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Results for “regulatory element transcripts”

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At least 19 recordsLinked to original sources

PubMed2026

Transposable element-driven expansion of enhancer RNA repertoires underlies regulatory innovation and polyploid adaptation in cereal crops.

Cereal genomes have undergone repeated polyploidization and transposable element (TE) proliferation, collectively generating complex regulatory landscapes. However, the evolutionary trajectories and functional implications of these landscapes remain largely unexplored. Using chromatin-bound RNA sequencing across seven cereal species, we systematically mapped 45,952 regulatory element transcripts (RETs), including 32,867 distal RETs corresponding to enhancer RNAs (eRNAs). Our analysis revealed that 56% of lineage-specific eRNAs originated from TE expansions, indicating that TEs serve as major reservoirs of species-specific regulatory innovation in cereals. Notably, we identified remarkable conservation in defense-related functions, root-specific expression, and TE-derived origins of eRNAs across both ancient and recent evolutionary layers of Triticeae, suggesting recurrent recruitment of TE-derived, root-associated regulatory elements throughout Triticeae evolution. Furthermore, we found that young eRNA pairs in hexaploid wheat with high sequence similarity, many originating from RLG_famc8.3 and DTC_famc4.3, exhibited pronounced root specificity and coordinated expression, suggesting targeted amplification and refinement of successful ancestral regulatory strategies established after Triticeae divergence. To facilitate community access, we developed Cereal-eRNAdb (http://bioinfo.cemps.ac.cn/Cereal-eRNAdb/), a comprehensive database integrating 69,426 eRNAs with functional annotations across 296 samples. Our findings suggest that TE-mediated innovation of root-specific eRNAs may contribute to Triticeae adaptation and provide a foundational resource for exploiting regulatory variation in cereal crop breeding.

Enhancer RNAs↗

PubMed2024

A computational model for bacteriophage ϕX174 gene expression.

Bacteriophage ϕX174 has been widely used as a model organism to study fundamental processes in molecular biology. However, several aspects of ϕX174 gene regulation are not fully resolved. Here we construct a computational model for ϕX174 and use the model to study gene regulation during the phage infection cycle. We estimate the relative strengths of transcription regulatory elements (promoters and terminators) by fitting the model to transcriptomics data. We show that the specific arrangement of a promoter followed immediately by a terminator, which occurs naturally in the ϕX174 genome, poses a parameter identifiability problem for the model, since the activity of one element can be partially compensated for by the other. We also simulate ϕX174 gene expression with two additional, putative transcription regulatory elements that have been proposed in prior studies. We find that the activities of these putative elements are estimated to be weak, and that variation in ϕX174 transcript abundances can be adequately explained without them. Overall, our work demonstrates that ϕX174 gene regulation is well described by the canonical set of promoters and terminators widely used in the literature.

Gene Expression Regulation, Viral↗

PubMed2026

Regulatory mechanisms of maternal imprinting at the murine Dlk1-Dio3 domain.

Genomic imprinting is an epigenetic process causing parent-of-origin specific gene expression. The Dlk1-Dio3 domain is one of the largest imprinted clusters. While DNA methylation at an intergenic CpG-island (IG-CGI) within the imprinting control region (ICR) controls expression from the paternal chromosome, mechanisms regulating the unmethylated maternal chromosome remain unknown. Within the transcriptional regulatory element (IG-TRE) of the ICR, deletions identified a minimal region in vitro exhibiting both silencing and enhancing activity, with SOX2 and ZFP281 contributing to enhancer function on the maternal chromosome. In vivo, however, this deletion did not affect maternal expression in mouse embryos; instead it activated Dlk1 on both parental chromosomes. Combining deletion of this IG-TRE with the lethal IG-CGI deletion rescued lethality in mice by balancing Dlk1 expression, despite persistent maternal gene upregulation. These results demonstrate that loss of expression at this domain is more detrimental than gain, highlighting the importance of in vivo analysis. Identification of active regulatory factors on the unmethylated maternal chromosome challenges the prevailing view that imprinting is primarily a methylation-driven phenomenon, further revealing the sophisticated hierarchical mechanisms governing imprinting control.

