Computational Genomics
A comparative genome approach to marker ordering
1 Laboratoire de génétique cellulaire BP 52627, 31326 Castanet Tolosan, France
2 Laboratoire de mathématiques et informatique appliquées, INRA BP 52627, 31326 Castanet Tolosan, France
3 CNRS UMR6061 Génétique et Développement, Université de Rennes 1 IFR 140, 2 Av du Pr Léon Bernard, CS 34317, 35043 Rennes, France
*To whom correspondence should be addressed.
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Abstract |
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Motivation: Genome maps are fundamental to the study of an organism and essential in the process of genome sequencing which in turn provides the ultimate map of the genome. The increased number of genomes being sequenced offers new opportunities for the mapping of closely related organisms. We propose here an algorithmic formalization of a genome comparison approach to marker ordering.
Results: In order to integrate a comparative mapping approach in the algorithmic process of map construction and selection, we propose to extend the usual statistical model describing the experimental data, here radiation hybrids (RH) data, in a statistical framework that models additionally the evolutionary relationships between a proposed map and a reference map: an existing map of the corresponding orthologous genes or markers in a closely related organism. This has concretely the effect of exploiting, in the process of map selection, the information of marker adjacencies in the related genome when the information provided by the experimental data is not conclusive for the purpose of ordering. In order to compute efficiently the map, we proceed to a reduction of the maximum likelihood estimation to the Traveling Salesman Problem. Experiments on simulated RH datasets as well as on a real RH dataset from the canine RH project show that maps produced using the likelihood defined by the new model are significantly better than maps built using the traditional RH model.
Availability: The comparative mapping approach is available in the last version of de Givry,S. et al. [(2004) Bioinformatics, 21, 1703–1704, www.inra.fr/mia/T/CarthaGene], a free (the LKH part is free for academic use only) mapping software in C++, including LKH (Helsgaun,K. (2000) Eur. J. Oper. Res., 126, 106–130, www.dat.ruc.dk/keld/research/LKH) for maximum likelihood computation.
Contact: thomas.faraut{at}toulouse.inra.fr
The authors wish it to be known that, in their opinion, the first two authors should be regarded as joint First Authors.
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