Identification of regulatory elements from nascent transcription using dREG

Histone H3.3 lysine 9 and 27 control repressive chromatin at cryptic enhancers and bivalent promoters

Histone modifications are associated with distinct transcriptional states, but it is unclear whether they instruct gene expression. To investigate this, we mutate histone H3.3 K9 and K27 residues in mouse embryonic stem cells (mESCs). Here, we find that H3.3K9 is essential for controlling specific distal intergenic regions and for proper H3K27me3 deposition at promoters. The H3.3K9A mutation resulted in decreased H3K9me3 at regions encompassing endogenous retroviruses and induced a gain of H3K27ac and nascent transcription. These changes in the chromatin environment unleash cryptic enhancers, resulting in the activation of distinctive transcriptional programs and culminating in protein expression normally restricted to specialized immune cell types. The H3.3K27A mutant disrupts the deposition and spreading of the repressive H3K27me3 mark, particularly impacting bivalent genes with higher basal levels of H3.3 at promoters. Therefore, H3.3K9 and K27 crucially orchestrate repressive chromatin states at cis-regulatory elements and bivalent promoters, respectively, and instruct proper transcription in mESCs.

Dynamic control of gene expression by ISGF3 and IRF1 during IFNβ and IFNγ signaling

Type I interferons (IFN-I, including IFNβ) and IFNγ produce overlapping, yet clearly distinct immunological activities. Recent data show that the distinctness of global transcriptional responses to the two IFN types is not apparent when comparing their immediate effects. By analyzing nascent transcripts induced by IFN-I or IFNγ over a period of 48 h, we now show that the distinctiveness of the transcriptomes emerges over time and is based on differential employment of the ISGF3 complex as well as of the second-tier transcription factor IRF1. The distinct transcriptional properties of ISGF3 and IRF1 correspond with a largely diverse nuclear protein interactome. Mechanistically, we describe the specific input of ISGF3 and IRF1 into enhancer activation and the regulation of chromatin accessibility at interferon-stimulated genes (ISG). We further report differences between the IFN types in altering RNA polymerase II pausing at ISG 5' ends. Our data provide insight how transcriptional regulators create immunological identities of IFN-I and IFNγ.

ZNF143 binds DNA and stimulates transcripstion initiation to activate and repress direct target genes

Transcription factors bind to sequence motifs and act as activators or repressors. Transcription factors interface with a constellation of accessory cofactors to regulate distinct mechanistic steps to regulate transcription. We rapidly degraded the essential and ubiquitously expressed transcription factor ZNF143 to determine its function in the transcription cycle. ZNF143 facilitates RNA Polymerase initiation and activates gene expression. ZNF143 binds the promoter of nearly all its activated target genes. ZNF143 also binds near the site of genic transcription initiation to directly repress a subset of genes. Although ZNF143 stimulates initiation at ZNF143-repressed genes (i.e. those that increase expression upon ZNF143 depletion), the molecular context of binding leads to cis repression. ZNF143 competes with other more efficient activators for promoter access, physically occludes transcription initiation sites and promoter-proximal sequence elements, and acts as a molecular roadblock to RNA Polymerases during early elongation. The term context specific is often invoked to describe transcription factors that have both activation and repression functions. We define the context and molecular mechanisms of ZNF143-mediated cis activation and repression.

A transcription factor (TF) inference method that broadly measures TF activity and identifies mechanistically distinct TF networks

TF profiler is a method of inferring transcription factor regulatory activity, i.e. when a TF is present and actively regulating transcription, directly directly from nascent sequencing assays such as PRO-seq and GRO-seq. Transcription factors orchestrate transcription and play a critical role in cellular maintenance, identity and response to external stimuli. While ChIP assays have measured DNA localization, they fall short of identifying when and where transcription factors are actively regulating transcription. Our method, on the other hand, uses RNA polymerase activity to infer TF activity across hundreds of data sets and transcription factors. Based on these classifications we identify three distinct classes of transcription factors: ubiquitous factors that play roles in cellular homeostasis, driving basal gene programs across tissues and cell types, tissue specific factors that act almost exclusively at enhancers and are themselves regulated at transcription, and stimulus responsive TFs which are regulated post-transcriptionally but act predominantly at enhancers. TF profiler is broadly applicable, providing regulatory insights on any PRO-seq sample for any transcription factor with a known binding motif.

Mapping catalytically engaged TOP2B in neurons reveals the principles of topoisomerase action within the genome

We trapped catalytically engaged topoisomerase IIβ (TOP2B) in covalent DNA cleavage complexes (TOP2Bccs) and mapped their positions genome-wide in cultured mouse cortical neurons. We report that TOP2Bcc distribution varies with both nucleosome and compartmental chromosome organization. While TOP2Bccs in gene bodies correlate with their level of transcription, highly expressed genes that lack the usually associated chromatin marks, such as H3K36me3, show reduced TOP2Bccs, suggesting that histone posttranslational modifications regulate TOP2B activity. Promoters with high RNA polymerase II occupancy show elevated TOP2B chromatin immunoprecipitation sequencing signals but low TOP2Bccs, indicating that TOP2B catalytic engagement is curtailed at active promoters. Surprisingly, either poisoning or inhibiting TOP2B increases nascent transcription at most genes and enhancers but reduces transcription within long genes. These effects are independent of transcript length and instead correlate with the presence of intragenic enhancers. Together, these results clarify how cells modulate the catalytic engagement of topoisomerases to affect transcription.

TRPS1 modulates chromatin accessibility to regulate estrogen receptor alpha (ER) binding and ER target gene expression in luminal breast cancer cells

Common genetic variants in the repressive GATA-family transcription factor (TF) TRPS1 locus are associated with breast cancer risk, and luminal breast cancer cell lines are particularly sensitive to TRPS1 knockout. We introduced an inducible degron tag into the native TRPS1 locus within a luminal breast cancer cell line to identify the direct targets of TRPS1 and determine how TRPS1 mechanistically regulates gene expression. We acutely deplete over 80 percent of TRPS1 from chromatin within 30 minutes of inducing degradation. We find that TRPS1 regulates transcription of hundreds of genes, including those related to estrogen signaling. TRPS1 directly regulates chromatin structure, which causes estrogen receptor alpha (ER) to redistribute in the genome. ER redistribution leads to both repression and activation of dozens of ER target genes. Downstream from these primary effects, TRPS1 depletion represses cell cycle-related gene sets and reduces cell doubling rate. Finally, we show that high TRPS1 activity, calculated using a gene expression signature defined by primary TRPS1-regulated genes, is associated with worse breast cancer patient prognosis. Taken together, these data suggest a model in which TRPS1 modulates the genomic distribution of ER, both activating and repressing transcription of genes related to cancer cell fitness.

