ChIP-seq Experiments Research Articles

Ethylene inhibits photosynthesis via temporally distinct responses in tomato plants.

Ethylene is a volatile plant hormone that regulates many developmental processes and responses toward (a)biotic stress. Studies have shown that high levels of ethylene repress vegetative growth in many important crops, including tomato (Solanum lycopersicum), possibly by inhibiting photosynthesis. We investigated the temporal effects of ethylene on young tomato plants using an automated ethylene gassing system to monitor the physiological, biochemical, and molecular responses through time course RNA-seq of a photosynthetically active source leaf. We found that ethylene evokes a dose-dependent inhibition of photosynthesis, which can be characterized by 3 temporally distinct phases. The earliest ethylene responses that marked the first phase and occurred a few hours after the start of the treatment were leaf epinasty and a decline in stomatal conductance, which led to lower light perception and CO2 uptake, respectively, resulting in a rapid decline of soluble sugar levels (glucose, fructose). The second phase of the ethylene effect was marked by low carbohydrate availability, which modulated plant energy metabolism to adapt by using alternative substrates (lipids and proteins) to fuel the TCA cycle. Long-term continuous exposure to ethylene led to the third phase, characterized by starch and chlorophyll breakdown, which further inhibited photosynthesis, leading to premature leaf senescence. To reveal early (3 h) ethylene-dependent regulators of photosynthesis, we performed a ChIP-seq experiment using anti-ETHYLENE INSENSITIVE 3-like 1 (EIL1) antibodies and found several candidate transcriptional regulators. Collectively, our study revealed a temporal sequence of events that led to the inhibition of photosynthesis by ethylene and identified potential transcriptional regulators responsible for this regulation.

PAPerFly: Partial Assembly-based Peak Finder for ab initio binding site reconstruction

BackgroundThe specific recognition of a DNA locus by a given transcription factor is a widely studied issue. It is generally agreed that the recognition can be influenced not only by the binding motif but by the larger context of the binding site. In this work, we present a novel heuristic algorithm that can reconstruct the unique binding sites captured in a sequencing experiment without using the reference genome.ResultsWe present PAPerFly, the Partial Assembly-based Peak Finder, a tool for the binding site and binding context reconstruction from the sequencing data without any prior knowledge. This tool operates without the need to know the reference genome of the respective organism. We employ algorithmic approaches that are used during genome assembly. The proposed algorithm constructs a de Bruijn graph from the sequencing data. Based on this graph, sequences and their enrichment are reconstructed using a novel heuristic algorithm. The reconstructed sequences are aligned and the peaks in the sequence enrichment are identified. Our approach was tested by processing several ChIP-seq experiments available in the ENCODE database and comparing the results of Paperfly and standard methods.ConclusionsWe show that PAPerFly, an algorithm tailored for experiment analysis without the reference genome, yields better results than an aggregation of ChIP-seq agnostic tools. Our tool is freely available at https://github.com/Caeph/paperfly/ or on Zenodo (https://doi.org/10.5281/zenodo.7116424).

Chronic social stress alters dexamethasone sensitivity of glucocorticoid receptor target genes

