Title
A parsimony approach to genome-wide ortholog assignment
Abstract
The assignment of orthologous genes between a pair of genomes is a fundamental and challenging problem in comparative genomics, since many computational methods for solving various biological problems critically rely on bona fide orthologs as input. While it is usually done using sequence similarity search, we recently proposed a new combinatorial approach that combines sequence similarity and genome rearrangement. This paper continues the development of the approach and unites genome rearrangement events and (post-speciation) duplication events in a single framework under the parsimony principle. In this framework, orthologous genes are assumed to correspond to each other in the most parsimonious evolutionary scenario involving both genome rearrangement and (post-speciation) gene duplication. Besides several original algorithmic contributions, the enhanced method allows for the detection of inparalogs. Following this approach, we have implemented a high-throughput system for ortholog assignment on a genome scale, called MSOAR, and applied it to the genomes of human and mouse. As the result will show, MSOAR is able to find 99 more true orthologs than the INPARANOID program did. We have also compared MSOAR with the iterated exemplar algorithm on simulated data and found that MSOAR performed very well in terms of assignment accuracy. These test results indiate that our approach is very promising for genome-wide ortholog assignment.
Year
DOI
Venue
2006
10.1007/11732990_47
RECOMB
Keywords
Field
DocType
genome rearrangement,bona fide orthologs,duplication event,assignment accuracy,genome scale,orthologous gene,parsimony approach,ortholog assignment,new combinatorial approach,unites genome rearrangement event,genome-wide ortholog assignment,gene duplication,high throughput
Genome,Gene,Biology,Inparanoid,Genome rearrangement,Comparative genomics,Homology (biology),Bioinformatics,Genetics,Gene duplication,Nearest neighbor search
Conference
Volume
ISSN
ISBN
3909
0302-9743
3-540-33295-2
Citations 
PageRank 
References 
11
0.76
18
Authors
6
Name
Order
Citations
PageRank
Zheng Fu1110.76
Xin Chen21539.25
Vladimir Vacic324717.37
Peng Nan41117.54
Yang Zhong5604.20
Tao Jiang61809155.32