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Enhancer RNA (eRNA) has emerged as a key player in cancer biology, influencing various aspects of tumor development and progression. In this study, we investigated the role of eRNAs in kidney renal clear cell carcinoma (KIRC), the most common subtype of renal cell carcinoma. Leveraging high-throughput sequencing data and bioinformatics analysis, we identified differentially expressed eRNAs in KIRC and constructed eRNA-centric regulatory networks. Our findings revealed that up-regulated eRNAs in KIRC potentially regulate immune response and hypoxia pathways, while down-regulated eRNAs may impact ion transport, cell cycle, and metabolism. Furthermore, we developed a diagnostic prediction model based on eRNA expression profiles, demonstrating its effectiveness in KIRC diagnosis. Finally, we elucidated the regulatory mechanism of an eRNA (ENSR00000305834) on the expression of SLC15A2, a potential prognostic biomarker in KIRC, through bioinformatics analysis and in vitro validation experiments. In summary, Our study highlights the clinical significance of eRNAs in KIRC and underscores their potential as therapeutic targets. [ABSTRACT FROM AUTHOR]

The global marine ecosystem is changing rapidly as the result of biogeochemical cycles and ecosystem structure being altered by industrial civilization. Invasive marine species (IMS) are one of the most damaging regional consequences of human activity, and one of the most easily attributable to specific processes. This makes IMS introduction one of most tractable threats for management by appropriate policies. Once established, a different set of policies are required either to restrict IMS spread, or to attempt local eradication. The key ecosystem management tool for IMS damage mitigation is rapid, widely deployable IMS detection. Environmental Nucleic Acids (eNA), combining environmental DNA (eDNA) and environmental RNA (eRNA) analyses, have emerged as valuable tools for sensitive, cost-effective and readily deployable detection of IMS. Methods for IMS detection by eNA are still being developed through a widespread and active research community, so identifying the limitations of current processes will help prioritise eNA-based IMS detection research. We analysed and synthesised the opinions of expert marine ecosystem managers and researchers in Australia and New Zealand about the knowledge gaps and research needs for eNA-based IMS detection. This synthesis was placed in context with current research literature on what eNA technologies are currently providing as an IMS management tool; what problems exist with the current technology; and what could be done to improve this general approach. Our analyses produced a list of priorities that chart a path towards the best possible systems for IMS detection by eNA. [ABSTRACT FROM AUTHOR]

Environmental DNA (eDNA) metabarcoding has emerged as a promising approach to assess biodiversity and derive ecological status classes from water samples. However, a limitation of eDNA surveys is that detected DNA molecules may originate from other places or even dead organisms, distorting local biodiversity assessments. Environmental RNA (eRNA) metabarcoding has recently been proposed as a complementary tool for more localized assessments of the biological community. In this study, we evaluated the effectiveness of eDNA and eRNA metabarcoding for inferring the richness and species distribution patterns of vertebrates and invertebrates in a Central European lowland river. We collected water samples and analyzed them using a 12S marker for vertebrates and a COI marker for invertebrates. We detected 31 fish, 16 mammal, 10 bird and one lamprey species in the vertebrate dataset. While results were largely consistent, we detected a higher number of species when analysing eRNA (mean = 30.89) than eDNA (mean = 26.16). Also, eRNA detections had a stronger local signature than eDNA detections when compared against species distribution patterns from traditional fish monitoring data. For invertebrates, we detected 109 arthropod, 22 annelid, 12 rotiferan, eight molluscan and four cnidarian species. In contrast to the pattern of vertebrate richness, we detected a higher richness using eDNA (mean = 41.37) compared to eRNA (mean = 22.42). Our findings primarily show that eDNA and eRNA-based detections are comparable for vertebrate and invertebrate taxa. Biological replication was important for both template molecules studied. Signal detections for vertebrates were more localized for eRNA compared to eDNA. Overall, the advantages of the extra steps needed for eRNA analyses depend on the study question but both methods provide important data for biodiversity monitoring and research. [ABSTRACT FROM AUTHOR]

Interleukin-6 (IL-6) plays a crucial role in various cellular functions, including innate and adaptive immune responses. Dysregulated expression of IL-6 is associated with hyperinflammation and chronic inflammatory diseases. In this study, we aimed to identify the enhancer regions responsible for robust Il6 mRNA expression in murine macrophages. Through comprehensive genome-wide ChIP- and ATAC-seq analyses, we identified two distinct clusters, termed E1 and E2 regions, located at −144 to −163 kb relative to the Il6 transcription start site in lipopolysaccharide (LPS)-activated murine macrophages. These clusters exhibited an accumulation of histone modification marks (H3K27ac and H3K4me1), as well as open chromatin, and were found to contain binding sites for the transcription factors PU.1, NF-κB, C/EBPβ, and JunB. Upregulation of non-coding RNA (ncRNA) transcripts from the E1 and E2 regions was observed upon LPS stimulation, and repression of these ncRNAs resulted in abrogation of Il6 expression. Additionally, deletion of either E1 or E2 region significantly impaired Il6 expression, while CRISPR/dCas9 activation-mediated recruitment of the co-activator p300 to the E1 and E2 regions facilitated Il6 expression. Collectively, our findings suggest that the E1 and E2 regions serve as putative enhancers for Il6 expression. [ABSTRACT FROM AUTHOR]

