Pietà G. Schofield

A role for Snf2-related nucleosome-spacing enzymes in genome-wide nucleosome organization.

Three chromatin remodeling enzymes in yeast drive higher-order chromatin compaction. The positioning of nucleosomes within the coding regions of eukaryotic genes is aligned with respect to transcriptional start sites. This organization is likely to influence many genetic processes, requiring access to the underlying DNA. Here, we show that the combined action of Isw1 and Chd1 nucleosome-spacing enzymes is required to maintain this organization. In the absence of these enzymes, regular positioning of the majority of nucleosomes is lost. Exceptions include the region upstream of the promoter, the +1 nucleosome, and a subset of locations distributed throughout coding regions where other factors are likely to be involved. These observations indicate that adenosine triphosphate–dependent remodeling enzymes are responsible for directing the positioning of the majority of nucleosomes within the Saccharomyces cerevisiae genome.

High-Resolution Whole-Genome Sequencing Reveals That Specific Chromatin Domains from Most Human Chromosomes Associate with Nucleoli

We present a genomewide, high-resolution study of nucleolar-associated chromatin using comparative genome hybridization, deep sequencing, and photoactivation microscopy. We show specific regions from most chromosomes associate with nucleoli. These regions are AT-rich, enriched in repressed genes, and overlap with nuclear lamina-associated loci.

How many biological replicates are needed in an RNA-seq experiment and which differential expression tool should you use?

RNA-seq is now the technology of choice for genome-wide differential gene expression experiments, but it is not clear how many biological replicates are needed to ensure valid biological interpretation of the results or which statistical tools are best for analyzing the data. An RNA-seq experiment with 48 biological replicates in each of two conditions was performed to answer these questions and provide guidelines for experimental design. With three biological replicates, nine of the 11 tools evaluated found only 20%-40% of the significantly differentially expressed (SDE) genes identified with the full set of 42 clean replicates. This rises to >85% for the subset of SDE genes changing in expression by more than fourfold. To achieve >85% for all SDE genes regardless of fold change requires more than 20 biological replicates. The same nine tools successfully control their false discovery rate at ≲5% for all numbers of replicates, while the remaining two tools fail to control their FDR adequately, particularly for low numbers of replicates. For future RNA-seq experiments, these results suggest that at least six biological replicates should be used, rising to at least 12 when it is important to identify SDE genes for all fold changes. If fewer than 12 replicates are used, a superior combination of true positive and false positive performances makes edgeR and DESeq2 the leading tools. For higher replicate numbers, minimizing false positives is more important and DESeq marginally outperforms the other tools.

Proteotoxic stress reprograms the chromatin landscape of SUMO modification

Cells use SUMO-2 to stabilize chromatin-associated proteins and cope with stress. SUMO-2 to the rescue In response to various proteotoxic stresses, such as heat shock or accumulation of misfolded proteins, cells activate protective mechanisms that depend on the production and function of heat shock proteins (HSPs) and other protein chaperones. Seifert et al. found that in response to various proteotoxic stresses, chromatin-associated proteins at sites of active genes were conjugated to SUMO-2 (small ubiquitin-like modifier 2) proteins. Rather than stimulate or repress target gene expression, conjugation with SUMO-2 enhanced the stability of protein complexes at transcription start sites, thus enabling cells to first withstand the initial effects of stress and express genes encoding HSPs and the other factors required for cell survival. The small ubiquitin-like modifier 2 (SUMO-2) is required for survival when cells are exposed to treatments that induce proteotoxic stress by causing the accumulation of misfolded proteins. Exposure of cells to heat shock or other forms of proteotoxic stress induces the conjugation of SUMO-2 to proteins in the nucleus. We investigated the chromatin landscape of SUMO-2 modifications in response to heat stress. Through chromatin immunoprecipitation assays coupled to high-throughput DNA sequencing and mRNA sequencing, we showed that in response to heat shock, SUMO-2 accumulated at nucleosome-depleted, active DNA regulatory elements, which represented binding sites for large protein complexes and were predominantly associated with active genes. However, SUMO did not act as a direct transcriptional repressor or activator of these genes during heat shock. Instead, integration of our results with published proteomics data on heat shock–induced SUMO-2 substrates supports a model in which the conjugation of SUMO-2 to proteins acts as an acute stress response that is required for the stability of protein complexes involved in gene expression and posttranscriptional modification of mRNA. We showed that the conjugation of SUMO-2 to chromatin-associated proteins is an integral component of the proteotoxic stress response, and propose that SUMO-2 fulfills its essential role in cell survival by contributing to the maintenance of protein complex homeostasis.

Statistical models for RNA-seq data derived from a two-condition 48-replicate experiment.

