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.

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.

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.

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.

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.

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.

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.

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.

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.

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

OBJECTIVES

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

DATA DESCRIPTION

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

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.

Supplementary Information

The online version contains supplementary material available at (10.1186/s12864-022-08352-8).

Nuclear mechanosensing drives chromatin remodelling in persistently activated fibroblasts

Fibrotic disease is caused by the continuous deposition of extracellular matrix by persistently activated fibroblasts (also known as myofibroblasts), even after the resolution of the injury. Using fibroblasts from porcine aortic valves cultured on hydrogels that can be softened via exposure to ultraviolet light, here we show that increased extracellular stiffness activates the fibroblasts, and that cumulative tension on the nuclear membrane and increases in the activity of histone deacetylases transform transiently activated fibroblasts into myofibroblasts displaying condensed chromatin with genome-wide alterations. The condensed structure of the myofibroblasts is associated with cytoskeletal stability, as indicated by the inhibition of chromatin condensation and myofibroblast persistence after detachment of the nucleus from the cytoskeleton via the displacement of endogenous nesprins from the nuclear envelope. We also show that the chromatin structure of myofibroblasts from patients with aortic valve stenosis is more condensed than that of myofibroblasts from healthy donors. Our findings suggest that nuclear mechanosensing drives distinct chromatin signatures in persistently activated fibroblasts.

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.

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.

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.

Just 2% of SARS-CoV-2-positive individuals carry 90% of the virus circulating in communities

We analyze data from the fall 2020 pandemic response efforts at the University of Colorado Boulder, where more than 72,500 saliva samples were tested for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) using qRT-PCR. All samples were collected from individuals who reported no symptoms associated with COVID-19 on the day of collection. From these, 1,405 positive cases were identified. The distribution of viral loads within these asymptomatic individuals was indistinguishable from what has been previously observed in symptomatic individuals. Regardless of symptomatic status, ∼50% of individuals who test positive for SARS-CoV-2 seem to be in noninfectious phases of the disease, based on having low viral loads in a range from which live virus has rarely been isolated. We find that, at any given time, just 2% of individuals carry 90% of the virions circulating within communities, serving as viral "supercarriers" and possibly also superspreaders.

Application of a bioinformatic pipeline to RNA-seq data identifies novel viruslike sequence in human blood

Numerous reports have suggested that infectious agents could play a role in neurodegenerative diseases, but specific etiological agents have not been convincingly demonstrated. To search for candidate agents in an unbiased fashion, we have developed a bioinformatic pipeline that identifies microbial sequences in mammalian RNA-seq data, including sequences with no significant nucleotide similarity hits in GenBank. Effectiveness of the pipeline was tested using publicly available RNA-seq data and in a reconstruction experiment using synthetic data. We then applied this pipeline to a novel RNA-seq dataset generated from a cohort of 120 samples from amyotrophic lateral sclerosis patients and controls, and identified sequences corresponding to known bacteria and viruses, as well as novel virus-like sequences. The presence of these novel virus-like sequences, which were identified in subsets of both patients and controls, were confirmed by quantitative RT-PCR. We believe this pipeline will be a useful tool for the identification of potential etiological agents in the many RNA-seq datasets currently being generated.

Just 2% of SARS-CoV-2-positive individuals carry 90% of the virus circulating in communities

We analyze data from the Fall 2020 pandemic response efforts at the University of Colorado Boulder (USA), where more than 72,500 saliva samples were tested for SARS-CoV-2 using quantitative RT-PCR. All samples were collected from individuals who reported no symptoms associated with COVID-19 on the day of collection. From these, 1,405 positive cases were identified. The distribution of viral loads within these asymptomatic individuals was indistinguishable from what has been previously reported in symptomatic individuals. Regardless of symptomatic status, approximately 50% of individuals who test positive for SARS-CoV-2 seem to be in non-infectious phases of the disease, based on having low viral loads in a range from which live virus has rarely been isolated. We find that, at any given time, just 2% of individuals carry 90% of the virions circulating within communities, serving as viral "super-carriers" and possibly also super-spreaders.

