A Gene's Ability to Buffer Variation Is Predicted by Its Fitness Contribution and Genetic Interactions

BACKGROUND: Many single-gene knockouts result in increased phenotypic (e.g., morphological) variability among the mutant's offspring. This has been interpreted as an intrinsic ability of genes to buffer genetic and environmental variation. A phenotypic capacitor is a gene that appears to mask phenotypic variation: when knocked out, the offspring shows more variability than the wild type. Theory predicts that this phenotypic potential should be correlated with a gene's knockout fitness and its number of negative genetic interactions. Based on experimentally measured phenotypic capacity, it was suggested that knockout fitness was unimportant, but that phenotypic capacitors tend to be hubs in genetic and physical interaction networks. METHODOLOGY/PRINCIPAL FINDINGS: We re-analyse the available experimental data in a combined model, which includes knockout fitness and network parameters as well as expression level and protein length as predictors of phenotypic potential. Contrary to previous conclusions, we find that the strongest predictor is in fact haploid knockout fitness (responsible for 9% of the variation in phenotypic potential), with an additional contribution from the genetic interaction network (5%); once these two factors are taken into account, protein-protein interactions do not make any additional contribution to the variation in phenotypic potential. CONCLUSIONS/SIGNIFICANCE: We conclude that phenotypic potential is not a mysterious "emergent" property of cellular networks. Instead, it is very simply determined by the overall fitness reduction of the organism (which in its compromised state can no longer compensate for multiple factors that contribute to phenotypic variation), and by the number (and presumably nature) of genetic interactions of the knocked-out gene. In this light, Hsp90, the prototypical phenotypic capacitor, may not be representative: typical phenotypic capacitors are not direct "buffers" of variation, but are simply genes encoding central cellular functions

Computational Modelling of Genome-Side Transcription Assembly Networks Using a Fluidics Analogy

Understanding how a myriad of transcription regulators work to modulate mRNA output at thousands of genes remains a fundamental challenge in molecular biology. Here we develop a computational tool to aid in assessing the plausibility of gene regulatory models derived from genome-wide expression profiling of cells mutant for transcription regulators. mRNA output is modelled as fluid flow in a pipe lattice, with assembly of the transcription machinery represented by the effect of valves. Transcriptional regulators are represented as external pressure heads that determine flow rate. Modelling mutations in regulatory proteins is achieved by adjusting valves' on/off settings. The topology of the lattice is designed by the experimentalist to resemble the expected interconnection between the modelled agents and their influence on mRNA expression. Users can compare multiple lattice configurations so as to find the one that minimizes the error with experimental data. This computational model provides a means to test the plausibility of transcription regulation models derived from large genomic data sets

Where Does Mediator Bind In Vivo?

Background: The Mediator complex associates with RNA polymerase (Pol) II, and it is recruited to enhancer regions by activator proteins under appropriate environmental conditions. However, the issue of Mediator association in yeast cells is controversial. Under optimal growth conditions (YPD medium), we were unable to detect Mediator at essentially any S. cerevisiae promoter region, including those supporting very high levels of transcription. In contrast, whole genome microarray experiments in synthetic complete (SC) medium reported that Mediator associates with many genes at both promoter and coding regions. Principal Findings: As assayed by chromatin immunoprecipitation, we show that there are a small number of Mediator targets in SC medium that are not observed in YPD medium. However, most Mediator targets identified in the genome-wide analysis are false positives that arose for several interrelated reasons: the use of overly lenient cut-offs; artifactual differences in apparent IP efficiencies among different genomic regions in the untagged strain; low fold-enrichments making it difficult to distinguish true Mediator targets from false positives that occur in the absence of the tagged Mediator protein. Lastly, apparent Mediator association in highly active coding regions is due to a non-specific effect on accessibility due to the lack of nucleosomes, not to a specific association of Mediator. Conclusions: These results indicate that Mediator does not bind to numerous sites in the yeast genome, but rathe

