Enhancer dependence of cell-type-specific gene expression increases with developmental age

From compartments to loops: understanding the unique chromatin organization in neuronal cells

The three-dimensional organization of the genome plays a central role in the regulation of cellular functions, particularly in the human brain. This review explores the intricacies of chromatin organization, highlighting the distinct structural patterns observed between neuronal and non-neuronal brain cells. We integrate findings from recent studies to elucidate the characteristics of various levels of chromatin organization, from differential compartmentalization and topologically associating domains (TADs) to chromatin loop formation. By defining the unique chromatin landscapes of neuronal and non-neuronal brain cells, these distinct structures contribute to the regulation of gene expression specific to each cell type. In particular, we discuss potential functional implications of unique neuronal chromatin organization characteristics, such as weaker compartmentalization, neuron-specific TAD boundaries enriched with active histone marks, and an increased number of chromatin loops. Additionally, we explore the role of Polycomb group (PcG) proteins in shaping cell-type-specific chromatin patterns. This review further emphasizes the impact of variations in chromatin architecture between neuronal and non-neuronal cells on brain development and the onset of neurological disorders. It highlights the need for further research to elucidate the details of chromatin organization in the human brain in order to unravel the complexities of brain function and the genetic mechanisms underlying neurological disorders. This research will help bridge a significant gap in our comprehension of the interplay between chromatin structure and cell functions.

A novel cis-regulatory element regulates αD and αA-globin gene expression in chicken erythroid cells

Background

Cis-regulatory elements (CREs) play crucial roles in regulating gene expression during erythroid cell differentiation. Genome-wide erythroid-specific CREs have not been characterized in chicken erythroid cells, which is an organism model used to study epigenetic regulation during erythropoiesis.

Methods

Analysis of public genome-wide accessibility (ATAC-seq) maps, along with transcription factor (TF) motif analysis, CTCF, and RNA Pol II occupancy, as well as transcriptome analysis in fibroblasts and erythroid HD3 cells, were used to characterize erythroid-specific CREs. An α-globin CRE was identified, and its regulatory activity was validated in vitro and in vivo by luciferase activity and genome-editing assays in HD3 cells, respectively. Additionally, circular chromosome conformation capture (UMI-4C) assays were used to distinguish its role in structuring the α-globin domain in erythroid chicken cells.

Results

Erythroid-specific CREs displayed occupancy by erythroid TF binding motifs, CTCF, and RNA Pol II, as well as an association with genes involved in hematopoiesis and cell differentiation. An α-globin CRE, referred to as CRE-2, was identified as exhibiting enhancer activity over αD and αA genes in vitro and in vivo. Induction of terminal erythroid differentiation showed that α-globin CRE-2 is required for the induction of αD and αA. Analysis of TF binding motifs at α-globin CRE-2 shows apparent regulation mediated by GATA-1, YY1, and CTCF binding.

Conclusion

Our findings demonstrate that cell-specific CREs constitute a key mechanism that contributes to the fine-tuning gene regulation of erythroid cell differentiation and provide insights into the annotation and characterization of CREs in chicken cells.

Integrative analysis of transcriptomic and epigenomic data reveals distinct patterns for developmental and housekeeping gene regulation

BACKGROUND

Regulation of transcription is central to the emergence of new cell types during development, and it often involves activation of genes via proximal and distal regulatory regions. The activity of regulatory elements is determined by transcription factors (TFs) and epigenetic marks, but despite extensive mapping of such patterns, the extraction of regulatory principles remains challenging.

RESULTS

Here we study differentially and similarly expressed genes along with their associated epigenomic profiles, chromatin accessibility and DNA methylation, during lineage specification at gastrulation in mice. Comparison of the three lineages allows us to identify genomic and epigenomic features that distinguish the two classes of genes. We show that differentially expressed genes are primarily regulated by distal elements, while similarly expressed genes are controlled by proximal housekeeping regulatory programs. Differentially expressed genes are relatively isolated within topologically associated domains, while similarly expressed genes tend to be located in gene clusters. Transcription of differentially expressed genes is associated with differentially open chromatin at distal elements including enhancers, while that of similarly expressed genes is associated with ubiquitously accessible chromatin at promoters.

CONCLUSION

Based on these associations of (linearly) distal genes' transcription start sites (TSSs) and putative enhancers for developmental genes, our findings allow us to link putative enhancers to their target promoters and to infer lineage-specific repertoires of putative driver transcription factors, within which we define subgroups of pioneers and co-operators.