Animals↗

PubMed2024

Cis-regulatory control of transcriptional timing and noise in response to estrogen.

Cis-regulatory elements control transcription levels, temporal dynamics, and cell-cell variation or transcriptional noise. However, the combination of regulatory features that control these different attributes is not fully understood. Here, we used single-cell RNA-seq during an estrogen treatment time course and machine learning to identify predictors of expression timing and noise. We found that genes with multiple active enhancers exhibit faster temporal responses. We verified this finding by showing that manipulation of enhancer activity changes the temporal response of estrogen target genes. Analysis of transcriptional noise uncovered a relationship between promoter and enhancer activity, with active promoters associated with low noise and active enhancers linked to high noise. Finally, we observed that co-expression across single cells is an emergent property associated with chromatin looping, timing, and noise. Overall, our results indicate a fundamental tradeoff between a gene's ability to quickly respond to incoming signals and maintain low variation across cells.

Humans↗

PubMed2025

The Fire Ant Social Chromosome Exerts a Major Influence on Genome Regulation.

Supergenes underlying complex trait polymorphisms ensure that sets of coadapted alleles remain genetically linked. Despite their prevalence in nature, the mechanisms of supergene effects on genome regulation are poorly understood. In the fire ant Solenopsis invicta, a supergene containing over 500 individual genes influences trait variation in multiple castes to collectively underpin a colony level social polymorphism. Here, we present results of an integrative investigation of supergene effects on gene regulation. We present analyses of ATAC-seq data to investigate variation in chromatin accessibility by supergene genotype and STARR-seq data to characterize enhancer activity by supergene haplotype. Integration with gene co-expression analyses, newly mapped intact transposable elements (TEs), and previously identified copy number variants (CNVs) collectively reveals widespread effects of the supergene on chromatin structure, gene transcription, and regulatory element activity, with a genome-wide bias for open chromatin and increased expression in the presence of the derived supergene haplotype, particularly in regions that harbor intact TEs. Integrated consideration of CNVs and regulatory element divergence suggests each evolved in concert to shape the expression of supergene encoded factors, including several transcription factors that may directly contribute to the trans-regulatory footprint of a heteromorphic social chromosome. Overall, we show how genome structure in the form of a supergene has wide-reaching effects on gene regulation and gene expression.

Animals↗

PubMed2026

Protocol to predict gene expression from transcriptomic data using PREDICT.

Linking DNA sequence variation to context-specific transcriptional programs is a critical challenge in regulatory genomics, especially for non-model organisms. Here, we present PREDICT, a modular Python package for discovering cis-regulatory elements and transcription factor binding motifs. We describe steps to identify enriched k-mers from differentially expressed genes, map them to known motifs, quantify their impact on gene expression, and visualize motif co-occurrences. PREDICT provides a robust, k-mer-based approach to uncover regulatory logic in diverse genomic systems. For complete details on the use and execution of this protocol, please refer to Yen et al. and Liu et al.1,2.

Gene Expression Profiling↗

PubMed2025

Tracing regulatory element networks using epigenetic traits to identify key transcription factors: TENET R/Bioconductor package.

SUMMARY: There is a lack of publicly available bioinformatic tools that can be widely used by researchers to identify transcription factors (TFs) that regulate cell type-specific regulatory elements (REs). To address this, we developed the Tracing regulatory Element Networks using Epigenetic Traits (TENET) R/Bioconductor package. By collecting hundreds of histone mark and open chromatin datasets from a variety of cell lines, primary cells, and tissues, and comparing these features along with matched DNA methylation and gene expression data, TENET identifies TFs and REs linked to a specific cell type. Moreover, we developed methods to interrogate findings using motifs, clinical information, and other genomic and chromatin conformation capture datasets, and applied them to pan-cancer data, highlighting TFs and REs associated with ten different cancer types. TENET enables researchers to better characterize the 3D epigenomes of cell types of interest for future clinical applications. AVAILABILITY AND IMPLEMENTATION: TENET is available at http://bioconductor.org/packages/TENET. Curated functional genomic datasets utilized by TENET are available at http://bioconductor.org/packages/TENET.AnnotationHub. Example datasets are available at http://bioconductor.org/packages/TENET.ExperimentHub.

