Discovery of directional and nondirectional pioneer transcription factors by modeling DNase profile magnitude and shape

Transcriptional and epigenetic characterization of a new in vitro platform to model the formation of human pharyngeal endoderm

BACKGROUND

The Pharyngeal Endoderm (PE) is an extremely relevant developmental tissue, serving as the progenitor for the esophagus, parathyroids, thyroids, lungs, and thymus. While several studies have highlighted the importance of PE cells, a detailed transcriptional and epigenetic characterization of this important developmental stage is still missing, especially in humans, due to technical and ethical constraints pertaining to its early formation.

RESULTS

Here we fill this knowledge gap by developing an in vitro protocol for the derivation of PE-like cells from human Embryonic Stem Cells (hESCs) and by providing an integrated multi-omics characterization. Our PE-like cells robustly express PE markers and are transcriptionally homogenous and similar to in vivo mouse PE cells. In addition, we define their epigenetic landscape and dynamic changes in response to Retinoic Acid by combining ATAC-Seq and ChIP-Seq of histone modifications. The integration of multiple high-throughput datasets leads to the identification of new putative regulatory regions and to the inference of a Retinoic Acid-centered transcription factor network orchestrating the development of PE-like cells.

CONCLUSIONS

By combining hESCs differentiation with computational genomics, our work reveals the epigenetic dynamics that occur during human PE differentiation, providing a solid resource and foundation for research focused on the development of PE derivatives and the modeling of their developmental defects in genetic syndromes.

Artificial intelligence in plant breeding

Harnessing cutting-edge technologies to enhance crop productivity is a pivotal goal in modern plant breeding. Artificial intelligence (AI) is renowned for its prowess in big data analysis and pattern recognition, and is revolutionizing numerous scientific domains including plant breeding. We explore the wider potential of AI tools in various facets of breeding, including data collection, unlocking genetic diversity within genebanks, and bridging the genotype-phenotype gap to facilitate crop breeding. This will enable the development of crop cultivars tailored to the projected future environments. Moreover, AI tools also hold promise for refining crop traits by improving the precision of gene-editing systems and predicting the potential effects of gene variants on plant phenotypes. Leveraging AI-enabled precision breeding can augment the efficiency of breeding programs and holds promise for optimizing cropping systems at the grassroots level. This entails identifying optimal inter-cropping and crop-rotation models to enhance agricultural sustainability and productivity in the field.

Genomic binding of NF-Y in mouse and human cells

NF-Y is a Transcription Factor that regulates transcription through binding to the CCAAT-box. To understand its strategy, we analyzed 16 ChIP-seq datasets from human and mouse cells. Shared loci, mostly located in promoters of expressed genes of cell cycle, metabolism and gene expression pathways, are associated with histone marks of active chromatin and specific modules of TFs. Other peaks are in enhancers and Transposable Elements -TE- of retroviral origin in human and mouse. We evaluated the relationship with USF1, a common synergistic partner in promoters and MLT1 TEs, upon NF-YB inactivation: USF1 binding decreases in promoters, modestly in MLT1, suggesting a pioneering role of NF-Y in formers, not in the latters. These data define a common set of NF-Y functional targets across different mammalian cell types, suggesting a pioneering role in promoters with respect to TEs.

TFscope: systematic analysis of the sequence features involved in the binding preferences of transcription factors

Characterizing the binding preferences of transcription factors (TFs) in different cell types and conditions is key to understand how they orchestrate gene expression. Here, we develop TFscope, a machine learning approach that identifies sequence features explaining the binding differences observed between two ChIP-seq experiments targeting either the same TF in two conditions or two TFs with similar motifs (paralogous TFs). TFscope systematically investigates differences in the core motif, nucleotide environment and co-factor motifs, and provides the contribution of each key feature in the two experiments. TFscope was applied to > 305 ChIP-seq pairs, and several examples are discussed.

CRISPR PERSIST-On enables heritable and fine-tunable human gene activation

Current technologies for upregulation of endogenous genes use targeted artificial transcriptional activators but stable gene activation requires persistent expression of these synthetic factors. Although general "hit-and-run" strategies exist for inducing long-term silencing of endogenous genes using targeted artificial transcriptional repressors, to our knowledge no equivalent approach for gene activation has been described to date. Here we show stable gene activation can be achieved by harnessing endogenous transcription factors ( EndoTF s) that are normally expressed in human cells. Specifically, EndoTFs can be recruited to activate endogenous human genes of interest by using CRISPR-based gene editing to introduce EndoTF DNA binding motifs into a target gene promoter. This Precision Editing of Regulatory Sequences to Induce Stable Transcription-On ( PERSIST-On ) approach results in stable long-term gene activation, which we show is durable for at least five months. Using a high-throughput CRISPR prime editing pooled screening method, we also show that the magnitude of gene activation can be finely tuned either by using binding sites for different EndoTF or by introducing specific mutations within such sites. Our results delineate a generalizable framework for using PERSIST-On to induce heritable and fine-tunable gene activation in a hit-and-run fashion, thereby enabling a wide range of research and therapeutic applications that require long-term upregulation of a target gene.

Dissection of core promoter syntax through single nucleotide resolution modeling of transcription initiation

Our understanding of how the DNA sequences of cis-regulatory elements encode transcription initiation patterns remains limited. Here we introduce CLIPNET, a deep learning model trained on population-scale PRO-cap data that accurately predicts the position and quantity of transcription initiation with single nucleotide resolution from DNA sequence. Interpretation of CLIPNET revealed a complex regulatory syntax consisting of DNA-protein interactions in five major positions between -200 and +50 bp relative to the transcription start site, as well as more subtle positional preferences among different transcriptional activators. Transcriptional activator and core promoter motifs occupy different positions and play distinct roles in regulating initiation, with the former driving initiation quantity and the latter initiation position. We identified core promoter motifs that explain initiation patterns in the majority of promoters and enhancers, including DPR motifs and AT-rich TBP binding sequences in TATA-less promoters. Our results provide insights into the sequence architecture governing transcription initiation.

Structural and dynamical aspect of DNA motif sequence specific binding of AP-1 transcription factor

Activator protein-1 (AP-1) comprises one of the largest and most evolutionary conserved families of ubiquitous eukaryotic transcription factors that act as a pioneer factor. Diversity in DNA binding interaction of AP-1 through a conserved basic-zipper (bZIP) domain directs in-depth understanding of how AP-1 achieves its DNA binding selectivity and consequently gene regulation specificity. Here, we address the structural and dynamical aspects of the DNA target recognition process of AP-1 using microsecond-long atomistic simulations based on the structure of the human AP-1 FosB/JunD bZIP-DNA complex. Our results show the unique role of DNA shape features in selective base specific interactions, characteristic ion population, and solvation properties of DNA grooves to form the motif sequence specific AP-1-DNA complex. The TpG step at the two terminals of the AP-1 site plays an important role in the structural adjustment of DNA by modifying the helical twist in the AP-1 bound state. We addressed the role of intrinsic motion of the bZIP domain in terms of opening and closing gripper motions of DNA binding helices, in target site recognition and binding of AP-1 factors. Our observations suggest that binding to the cognate motif in DNA is mainly accompanied with the precise adjustment of closing gripper motion of DNA binding helices of the bZIP domain.

