability to mount a rapid transcriptional response to environmental changes is especially important in nonmotile organisms such as plants. The challenge is to capture these dynamic, genome-wide events and model them in GRNs. In this review, we cover recent progress in capturing dynamic interactions of transcription factors with their targets-at both the local and genome-wide levels-and how they are used to learn how GRNs operate as a function of time. We also discuss recent advances that employ time-based machine learning approaches to forecast gene expression at future time points, a key goal of systems biology.

Transcription factor enrichment analysis (TFEA) quantifies the activity of multiple transcription factors from a single experiment

Detecting changes in the activity of a transcription factor (TF) in response to a perturbation provides insights into the underlying cellular process. Transcription Factor Enrichment Analysis (TFEA) is a robust and reliable computational method that detects positional motif enrichment associated with changes in transcription observed in response to a perturbation. TFEA detects positional motif enrichment within a list of ranked regions of interest (ROIs), typically sites of RNA polymerase initiation inferred from regulatory data such as nascent transcription. Therefore, we also introduce muMerge, a statistically principled method of generating a consensus list of ROIs from multiple replicates and conditions. TFEA is broadly applicable to data that informs on transcriptional regulation including nascent transcription (eg. PRO-Seq), CAGE, histone ChIP-Seq, and accessibility data (e.g., ATAC-Seq). TFEA not only identifies the key regulators responding to a perturbation, but also temporally unravels regulatory networks with time series data. Consequently, TFEA serves as a hypothesis-generating tool that provides an easy, rigorous, and cost-effective means to broadly assess TF activity yielding new biological insights.

Qki activates Srebp2-mediated cholesterol biosynthesis for maintenance of eye lens transparency

Defective cholesterol biosynthesis in eye lens cells is often associated with cataracts; however, how genes involved in cholesterol biosynthesis are regulated in lens cells remains unclear. Here, we show that Quaking (Qki) is required for the transcriptional activation of genes involved in cholesterol biosynthesis in the eye lens. At the transcriptome level, lens-specific Qki-deficient mice present downregulation of genes associated with the cholesterol biosynthesis pathway, resulting in a significant reduction of total cholesterol level in the eye lens. Mice with Qki depletion in lens epithelium display progressive accumulation of protein aggregates, eventually leading to cataracts. Notably, these defects are attenuated by topical sterol administration. Mechanistically, we demonstrate that Qki enhances cholesterol biosynthesis by recruiting Srebp2 and Pol II in the promoter regions of cholesterol biosynthesis genes. Supporting its function as a transcription co-activator, we show that Qki directly interacts with single-stranded DNA. In conclusion, we propose that Qki-Srebp2-mediated cholesterol biosynthesis is essential for maintaining the cholesterol level that protects lens from cataract development.

To mock or not: a comprehensive comparison of mock IP and DNA input for ChIP-seq

Chromatin immunoprecipitation (IP) followed by sequencing (ChIP-seq) is the gold standard to detect transcription-factor (TF) binding sites in the genome. Its success depends on appropriate controls removing systematic biases. The predominantly used controls, i.e. DNA input, correct for uneven sonication, but not for nonspecific interactions of the IP antibody. Another type of controls, 'mock' IP, corrects for both of the issues, but is not widely used because it is considered susceptible to technical noise. The tradeoff between the two control types has not been investigated systematically. Therefore, we generated comparable DNA input and mock IP experiments. Because mock IPs contain only nonspecific interactions, the sites predicted from them using DNA input indicate the spurious-site abundance. This abundance is highly correlated with the 'genomic activity' (e.g. chromatin openness). In particular, compared to cell lines, complex samples such as whole organisms have more spurious sites-probably because they contain multiple cell types, resulting in more expressed genes and more open chromatin. Consequently, DNA input and mock IP controls performed similarly for cell lines, whereas for complex samples, mock IP substantially reduced the number of spurious sites. However, DNA input is still informative; thus, we developed a simple framework integrating both controls, improving binding site detection.

