Bioinformatics Advance Access originally published online on December 14, 2004
Bioinformatics 2005 21(8):1713-1714; doi:10.1093/bioinformatics/bti208
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GeneContent: software for whole-genome phylogenetic analysis
1Department of Genetics, Development and Cell Biology, Iowa State University Ames, IA 50011, USA
2Center for Bioinformatics and Biological Statistics, Iowa State University Ames, IA 50011, USA
3Department of Electrical and Computer Engineering, Iowa State University Ames, IA 50011, USA
4Department of Mathematics and Statistics, University of West Florida Pensacola, FL 32514, USA
*To whom correspondence should be addressed.
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Abstract |
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Summary: GeneContent is a software system to infer the genome phylogeny based on an additive genome distance that can be estimated from the extended gene content data, which contains the genome-wide information (absence of a gene family, presence as single copy or presence as duplicates) across multiple species. GeneContent can also be used to explore the genome-wide evolutionary pattern of gene loss and proliferation.
Availability: Distribution packages of GeneContent for both Microsoft Windows and Linux operating systems are available at http://xgu.zool.iastate.edu
Contact: xgu{at}iastate.edu
Since phylogenetic trees inferred from individual genes may be inconsistent, the whole-genome approach, such as the gene content, becomes an attractive approach to extract bulk phylogenetic signals. For instance, some authors (e.g. Snel et al., 1999; Huynen et al., 1999; Lin et al., 2000; Korbel et al., 2002) estimated the fraction of shared genes for genome pairs, and transformed it to the genome distance matrix by some ad hoc distance measures. Other methods include the coefficient of co-occurrence of genomics (Natale et al., 2000) and the ratio of orthologs to the number of genes in the smaller genome (Clarke et al., 2002). In addition, various parsimony algorithms have also been used (e.g. Fitz-Gibbon and House, 1999; House and Fitz-Gibbon, 2002).
However, the statistical model of genome evolution should be addressed appropriately for having a reliable phylogenetic inference rather than the best phenotypical clustering. To this end, Gu and Zhang (2004) proposed a statistical framework for the phylogenetic gene-content analysis, which has been successfully applied for the tree of life. We have subsequently developed a user-friendly GUI-based software system, GeneContent, to facilitate the further study in comparative genomics.
The software GeneContent deals with two types of gene-content data: the conventional gene content (Snel et al., 1999; Huynen et al., 1999; Lin and Gerstein, 2000; Korbel et al., 2002) contains the genome-wide information for the presence/absence of gene families across multiple species, while the extended gene content (Gu and Zhang, 2004) contains the genome-wide information as follows: absence of a gene family, presence as single copy or presence as duplicates. The advantage of extended gene content for phylogenomics is demonstrated below.
Based on the birth–death stochastic model (Gu and Zhang, 2004), an additive genome distance measure between two species can be defined as G=2(
+ µ)t, where is the proliferation (duplicate) rate of a gene family, µ is the loss rate of genes and t is the evolutionary time units. It has been shown that for two genomes, it is difficult to utilize the conventional gene-content data to estimate the genome distance G, except for the special case, where = 0. Gu and Zhang (2004) have solved this problem by introducing the concept of extended gene content, and proposed an efficient algorithm for genome-wide phylogenetic analysis since it does not require much computational time.
The interface of the software GeneContent (Fig. 1) is straightforward and easy to use. The input of the data is in the text file, in which the rows correspond to different genomes and the columns to gene families. The values for each entry of the data matrix could represent the size of gene family in the genome, gene content or extended gene content. Our program will trim the input matrix to fit the type of input as specified by the user. GeneContent provides three options to calculate genome distance: the Poisson distance, the gene content (under the special case where = 0) and the extended gene content. By default, both gene content and extended gene content methods will be provided, except that the input matrix only contains two types of values (i.e. 0 for absence and 1 for presence); in this case, the extended gene content method will be disabled. The Poisson distance is available for comparison purpose. Note that the gene-content distance between species (A and B) is calculated DAB = 1 – JAB, where JAB is the Jaccard coefficient, which reflects the similarity of gene content between A and B (Wolf et al., 2002).
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After obtaining the genome distance matrix, the software is able to infer the genome phylogeny using the neighbor-joining method (Saitou and Nei, 1987). The statistical reliability of the inferred genome phylogeny is examined by the conventional bootstrapping approach. Since the inferred phylogeny is un-rooted, the option for changing the root under the tree-view is available, as well as other options for visualization editing. The inferred genome tree can be saved as a text file in the Phylip format, which is useful in some cases.
The performance of the above algorithm has been examined by the universal genome tree of 36 complete genomes (Gu and Zhang, 2004). In the current version, we have implemented some options to explore the pattern of genome evolution. For instance, the proliferation/loss rate ratio can be mapped onto the phylogenetic tree, and the bootstrapping test can be performed to examine whether it remains a constant among lineages. We will upgrade our software in two directions. The first one is to improve the evolutionary model by considering more factors such as lateral gene transfer and co-evolution among gene families. The second direction is to implement more sophisticated tree-making algorithms, e.g. a fast algorithm for the maximum-likelihood inference of genome phylogeny.
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Acknowledgments |
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This work was supported by the NIH grant RO1 GM62118 to X.G.
Received on September 3, 2004; revised on November 30, 2004; accepted on December 2, 2004
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