Abstract Background Intervertebral disc degeneration (IVDD) is a common degenerative condition leading to abnormal stress distribution under load, causing intervertebral stenosis, facet joint degeneration, and foraminal stenosis. Very little is known about the molecular mechanism of eRNAs in IVDD. Methods Gene expression profiles of 38 annulus disc samples composed of 27 less degenerated discs (LDs) and 11 more degenerated discs (MDs) were retrieved from the GEO database. Then, differentially expressed enhancer RNAs (DEeRNAs), differentially expressed target genes (DETGs), and differentially expressed transcription factors (DETFs), hallmark of cancer signalling pathways according to GSVA; the types and quantity of immune cells according to CIBERSORT; and immune gene sets according to ssGSEA were analysed to construct an IVDD-related eRNA network. Then, multidimensional validation was performed to explore the interactions among DEeRNAs, DETFs and DEGs in space. Results A total of 53 components, 14 DETGs, 15 DEeRNAs, 3 DETFs, 5 immune cells, 9 hallmarks, and 7 immune gene sets, were selected to construct the regulatory network. After validation by online multidimensional databases, 21 interactive DEeRNA-DEG-DETF axes related to IVDD exacerbation were identified, among which the C1S-CTNNB1-CHD4 axis was the most significant. Conclusion Based upon the results of our study, we theorize that the C1S-CTNNB1-CHD4 axis plays a vital role in IVDD exacerbation. Specifically, C1S recruits CTNNB1 and upregulates the expression of CHD4 in IVDD, and subsequently, CHD4 suppresses glycolysis and activates oxidative phosphorylation, thus generating insoluble collagen fibre deposits and leading to the progression of IVDD. Overall, these DEeRNAs could comprise promising therapeutic targets for IVDD due to their high tissue specificity.

Background: The etiology of gallstone disease (GSD) has not been fully elucidated. Consequently, the primary objective of this study was to scrutinize and provisionally authenticate the distinctive expression profiles of long non-coding RNAs (lncRNAs) and messenger RNAs (mRNAs) in GSD. Methods: RiboNucleic Acid (RNA) sequencing was used on four paired human gallbladder samples for the purpose of this study. Differentially expressed lncRNAs (DElncRNAs) and mRNAs (DEmRNAs) were identified and subjected to analysis of their biological functions. The Pearson's correlation coefficients between DElncRNAs and DEmRNAs were computed to construct a co-expression network delineating their associations. Furthermore, both cis- and trans-regulatory networks of selected lncRNAs were established and visualized. Additionally, a competing endogenous RNA (ceRNA) regulatory network was constructed. To validate the RNA-sequencing data, we performed a Quantitative Real-time Polymerase Chain Reaction (RT-qPCR) on 10 paired human gallbladder samples, assessing the expressions of the top 4 DEmRNAs and DElncRNAs in gallstone and control samples. Results: A total of 934 DEmRNAs and 304DElncRNAs were successfully identified. Functional enrichment analysis indicated a predominant involvement in metabolic-related biological functions. Correlation analysis revealed a strong association between the expressions of 597 DEmRNAs and 194 DElncRNAs. Subsequently, both a cis-lncRNA-mRNA and a trans-lncRNA-Transcription Factor (TF)-mRNA regulatory network were meticulously constructed. Additionally, a ceRNA network, comprising of 24 DElncRNAs, 201 DEmRNAs, and 120 predicted miRNAs, was established. Furthermore, using RT-qPCR, we observed significant upregulation of AC004692.4, HECW1-IT1, SFRP4, and COMP, while LINC01564, SLC26A3, RP1-27K12.2, and GSTA2 exhibited marked downregulation in gallstone samples. Importantly, these findings were consistent with the sequencing. Conclusion: We conducted a screening process to identify DElncRNAs and DEmRNAs in GSD. This approach contributes to a deeper understanding of the genetic factors involved in the etiology of gallstones. [ABSTRACT FROM AUTHOR]

Background: Intervertebral disc degeneration (IVDD) is a common degenerative condition leading to abnormal stress distribution under load, causing intervertebral stenosis, facet joint degeneration, and foraminal stenosis. Very little is known about the molecular mechanism of eRNAs in IVDD. Methods: Gene expression profiles of 38 annulus disc samples composed of 27 less degenerated discs (LDs) and 11 more degenerated discs (MDs) were retrieved from the GEO database. Then, differentially expressed enhancer RNAs (DEeRNAs), differentially expressed target genes (DETGs), and differentially expressed transcription factors (DETFs), hallmark of cancer signalling pathways according to GSVA; the types and quantity of immune cells according to CIBERSORT; and immune gene sets according to ssGSEA were analysed to construct an IVDD-related eRNA network. Then, multidimensional validation was performed to explore the interactions among DEeRNAs, DETFs and DEGs in space. Results: A total of 53 components, 14 DETGs, 15 DEeRNAs, 3 DETFs, 5 immune cells, 9 hallmarks, and 7 immune gene sets, were selected to construct the regulatory network. After validation by online multidimensional databases, 21 interactive DEeRNA-DEG-DETF axes related to IVDD exacerbation were identified, among which the C1S-CTNNB1-CHD4 axis was the most significant. Conclusion: Based upon the results of our study, we theorize that the C1S-CTNNB1-CHD4 axis plays a vital role in IVDD exacerbation. Specifically, C1S recruits CTNNB1 and upregulates the expression of CHD4 in IVDD, and subsequently, CHD4 suppresses glycolysis and activates oxidative phosphorylation, thus generating insoluble collagen fibre deposits and leading to the progression of IVDD. Overall, these DEeRNAs could comprise promising therapeutic targets for IVDD due to their high tissue specificity. [ABSTRACT FROM AUTHOR]