MMCT-Loop: a mix model-based pipeline for calling targeted 3D chromatin loops

Protein-specific Chromatin Conformation Capture (3C)-based technologies have become essential for identifying distal genomic interactions with critical roles in gene regulation. The standard techniques include Chromatin Interaction Analysis by Paired-End Tag (ChIA-PET), in situ Hi-C followed by chromatin immunoprecipitation (HiChIP) also known as PLAC-seq. To identify chromatin interactions from these data, a variety of computational methods have emerged. Although these state-of-art methods address many issues with loop calling, only few methods can fit different data types simultaneously, and the accuracy as well as the efficiency these approaches remains limited. Here we have generated a pipeline, MMCT-Loop, which ensures the accurate identification of strong loops as well as dynamic or weak loops through a mixed model. MMCT-Loop outperforms existing methods in accuracy, and the detected loops show higher activation functionality. To highlight the utility of MMCT-Loop, we applied it to conformational data derived from neural stem cell (NSCs) and uncovered several previously unidentified regulatory regions for key master regulators of stem cell identity. MMCT-Loop is an accurate and efficient loop caller for targeted conformation capture data, which supports raw data or pre-processed valid pairs as input, the output interactions are formatted and easily uploaded to a genome browser for visualization.

DNA methylation-dependent and -independent binding of CDX2 directs activation of distinct developmental and homeostatic genes

Precise spatiotemporal and cell type-specific gene expression is essential for proper tissue development and function. Transcription factors (TFs) guide this process by binding to developmental stage-specific targets and establishing an appropriate enhancer landscape. In turn, DNA and chromatin modifications direct the genomic binding of TFs. However, how TFs navigate various chromatin features and selectively bind a small portion of the millions of possible genomic target loci is still not well understood. Here we show that Cdx2 - a pioneer TF that binds distinct targets in developing versus adult intestinal epithelial cells - has a preferential affinity for a non-canonical CpG-containing motif in vivo. A higher frequency of this motif at embryonic and fetal Cdx2 target loci and the specifically methylated state of the CpG during development allows selective Cdx2 binding and activation of developmental enhancers and linked genes. Conversely, demethylation at these enhancers prohibits ectopic Cdx2 binding in adult cells, where Cdx2 binds its canonical motif without a CpG. This differential Cdx2 binding allows for corecruitment of Ctcf and Hnf4, facilitating the establishment of intestinal superenhancers during development and enhancers mediating adult homeostatic functions, respectively. Induced gain of DNA methylation in the adult mouse epithelium or cultured cells causes ectopic recruitment of Cdx2 to the developmental target loci and facilitates cobinding of the partner TFs. Together, our results demonstrate that the differential CpG motif requirements for Cdx2 binding to developmental versus adult target sites allow it to navigate different DNA methylation profiles and activate cell type-specific genes at appropriate times.

Identifying quantitatively differential chromosomal compartmentalization changes and their biological significance from Hi-C data using DARIC

BACKGROUND

Chromosomal compartmentalization plays a critical role in maintaining proper transcriptional programs in cell differentiation and oncogenesis. However, currently the prevalent method for comparative analysis of compartmentalization landscapes between different cell types is limited to the qualitative switched compartments.

RESULTS

To identify genomic regions with quantitatively differential compartmentalization changes from genome-wide chromatin conformation data like Hi-C, we developed a computational framework named DARIC. DARIC includes three modules: compartmentalization quantification, normalization, and differential analysis. Comparing DARIC with the conventional compartment switching analysis reveals substantial regions characterized by quantitatively significant compartmentalization changes without switching. These changes are accompanied by changes in gene expression, chromatin accessibility, H3K27ac intensity, as well as the interactions with nuclear lamina proteins and nuclear positioning, highlighting the functional importance of such quantitative changes in gene regulation. We applied DARIC to dissect the quantitative compartmentalization changes during human cardiomyocyte differentiation and identified two distinct mechanisms for gene activation based on the association with compartmentalization changes. Using the quantitative compartmentalization measurement module from DARIC, we further dissected the compartment variability landscape in the human genome by analyzing a compendium of 32 Hi-C datasets from 4DN. We discovered an interesting correlation between compartmentalization variability and sub-compartments.

CONCLUSIONS

DARIC is a useful tool for analyzing quantitative compartmentalization changes and mining novel biological insights from increasing Hi-C data. Our results demonstrate the functional significance of quantitative compartmentalization changes in gene regulation, and provide new insights into the relationship between compartmentalization variability and sub-compartments in the human genome.

Understanding blood development and leukemia using sequencing-based technologies and human cell systems

Our current understanding of human hematopoiesis has undergone significant transformation throughout the years, challenging conventional views. The evolution of high-throughput technologies has enabled the accumulation of diverse data types, offering new avenues for investigating key regulatory processes in blood cell production and disease. In this review, we will explore the opportunities presented by these advancements for unraveling the molecular mechanisms underlying normal and abnormal hematopoiesis. Specifically, we will focus on the importance of enhancer-associated regulatory networks and highlight the crucial role of enhancer-derived transcription regulation. Additionally, we will discuss the unprecedented power of single-cell methods and the progression in using in vitro human blood differentiation system, in particular induced pluripotent stem cell models, in dissecting hematopoietic processes. Furthermore, we will explore the potential of ever more nuanced patient profiling to allow precision medicine approaches. Ultimately, we advocate for a multiparameter, regulatory network-based approach for providing a more holistic understanding of normal hematopoiesis and blood disorders.