Epigenetic profiling reveals key genes and cis-regulatory networks specific to human parathyroids

In all terrestrial vertebrates, the parathyroid glands are critical regulators of calcium homeostasis and the sole source of parathyroid hormone (PTH). Hyperparathyroidism and hypoparathyroidism are clinically important disorders affecting multiple organs. However, our knowledge regarding regulatory mechanisms governing the parathyroids has remained limited. Here, we present the comprehensive maps of the chromatin landscape of the human parathyroid glands, identifying active regulatory elements and chromatin interactions. These data allow us to define regulatory circuits and previously unidentified genes that play crucial roles in parathyroid biology. We experimentally validate candidate parathyroid-specific enhancers and demonstrate their integration with GWAS SNPs for parathyroid-related diseases and traits. For instance, we observe reduced activity of a parathyroid-specific enhancer of the Calcium Sensing Receptor gene, which contains a risk allele associated with higher PTH levels compared to the wildtype allele. Our datasets provide a valuable resource for unraveling the mechanisms governing parathyroid gland regulation in health and disease.

RNA polymerase II promotes the organization of chromatin following DNA replication

Understanding how chromatin organisation is duplicated on the two daughter strands is a central question in epigenetics. In mammals, following the passage of the replisome, nucleosomes lose their defined positioning and transcription contributes to their re-organisation. However, whether transcription plays a greater role in the organization of chromatin following DNA replication remains unclear. Here we analysed protein re-association with newly replicated DNA upon inhibition of transcription using iPOND coupled to quantitative mass spectrometry. We show that nucleosome assembly and the re-establishment of most histone modifications are uncoupled from transcription. However, RNAPII acts to promote the re-association of hundreds of proteins with newly replicated chromatin via pathways that are not observed in steady-state chromatin. These include ATP-dependent remodellers, transcription factors and histone methyltransferases. We also identify a set of DNA repair factors that may handle transcription-replication conflicts during normal transcription in human non-transformed cells. Our study reveals that transcription plays a greater role in the organization of chromatin post-replication than previously anticipated.

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.

Multifaceted SOX2-chromatin interaction underpins pluripotency progression in early embryos

Pioneer transcription factors (TFs), such as OCT4 and SOX2, play crucial roles in pluripotency regulation. However, the master TF-governed pluripotency regulatory circuitry was largely inferred from cultured cells. In this work, we investigated SOX2 binding from embryonic day 3.5 (E3.5) to E7.5 in the mouse. In E3.5 inner cell mass (ICM), SOX2 regulates the ICM-trophectoderm program but is dispensable for opening global enhancers. Instead, SOX2 occupies preaccessible enhancers in part opened by early-stage expressing TFs TFAP2C and NR5A2. SOX2 then widely redistributes when cells adopt naive and formative pluripotency by opening enhancers or poising them for rapid future activation. Hence, multifaceted pioneer TF-enhancer interaction underpins pluripotency progression in embryos, including a distinctive state in E3.5 ICM that bridges totipotency and pluripotency.

Computational tools for inferring transcription factor activity

Transcription factors (TFs) are essential players in orchestrating the regulatory landscape in cells. Still, their exact modes of action and dependencies on other regulatory aspects remain elusive. Since TFs act cell type-specific and each TF has its own characteristics, untangling their regulatory interactions from an experimental point of view is laborious and convoluted. Thus, there is an ongoing development of computational tools that estimate transcription factor activity (TFA) from a variety of data modalities, either based on a mapping of TFs to their putative target genes or in a genome-wide, gene-unspecific fashion. These tools can help to gain insights into TF regulation and to prioritize candidates for experimental validation. We want to give an overview of available computational tools that estimate TFA, illustrate examples of their application, debate common result validation strategies, and discuss assumptions and concomitant limitations.

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.

Gene regulatory network inference in the era of single-cell multi-omics

The interplay between chromatin, transcription factors and genes generates complex regulatory circuits that can be represented as gene regulatory networks (GRNs). The study of GRNs is useful to understand how cellular identity is established, maintained and disrupted in disease. GRNs can be inferred from experimental data - historically, bulk omics data - and/or from the literature. The advent of single-cell multi-omics technologies has led to the development of novel computational methods that leverage genomic, transcriptomic and chromatin accessibility information to infer GRNs at an unprecedented resolution. Here, we review the key principles of inferring GRNs that encompass transcription factor-gene interactions from transcriptomics and chromatin accessibility data. We focus on the comparison and classification of methods that use single-cell multimodal data. We highlight challenges in GRN inference, in particular with respect to benchmarking, and potential further developments using additional data modalities.

Chromatin accessibility in the Drosophila embryo is determined by transcription factor pioneering and enhancer activation

Chromatin accessibility is integral to the process by which transcription factors (TFs) read out cis-regulatory DNA sequences, but it is difficult to differentiate between TFs that drive accessibility and those that do not. Deep learning models that learn complex sequence rules provide an unprecedented opportunity to dissect this problem. Using zygotic genome activation in Drosophila as a model, we analyzed high-resolution TF binding and chromatin accessibility data with interpretable deep learning and performed genetic validation experiments. We identify a hierarchical relationship between the pioneer TF Zelda and the TFs involved in axis patterning. Zelda consistently pioneers chromatin accessibility proportional to motif affinity, whereas patterning TFs augment chromatin accessibility in sequence contexts where they mediate enhancer activation. We conclude that chromatin accessibility occurs in two tiers: one through pioneering, which makes enhancers accessible but not necessarily active, and the second when the correct combination of TFs leads to enhancer activation.

Recapitulation of patient-specific 3D chromatin conformation using machine learning

Regulatory networks containing enhancer-gene edges define cellular states. Multiple efforts have revealed these networks for reference tissues and cell lines by integrating multi-omics data. However, the methods developed cannot be applied for large patient cohorts due to the infeasibility of chromatin immunoprecipitation sequencing (ChIP-seq) for limited biopsy material. We trained machine-learning models using chromatin interaction analysis with paired-end tag sequencing (ChIA-PET) and high-throughput chromosome conformation capture combined with chromatin immunoprecipitation (HiChIP) data that can predict connections using only assay for transposase-accessible chromatin using sequencing (ATAC-seq) and RNA-seq data as input, which can be generated from biopsies. Our method overcomes limitations of correlation-based approaches that cannot distinguish between distinct target genes of given enhancers or between active vs. poised states in different samples, a hallmark of network rewiring in cancer. Application of our model on 371 samples across 22 cancer types revealed 1,780 enhancer-gene connections for 602 cancer genes. Using CRISPR interference (CRISPRi), we validated enhancers predicted to regulate ESR1 in estrogen receptor (ER)+ breast cancer and A1CF in liver hepatocellular carcinoma.

