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      Mouse Phenome Database: towards a more FAIR-compliant and TRUST-worthy data repository and tool suite for phenotypes and genotypes

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          Abstract

          The Mouse Phenome Database (MPD; https://phenome.jax.org; RRID:SCR_003212), supported by the US National Institutes of Health, is a Biomedical Data Repository listed in the Trans-NIH Biomedical Informatics Coordinating Committee registry. As an increasingly FAIR-compliant and TRUST-worthy data repository, MPD accepts phenotype and genotype data from mouse experiments and curates, organizes, integrates, archives, and distributes those data using community standards. Data are accompanied by rich metadata, including widely used ontologies and detailed protocols. Data are from all over the world and represent genetic, behavioral, morphological, and physiological disease-related characteristics in mice at baseline or those exposed to drugs or other treatments. MPD houses data from over 6000 strains and populations, representing many reproducible strain types and heterogenous populations such as the Diversity Outbred where each mouse is unique but can be genotyped throughout the genome. A suite of analysis tools is available to aggregate, visualize, and analyze these data within and across studies and populations in an increasingly traceable and reproducible manner. We have refined existing resources and developed new tools to continue to provide users with access to consistent, high-quality data that has translational relevance in a modernized infrastructure that enables interaction with a suite of bioinformatics analytic and data services.

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          Most cited references26

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          The FAIR Guiding Principles for scientific data management and stewardship

          There is an urgent need to improve the infrastructure supporting the reuse of scholarly data. A diverse set of stakeholders—representing academia, industry, funding agencies, and scholarly publishers—have come together to design and jointly endorse a concise and measureable set of principles that we refer to as the FAIR Data Principles. The intent is that these may act as a guideline for those wishing to enhance the reusability of their data holdings. Distinct from peer initiatives that focus on the human scholar, the FAIR Principles put specific emphasis on enhancing the ability of machines to automatically find and use the data, in addition to supporting its reuse by individuals. This Comment is the first formal publication of the FAIR Principles, and includes the rationale behind them, and some exemplar implementations in the community.
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            Mouse genomic variation and its effect on phenotypes and gene regulation.

            We report genome sequences of 17 inbred strains of laboratory mice and identify almost ten times more variants than previously known. We use these genomes to explore the phylogenetic history of the laboratory mouse and to examine the functional consequences of allele-specific variation on transcript abundance, revealing that at least 12% of transcripts show a significant tissue-specific expression bias. By identifying candidate functional variants at 718 quantitative trait loci we show that the molecular nature of functional variants and their position relative to genes vary according to the effect size of the locus. These sequences provide a starting point for a new era in the functional analysis of a key model organism.
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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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                Author and article information

                Contributors
                Journal
                Nucleic Acids Res
                Nucleic Acids Res
                nar
                Nucleic Acids Research
                Oxford University Press
                0305-1048
                1362-4962
                06 January 2023
                04 November 2022
                04 November 2022
                : 51
                : D1
                : D1067-D1074
                Affiliations
                The Jackson Laboratory , Bar Harbor Maine, 04609, USA
                The Jackson Laboratory , Bar Harbor Maine, 04609, USA
                The Jackson Laboratory , Bar Harbor Maine, 04609, USA
                The Jackson Laboratory , Bar Harbor Maine, 04609, USA
                The Jackson Laboratory , Bar Harbor Maine, 04609, USA
                The Jackson Laboratory , Bar Harbor Maine, 04609, USA
                The Jackson Laboratory , Bar Harbor Maine, 04609, USA
                The Jackson Laboratory , Bar Harbor Maine, 04609, USA
                The Jackson Laboratory , Bar Harbor Maine, 04609, USA
                The Jackson Laboratory , Bar Harbor Maine, 04609, USA
                The Jackson Laboratory , Bar Harbor Maine, 04609, USA
                The Jackson Laboratory , Bar Harbor Maine, 04609, USA
                The Jackson Laboratory , Bar Harbor Maine, 04609, USA
                The Jackson Laboratory , Bar Harbor Maine, 04609, USA
                The Jackson Laboratory , Bar Harbor Maine, 04609, USA
                The Jackson Laboratory , Bar Harbor Maine, 04609, USA
                The Jackson Laboratory , Bar Harbor Maine, 04609, USA
                The Jackson Laboratory , Bar Harbor Maine, 04609, USA
                The Jackson Laboratory , Bar Harbor Maine, 04609, USA
                Author notes
                To whom correspondence should be addressed. Tel: +1 207 288 6016; Email: molly.bogue@ 123456jax.org

                The authors wish it to be known that, in their opinion, the first two authors should be regarded as Joint First Authors.

                Author information
                https://orcid.org/0000-0001-6624-9261
                https://orcid.org/0000-0002-1473-4174
                Article
                gkac1007
                10.1093/nar/gkac1007
                9825561
                36330959
                09c75fb5-6417-4cc2-9dd2-db327c7f0e80
                © The Author(s) 2022. Published by Oxford University Press on behalf of Nucleic Acids Research.

                This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( https://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.

                History
                : 02 November 2022
                : 11 October 2022
                : 20 September 2022
                Page count
                Pages: 8
                Funding
                Funded by: National Institutes of Health, DOI 10.13039/100000002;
                Award ID: DA028420
                Award ID: AG066346
                Award ID: DA039841
                Award ID: OD030187
                Funded by: Jackson Laboratory Director's Innovation Fund and Cube Initiative;
                Categories
                AcademicSubjects/SCI00010
                Database Issue

                Genetics
                Genetics

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