A comprehensive revisit of the machine-learning tools developed for the identification of enhancers in the human genome

Enhancers are non-coding DNA elements that play a crucial role in enhancing the transcription rate of a specific gene in the genome. Experiments for identifying enhancers can be restricted by their conditions and involve complicated, time-consuming, laborious, and costly steps. To overcome these challenges, computational platforms have been developed to complement experimental methods that enable high-throughput identification of enhancers. Over the last few years, the development of various enhancer computational tools has resulted in significant progress in predicting putative enhancers. Thus, researchers are now able to use a variety of strategies to enhance and advance enhancer study. In this review, an overview of machine learning (ML)-based prediction methods for enhancer identification and related databases has been provided. The existing enhancer-prediction methods have also been reviewed regarding their algorithms, feature selection processes, validation techniques, and software utility. In addition, the advantages and drawbacks of these ML approaches and guidelines for developing bioinformatic tools have been highlighted for a more efficient enhancer prediction. This review will serve as a useful resource for experimentalists in selecting the appropriate ML tool for their study, and for bioinformaticians in developing more accurate and advanced ML-based predictors.

In silico enhancer mining reveals SNS-032 and EHMT2 inhibitors as therapeutic candidates in high-grade serous ovarian cancer

BACKGROUND

Epigenomic dysregulation has been linked to solid tumour malignancies, including ovarian cancers. Profiling of re-programmed enhancer locations associated with disease has the potential to improve stratification and thus therapeutic choices. Ovarian cancers are subdivided into histological subtypes that have significant molecular and clinical differences, with high-grade serous carcinoma representing the most common and aggressive subtype.

METHODS

We interrogated the enhancer landscape(s) of normal ovary and subtype-specific ovarian cancer states using publicly available data. With an initial focus on H3K27ac histone mark, we developed a computational pipeline to predict drug compound activity based on epigenomic stratification. Lastly, we substantiated our predictions in vitro using patient-derived clinical samples and cell lines.

RESULTS

Using our in silico approach, we highlighted recurrent and privative enhancer landscapes and identified the differential enrichment of a total of 164 transcription factors involved in 201 protein complexes across the subtypes. We pinpointed SNS-032 and EHMT2 inhibitors BIX-01294 and UNC0646 as therapeutic candidates in high-grade serous carcinoma, as well as probed the efficacy of specific inhibitors in vitro.

CONCLUSION

Here, we report the first attempt to exploit ovarian cancer epigenomic landscapes for drug discovery. This computational pipeline holds enormous potential for translating epigenomic profiling into therapeutic leads.

Identifying Quantitatively Differential Chromosomal Compartmentalization Changes and Their Biological Significance from Hi-C data using DARIC

Background

Chromosomal compartmentalization plays a critical role in maintaining proper transcriptional programs in cell differentiation and oncogenesis. However, currently the prevalent method for comparative analysis of compartmentalization landscapes between different cell types is limited to the qualitative switched compartments.

Results

To identify genomic regions with quantitatively differential compartmentalization changes from genome-wide chromatin conformation data like Hi-C, we developed a computational framework named DARIC. DARIC includes three modules: compartmentalization quantification, normalization, and differential analysis. Comparing DARIC with the conventional compartment switching analysis reveals substantial regions characterized by quantitatively significant compartmentalization changes without switching. These changes are accompanied by changes in gene expression, chromatin accessibility, H3K27ac intensity, as well as the interactions with nuclear lamina proteins and nuclear positioning, highlighting the functional importance of such quantitative changes in gene regulation. We applied DARIC to dissect the quantitative compartmentalization changes during human cardiomyocyte differentiation and identified two distinct mechanisms for gene activation based on the association with compartmentalization changes. Using the quantitative compartmentalization measurement module from DARIC, we further dissected the compartment variability landscape in the human genome by analyzing a compendium of 32 Hi-C datasets from 4DN. We discovered an interesting correlation between compartmentalization variability and sub-compartments.

Conclusions

DARIC is a useful tool for analyzing quantitative compartmentalization changes and mining novel biological insights from increasing Hi-C data. Our results demonstrate the functional significance of quantitative compartmentalization changes in gene regulation, and provide new insights into the relationship between compartmentalization variability and sub-compartments in the human genome.

