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

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

Macrophages derived from human induced pluripotent stem cells (iPSCs) serve as a high-fidelity cellular model for investigating HIV-1, dengue, and influenza viruses.

Macrophages are important target cells for diverse viruses and thus represent a valuable system for studying virus biology. Isolation of primary human macrophages is done by culture of dissociated tissues or from differentiated blood monocytes, but these methods are both time consuming and result in low numbers of recovered macrophages. Here, we explore whether macrophages derived from human induced pluripotent stem cells (iPSCs)-which proliferate indefinitely and potentially provide unlimited starting material-could serve as a faithful model system for studying virus biology. Human iPSC-derived monocytes were differentiated into macrophages and then infected with HIV-1, dengue virus, or influenza virus as model human viruses. We show that iPSC-derived macrophages support the replication of these viruses with kinetics and phenotypes similar to human blood monocyte-derived macrophages. These iPSC-derived macrophages were virtually indistinguishable from human blood monocyte-derived macrophages based on surface marker expression (flow cytometry), transcriptomics (RNA sequencing), and chromatin accessibility profiling. iPSC lines were additionally generated from non-human primate (chimpanzee) fibroblasts. When challenged with dengue virus, human and chimpanzee iPSC-derived macrophages show differential susceptibility to infection, thus providing a valuable resource for studying the species-tropism of viruses. We also show that blood- and iPSC-derived macrophages both restrict influenza virus at a late stage of the virus lifecycle. Collectively, our results substantiate iPSC-derived macrophages as an alternative to blood monocyte-derived macrophages for the study of virus biology. IMPORTANCE: Macrophages have complex relationships with viruses: while macrophages aid in the removal of pathogenic viruses from the body, macrophages are also manipulated by some viruses to serve as vessels for viral replication, dissemination, and long-term persistence. Here, we show that iPSC-derived macrophages are an excellent model that can be exploited in virology.

Internal and external normalization of nascent RNA sequencing run-on experiments.

In experiments with significant perturbations to transcription, nascent RNA sequencing protocols are dependent on external spike-ins for reliable normalization. Unlike in RNA-seq, these spike-ins are not standardized and, in many cases, depend on a run-on reaction that is assumed to have constant efficiency across samples. To assess the validity of this assumption, we analyze a large number of published nascent RNA spike-ins to quantify their variability across existing normalization methods. Furthermore, we develop a new biologically-informed Bayesian model to estimate the error in spike-in based normalization estimates, which we term Virtual Spike-In (VSI). We apply this method both to published external spike-ins as well as using reads at the [Formula: see text] end of long genes, building on prior work from Mahat (Mol Cell 62(1):63-78, 2016. https://doi.org/10.1016/j.molcel.2016.02.025 ) and Vihervaara (Nat Commun 8(1):255, 2017. https://doi.org/10.1038/s41467-017-00151-0 ). We find that spike-ins in existing nascent RNA experiments are typically under sequenced, with high variability between samples. Furthermore, we show that these high variability estimates can have significant downstream effects on analysis, complicating biological interpretations of results.

Cellular zinc status alters chromatin accessibility and binding of transcription factor p53 to genomic sites.

Zinc (Zn2+) is an essential metal required by approximately 2500 proteins. Nearly half of these proteins act on DNA, including > 850 human transcription factors, polymerases, DNA damage response factors, and proteins involved in chromatin architecture. How these proteins acquire their essential Zn2+ cofactor and whether they are sensitive to changes in the labile Zn2+ pool in cells remain open questions. Here, we examine how changes in the labile Zn2+ pool affect chromatin accessibility and transcription factor binding to DNA. We observed both increases and decreases in accessibility in different chromatin regions via ATAC-seq upon treating MCF10A cells with elevated Zn2+ or the Zn2+-specific chelator tris(2-pyridylmethyl)amine (TPA). Transcription factor enrichment analysis was used to correlate changes in chromatin accessibility with transcription factor motifs, revealing 477 transcription factor motifs that were differentially enriched upon Zn2+ perturbation. 186 of these transcription factor motifs were enriched in Zn2+ and depleted in TPA, and the majority correspond to Zn2+ finger transcription factors. We selected TP53 as a candidate to examine how changes in motif enrichment correlate with changes in transcription factor occupancy by ChIP-qPCR. Using publicly available ChIP-seq and nascent transcription datasets, we narrowed the 50,000+ ATAC-seq peaks to 2164 TP53 targets and subsequently selected 6 high-probability TP53 binding sites for testing. ChIP-qPCR revealed that for 5 of the 6 targets, TP53 binding correlates with the local accessibility determined by ATAC-seq. These results demonstrate that changes in labile zinc directly alter chromatin accessibility and transcription factor binding to DNA.