Competition between PRC2.1 and 2.2 subcomplexes regulates PRC2 chromatin occupancy in human stem cells

Polycomb repressive complex 2 (PRC2) silences expression of developmental transcription factors in pluripotent stem cells by methylating lysine 27 on histone H3. Two mutually exclusive subcomplexes, PRC2.1 and PRC2.2, are defined by the set of accessory proteins bound to the core PRC2 subunits. Here we introduce separation-of-function mutations into the SUZ12 subunit of PRC2 to drive it into a PRC2.1 or 2.2 subcomplex in human induced pluripotent stem cells (iPSCs). We find that PRC2.2 occupies polycomb target genes at low levels and that homeobox transcription factors are upregulated when this complex is exclusively present. In contrast with previous studies, we find that chromatin occupancy of PRC2 increases drastically when it is forced to form PRC2.1. Additionally, several cancer-associated mutations also coerce formation of PRC2.1. We suggest that PRC2 chromatin occupancy can be altered in the context of disease or development by tuning the ratio of PRC2.1 to PRC2.2.

Remodeling of Zn2+ homeostasis upon differentiation of mammary epithelial cells

Zinc is the second most abundant transition metal in humans and an essential nutrient required for growth and development of newborns. During lactation, mammary epithelial cells differentiate into a secretory phenotype, uptake zinc from blood circulation, and export it into mother's milk. At the cellular level, many zinc-dependent cellular processes, such as transcription, metabolism of nutrients, and proliferation are involved in the differentiation of mammary epithelial cells. Using mouse mammary epithelial cells as a model system, we investigated the remodeling of zinc homeostasis during differentiation induced by treatment with the lactogenic hormones cortisol and prolactin. RNA-Seq at different stages of differentiation revealed changes in global gene expression, including genes encoding zinc-dependent proteins and regulators of zinc homeostasis. Increases in mRNA levels of three zinc homeostasis genes, Slc39a14 (ZIP14) and metallothioneins (MTs) I and II were induced by cortisol but not by prolactin. The cortisol-induced increase was partially mediated by the nuclear glucocorticoid receptor signaling pathway. An increase in the cytosolic labile Zn2+ pool was also detected in lactating mammary cells, consistent with upregulation of MTs. We found that the zinc transporter ZIP14 was important for the expression of a major milk protein, whey acid protein (WAP), as knockdown of ZIP14 dramatically decreased WAP mRNA levels. In summary, our study demonstrated remodeling of zinc homeostasis upon differentiation of mammary epithelial cells resulting in changes in cytosolic Zn2+ and differential expression of zinc homeostasis genes, and these changes are important for establishing the lactation phenotype.

The MUC5B-associated variant rs35705950 resides within an enhancer subject to lineage- and disease-dependent epigenetic remodeling

The G/T transversion rs35705950, located approximately 3 kb upstream of the MUC5B start site, is the cardinal risk factor for idiopathic pulmonary fibrosis (IPF). Here, we investigate the function and chromatin structure of this –3 kb region and provide evidence that it functions as a classically defined enhancer subject to epigenetic programming. We use nascent transcript analysis to show that RNA polymerase II loads within 10 bp of the G/T transversion site, definitively establishing enhancer function for the region. By integrating Assay for Transposase-Accessible Chromatin using sequencing (ATAC-seq) analysis of fresh and cultured human airway epithelial cells with nuclease sensitivity data, we demonstrate that this region is in accessible chromatin that affects the expression of MUC5B. Through applying paired single-nucleus RNA- and ATAC-seq to frozen tissue from IPF lungs, we extend these findings directly to disease, with results indicating that epigenetic programming of the –3 kb enhancer in IPF occurs in both MUC5B-expressing and nonexpressing lineages. In aggregate, our results indicate that the MUC5B-associated variant rs35705950 resides within an enhancer that is subject to epigenetic remodeling and contributes to pathologic misexpression in IPF.

Applying knowledge-driven mechanistic inference to toxicogenomics

When considering toxic chemicals in the environment, a mechanistic, causal explanation of toxicity may be preferred over a statistical or machine learning-based prediction by itself. Elucidating a mechanism of toxicity is, however, a costly and time-consuming process that requires the participation of specialists from a variety of fields, often relying on animal models. We present an innovative mechanistic inference framework (MechSpy), which can be used as a hypothesis generation aid to narrow the scope of mechanistic toxicology analysis. MechSpy generates hypotheses of the most likely mechanisms of toxicity, by combining a semantically-interconnected knowledge representation of human biology, toxicology and biochemistry with gene expression time series on human tissue. Using vector representations of biological entities, MechSpy seeks enrichment in a manually curated list of high-level mechanisms of toxicity, represented as biochemically- and causally-linked ontology concepts. Besides predicting the canonical mechanism of toxicity for many well-studied compounds, we experimentally validated some of our predictions for other chemicals without an established mechanism of toxicity. This mechanistic inference framework is an advantageous tool for predictive toxicology, and the first of its kind to produce a mechanistic explanation for each prediction. MechSpy can be modified to include additional mechanisms of toxicity, and is generalizable to other types of mechanisms of human biology.