PROMPT: a protein mapping and comparison tool

BACKGROUND: Comparison of large protein datasets has become a standard task in bioinformatics. Typically researchers wish to know whether one group of proteins is significantly enriched in certain annotation attributes or sequence properties compared to another group, and whether this enrichment is statistically significant. In order to conduct such comparisons it is often required to integrate molecular sequence data and experimental information from disparate incompatible sources. While many specialized programs exist for comparisons of this kind in individual problem domains, such as expression data analysis, no generic software solution capable of addressing a wide spectrum of routine tasks in comparative proteomics is currently available. RESULTS: PROMPT is a comprehensive bioinformatics software environment which enables the user to compare arbitrary protein sequence sets, revealing statistically significant differences in their annotation features. It allows automatic retrieval and integration of data from a multitude of molecular biological databases as well as from a custom XML format. Similarity-based mapping of sequence IDs makes it possible to link experimental information obtained from different sources despite discrepancies in gene identifiers and minor sequence variation. PROMPT provides a full set of statistical procedures to address the following four use cases: i) comparison of the frequencies of categorical annotations between two sets, ii) enrichment of nominal features in one set with respect to another one, iii) comparison of numeric distributions, and iv) correlation of numeric variables. Analysis results can be visualized in the form of plots and spreadsheets and exported in various formats, including Microsoft Excel. CONCLUSION: PROMPT is a versatile, platform-independent, easily expandable, stand-alone application designed to be a practical workhorse in analysing and mining protein sequences and associated annotation. The availability of the Java Application Programming Interface and scripting capabilities on one hand, and the intuitive Graphical User Interface with context-sensitive help system on the other, make it equally accessible to professional bioinformaticians and biologically-oriented users. PROMPT is freely available for academic users from

On the Growth of Scientific Knowledge: Yeast Biology as a Case Study

The tempo and mode of human knowledge expansion is an enduring yet poorly understood topic. Through a temporal network analysis of three decades of discoveries of protein interactions and genetic interactions in baker's yeast, we show that the growth of scientific knowledge is exponential over time and that important subjects tend to be studied earlier. However, expansions of different domains of knowledge are highly heterogeneous and episodic such that the temporal turnover of knowledge hubs is much greater than expected by chance. Familiar subjects are preferentially studied over new subjects, leading to a reduced pace of innovation. While research is increasingly done in teams, the number of discoveries per researcher is greater in smaller teams. These findings reveal collective human behaviors in scientific research and help design better strategies in future knowledge exploration

Stability of mRNA/DNA and DNA/DNA Duplexes Affects mRNA Transcription

Nucleic acids, due to their structural and chemical properties, can form double-stranded secondary structures that assist the transfer of genetic information and can modulate gene expression. However, the nucleotide sequence alone is insufficient in explaining phenomena like intron-exon recognition during RNA processing. This raises the question whether nucleic acids are endowed with other attributes that can contribute to their biological functions. In this work, we present a calculation of thermodynamic stability of DNA/DNA and mRNA/DNA duplexes across the genomes of four species in the genus Saccharomyces by nearest-neighbor method. The results show that coding regions are more thermodynamically stable than introns, 3′-untranslated regions and intergenic sequences. Furthermore, open reading frames have more stable sense mRNA/DNA duplexes than the potential antisense duplexes, a property that can aid gene discovery. The lower stability of the DNA/DNA and mRNA/DNA duplexes of 3′-untranslated regions and the higher stability of genes correlates with increased mRNA level. These results suggest that the thermodynamic stability of DNA/DNA and mRNA/DNA duplexes affects mRNA transcription

Genome-Wide Modeling of Transcription Preinitiation Complex Disassembly Mechanisms using ChIP-chip Data

Apparent occupancy levels of proteins bound to DNA in vivo can now be routinely measured on a genomic scale. A challenge in relating these occupancy levels to assembly mechanisms that are defined with biochemically isolated components lies in the veracity of assumptions made regarding the in vivo system. Assumptions regarding behavior of molecules in vivo can neither be proven true nor false, and thus is necessarily subjective. Nevertheless, within those confines, connecting in vivo protein-DNA interaction observations with defined biochemical mechanisms is an important step towards fully defining and understanding assembly/disassembly mechanisms in vivo. To this end, we have developed a computational program PathCom that models in vivo protein-DNA occupancy data as biochemical mechanisms under the assumption that occupancy levels can be related to binding duration and explicitly defined assembly/disassembly reactions. We exemplify the process with the assembly of the general transcription factors (TBP, TFIIB, TFIIE, TFIIF, TFIIH, and RNA polymerase II) at the genes of the budding yeast Saccharomyces. Within the assumption inherent in the system our modeling suggests that TBP occupancy at promoters is rather transient compared to other general factors, despite the importance of TBP in nucleating assembly of the preinitiation complex. PathCom is suitable for modeling any assembly/disassembly pathway, given that all the proteins (or species) come together to form a complex

