Analysis of nascent RNA identifies a unified architecture of initiation regions at mammalian promoters and enhancers

CTCF blocks antisense transcription initiation at divergent promoters

Transcription at most promoters is divergent, initiating at closely spaced oppositely oriented core promoters to produce sense transcripts along with often unstable upstream antisense transcripts (uasTrx). How antisense transcription is regulated and to what extent it is coordinated with sense transcription is not well understood. Here, by combining acute degradation of the multi-functional transcription factor CTCF and nascent transcription measurements, we find that CTCF specifically suppresses antisense but not sense transcription at hundreds of divergent promoters. Primary transcript RNA-FISH shows that CTCF lowers burst fraction but not burst intensity of uasTrx and that co-bursting of sense and antisense transcripts is disfavored. Genome editing, chromatin conformation studies and high-resolution transcript mapping revealed that precisely positioned CTCF directly suppresses the initiation of uasTrx, in a manner independent of its architectural function. In sum, CTCF shapes the transcriptional landscape in part by suppressing upstream antisense transcription.

Application of nucleoside or nucleotide analogues in RNA dynamics and RNA-binding protein analysis

Cellular RNAs undergo dynamic changes during RNA biological processes, which are tightly orchestrated by RNA-binding proteins (RBPs). Yet, the investigation of RNA dynamics is hurdled by highly abundant steady-state RNAs, which make the signals of dynamic RNAs less detectable. Notably, the exert of nucleoside or nucleotide analogue-based RNA technologies has provided a remarkable platform for RNA dynamics research, revealing diverse unnoticed features in RNA metabolism. In this review, we focus on the application of two types of analogue-based RNA sequencing, antigen-/antibody- and click chemistry-based methodologies, and summarize the RNA dynamics features revealed. Moreover, we discuss emerging single-cell newly transcribed RNA sequencing methodologies based on nucleoside analogue labeling, which provides novel insights into RNA dynamics regulation at single-cell resolution. On the other hand, we also emphasize the identification of RBPs that interact with polyA, non-polyA RNAs, or newly transcribed RNAs and also their associated RNA-binding domains at genomewide level through ultraviolet crosslinking and mass spectrometry in different contexts. We anticipated that further modification and development of these analogue-based RNA and RBP capture technologies will aid in obtaining an unprecedented understanding of RNA biology. This article is categorized under: RNA Interactions with Proteins and Other Molecules > Protein-RNA Recognition RNA Structure and Dynamics > RNA Structure, Dynamics and Chemistry RNA Methods > RNA Analyses in Cells.

CTCF blocks antisense transcription initiation at divergent promoters

Transcription at most promoters is divergent, initiating at closely spaced oppositely oriented core promoters to produce sense transcripts along with often unstable upstream antisense transcripts (uasTrx). How antisense transcription is regulated and to what extent it is coordinated with sense transcription is not well understood. Here, by combining acute degradation of the multi-functional transcription factor CTCF and nascent transcription measurements, we find that CTCF specifically suppresses antisense but not sense transcription at hundreds of divergent promoters. Primary transcript RNA-FISH shows that CTCF lowers burst fraction but not burst intensity of uasTrx and that co-bursting of sense and antisense transcripts is disfavored. Genome editing, chromatin conformation studies and high-resolution transcript mapping revealed that precisely positioned CTCF directly suppresses the initiation of uasTrx, in a manner independent of its architectural function. In sum, CTCF shapes the transcriptional landscape in part by suppressing upstream antisense transcription.

Functional genomic assays to annotate enhancer-promoter interactions genome wide

Enhancers are pivotal for regulating gene transcription that occurs at promoters. Identification of the interacting enhancer-promoter pairs and understanding the mechanisms behind how they interact and how enhancers modulate transcription can provide fundamental insight into gene regulatory networks. Recently, advances in high-throughput methods in three major areas-chromosome conformation capture assay, such as Hi-C to study basic chromatin architecture, ectopic reporter experiments such as self-transcribing active regulatory region sequencing (STARR-seq) to quantify promoter and enhancer activity, and endogenous perturbations such as clustered regularly interspaced short palindromic repeat interference (CRISPRi) to identify enhancer-promoter compatibility-have further our knowledge about transcription. In this review, we will discuss the major method developments and key findings from these assays.

Multiplexed functional genomic assays to decipher the noncoding genome

Linkage disequilibrium and the incomplete regulatory annotation of the noncoding genome complicates the identification of functional noncoding genetic variants and their causal association with disease. Current computational methods for variant prioritization have limited predictive value, necessitating the application of highly parallelized experimental assays to efficiently identify functional noncoding variation. Here, we summarize two distinct approaches, massively parallel reporter assays and CRISPR-based pooled screens and describe their flexible implementation to characterize human noncoding genetic variation at unprecedented scale. Each approach provides unique advantages and limitations, highlighting the importance of multimodal methodological integration. These multiplexed assays of variant effects are undoubtedly poised to play a key role in the experimental characterization of noncoding genetic risk, informing our understanding of the underlying mechanisms of disease-associated loci and the development of more robust predictive classification algorithms.

Epigenetics of neural differentiation: Spotlight on enhancers

Neural induction, both in vivo and in vitro, includes cellular and molecular changes that result in phenotypic specialization related to specific transcriptional patterns. These changes are achieved through the implementation of complex gene regulatory networks. Furthermore, these regulatory networks are influenced by epigenetic mechanisms that drive cell heterogeneity and cell-type specificity, in a controlled and complex manner. Epigenetic marks, such as DNA methylation and histone residue modifications, are highly dynamic and stage-specific during neurogenesis. Genome-wide assessment of these modifications has allowed the identification of distinct non-coding regulatory regions involved in neural cell differentiation, maturation, and plasticity. Enhancers are short DNA regulatory regions that bind transcription factors (TFs) and interact with gene promoters to increase transcriptional activity. They are of special interest in neuroscience because they are enriched in neurons and underlie the cell-type-specificity and dynamic gene expression profiles. Classification of the full epigenomic landscape of neural subtypes is important to better understand gene regulation in brain health and during diseases. Advances in novel next-generation high-throughput sequencing technologies, genome editing, Genome-wide association studies (GWAS), stem cell differentiation, and brain organoids are allowing researchers to study brain development and neurodegenerative diseases with an unprecedented resolution. Herein, we describe important epigenetic mechanisms related to neurogenesis in mammals. We focus on the potential roles of neural enhancers in neurogenesis, cell-fate commitment, and neuronal plasticity. We review recent findings on epigenetic regulatory mechanisms involved in neurogenesis and discuss how sequence variations within enhancers may be associated with genetic risk for neurological and psychiatric disorders.

