Phage_Finder: Automated identification and classification of prophage regions in complete bacterial genome sequences

Phage_Finder, a heuristic computer program, was created to identify prophage regions in completed bacterial genomes. Using a test dataset of 42 bacterial genomes whose prophages have been manually identified, Phage_Finder found 91% of the regions, resulting in 7% false positive and 9% false negative prophages. A search of 302 complete bacterial genomes predicted 403 putative prophage regions, accounting for 2.7% of the total bacterial DNA. Analysis of the 285 putative attachment sites revealed tRNAs are targets for integration slightly more frequently (33%) than intergenic (31%) or intragenic (28%) regions, while tmRNAs were targeted in 8% of the regions. The most popular tRNA targets were Arg, Leu, Ser and Thr. Mapping of the insertion point on a consensus tRNA molecule revealed novel insertion points on the 5′ side of the D loop, the 3′ side of the anticodon loop and the anticodon. A novel method of constructing phylogenetic trees of phages and prophages was developed based on the mean of the BLAST score ratio (BSR) of the phage/prophage proteomes. This method verified many known bacteriophage groups, making this a useful tool for predicting the relationships of prophages from bacterial genomes

A legume genomics resource: The Chickpea Root Expressed Sequence Tag Database

Chickpea, a lesser-studied grain legume, is being investigated due to its taxonomic proximity with the model legume genome Medicago truncatula and its ability to endure and grow in relatively low soil water contents making it a model legume crop for the study of agronomic response to drought stress. Public databases currently contain very few sequences from chickpea associated with expression in root tissues. However, root traits are likely to be one of the most important components of drought tolerance in chickpea. Thus, we have generated a set of over 2800 chickpea expressed sequence tags (ESTs) from a library constructed after subtractive suppressive hybridization (SSH) of root tissue from two closely related chickpea genotypes possessing different sources of drought avoidance and tolerance (ICC4958 and Annigeri respectively). This database provides researchers in legume genomics with a major new resource for data mining associated with root traits and drought tolerance. This report describes the development and utilization of the database and provides the tools we have developed to facilitate the bioinformatics pipeline used for analysis of the ESTs in this database. We also discuss applications that have already been achieved using this resourc

A legume genomics resource: The Chickpea Root Expressed Sequence Tag Database

Chickpea, a lesser-studied grain legume, is being investigated due to its taxonomic proximity with the model legume genome Medicago truncatula and its ability to endure and grow in relatively low soil water contents making it a model legume crop for the study of agronomic response to drought stress. Public databases currently contain very few sequences from chickpea associated with expression in root tissues. However, root traits are likely to be one of the most important components of drought tolerance in chickpea. Thus, we have generated a set of over 2800 chickpea expressed sequence tags (ESTs) from a library constructed after subtractive suppressive hybridization (SSH) of root tissue from two closely related chickpea genotypes possessing different sources of drought avoidance and tolerance (ICC4958 and Annigeri respectively). This database provides researchers in legume genomics with a major new resource for data mining associated with root traits and drought tolerance. This report describes the development and utilization of the database and provides the tools we have developed to facilitate the bioinformatics pipeline used for analysis of the ESTs in this database. We also discuss applications that have already been achieved using this resource