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An approach of orthology detection from homologous sequences under minimum evolution.

Kim KM, Sung S, Caetano-Anollés G, Han JY, Kim H - Nucleic Acids Res. (2008)

Bottom Line: For this reason, several methods based on evolutionary distance, phylogeny and BLAST have tried to detect orthologs with more precision.Calculation of evolutionary cost requires the reconstruction of a neighbor-joining (NJ) tree, but calculations are unaffected by the topology of any given NJ tree.Sensitivity and specificity estimates indicate that the concept of minimum evolution could be valuable for the detection of orthologs.

View Article: PubMed Central - PubMed

Affiliation: Department of Agricultural Biotechnology, Laboratory of Bioinformatics and Population Genetics, Seoul National University, Seoul 151-742, Korea.

ABSTRACT
In the field of phylogenetics and comparative genomics, it is important to establish orthologous relationships when comparing homologous sequences. Due to the slight sequence dissimilarity between orthologs and paralogs, it is prone to regarding paralogs as orthologs. For this reason, several methods based on evolutionary distance, phylogeny and BLAST have tried to detect orthologs with more precision. Depending on their algorithmic implementations, each of these methods sometimes has increased false negative or false positive rates. Here, we developed a novel algorithm for orthology detection that uses a distance method based on the phylogenetic criterion of minimum evolution. Our algorithm assumes that sets of sequences exhibiting orthologous relationships are evolutionarily less costly than sets that include one or more paralogous relationships. Calculation of evolutionary cost requires the reconstruction of a neighbor-joining (NJ) tree, but calculations are unaffected by the topology of any given NJ tree. Unlike tree reconciliation, our algorithm appears free from the problem of incorrect topologies of species and gene trees. The reliability of the algorithm was tested in a comparative analysis with two other orthology detection methods using 95 manually curated KOG datasets and 21 experimentally verified EXProt datasets. Sensitivity and specificity estimates indicate that the concept of minimum evolution could be valuable for the detection of orthologs.

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Tree reconciliation versus Mestortho. (a) Phylogenetic tree reconstructed from the sequences of myoglobin, and α- and β-hemoglobins. Boxed sequences have no genetic distance between them. The sequences within the three dotted ellipses have orthologous relationships according to previous reports. (b) Results of Mestortho for the aligned dataset. The letter C and N in the first row of each Table denotes ‘co-orthology’ and ‘no genetic distance’. The sequences having relationships of co-orthology and no genetic distance were marked by red and blue bars, respectively. The abbreviations Hpor, Hsap and Mmus indicate H. portusjacksoni (Port Jackson shark), H. sapiens (human) and Mus musculus (mouse).
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Figure 4: Tree reconciliation versus Mestortho. (a) Phylogenetic tree reconstructed from the sequences of myoglobin, and α- and β-hemoglobins. Boxed sequences have no genetic distance between them. The sequences within the three dotted ellipses have orthologous relationships according to previous reports. (b) Results of Mestortho for the aligned dataset. The letter C and N in the first row of each Table denotes ‘co-orthology’ and ‘no genetic distance’. The sequences having relationships of co-orthology and no genetic distance were marked by red and blue bars, respectively. The abbreviations Hpor, Hsap and Mmus indicate H. portusjacksoni (Port Jackson shark), H. sapiens (human) and Mus musculus (mouse).

Mentions: We collected protein sequences of 14 globin-related genes from the NCBI and reconstructed an NJ tree from an alignment with 160 amino acid sites. For human, mouse and shark, myoglobin genes were clustered monophyletically (Figure 4a). Four sequences of human in the cluster of myoglobin showed no genetic distance from each other (Figure 4b). The α- and β-hemoglobin clusters had paraphyletic relationships due to shark hemoglobin sequences (Figure 4a), but were identified as orthologous groups by Mestortho (Figure 4b). The human β-hemoglobin sequences P68871 and P68872, which showed no genetic distance to each other, were co-orthologs of P68226 (Figure 4a and b). Under the concept of tree reconciliation, two hemoglobin sequences of shark showed co-orthology (Figure 4a), but were identified as paralogs by Mestortho (Figure 4b).Figure 4.


An approach of orthology detection from homologous sequences under minimum evolution.