Population-level variation in enhancer expression identifies disease mechanisms in the human brain

Identification of risk variants for neuropsychiatric diseases within enhancers underscores the importance of understanding population-level variation in enhancer function in the human brain. Besides regulating tissue-specific and cell-type-specific transcription of target genes, enhancers themselves can be transcribed. By jointly analyzing large-scale cell-type-specific transcriptome and regulome data, we cataloged 30,795 neuronal and 23,265 non-neuronal candidate transcribed enhancers. Examination of the transcriptome in 1,382 brain samples identified robust expression of transcribed enhancers. We explored gene-enhancer coordination and found that enhancer-linked genes are strongly implicated in neuropsychiatric disease. We identified expression quantitative trait loci (eQTLs) for both genes and enhancers and found that enhancer eQTLs mediate a substantial fraction of neuropsychiatric trait heritability. Inclusion of enhancer eQTLs in transcriptome-wide association studies enhanced functional interpretation of disease loci. Overall, our study characterizes the gene-enhancer regulome and genetic mechanisms in the human cortex in both healthy and diseased states.

iPro-WAEL: a comprehensive and robust framework for identifying promoters in multiple species

Promoters are consensus DNA sequences located near the transcription start sites and they play an important role in transcription initiation. Due to their importance in biological processes, the identification of promoters is significantly important for characterizing the expression of the genes. Numerous computational methods have been proposed to predict promoters. However, it is difficult for these methods to achieve satisfactory performance in multiple species. In this study, we propose a novel weighted average ensemble learning model, termed iPro-WAEL, for identifying promoters in multiple species, including Human, Mouse, E.coli, Arabidopsis, B.amyloliquefaciens, B.subtilis and R.capsulatus. Extensive benchmarking experiments illustrate that iPro-WAEL has optimal performance and is superior to the current methods in promoter prediction. The experimental results also demonstrate a satisfactory prediction ability of iPro-WAEL on cross-cell lines, promoters annotated by other methods and distinguishing between promoters and enhancers. Moreover, we identify the most important transcription factor binding site (TFBS) motif in promoter regions to facilitate the study of identifying important motifs in the promoter regions. The source code of iPro-WAEL is freely available at https://github.com/HaoWuLab-Bioinformatics/iPro-WAEL.

P14AS upregulates gene expression in the CDKN2A/2B locus through competitive binding to PcG protein CBX7

Background: It is well known that P16 ^INK4A , P14 ^ARF , P15 ^INK4B mRNAs, and ANRIL lncRNA are transcribed from the CDKN2A/2B locus. LncRNA P14AS is a lncRNA transcribed from antisense strand of P14 ^ARF promoter to intron-1. Our previous study showed that P14AS could upregulate the expression level of ANRIL and P16 ^INK4A and promote the proliferation of cancer cells. Because polycomb group protein CBX7 could repress P16 ^INK4A expression and bind ANRIL, we wonder whether the P14AS-upregulated ANRIL and P16 ^INK4A expression is mediated with CBX7. Results: In this study, we found that the upregulation of P16 ^INK4A , P14 ^ARF , P15 ^INK4B and ANRIL expression was induced by P14AS overexpression only in HEK293T and HCT116 cells with active endogenous CBX7 expression, but not in MGC803 and HepG2 cells with weak CBX7 expression. Further studies showed that the stable shRNA-knockdown of CBX7 expression abolished the P14AS-induced upregulation of these P14AS target genes in HEK293T and HCT116 cells whereas enforced CBX7 overexpression enabled P14AS to upregulate expression of these target genes in MGC803 and HepG2 cells. Moreover, a significant association between the expression levels of P14AS and its target genes were observed only in human colon cancer tissue samples with high level of CBX7 expression (n = 38, p < 0.05), but not in samples (n = 37) with low level of CBX7 expression, nor in paired surgical margin tissues. In addition, the results of RNA immunoprecipitation (RIP)- and chromatin immunoprecipitation (ChIP)-PCR analyses revealed that lncRNA P14AS could competitively bind to CBX7 protein which prevented the bindings of CBX7 to both lncRNA ANRIL and the promoters of P16 ^INK4A , P14 ^ARF and P15 ^INK4B genes. The amounts of repressive histone modification H3K9m3 was also significantly decreased at the promoters of these genes by P14AS in CBX7 actively expressing cells. Conclusions: CBX7 expression is essential for P14AS to upregulate the expression of P16 ^INK4A , P14 ^ARF , P15 ^INK4B and ANRIL genes in the CDKN2A/2Blocus. P14AS may upregulate these genes' expression through competitively blocking CBX7-binding to ANRIL lncRNA and target gene promoters.

