SpliceNet: recovering splicing isoform-specific differential gene networks from RNA-Seq data of normal and diseased samples

Conventionally, overall gene expressions from microarrays are used to infer gene networks, but it is challenging to account splicing isoforms. High-throughput RNA Sequencing has made splice variant profiling practical. However, its true merit in quantifying splicing isoforms and isoform-specific exon expressions is not well explored in inferring gene networks. This study demonstrates SpliceNet, a method to infer isoform-specific co-expression networks from exon-level RNA-Seq data, using large dimensional trace. It goes beyond differentially expressed genes and infers splicing isoform network changes between normal and diseased samples. It eases the sample size bottleneck; evaluations on simulated data and lung cancer-specific ERBB2 and MAPK signaling pathways, with varying number of samples, evince the merit in handling high exon to sample size ratio datasets. Inferred network rewiring of well established Bcl-x and EGFR centered networks from lung adenocarcinoma expression data is in good agreement with literature. Gene level evaluations demonstrate a substantial performance of SpliceNet over canonical correlation analysis, a method that is currently applied to exon level RNA-Seq data. SpliceNet can also be applied to exon array data. SpliceNet is distributed as an R package available at http://www.jjwanglab.org/SpliceNet.     

GeneDistiller—Distilling Candidate Genes from Linkage Intervals

Background

Linkage studies often yield intervals containing several hundred positional candidate genes. Different manual or automatic approaches exist for the determination of the gene most likely to cause the disease. While the manual search is very flexible and takes advantage of the researchers'' background knowledge and intuition, it may be very cumbersome to collect and study the relevant data. Automatic solutions on the other hand usually focus on certain models, remain “black boxes” and do not offer the same degree of flexibility.

Methodology

We have developed a web-based application that combines the advantages of both approaches. Information from various data sources such as gene-phenotype associations, gene expression patterns and protein-protein interactions was integrated into a central database. Researchers can select which information for the genes within a candidate interval or for single genes shall be displayed. Genes can also interactively be filtered, sorted and prioritised according to criteria derived from the background knowledge and preconception of the disease under scrutiny.

Conclusions

GeneDistiller provides knowledge-driven, fully interactive and intuitive access to multiple data sources. It displays maximum relevant information, while saving the user from drowning in the flood of data. A typical query takes less than two seconds, thus allowing an interactive and explorative approach to the hunt for the candidate gene.

Access

GeneDistiller can be freely accessed at http://www.genedistiller.org     

SeqFeatR for the Discovery of Feature-Sequence Associations

Specific selection pressures often lead to specifically mutated genomes. The open source software SeqFeatR has been developed to identify associations between mutation patterns in biological sequences and specific selection pressures (“features”). For instance, SeqFeatR has been used to discover in viral protein sequences new T cell epitopes for hosts of given HLA types. SeqFeatR supports frequentist and Bayesian methods for the discovery of statistical sequence-feature associations. Moreover, it offers novel ways to visualize results of the statistical analyses and to relate them to further properties. In this article we demonstrate various functions of SeqFeatR with real data. The most frequently used set of functions is also provided by a web server. SeqFeatR is implemented as R package and freely available from the R archive CRAN (http://cran.r-project.org/web/packages/SeqFeatR/index.html). The package includes a tutorial vignette. The software is distributed under the GNU General Public License (version 3 or later). The web server URL is https://seqfeatr.zmb.uni-due.de.     

The Roles of Multiple UNC-40 (DCC) Receptor-Mediated Signals in Determining Neuronal Asymmetry Induced by the UNC-6 (Netrin) Ligand