Comparative genomics analyses reveal sequence determinants underlying interspecies variations in injury-responsive enhancers

BACKGROUND

Injury induces profound transcriptional remodeling events, which could lead to only wound healing, partial tissue repair, or perfect regeneration in different species. Injury-responsive enhancers (IREs) are cis-regulatory elements activated in response to injury signals, and have been demonstrated to promote tissue regeneration in some organisms such as zebrafish and flies. However, the functional significances of IREs in mammals remain elusive. Moreover, whether the transcriptional responses elicited by IREs upon injury are conserved or specialized in different species, and what sequence features may underlie the functional variations of IREs have not been elucidated.

RESULTS

We identified a set of IREs that are activated in both regenerative and non-regenerative neonatal mouse hearts upon myocardial ischemia-induced damage by integrative epigenomic and transcriptomic analyses. Motif enrichment analysis showed that AP-1 and ETS transcription factor binding motifs are significantly enriched in both zebrafish and mouse IREs. However, the IRE-associated genes vary considerably between the two species. We further found that the IRE-related sequences in zebrafish and mice diverge greatly, with the loss of IRE inducibility accompanied by a reduction in AP-1 and ETS motif frequencies. The functional turnover of IREs between zebrafish and mice is correlated with changes in transcriptional responses of the IRE-associated genes upon injury. Using mouse cardiomyocytes as a model, we demonstrated that the reduction in AP-1 or ETS motif frequency attenuates the activation of IREs in response to hypoxia-induced damage.

CONCLUSIONS

By performing comparative genomics analyses on IREs, we demonstrated that inter-species variations in AP-1 and ETS motifs may play an important role in defining the functions of enhancers during injury response. Our findings provide important insights for understanding the molecular mechanisms of transcriptional remodeling in response to injury across species.

In Vivo Dissection of Chamber-Selective Enhancers Reveals Estrogen-Related Receptor as a Regulator of Ventricular Cardiomyocyte Identity

BACKGROUND

Cardiac chamber-selective transcriptional programs underpin the structural and functional differences between atrial and ventricular cardiomyocytes (aCMs and vCMs). The mechanisms responsible for these chamber-selective transcriptional programs remain largely undefined.

METHODS

We nominated candidate chamber-selective enhancers (CSEs) by determining the genome-wide occupancy of 7 key cardiac transcription factors (GATA4, MEF2A, MEF2C, NKX2-5, SRF, TBX5, TEAD1) and transcriptional coactivator P300 in atria and ventricles. Candidate enhancers were tested using an adeno-associated virus-mediated massively parallel reporter assay. Chromatin features of CSEs were evaluated by performing assay of transposase accessible chromatin sequencing and acetylation of histone H3 at lysine 27-HiChIP on aCMs and vCMs. CSE sequence requirements were determined by systematic tiling mutagenesis of 29 CSEs at 5 bp resolution. Estrogen-related receptor (ERR) function in cardiomyocytes was evaluated by Cre-loxP-mediated inactivation of ERRα and ERRγ in cardiomyocytes.

RESULTS

We identified 134 066 and 97 506 regions reproducibly occupied by at least 1 transcription factor or P300, in atria or ventricles, respectively. Enhancer activities of 2639 regions bound by transcription factors or P300 were tested in aCMs and vCMs by adeno-associated virus-mediated massively parallel reporter assay. This identified 1092 active enhancers in aCMs or vCMs. Several overlapped loci associated with cardiovascular disease through genome-wide association studies, and 229 exhibited chamber-selective activity in aCMs or vCMs. Many CSEs exhibited differential chromatin accessibility between aCMs and vCMs, and CSEs were enriched for aCM- or vCM-selective acetylation of histone H3 at lysine 27-anchored loops. Tiling mutagenesis of 29 CSEs identified the binding motif of ERRα/γ as important for ventricular enhancer activity. The requirement of ERRα/γ to activate ventricular CSEs and promote vCM identity was confirmed by loss of the vCM gene profile in ERRα/γ knockout vCMs.

CONCLUSIONS

We identified 229 CSEs that could be useful research tools or direct therapeutic gene expression. We showed that chamber-selective multi-transcription factor, P300 occupancy, open chromatin, and chromatin looping are predictive features of CSEs. We found that ERRα/γ are essential for maintenance of ventricular identity. Finally, our gene expression, epigenetic, 3-dimensional genome, and enhancer activity atlas provide key resources for future studies of chamber-selective gene regulation.

Three-dimensional chromatin re-organization during muscle stem cell aging

Age-related skeletal muscle atrophy or sarcopenia is a significant societal problem that is becoming amplified as the world's population continues to increase. The regeneration of damaged skeletal muscle is mediated by muscle stem cells, but in old age muscle stem cells become functionally attenuated. The molecular mechanisms that govern muscle stem cell aging encompass changes across multiple regulatory layers and are integrated by the three-dimensional organization of the genome. To quantitatively understand how hierarchical chromatin architecture changes during muscle stem cell aging, we generated 3D chromatin conformation maps (Hi-C) and integrated these datasets with multi-omic (chromatin accessibility and transcriptome) profiles from bulk populations and single cells. We observed that muscle stem cells display static behavior at global scales of chromatin organization during aging and extensive rewiring of local contacts at finer scales that were associated with variations in transcription factor binding and aberrant gene expression. These data provide insights into genome topology as a regulator of molecular function in stem cell aging.