Combining signal and sequence to detect RNA polymerase initiation in ATAC-seq data

The assay for transposase-accessible chromatin followed by sequencing (ATAC-seq) is an inexpensive protocol for measuring open chromatin regions. ATAC-seq is also relatively simple and requires fewer cells than many other high-throughput sequencing protocols. Therefore, it is tractable in numerous settings where other high throughput assays are challenging to impossible. Hence it is important to understand the limits of what can be inferred from ATAC-seq data. In this work, we leverage ATAC-seq to predict the presence of nascent transcription. Nascent transcription assays are the current gold standard for identifying regions of active transcription, including markers for functional transcription factor (TF) binding. We combine mapped short reads from ATAC-seq with the underlying peak sequence, to determine regions of active transcription genome-wide. We show that a hybrid signal/sequence representation classified using recurrent neural networks (RNNs) can identify these regions across different cell types.

TFIID Enables RNA Polymerase II Promoter-Proximal Pausing

RNA polymerase II (RNAPII) transcription is governed by the pre-initiation complex (PIC), which contains TFIIA, TFIIB, TFIID, TFIIE, TFIIF, TFIIH, RNAPII, and Mediator. After initiation, RNAPII enzymes pause after transcribing less than 100 bases; precisely how RNAPII pausing is enforced and regulated remains unclear. To address specific mechanistic questions, we reconstituted human RNAPII promoter-proximal pausing in vitro, entirely with purified factors (no extracts). As expected, NELF and DSIF increased pausing, and P-TEFb promoted pause release. Unexpectedly, the PIC alone was sufficient to reconstitute pausing, suggesting RNAPII pausing is an inherent PIC function. In agreement, pausing was lost upon replacement of the TFIID complex with TATA-binding protein (TBP), and PRO-seq experiments revealed widespread disruption of RNAPII pausing upon acute depletion (t = 60 min) of TFIID subunits in human or Drosophila cells. These results establish a TFIID requirement for RNAPII pausing and suggest pause regulatory factors may function directly or indirectly through TFIID.

Two-stage ML Classifier for Identifying Host Protein Targets of the Dengue Protease

Flaviviruses such as dengue encode a protease that is essential for viral replication. The protease functions by cleaving well-conserved positions in the viral polyprotein. In addition to the viral polyprotein, the dengue protease cleaves at least one host protein involved in immune response. This raises the question, what other host proteins are targeted and cleaved? Here we present a new computational method for identifying putative host protein targets of the dengue virus protease. Our method relies on biochemical and secondary structure features at the known cleavage sites in the viral polyprotein in a two-stage classification process to identify putative cleavage targets. The accuracy of our predictions scaled inversely with evolutionary distance when we applied it to the known cleavage sites of several other flaviviruses-a good indication of the validity of our predictions. Ultimately, our classifier identified 257 human protein sites possessing both a similar target motif and accessible local structure. These proteins are promising candidates for further investigation. As the number of viral sequences expands, our method could be adopted to predict host targets of other flaviviruses.

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

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

Nascent transcript analysis of glucocorticoid crosstalk with TNF defines primary and cooperative inflammatory repression

The glucocorticoid receptor (NR3C1, also known as GR) binds to specific DNA sequences and directly induces transcription of anti-inflammatory genes that contribute to cytokine repression, frequently in cooperation with NF-kB. Whether inflammatory repression also occurs through local interactions between GR and inflammatory gene regulatory elements has been controversial. Here, using global run-on sequencing (GRO-seq) in human airway epithelial cells, we show that glucocorticoid signaling represses transcription within 10 min. Many repressed regulatory regions reside within “hyper-ChIPable” genomic regions that are subject to dynamic, yet nonspecific, interactions with some antibodies. When this artifact was accounted for, we determined that transcriptional repression does not require local GR occupancy. Instead, widespread transcriptional induction through canonical GR binding sites is associated with reciprocal repression of distal TNF-regulated enhancers through a chromatin-dependent process, as evidenced by chromatin accessibility and motif displacement analysis. Simultaneously, transcriptional induction of key anti-inflammatory effectors is decoupled from primary repression through cooperation between GR and NF-kB at a subset of regulatory regions. Thus, glucocorticoids exert bimodal restraints on inflammation characterized by rapid primary transcriptional repression without local GR occupancy and secondary anti-inflammatory effects resulting from transcriptional cooperation between GR and NF-kB.