The polarization of post-mitotic neurons is poorly understood. Preexisting spatially asymmetric cues, distributed within the neuron or as extracellular gradients, could be required for neurons to polarize. Alternatively, neurons might have the intrinsic ability to polarize without any preestablished asymmetric cues. In Caenorhabditis elegans, the UNC-40 (DCC) receptor mediates responses to the extracellular UNC-6 (netrin) guidance cue. For the HSN neuron, an UNC-6 ventral-dorsal gradient asymmetrically localizes UNC-40 to the ventral HSN surface. There an axon forms, which is ventrally directed by UNC-6. In the absence of UNC-6, UNC-40 is equally distributed and the HSN axon travels anteriorly in response to other cues. However, we find that a single amino acid change in the UNC-40 ectodomain causes randomly oriented asymmetric UNC-40 localization and a wandering axon phenotype. With UNC-6, there is normal UNC-40 localization and axon migration. A single UNC-6 amino acid substitution enhances the mutant phenotypes, whereas UNC-6 second-site amino acid substitutions suppress the phenotypes. We propose that UNC-40 mediates multiple signals to polarize and orient asymmetry. One signal triggers the intrinsic ability of HSN to polarize and causes randomly oriented asymmetry. Concurrently, another signal biases the orientation of the asymmetry relative to the UNC-6 gradient. The UNC-40 ectodomain mutation activates the polarization signal, whereas different forms of the UNC-6 ligand produce UNC-40 conformational changes that allow or prohibit the orientation signal.A major challenge for developmental neuroscience has been to understand how axons are able to detect and follow molecular gradients of different extracellular guidance cues. Attractive guidance cues are proposed to stimulate cytoplasmic signaling pathways that promote actin polymerization (Huber et al. 2003). Thus the direction of axon outgrowth is directly linked to the extracellular gradient of the guidance cue; i.e., there is greater extension on the side of the neuron that is closest to the source of the cue. Netrins are bifunctional guidance cues that are attractive to some axons but repulsive to others. Studies have shown that the axon response to netrin is determined by the composition of netrin receptors on the cell surface and the internal state of the growth cone (Round and Stein 2007). The UNC-6 (netrin) guidance cue in Caenorhabditis elegans interacts with the UNC-40 (DCC) receptor to mediate attraction (Hedgecock et al. 1990; Ishii et al. 1992; Chan et al. 1996). The AVM and HSN neurons are useful for studying UNC-40-mediated responses to UNC-6. The cell bodies of these neurons are situated on the lateral body wall and send a single axon ventrally during larval development.In AVM and HSN, a signaling module comprising UNC-6, UNC-40, phosphoinositide 3-kinase (PI3K), Rac, and MIG-10 (lamellipodin) is thought to transmit the directional information provided by the graded distribution of extracellular guidance cues to the internal cellular machinery that promotes directed outgrowth (Adler et al. 2006; Chang et al. 2006; Quinn et al. 2006, 2008). MIG-10 appears to provide an important link because this family of proteins can interact with proteins that promote actin polymerization, and it is associated with asymmetric concentrations of f-actin and microtubules in turning growth cones (Krause et al. 2004; Quinn et al. 2008). MIG-10 is observed as asymmetrically localized to the ventral site of axon outgrowth in developing HSN neurons. This MIG-10 localization is sensitive to the source of UNC-6. Normally, the source of UNC-6 is ventral; in the absence of UNC-6, there is an equal distribution of MIG-10 along the cell surface, whereas ectopic UNC-6 expression from dorsal muscles causes dorsal MIG-10 localization (Adler et al. 2006). The UNC-40 receptor is also asymmetrically localized in HSN, and this localization is also dependent on UNC-6 (Adler et al. 2006). UNC-40 signaling activates Rac GTPase, and MIG-10 interacts specifically with the activated Rac (Quinn et al. 2008). Therefore, the asymmetric activation of Rac through UNC-40 recruits asymmetric MIG-10 localization.By activating or directing components to the surface nearest the UNC-6 source, the asymmetric distribution of UNC-6 could polarize the neuron. However, an alternative idea is suggested from studies of chemotaxing cells. This model predicts that chemoattractant signaling involves two different elements: one that activates the intrinsic ability of cells to generate asymmetry and another that biases the orientation of the asymmetry (Wedlich-Soldner and Li 2003). The polarization signal does not depend on the spatial information provided by the chemoattractant gradient, whereas the orientation signal does. The asymmetric localization of the UNC-40 and MIG-10 signaling complex is suggestive of the segregation of signaling components into separate “front” and “rear” regions during chemotactic cell migration (Weiner 2002; Mortimer et al. 2008). It is hypothesized that this segregation is accomplished through short-range positive feedback mechanisms that promote the local production or recruitment of signaling molecules. In addition, a long-range inhibition mechanism globally increases the degradation of these molecules. Together such mechanisms could strongly amplify the asymmetric distribution of molecules needed for directed movement. This model has been put forth to explain why chemotactic cells polarize and move in a random direction when encountering a uniform chemoattractant concentration. Although the chemoattractant receptors may be uniformly stimulated across the surface of the cells, randomly oriented asymmetry can be established through these mechanisms.If the AVM and HSN neurons behave similarly to chemotactic cells, then uniformly stimulating UNC-40 receptors might similarly cause nonspecific asymmetric UNC-40 localization and axon migrations in varying directions. However, this is difficult to test in vivo. Unlike exposing chemotactic cells to a uniform concentration of a chemotractant in vitro, there is no reliable way to ensure that a neuron in vivo is exposed to a uniform concentration of UNC-6. The pseudocoelomic cavity of C. elegans is fluid filled, and UNC-6 expression patterns are spatially and temporally complex (Wadsworth et al. 1996). How the distribution of UNC-6 is affected by interactions with the extracellular matrix and cell surfaces is unknown.Using a genetic approach, we have found an UNC-40 mutation that triggers randomly oriented neuronal asymmetry. On the basis of the models proposed for chemotactic cells, we suggest that there is an UNC-6/UNC-40-mediated signal that specifically induces the neuron''s intrinsic ability to polarize. The UNC-40 mutation activates this signal; however, a second signal, which normally would concurrently orient asymmetry relative to the UNC-6 gradient, is not activated. Single amino acid changes within the UNC-6 ligand can enhance or suppress the randomly oriented asymmetry phenotype caused by the UNC-40 mutation. This suggests that specific UNC-40 conformations uncouple the activation of the different signals.     