Kinetic Modeling and Meta-Analysis of the Bacillus subtilis SigB Regulon during Spore Germination and Outgrowth

The exponential increase in the number of conducted studies combined with the development of sequencing methods have led to an enormous accumulation of partially processed experimental data in the past two decades. Here, we present an approach using literature-mined data complemented with gene expression kinetic modeling and promoter sequence analysis. This approach allowed us to identify the regulon of Bacillus subtilis sigma factor SigB of RNA polymerase (RNAP) specifically expressed during germination and outgrowth. SigB is critical for the cell's response to general stress but is also expressed during spore germination and outgrowth, and this specific regulon is not known. This approach allowed us to (i) define a subset of the known SigB regulon controlled by SigB specifically during spore germination and outgrowth, (ii) identify the influence of the promoter sequence binding motif organization on the expression of the SigB-regulated genes, and (iii) suggest additional sigma factors co-controlling other SigB-dependent genes. Experiments then validated promoter sequence characteristics necessary for direct RNAP-SigB binding. In summary, this work documents the potential of computational approaches to unravel new information even for a well-studied system; moreover, the study specifically identifies the subset of the SigB regulon, which is activated during germination and outgrowth.

Cytokinin-Regulated Expression of Arabidopsis thaliana PAP Genes and Its Implication for the Expression of Chloroplast-Encoded Genes

Cytokinins (CKs) are known to regulate the biogenesis of chloroplasts under changing environmental conditions and at different stages of plant ontogenesis. However, the underlying mechanisms are still poorly understood. Apparently, the mechanisms can be duplicated in several ways, including the influence of nuclear genes that determine the expression of plastome through the two-component CK regulatory circuit. In this study, we evaluated the role of cytokinins and CK signaling pathway on the expression of nuclear genes for plastid RNA polymerase-associated proteins (PAPs). Cytokinin induced the expression of all twelve Arabidopsis thalianaPAP genes irrespective of their functions via canonical CK signaling pathway but this regulation might be indirect taking into consideration their different functions and versatile structure of promoter regions. The disruption of PAP genes contributed to the abolishment of positive CK effect on the accumulation of the chloroplast gene transcripts and transcripts of the nuclear genes for plastid transcription machinery as can be judged from the analysis of pap1 and pap6 mutants. However, the CK regulatory circuit in the mutants remained practically unperturbed. Knock-out of PAP genes resulted in cytokinin overproduction as a consequence of the strong up-regulation of the genes for CK synthesis.

Site-Specific Phosphorylation of Histone H1.4 Is Associated with Transcription Activation

Core histone variants, such as H2A.X and H3.3, serve specialized roles in chromatin processes that depend on the genomic distributions and amino acid sequence differences of the variant proteins. Modifications of these variants alter interactions with other chromatin components and thus the protein’s functions. These inferences add to the growing arsenal of evidence against the older generic view of those linker histones as redundant repressors. Furthermore, certain modifications of specific H1 variants can confer distinct roles. On the one hand, it has been reported that the phosphorylation of H1 results in its release from chromatin and the subsequent transcription of HIV-1 genes. On the other hand, recent evidence indicates that phosphorylated H1 may in fact be associated with active promoters. This conflict suggests that different H1 isoforms and modified versions of these variants are not redundant when together but may play distinct functional roles. Here, we provide the first genome-wide evidence that when phosphorylated, the H1.4 variant remains associated with active promoters and may even play a role in transcription activation. Using novel, highly specific antibodies, we generated the first genome-wide view of the H1.4 isoform phosphorylated at serine 187 (pS187-H1.4) in estradiol-inducible MCF7 cells. We observe that pS187-H1.4 is enriched primarily at the transcription start sites (TSSs) of genes activated by estradiol treatment and depleted from those that are repressed. We also show that pS187-H1.4 associates with ‘early estrogen response’ genes and stably interacts with RNAPII. Based on the observations presented here, we propose that phosphorylation at S187 by CDK9 represents an early event required for gene activation. This event may also be involved in the release of promoter-proximal polymerases to begin elongation by interacting directly with the polymerase or other parts of the transcription machinery. Although we focused on estrogen-responsive genes, taking into account previous evidence of H1.4′s enrichment of promoters of pluripotency genes, and its involvement with rDNA activation, we propose that H1.4 phosphorylation for gene activation may be a more global observation.

