Abstract
Although next-generation sequencing has revolutionized the ability to associate variants with human diseases, diagnostic rates and development of new therapies are still limited by a lack of knowledge of the functions and pathobiological mechanisms of most genes. To address this challenge, the International Mouse Phenotyping Consortium is creating a genome- and phenome-wide catalog of gene function by characterizing new knockout-mouse strains across diverse biological systems through a broad set of standardized phenotyping tests. All mice will be readily available to the biomedical community. Analyzing the first 3,328 genes identified models for 360 diseases, including the first models, to our knowledge, for type C Bernard–Soulier, Bardet–Biedl-5 and Gordon Holmes syndromes. 90% of our phenotype annotations were novel, providing functional evidence for 1,092 genes and candidates in genetically uncharacterized diseases including arrhythmogenic right ventricular dysplasia 3. Finally, we describe our role in variant functional validation with The 100,000 Genomes Project and others.
Similar content being viewed by others
References
Bello, S.M., Smith, C.L. & Eppig, J.T. Allele, phenotype and disease data at Mouse Genome Informatics: improving access and analysis. Mamm. Genome 26, 285–294 (2015).
Begley, C.G. & Ellis, L.M. Drug development: raise standards for preclinical cancer research. Nature 483, 531–533 (2012).
Fonio, E., Golani, I. & Benjamini, Y. Measuring behavior of animal models: faults and remedies. Nat. Methods 9, 1167–1170 (2012).
Kilkenny, C., Browne, W.J., Cuthill, I.C., Emerson, M. & Altman, D.G. Improving bioscience research reporting: the ARRIVE guidelines for reporting animal research. PLoS Biol. 8, e1000412 (2010).
Brown, S.D.M. & Moore, M.W. The International Mouse Phenotyping Consortium: past and future perspectives on mouse phenotyping. Mamm. Genome 23, 632–640 (2012).
Hrabě de Angelis, M. et al. Analysis of mammalian gene function through broad-based phenotypic screens across a consortium of mouse clinics. Nat. Genet. 47, 969–978 (2015).
Skarnes, W.C. et al. A conditional knockout resource for the genome-wide study of mouse gene function. Nature 474, 337–342 (2011).
Bradley, A. et al. The mammalian gene function resource: the International Knockout Mouse Consortium. Mamm. Genome 23, 580–586 (2012).
Rosen, B., Schick, J. & Wurst, W. Beyond knockouts: the International Knockout Mouse Consortium delivers modular and evolving tools for investigating mammalian genes. Mamm. Genome 26, 456–466 (2015).
Dickinson, M.E. et al. High-throughput discovery of novel developmental phenotypes. Nature 537, 508–514 (2016).
Adams, D. et al. Bloomsbury report on mouse embryo phenotyping: recommendations from the IMPC workshop on embryonic lethal screening. Dis. Model. Mech. 6, 571–579 (2013).
Kurbatova, N., Mason, J.C., Morgan, H., Meehan, T.F. & Karp, N.A. PhenStat: a tool kit for standardized analysis of high throughput phenotypic data. PLoS One 10, e0131274 (2015).
West, D.B. et al. A lacZ reporter gene expression atlas for 313 adult KOMP mutant mouse lines. Genome Res. 25, 598–607 (2015).
Adissu, H.A. et al. Histopathology reveals correlative and unique phenotypes in a high-throughput mouse phenotyping screen. Dis. Model. Mech. 7, 515–524 (2014).
Koscielny, G. et al. The International Mouse Phenotyping Consortium Web Portal, a unified point of access for knockout mice and related phenotyping data. Nucleic Acids Res. 42, D802–D809 (2014).
Freedman, L.P., Cockburn, I.M. & Simcoe, T.S. The economics of reproducibility in preclinical research. PLoS Biol. 13, e1002165 (2015).
Amberger, J.S., Bocchini, C.A., Schiettecatte, F., Scott, A.F. & Hamosh, A. OMIM.org: Online Mendelian Inheritance in Man (OMIM®), an online catalog of human genes and genetic disorders. Nucleic Acids Res. 43, D789–D798 (2015).
Rath, A. et al. Representation of rare diseases in health information systems: the Orphanet approach to serve a wide range of end users. Hum. Mutat. 33, 803–808 (2012).
Köhler, S. et al. The Human Phenotype Ontology in 2017. Nucleic Acids Res. 45, D1, D865–D876 (2017).
Mungall, C.J. et al. Use of model organism and disease databases to support matchmaking for human disease gene discovery. Hum. Mutat. 36, 979–984 (2015).
Smith, C.L. & Eppig, J.T. Expanding the mammalian phenotype ontology to support automated exchange of high throughput mouse phenotyping data generated by large-scale mouse knockout screens. J. Biomed. Semantics 6, 11 (2015).