Gene set enrichment analysis for multiple continuous phenotypes

Background

Gene set analysis (GSA) methods test the association of sets of genes with phenotypes in gene expression microarray studies. While GSA methods on a single binary or categorical phenotype abounds, little attention has been paid to the case of a continuous phenotype, and there is no method to accommodate correlated multiple continuous phenotypes.

Result

We propose here an extension of the linear combination test (LCT) to its new version for multiple continuous phenotypes, incorporating correlations among gene expressions of functionally related gene sets, as well as correlations among multiple phenotypes. Further, we extend our new method to its nonlinear version, referred as nonlinear combination test (NLCT), to test potential nonlinear association of gene sets with multiple phenotypes. Simulation study and a real microarray example demonstrate the practical aspects of the proposed methods.

Conclusion

The proposed approaches are effective in controlling type I errors and powerful in testing associations between gene-sets and multiple continuous phenotypes. They are both computationally effective. Naively (univariately) analyzing a group of multiple correlated phenotypes could be dangerous. R-codes to perform LCT and NLCT for multiple continuous phenotypes are available at http://www.ualberta.ca/~yyasui/homepage.html.

Electronic supplementary material

The online version of this article (doi:10.1186/1471-2105-15-260) contains supplementary material, which is available to authorized users.     

RIDDLE: reflective diffusion and local extension reveal functional associations for unannotated gene sets via proximity in a gene network

The growing availability of large-scale functional networks has promoted the development of many successful techniques for predicting functions of genes. Here we extend these network-based principles and techniques to functionally characterize whole sets of genes. We present RIDDLE (Reflective Diffusion and Local Extension), which uses well developed guilt-by-association principles upon a human gene network to identify associations of gene sets. RIDDLE is particularly adept at characterizing sets with no annotations, a major challenge where most traditional set analyses fail. Notably, RIDDLE found microRNA-450a to be strongly implicated in ocular diseases and development. A web application is available at http://www.functionalnet.org/RIDDLE.     

CAPE: An R Package for Combined Analysis of Pleiotropy and Epistasis

Contemporary genetic studies are revealing the genetic complexity of many traits in humans and model organisms. Two hallmarks of this complexity are epistasis, meaning gene-gene interaction, and pleiotropy, in which one gene affects multiple phenotypes. Understanding the genetic architecture of complex traits requires addressing these phenomena, but interpreting the biological significance of epistasis and pleiotropy is often difficult. While epistasis reveals dependencies between genetic variants, it is often unclear how the activity of one variant is specifically modifying the other. Epistasis found in one phenotypic context may disappear in another context, rendering the genetic interaction ambiguous. Pleiotropy can suggest either redundant phenotype measures or gene variants that affect multiple biological processes. Here we present an R package, R/cape, which addresses these interpretation ambiguities by implementing a novel method to generate predictive and interpretable genetic networks that influence quantitative phenotypes. R/cape integrates information from multiple related phenotypes to constrain models of epistasis, thereby enhancing the detection of interactions that simultaneously describe all phenotypes. The networks inferred by R/cape are readily interpretable in terms of directed influences that indicate suppressive and enhancing effects of individual genetic variants on other variants, which in turn account for the variance in quantitative traits. We demonstrate the utility of R/cape by analyzing a mouse backcross, thereby discovering novel epistatic interactions influencing phenotypes related to obesity and diabetes. R/cape is an easy-to-use, platform-independent R package and can be applied to data from both genetic screens and a variety of segregating populations including backcrosses, intercrosses, and natural populations. The package is freely available under the GPL-3 license at http://cran.r-project.org/web/packages/cape.