Transcription Factors↗

PubMed2026

Small Copy Number Neutral Intrachromosomal Translocation of PAX6 and Aniridia.

IMPORTANCE: Approximately 5% to 10% of individuals with classic aniridia do not receive a molecular diagnosis after clinical testing for variants in PAX6 and its downstream regulatory region. OBJECTIVE: To apply optical genome mapping (OGM) and long-read whole-genome sequencing (lrWGS) to diagnose an individual with unexplained classic aniridia. DESIGN, SETTING, AND PARTICIPANTS: High-quality DNA was extracted from the blood of a 16-year-old male patient with classic aniridia and prior negative clinical test results that included sequencing and copy number analysis of PAX6 exons and downstream regulatory region as well as genomic analysis via short-read whole-genome sequencing (srWGS) and analyzed using OGM and lrWGS. All analyses were performed in a research laboratory in Wisconsin from January 2019 to September 2025. INTERVENTIONS: OGM and lrWGS. MAIN OUTCOMES AND MEASURES: Identification of a structural variant disrupting PAX6 expression in an individual with classic aniridia, following negative prior testing including srWGS. RESULTS: OGM identified a 55-kb deletion on 11p13 encompassing all PAX6 exons and exon 12 of ELP4, with insertion of this segment into 11q21. lrWGS delineated the exact breakpoints, confirming that the downstream regulatory region, required for normal PAX6 expression, remained at the 11p13 locus. Consequently, the translocated copy of PAX6 at 11q21 is expected to lack expression due to the loss of its essential regulatory elements. CONCLUSIONS AND RELEVANCE: These findings in an individual with classic aniridia harboring an intrachromosomal rearrangement at the PAX6 locus identified by OGM and lrWGS may represent the smallest reported structural variant to separate the PAX6 coding sequence from its downstream regulatory region. This structural variant may have fallen below the detection threshold of srWGS due to its balanced nature and small size, suggesting OGM and lrWGS would be needed for definitive identification.

Aniridia↗

PubMed2026

ChromBERT-tools: a versatile toolkit for context-specific regulatory representations of transcription regulators across different cell types.

SUMMARY: Representations that encode the genome-wide regulatory behavior of transcription regulators provide a foundation for flexible transcription modeling and in silico regulatory analysis. Existing regulator representations are commonly derived from gene co-expression, motif annotations, or static protein features, which capture useful but limited aspects of regulator identity but do not directly model how regulators participate in region-specific regulatory programs across the genome. ChromBERT addresses this gap by learning context-aware regulatory representations from large-scale ChIP-seq data. However, routine bioinformatics applications require lightweight, accessible, and modular tools for generating, adapting, and interpreting these representations in user-defined biological contexts. Here, we present ChromBERT-tools, a user-oriented toolkit built upon ChromBERT that converts its regulatory representation framework into practical workflows for customizable analysis across cellular contexts. ChromBERT-tools provides command-line interfaces and Python APIs organized into three functional layers: representation generation, predictive modeling, and regulatory interpretation. The representation generation layer produces representations of genomic regions and transcription regulators. The predictive modeling layer fine-tunes ChromBERT for genome-wide regulatory activity prediction through classification or regression tasks, with optimized implementation to reduce running time and computational resource requirements. The regulatory interpretation layer supports inference of the context-specific roles of cis-regulatory elements and transcription regulators. These modules can be used independently or integrated into end-to-end workflows, enabling flexible analyses across diverse datasets. ChromBERT-tools lowers the barrier to applying context-specific regulatory representations in routine genomic analyses. AVAILABILITY AND IMPLEMENTATION: ChromBERT-tools is freely available at https://github.com/TongjiZhanglab/ChromBERT-tools, with documentation at https://chrombert-tools.readthedocs.io/en/latest/. A frozen archival snapshot is available on Zenodo under DOI: 10.5281/zenodo.20094206.

Software↗

PubMed2026

PETScan: score-based genome-wide association analysis of RNA-Seq and ATAC-Seq data.