Transcriptional Responses to IFN-γ Require Mediator Kinase-Dependent Pause Release and Mechanistically Distinct CDK8 and CDK19 Functions

Transcriptional responses to external stimuli remain poorly understood. Using global nuclear run-on followed by sequencing (GRO-seq) and precision nuclear run-on sequencing (PRO-seq), we show that CDK8 kinase activity promotes RNA polymerase II pause release in response to interferon-γ (IFN-γ), a universal cytokine involved in immunity and tumor surveillance. The Mediator kinase module contains CDK8 or CDK19, which are presumed to be functionally redundant. We implemented cortistatin A, chemical genetics, transcriptomics, and other methods to decouple their function while assessing enzymatic versus structural roles. Unexpectedly, CDK8 and CDK19 regulated different gene sets via distinct mechanisms. CDK8-dependent regulation required its kinase activity, whereas CDK19 governed IFN-γ responses through its scaffolding function (i.e., it was kinase independent). Accordingly, CDK8, not CDK19, phosphorylates the STAT1 transcription factor (TF) during IFN-γ stimulation, and CDK8 kinase inhibition blocked activation of JAK-STAT pathway TFs. Cytokines such as IFN-γ rapidly mobilize TFs to "reprogram" cellular transcription; our results implicate CDK8 and CDK19 as essential for this transcriptional reprogramming.

Genome-wide dose-dependent inhibition of histone deacetylases studies reveal their roles in enhancer remodeling and suppression of oncogenic super-enhancers

Histone deacetylase inhibitors (HDACIs) are known to alter gene expression by both up- and down-regulation of protein-coding genes in normal and cancer cells. However, the exact regulatory mechanisms of action remain uncharacterized. Here we investigated genome wide dose-dependent epigenetic and transcriptome changes in response to HDACI largazole in a transformed and a non-transformed cell line. Exposure to low nanomolar largazole concentrations (<GI₅₀) predominantly resulted in upregulation of gene transcripts whereas higher largazole doses (≥GI₅₀) triggered a general decrease in mRNA accumulation. Largazole induces elevation of histone H3 acetylation at Lys-9 and Lys-27 along many gene bodies but does not correlate with up- or down-regulation of the associated transcripts. A higher dose of largazole results in more RNA polymerase II pausing at the promoters of actively transcribed genes and cell death. The most prevalent changes associated with transcriptional regulation occur at distal enhancer elements. Largazole promotes H3K27 acetylation at a subset of poised enhancers and unexpectedly, we also found active enhancers that become decommissioned in a dose and cell type-dependent manner. In particular, largazole decreases RNA polymerase II accumulation at super-enhancers (SEs) and preferentially suppresses SE-driven transcripts that are associated with oncogenic activities in transformed cells.

Heat shock in C. elegans induces downstream of gene transcription and accumulation of double-stranded RNA

We observed that heat shock of Caenorhabditis elegans leads to the formation of nuclear double-stranded RNA (dsRNA) foci, detectable with a dsRNA-specific monoclonal antibody. These foci significantly overlap with nuclear HSF-1 granules. To investigate the molecular mechanism(s) underlying dsRNA foci formation, we used RNA-seq to globally characterize total RNA and immunoprecipitated dsRNA from control and heat shocked worms. We find a subset of both sense and antisense transcripts enriched in the dsRNA pool by heat shock overlap with dsRNA transcripts enriched by deletion of tdp-1, which encodes the C. elegans ortholog of TDP-43. Interestingly, transcripts involved in translation are over-represented in the dsRNAs induced by either heat shock or deletion of tdp-1. Also enriched in the dsRNA transcripts are sequences downstream of annotated genes (DoGs), which we globally quantified with a new algorithm. To validate these observations, we used fluorescence in situ hybridization (FISH) to confirm both antisense and downstream of gene transcription for eif-3.B, one of the affected loci we identified.