Environmental DNA (eDNA) metabarcoding has emerged as a promising approach to assess biodiversity and derive ecological status classes from water samples. However, a limitation of eDNA surveys is that detected DNA molecules may originate from other places or even dead organisms, distorting local biodiversity assessments. Environmental RNA (eRNA) metabarcoding has recently been proposed as a complementary tool for more localized assessments of the biological community. In this study, we evaluated the effectiveness of eDNA and eRNA metabarcoding for inferring the richness and species distribution patterns of vertebrates and invertebrates in a Central European lowland river. We collected water samples and analyzed them using a 12S marker for vertebrates and a COI marker for invertebrates. We detected 31 fish, 16 mammal, 10 bird and one lamprey species in the vertebrate dataset. While results were largely consistent, we detected a higher number of species when analysing eRNA (mean = 30.89) than eDNA (mean = 26.16). Also, eRNA detections had a stronger local signature than eDNA detections when compared against species distribution patterns from traditional fish monitoring data. For invertebrates, we detected 109 arthropod, 22 annelid, 12 rotiferan, eight molluscan and four cnidarian species. In contrast to the pattern of vertebrate richness, we detected a higher richness using eDNA (mean = 41.37) compared to eRNA (mean = 22.42). Our findings primarily show that eDNA and eRNA-based detections are comparable for vertebrate and invertebrate taxa. Biological replication was important for both template molecules studied. Signal detections for vertebrates were more localized for eRNA compared to eDNA. Overall, the advantages of the extra steps needed for eRNA analyses depend on the study question but both methods provide important data for biodiversity monitoring and research.

Background Venous thromboembolism is associated with endothelial cell activation that contributes to the inflammation‐dependent activation of the coagulation system. Cellular damage is associated with the release of different species of extracellular RNA (eRNA) involved in inflammation and coagulation. TLR3 (toll‐like receptor 3), which recognizes (viral) single‐stranded or double‐stranded RNAs and self‐RNA fragments, might be the receptor of these species of eRNA during venous thromboembolism. Here, we investigate how the TLR3/eRNA axis contributes to venous thromboembolism. Methods and Results Thrombus formation and size in wild‐type and TLR3 deficient (−/−) mice were monitored by ultrasonography after venous thrombosis induction using the ferric chloride and stasis models. Mice were treated with RNase I, with polyinosinic‐polycytidylic acid, a TLR3 agonist, or with RNA extracted from murine endothelial cells. Gene expression and signaling pathway activation were analyzed in HEK293T cells overexpressing TLR3 in response to eRNA or in human umbilical vein endothelial cells transfected with a small interference RNA against TLR3. Plasma clot formation on treated human umbilical vein endothelial cells was analyzed. Thrombosis exacerbated eRNA release in vivo and increased eRNA content within the thrombus. RNase I treatment reduced thrombus size compared with vehicle‐treated mice (P

Simple Summary: Cervical cancer is the fourth most common cancer among women worldwide. The current survival rate of patients with recurrence and metastasis is less than 16.8%. Our research will establish a prognostic model regarding eRNA, which can effectively classify patient prognostic risk. It provides clues for the study of molecular mechanisms in high-risk patients and also provides some potential drugs for the personalized treatment of patients. The survival of CESC patients is closely related to the expression of enhancer RNA (eRNA). In this work, we downloaded eRNA expression, clinical, and gene expression data from the TCeA and TCGA portals. A total of 7936 differentially expressed eRNAs were discovered by limma analysis, and the relationship between these eRNAs and survival was analyzed by univariate Cox hazard analysis, LASSO regression, and multivariate Cox hazard analysis to obtain an 8-eRNA model. Risk score heat maps, KM curves, ROC analysis, robustness analysis, and nomograms further indicate that this 8-eRNA model is a novel indicator with high prognostic performance independent of clinicopathological classification. The model divided patients into high-risk and low-risk groups, compared pathway diversity between the two groups through GSEA analysis, and provided potential therapeutic agents for high-risk patients. [ABSTRACT FROM AUTHOR]

Summary: Background: The 5-year survival rate of oesophageal squamous cell carcinoma (ESCC) is approximately 20%. The prognosis and drug response exhibit substantial heterogeneity in ESCC, impeding progress in survival outcomes. Our goal is to identify a signature for tumour subtype classification, enabling precise clinical treatments. Methods: Utilising pre-treatment multi-omics data from an ESCC dataset (n = 310), an enhancer methylation-eRNA-target gene regulation network was constructed and validated by in vitro experiments. Four machine learning methods collectively identified core target genes, establishing an Enhancer Demethylation-Regulated Gene Score (EDRGS) model for classification. The molecular function of EDRGS subtyping was explored in scRNA-seq (n = 60) and bulk-seq (n = 310), and the EDRGS's potential to predict treatment response was assessed in datasets of various cancer types. Findings: EDRGS stratified ESCCs into EDRGS-high/low subtypes, with EDRGS-high signifying a less favourable prognosis in ESCC and nine additional cancer types. EDRGS-high exhibited an immune-hot but immune-suppressive phenotype with elevated immune checkpoint expression, increased T cell infiltration, and IFNγ signalling in ESCC, suggesting a better response to immunotherapy. Notably, EDRGS outperformed PD-L1 in predicting anti-PD-1/L1 therapy effectiveness in ESCC (n = 42), kidney renal clear cell carcinoma (KIRC, n = 181), and bladder urothelial carcinoma (BLCA, n = 348) cohorts. EDRGS-low showed a cell cycle-activated phenotype with higher CDK4 and/or CDK6 expression, demonstrating a superior response to the CDK4/6 inhibitor palbociclib, validated in ESCC (n = 26), melanoma (n = 18), prostate cancer (n = 15) cells, and PDX models derived from patients with pancreatic cancer (n = 30). Interpretation: Identification of EDRGS subtypes enlightens ESCC categorisation, offering clinical insights for patient management in immunotherapy (anti-PD-1/L1) and CDK4/6 inhibitor therapy across cancer types. Funding: This study was supported by funding from the National Key R&D Program of China (2021YFC2501000, 2020YFA0803300), the National Natural Science Foundation of China (82030089, 82188102), the CAMS Innovation Fund for Medical Sciences (2021-I2M-1-018, 2022-I2M-2-001, 2021-I2M-1-067), the Fundamental Research Funds for the Central Universities (3332021091).