Kim KM, Sung S, Caetano-Anollés G, Han JY, Kim H - Nucleic Acids Res. (2008)

Tree reconciliation versus Mestortho. (a) Phylogenetic tree reconstructed from the sequences of myoglobin, and α- and β-hemoglobins. Boxed sequences have no genetic distance between them. The sequences within the three dotted ellipses have orthologous relationships according to previous reports. (b) Results of Mestortho for the aligned dataset. The letter C and N in the first row of each Table denotes ‘co-orthology’ and ‘no genetic distance’. The sequences having relationships of co-orthology and no genetic distance were marked by red and blue bars, respectively. The abbreviations Hpor, Hsap and Mmus indicate H. portusjacksoni (Port Jackson shark), H. sapiens (human) and Mus musculus (mouse).
© Copyright Policy - creative-commons
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC2553584&req=5

Figure 4: Tree reconciliation versus Mestortho. (a) Phylogenetic tree reconstructed from the sequences of myoglobin, and α- and β-hemoglobins. Boxed sequences have no genetic distance between them. The sequences within the three dotted ellipses have orthologous relationships according to previous reports. (b) Results of Mestortho for the aligned dataset. The letter C and N in the first row of each Table denotes ‘co-orthology’ and ‘no genetic distance’. The sequences having relationships of co-orthology and no genetic distance were marked by red and blue bars, respectively. The abbreviations Hpor, Hsap and Mmus indicate H. portusjacksoni (Port Jackson shark), H. sapiens (human) and Mus musculus (mouse).
Mentions: We collected protein sequences of 14 globin-related genes from the NCBI and reconstructed an NJ tree from an alignment with 160 amino acid sites. For human, mouse and shark, myoglobin genes were clustered monophyletically (Figure 4a). Four sequences of human in the cluster of myoglobin showed no genetic distance from each other (Figure 4b). The α- and β-hemoglobin clusters had paraphyletic relationships due to shark hemoglobin sequences (Figure 4a), but were identified as orthologous groups by Mestortho (Figure 4b). The human β-hemoglobin sequences P68871 and P68872, which showed no genetic distance to each other, were co-orthologs of P68226 (Figure 4a and b). Under the concept of tree reconciliation, two hemoglobin sequences of shark showed co-orthology (Figure 4a), but were identified as paralogs by Mestortho (Figure 4b).Figure 4.

Bottom Line: For this reason, several methods based on evolutionary distance, phylogeny and BLAST have tried to detect orthologs with more precision.Calculation of evolutionary cost requires the reconstruction of a neighbor-joining (NJ) tree, but calculations are unaffected by the topology of any given NJ tree.Sensitivity and specificity estimates indicate that the concept of minimum evolution could be valuable for the detection of orthologs.

View Article: PubMed Central - PubMed

Affiliation: Department of Agricultural Biotechnology, Laboratory of Bioinformatics and Population Genetics, Seoul National University, Seoul 151-742, Korea.

ABSTRACT
In the field of phylogenetics and comparative genomics, it is important to establish orthologous relationships when comparing homologous sequences. Due to the slight sequence dissimilarity between orthologs and paralogs, it is prone to regarding paralogs as orthologs. For this reason, several methods based on evolutionary distance, phylogeny and BLAST have tried to detect orthologs with more precision. Depending on their algorithmic implementations, each of these methods sometimes has increased false negative or false positive rates. Here, we developed a novel algorithm for orthology detection that uses a distance method based on the phylogenetic criterion of minimum evolution. Our algorithm assumes that sets of sequences exhibiting orthologous relationships are evolutionarily less costly than sets that include one or more paralogous relationships. Calculation of evolutionary cost requires the reconstruction of a neighbor-joining (NJ) tree, but calculations are unaffected by the topology of any given NJ tree. Unlike tree reconciliation, our algorithm appears free from the problem of incorrect topologies of species and gene trees. The reliability of the algorithm was tested in a comparative analysis with two other orthology detection methods using 95 manually curated KOG datasets and 21 experimentally verified EXProt datasets. Sensitivity and specificity estimates indicate that the concept of minimum evolution could be valuable for the detection of orthologs.

Show MeSH