Implication of a new function of human tDNAs in chromatin organization

Transfer RNA genes (tDNAs) are essential genes that encode tRNAs in all species. To understand new functions of tDNAs, other than that of encoding tRNAs, we used ENCODE data to examine binding characteristics of transcription factors (TFs) for all tDNA regions (489 loci) in the human genome. We divided the tDNAs into three groups based on the number of TFs that bound to them. At the two extremes were tDNAs to which many TFs bound (Group 1) and those to which no TFs bound (Group 3). Several TFs involved in chromatin remodeling such as ATF3, EP300 and TBL1XR1 bound to almost all Group 1 tDNAs. Furthermore, almost all Group 1 tDNAs included DNase I hypersensitivity sites and may thus interact with other chromatin regions through their bound TFs, and they showed highly conserved synteny across tetrapods. In contrast, Group 3 tDNAs did not possess these characteristics. These data suggest the presence of a previously uncharacterized function of these tDNAs. We also examined binding of CTCF to tDNAs and their involvement in topologically associating domains (TADs) and lamina-associated domains (LADs), which suggest a new perspective on the evolution and function of tDNAs.

Dynamic Chromatin Structure and Epigenetics Control the Fate of Malaria Parasites

Multiple hosts and various life cycle stages prompt the human malaria parasite, Plasmodium falciparum, to acquire sophisticated molecular mechanisms to ensure its survival, spread, and transmission to its next host. To face these environmental challenges, increasing evidence suggests that the parasite has developed complex and complementary layers of regulatory mechanisms controlling gene expression. Here, we discuss the recent developments in the discovery of molecular components that contribute to cell replication and differentiation and highlight the major contributions of epigenetics, transcription factors, and nuclear architecture in controlling gene regulation and life cycle progression in Plasmodium spp.

Hog1-induced transcription of RTC3 and HSP12 is robust and occurs in cells lacking Msn2, Msn4, Hot1 and Sko1

The yeast MAP kinase Hog1 pathway activates transcription of several hundreds genes. Large-scale gene expression and DNA binding assays suggest that most Hog1-induced genes are regulated by the transcriptional activators Msn2/4, Hot1 and Sko1. These studies also revealed the target genes of each activator and the putative binding sites on their promoters. In a previous study we identified a group of genes, which we considered the bona fide targets of Hog1, because they were induced in response to expression of intrinsically active mutant of Hog1, in the absence of any stress. We previously analyzed the promoter of the most highly induced gene, STL1, and noticed that some promoter properties were different from those proposed by large-scale data. We therefore continue to study promoters individually and present here analyses of promoters of more Hog1's targets, RTC3, HSP12, DAK1 and ALD3. We report that RTC3 and HSP12 promoters are robust and are induced, to different degrees, even in cells lacking all four activators. DAK1 and ALD3 promoters are not robust and fully depend on a single activator, DAK1 on Sko1 and ALD3 on Msn2/4. Most of these observations could not be inferred from the large-scale data. Msn2/4 are involved in regulating all four promoters. It was assumed, therefore, that the promoters are spontaneously active in ras2Δ cells, in which Msn2/4 are known to be de-repressed. Intriguingly, the promoters were not active in BY4741ras2Δ cells, but were de-repressed, as expected, in ras2Δ cells of other genetic backgrounds. This study describes two phenomena. One, some Hog1's target promoters are most robust, backupped by many activators. Second, in contrast to most laboratory strains, the widely used BY4741 strain does not induce Msn2/4 activity when the Ras/cAMP cascade is downregulated.

A single ChIP-seq dataset is sufficient for comprehensive analysis of motifs co-occurrence with MCOT package

Recognition of composite elements consisting of two transcription factor binding sites gets behind the studies of tissue-, stage- and condition-specific transcription. Genome-wide data on transcription factor binding generated with ChIP-seq method facilitate an identification of composite elements, but the existing bioinformatics tools either require ChIP-seq datasets for both partner transcription factors, or omit composite elements with motifs overlapping. Here we present an universal Motifs Co-Occurrence Tool (MCOT) that retrieves maximum information about overrepresented composite elements from a single ChIP-seq dataset. This includes homo- and heterotypic composite elements of four mutual orientations of motifs, separated with a spacer or overlapping, even if recognition of motifs within composite element requires various stringencies. Analysis of 52 ChIP-seq datasets for 18 human transcription factors confirmed that for over 60% of analyzed datasets and transcription factors predicted co-occurrence of motifs implied experimentally proven protein-protein interaction of respecting transcription factors. Analysis of 164 ChIP-seq datasets for 57 mammalian transcription factors showed that abundance of predicted composite elements with an overlap of motifs compared to those with a spacer more than doubled; and they had 1.5-fold increase of asymmetrical pairs of motifs with one more conservative 'leading' motif and another one 'guided'.

