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The use of standardised phenotyping screens to identify abnormal phenotypes in mouse knockouts, together with the use of ontologies to describe such phenotypic features, allows the implementation of an automated and unbiased pipeline to identify new models of disease by performing phenotype comparisons across species. Using data from the International Mouse Phenotyping Consortium (IMPC), approximately half of mouse mutants are able to mimic, at least partially, the human ortholog disease phenotypes as computed by the PhenoDigm algorithm. We found the number of phenotypic abnormalities in the mouse and the corresponding Mendelian disorder, the pleiotropy and severity of the disease, and the viability and zygosity status of the mouse knockout to be associated with the ability of mouse models to recapitulate the human disorder. An analysis of the IMPC impact on disease gene discovery through a publication-tracking system revealed that the resource has been implicated in at least 109 validated rare disease–gene associations over the last decade.

Mouse models are relevant to studying the functionality of genes involved in human diseases; however, translation of phenotypes can be challenging. Here, we investigated genes related to monogenic forms of cardiovascular disease based on the Genomics England PanelApp and aligned them to International Mouse Phenotyping Consortium (IMPC) data. We found 153 genes associated with cardiomyopathy, cardiac arrhythmias or congenital heart disease in humans, of which 151 have one-to-one mouse orthologues. For 37.7% (57/151), viability and heart data captured by electrocardiography, transthoracic echocardiography, morphology and pathology from embryos and young adult mice are available. In knockout mice, 75.4% (43/57) of these genes showed non-viable phenotypes, whereas records of prenatal, neonatal or infant death in humans were found for 35.1% (20/57). Multisystem phenotypes are common, with 58.8% (20/34) of heterozygous (homozygous lethal) and 78.6% (11/14) of homozygous (viable) mice showing cardiovascular, metabolic/homeostasis, musculoskeletal, hematopoietic, nervous system and/or growth abnormalities mimicking the clinical manifestations observed in patients. These IMPC data are critical beyond cardiac diagnostics given their multisystemic nature, allowing detection of abnormalities across physiological systems and providing a valuable resource to understand pleiotropic effects.

Protein coding genes exhibit different degrees of intolerance to loss-of-function variation. The most intolerant genes, whose function is essential for cell or/and organism survival, inform on fundamental biological processes related to cell proliferation and organism development and provide a window on the molecular mechanisms of human disease. Here we present a brief overview of the resources and knowledge gathered around gene essentiality, from cancer cell lines to model organisms to human development. We outline the implications of using different sources of evidence and definitions to determine which genes are essential and highlight how information on the essentiality status of a gene can inform novel disease gene discovery and therapeutic target identification.

SPTBN1 encodes βII-spectrin, the ubiquitously expressed β-spectrin that forms micrometer-scale networks associated with plasma membranes. Mice deficient in neuronal βII-spectrin have defects in cortical organization, developmental delay and behavioral deficiencies. These phenotypes, while less severe, are observed in haploinsufficient animals, suggesting that individuals carrying heterozygous SPTBN1 variants may also show measurable compromise of neural development and function. Here we identify heterozygous SPTBN1 variants in 29 individuals with developmental, language and motor delays; mild to severe intellectual disability; autistic features; seizures; behavioral and movement abnormalities; hypotonia; and variable dysmorphic facial features. We show that these SPTBN1 variants lead to effects that affect βII-spectrin stability, disrupt binding to key molecular partners, and disturb cytoskeleton organization and dynamics. Our studies define SPTBN1 variants as the genetic basis of a neurodevelopmental syndrome, expand the set of spectrinopathies affecting the brain and underscore the critical role of βII-spectrin in the central nervous system. SPTBN1 mutations cause a neurodevelopmental syndrome characterized by intellectual disability, language and motor delays, autism, seizures and other features. The variants disrupt βII-spectrin function and disturb cytoskeletal organization and dynamics.

The identification of causal variants in sequencing studies remains a considerable challenge that can be partially addressed by new gene-specific knowledge. Here, we integrate measures of how essential a gene is to supporting life, as inferred from viability and phenotyping screens performed on knockout mice by the International Mouse Phenotyping Consortium and essentiality screens carried out on human cell lines. We propose a cross-species gene classification across the Fu ll S pectrum of I ntolerance to L oss-of-function (FUSIL) and demonstrate that genes in five mutually exclusive FUSIL categories have differing biological properties. Most notably, Mendelian disease genes, particularly those associated with developmental disorders, are highly overrepresented among genes non-essential for cell survival but required for organism development. After screening developmental disorder cases from three independent disease sequencing consortia, we identify potentially pathogenic variants in genes not previously associated with rare diseases. We therefore propose FUSIL as an efficient approach for disease gene discovery. Discovery of causal variants for monogenic disorders has been facilitated by whole exome and genome sequencing, but does not provide a diagnosis for all patients. Here, the authors propose a Full Spectrum of Intolerance to Loss-of-Function (FUSIL) categorization that integrates gene essentiality information to aid disease gene discovery.

