Gene Expression Trajectories Aiding the Unveiling of Phenotypic Similarities in Developmental Disorders: Insights from Human-Mouse Comparative Analysis
PEDIATRIC MEDICINE(2023)
Abstract
Background: Developmental disorders result from impaired prenatal development, often attributed to deleterious genetic variations. Knockout mouse models are critical tools in diseases research, but null mutations of orthologous genes in humans and mice often resulted in different phenotypes. As phenotypes are described during developmental processes, we explored the temporal patterns of gene expression trajectories during development. Methods: We utilized Spearman correlation analysis to compute the expression similarity of orthologous genes in temporal expression data of humans and mice. Gene list associated with developmental disorders was downloaded from the Developmental Disorders Genotype -to -Phenotype (DDG2P) database and classified according to the full spectrum of intolerance to loss -of -function (FUSIL) categorization. The phenotypic similarities of orthologous genes were quantified using Phenodigm scores derived from the calculations based on Human Phenotype Ontology (HPO) and Model Phenotype Ontology (MPO) terms. The phenotypic similarities of ionotropic glutamate receptors (iGluRs) genes with protein -truncating variants (PTVs) were computed as refined Phenodigm scores, utilizing manually curated profiles from the HPO terms and MPO terms. Results: This study investigated the expression trajectories of DDG2P genes and their association with phenotypic similarities between humans and mice. We observed that DDG2P genes showed more similar expression trajectories in major tissues compared to non-DDG2P genes. Additionally, in DDG2P genes, viable with phenotype (VP) genes with similar expression trajectories in the brain exhibited analogous phenotypes across humans and mice (autosomal dominant genes: Wilcoxon test: Z =11, P=0.02; autosomal recessive genes: Wilcoxon test: Z =9, P=0.003). To illustrate the feasibility of utilizing gene expression trajectory similarity to assist in inferring phenotypic similarity, we examined a gene family associated with neurodevelopmental disorder. Our findings suggest that similar expression trajectories of iGluRs genes in the brain and cerebellum could assist in predicting comparable neurological phenotypes across species. Conclusions: The gene expression trajectory offered a potential elucidation for the disparate phenotypes observed due to null mutations in humans and mice. Leveraging gene expression trajectories might enhance the precision in predicting candidate pathogenic genes.
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Key words
Developmental disorders,mouse models,gene expression trajectories,phenotypic similarity
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