Smedley, D. et al. PhenoDigm: analyzing curated annotations to associate animal models with human diseases. Database (Oxford) 2013, bat025 (2013).
Savoia, A. et al. Spectrum of the mutations in Bernard-Soulier syndrome. Hum. Mutat. 35, 1033–1045 (2014).
Khan, S.A. et al. Genetics of human Bardet-Biedl syndrome, an updates. Clin. Genet. 90, 3–15 (2016).
Margolin, D.H. et al. Ataxia, dementia, and hypogonadotropism caused by disordered ubiquitination. N. Engl. J. Med. 368, 1992–2003 (2013).
Santens, P. et al. RNF216 mutations as a novel cause of autosomal recessive Huntington-like disorder. Neurology 84, 1760–1766 (2015).
White, J.K. et al. Genome-wide generation and systematic phenotyping of knockout mice reveals new roles for many genes. Cell 154, 452–464 (2013).
Gene Ontology Consortium. Gene Ontology Consortium: going forward. Nucleic Acids Res. 43, D1049–D1056 (2015).
Pandey, A.K., Lu, L., Wang, X., Homayouni, R. & Williams, R.W. Functionally enigmatic genes: a case study of the brain ignorome. PLoS One 9, e88889 (2014).
Petryszak, R. et al. Expression Atlas update: an integrated database of gene and protein expression in humans, animals and plants. Nucleic Acids Res. 44, D746–D752 (2016).
Kingsley, P.D. et al. Ontogeny of erythroid gene expression. Blood 121, e5–e13 (2013).
Boria, I. et al. The ribosomal basis of Diamond-Blackfan anemia: mutation and database update. Hum. Mutat. 31, 1269–1279 (2010).
Kizil, C. et al. Simplet/Fam53b is required for Wnt signal transduction by regulating β-catenin nuclear localization. Development 141, 3529–3539 (2014).
Smedley, D. et al. Next-generation diagnostics and disease-gene discovery with the Exomiser. Nat. Protoc. 10, 2004–2015 (2015).
Bone, W.P. et al. Computational evaluation of exome sequence data using human and model organism phenotypes improves diagnostic efficiency. Genet. Med. 18, 608–617 (2016).
Harkness, J.H., Shi, X., Janowsky, A. & Phillips, T.J. Trace amine-associated receptor 1 regulation of methamphetamine intake and related traits. Neuropsychopharmacology 40, 2175–2184 (2015).
Cade, B.E. et al. Genetic associations with obstructive sleep apnea traits in Hispanic/Latino Americans. Am. J. Respir. Crit. Care Med. 194, 886–897 (2016).
Knowles, J.W. et al. Identification and validation of N-acetyltransferase 2 as an insulin sensitivity gene. J. Clin. Invest. 126, 403 (2016).
Lang, B. et al. Recurrent deletions of ULK4 in schizophrenia: a gene crucial for neuritogenesis and neuronal motility. J. Cell Sci. 127, 630–640 (2014).
McIntyre, R.E. et al. A genome-wide association study for regulators of micronucleus formation in mice. G3 (Bethesda) 6, 2343–2354 (2016).
Levy, R., Mott, R.F., Iraqi, F.A. & Gabet, Y. Collaborative cross mice in a genetic association study reveal new candidate genes for bone microarchitecture. BMC Genomics 16, 1013 (2015).
Ringwald, M. et al. The IKMC web portal: a central point of entry to data and resources from the International Knockout Mouse Consortium. Nucleic Acids Res. 39, D849–D855 (2011).
Karp, N.A., Melvin, D., Sanger Mouse Genetics Project & Mott, R.F. Robust and sensitive analysis of mouse knockout phenotypes. PLoS One 7, e52410 (2012).
Sayers, E.W. et al. Database resources of the National Center for Biotechnology Information. Nucleic Acids Res. 40, D13–D25 (2012).
Binns, D. et al. QuickGO: a web-based tool for Gene Ontology searching. Bioinformatics 25, 3045–3046 (2009).