Motivation: High-throughput RNA sequencing (RNA-seq) is now the standard method to determine differential gene expression. Identifying differentially expressed genes crucially depends on estimates of read-count variability. These estimates are typically based on statistical models such as the negative binomial distribution, which is employed by the tools edgeR, DESeq and cuffdiff. Until now, the validity of these models has usually been tested on either low-replicate RNA-seq data or simulations. Results: A 48-replicate RNA-seq experiment in yeast was performed and data tested against theoretical models. The observed gene read counts were consistent with both log-normal and negative binomial distributions, while the mean-variance relation followed the line of constant dispersion parameter of ∼0.01. The high-replicate data also allowed for strict quality control and screening of ‘bad’ replicates, which can drastically affect the gene read-count distribution. Availability and implementation: RNA-seq data have been submitted to ENA archive with project ID PRJEB5348. Contact: g.j.barton@dundee.ac.uk

The Chromatin Remodelling Enzymes SNF2H and SNF2L Position Nucleosomes adjacent to CTCF and Other Transcription Factors

Within the genomes of metazoans, nucleosomes are highly organised adjacent to the binding sites for a subset of transcription factors. Here we have sought to investigate which chromatin remodelling enzymes are responsible for this. We find that the ATP-dependent chromatin remodelling enzyme SNF2H plays a major role organising arrays of nucleosomes adjacent to the binding sites for the architectural transcription factor CTCF sites and acts to promote CTCF binding. At many other factor binding sites SNF2H and the related enzyme SNF2L contribute to nucleosome organisation. The action of SNF2H at CTCF sites is functionally important as depletion of CTCF or SNF2H affects transcription of a common group of genes. This suggests that chromatin remodelling ATPase’s most closely related to the Drosophila ISWI protein contribute to the function of many human gene regulatory elements.

Disease induced dynamics in host–parasitoid systems: chaos and coexistence

All animals and plants are, to some extent, susceptible to disease caused by varying combinations of parasites, viruses and bacteria. In this paper, we present a mathematical model of interactions between a host, two parasitoids and a pathogen which shows that the presence of an infection can preserve and promote diversity in such multi-species systems. Initially, we use a system of ordinary differential equations to investigate interactions between two species of parasitoids, a host and a host infection. We show that the presence of all four species is necessary for the system as a whole to persist, and that in particular, the presence of the pathogen is necessary for the coexistence of the two parasitoid species. The inclusion of infection induces a wide range of dynamics, including chaos, and these dynamics are robust for a wide range of parameter values. We then extend the model to include spatial effects by introducing random motility (diffusion) of all three species and examine the subsequent spatio-temporal dynamics, including travelling waves and other more complicated heterogeneous behaviour. The computational simulation results of the model suggest that infection in the hosts can blunt the effects of competition between parasitoids, allowing the weaker competitor to survive. Regardless of the nature of the stability of the coexistent steady state of the system, there is an initial period of transient dynamics, the length of which can be extended by an appropriate choice of initial conditions. The existence of these transient dynamics suggests that systems subject to regular restoration to a starting state, such as agro-ecosystems, may be kept in a continual state of dynamic transience, and this has implications for the use of natural enemies to control insect pests, the preservation of biodiversity in farmland habitats and the more general dynamics of disease processes.

Modelling contact spread of infection in host-parasitoid systems: vertical transmission of pathogens can cause chaos.

All animals and plants are, to some extent, susceptible to disease caused by varying combinations of parasites, viruses and bacteria. In this paper, we develop a mathematical model of contact spread infection to investigate the effect of introducing a parasitoid-vectored infection into a one-host-two-parasitoid competition model. We use a system of ordinary differential equations to investigate the separate influences of horizontal and vertical pathogen transmission on a model system appropriate for a variety of competitive situations. Computational simulations and steady-state analysis show that the transient and long-term dynamics exhibited under contact spread infection are highly complex. Horizontal pathogen transmission has a stabilising effect on the system whilst vertical transmission can destabilise it to the point of chaotic fluctuations in population levels. This has implications when considering the introduction of host pathogens for the control of insect vectored diseases such as bovine tuberculosis or yellow fever.

Mutational signatures of DNA mismatch repair deficiency in C. elegans and human cancers.

Throughout their lifetime, cells are subject to extrinsic and intrinsic mutational processes leaving behind characteristic signatures in the genome. DNA mismatch repair (MMR) deficiency leads to hypermutation and is found in different cancer types. Although it is possible to associate mutational signatures extracted from human cancers with possible mutational processes, the exact causation is often unknown. Here, we use C. elegans genome sequencing of pms-2 and mlh-1 knockouts to reveal the mutational patterns linked to C. elegans MMR deficiency and their dependency on endogenous replication errors and errors caused by deletion of the polymerase ε subunit pole-4 Signature extraction from 215 human colorectal and 289 gastric adenocarcinomas revealed three MMR-associated signatures, one of which closely resembles the C. elegans MMR spectrum and strongly discriminates microsatellite stable and unstable tumors (AUC = 98%). A characteristic difference between human and C. elegans MMR deficiency is the lack of elevated levels of NCG > NTG mutations in C. elegans, likely caused by the absence of cytosine (CpG) methylation in worms. The other two human MMR signatures may reflect the interaction between MMR deficiency and other mutagenic processes, but their exact cause remains unknown. In summary, combining information from genetically defined models and cancer samples allows for better aligning mutational signatures to causal mutagenic processes.