Automated construction of genetic networks from mutant data

Geneticists use mutations to investigate biological phenomena. Mutations cause changes of organism’s phenotype and may reveal which genes participate in a certain biological process and how. To represent these functional interactions between genes, a gene regulatory network is an often used formalism. We have developed a system called GenePath (1) for automated construction of genetic networks from mutant data

GenePath: a System for Automated Construction of Genetic Networks from Mutant Data

Motivation: Genetic pathways are often used in the analysis of biological phenomena. In classical genetics, they are constructed manually from experimental data on mutants. The field lacks formalism to guide such analysis, and accounting for all the data becomes complicated when large amounts of data are considered. Results: We have developed GenePath, an intelligent assistant that mimics expert geneticists in the analysis of genetic data. GenePath employs expert-defined patterns to uncover gene relations from the data, and uses these relations as constraints that guide the search for a plausible genetic network. GenePath provides formalism to genetic data analysis, facilitates the consideration of all the available data in a consistent and systematic manner, and aids in the examination of the large number of possible consequences of a planned experiment. It also provides an explanation mechanism that traces back every finding to the pertinent data. GenePath was successfully tested on several genetic problems. Availability: GenePath can be accessed at http://genepath.org. Supplementary information: Supplementary material is available at http://genepath.org/bi-supp

Web-enabled knowledge-based analysis of genetic data

We present a web-based implementation of GenePath, an intelligent assistant tool for data analysis in functional genomics. GenePath considers mutant data and uses expert-defined patterns to find gene-to-gene or gene-to-outcome relations. It presents the results of analysis as genetic networks, wherein a set of genes has various influence on one another and on a biological outcome. In the paper, we particularly focus on its web-based interface and explanation mechanisms

Gene prioritization by compressive data fusion and chaining

Data integration procedures combine heterogeneous data sets into predictive models, but they are limited to data explicitly related to the target object type, such as genes. Collage is a new data fusion approach to gene prioritization. It considers data sets of various association levels with the prediction task, utilizes collective matrix factorization to compress the data, and chaining to relate different object types contained in a data compendium. Collage prioritizes genes based on their similarity to several seed genes. We tested Collage by prioritizing bacterial response genes in Dictyostelium as a novel model system for prokaryote-eukaryote interactions. Using 4 seed genes and 14 data sets, only one of which was directly related to the bacterial response, Collage proposed 8 candidate genes that were readily validated as necessary for the response of Dictyostelium to Gram-negative bacteria. These findings establish Collage as a method for inferring biological knowledge from the integration of heterogeneous and coarsely related data sets

A new social gene in Dictyostelium discoideum, chtB

Background: Competitive social interactions are ubiquitous in nature, but their genetic basis is difficult to determine. Much can be learned from single gene knockouts in a eukaryote microbe. The mutants can be competed with the parent to discern the social impact of that specific gene. Dictyostelium discoideum is a social amoeba that exhibits cooperative behavior in the construction of a multicellular fruiting body. It is a good model organism to study the genetic basis of cooperation since it has a sequenced genome and it is amenable to genetic manipulation. When two strains of D. discoideum are mixed, a cheater strain can exploit its social partner by differentiating more spore than its fair share relative to stalk cells. Cheater strains can be generated in the lab or found in the wild and genetic analyses have shown that cheating behavior can be achieved through many pathways. Results: We have characterized the knockout mutant chtB, which was isolated from a screen for cheater mutants that were also able to form normal fruiting bodies on their own. When mixed in equal proportions with parental strain cells, chtB mutants contributed almost 60% of the total number of spores. To do so, chtB cells inhibit wild type cells from becoming spores, as indicated by counts and by the wild type cells’ reduced expression of the prespore gene, cotB. We found no obvious fitness costs (morphology, doubling time in liquid medium, spore production, and germination efficiency) associated with the cheating ability of the chtB knockout. Conclusions: In this study we describe a new gene in D. discoideum, chtB, which when knocked out inhibits the parental strain from producing spores. Moreover, under lab conditions, we did not detect any fitness costs associated with this behavior