ADH-Enhancer: an attention-based deep hybrid framework for enhancer identification and strength prediction

Enhancers play an important role in the process of gene expression regulation. In DNA sequence abundance or absence of enhancers and irregularities in the strength of enhancers affects gene expression process that leads to the initiation and propagation of diverse types of genetic diseases such as hemophilia, bladder cancer, diabetes and congenital disorders. Enhancer identification and strength prediction through experimental approaches is expensive, time-consuming and error-prone. To accelerate and expedite the research related to enhancers identification and strength prediction, around 19 computational frameworks have been proposed. These frameworks used machine and deep learning methods that take raw DNA sequences and predict enhancer's presence and strength. However, these frameworks still lack in performance and are not useful in real time analysis. This paper presents a novel deep learning framework that uses language modeling strategies for transforming DNA sequences into statistical feature space. It applies transfer learning by training a language model in an unsupervised fashion by predicting a group of nucleotides also known as k-mers based on the context of existing k-mers in a sequence. At the classification stage, it presents a novel classifier that reaps the benefits of two different architectures: convolutional neural network and attention mechanism. The proposed framework is evaluated over the enhancer identification benchmark dataset where it outperforms the existing best-performing framework by 5%, and 9% in terms of accuracy and MCC. Similarly, when evaluated over the enhancer strength prediction benchmark dataset, it outperforms the existing best-performing framework by 4%, and 7% in terms of accuracy and MCC.

Genome-wide identification of transcriptional enhancers during human placental development and association with function, differentiation, and disease†

The placenta is a dynamic organ that must perform a remarkable variety of functions during its relatively short existence in order to support a developing fetus. These functions include nutrient delivery, gas exchange, waste removal, hormone production, and immune barrier protection. Proper placenta development and function are critical for healthy pregnancy outcomes, but the underlying genomic regulatory events that control this process remain largely unknown. We hypothesized that mapping sites of transcriptional enhancer activity and associated changes in gene expression across gestation in human placenta tissue would identify genomic loci and predicted transcription factor activity related to critical placenta functions. We used a suite of genomic assays [i.e., RNA-sequencing (RNA-seq), Precision run-on-sequencing (PRO-seq), and Chromatin immunoprecipitation-sequencing (ChIP-seq)] and computational pipelines to identify a set of >20 000 enhancers that are active at various time points in gestation. Changes in the activity of these enhancers correlate with changes in gene expression. In addition, some of these enhancers encode risk for adverse pregnancy outcomes. We further show that integrating enhancer activity, transcription factor motif analysis, and transcription factor expression can identify distinct sets of transcription factors predicted to be more active either in early pregnancy or at term. Knockdown of selected identified transcription factors in a trophoblast stem cell culture model altered the expression of key placental marker genes. These observations provide a framework for future mechanistic studies of individual enhancer-transcription factor-target gene interactions and have the potential to inform genetic risk prediction for adverse pregnancy outcomes.

Atlas of nascent RNA transcripts reveals enhancer to gene linkages

Gene transcription is controlled and modulated by regulatory regions, including enhancers and promoters. These regions are abundant in unstable, non-coding bidirectional transcription. Using nascent RNA transcription data across hundreds of human samples, we identified over 800,000 regions containing bidirectional transcription. We then identify highly correlated transcription between bidirectional and gene regions. The identified correlated pairs, a bidirectional region and a gene, are enriched for disease associated SNPs and often supported by independent 3D data. We present these resources as an SQL database which serves as a resource for future studies into gene regulation, enhancer associated RNAs, and transcription factors.

The Androgen Receptor Does Not Directly Regulate the Transcription of DNA Damage Response Genes

The clinical success of combined androgen deprivation therapy (ADT) and radiotherapy (RT) in prostate cancer created interest in understanding the mechanistic links between androgen receptor (AR) signaling and the DNA damage response (DDR). Convergent data have led to a model where AR both regulates, and is regulated by, the DDR. Integral to this model is that the AR regulates the transcription of DDR genes both at a steady state and in response to ionizing radiation (IR). In this study, we sought to determine which immediate transcriptional changes are induced by IR in an AR-dependent manner. Using PRO-seq to quantify changes in nascent RNA transcription in response to IR, the AR antagonist enzalutamide, or the combination of the two, we find that enzalutamide treatment significantly decreased expression of canonical AR target genes but had no effect on DDR gene sets in prostate cancer cells. Surprisingly, we also found that the AR is not a primary regulator of DDR genes either in response to IR or at a steady state in asynchronously growing prostate cancer cells.

IMPLICATIONS

Our data indicate that the clinical benefit of combining ADT with RT is not due to direct AR regulation of DDR gene transcription, and that the field needs to consider alternative mechanisms for this clinical benefit.

PRO-seq: Precise Mapping of Engaged RNA Pol II at Single-Nucleotide Resolution

Gene regulation is dependent on the production of mRNAs and a repertoire of non-coding RNAs by RNA polymerase II (RNAPII). Precision run-on sequencing (PRO-seq) maps the position of engaged RNAPII complexes at single-nucleotide resolution and can reveal direct targets of regulation, locations of enhancers, and transcription mechanisms that are difficult or impossible to measure by analysis of total cellular RNA. Briefly, this method first involves permeabilizing cells with mild detergents to remove intracellular NTPs and halt transcription. Transcription is then resumed in the presence of biotin-NTPs and sarkosyl to allow transcriptional incorporation of a single biotinylated NTP by RNAPII. The biotin moiety is then bound to streptavidin beads to stringently enrich for nascent RNAs. Sequencing libraries are then generated such that the first base read corresponds to the 3' end of the nascent transcript. Here, we describe our current protocol for generating PRO-seq libraries from metazoan cells, including adaptations of previously published protocols to incorporate unique molecular identifiers, reduce ligation bias, and improve library yields. Additional commentary describes quality control and processing of PRO-seq data and references for more advanced downstream analysis such as gene and enhancer identification. © 2023 Wiley Periodicals LLC. Basic Protocol 1: Cell permeabilization for PRO-seq Basic Protocol 2: Construction of PRO-seq libraries Support Protocol: Adenylation of 3' adapter.

Global identification of SWI/SNF targets reveals compensation by EP400

Mammalian SWI/SNF chromatin remodeling complexes move and evict nucleosomes at gene promoters and enhancers to modulate DNA access. Although SWI/SNF subunits are commonly mutated in disease, therapeutic options are limited by our inability to predict SWI/SNF gene targets and conflicting studies on functional significance. Here, we leverage a fast-acting inhibitor of SWI/SNF remodeling to elucidate direct targets and effects of SWI/SNF. Blocking SWI/SNF activity causes a rapid and global loss of chromatin accessibility and transcription. Whereas repression persists at most enhancers, we uncover a compensatory role for the EP400/TIP60 remodeler, which reestablishes accessibility at most promoters during prolonged loss of SWI/SNF. Indeed, we observe synthetic lethality between EP400 and SWI/SNF in cancer cell lines and human cancer patient data. Our data define a set of molecular genomic features that accurately predict gene sensitivity to SWI/SNF inhibition in diverse cancer cell lines, thereby improving the therapeutic potential of SWI/SNF inhibitors.

