DODO: an efficient orthologous genes assignment tool based on domain architectures. Domain based ortholog detection

<p>Abstract</p> <p>Background</p> <p>Orthologs are genes derived from the same ancestor gene loci after speciation events. Orthologous proteins usually have similar sequences and perform comparable biological functions. Therefore, ortholog identification is useful in annotations of newly sequenced genomes. With rapidly increasing number of sequenced genomes, constructing or updating ortholog relationship between all genomes requires lots of effort and computation time. In addition, elucidating ortholog relationships between distantly related genomes is challenging because of the lower sequence similarity. Therefore, an efficient ortholog detection method that can deal with large number of distantly related genomes is desired.</p> <p>Results</p> <p>An efficient ortholog detection pipeline DODO (DOmain based Detection of Orthologs) is created on the basis of domain architectures in this study. Supported by domain composition, which usually directly related with protein function, DODO could facilitate orthologs detection across distantly related genomes. DODO works in two main steps. Starting from domain information, it first assigns protein groups according to their domain architectures and further identifies orthologs within those groups with much reduced complexity. Here DODO is shown to detect orthologs between two genomes in considerably shorter period of time than traditional methods of reciprocal best hits and it is more significant when analyzed a large number of genomes. The output results of DODO are highly comparable with other known ortholog databases.</p> <p>Conclusions</p> <p>DODO provides a new efficient pipeline for detection of orthologs in a large number of genomes. In addition, a database established with DODO is also easier to maintain and could be updated relatively effortlessly. The pipeline of DODO could be downloaded from <url>http://140.109.42.19:16080/dodo_web/home.htm</url></p

Robust sequence alignment using evolutionary rates coupled with an amino acid substitution matrix

BACKGROUND: Selective pressures at the DNA level shape genes into profiles consisting of patterns of rapidly evolving sites and sites withstanding change. These profiles remain detectable even when protein sequences become extensively diverged. A common task in molecular biology is to infer functional, structural or evolutionary relationships by querying a database using an algorithm. However, problems arise when sequence similarity is low. This study presents an algorithm that uses the evolutionary rate at codon sites, the dN/dS (ω) parameter, coupled to a substitution matrix as an alignment metric for detecting distantly related proteins. The algorithm, called BLOSUM-FIRE couples a newer and improved version of the original FIRE (Functional Inference using Rates of Evolution) algorithm with an amino acid substitution matrix in a dynamic scoring function. The enigmatic hepatitis B virus X protein was used as a test case for BLOSUM-FIRE and its associated database EvoDB. RESULTS: The evolutionary rate based approach was coupled with a conventional BLOSUM substitution matrix. The two approaches are combined in a dynamic scoring function, which uses the selective pressure to score aligned residues. The dynamic scoring function is based on a coupled additive approach that scores aligned sites based on the level of conservation inferred from the ω values. Evaluation of the accuracy of this new implementation, BLOSUM-FIRE, using MAFFT alignment as reference alignments has shown that it is more accurate than its predecessor FIRE. Comparison of the alignment quality with widely used algorithms (MUSCLE, T-COFFEE, and CLUSTAL Omega) revealed that the BLOSUM-FIRE algorithm performs as well as conventional algorithms. Its main strength lies in that it provides greater potential for aligning divergent sequences and addresses the problem of low specificity inherent in the original FIRE algorithm. The utility of this algorithm is demonstrated using the Hepatitis B virus X (HBx) protein, a protein of unknown function, as a test case. CONCLUSION: This study describes the utility of an evolutionary rate based approach coupled to the BLOSUM62 amino acid substitution matrix in inferring protein domain function. We demonstrate that such an approach is robust and performs as well as an array of conventional algorithms.This item is part of the UA Faculty Publications collection. For more information this item or other items in the UA Campus Repository, contact the University of Arizona Libraries at [email protected]