Complexity of enhancer networks predicts cell identity and disease genes revealed by single-cell multi-omics analysis

Many enhancers exist as clusters in the genome and control cell identity and disease genes; however, the underlying mechanism remains largely unknown. Here, we introduce an algorithm, eNet, to build enhancer networks by integrating single-cell chromatin accessibility and gene expression profiles. The complexity of enhancer networks is assessed by two metrics: the number of enhancers and the frequency of predicted enhancer interactions (PEIs) based on chromatin co-accessibility. We apply eNet algorithm to a human blood dataset and find cell identity and disease genes tend to be regulated by complex enhancer networks. The network hub enhancers (enhancers with frequent PEIs) are the most functionally important. Compared with super-enhancers, enhancer networks show better performance in predicting cell identity and disease genes. eNet is robust and widely applicable in various human or mouse tissues datasets. Thus, we propose a model of enhancer networks containing three modes: Simple, Multiple and Complex, which are distinguished by their complexity in regulating gene expression. Taken together, our work provides an unsupervised approach to simultaneously identify key cell identity and disease genes and explore the underlying regulatory relationships among enhancers in single cells.

CFA: An explainable deep learning model for annotating the transcriptional roles of cis-regulatory modules based on epigenetic codes

Metazoa gene expression is controlled by modular DNA segments called cis-regulatory modules (CRMs). CRMs can convey promoter/enhancer/insulator roles, generating additional regulation layers in transcription. Experiments for understanding CRM roles are low-throughput and costly. Large-scale CRM function investigation still depends on computational methods. However, existing in silico tools only recognize enhancers or promoters exclusively, thus accumulating errors when considering CRM promoter/enhancer/insulator roles altogether. Currently, no algorithm can concurrently consider these CRM roles. In this research, we developed the CRM Function Annotator (CFA) model. CFA provides complete CRM transcriptional role labeling based on epigenetic profiling interpretation. We demonstrated that CFA achieves high performance (test macro auROC/auPRC = 94.1%/90.3%) and outperforms existing tools in promoter/enhancer/insulator identification. CFA is also inspected to recognize explainable epigenetic codes consistent with previous findings when labeling CRM roles. By considering the higher-order combinations of the epigenetic codes, CFA significantly reduces false-positive rates in CRM transcriptional role annotation. CFA is available at https://github.com/cobisLab/CFA/.

Single-cell chromatin accessibility identifies enhancer networks driving gene expression during spinal cord development in mouse

Spinal cord development is precisely orchestrated by spatiotemporal gene regulatory programs. However, the underlying epigenetic mechanisms remain largely elusive. Here, we profiled single-cell chromatin accessibility landscapes in mouse neural tubes spanning embryonic days 9.5-13.5. We identified neuronal-cell-cluster-specific cis-regulatory elements in neural progenitors and neurons. Furthermore, we applied a novel computational method, eNet, to build enhancer networks by integrating single-cell chromatin accessibility and gene expression data and identify the hub enhancers within enhancer networks. It was experimentally validated in vivo for Atoh1 that knockout of the hub enhancers, but not the non-hub enhancers, markedly decreased Atoh1 expression and reduced dp1/dI1 cells. Together, our work provides insights into the epigenetic regulation of spinal cord development and a proof-of-concept demonstration of enhancer networks as a general mechanism in transcriptional regulation.

ARID1B, a molecular suppressor of erythropoiesis, is essential for the prevention of Monge's disease

At high altitude Andean region, hypoxia-induced excessive erythrocytosis (EE) is the defining feature of Monge's disease or chronic mountain sickness (CMS). At the same altitude, resides a population that has developed adaptive mechanism(s) to constrain this hypoxic response (non-CMS). In this study, we utilized an in vitro induced pluripotent stem cell model system to study both populations using genomic and molecular approaches. Our whole genome analysis of the two groups identified differential SNPs between the CMS and non-CMS subjects in the ARID1B region. Under hypoxia, the expression levels of ARID1B significantly increased in the non-CMS cells but decreased in the CMS cells. At the molecular level, ARID1B knockdown (KD) in non-CMS cells increased the levels of the transcriptional regulator GATA1 by 3-fold and RBC levels by 100-fold under hypoxia. ARID1B KD in non-CMS cells led to increased proliferation and EPO sensitivity by lowering p53 levels and decreasing apoptosis through GATA1 mediation. Interestingly, under hypoxia ARID1B showed an epigenetic role, altering the chromatin states of erythroid genes. Indeed, combined Real-time PCR and ATAC-Seq results showed that ARID1B modulates the expression of GATA1 and p53 and chromatin accessibility at GATA1/p53 target genes. We conclude that ARID1B is a novel erythroid regulator under hypoxia that controls various aspects of erythropoiesis in high-altitude dwellers.