Inhibition of CDK12 elevates cancer cell dependence on P-TEFb by stimulation of RNA polymerase II pause release

P-TEFb and CDK12 facilitate transcriptional elongation by RNA polymerase II. Given the prominence of both kinases in cancer, gaining a better understanding of their interplay could inform the design of novel anti-cancer strategies. While down-regulation of DNA repair genes in CDK12-targeted cancer cells is being explored therapeutically, little is known about mechanisms and significance of transcriptional induction upon inhibition of CDK12. We show that selective targeting of CDK12 in colon cancer-derived cells activates P-TEFb via its release from the inhibitory 7SK snRNP. In turn, P-TEFb stimulates Pol II pause release at thousands of genes, most of which become newly dependent on P-TEFb. Amongst the induced genes are those stimulated by hallmark pathways in cancer, including p53 and NF-κB. Consequently, CDK12-inhibited cancer cells exhibit hypersensitivity to inhibitors of P-TEFb. While blocking P-TEFb triggers their apoptosis in a p53-dependent manner, it impedes cell proliferation irrespective of p53 by preventing induction of genes downstream of the DNA damage-induced NF-κB signaling. In summary, stimulation of Pol II pause release at the signal-responsive genes underlies the functional dependence of CDK12-inhibited cancer cells on P-TEFb. Our study establishes the mechanistic underpinning for combinatorial targeting of CDK12 with either P-TEFb or the induced oncogenic pathways in cancer.

Landscape of enhancer disruption and functional screen in melanoma cells

BACKGROUND

The high mutation rate throughout the entire melanoma genome presents a major challenge in stratifying true driver events from the background mutations. Numerous recurrent non-coding alterations, such as those in enhancers, can shape tumor evolution, thereby emphasizing the importance in systematically deciphering enhancer disruptions in melanoma.

RESULTS

Here, we leveraged 297 melanoma whole-genome sequencing samples to prioritize highly recurrent regions. By performing a genome-scale CRISPR interference (CRISPRi) screen on highly recurrent region-associated enhancers in melanoma cells, we identified 66 significant hits which could have tumor-suppressive roles. These functional enhancers show unique mutational patterns independent of classical significantly mutated genes in melanoma. Target gene analysis for the essential enhancers reveal many known and hidden mechanisms underlying melanoma growth. Utilizing extensive functional validation experiments, we demonstrate that a super enhancer element could modulate melanoma cell proliferation by targeting MEF2A, and another distal enhancer is able to sustain PTEN tumor-suppressive potential via long-range interactions.

CONCLUSIONS

Our study establishes a catalogue of crucial enhancers and their target genes in melanoma growth and progression, and illuminates the identification of novel mechanisms of dysregulation for melanoma driver genes and new therapeutic targeting strategies.

Nascent transcription upon interferon-α2 stimulation on human and rhesus macaque lymphoblastoid cell lines

OBJECTIVES

The interferon-triggered innate immune response has been observed to be under strong diversifying selection to counteract the many pathogens hosts have to defend against. In particular, rewiring of gene transcription regulation allows organisms to rapidly acquire new phenotypes by removing and adding genes into the innate immune gene network. Dissecting the molecular processes by which this rewiring takes place, either by changing the DNA regulatory elements or by changing the activity of the regulators across species, is key to better understand this evolutionary process.

DATA DESCRIPTION

To better comprehend the evolutionary dynamics that have occurred in the initial transcriptional response to interferon in primates, we present Precision Run-On (PRO-seq) datasets made after 1 h of interferon-α2 stimulation on human and rhesus macaque lymphoblastoid cell lines. Further, we tested the difference between using either species' cognate interferon versus using the other orthologous interferon to account for any potential impacts in the interaction of the orthologous interferons with their cellular membrane receptors. This data provides insights into the regulatory mechanisms that drive species-specific responses to environmental perturbations, such as the one driven by the interactions of pathogens and their hosts.

Widespread priming of transcriptional regulatory elements by incipient accessibility or RNA polymerase II pause in early embryos of the sea urchin Strongylocentrotus purpuratus

Transcriptional regulatory elements (TREs) are the primary nodes that control developmental gene regulatory networks. In embryo stages, larvae, and adult differentiated red spherule cells of the sea urchin Strongylocentrotus purpuratus, transcriptionally engaged TREs are detected by Precision Run-On Sequencing (PRO-seq), which maps genome-wide at base pair resolution the location of paused or elongating RNA polymerase II (Pol II). In parallel, TRE accessibility is estimated by the Assay for Transposase-Accessible Chromatin using Sequencing (ATAC-seq). Our analysis identifies surprisingly early and widespread TRE accessibility in 4-cell cleavage embryos that is not necessarily followed by concurrent or subsequent transcription. TRE transcriptional differences identified by PRO-seq provide more contrast among embryonic stages than ATAC-seq accessibility differences, in agreement with the apparent excess of accessible but inactive TREs during embryogenesis. Global TRE accessibility reaches a maximum around the 20-hour late blastula stage, which coincides with the consolidation of major embryo regionalizations and peak histone variant H2A.Z expression. A transcriptional potency model based on labile nucleosome TRE occupancy driven by DNA sequences and the prevalence of histone variants is proposed in order to explain the basal accessibility of transcriptionally inactive TREs during embryogenesis. However, our results would not reconcile well with labile nucleosome models based on simple A/T sequence enrichment. In addition, a large number of distal TREs become transcriptionally disengaged during developmental progression, in support of an early Pol II paused model for developmental gene regulation that eventually resolves in transcriptional activation or silencing. Thus, developmental potency in early embryos may be facilitated by incipient accessibility and transcriptional pause at TREs.

RNA polymerase II dynamics shape enhancer-promoter interactions

How enhancers control target gene expression over long genomic distances remains an important unsolved problem. Here we investigated enhancer-promoter communication by integrating data from nucleosome-resolution genomic contact maps, nascent transcription and perturbations affecting either RNA polymerase II (Pol II) dynamics or the activity of thousands of candidate enhancers. Integration of new Micro-C experiments with published CRISPRi data demonstrated that enhancers spend more time in close proximity to their target promoters in functional enhancer-promoter pairs compared to nonfunctional pairs, which can be attributed in part to factors unrelated to genomic position. Manipulation of the transcription cycle demonstrated a key role for Pol II in enhancer-promoter interactions. Notably, promoter-proximal paused Pol II itself partially stabilized interactions. We propose an updated model in which elements of transcriptional dynamics shape the duration or frequency of interactions to facilitate enhancer-promoter communication.

Decoding enhancer complexity with machine learning and high-throughput discovery

Enhancers are genomic DNA elements controlling spatiotemporal gene expression. Their flexible organization and functional redundancies make deciphering their sequence-function relationships challenging. This article provides an overview of the current understanding of enhancer organization and evolution, with an emphasis on factors that influence these relationships. Technological advancements, particularly in machine learning and synthetic biology, are discussed in light of how they provide new ways to understand this complexity. Exciting opportunities lie ahead as we continue to unravel the intricacies of enhancer function.

