PPLook: an automated data mining tool for protein-protein interaction

<p>Abstract</p> <p>Background</p> <p>Extracting and visualizing of protein-protein interaction (PPI) from text literatures are a meaningful topic in protein science. It assists the identification of interactions among proteins. There is a lack of tools to extract PPI, visualize and classify the results.</p> <p>Results</p> <p>We developed a PPI search system, termed PPLook, which automatically extracts and visualizes protein-protein interaction (PPI) from text. Given a query protein name, PPLook can search a dataset for other proteins interacting with it by using a keywords dictionary pattern-matching algorithm, and display the topological parameters, such as the number of nodes, edges, and connected components. The visualization component of PPLook enables us to view the interaction relationship among the proteins in a three-dimensional space based on the OpenGL graphics interface technology. PPLook can also provide the functions of selecting protein semantic class, counting the number of semantic class proteins which interact with query protein, counting the literature number of articles appearing the interaction relationship about the query protein. Moreover, PPLook provides heterogeneous search and a user-friendly graphical interface.</p> <p>Conclusions</p> <p>PPLook is an effective tool for biologists and biosystem developers who need to access PPI information from the literature. PPLook is freely available for non-commercial users at <url>http://meta.usc.edu/softs/PPLook</url>.</p

Using Unsupervised Patterns to Extract Gene Regulation Relationships for Network Construction

BACKGROUND: The gene expression is usually described in the literature as a transcription factor X that regulates the target gene Y. Previously, some studies discovered gene regulations by using information from the biomedical literature and most of them require effort of human annotators to build the training dataset. Moreover, the large amount of textual knowledge recorded in the biomedical literature grows very rapidly, and the creation of manual patterns from literatures becomes more difficult. There is an increasing need to automate the process of establishing patterns. METHODOLOGY/PRINCIPAL FINDINGS: In this article, we describe an unsupervised pattern generation method called AutoPat. It is a gene expression mining system that can generate unsupervised patterns automatically from a given set of seed patterns. The high scalability and low maintenance cost of the unsupervised patterns could help our system to extract gene expression from PubMed abstracts more precisely and effectively. CONCLUSIONS/SIGNIFICANCE: Experiments on several regulators show reasonable precision and recall rates which validate AutoPat's practical applicability. The conducted regulation networks could also be built precisely and effectively. The system in this study is available at http://ikmbio.csie.ncku.edu.tw/AutoPat/

An Improved, Bias-Reduced Probabilistic Functional Gene Network of Baker's Yeast, Saccharomyces cerevisiae

Background: Probabilistic functional gene networks are powerful theoretical frameworks for integrating heterogeneous functional genomics and proteomics data into objective models of cellular systems. Such networks provide syntheses of millions of discrete experimental observations, spanning DNA microarray experiments, physical protein interactions, genetic interactions, and comparative genomics; the resulting networks can then be easily applied to generate testable hypotheses regarding specific gene functions and associations. Methodology/Principal Findings: We report a significantly improved version (v. 2) of a probabilistic functional gene network [1] of the baker's yeast, Saccharomyces cerevisiae. We describe our optimization methods and illustrate their effects in three major areas: the reduction of functional bias in network training reference sets, the application of a probabilistic model for calculating confidences in pair-wise protein physical or genetic interactions, and the introduction of simple thresholds that eliminate many false positive mRNA co-expression relationships. Using the network, we predict and experimentally verify the function of the yeast RNA binding protein Puf6 in 60S ribosomal subunit biogenesis. Conclusions/Significance: YeastNet v. 2, constructed using these optimizations together with additional data, shows significant reduction in bias and improvements in precision and recall, in total covering 102,803 linkages among 5,483 yeast proteins (95% of the validated proteome). YeastNet is available from http://www.yeastnet.org.This work was supported by grants from the N.S.F. (IIS-0325116, EIA-0219061), N.I.H. (GM06779-01,GM076536-01), Welch (F-1515), and a Packard Fellowship (EMM). These agencies were not involved in the design and conduct of the study, in the collection, analysis, and interpretation of the data, or in the preparation, review, or approval of the manuscript.Cellular and Molecular Biolog

Biogeographical Survey Identifies Consistent Alternative Physiological Optima and a Minor Role for Environmental Drivers in Maintaining a Polymorphism