Glucocorticoids are well-known for their role in adapting to physical and psycho-emotional stress. The prefrontal cortex (PFC) is a crucial target-tissue for glucocorticoid receptors (GR) that coordinates the stress response. Transcriptome sequencing was conducted on the prefrontal cortex of male C57Bl/6 mice subjected to 30 days of chronic social defeat stress (CSDS). Prior to tissue extraction, the mice were injected with either 2 µg/g dexamethasone or saline, resulting in four groups: CSDS+sal, CSDS+dex, control+sal, and control+dex. The study sought to identify genes regulated by GR within the differentially expressed genes (DEG) by analyzing five public GR ChIPseq experiments performed on rodent brain tissue. This endeavor aimed to elucidate the role of GR in the PFC stress response. GR binding sites that were situated –5k to +1k bp from tss were categorized as regulatory regions. The closest genes were then identified. For further analysis, 3023 genes recognized as GR-regulated by at least two studies were selected. Of these, 320 genes were demonstrated to be expressed in the PFC based on our RNAseq data. We found a significant increase in GR sites among PFC DEGs that responded to DEX treatment in both the control group (control+sal vs control+dex: OR=2.17, p 0.001) and CSDS (CSDS+sal vs CSDS+dex: OR=1.86, p 0.001). However, chronic stress alone did not result in enrichment of genes regulated by GR. Notably, genes that responded differently to DEX treatment in CSDS and control showed a higher OR value (dex*CSDS: OR=2.32, p 0.01). Common GR-target genes between DEX-con and DEX-csds exhibited the same expression change direction, except for the Sft2d2 gene, which encodes a vesicle transport protein. These genes are involved in PDZ domain binding (Fzd2, Mpp3), serine/threonine kinase activity (Rps6ka5, Akt2, Camkk1), and oxidoreductase activity (Prodh, Smox). GR-regulated genes specific to the CSDS group participate in cytokine production (e.g., Ltbp1, P2rx7, Dhx33, Hdac9, Bcl6, Lgr4, etc.) and modulate chemical synaptic transmission (e.g., Arc, Syt12, Cacng3, etc.), including components of the glutamatergic synapse (e.g., Magi2, Erc2, Dnm1, Clstn2, and Itgb1). Changes in expression of structural component genes, including those involved in membrane raft (Cavin1, Smpd2, and Slc2a1) and anchoring junction (B4galt1, Gjb6, Fzd4, and Limk1) genes, indicate the control group’s response to DEX treatment. A total of 14 genes showed differential regulation by GR in both CSDS and control groups. Among these genes are those involved in axon elongation (Link1, Rasgrf1), synaptic morphology (Clstn2), and vesicle endocytosis (Dnm1). Additionally, vital genes for axonal regeneration (Tubb3), neuroprotection (Hspb8), regulation of apoptosis (Bugalt1), and microglia activation (Cavin1) are included. In conclusion, we aimed to decipher the pathways of GR regulation triggered by social stress and DEX treatment in the PFC. Chronic stress resulted in alterations in GR regulatory networks in the PFC that impacted processes related to synapse function and the inflammatory response.

SIRT6 promotes metastasis and relapse in HER2-positive breast cancer

The histone deacetylase sirtuin 6 (SIRT6) has been endowed with anti-cancer capabilities in many tumor types. Here, we investigate the impact of SIRT6-overexpression (SIRT6-OE) in Delta16HER2 mice, which are a bona fide model of HER2-positive breast cancer. After an initial delay in the tumor onset, SIRT6-OE induces a more aggressive phenotype of Delta16HER2 tumors promoting the formation of higher number of tumor foci and metastases than controls. This phenotype of SIRT6-OE tumors is associated with cancer stem cell (CSC)-like features and tumor dormancy, and low senescence and oxidative DNA damage. Accordingly, a sub-set of HER2-positive breast cancer patients with concurrent SIRT6-OE has a significant poorer relapse-free survival (RFS) probability than patients with low expression of SIRT6. ChIP-seq, RNA-seq and RT-PCR experiments indicate that SIRT6-OE represses the expression of the T-box transcription factor 3 (Tbx3) by deacetylation of H3K9ac. Accordingly, loss-of-function mutations of TBX3 or low TBX3 expression levels are predictive of poor prognosis in HER2-positive breast cancer patients. Our work indicates that high levels of SIRT6 are indicative of poor prognosis and high risk of metastasis in HER2-positive breast cancer and suggests further investigation of TBX3 as a downstream target of SIRT6 and co-marker of poor-prognosis. Our results point to a breast cancer subtype-specific effect of SIRT6 and warrant future studies dissecting the mechanisms of SIRT6 regulation in different breast cancer subtypes.

Macromolecular Complex Including MLL3, Carabin and Calcineurin Regulates Cardiac Remodeling.

