Ubiquitous heterogeneity and asymmetry of the chromatin environment at regulatory elements

Cell-free DNA end characteristics enable accurate and sensitive cancer diagnosis

The fragmentation patterns of cell-free DNA (cfDNA) in plasma can potentially be utilized as diagnostic biomarkers in liquid biopsy. However, our knowledge of this biological process and the information encoded in fragmentation patterns remains preliminary. Here, we investigated the cfDNA fragmentomic characteristics against nucleosome positioning patterns in hematopoietic cells. cfDNA molecules with ends located within nucleosomes were relatively shorter with altered end motif patterns, demonstrating the feasibility of enriching tumor-derived cfDNA in patients with cancer through the selection of molecules possessing such ends. We then developed three cfDNA fragmentomic metrics after end selection, which showed significant alterations in patients with cancer and enabled cancer diagnosis. By incorporating machine learning, we further built high-performance diagnostic models, which achieved an overall area under the curve of 0.95 and 85.1% sensitivity at 95% specificity. Hence, our investigations explored the end characteristics of cfDNA fragmentomics and their merits in building accurate and sensitive cancer diagnostic models.

Evolution of promoter-proximal pausing enabled a new layer of transcription control

Promoter-proximal pausing of RNA polymerase II (Pol II) is a key regulatory step during transcription. Despite the central role of pausing in gene regulation, we do not understand the evolutionary processes that led to the emergence of Pol II pausing or its transition to a rate-limiting step actively controlled by transcription factors. Here we analyzed transcription in species across the tree of life. Unicellular eukaryotes display a slow acceleration of Pol II near transcription start sites that transitioned to a longer-lived, focused pause in metazoans. This event coincided with the evolution of new subunits in the NELF and 7SK complexes. Depletion of NELF in mammals shifted the promoter-proximal buildup of Pol II from the pause site into the early gene body and compromised transcriptional activation for a set of heat shock genes. Our work details the evolutionary history of Pol II pausing and sheds light on how new transcriptional regulatory mechanisms evolve.

FACT maintains chromatin architecture and thereby stimulates RNA polymerase II pausing during transcription in vivo

Facilitates chromatin transcription (FACT) is a histone chaperone that supports transcription through chromatin in vitro, but its functional roles in vivo remain unclear. Here, we analyze the in vivo functions of FACT with the use of multi-omics analysis after rapid FACT depletion from human cells. We show that FACT depletion destabilizes chromatin and leads to transcriptional defects, including defective promoter-proximal pausing and elongation, and increased premature termination of RNA polymerase II. Unexpectedly, our analysis revealed that promoter-proximal pausing depends not only on the negative elongation factor (NELF) but also on the +1 nucleosome, which is maintained by FACT.

RBM22 regulates RNA polymerase II 5' pausing, elongation rate, and termination by coordinating 7SK-P-TEFb complex and SPT5

BACKGROUND

Splicing factors are vital for the regulation of RNA splicing, but some have also been implicated in regulating transcription. The underlying molecular mechanisms of their involvement in transcriptional processes remain poorly understood.

RESULTS

Here, we describe a direct role of splicing factor RBM22 in coordinating multiple steps of RNA Polymerase II (RNAPII) transcription in human cells. The RBM22 protein widely occupies the RNAPII-transcribed gene locus in the nucleus. Loss of RBM22 promotes RNAPII pause release, reduces elongation velocity, and provokes transcriptional readthrough genome-wide, coupled with production of transcripts containing sequences from downstream of the gene. RBM22 preferentially binds to the hyperphosphorylated, transcriptionally engaged RNAPII and coordinates its dynamics by regulating the homeostasis of the 7SK-P-TEFb complex and the association between RNAPII and SPT5 at the chromatin level.

CONCLUSIONS

Our results uncover the multifaceted role of RBM22 in orchestrating the transcriptional program of RNAPII and provide evidence implicating a splicing factor in both RNAPII elongation kinetics and termination control.

Molecular phenotyping of small cell lung cancer using targeted cfDNA profiling of transcriptional regulatory regions

We report an approach for cancer phenotyping based on targeted sequencing of cell-free DNA (cfDNA) for small cell lung cancer (SCLC). In SCLC, differential activation of transcription factors (TFs), such as ASCL1, NEUROD1, POU2F3, and REST defines molecular subtypes. We designed a targeted capture panel that identifies chromatin organization signatures at 1535 TF binding sites and 13,240 gene transcription start sites and detects exonic mutations in 842 genes. Sequencing of cfDNA from SCLC patient-derived xenograft models captured TF activity and gene expression and revealed individual highly informative loci. Prediction models of ASCL1 and NEUROD1 activity using informative loci achieved areas under the receiver operating characteristic curve (AUCs) from 0.84 to 0.88 in patients with SCLC. As non-SCLC (NSCLC) often transforms to SCLC following targeted therapy, we applied our framework to distinguish NSCLC from SCLC and achieved an AUC of 0.99. Our approach shows promising utility for SCLC subtyping and transformation monitoring, with potential applicability to diverse tumor types.

Detection of new pioneer transcription factors as cell-type-specific nucleosome binders

Wrapping of DNA into nucleosomes restricts accessibility to DNA and may affect the recognition of binding motifs by transcription factors. A certain class of transcription factors, the pioneer transcription factors, can specifically recognize their DNA binding sites on nucleosomes, initiate local chromatin opening, and facilitate the binding of co-factors in a cell-type-specific manner. For the majority of human pioneer transcription factors, the locations of their binding sites, mechanisms of binding, and regulation remain unknown. We have developed a computational method to predict the cell-type-specific ability of transcription factors to bind nucleosomes by integrating ChIP-seq, MNase-seq, and DNase-seq data with details of nucleosome structure. We have demonstrated the ability of our approach in discriminating pioneer from canonical transcription factors and predicted new potential pioneer transcription factors in H1, K562, HepG2, and HeLa-S3 cell lines. Last, we systematically analyzed the interaction modes between various pioneer transcription factors and detected several clusters of distinctive binding sites on nucleosomal DNA.

Detection of new pioneer transcription factors as cell-type specific nucleosome binders

Wrapping of DNA into nucleosomes restricts accessibility to the DNA and may affect the recognition of binding motifs by transcription factors. A certain class of transcription factors, the pioneer transcription factors, can specifically recognize their DNA binding sites on nucleosomes, may initiate local chromatin opening and facilitate the binding of co-factors in a cell-type-specific manner. For the majority of human pioneer transcription factors, the locations of their binding sites, mechanisms of binding and regulation remain unknown. We have developed a computational method to predict the cell-type-specific ability of transcription factors to bind nucleosomes by integrating ChIP-seq, MNase-seq and DNase-seq data with details of nucleosome structure. We have demonstrated the ability of our approach in discriminating pioneer from canonical transcription factors and predicted new potential pioneer transcription factors in H1, K562, HepG2 and HeLa cell lines. Lastly, we systemically analyzed the interaction modes between various pioneer transcription factors and detected several clusters of distinctive binding sites on nucleosomal DNA.