Enhancers regulate 3' end processing activity to control expression of alternative 3'UTR isoforms

Multi-UTR genes are widely transcribed and express their alternative 3'UTR isoforms in a cell type-specific manner. As transcriptional enhancers regulate mRNA expression, we investigated if they also regulate 3'UTR isoform expression. Endogenous enhancer deletion of the multi-UTR gene PTEN did not impair transcript production but prevented 3'UTR isoform switching which was recapitulated by silencing of an enhancer-bound transcription factor. In reporter assays, enhancers increase transcript production when paired with single-UTR gene promoters. However, when combined with multi-UTR gene promoters, they change 3'UTR isoform expression by increasing 3' end processing activity of polyadenylation sites. Processing activity of polyadenylation sites is affected by transcription factors, including NF-κB and MYC, transcription elongation factors, chromatin remodelers, and histone acetyltransferases. As endogenous cell type-specific enhancers are associated with genes that increase their short 3'UTRs in a cell type-specific manner, our data suggest that transcriptional enhancers integrate cellular signals to regulate cell type-and condition-specific 3'UTR isoform expression.

Bacon: a comprehensive computational benchmarking framework for evaluating targeted chromatin conformation capture-specific methodologies

Chromatin conformation capture (3C)-based technologies have enabled the accurate detection of topological genomic interactions, and the adoption of ChIP techniques to 3C-based protocols makes it possible to identify long-range interactions. To analyze these large and complex datasets, computational methods are undergoing rapid and expansive evolution. Thus, a thorough evaluation of these analytical pipelines is necessary to identify which commonly used algorithms and processing pipelines need to be improved. Here we present a comprehensive benchmark framework, Bacon, to evaluate the performance of several computational methods. Finally, we provide practical recommendations for users working with HiChIP and/or ChIA-PET analyses.

Enhancer architecture-dependent multilayered transcriptional regulation orchestrates RA signaling-induced early lineage differentiation of ESCs

Signaling pathway-driven target gene transcription is critical for fate determination of embryonic stem cells (ESCs), but enhancer-dependent transcriptional regulation in these processes remains poorly understood. Here, we report enhancer architecture-dependent multilayered transcriptional regulation at the Halr1–Hoxa1 locus that orchestrates retinoic acid (RA) signaling-induced early lineage differentiation of ESCs. We show that both homeobox A1 (Hoxa1) and Hoxa adjacent long non-coding RNA 1 (Halr1) are identified as direct downstream targets of RA signaling and regulated by RARA/RXRA via RA response elements (RAREs). Chromosome conformation capture-based screens indicate that RA signaling promotes enhancer interactions essential for Hoxa1 and Halr1 expression and mesendoderm differentiation of ESCs. Furthermore, the results also show that HOXA1 promotes expression of Halr1 through binding to enhancer; conversely, loss of Halr1 enhances interaction between Hoxa1 chromatin and four distal enhancers but weakens interaction with chromatin inside the HoxA cluster, leading to RA signaling-induced Hoxa1 overactivation and enhanced endoderm differentiation. These findings reveal complex transcriptional regulation involving synergistic regulation by enhancers, transcription factors and lncRNA. This work provides new insight into intrinsic molecular mechanisms underlying ESC fate determination during RA signaling-induced early differentiation.

TRANSCRIPTIONAL PROFILE AND CHROMATIN ACCESSIBILITY IN ZEBRAFISH MELANOCYTES AND MELANOMA TUMORS

Transcriptional and epigenetic characterization of melanocytes and melanoma cells isolated from their in vivo context promises to unveil key differences between these developmentally related normal and cancer cell populations. We therefore engineered an enhanced Danio rerio (zebrafish) melanoma model with fluorescently labeled melanocytes to allow for isolation of normal (wild type) and premalignant (BRAF^V600E-mutant) populations for comparison to fully transformed BRAF^V600E-mutant, p53 loss-of-function melanoma cells. Using fluorescence-activated cell sorting to isolate these populations, we performed high-quality RNA- and ATAC-seq on sorted zebrafish melanocytes vs. melanoma cells, which we provide as a resource here. Melanocytes had consistent transcriptional and accessibility profiles, as did melanoma cells. Comparing melanocytes and melanoma, we note 4128 differentially expressed genes and 56,936 differentially accessible regions with overall gene expression profiles analogous to human melanocytes and the pigmentation melanoma subtype. Combining the RNA- and ATAC-seq data surprisingly revealed that increased chromatin accessibility did not always correspond with increased gene expression, suggesting that though there is widespread dysregulation in chromatin accessibility in melanoma, there is a potentially more refined gene expression program driving cancerous melanoma. These data serve as a resource to identify candidate regulators of the normal vs. diseased states in a genetically controlled in vivo context.