Cardiac hypertrophy is an intermediate stage in the development of heart failure. The structural and functional processes occurring in cardiac hypertrophy include extensive gene reprogramming, which is dependent on epigenetic regulation and chromatin remodeling. However, the chromatin remodelers and their regulatory functions involved in the pathogenesis of cardiac hypertrophy are not well characterized. Protein interaction was determined by immunoprecipitation assay in primary cardiomyocytes and mouse cardiac samples subjected or not to transverse aortic constriction for 1 week. Chromatin immunoprecipitation and DNA sequencing (ChIP-seq) experiments were performed on the chromatin of adult mouse cardiomyocytes. We report that the calcium-activated protein phosphatase CaN (calcineurin), its endogenous inhibitory protein carabin, the STK24 (STE20-like protein kinase 3), and the histone monomethyltransferase, MLL3 (mixed lineage leukemia 3) form altogether a macromolecular complex at the chromatin of cardiomyocytes. Under basal conditions, carabin prevents CaN activation while the serine/threonine kinase STK24 maintains MLL3 inactive via phosphorylation. After 1 week of transverse aortic constriction, both carabin and STK24 are released from the CaN-MLL3 complex leading to the activation of CaN, dephosphorylation of MLL3, and in turn, histone H3 lysine 4 monomethylation. Selective cardiac MLL3 knockdown mitigates hypertrophy, and chromatin immunoprecipitation and DNA sequencing analysis demonstrates that MLL3 is de novo recruited at the transcriptional start site of genes implicated in cardiomyopathy in stress conditions. We also show that CaN and MLL3 colocalize at chromatin and that CaN activates MLL3 histone methyl transferase activity at distal intergenic regions under hypertrophic conditions. Our study reveals an unsuspected epigenetic mechanism of CaN that directly regulates MLL3 histone methyl transferase activity to promote cardiac remodeling.

Discovery of a non-canonical GRHL1 binding site using deep convolutional and recurrent neural networks

BackgroundTranscription factors regulate gene expression by binding to transcription factor binding sites (TFBSs). Most models for predicting TFBSs are based on position weight matrices (PWMs), which require a specific motif to be present in the DNA sequence and do not consider interdependencies of nucleotides. Novel approaches such as Transcription Factor Flexible Models or recurrent neural networks consequently provide higher accuracies. However, it is unclear whether such approaches can uncover novel non-canonical, hitherto unexpected TFBSs relevant to human transcriptional regulation.ResultsIn this study, we trained a convolutional recurrent neural network with HT-SELEX data for GRHL1 binding and applied it to a set of GRHL1 binding sites obtained from ChIP-Seq experiments from human cells. We identified 46 non-canonical GRHL1 binding sites, which were not found by a conventional PWM approach. Unexpectedly, some of the newly predicted binding sequences lacked the CNNG core motif, so far considered obligatory for GRHL1 binding. Using isothermal titration calorimetry, we experimentally confirmed binding between the GRHL1-DNA binding domain and predicted GRHL1 binding sites, including a non-canonical GRHL1 binding site. Mutagenesis of individual nucleotides revealed a correlation between predicted binding strength and experimentally validated binding affinity across representative sequences. This correlation was neither observed with a PWM-based nor another deep learning approach.ConclusionsOur results show that convolutional recurrent neural networks may uncover unanticipated binding sites and facilitate quantitative transcription factor binding predictions.

HOCOMOCO in 2024: a rebuild of the curated collection of binding models for human and mouse transcription factors.

We present a major update of the HOCOMOCO collection that provides DNA binding specificity patterns of 949 human transcription factors and 720 mouse orthologs. To make this release, we performed motif discovery in peak sets that originated from 14 183 ChIP-Seq experiments and reads from 2554 HT-SELEX experiments yielding more than 400 thousand candidate motifs. The candidate motifs were annotated according to their similarity to known motifs and the hierarchy of DNA-binding domains of the respective transcription factors. Next, the motifs underwent human expert curation to stratify distinct motif subtypes and remove non-informative patterns and common artifacts. Finally, the curated subset of 100 thousand motifs was supplied to the automated benchmarking to select the best-performing motifs for each transcription factor. The resulting HOCOMOCO v12 core collection contains 1443 verified position weight matrices, including distinct subtypes of DNA binding motifs for particular transcription factors. In addition to the core collection, HOCOMOCO v12 provides motif sets optimized for the recognition of binding sites in vivo and in vitro, and for annotation of regulatory sequence variants. HOCOMOCO is available at https://hocomoco12.autosome.org and https://hocomoco.autosome.org.

