Jennifer Bryan

Dynamics of the yeast transcriptome during wine fermentation reveals a novel fermentation stress response

In this study, genome-wide expression analyses were used to study the response of Saccharomyces cerevisiae to stress throughout a 15-day wine fermentation. Forty per cent of the yeast genome significantly changed expression levels to mediate long-term adaptation to fermenting grape must. Among the genes that changed expression levels, a group of 223 genes was identified, which was designated as fermentation stress response (FSR) genes that were dramatically induced at various points during fermentation. FSR genes sustain high levels of induction up to the final time point and exhibited changes in expression levels ranging from four- to 80-fold. The FSR is novel; 62% of the genes involved have not been implicated in global stress responses and 28% of the FSR genes have no functional annotation. Genes involved in respiratory metabolism and gluconeogenesis were expressed during fermentation despite the presence of high concentrations of glucose. Ethanol, rather than nutrient depletion, seems to be responsible for entry of yeast cells into the stationary phase.

Synthetic Lethality of Cohesins with PARPs and Replication Fork Mediators

Synthetic lethality has been proposed as a way to leverage the genetic differences found in tumor cells to affect their selective killing. Cohesins, which tether sister chromatids together until anaphase onset, are mutated in a variety of tumor types. The elucidation of synthetic lethal interactions with cohesin mutants therefore identifies potential therapeutic targets. We used a cross-species approach to identify robust negative genetic interactions with cohesin mutants. Utilizing essential and non-essential mutant synthetic genetic arrays in Saccharomyces cerevisiae, we screened genome-wide for genetic interactions with hypomorphic mutations in cohesin genes. A somatic cell proliferation assay in Caenorhabditis elegans demonstrated that the majority of interactions were conserved. Analysis of the interactions found that cohesin mutants require the function of genes that mediate replication fork progression. Conservation of these interactions between replication fork mediators and cohesin in both yeast and C. elegans prompted us to test whether other replication fork mediators not found in the yeast were required for viability in cohesin mutants. PARP1 has roles in the DNA damage response but also in the restart of stalled replication forks. We found that a hypomorphic allele of the C. elegans SMC1 orthologue, him-1(e879), genetically interacted with mutations in the orthologues of PAR metabolism genes resulting in a reduced brood size and somatic cell defects. We then demonstrated that this interaction is conserved in human cells by showing that PARP inhibitors reduce the viability of cultured human cells depleted for cohesin components. This work demonstrates that large-scale genetic interaction screening in yeast can identify clinically relevant genetic interactions and suggests that PARP inhibitors, which are currently undergoing clinical trials as a treatment of homologous recombination-deficient cancers, may be effective in treating cancers that harbor cohesin mutations.

Synthetic lethal genetic interactions that decrease somatic cell proliferation in Caenorhabditis elegans identify the alternative RFCCTF18 as a candidate cancer drug target.

Somatic mutations causing chromosome instability (CIN) in tumors can be exploited for selective killing of cancer cells by knockdown of second-site genes causing synthetic lethality. We tested and statistically validated synthetic lethal (SL) interactions between mutations in six Saccharomyces cerevisiae CIN genes orthologous to genes mutated in colon tumors and five additional CIN genes. To identify which SL interactions are conserved in higher organisms and represent potential chemotherapeutic targets, we developed an assay system in Caenorhabditis elegans to test genetic interactions causing synthetic proliferation defects in somatic cells. We made use of postembryonic RNA interference and the vulval cell lineage of C. elegans as a readout for somatic cell proliferation defects. We identified SL interactions between members of the cohesin complex and CTF4, RAD27, and components of the alternative RFC(CTF18) complex. The genetic interactions tested are highly conserved between S. cerevisiae and C. elegans and suggest that the alternative RFC components DCC1, CTF8, and CTF18 are ideal therapeutic targets because of their mild phenotype when knocked down singly in C. elegans. Furthermore, the C. elegans assay system will contribute to our knowledge of genetic interactions in a multicellular animal and is a powerful approach to identify new cancer therapeutic targets.

Global Analysis of Yeast Endosomal Transport Identifies the Vps55/68 Sorting Complex

Endosomal transport is critical for cellular processes ranging from receptor down-regulation and retroviral budding to the immune response. A full understanding of endosome sorting requires a comprehensive picture of the multiprotein complexes that orchestrate vesicle formation and fusion. Here, we use unsupervised, large-scale phenotypic analysis and a novel computational approach for the global identification of endosomal transport factors. This technique effectively identifies components of known and novel protein assemblies. We report the characterization of a previously undescribed endosome sorting complex that contains two well-conserved proteins with four predicted membrane-spanning domains. Vps55p and Vps68p form a complex that acts with or downstream of ESCRT function to regulate endosomal trafficking. Loss of Vps68p disrupts recycling to the TGN as well as onward trafficking to the vacuole without preventing the formation of lumenal vesicles within the MVB. Our results suggest the Vps55/68 complex mediates a novel, conserved step in the endosomal maturation process.

Quantitative Detection and Resolution of BRAF V600 Status in Colorectal Cancer Using Droplet Digital PCR and a Novel Wild-Type Negative Assay.