Nucleosome repositioning in chronic lymphocytic leukemia

The location of nucleosomes in the human genome determines the primary chromatin structure and regulates access to regulatory regions. However, genome-wide information on deregulated nucleosome occupancy and its implications in primary cancer cells is scarce. Here, we conducted a genome-wide comparison of high-resolution nucleosome maps in peripheral blood B cells from patients with chronic lymphocytic leukemia (CLL) and healthy individuals at single-base-pair resolution. Our investigation uncovered significant changes of nucleosome positioning in CLL. Globally, the spacing between nucleosomes-the nucleosome repeat length (NRL)-is shortened in CLL. This effect is stronger in the more aggressive IGHV-unmutated CLL subtype than in the IGHV-mutated CLL subtype. Changes in nucleosome occupancy at specific sites are linked to active chromatin remodeling and reduced DNA methylation. Nucleosomes lost or gained in CLL marks differential binding of 3D chromatin organizers such as CTCF as well as immune response-related transcription factors and delineated mechanisms of epigenetic deregulation. The principal component analysis of nucleosome occupancy in cancer-specific regions allowed the classification of samples between cancer subtypes and normal controls. Furthermore, patients could be better assigned to CLL subtypes according to differential nucleosome occupancy than based on DNA methylation or gene expression. Thus, nucleosome positioning constitutes a novel readout to dissect molecular mechanisms of disease progression and to stratify patients. Furthermore, we anticipate that the global nucleosome repositioning detected in our study, such as changes in the NRL, can be exploited for liquid biopsy applications based on cell-free DNA to stratify patients and monitor disease progression.

Flipons and small RNAs accentuate the asymmetries of pervasive transcription by the reset and sequence-specific microcoding of promoter conformation

The role of alternate DNA conformations such as Z-DNA in the regulation of transcription is currently underappreciated. These structures are encoded by sequences called flipons, many of which are enriched in promoter and enhancer regions. Through a change in their conformation, flipons provide a tunable mechanism to mechanically reset promoters for the next round of transcription. They act as actuators that capture and release energy to ensure that the turnover of the proteins at promoters is optimized to cell state. Likewise, the single-stranded DNA formed as flipons cycle facilitates the docking of RNAs that are able to microcode promoter conformations and canalize the pervasive transcription commonly observed in metazoan genomes. The strand-specific nature of the interaction between RNA and DNA likely accounts for the known asymmetry of epigenetic marks present on the histone tetramers that pair to form nucleosomes. The role of these supercoil-dependent processes in promoter choice and transcriptional interference is reviewed. The evolutionary implications are examined: the resilience and canalization of flipon-dependent gene regulation is contrasted with the rapid adaptation enabled by the spread of flipon repeats throughout the genome. Overall, the current findings underscore the important role of flipons in modulating the readout of genetic information and how little we know about their biology.

Multi-landmark alignment of genomic signals reveals conserved expression patterns across transcription start sites

The prevalent one-dimensional alignment of genomic signals to a reference landmark is a cornerstone of current methods to study transcription and its DNA-dependent processes but it is prone to mask potential relations among multiple DNA elements. We developed a systematic approach to align genomic signals to multiple locations simultaneously by expanding the dimensionality of the genomic-coordinate space. We analyzed transcription in human and uncovered a complex dependence on the relative position of neighboring transcription start sites (TSSs) that is consistently conserved among cell types. The dependence ranges from enhancement to suppression of transcription depending on the relative distances to the TSSs, their intragenic position, and the transcriptional activity of the gene. Our results reveal a conserved hierarchy of alternative TSS usage within a previously unrecognized level of genomic organization and provide a general methodology to analyze complex functional relationships among multiple types of DNA elements.

SeATAC: a tool for exploring the chromatin landscape and the role of pioneer factors

Assay for Transposase-Accessible Chromatin with sequencing (ATAC-seq) reveals chromatin accessibility across the genome. Currently, no method specifically detects differential chromatin accessibility. Here, SeATAC uses a conditional variational autoencoder model to learn the latent representation of ATAC-seq V-plots and outperforms MACS2 and NucleoATAC on six separate tasks. Applying SeATAC to several pioneer factor-induced differentiation or reprogramming ATAC-seq datasets suggests that induction of these factors not only relaxes the closed chromatin but also decreases chromatin accessibility of 20% to 30% of their target sites. SeATAC is a novel tool to accurately reveal genomic regions with differential chromatin accessibility from ATAC-seq data.

Comprehensive computational analysis of epigenetic descriptors affecting CRISPR-Cas9 off-target activity

BACKGROUND

A common issue in CRISPR-Cas9 genome editing is off-target activity, which prevents the widespread use of CRISPR-Cas9 in medical applications. Among other factors, primary chromatin structure and epigenetics may influence off-target activity.

METHODS

In this work, we utilize crisprSQL, an off-target database, to analyze the effect of 19 epigenetic descriptors on CRISPR-Cas9 off-target activity. Termed as 19 epigenetic features/scores, they consist of 6 experimental epigenetic and 13 computed nucleosome organization-related features. In terms of novel features, 15 of the epigenetic scores are newly considered. The 15 newly considered scores consist of 13 freshly computed nucleosome occupancy/positioning scores and 2 experimental features (MNase and DRIP). The other 4 existing scores are experimental features (CTCF, DNase I, H3K4me3, RRBS) commonly used in deep learning models for off-target activity prediction. For data curation, MNase was aggregated from existing experimental nucleosome occupancy data. Based on the sequence context information available in crisprSQL, we also computed nucleosome occupancy/positioning scores for off-target sites.

RESULTS

To investigate the relationship between the 19 epigenetic features and off-target activity, we first conducted Spearman and Pearson correlation analysis. Such analysis shows that some computed scores derived from training-based models and training-free algorithms outperform all experimental epigenetic features. Next, we evaluated the contribution of all epigenetic features in two successful machine/deep learning models which predict off-target activity. We found that some computed scores, unlike all 6 experimental features, significantly contribute to the predictions of both models. As a practical research contribution, we make the off-target dataset containing all 19 epigenetic features available to the research community.

CONCLUSIONS

Our comprehensive computational analysis helps the CRISPR-Cas9 community better understand the relationship between epigenetic features and CRISPR-Cas9 off-target activity.