Genetic polymorphisms of interleukin-6 influence the development of hepatitis B virus-related liver cirrhosis in the Han Chinese population

BACKGROUND

Interleukin-6 (IL-6) plays an important role in chronic inflammation. Thus, we aimed to investigate the effects of IL-6 polymorphisms on predicting the progression of hepatitis B virus (HBV)-r elated liver cirrhosis.

METHODS

A cross-sectional study was conducted to analyse IL-6 polymorphisms and serum levels of IL-6 in HBV-infected patients at different clinical phases and in healthy controls. IL-6 polymorphisms were detected by the TaqMan PCR method, and plasma IL-6 levels were assessed by ELISA.

RESULTS

Our analysis included 182 chronic hepatitis B (CHB) patients, 190 HBV-infected liver cirrhosis cases, 125 inactive HBsAg carriers, and 246 healthy controls. Seven SNPs in IL-6 including rs10499563, rs17147230, rs1800796, rs2069837, rs1524107, rs2066992, and rs2069852 were analysed. In a haplotype analysis between HBV-infected liver cirrhosis cases and CHB patients, inactive HBV carriers or healthy controls, haplotype CT in block 1 and haplotype GGCGG in block 2 were associated with liver cirrhosis (P <0.05). Moreover, the genotype or allele frequencies were significantly different in IL-6 rs10499563 and rs2069837 when HBV-infected liver cirrhosis patients were compared with CHB patients, inactive HBV carriers or healthy controls. A further study found that compared with that in the healthy controls, inactive HBV carriers or CHB patients, plasma IL-6 was elevated in HBV-infected liver cirrhosis patients.

CONCLUSION

In conclusion, the IL-6 rs10499563 and rs2069837 polymorphisms are associated with incidence of liver cirrhosis may through their effects on IL-6 expression and these two single nucleotide polymorphisms can be used as potential prognostic markers of HBV-related liver cirrhosis.

Transient genome-wide interactions of the master transcription factor NLP7 initiate a rapid nitrogen-response cascade

Dynamic reprogramming of gene regulatory networks (GRNs) enables organisms to rapidly respond to environmental perturbation. However, the underlying transient interactions between transcription factors (TFs) and genome-wide targets typically elude biochemical detection. Here, we capture both stable and transient TF-target interactions genome-wide within minutes after controlled TF nuclear import using time-series chromatin immunoprecipitation (ChIP-seq) and/or DNA adenine methyltransferase identification (DamID-seq). The transient TF-target interactions captured uncover the early mode-of-action of NIN-LIKE PROTEIN 7 (NLP7), a master regulator of the nitrogen signaling pathway in plants. These transient NLP7 targets captured in root cells using temporal TF perturbation account for 50% of NLP7-regulated genes not detectably bound by NLP7 in planta. Rapid and transient NLP7 binding activates early nitrogen response TFs, which we validate to amplify the NLP7-initiated transcriptional cascade. Our approaches to capture transient TF-target interactions genome-wide can be applied to validate dynamic GRN models for any pathway or organism of interest.

Conventional methods cannot reveal transient transcription factors (TFs) and targets interactions. Here, Alvarez et al. capture both stable and transient TF-target interactions by time-series ChIP-seq and/or DamID-seq in a cell-based TF perturbation system and show NLP7 as a master TF to initiate a rapid nitrogen-response cascade.

Predicting gene expression in the human malaria parasite Plasmodium falciparum using histone modification, nucleosome positioning, and 3D localization features

Empirical evidence suggests that the malaria parasite Plasmodium falciparum employs a broad range of mechanisms to regulate gene transcription throughout the organism's complex life cycle. To better understand this regulatory machinery, we assembled a rich collection of genomic and epigenomic data sets, including information about transcription factor (TF) binding motifs, patterns of covalent histone modifications, nucleosome occupancy, GC content, and global 3D genome architecture. We used these data to train machine learning models to discriminate between high-expression and low-expression genes, focusing on three distinct stages of the red blood cell phase of the Plasmodium life cycle. Our results highlight the importance of histone modifications and 3D chromatin architecture in Plasmodium transcriptional regulation and suggest that AP2 transcription factors may play a limited regulatory role, perhaps operating in conjunction with epigenetic factors.