Identification of mammalian transcription factors that bind to inaccessible chromatin

Transcription factors (TFs) are proteins that affect gene expression by binding to regulatory regions of DNA in a sequence specific manner. The binding of TFs to DNA is controlled by many factors, including the DNA sequence, concentration of TF, chromatin accessibility and co-factors. Here, we systematically investigated the binding mechanism of hundreds of TFs by analysing ChIP-seq data with our explainable statistical model, ChIPanalyser. This tool uses as inputs the DNA sequence binding motif; the capacity to distinguish between strong and weak binding sites; the concentration of TF; and chromatin accessibility. We found that approximately one third of TFs are predicted to bind the genome in a DNA accessibility independent fashion, which includes TFs that can open the chromatin, their co-factors and TFs with similar motifs. Our model predicted this to be the case when the TF binds to its strongest binding regions in the genome, and only a small number of TFs have the capacity to bind dense chromatin at their weakest binding regions, such as CTCF, USF2 and CEBPB. Our study demonstrated that the binding of hundreds of human and mouse TFs is predicted by ChIPanalyser with high accuracy and showed that many TFs can bind dense chromatin.

FoxM1 coordinates cell division, protein synthesis, and mitochondrial activity in a subset of β cells during acute metabolic stress

Pancreatic β cells display functional and transcriptional heterogeneity in health and disease. The sequence of events leading to β cell heterogeneity during metabolic stress is poorly understood. Here, we characterize β cell responses to early metabolic stress in vivo by employing RNA sequencing (RNA-seq), assay for transposase-accessible chromatin with sequencing (ATAC-seq), single-cell RNA-seq (scRNA-seq), chromatin immunoprecipitation sequencing (ChIP-seq), and real-time imaging to decipher temporal events of chromatin remodeling and gene expression regulating the unfolded protein response (UPR), protein synthesis, mitochondrial function, and cell-cycle progression. We demonstrate that a subpopulation of β cells with active UPR, decreased protein synthesis, and insulin secretary capacities is more susceptible to proliferation after insulin depletion. Alleviation of endoplasmic reticulum (ER) stress precedes the progression of the cell cycle and mitosis and ensures appropriate insulin synthesis. Furthermore, metabolic stress rapidly activates key transcription factors including FoxM1, which impacts on proliferative and quiescent β cells by regulating protein synthesis, ER stress, and mitochondrial activity via direct repression of mitochondrial-encoded genes.

Leveraging epigenomes and three-dimensional genome organization for interpreting regulatory variation

Understanding the impact of regulatory variants on complex phenotypes is a significant challenge because the genes and pathways that are targeted by such variants and the cell type context in which regulatory variants operate are typically unknown. Cell-type-specific long-range regulatory interactions that occur between a distal regulatory sequence and a gene offer a powerful framework for examining the impact of regulatory variants on complex phenotypes. However, high-resolution maps of such long-range interactions are available only for a handful of cell types. Furthermore, identifying specific gene subnetworks or pathways that are targeted by a set of variants is a significant challenge. We have developed L-HiC-Reg, a Random Forests regression method to predict high-resolution contact counts in new cell types, and a network-based framework to identify candidate cell-type-specific gene networks targeted by a set of variants from a genome-wide association study (GWAS). We applied our approach to predict interactions in 55 Roadmap Epigenomics Mapping Consortium cell types, which we used to interpret regulatory single nucleotide polymorphisms (SNPs) in the NHGRI-EBI GWAS catalogue. Using our approach, we performed an in-depth characterization of fifteen different phenotypes including schizophrenia, coronary artery disease (CAD) and Crohn's disease. We found differentially wired subnetworks consisting of known as well as novel gene targets of regulatory SNPs. Taken together, our compendium of interactions and the associated network-based analysis pipeline leverages long-range regulatory interactions to examine the context-specific impact of regulatory variation in complex phenotypes.

AP-1 is a regulatory transcription factor of inflammaging in the murine kidney and liver

Aging is characterized by chronic low-grade inflammation in multiple tissues, also termed "inflammaging", which represents a significant risk factor for many aging-related chronic diseases. However, the mechanisms and regulatory networks underlying inflammaging across different tissues have not yet been fully elucidated. Here, we profiled the transcriptomes and epigenomes of the kidney and liver from young and aged mice and found that activation of the inflammatory response is a conserved signature in both tissues. Moreover, we revealed links between transcriptome changes and chromatin dynamics through integrative analysis and identified AP-1 and ETS family transcription factors (TFs) as potential regulators of inflammaging. Further in situ validation showed that c-JUN (a member of the AP-1 family) was mainly activated in aged renal and hepatic cells, while increased SPI1 (a member of the ETS family) was mostly induced by elevated infiltration of macrophages, indicating that these TFs have different mechanisms in inflammaging. Functional data demonstrated that genetic knockdown of Fos, a major member of the AP-1 family, significantly attenuated the inflammatory response in aged kidneys and livers. Taken together, our results revealed conserved signatures and regulatory TFs of inflammaging in the kidney and liver, providing novel targets for the development of anti-aging interventions.

Inference of cell type-specific gene regulatory networks on cell lineages from single cell omic datasets

Cell type-specific gene expression patterns are outputs of transcriptional gene regulatory networks (GRNs) that connect transcription factors and signaling proteins to target genes. Single-cell technologies such as single cell RNA-sequencing (scRNA-seq) and single cell Assay for Transposase-Accessible Chromatin using sequencing (scATAC-seq), can examine cell-type specific gene regulation at unprecedented detail. However, current approaches to infer cell type-specific GRNs are limited in their ability to integrate scRNA-seq and scATAC-seq measurements and to model network dynamics on a cell lineage. To address this challenge, we have developed single-cell Multi-Task Network Inference (scMTNI), a multi-task learning framework to infer the GRN for each cell type on a lineage from scRNA-seq and scATAC-seq data. Using simulated and real datasets, we show that scMTNI is a broadly applicable framework for linear and branching lineages that accurately infers GRN dynamics and identifies key regulators of fate transitions for diverse processes such as cellular reprogramming and differentiation.