Functional analysis of structural variants in single cells using Strand-seq

Somatic structural variants (SVs) are widespread in cancer, but their impact on disease evolution is understudied due to a lack of methods to directly characterize their functional consequences. We present a computational method, scNOVA, which uses Strand-seq to perform haplotype-aware integration of SV discovery and molecular phenotyping in single cells by using nucleosome occupancy to infer gene expression as a readout. Application to leukemias and cell lines identifies local effects of copy-balanced rearrangements on gene deregulation, and consequences of SVs on aberrant signaling pathways in subclones. We discovered distinct SV subclones with dysregulated Wnt signaling in a chronic lymphocytic leukemia patient. We further uncovered the consequences of subclonal chromothripsis in T cell acute lymphoblastic leukemia, which revealed c-Myb activation, enrichment of a primitive cell state and informed successful targeting of the subclone in cell culture, using a Notch inhibitor. By directly linking SVs to their functional effects, scNOVA enables systematic single-cell multiomic studies of structural variation in heterogeneous cell populations.

Modelling clinical DNA fragmentation in the development of universal PCR-based assays for bisulfite-converted, formalin-fixed and cell-free DNA sample analysis

In fragmented DNA, PCR-based methods quantify the number of intact regions at a specific amplicon length. However, the relationship between the population of DNA fragments within a sample and the likelihood they will amplify has not been fully described. To address this, we have derived a mathematical equation that relates the distribution profile of a stochastically fragmented DNA sample to the probability that a DNA fragment within that sample can be amplified by any PCR assay of arbitrary length. Two panels of multiplex PCR assays for quantifying fragmented DNA were then developed: a four-plex panel that can be applied to any human DNA sample and used to estimate the percentage of regions that are intact at any length; and a two-plex panel optimized for quantifying circulating cell-free DNA (cfDNA). For these assays, regions of the human genome least affected by copy number aberration were identified and selected; within these copy-neutral regions, each PCR assay was designed to amplify both genomic and bisulfite-converted DNA; and all assays were validated for use in both conventional qPCR and droplet-digital PCR. Finally, using the cfDNA-optimized assays we find evidence of universally conserved nucleosome positioning among individuals.

ChromDMM: a Dirichlet-multinomial mixture model for clustering heterogeneous epigenetic data

MOTIVATION

Research on epigenetic modifications and other chromatin features at genomic regulatory elements elucidates essential biological mechanisms including the regulation of gene expression. Despite the growing number of epigenetic datasets, new tools are still needed to discover novel distinctive patterns of heterogeneous epigenetic signals at regulatory elements.

RESULTS

We introduce ChromDMM, a product Dirichlet-multinomial mixture model for clustering genomic regions that are characterized by multiple chromatin features. ChromDMM extends the mixture model framework by profile shifting and flipping that can probabilistically account for inaccuracies in the position and strand-orientation of the genomic regions. Owing to hyper-parameter optimization, ChromDMM can also regularize the smoothness of the epigenetic profiles across the consecutive genomic regions. With simulated data, we demonstrate that ChromDMM clusters, shifts and strand-orients the profiles more accurately than previous methods. With ENCODE data, we show that the clustering of enhancer regions in the human genome reveals distinct patterns in several chromatin features. We further validate the enhancer clusters by their enrichment for transcriptional regulatory factor binding sites.

AVAILABILITY AND IMPLEMENTATION

ChromDMM is implemented as an R package and is available at https://github.com/MariaOsmala/ChromDMM.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Regulating specificity in enhancer-promoter communication

Enhancers are cis-regulatory elements that can activate transcription remotely to regulate a specific pattern of a gene's expression. Genes typically have many enhancers that are often intermingled in the loci of other genes. To regulate expression, enhancers must therefore activate their correct promoter while ignoring others that may be in closer linear proximity. In this review, we discuss mechanisms by which enhancers engage with promoters, including recent findings on the role of cohesin and the Mediator complex, and how this specificity in enhancer-promoter communication is encoded. Genetic dissection of model loci, in addition to more recent findings using genome-wide approaches, highlight the core promoter sequence, its accessibility, cofactor-promoter preference, in addition to the surrounding genomic context, as key components.

NucPosDB: a database of nucleosome positioning in vivo and nucleosomics of cell-free DNA

Nucleosome positioning is involved in many gene regulatory processes happening in the cell, and it may change as cells differentiate or respond to the changing microenvironment in a healthy or diseased organism. One important implication of nucleosome positioning in clinical epigenetics is its use in the “nucleosomics” analysis of cell-free DNA (cfDNA) for the purpose of patient diagnostics in liquid biopsies. The rationale for this is that the apoptotic nucleases that digest chromatin of the dying cells mostly cut DNA between nucleosomes. Thus, the short pieces of DNA in body fluids reflect the positions of nucleosomes in the cells of origin. Here, we report a systematic nucleosomics database — NucPosDB — curating published nucleosome positioning datasets in vivo as well as datasets of sequenced cell-free DNA (cfDNA) that reflect nucleosome positioning in situ in the cells of origin. Users can select subsets of the database by a number of criteria and then obtain raw or processed data. NucPosDB also reports the originally determined regions with stable nucleosome occupancy across several individuals with a given condition. An additional section provides a catalogue of computational tools for the analysis of nucleosome positioning or cfDNA experiments and theoretical algorithms for the prediction of nucleosome positioning preferences from DNA sequence. We provide an overview of the field, describe the structure of the database in this context, and demonstrate data variability using examples of different medical conditions. NucPosDB is useful both for the analysis of fundamental gene regulation processes and the training of computational models for patient diagnostics based on cfDNA. The database currently curates ~ 400 publications on nucleosome positioning in cell lines and in situ as well as cfDNA from > 10,000 patients and healthy volunteers. For open-access cfDNA datasets as well as key MNase-seq datasets in human cells, NucPosDB allows downloading processed mapped data in addition to the regions with stable nucleosome occupancy. NucPosDB is available at https://generegulation.org/nucposdb/.

DeNOPA: decoding nucleosome positions sensitively with sparse ATAC-seq data

As the basal bricks, the dynamics and arrangement of nucleosomes orchestrate the higher architecture of chromatin in a fundamental way, thereby affecting almost all nuclear biology processes. Thanks to its rather simple protocol, assay for transposase-accessible chromatin using sequencing (ATAC)-seq has been rapidly adopted as a major tool for chromatin-accessible profiling at both bulk and single-cell levels; however, to picture the arrangement of nucleosomes per se remains a challenge with ATAC-seq. In the present work, we introduce a novel ATAC-seq analysis toolkit, named decoding nucleosome organization profile based on ATAC-seq data (deNOPA), to predict nucleosome positions. Assessments showed that deNOPA outperformed state-of-the-art tools with ultra-sparse ATAC-seq data, e.g. no more than 0.5 fragment per base pair. The remarkable performance of deNOPA was fueled by the short fragment reads, which compose nearly half of sequenced reads in the ATAC-seq libraries and are commonly discarded by state-of-the-art nucleosome positioning tools. However, we found that the short fragment reads enrich information on nucleosome positions and that the linker regions were predicted by reads from both short and long fragments using Gaussian smoothing. Last, using deNOPA, we showed that the dynamics of nucleosome organization may not directly couple with chromatin accessibility in the cis-regulatory regions when human cells respond to heat shock stimulation. Our deNOPA provides a powerful tool with which to analyze the dynamics of chromatin at nucleosome position level with ultra-sparse ATAC-seq data.

