Dataset Information

An automated method for rapid identification of putative gene family members in plants.

ABSTRACT:

Background

Gene duplication events have played a significant role in genome evolution, particularly in plants. Exhaustive searches for all members of a known gene family as well as the identification of new gene families has become increasingly important. Subfunctionalization via changes in regulatory sequences following duplication (adaptive selection) appears to be a common mechanism of evolution in plants and can be accompanied by purifying selection on the coding region. Such negative selection can be detected by a bias toward synonymous over nonsynonymous substitutions. However, the process of identifying this bias requires many steps usually employing several different software programs. We have simplified the process and significantly shortened the time required by condensing many steps into a few scripts or programs to rapidly identify putative gene family members beginning with a single query sequence.

Results

In this report we 1) describe the software tools (SimESTs, PCAT, and SCAT) developed to automate the gene family identification, 2) demonstrate the validity of the method by correctly identifying 3 of 4 PAL gene family members from Arabidopsis using EST data alone, 3) identify 2 to 6 CAD gene family members from Glycine max (previously unidentified), and 4) identify 2 members of a putative Glycine max gene family previously unidentified in any plant species.

Conclusion

Gene families in plants, particularly that subset where purifying selection has occurred in the coding region, can be identified quickly and easily by integrating our software tools and commonly available contig assembly and ORF identification programs.

SUBMITTER: Frank RL

PROVIDER: S-EPMC1683565 | biostudies-literature | 2006 Sep

REPOSITORIES: biostudies-literature

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Publications

An automated method for rapid identification of putative gene family members in plants.

Frank Ronald L RL Mane Ajay A Ercal Fikret F

BMC bioinformatics 20060906

<h4>Background</h4>Gene duplication events have played a significant role in genome evolution, particularly in plants. Exhaustive searches for all members of a known gene family as well as the identification of new gene families has become increasingly important. Subfunctionalization via changes in regulatory sequences following duplication (adaptive selection) appears to be a common mechanism of evolution in plants and can be accompanied by purifying selection on the coding region. Such negativ ...[more]

PMID: 17118140

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Project description:BackgroundFirst pass methods based on BLAST match are commonly used as an initial step to separate the different phylogenetic histories of genes in microbial genomes, and target putative horizontal gene transfer (HGT) events. This will continue to be necessary given the rapid growth of genomic data and the technical difficulties in conducting large-scale explicit phylogenetic analyses. However, these methods often produce misleading results due to their inability to resolve indirect phylogenetic links and their vulnerability to stochastic events.ResultsA new computational method of rapid, exhaustive and genome-wide detection of HGT was developed, featuring the systematic analysis of BLAST hit distribution patterns in the context of a priori defined hierarchical evolutionary categories. Genes that fall beyond a series of statistically determined thresholds are identified as not adhering to the typical vertical history of the organisms in question, but instead having a putative horizontal origin. Tests on simulated genomic data suggest that this approach effectively targets atypically distributed genes that are highly likely to be HGT-derived, and exhibits robust performance compared to conventional BLAST-based approaches. This method was further tested on real genomic datasets, including Rickettsia genomes, and was compared to previous studies. Results show consistency with currently employed categories of HGT prediction methods. In-depth analysis of both simulated and real genomic data suggests that the method is notably insensitive to stochastic events such as gene loss, rate variation and database error, which are common challenges to the current methodology. An automated pipeline was created to implement this approach and was made publicly available at: https://github.com/DittmarLab/HGTector. The program is versatile, easily deployed, has a low requirement for computational resources.ConclusionsHGTector is an effective tool for initial or standalone large-scale discovery of candidate HGT-derived genes.

Project description:BackgroundActinobacillus suis disease has been reported in a wide range of vertebrate species, but is most commonly found in swine. A. suis is a commensal of the tonsils of the soft palate of swine, but in the presence of unknown stimuli it can invade the bloodstream, causing septicaemia and sequelae such as meningitis, arthritis, and death. It is genotypically and phenotypically similar to A. pleuropneumoniae, the causative agent of pleuropneumonia, and to other members of the family Pasteurellaceae that colonise tonsils. At present, very little is known about the genes involved in attachment, colonisation, and invasion by A. suis (or related members of the tonsil microbiota).ResultsBioinformatic analyses of the A. suis H91-0380 genome were done using BASys and blastx in GenBank. Forty-seven putative adhesin-associated genes predicted to encode 24 putative adhesins were discovered. Among these are 6 autotransporters, 25 fimbriae-associated genes (encoding 3 adhesins), 12 outer membrane proteins, and 4 additional genes (encoding 3 adhesins). With the exception of 2 autotransporter-encoding genes (aidA and ycgV), both with described roles in virulence in other species, all of the putative adhesin-associated genes had homologues in A. pleuropneumoniae. However, the majority of the closest homologues of the A. suis adhesins are found in A. ureae and A. capsulatus--species not known to infect swine, but both of which can cause systemic infections.ConclusionsA. suis and A. pleuropneumoniae share many of the same putative adhesins, suggesting that the different diseases, tissue tropism, and host range of these pathogens are due to subtle genetic differences, or perhaps differential expression of virulence factors during infection. However, many of the putative adhesins of A. suis share even greater homology with those of other pathogens within the family Pasteurellaceae. Similar to A. suis, these pathogens (A. capsulatus and A. ureae) cause systemic infections and it is tempting to speculate that they employ similar strategies to invade the host, but more work is needed before that assertion can be made. This work begins to examine adhesin-associated factors that allow some members of the family Pasteurellaceae to invade the bloodstream while others cause a more localised infection.

Dataset Information

An automated method for rapid identification of putative gene family members in plants.

Background

Results

Conclusion

Publications

An automated method for rapid identification of putative gene family members in plants.

Similar Datasets

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