Shared regulation and functional relevance of local gene co-expression revealed by single cell analysis

Most human genes are co-expressed with a nearby gene. Previous studies have revealed this local gene co-expression to be widespread across chromosomes and across dozens of tissues. Yet, so far these studies used bulk RNA-seq, averaging gene expression measurements across millions of cells, thus being unclear if this co-expression stems from transcription events in single cells. Here, we leverage single cell datasets in >85 individuals to identify gene co-expression across cells, unbiased by cell-type heterogeneity and benefiting from the co-occurrence of transcription events in single cells. We discover >3800 co-expressed gene pairs in two human cell types, induced pluripotent stem cells (iPSCs) and lymphoblastoid cell lines (LCLs) and (i) compare single cell to bulk RNA-seq in identifying local gene co-expression, (ii) show that many co-expressed genes – but not the majority – are composed of functionally related genes and (iii) using proteomics data, provide evidence that their co-expression is maintained up to the protein level. Finally, using single cell RNA-sequencing (scRNA-seq) and single cell ATAC-sequencing (scATAC-seq) data for the same single cells, we identify gene-enhancer associations and reveal that >95% of co-expressed gene pairs share regulatory elements. These results elucidate the potential reasons for co-expression in single cell gene regulatory networks and warrant a deeper study of shared regulatory elements, in view of explaining disease comorbidity due to affecting several genes. Our in-depth view of local gene co-expression and regulatory element co-activity advances our understanding of the shared regulatory architecture between genes.

Using single-cell data from cell lines, the co-expression of genes and co-activity of regulatory elements is analyzed, providing insight into shared architecture and regulation between genes.

Enhancer-Mediated Formation of Nuclear Transcription Initiation Domains

Enhancers in higher eukaryotes and upstream activating sequences (UASs) in yeast have been shown to recruit components of the RNA polymerase II (Pol II) transcription machinery. At least a fraction of Pol II recruited to enhancers in higher eukaryotes initiates transcription and generates enhancer RNA (eRNA). In contrast, UASs in yeast do not recruit transcription factor TFIIH, which is required for transcription initiation. For both yeast and mammalian systems, it was shown that Pol II is transferred from enhancers/UASs to promoters. We propose that there are two modes of Pol II recruitment to enhancers in higher eukaryotes. Pol II complexes that generate eRNAs are recruited via TFIID, similar to mechanisms operating at promoters. This may involve the binding of TFIID to acetylated nucleosomes flanking the enhancer. The resulting eRNA, together with enhancer-bound transcription factors and co-regulators, contributes to the second mode of Pol II recruitment through the formation of a transcription initiation domain. Transient contacts with target genes, governed by proteins and RNA, lead to the transfer of Pol II from enhancers to TFIID-bound promoters.

Predicting which genes will respond to transcription factor perturbations

The ability to predict which genes will respond to the perturbation of a transcription factor serves as a benchmark for our systems-level understanding of transcriptional regulatory networks. In previous work, machine learning models have been trained to predict static gene expression levels in a biological sample by using data from the same or similar samples, including data on their transcription factor binding locations, histone marks, or DNA sequence. We report on a different challenge-training machine learning models to predict which genes will respond to the perturbation of a transcription factor without using any data from the perturbed cells. We find that existing transcription factor location data (ChIP-seq) from human cells have very little detectable utility for predicting which genes will respond to perturbation of a transcription factor. Features of genes, including their preperturbation expression level and expression variation, are very useful for predicting responses to perturbation of any transcription factor. This shows that some genes are poised to respond to transcription factor perturbations and others are resistant, shedding light on why it has been so difficult to predict responses from binding locations. Certain histone marks, including H3K4me1 and H3K4me3, have some predictive power when located downstream of the transcription start site. However, the predictive power of histone marks is much less than that of gene expression level and expression variation. Sequence-based or epigenetic properties of genes strongly influence their tendency to respond to direct transcription factor perturbations, partially explaining the oft-noted difficulty of predicting responsiveness from transcription factor binding location data. These molecular features are largely reflected in and summarized by the gene's expression level and expression variation. Code is available at https://github.com/BrentLab/TFPertRespExplainer.

Computational identification of signals predictive for nuclear RNA exosome degradation pathway targeting

The RNA exosome degrades transcripts in the nucleoplasm of mammalian cells. Its substrate specificity is mediated by two adaptors: the ‘nuclear exosome targeting (NEXT)’ complex and the ‘poly(A) exosome targeting (PAXT)’ connection. Previous studies have revealed some DNA/RNA elements that differ between the two pathways, but how informative these features are for distinguishing pathway targeting, or whether additional genomic features that are informative for such classifications exist, is unknown. Here, we leverage the wealth of available genomic data and develop machine learning models that predict exosome targets and subsequently rank the features the models use by their predictive power. As expected, features around transcript end sites were most predictive; specifically, the lack of canonical 3′ end processing was highly predictive of NEXT targets. Other associated features, such as promoter-proximal G/C content and 5′ splice sites, were informative, but only for distinguishing NEXT and not PAXT targets. Finally, we discovered predictive features not previously associated with exosome targeting, in particular RNA helicase DDX3X binding sites. Overall, our results demonstrate that nucleoplasmic exosome targeting is to a large degree predictable, and our approach can assess the predictive power of previously known and new features in an unbiased way.

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 (RNA-seq) assays in K562 cells and show that nuclear run-on followed by cap-selection assay (GRO/PRO-cap) has advantages in enhancer RNA detection and active enhancer identification. We also introduce a tool, peak identifier for nascent transcript starts (PINTS), to identify active promoters and enhancers genome wide and pinpoint the precise location of 5' transcription start sites. Finally, we compiled a comprehensive enhancer candidate compendium based on the detected enhancer RNA (eRNA) transcription start sites (TSSs) available in 120 cell and tissue types, which can be accessed at https://pints.yulab.org . With 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.

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.

Compatibility rules of human enhancer and promoter sequences

Gene regulation in the human genome is controlled by distal enhancers that activate specific nearby promoters1. A proposed model for this specificity is that promoters have sequence-encoded preferences for certain enhancers, for example, mediated by interacting sets of transcription factors or cofactors2. This 'biochemical compatibility' model has been supported by observations at individual human promoters and by genome-wide measurements in Drosophila3-9. However, the degree to which human enhancers and promoters are intrinsically compatible has not yet been systematically measured, and how their activities combine to control RNA expression remains unclear. Here we design a high-throughput reporter assay called enhancer × promoter self-transcribing active regulatory region sequencing (ExP STARR-seq) and applied it to examine the combinatorial compatibilities of 1,000 enhancer and 1,000 promoter sequences in human K562 cells. We identify simple rules for enhancer-promoter compatibility, whereby most enhancers activate all promoters by similar amounts, and intrinsic enhancer and promoter activities multiplicatively combine to determine RNA output (R2 = 0.82). In addition, two classes of enhancers and promoters show subtle preferential effects. Promoters of housekeeping genes contain built-in activating motifs for factors such as GABPA and YY1, which decrease the responsiveness of promoters to distal enhancers. Promoters of variably expressed genes lack these motifs and show stronger responsiveness to enhancers. Together, this systematic assessment of enhancer-promoter compatibility suggests a multiplicative model tuned by enhancer and promoter class to control gene transcription in the human genome.

