ArticleMolecular biology and evolution2014
Modeling gene expression evolution with an extended Ornstein-Uhlenbeck process accounting for within-species variation.
Article in Molecular biology and evolution, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 70 papers.
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70 citing papers in PubMed.
- Accelerated Evolution of Context-Dependent Gene Expression in Primate Immune Cells.bioRxiv : the preprint server for biology · 2026Article
- Lineage-aware stochastic modeling reveals gene-expression dynamics in development and disease.bioRxiv : the preprint server for biology · 2026Article
- Stabilizing and directional selection shape the genetic variation of gene expression in the transcriptome of Chlamydomonas.Molecular biology and evolution · 2026Article
- Discriminating models of trait evolution.Evolution; international journal of organic evolution · 2026Article
- Taxonomic variation in immune response strategies among primates.Genes and immunity · 2025Review
- Robust regression rescues poor phylogenetic decisions.BMC ecology and evolution · 2025Article
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- Integrating Intermediate Traits in Phylogenetic Genotype-to-Phenotype Studies.Integrative and comparative biology · 2025Review
- Rates of Evolution of Developmental Changes in Gene Expression in Sordariomycetes.Molecular biology and evolution · 2025Article
- Quantifying Transcriptome Turnover on Phylogenies by Modeling Gene Expression as a Binary Trait.Molecular biology and evolution · 2025Article
- Stochastic modeling of single-cell gene expression adaptation reveals non-genomic contribution to evolution of tumor subclones.Cell systems · 2025Article
- TraitTrainR: accelerating large-scale simulation under models of continuous trait evolution.Bioinformatics advances · 2025Article
- Where the "ruber" Meets the Road: Using the Genome of the Red Diamond Rattlesnake to Unravel the Evolutionary Processes Driving Venom Evolution.Genome biology and evolution · 2024Article
- Lineage-specific splicing regulation of MAPT gene in the primate brain.Cell genomics · 2024Article
- Stochastic modelling of single-cell gene expression adaptation reveals non-genomic contribution to evolution of tumor subclones.bioRxiv : the preprint server for biology · 2024Article
- Evolution of Transcript Abundance is Influenced by Indels in Protein Low Complexity Regions.Journal of molecular evolution · 2024Article
- Cell type evolution reconstruction across species through cell phylogenies of single-cell RNA sequencing data.Nature ecology & evolution · 2024Article
- Article
- Predicting evolutionary targets and parameters of gene deletion from expression data.Bioinformatics advances · 2024Article
- Evaluating the Performance of Widely Used Phylogenetic Models for Gene Expression Evolution.Genome biology and evolution · 2023Article
10 more citing papers are in PubMed but not listed here.
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3 authors.
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Abstract
Much of the phenotypic variation observed between even closely related species may be driven by differences in gene expression levels. The current availability of reliable techniques like RNA-Seq, which can quantify expression levels across species, has enabled comparative studies. Ornstein-Uhlenbeck (OU) processes have been proposed to model gene expression evolution as they model both random drift and stabilizing selection and can be extended to model changes in selection regimes. The OU models provide a statistical framework that allows comparisons of specific hypotheses of selective regimes, including random drift, constrained drift, and expression level shifts. In this way, inferences may be made about the mode of selection acting on the expression level of a gene. We augment this model to include within-species expression variance, allowing for modeling of nonevolutionary expression variance that could be caused by individual genetic, environmental, or technical variation. Through simulations, we explore the reliability of parameter estimates and the extent to which different selective regimes can be distinguished using phylogenies of varying size using both the typical OU model and our extended model. We find that if individual variation is not accounted for, nonevolutionary expression variation is often mistaken for strong stabilizing selection. The methods presented in this article are increasingly relevant as comparative expression data becomes more available and researchers turn to expression as a primary evolving phenotype.
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