Factorbook: an updated catalog of transcription factor motifs and candidate regulatory motif sites

The human genome contains ∼2000 transcriptional regulatory proteins, including ∼1600 DNA-binding transcription factors (TFs) recognizing characteristic sequence motifs to exert regulatory effects on gene expression. The binding specificities of these factors have been profiled both in vitro, using techniques such as HT-SELEX, and in vivo, using techniques including ChIP-seq. We previously developed Factorbook, a TF-centric database of annotations, motifs, and integrative analyses based on ChIP-seq data from Phase II of the ENCODE Project. Here we present an update to Factorbook which significantly expands the breadth of cell type and TF coverage. The update includes an expanded motif catalog derived from thousands of ENCODE Phase II and III ChIP-seq experiments and HT-SELEX experiments; this motif catalog is integrated with the ENCODE registry of candidate cis-regulatory elements to annotate a comprehensive collection of genome-wide candidate TF binding sites. The database also offers novel tools for applying the motif models within machine learning frameworks and using these models for integrative analysis, including annotation of variants and disease and trait heritability. Factorbook is publicly available at www.factorbook.org; we will continue to expand the resource as ENCODE Phase IV data are released.

OpenAnnotate: a web server to annotate the chromatin accessibility of genomic regions

Chromatin accessibility, as a powerful marker of active DNA regulatory elements, provides valuable information for understanding regulatory mechanisms. The revolution in high-throughput methods has accumulated massive chromatin accessibility profiles in public repositories. Nevertheless, utilization of these data is hampered by cumbersome collection, time-consuming processing, and manual chromatin accessibility (openness) annotation of genomic regions. To fill this gap, we developed OpenAnnotate (http://health.tsinghua.edu.cn/openannotate/) as the first web server for efficiently annotating openness of massive genomic regions across various biosample types, tissues, and biological systems. In addition to the annotation resource from 2729 comprehensive profiles of 614 biosample types of human and mouse, OpenAnnotate provides user-friendly functionalities, ultra-efficient calculation, real-time browsing, intuitive visualization, and elaborate application notebooks. We show its unique advantages compared to existing databases and toolkits by effectively revealing cell type-specificity, identifying regulatory elements and 3D chromatin contacts, deciphering gene functional relationships, inferring functions of transcription factors, and unprecedentedly promoting single-cell data analyses. We anticipate OpenAnnotate will provide a promising avenue for researchers to construct a more holistic perspective to understand regulatory mechanisms.

Chromatin Profiling Techniques: Exploring the Chromatin Environment and Its Contributions to Complex Traits

The genetic architecture of complex traits is multifactorial. Genome-wide association studies (GWASs) have identified risk loci for complex traits and diseases that are disproportionately located at the non-coding regions of the genome. On the other hand, we have just begun to understand the regulatory roles of the non-coding genome, making it challenging to precisely interpret the functions of non-coding variants associated with complex diseases. Additionally, the epigenome plays an active role in mediating cellular responses to fluctuations of sensory or environmental stimuli. However, it remains unclear how exactly non-coding elements associate with epigenetic modifications to regulate gene expression changes and mediate phenotypic outcomes. Therefore, finer interrogations of the human epigenomic landscape in associating with non-coding variants are warranted. Recently, chromatin-profiling techniques have vastly improved our understanding of the numerous functions mediated by the epigenome and DNA structure. Here, we review various chromatin-profiling techniques, such as assays of chromatin accessibility, nucleosome distribution, histone modifications, and chromatin topology, and discuss their applications in unraveling the brain epigenome and etiology of complex traits at tissue homogenate and single-cell resolution. These techniques have elucidated compositional and structural organizing principles of the chromatin environment. Taken together, we believe that high-resolution epigenomic and DNA structure profiling will be one of the best ways to elucidate how non-coding genetic variations impact complex diseases, ultimately allowing us to pinpoint cell-type targets with therapeutic potential.

Two distinct mechanisms of RNA polymerase II elongation stimulation in vivo

Transcription by RNA polymerase II (RNA Pol II) relies on the elongation factors PAF1 complex (PAF), RTF1, and SPT6. Here, we use rapid factor depletion and multi-omics analysis to investigate how these elongation factors influence RNA Pol II elongation activity in human cells. Whereas depletion of PAF subunits PAF1 and CTR9 has little effect on cellular RNA synthesis, depletion of RTF1 or SPT6 strongly compromises RNA Pol II activity, albeit in fundamentally different ways. RTF1 depletion decreases RNA Pol II velocity, whereas SPT6 depletion impairs RNA Pol II progression through nucleosomes. These results show that distinct elongation factors stimulate either RNA Pol II velocity or RNA Pol II progression through chromatin in vivo. Further analysis provides evidence for two distinct barriers to early elongation: the promoter-proximal pause site and the +1 nucleosome. It emerges that the first barrier enables loading of elongation factors that are required to overcome the second and subsequent barriers to transcription.

NUCOME: A comprehensive database of nucleosome organization referenced landscapes in mammalian genomes

Background

Nucleosome organization is involved in many regulatory activities in various organisms. However, studies integrating nucleosome organization in mammalian genomes are very limited mainly due to the lack of comprehensive data quality control (QC) assessment and uneven data quality of public data sets.

Results

The NUCOME is a database focused on filtering qualified nucleosome organization referenced landscapes covering various cell types in human and mouse based on QC metrics. The filtering strategy guarantees the quality of nucleosome organization referenced landscapes and exempts users from redundant data set selection and processing. The NUCOME database provides standardized, qualified data source and informative nucleosome organization features at a whole-genome scale and on the level of individual loci.

Conclusions

The NUCOME provides valuable data resources for integrative analyses focus on nucleosome organization. The NUCOME is freely available at http://compbio-zhanglab.org/NUCOME.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12859-021-04239-9.

MetaTX: deciphering the distribution of mRNA-related features in the presence of isoform ambiguity, with applications in epitranscriptome analysis

MOTIVATION

The distribution of biological features strongly indicates their functional relevance. Compared to DNA-related features, deciphering the distribution of mRNA-related features is non-trivial due to the existence of isoform ambiguity and compositional diversity of mRNAs.

RESULTS

We propose here a rigorous statistical framework, MetaTX, for deciphering the distribution of mRNA-related features. Through a standardized mRNA model, MetaTX firstly unifies various mRNA transcripts of diverse compositions, and then corrects the isoform ambiguity by incorporating the overall distribution pattern of the features through an EM algorithm. MetaTX was tested on both simulated and real data. Results suggested that MetaTX substantially outperformed existing direct methods on simulated datasets, and that a more informative distribution pattern was produced for all the three datasets tested, which contain N6-Methyladenosine sites generated by different technologies. MetaTX should make a useful tool for studying the distribution and functions of mRNA-related biological features, especially for mRNA modifications such as N6-Methyladenosine.