An intronic LINE-1 regulates IFNAR1 expression in human immune cells.

BACKGROUND: Despite their origins as selfish parasitic sequences, some transposons in the human genome have been co-opted to serve as regulatory elements, contributing to the evolution of transcriptional networks. Most well-characterized examples of transposon-derived regulatory elements derive from endogenous retroviruses (ERVs), due to the intrinsic regulatory activity of proviral long terminal repeat regions. However, one subclass of transposable elements, the Long Interspersed Nuclear Elements (LINEs), have been largely overlooked in the search for functional regulatory transposons, and considered to be broadly epigenetically repressed. RESULTS: We examined the chromatin state of LINEs by analyzing epigenomic data from human immune cells. Many LINEs are marked by the repressive H3K9me3 modification, but a subset exhibits evidence of enhancer activity in human immune cells despite also showing evidence of epigenetic repression. We hypothesized that these competing forces of repressive and activating epigenetic marks might lead to inducible enhancer activity. We investigated a specific L1M2a element located within the first intron of Interferon Alpha/Beta Receptor 1 (IFNAR1). This element shows epigenetic signatures of B cell-specific enhancer activity, despite being repressed by the Human Silencing Hub (HUSH) complex. CRISPR deletion of the element in B lymphoblastoid cells revealed that the element acts as an enhancer that regulates both steady state and interferon-inducible expression of IFNAR1. CONCLUSIONS: Our study experimentally demonstrates that an L1M2a element was co-opted to function as an interferon-inducible enhancer of IFNAR1, creating a feedback loop wherein IFNAR1 is transcriptionally upregulated by interferon signaling. This finding suggests that other LINEs may exhibit cryptic cell type-specific or context-dependent enhancer activity. LINEs have received less attention than ERVs in the effort to understand the contribution of transposons to the regulatory landscape of cellular genomes, but these are likely important, lineage-specific players in the rapid evolution of immune system regulatory networks and deserve further study.

Atlas of nascent RNA transcripts reveals enhancer to gene linkages.

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

Human mRNA in saliva can correctly identify individuals harboring acute infection.

The COVID-19 pandemic demonstrated the poor ability of body temperature to reliably identify SARS-CoV-2-infected individuals, an observation that has been made before in the context of other infectious diseases. While acute infection does not always cause fever, it does reliably drive host transcriptional responses as the body responds at the site of infection. These transcriptional changes can occur both in cells that are directly harboring replicating pathogens and in cells elsewhere that receive a molecular signal that infection is occurring. Here, we identify a core set of approximately 70 human genes that are together upregulated in cultured human cells infected by a broad array of viral, bacterial, and fungal pathogens. We have named these "core response" genes. In theory, transcripts from these genes could serve as biomarkers of infection in the human body, in a way that is agnostic to the specific pathogen causing infection. As such, we perform human studies to show that these infection-induced human transcripts can be measured in the saliva of people harboring different types of infections. The number of these transcripts in saliva can correctly classify infection status (whether a person harbors an infection) 91% of the time. Furthermore, in the case of SARS-CoV-2 specifically, the number of core response transcripts in saliva correctly identifies infectious individuals even when enrollees, themselves, are asymptomatic and do not know they are infected.IMPORTANCEThere are a variety of clinical and laboratory criteria available to clinicians in controlled healthcare settings to help them identify whether an infectious disease is present. However, in situations such as a new epidemic caused by an unknown infectious agent, in health screening contexts performed within communities and outside of healthcare facilities or in battlefield or potential biowarfare situations, this gets more difficult. Pathogen-agnostic methods for rapid screening and triage of large numbers of people for infection status are needed, in particular methods that might work on an easily accessible biospecimen like saliva. Here, we identify a small, core set of approximately 70 human genes whose transcripts serve as saliva-based biomarkers of infection in the human body, in a way that is agnostic to the specific pathogen causing infection.