This is a PLOS Computational Biology Software Article

     

SANTA: Quantifying the Functional Content of Molecular Networks

Linking networks of molecular interactions to cellular functions and phenotypes is a key goal in systems biology. Here, we adapt concepts of spatial statistics to assess the functional content of molecular networks. Based on the guilt-by-association principle, our approach (called SANTA) quantifies the strength of association between a gene set and a network, and functionally annotates molecular networks like other enrichment methods annotate lists of genes. As a general association measure, SANTA can (i) functionally annotate experimentally derived networks using a collection of curated gene sets and (ii) annotate experimentally derived gene sets using a collection of curated networks, as well as (iii) prioritize genes for follow-up analyses. We exemplify the efficacy of SANTA in several case studies using the S. cerevisiae genetic interaction network and genome-wide RNAi screens in cancer cell lines. Our theory, simulations, and applications show that SANTA provides a principled statistical way to quantify the association between molecular networks and cellular functions and phenotypes. SANTA is available from http://bioconductor.org/packages/release/bioc/html/SANTA.html.     

Presaging Critical Residues in Protein interfaces-Web Server (PCRPi-W): A Web Server to Chart Hot Spots in Protein Interfaces

Background

It is well established that only a portion of residues that mediate protein-protein interactions (PPIs), the so-called hot spot, contributes the most to the total binding energy, and thus its identification is an important and relevant question that has clear applications in drug discovery and protein design. The experimental identification of hot spots is however a lengthy and costly process, and thus there is an interest in computational tools that can complement and guide experimental efforts.

Principal Findings

Here, we present Presaging Critical Residues in Protein interfaces-Web server (http://www.bioinsilico.org/PCRPi), a web server that implements a recently described and highly accurate computational tool designed to predict critical residues in protein interfaces: PCRPi. PRCPi depends on the integration of structural, energetic, and evolutionary-based measures by using Bayesian Networks (BNs).

Conclusions

PCRPi-W has been designed to provide an easy and convenient access to the broad scientific community. Predictions are readily available for download or presented in a web page that includes among other information links to relevant files, sequence information, and a Jmol applet to visualize and analyze the predictions in the context of the protein structure.     

Vfold: A Web Server for RNA Structure and Folding Thermodynamics Prediction

Background

The ever increasing discovery of non-coding RNAs leads to unprecedented demand for the accurate modeling of RNA folding, including the predictions of two-dimensional (base pair) and three-dimensional all-atom structures and folding stabilities. Accurate modeling of RNA structure and stability has far-reaching impact on our understanding of RNA functions in human health and our ability to design RNA-based therapeutic strategies.

Results

The Vfold server offers a web interface to predict (a) RNA two-dimensional structure from the nucleotide sequence, (b) three-dimensional structure from the two-dimensional structure and the sequence, and (c) folding thermodynamics (heat capacity melting curve) from the sequence. To predict the two-dimensional structure (base pairs), the server generates an ensemble of structures, including loop structures with the different intra-loop mismatches, and evaluates the free energies using the experimental parameters for the base stacks and the loop entropy parameters given by a coarse-grained RNA folding model (the Vfold model) for the loops. To predict the three-dimensional structure, the server assembles the motif scaffolds using structure templates extracted from the known PDB structures and refines the structure using all-atom energy minimization.

Conclusions

The Vfold-based web server provides a user friendly tool for the prediction of RNA structure and stability. The web server and the source codes are freely accessible for public use at “http://rna.physics.missouri.edu”.     

