Joshua J. Waterfall

Nascent RNA Sequencing Reveals Widespread Pausing and Divergent Initiation at Human Promoters

RNA polymerases are highly regulated molecular machines. We present a method (global run-on sequencing, GRO-seq) that maps the position, amount, and orientation of transcriptionally engaged RNA polymerases genome-wide. In this method, nuclear run-on RNA molecules are subjected to large-scale parallel sequencing and mapped to the genome. We show that peaks of promoter-proximal polymerase reside on ∼30% of human genes, transcription extends beyond pre-messenger RNA 3′ cleavage, and antisense transcription is prevalent. Additionally, most promoters have an engaged polymerase upstream and in an orientation opposite to the annotated gene. This divergent polymerase is associated with active genes but does not elongate effectively beyond the promoter. These results imply that the interplay between polymerases and regulators over broad promoter regions dictates the orientation and efficiency of productive transcription.

Universally Sloppy Parameter Sensitivities in Systems Biology Models

Quantitative computational models play an increasingly important role in modern biology. Such models typically involve many free parameters, and assigning their values is often a substantial obstacle to model development. Directly measuring in vivo biochemical parameters is difficult, and collectively fitting them to other experimental data often yields large parameter uncertainties. Nevertheless, in earlier work we showed in a growth-factor-signaling model that collective fitting could yield well-constrained predictions, even when it left individual parameters very poorly constrained. We also showed that the model had a “sloppy” spectrum of parameter sensitivities, with eigenvalues roughly evenly distributed over many decades. Here we use a collection of models from the literature to test whether such sloppy spectra are common in systems biology. Strikingly, we find that every model we examine has a sloppy spectrum of sensitivities. We also test several consequences of this sloppiness for building predictive models. In particular, sloppiness suggests that collective fits to even large amounts of ideal time-series data will often leave many parameters poorly constrained. Tests over our model collection are consistent with this suggestion. This difficulty with collective fits may seem to argue for direct parameter measurements, but sloppiness also implies that such measurements must be formidably precise and complete to usefully constrain many model predictions. We confirm this implication in our growth-factor-signaling model. Our results suggest that sloppy sensitivity spectra are universal in systems biology models. The prevalence of sloppiness highlights the power of collective fits and suggests that modelers should focus on predictions rather than on parameters.

A Rapid, Extensive, and Transient Transcriptional Response to Estrogen Signaling in Breast Cancer Cells

We report the immediate effects of estrogen signaling on the transcriptome of breast cancer cells using global run-on and sequencing (GRO-seq). The data were analyzed using a new bioinformatic approach that allowed us to identify transcripts directly from the GRO-seq data. We found that estrogen signaling directly regulates a strikingly large fraction of the transcriptome in a rapid, robust, and unexpectedly transient manner. In addition to protein-coding genes, estrogen regulates the distribution and activity of all three RNA polymerases and virtually every class of noncoding RNA that has been described to date. We also identified a large number of previously undetected estrogen-regulated intergenic transcripts, many of which are found proximal to estrogen receptor binding sites. Collectively, our results provide the most comprehensive measurement of the primary and immediate estrogen effects to date and a resource for understanding rapid signal-dependent transcription in other systems.

Succinate Dehydrogenase Mutation Underlies Global Epigenomic Divergence in Gastrointestinal Stromal Tumor

Gastrointestinal stromal tumors (GIST) harbor driver mutations of signal transduction kinases such as KIT, or, alternatively, manifest loss-of-function defects in the mitochondrial succinate dehydrogenase (SDH) complex, a component of the Krebs cycle and electron transport chain. We have uncovered a striking divergence between the DNA methylation profiles of SDH-deficient GIST (n = 24) versus KIT tyrosine kinase pathway-mutated GIST (n = 39). Infinium 450K methylation array analysis of formalin-fixed paraffin-embedded tissues disclosed an order of magnitude greater genomic hypermethylation relative to SDH-deficient GIST versus the KIT-mutant group (84.9 K vs. 8.4 K targets). Epigenomic divergence was further found among SDH-mutant paraganglioma/pheochromocytoma (n = 29), a developmentally distinct SDH-deficient tumor system. Comparison of SDH-mutant GIST with isocitrate dehydrogenase-mutant glioma, another Krebs cycle-defective tumor type, revealed comparable measures of global hypo- and hypermethylation. These data expose a vital connection between succinate metabolism and genomic DNA methylation during tumorigenesis, and generally implicate the mitochondrial Krebs cycle in nuclear epigenomic maintenance.

High prevalence of MAP2K1 mutations in variant and IGHV4-34-expressing hairy-cell leukemias.

To understand the genetic mechanisms driving variant and IGHV4-34–expressing hairy-cell leukemias, we performed whole-exome sequencing of leukemia samples from ten affected individuals, including six with matched normal samples. We identified activating mutations in the MAP2K1 gene (encoding MEK1) in 5 of these 10 samples and in 10 of 21 samples in a validation set (overall frequency of 15/31), suggesting potential new strategies for treating individuals with these diseases.