PGE2 alters chromatin through H2A.Z-variant enhancer nucleosome modification to promote hematopoietic stem cell fate

Prostaglandin E2 (PGE2) and 16,16-dimethyl-PGE2 (dmPGE2) are important regulators of hematopoietic stem and progenitor cell (HSPC) fate and offer potential to enhance stem cell therapies [C. Cutler et al. Blood 122, 3074-3081(2013); W. Goessling et al. Cell Stem Cell 8, 445-458 (2011); W. Goessling et al. Cell 136, 1136-1147 (2009)]. Here, we report that PGE2-induced changes in chromatin at enhancer regions through histone-variant H2A.Z permit acute inflammatory gene induction to promote HSPC fate. We found that dmPGE2-inducible enhancers retain MNase-accessible, H2A.Z-variant nucleosomes permissive of CREB transcription factor (TF) binding. CREB binding to enhancer nucleosomes following dmPGE2 stimulation is concomitant with deposition of histone acetyltransferases p300 and Tip60 on chromatin. Subsequent H2A.Z acetylation improves chromatin accessibility at stimuli-responsive enhancers. Our findings support a model where histone-variant nucleosomes retained within inducible enhancers facilitate TF binding. Histone-variant acetylation by TF-associated nucleosome remodelers creates the accessible nucleosome landscape required for immediate enhancer activation and gene induction. Our work provides a mechanism through which inflammatory mediators, such as dmPGE2, lead to acute transcriptional changes and modify HSPC behavior to improve stem cell transplantation.

Transcriptional activation of Jun and Fos members of the AP-1 complex is a conserved signature of immune aging that contributes to inflammaging

Diverse mouse strains have different health and life spans, mimicking the diversity among humans. To capture conserved aging signatures, we studied long-lived C57BL/6J and short-lived NZO/HILtJ mouse strains by profiling transcriptomes and epigenomes of immune cells from peripheral blood and the spleen from young and old mice. Transcriptional activation of the AP-1 transcription factor complex, particularly Fos, Junb, and Jun genes, was the most significant and conserved aging signature across tissues and strains. ATAC-seq data analyses showed that the chromatin around these genes was more accessible with age and there were significantly more binding sites for these TFs with age across all studied tissues, targeting pro-inflammatory molecules including Il6. Age-related increases in binding sites of JUN and FOS factors were also conserved in human peripheral blood ATAC-seq data. Single-cell RNA-seq data from the mouse aging cell atlas Tabula Muris Senis showed that the expression of these genes increased with age in B, T, NK cells, and macrophages, with macrophages from old mice expressing these molecules more abundantly than other cells. Functional data showed that upon myeloid cell activation via poly(I:C), the levels of JUN protein and its binding activity increased more significantly in spleen cells from old compared to young mice. In addition, upon activation, old cells produced more IL6 compared to young cells. In sum, we showed that the aging-related transcriptional activation of Jun and Fos family members in AP-1 complex is conserved across immune tissues and long- and short-living mouse strains, possibly contributing to increased inflammation with age.

Identifying strengths and weaknesses of methods for computational network inference from single-cell RNA-seq data

Single-cell RNA-sequencing (scRNA-seq) offers unparalleled insight into the transcriptional programs of different cellular states by measuring the transcriptome of thousands of individual cells. An emerging problem in the analysis of scRNA-seq is the inference of transcriptional gene regulatory networks and a number of methods with different learning frameworks have been developed to address this problem. Here, we present an expanded benchmarking study of eleven recent network inference methods on seven published scRNA-seq datasets in human, mouse, and yeast considering different types of gold standard networks and evaluation metrics. We evaluate methods based on their computing requirements as well as on their ability to recover the network structure. We find that, while most methods have a modest recovery of experimentally derived interactions based on global metrics such as Area Under the Precision Recall curve, methods are able to capture targets of regulators that are relevant to the system under study. Among the top performing methods that use only expression were SCENIC, PIDC, MERLIN or Correlation. Addition of prior biological knowledge and the estimation of transcription factor activities resulted in the best overall performance with the Inferelator and MERLIN methods that use prior knowledge outperforming methods that use expression alone. We found that imputation for network inference did not improve network inference accuracy and could be detrimental. Comparisons of inferred networks for comparable bulk conditions showed that the networks inferred from scRNA-seq datasets are often better or at par with the networks inferred from bulk datasets. Our analysis should be beneficial in selecting methods for network inference. At the same time, this highlights the need for improved methods and better gold standards for regulatory network inference from scRNAseq datasets.

Strand Asymmetries Across Genomic Processes

Across biological systems, a number of genomic processes, including transcription, replication, DNA repair, and transcription factor binding, display intrinsic directionalities. These directionalities are reflected in the asymmetric distribution of nucleotides, motifs, genes, transposon integration sites, and other functional elements across the two complementary strands. Strand asymmetries, including GC skews and mutational biases, have shaped the nucleotide composition of diverse organisms. The investigation of strand asymmetries often serves as a method to understand underlying biological mechanisms, including protein binding preferences, transcription factor interactions, retrotransposition, DNA damage and repair preferences, transcription-replication collisions, and mutagenesis mechanisms. Research into this subject also enables the identification of functional genomic sites, such as replication origins and transcription start sites. Improvements in our ability to detect and quantify DNA strand asymmetries will provide insights into diverse functionalities of the genome, the contribution of different mutational mechanisms in germline and somatic mutagenesis, and our knowledge of genome instability and evolution, which all have significant clinical implications in human disease, including cancer. In this review, we describe key developments that have been made across the field of genomic strand asymmetries, as well as the discovery of associated mechanisms.

Proteomic profiling reveals distinct phases to the restoration of chromatin following DNA replication

Chromatin organization must be maintained during cell proliferation to preserve cellular identity and genome integrity. However, DNA replication results in transient displacement of DNA-bound proteins, and it is unclear how they regain access to newly replicated DNA. Using quantitative proteomics coupled to Nascent Chromatin Capture or isolation of Proteins on Nascent DNA, we provide time-resolved binding kinetics for thousands of proteins behind replisomes within euchromatin and heterochromatin in human cells. This shows that most proteins regain access within minutes to newly replicated DNA. In contrast, 25% of the identified proteins do not, and this delay cannot be inferred from their known function or nuclear abundance. Instead, chromatin organization and G1 phase entry affect their reassociation. Finally, DNA replication not only disrupts but also promotes recruitment of transcription factors and chromatin remodelers, providing a significant advance in understanding how DNA replication could contribute to programmed changes of cell memory.