Chromatin-Associated Proteins HP1 and Mod(mdg4) Modify Y-Linked Regulatory Variation in the Drosophila Testis

Chromatin remodeling is crucial for gene regulation. Remodeling is often mediated through chemical modifications of the DNA template, DNA-associated proteins, and RNA-mediated processes. Y-linked regulatory variation (YRV) refers to the quantitative effects that polymorphic tracts of Y-linked chromatin exert on gene expression of X-linked and autosomal genes. Here we show that naturally occurring polymorphisms in the Drosophila melanogaster Y chromosome contribute disproportionally to gene expression variation in the testis. The variation is dependent on wild-type expression levels of mod(mdg4) as well as Su(var)205; the latter gene codes for heterochromatin protein 1 (HP1) in Drosophila. Testis-specific YRV is abolished in genotypes with heterozygous loss-of-function mutations for mod(mdg4) and Su(var)205 but not in similar experiments with JIL-1. Furthermore, the Y chromosome differentially regulates several ubiquitously expressed genes. The results highlight the requirement for wild-type dosage of Su(var)205 and mod(mdg4) in enabling naturally occurring Y-linked regulatory variation in the testis. The phenotypes that emerge in the context of wild-type levels of the HP1 and Mod(mdg4) proteins might be part of an adaptive response to the environment.     

Approximate Bayesian Computation

Approximate Bayesian computation (ABC) constitutes a class of computational methods rooted in Bayesian statistics. In all model-based statistical inference, the likelihood function is of central importance, since it expresses the probability of the observed data under a particular statistical model, and thus quantifies the support data lend to particular values of parameters and to choices among different models. For simple models, an analytical formula for the likelihood function can typically be derived. However, for more complex models, an analytical formula might be elusive or the likelihood function might be computationally very costly to evaluate. ABC methods bypass the evaluation of the likelihood function. In this way, ABC methods widen the realm of models for which statistical inference can be considered. ABC methods are mathematically well-founded, but they inevitably make assumptions and approximations whose impact needs to be carefully assessed. Furthermore, the wider application domain of ABC exacerbates the challenges of parameter estimation and model selection. ABC has rapidly gained popularity over the last years and in particular for the analysis of complex problems arising in biological sciences (e.g., in population genetics, ecology, epidemiology, and systems biology).

This is a “Topic Page” article for PLOS Computational Biology.

     

Integrative Multi-omics Module Network Inference with Lemon-Tree

Module network inference is an established statistical method to reconstruct co-expression modules and their upstream regulatory programs from integrated multi-omics datasets measuring the activity levels of various cellular components across different individuals, experimental conditions or time points of a dynamic process. We have developed Lemon-Tree, an open-source, platform-independent, modular, extensible software package implementing state-of-the-art ensemble methods for module network inference. We benchmarked Lemon-Tree using large-scale tumor datasets and showed that Lemon-Tree algorithms compare favorably with state-of-the-art module network inference software. We also analyzed a large dataset of somatic copy-number alterations and gene expression levels measured in glioblastoma samples from The Cancer Genome Atlas and found that Lemon-Tree correctly identifies known glioblastoma oncogenes and tumor suppressors as master regulators in the inferred module network. Novel candidate driver genes predicted by Lemon-Tree were validated using tumor pathway and survival analyses. Lemon-Tree is available from http://lemon-tree.googlecode.com under the GNU General Public License version 2.0.

This is a PLOS Computational Biology Software Article

     

Decreased Energy Metabolism Extends Life Span in Caenorhabditis elegans Without Reducing Oxidative Damage