AVAILABILITY AND IMPLEMENTATION

The MetaTX R package is freely available at GitHub: https://github.com/yue-wang-biomath/MetaTX.1.0.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Profiling the genetic determinants of chromatin accessibility with scalable single-cell CRISPR screens

CRISPR screens have been used to connect genetic perturbations with changes in gene expression and phenotypes. Here we describe a CRISPR-based, single-cell combinatorial indexing assay for transposase-accessible chromatin (CRISPR-sciATAC) to link genetic perturbations to genome-wide chromatin accessibility in a large number of cells. In human myelogenous leukemia cells, we apply CRISPR-sciATAC to target 105 chromatin-related genes, generating chromatin accessibility data for ~30,000 single cells. We correlate the loss of specific chromatin remodelers with changes in accessibility globally and at the binding sites of individual transcription factors (TFs). For example, we show that loss of the H3K27 methyltransferase EZH2 increases accessibility at heterochromatic regions involved in embryonic development and triggers expression of genes in the HOXA and HOXD clusters. At a subset of regulatory sites, we also analyze changes in nucleosome spacing following the loss of chromatin remodelers. CRISPR-sciATAC is a high-throughput, single-cell method for studying the effect of genetic perturbations on chromatin in normal and disease states.

ΔNp63 is a pioneer factor that binds inaccessible chromatin and elicits chromatin remodeling

BACKGROUND

ΔNp63 is a master transcriptional regulator playing critical roles in epidermal development and other cellular processes. Recent studies suggest that ΔNp63 functions as a pioneer factor that can target its binding sites within inaccessible chromatin and induce chromatin remodeling.

METHODS

In order to examine if ΔNp63 can bind to inaccessible chromatin and to determine if specific histone modifications are required for binding, we induced ΔNp63 expression in two p63-naïve cell lines. ΔNp63 binding was then examined by ChIP-seq and the chromatin at ΔNp63 targets sites was examined before and after binding. Further analysis with competitive nucleosome binding assays was used to determine how ΔNp63 directly interacts with nucleosomes.

RESULTS

Our results show that before ΔNp63 binding, targeted sites lack histone modifications, indicating ΔNp63's capability to bind at unmodified chromatin. Moreover, the majority of the sites that are bound by ectopic ΔNp63 expression exist in an inaccessible state. Once bound, ΔNp63 induces acetylation of the histone and the repositioning of nucleosomes at its binding sites. Further analysis with competitive nucleosome binding assays reveal that ΔNp63 can bind directly to nucleosome edges with significant binding inhibition occurring within 50 bp of the nucleosome dyad.

CONCLUSION

Overall, our results demonstrate that ΔNp63 is a pioneer factor that binds nucleosome edges at inaccessible and unmodified chromatin sites and induces histone acetylation and nucleosome repositioning.

Chromatin information content landscapes inform transcription factor and DNA interactions

Interactions between transcription factors and chromatin are fundamental to genome organization and regulation and, ultimately, cell state. Here, we use information theory to measure signatures of organized chromatin resulting from transcription factor-chromatin interactions encoded in the patterns of the accessible genome, which we term chromatin information enrichment (CIE). We calculate CIE for hundreds of transcription factor motifs across human samples and identify two classes: low and high CIE. The 10-20% of common and tissue-specific high CIE transcription factor motifs, associate with higher protein-DNA residence time, including different binding site subclasses of the same transcription factor, increased nucleosome phasing, specific protein domains, and the genetic control of both chromatin accessibility and gene expression. These results show that variations in the information encoded in chromatin architecture reflect functional biological variation, with implications for cell state dynamics and memory.

Self-organizing maps with variable neighborhoods facilitate learning of chromatin accessibility signal shapes associated with regulatory elements

BACKGROUND

Assigning chromatin states genome-wide (e.g. promoters, enhancers, etc.) is commonly performed to improve functional interpretation of these states. However, computational methods to assign chromatin state suffer from the following drawbacks: they typically require data from multiple assays, which may not be practically feasible to obtain, and they depend on peak calling algorithms, which require careful parameterization and often exclude the majority of the genome. To address these drawbacks, we propose a novel learning technique built upon the Self-Organizing Map (SOM), Self-Organizing Map with Variable Neighborhoods (SOM-VN), to learn a set of representative shapes from a single, genome-wide, chromatin accessibility dataset to associate with a chromatin state assignment in which a particular RE is prevalent. These shapes can then be used to assign chromatin state using our workflow.

RESULTS

We validate the performance of the SOM-VN workflow on 14 different samples of varying quality, namely one assay each of A549 and GM12878 cell lines and two each of H1 and HeLa cell lines, primary B-cells, and brain, heart, and stomach tissue. We show that SOM-VN learns shapes that are (1) non-random, (2) associated with known chromatin states, (3) generalizable across sets of chromosomes, and (4) associated with magnitude and multimodality. We compare the accuracy of SOM-VN chromatin states against the Clustering Aggregation Tool (CAGT), an unsupervised method that learns chromatin accessibility signal shapes but does not associate these shapes with REs, and we show that overall precision and recall is increased when learning shapes using SOM-VN as compared to CAGT. We further compare enhancer state assignments from SOM-VN in signals above a set threshold to enhancer state assignments from Predicting Enhancers from ATAC-seq Data (PEAS), a deep learning method that assigns enhancer chromatin states to peaks. We show that the precision-recall area under the curve for the assignment of enhancer states is comparable to PEAS.

CONCLUSIONS

Our work shows that the SOM-VN workflow can learn relationships between REs and chromatin accessibility signal shape, which is an important step toward the goal of assigning and comparing enhancer state across multiple experiments and phenotypic states.

ATACdb: a comprehensive human chromatin accessibility database

Accessible chromatin is a highly informative structural feature for identifying regulatory elements, which provides a large amount of information about transcriptional activity and gene regulatory mechanisms. Human ATAC-seq datasets are accumulating rapidly, prompting an urgent need to comprehensively collect and effectively process these data. We developed a comprehensive human chromatin accessibility database (ATACdb, http://www.licpathway.net/ATACdb), with the aim of providing a large amount of publicly available resources on human chromatin accessibility data, and to annotate and illustrate potential roles in a tissue/cell type-specific manner. The current version of ATACdb documented a total of 52 078 883 regions from over 1400 ATAC-seq samples. These samples have been manually curated from over 2200 chromatin accessibility samples from NCBI GEO/SRA. To make these datasets more accessible to the research community, ATACdb provides a quality assurance process including four quality control (QC) metrics. ATACdb provides detailed (epi)genetic annotations in chromatin accessibility regions, including super-enhancers, typical enhancers, transcription factors (TFs), common single-nucleotide polymorphisms (SNPs), risk SNPs, eQTLs, LD SNPs, methylations, chromatin interactions and TADs. Especially, ATACdb provides accurate inference of TF footprints within chromatin accessibility regions. ATACdb is a powerful platform that provides the most comprehensive accessible chromatin data, QC, TF footprint and various other annotations.