Transcription dosage compensation does not occur in Down syndrome.

BACKGROUND: The increase in DNA copy number in Down syndrome (DS; caused by trisomy 21) has led to the DNA dosage hypothesis, which posits that the level of gene expression is proportional to the gene's DNA copy number. Yet many reports have suggested that a proportion of chromosome 21 genes are dosage compensated back towards typical expression levels (1.0×). In contrast, other reports suggest that dosage compensation is not a common mechanism of gene regulation in trisomy 21, providing support to the DNA dosage hypothesis. RESULTS: In our work, we use both simulated and real data to dissect the elements of differential expression analysis that can lead to the appearance of dosage compensation, even when compensation is demonstrably absent. Using lymphoblastoid cell lines derived from a family with an individual with Down syndrome, we demonstrate that dosage compensation is nearly absent at both nascent transcription (GRO-seq) and steady-state RNA (RNA-seq) levels. Furthermore, we link the limited apparent dosage compensation to expected allelic variation in transcription levels. CONCLUSIONS: Transcription dosage compensation does not occur in Down syndrome. Simulated data containing no dosage compensation can appear to have dosage compensation when analyzed via standard methods. Moreover, some chromosome 21 genes that appear to be dosage compensated are consistent with allele specific expression.

Mediator kinase inhibition suppresses hyperactive interferon signaling in Down syndrome.

Hyperactive interferon (IFN) signaling is a hallmark of Down syndrome (DS), a condition caused by trisomy 21 (T21); strategies that normalize IFN signaling could benefit this population. Mediator-associated kinases CDK8 and CDK19 drive inflammatory responses through incompletely understood mechanisms. Using sibling-matched cell lines with/without T21, we investigated Mediator kinase function in the context of hyperactive IFN in DS. Activation of IFN-response genes was suppressed in cells treated with the CDK8/CDK19 inhibitor cortistatin A, and this occurred through suppression of IFN-responsive transcription factor activity. Moreover, we discovered that CDK8/CDK19 affect splicing, a novel means by which Mediator kinases control gene expression. Kinase inhibition altered splicing in pathway-specific ways and selectively affected IFN-responsive gene splicing in T21 cells. To further probe Mediator kinase function, we completed cytokine screens and untargeted metabolomics experiments. Cytokines are master regulators of inflammatory responses; by screening 105 different cytokine proteins, we show that Mediator kinases help drive IFN-dependent cytokine responses at least in part through transcriptional regulation of cytokine genes and receptors. Metabolomics revealed that Mediator kinase inhibition altered core metabolic pathways, including broad up-regulation of anti-inflammatory lipid mediators. Elevated levels of lipid mediators persisted at least 24hr after Mediator kinase inhibition, and many identified lipids serve as ligands for nuclear receptors (e.g. PPAR, LXR) or G-protein coupled receptors (GPCRs; e.g. FFAR4). Notably, ligand-dependent activation of these GPCRs or nuclear receptors will propagate anti-inflammatory signaling pathways and gene expression programs, and this mechanistic link suggests that metabolic changes caused by CDK8/CDK19 inhibition can durably and independently suppress pro-inflammatory IFN responses. Collectively, our results establish that Mediator kinase inhibition antagonizes IFN signaling through transcriptional, metabolic, and cytokine responses, with implications for DS and other chronic inflammatory conditions.

Transcription dosage compensation does not occur in Down syndrome.

