Mary A. Allen

HIF1A Employs CDK8-Mediator to Stimulate RNAPII Elongation in Response to Hypoxia

The transcription factor HIF1A is a key mediator of the cellular response to hypoxia. Despite the importance of HIF1A in homeostasis and various pathologies, little is known about how it regulates RNA polymerase II (RNAPII). We report here that HIF1A employs a specific variant of the Mediator complex to stimulate RNAPII elongation. The Mediator-associated kinase CDK8, but not the paralog CDK19, is required for induction of many HIF1A target genes. HIF1A induces binding of CDK8-Mediator and the super elongation complex (SEC), containing AFF4 and CDK9, to alleviate RNAPII pausing. CDK8 is dispensable for HIF1A chromatin binding and histone acetylation, but it is essential for binding of SEC and RNAPII elongation. Global analysis of active RNAPII reveals that hypoxia-inducible genes are paused and active prior to their induction. Our results provide a mechanistic link between HIF1A and CDK8, two potent oncogenes, in the cellular response to hypoxia.

Global analysis of p53-regulated transcription identifies its direct targets and unexpected regulatory mechanisms

The p53 transcription factor is a potent suppressor of tumor growth. We report here an analysis of its direct transcriptional program using Global Run-On sequencing (GRO-seq). Shortly after MDM2 inhibition by Nutlin-3, low levels of p53 rapidly activate ∼200 genes, most of them not previously established as direct targets. This immediate response involves all canonical p53 effector pathways, including apoptosis. Comparative global analysis of RNA synthesis vs steady state levels revealed that microarray profiling fails to identify low abundance transcripts directly activated by p53. Interestingly, p53 represses a subset of its activation targets before MDM2 inhibition. GRO-seq uncovered a plethora of gene-specific regulatory features affecting key survival and apoptotic genes within the p53 network. p53 regulates hundreds of enhancer-derived RNAs. Strikingly, direct p53 targets harbor pre-activated enhancers highly transcribed in p53 null cells. Altogether, these results enable the study of many uncharacterized p53 target genes and unexpected regulatory mechanisms. DOI: http://dx.doi.org/10.7554/eLife.02200.001

Genes involved in pre-mRNA 3'-end formation and transcription termination revealed by a lin-15 operon Muv suppressor screen

RNA polymerase II (Pol II) transcription termination involves two linked processes: mRNA 3′-end formation and release of Pol II from DNA. Signals for 3′ processing are recognized by a protein complex that includes cleavage polyadenylation specificity factor (CPSF) and cleavage stimulation factor (CstF). Here we identify suppressors encoding proteins that play roles in processes at the 3′ ends of genes by exploiting a mutation in which the 3′ end of another gene is transposed into the first gene of the Caenorhabditis elegans lin-15 operon. As expected, genes encoding CPSF and CstF were identified in the screen. We also report three suppressors encoding proteins containing a domain that interacts with the C-terminal domain of Pol II (CID). We show that two of the CID proteins are needed for efficient 3′ cleavage and thus may connect transcription termination with RNA cleavage. Furthermore, our results implicate a serine/arginine-rich (SR) protein, SRp20, in events following 3′-end cleavage, leading to termination of transcription.

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.

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.

Retrospective Reflections of a Whistleblower: Opinions on Misconduct Responses

Almost 10 years ago, when I was in my fourth year of graduate school, my fellow graduate students discovered that our thesis advisor had engaged in misconduct by falsifying and fabricating data in two grant applications. We informed the university and my advisor resigned. This event was a turning point in my life. Years later, I have gathered my thoughts and reflections on the experience. I believe we must first prevent what misconduct we can. But unfortunately some misconduct will still occur and in those circumstances we must respond to protect those affected by the misconduct and to progress beyond the event. In so doing, we get the most value out of scientific research.

FStitch: a fast and simple algorithm for detecting nascent RNA transcripts

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. A detailed study of GRO-seq data has the potential to inform on many aspects of the transcription process. 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, a hidden Markov model (HMM) and logistic regression to robustly classify which regions of the genome are transcribed. Our algorithm builds on the strengths of previous approaches but is accurate, dependent on very little training data, robust to varying read depth, annotation agnostic, and fast.

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.

RNA Pol II transcription model and interpretation of GRO-seq data.

A mixture model and statistical method is proposed to interpret the distribution of reads from a nascent transcriptional assay, such as global run-on sequencing (GRO-seq) data. The model is annotation agnostic and leverages on current understanding of the behavior of RNA polymerase II. Briefly, it assumes that polymerase loads at key positions (transcription start sites) within the genome. Once loaded, polymerase either remains in the initiation form (with some probability) or transitions into an elongating form (with the remaining probability). The model can be fit genome-wide, allowing patterns of Pol II behavior to be assessed on each distinct transcript. Furthermore, it allows for the first time a principled approach to distinguishing the initiation signal from the elongation signal; in particular, it implies a data driven method for calculating the pausing index, a commonly used metric that informs on the behavior of RNA polymerase II. We demonstrate that this approach improves on existing analyses of GRO-seq data and uncovers a novel biological understanding of the impact of knocking down the Male Specific Lethal (MSL) complex in Drosophilia melanogaster.

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 antisense transcripts are generally increased after heat shock, and 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.