Recurrent epimutation of SDHC in gastrointestinal stromal tumors

Methylation of the SDH gene explains the loss of SDH gene expression in SDH wild-type gastrointestinal stromal tumors. All Roads Lead to Loss of Expression Gastrointestinal stromal tumors are the most common mesenchymal tumors in the gastrointestinal tract, and they can occur in isolation or as part of a constellation of cancers known as Carney triad. A subtype of this cancer, characterized by lack of expression in a gene called SDH, is not well understood and lacks a specific treatment, and this is the type that most commonly occurs in children. Now, Killian et al. have identified methylation of the SDH gene in patients with SDH-deficient gastrointestinal stromal tumors who lack mutations in the SDH gene. This finding provides a common link explaining the pathogenesis of these SDH-deficient tumors, including many of the ones associated with Carney triad. Succinate dehydrogenase (SDH) is a conserved effector of cellular metabolism and energy production, and loss of SDH function is a driver mechanism in several cancers. SDH-deficient gastrointestinal stromal tumors (dSDH GISTs) collectively manifest similar phenotypes, including hypermethylated epigenomic signatures, tendency to occur in pediatric patients, and lack of KIT/PDGFRA mutations. dSDH GISTs often harbor deleterious mutations in SDH subunit genes (SDHA, SDHB, SDHC, and SDHD, termed SDHx), but some are SDHx wild type (WT). To further elucidate mechanisms of SDH deactivation in SDHx-WT GIST, we performed targeted exome sequencing on 59 dSDH GISTs to identify 43 SDHx-mutant and 16 SDHx-WT cases. Genome-wide DNA methylation and expression profiling exposed SDHC promoter–specific CpG island hypermethylation and gene silencing in SDHx-WT dSDH GISTs [15 of 16 cases (94%)]. Six of 15 SDHC-epimutant GISTs occurred in the setting of the multitumor syndrome Carney triad. We observed neither SDHB promoter hypermethylation nor large deletions on chromosome 1q in any SDHx-WT cases. Deep genome sequencing of a 130-kbp (kilo–base pair) window around SDHC revealed no recognizable sequence anomalies in SDHC-epimutant tumors. More than 2000 benign and tumor reference tissues, including stem cells and malignancies with a hypermethylator epigenotype, exhibit solely a non-epimutant SDHC promoter. Mosaic constitutional SDHC promoter hypermethylation in blood and saliva from patients with SDHC-epimutant GIST implicates a postzygotic mechanism in the establishment and maintenance of SDHC epimutation. The discovery of SDHC epimutation provides a unifying explanation for the pathogenesis of dSDH GIST, whereby loss of SDH function stems from either SDHx mutation or SDHC epimutation.

Transcriptional activation by the thyroid hormone receptor through ligand-dependent receptor recruitment and chromatin remodelling

A bimodal switch model is widely used to describe transcriptional regulation by the thyroid hormone receptor (TR). In this model, the unliganded TR forms stable, chromatin-bound complexes with transcriptional co-repressors to repress transcription. Binding of hormone dissociates co-repressors and facilitates recruitment of co-activators to activate transcription. Here we show that in addition to hormone-independent TR occupancy, ChIP-seq against endogenous TR in mouse liver tissue demonstrates considerable hormone-induced TR recruitment to chromatin associated with chromatin remodelling and activated gene transcription. Genome-wide footprinting analysis using DNase-seq provides little evidence for TR footprints both in the absence and presence of hormone, suggesting that unliganded TR engagement with repressive complexes on chromatin is, similar to activating receptor complexes, a highly dynamic process. This dynamic and ligand-dependent interaction with chromatin is likely shared by all steroid hormone receptors regardless of their capacity to repress transcription in the absence of ligand.

Extracting Falsifiable Predictions from Sloppy Models

Abstract:  Successful predictions are among the most compelling validations of any model. Extracting falsifiable predictions from nonlinear multiparameter models is complicated by the fact that such models are commonly sloppy, possessing sensitivities to different parameter combinations that range over many decades. Here we discuss how sloppiness affects the sorts of data that best constrain model predictions, makes linear uncertainty approximations dangerous, and introduces computational difficulties in Monte‐Carlo uncertainty analysis. We also present a useful test problem and suggest refinements to the standards by which models are communicated.

The role of mutation of metabolism-related genes in genomic hypermethylation.

Genetic mutations, metabolic dysfunction, and epigenetic misregulation are commonly considered to play distinct roles in tumor development and maintenance. However, intimate relationships between these mechanisms are now emerging. In particular, mutations in genes for the core metabolic enzymes IDH, SDH, and FH are significant drivers of diverse tumor types. In each case, the resultant accumulation of particular metabolites inhibits TET enzymes responsible for oxidizing 5-methylcytosine, leading to pervasive DNA hypermethylation.

A methyl-deviator epigenotype of estrogen receptor-positive breast carcinoma is associated with malignant biology.

We broadly profiled DNA methylation in breast cancers (n = 351) and benign parenchyma (n = 47) for correspondence with disease phenotype, using FFPE diagnostic surgical pathology specimens. Exploratory analysis revealed a distinctive primary invasive carcinoma subclass featuring extreme global methylation deviation. Subsequently, we tested the correlation between methylation remodeling pervasiveness and malignant biological features. A methyl deviation index (MDI) was calculated for each lesion relative to terminal ductal-lobular unit baseline, and group comparisons revealed that high-grade and short-survival estrogen receptor-positive (ER(+)) cancers manifest a significantly higher MDI than low-grade and long-survival ER(+) cancers. In contrast, ER(-) cancers display a significantly lower MDI, revealing a striking epigenomic distinction between cancer hormone receptor subtypes. Kaplan-Meier survival curves of MDI-based risk classes showed significant divergence between low- and high-risk groups. MDI showed superior prognostic performance to crude methylation levels, and MDI retained prognostic significance (P < 0.01) in Cox multivariate analysis, including clinical stage and pathological grade. Most MDI targets individually are significant markers of ER(+) cancer survival. Lymphoid and mesenchymal indexes were not substantially different between ER(+) and ER(-) groups and do not explain MDI dichotomy. However, the mesenchymal index was associated with ER(+) cancer survival, and a high lymphoid index was associated with medullary carcinoma. Finally, a comparison between metastases and primary tumors suggests methylation patterns are established early and maintained through disease progression for both ER(+) and ER(-) tumors.