Inner nuclear protein Matrin-3 coordinates cell differentiation by stabilizing chromatin architecture

Precise control of gene expression during differentiation relies on the interplay of chromatin and nuclear structure. Despite an established contribution of nuclear membrane proteins to developmental gene regulation, little is known regarding the role of inner nuclear proteins. Here we demonstrate that loss of the nuclear scaffolding protein Matrin-3 (Matr3) in erythroid cells leads to morphological and gene expression changes characteristic of accelerated maturation, as well as broad alterations in chromatin organization similar to those accompanying differentiation. Matr3 protein interacts with CTCF and the cohesin complex, and its loss perturbs their occupancy at a subset of sites. Destabilization of CTCF and cohesin binding correlates with altered transcription and accelerated differentiation. This association is conserved in embryonic stem cells. Our findings indicate Matr3 negatively affects cell fate transitions and demonstrate that a critical inner nuclear protein impacts occupancy of architectural factors, culminating in broad effects on chromatin organization and cell differentiation.

Heterogeneity among enhancer RNAs: origins, consequences and perspectives

Enhancer RNAs (eRNAs) are non-coding RNAs transcribed from distal cis-regulatory elements (i.e. enhancers), which are stereotyped as short, rarely spliced and unstable. In fact, a non-negligible fraction of eRNAs seems to be longer, spliced and more stable, and their cognate enhancers are epigenomically and functionally distinguishable from typical enhancers. In this review, we first summarized the genomic and molecular origins underlying the observed heterogeneity among eRNAs. Then, we discussed how their heterogeneous properties (e.g. stability) affect the modes of interaction with their regulatory partners, from promiscuous cis-interactions to specific trans-interactions. Finally, we highlighted the existence of a seemingly continuous spectrum of eRNA properties and its implications in the genomic origins of non-coding RNA genes from an evolutionary perspective.

Mapping the evolving landscape of super-enhancers during cell differentiation

BACKGROUND

Super-enhancers are clusters of enhancer elements that play critical roles in the maintenance of cell identity. Current investigations on super-enhancers are centered on the established ones in static cell types. How super-enhancers are established during cell differentiation remains obscure.

RESULTS

Here, by developing an unbiased approach to systematically analyze the evolving landscape of super-enhancers during cell differentiation in multiple lineages, we discover a general trend where super-enhancers emerge through three distinct temporal patterns: conserved, temporally hierarchical, and de novo. The three types of super-enhancers differ further in association patterns in target gene expression, functional enrichment, and 3D chromatin organization, suggesting they may represent distinct structural and functional subtypes. Furthermore, we dissect the enhancer repertoire within temporally hierarchical super-enhancers, and find enhancers that emerge at early and late stages are enriched with distinct transcription factors, suggesting that the temporal order of establishment of elements within super-enhancers may be directed by underlying DNA sequence. CRISPR-mediated deletion of individual enhancers in differentiated cells shows that both the early- and late-emerged enhancers are indispensable for target gene expression, while in undifferentiated cells early enhancers are involved in the regulation of target genes.

CONCLUSIONS

In summary, our analysis highlights the heterogeneity of the super-enhancer population and provides new insights to enhancer functions within super-enhancers.

GATA1 pathogenic variants disrupt MYH10 silencing during megakaryopoiesis

BACKGROUND

GATA1 is an essential transcription factor for both polyploidization and megakaryocyte (MK) differentiation. The polyploidization defect observed in GATA1 variant carriers is not well understood.

OBJECTIVE

To extensively phenotype two pedigrees displaying different variants in the GATA1 gene and determine if GATA1 controls MYH10 expression levels, a key modulator of MK polyploidization.

METHOD

A total of 146 unrelated propositi with constitutional thrombocytopenia were screened on a multigene panel. We described the genotype-phenotype correlation in GATA1 variant carriers and investigated the effect of these novel variants on MYH10 transcription using luciferase constructs.

RESULTS

The clinical profile associated with the p.L268M variant localized in the C terminal zinc finger was unusual in that the patient displayed bleeding and severe platelet aggregation defects without early-onset thrombocytopenia. p.N206I localized in the N terminal zinc finger was associated, on the other hand, with severe thrombocytopenia (15G/L) in early life. High MYH10 levels were evidenced in platelets of GATA1 variant carriers. Analysis of MKs anti-GATA1 chromatin immunoprecipitation-sequencing data revealed two GATA1 binding sites, located in the 3' untranslated region and in intron 8 of the MYH10 gene. Luciferase reporter assays showed their respective role in the regulation of MYH10 gene expression. Both GATA1 variants significantly alter intron 8 driven MYH10 transcription.