Multi-scale gene regulation mechanism: Spatiotemporal transmission of genetic information

Gene expression is regulated by many factors, including transcription factors, chromatin three-dimensional topology, modifications of DNA and histone proteins, and non-coding RNAs. The execution of these complex mechanisms requires an effectively coordinated regulation system. In this review, we emphasize that the multi-scale heterogeneous DNA sequence plays a fundamental and important role for gene expression activity and usage of different means of epigenetic regulation. We illustrate here that the chromatin structure organization provides a stage for spatiotemporal regulation between different genes or gene modules and to realize their downstream functional cooperation. Such a perspective expands our understanding of the central dogma: In addition to one-dimensional sequence information, inter-gene interactions can also be transferred from DNA and RNA to protein levels.

Chromatin accessibility: methods, mechanisms, and biological insights

Access to DNA is a prerequisite to the execution of essential cellular processes that include transcription, replication, chromosomal segregation, and DNA repair. How the proteins that regulate these processes function in the context of chromatin and its dynamic architectures is an intensive field of study. Over the past decade, genome-wide assays and new imaging approaches have enabled a greater understanding of how access to the genome is regulated by nucleosomes and associated proteins. Additional mechanisms that may control DNA accessibility in vivo include chromatin compaction and phase separation - processes that are beginning to be understood. Here, we review the ongoing development of accessibility measurements, we summarize the different molecular and structural mechanisms that shape the accessibility landscape, and we detail the many important biological functions that are linked to chromatin accessibility.

Sequence-Specific Structural Features and Solvation Properties of Transcription Factor Binding DNA Motifs: Insights from Molecular Dynamics Simulation

Sequence-specific recognition of transcription factor (TF) binding motifs in the target site of DNA over the vast amount of non-target DNA is of primary importance for the transcriptional regulation of gene expression by the TFs. Binding of TFs to the target site of DNA relies not only on the direct contact formation but also on the structural and conformational features of DNA. Recognition of DNA structural features or shape readout by proteins is an important factor in the context of TF-DNA interaction. Based on the atomistic molecular simulation, here we report the sequence-dependent unique structural features, solvation, and ion-binding properties of biologically relevant AT- and GC-rich human TF binding motifs in DNA. Counterion and water distribution around the motif is found to be sensitive to the motif sequence, which is accompanied with the DNA shape features. The motif sequence affects the electrostatic potential along the grooves, and cytosine methylation alters the DNA shape features. Characteristic solvation properties of TF binding motif DNA fragments infer that an ionic environment and hydration influences are essential to describe TF-DNA interactions.

Temporal change in chromatin accessibility predicts regulators of nodulation in Medicago truncatula

Background

Symbiotic associations between bacteria and leguminous plants lead to the formation of root nodules that fix nitrogen needed for sustainable agricultural systems. Symbiosis triggers extensive genome and transcriptome remodeling in the plant, yet an integrated understanding of the extent of chromatin changes and transcriptional networks that functionally regulate gene expression associated with symbiosis remains poorly understood. In particular, analyses of early temporal events driving this symbiosis have only captured correlative relationships between regulators and targets at mRNA level. Here, we characterize changes in transcriptome and chromatin accessibility in the model legume Medicago truncatula, in response to rhizobial signals that trigger the formation of root nodules.

Results

We profiled the temporal chromatin accessibility (ATAC-seq) and transcriptome (RNA-seq) dynamics of M. truncatula roots treated with bacterial small molecules called lipo-chitooligosaccharides that trigger host symbiotic pathways of nodule development. Using a novel approach, dynamic regulatory module networks, we integrated ATAC-seq and RNA-seq time courses to predict cis-regulatory elements and transcription factors that most significantly contribute to transcriptomic changes associated with symbiosis. Regulators involved in auxin (IAA4-5, SHY2), ethylene (EIN3, ERF1), and abscisic acid (ABI5) hormone response, as well as histone and DNA methylation (IBM1), emerged among those most predictive of transcriptome dynamics. RNAi-based knockdown of EIN3 and ERF1 reduced nodule number in M. truncatula validating the role of these predicted regulators in symbiosis between legumes and rhizobia.

Conclusions

Our transcriptomic and chromatin accessibility datasets provide a valuable resource to understand the gene regulatory programs controlling the early stages of the dynamic process of symbiosis. The regulators identified provide potential targets for future experimental validation, and the engineering of nodulation in species is unable to establish that symbiosis naturally.

Comparative functional genomics identifies unique molecular features of EPSCs

The authors provide a comprehensive resource on proteomics, transcriptomic, and epigenetic level details of EPSCs to shed light on possible molecular pathways regulating their expanded pluripotency potential.

Extended pluripotent or expanded potential stem cells (EPSCs) possess superior developmental potential to embryonic stem cells (ESCs). However, the molecular underpinning of EPSC maintenance in vitro is not well defined. We comparatively studied transcriptome, chromatin accessibility, active histone modification marks, and relative proteomes of ESCs and the two well-established EPSC lines to probe the molecular foundation underlying EPSC developmental potential. Despite some overlapping transcriptomic and chromatin accessibility features, we defined sets of molecular signatures that distinguish EPSCs from ESCs in transcriptional and translational regulation as well as metabolic control. Interestingly, EPSCs show similar reliance on pluripotency factors Oct4, Sox2, and Nanog for self-renewal as ESCs. Our study provides a rich resource for dissecting the regulatory network that governs the developmental potency of EPSCs and exploring alternative strategies to capture totipotent stem cells in culture.

Sex Differences in the Molecular Programs of Pancreatic Cells Contribute to the Differential Risks of Type 2 Diabetes

Epidemiology studies demonstrate that women are at a significantly lower risk of developing type 2 diabetes (T2D) compared to men. However, the molecular basis of this risk difference is not well understood. In this study, we examined the sex differences in the genetic programs of pancreatic endocrine cells. We combined pancreas perifusion data and single-cell genomic data from our laboratory and from publicly available data sets to investigate multiple axes of the sex differences in the human pancreas at the single-cell type and single-cell level. We systematically compared female and male islet secretion function, gene expression program, and regulatory principles of pancreatic endocrine cells. The perifusion data indicate that female endocrine cells have a higher secretion capacity than male endocrine cells. Single-cell RNA-sequencing analysis suggests that endocrine cells in male controls have molecular signatures that resemble T2D. In addition, we identified genomic elements associated with genome-wide association study T2D loci to have differential accessibility between female and male delta cells. These genomic elements may play a sex-specific causal role in the pathogenesis of T2D. We provide molecular mechanisms that explain the differential risk of T2D between women and men. Knowledge gained from our study will accelerate the development of diagnostics and therapeutics in sex-aware precision medicine for diabetes.