Multi-omics to characterize the functional relationships of R-loops with epigenetic modifications, RNAPII transcription and gene expression

Abnormal accumulation of R-loops results in replication stress, genome instability, chromatin alterations and gene silencing. Little research has been done to characterize functional relationships among R-loops, histone marks, RNA polymerase II (RNAPII) transcription and gene regulation. We built extremely randomized trees (ETs) models to predict the genome-wide R-loops using RNAPII and multiple histone modifications chromatin immunoprecipitation (ChIP)-seq, DNase-seq, Global Run-On sequencing (GRO-seq) and R-loop profiling data. We compared the performance of ET models to multiple machine learning approaches, and the proposed ET models achieved the best and extremely robust performances. Epigenetic profiles are highly predictive of R-loops genome-widely and they are strongly associated with R-loop formation. In addition, the presence of R-loops is significantly correlated with RNAPII transcription activity, H3K4me3 and open chromatin around the transcription start site, and H3K9me1 and H3K9me3 around the transcription termination site. RNAPII pausing defects were correlated with 5′R-loops accumulation, and transcriptional termination defects and read-throughs were correlated with 3′R-loops accumulation. Furthermore, we found driver genes with 5′R-loops and RNAPII pausing defects express significantly higher and genes with 3′R-loops and read-through transcription express significantly lower than genes without R-loops. These driver genes are enriched with chromosomal instability, Hippo–Merlin signaling Dysregulation, DNA damage response and TGF-β pathways, indicating R-loops accumulating at the 5′ end of genes play oncogenic roles, whereas at the 3′ end of genes play tumor-suppressive roles in tumorigenesis.

Global-run on sequencing identifies Gm11967 as an Akt-dependent long noncoding RNA involved in insulin sensitivity

The insulin responsive Akt and FoxO1 signaling axis is a key regulator of the hepatic transcriptional response to nutrient intake. Here, we used global run-on sequencing (GRO-seq) to measure the nascent transcriptional response to fasting and refeeding as well as define the specific role of hepatic Akt and FoxO1 signaling in mediating this response. We identified 599 feeding-regulated transcripts, as well as over 6,000 eRNAs, and mapped their dependency on Akt and FoxO1 signaling. Further, we identified several feeding-regulated lncRNAs, including the lncRNA Gm11967, whose expression was dependent upon the liver Akt-FoxO1 axis. Restoring Gm11967 expression in mice lacking liver Akt improved insulin sensitivity and induced glucokinase protein expression, indicating that Akt-dependent control of Gm11967 contributes to the translational control of glucokinase. More broadly, we have generated a unique genome-wide dataset that defines the feeding and Akt/FoxO1-dependent transcriptional changes in response to nutrient availability.

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.

Screening thousands of transcribed coding and non-coding regions reveals sequence determinants of RNA polymerase II elongation potential

Precise regulation of transcription by RNA polymerase II (RNAPII) is critical for organismal growth and development. However, what determines whether an engaged RNAPII will synthesize a full-length transcript or terminate prematurely is poorly understood. Notably, RNAPII is far more susceptible to termination when transcribing non-coding RNAs than when synthesizing protein-coding mRNAs, but the mechanisms underlying this are unclear. To investigate the impact of transcribed sequence on elongation potential, we developed a method to screen the effects of thousands of INtegrated Sequences on Expression of RNA and Translation using high-throughput sequencing (INSERT-seq). We found that higher AT content in non-coding RNAs, rather than specific sequence motifs, drives RNAPII termination. Further, we demonstrate that 5' splice sites autonomously stimulate processive transcription, even in the absence of polyadenylation signals. Our results reveal a potent role for the transcribed sequence in dictating gene output and demonstrate the power of INSERT-seq toward illuminating these contributions.

Oncogenic chimeric transcription factors drive tumor-specific transcription, processing, and translation of silent genomic regions

Many cancers are characterized by gene fusions encoding oncogenic chimeric transcription factors (TFs) such as EWS::FLI1 in Ewing sarcoma (EwS). Here, we find that EWS::FLI1 induces the robust expression of a specific set of novel spliced and polyadenylated transcripts within otherwise transcriptionally silent regions of the genome. These neogenes (NGs) are virtually undetectable in large collections of normal tissues or non-EwS tumors and can be silenced by CRISPR interference at regulatory EWS::FLI1-bound microsatellites. Ribosome profiling and proteomics further show that some NGs are translated into highly EwS-specific peptides. More generally, we show that hundreds of NGs can be detected in diverse cancers characterized by chimeric TFs. Altogether, this study identifies the transcription, processing, and translation of novel, specific, highly expressed multi-exonic transcripts from otherwise silent regions of the genome as a new activity of aberrant TFs in cancer.

Enhancer transcription detected in the nascent transcriptomic landscape of bread wheat

The precise spatiotemporal gene expression is orchestrated by enhancers that lack general sequence features and thus are difficult to be computationally identified. By nascent RNA sequencing combined with epigenome profiling, we detect active transcription of enhancers from the complex bread wheat genome. We find that genes associated with transcriptional enhancers are expressed at significantly higher levels, and enhancer RNA is more precise and robust in predicting enhancer activity compared to chromatin features. We demonstrate that sub-genome-biased enhancer transcription could drive sub-genome-biased gene expression. This study highlights enhancer transcription as a hallmark in regulating gene expression in wheat.

