Cell atlases and the developmental foundations of the phenotype

It is widely acknowledged that development shapes phenotypes, yet the extent to which genes with similar expression patterns during development lead to equivalent organismal phenotypes when mutated remains unclear. Here, we propose addressing this issue, which we term the [Formula: see text]evelopment-to-[Formula: see text]henotype, or [Formula: see text]-[Formula: see text], rule, by leveraging single-cell gene expression atlases and phenotypic ontologies, using Caenorhabditis elegans as a model system. This framework quantifies the proportionality between developmental expression and phenotypic similarities, demonstrating that the relationship holds on average. Genes that strongly fulfill the rule exhibit broad "housekeeping" expression and are associated with systemic phenotypes, whereas weak similarities correspond to specific expression patterns and specialized phenotypes. Deviations from the [Formula: see text]-[Formula: see text] rule provide insights into developmental divergence and phenotypic degeneracy, highlighting genes with narrow functional roles but systemic phenotypic impact. Furthermore, genes that closely adhere to the rule exhibit the highest pleiotropic impact on organismal traits. Our analysis also identifies cell types, such as ASK neurons, as key mediators of phenotype-specific gene contributions, exemplified by their association with chemosensory behavior and chemotaxis. These findings validate the [Formula: see text]-[Formula: see text] rule and underscore the role of cells as critical mediators of the genotype-phenotype map, offering a unified framework to understand the developmental origins of phenotypic complexity.

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Publication Details

Journal
PLoS Computational Biology
Published
2026-02-09
DOI
https://doi.org/10.1371/journal.pcbi.1013944
Primary Topic
Developmental Biology and Gene Regulation
Type
article
Field-Weighted Citation Impact
0.00

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article

Cell atlases and the developmental foundations of the phenotype

Juan F. Poyatos, Alicia Lou
PLoS Computational Biology
Developmental Biology and Gene Regulation
article

Cell atlases and the developmental foundations of the phenotype

Juan F. Poyatos, Alicia Lou
article en

Abstract

It is widely acknowledged that development shapes phenotypes, yet the extent to which genes with similar expression patterns during development lead to equivalent organismal phenotypes when mutated remains unclear. Here, we propose addressing this issue, which we term the [Formula: see text]evelopment-to-[Formula: see text]henotype, or [Formula: see text]-[Formula: see text], rule, by leveraging single-cell gene expression atlases and phenotypic ontologies, using Caenorhabditis elegans as a model system. This framework quantifies the proportionality between developmental expression and phenotypic similarities, demonstrating that the relationship holds on average. Genes that strongly fulfill the rule exhibit broad "housekeeping" expression and are associated with systemic phenotypes, whereas weak similarities correspond to specific expression patterns and specialized phenotypes. Deviations from the [Formula: see text]-[Formula: see text] rule provide insights into developmental divergence and phenotypic degeneracy, highlighting genes with narrow functional roles but systemic phenotypic impact. Furthermore, genes that closely adhere to the rule exhibit the highest pleiotropic impact on organismal traits. Our analysis also identifies cell types, such as ASK neurons, as key mediators of phenotype-specific gene contributions, exemplified by their association with chemosensory behavior and chemotaxis. These findings validate the [Formula: see text]-[Formula: see text] rule and underscore the role of cells as critical mediators of the genotype-phenotype map, offering a unified framework to understand the developmental origins of phenotypic complexity.

PLoS Computational BiologyVol. 22(2)
Centro Nacional de Biotecnología (ES)
Ministerio de Ciencia e Innovación, European Regional Development Fund, Agencia Estatal de Investigación
Openalex Percentile: Top 62%
Developmental Biology and Gene Regulation
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