MOTIVATION: High-dimensional sequencing data, such as RNA-Seq for gene expression and ATAC-Seq for chromatin accessibility, are widely used in studying systems biology. Accessible chromatin allows transcription factors and regulatory elements to bind to DNA, thereby regulating transcription through the activation or repression of target genes. The association analysis of RNA-Seq and ATAC-Seq data provides insights into gene regulatory mechanisms. Most existing analytic tools exclusively focus on cis-associations, despite regulatory elements being able to physically interact with distant target genes. Furthermore, conventional approaches often utilize Pearson or Spearman correlations, which ignore the count-based nature of RNA-Seq data. RESULTS: To address these limitations, we introduce PETScan, a computationally efficient genome-wide PEak-Transcript Score-based association analysis, utilizing negative binomial models to better accommodate RNA-Seq data. We leverage score tests and matrix calculations for improved computational efficiency, and combine an empirical permutation method with genomic control to ensure valid p-value calculations in studies with limited sample sizes. In real-world datasets, PETScan achieved three orders of magnitude faster than Wald tests, while identifying similar significant gene-peak pairs. AVAILABILITY: The PETScan R package is available on GitHub at https://github.com/yajing-hao/PETScan.

Chromatin Immunoprecipitation Sequencing↗

PubMed2025

Through the lens of bioenergy crops: advances, bottlenecks, and promises of plant engineering.

Advances in engineering of bioenergy crops were driven over the past years by adapting technological breakthroughs and accelerating conventional applications but also exposed intriguing challenges. New tools revealed rich interconnectivity in the exponentially growing and dynamic 'big' omics data' of metabolomes, transcriptomes, and genomes at previously inaccessible magnitude (global, cross-species, meta-) and resolution (single cell). Insights enabled fresh hypotheses and stimulated disciplines such as functional genomics with discovery of broad regulatory networks and their determinants, that is, DNA parts, including promoters, regulatory elements, and transcription factors. Their rational design, assembly into increasingly complex blueprints, and installation into diverse chassis is an existing frontier that may benefit from emerging technologies to address bottlenecks. Interweaving nature-inspired to fully synthetic parts has already allowed building of fine-tuned regulatory circuits, or new-to-nature metabolic routes insulated from the biological context of the chassis species. Similarly, developments and the evolving need for unifying principles in plant transformation and species-agnostic technologies highlight future opportunities for engineering the next generation of bioenergy plants.

Crops, Agricultural↗

PubMed2027

Inferring Gene Regulatory Networks in Stem Cells: Methods and Applications.

Gene regulatory networks (GRNs) represent the complex interplay of transcription factors, regulatory elements, and target genes that orchestrate cellular identity and function, playing a crucial role in the differentiation and maintenance of stem cells. This chapter provides an overview of experimental and computational methodologies for inferring GRNs, with particular emphasis on single-cell approaches. We first review key experimental techniques for detecting transcription factor binding sites, chromatin accessibility, and DNA motifs, alongside essential databases that support GRN reconstruction. We then introduce computational inference methods that can be categorized into four principal frameworks: correlation-based approaches, regression and machine learning models, probabilistic and deep learning methods, and integrative or message-passing frameworks. To illustrate practical application, we present a case study applying the pySCENIC workflow to a peripheral blood mononuclear cell single-cell RNA sequencing dataset from mouse, demonstrating how regulon-based analysis can reveal cell-type-specific regulatory programs. This chapter aims to serve as a practical guide for researchers seeking to understand and implement GRN inference methodologies in stem cell biology and related fields.

Gene Regulatory Networks↗

PubMed2026

Identifying transcription factors controlling the basal expression of human MRP4 highlights a substantial role for Sp1.

The multidrug resistance protein 4 (MRP4/ABCC4) is a versatile efflux pump, known to transport several drugs but also signaling molecules such as cyclic nucleotides and lipid mediators. Based on this substrate spectrum and its broad tissue distribution, MRP4 plays a significant physiological and pathophysiological role in both the cardiovascular and oncological fields. However, the determinants of its gene expression are still incompletely defined. This study aimed to identify key regulatory elements and transcription factors that are essential for basal MRP4 expression. Using luciferase reporter assays with a series of 5'-deletion constructs, we identified a region upstream of the transcription start site as crucial for basal expression across diverse cell types. This region is evolutionary highly conserved and contains putative binding sites for Sp1 and Ets transcription factors. Site-directed mutagenesis of both binding elements resulted in a significant decrease in the promoter activity in HeLa and megakaryoblastic M07e cells. The binding of Sp1 to this region was further confirmed by electrophoretic mobility shift and chromatin immunoprecipitation assays. Finally, siRNA knockdown of Sp1 led to a significant decrease in MRP4 protein levels and function. In summary, we show that Sp1 binds to the MRP4 promoter and plays an essential role in the basal expression of MRP4, with Ets factors also potentially cooperating in this regulation.