Prenatal immune stress blunts microglia reactivity, impairing neurocircuitry

Recent studies suggested that microglia, the primary brain immune cells, can affect circuit connectivity and neuronal function1,2. Microglia infiltrate the neuroepithelium early in embryonic development and are maintained in the brain throughout adulthood3,4. Several maternal environmental factors-such as an aberrant microbiome, immune activation and poor nutrition-can influence prenatal brain development5,6. Nevertheless, it is unknown how changes in the prenatal environment instruct the developmental trajectory of infiltrating microglia, which in turn affect brain development and function. Here we show that, after maternal immune activation (MIA) in mice, microglia from the offspring have a long-lived decrease in immune reactivity (blunting) across the developmental trajectory. The blunted immune response was accompanied by changes in chromatin accessibility and reduced transcription factor occupancy of the open chromatin. Single-cell RNA-sequencing analysis revealed that MIA does not induce a distinct subpopulation but, rather, decreases the contribution to inflammatory microglia states. Prenatal replacement of microglia from MIA offspring with physiological infiltration of naive microglia ameliorated the immune blunting and restored a decrease in presynaptic vesicle release probability onto dopamine receptor type-two medium spiny neurons, indicating that aberrantly formed microglia due to an adverse prenatal environment affect the long-term microglia reactivity and proper striatal circuit development.

Intrinsic bias estimation for improved analysis of bulk and single-cell chromatin accessibility profiles using SELMA

Genome-wide profiling of chromatin accessibility by DNase-seq or ATAC-seq has been widely used to identify regulatory DNA elements and transcription factor binding sites. However, enzymatic DNA cleavage exhibits intrinsic sequence biases that confound chromatin accessibility profiling data analysis. Existing computational tools are limited in their ability to account for such intrinsic biases and not designed for analyzing single-cell data. Here, we present Simplex Encoded Linear Model for Accessible Chromatin (SELMA), a computational method for systematic estimation of intrinsic cleavage biases from genomic chromatin accessibility profiling data. We demonstrate that SELMA yields accurate and robust bias estimation from both bulk and single-cell DNase-seq and ATAC-seq data. SELMA can utilize internal mitochondrial DNA data to improve bias estimation. We show that transcription factor binding inference from DNase footprints can be improved by incorporating estimated biases using SELMA. Furthermore, we show strong effects of intrinsic biases in single-cell ATAC-seq data, and develop the first single-cell ATAC-seq intrinsic bias correction model to improve cell clustering. SELMA can enhance the performance of existing bioinformatics tools and improve the analysis of both bulk and single-cell chromatin accessibility sequencing data.

Genome-wide profiling of chromatin accessibility by DNase-seq or ATAC-seq has been widely used to identify regulatory DNA elements and transcription factor binding sites. Here the authors develop a computational model, SELMA, to estimate and correct enzymatic cleavage biases in chromatin accessibility profiling data.

LEAFY COTYLEDONs: Connecting different stages of plant development

The life of higher plants progresses successively through embryonic, juvenile, adult, and reproductive stages. LEAFY COTYLEDON (LEC) transcription factors, first discovered in Arabidopsis thaliana several decades ago, play a key role in regulating plant embryonic development, seed maturation, and subsequent growth. Existing studies have demonstrated that LECs together with other transcription factors form a huge and complex regulatory network to regulate many aspects of plant growth and development and respond to environmental stresses. Here, we focus on the role that has received little attention about the LECs linking different developmental stages and generational cycles in plants. We summarize the current fragmented research progress on the LECs role and molecular mechanism in connecting embryonic and vegetative growth periods and the reproductive stage. Furthermore, the possibility of LECs controlling the maintenance and transition of plant growth stages through epigenetic modifications is discussed.

dbEmbryo multi-omics database for analyses of synergistic regulation in early mammalian embryo development

During early mammalian embryo development, different epigenetic marks undergo reprogramming and play crucial roles in the mediation of gene expression. Currently, several databases provide multi-omics information on early embryos. However, how interconnected epigenetic markers function together to coordinate the expression of the genetic code in a spatiotemporal manner remains difficult to analyze, markedly limiting scientific and clinical research. Here, we present dbEmbryo, an integrated and interactive multi-omics database for human and mouse early embryos. dbEmbryo integrates data on gene expression, DNA methylation, histone modifications, chromatin accessibility, and higher-order chromatin structure profiles for human and mouse early embryos. It incorporates customized analysis tools, such as "multi-omics visualization," "Gene&Peak annotation," "ZGA gene cluster," "cis-regulation," "synergistic regulation," "promoter signal enrichment," and "3D genome." Users can retrieve gene expression and epigenetic profile patterns to analyze synergistic changes across different early embryo developmental stages. We showed the uniqueness of dbEmbryo among extant databases containing data on early embryo development and provided an overview. Using dbEmbryo, we obtained a phase-separated model of transcriptional control during early embryo development. dbEmbryo offers web-based analytical tools and a comprehensive resource for biologists and clinicians to decipher molecular regulatory mechanisms of human and mouse early embryo development.

Etv2 regulates enhancer chromatin status to initiate Shh expression in the limb bud

Sonic hedgehog (Shh) is essential for limb development, and the mechanisms that govern the propagation and maintenance of its expression has been well studied; however, the mechanisms that govern the initiation of Shh expression are incomplete. Here we report that ETV2 initiates Shh expression by changing the chromatin status of the developmental limb enhancer, ZRS. Etv2 expression precedes Shh in limb buds, and Etv2 inactivation prevents the opening of limb chromatin, including the ZRS, resulting in an absence of Shh expression. Etv2 overexpression in limb buds causes nucleosomal displacement at the ZRS, ectopic Shh expression, and polydactyly. Areas of nucleosome displacement coincide with ETS binding site clusters. ETV2 also functions as a transcriptional activator of ZRS and is antagonized by ETV4/5 repressors. Known human polydactyl mutations introduce novel ETV2 binding sites in the ZRS, suggesting that ETV2 dosage regulates ZRS activation. These studies identify ETV2 as a pioneer transcription factor (TF) regulating the onset of Shh expression, having both a chromatin regulatory role and a transcriptional activation role.

The embryonic limb bud is known to be patterned by a Shh morphogen gradient, though how Shh expression is activated remains less clear. Here the authors show that Etv2 acts as a pioneer transcription factor to mediate accessibility of the ZRS enhancer and initiate Shh expression.

Generating specificity in genome regulation through transcription factor sensitivity to chromatin

Cell type-specific gene expression relies on transcription factors (TFs) binding DNA sequence motifs embedded in chromatin. Understanding how motifs are accessed in chromatin is crucial to comprehend differential transcriptional responses and the phenotypic impact of sequence variation. Chromatin obstacles to TF binding range from DNA methylation to restriction of DNA access by nucleosomes depending on their position, composition and modification. In vivo and in vitro approaches now enable the study of TF binding in chromatin at unprecedented resolution. Emerging insights suggest that TFs vary in their ability to navigate chromatin states. However, it remains challenging to link binding and transcriptional outcomes to molecular characteristics of TFs or the local chromatin substrate. Here, we discuss our current understanding of how TFs access DNA in chromatin and novel techniques and directions towards a better understanding of this critical step in genome regulation.