CTCF modulates adipocyte lipolysis via directly regulating the expression of Beclin 1 with the cooperation of PPARγ

Dysregulated lipolysis is a risk factor contributing to metabolic diseases and autophagy is known to be important in lipolysis. CTCF is involved in diverse cellular processes including adipogenesis, yet its role in lipolysis or autophagy remains unknown. We identified lipolytic genes were downregulated in CTCF knockdown adipocytes based on the RNA-seq data. Further validation showed that CTCF knockdown restrained adipocyte lipolysis while overexpression of CTCF had opposite effects. Similarly, overexpression and knockdown studies demonstrated that CTCF was a positive regulator of autophagy. Treatment with autophagy inducer relieved the suppression of lipolysis caused by CTCF knockdown, while autophagy inhibitor treatment alleviated lipolysis stimulated by CTCF overexpression, indicating that CTCF regulates adipocyte lipolysis through autophagy. Mechanistically, CTCF interacted with PPARγ to coordinately enhanced lipolytic capacity. Data of chip-seq, chip-qPCR and further experiments confirmed that CTCF and PPARγ separately stimulated transactivation of autophagy regulatory protein Beclin 1, while co-expression of the two displayed synergistic effects to regulate autophagy flux. Expectedly, overexpression of Beclin 1 abolished the blockage of lipolysis and autophagy caused by CTCF knockdown. Collectively, CTCF cooperates with PPARγ to regulate autophagy via directly modulating BECLIN 1 transcription, thereby leading to increased adipocyte lipolysis.

Software pipelines for RNA-Seq, ChIP-Seq and germline variant calling analyses in common workflow language (CWL).

Background: Automating data analysis pipelines is a key requirement to ensure reproducibility of results, especially when dealing with large volumes of data. Here we assembled automated pipelines for the analysis of High-throughput Sequencing (HTS) data originating from RNA-Seq, ChIP-Seq and Germline variant calling experiments. We implemented these workflows in Common workflow language (CWL) and evaluated their performance by: i) reproducing the results of two previously published studies on Chronic Lymphocytic Leukemia (CLL), and ii) analyzing whole genome sequencing data from four Genome in a Bottle Consortium (GIAB) samples, comparing the detected variants against their respective golden standard truth sets. Findings: We demonstrated that CWL-implemented workflows clearly achieved high accuracy in reproducing previously published results, discovering significant biomarkers and detecting germline SNP and small INDEL variants. Conclusion: CWL pipelines are characterized by reproducibility and reusability; combined with containerization, they provide the ability to overcome issues of software incompatibility and laborious configuration requirements. In addition, they are flexible and can be used immediately or adapted to the specific needs of an experiment or study. The CWL-based workflows developed in this study, along with version information for all software tools, are publicly available on GitHub (https://github.com/BiodataAnalysisGroup/CWL_HTS_pipelines) under the MIT License. They are suitable for the analysis of short-read (such as Illumina-based) data and constitute an open resource that can facilitate automation, reproducibility and cross-platform compatibility for standard bioinformatic analyses.

The novel CDK9 inhibitor, XPW1, alone and in combination with BRD4 inhibitor JQ1, for the treatment of clear cell renal cell carcinoma.

Clear cell renal cell carcinoma (ccRCC) is a highly lethal malignancy with few therapeutic options. Cyclin‑dependent kinase 9 (CDK9), a potential therapeutic target of many cancers, has been recently observed to be upregulated in ccRCC patients. Therefore, we aimed to investigate the therapeutic potential of CDK9 in ccRCC and develop a novel CDK9 inhibitor with low toxicity for ccRCC treatment. The expression of CDK9 in ccRCC was checked using the online database and tissue microarray analysis. shRNA-mediated CDK9 knockdown and CDK inhibitor were applied to evaluate the effect of CDK9 on ccRCC. Medicinal chemistry methods were used to develop a new CDK9 inhibitor with drugability. RNA-seq and ChIP-seq experiments were conducted to explore the mechanism of action. MTS, western blotting, and colony formation assays were performed to evaluate the anti-ccRCC effects of CDK9 knockdown and inhibition in vitro. The in vivo anti-tumour efficacy was evaluated in a xenograft model. CDK9 is overexpressed and associated with poor survival in ccRCC. Knockdown or inhibition of CDK9 significantly suppressed ccRCC cells. XPW1 was identified as a new potent and selective CDK9 inhibitor with excellent anti-ccRCC activity and low toxicity. In mechanism, XPW1 transcriptionally inhibited DNA repair programmes in ccRCC cells, resulting in an excellent anti-tumour effect. CDK9 and BRD4 were two highly correlated transcriptional regulators in ccRCC patients, and the BRD4 inhibitor JQ1 enhanced XPW1's anti-ccRCC effects in vitro and in vivo. This work provides valuable insights into the therapeutic potential of CDK9 in ccRCC. The CDK9 inhibitor XPW1 would be a novel therapeutic agent for targeting ccRCC, alone or in rational combinations.