Here, we used RNA capture-seq to identify a large population of lncRNAs that are expressed in the infralimbic prefrontal cortex of adult male mice in response to fear-related learning. Combining these data with cell-type-specific ATAC-seq on neurons that had been selectively activated by fear extinction learning, we find inducible 434 lncRNAs that are derived from enhancer regions in the vicinity of protein-coding genes. In particular, we discover an experience-induced lncRNA we call ADRAM (activity-dependent lncRNA associated with memory) that acts as both a scaffold and a combinatorial guide to recruit the brain-enriched chaperone protein 14-3-3 to the promoter of the memory-associated immediate-early gene Nr4a2 and is required fear extinction memory. This study expands the lexicon of experience-dependent lncRNA activity in the brain and highlights enhancer-derived RNAs (eRNAs) as key players in the epigenomic regulation of gene expression associated with the formation of fear extinction memory.

Smoking and HPV infection are known causes for the vast majority of head and neck squamous cell carcinomas (HNSCC) due to their likelihood of causing gene dysregulation and genomic alterations. Enhancer RNAs (eRNAs) are non-coding RNAs that are known to increase nearby and target gene expression, and activity that has been suggested to be affected by genetic and epigenetic alterations. Here we sought to identify the effects of smoking and HPV status on eRNA expression in HNSCC tumors. We focused on four patient cohorts including smoking/HPV+, smoking/HPV-, non-smoking/HPV+, and non-smoking/HPV- patients. We used TCGA RNA-seq data from cancer tumors and adjacent normal tissue, extracted eRNA read counts, and correlated these to survival, clinical variables, immune infiltration, cancer pathways, and genomic alterations. We found a large number of differentially expressed eRNA in each patient cohort. We also found several dysregulated eRNA correlated to patient survival, clinical variables, immune pathways, and genomic alterations. Additionally, we were able to find dysregulated eRNA nearby seven key HNSCC-related oncogenes. For example, we found eRNA chr14:103272042-103272430 (eRNA-24036), which is located close to the TRAF3 gene to be differentially expressed and correlated with the pathologic N stage and immune cell populations. Using a separate validation dataset, we performed differential expression and immune infiltration analysis to validate our results from the TCGA data. Our findings may explain the association between eRNA expression, enhancer activity, and nearby gene dysregulation.

Fishes are ecologically important organisms that have long lifespans, high mobilities, and diverse trophic levels. Due to their importance, fishes are used as bioindicators for monitoring aquatic environments. One method for monitoring fishes is based on environmental DNA (eDNA), which are the deoxynucleic acids released by organisms into the environment. However, there has been a problem with false positives because eDNA is relatively stable in the environment and could even likely represent dead or non-inhabiting organisms. To address this weakness, environmental RNA (eRNA), which degrades more rapidly than eDNA in the environment, can be utilized to complement eDNA. But, to date, few studies have used eRNA for freshwater fish monitoring. In this study, to determine the relative usefulness of eDNA and eRNA metabarcoding in freshwater fishes, we performed eDNA and eRNA metabarcoding on 12S rRNA targeting fish using water samples that were collected from three locations in the Han River. We then calculated the sensitivity and positive predictivity of this approach by comparing our data to the previous specimen capture survey (PSCS) data from the last six years. The results showed that 42 species were detected by eDNA and 19 by eRNA at the three locations. At all locations, compared to the PSCS data, the average sensitivity was higher for eDNA (46.1%) than for eRNA (34.6%), and the average positive predictivity was higher for eRNA (31.7%) than for eDNA (20.7%). This confirmed that eDNA metabarcoding has the advantage of broadly determining species presence or absence (including those that are no longer present or dead), but it also generates false positives; meanwhile, eRNA metabarcoding reports living fish species, but detects fewer species than eDNA. Combining eDNA and eRNA therefore emphasizes their advantages and compensates for their disadvantages, and conducting this may therefore be useful for identifying false positives and monitoring the fish species that are actually present in the environment. This metabarcoding technique can be used in the future to provide insights into the aquatic environment and the monitoring of fisheries. [ABSTRACT FROM AUTHOR]

Abstract Aquatic viruses are major threats to global aquacultural productivity. While conventional diagnostic methods for disease investigation are laborious, time‐consuming, and often involve the sacrifice of animals, environmental DNA and RNA (eDNA/eRNA) tools have the potential in being non‐invasive alternatives for the effective and early detection of various pathogens simultaneously. In this study, three seawater filtration methods—Sterivex syringe filtration, centrifugal ultrafiltration, and vacuum pump filtration with iron flocculation—were assessed for the recovery rates in co‐detecting fish virus eDNA/eRNA from natural seawater that was spiked with fish red seabream iridovirus (RSIV, DNA virus) and nervous necrosis virus (NNV, RNA virus). The centrifugal ultrafiltration method was the most effective for the capture of small‐sized viruses like NNV with a recovery rate of 63.23%, while the method of vacuum pump filtration with iron flocculation and chloroform disintegration of filter membranes had the highest RSIV recovery rate of 32.61%. We also optimized both automated and manual nucleic acid extraction methods and found comparable eDNA/eRNA extraction efficiencies. Our findings from the systematic comparison of seawater filtration and extraction methods suggest that each seawater filtration/nucleic acid extraction method can cater to different aquatic animal virus surveillance and disease investigation scenarios. These highlight the potential of virus eDNA/eRNA approaches for advancing the field of disease ecology and safeguarding aquatic animal health.