A dichotomy of gene regulatory associations during the activated B-cell to plasmablast transition

The activated B-cell (ABC) to plasmablast transition encompasses the cusp of antibody-secreting cell (ASC) differentiation. We explore this transition with integrated analysis in human cells, focusing on changes that follow removal from CD40-mediated signals. Within hours of input signal loss, cell growth programs shift toward enhanced proliferation, accompanied by ER-stress response, and up-regulation of ASC features. Clustering of genomic occupancy for IRF4, BLIMP1, XBP1, and CTCF with histone marks identifies a dichotomy: XBP1 and IRF4 link to induced but not repressed gene modules in plasmablasts, whereas BLIMP1 links to modules of ABC genes that are repressed, but not to activated genes. Between ABC and plasmablast states, IRF4 shifts away from AP1/IRF composite elements while maintaining occupancy at IRF and ETS/IRF elements. This parallels the loss of BATF expression, which is identified as a potential BLIMP1 target. In plasmablasts, IRF4 acquires an association with CTCF, a feature maintained in plasma cell myeloma lines. Thus, shifting occupancy links IRF4 to both ABC and ASC gene expression, whereas BLIMP1 occupancy links to repression of the activation state.

An integrative ENCODE resource for cancer genomics

ENCODE comprises thousands of functional genomics datasets, and the encyclopedia covers hundreds of cell types, providing a universal annotation for genome interpretation. However, for particular applications, it may be advantageous to use a customized annotation. Here, we develop such a custom annotation by leveraging advanced assays, such as eCLIP, Hi-C, and whole-genome STARR-seq on a number of data-rich ENCODE cell types. A key aspect of this annotation is comprehensive and experimentally derived networks of both transcription factors and RNA-binding proteins (TFs and RBPs). Cancer, a disease of system-wide dysregulation, is an ideal application for such a network-based annotation. Specifically, for cancer-associated cell types, we put regulators into hierarchies and measure their network change (rewiring) during oncogenesis. We also extensively survey TF-RBP crosstalk, highlighting how SUB1, a previously uncharacterized RBP, drives aberrant tumor expression and amplifies the effect of MYC, a well-known oncogenic TF. Furthermore, we show how our annotation allows us to place oncogenic transformations in the context of a broad cell space; here, many normal-to-tumor transitions move towards a stem-like state, while oncogene knockdowns show an opposing trend. Finally, we organize the resource into a coherent workflow to prioritize key elements and variants, in addition to regulators. We showcase the application of this prioritization to somatic burdening, cancer differential expression and GWAS. Targeted validations of the prioritized regulators, elements and variants using siRNA knockdowns, CRISPR-based editing, and luciferase assays demonstrate the value of the ENCODE resource.

Enhancer prediction in the human genome by probabilistic modelling of the chromatin feature patterns

Background

The binding sites of transcription factors (TFs) and the localisation of histone modifications in the human genome can be quantified by the chromatin immunoprecipitation assay coupled with next-generation sequencing (ChIP-seq). The resulting chromatin feature data has been successfully adopted for genome-wide enhancer identification by several unsupervised and supervised machine learning methods. However, the current methods predict different numbers and different sets of enhancers for the same cell type and do not utilise the pattern of the ChIP-seq coverage profiles efficiently.

Results

In this work, we propose a PRobabilistic Enhancer PRedictIoN Tool (PREPRINT) that assumes characteristic coverage patterns of chromatin features at enhancers and employs a statistical model to account for their variability. PREPRINT defines probabilistic distance measures to quantify the similarity of the genomic query regions and the characteristic coverage patterns. The probabilistic scores of the enhancer and non-enhancer samples are utilised to train a kernel-based classifier. The performance of the method is demonstrated on ENCODE data for two cell lines. The predicted enhancers are computationally validated based on the transcriptional regulatory protein binding sites and compared to the predictions obtained by state-of-the-art methods.

Conclusion

PREPRINT performs favorably to the state-of-the-art methods, especially when requiring the methods to predict a larger set of enhancers. PREPRINT generalises successfully to data from cell type not utilised for training, and often the PREPRINT performs better than the previous methods. The PREPRINT enhancers are less sensitive to the choice of prediction threshold. PREPRINT identifies biologically validated enhancers not predicted by the competing methods. The enhancers predicted by PREPRINT can aid the genome interpretation in functional genomics and clinical studies.

Molecular Basis of the Function of Transcriptional Enhancers

Transcriptional enhancers are major genomic elements that control gene activity in eukaryotes. Recent studies provided deeper insight into the temporal and spatial organization of transcription in the nucleus, the role of non-coding RNAs in the process, and the epigenetic control of gene expression. Thus, multiple molecular details of enhancer functioning were revealed. Here, we describe the recent data and models of molecular organization of enhancer-driven transcription.

Transcriptional corepressor SIN3A regulates hippocampal synaptic plasticity via Homer1/mGluR5 signaling

Long-term memory depends on the control of activity-dependent neuronal gene expression, which is regulated by epigenetic modifications. The epigenetic modification of histones is orchestrated by the opposing activities of 2 classes of regulatory complexes: permissive coactivators and silencing corepressors. Much work has focused on coactivator complexes, but little is known about the corepressor complexes that suppress the expression of plasticity-related genes. Here, we define a critical role for the corepressor SIN3A in memory and synaptic plasticity, showing that postnatal neuronal deletion of Sin3a enhances hippocampal long-term potentiation and long-term contextual fear memory. SIN3A regulates the expression of genes encoding proteins in the postsynaptic density. Loss of SIN3A increases expression of the synaptic scaffold Homer1, alters the metabotropic glutamate receptor 1α (mGluR1α) and mGluR5 dependence of long-term potentiation, and increases activation of ERK in the hippocampus after learning. Our studies define a critical role for corepressors in modulating neural plasticity and memory consolidation and reveal that Homer1/mGluR signaling pathways may be central molecular mechanisms for memory enhancement.