NRF2 interacts with distal enhancer and inhibits nitric oxide synthase 2 expression in KRAS-driven pancreatic cancer cells

Nitric oxide is a pleiotropic free radical produced by three nitric oxide synthases (NOS1–3), of which inducible NOS2 is involved in tumor initiation and progression. In this study, RNA-seq, ChIP-seq and qRT-PCR experiments combined with bioinformatic analyses showed that NRF2 is a repressor of NOS2 gene by maintaining a distal enhancer located 22 kb downstream of TSS in an inactive state. Deletion of NRF2 leads to activation of the enhancer, which exerts a pioneering function before it is fully activated. Specifically, NRF2 controls the expression of NOS2 in response to intracellular oxidative stress and extracellular oxygen pressure. We found that abrogation of NOS2 expression by siRNAs partially reduced the ability of WT Panc-1 cells to form 3D spheroids, but strongly reduced the formation of 3D spheroids by NRF2-depleted Panc-1 cells. Mechanistically, this effect correlates with the finding that NOS2 and nitric oxide stimulate epithelial-to-mesenchymal transition in NRF2-depleted Panc-1 and MIA PaCa-2 cells. We also found that knockdown of NOS2 leads to blockade of 3D matrigel invasion of NRF2-depleted PDAC cells, demonstrating that a short-circuit in the reciprocal regulation of NOS2 and NRF2 attenuates the malignancy of PDAC cells. In summary, we show for the first time that: (i) NRF2 is a suppressor of NOS2 in pancreatic cancer cells; (ii) NRF2 binds to and inactivates an enhancer located 22 kb downstream of TSS of the NOS2 gene; (iii) activation of NOS2 requires suppression of NRF2; (iv) NOS2 is required for NRF2-depleted Panc-1 cells to maintain their malignancy and invasiveness.

Characterizing intergenic transcription at RNA polymerase II binding sites in normal and cancer tissues

Intergenic transcription in normal and cancerous tissues is pervasive but incompletely understood. To investigate this, we constructed an atlas of over 180,000 consensus RNA polymerase II (RNAPII)-bound intergenic regions from 900 RNAPII chromatin immunoprecipitation sequencing (ChIP-seq) experiments in normal and cancer samples. Through unsupervised analysis, we identified 51 RNAPII consensus clusters, many of which mapped to specific biotypes and revealed tissue-specific regulatory signatures. We developed a meta-clustering methodology to integrate our RNAPII atlas with active transcription across 28,797 RNA sequencing (RNA-seq) samples from The Cancer Genome Atlas (TCGA), Genotype-Tissue Expression (GTEx), and Encyclopedia of DNA Elements (ENCODE). This analysis revealed strong tissue- and disease-specific interconnections between RNAPII occupancy and transcriptional activity. We demonstrate that intergenic transcription at RNAPII-bound regions is a novel per-cancer and pan-cancer biomarker. This biomarker displays genomic and clinically relevant characteristics, distinguishing cancer subtypes and linking to overall survival. Our results demonstrate the effectiveness of coherent data integration to uncover intergenic transcriptional activity in normal and cancer tissues.

Short Sequence Aligner Benchmarking for Chromatin Research.

Much of today's molecular science revolves around next-generation sequencing. Frequently, the first step in analyzing such data is aligning sequencing reads to a reference genome. This step is often taken for granted, but any analysis downstream of the alignment will be affected by the aligner's ability to correctly map sequences. In most cases, for research into chromatin structure and nucleosome positioning, ATAC-seq, ChIP-seq, and MNase-seq experiments use short read lengths. How well aligners manage these reads is critical. Most aligner programs will output mapped reads and unmapped reads. However, from a biological point of view, reads will fall into one of three categories: correctly mapped, incorrectly mapped, and unmapped. While increased sequencing depth can often compensate for unmapped reads, incorrectly and correctly mapped reads appear algorithmically identical but can produce biologically significant alterations in the results. For this reason, we are benchmarking various alignment programs to determine their propensity to incorrectly map short reads. As short-read alignment is an important step in ATAC-seq, ChIP-seq, and MNase-seq experiments, caution should be taken in mapping reads to ensure that the most accurate conclusions can be made from the data generated. Our analysis is intended to help investigators new to the field pick the alignment program best suited for their experimental conditions. In general, the aligners we tested performed well. BWA, Bowtie2, and Chromap were all exceptionally accurate, and we recommend using them. Furthermore, we show that longer read lengths do in fact lead to more accurate mappings.