Abstract Environmental DNA (eDNA) analysis is now a widely‐used tool to non‐invasively monitor a variety of organisms. However, eDNA applications are limited with respect to gaining information on population demography and the status of individuals within a population. Although in its infancy, environmental RNA (eRNA) analysis has the potential to reveal information about populations that may be important for conservation or management decisions. Using gene databases and current literature, we synthesized information about gene products that may be useful eRNA targets for environmental samples focusing on the model organisms Danio rerio (zebrafish), Xenopus laevis (African clawed frog), and X. tropicalis (Western clawed frog). We suggested that appropriate gene products must be expressed in tissues thought to contribute to environmental samples, must be exclusively expressed or upregulated by at least 2‐fold in portions of populations (e.g., a single age class), and must be useful to a relevant application for population monitoring. We categorized 127 total eRNA targets based on their potential applications: distinguishing and quantifying living communities, determining population age structure, determining sex ratios, and assessing population health. There are many uncertainties and current limitations that need to be addressed before eRNA can be an established method in population management including understanding the ecology of eRNA, determining methods for determining assay specificity, and applying what we know from model organisms to other species. However, we see immense potential in the utility of eRNA in gathering population‐level information and serving as an important tool for managers in the near future.

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

Enhancers are key regulatory elements that exert crucial roles in diverse biological processes, including tumorigenesis and cancer development. Active enhancers could produce transcripts termed enhancer RNAs (eRNAs), which could be used as an index of enhancer activity. Here, we present a versatile data portal, enhancer activity quantitative trait loci database (eaQTLdb; http://www.bioailab.com:3838/eaQTLdb), for exploring the effects of genetic variants on enhancer activity and prioritizing candidate variants across different cancer types. By leveraging the accumulated multiomics data, we systematically identified genetic variants which influence enhancer activity in different cancer types, termed as eaQTLs. We have linked the eaQTLs to hallmarks of cancer and patients' overall survival to illustrate their potential biological roles in cancer development and progression. Notably, eaQTLs associated with the infiltration abundance of 24 different immune cell types were identified and incorporated into eaQTLdb. In addition, we applied colocalization analyses to examine 59 complex diseases and traits to identify eaQTLs colocalized with diseases/traits GWAS signals. Overall, eaQTLdb, incorporating a rich resource for exploration of eaQTLs in different cancer types, will not only benefit users in prioritizing candidate genetic variants and enhancers, but also help researchers decipher the roles of eaQTLs in the dysregulated pathways of cancer and tumor immune microenvironment, opening new diagnostic and therapeutic avenues in precise medicine. [ABSTRACT FROM AUTHOR]

Introduction: Transcriptional activation depends on the interplay of chromatin modifiers to establish a permissive epigenetic landscape. While histone 3 lysine 9 (H3K9) methylation has long been associated with gene repression, there is limited evidence to support a role for H3K9 demethylases in gene activation. Methods: We leveraged knockdown and overexpression of JMJD2d / Kdm4d in mouse embryonic fibroblasts, coupled with extensive epigenomic analysesm to decipher the role of histone 3 lysine 9 demethylases in the innate immune response. Results: Here we describe the H3K9 demethylase Kdm4d/JMJD2d as a positive regulator of type I interferon responses. In mouse embryonic fibroblasts (MEFs), depletion of JMJD2d attenuates the transcriptional response, conferring increased viral susceptibility, while overexpression of the demethylase results in more robust IFN activation. We find that the underlying mechanism of JMJD2d in type I interferon responses consists of an effect both on the transcription of enhancer RNAs (eRNAs) and on dynamic H3K9me2 at associated promoters. In support of these findings, we establish that JMJD2d is associated with enhancer regions throughout the genome prior to stimulation but is redistributed to inducible promoters in conjunction with transcriptional activation. Discussion: Taken together, our data reveal JMJD2d as a chromatin modifier that connects enhancer transcription with promoter demethylation to modulate transcriptional responses. [ABSTRACT FROM AUTHOR]

Aquatic non-indigenous species (NIS) threaten biodiversity, ecosystem functions, and the economy worldwide. Monitoring NIS is of immediate concern to identify newly arriving species, assess the efficacy of mitigation measures, and report long-term indicators of introduction, spread, and impacts. The challenges associated with conventional methods of specimen collection and morphological identification have led to the development of alternative methods, such as DNA-based methods, which could offer rapid and cost-effective detection of NIS. Depending on whether a few (targeted monitoring) or many species (passive monitoring) are being monitored, environmental DNA (eDNA) can infer presence-absence and relative abundances, enabling informed decisions and actions to be made based on patterns of detection. Compared to more conventional methods, eDNA tools can increase the levels of detection and sensitivity for rare and elusive species, which is even more noticeable for some taxa when using targeted monitoring. The use of DNA-based tools not only minimizes the onus on taxonomic expertise and reduces resource demands but can also be more sensitive and cost-efficient in detecting NIS, thus proving its value as an early warning tool. As nucleic acid (DNA/RNA) methods advance rapidly for NIS detection, there must be a balance between method sensitivity, logistical requirements, and associated costs, which must be factored into future management decisions. While there are many complementary reviews available, our aim is to emphasize the importance of incorporating eDNA tools into NIS surveys and to highlight the available opportunities in this field. [ABSTRACT FROM AUTHOR]

The survival of CESC patients is closely related to the expression of enhancer RNA (eRNA). In this work, we downloaded eRNA expression, clinical, and gene expression data from the TCeA and TCGA portals. A total of 7936 differentially expressed eRNAs were discovered by limma analysis, and the relationship between these eRNAs and survival was analyzed by univariate Cox hazard analysis, LASSO regression, and multivariate Cox hazard analysis to obtain an 8-eRNA model. Risk score heat maps, KM curves, ROC analysis, robustness analysis, and nomograms further indicate that this 8-eRNA model is a novel indicator with high prognostic performance independent of clinicopathological classification. The model divided patients into high-risk and low-risk groups, compared pathway diversity between the two groups through GSEA analysis, and provided potential therapeutic agents for high-risk patients.

Enhancers are a class of cis-regulatory elements in the genome that instruct the spatiotemporal transcriptional program. Last decade has witnessed an exploration of non-coding transcripts pervasively transcribed from active enhancers in diverse contexts, referred to as enhancer RNAs (eRNAs). Emerging evidence unequivocally suggests eRNAs are an important layer in transcriptional regulation. In this mini-review, we summarize the well-established regulatory models for eRNA actions and highlight the recent insights into the structure and chemical modifications of eRNAs underlying their functions. We also explore the potential roles of eRNAs in transcriptional condensates.