Transcriptional regulatory module analysis reveals that bridge proteins reconcile multiple signals in extracellular electron transfer pathways

Shewanella oneidensis MR-1 shows remarkable respiratory versatility with a large variety of extracellular electron acceptors (termed extracellular electron transfer, EET). To utilize the various electron acceptors, the bacterium must employ complex regulatory mechanisms to elicit the relevant EET pathways. To investigate the relevant mechanisms, we integrated EET genes and related transcriptional factors (TFs) into transcriptional regulatory modules (TRMs) and showed that many bridge proteins in these modules were signal proteins, which generally contained one or more signal processing domains (eg, GGDEF, EAL, PAS, etc.). Since Shewanella has to respond to diverse environmental conditions despite encoding few EET-relevant TFs, the overabundant signal proteins involved in the TRMs can help decipher the mechanism by which these microbes elicit a wide range of condition-specific responses. By combining proteomic data and protein bioinformatic analysis, we demonstrated that diverse signal proteins reconciled the different EET pathways, and we discussed the functional roles of signal proteins involved in the well-known MtrCAB pathway. Additionally, we showed that the signal proteins SO_2145 and SO_1417 played central roles in triggering EET pathways in anaerobic environments. Taken together, our results suggest that signal proteins have a profound impact on the transcriptional regulation of EET genes and thus have potential applications in microbial fuel cells.

Homodimerization regulates an endothelial specific signature of the SOX18 transcription factor

During embryogenesis, vascular development relies on a handful of transcription factors that instruct cell fate in a distinct sub-population of the endothelium (1). The SOXF proteins that comprise SOX7, 17 and 18, are molecular switches modulating arterio-venous and lymphatic endothelial differentiation (2,3). Here, we show that, in the SOX-F family, only SOX18 has the ability to switch between a monomeric and a dimeric form. We characterized the SOX18 dimer in binding assays in vitro, and using a split-GFP reporter assay in a zebrafish model system in vivo. We show that SOX18 dimerization is driven by a novel motif located in the vicinity of the C-terminus of the DNA binding region. Insertion of this motif in a SOX7 monomer forced its assembly into a dimer. Genome-wide analysis of SOX18 binding locations on the chromatin revealed enrichment for a SOX dimer binding motif, correlating with genes with a strong endothelial signature. Using a SOX18 small molecule inhibitor that disrupts dimerization, we revealed that dimerization is important for transcription. Overall, we show that dimerization is a specific feature of SOX18 that enables the recruitment of key endothelial transcription factors, and refines the selectivity of the binding to discrete genomic locations assigned to endothelial specific genes.

A Comparative Study of Network Motifs in the Integrated Transcriptional Regulation and Protein Interaction Networks of Shewanella

The Shewanella species shows a remarkable respiratory versatility with a great variety of extracellular electron acceptors (termed Extracellular Electron Transfer, EET). To explore relevant mechanisms from the network motif view, we constructed the integrated networks that combined transcriptional regulation interactions (TRIs) and protein-protein interactions (PPIs) for 13 Shewanella species, identified and compared the network motifs in these integrated networks. We found that the network motifs were evolutionary conserved in these integrated networks. The functional significance of the highly conserved motifs was discussed, especially the important ones that were potentially involved in the Shewanella EET processes. More importantly, we found that: 1) the motif co-regulated PPI took a role in the "standby mode" of protein utilization, which will be helpful for cells to rapidly response to environmental changes; and 2) the type II cofactors, which involved in the motif TRI interacting with a third protein, mainly carried out a signalling role in Shewanella oneidensis MR-1.

Evolution and Expression Divergence of the CYP78A Subfamily Genes in Soybean

Gene expression divergence is an important evolutionary driving force for the retention of duplicate genes. In this study, we identified three CYP78A subfamily genes in soybean, GmCYP78A70, GmCYP78A57 and GmCYP78A72, which experienced different duplication events. GmCYP78A70 was mainly expressed in leaf tissue and the vegetative phase, whereas GmCYP78A57 was mainly expressed in floral tissue and seed, i.e., the reproductive phase. Expression of GmCYP78A72 could be detected in all the tissues and phases mentioned above. The expression levels of GmCYP78A70 and GmCYP78A57 in different soybean cultivars showed positive correlations with leaf size and 100-seed weight, respectively. The population genetics analysis indicated that the three genes had experienced different selective pressures during domestication and improved breeding of soybean. Deciphering the function of this subfamily of genes may well prove useful to breeders for improving soybean’s agronomic traits.