Inflammatory Immune-Associated eRNA: Mechanisms, Functions and Therapeutic Prospects

The rapid development of multiple high-throughput sequencing technologies has made it possible to explore the critical roles and mechanisms of functional enhancers and enhancer RNAs (eRNAs). The inflammatory immune response, as a fundamental pathological process in infectious diseases, cancers and immune disorders, coordinates the balance between the internal and external environment of the organism. It has been shown that both active enhancers and intranuclear eRNAs are preferentially expressed over inflammation-related genes in response to inflammatory stimuli, suggesting that enhancer transcription events and their products influence the expression and function of inflammatory genes. Therefore, in this review, we summarize and discuss the relevant inflammatory roles and regulatory mechanisms of eRNAs in inflammatory immune cells, non-inflammatory immune cells, inflammatory immune diseases and tumors, and explore the potential therapeutic effects of enhancer inhibitors affecting eRNA production for diseases with inflammatory immune responses.

Functional annotation of breast cancer risk loci: current progress and future directions

Genome-wide association studies coupled with large-scale replication and fine-scale mapping studies have identified more than 150 genomic regions that are associated with breast cancer risk. Here, we review efforts to translate these findings into a greater understanding of disease mechanism. Our review comes in the context of a recently published fine-scale mapping analysis of these regions, which reported 352 independent signals and a total of 13,367 credible causal variants. The vast majority of credible causal variants map to noncoding DNA, implicating regulation of gene expression as the mechanism by which functional variants influence risk. Accordingly, we review methods for defining candidate-regulatory sequences, methods for identifying putative target genes and methods for linking candidate-regulatory sequences to putative target genes. We provide a summary of available data resources and identify gaps in these resources. We conclude that while much work has been done, there is still much to do. There are, however, grounds for optimism; combining statistical data from fine-scale mapping with functional data that are more representative of the normal "at risk" breast, generated using new technologies, should lead to a greater understanding of the mechanisms that influence an individual woman's risk of breast cancer.

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

Super-enhancers and novel therapeutic targets in colorectal cancer

Transcription factors, cofactors, chromatin regulators, and transcription apparatuses interact with transcriptional regulatory elements, including promoters, enhancers, and super-enhancers (SEs), to coordinately regulate the transcription of target genes and thereby control cell behaviors. Among these transcriptional regulatory components and related elements, SEs often play a central role in determining cell identity and tumor initiation and progression. Therefore, oncogenic SEs, which are generated within cancer cells in oncogenes and other genes important in tumor pathogenesis, have emerged as attractive targets for novel cancer therapeutic strategies in recent years. Herein, we review the identification, formation and activation modes, and regulatory mechanisms for downstream genes and pathways of oncogenic SEs. We also review the therapeutic strategies and compounds targeting oncogenic SEs in colorectal cancer and other malignancies.

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.

Regulating specificity in enhancer-promoter communication

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

Enhancer RNA: What we know and what we can achieve

Enhancers are important cis-acting elements that can regulate gene transcription and cell fate alongside promoters. In fact, many human cancers and diseases are associated with the malfunction of enhancers. Recent studies have shown that enhancers can produce enhancer RNAs (eRNAs) by RNA polymerase II. In this review, we discuss eRNA production, characteristics, functions and mechanics. eRNAs can determine chromatin accessibility, histone modification and gene expression by constructing a 'chromatin loop', thereby bringing enhancers to their target gene. eRNA can also be involved in the phase separation with enhancers and other proteins. eRNAs are abundant, and importantly, tissue-specific in tumours, various diseases and stem cells; thus, eRNAs can be a potential target for disease diagnosis and treatment. As eRNA is produced from the active transcription of enhancers and is involved in the regulation of cell fate, its manipulation will influence cell function, and therefore, it can be a new target for biological therapy.

Cis-regulatory sequences in plants: Their importance, discovery, and future challenges

The identification and characterization of cis-regulatory DNA sequences and how they function to coordinate responses to developmental and environmental cues is of paramount importance to plant biology. Key to these regulatory processes are cis-regulatory modules (CRMs), which include enhancers and silencers. Despite the extraordinary advances in high-quality sequence assemblies and genome annotations, the identification and understanding of CRMs, and how they regulate gene expression, lag significantly behind. This is especially true for their distinguishing characteristics and activity states. Here, we review the current knowledge on CRMs and breakthrough technologies enabling identification, characterization, and validation of CRMs; we compare the genomic distributions of CRMs with respect to their target genes between different plant species, and discuss the role of transposable elements harboring CRMs in the evolution of gene expression. This is an exciting time to study cis-regulomes in plants; however, significant existing challenges need to be overcome to fully understand and appreciate the role of CRMs in plant biology and in crop improvement.

CT-FOCS: a novel method for inferring cell type-specific enhancer–promoter maps

Spatiotemporal gene expression patterns are governed to a large extent by the activity of enhancer elements, which engage in physical contacts with their target genes. Identification of enhancer–promoter (EP) links that are functional only in a specific subset of cell types is a key challenge in understanding gene regulation. We introduce CT-FOCS (cell type FOCS), a statistical inference method that uses linear mixed effect models to infer EP links that show marked activity only in a single or a small subset of cell types out of a large panel of probed cell types. Analyzing 808 samples from FANTOM5, covering 472 cell lines, primary cells and tissues, CT-FOCS inferred such EP links more accurately than recent state-of-the-art methods. Furthermore, we show that strictly cell type-specific EP links are very uncommon in the human genome.