A-MYB and BRDT-dependent RNA Polymerase II pause release orchestrates transcriptional regulation in mammalian meiosis

During meiotic prophase I, spermatocytes must balance transcriptional activation with homologous recombination and chromosome synapsis, biological processes requiring extensive changes to chromatin state. We explored the interplay between chromatin accessibility and transcription through prophase I of mammalian meiosis by measuring genome-wide patterns of chromatin accessibility, nascent transcription, and processed mRNA. We find that Pol II is loaded on chromatin and maintained in a paused state early during prophase I. In later stages, paused Pol II is released in a coordinated transcriptional burst mediated by the transcription factors A-MYB and BRDT, resulting in ~3-fold increase in transcription. Transcriptional activity is temporally and spatially segregated from key steps of meiotic recombination: double strand breaks show evidence of chromatin accessibility earlier during prophase I and at distinct loci from those undergoing transcriptional activation, despite shared chromatin marks. Our findings reveal mechanisms underlying chromatin specialization in either transcription or recombination in meiotic cells.

Gene silencing dynamics are modulated by transiently active regulatory elements

Transcriptional enhancers have been extensively characterized, but cis-regulatory elements involved in acute gene repression have received less attention. Transcription factor GATA1 promotes erythroid differentiation by activating and repressing distinct gene sets. Here, we study the mechanism by which GATA1 silences the proliferative gene Kit during murine erythroid cell maturation and define stages from initial loss of activation to heterochromatinization. We find that GATA1 inactivates a potent upstream enhancer but concomitantly creates a discrete intronic regulatory region marked by H3K27ac, short noncoding RNAs, and de novo chromatin looping. This enhancer-like element forms transiently and serves to delay Kit silencing. The element is ultimately erased via the FOG1/NuRD deacetylase complex, as revealed by the study of a disease-associated GATA1 variant. Hence, regulatory sites can be self-limiting by dynamic co-factor usage. Genome-wide analyses across cell types and species uncover transiently active elements at numerous genes during repression, suggesting that modulation of silencing kinetics is widespread.

Reactivation of Epstein-Barr Virus from Latency Involves Increased RNA Polymerase Activity at CTCF Binding Sites on the Viral Genome

The ability of Epstein-Barr virus (EBV) to switch between latent and lytic infection is key to its long-term persistence, yet the molecular mechanisms behind this switch remain unclear. To investigate transcriptional events during the latent-to-lytic switch, we utilized Precision nuclear Run On followed by deep Sequencing (PRO-Seq) to map cellular RNA polymerase (Pol) activity to single-nucleotide resolution on the host and EBV genome in three different models of EBV latency and reactivation. In latently infected Mutu-I Burkitt lymphoma (BL) cells, Pol activity was enriched at the Qp promoter, the EBER region, and the BHLF1/LF3 transcripts. Upon reactivation with phorbol ester and sodium butyrate, early-phase Pol activity occurred bidirectionally at CTCF sites within the LMP-2A, EBER-1, and RPMS1 loci. PRO-Seq analysis of Akata cells reactivated from latency with anti-IgG and a lymphoblastoid cell line (LCL) reactivated with small molecule C60 showed a similar pattern of early bidirectional transcription initiating around CTCF binding sites, although the specific CTCF sites and viral genes were different for each latency model. The functional importance of CTCF binding, transcription, and reactivation was confirmed using an EBV mutant lacking the LMP-2A CTCF binding site. This virus was unable to reactivate and had disrupted Pol activity at multiple CTCF binding sites relative to the wild-type (WT) virus. Overall, these data suggest that CTCF regulates the viral early transcripts during reactivation from latency. These activities likely help maintain the accessibility of the viral genome to initiate productive replication. IMPORTANCE The ability of EBV to switch between latent and lytic infection is key to its long-term persistence in memory B cells, and its ability to persist in proliferating cells is strongly linked to oncogenesis. During latency, most viral genes are epigenetically silenced, and the virus must overcome this repression to reactivate lytic replication. Reactivation occurs once the immediate early (IE) EBV lytic genes are expressed. However, the molecular mechanisms behind the switch from the latent transcriptional program to begin transcription of the IE genes remain unknown. In this study, we mapped RNA Pol positioning and activity during latency and reactivation. Unexpectedly, Pol activity accumulated at distinct regions characteristic of transcription initiation on the EBV genome previously shown to be associated with CTCF. We propose that CTCF binding at these regions retains Pol to maintain a stable latent chromosome conformation and a rapid response to various reactivation signals.

PRO-IP-seq Tracks Molecular Modifications of Engaged Pol II Complexes at Nucleotide Resolution

RNA Polymerase II (Pol II) is a multi-subunit complex that undergoes covalent modifications as transcription proceeds through genes and enhancers. Rate-limiting steps of transcription control Pol II recruitment, site and degree of initiation, pausing duration, productive elongation, nascent transcript processing, transcription termination, and Pol II recycling. Here, we developed Precision Run-On coupled to Immuno-Precipitation sequencing (PRO-IP-seq) and tracked phosphorylation of Pol II C-terminal domain (CTD) at nucleotide-resolution. We uncovered precise positional control of Pol II CTD phosphorylation as transcription proceeds from the initiating nucleotide, through early and late promoter-proximal pause, and into productive elongation. Pol II CTD was predominantly unphosphorylated in the early pause-region, whereas serine-2- and serine-5-phosphorylations occurred preferentially in the later pause-region. Serine-7-phosphorylation dominated after the pause-release in a region where Pol II accelerates to its full elongational speed. Interestingly, tracking transcription upon heat-induced reprogramming demonstrated that Pol II with phosphorylated CTD remains paused on heat-repressed genes.