Combinatorial targeting of a specific EMT/MET network by macroH2A variants safeguards mesenchymal identity.

Generation of induced pluripotent stem cells from specialized cell types provides an excellent model to study how cells maintain their stability, and how they can change identity, especially in the context of disease. Previous studies have shown that chromatin safeguards cell identity by acting as a barrier to reprogramming. We investigated mechanisms by which the histone macroH2A variants inhibit reprogramming and discovered that they work as gate keepers of the mesenchymal cell state by blocking epithelial transition, a step required for reprogramming of mouse fibroblasts. More specifically, we found that individual macroH2A variants regulate the expression of defined sets of genes, whose overall function is to stabilize the mesenchymal gene expression program, thus resisting reprogramming. We identified a novel gene network (MSCN, mesenchymal network) composed of 63 macroH2A-regulated genes related to extracellular matrix, cell membrane, signaling and the transcriptional regulators Id2 and Snai2, all of which function as guardians of the mesenchymal phenotype. ChIP-seq and KD experiments revealed a macroH2A variant-specific combinatorial targeting of the genes reconstructing the MSCN, thus generating robustness in gene expression programs to resist cellular reprogramming.

Rescuing biologically relevant consensus regions across replicated samples

BackgroundProtein-DNA binding sites of ChIP-seq experiments are identified where the binding affinity is significant based on a given threshold. The choice of the threshold is a trade-off between conservative region identification and discarding weak, but true binding sites.ResultsWe rescue weak binding sites using MSPC, which efficiently exploits replicates to lower the threshold required to identify a site while keeping a low false-positive rate, and we compare it to IDR, a widely used post-processing method for identifying highly reproducible peaks across replicates. We observe several master transcription regulators (e.g., SP1 and GATA3) and HDAC2-GATA1 regulatory networks on rescued regions in K562 cell line.ConclusionsWe argue the biological relevance of weak binding sites and the information they add when rescued by MSPC. An implementation of the proposed extended MSPC methodology and the scripts to reproduce the performed analysis are freely available at https://genometric.github.io/MSPC/; MSPC is distributed as a command-line application and an R package available from Bioconductor (https://doi.org/doi:10.18129/B9.bioc.rmspc).

C4S DB: Comprehensive Collection and Comparison for ChIP-Seq Database

Combining multiple binding profiles, such as transcription factors and histone modifications, is a crucial step in revealing the functions of complex biological systems. Although a massive amount of chromatin immunoprecipitation followed by sequencing (ChIP-seq) data is available, existing ChIP-seq databases or repositories focus on individual experiments, and it is difficult to elucidate orchestrated regulation by DNA-binding elements. We developed the Comprehensive Collection and Comparison for ChIP-Seq Database (C4S DB) to provide researchers with insights into the combination of DNA binding elements based on quality-assessed public ChIP-seq data. The C4S DB is based on >16,000 human ChIP-seq experiments and provides two main web interfaces to discover the relationships between ChIP-seq data. “Gene browser” illustrates the landscape of distributions of binding elements around a specified gene, and “global similarity,” a hierarchical clustering heatmap based on a similarity between two ChIP-seq experiments, gives an overview of genome-wide relations of regulatory elements. These functions promote the identification or evaluation of both gene-specific and genome-wide colocalization or mutually exclusive localization. Modern web technologies allow users to search for and aggregate large-scale experimental data through interactive web interfaces with quick responses. The C4S DB is available at https://c4s.site.

Phase Separation Modulates the Formation and Stabilities of DNA Guanine Quadruplex.

In the presence of monovalent alkali metal ions, G-rich DNA sequences containing four runs of contiguous guanines can fold into G-quadruplex (G4) structures. Recent studies showed that these structures are located in critical regions of the human genome and assume important functions in many essential DNA metabolic processes, including replication, transcription, and repair. However, not all potential G4-forming sequences are actually folded into G4 structures in cells, where G4 structures are known to be dynamic and modulated by G4-binding proteins as well as helicases. It remains unclear whether there are other factors influencing the formation and stability of G4 structures in cells. Herein, we showed that DNA G4s can undergo phase separation in vitro. In addition, immunofluorescence microscopy and ChIP-seq experiments with the use of BG4, a G4 structure-specific antibody, revealed that disruption of phase separation could result in global destabilization of G4 structures in cells. Together, our work revealed phase separation as a new determinant in modulating the formation and stability of G4 structures in human cells.

