Improving the specificity of high-throughput ortholog prediction
| Autor: | Fiona M. Roche, Fiona S. L. Brinkman, Yvonne Y. Li, Benjamin G. S. Horsman, Debra L. Fulton, Matthew R. Laird |
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| Jazyk: | angličtina |
| Rok vydání: | 2006 |
| Předmět: |
animal structures
Molecular Sequence Data Computational biology Biology lcsh:Computer applications to medicine. Medical informatics Biochemistry Genome Sensitivity and Specificity Conserved sequence Evolution Molecular 03 medical and health sciences Structural Biology Phylogenetics Sequence Homology Nucleic Acid Gene duplication Molecular Biology Gene lcsh:QH301-705.5 Conserved Sequence 030304 developmental biology Genetics Comparative genomics 0303 health sciences Phylogenetic tree Base Sequence Applied Mathematics Methodology Article 030302 biochemistry & molecular biology Chromosome Mapping Genetic Variation Genome project Sequence Analysis DNA Computer Science Applications lcsh:Biology (General) lcsh:R858-859.7 Sequence Alignment Algorithms |
| Zdroj: | BMC Bioinformatics BMC Bioinformatics, Vol 7, Iss 1, p 270 (2006) |
| DOI: | 10.14288/1.0215896 |
| Popis: | Background Orthologs (genes that have diverged after a speciation event) tend to have similar function, and so their prediction has become an important component of comparative genomics and genome annotation. The gold standard phylogenetic analysis approach of comparing available organismal phylogeny to gene phylogeny is not easily automated for genome-wide analysis; therefore, ortholog prediction for large genome-scale datasets is typically performed using a reciprocal-best-BLAST-hits (RBH) approach. One problem with RBH is that it will incorrectly predict a paralog as an ortholog when incomplete genome sequences or gene loss is involved. In addition, there is an increasing interest in identifying orthologs most likely to have retained similar function. Results To address these issues, we present here a high-throughput computational method named Ortholuge that further evaluates previously predicted orthologs (including those predicted using an RBH-based approach) – identifying which orthologs most closely reflect species divergence and may more likely have similar function. Ortholuge analyzes phylogenetic distance ratios involving two comparison species and an outgroup species, noting cases where relative gene divergence is atypical. It also identifies some cases of gene duplication after species divergence. Through simulations of incomplete genome data/gene loss, we show that the vast majority of genes falsely predicted as orthologs by an RBH-based method can be identified. Ortholuge was then used to estimate the number of false-positives (predominantly paralogs) in selected RBH-predicted ortholog datasets, identifying approximately 10% paralogs in a eukaryotic data set (mouse-rat comparison) and 5% in a bacterial data set (Pseudomonas putida – Pseudomonas syringae species comparison). Higher quality (more precise) datasets of orthologs, which we term "ssd-orthologs" (s upporting-s pecies-d ivergence-orthologs), were also constructed. These datasets, as well as Ortholuge software that may be used to characterize other species' datasets, are available at http://www.pathogenomics.ca/ortholuge/ (software under GNU General Public License). Conclusion The Ortholuge method reported here appears to significantly improve the specificity (precision) of high-throughput ortholog prediction for both bacterial and eukaryotic species. This method, and its associated software, will aid those performing various comparative genomics-based analyses, such as the prediction of conserved regulatory elements upstream of orthologous genes. |
| Databáze: | OpenAIRE |
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