RANKL-responsive epigenetic mechanism reprograms macrophages into bone-resorbing osteoclasts

Monocyte/macrophage lineage cells are highly plastic and can differentiate into various cells under different environmental stimuli. Bone-resorbing osteoclasts are derived from the monocyte/macrophage lineage in response to receptor activator of NF-κB ligand (RANKL). However, the epigenetic signature contributing to the fate commitment of monocyte/macrophage lineage differentiation into human osteoclasts is largely unknown. In this study, we identified RANKL-responsive human osteoclast-specific superenhancers (SEs) and SE-associated enhancer RNAs (SE-eRNAs) by integrating data obtained from ChIP-seq, ATAC-seq, nuclear RNA-seq and PRO-seq analyses. RANKL induced the formation of 200 SEs, which are large clusters of enhancers, while suppressing 148 SEs in macrophages. RANKL-responsive SEs were strongly correlated with genes in the osteoclastogenic program and were selectively increased in human osteoclasts but marginally presented in osteoblasts, CD4+ T cells, and CD34+ cells. In addition to the major transcription factors identified in osteoclasts, we found that BATF binding motifs were highly enriched in RANKL-responsive SEs. The depletion of BATF1/3 inhibited RANKL-induced osteoclast differentiation. Furthermore, we found increased chromatin accessibility in SE regions, where RNA polymerase II was significantly recruited to induce the extragenic transcription of SE-eRNAs, in human osteoclasts. Knocking down SE-eRNAs in the vicinity of the NFATc1 gene diminished the expression of NFATc1, a major regulator of osteoclasts, and osteoclast differentiation. Inhibiting BET proteins suppressed the formation of some RANKL-responsive SEs and NFATc1-associated SEs, and the expression of SE-eRNA:NFATc1. Moreover, SE-eRNA:NFATc1 was highly expressed in the synovial macrophages of rheumatoid arthritis patients exhibiting high-osteoclastogenic potential. Our genome-wide analysis revealed RANKL-inducible SEs and SE-eRNAs as osteoclast-specific signatures, which may contribute to the development of osteoclast-specific therapeutic interventions.

Mapping Transcription Regulation with Run-on and Sequencing Data Using the Web-Based tfTarget Gateway

Run-on and sequencing assays like GRO-seq, PRO-seq, and ChRO-seq allow for joint profiling of transcription activity of transcriptional regulatory elements (TREs), i.e., promoters and active enhancers, and target genes. Variation in biological conditions, such as treated vs. control, results in changes in the activity of transcription factors (TFs), which induces concerted changes in TREs and target genes. By modeling the differences between two biological conditions, we developed the computational pipeline known as tfTarget that predicts a set of putative TREs and target genes responding to each TF under the biological condition of interest. In this chapter, we demonstrate the use of the new web-based tfTarget in mapping transcription regulation using run-on sequencing data.

Transcription factor antagonism regulates heterogeneity in embryonic stem cell states

Gene expression heterogeneity underlies cell states and contributes to developmental robustness. While heterogeneity can arise from stochastic transcriptional processes, the extent to which it is regulated is unclear. Here, we characterize the regulatory program underlying heterogeneity in murine embryonic stem cell (mESC) states. We identify differentially active and transcribed enhancers (DATEs) across states. DATEs regulate differentially expressed genes and are distinguished by co-binding of transcription factors Klf4 and Zfp281. In contrast to other factors that interact in a positive feedback network stabilizing mESC cell-type identity, Klf4 and Zfp281 drive opposing transcriptional and chromatin programs. Abrogation of factor binding to DATEs dampens variation in gene expression, and factor loss alters kinetics of switching between states. These results show antagonism between factors at enhancers results in gene expression heterogeneity and formation of cell states, with implications for the generation of diverse cell types during development.

RNA Pol II pausing facilitates phased pluripotency transitions by buffering transcription

Promoter-proximal RNA Pol II pausing is a critical step in transcriptional control. Pol II pausing has been predominantly studied in tissue culture systems. While Pol II pausing has been shown to be required for mammalian development, the phenotypic and mechanistic details of this requirement are unknown. Here, we found that loss of Pol II pausing stalls pluripotent state transitions within the epiblast of the early mouse embryo. Using Nelfb -/- mice and a NELFB degron mouse pluripotent stem cell model, we show that embryonic stem cells (ESCs) representing the naïve state of pluripotency successfully initiate a transition program but fail to balance levels of induced and repressed genes and enhancers in the absence of NELF. We found an increase in chromatin-associated NELF during transition from the naïve to later pluripotent states. Overall, our work defines the acute and long-term molecular consequences of NELF loss and reveals a role for Pol II pausing in the pluripotency continuum as a modulator of cell state transitions.

Genetic dissection of the RNA polymerase II transcription cycle

How DNA sequence affects the dynamics and position of RNA Polymerase II (Pol II) during transcription remains poorly understood. Here, we used naturally occurring genetic variation in F1 hybrid mice to explore how DNA sequence differences affect the genome-wide distribution of Pol II. We measured the position and orientation of Pol II in eight organs collected from heterozygous F1 hybrid mice using ChRO-seq. Our data revealed a strong genetic basis for the precise coordinates of transcription initiation and promoter proximal pause, allowing us to redefine molecular models of core transcriptional processes. Our results implicate DNA sequence, including both known and novel DNA sequence motifs, as key determinants of the position of Pol II initiation and pause. We report evidence that initiation site selection follows a stochastic process similar to Brownian motion along the DNA template. We found widespread differences in the position of transcription termination, which impact the primary structure and stability of mature mRNA. Finally, we report evidence that allelic changes in transcription often affect mRNA and ncRNA expression across broad genomic domains. Collectively, we reveal how DNA sequences shape core transcriptional processes at single nucleotide resolution in mammals.

HSFs drive transcription of distinct genes and enhancers during oxidative stress and heat shock

Reprogramming of transcription is critical for the survival under cellular stress. Heat shock has provided an excellent model to investigate nascent transcription in stressed cells, but the molecular mechanisms orchestrating RNA synthesis during other types of stress are unknown. We utilized PRO-seq and ChIP-seq to study how Heat Shock Factors, HSF1 and HSF2, coordinate transcription at genes and enhancers upon oxidative stress and heat shock. We show that pause-release of RNA polymerase II (Pol II) is a universal mechanism regulating gene transcription in stressed cells, while enhancers are activated at the level of Pol II recruitment. Moreover, besides functioning as conventional promoter-binding transcription factors, HSF1 and HSF2 bind to stress-induced enhancers to trigger Pol II pause-release from poised gene promoters. Importantly, HSFs act at distinct genes and enhancers in a stress type-specific manner. HSF1 binds to many chaperone genes upon oxidative and heat stress but activates them only in heat-shocked cells. Under oxidative stress, HSF1 localizes to a unique set of promoters and enhancers to trans-activate oxidative stress-specific genes. Taken together, we show that HSFs function as multi-stress-responsive factors that activate distinct genes and enhancers when encountering changes in temperature and redox state.

Quantifying RNA synthesis at rate-limiting steps of transcription using nascent RNA-sequencing data

Nascent RNA-sequencing tracks transcription at nucleotide resolution. The genomic distribution of engaged transcription complexes, in turn, uncovers functional genomic regions. Here, we provide analytical steps to (1) identify transcribed regulatory elements de novo genome-wide, (2) quantify engaged transcription complexes at enhancers, promoter-proximal regions, divergent transcripts, gene bodies, and termination windows, and (3) measure distribution of transcription machineries and regulatory proteins across functional genomic regions. This protocol tracks engaged transcription complexes across functional genomic regions demonstrated in human K562 erythroleukemia cells.

