FORMIDABEL: The Belgian Ants Database

FORMIDABEL is a database of Belgian Ants containing more than 27.000 occurrence records. These records originate from collections, field sampling and literature. The database gives information on 76 native and 9 introduced ant species found in Belgium. The collection records originated mainly from the ants collection in Royal Belgian Institute of Natural Sciences (RBINS), the ‘Gaspar’ Ants collection in Gembloux and the zoological collection of the University of Liège (ULG). The oldest occurrences date back from May 1866, the most recent refer to August 2012. FORMIDABEL is a work in progress and the database is updated twice a year.The latest version of the dataset is publicly and freely accessible through this url: http://ipt.biodiversity.be/resource.do?r=formidabel. The dataset is also retrievable via the GBIF data portal through this link: http://data.gbif.org/datasets/resource/14697A dedicated geo-portal, developed by the Belgian Biodiversity Platform is accessible at: http://www.formicidae-atlas.bePurpose: FORMIDABEL is a joint cooperation of the Flemish ants working group “Polyergus” (http://formicidae.be) and the Wallonian ants working group “FourmisWalBru” (http://fourmiswalbru.be). The original database was created in 2002 in the context of the preliminary red data book of Flemish Ants (Dekoninck et al. 2003). Later, in 2005, data from the Southern part of Belgium; Wallonia and Brussels were added. In 2012 this dataset was again updated for the creation of the first Belgian Ants Atlas (Figure 1) (Dekoninck et al. 2012). The main purpose of this atlas was to generate maps for all outdoor-living ant species in Belgium using an overlay of the standard Belgian ecoregions. By using this overlay for most species, we can discern a clear and often restricted distribution pattern in Belgium, mainly based on vegetation and soil types.Open in a separate windowFigure 1.www.formicidae-atlas.be     

WGDB: Wood Gene Database with search interface

Wood quality can be defined in terms of particular end use with the involvement of several traits. Over the last fifteen years researchers have assessed the wood quality traits in forest trees. The wood quality was categorized as: cell wall biochemical traits, fibre properties include the microfibril angle, density and stiffness in loblolly pine [1]. The user friendly and an open-access database has been developed named Wood Gene Database (WGDB) for describing the wood genes along the information of protein and published research articles. It contains 720 wood genes from species namely Pinus, Deodar, fast growing trees namely Poplar, Eucalyptus. WGDB designed to encompass the majority of publicly accessible genes codes for cellulose, hemicellulose and lignin in tree species which are responsive to wood formation and quality. It is an interactive platform for collecting, managing and searching the specific wood genes; it also enables the data mining relate to the genomic information specifically in Arabidopsis thaliana, Populus trichocarpa, Eucalyptus grandis, Pinus taeda, Pinus radiata, Cedrus deodara, Cedrus atlantica. For user convenience, this database is cross linked with public databases namely NCBI, EMBL & Dendrome with the search engine Google for making it more informative and provides bioinformatics tools named BLAST,COBALT.

Availability

The database is freely available on www.wgdb.in     

Cry‐Bt identifier: A biological database for PCR detection of Cry genes present in transgenic plants

We describe the development of a user friendly tool that would assist in the retrieval of information relating to Cry genes in transgenic crops. The tool also helps in detection of transformed Cry genes from Bacillus thuringiensis present in transgenic plants by providing suitable designed primers for PCR identification of these genes. The tool designed based on relational database model enables easy retrieval of information from the database with simple user queries. The tool also enables users to access related information about Cry genes present in various databases by interacting with different sources (nucleotide sequences, protein sequence, sequence comparison tools, published literature, conserved domains, evolutionary and structural data).

Availability

http://insilicogenomics.in/Cry-btIdentifier/welcome.html     

MAPS Database: Medicinal plant Activities,Phytochemical and Structural Database

Drug development from natural sources is an important and fast developing area. Natural sources (plants) have been used to cure a range of diseases for Thousands of years. Different online medicinal plant databases provide information about classifications, activities, phytochemicals and structure of phytochemicals in different formats. These databases do not cover all aspects of medicinal plants. MAPS (Medicinal plant Activities, Phytochemicals & structural database) has been constructed with uniqueness that it combines all information in one web resource and additionally provides test targets on which particular plant found to be effective with reference to the original paper as well. MAPS database is user friendly information resource, including the data of > 500 medicinal plants. This database includes phytochemical constituents, their structure in mol format, different activities possessed by the medicinal plant with the targets reported in literature.