The International Mouse Phenotyping Consortium (IMPC) is building a catalogue of mammalian gene function by producing and phenotyping a knockout mouse line for every protein-coding gene. To date, the IMPC has generated and characterised 5186 mutant lines. One-third of the lines have been found to be non-viable and over 300 new mouse models of human disease have been identified thus far. While current bioinformatics efforts are focused on translating results to better understand human disease processes, IMPC data also aids understanding genetic function and processes in other species. Here we show, using gorilla genomic data, how genes essential to development in mice can be used to help assess the potentially deleterious impact of gene variants in other species. This type of analyses could be used to select optimal breeders in endangered species to maintain or increase fitness and avoid variants associated to impaired-health phenotypes or loss-of-function mutations in genes of critical importance. We also show, using selected examples from various mammal species, how IMPC data can aid in the identification of candidate genes for studying a condition of interest, deliver information about the mechanisms involved, or support predictions for the function of genes that may play a role in adaptation. With genotyping costs decreasing and the continued improvements of bioinformatics tools, the analyses we demonstrate can be routinely applied.

The International Mouse Phenotyping Consortium (IMPC) continues to expand the catalogue of mammalian gene function by conducting genome and phenome-wide phenotyping on knockout mouse lines. The extensive and standardized phenotype screens allow the identification of new potential models for human disease through cross-species comparison by computing the similarity between the phenotypes observed in the mutant mice and the human phenotypes associated to their orthologous loci in Mendelian disease. Here, we present an update on the novel disease models available from the most recent data release (DR10.0), with 5861 mouse genes fully or partially phenotyped and a total number of 69,982 phenotype calls reported. With approximately one-third of human Mendelian genes with orthologous null mouse phenotypes described, the range of available models relevant for human diseases keeps increasing. Among the breadth of new data, we identify previously uncharacterized disease genes in the mouse and additional phenotypes for genes with existing mutant lines mimicking the associated disorder. The automated and unbiased discovery of relevant models for all types of rare diseases implemented by the IMPC constitutes a powerful tool for human genetics and precision medicine.

Background The diagnostic rate of Mendelian disorders in sequencing studies continues to increase, along with the pace of novel disease gene discovery. However, variant interpretation in novel genes not currently associated with disease is particularly challenging and strategies combining gene functional evidence with approaches that evaluate the phenotypic similarities between patients and model organisms have proven successful. A full spectrum of intolerance to loss-of-function variation has been previously described, providing evidence that gene essentiality should not be considered as a simple and fixed binary property. Methods Here we further dissected this spectrum by assessing the embryonic stage at which homozygous loss-of-function results in lethality in mice from the International Mouse Phenotyping Consortium, classifying the set of lethal genes into one of three windows of lethality: early, mid, or late gestation lethal. We studied the correlation between these windows of lethality and various gene features including expression across development, paralogy and constraint metrics together with human disease phenotypes. We explored a gene similarity approach for novel gene discovery and investigated unsolved cases from the 100,000 Genomes Project. Results We found that genes in the early gestation lethal category have distinct characteristics and are enriched for genes linked with recessive forms of inherited metabolic disease. We identified several genes sharing multiple features with known biallelic forms of inborn errors of the metabolism and found signs of enrichment of biallelic predicted pathogenic variants among early gestation lethal genes in patients recruited under this disease category. We highlight two novel gene candidates with phenotypic overlap between the patients and the mouse knockouts. Conclusions Information on the developmental period at which embryonic lethality occurs in the knockout mouse may be used for novel disease gene discovery that helps to prioritise variants in unsolved rare disease cases.

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The International Mouse Phenotyping Consortium (IMPC; https://www.mousephenotype.org/) web portal contains phenotype data for mouse protein-coding genes derived from analysis of data obtained in a systematic and high-throughput fashion from knock-out lines produced by IMPC. The project has produced >1,400 mouse models of human disease that recapitulate phenotypes observed in patients. Over 8000 papers rely on data or reagents generated by IMPC, demonstrating the impact of the project on the research and clinical communities, and IMPC data is incorporated into other resources, such as MGI, Open Targets and UniProt. Data release (DR23.0, 2025) contains > 100 million data points from 9,277 genes and identified 113,803 significant phenotypes. To manage efficient access to this quantity of high dimensional data the IMPC web portal has been rebuilt using a cloud native architecture. The modern user interface retains the look and feel of the original portal with improvements identified through a usability study. New data visualisation and training materials for large scale data access through the API have also been developed to make the resource easier to use.