Graph embedding and unsupervised learning predict genomic sub-compartments from HiC chromatin interaction data

Chromatin interaction studies can reveal how the genome is organized into spatially confined sub-compartments in the nucleus. However, accurately identifying sub-compartments from chromatin interaction data remains a challenge in computational biology. Here, we present Sub-Compartment Identifier (SCI), an algorithm that uses graph embedding followed by unsupervised learning to predict sub-compartments using Hi-C chromatin interaction data. We find that the network topological centrality and clustering performance of SCI sub-compartment predictions are superior to those of hidden Markov model (HMM) sub-compartment predictions. Moreover, using orthogonal Chromatin Interaction Analysis by in-situ Paired-End Tag Sequencing (ChIA-PET) data, we confirmed that SCI sub-compartment prediction outperforms HMM. We show that SCI-predicted sub-compartments have distinct epigenetic marks, transcriptional activities, and transcription factor enrichment. Moreover, we present a deep neural network to predict sub-compartments using epigenome, replication timing, and sequence data. Our neural network predicts more accurate sub-compartment predictions when SCI-determined sub-compartments are used as labels for training.

Exploring 3D chromatin contacts in gene regulation: The evolution of approaches for the identification of functional enhancer-promoter interaction

Mechanisms underlying gene regulation are key to understand how multicellular organisms with various cell types develop from the same genetic blueprint. Dynamic interactions between enhancers and genes are revealed to play central roles in controlling gene transcription, but the determinants to link functional enhancer-promoter pairs remain elusive. A major challenge is the lack of reliable approach to detect and verify functional enhancer-promoter interactions (EPIs). In this review, we summarized the current methods for detecting EPIs and described how developing techniques facilitate the identification of EPI through assessing the merits and drawbacks of these methods. We also reviewed recent state-of-art EPI prediction methods in terms of their rationale, data usage and characterization. Furthermore, we briefly discussed the evolved strategies for validating functional EPIs.

Role of cell-type specific nucleosome positioning in inducible activation of mammalian promoters

The organization of nucleosomes across functional genomic elements represents a critical layer of control. Here, we present a strategy for high-resolution nucleosome profiling at selected genomic features, and use this to analyse dynamic nucleosome positioning at inducible and cell-type-specific mammalian promoters. We find that nucleosome patterning at inducible promoters frequently resembles that at active promoters, even before stimulus-driven activation. Accordingly, the nucleosome profile at many inactive inducible promoters is sufficient to predict cell-type-specific responsiveness. Induction of gene expression is generally not associated with major changes to nucleosome patterning, and a subset of inducible promoters can be activated without stable nucleosome depletion from their transcription start sites. These promoters are generally dependent on remodelling enzymes for their inducible activation, and exhibit transient nucleosome depletion only at alleles undergoing transcription initiation. Together, these data reveal how the responsiveness of inducible promoters to activating stimuli is linked to cell-type-specific nucleosome patterning.

Nucleosome organisation plays important roles in regulating functional genomic elements. Here, the authors use high-resolution profiling to analyse dynamic nucleosome positioning at inducible and cell-type-specific promoters, providing a global view of chromatin architecture at inducible promoters.

Novel approach reveals genomic landscapes of single-strand DNA breaks with nucleotide resolution in human cells

Single-strand breaks (SSBs) represent the major form of DNA damage, yet techniques to map these lesions genome-wide with nucleotide-level precision are limited. Here, we present a method, termed SSiNGLe, and demonstrate its utility to explore the distribution and dynamic changes in genome-wide SSBs in response to different biological and environmental stimuli. We validate SSiNGLe using two very distinct sequencing techniques and apply it to derive global profiles of SSBs in different biological states. Strikingly, we show that patterns of SSBs in the genome are non-random, specific to different biological states, enriched in regulatory elements, exons, introns, specific types of repeats and exhibit differential preference for the template strand between exons and introns. Furthermore, we show that breaks likely contribute to naturally occurring sequence variants. Finally, we demonstrate strong links between SSB patterns and age. Overall, SSiNGLe provides access to unexplored realms of cellular biology, not obtainable with current approaches.

Prediction of regulatory motifs from human Chip-sequencing data using a deep learning framework

The identification of transcription factor binding sites and cis-regulatory motifs is a frontier whereupon the rules governing protein–DNA binding are being revealed. Here, we developed a new method (DEep Sequence and Shape mOtif or DESSO) for cis-regulatory motif prediction using deep neural networks and the binomial distribution model. DESSO outperformed existing tools, including DeepBind, in predicting motifs in 690 human ENCODE ChIP-sequencing datasets. Furthermore, the deep-learning framework of DESSO expanded motif discovery beyond the state-of-the-art by allowing the identification of known and new protein–protein–DNA tethering interactions in human transcription factors (TFs). Specifically, 61 putative tethering interactions were identified among the 100 TFs expressed in the K562 cell line. In this work, the power of DESSO was further expanded by integrating the detection of DNA shape features. We found that shape information has strong predictive power for TF–DNA binding and provides new putative shape motif information for human TFs. Thus, DESSO improves in the identification and structural analysis of TF binding sites, by integrating the complexities of DNA binding into a deep-learning framework.

CTCF-dependent chromatin boundaries formed by asymmetric nucleosome arrays with decreased linker length

The CCCTC-binding factor (CTCF) organises the genome in 3D through DNA loops and in 1D by setting boundaries isolating different chromatin states, but these processes are not well understood. Here we investigate chromatin boundaries in mouse embryonic stem cells, defined by the regions with decreased Nucleosome Repeat Length (NRL) for ∼20 nucleosomes near CTCF sites, affecting up to 10% of the genome. We found that the nucleosome-depleted region (NDR) near CTCF is asymmetrically located >40 nucleotides 5'-upstream from the centre of CTCF motif. The strength of CTCF binding to DNA and the presence of cohesin is correlated with the decrease of NRL near CTCF, and anti-correlated with the level of asymmetry of the nucleosome array. Individual chromatin remodellers have different contributions, with Snf2h having the strongest effect on the NRL decrease near CTCF and Chd4 playing a major role in the symmetry breaking. Upon differentiation, a subset of preserved, common CTCF sites maintains asymmetric nucleosome pattern and small NRL. The sites which lost CTCF upon differentiation are characterized by nucleosome rearrangement 3'-downstream, with unchanged NDR 5'-upstream of CTCF motifs. Boundaries of topologically associated chromatin domains frequently contain several inward-oriented CTCF motifs whose effects, described above, add up synergistically.

SPar-K: a method to partition NGS signal data

SUMMARY

We present SPar-K (Signal Partitioning with K-means), a method to search for archetypical chromatin architectures by partitioning a set of genomic regions characterized by chromatin signal profiles around ChIP-seq peaks and other kinds of functional sites. This method efficiently deals with problems of data heterogeneity, limited misalignment of anchor points and unknown orientation of asymmetric patterns.

