A Caenorhabditis elegans genetic-interaction map wiggles into view

Systematic mapping of genetic-interaction networks will provide an essential foundation for understanding complex genetic disorders, mechanisms of genetic buffering and principles of robustness and evolvability. A recent study of signaling pathways in Caenorhabditis elegans lays the next row of bricks in this foundation

Diverse roles of actin in C. elegans early embryogenesis

<p>Abstract</p> <p>Background</p> <p>The actin cytoskeleton plays critical roles in early development in <it>Caenorhabditis elegans</it>. To further understand the complex roles of actin in early embryogenesis we use RNAi and <it>in vivo </it>imaging of filamentous actin (F-actin) dynamics.</p> <p>Results</p> <p>Using RNAi, we found processes that are differentially sensitive to levels of actin during early embryogenesis. Mild actin depletion shows defects in cortical ruffling, pseudocleavage, and establishment of polarity, while more severe depletion shows defects in polar body extrusion, cytokinesis, chromosome segregation, and eventually, egg production. These defects indicate that actin is required for proper oocyte development, fertilization, and a wide range of important events during early embryogenesis, including proper chromosome segregation. <it>In vivo </it>visualization of the cortical actin cytoskeleton shows dynamics that parallel but are distinct from the previously described myosin dynamics. Two distinct types of actin organization are observed at the cortex. During asymmetric polarization to the anterior, or the establishment phase (Phase I), actin forms a meshwork of microfilaments and focal accumulations throughout the cortex, while during the anterior maintenance phase (Phase II) it undergoes a morphological transition to asymmetrically localized puncta. The proper asymmetric redistribution is dependent on the PAR proteins, while both asymmetric redistribution and morphological transitions are dependent upon PFN-1 and NMY-2. Just before cytokinesis, actin disappears from most of the cortex and is only found around the presumptive cytokinetic furrow. Finally, we describe dynamic actin-enriched comets in the early embryo.</p> <p>Conclusion</p> <p>During early <it>C. elegans </it>embryogenesis actin plays more roles and its organization is more dynamic than previously described. Morphological transitions of F-actin, from meshwork to puncta, as well as asymmetric redistribution, are regulated by the PAR proteins. Results from this study indicate new insights into the cellular and developmental roles of the actin cytoskeleton.</p

microRNA Target Predictions across Seven Drosophila Species and Comparison to Mammalian Targets

microRNAs are small noncoding genes that regulate the protein production of genes by binding to partially complementary sites in the mRNAs of targeted genes. Here, using our algorithm PicTar, we exploit cross-species comparisons to predict, on average, 54 targeted genes per microRNA above noise in Drosophila melanogaster. Analysis of the functional annotation of target genes furthermore suggests specific biological functions for many microRNAs. We also predict combinatorial targets for clustered microRNAs and find that some clustered microRNAs are likely to coordinately regulate target genes. Furthermore, we compare microRNA regulation between insects and vertebrates. We find that the widespread extent of gene regulation by microRNAs is comparable between flies and mammals but that certain microRNAs may function in clade-specific modes of gene regulation. One of these microRNAs (miR-210) is predicted to contribute to the regulation of fly oogenesis. We also list specific regulatory relationships that appear to be conserved between flies and mammals. Our findings provide the most extensive microRNA target predictions in Drosophila to date, suggest specific functional roles for most microRNAs, indicate the existence of coordinate gene regulation executed by clustered microRNAs, and shed light on the evolution of microRNA function across large evolutionary distances. All predictions are freely accessible at our searchable Web site http://pictar.bio.nyu.edu