Single-cell-resolved dynamics of chromatin architecture delineate cell and regulatory states in zebrafish embryos

DNA accessibility of cis-regulatory elements (CREs) dictates transcriptional activity and drives cell differentiation during development. While many genes regulating embryonic development have been identified, the underlying CRE dynamics controlling their expression remain largely uncharacterized. To address this, we produced a multimodal resource and genomic regulatory map for the zebrafish community, which integrates single-cell combinatorial indexing assay for transposase-accessible chromatin with high-throughput sequencing (sci-ATAC-seq) with bulk histone PTMs and Hi-C data to achieve a genome-wide classification of the regulatory architecture determining transcriptional activity in the 24-h post-fertilization (hpf) embryo. We characterized the genome-wide chromatin architecture at bulk and single-cell resolution, applying sci-ATAC-seq on whole 24-hpf stage zebrafish embryos, generating accessibility profiles for ∼23,000 single nuclei. We developed a genome segmentation method, ScregSeg (single-cell regulatory landscape segmentation), for defining regulatory programs, and candidate CREs, specific to one or more cell types. We integrated the ScregSeg output with bulk measurements for histone post-translational modifications and 3D genome organization and identified new regulatory principles between chromatin modalities prevalent during zebrafish development. Sci-ATAC-seq profiling of npas4l/cloche mutant embryos identified novel cellular roles for this hematovascular transcriptional master regulator and suggests an intricate mechanism regulating its expression. Our work defines regulatory architecture and principles in the zebrafish embryo and establishes a resource of cell-type-specific genome-wide regulatory annotations and candidate CREs, providing a valuable open resource for genomics, developmental, molecular, and computational biology.

Fine mapping with epigenetic information and 3D structure

Since 2005, thousands of genome-wide association studies (GWAS) have been published, identifying hundreds of thousands of genetic variants that increase risk of complex traits such as autoimmune diseases. This wealth of data has the potential to improve patient care, through personalized medicine and the identification of novel drug targets. However, the potential of GWAS for clinical translation has not been fully achieved yet, due to the fact that the functional interpretation of risk variants and the identification of causal variants and genes are challenging. The past decade has seen the development of great advances that are facilitating the overcoming of these limitations, by utilizing a plethora of genomics and epigenomics tools to map and characterize regulatory elements and chromatin interactions, which can be used to fine map GWAS loci, and advance our understanding of the biological mechanisms that cause disease.

AIRE in context: Leveraging chromatin plasticity to trigger ectopic gene expression

The emergence of antigen receptor diversity in clonotypic lymphocytes drove the evolution of a novel gene, Aire, that enabled the adaptive immune system to discriminate foreign invaders from self-constituents. AIRE functions in the epithelial cells of the thymus to express genes highly restricted to alternative cell lineages. This somatic plasticity facilitates the selection of a balanced repertoire of T cells that protects the host from harmful self-reactive clones, yet maintains a wide range of affinities for virtually any foreign antigen. Here, we review the latest understanding of AIRE's molecular actions with a focus on its interplay with chromatin. We argue that AIRE is a multi-valent chromatin effector that acts late in the transcription cycle to modulate the activity of previously poised non-coding regulatory elements of tissue-specific genes. We postulate a role for chromatin instability-caused in part by ATP-dependent chromatin remodeling-that variably sets the scope of the accessible landscape on which AIRE can act. We highlight AIRE's intrinsic repressive function and its relevance in providing feedback control. We synthesize these recent advances into a putative model for the mechanistic modes by which AIRE triggers ectopic transcription for immune repertoire selection.

Genome-Wide Profiling of Transcription Initiation with STRIPE-seq

Transcription start site (TSS) usage is a critical factor in the regulation of gene expression. A number of methods for global TSS mapping have been developed, but barriers of expense, technical difficulty, time, and/or cost have limited their broader adoption. To address these issues, we developed Survey of TRanscription Initiation at Promoter Elements with high-throughput sequencing (STRIPE-seq). Requiring only three enzymatic steps with intervening bead cleanups, a STRIPE-seq library can be prepared from as little as 50 ng total RNA in ~5 h at a cost of ~$12 (US). In addition to profiling TSS usage, STRIPE-seq provides information on transcript levels that can be used for differential expression analysis. Thanks to its simplicity and low cost, we envision that STRIPE-seq could be employed by any molecular biology laboratory interested in profiling transcription initiation.

Pregnancy, preeclampsia and maternal aging: From epidemiology to functional genomics

Women live longer than men but experience greater disability and a longer period of illness as they age. Despite clear sex differences in aging, the impact of pregnancy and its complications, such as preeclampsia, on aging is an underexplored area of geroscience. This review summarizes our current knowledge about the complex links between pregnancy and age-related diseases, including evidence from epidemiology, clinical research, and genetics. We discuss the relationship between normal and pathological pregnancy and maternal aging, using preeclampsia as a primary example. We review the results of human genetics studies of preeclampsia, including genome wide association studies (GWAS), and attempted to catalog genes involved in preeclampsia as a gateway to mechanisms underlying an increased risk of later life cardio- and neuro- vascular events. Lastly, we discuss challenges in interpreting the GWAS of preeclampsia and provide a functional genomics framework for future research needed to fully realize the promise of GWAS in identifying targets for geroprotective prevention and therapeutics against preeclampsia.

Integration of high-resolution promoter profiling assays reveals novel, cell type-specific transcription start sites across 115 human cell and tissue types

Accurate transcription start site (TSS) annotations are essential for understanding transcriptional regulation and its role in human disease. Gene collections such as GENCODE contain annotations for tens of thousands of TSSs, but not all of these annotations are experimentally validated nor do they contain information on cell type–specific usage. Therefore, we sought to generate a collection of experimentally validated TSSs by integrating RNA Annotation and Mapping of Promoters for the Analysis of Gene Expression (RAMPAGE) data from 115 cell and tissue types, which resulted in a collection of approximately 50 thousand representative RAMPAGE peaks. These peaks are primarily proximal to GENCODE-annotated TSSs and are concordant with other transcription assays. Because RAMPAGE uses paired-end reads, we were then able to connect peaks to transcripts by analyzing the genomic positions of the 3′ ends of read mates. Using this paired-end information, we classified the vast majority (37 thousand) of our RAMPAGE peaks as verified TSSs, updating TSS annotations for 20% of GENCODE genes. We also found that these updated TSS annotations are supported by epigenomic and other transcriptomic data sets. To show the utility of this RAMPAGE rPeak collection, we intersected it with the NHGRI/EBI genome-wide association study (GWAS) catalog and identified new candidate GWAS genes. Overall, our work shows the importance of integrating experimental data to further refine TSS annotations and provides a valuable resource for the biological community.