The contribution of adaptive mechanisms in maintaining genetic polymorphisms is still debated in many systems. To understand the contribution of selective factors in maintaining polymorphism, we investigated large-scale (>1000 km) geographic variation in morph frequencies and fitness-related physiological traits in the damselfly Nehalennia irene. As fitness-related physiological traits, we investigated investment in immune function (phenoloxidase activity), energy storage and fecundity (abdomen protein and lipid content), and flight muscles (thorax protein content). In the first part of the study, our aim was to identify selective agents maintaining the large-scale spatial variation in morph frequencies. Morph frequencies varied considerably among populations, but, in contrast to expectation, in a geographically unstructured way. Furthermore, frequencies co-varied only weakly with the numerous investigated ecological parameters. This suggests that spatial frequency patterns are driven by stochastic processes, or alternatively, are consequence of highly variable and currently unidentified ecological conditions. In line with this, the investigated ecological parameters did not affect the fitness-related physiological traits differently in both morphs. In the second part of the study, we aimed at identifying trade-offs between fitness-related physiological traits that may contribute to the local maintenance of both colour morphs by defining alternative phenotypic optima, and test the spatial consistency of such trade-off patterns. The female morph with higher levels of phenoloxidase activity had a lower thorax protein content, and vice versa, suggesting a trade-off between investments in immune function and in flight muscles. This physiological trade-off was consistent across the geographical scale studied and supports widespread correlational selection, possibly driven by male harassment, favouring alternative trait combinations in both female morphs

Genetics and evidence for balancing selection of a sex-linked colour polymorphism in a songbird

Colour polymorphisms play a key role in sexual selection and speciation, yet the mechanisms that generate and maintain them are not fully understood. Here, we use genomic and transcriptomic tools to identify the precise genetic architecture and evolutionary history of a sex-linked colour polymorphism in the Gouldian finch Erythrura gouldiae that is also accompanied by remarkable differences in behaviour and physiology. We find that differences in colour are associated with an ~72-kbp region of the Z chromosome in a putative regulatory region for follistatin, an antagonist of the TGF-β superfamily genes. The region is highly differentiated between morphs, unlike the rest of the genome, yet we find no evidence that an inversion is involved in maintaining the distinct haplotypes. Coalescent simulations confirm that there is elevated nucleotide diversity and an excess of intermediate frequency alleles at this locus. We conclude that this pleiotropic colour polymorphism is most probably maintained by balancing selection

The transcriptomic basis of oviposition behaviour in the parasitoid wasp Nasonia vitripennis

Linking behavioural phenotypes to their underlying genotypes is crucial for uncovering the mechanisms that underpin behaviour and for understanding the origins and maintenance of genetic variation in behaviour. Recently, interest has begun to focus on the transcriptome as a route for identifying genes and gene pathways associated with behaviour. For many behavioural traits studied at the phenotypic level, we have little or no idea of where to start searching for "candidate" genes: the transcriptome provides such a starting point. Here we consider transcriptomic changes associated with oviposition in the parasitoid wasp Nasonia vitripennis. Oviposition is a key behaviour for parasitoids, as females are faced with a variety of decisions that will impact offspring fitness. These include choosing between hosts of differing quality, as well as making decisions regarding clutch size and offspring sex ratio. We compared the whole-body transcriptomes of resting or ovipositing female Nasonia using a "DeepSAGE" gene expression approach on the Illumina sequencing platform. We identified 332 tags that were significantly differentially expressed between the two treatments, with 77% of the changes associated with greater expression in resting females. Oviposition therefore appears to focus gene expression away from a number of physiological processes, with gene ontologies suggesting that aspects of metabolism may be down-regulated during egg-laying. Nine of the most abundant differentially expressed tags showed greater expression in ovipositing females though, including the genes purity-of-essence (associated with behavioural phenotypes in Drosophila) and glucose dehydrogenase (GLD). The GLD protein has been implicated in sperm storage and release in Drosophila and so provides a possible candidate for the control of sex allocation by female Nasonia during oviposition. Oviposition in Nasonia therefore clearly modifies the transcriptome, providing a starting point for the genetic dissection of oviposition.Publisher PDFPeer reviewe