Maximal Extraction of Biological Information from Genetic Interaction Data

Targeted genetic perturbation is a powerful tool for inferring gene function in model organisms. Functional relationships between genes can be inferred by observing the effects of multiple genetic perturbations in a single strain. The study of these relationships, generally referred to as genetic interactions, is a classic technique for ordering genes in pathways, thereby revealing genetic organization and gene-to-gene information flow. Genetic interaction screens are now being carried out in high-throughput experiments involving tens or hundreds of genes. These data sets have the potential to reveal genetic organization on a large scale, and require computational techniques that best reveal this organization. In this paper, we use a complexity metric based in information theory to determine the maximally informative network given a set of genetic interaction data. We find that networks with high complexity scores yield the most biological information in terms of (i) specific associations between genes and biological functions, and (ii) mapping modules of co-functional genes. This information-based approach is an automated, unsupervised classification of the biological rules underlying observed genetic interactions. It might have particular potential in genetic studies in which interactions are complex and prior gene annotation data are sparse

Recombinational Landscape and Population Genomics of Caenorhabditis elegans

Recombination rate and linkage disequilibrium, the latter a function of population genomic processes, are the critical parameters for mapping by linkage and association, and their patterns in Caenorhabditis elegans are poorly understood. We performed high-density SNP genotyping on a large panel of recombinant inbred advanced intercross lines (RIAILs) of C. elegans to characterize the landscape of recombination and, on a panel of wild strains, to characterize population genomic patterns. We confirmed that C. elegans autosomes exhibit discrete domains of nearly constant recombination rate, and we show, for the first time, that the pattern holds for the X chromosome as well. The terminal domains of each chromosome, spanning about 7% of the genome, exhibit effectively no recombination. The RIAILs exhibit a 5.3-fold expansion of the genetic map. With median marker spacing of 61 kb, they are a powerful resource for mapping quantitative trait loci in C. elegans. Among 125 wild isolates, we identified only 41 distinct haplotypes. The patterns of genotypic similarity suggest that some presumed wild strains are laboratory contaminants. The Hawaiian strain, CB4856, exhibits genetic isolation from the remainder of the global population, whose members exhibit ample evidence of intercrossing and recombining. The population effective recombination rate, estimated from the pattern of linkage disequilibrium, is correlated with the estimated meiotic recombination rate, but its magnitude implies that the effective rate of outcrossing is extremely low, corroborating reports of selection against recombinant genotypes. Despite the low population, effective recombination rate and extensive linkage disequilibrium among chromosomes, which are techniques that account for background levels of genomic similarity, permit association mapping in wild C. elegans strains

Matrix Metalloproteinase-Induced Epithelial-Mesenchymal Transition in Breast Cancer

Matrix metalloproteinases (MMPs) degrade and modify the extracellular matrix (ECM) as well as cell-ECM and cell-cell contacts, facilitating detachment of epithelial cells from the surrounding tissue. MMPs play key functions in embryonic development and mammary gland branching morphogenesis, but they are also upregulated in breast cancer, where they stimulate tumorigenesis, cancer cell invasion and metastasis. MMPs have been investigated as potential targets for cancer therapy, but clinical trials using broad-spectrum MMP inhibitors yielded disappointing results, due in part to lack of specificity toward individual MMPs and specific stages of tumor development. Epithelial-mesenchymal transition (EMT) is a developmental process in which epithelial cells take on the characteristics of invasive mesenchymal cells, and activation of EMT has been implicated in tumor progression. Recent findings have implicated MMPs as promoters and mediators of developmental and pathogenic EMT processes in the breast. In this review, we will summarize recent studies showing how MMPs activate EMT in mammary gland development and in breast cancer, and how MMPs mediate breast cancer cell motility, invasion, and EMT-driven breast cancer progression. We also suggest approaches to inhibit these MMP-mediated malignant processes for therapeutic benefit