Semi-supervised learning improves regulatory sequence prediction with unlabeled sequences

MotivationGenome-wide association studies have systematically identified thousands of single nucleotide polymorphisms (SNPs) associated with complex genetic diseases. However, the majority of those SNPs were found in non-coding genomic regions, preventing the understanding of the underlying causal mechanism. Predicting molecular processes based on the DNA sequence represents a promising approach to understand the role of those non-coding SNPs. Over the past years, deep learning was successfully applied to regulatory sequence prediction using supervised learning. Supervised learning required DNA sequences associated with functional data for training, whose amount is strongly limited by the finite size of the human genome. Conversely, the amount of mammalian DNA sequences is exponentially increasing due to ongoing large sequencing projects, but without functional data in most cases.ResultsTo alleviate the limitations of supervised learning, we propose a paradigm shift with semi-supervised learning, which does not only exploit labeled sequences (e.g. human genome with ChIP-seq experiment), but also unlabeled sequences available in much larger amounts (e.g. from other species without ChIP-seq experiment, such as chimpanzee). Our approach is flexible and can be plugged into any neural architecture including shallow and deep networks, and shows strong predictive performance improvements compared to supervised learning in most cases (up to 70%).Availability and implementationhttps://forgemia.inra.fr/raphael.mourad/deepgnn.

Characterizing the targets of transcription regulators by aggregating ChIP-seq and perturbation expression data sets.

Mapping the gene targets of chromatin-associated transcription regulators (TRs) is a major goal of genomics research. ChIP-seq of TRs and experiments that perturb a TR and measure the differential abundance of gene transcripts are a primary means by which direct relationships are tested on a genomic scale. It has been reported that there is a poor overlap in the evidence across gene regulation strategies, emphasizing the need for integrating results from multiple experiments. Although research consortia interested in gene regulation have produced a valuable trove of high-quality data, there is an even greater volume of TR-specific data throughout the literature. In this study, we show a workflow for the identification, uniform processing, and aggregation of ChIP-seq and TR perturbation experiments for the ultimate purpose of ranking human and mouse TR-target interactions. Focusing on an initial set of eight regulators (ASCL1, HES1, MECP2, MEF2C, NEUROD1, PAX6, RUNX1, and TCF4), we identified 497 experiments suitable for analysis. We used this corpus to examine data concordance, to identify systematic patterns of the two data types, and to identify putative orthologous interactions between human and mouse. We build upon commonly used strategies to forward a procedure for aggregating and combining these two genomic methodologies, assessing these rankings against independent literature-curated evidence. Beyond a framework extensible to other TRs, our work also provides empirically ranked TR-target listings, as well as transparent experiment-level gene summaries for community use.

An essential role for the Ino80 chromatin remodeling complex in regulation of gene expression during cellular quiescence

Cellular quiescence is an important physiological state both in unicellular and multicellular eukaryotes. Quiescent cells are halted for proliferation and stop the cell cycle at the G0 stage. Using fission yeast as a model organism, we have previously found that several subunits of a conserved chromatin remodeling complex, Ino80C (INOsitol requiring nucleosome remodeling factor), are required for survival in quiescence. Here, we demonstrate that Ino80C has a key function in the regulation of gene expression in G0 cells. We show that null mutants for two Ino80C subunits, Iec1 and Ies2, a putative subunit Arp42, a null mutant for the histone variant H2A.Z, and a null mutant for the Inositol kinase Asp1 have very similar phenotypes in quiescence. These mutants show reduced transcription genome-wide and specifically fail to activate 149 quiescence genes, of which many are localized to the subtelomeric regions. Using spike in normalized ChIP-seq experiments, we show that there is a global reduction of H2A.Z levels in quiescent wild-type cells but not in iec1∆ cells and that a subtelomeric chromosome boundary element is strongly affected by Ino80C. Based on these observations, we propose a model in which Ino80C is evicting H2A.Z from chromatin in quiescent cells, thereby inactivating the subtelomeric boundary element, leading to a reorganization of the chromosome structure and activation of genes required to survive in quiescence.