Background: Trisomy 21, also known as Down syndrome, describes the genetic condition of having an extra copy of chromosome 21. The increase in DNA copy number has led to the "DNA dosage hypothesis", which claims that the level of gene transcription is proportional to the gene's DNA copy number. Yet many reports have suggested that a proportion of chromosome 21 genes are dosage compensated back towards typical expression levels (1.0x). In contrast, other reports suggest that dosage compensation is not a common mechanism of gene regulation in Trisomy 21, providing support to the DNA dosage hypothesis. Results: In our work, we use both simulated and real data to dissect the elements of differential expression analysis that can lead to the appearance of dosage compensation even when compensation is demonstrably absent. Using lymphoblastoid cell lines derived from a family of an individual with Down syndrome, we demonstrate that dosage compensation is nearly absent at both nascent transcription (GRO-seq) and steady-state RNA (RNA-seq) levels. Conclusions: Transcriptional dosage compensation does not occur in Down syndrome. Simulated data containing no dosage compensation can appear to have dosage compensation when analyzed via standard methods. Moreover, some chromosome 21 genes that appear to be dosage compensated are consistent with allele specific expression.

Determination of steady-state transcriptome modifications associated with repeated homotypic stress in the rat rostral posterior hypothalamic region.

Chronic stress is epidemiologically correlated with physical and psychiatric disorders. Whereas many animal models of chronic stress induce symptoms of psychopathology, repeated homotypic stressors to moderate intensity stimuli typically reduce stress-related responses with fewer, if any, pathological symptoms. Recent results indicate that the rostral posterior hypothalamic (rPH) region is a significant component of the brain circuitry underlying response reductions (habituation) associated with repeated homotypic stress. To test whether posterior hypothalamic transcriptional regulation associates with the neuroendocrine modifications induced by repeated homotypic stress, RNA-seq was performed in the rPH dissected from adult male rats that experienced either no stress, 1, 3, or 7 stressful loud noise exposures. Plasma samples displayed reliable increases of corticosterone in all stressed groups, with the smallest increase in the group exposed to 7 loud noises, indicating significant habituation compared to the other stressed groups. While few or no differentially expressed genes were detected 24-h after one or three loud noise exposures, relatively large numbers of transcripts were differentially expressed between the group exposed to 7 loud noises when compared to the control or 3-stress groups, respectively, which correlated with the corticosterone response habituation observed. Gene ontology analyses indicated multiple significant functional terms related to neuron differentiation, neural membrane potential, pre- and post-synaptic elements, chemical synaptic transmission, vesicles, axon guidance and projection, glutamatergic and GABAergic neurotransmission. Some of the differentially expressed genes (Myt1l, Zmat4, Dlx6, Csrnp3) encode transcription factors that were independently predicted by transcription factor enrichment analysis to target other differentially regulated genes in this study. A similar experiment employing in situ hybridization histochemical analysis in additional animals validated the direction of change of the 5 transcripts investigated (Camk4, Gabrb2, Gad1, Grin2a and Slc32a) with a high level of temporal and regional specificity for the rPH. In aggregate, the results suggest that distinct patterns of gene regulation are obtained in response to a repeated homotypic stress regimen; they also point to a significant reorganization of the rPH region that may critically contribute to the phenotypic modifications associated with repeated homotypic stress habituation.

Integrated genomics approaches identify transcriptional mediators and epigenetic responses to Afghan desert particulate matter in small airway epithelial cells.

