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      Evolutionary conservation and selection of human disease gene orthologs in the rat and mouse genomes

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          Abstract

          Human disease genes differ significantly from their rodent orthologs with respect to their overall levels of conservation and their rates of evolutionary change. Rodent orthologs of human trinucleotide repeat-expansion disease genes were also found to contain substantially fewer such repeats.

          Abstract

          Background

          Model organisms have contributed substantially to our understanding of the etiology of human disease as well as having assisted with the development of new treatment modalities. The availability of the human, mouse and, most recently, the rat genome sequences now permit the comprehensive investigation of the rodent orthologs of genes associated with human disease. Here, we investigate whether human disease genes differ significantly from their rodent orthologs with respect to their overall levels of conservation and their rates of evolutionary change.

          Results

          Human disease genes are unevenly distributed among human chromosomes and are highly represented (99.5%) among human-rodent ortholog sets. Differences are revealed in evolutionary conservation and selection between different categories of human disease genes. Although selection appears not to have greatly discriminated between disease and non-disease genes, synonymous substitution rates are significantly higher for disease genes. In neurological and malformation syndrome disease systems, associated genes have evolved slowly whereas genes of the immune, hematological and pulmonary disease systems have changed more rapidly. Amino-acid substitutions associated with human inherited disease occur at sites that are more highly conserved than the average; nevertheless, 15 substituting amino acids associated with human disease were identified as wild-type amino acids in the rat. Rodent orthologs of human trinucleotide repeat-expansion disease genes were found to contain substantially fewer of such repeats. Six human genes that share the same characteristics as triplet repeat-expansion disease-associated genes were identified; although four of these genes are expressed in the brain, none is currently known to be associated with disease.

          Conclusions

          Most human disease genes have been retained in rodent genomes. Synonymous nucleotide substitutions occur at a higher rate in disease genes, a finding that may reflect increased mutation rates in the chromosomal regions in which disease genes are found. Rodent orthologs associated with neurological function exhibit the greatest evolutionary conservation; this suggests that rodent models of human neurological disease are likely to most faithfully represent human disease processes. However, with regard to neurological triplet repeat expansion-associated human disease genes, the contraction, relative to human, of rodent trinucleotide repeats suggests that rodent loci may not achieve a 'critical repeat threshold' necessary to undergo spontaneous pathological repeat expansions. The identification of six genes in this study that have multiple characteristics associated with repeat expansion-disease genes raises the possibility that not all human loci capable of facilitating neurological disease by repeat expansion have as yet been identified.

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          Most cited references30

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          Automatic clustering of orthologs and in-paralogs from pairwise species comparisons.

          Orthologs are genes in different species that originate from a single gene in the last common ancestor of these species. Such genes have often retained identical biological roles in the present-day organisms. It is hence important to identify orthologs for transferring functional information between genes in different organisms with a high degree of reliability. For example, orthologs of human proteins are often functionally characterized in model organisms. Unfortunately, orthology analysis between human and e.g. invertebrates is often complex because of large numbers of paralogs within protein families. Paralogs that predate the species split, which we call out-paralogs, can easily be confused with true orthologs. Paralogs that arose after the species split, which we call in-paralogs, however, are bona fide orthologs by definition. Orthologs and in-paralogs are typically detected with phylogenetic methods, but these are slow and difficult to automate. Automatic clustering methods based on two-way best genome-wide matches on the other hand, have so far not separated in-paralogs from out-paralogs effectively. We present a fully automatic method for finding orthologs and in-paralogs from two species. Ortholog clusters are seeded with a two-way best pairwise match, after which an algorithm for adding in-paralogs is applied. The method bypasses multiple alignments and phylogenetic trees, which can be slow and error-prone steps in classical ortholog detection. Still, it robustly detects complex orthologous relationships and assigns confidence values for both orthologs and in-paralogs. The program, called INPARANOID, was tested on all completely sequenced eukaryotic genomes. To assess the quality of INPARANOID results, ortholog clusters were generated from a dataset of worm and mammalian transmembrane proteins, and were compared to clusters derived by manual tree-based ortholog detection methods. This study led to the identification with a high degree of confidence of over a dozen novel worm-mammalian ortholog assignments that were previously undetected because of shortcomings of phylogenetic methods.A WWW server that allows searching for orthologs between human and several fully sequenced genomes is installed at http://www.cgb.ki.se/inparanoid/. This is the first comprehensive resource with orthologs of all fully sequenced eukaryotic genomes. Programs and tables of orthology assignments are available from the same location. Copyright 2001 Academic Press.
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            Estimating synonymous and nonsynonymous substitution rates under realistic evolutionary models.

            Q. Z. Yang (2000)
            Approximate methods for estimating the numbers of synonymous and nonsynonymous substitutions between two DNA sequences involve three steps: counting of synonymous and nonsynonymous sites in the two sequences, counting of synonymous and nonsynonymous differences between the two sequences, and correcting for multiple substitutions at the same site. We examine complexities involved in those steps and propose a new approximate method that takes into account two major features of DNA sequence evolution: transition/transversion rate bias and base/codon frequency bias. We compare the new method with maximum likelihood, as well as several other approximate methods, by examining infinitely long sequences, performing computer simulations, and analyzing a real data set. The results suggest that when there are transition/transversion rate biases and base/codon frequency biases, previously described approximate methods for estimating the nonsynonymous/synonymous rate ratio may involve serious biases, and the bias can be both positive and negative. The new method is, in general, superior to earlier approximate methods and may be useful for analyzing large data sets, although maximum likelihood appears to always be the method of choice.
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              The Ka/Ks ratio: diagnosing the form of sequence evolution

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                Author and article information

                Journal
                Genome Biol
                Genome Biology
                BioMed Central (London )
                1465-6906
                1465-6914
                2004
                28 June 2004
                : 5
                : 7
                : R47
                Affiliations
                [1 ]Department of Bioinformatics, Genome Therapeutics Corporation, Waltham, MA 02453, USA
                [2 ]MRC Functional Genetics Unit, Department of Human Anatomy and Genetics, University of Oxford, South Parks Road, Oxford OX1 3QX, UK
                [3 ]Institute of Medical Genetics, University of Wales College of Medicine, Heath Park, Cardiff CF14 4XN, UK
                [4 ]Genome Sequencing Center, Genome Therapeutics Corporation, Waltham, MA 02453, USA
                [5 ]Agencourt Bioscience Corporation, Beverly, MA 01915, USA
                [6 ]Grup de Recerca en Informàtica Biomèdica, Departament de Ciències Experimentals i de la Salut, Universitat Pompeu Fabra, Barcelona 08003, Spain
                Article
                gb-2004-5-7-r47
                10.1186/gb-2004-5-7-r47
                463309
                15239832
                8e10ce1b-39f7-488d-977e-7d643612987f
                Copyright © 2004 Huang et al.; licensee BioMed Central Ltd. This is an Open Access article: verbatim copying and redistribution of this article are permitted in all media for any purpose, provided this notice is preserved along with the article's original URL.
                History
                : 16 March 2004
                : 10 May 2004
                : 28 May 2004
                Categories
                Research

                Genetics
                Genetics

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