AVAILABILITY AND IMPLEMENTATION

SPar-K is a C++ program available on GitHub https://github.com/romaingroux/SPar-K and Docker Hub https://hub.docker.com/r/rgroux/spar-k.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

EpiSAFARI: sensitive detection of valleys in epigenetic signals for enhancing annotations of functional elements

MOTIVATION

Functional genomics experiments generate genomewide signal profiles that are dense information sources for annotating the regulatory elements. These profiles measure epigenetic activity at the nucleotide resolution and they exhibit distinctive patterns as they fluctuate along the genome. Most notable of these patterns are the valley patterns that are prevalently observed in assays such as ChIP Sequencing and bisulfite sequencing. The genomic positions of valleys pinpoint locations of cis-regulatory elements such as enhancers and insulators. Systematic identification of the valleys provides novel information for delineating the annotation of regulatory elements. Nevertheless, the valleys are not reported by majority of the analysis pipelines.

RESULTS

We describe EpiSAFARI, a computational method for sensitive detection of valleys from diverse types of epigenetic profiles. EpiSAFARI employs a novel smoothing method for decreasing noise in signal profiles and accounts for technical factors such as sparse signals, mappability and nucleotide content. In performance comparisons, EpiSAFARI performs favorably in terms of accuracy. The histone modification valleys detected by EpiSAFARI exhibit high conservation, transcription factor binding and they are enriched in nascent transcription. In addition, the large clusters of histone valleys are found to be enriched at the promoters of the developmentally associated genes. Differential histone valleys exhibit concordance with differential DNase signal at cell line specific valleys. DNA methylation valleys exhibit elevated conservation and high transcription factor binding. Specifically, we observed enriched binding of transcription factors associated with chromatin structure around methyl-valleys.

AVAILABILITY AND IMPLEMENTATION

EpiSAFARI is publicly available at https://github.com/harmancilab/EpiSAFARI.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

NUCLIZE for quantifying epigenome: generating histone modification data at single-nucleosome resolution using genuine nucleosome positions

Background

Defining histone modification at single-nucleosome resolution provides accurate epigenomic information in individual nucleosomes. However, most of histone modification data deposited in current databases, such as ENCODE and Roadmap, have low resolution with peaks of several kilo-base pairs (kb), which due to the technical defects of regular ChIP-Seq technology.

Results

To generate histone modification data at single-nucleosome resolution, we developed a novel approach, NUCLIZE, using synergistic analyses of histone modification data from ChIP-Seq and high-resolution nucleosome mapping data from native MNase-Seq. With this approach, we generated quantitative epigenomics data of single and multivalent histone modification marks in each nucleosome. We found that the dominant trivalent histone mark (H3K4me3/H3K9ac/H3K27ac) and others showed defined and specific patterns near each TSS, indicating potential epigenetic codes regulating gene transcription.

Conclusions

Single-nucleosome histone modification data render epigenomic data become quantitative, which is essential for investigating dynamic changes of epigenetic regulation in the biological process or for functional epigenomics studies. Thus, NUCLIZE turns current epigenomic mapping studies into genuine functional epigenomics studies with quantitative epigenomic data.

Electronic supplementary material

The online version of this article (10.1186/s12864-019-5932-6) contains supplementary material, which is available to authorized users.

Theory of Site-Specific DNA-Protein Interactions in the Presence of Nucleosome Roadblocks

We show that nucleosomes exert a maximal amount of hindrance to the one-dimensional diffusion of transcription factors (TFs) when they are present between TFs and their cognate sites on DNA. The effective one-dimensional diffusion coefficient of TFs (χ_TF) decreases with a rise in the free-energy barrier (μ_NU) of the sliding of nucleosomes as χ_TF∝exp(-μ_NU). The average time (η_L) required by TFs to slide over L sites on DNA increases with μ_NU as η_L∝exp(μ_NU). When TFs move close to nucleosomes, then they exhibit typical subdiffusion. Nucleosomes can enhance the search dynamics of TFs when TFs are present between nucleosomes and TF binding sites. These results suggest that nucleosome-depleted regions around the cognate sites of TFs are mandatory for efficient site-specific binding of TFs. Remarkably, the genome-wide in vivo positioning pattern of TFs shows a maximum at their specific binding sites where the occupancy of nucleosomes shows a minimum. This could be a consequence of an increasing level of breathing dynamics of nucleosome cores and decreasing levels of fluctuations in the DNA binding domains of TFs as they move across TF binding sites. The dynamics of TFs becomes slow as they approach their cognate sites so that TFs form a tight site-specific complex, whereas the dynamics of nucleosomes becomes rapid so that they quickly pass through the cognate sites of TFs. Several in vivo data sets on the genome-wide positioning pattern of nucleosomes and TFs agree well with our arguments. The retarding effects of nucleosomes can be minimized when the degree of condensation of DNA is such that it can permit a jump size associated with the dynamics of TFs beyond ∼160-180 bp.

Nucleosome dynamics of human iPSC during neural differentiation

Nucleosome positioning is important for neurodevelopment, and genes mediating chromatin remodelling are strongly associated with human neurodevelopmental disorders. To investigate changes in nucleosome positioning during neural differentiation, we generate genome‐wide nucleosome maps from an undifferentiated human‐induced pluripotent stem cell (hiPSC) line and after its differentiation to the neural progenitor cell (NPC) stage. We find that nearly 3% of nucleosomes are highly positioned in NPC, but significantly, there are eightfold fewer positioned nucleosomes in pluripotent cells, indicating increased positioning during cell differentiation. Positioned nucleosomes do not strongly correlate with active chromatin marks or gene transcription. Unexpectedly, we find a small population of nucleosomes that occupy similar positions in pluripotent and neural progenitor cells and are found at binding sites of the key gene regulators NRSF/REST and CTCF. Remarkably, the presence of these nucleosomes appears to be independent of the associated regulatory complexes. Together, these results present a scenario in human cells, where positioned nucleosomes are sparse and dynamic, but may act to alter gene expression at a distance via the structural conformation at sites of chromatin regulation.

The interaction landscape between transcription factors and the nucleosome

Nucleosomes cover most of the genome and are thought to be displaced by transcription factors in regions that direct gene expression. However, the modes of interaction between transcription factors and nucleosomal DNA remain largely unknown. Here we systematically explore interactions between the nucleosome and 220 transcription factors representing diverse structural families. Consistent with earlier observations, we find that the majority of the studied transcription factors have less access to nucleosomal DNA than to free DNA. The motifs recovered from transcription factors bound to nucleosomal and free DNA are generally similar. However, steric hindrance and scaffolding by the nucleosome result in specific positioning and orientation of the motifs. Many transcription factors preferentially bind close to the end of nucleosomal DNA, or to periodic positions on the solvent-exposed side of the DNA. In addition, several transcription factors usually bind to nucleosomal DNA in a particular orientation. Some transcription factors specifically interact with DNA located at the dyad position at which only one DNA gyre is wound, whereas other transcription factors prefer sites spanning two DNA gyres and bind specifically to each of them. Our work reveals notable differences in the binding of transcription factors to free and nucleosomal DNA, and uncovers a diverse interaction landscape between transcription factors and the nucleosome.