Humans↗

PubMed2020

Glucocorticoids mobilize macrophages by transcriptionally up-regulating the exopeptidase DPP4.

Glucocorticoids are potent endogenous anti-inflammatory molecules, and their cognate receptor, glucocorticoid receptor (GR), is expressed in nearly all immune cells. Macrophages are heterogeneous immune cells having a central role in both tissue homeostasis and inflammation and also play a role in the pathogenesis of some inflammatory diseases. Paradoxically, glucocorticoids have only a limited efficacy in controlling the resolution of these macrophage-related diseases. Here, we report that the transcriptomes of monocyte-like THP-1 cells and macrophage-like THP-1 cells (THP1-MΦ) have largely conserved gene expression patterns. In contrast, the differentiation to THP1-MΦ significantly altered the sensitivity of gene transcription to glucocorticoids. Among glucocorticoid-regulated genes, we identified the exopeptidase dipeptidyl peptidase-4 (DPP4) as a critical glucocorticoid-responsive gene in THP1-MΦ. We found that GR directly induces DPP4 gene expression by binding to two glucocorticoid-responsive elements (GREs) within the DPP4 promoter. Additionally, we show that glucocorticoid-induced DPP4 expression is blocked by the GR antagonist RU-486 and by GR siRNA transfection and that DPP4 enzyme activity is reduced by DPP4 inhibitors. Of note, glucocorticoids highly stimulated macrophage mobility; unexpectedly, DPP4 mediated the glucocorticoid-induced macrophage migration, and siRNA-mediated knockdowns of GR and DPP4 blocked dexamethasone-induced THP1-MΦ migration. Moreover, glucocorticoid-induced DPP4 activation was also observed in proinflammatory M1-polarized murine macrophages, as well as peritoneal macrophages, and was associated with increased macrophage migration. Our results indicate that glucocorticoids directly up-regulate DPP4 expression and thereby induce migration in macrophages, potentially explaining why glucocorticoid therapy is less effective in controlling macrophage-dominated inflammatory disorders.

Animals↗

PubMed2023

H3.3 contributes to chromatin accessibility and transcription factor binding at promoter-proximal regulatory elements in embryonic stem cells.

BACKGROUND: The histone variant H3.3 is enriched at active regulatory elements such as promoters and enhancers in mammalian genomes. These regions are highly accessible, creating an environment that is permissive to transcription factor binding and the recruitment of transcriptional coactivators that establish a unique chromatin post-translational landscape. How H3.3 contributes to the establishment and function of chromatin states at these regions is poorly understood. RESULTS: We perform genomic analyses of features associated with active promoter chromatin in mouse embryonic stem cells (ESCs) and find evidence of subtle yet widespread promoter dysregulation in the absence of H3.3. Loss of H3.3 results in reduced chromatin accessibility and transcription factor (TF) binding at promoters of expressed genes in ESCs. Likewise, enrichment of the transcriptional coactivator p300 and downstream histone H3 acetylation at lysine 27 (H3K27ac) is reduced at promoters in the absence of H3.3, along with reduced enrichment of the acetyl lysine reader BRD4. Despite the observed chromatin dysregulation, H3.3 KO ESCs maintain transcription from ESC-specific genes. However, upon undirected differentiation, H3.3 KO cells retain footprinting of ESC-specific TF motifs and fail to generate footprints of lineage-specific TF motifs, in line with their diminished capacity to differentiate. CONCLUSIONS: H3.3 facilitates DNA accessibility, transcription factor binding, and histone post-translational modification at active promoters. While H3.3 is not required for maintaining transcription in ESCs, it does promote de novo transcription factor binding which may contribute to the dysregulation of cellular differentiation in the absence of H3.3.