Availability

http://www.mapsdatabase.com     

Enrichment Map: A Network-Based Method for Gene-Set Enrichment Visualization and Interpretation

Background

Gene-set enrichment analysis is a useful technique to help functionally characterize large gene lists, such as the results of gene expression experiments. This technique finds functionally coherent gene-sets, such as pathways, that are statistically over-represented in a given gene list. Ideally, the number of resulting sets is smaller than the number of genes in the list, thus simplifying interpretation. However, the increasing number and redundancy of gene-sets used by many current enrichment analysis software works against this ideal.

Principal Findings

To overcome gene-set redundancy and help in the interpretation of large gene lists, we developed “Enrichment Map”, a network-based visualization method for gene-set enrichment results. Gene-sets are organized in a network, where each set is a node and edges represent gene overlap between sets. Automated network layout groups related gene-sets into network clusters, enabling the user to quickly identify the major enriched functional themes and more easily interpret the enrichment results.

Conclusions

Enrichment Map is a significant advance in the interpretation of enrichment analysis. Any research project that generates a list of genes can take advantage of this visualization framework. Enrichment Map is implemented as a freely available and user friendly plug-in for the Cytoscape network visualization software (http://baderlab.org/Software/EnrichmentMap/).     

GeneComps and ChemComps: a new CTD metric to identify genes and chemicals with shared toxicogenomic profiles

The Comparative Toxicogenomics Database is a public resource that promotes understanding about the effects of environmental chemicals on human health. Currently, CTD describes over 184,000 molecular interactions for more than 5,100 chemicals and 16,300 genes/proteins. We have leveraged this dataset of chemical-gene relationships to compute similarity indices following the statistical method of the Jaccard index. These scores are used to produce lists of comparable genes (“GeneComps”) or chemicals (“ChemComps”) based on shared toxicogenomic profiles. GeneComps and ChemComps are now provided for every curated gene and chemical in CTD. ChemComps are particularly significant because they provide a way to group chemicals based upon their biological effects, instead of their physical or structural properties. These metrics provide a novel way to view and classify genes and chemicals and will help advance testable hypotheses about environmental chemical-genedisease networks.

Availability

CTD is freely available at http://ctd.mdibl.org/     

Mammalian Mitochondrial ncRNA Database

Mammalian Mitochondrial ncRNA is a web-based database, which provides specific information on non-coding RNA in mammals. This database includes easy searching, comparing with BLAST and retrieving information on predicted structure and its function about mammalian ncRNAs.

Availability

The database is available for free at http://www.iitm.ac.in/bioinfo/mmndb/     

An Online Database for Informing Ecological Network Models: http://kelpforest.ucsc.edu

Ecological network models and analyses are recognized as valuable tools for understanding the dynamics and resiliency of ecosystems, and for informing ecosystem-based approaches to management. However, few databases exist that can provide the life history, demographic and species interaction information necessary to parameterize ecological network models. Faced with the difficulty of synthesizing the information required to construct models for kelp forest ecosystems along the West Coast of North America, we developed an online database (http://kelpforest.ucsc.edu/) to facilitate the collation and dissemination of such information. Many of the database''s attributes are novel yet the structure is applicable and adaptable to other ecosystem modeling efforts. Information for each taxonomic unit includes stage-specific life history, demography, and body-size allometries. Species interactions include trophic, competitive, facilitative, and parasitic forms. Each data entry is temporally and spatially explicit. The online data entry interface allows researchers anywhere to contribute and access information. Quality control is facilitated by attributing each entry to unique contributor identities and source citations. The database has proven useful as an archive of species and ecosystem-specific information in the development of several ecological network models, for informing management actions, and for education purposes (e.g., undergraduate and graduate training). To facilitate adaptation of the database by other researches for other ecosystems, the code and technical details on how to customize this database and apply it to other ecosystems are freely available and located at the following link (https://github.com/kelpforest-cameo/databaseui).     

The Role of eIF1 in Translation Initiation Codon Selection in Caenorhabditis elegans