On the basis of the free radical and rate of living theories of aging, it has been proposed that decreased metabolism leads to increased longevity through a decreased production of reactive oxygen species (ROS). In this article, we examine the relationship between mitochondrial energy metabolism and life span by using the Clk mutants in Caenorhabditis elegans. Clk mutants are characterized by slow physiologic rates, delayed development, and increased life span. This phenotype suggests that increased life span may be achieved by decreasing energy expenditure. To test this hypothesis, we identified six novel Clk mutants in a screen for worms that have slow defecation and slow development and that can be maternally rescued. Interestingly, all 11 Clk mutants have increased life span despite the fact that slow physiologic rates were used as the only screening criterion. Although mitochondrial function is decreased in the Clk mutants, ATP levels are normal or increased, suggesting decreased energy utilization. To determine whether the longevity of the Clk mutants results from decreased production of ROS, we examined sensitivity to oxidative stress and oxidative damage. We found no evidence for systematically increased resistance to oxidative stress or decreased oxidative damage in the Clk mutants despite normal or elevated levels of superoxide dismutases. Overall, our findings suggest that decreased energy metabolism can lead to increased life span without decreased production of ROS.MUTATIONS in clk-1 have been shown to increase longevity in both worms and mice, suggesting that these mutations affect an evolutionarily conserved mechanism of life span extension (Lakowski and Hekimi 1996; Liu et al. 2005; Lapointe et al. 2009). The CLK-1 protein encodes a hydroxylase involved in the synthesis of ubiquinone (Ewbank et al. 1997), a multifunctional, lipid-like molecule that transfers electrons in the electron transport chain and may also act as an intracellular antioxidant (Maroz et al. 2009). clk-1 was originally identified in worms in a screen for maternally rescued mutations that result in abnormal development and behavior. In addition to slow development and slow defecation, clk-1 mutants show decreased brood size, a decreased rate of thrashing, and a decreased rate of pharyngeal pumping (Wong et al. 1995). It was a surprise, however, that clk-1 worms also displayed extended longevity, because, at the time that it was discovered, only two other mutants, age-1 and daf-2, with very different phenotypes, had been found to extend longevity (Friedman and Johnson 1988; Kenyon et al. 1993).It is currently uncertain how mutations in clk-1 result in the overall slowing of development and physiologic rates as well as an extended life span. One classic theory of aging, called the rate of living theory, postulates the existence of a link between energy metabolism and aging (Pearl 1922; Speakman 2005). This theory proposes that what determines the life span of an organism is the rate at which it produces and uses energy at the cellular level. Thus, the fact that clk-1 worms exhibit slow physiologic rates and development suggests a decrease in the rate that these worms utilize energy, and, by the rate of living theory, this could account for their long life span.In support of the rate of living theory, the loss of clk-1 has been shown to result in decreased whole-worm oxygen consumption (Felkai et al. 1999; Yang et al. 2007) and decreased electron transfer from complex I to complex III in the electron transport chain (Kayser et al. 2004b), although this has not been observed by all investigators (Miyadera et al. 2001). While some reports have suggested that energy consumption is not reduced in clk-1 worms, at least under liquid culture conditions (Braeckman et al. 2002), the observation that clk-1 worms have higher levels of ATP than wild-type worms (Braeckman et al. 1999) suggests a decreased use of energy in clk-1 worms regardless of whether energy production is normal or decreased. It has also been found that clk-1 double-mutant combinations that exhibit slower development than clk-1 worms live even longer than clk-1 worms (Lakowski and Hekimi 1996). In addition, overexpression of clk-1 prevents the slowing of the defecation rate with age, increases mitochondrial function, and decreases life span (Felkai et al. 1999).Drawing on ideas from the free radical theory of aging (Harman 1956), it has been suggested that a possible mechanism underlying the rate of living theory is that decreased metabolism results in a lower rate of production of reactive oxygen species (ROS). As the free radical theory of aging proposes that aging results from the accumulation of molecular damage caused by ROS, then lower ROS production should result in slower aging. In clk-1 worms, it has not been possible to directly measure levels of ROS in vivo; however, measurement of hydrogen peroxide production from submitochondrial particles has demonstrated increased ROS generation in clk-1 mitochondria compared to wild type (Yang et al. 2009). In addition, the superoxide production potential is increased in clk-1 worms compared to wild-type N2 worms (Braeckman et al. 2002). Despite showing increased levels of ROS production, clk-1 worms have been found to have normal or decreased levels of oxidative damage (Kayser et al. 2004a; Yang et al. 2007, 2009) and decreased accumulation of lipofuscin (Braeckman et al. 2002). The decrease in oxidative damage that occurs in spite of increased ROS production likely results from increased antioxidant defenses. In support of this conclusion, sod-2 and sod-3 mRNA are increased in clk-1 worms compared to wild type (Yang et al. 2007).Clearly, the levels of ROS production and antioxidant defense are altered in clk-1 worms and likely contribute to the physiology and life span of these worms. Evidence supporting a role for altered ROS levels in determining the clk-1 phenotype comes from the demonstration that increasing the levels of ROS through decreasing superoxide dismutase expression has been shown to modulate a variety of phenotypes in clk-1 worms (Shibata et al. 2003; Yang et al. 2007). It is important to note, however, that the decrease in oxidative damage in clk-1 worms appears not to contribute to their long life as it is possible to experimentally increase oxidative damage in clk-1 worms beyond wild-type levels without reducing life span (Yang et al. 2007).In addition to clk-1, four other genes have been identified that yield a clk-1-like phenotype (Clk phenotype), which includes slow development, slow defecation, slow pharyngeal pumping, decreased brood size and long life span coupled with maternal rescue (homozygous mutants from heterozygous mothers are phenotypically normal) (Hekimi et al. 1995; Lemieux et al. 2001). The Clk phenotype has been studied in most detail in clk-1 worms (Wong et al. 1995) and, subsequently, with gro-1 (Lemieux et al. 2001), clk-2 (Benard et al. 2001), and tpk-1 worms (de Jong et al. 2004), while clk-3 worms have not been extensively studied [although clk-3 worm energy metabolism and oxygen consumption have been examined (Braeckman et al. 2002; Shoyama et al. 2009)]. Despite the phenotypic similarity of these mutants, the mutations that have been identified thus far have been shown to occur in genes encoding proteins with a wide range of functions with no obvious relationship to one another. gro-1 encodes a tRNA-modifying enzyme (Lemieux et al. 2001), clk-2 encodes a homolog of yeast Tel2p and a regulator of several PI3K-related protein kinases (Ahmed et al. 2001; Benard et al. 2001; Jiang et al. 2003; Takai et al. 2007), and tpk-1 encodes thiamine pyrophosphokinase, which is necessary for the assimilation of thiamine (vitamin B1) (de Jong et al. 2004).All of the Clk mutants that have been identified exhibit slow physiologic rates and increased life span, suggesting that one may be sufficient for the other. To test this hypothesis, we identified six novel Clk mutants and demonstrate that these strains bear all of the characteristic features of the Clk phenotype, including extended longevity. We further show that mitochondrial function is decreased in the Clk mutants but that this decrease does not result in increased resistance to oxidative stress or decreased oxidative damage. Our results provide a plausible explanation for the extended life span observed in the Clk mutants and support aspects of the rate of living theory of aging while casting further doubt on the free radical theory of aging.     

