UNLABELLED: Transcript Structure and Domain Display (TSDD) is a publicly available, web-based program that provides publication quality images of transcript structures and domains. TSDD is capable of producing transcript structures from GFF/GFF3 and BED files. Alternatively, the GFF files of several model organisms have been pre-loaded so that users only needs to enter the locus IDs of the transcripts to be displayed. Visualization of transcripts provides many benefits to researchers, ranging from evolutionary analysis of DNA-binding domains to predictive function modeling. AVAILABILITY AND IMPLEMENTATION: TSDD is freely available for non-commercial users at http://shenlab.sols.unlv.edu/shenlab/software/TSD/transcript_display.html CONTACT: : [email protected].

BACKGROUND: Regulation of gene expression at the level of transcription is a major control point in many biological processes. Transcription factors (TFs) can activate and/or repress the transcriptional rate of target genes and vascular plant genomes devote approximately 7% of their coding capacity to TFs. Global analysis of TFs has only been performed for three complete higher plant genomes - Arabidopsis (Arabidopsis thaliana), poplar (Populus trichocarpa) and rice (Oryza sativa). Presently, no large-scale analysis of TFs has been made from a member of the Solanaceae, one of the most important families of vascular plants. To fill this void, we have analysed tobacco (Nicotiana tabacum) TFs using a dataset of 1,159,022 gene-space sequence reads (GSRs) obtained by methylation filtering of the tobacco genome. An analytical pipeline was developed to isolate TF sequences from the GSR data set. This involved multiple (typically 10-15) independent searches with different versions of the TF family-defining domain(s) (normally the DNA-binding domain) followed by assembly into contigs and verification. Our analysis revealed that tobacco contains a minimum of 2,513 TFs representing all of the 64 well-characterised plant TF families. The number of TFs in tobacco is higher than previously reported for Arabidopsis and rice. RESULTS: TOBFAC: the database of tobacco transcription factors, is an integrative database that provides a portal to sequence and phylogeny data for the identified TFs, together with a large quantity of other data concerning TFs in tobacco. The database contains an individual page dedicated to each of the 64 TF families. These contain background information, domain architecture via Pfam links, a list of all sequences and an assessment of the minimum number of TFs in this family in tobacco. Downloadable phylogenetic trees of the major families are provided along with detailed information on the bioinformatic pipeline that was used to find all family members. TOBFAC also contains EST data, a list of published tobacco TFs and a list of papers concerning tobacco TFs. The sequences and annotation data are stored in relational tables using a PostgrelSQL relational database management system. The data processing and analysis pipelines used the Perl programming language. The web interface was implemented in JavaScript and Perl CGI running on an Apache web server. The computationally intensive data processing and analysis pipelines were run on an Apple XServe cluster with more than 20 nodes. CONCLUSION: TOBFAC is an expandable knowledgebase of tobacco TFs with data currently available for over 2,513 TFs from 64 gene families. TOBFAC integrates available sequence information, phylogenetic analysis, and EST data with published reports on tobacco TF function. The database provides a major resource for the study of gene expression in tobacco and the Solanaceae and helps to fill a current gap in studies of TF families across the plant kingdom. TOBFAC is publicly accessible at http://compsysbio.achs.virginia.edu/tobfac/.

BACKGROUND: Cowpea [Vigna unguiculata (L.) Walp.] is one of the most important food and forage legumes in the semi-arid tropics because of its ability to tolerate drought and grow on poor soils. It is cultivated mostly by poor farmers in developing countries, with 80% of production taking place in the dry savannah of tropical West and Central Africa. Cowpea is largely an underexploited crop with relatively little genomic information available for use in applied plant breeding. The goal of the Cowpea Genomics Initiative (CGI), funded by the Kirkhouse Trust, a UK-based charitable organization, is to leverage modern molecular genetic tools for gene discovery and cowpea improvement. One aspect of the initiative is the sequencing of the gene-rich region of the cowpea genome (termed the genespace) recovered using methylation filtration technology and providing annotation and analysis of the sequence data. DESCRIPTION: CGKB, Cowpea Genespace/Genomics Knowledge Base, is an annotation knowledge base developed under the CGI. The database is based on information derived from 298,848 cowpea genespace sequences (GSS) isolated by methylation filtering of genomic DNA. The CGKB consists of three knowledge bases: GSS annotation and comparative genomics knowledge base, GSS enzyme and metabolic pathway knowledge base, and GSS simple sequence repeats (SSRs) knowledge base for molecular marker discovery. A homology-based approach was applied for annotations of the GSS, mainly using BLASTX against four public FASTA formatted protein databases (NCBI GenBank Proteins, UniProtKB-Swiss-Prot, UniprotKB-PIR (Protein Information Resource), and UniProtKB-TrEMBL). Comparative genome analysis was done by BLASTX searches of the cowpea GSS against four plant proteomes from Arabidopsis thaliana, Oryza sativa, Medicago truncatula, and Populus trichocarpa. The possible exons and introns on each cowpea GSS were predicted using the HMM-based Genscan gene predication program and the potential domains on annotated GSS were analyzed using the HMMER package against the Pfam database. The annotated GSS were also assigned with Gene Ontology annotation terms and integrated with 228 curated plant metabolic pathways from the Arabidopsis Information Resource (TAIR) knowledge base. The UniProtKB-Swiss-Prot ENZYME database was used to assign putative enzymatic function to each GSS. Each GSS was also analyzed with the Tandem Repeat Finder (TRF) program in order to identify potential SSRs for molecular marker discovery. The raw sequence data, processed annotation, and SSR results were stored in relational tables designed in key-value pair fashion using a PostgreSQL relational database management system. The biological knowledge derived from the sequence data and processed results are represented as views or materialized views in the relational database management system. All materialized views are indexed for quick data access and retrieval. Data processing and analysis pipelines were implemented using the Perl programming language. The web interface was implemented in JavaScript and Perl CGI running on an Apache web server. The CPU intensive data processing and analysis pipelines were run on a computer cluster of more than 30 dual-processor Apple XServes. A job management system called Vela was created as a robust way to submit large numbers of jobs to the Portable Batch System (PBS). CONCLUSION: CGKB is an integrated and annotated resource for cowpea GSS with features of homology-based and HMM-based annotations, enzyme and pathway annotations, GO term annotation, toolkits, and a large number of other facilities to perform complex queries. The cowpea GSS, chloroplast sequences, mitochondrial sequences, retroelements, and SSR sequences are available as FASTA formatted files and downloadable at CGKB. This database and web interface are publicly accessible at http://cowpeagenomics.med.virginia.edu/CGKB/.