Robin D. Dowell

Tissue-specific transcriptional regulation has diverged significantly between human and mouse

We demonstrate that the binding sites for highly conserved transcription factors vary extensively between human and mouse. We mapped the binding of four tissue-specific transcription factors (FOXA2, HNF1A, HNF4A and HNF6) to 4,000 orthologous gene pairs in hepatocytes purified from human and mouse livers. Despite the conserved function of these factors, from 41% to 89% of their binding events seem to be species specific. When the same protein binds the promoters of orthologous genes, approximately two-thirds of the binding sites do not align.

The distributed annotation system.

BackgroundCurrently, most genome annotation is curated by centralized groups with limited resources. Efforts to share annotations transparently among multiple groups have not yet been satisfactory.ResultsHere we introduce a concept called the Distributed Annotation System (DAS). DAS allows sequence annotations to be decentralized among multiple third-party annotators and integrated on an as-needed basis by client-side software. The communication between client and servers in DAS is defined by the DAS XML specification. Annotations are displayed in layers, one per server. Any client or server adhering to the DAS XML specification can participate in the system; we describe a simple prototype client and server example.ConclusionsThe DAS specification is being used experimentally by Ensembl, WormBase, and the Berkeley Drosophila Genome Project. Continued success will depend on the readiness of the research community to adopt DAS and provide annotations. All components are freely available from the project website http://www.biodas.org/.

Genotype to Phenotype: A Complex Problem

In yeast, the impact of gene knockouts depends on genetic background. We generated a high-resolution whole-genome sequence and individually deleted 5100 genes in Σ1278b, a Saccharomyces cerevisiae strain closely related to reference strain S288c. Similar to the variation between human individuals, Σ1278b and S288c average 3.2 single-nucleotide polymorphisms per kilobase. A genome-wide comparison of deletion mutant phenotypes identified a subset of genes that were conditionally essential by strain, including 44 essential genes unique to Σ1278b and 13 unique to S288c. Genetic analysis indicates the conditional phenotype was most often governed by complex genetic interactions, depending on multiple background-specific modifiers. Our comprehensive analysis suggests that the presence of a complex set of modifiers will often underlie the phenotypic differences between individuals.

Evaluation of several lightweight stochastic context-free grammars for RNA secondary structure prediction

BackgroundRNA secondary structure prediction methods based on probabilistic modeling can be developed using stochastic context-free grammars (SCFGs). Such methods can readily combine different sources of information that can be expressed probabilistically, such as an evolutionary model of comparative RNA sequence analysis and a biophysical model of structure plausibility. However, the number of free parameters in an integrated model for consensus RNA structure prediction can become untenable if the underlying SCFG design is too complex. Thus a key question is, what small, simple SCFG designs perform best for RNA secondary structure prediction?ResultsNine different small SCFGs were implemented to explore the tradeoffs between model complexity and prediction accuracy. Each model was tested for single sequence structure prediction accuracy on a benchmark set of RNA secondary structures.ConclusionsFour SCFG designs had prediction accuracies near the performance of current energy minimization programs. One of these designs, introduced by Knudsen and Hein in their PFOLD algorithm, has only 21 free parameters and is significantly simpler than the others.

Core transcriptional regulatory circuitry in human hepatocytes

We mapped the transcriptional regulatory circuitry for six master regulators in human hepatocytes using chromatin immunoprecipitation and high‐resolution promoter microarrays. The results show that these regulators form a highly interconnected core circuitry, and reveal the local regulatory network motifs created by regulator–gene interactions. Autoregulation was a prominent theme among these regulators. We found that hepatocyte master regulators tend to bind promoter regions combinatorially and that the number of transcription factors bound to a promoter corresponds with observed gene expression. Our studies reveal portions of the core circuitry of human hepatocytes.

Toggle involving cis-interfering noncoding RNAs controls variegated gene expression in yeast

The identification of specific functional roles for the numerous long noncoding (nc)RNAs found in eukaryotic transcriptomes is currently a matter of intense study amid speculation that these ncRNAs have key regulatory roles. We have identified a pair of cis-interfering ncRNAs in yeast that contribute to the control of variegated gene expression at the FLO11 locus by implementing a regulatory circuit that toggles between two stable states. These capped, polyadenylated ncRNAs are transcribed across the large intergenic region upstream of the FLO11 ORF. As with mammalian long intervening (li)ncRNAs, these yeast ncRNAs (ICR1 and PWR1) are themselves regulated by transcription factors (Sfl1 and Flo8) and chromatin remodelers (Rpd3L) that are key elements in phenotypic transitions in yeast. The mechanism that we describe explains the unanticipated role of a histone deacetylase complex in activating gene expression, because Rpd3L mutants force the ncRNA circuit into a state that silences the expression of the adjacent variegating gene.

Polyploidy can drive rapid adaptation in yeast

Polyploidy is observed across the tree of life, yet its influence on evolution remains incompletely understood. Polyploidy, usually whole-genome duplication, is proposed to alter the rate of evolutionary adaptation. This could occur through complex effects on the frequency or fitness of beneficial mutations. For example, in diverse cell types and organisms, immediately after a whole-genome duplication, newly formed polyploids missegregate chromosomes and undergo genetic instability. The instability following whole-genome duplications is thought to provide adaptive mutations in microorganisms and can promote tumorigenesis in mammalian cells. Polyploidy may also affect adaptation independently of beneficial mutations through ploidy-specific changes in cell physiology. Here we perform in vitro evolution experiments to test directly whether polyploidy can accelerate evolutionary adaptation. Compared with haploids and diploids, tetraploids undergo significantly faster adaptation. Mathematical modelling suggests that rapid adaptation of tetraploids is driven by higher rates of beneficial mutations with stronger fitness effects, which is supported by whole-genome sequencing and phenotypic analyses of evolved clones. Chromosome aneuploidy, concerted chromosome loss, and point mutations all provide large fitness gains. We identify several mutations whose beneficial effects are manifest specifically in the tetraploid strains. Together, these results provide direct quantitative evidence that in some environments polyploidy can accelerate evolutionary adaptation.

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

High-resolution computational models of genome binding events

Direct physical information that describes where transcription factors, nucleosomes, modified histones, RNA polymerase II and other key proteins interact with the genome provides an invaluable mechanistic foundation for understanding complex programs of gene regulation. We present a method, joint binding deconvolution (JBD), which uses additional easily obtainable experimental data about chromatin immunoprecipitation (ChIP) to improve the spatial resolution of the transcription factor binding locations inferred from ChIP followed by DNA microarray hybridization (ChIP-Chip) data. Based on this probabilistic model of binding data, we further pursue improved spatial resolution by using sequence information. We produce positional priors that link ChIP-Chip data to sequence data by guiding motif discovery to inferred protein-DNA binding sites. We present results on the yeast transcription factors Gcn4 and Mig2 to demonstrate JBDs spatial resolution capabilities and show that positional priors allow computational discovery of the Mig2 motif when a standard approach fails.