A Trihelix Family Transcription Factor Is Associated with Key Genes in Mixed-Linkage Glucan Accumulation

Mixed-linkage glucan (MLG) is a polysaccharide that is highly abundant in grass endosperm cell walls and present at lower amounts in other tissues. Cellulose synthase-like F (CSLF) and cellulose synthase-like H genes synthesize MLG, but it is unknown if other genes participate in the production and restructuring of MLG. Using Brachypodium distachyon transcriptional profiling data, we identified a B distachyon trihelix family transcription factor (BdTHX1) that is highly coexpressed with the B distachyon CSLF6 gene (BdCSLF6), which suggests that BdTHX1 is involved in the regulation of MLG biosynthesis. To determine the genes regulated by this transcription factor, we conducted chromatin immunoprecipitation sequencing (ChIP-seq) experiments using immature B distachyon seeds and an anti-BdTHX1 polyclonal antibody. The ChIP-seq experiment identified the second intron of BdCSLF6 as one of the most enriched sequences. The binding of BdTHX1 to the BdCSLF6 intron sequence was confirmed using electrophoretic mobility shift assays (EMSA). ChIP-seq also showed that a gene encoding a grass-specific glycoside hydrolase family 16 endotransglucosylase/hydrolase (BdXTH8) is bound by BdTHX1, and the binding was confirmed by EMSA. Radiochemical transglucanase assays showed that BdXTH8 exhibits predominantly MLG:xyloglucan endotransglucosylase activity, a hetero-transglycosylation reaction, and can thus produce MLG-xyloglucan covalent bonds; it also has a lower xyloglucan:xyloglucan endotransglucosylase activity. B distachyon shoots regenerated from transformed calli overexpressing BdTHX1 showed an abnormal arrangement of vascular tissue and seedling-lethal phenotypes. These results indicate that the transcription factor BdTHX1 likely plays an important role in MLG biosynthesis and restructuring by regulating the expression of BdCSLF6 and BdXTH8.

Waves of chromatin modifications in mouse dendritic cells in response to LPS stimulation

BACKGROUND

The importance of transcription factors (TFs) and epigenetic modifications in the control of gene expression is widely accepted. However, causal relationships between changes in TF binding, histone modifications, and gene expression during the response to extracellular stimuli are not well understood. Here, we analyze the ordering of these events on a genome-wide scale in dendritic cells in response to lipopolysaccharide (LPS) stimulation.

RESULTS

Using a ChIP-seq time series dataset, we find that the LPS-induced accumulation of different histone modifications follows clearly distinct patterns. Increases in H3K4me3 appear to coincide with transcriptional activation. In contrast, H3K9K14ac accumulates early after stimulation, and H3K36me3 at later time points. Integrative analysis with TF binding data reveals potential links between TF activation and dynamics in histone modifications. Especially, LPS-induced increases in H3K9K14ac and H3K4me3 are associated with binding by STAT1/2 and were severely impaired in Stat1-/- cells.

CONCLUSIONS

While the timing of short-term changes of some histone modifications coincides with changes in transcriptional activity, this is not the case for others. In the latter case, dynamics in modifications more likely reflect strict regulation by stimulus-induced TFs and their interactions with chromatin modifiers.

Poly(ADP-ribosyl)ation associated changes in CTCF-chromatin binding and gene expression in breast cells

CTCF is an evolutionarily conserved and ubiquitously expressed architectural protein regulating a plethora of cellular functions via different molecular mechanisms. CTCF can undergo a number of post-translational modifications which change its properties and functions. One such modifications linked to cancer is poly(ADP-ribosyl)ation (PARylation). The highly PARylated CTCF form has an apparent molecular mass of 180 kDa (referred to as CTCF180), which can be distinguished from hypo- and non-PARylated CTCF with the apparent molecular mass of 130 kDa (referred to as CTCF130). The existing data accumulated so far have been mainly related to CTCF130. However, the properties of CTCF180 are not well understood despite its abundance in a number of primary tissues. In this study we performed ChIP-seq and RNA-seq analyses in human breast cells 226LDM, which display predominantly CTCF130 when proliferating, but CTCF180 upon cell cycle arrest. We observed that in the arrested cells the majority of sites lost CTCF, whereas fewer sites gained CTCF or remain bound (i.e. common sites). The classical CTCF binding motif was found in the lost and common, but not in the gained sites. The changes in CTCF occupancies in the lost and common sites were associated with increased chromatin densities and altered expression from the neighboring genes. Based on these results we propose a model integrating the CTCF130/180 transition with CTCF-DNA binding and gene expression changes. This study also issues an important cautionary note concerning the design and interpretation of any experiments using cells and tissues where CTCF180 may be present.