Dissecting Nucleosome Free Regions by a Segmental Semi-Markov Model

BACKGROUND: Nucleosome free regions (NFRs) play important roles in diverse biological processes including gene regulation. A genome-wide quantitative portrait of each individual NFR, with their starting and ending positions, lengths, and degrees of nucleosome depletion is critical for revealing the heterogeneity of gene regulation and chromatin organization. By averaging nucleosome occupancy levels, previous studies have identified the presence of NFRs in the promoter regions across many genes. However, evaluation of the quantitative characteristics of individual NFRs requires an NFR calling method. METHODOLOGY: In this study, we propose a statistical method to identify the patterns of NFRs from a genome-wide measurement of nucleosome occupancy. This method is based on an appropriately designed segmental semi-Markov model, which can capture each NFR pattern and output its quantitative characterizations. Our results show that the majority of the NFRs are located in intergenic regions or promoters with a length of about 400-600bp and varying degrees of nucleosome depletion. Our quantitative NFR mapping allows for an investigation of the relative impacts of transcription machinery and DNA sequence in evicting histones from NFRs. We show that while both factors have significant overall effects, their specific contributions vary across different subtypes of NFRs. CONCLUSION: The emphasis of our approach on the variation rather than the consensus of nucleosome free regions sets the tone for enabling the exploration of many subtler dynamic aspects of chromatin biology

Stochastic signalling rewires the interaction map of a multiple feedback network during yeast evolution

During evolution, genetic networks are rewired through strengthening or weakening their interactions to develop new regulatory schemes. In the galactose network, the GAL1/GAL3 paralogues and the GAL2 gene enhance their own expression mediated by the Gal4p transcriptional activator. The wiring strength in these feedback loops is set by the number of Gal4p binding sites. Here we show using synthetic circuits that multiplying the binding sites increases the expression of a gene under the direct control of an activator, but this enhancement is not fed back in the circuit. The feedback loops are rather activated by genes that have frequent stochastic bursts and fast RNA decay rates. In this way, rapid adaptation to galactose can be triggered even by weakly expressed genes. Our results indicate that nonlinear stochastic transcriptional responses enable feedback loops to function autonomously, or contrary to what is dictated by the strength of interactions enclosing the circuit

Control of Cyclin C Levels during Development of Dictyostelium

Background: Cdk8 and its partner cyclin C form part of the mediator complex which links the basal transcription machinery to regulatory proteins. The pair are required for correct regulation of a subset of genes and have been implicated in control of development in a number of organisms including the social amoeba Dictyostelium discoideum. When feeding, Dictyostelium amoebae are unicellular but upon starvation they aggregate to form a multicellular structure which develops into a fruiting body containing spores. Cells in which the gene encoding Cdk8 has been deleted fail to enter aggregates due to a failure of early gene expression.Principal Findings: We have monitored the expression levels of cyclin C protein during development and find levels decrease after the multicellular mound is formed. This decrease is triggered by extracellular cAMP that, in turn, is working in part through an increase in intracellular cAMP. The loss of cyclin C is coincident with a reduction in the association of Cdk8 with a high molecular weight complex in the nucleus. Overexpression of cyclin C and Cdk8 lead to an increased rate of early development, consistent with the levels being rate limiting.Conclusions: Overall these results show that both cyclin C and Cdk8 are regulated during development in response to extracellular signals and the levels of these proteins are important in controlling the timing of developmental processes. These findings have important implications for the role of these proteins in controlling development, suggesting that they are targets for developmental signals to regulate gene expression.</p