Dynamic regulatory module networks for inference of cell type-specific transcriptional networks

Changes in transcriptional regulatory networks can significantly alter cell fate. To gain insight into transcriptional dynamics, several studies have profiled bulk multi-omic data sets with parallel transcriptomic and epigenomic measurements at different stages of a developmental process. However, integrating these data to infer cell type-specific regulatory networks is a major challenge. We present dynamic regulatory module networks (DRMNs), a novel approach to infer cell type-specific cis-regulatory networks and their dynamics. DRMN integrates expression, chromatin state, and accessibility to predict cis-regulators of context-specific expression, where context can be cell type, developmental stage, or time point, and uses multitask learning to capture network dynamics across linearly and hierarchically related contexts. We applied DRMNs to study regulatory network dynamics in three developmental processes, each showing different temporal relationships and measuring a different combination of regulatory genomic data sets: cellular reprogramming, liver dedifferentiation, and forward differentiation. DRMN identified known and novel regulators driving cell type-specific expression patterns, showing its broad applicability to examine dynamics of gene regulatory networks from linearly and hierarchically related multi-omic data sets.

Kinetic principles underlying pioneer function of GAGA transcription factor in live cells

How pioneer factors interface with chromatin to promote accessibility for transcription control is poorly understood in vivo. Here, we directly visualize chromatin association by the prototypical GAGA pioneer factor (GAF) in live Drosophila hemocytes. Single-particle tracking reveals that most GAF is chromatin bound, with a stable-binding fraction showing nucleosome-like confinement residing on chromatin for more than 2 min, far longer than the dynamic range of most transcription factors. These kinetic properties require the full complement of GAF's DNA-binding, multimerization and intrinsically disordered domains, and are autonomous from recruited chromatin remodelers NURF and PBAP, whose activities primarily benefit GAF's neighbors such as Heat Shock Factor. Evaluation of GAF kinetics together with its endogenous abundance indicates that, despite on-off dynamics, GAF constitutively and fully occupies major chromatin targets, thereby providing a temporal mechanism that sustains open chromatin for transcriptional responses to homeostatic, environmental and developmental signals.

Peptide fusion improves prime editing efficiency

Prime editing enables search-and-replace genome editing but is limited by low editing efficiency. We present a high-throughput approach, the Peptide Self-Editing sequencing assay (PepSEq), to measure how fusion of 12,000 85-amino acid peptides influences prime editing efficiency. We show that peptide fusion can enhance prime editing, prime-enhancing peptides combine productively, and a top dual peptide-prime editor increases prime editing significantly in multiple cell lines across dozens of target sites. Top prime-enhancing peptides function by increasing translation efficiency and serve as broadly useful tools to improve prime editing efficiency.

Integrative epigenomic and transcriptomic analysis reveals the requirement of JUNB for hematopoietic fate induction

Human pluripotent stem cell differentiation towards hematopoietic progenitor cell can serve as an in vitro model for human embryonic hematopoiesis, but the dynamic change of epigenome and transcriptome remains elusive. Here, we systematically profile the chromatin accessibility, H3K4me3 and H3K27me3 modifications, and the transcriptome of intermediate progenitors during hematopoietic progenitor cell differentiation in vitro. The integrative analyses reveal sequential opening-up of regions for the binding of hematopoietic transcription factors and stepwise epigenetic reprogramming of bivalent genes. Single-cell analysis of cells undergoing the endothelial-to-hematopoietic transition and comparison with in vivo hemogenic endothelial cells reveal important features of in vitro and in vivo hematopoiesis. We find that JUNB is an essential regulator for hemogenic endothelium specialization and endothelial-to-hematopoietic transition. These studies depict an epigenomic roadmap from human pluripotent stem cells to hematopoietic progenitor cells, which may pave the way to generate hematopoietic progenitor cells with improved developmental potentials.

Profiling the quantitative occupancy of myriad transcription factors across conditions by modeling chromatin accessibility data

Over a thousand different transcription factors (TFs) bind with varying occupancy across the human genome. Chromatin immunoprecipitation (ChIP) can assay occupancy genome-wide, but only one TF at a time, limiting our ability to comprehensively observe the TF occupancy landscape, let alone quantify how it changes across conditions. We developed TF occupancy profiler (TOP), a Bayesian hierarchical regression framework, to profile genome-wide quantitative occupancy of numerous TFs using data from a single chromatin accessibility experiment (DNase- or ATAC-seq). TOP is supervised, and its hierarchical structure allows it to predict the occupancy of any sequence-specific TF, even those never assayed with ChIP. We used TOP to profile the quantitative occupancy of hundreds of sequence-specific TFs at sites throughout the genome and examined how their occupancies changed in multiple contexts: in approximately 200 human cell types, through 12 h of exposure to different hormones, and across the genetic backgrounds of 70 individuals. TOP enables cost-effective exploration of quantitative changes in the landscape of TF binding.

3DCoop: An approach for computational inference of cell-type-specific transcriptional regulators cooperation in 3D chromatin

Precise identification of context-specific transcriptional regulators (TRs) cooperation facilitates the understanding of complex gene regulation. However, previous methods are highly reliant on the availability of ChIPped TRs. Here, we provide a protocol for running 3DCoop, a pipeline for computational inference of cell type-specific TR cooperation in 3D chromatin by integrating TR motifs, open chromatin profiles, gene expression, and chromatin loops. 3DCoop provides a feasible solution to study the potential interplay among TRs across multiple human or mouse tissue/cell types.

For complete details on the use and execution of this protocol, please refer to Yi et al. (2021).

