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      A new set of BXD recombinant inbred lines from advanced intercross populations in mice

      , 1 , 2 , 1 , , 2 , 1

      BMC Genetics

      BioMed Central

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          Abstract

          Background

          Recombinant inbred (RI) strains are an important resource for mapping complex traits in many species. While large RI panels are available for Arabidopsis, maize, C. elegans, and Drosophila, mouse RI panels typically consist of fewer than 30 lines. This is a severe constraint on the power and precision of mapping efforts and greatly hampers analysis of epistatic interactions.

          Results

          In order to address these limitations and to provide the community with a more effective collaborative RI mapping panel we generated new BXD RI strains from two independent advanced intercrosses (AI) between C57BL/6J (B6) and DBA/2J (D2) progenitor strains. Progeny were intercrossed for 9 to 14 generations before initiating inbreeding, which is still ongoing for some strains. Since this AI base population is highly recombinant, the 46 advanced recombinant inbred (ARI) strains incorporate approximately twice as many recombinations as standard RI strains, a fraction of which are inevitably shared by descent. When combined with the existing BXD RI strains, the merged BXD strain set triples the number of previously available unique recombinations and quadruples the total number of recombinations in the BXD background.

          Conclusion

          The combined BXD strain set is the largest mouse RI mapping panel. It is a powerful tool for collaborative analysis of quantitative traits and gene function that will be especially useful to study variation in transcriptome and proteome data sets under multiple environments. Additional strains also extend the value of the extensive phenotypic characterization of the previously available strains. A final advantage of expanding the BXD strain set is that both progenitors have been sequenced, and approximately 1.8 million SNPs have been characterized. This provides unprecedented power in screening candidate genes and can reduce the effective length of QTL intervals. It also makes it possible to reverse standard mapping strategies and to explore downstream effects of known sequence variants.

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          Most cited references 47

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          'Touchdown' PCR to circumvent spurious priming during gene amplification.

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            Bay-0 x Shahdara recombinant inbred line population: a powerful tool for the genetic dissection of complex traits in Arabidopsis.

            Natural genetic variation in Arabidopsis is considerable, but has not yet been used extensively as a source of variants to identify new genes of interest. From the cross between two genetically distant ecotypes, Bay-0 and Shahdara, we generated a Recombinant Inbred Line (RIL) population dedicated to Quantitative Trait Locus (QTL) mapping. A set of 38 physically anchored microsatellite markers was created to construct a robust genetic map from the 420 F6 lines. These markers, evenly distributed throughout the five chromosomes, revealed a remarkable equilibrium in the segregation of parental alleles in the genome. As a model character, we have analysed the genetic basis of variation in flowering time in two different environments. The simultaneous mapping of both large- and small-effect QTLs responsible for this variation explained 90% of the total genotypic variance. Two of the detected QTLs colocalize very precisely with FRIGIDA and FLOWERING LOCUS C genes; we provide information on the polymorphism of genes confirming this hypothesis. Another QTL maps in a region where no QTL had been found previously for this trait. This confirms the accuracy of QTL detection using the Bay-0 x Shahdara RIL population, which constitutes the largest in size available so far in Arabidopsis. As an alternative to mutant analysis, this population represents a powerful tool which is currently being used to undertake the genetic dissection of complex metabolic pathways.
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              Analysing complex genetic traits with chromosome substitution strains.

              Many valuable animal models of human disease are known and new models are continually being generated in existing inbred strains,. Some disease models are simple mendelian traits, but most have a polygenic basis. The current approach to identifying quantitative trait loci (QTLs) that underlie such traits is to localize them in crosses, construct congenic strains carrying individual QTLs, and finally map and clone the genes. This process is time-consuming and expensive, requiring the genotyping of large crosses and many generations of breeding. Here we describe a different approach in which a panel of chromosome substitution strains (CSSs) is used for QTL mapping. Each of these strains has a single chromosome from the donor strain substituting for the corresponding chromosome in the host strain. We discuss the construction, applications and advantages of CSSs compared with conventional crosses for detecting and analysing QTLs, including those that have weak phenotypic effects.
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                Author and article information

                Journal
                BMC Genet
                BMC Genetics
                BioMed Central (London )
                1471-2156
                2004
                29 April 2004
                : 5
                : 7
                Affiliations
                [1 ]Center for Neuroscience Department of Anatomy and Neurobiology University of Tennessee Health Science Center 855 Monroe Avenue Memphis, Tennessee 38163 USA
                [2 ]Louis Thomas Laboratory Department of Molecular Biology Washington Road Princeton University Princeton, NJ 08544 USA
                Article
                1471-2156-5-7
                10.1186/1471-2156-5-7
                420238
                15117419
                Copyright © 2004 Peirce 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.
                Categories
                Methodology Article

                Genetics

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