Environmental DNA (eDNA) sequencing—DNA collected from the environment from living cells or shed DNA—was first developed for working with microbes and has greatly benefitted microbial ecologists for decades since. These tools have only become increasingly powerful with the advent of metabarcoding and metagenomics. Most new studies that examine diverse assemblages of bacteria, archaea, protists, fungi, and viruses lean heavily into eDNA using these newer technologies, as the necessary sequencing technology and bioinformatic tools have become increasingly affordable and user friendly. However, eDNA methods are rapidly evolving, and sometimes it can feel overwhelming to simply keep up with the basics. In this review, we provide a starting point for microbial ecologists who are new to DNA-based methods by detailing the eDNA methods that are most pertinent, including study design, sample collection and storage, selecting the right sequencing technology, lab protocols, equipment, and a few bioinformatic tools. Furthermore, we focus on how eDNA work can benefit restoration and what modifications are needed when working in this subfield. [ABSTRACT FROM AUTHOR]

Approaches involving environmental DNA/RNA (eDNA/eRNA) – collectively eNA – can be used for pathogen discovery, ecology studies, surveillance, disease risk assessment, and early warning systems, after appropriate validation. eNA can provide evidence of the presence of pathogens in a system, and increases the spatiotemporal scope and efficiency of surveillance efforts – but it cannot, on its own, provide confirmatory evidence of infection of local hosts. The 'pathogen eNA continuum' provides a framework for designing pathogen eDNA/eRNA investigations, to elucidate pathogen life cycles, host reservoirs and vectors, and to link environmental detection to actual infections. Pathogen eRNA may provide additional insight into pathogen viability and activity, and can be used alternatively or in addition to eDNA. eNA approaches can be developed for predictive spatiotemporal modelling of pathogen distribution and impacts. Detection of pathogens, parasites, and other symbionts in environmental samples via eDNA/eRNA (collectively eNA) is an increasingly important source of information about their occurrence and activity. There is great potential for using such detections as a proxy for infection of host organisms in connected habitats, for pathogen monitoring and surveillance, and for early warning systems for disease. However, many factors require consideration, and appropriate methods developed and verified, in order that eNA detections can be reliably interpreted and adopted for surveillance and assessment of disease risk, and potentially inclusion in international standards, such as the World Organisation for Animal Health guidelines. Disease manifestation results from host–symbiont–environment interactions between hosts, demanding a multifactorial approach to interpretation of eNA signals. [ABSTRACT FROM AUTHOR]

Background: Hepatocellular carcinoma (HCC) remains notorious for its high malignancy, poor prognosis and high mortality. The exploration of novel therapeutic agents for HCC has remained challenging due to its complex aetiology. Therefore, it is necessary to elucidate the pathogenesis and mechanism of HCC for clinical intervention. Methods: We collected data from several public data portals and systematically analysed the association between transcription factors (TFs), eRNA-associated enhancers and downstream targets. We next filtered the prognostic genes and established a novel prognosis-related nomogram model. Moreover, we explored the potential mechanisms of the identified prognostic genes. The expression level was validated by several ways. Results: We first constructed a significant TF-enhancer-target regulatory network and identified DAPK1 as a coregulatory differentially expressed prognosis-related gene. We combined common clinicopathological factors and built a prognostic nomogram model for HCC. We found that our regulatory network was correlated with the processes of synthesizing various substances. Moreover, we explored the role of DAPK1 in HCC and found that it was associated with immune cell infiltration and DNA methylation. Several immunostimulators and targeting drugs could be promising immune therapy targets. The tumor immune microenvironment was analyzed. Finally, the lower DAPK1 expression in HCC was validated via the GEO database, UALCAN cohort, and qRT-PCR. Conclusion: In conclusion, we established a significant TF-enhancer-target regulatory network and identified downregulated DAPK1 as an important prognostic and diagnostic gene in HCC. Its potential biological functions and mechanisms were annotated using bioinformatics tools. [ABSTRACT FROM AUTHOR]

Cell type-specific gene expression is coordinated by DNA-encoded enhancers and the transcription factors (TFs) that bind to them in a sequence-specific manner. As such, these enhancers and TFs are critical mediators of normal development and altered enhancer or TF function is associated with the development of diseases such as cancer. While initially defined by their ability to activate gene transcription in reporter assays, putative enhancer elements are now frequently defined by their unique chromatin features including DNase hypersensitivity and transposase accessibility, bidirectional enhancer RNA (eRNA) transcription, CpG hypomethylation, high H3K27ac and H3K4me1, sequence-specific transcription factor binding, and co-factor recruitment. Identification of these chromatin features through sequencing-based assays has revolutionized our ability to identify enhancer elements on a genome-wide scale, and genome-wide functional assays are now capitalizing on this information to greatly expand our understanding of how enhancers function to provide spatiotemporal coordination of gene expression programs. Here, we highlight recent technological advances that are providing new insights into the molecular mechanisms by which these critical cis-regulatory elements function in gene control. We pay particular attention to advances in our understanding of enhancer transcription, enhancer-promoter syntax, 3D organization and biomolecular condensates, transcription factor and co-factor dependencies, and the development of genome-wide functional enhancer screens. [ABSTRACT FROM AUTHOR]