Acknowledgements
This work was supported by NIH grants U54 HG006370 (T.F.M., P.F., A.-M.M., H.P., D.S. and S.D.M.B.), U42 OD011185 (S.A.M.), U54 HG006332 (R.E.B. and K.L.S.), U54 HG006348-S1 and OD011174 (A.L.B.), 1R24OD011883 (C.J.M., M.H., N.W. and D.S.), HG006364-03S1, U54H G006364 (K.C.K.L. and C.M.) and U42 OD011175 (C.M. and K.C.K.L.). Additional support was provided by the Wellcome Trust, Medical Research Council Strategic Award 53658 (S.W. and S.D.M.B.); the government of Canada through Genome Canada and Ontario Genomics (OGI-051) (C.M. and S.D.M.B.); the National Centre for Scientific Research (CNRS); the French National Institute of Health and Medical Research (INSERM); the University of Strasbourg (UDS); the Centre Européen de Recherche en Biologie et en Médecine; the Agence Nationale de la Recherche under the framework program Investissements d'Avenir labeled ANR-10-IDEX-0002-02, ANR-10-INBS-07 PHENOMIN (Y.H.); the German Federal Ministry of Education and Research through Infrafrontier grant 01KX1012 (S.A.M., V.G.-D. and M.H.d.A.); and the 'EUCOMM: Tools for Functional Annotation of the Mouse Genome' (EUCOMMTOOLS) project, grant agreement FP7-HEALTH-F4-2010-261492 (W.W.).
Author information
Authors and Affiliations
Consortia
Contributions
T.F.M., D.B.W., N.C. and D. Smedley contributed to data analysis, writing the paper and the design and execution of the work. N.H., M.H., N.W., C.J.M., P.M., J.O.J., C.-K.C., I.T., H.M., M.R., N.K., J.W., H.W., J.M. and D. Sneddon contributed to development of the software, statistical analysis, database and APIs. L.S., T.F., N.R. and S.G. performed quality control of the phenotype data. J.B., J.K.W., S.Y.C., G.F.C., M.E.S., C.L.R., J.G., V.G.-D., T.S., G.P. and L.R.B. led the experimental work and data production. I.M., J.S., A.B., M.E.D., M.H.d.A., M.M., Y.H., G.P.T.-V., K.C.K.L., X.G., C.M., M.J.J., S.A.M., K.L.S., R.E.B., S.W., A.-M.M., P.F., H.P., J.W., A.L.B., W.C.S., D.J.A., S.D.M.B., W.W., S.N., A.M.F., L.M.J.N., Y.O. and J.K.S. were senior principal investigators of the key programs that contributed to the paper and were critical in the design, management and execution of the study, and the writing and reviewing of the manuscript. The additional IMPC consortium members all contributed to data acquisition and data handling.
Corresponding author
Ethics declarations
Competing interests
The authors declare no competing financial interests.
Additional information
A full list of members and affiliations appears in the Supplementary Note.
Integrated supplementary information
Supplementary Figure 1 Precision and recall of the automated PhenoDigm algorithm.
IMPC mouse strains were ranked by the PhenoDigm algorithm for diseases involved in 650 known gene associations from OMIM and Orphanet then the precision and recall of the lines involving the orthologue of the known disease gene were plotted. Performance was measured where models were excluded below a threshold of either 1.0, 1.25, 1.35, 1.5 or 1.75 for the geometric mean of the information content and Jaccard index of the best phenotype match.
Supplementary information
Supplementary Text and Figures
Supplementary Figure 1 and Supplementary Note. (PDF 259 kb)
Supplementary Table 1
Reproducibility of 2547 MGI curated gene–phenotype associations that have also been assessed by the IMPC. (XLSX 114 kb)
Supplementary Table 2
Comparison of human mendelian disease caused by known gene mutations with targeted null mice. (XLSX 82 kb)
Supplementary Table 3
Summary of phenotypes for human mendelian disease mapping to mouse mutations with adult mutant phenotypes. (XLSX 53 kb)
Supplementary Table 4
Manual curation of human disease and mouse phenotypes for 100 genes. (XLSX 66 kb)
Supplementary Table 5
Mutant mouse gene IDs with phenotypes having no or minimal Gene Ontology annotations. (XLSX 164 kb)
Supplementary Table 6
Candidate genes for genetically mapped human mendelian disease. (XLSX 51 kb)
Supplementary Table 7
Contributing institute animal welfare approvals. (XLSX 10 kb)
Rights and permissions
About this article
Cite this article
Meehan, T., Conte, N., West, D. et al. Disease model discovery from 3,328 gene knockouts by The International Mouse Phenotyping Consortium. Nat Genet 49, 1231–1238 (2017). https://doi.org/10.1038/ng.3901
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1038/ng.3901
- Springer Nature America, Inc.
This article is cited by
-
Multiple reaction monitoring assays for large-scale quantitation of proteins from 20 mouse organs and tissues
Communications Biology (2024)
-
Commentary: The International Mouse Phenotyping Consortium: high-throughput in vivo functional annotation of the mammalian genome
Mammalian Genome (2024)
-
Spatiotemporal transcriptomic maps of whole mouse embryos at the onset of organogenesis
Nature Genetics (2023)
-
Exploring scavenger receptor class F member 2 and the importance of scavenger receptor family in prediagnostic diseases
Toxicological Research (2023)
-
Sequence variants in different genes underlying Bardet-Biedl syndrome in four consanguineous families
Molecular Biology Reports (2023)