PANTHER version 6: protein sequence and function evolution data with expanded representation of biological pathways

PANTHER is a freely available, comprehensive software system for relating protein sequence evolution to the evolution of specific protein functions and biological roles. Since 2005, there have been three main improvements to PANTHER. First, the sequences used to create evolutionary trees are carefully selected to provide coverage of phylogenetic as well as functional information. Second, PANTHER is now a member of the InterPro Consortium, and the PANTHER hidden markov Models (HMMs) are distributed as part of InterProScan. Third, we have dramatically expanded the number of pathways associated with subfamilies in PANTHER. Pathways provide a detailed, structured representation of protein function in the context of biological reaction networks. PANTHER pathways were generated using the emerging Systems Biology Markup Language (SBML) standard using pathway network editing software called CellDesigner. The pathway collection currently contains ∼1500 reactions in 130 pathways, curated by expert biologists with authorship attribution. The curation environment is designed to be easy to use, and the number of pathways is growing steadily. Because the reaction participants are linked to subfamilies and corresponding HMMs, reactions can be inferred across numerous different organisms. The HMMs can be downloaded by FTP, and tools for analyzing data in the context of pathways and function ontologies are available at

WormBase 2012: more genomes, more data, new website

Since its release in 2000, WormBase (http://www.wormbase.org) has grown from a small resource focusing on a single species and serving a dedicated research community, to one now spanning 15 species essential to the broader biomedical and agricultural research fields. To enhance the rate of curation, we have automated the identification of key data in the scientific literature and use similar methodology for data extraction. To ease access to the data, we are collaborating with journals to link entities in research publications to their report pages at WormBase. To facilitate discovery, we have added new views of the data, integrated large-scale datasets and expanded descriptions of models for human disease. Finally, we have introduced a dramatic overhaul of the WormBase website for public beta testing. Designed to balance complexity and usability, the new site is species-agnostic, highly customizable, and interactive. Casual users and developers alike will be able to leverage the public RESTful application programming interface (API) to generate custom data mining solutions and extensions to the site. We report on the growth of our database and on our work in keeping pace with the growing demand for data, efforts to anticipate the requirements of users and new collaborations with the larger science community

Gene3D: merging structure and function for a Thousand genomes

Over the last 2 years the Gene3D resource has been significantly improved, and is now more accurate and with a much richer interactive display via the Gene3D website (http://gene3d.biochem.ucl.ac.uk/). Gene3D provides accurate structural domain family assignments for over 1100 genomes and nearly 10 000 000 proteins. A hidden Markov model library, constructed from the manually curated CATH structural domain hierarchy, is used to search UniProt, RefSeq and Ensembl protein sequences. The resulting matches are refined into simple multi-domain architectures using a recently developed in-house algorithm, DomainFinder 3 (available at: ftp://ftp.biochem.ucl.ac.uk/pub/gene3d_data/DomainFinder3/). The domain assignments are integrated with multiple external protein function descriptions (e.g. Gene Ontology and KEGG), structural annotations (e.g. coiled coils, disordered regions and sequence polymorphisms) and family resources (e.g. Pfam and eggNog) and displayed on the Gene3D website. The website allows users to view descriptions for both single proteins and genes and large protein sets, such as superfamilies or genomes. Subsets can then be selected for detailed investigation or associated functions and interactions can be used to expand explorations to new proteins. Gene3D also provides a set of services, including an interactive genome coverage graph visualizer, DAS annotation resources, sequence search facilities and SOAP services

PANTHER version 7: improved phylogenetic trees, orthologs and collaboration with the Gene Ontology Consortium

Protein Analysis THrough Evolutionary Relationships (PANTHER) is a comprehensive software system for inferring the functions of genes based on their evolutionary relationships. Phylogenetic trees of gene families form the basis for PANTHER and these trees are annotated with ontology terms describing the evolution of gene function from ancestral to modern day genes. One of the main applications of PANTHER is in accurate prediction of the functions of uncharacterized genes, based on their evolutionary relationships to genes with functions known from experiment. The PANTHER website, freely available at http://www.pantherdb.org, also includes software tools for analyzing genomic data relative to known and inferred gene functions. Since 2007, there have been several new developments to PANTHER: (i) improved phylogenetic trees, explicitly representing speciation and gene duplication events, (ii) identification of gene orthologs, including least diverged orthologs (best one-to-one pairs), (iii) coverage of more genomes (48 genomes, up to 87% of genes in each genome; see http://www.pantherdb.org/panther/summaryStats.jsp), (iv) improved support for alternative database identifiers for genes, proteins and microarray probes and (v) adoption of the SBGN standard for display of biological pathways. In addition, PANTHER trees are being annotated with gene function as part of the Gene Ontology Reference Genome project, resulting in an increasing number of curated functional annotations

TreeFam: 2008 Update

TreeFam (http://www.treefam.org) was developed to provide curated phylogenetic trees for all animal gene families, as well as orthologue and paralogue assignments. Release 4.0 of TreeFam contains curated trees for 1314 families and automatically generated trees for another 14 351 families. We have expanded TreeFam to include 25 fully sequenced animal genomes, as well as four genomes from plant and fungal outgroup species. We have also introduced more accurate approaches for automatically grouping genes into families, for building phylogenetic trees, and for inferring orthologues and paralogues. The user interface for viewing phylogenetic trees and family information has been improved. Furthermore, a new perl API lets users easily extract data from the TreeFam mysql database