Military Deployment to Southwest Asia and Afghanistan and exposure to toxic airborne particulates have been associated with an increased risk of developing respiratory disease, collectively termed deployment-related respiratory diseases (DRRDs). Our knowledge about how particulates mediate respiratory disease is limited, precluding the appropriate recognition or management. Central to this limitation is the lack of understanding of how exposures translate into dysregulated cell identity with dysregulated transcriptional programs. The small airway epithelium is involved in both the pathobiology of DRRD and fine particulate matter deposition. To characterize small airway epithelial cell epigenetic and transcriptional responses to Afghan desert particulate matter (APM) and investigate the functional interactions of transcription factors that mediate these responses, we applied two genomics assays, the assay for transposase accessible chromatin with sequencing (ATAC-seq) and Precision Run-on sequencing (PRO-seq). We identified activity changes in a series of transcriptional pathways as candidate regulators of susceptibility to subsequent insults, including signal-dependent pathways, such as loss of cytochrome P450 or P53/P63, and lineage-determining transcription factors, such as GRHL2 loss or TEAD3 activation. We further demonstrated that TEAD3 activation was unique to APM exposure despite similar inflammatory responses when compared with wood smoke particle exposure and that P53/P63 program loss was uniquely positioned at the intersection of signal-dependent and lineage-determining transcriptional programs. Our results establish the utility of an integrated genomics approach in characterizing responses to exposures and identifying genomic targets for the advanced investigation of the pathogenesis of DRRD.

Suppression of p53 response by targeting p53-Mediator binding with a stapled peptide.

DNA-binding transcription factors (TFs) remain challenging to target with molecular probes. Many TFs function in part through interaction with Mediator, a 26-subunit complex that controls RNA polymerase II activity genome-wide. We sought to block p53 function by disrupting the p53-Mediator interaction. Through rational design and activity-based screening, we characterize a stapled peptide, with functional mimics of both p53 activation domains, that blocks p53-Mediator binding and selectively inhibits p53-dependent transcription in human cells; importantly, this "bivalent" peptide has negligible impact, genome-wide, on non-p53 target genes. Our proof-of-concept strategy circumvents the TF entirely and targets the TF-Mediator interface instead, with desired functional outcomes (i.e., selective inhibition of p53 activation). Furthermore, these results demonstrate that TF activation domains represent viable starting points for Mediator-targeting molecular probes, as an alternative to large compound libraries. Different TFs bind Mediator through different subunits, suggesting this strategy could be broadly applied to selectively alter gene expression programs.

Protocol variations in run-on transcription dataset preparation produce detectable signatures in sequencing libraries.

BACKGROUND: A variety of protocols exist for producing whole genome run-on transcription datasets. However, little is known about how differences between these protocols affect the signal within the resulting libraries. RESULTS: Using run-on transcription datasets generated from the same biological system, we show that a variety of GRO- and PRO-seq preparation methods leave identifiable signatures within each library. Specifically we show that the library preparation method results in differences in quality control metrics, as well as differences in the signal distribution at the 5 ' end of transcribed regions. These shifts lead to disparities in eRNA identification, but do not impact analyses aimed at inferring the key regulators involved in changes to transcription. CONCLUSIONS: Run-on sequencing protocol variations result in technical signatures that can be used to identify both the enrichment and library preparation method of a particular data set. These technical signatures are batch effects that limit detailed comparisons of pausing ratios and eRNAs identified across protocols. However, these batch effects have only limited impact on our ability to infer which regulators underlie the observed transcriptional changes.

Deconvolution of multiplexed transcriptional responses to wood smoke particles defines rapid aryl hydrocarbon receptor signaling dynamics.

The heterogeneity of respirable particulates and compounds complicates our understanding of transcriptional responses to air pollution. Here, we address this by applying precision nuclear run-on sequencing and the assay for transposase-accessible chromatin sequencing to measure nascent transcription and chromatin accessibility in airway epithelial cells after wood smoke particle (WSP) exposure. We used transcription factor enrichment analysis to identify temporally distinct roles for ternary response factor-serum response factor complexes, the aryl hydrocarbon receptor (AHR), and NFκB in regulating transcriptional changes induced by WSP. Transcription of canonical targets of the AHR, such as CYP1A1 and AHRR, was robustly increased after just 30 min of WSP exposure, and we discovered novel AHR-regulated pathways and targets including the DNA methyltransferase, DNMT3L. Transcription of these genes and associated enhancers rapidly returned to near baseline by 120 min after exposure. The kinetics of AHR- and NFκB-regulated responses to WSP were distinguishable based on the timing of both transcriptional responses and chromatin remodeling, with induction of several cytokines implicated in maintaining NFκB-mediated responses through 120 min of exposure. In aggregate, our data establish a direct and primary role for AHR in mediating airway epithelial responses to WSP and identify crosstalk between AHR and NFκB signaling in controlling proinflammatory gene expression. This work also defines an integrated genomics-based strategy for deconvoluting multiplexed transcriptional responses to heterogeneous environmental exposures.