Animals↗

PubMed2019

Profiling the long noncoding RNA interaction network in the regulatory elements of target genes by chromatin in situ reverse transcription sequencing.

Long noncoding RNAs (lncRNAs) can regulate the activity of target genes by participating in the organization of chromatin architecture. We have devised a "chromatin-RNA in situ reverse transcription sequencing" (CRIST-seq) approach to profile the lncRNA interaction network in gene regulatory elements by combining the simplicity of RNA biotin labeling with the specificity of the CRISPR/Cas9 system. Using gene-specific gRNAs, we describe a pluripotency-specific lncRNA interacting network in the promoters of Sox2 and Pou5f1, two critical stem cell factors that are required for the maintenance of pluripotency. The promoter-interacting lncRNAs were specifically activated during reprogramming into pluripotency. Knockdown of these lncRNAs caused the stem cells to exit from pluripotency. In contrast, overexpression of the pluripotency-associated lncRNA activated the promoters of core stem cell factor genes and enhanced fibroblast reprogramming into pluripotency. These CRIST-seq data suggest that the Sox2 and Pou5f1 promoters are organized within a unique lncRNA interaction network that determines the fate of pluripotency during reprogramming. This CRIST approach may be broadly used to map lncRNA interaction networks at target loci across the genome.

Animals↗

PubMed2026

Transcriptional perturbation of LINE-1 elements reveals their cis-regulatory potential.

Long interspersed element-1 (LINE-1 or L1) retrotransposons constitute the largest transposable element family in mammalian genomes and contribute prominently to inter- and intra-individual genetic variation. Although most L1 elements are inactive, some evolutionary younger elements remain intact and genetically competent for transcription and occasionally retrotransposition. Despite being generally more abundant in gene-poor regions, intact or full-length L1s (FL-L1) are also enriched around specific classes of genes and on the eutherian X chromosome. How proximal FL-L1 may affect nearby gene expression remains unclear. Here, we examine this systematically using engineered mouse embryonic stem cells (ESCs) in which expression of one active L1 subfamily is perturbed. We find that FL-L1 activation leads to the misregulation of ~1024 genes, whereas FL-L1 repression affects ~81 genes. In most cases (68%), misexpressed genes contain an intronic FL-L1 or lie near a FL-L1 (< 260 kb). Gene ontology analysis shows that upon L1 activation, upregulated genes are enriched for neuronal function-related terms, suggesting that some L1 elements may have evolved to control neuronal gene networks. These results illustrate the cis-regulatory potential of FL-L1 elements and suggest a broader role for L1s than originally anticipated.

Animals↗

PubMed2026

Genetic Deletion of Cis-Regulatory Elements to Dissect the Function of the Non-coding Genome in human Preimplantation Models.

Cis-regulatory elements coordinate gene expression in a spatially and temporally controlled manner and contribute to the establishment of distinct cellular states during development. A substantial proportion of transcriptionally active cis-regulatory elements in primate embryos originated from ancient retroviral integrations into the germline. These endogenous retroviruses, also known as long terminal repeat retrotransposons, retain intrinsic regulatory activity and are often species-specific, making them strong candidates for regulating species-divergent aspects of embryonic development. Ethical and legal restrictions on human embryo research have historically limited direct investigation of gene regulation during human embryogenesis. Human naive pluripotent stem cells and three-dimensional stem cell-based blastocyst models provide alternative systems for studying early developmental processes. This protocol describes the CRISPR-Cas9-mediated deletion of endogenous retrovirus-derived cis-regulatory elements in human naive pluripotent stem cells. Preassembled Cas9 and single-guide RNA ribonucleoprotein complexes are delivered by nucleofection, followed by single-cell cloning, PCR-based genotyping, Sanger sequencing, expansion, cryopreservation, and genomic stability assessment of the edited lines. The resulting wild-type, heterozygous, and homozygous or hemizygous deletion clones provide a platform for investigating the contribution of individual endogenous retrovirus-derived elements to gene regulation in human preimplantation models. This method enables direct functional interrogation of species-specific non-coding regulatory sequences and supports the study of transcriptional mechanisms involved in early human development.

Humans↗