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      Collaborative Cross and Diversity Outbred data resources in the Mouse Phenome Database

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      , ,
      Mammalian Genome
      Springer US

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          Abstract

          The Mouse Phenome Database was originally conceived as a platform for the integration of phenotype data collected on a defined collection of 40 inbred mouse strains—the “phenome panel.” This model provided an impetus for community data sharing, and integration was readily achieved through the reproducible genotypes of the phenome panel strains. Advances in the development of mouse populations lead to an expanded role of the Mouse Phenome Database to encompass new strain panels and inbred strain crosses. The recent introduction of the Collaborative Cross and Diversity Outbred mice, which share an extensive pool of genetic variation from eight founder inbred strains, presents new opportunities and challenges for community data resources. A wide variety of molecular and clinical phenotypes are being collected across genotypes, tissues, ages, environmental exposures, interventions, and treatments. The Mouse Phenome Database provides a framework for retrieval, integration, analysis, and display of these data, enabling them to be evaluated in the context of existing data from standard inbred strains. Primary data in the Mouse Phenome Database are supported by extensive metadata on protocols and procedures. These are centrally curated to ensure accuracy and reproducibility and to provide data in consistent formats. The Mouse Phenome Database represents an established and growing community data resource for mouse phenotype data and encourages submissions from new mouse resources, enabling investigators to integrate existing data into their studies of the phenotypic consequences of genetic variation.

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          Most cited references30

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          High-resolution genetic mapping using the Mouse Diversity outbred population.

          The JAX Diversity Outbred population is a new mouse resource derived from partially inbred Collaborative Cross strains and maintained by randomized outcrossing. As such, it segregates the same allelic variants as the Collaborative Cross but embeds these in a distinct population architecture in which each animal has a high degree of heterozygosity and carries a unique combination of alleles. Phenotypic diversity is striking and often divergent from phenotypes seen in the founder strains of the Collaborative Cross. Allele frequencies and recombination density in early generations of Diversity Outbred mice are consistent with expectations based on simulations of the mating design. We describe analytical methods for genetic mapping using this resource and demonstrate the power and high mapping resolution achieved with this population by mapping a serum cholesterol trait to a 2-Mb region on chromosome 3 containing only 11 genes. Analysis of the estimated allele effects in conjunction with complete genome sequence data of the founder strains reduced the pool of candidate polymorphisms to seven SNPs, five of which are located in an intergenic region upstream of the Foxo1 gene.
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            The International Mouse Phenotyping Consortium: past and future perspectives on mouse phenotyping.

            Determining the function of all mammalian genes remains a major challenge for the biomedical science community in the 21st century. The goal of the International Mouse Phenotyping Consortium (IMPC) over the next 10 years is to undertake broad-based phenotyping of 20,000 mouse genes, providing an unprecedented insight into mammalian gene function. This short article explores the drivers for large-scale mouse phenotyping and provides an overview of the aims and processes involved in IMPC mouse production and phenotyping.
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              A high-resolution association mapping panel for the dissection of complex traits in mice.

              Systems genetics relies on common genetic variants to elucidate biologic networks contributing to complex disease-related phenotypes. Mice are ideal model organisms for such approaches, but linkage analysis has been only modestly successful due to low mapping resolution. Association analysis in mice has the potential of much better resolution, but it is confounded by population structure and inadequate power to map traits that explain less than 10% of the variance, typical of mouse quantitative trait loci (QTL). We report a novel strategy for association mapping that combines classic inbred strains for mapping resolution and recombinant inbred strains for mapping power. Using a mixed model algorithm to correct for population structure, we validate the approach by mapping over 2500 cis-expression QTL with a resolution an order of magnitude narrower than traditional QTL analysis. We also report the fine mapping of metabolic traits such as plasma lipids. This resource, termed the Hybrid Mouse Diversity Panel, makes possible the integration of multiple data sets and should prove useful for systems-based approaches to complex traits and studies of gene-by-environment interactions.
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                Author and article information

                Contributors
                207 288 6016 , molly.bogue@jax.org
                Journal
                Mamm Genome
                Mamm. Genome
                Mammalian Genome
                Springer US (New York )
                0938-8990
                1432-1777
                19 August 2015
                19 August 2015
                2015
                : 26
                : 9-10
                : 511-520
                Affiliations
                The Jackson Laboratory, 600 Main Street, Bar Harbor, ME 04609 USA
                Article
                9595
                10.1007/s00335-015-9595-6
                4602074
                26286858
                b7d33641-0a44-4dcb-b708-d44816b10b3b
                © The Author(s) 2015

                Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License ( http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.

                History
                : 14 May 2015
                : 10 August 2015
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                Custom metadata
                © Springer Science+Business Media New York 2015

                Genetics
                Genetics

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