"Just Another Tool for Online Studies” (JATOS): An Easy Solution for Setup and Management of Web Servers Supporting Online Studies

We present here “Just Another Tool for Online Studies” (JATOS): an open source, cross-platform web application with a graphical user interface (GUI) that greatly simplifies setting up and communicating with a web server to host online studies that are written in JavaScript. JATOS is easy to install in all three major platforms (Microsoft Windows, Mac OS X, and Linux), and seamlessly pairs with a database for secure data storage. It can be installed on a server or locally, allowing researchers to try the application and feasibility of their studies within a browser environment, before engaging in setting up a server. All communication with the JATOS server takes place via a GUI (with no need to use a command line interface), making JATOS an especially accessible tool for researchers without a strong IT background. We describe JATOS’ main features and implementation and provide a detailed tutorial along with example studies to help interested researchers to set up their online studies. JATOS can be found under the Internet address: www.jatos.org.     

QuIN: A Web Server for Querying and Visualizing Chromatin Interaction Networks

Recent studies of the human genome have indicated that regulatory elements (e.g. promoters and enhancers) at distal genomic locations can interact with each other via chromatin folding and affect gene expression levels. Genomic technologies for mapping interactions between DNA regions, e.g., ChIA-PET and HiC, can generate genome-wide maps of interactions between regulatory elements. These interaction datasets are important resources to infer distal gene targets of non-coding regulatory elements and to facilitate prioritization of critical loci for important cellular functions. With the increasing diversity and complexity of genomic information and public ontologies, making sense of these datasets demands integrative and easy-to-use software tools. Moreover, network representation of chromatin interaction maps enables effective data visualization, integration, and mining. Currently, there is no software that can take full advantage of network theory approaches for the analysis of chromatin interaction datasets. To fill this gap, we developed a web-based application, QuIN, which enables: 1) building and visualizing chromatin interaction networks, 2) annotating networks with user-provided private and publicly available functional genomics and interaction datasets, 3) querying network components based on gene name or chromosome location, and 4) utilizing network based measures to identify and prioritize critical regulatory targets and their direct and indirect interactions. AVAILABILITY: QuIN’s web server is available at http://quin.jax.org QuIN is developed in Java and JavaScript, utilizing an Apache Tomcat web server and MySQL database and the source code is available under the GPLV3 license available on GitHub: https://github.com/UcarLab/QuIN/.

This is a PLOS Computational Biology Software paper.