Fishes are ecologically important organisms that have long lifespans, high mobilities, and diverse trophic levels. Due to their importance, fishes are used as bioindicators for monitoring aquatic environments. One method for monitoring fishes is based on environmental DNA (eDNA), which are the deoxynucleic acids released by organisms into the environment. However, there has been a problem with false positives because eDNA is relatively stable in the environment and could even likely represent dead or non-inhabiting organisms. To address this weakness, environmental RNA (eRNA), which degrades more rapidly than eDNA in the environment, can be utilized to complement eDNA. But, to date, few studies have used eRNA for freshwater fish monitoring. In this study, to determine the relative usefulness of eDNA and eRNA metabarcoding in freshwater fishes, we performed eDNA and eRNA metabarcoding on 12S rRNA targeting fish using water samples that were collected from three locations in the Han River. We then calculated the sensitivity and positive predictivity of this approach by comparing our data to the previous specimen capture survey (PSCS) data from the last six years. The results showed that 42 species were detected by eDNA and 19 by eRNA at the three locations. At all locations, compared to the PSCS data, the average sensitivity was higher for eDNA (46.1%) than for eRNA (34.6%), and the average positive predictivity was higher for eRNA (31.7%) than for eDNA (20.7%). This confirmed that eDNA metabarcoding has the advantage of broadly determining species presence or absence (including those that are no longer present or dead), but it also generates false positives; meanwhile, eRNA metabarcoding reports living fish species, but detects fewer species than eDNA. Combining eDNA and eRNA therefore emphasizes their advantages and compensates for their disadvantages, and conducting this may therefore be useful for identifying false positives and monitoring the fish species that are actually present in the environment. This metabarcoding technique can be used in the future to provide insights into the aquatic environment and the monitoring of fisheries.

Abstract 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.

Cancer is driven by both genetic and epigenetic changes that impact on gene expression profiles and the resulting tumourigenic phenotype. Enhancers are transcriptional regulatory elements that are key to our understanding of how this rewiring of gene expression is achieved in cancer cells. Here, we have harnessed the power of RNA-seq data from hundreds of patients with oesophageal adenocarcinoma (OAC) or its precursor state Barrett’s oesophagus coupled with open chromatin maps to identify potential enhancer RNAs and their associated enhancer regions in this cancer. We identify ~1000 OAC-specific enhancers and use these data to uncover new cellular pathways that are operational in OAC. Among these are enhancers for JUP, MYBL2, and CCNE1, and we show that their activity is required for cancer cell viability. We also demonstrate the clinical utility of our dataset for identifying disease stage and patient prognosis. Our data therefore identify an important set of regulatory elements that enhance our molecular understanding of OAC and point to potential new therapeutic directions.

The genome is pervasively transcribed to produce a vast array of non-coding RNAs (ncRNAs). Long non-coding RNAs (lncRNAs) are transcripts of >200 nucleotides and are best known for their ability to regulate gene expression. Enhancer RNAs (eRNAs) are subclass of lncRNAs that are synthesized from enhancer regions and have also been shown to coordinate gene expression. The biological function and significance of most lncRNAs and eRNAs remain to be determined. Epithelial to mesenchymal transition (EMT) is a ubiquitous cellular process that occurs during cellular migration, homeostasis, fibrosis, and cancer-cell metastasis. EMT-transcription factors, such as SNAI1 induce a complex transcriptional program that coordinates the morphological and molecular changes associated with EMT. Such complex transcriptional programs are often subject to coordination by networks of ncRNAs and thus can be leveraged to identify novel functional ncRNA loci. Here, using a genome-wide CRISPR activation (CRISPRa) screen targeting ∼10,000 lncRNA loci we identified ncRNA loci that could either promote or attenuate EMT. We discovered a novel locus that we named SCREEM (SNAI1 cis-regulatory eRNAs expressed in monocytes). The SCREEM locus contained a cluster of eRNAs that when activated using CRISPRa induced expression of the neighboring gene SNAI1, driving concomitant EMT. However, the SCREEM eRNA transcripts themselves appeared dispensable for the induction of SNAI1 expression. Interestingly, the SCREEM eRNAs and SNAI1 were co-expressed in activated monocytes, where the SCREEM locus demarcated a monocyte-specific super-enhancer. These findings suggest a potential role for SNAI1 in monocytes. Exploration of the SCREEM-SNAI axis could reveal novel aspects of monocyte biology.

Nuclear receptors induce both transcriptional activation and repression programs responsible for development, homeostasis, and disease. Here, we report a previously overlooked enhancer decommissioning strategy underlying a large estrogen receptor alpha (ERα)-dependent transcriptional repression program. The unexpected signature for this E2-induced program resides in indirect recruitment of ERα to a large cohort of pioneer factor basally active FOXA1-bound enhancers that lack cognate ERα DNA-binding elements. Surprisingly, these basally active estrogen-repressed (BAER) enhancers are decommissioned by ERα-dependent recruitment of the histone demethylase KDM2A, functioning independently of its demethylase activity. Rather, KDM2A tethers the E3 ubiquitin-protein ligase NEDD4 to ubiquitylate/dismiss Pol II to abrogate eRNA transcription, with consequent target gene downregulation. Thus, our data reveal that Pol II ubiquitylation/dismissal may serve as a potentially broad strategy utilized by indirectly bound nuclear receptors to abrogate large programs of pioneer factor-mediated, eRNA-producing enhancers.

A vast number of different neuronal activity patterns could each induce a different set of activity-regulated genes. Mapping this coupling between activity pattern and gene induction would allow inference of a neuron's activity-pattern history from its gene expression and improve our understanding of activity-pattern-dependent synaptic plasticity. In genome-scale experiments comparing brief and sustained activity patterns, we reveal that activity-duration history can be inferred from gene expression profiles. Brief activity selectively induces a small subset of the activity-regulated gene program that corresponds to the first of three temporal waves of genes induced by sustained activity. Induction of these first-wave genes is mechanistically distinct from that of the later waves because it requires MAPK/ERK signaling but does not require de novo translation. Thus, the same mechanisms that establish the multi-wave temporal structure of gene induction also enable different gene sets to be induced by different activity durations.