Control of inducible gene expression links cohesin to hematopoietic progenitor self-renewal and differentiation

Cohesin is important for 3D genome organization. Nevertheless, even the complete removal of cohesin has surprisingly little impact on steady-state gene transcription and enhancer activity. Here we show that cohesin is required for the core transcriptional response of primary macrophages to microbial signals, and for inducible enhancer activity that underpins inflammatory gene expression. Consistent with a role for inflammatory signals in promoting myeloid differentiation of hematopoietic stem and progenitor cells (HPSCs), cohesin mutations in HSPCs led to reduced inflammatory gene expression and increased resistance to differentiation-inducing inflammatory stimuli. These findings uncover an unexpected dependence of inducible gene expression on cohesin, link cohesin with myeloid differentiation, and may help explain the prevalence of cohesin mutations in human acute myeloid leukemia.

Transcriptome and Functional Profile of Cardiac Myocytes Is Influenced by Biological Sex

BACKGROUND

Although cardiovascular disease is the primary killer of women in the United States, women and female animals have traditionally been omitted from research studies. In reports that do include both sexes, significant sexual dimorphisms have been demonstrated in development, presentation, and outcome of cardiovascular disease. However, there is little understanding of the mechanisms underlying these observations. A more thorough understanding of sex-specific cardiovascular differences both at baseline and in disease is required to effectively consider and treat all patients with cardiovascular disease.

METHODS AND RESULTS

We analyzed contractility in the whole rat heart, adult rat ventricular myocytes (ARVMs), and myofibrils from both sexes of rats and observed functional sex differences at all levels. Hearts and ARVMs from female rats displayed greater fractional shortening than males, and female ARVMs and myofibrils took longer to relax. To define factors underlying these functional differences, we performed an RNA sequencing experiment on ARVMs from male and female rats and identified ≈600 genes were expressed in a sexually dimorphic manner. Further analysis revealed sex-specific enrichment of signaling pathways and key regulators. At the protein level, female ARVMs exhibited higher protein kinase A activity, consistent with pathway enrichment identified through RNA sequencing. In addition, activating the protein kinase A pathway diminished the contractile sexual dimorphisms previously observed.

CONCLUSIONS

These data support the notion that sex-specific gene expression differences at baseline influence cardiac function, particularly through the protein kinase A pathway, and could potentially be responsible for differences in cardiovascular disease presentation and outcomes.

PI(3,5)P2 controls vacuole potassium transport to support cellular osmoregulation

Lysosomes are dynamic organelles with critical roles in cellular physiology. The lysosomal signaling lipid phosphatidylinositol 3,5-bisphosphate (PI(3,5)P₂) is a key regulator that has been implicated to control lysosome ion homeostasis, but the scope of ion transporters targeted by PI(3,5)P₂ and the purpose of this regulation is not well understood. Through an unbiased screen in Saccharomyces cerevisiae, we identified loss-of-function mutations in the vacuolar H⁺-ATPase (V-ATPase) and in Vnx1, a vacuolar monovalent cation/proton antiporter, as suppressor mutations that relieve the growth defects and osmotic swelling of vacuoles (lysosomes) in yeast lacking PI(3,5)P₂. We observed that depletion of PI(3,5)P₂ synthesis in yeast causes a robust accumulation of multiple cations, most notably an ∼85 mM increase in the cellular concentration of potassium, a critical ion used by cells to regulate osmolarity. The accumulation of potassium and other cations in PI(3,5)P₂-deficient yeast is relieved by mutations that inactivate Vnx1 or inactivate the V-ATPase and by mutations that increase the activity of a vacuolar cation export channel, Yvc1. Collectively, our data demonstrate that PI(3,5)P₂ signaling orchestrates vacuole/lysosome cation transport to aid cellular osmoregulation.

Detecting Differential Transcription Factor Activity from ATAC-Seq Data

Transcription factors are managers of the cellular factory, and key components to many diseases. Many non-coding single nucleotide polymorphisms affect transcription factors, either by directly altering the protein or its functional activity at individual binding sites. Here we first briefly summarize high-throughput approaches to studying transcription factor activity. We then demonstrate, using published chromatin accessibility data (specifically ATAC-seq), that the genome-wide profile of TF recognition motifs relative to regions of open chromatin can determine the key transcription factor altered by a perturbation. Our method of determining which TFs are altered by a perturbation is simple, is quick to implement, and can be used when biological samples are limited. In the future, we envision that this method could be applied to determine which TFs show altered activity in response to a wide variety of drugs and diseases.