The selection of a proper AUG start codon requires the base-pairing interactions between the codon on the mRNA and the anticodon of the initiator tRNA. This selection process occurs in a pre-initiation complex that includes multiple translation initiation factors and the small ribosomal subunit. To study how these initiation factors are involved in start codon recognition in multicellular organisms, we isolated mutants that allow the expression of a GFP reporter containing a non-AUG start codon. Here we describe the characterization of mutations in eif-1, which encodes the Caenorhabditis elegans translation initiation factor 1 (eIF1). Two mutations were identified, both of which are substitutions of amino acid residues that are identical in all eukaryotic eIF1 proteins. These residues are located in a structural region where the amino acid residues affected by the Saccharomyces cerevisiae eIF1 mutations are also localized. Both C. elegans mutations are dominant in conferring a non-AUG translation initiation phenotype and lead to growth arrest defects in homozygous animals. By assaying reporter constructs that have base changes at the AUG start codon, these mutants are found to allow expression from most reporters that carry single base changes within the AUG codon. This trend of non-AUG mediated initiation was also observed previously for C. elegans eIF2β mutants, indicating that these two factors play a similar role. These results support that eIF1 functions in ensuring the fidelity of AUG start codon recognition in a multicellular organism.TRANSLATION initiation is thought to be one of the most complex cellular processes in eukaryotes. It involves at least 12 translation initiation factors (eIFs) comprising over 30 polypeptides (Pestova et al. 2007). These factors bring together an initiator methionyl tRNA (Met-tRNAi), the small ribosomal subunit, and a mRNA to form a 48S initiation complex. An important role performed by this complex is to select an AUG codon to initiate translation of the mRNA. Since the first AUG at the 5′ end of most mRNAs is selected as the start site, it is believed that the initiation complex scans for an AUG start codon as it moves from the 5′-capped end of the mRNA toward the 3′ end, as proposed in the ribosomal scanning model (Kozak 1978; Kozak 1989). The recognition of the AUG start codon is mediated by the anticodon of the Met-tRNAi, and the matching base-pairing interactions between the codon of the mRNA and the anticodon determine the site of initiation (Cigan et al. 1988). These base-pairing interactions are essential, but are likely not the only components required for accurately selecting the correct AUG start codon. Numerous initiation factors along with base-pairing interactions have been shown to aid in the AUG recognition process (Pestova et al. 2007).Translation initiation factors involved in start codon selection fidelity were first identified through genetic studies performed in the yeast Saccharomyces cerevisiae. Mutant strains with a modified His4 gene that had an AUU instead of an AUG at the native start site were selected for the ability to survive on media lacking histidine (Donahue et al. 1988; Castilho-Valavicius et al. 1990). These mutants were found to be able to produce the His4 protein by using a downstream inframe UUG codon (the third codon within the His4 coding region) as the translation start site. Further analyses determined that non-AUG initiation occurred mostly from a UUG codon and not significantly from other codons (Huang et al. 1997). These mutants defined five genetic loci and were named sui1-sui5 (suppressor of initiation codon) on the basis of their ability to initiate translation at a non-AUG codon.The sui1 suppressors were found to have missense mutations in eIF1. These missense mutations showed semidominant or codominant properties in non-AUG translation initiation while deletion of the eIF1 gene led to lethality in yeast (Yoon and Donahue 1992). eIF1 is a highly conserved protein with a size of approximately 12 kDa that plays a vital role in multiple translation initiation steps. eIF1 is incorporated into a multifactor complex that includes eIF1A, eIF3, and eIF5 and stimulates the recruiting of the ternary complex (consisting of eIF2 · GTP and the charged Met-tRNAi) to the small ribosomal subunit to form the 43S pre-initiation complex (Singh et al. 2004). eIF1 acts synergistically with eIF1A to promote continuous ribosomal scanning for AUG codons by stabilizing an open conformation that allows mRNA to pass through the complex (Maag et al. 2005; Cheung et al. 2007; Passmore et al. 2007). It also mediates the assembly of the ribosomal initiation complex at the AUG start codon (Pestova et al. 1998). eIF1 dissociates from the complex upon recognition of the AUG codon and this dissociation is necessary to trigger a series of conformational changes leading to the translation elongation phase (Algire et al. 2005). Consistent with these roles, sui1 mutations reduce the affinity of eIF1 for the ribosome and cause premature release of eIF1 at non-AUG codons (Cheung et al. 2007). Other sui mutations support the involvement of four additional genes in translation initiation fidelity in yeast. Mutations have been isolated in the heterotrimeric eIF2 as SUI2 (α-subunit) (Cigan et al. 1989), SUI3 (β-subunit) (Donahue et al. 1988), and SUI4 (γ-subunit) (Huang et al. 1997), and a mutation in eIF5 corresponds to the SUI5 mutant (Huang et al. 1997).However, the genetic studies that identified these translation fidelity mutants were conducted only in yeast. It is not known if there are similar mechanisms regulating translation initiation fidelity in multicellular organisms. To address this question, we designed a genetic system to isolate C. elegans mutants that have reduced fidelity in AUG start codon selection (Zhang and Maduzia 2010). Mutants were selected on the basis of their ability to express a GFP reporter that contains a GUG codon in place of its native translation start site. Here we report the characterization of two mutants that have mutations in eIF1. Unlike yeast sui1 mutants, which preferred the UUG codon, these mutants are capable of using a subset of non-AUG codons for translation initiation. Our results are consistent with eIF1 playing a role in the fidelity of AUG codon selection, perhaps by discriminating base-pairing interactions between the codon and anticodon during start-site selection.     