Beyond MITF: Multiple transcription factors directly regulate the cellular phenotype in melanocytes and melanoma

MITF governs multiple steps in the development of melanocytes, including specification from neural crest, growth, survival, and terminal differentiation. In addition, the level of MITF activity determines the phenotype adopted by melanoma cells, whether invasive, proliferative, or differentiated. However, MITF does not act alone. Here, we review literature on the transcription factors that co-regulate MITF-dependent genes. ChIP-seq studies have indicated that the transcription factors SOX10, YY1, and TFAP2A co-occupy subsets of regulatory elements bound by MITF in melanocytes. Analyses at single loci also support roles for LEF1, RB1, IRF4, and PAX3 acting in combination with MITF, while sequence motif analyses suggest that additional transcription factors colocalize with MITF at many melanocyte-specific regulatory elements. However, the precise biochemical functions of each of these MITF collaborators and their contributions to gene expression remain to be elucidated. Analogous to the transcriptional networks in morphogen-patterned tissues during embryogenesis, we anticipate that the level of MITF activity is controlled not only by the concentration of activated MITF, but also by additional transcription factors that either quantitatively or qualitatively influence the expression of MITF-target genes.

A B-ARR-mediated cytokinin transcriptional network directs hormone cross-regulation and shoot development

Cytokinin fulfills its diverse roles in planta through a series of transcriptional responses. We identify the in vivo DNA binding site profiles for three genetically redundant type-B ARABIDOPSIS RESPONSE REGULATORS (B-ARRs): ARR1, ARR10, and ARR12. The expression and genome-wide DNA binding locations of the three B-ARRs extensively overlap. Constructing a primary cytokinin response transcriptional network reveals a recurring theme of widespread cross-regulation between the components of the cytokinin pathway and other plant hormone pathways. The B-ARRs are found to have similar DNA binding motifs, though sequences flanking the core motif were degenerate. Cytokinin treatments amalgamate the three different B-ARRs motifs to identical DNA binding signatures (AGATHY, H(a/t/c), Y(t/c)) which suggests cytokinin may regulate binding activity of B-ARR family members. Furthermore, we find that WUSCHEL, a key gene required for apical meristem maintenance, is a cytokinin-dependent B-ARR target gene, demonstrating the importance of the cytokinin transcription factor network in shoot development.

Genexpi: a toolset for identifying regulons and validating gene regulatory networks using time-course expression data

BACKGROUND

Identifying regulons of sigma factors is a vital subtask of gene network inference. Integrating multiple sources of data is essential for correct identification of regulons and complete gene regulatory networks. Time series of expression data measured with microarrays or RNA-seq combined with static binding experiments (e.g., ChIP-seq) or literature mining may be used for inference of sigma factor regulatory networks.

RESULTS

We introduce Genexpi: a tool to identify sigma factors by combining candidates obtained from ChIP experiments or literature mining with time-course gene expression data. While Genexpi can be used to infer other types of regulatory interactions, it was designed and validated on real biological data from bacterial regulons. In this paper, we put primary focus on CyGenexpi: a plugin integrating Genexpi with the Cytoscape software for ease of use. As a part of this effort, a plugin for handling time series data in Cytoscape called CyDataseries has been developed and made available. Genexpi is also available as a standalone command line tool and an R package.

CONCLUSIONS

Genexpi is a useful part of gene network inference toolbox. It provides meaningful information about the composition of regulons and delivers biologically interpretable results.

Transcription factor-dependent 'anti-repressive' mammalian enhancers exclude H3K27me3 from extended genomic domains

Compacted chromatin and nucleosomes are known barriers to gene expression; the nature and relative importance of other transcriptional constraints remain unclear, especially at distant enhancers. Polycomb repressor complex 2 (PRC2) places the histone mark H3K27me3 predominantly at promoters, where its silencing activity is well documented. In adult tissues, enhancers lack H3K27me3, and it is unknown whether intergenic H3K27me3 deposits affect nearby genes. In primary intestinal villus cells, we identified hundreds of tissue-restricted enhancers that require the transcription factor (TF) CDX2 to prevent the incursion of H3K27me3 from adjoining areas of elevated basal marking into large well-demarcated genome domains. Similarly, GATA1-dependent enhancers exclude H3K27me3 from extended regions in erythroid blood cells. Excess intergenic H3K27me3 in both TF-deficient tissues is associated with extreme mRNA deficits, which are significantly rescued in intestinal cells lacking PRC2. Explaining these observations, enhancers show TF-dependent binding of the H3K27 demethylase KDM6A. Thus, in diverse cell types, certain genome regions far from promoters accumulate H3K27me3, and optimal gene expression depends on enhancers clearing this repressive mark. These findings reveal new "anti-repressive" function for hundreds of tissue-specific enhancers.