Human TFIIH Kinase CDK7 Regulates Transcription-Associated Chromatin Modifications

CDK7 phosphorylates the RNA polymerase II (pol II) C-terminal domain CTD and activates the P-TEFb-associated kinase CDK9, but its regulatory roles remain obscure. Here, using human CDK7 analog-sensitive (CDK7as) cells, we observed reduced capping enzyme recruitment, increased pol II promoter-proximal pausing, and defective termination at gene 3' ends upon CDK7 inhibition. We also noted that CDK7 regulates chromatin modifications downstream of transcription start sites. H3K4me3 spreading was restricted at gene 5' ends and H3K36me3 was displaced toward gene 3' ends in CDK7as cells. Mass spectrometry identified factors that bound TFIIH-phosphorylated versus P-TEFb-phosphorylated CTD (versus unmodified); capping enzymes and H3K4 methyltransferase complexes, SETD1A/B, selectively bound phosphorylated CTD, and the H3K36 methyltransferase SETD2 specifically bound P-TEFb-phosphorylated CTD. Moreover, TFIIH-phosphorylated CTD stimulated SETD1A/B activity toward nucleosomes, revealing a mechanistic basis for CDK7 regulation of H3K4me3 spreading. Collectively, these results implicate a CDK7-dependent "CTD code" that regulates chromatin marks in addition to RNA processing and pol II pausing.

Enhancer RNA profiling predicts transcription factor activity

Transcription factors (TFs) exert their regulatory influence through the binding of enhancers, resulting in coordination of gene expression programs. Active enhancers are often characterized by the presence of short, unstable transcripts termed enhancer RNAs (eRNAs). While their function remains unclear, we demonstrate that eRNAs are a powerful readout of TF activity. We infer sites of eRNA origination across hundreds of publicly available nascent transcription data sets and show that eRNAs initiate from sites of TF binding. By quantifying the colocalization of TF binding motif instances and eRNA origins, we derive a simple statistic capable of inferring TF activity. In doing so, we uncover dozens of previously unexplored links between diverse stimuli and the TFs they affect.

The Influence of Polyploidy on the Evolution of Yeast Grown in a Sub-Optimal Carbon Source

Polyploidization events have occurred during the evolution of many fungi, plant, and animal species and are thought to contribute to speciation and tumorigenesis, however little is known about how ploidy level contributes to adaptation at the molecular level. Here we integrate whole genome sequencing, RNA expression analysis, and relative fitness of ∼100 evolved clones at three ploidy levels. Independent haploid, diploid, and tetraploid populations were grown in a low carbon environment for 250 generations. We demonstrate that the key adaptive mutation in the evolved clones is predicted by a gene expression signature of just five genes. All of the adaptive mutations identified encompass a narrow set of genes, however the tetraploid clones gain a broader spectrum of adaptive mutations than haploid or diploid clones. While many of the adaptive mutations occur in genes that encode proteins with known roles in glucose sensing and transport, we discover mutations in genes with no canonical role in carbon utilization (IPT1 and MOT3), as well as identify novel dominant mutations in glucose signal transducers thought to only accumulate recessive mutations in carbon limited environments (MTH1 and RGT1). We conclude that polyploid cells explore more genotypic and phenotypic space than lower ploidy cells. Our study provides strong evidence for the beneficial role of polyploidization events that occur during the evolution of many species and during tumorigenesis.

An Annotation Agnostic Algorithm for Detecting Nascent RNA Transcripts in GRO-Seq

We present a fast and simple algorithm to detect nascent RNA transcription in global nuclear run-on sequencing (GRO-seq). GRO-seq is a relatively new protocol that captures nascent transcripts from actively engaged polymerase, providing a direct read-out on bona fide transcription. Most traditional assays, such as RNA-seq, measure steady state RNA levels which are affected by transcription, post-transcriptional processing, and RNA stability. GRO-seq data, however, presents unique analysis challenges that are only beginning to be addressed. Here, we describe a new algorithm, Fast Read Stitcher (FStitch), that takes advantage of two popular machine-learning techniques, hidden Markov models and logistic regression, to classify which regions of the genome are transcribed. Given a small user-defined training set, our algorithm is accurate, robust to varying read depth, annotation agnostic, and fast. Analysis of GRO-seq data without a priori need for annotation uncovers surprising new insights into several aspects of the transcription process.