A need exists for robust and cost-effective assays to detect a single or small set of actionable point mutations, or a complete set of clinically informative mutant alleles. Knowledge of these mutations can be used to alert the clinician to a rare mutation that might necessitate more aggressive clinical monitoring or a personalized course of treatment. An example is BRAF, a (proto)oncogene susceptible to either common or rare mutations in codon V600 and adjacent codons. We report a diagnostic technology that leverages the unique capabilities of droplet digital PCR to achieve not only accurate and sensitive detection of BRAF(V600E) but also all known somatic point mutations within the BRAF V600 codon. The simple and inexpensive two-well droplet digital PCR assay uses a chimeric locked nucleic acid/DNA probe against wild-type BRAF and a novel wild-type-negative screening paradigm. The assay shows complete diagnostic accuracy when applied to formalin-fixed, paraffin-embedded tumor specimens from metastatic colorectal cancer patients deficient for Mut L homologue-1.

ddpcr: an R package and web application for analysis of droplet digital PCR data.

Droplet digital polymerase chain reaction (ddPCR) is a novel platform for exact quantification of DNA which holds great promise in clinical diagnostics. It is increasingly popular due to its digital nature, which provides more accurate quantification and higher sensitivity than traditional real-time PCR. However, clinical adoption has been slowed in part by the lack of software tools available for analyzing ddPCR data. Here, we present ddpcr – a new R package for ddPCR visualization and analysis. In addition, ddpcr includes a web application (powered by the Shiny R package) that allows users to analyze ddPCR data using an interactive graphical interface.

Discovery and Expansion of Gene Modules by Seeking Isolated Groups in a Random Graph Process

Background A central problem in systems biology research is the identification and extension of biological modules–groups of genes or proteins participating in a common cellular process or physical complex. As a result, there is a persistent need for practical, principled methods to infer the modular organization of genes from genome-scale data. Results We introduce a novel approach for the identification of modules based on the persistence of isolated gene groups within an evolving graph process. First, the underlying genomic data is summarized in the form of ranked gene–gene relationships, thereby accommodating studies that quantify the relevant biological relationship directly or indirectly. Then, the observed gene–gene relationship ranks are viewed as the outcome of a random graph process and candidate modules are given by the identifiable subgraphs that arise during this process. An isolation index is computed for each module, which quantifies the statistical significance of its survival time. Conclusions The Miso (module isolation) method predicts gene modules from genomic data and the associated isolation index provides a module-specific measure of confidence. Improving on existing alternative, such as graph clustering and the global pruning of dendrograms, this index offers two intuitively appealing features: (1) the score is module-specific; and (2) different choices of threshold correlate logically with the resulting performance, i.e. a stringent cutoff yields high quality predictions, but low sensitivity. Through the analysis of yeast phenotype data, the Miso method is shown to outperform existing alternatives, in terms of the specificity and sensitivity of its predictions.

Excuse Me, Do You Have a Moment to Talk About Version Control?

ABSTRACT Data analysis, statistical research, and teaching statistics have at least one thing in common: these activities all produce many files! There are data files, source code, figures, tables, prepared reports, and much more. Most of these files evolve over the course of a project and often need to be shared with others, for reading or edits, as a project unfolds. Without explicit and structured management, project organization can easily descend into chaos, taking time away from the primary work and reducing the quality of the final product. This unhappy result can be avoided by repurposing tools and workflows from the software development world, namely, distributed version control. This article describes the use of the version control system Git and the hosting site GitHub for statistical and data scientific workflows. Special attention is given to projects that use the statistical language R and, optionally, R Markdown documents. Supplementary materials include an annotated set of links to step-by-step tutorials, real world examples, and other useful learning resources. Supplementary materials for this article are available online.

Functions of stone cells and oleoresin terpenes in the conifer defense syndrome

Conifers depend on complex defense systems against herbivores. Stone cells (SC) and oleoresin are physical and chemical defenses of Sitka spruce that have been separately studied in previous work. Weevil oviposit at the tip of the previous years apical shoot (PYAS). We investigated interactions between weevil larvae and trees in controlled oviposition experiments with resistant (R) and susceptible (S) Sitka spruce. R trees have an abundance of SC in the PYAS cortex. SC are mostly absent in S trees. R trees and S trees also differ in the composition of oleoresin terpenes. Transcriptomes of R and S trees revealed differences in long-term weevil-induced responses. Performance of larvae was significantly reduced on R trees compared with S trees under experimental conditions that mimicked natural oviposition behavior at apical shoot tips and may be attributed to the effects of SC. In oviposition experiments designed for larvae to feed below the area of highest SC abundance, larvae showed an unusual feeding behavior and oleoresin appeared to function as the major defense. The results support a role for both SC and oleoresin terpenes and possible synergies between these traits in the defense syndrome of weevil-resistant Sitka spruce.

Data Science: A Three Ring Circus or a Big Tent?

This is part of a collection of discussion pieces on David Donohos paper 50 Years of Data Science, appearing in Volume 26, Issue 4 of the Journal of Computational and Graphical Statistics (2017).