Enhancers not only activate target promoters to stimulate messenger RNA (mRNA) synthesis, but they themselves also undergo transcription to produce enhancer RNAs (eRNAs), the significance of which is not well understood. Transcription at the participating enhancer- promoter pair appears coordinated, but it is unclear why and how. Here, we employ cell-free transcription assays using constructs derived from the human GREB1 locus to demonstrate that transcription at an enhancer and its target promoter is interdependent. This interdependence is observable under conditions where direct enhancer-promoter contact (EPC) takes place. We demonstrate that transcription activation at a participating enhancer-promoter pair is dependent on i) the mutual availability of the enhancer and promoter, ii) the state of transcription at both the enhancer and promoter, iii) local abundance of both eRNA and mRNA, and iv) direct EPC. Our results suggest transcriptional interdependence between the enhancer and the promoter as the basis of their transcriptional concurrence and coordination throughout the genome. We propose a model where transcriptional concurrence, coordination and interdependence are possible if the participating enhancer and promoter are entangled in the form of EPC, reside in a proteinaceous bubble, and utilize shared transcriptional resources and regulatory inputs. [ABSTRACT FROM AUTHOR]

Organisms release their nucleic acid in the environment, including the DNA and RNA, which can be used to detect their presence. eDNA/eRNA techniques are being used in different sectors to identify organisms from soil, water, air, and ice. The advancement in technology led to easier detection of different organisms without impacting the environment or the organism itself. These methods are being employed in different areas, including surveillance, history, and conservation. eDNA and eRNA methods are being extensively used in aquaculture and fisheries settings to understand the presence of different fish species and pathogens in water. However, there are some challenges associated with the reliability of results because of the degradation of nucleic acid by several factors. In aquaculture, there are several diseases and parasites detected with these methods. In this review, we discuss different aquaculture diseases and parasites detected with eDNA/eRNA approach and the fate of these nucleic acids when subjected to different water quality and environmental parameters. This review intends to help the researcher with the potential of eDNA/eRNA-based detection of pathogens in aquaculture; this will be useful to predict a potential outbreak before it occurs. Along with that, this paper intends to help people understand several factors that degrade and can hamper the detection of these nucleic acids. [ABSTRACT FROM AUTHOR]

eRNAs as the products of enhancers can regulate gene expression via various possible ways, but which regulation way is more reasonable is debatable in biology, and in particular, how eRNAs impact gene expression remains unclear. Here we introduce a mechanistic model of gene expression to address these issues. This model considers three possible regulation ways of eRNA: Type-I by which eRNA regulates transcriptional activity by facilitating the formation of enhancer-promoter (E-P) loop, Type-II by which eRNA directly promotes the mRNA production rate, and mixed regulation (i.e., the combination of Type-I and Type-II). We show that with the increase of the E-P loop length, mRNA distribution can transition from unimodality to bimodality or vice versa in all the three regulation cases. However, in contrast to the other two regulations, Type-II regulation can lead to the highest mean mRNA level and the lowest mRNA noise, independent of the E-P loop length. These results would not only reveal the essential mechanism of how eRNA regulates gene expression, but also imply a new mechanism for phenotypic switching, namely the E-P loop can induce phenotypic switching.

Background: Osteosarcoma (OS) is a common malignant tumor in osteoarticular system, the 5-year overall survival of which is poor. Enhancer RNAs (eRNAs) have been implicated in the tumorigenesis of various cancer types, whereas their roles in OS tumorigenesis remains largely unclear. Methods: Differentially expressed eRNAs (DEEs), transcription factors (DETFs), target genes (DETGs) were identified using limma (Linear Models for Microarray Analysis) package. Prognosis-related DEEs were accessed by univariate Cox regression analysis. A multivariate model was constructed to evaluate the prognosis of OS samples. Prognosis-related DEEs, DETFs, DETGs, immune cells, and hallmark gene sets were co-analyzed to construct an regulatory network. Specific inhibitors were also filtered by connectivity Map analysis. External validation and scRNA-seq analysis were performed to verify our key findings. Results: 3,981 DETGs, 468 DEEs, 51 DETFs, and 27 differentially expressed hallmark gene sets were identified. A total of Multivariate risk predicting model based on 18 prognosis-related DEEs showed a high accuracy (area under curve (AUC) = 0.896). GW-8510 was the candidate inhibitor targeting prognosis-related DEEs (mean = 0.670, p

Vast global declines of freshwater and marine fish diversity and population abundance pose serious threats to both ecosystem sustainability and human livelihoods. Environmental DNA (eDNA)-based biomonitoring provides robust, efficient, and cost-effective assessment of species occurrences and population trends in diverse aquatic environments. Thus, it holds great potential for improving conventional surveillance frameworks to facilitate fish conservation and fisheries management. However, the many technical considerations and rapid developments underway in the eDNA arena can overwhelm researchers and practitioners new to the field. Here, we systematically analysed 416 fish eDNA studies to summarize research trends in terms of investigated targets, research aims, and study systems, and reviewed the applications, rationales, methodological considerations, and limitations of eDNA methods with an emphasis on fish and fisheries research. We highlighted how eDNA technology may advance our knowledge of fish behaviour, species distributions, population genetics, community structures, and ecological interactions. We also synthesized the current knowledge of several important methodological concerns, including the qualitative and quantitative power eDNA has to recover fish biodiversity and abundance, and the spatial and temporal representations of eDNA with respect to its sources. To facilitate ecological applications implementing fish eDNA techniques, recent literature was summarized to generate guidelines for effective sampling in lentic, lotic, and marine habitats. Finally, we identified current gaps and limitations, and pointed out newly emerging research avenues for fish eDNA. As methodological optimization and standardization improve, eDNA technology should revolutionize fish monitoring and promote biodiversity conservation and fisheries management that transcends geographic and temporal boundaries. [ABSTRACT FROM AUTHOR]