Model based heritability scores for high-throughput sequencing data

Background

Heritability of a phenotypic or molecular trait measures the proportion of variance that is attributable to genotypic variance. It is an important concept in breeding and genetics. Few methods are available for calculating heritability for traits derived from high-throughput sequencing.

Results

We propose several statistical models and different methods to compute and test a heritability measure for such data based on linear and generalized linear mixed effects models. We also provide methodology for hypothesis testing and interval estimation. Our analyses show that, among the methods, the negative binomial mixed model (NB-fit), compound Poisson mixed model (CP-fit), and the variance stabilizing transformed linear mixed model (VST) outperform the voom-transformed linear mixed model (voom). NB-fit and VST appear to be more robust than CP-fit for estimating and testing the heritability scores, while NB-fit is the most computationally expensive. CP-fit performed best in terms of the coverage of the confidence intervals. In addition, we applied the methods to both microRNA (miRNA) and messenger RNA (mRNA) sequencing datasets from a recombinant inbred mouse panel. We show that miRNA and mRNA expression can be a highly heritable molecular trait in mouse, and that some top heritable features coincide with expression quantitative trait loci.

Conclusions

The models and methods we investigated in this manuscript is applicable and extendable to sequencing experiments where some biological replicates are available and the environmental variation is properly controlled. The CP-fit approach for assessing heritability was implemented for the first time to our knowledge. All the methods presented, as well as the generation of simulated sequencing data under either negative binomial or compound Poisson mixed models, are provided in the R package HeritSeq.

Electronic supplementary material

The online version of this article (doi:10.1186/s12859-017-1539-6) contains supplementary material, which is available to authorized users.

A generative model for the behavior of RNA polymerase

MOTIVATION

Transcription by RNA polymerase is a highly dynamic process involving multiple distinct points of regulation. Nascent transcription assays are a relatively new set of high throughput techniques that measure the location of actively engaged RNA polymerase genome wide. Hence, nascent transcription is a rich source of information on the regulation of RNA polymerase activity. To fully dissect this data requires the development of stochastic models that can both deconvolve the stages of polymerase activity and identify significant changes in activity between experiments.

RESULTS

We present a generative, probabilistic model of RNA polymerase that fully describes loading, initiation, elongation and termination. We fit this model genome wide and profile the enzymatic activity of RNA polymerase across various loci and following experimental perturbation. We observe striking correlation of predicted loading events and regulatory chromatin marks. We provide principled statistics that compute probabilities reminiscent of traveler's and divergent ratios. We finish with a systematic comparison of RNA Polymerase activity at promoter versus non-promoter associated loci.

AVAILABILITY AND IMPLEMENTATION

Transcription Fit (Tfit) is a freely available, open source software package written in C/C ++ that requires GNU compilers 4.7.3 or greater. Tfit is available from GitHub (https://github.com/azofeifa/Tfit).

CONTACT

robin.dowell@colorado.eduSupplementary information: Supplementary data are available at Bioinformatics online.

A Modeling Framework for Generation of Positional and Temporal Simulations of Transcriptional Regulation

We present a modeling framework aimed at capturing both the positional and temporal behavior of transcriptional regulatory proteins in eukaryotic cells. There is growing evidence that transcriptional regulation is the complex behavior that emerges not solely from the individual components, but rather from their collective behavior, including competition and cooperation. Our framework describes individual regulatory components using generic action oriented descriptions of their biochemical interactions with a DNA sequence. All the possible actions are based on the current state of factors bound to the DNA. We developed a rule builder to automatically generate the complete set of biochemical interaction rules for any given DNA sequence. Off-the-shelf stochastic simulation engines can model the behavior of a system of rules and the resulting changes in the configuration of bound factors can be visualized. We compared our model to experimental data at well-studied loci in yeast, confirming that our model captures both the positional and temporal behavior of transcriptional regulation.

Survey of cryptic unstable transcripts in yeast

Background

Cryptic unstable transcripts (CUTs) are a largely unexplored class of nuclear exosome degraded, non-coding RNAs in budding yeast. It is highly debated whether CUT transcription has a functional role in the cell or whether CUTs represent noise in the yeast transcriptome.

We sought to ascertain the extent of conserved CUT expression across a variety of Saccharomyces yeast strains to further understand and characterize the nature of CUT expression.