A Genome-Wide Map of Conserved MicroRNA Targets in C. elegans

SummaryBackgroundMetazoan miRNAs regulate protein-coding genes by binding the 3′ UTR of cognate mRNAs. Identifying targets for the 115 known C. elegans miRNAs is essential for understanding their function.ResultsBy using a new version of PicTar and sequence alignments of three nematodes, we predict that miRNAs regulate at least 10% of C. elegans genes through conserved interactions. We have developed a new experimental pipeline to assay 3′ UTR-mediated posttranscriptional gene regulation via an endogenous reporter expression system amenable to high-throughput cloning, demonstrating the utility of this system using one of the most intensely studied miRNAs, let-7. Our expression analyses uncover several new potential let-7 targets and suggest a new let-7 activity in head muscle and neurons. To explore genome-wide trends in miRNA function, we analyzed functional categories of predicted target genes, finding that one-third of C. elegans miRNAs target gene sets are enriched for specific functional annotations. We have also integrated miRNA target predictions with other functional genomic data from C. elegans.ConclusionsAt least 10% of C. elegans genes are predicted miRNA targets, and a number of nematode miRNAs seem to regulate biological processes by targeting functionally related genes. We have also developed and successfully utilized an in vivo system for testing miRNA target predictions in likely endogenous expression domains. The thousands of genome-wide miRNA target predictions for nematodes, humans, and flies are available from the PicTar website and are linked to an accessible graphical network-browsing tool allowing exploration of miRNA target predictions in the context of various functional genomic data resources

MINE: Module Identification in Networks

<p>Abstract</p> <p>Background</p> <p>Graphical models of network associations are useful for both visualizing and integrating multiple types of association data. Identifying modules, or groups of functionally related gene products, is an important challenge in analyzing biological networks. However, existing tools to identify modules are insufficient when applied to dense networks of experimentally derived interaction data. To address this problem, we have developed an agglomerative clustering method that is able to identify highly modular sets of gene products within highly interconnected molecular interaction networks.</p> <p>Results</p> <p>MINE outperforms MCODE, CFinder, NEMO, SPICi, and MCL in identifying non-exclusive, high modularity clusters when applied to the <it>C. elegans </it>protein-protein interaction network. The algorithm generally achieves superior geometric accuracy and modularity for annotated functional categories. In comparison with the most closely related algorithm, MCODE, the top clusters identified by MINE are consistently of higher density and MINE is less likely to designate overlapping modules as a single unit. MINE offers a high level of granularity with a small number of adjustable parameters, enabling users to fine-tune cluster results for input networks with differing topological properties.</p> <p>Conclusions</p> <p>MINE was created in response to the challenge of discovering high quality modules of gene products within highly interconnected biological networks. The algorithm allows a high degree of flexibility and user-customisation of results with few adjustable parameters. MINE outperforms several popular clustering algorithms in identifying modules with high modularity and obtains good overall recall and precision of functional annotations in protein-protein interaction networks from both <it>S. cerevisiae </it>and <it>C. elegans</it>.</p

Rational Design of Temperature-Sensitive Alleles Using Computational Structure Prediction

Temperature-sensitive (ts) mutations are mutations that exhibit a mutant phenotype at high or low temperatures and a wild-type phenotype at normal temperature. Temperature-sensitive mutants are valuable tools for geneticists, particularly in the study of essential genes. However, finding ts mutations typically relies on generating and screening many thousands of mutations, which is an expensive and labor-intensive process. Here we describe an in silico method that uses Rosetta and machine learning techniques to predict a highly accurate “top 5” list of ts mutations given the structure of a protein of interest. Rosetta is a protein structure prediction and design code, used here to model and score how proteins accommodate point mutations with side-chain and backbone movements. We show that integrating Rosetta relax-derived features with sequence-based features results in accurate temperature-sensitive mutation predictions

Shaping the Future of Research: a perspective from junior scientists

The landscape of scientific research and funding is in flux as a result of tight budgets, evolving models of both publishing and evaluation, and questions about training and workforce stability. As future leaders, junior scientists are uniquely poised to shape the culture and practice of science in response to these challenges. A group of postdocs in the Boston area who are invested in improving the scientific endeavor, planned a symposium held on October 2 nd and 3 rd, 2014, as a way to join the discussion about the future of US biomedical research. Here we present a report of the proceedings of participant-driven workshops and the organizers’ synthesis of the outcomes