Gender specific eRNA TBX5-AS1 as the immunological biomarker for male patients with lung squamous cell carcinoma in pan-cancer screening

As an innate feature of human beings, gender differences have an influence on various biological phenotypes, yet it does not attract enough attention in genomics studies. The prognosis of multiple carcinomas usually exhibits a favorable ending for female patients, but the neglect of gender differences can cause serious bias in survival analysis. Enhancer RNAs (eRNAs) are mostly downstream of androgens or estrogen. The present study was aimed to screen eRNAs in patients with non-small-cell lung cancer. The findings revealed that eRNA TBX5-AS1 was expressed differently between female and male patients. Meanwhile, its prognostic significance appeared only in male patients with squamous cell carcinoma (SCC) type. The Gene Set Enrichment Analysis proved that the expression level of TBX5-AS1 increased following the activation of the androgen signaling pathway. In pan-cancer analysis, the prognostic prediction based on gender grouping obtained more meaningful results, and the synergy between TBX5-AS1 and its homologous target was more consistent. Furthermore, immunity variations between sexes prompted us to explore the role that TBX5-AS1 played in tumor microenvironment and immunotherapy. The robust evidence proved that male patients with high expression of TBX5-AS1 possessed a malignant immune microenvironment and urgently needed immune checkpoint inhibitor treatment. In conclusion, TBX5-AS1 may be one of the strongest candidates to predict prognosis for male patients with SCC and provide a reference for immunotherapy.

The Hda1 histone deacetylase limits divergent non-coding transcription and restricts transcription initiation frequency

Nucleosome-depleted regions (NDRs) at gene promoters support initiation of RNA polymerase II transcription. Interestingly, transcription often initiates in both directions, resulting in an mRNA and a divergent non-coding (DNC) transcript of unclear purpose. Here, we characterized the genetic architecture and molecular mechanism of DNC transcription in budding yeast. Using high-throughput reverse genetic screens based on quantitative single-cell fluorescence measurements, we identified the Hda1 histone deacetylase complex (Hda1C) as a repressor of DNC transcription. Nascent transcription profiling showed a genome-wide role of Hda1C in repression of DNC transcription. Live-cell imaging of transcription revealed that mutations in the Hda3 subunit increased the frequency of DNC transcription. Hda1C contributed to decreased acetylation of histone H3 in DNC transcription regions, supporting DNC transcription repression by histone deacetylation. Our data support the interpretation that DNC transcription results as a consequence of the NDR-based architecture of eukaryotic promoters, but that it is governed by locus-specific repression to maintain genome fidelity.

TSSr: an R package for comprehensive analyses of TSS sequencing data

Transcription initiation is regulated in a highly organized fashion to ensure proper cellular functions. Accurate identification of transcription start sites (TSSs) and quantitative characterization of transcription initiation activities are fundamental steps for studies of regulated transcriptions and core promoter structures. Several high-throughput techniques have been developed to sequence the very 5'end of RNA transcripts (TSS sequencing) on the genome scale. Bioinformatics tools are essential for processing, analysis, and visualization of TSS sequencing data. Here, we present TSSr, an R package that provides rich functions for mapping TSS and characterizations of structures and activities of core promoters based on all types of TSS sequencing data. Specifically, TSSr implements several newly developed algorithms for accurately identifying TSSs from mapped sequencing reads and inference of core promoters, which are a prerequisite for subsequent functional analyses of TSS data. Furthermore, TSSr also enables users to export various types of TSS data that can be visualized by genome browser for inspection of promoter activities in association with other genomic features, and to generate publication-ready TSS graphs. These user-friendly features could greatly facilitate studies of transcription initiation based on TSS sequencing data. The source code and detailed documentations of TSSr can be freely accessed at https://github.com/Linlab-slu/TSSr.

A hypothetical model of trans-acting R-loops-mediated promoter-enhancer interactions by Alu elements

Enhancers modulate gene expression by interacting with promoters. Models of enhancer-promoter interactions (EPIs) in the literature involve the activity of many components, including transcription factors and nucleic acid. However, the role that sequence similarity plays in EPIs remains largely unexplored. Herein, we report that Alu-derived sequences dominate sequence similarity between enhancers and promoters. After rejecting alternative DNA:DNA and DNA:RNA triplex models, we propose that enhancer-associated RNAs (eRNAs) may directly contact their targeted promoters by forming trans-acting R-loops at those Alu sequences. We show how the characteristic distribution of functional genomic data, such as RNA-DNA proximate ligation reads, binding of transcription factors, and RNA-binding proteins, all align with the Alu sequences of EPIs. We also show that these aligned Alu sequences may be subject to the constraint of coevolution, further implying the functional significance of these R-loop hybrids. Finally, our results imply that eRNA and Alu elements associate in a manner previously unrecognized in EPIs and the evolution of gene regulation networks in mammals.

Epromoters function as a hub to recruit key transcription factors required for the inflammatory response

Gene expression is controlled by the involvement of gene-proximal (promoters) and distal (enhancers) regulatory elements. Our previous results demonstrated that a subset of gene promoters, termed Epromoters, work as bona fide enhancers and regulate distal gene expression. Here, we hypothesized that Epromoters play a key role in the coordination of rapid gene induction during the inflammatory response. Using a high-throughput reporter assay we explored the function of Epromoters in response to type I interferon. We find that clusters of IFNa-induced genes are frequently associated with Epromoters and that these regulatory elements preferentially recruit the STAT1/2 and IRF transcription factors and distally regulate the activation of interferon-response genes. Consistently, we identified and validated the involvement of Epromoter-containing clusters in the regulation of LPS-stimulated macrophages. Our findings suggest that Epromoters function as a local hub recruiting the key TFs required for coordinated regulation of gene clusters during the inflammatory response.