Results

We sequenced the WT and rrp6Δ transcriptomes of three S.cerevisiae strains: S288c, Σ1278b, JAY291 and the S.paradoxus strain N17 and utilized a hidden Markov model to annotate CUTs in these four strains. Utilizing a four-way genomic alignment we identified a large population of CUTs with conserved syntenic expression across all four strains. By identifying configurations of gene-CUT pairs, where CUT expression originates from the gene 5’ or 3′ nucleosome free region, we observed distinct gene expression trends specific to these configurations which were most prevalent in the presence of conserved CUT expression. Divergent pairs correlate with higher expression of genes, and convergent pairs correlate with reduced gene expression.

Conclusions

Our RNA-seq based method has greatly expanded upon previous CUT annotations in S.cerevisiae underscoring the extensive and pervasive nature of unstable transcription. Furthermore we provide the first assessment of conserved CUT expression in yeast and globally demonstrate possible modes of CUT-based regulation of gene expression.

Electronic supplementary material

The online version of this article (doi:10.1186/s12864-016-2622-5) contains supplementary material, which is available to authorized users.

Identification of Mediator Kinase Substrates in Human Cells using Cortistatin A and Quantitative Phosphoproteomics

Cortistatin A (CA) is a highly selective inhibitor of the Mediator kinases CDK8 and CDK19. Using CA, we now report a large-scale identification of Mediator kinase substrates in human cells (HCT116). We identified over 16,000 quantified phosphosites including 78 high-confidence Mediator kinase targets within 64 proteins, including DNA-binding transcription factors and proteins associated with chromatin, DNA repair, and RNA polymerase II. Although RNA-seq data correlated with Mediator kinase targets, the effects of CA on gene expression were limited and distinct from CDK8 or CDK19 knockdown. Quantitative proteome analyses, tracking around 7,000 proteins across six time points (0-24 hr), revealed that CA selectively affected pathways implicated in inflammation, growth, and metabolic regulation. Contrary to expectations, increased turnover of Mediator kinase targets was not generally observed. Collectively, these data support Mediator kinases as regulators of chromatin and RNA polymerase II activity and suggest their roles extend beyond transcription to metabolism and DNA repair.

Foxc1 reinforces quiescence in self-renewing hair follicle stem cells

Stem cell quiescence preserves the cell reservoir by minimizing cell division over extended periods of time. Self-renewal of quiescent stem cells (SCs) requires the reentry into the cell cycle. In this study, we show that murine hair follicle SCs induce the Foxc1 transcription factor when activated. Deleting Foxc1 in activated, but not quiescent, SCs causes failure of the cells to reestablish quiescence and allows premature activation. Deleting Foxc1 in the SC niche of gene-targeted mice leads to loss of the old hair without impairing quiescence. In self-renewing SCs, Foxc1 activates Nfatc1 and bone morphogenetic protein (BMP) signaling, two key mechanisms that govern quiescence. These findings reveal a dynamic, cell-intrinsic mechanism used by hair follicle SCs to reinforce quiescence upon self-renewal and suggest a unique ability of SCs to maintain cell identity.

A trans-acting Variant within the Transcription Factor RIM101 Interacts with Genetic Background to Determine its Regulatory Capacity

Most genetic variants associated with disease occur within regulatory regions of the genome, underscoring the importance of defining the mechanisms underlying differences in regulation of gene expression between individuals. We discovered a pair of co-regulated, divergently oriented transcripts, AQY2 and ncFRE6, that are expressed in one strain of Saccharomyces cerevisiae, ∑1278b, but not in another, S288c. By combining classical genetics techniques with high-throughput sequencing, we identified a trans-acting single nucleotide polymorphism within the transcription factor RIM101 that causes the background-dependent expression of both transcripts. Subsequent RNA-seq experiments revealed that RIM101 regulates many more targets in S288c than in ∑1278b and that deletion of RIM101 in both backgrounds abrogates the majority of differential expression between the strains. Strikingly, only three transcripts undergo a significant change in expression after swapping RIM101 alleles between backgrounds, implying that the differences in the RIM101 allele lead to a remarkably focused transcriptional response. However, hundreds of RIM101-dependent targets undergo a subtle but consistent shift in expression in the S288c RIM101-swapped strain, but not its ∑1278b counterpart. We conclude that ∑1278b may harbor a variant(s) that buffers against widespread transcriptional dysregulation upon introduction of a non-native RIM101 allele, emphasizing the importance of accounting for genetic background when assessing the impact of a regulatory variant.