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

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Identification of transcribed regulatory elements de novo genome-wide

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Quantification of engaged transcription complexes at functional genomic regions

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Measuring distribution of transcription regulators across the functional genomic regions

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Revealing functional genomic regions from nascent transcription data

Prediction of histone post-translational modification patterns based on nascent transcription data

The role of histone modifications in transcription remains incompletely understood. Here, we examine the relationship between histone modifications and transcription using experimental perturbations combined with sensitive machine-learning tools. Transcription predicted the variation in active histone marks and complex chromatin states, like bivalent promoters, down to single-nucleosome resolution and at an accuracy that rivaled the correspondence between independent ChIP-seq experiments. Blocking transcription rapidly removed two punctate marks, H3K4me3 and H3K27ac, from chromatin indicating that transcription is required for active histone modifications. Transcription was also required for maintenance of H3K27me3, consistent with a role for RNA in recruiting PRC2. A subset of DNase-I-hypersensitive sites were refractory to prediction, precluding models where transcription initiates pervasively at any open chromatin. Our results, in combination with past literature, support a model in which active histone modifications serve a supportive, rather than an essential regulatory, role in transcription.

A comparison of experimental assays and analytical methods for genome-wide identification of active enhancers

Mounting evidence supports the idea that transcriptional patterns serve as more specific identifiers of active enhancers than histone marks; however, the optimal strategy to identify active enhancers both experimentally and computationally has not been determined. Here, we compared 13 genome-wide RNA sequencing assays in K562 cells and showed that the nuclear run-on followed by cap-selection assay (GRO/PRO-cap) has advantages in eRNA detection and active enhancer identification. We also introduced a tool, Peak Identifier for Nascent Transcript Starts (PINTS), to identify active promoters and enhancers genome-wide and pinpoint the precise location of the 5′ transcription start sites. Finally, we compiled a comprehensive enhancer candidate compendium based on the detected eRNA TSSs available in 120 cell and tissue types that can be accessed at https://pints.yulab.org. With the knowledge of the best available assays and pipelines, this large-scale annotation of candidate enhancers will pave the way for selection and characterization of their functions in a time- and labor-efficient manner in the future.

CoRE-ATAC: A deep learning model for the functional classification of regulatory elements from single cell and bulk ATAC-seq data

Cis-Regulatory elements (cis-REs) include promoters, enhancers, and insulators that regulate gene expression programs via binding of transcription factors. ATAC-seq technology effectively identifies active cis-REs in a given cell type (including from single cells) by mapping accessible chromatin at base-pair resolution. However, these maps are not immediately useful for inferring specific functions of cis-REs. For this purpose, we developed a deep learning framework (CoRE-ATAC) with novel data encoders that integrate DNA sequence (reference or personal genotypes) with ATAC-seq cut sites and read pileups. CoRE-ATAC was trained on 4 cell types (n = 6 samples/replicates) and accurately predicted known cis-RE functions from 7 cell types (n = 40 samples) that were not used in model training (mean average precision = 0.80, mean F1 score = 0.70). CoRE-ATAC enhancer predictions from 19 human islet samples coincided with genetically modulated gain/loss of enhancer activity, which was confirmed by massively parallel reporter assays (MPRAs). Finally, CoRE-ATAC effectively inferred cis-RE function from aggregate single nucleus ATAC-seq (snATAC) data from human blood-derived immune cells that overlapped with known functional annotations in sorted immune cells, which established the efficacy of these models to study cis-RE functions of rare cells without the need for cell sorting. ATAC-seq maps from primary human cells reveal individual- and cell-specific variation in cis-RE activity. CoRE-ATAC increases the functional resolution of these maps, a critical step for studying regulatory disruptions behind diseases.

Multiple stages of evolutionary change in anthrax toxin receptor expression in humans

The advent of animal husbandry and hunting increased human exposure to zoonotic pathogens. To understand how a zoonotic disease may have influenced human evolution, we study changes in human expression of anthrax toxin receptor 2 (ANTXR2), which encodes a cell surface protein necessary for Bacillus anthracis virulence toxins to cause anthrax disease. In immune cells, ANTXR2 is 8-fold down-regulated in all available human samples compared to non-human primates, indicating regulatory changes early in the evolution of modern humans. We also observe multiple genetic signatures consistent with recent positive selection driving a European-specific decrease in ANTXR2 expression in multiple tissues affected by anthrax toxins. Our observations fit a model in which humans adapted to anthrax disease following early ecological changes associated with hunting and scavenging, as well as a second period of adaptation after the rise of modern agriculture.

Identification and prediction of developmental enhancers in sea urchin embryos

Background

The transcription of developmental regulatory genes is often controlled by multiple cis-regulatory elements. The identification and functional characterization of distal regulatory elements remains challenging, even in tractable model organisms like sea urchins.

Results

We evaluate the use of chromatin accessibility, transcription and RNA Polymerase II for their ability to predict enhancer activity of genomic regions in sea urchin embryos. ATAC-seq, PRO-seq, and Pol II ChIP-seq from early and late blastula embryos are manually contrasted with experimental cis-regulatory analyses available in sea urchin embryos, with particular attention to common developmental regulatory elements known to have enhancer and silencer functions differentially deployed among embryonic territories. Using the three functional genomic data types, machine learning models are trained and tested to classify and quantitatively predict the enhancer activity of several hundred genomic regions previously validated with reporter constructs in vivo.

Conclusions

Overall, chromatin accessibility and transcription have substantial power for predicting enhancer activity. For promoter-overlapping cis-regulatory elements in particular, the distribution of Pol II is the best predictor of enhancer activity in blastula embryos. Furthermore, ATAC- and PRO-seq predictive value is stage dependent for the promoter-overlapping subset. This suggests that the sequence of regulatory mechanisms leading to transcriptional activation have distinct relevance at different levels of the developmental gene regulatory hierarchy deployed during embryogenesis.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12864-021-07936-0.

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

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

PEPPRO: quality control and processing of nascent RNA profiling data

Nascent RNA profiling is growing in popularity; however, there is no standard analysis pipeline to uniformly process the data and assess quality. Here, we introduce PEPPRO, a comprehensive, scalable workflow for GRO-seq, PRO-seq, and ChRO-seq data. PEPPRO produces uniformly processed output files for downstream analysis and assesses adapter abundance, RNA integrity, library complexity, nascent RNA purity, and run-on efficiency. PEPPRO is restartable and fault-tolerant, records copious logs, and provides a web-based project report. PEPPRO can be run locally or using a cluster, providing a portable first step for genomic nascent RNA analysis.

H3K27ac bookmarking promotes rapid post-mitotic activation of the pluripotent stem cell program without impacting 3D chromatin reorganization

During self-renewal, cell-type-defining features are drastically perturbed in mitosis and must be faithfully reestablished upon G1 entry, a process that remains largely elusive. Here, we characterized at a genome-wide scale the dynamic transcriptional and architectural resetting of mouse pluripotent stem cells (PSCs) upon mitotic exit. We captured distinct waves of transcriptional reactivation with rapid induction of stem cell genes and transient activation of lineage-specific genes. Topological reorganization at different hierarchical levels also occurred in an asynchronous manner and showed partial coordination with transcriptional resetting. Globally, rapid transcriptional and architectural resetting associated with mitotic retention of H3K27 acetylation, supporting a bookmarking function. Indeed, mitotic depletion of H3K27ac impaired the early reactivation of bookmarked, stem-cell-associated genes. However, 3D chromatin reorganization remained largely unaffected, suggesting that these processes are driven by distinct forces upon mitotic exit. This study uncovers principles and mediators of PSC molecular resetting during self-renewal.