R-loopBase: a knowledgebase for genome-wide R-loop formation and regulation

R-loops play versatile roles in many physiological and pathological processes, and are of great interest to scientists in multiple fields. However, controversy about their genomic localization and incomplete understanding of their regulatory network raise great challenges for R-loop research. Here, we present R-loopBase (https://rloopbase.nju.edu.cn) to tackle these pressing issues by systematic integration of genomics and literature data. First, based on 107 high-quality genome-wide R-loop mapping datasets generated by 11 different technologies, we present a reference set of human R-loop zones for high-confidence R-loop localization, and spot conservative genomic features associated with R-loop formation. Second, through literature mining and multi-omics analyses, we curate the most comprehensive list of R-loop regulatory proteins and their targeted R-loops in multiple species to date. These efforts help reveal a global regulatory network of R-loop dynamics and its potential links to the development of cancers and neurological diseases. Finally, we integrate billions of functional genomic annotations, and develop interactive interfaces to search, visualize, download and analyze R-loops and R-loop regulators in a well-annotated genomic context. R-loopBase allows all users, including those with little bioinformatics background to utilize these data for their own research. We anticipate R-loopBase will become a one-stop resource for the R-loop community.

Genomic Marks Associated with Chromatin Compartments in the CTCF, RNAPII Loop and Genomic Windows

The nature of genome organization into two basic structural compartments is as yet undiscovered. However, it has been indicated to be a mechanism of gene expression regulation. Using the classification approach, we ranked genomic marks that hint at compartmentalization. We considered a broad range of marks, including GC content, histone modifications, DNA binding proteins, open chromatin, transcription and genome regulatory segmentation in GM12878 cells. Genomic marks were defined over CTCF or RNAPII loops, which are basic elements of genome 3D structure, and over 100 kb genomic windows. Experiments were carried out to empirically assess the whole set of features, as well as the individual features in classification of loops/windows, into compartment A or B. Using Monte Carlo Feature Selection and Analysis of Variance, we constructed a ranking of feature importance for classification. The best simple indicator of compartmentalization is DNase-seq open chromatin measurement for CTCF loops, H3K4me1 for RNAPII loops and H3K79me2 for genomic windows. Among DNA binding proteins, this is RUNX3 transcription factor for loops and RNAPII for genomic windows. Chromatin state prediction methods that indicate active elements like promoters, enhancers or heterochromatin enhance the prediction of loop segregation into compartments. However, H3K9me3, H4K20me1, H3K27me3 histone modifications and GC content poorly indicate compartments.

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.

RNA polymerase mapping in plants identifies intergenic regulatory elements enriched in causal variants

Control of gene expression is fundamental at every level of cell function. Promoter-proximal pausing and divergent transcription at promoters and enhancers, which are prominent features in animals, have only been studied in a handful of research experiments in plants. PRO-Seq analysis in cassava (Manihot esculenta) identified peaks of transcriptionally engaged RNA polymerase at both the 5' and 3' end of genes, consistent with paused or slowly moving Polymerase. In addition, we identified divergent transcription at intergenic sites. A full genome search for bi-directional transcription using an algorithm for enhancer detection developed in mammals (dREG) identified many intergenic regulatory element (IRE) candidates. These sites showed distinct patterns of methylation and nucleotide conservation based on genomic evolutionary rate profiling (GERP). SNPs within these IRE candidates explained significantly more variation in fitness and root composition than SNPs in chromosomal segments randomly ascertained from the same intergenic distribution, strongly suggesting a functional importance of these sites. Maize GRO-Seq data showed RNA polymerase occupancy at IREs consistent with patterns in cassava. Furthermore, these IREs in maize significantly overlapped with sites previously identified on the basis of open chromatin, histone marks, and methylation, and were enriched for reported eQTL. Our results suggest that bidirectional transcription can identify intergenic genomic regions in plants that play an important role in transcription regulation and whose identification has the potential to aid crop improvement.

Integrative epigenomic and high-throughput functional enhancer profiling reveals determinants of enhancer heterogeneity in gastric cancer

BACKGROUND

Enhancers are distal cis-regulatory elements required for cell-specific gene expression and cell fate determination. In cancer, enhancer variation has been proposed as a major cause of inter-patient heterogeneity-however, most predicted enhancer regions remain to be functionally tested.

METHODS

We analyzed 132 epigenomic histone modification profiles of 18 primary gastric cancer (GC) samples, 18 normal gastric tissues, and 28 GC cell lines using Nano-ChIP-seq technology. We applied Capture-based Self-Transcribing Active Regulatory Region sequencing (CapSTARR-seq) to assess functional enhancer activity. An Activity-by-contact (ABC) model was employed to explore the effects of histone acetylation and CapSTARR-seq levels on enhancer-promoter interactions.

RESULTS

We report a comprehensive catalog of 75,730 recurrent predicted enhancers, the majority of which are GC-associated in vivo (> 50,000) and associated with lower somatic mutation rates inferred by whole-genome sequencing. Applying CapSTARR-seq to the enhancer catalog, we observed significant correlations between CapSTARR-seq functional activity and H3K27ac/H3K4me1 levels. Super-enhancer regions exhibited increased CapSTARR-seq signals compared to regular enhancers, even when decoupled from native chromatin contexture. We show that combining histone modification and CapSTARR-seq functional enhancer data improves the prediction of enhancer-promoter interactions and pinpointing of germline single nucleotide polymorphisms (SNPs), somatic copy number alterations (SCNAs), and trans-acting TFs involved in GC expression. We identified cancer-relevant genes (ING1, ARL4C) whose expression between patients is influenced by enhancer differences in genomic copy number and germline SNPs, and HNF4α as a master trans-acting factor associated with GC enhancer heterogeneity.

CONCLUSIONS

Our results indicate that combining histone modification and functional assay data may provide a more accurate metric to assess enhancer activity than either platform individually, providing insights into the relative contribution of genetic (cis) and regulatory (trans) mechanisms to GC enhancer functional heterogeneity.