New metric tracking evolutionary constraints in 462 mammal species improves selection of rare genetic disease causative genes
Background
With advancements in next-generation sequencing technologies, the cost of decoding patient exomes or whole genomes has significantly decreased. However, accurately identifying the actual causative variants that induce diseases from genomic data remains a difficult challenge. Existing metrics built on human population genomic data have evaluated gene importance by measuring how much loss-of-function variants are depleted within a population. Representative examples include gnomAD's probability of loss-of-function intolerance (pLI) and the upper bound of the observed-to-expected ratio (LOEUF).
While these human population-based metrics have contributed to identifying genes for fatal severe diseases, they possess fundamental limitations. Due to the statistical limitations of sample sizes in human population data, it was difficult to statistically determine whether variant depletion was significant in genes with short sequence lengths. Genes subject to weak natural selection pressure, such as those associated with recessive genetic disorders or diseases that manifest in adulthood, were frequently omitted from analysis because the signal of variant depletion within the population was not distinct. Furthermore, there was a lack of tools to precisely evaluate the harmfulness of missense mutations—where a single amino acid changes—on protein function at the gene level.
Key Findings
The researchers expanded their focus from the population genomics of a single human species to all 462 mammal species. This was the background for developing GISMO and GISMO-mis, new metrics that measure gene essentiality by quantifying the purifying selection signals preserved across the mammalian evolutionary trajectory spanning approximately 100 million years. Based on multiple sequence alignment data of 462 mammal species, the research team quantified how strictly each gene-coding region has excluded mutations during the evolutionary process.
GISMO evaluates the intensity of evolutionary constraints across a gene, while GISMO-mis calculates a constraint index specialized for deleterious missense mutations that have significant impacts on protein structure and function. Analysis results showed that GISMO and GISMO-mis form a complementary relationship with existing human population-based metrics, significantly improving the discriminative power for gene deficiency. In more than 1,000 short protein-coding genes where it was difficult to distinguish essential genes using gnomAD metrics, GISMO captured distinct evolutionary conservation signals and accurately classified them as essential genes. This demonstrates that even if loss-of-function variants are rarely observed in human populations, regions with amino acid sequences strictly conserved throughout mammalian evolutionary history carry a high risk of disease.
The utility of the new metrics was also confirmed in the analysis of an actual cohort of patients with rare developmental disorders. When the research team re-analyzed data from neurodevelopmental disorder patients carrying de novo mutations using GISMO-mis, candidate causative genes that had remained low in priority with existing metrics were repositioned to the top. In particular, the accuracy of predicting the pathogenicity of missense mutations related to congenital heart defects and autism spectrum disorder showed a significant improvement compared to previous models.
Significance and Outlook
This study clearly demonstrates with robust data that the big data of comparative genomics can solve long-standing challenges in human genomics medicine. The 100-million-year natural filtration mechanism provided by the evolutionary data of 462 mammal species precisely fills the gaps that databases of hundreds of thousands of humans could not fill. It has opened a new analytical paradigm for discovering disease genes by integrating human population data with evolutionary conservation data.
Challenges also remain. While metrics based on interspecies comparisons are excellent for identifying fundamental biological mechanisms shared across all mammals, it is difficult to exclude the possibility that genes related to immune responses or higher brain functions uniquely developed in humans may be measured as having low evolutionary constraint. Follow-up research expanding the model to non-translated regulatory regions or non-coding RNA mutations is also required. Despite these constraints, if the GISMO metric group is incorporated into the pipeline for prioritizing disease candidate genes, it is expected to become a key asset in reducing the undiagnosed rate in the field of clinical genomic diagnosis.
Nature Genetics, Published online: 20 October 2026; doi:10.1038/s41588-026-02783-9GISMO and GISMO-mis are new metrics of evolutionary constraint developed across 462 mammalian species. These metrics provide complementary measures of gene essentiality and improve prioritization of human disease genes.
More than half of patients suspected of having rare diseases who request exome analysis in clinical settings remain undiagnosed because the causative variant cannot be identified. This is because many variants of uncertain significance (VUS), whose functions are not clearly understood, are detected. GISMO and GISMO-mis can be directly utilized as filters in the diagnostic pipeline to rapidly identify actual pathogenic variants among numerous VUS.
In the drug development industry, it also significantly reduces trial and error in the target discovery stage. If a specific gene shows a high GISMO score across mammals, the risk of inducing severe toxicity upon inhibiting that gene can be predicted in advance. Conversely, if a gene that appeared to have low importance in human population data shows high evolutionary constraint in diseased tissue, strategic decision-making becomes possible to prioritize it as a strong therapeutic target.