Leaps and lulls in the developmental transcriptome of Dictyostelium discoideum

Development of the soil amoeba Dictyostelium discoideum is triggered by starvation. When placed on a solid substrate, the starving solitary amoebae cease growth, communicate via extracellular cAMP, aggregate by tens of thousands and develop into multicellular organisms. Early phases of the developmental program are often studied in cells starved in suspension while cAMP is provided exogenously. Previous studies revealed massive shifts in the transcriptome under both developmental conditions and a close relationship between gene expression and morphogenesis, but were limited by the sampling frequency and the resolution of the methods. Here, we combine the superior depth and specificity of RNA-seq-based analysis of mRNA abundance with high frequency sampling during filter development and cAMP pulsing in suspension. We found that the developmental transcriptome exhibits mostly gradual changes interspersed by a few instances of large shifts. For each time point we treated the entire transcriptome as single phenotype, and were able to characterize development as groups of similar time points separated by gaps. The grouped time points represented gradual changes in mRNA abundance, or molecular phenotype, and the gaps represented times during which many genes are differentially expressed rapidly, and thus the phenotype changes dramatically. Comparing developmental experiments revealed that gene expression in filter developed cells lagged behind those treated with exogenous cAMP in suspension. The high sampling frequency revealed many genes whose regulation is reproducibly more complex than indicated by previous studies. Gene Ontology enrichment analysis suggested that the transition to multicellularity coincided with rapid accumulation of transcripts associated with DNA processes and mitosis. Later development included the up-regulation of organic signaling molecules and co-factor biosynthesis. Our analysis also demonstrated a high level of synchrony among the developing structures throughout development. Our data describe D. discoideum development as a series of coordinated cellular and multicellular activities. Coordination occurred within fields of aggregating cells and among multicellular bodies, such as mounds or migratory slugs that experience both cell-cell contact and various soluble signaling regimes. These time courses, sampled at the highest temporal resolution to date in this system, provide a comprehensive resource for studies of developmental gene expression

Cheating by Exploitation of Developmental Prestalk Patterning in Dictyostelium discoideum

The cooperative developmental system of the social amoeba Dictyostelium discoideum is susceptible to exploitation by cheaters—strains that make more than their fair share of spores in chimerae. Laboratory screens in Dictyostelium have shown that the genetic potential for facultative cheating is high, and field surveys have shown that cheaters are abundant in nature, but the cheating mechanisms are largely unknown. Here we describe cheater C (chtC), a strong facultative cheater mutant that cheats by affecting prestalk differentiation. The chtC gene is developmentally regulated and its mRNA becomes stalk-enriched at the end of development. chtC mutants are defective in maintaining the prestalk cell fate as some of their prestalk cells transdifferentiate into prespore cells, but that defect does not affect gross developmental morphology or sporulation efficiency. In chimerae between wild-type and chtC mutant cells, the wild-type cells preferentially give rise to prestalk cells, and the chtC mutants increase their representation in the spore mass. Mixing chtC mutants with other cell-type proportioning mutants revealed that the cheating is directly related to the prestalk-differentiation propensity of the victim. These findings illustrate that a cheater can victimize cooperative strains by exploiting an established developmental pathway

Learning to get along despite struggling to get by

A review of evolutionary theories for cooperation, with emphasis on the mechanisms that can favor cooperation and reduce conflict within multicellular organisms, enabling the transition from unicellular to multicellular life

Cyclic AMP Is Dispensable for Allorecognition in Dictyostelium Cells Overexpressing PKA-C

Allorecognition and tissue formation are interconnected processes that require signaling between matching pairs of the polymorphic transmembrane proteins TgrB1 and TgrC1 in Dictyostelium. Extracellular and intracellular cAMP signaling are essential to many developmental processes. The three adenylate cyclase genes, acaA, acrA and acgA are required for aggregation, culmination and spore dormancy, respectively, and some of their functions can be suppressed by activation of the cAMP-dependent protein kinase PKA. Previous studies have suggested that cAMP signaling might be dispensable for allorecognition and tissue formation, while others have argued that it is essential throughout development. Here, we show that allorecognition and tissue formation do not require cAMP production as long as PKA is active. We eliminated cAMP production by deleting the three adenylate cyclases and overexpressed PKA-C to enable aggregation. The cells exhibited cell polarization, tissue formation and cooperation with allotype-compatible wild-type cells, but not with incompatible cells. Therefore, TgrB1-TgrC1 signaling controls allorecognition and tissue formation, while cAMP is dispensable as long as PKA-C is overexpressed

GenePath: from mutations to genetic networks and back

GenePath is a web-based application for the analysis of mutant-based experiments and synthesis of genetic networks. Here, we introduce GenePath and describe a number of new approaches, including conflict resolution, handling cyclic pathways, confidence level assignment, what-if analysis and new experiment proposal. We illustrate the key concepts using data from a study of adhesion genes in Dictyostelium discoideum and show that GenePath discovered genetic interactions that were ignored in the original publication. GenePath is available at