Regulation of circadian clock transcriptional output by CLOCK:BMAL1

The mammalian circadian clock relies on the transcription factor CLOCK:BMAL1 to coordinate the rhythmic expression of 15% of the transcriptome and control the daily regulation of biological functions. The recent characterization of CLOCK:BMAL1 cistrome revealed that although CLOCK:BMAL1 binds synchronously to all of its target genes, its transcriptional output is highly heterogeneous. By performing a meta-analysis of several independent genome-wide datasets, we found that the binding of other transcription factors at CLOCK:BMAL1 enhancers likely contribute to the heterogeneity of CLOCK:BMAL1 transcriptional output. While CLOCK:BMAL1 rhythmic DNA binding promotes rhythmic nucleosome removal, it is not sufficient to generate transcriptionally active enhancers as assessed by H3K27ac signal, RNA Polymerase II recruitment, and eRNA expression. Instead, the transcriptional activity of CLOCK:BMAL1 enhancers appears to rely on the activity of ubiquitously expressed transcription factors, and not tissue-specific transcription factors, recruited at nearby binding sites. The contribution of other transcription factors is exemplified by how fasting, which effects several transcription factors but not CLOCK:BMAL1, either decreases or increases the amplitude of many rhythmically expressed CLOCK:BMAL1 target genes. Together, our analysis suggests that CLOCK:BMAL1 promotes a transcriptionally permissive chromatin landscape that primes its target genes for transcription activation rather than directly activating transcription, and provides a new framework to explain how environmental or pathological conditions can reprogram the rhythmic expression of clock-controlled genes.

MuSERA: Multiple Sample Enriched Region Assessment

Enriched region (ER) identification is a fundamental step in several next-generation sequencing (NGS) experiment types. Yet, although NGS experimental protocols recommend producing replicate samples for each evaluated condition and their consistency is usually assessed, typically pipelines for ER identification do not consider available NGS replicates. This may alter genome-wide descriptions of ERs, hinder significance of subsequent analyses on detected ERs and eventually preclude biological discoveries that evidence in replicate could support. MuSERA is a broadly useful stand-alone tool for both interactive and batch analysis of combined evidence from ERs in multiple ChIP-seq or DNase-seq replicates. Besides rigorously combining sample replicates to increase statistical significance of detected ERs, it also provides quantitative evaluations and graphical features to assess the biological relevance of each determined ER set within its genomic context; they include genomic annotation of determined ERs, nearest ER distance distribution, global correlation assessment of ERs and an integrated genome browser. We review MuSERA rationale and implementation, and illustrate how sets of significant ERs are expanded by applying MuSERA on replicates for several types of NGS data, including ChIP-seq of transcription factors or histone marks and DNase-seq hypersensitive sites. We show that MuSERA can determine a new, enhanced set of ERs for each sample by locally combining evidence on replicates, and prove how the easy-to-use interactive graphical displays and quantitative evaluations that MuSERA provides effectively support thorough inspection of obtained results and evaluation of their biological content, facilitating their understanding and biological interpretations. MuSERA is freely available at http://www.bioinformatics.deib.polimi.it/MuSERA/.

Zebrafish Transcription Factor ORFeome for Gene Discovery and Regulatory Network Elucidation

The completion of the zebrafish genome sequence and advances in miniaturization and multiplexing were essential to the creation of techniques such as RNA-seq, ChIP-seq, and high-throughput behavioral and chemical screens. Multiplexing was also instrumental in the recent enhancement of the classic yeast one-hybrid interaction techniques to provide unprecedented discovery capabilities for protein-DNA interactions. Unfortunately its use for zebrafish research is currently hampered by the lack of an open reading frame (ORF) clone collection. As a first step toward a complete collection, we describe a small library of transcriptional regulatory proteins comprising 142 ORFs and its potential applications.