InParanoid 7: new algorithms and tools for eukaryotic orthology analysis

The InParanoid project gathers proteomes of completely sequenced eukaryotic species plus Escherichia coli and calculates pairwise ortholog relationships among them. The new release 7.0 of the database has grown by an order of magnitude over the previous version and now includes 100 species and their collective 1.3 million proteins organized into 42.7 million pairwise ortholog groups. The InParanoid algorithm itself has been revised and is now both more specific and sensitive. Based on results from our recent benchmarking of low-complexity filters in homology assignment, a two-pass BLAST approach was developed that makes use of high-precision compositional score matrix adjustment, but avoids the alignment truncation that sometimes follows. We have also updated the InParanoid web site (http://InParanoid.sbc.su.se). Several features have been added, the response times have been improved and the site now sports a new, clearer look. As the number of ortholog databases has grown, it has become difficult to compare among these resources due to a lack of standardized source data and incompatible representations of ortholog relationships. To facilitate data exchange and comparisons among ortholog databases, we have developed and are making available two XML schemas: SeqXML for the input sequences and OrthoXML for the output ortholog clusters

Selective Killing of Cancer Cells by Ashwagandha Leaf Extract and Its Component Withanone Involves ROS Signaling

Ashwagandha is a popular Ayurvedic herb used in Indian traditional home medicine. It has been assigned a variety of health-promoting effects of which the mechanisms remain unknown. We previously reported the selective killing of cancer cells by leaf extract of Ashwagandha (i-Extract) and its purified component Withanone. In the present study, we investigated its mechanism by loss-of-function screening (abrogation of i-Extract induced cancer cell killing) of the cellular targets and gene pathways.Randomized ribozyme library was introduced into cancer cells prior to the treatment with i-Extract. Ribozymes were recovered from cells that survived the i-Extract treatment. Gene targets of the selected ribozymes (as predicted by database search) were analyzed by bioinformatics and pathway analyses. The targets were validated for their role in i-Extract induced selective killing of cancer cells by biochemical and molecular assays. Fifteen gene-targets were identified and were investigated for their role in specific cancer cell killing activity of i-Extract and its two major components (Withaferin A and Withanone) by undertaking the shRNA-mediated gene silencing approach. Bioinformatics on the selected gene-targets revealed the involvement of p53, apoptosis and insulin/IGF signaling pathways linked to the ROS signaling. We examined the involvement of ROS-signaling components (ROS levels, DNA damage, mitochondrial structure and membrane potential) and demonstrate that the selective killing of cancer cells is mediated by induction of oxidative stress.Ashwagandha leaf extract and Withanone cause selective killing of cancer cells by induction of ROS-signaling and hence are potential reagents that could be recruited for ROS-mediated cancer chemotherapy

Phytozome: a comparative platform for green plant genomics

The number of sequenced plant genomes and associated genomic resources is growing rapidly with the advent of both an increased focus on plant genomics from funding agencies, and the application of inexpensive next generation sequencing. To interact with this increasing body of data, we have developed Phytozome (http://www.phytozome.net), a comparative hub for plant genome and gene family data and analysis. Phytozome provides a view of the evolutionary history of every plant gene at the level of sequence, gene structure, gene family and genome organization, while at the same time providing access to the sequences and functional annotations of a growing number (currently 25) of complete plant genomes, including all the land plants and selected algae sequenced at the Joint Genome Institute, as well as selected species sequenced elsewhere. Through a comprehensive plant genome database and web portal, these data and analyses are available to the broader plant science research community, providing powerful comparative genomics tools that help to link model systems with other plants of economic and ecological importance

Differential Micro RNA Expression in PBMC from Multiple Sclerosis Patients

Differences in gene expression patterns have been documented not only in Multiple Sclerosis patients versus healthy controls but also in the relapse of the disease. Recently a new gene expression modulator has been identified: the microRNA or miRNA. The aim of this work is to analyze the possible role of miRNAs in multiple sclerosis, focusing on the relapse stage. We have analyzed the expression patterns of 364 miRNAs in PBMC obtained from multiple sclerosis patients in relapse status, in remission status and healthy controls. The expression patterns of the miRNAs with significantly different expression were validated in an independent set of samples. In order to determine the effect of the miRNAs, the expression of some predicted target genes of these were studied by qPCR. Gene interaction networks were constructed in order to obtain a co-expression and multivariate view of the experimental data. The data analysis and later validation reveal that two miRNAs (hsa-miR-18b and hsa-miR-599) may be relevant at the time of relapse and that another miRNA (hsa-miR-96) may be involved in remission. The genes targeted by hsa-miR-96 are involved in immunological pathways as Interleukin signaling and in other pathways as wnt signaling. This work highlights the importance of miRNA expression in the molecular mechanisms implicated in the disease. Moreover, the proposed involvement of these small molecules in multiple sclerosis opens up a new therapeutic approach to explore and highlight some candidate biomarker targets in MS