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     

BGD: A Database of Bat Genomes

Bats account for ~20% of mammalian species, and are the only mammals with true powered flight. For the sake of their specialized phenotypic traits, many researches have been devoted to examine the evolution of bats. Until now, some whole genome sequences of bats have been assembled and annotated, however, a uniform resource for the annotated bat genomes is still unavailable. To make the extensive data associated with the bat genomes accessible to the general biological communities, we established a Bat Genome Database (BGD). BGD is an open-access, web-available portal that integrates available data of bat genomes and genes. It hosts data from six bat species, including two megabats and four microbats. Users can query the gene annotations using efficient searching engine, and it offers browsable tracks of bat genomes. Furthermore, an easy-to-use phylogenetic analysis tool was also provided to facilitate online phylogeny study of genes. To the best of our knowledge, BGD is the first database of bat genomes. It will extend our understanding of the bat evolution and be advantageous to the bat sequences analysis. BGD is freely available at: http://donglab.ecnu.edu.cn/databases/BatGenome/.     

ATGme: Open-source web application for rare codon identification and custom DNA sequence optimization

Background

Codon usage plays a crucial role when recombinant proteins are expressed in different organisms. This is especially the case if the codon usage frequency of the organism of origin and the target host organism differ significantly, for example when a human gene is expressed in E. coli. Therefore, to enable or enhance efficient gene expression it is of great importance to identify rare codons in any given DNA sequence and subsequently mutate these to codons which are more frequently used in the expression host.

Results

We describe an open-source web-based application, ATGme, which can in a first step identify rare and highly rare codons from most organisms, and secondly gives the user the possibility to optimize the sequence.

Conclusions

This application provides a simple user-friendly interface utilizing three optimization strategies: 1. one-click optimization, 2. bulk optimization (by codon-type), 3. individualized custom (codon-by-codon) optimization. ATGme is an open-source application which is freely available at: http://atgme.org     

杨树派间不同种的遗传密码子使用频率分析

遗传密码子的简并性特征造成了不同物种使用的密码子存在偏爱性。了解不同物种的密码子使用特点,可以为外源基因导入过程中的基因改造提供依据,从而实现外源基因的高效表达。杨树是世界上广泛栽培的重要造林树种之一,已经成为林木基因工程研究的模式植物。本研究采用高频密码子分析法,对美洲山杨P.tremuloides,毛白杨P.tomentosa,美洲黑杨P.deltoids和毛果杨P.trichocarpa 4种杨树的蛋白质编码基因序列(CDS)进行了分析,计算出了杨树同义密码子相对使用频率(RFSC),确定了4种杨树的高频率密码子,发现虽然不同种类的杨树密码子使用上有一些差别,但是偏爱密码子的差别却很小,共性的密码子占绝大多数。仅有Pro,Thr和Cys等少数几个氨基酸的偏爱密码子有差别。这种“共性”提示我们,用不同种的杨树中任何一种杨树的偏爱密码子所设计的外源基因在其他杨树中也可以使用。     

ASRDb: A comprehensive resource for archaeal stress response genes

An organism''s survival strategy under the constantly changing environment depends on its ability to sense and respond to changes in its environment. Archaea, being capable to grow under various extreme environmental conditions, provide valuable model for exploring how single-celled organisms respond to environmental stresses. However, no such approach has ever been made to make an integrated classification of various archaeal stress responses.Archaeal Stress Response Database (ASRDb) is a web accessible (http://121.241.218.70/ASRDb) database that represents the first online available resource providing a comprehensive overview of stress response genes of 66 archaeal genomes. This database currently contains almost 6000 stress specific genes of 66 archaeal genomes. All the stress specific genes are grouped into 17 different stress categories. A user-friendly interface has been designed to examine data using query tools. This database provides an efficient search engine for random and advanced database search operations. We have incorporated BLAST search options to the resulting sequences retrieved from database search operations. A site map page representing the schematic diagram will enable user to understand the logic behind the construction of the database. We have also provided a very rich and informative help page to make user familiar with the database. We sincerely believe that ASRDb will be of particular interest to the life science community and facilitates the biologists to unravel the role of stress specific genes in the adaptation of microorganisms under various extreme environmental conditions.