Stress-induced transcriptional memory accelerates promoter-proximal pause release and decelerates termination over mitotic divisions

Heat shock instantly reprograms transcription. Whether gene and enhancer transcription fully recover from stress and whether stress establishes a memory by provoking transcription regulation that persists through mitosis remained unknown. Here, we measured nascent transcription and chromatin accessibility in unconditioned cells and in the daughters of stress-exposed cells. Tracking transcription genome-wide at nucleotide-resolution revealed that cells precisely restored RNA polymerase II (Pol II) distribution at gene bodies and enhancers upon recovery from stress. However, a single heat exposure in embryonic fibroblasts primed a faster gene induction in their daughter cells by increasing promoter-proximal Pol II pausing and by accelerating the pause release. In K562 erythroleukemia cells, repeated stress refined basal and heat-induced transcription over mitotic division and decelerated termination-coupled pre-mRNA processing. The slower termination retained transcripts on the chromatin and reduced recycling of Pol II. These results demonstrate that heat-induced transcriptional memory acts through promoter-proximal pause release and pre-mRNA processing at transcription termination.

Computational methods and next-generation sequencing approaches to analyze epigenetics data: Profiling of methods and applications

Epigenetics is mainly comprised of features that regulate genomic interactions thereby playing a crucial role in a vast array of biological processes. Epigenetic mechanisms such as DNA methylation and histone modifications influence gene expression by modulating the packaging of DNA in the nucleus. A plethora of studies have emphasized the importance of analyzing epigenetics data through genome-wide studies and high-throughput approaches, thereby providing key insights towards epigenetics-based diseases such as cancer. Recent advancements have been made towards translating epigenetics research into a high throughput approach such as genome-scale profiling. Amongst all, bioinformatics plays a pivotal role in achieving epigenetics-related computational studies. Despite significant advancements towards epigenomic profiling, it is challenging to understand how various epigenetic modifications such as chromatin modifications and DNA methylation regulate gene expression. Next-generation sequencing (NGS) provides accurate and parallel sequencing thereby allowing researchers to comprehend epigenomic profiling. In this review, we summarize different computational methods such as machine learning and other bioinformatics tools, publicly available databases and resources to identify key modifications associated with epigenetic machinery. Additionally, the review also focuses on understanding recent methodologies related to epigenome profiling using NGS methods ranging from library preparation, different sequencing platforms and analytical techniques to evaluate various epigenetic modifications such as DNA methylation and histone modifications. We also provide detailed information on bioinformatics tools and computational strategies responsible for analyzing large scale data in epigenetics.

Recurrent evolution of vertebrate transcription factors by transposase capture

Genes with novel cellular functions may evolve through exon shuffling, which can assemble novel protein architectures. Here, we show that DNA transposons provide a recurrent supply of materials to assemble protein-coding genes through exon shuffling. We find that transposase domains have been captured-primarily via alternative splicing-to form fusion proteins at least 94 times independently over the course of ~350 million years of tetrapod evolution. We find an excess of transposase DNA binding domains fused to host regulatory domains, especially the Krüppel-associated box (KRAB) domain, and identify four independently evolved KRAB-transposase fusion proteins repressing gene expression in a sequence-specific fashion. The bat-specific KRABINER fusion protein binds its cognate transposons genome-wide and controls a network of genes and cis-regulatory elements. These results illustrate how a transcription factor and its binding sites can emerge.

Transcriptionally active enhancers in human cancer cells

The growth of human cancer cells is driven by aberrant enhancer and gene transcription activity. Here, we use transient transcriptome sequencing (TT-seq) to map thousands of transcriptionally active putative enhancers in fourteen human cancer cell lines covering seven types of cancer. These enhancers were associated with cell type-specific gene expression, enriched for genetic variants that predispose to cancer, and included functionally verified enhancers. Enhancer-promoter (E-P) pairing by correlation of transcription activity revealed ~ 40,000 putative E-P pairs, which were depleted for housekeeping genes and enriched for transcription factors, cancer-associated genes, and 3D conformational proximity. The cell type specificity and transcription activity of target genes increased with the number of paired putative enhancers. Our results represent a rich resource for future studies of gene regulation by enhancers and their role in driving cancerous cell growth.

Defining data-driven primary transcript annotations with primaryTranscriptAnnotation in R

SUMMARY

Nascent transcript measurements derived from run-on sequencing experiments are critical for the investigation of transcriptional mechanisms and regulatory networks. However, conventional mRNA gene annotations significantly differ from the boundaries of primary transcripts. New primary transcript annotations are needed to accurately interpret run-on data. We developed the primaryTranscriptAnnotation R package to infer the transcriptional start and termination sites of primary transcripts from genomic run-on data. We then used these inferred coordinates to annotate transcriptional units identified de novo. This package provides the novel utility to integrate data-driven primary transcript annotations with transcriptional unit coordinates identified in an unbiased manner. Highlighting the importance of using accurate primary transcript coordinates, we demonstrate that this new methodology increases the detection of differentially expressed transcripts and provides more accurate quantification of RNA polymerase pause indices.

AVAILABILITY AND IMPLEMENTATION

https://github.com/WarrenDavidAnderson/genomicsRpackage/tree/master/primaryTranscriptAnnotation.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Robust partitioning of microRNA targets from downstream regulatory changes

The biological impact of microRNAs (miRNAs) is determined by their targets, and robustly identifying direct miRNA targets remains challenging. Existing methods suffer from high false-positive rates and are unable to effectively differentiate direct miRNA targets from downstream regulatory changes. Here, we present an experimental and computational framework to deconvolute post-transcriptional and transcriptional changes using a combination of RNA-seq and PRO-seq. This novel approach allows us to systematically profile the regulatory impact of a miRNA. We refer to this approach as CARP: Combined Analysis of RNA-seq and PRO-seq. We apply CARP to multiple miRNAs and show that it robustly distinguishes direct targets from downstream changes, while greatly reducing false positives. We validate our approach using Argonaute eCLIP-seq and ribosome profiling, demonstrating that CARP defines a comprehensive repertoire of targets. Using this approach, we identify miRNA-specific activity of target sites within the open reading frame. Additionally, we show that CARP facilitates the dissection of complex changes in gene regulatory networks triggered by miRNAs and identification of transcription factors that mediate downstream regulatory changes. Given the robustness of the approach, CARP would be particularly suitable for dissecting miRNA regulatory networks in vivo.