CONCLUSION

The discovery of an association between MYH10 and GATA1 is a novel one. Overall, this study suggests that impaired MYH10 silencing via an intronic regulatory element is the most likely cause of GATA1-related polyploidization defect.

Integrative machine learning framework for the identification of cell-specific enhancers from the human genome

Enhancers are deoxyribonucleic acid (DNA) fragments which when bound by transcription factors enhance the transcription of related genes. Due to its sporadic distribution and similar fractions, identification of enhancers from the human genome seems a daunting task. Compared to the traditional experimental approaches, computational methods with easy-to-use platforms could be efficiently applied to annotate enhancers' functions and physiological roles. In this aspect, several bioinformatics tools have been developed to identify enhancers. Despite their spectacular performances, existing methods have certain drawbacks and limitations, including fixed length of sequences being utilized for model development and cell-specificity negligence. A novel predictor would be beneficial in the context of genome-wide enhancer prediction by addressing the above-mentioned issues. In this study, we constructed new datasets for eight different cell types. Utilizing these data, we proposed an integrative machine learning (ML)-based framework called Enhancer-IF for identifying cell-specific enhancers. Enhancer-IF comprehensively explores a wide range of heterogeneous features with five commonly used ML methods (random forest, extremely randomized tree, multilayer perceptron, support vector machine and extreme gradient boosting). Specifically, these five classifiers were trained with seven encodings and obtained 35 baseline models. The output of these baseline models was integrated and again inputted to five classifiers for the construction of five meta-models. Finally, the integration of five meta-models through ensemble learning improved the model robustness. Our proposed approach showed an excellent prediction performance compared to the baseline models on both training and independent datasets in different cell types, thus highlighting the superiority of our approach in the identification of the enhancers. We assume that Enhancer-IF will be a valuable tool for screening and identifying potential enhancers from the human DNA sequences.

'Enhancing' red cell fate through epigenetic mechanisms

PURPOSE OF REVIEW

Transcription of erythroid-specific genes is regulated by the three-dimensional (3D) structure and composition of chromatin, which dynamically changes during erythroid differentiation. Chromatin organization and dynamics are regulated by several epigenetic mechanisms involving DNA (de-)methylation, posttranslational modifications (PTMs) of histones, chromatin-associated structural proteins, and higher-order structural changes and interactions. This review addresses examples of recent developments in several areas delineating the interface of chromatin regulation and erythroid-specific lineage transcription.

RECENT FINDINGS

We survey and discuss recent studies that focus on the erythroid chromatin landscape, erythroid enhancer-promotor interactions, super-enhancer functionality, the role of chromatin modifiers and epigenetic crosstalk, as well as the progress in mapping red blood cell (RBC) trait-associated genetic variants within cis-regulatory elements (CREs) identified in genome-wide association study (GWAS) efforts as a step toward determining their impact on erythroid-specific gene expression.

SUMMARY

As one of the best characterized and accessible cell differentiation systems, erythropoiesis has been at the forefront of studies aiming to conceptualize how chromatin dynamics regulate transcription. New emerging technologies that bring a significantly enhanced spatial and temporal resolution of chromatin structure, and allow investigation of small cell numbers, have advanced our understanding of chromatin dynamics during erythroid differentiation in vivo.

Arid4b physically interacts with Tfap2c in mouse embryonic stem cells

Precise regulation of gene expression is required for embryonic stem cell (ESC) differentiation. Transcription factor (TF) networks coordinate the balance of pluripotency and differentiation in response to extracellular and intracellular signals. Chromatin factors work alongside TFs to achieve timely regulation of gene expression for differentiation process. Our previous studies showed that a member of the Sin3a corepressor complex, Arid4b, is critical for proper mouse ESC differentiation into mesoderm and endoderm. We found elevated histone 3 lysine 27 acetylation (H3K27Ac) in a subset of genomic loci in meso/endoderm directed arid4bΔ cells, coincident with their derepression. We reasoned that Sin3a complex may be required for the suppression of these genes during differentiation. To identify TFs that might cooperate with Arid4b for this function, we found consensus TF binding sequences enriched in H3K27Ac elevated regions in arid4bΔ cells. Of these candidate TFs, we validated expression of Bach1, Ddit3, Prrx2, Znf354c and Tfap2c in mESCs. We then demonstrated a physical interaction between Arid4b and Tfap2c in mESCs using endogenous coimmunoprecipitation and proximity ligation assay experiments. Our results point to a role of Arid4b in the Sin3a complex in repression of a subset of Tfap2c-regulated genes during meso/endoderm differentiation.