Contribution of radiation hybrids to genome mapping in domestic animals.

Radiation hybrid mapping has emerged in the end of the 1990 s as a successful and complementary approach to map genomes, essentially because of its ability to bridge the gaps between genetic and clone-based physical maps, but also using comparative mapping approaches, between 'gene-rich' and 'gene-poor' maps. Since its early development in human, radiation hybrid mapping played a pivotal role in the process of mapping animal genomes, especially mammalian ones. We review here all the different steps involved in radiation hybrid mapping from the constitution of panels to the construction of maps. A description of its contribution to whole genome maps with a special emphasis on domestic animals will also be presented. Finally, current applications of radiation hybrid mapping in the context of whole genome assemblies will be described.

A comparative genome approach to marker ordering.

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.

Searching RNA motifs and their intermolecular contacts with constraint networks.

MOTIVATION: Searching RNA gene occurrences in genomic sequences is a task whose importance has been renewed by the recent discovery of numerous functional RNA, often interacting with other ligands. Even if several programs exist for RNA motif search, none exists that can represent and solve the problem of searching for occurrences of RNA motifs in interaction with other molecules. RESULTS: We present a constraint network formulation of this problem. RNA are represented as structured motifs that can occur on more than one sequence and which are related together by possible hybridization. The implemented tool MilPat is used to search for several sRNA families in genomic sequences. Results show that MilPat allows to efficiently search for interacting motifs in large genomic sequences and offers a simple and extensible framework to solve such problems. New and known sRNA are identified as H/ACA candidates in Methanocaldococcus jannaschii. AVAILABILITY: http://carlit.toulouse.inra.fr/MilPaT/MilPat.pl.

Genome sequence of the plant pathogen Ralstonia solanacearum.

Ralstonia solanacearum is a devastating, soil-borne plant pathogen with a global distribution and an unusually wide host range. It is a model system for the dissection of molecular determinants governing pathogenicity. We present here the complete genome sequence and its analysis of strain GMI1000. The 5.8-megabase (Mb) genome is organized into two replicons: a 3.7-Mb chromosome and a 2.1-Mb megaplasmid. Both replicons have a mosaic structure providing evidence for the acquisition of genes through horizontal gene transfer. Regions containing genetically mobile elements associated with the percentage of G+C bias may have an important function in genome evolution. The genome encodes many proteins potentially associated with a role in pathogenicity. In particular, many putative attachment factors were identified. The complete repertoire of type III secreted effector proteins can be studied. Over 40 candidates were identified. Comparison with other genomes suggests that bacterial plant pathogens and animal pathogens harbour distinct arrays of specialized type III-dependent effectors.

A composite genetic map of the parasitoid wasp Trichogramma brassicae based on RAPD markers.

Three linkage maps of the genome of the microhymenopteran Trichogramma brassicae were constructed from the analysis of segregation of random amplified polymorphic DNA markers in three F2 populations. These populations were composed of the haploid male progeny of several virgin F1 females, which resulted from the breeding of four parental lines that were nearly fixed for different random amplified polymorphic DNA markers and that were polymorphic for longevity and fecundity characters. As the order of markers common to the three mapping populations was found to be well conserved, a composite linkage map was constructed. Eighty-four markers were organized into five linkage groups and two pairs. The mean interval between two markers was 17.7 cM, and the map spanned 1330 cM.

CARTHAGENE: constructing and joining maximum likelihood genetic maps.

Genetic mapping is an important step in the study of any organism. An accurate genetic map is extremely valuable for locating genes or more generally either qualitative or quantitative trait loci (QTL). This paper presents a new approach to two important problems in genetic mapping: automatically ordering markers to obtain a multipoint maximum likelihood map and building a multipoint maximum likelihood map using pooled data from several crosses. The approach is embodied in an hybrid algorithm that mixes the statistical optimization algorithm EM with local search techniques which have been developed in the artificial intelligence and operations research communities. An efficient implementation of the EM algorithm provides maximum likelihood recombination fractions, while the local search techniques look for orders that maximize this maximum likelihood. The specificity of the approach lies in the neighborhood structure used in the local search algorithms which has been inspired by an analogy between the marker ordering problem and the famous traveling salesman problem. The approach has been used to build joined maps for the wasp Trichogramma brassicae and on random pooled data sets. In both cases, it compares quite favorably with existing softwares as far as maximum likelihood is considered as a significant criteria.