Hotspots of Aberrant Enhancer Activity in Fibrolamellar Carcinoma Reveal Candidate Oncogenic Pathways and Therapeutic Vulnerabilities

Fibrolamellar carcinoma (FLC) is a rare, therapeutically intractable liver cancer that disproportionately affects youth. Although FLC tumors exhibit a distinct gene expression profile, the chromatin regulatory landscape and the genes most critical for tumor cell survival remain unclear. Here, we use chromatin run-on sequencing to discover ∼7,000 enhancers and 141 enhancer hotspots activated in FLC relative to nonmalignant liver. Bioinformatic analyses reveal aberrant ERK/MEK signaling and candidate master transcriptional regulators. We also define the genes most strongly associated with hotspots of FLC enhancer activity, including CA12 and SLC16A14. Treatment of FLC cell models with inhibitors of CA12 or SLC16A14 independently reduce cell viability and/or significantly enhance the effect of the MEK inhibitor cobimetinib. These findings highlight molecular targets for drug development, as well as drug combination approaches.

An inferred fitness consequence map of the rice genome

The extent to which sequence variation impacts plant fitness is poorly understood. High-resolution maps detailing the constraint acting on the genome, especially in regulatory sites, would be beneficial as functional annotation of noncoding sequences remains sparse. Here, we present a fitness consequence (fitCons) map for rice (Oryza sativa). We inferred fitCons scores (ρ) for 246 inferred genome classes derived from nine functional genomic and epigenomic datasets, including chromatin accessibility, messenger RNA/small RNA transcription, DNA methylation, histone modifications and engaged RNA polymerase activity. These were integrated with genome-wide polymorphism and divergence data from 1,477 rice accessions and 11 reference genome sequences in the Oryzeae. We found ρ to be multimodal, with ~9% of the rice genome falling into classes where more than half of the bases would probably have a fitness consequence if mutated. Around 2% of the rice genome showed evidence of weak negative selection, frequently at candidate regulatory sites, including a novel set of 1,000 potentially active enhancer elements. This fitCons map provides perspective on the evolutionary forces associated with genome diversity, aids in genome annotation and can guide crop breeding programs.

Lessons from eRNAs: understanding transcriptional regulation through the lens of nascent RNAs

Nascent transcription assays, such as global run-on sequencing (GRO-seq) and precision run-on sequencing (PRO-seq), have uncovered a myriad of unstable RNAs being actively produced from numerous sites genome-wide. These transcripts provide a more complete and immediate picture of the impact of regulatory events. Transcription factors recruit RNA polymerase II, effectively initiating the process of transcription; repressors inhibit polymerase recruitment. Efficiency of recruitment is dictated by sequence elements in and around the RNA polymerase loading zone. A combination of sequence elements and RNA binding proteins subsequently influence the ultimate stability of the resulting transcript. Some of these transcripts are capable of providing feedback on the process, influencing subsequent transcription. By monitoring RNA polymerase activity, nascent assays provide insights into every step of the regulated process of transcription.

AlleleHMM: a data-driven method to identify allele specific differences in distributed functional genomic marks

How DNA sequence variation influences gene expression remains poorly understood. Diploid organisms have two homologous copies of their DNA sequence in the same nucleus, providing a rich source of information about how genetic variation affects a wealth of biochemical processes. However, few computational methods have been developed to discover allele specific differences in functional genomic data. Existing methods either treat each SNP independently, limiting statistical power, or combine SNPs across gene annotations, preventing the discovery of allele specific differences in unexpected genomic regions. Here we introduce AlleleHMM, a new computational method to identify blocks of neighboring SNPs that share similar allele specific differences in mark abundance. AlleleHMM uses a hidden Markov model to divide the genome into three hidden states based on allele frequencies in genomic data: a symmetric state (state S) which shows no difference between alleles, and regions with a higher signal on the maternal (state M) or paternal (state P) allele. AlleleHMM substantially outperformed naive methods using both simulated and real genomic data, particularly when input data had realistic levels of overdispersion. Using global run-on sequencing (GRO-seq) data, AlleleHMM identified thousands of allele specific blocks of transcription in both coding and non-coding genomic regions. AlleleHMM is a powerful tool for discovering allele specific regions in functional genomic datasets.

Enhancer LncRNAs Influence Chromatin Interactions in Different Ways

More than 98% of the human genome does not encode proteins, and the vast majority of the noncoding regions have not been well studied. Some of these regions contain enhancers and functional non-coding RNAs. Previous research suggested that enhancer transcripts could be potent independent indicators of enhancer activity, and some enhancer lncRNAs (elncRNAs) have been proven to play critical roles in gene regulation. Here, we identified enhancer–promoter interactions from high-throughput chromosome conformation capture (Hi-C) data. We found that elncRNAs were highly enriched surrounding chromatin loop anchors. Additionally, the interaction frequency of elncRNA-associated enhancer–promoter pairs was significantly higher than the interaction frequency of other enhancer–promoter pairs, suggesting that elncRNAs may reinforce the interactions between enhancers and promoters. We also found that elncRNA expression levels were positively correlated with the interaction frequency of enhancer–promoter pairs. The promoters interacting with elncRNA-associated enhancers were rich in RNA polymerase II and YY1 transcription factor binding sites. We clustered enhancer–promoter pairs into different groups to reflect the different ways in which elncRNAs could influence enhancer–promoter pairs. Interestingly, G-quadruplexes were found to potentially mediate some enhancer–promoter interaction pairs, and the interaction frequency of these pairs was significantly higher than that of other enhancer–promoter pairs. We also found that the G-quadruplexes on enhancers were highly related to the expression of elncRNAs. G-quadruplexes located in the promoters of elncRNAs led to high expression of elncRNAs, whereas G-quadruplexes located in the gene bodies of elncRNAs generally resulted in low expression of elncRNAs.

NET-CAGE characterizes the dynamics and topology of human transcribed cis-regulatory elements

Promoters and enhancers are key cis-regulatory elements, but how they operate to generate cell type-specific transcriptomes is not fully understood. We developed a simple and robust method, native elongating transcript-cap analysis of gene expression (NET-CAGE), to sensitively detect 5' ends of nascent RNAs in diverse cells and tissues, including unstable transcripts such as enhancer-derived RNAs. We studied RNA synthesis and degradation at the transcription start site level, characterizing the impact of differential promoter usage on transcript stability. We quantified transcription from cis-regulatory elements without the influence of RNA turnover, and show that enhancer-promoter pairs are generally activated simultaneously on stimulation. By integrating NET-CAGE data with chromatin interaction maps, we show that cis-regulatory elements are topologically connected according to their cell type specificity. We identified new enhancers with high sensitivity, and delineated primary locations of transcription within super-enhancers. Our NET-CAGE dataset derived from human and mouse cells expands the FANTOM5 atlas of transcribed enhancers, with broad applicability to biomedical research.