Characterization of Global Gene Expression, Regulation of Metal Ions, and Infection Outcomes in Immune-Competent 129S6 Mouse Macrophages.

Nutritional immunity involves cellular and physiological responses to invading pathogens, such as limiting iron, increasing exposure to bactericidal copper, and altering zinc to restrict the growth of pathogens. Here, we examine infection of bone marrow-derived macrophages from 129S6/SvEvTac mice by Salmonella enterica serovar Typhimurium. The 129S6/SvEvTac mice possess a functional Slc11a1 (Nramp-1), a phagosomal transporter of divalent cations that plays an important role in modulating metal availability to the pathogen. We carried out global RNA sequencing upon treatment with live or heat-killed Salmonella at 2 h and 18 h postinfection and observed widespread changes in metal transport, metal-dependent genes, and metal homeostasis genes, suggesting significant remodeling of iron, copper, and zinc availability by host cells. Changes in host cell gene expression suggest infection increases cytosolic zinc while simultaneously limiting zinc within the phagosome. Using a genetically encoded sensor, we demonstrate that cytosolic labile zinc increases 45-fold at 12 h postinfection. Further, manipulation of zinc in the medium alters bacterial clearance and replication, with zinc depletion inhibiting both processes. Comparing the transcriptomic changes to published data on infection of C57BL/6 macrophages revealed notable differences in metal regulation and the global immune response. Our results reveal that 129S6 macrophages represent a distinct model system compared to C57BL/6 macrophages. Further, our results indicate that manipulation of zinc at the host-pathogen interface is more nuanced than that of iron or copper. The 129S6 macrophages leverage intricate means of manipulating zinc availability and distribution to limit the pathogen's access to zinc, while simultaneously ensuring sufficient zinc to support the immune response.

The Δ40p53 isoform inhibits p53-dependent eRNA transcription and enables regulation by signal-specific transcription factors during p53 activation.

The naturally occurring Δ40p53 isoform heterotetramerizes with wild-type p53 (WTp53) to regulate development, aging, and stress responses. How Δ40p53 alters WTp53 function remains enigmatic because their co-expression causes tetramer heterogeneity. We circumvented this issue with a well-tested strategy that expressed Δ40p53:WTp53 as a single transcript, ensuring a 2:2 tetramer stoichiometry. Human MCF10A cell lines expressing Δ40p53:WTp53, WTp53, or WTp53:WTp53 (as controls) from the native TP53 locus were examined with transcriptomics (precision nuclear run-on sequencing [PRO-seq] and RNA sequencing [RNA-seq]), metabolomics, and other methods. Δ40p53:WTp53 was transcriptionally active, and, although phenotypically similar to WTp53 under normal conditions, it failed to induce growth arrest upon Nutlin-induced p53 activation. This occurred via Δ40p53:WTp53-dependent inhibition of enhancer RNA (eRNA) transcription and subsequent failure to induce mRNA biogenesis, despite similar genomic occupancy to WTp53. A different stimulus (5-fluorouracil [5FU]) also showed Δ40p53:WTp53-specific changes in mRNA induction; however, other transcription factors (TFs; e.g., E2F2) could then drive the response, yielding similar outcomes vs. WTp53. Our results establish that Δ40p53 tempers WTp53 function to enable compensatory responses by other stimulus-specific TFs. Such modulation of WTp53 activity may be an essential physiological function for Δ40p53. Moreover, Δ40p53:WTp53 functional distinctions uncovered herein suggest an eRNA requirement for mRNA biogenesis and that human p53 evolved as a tetramer to support eRNA transcription.

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

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