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Inference of transcriptional regulator (TR) cooperation in 3D chromatin

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Integration of TR motifs, open chromatin, gene expression, and chromatin loops

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Identification of context-specific TR cooperation not relying on ChIPped factors

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3DCoop facilitates TR cooperation study across multiple human/mouse cell types

TFAP2 paralogs facilitate chromatin access for MITF at pigmentation and cell proliferation genes

In developing melanocytes and in melanoma cells, multiple paralogs of the Activating-enhancer-binding Protein 2 family of transcription factors (TFAP2) contribute to expression of genes encoding pigmentation regulators, but their interaction with Microphthalmia transcription factor (MITF), a master regulator of these cells, is unclear. Supporting the model that TFAP2 facilitates MITF's ability to activate expression of pigmentation genes, single-cell seq analysis of zebrafish embryos revealed that pigmentation genes are only expressed in the subset of mitfa-expressing cells that also express tfap2 paralogs. To test this model in SK-MEL-28 melanoma cells we deleted the two TFAP2 paralogs with highest expression, TFAP2A and TFAP2C, creating TFAP2 knockout (TFAP2-KO) cells. We then assessed gene expression, chromatin accessibility, binding of TFAP2A and of MITF, and the chromatin marks H3K27Ac and H3K27Me3 which are characteristic of active enhancers and silenced chromatin, respectively. Integrated analyses of these datasets indicate TFAP2 paralogs directly activate enhancers near genes enriched for roles in pigmentation and proliferation, and directly repress enhancers near genes enriched for roles in cell adhesion. Consistently, compared to WT cells, TFAP2-KO cells proliferate less and adhere to one another more. TFAP2 paralogs and MITF co-operatively activate a subset of enhancers, with the former necessary for MITF binding and chromatin accessibility. By contrast, TFAP2 paralogs and MITF do not appear to co-operatively inhibit enhancers. These studies reveal a mechanism by which TFAP2 profoundly influences the set of genes activated by MITF, and thereby the phenotype of pigment cells and melanoma cells.

Pioneer factors as master regulators of the epigenome and cell fate

Pioneer factors are transcription factors with the unique ability to initiate opening of closed chromatin. The stability of cell identity relies on robust mechanisms that maintain the epigenome and chromatin accessibility to transcription factors. Pioneer factors counter these mechanisms to implement new cell fates through binding of DNA target sites in closed chromatin and introduction of active-chromatin histone modifications, primarily at enhancers. As master regulators of enhancer activation, pioneers are thus crucial for the implementation of correct cell fate decisions in development, and as such, they hold tremendous potential for therapy through cellular reprogramming. The power of pioneer factors to reshape the epigenome also presents an Achilles heel, as their misexpression has major pathological consequences, such as in cancer. In this Review, we discuss the emerging mechanisms of pioneer factor functions and their roles in cell fate specification, cellular reprogramming and cancer.

Deciphering the Retinal Epigenome during Development, Disease and Reprogramming: Advancements, Challenges and Perspectives

Retinal neurogenesis is driven by concerted actions of transcription factors, some of which are expressed in a continuum and across several cell subtypes throughout development. While seemingly redundant, many factors diversify their regulatory outcome on gene expression, by coordinating variations in chromatin landscapes to drive divergent retinal specification programs. Recent studies have furthered the understanding of the epigenetic contribution to the progression of age-related macular degeneration, a leading cause of blindness in the elderly. The knowledge of the epigenomic mechanisms that control the acquisition and stabilization of retinal cell fates and are evoked upon damage, holds the potential for the treatment of retinal degeneration. Herein, this review presents the state-of-the-art approaches to investigate the retinal epigenome during development, disease, and reprogramming. A pipeline is then reviewed to functionally interrogate the epigenetic and transcriptional networks underlying cell fate specification, relying on a truly unbiased screening of open chromatin states. The related work proposes an inferential model to identify gene regulatory networks, features the first footprinting analysis and the first tentative, systematic query of candidate pioneer factors in the retina ever conducted in any model organism, leading to the identification of previously uncharacterized master regulators of retinal cell identity, such as the nuclear factor I, NFI. This pipeline is virtually applicable to the study of genetic programs and candidate pioneer factors in any developmental context. Finally, challenges and limitations intrinsic to the current next-generation sequencing techniques are discussed, as well as recent advances in super-resolution imaging, enabling spatio-temporal resolution of the genome.

Epigenetic basis of oncogenic-Kras-mediated epithelial-cellular proliferation and plasticity

Oncogenic Kras induces a hyper-proliferative state that permits cells to progress to neoplasms in diverse epithelial tissues. Depending on the cell of origin, this also involves lineage transformation. Although a multitude of downstream factors have been implicated in these processes, the precise chronology of molecular events controlling them remains elusive. Using mouse models, primary human tissues, and cell lines, we show that, in Kras-mutant alveolar type II cells (AEC2), FOSL1-based AP-1 factor guides the mSWI/SNF complex to increase chromatin accessibility at genomic loci controlling the expression of genes necessary for neoplastic transformation. We identified two orthogonal processes in Kras-mutant distal airway club cells. The first promoted their transdifferentiation into an AEC2-like state through NKX2.1, and the second controlled oncogenic transformation through the AP-1 complex. Our results suggest that neoplasms retain an epigenetic memory of their cell of origin through cell-type-specific transcription factors. Our analysis showed that a cross-tissue-conserved AP-1-dependent chromatin remodeling program regulates carcinogenesis.

Current status and future perspectives on the evolution of cis-regulatory elements in plants

Cis-regulatory elements (CREs) are short stretches (∼5-15 base pairs) of DNA capable of being bound by a transcription factor and influencing the expression of nearby genes. These regions are of great interest to anyone studying the relationship between phenotype and genotype as these sequences often dictate genes' spatio-temporal expression. Indeed, several associative signals between genotype and phenotype are known to lie outside of protein-coding regions. Therefore, a key to understand evolutionary biology requires their characterization in current and future genome assemblies. In this review, we cover some recent examples of how CRE variation contributes to phenotypic evolution, discuss evidence for the selective pressures experienced by non-coding regions of the genome, and consider several studies on accessible chromatin regions in plants and what they can tell us about CREs. Finally, we discuss how current advances in sequencing technologies will improve our knowledge of CRE variation.

Unveiling E2F4, TEAD1 and AP-1 as regulatory transcription factors of the replicative senescence program by multi-omics analysis

Senescence, a stable state of growth arrest, affects many physiological and pathophysiological processes, especially aging. Previous work has indicated that transcription factors (TFs) play a role in regulating senescence. However, a systematic study of regulatory TFs during replicative senescence (RS) using multi-omics analysis is still lacking. Here, we generated time-resolved RNA-seq, reduced representation bisulfite sequencing (RRBS) and ATAC-seq datasets during RS of mouse skin fibroblasts, which demonstrated that an enhanced inflammatory response and reduced proliferative capacity were the main characteristics of RS in both the transcriptome and epigenome. Through integrative analysis and genetic manipulations, we found that transcription factors E2F4, TEAD1 and AP-1 are key regulators of RS. Overexpression of E2f4 improved cellular proliferative capacity, attenuated SA-β-Gal activity and changed RS-associated differentially methylated sites (DMSs). Moreover, knockdown of Tead1 attenuated SA-β-Gal activity and partially altered the RS-associated transcriptome. In addition, knockdown of Atf3, one member of AP-1 superfamily TFs, reduced Cdkn2a (p16) expression in pre-senescent fibroblasts. Taken together, the results of this study identified transcription factors regulating the senescence program through multi-omics analysis, providing potential therapeutic targets for anti-aging.