Abstract
The origins of multicellular physiology are tied to evolution of gene expression. Genes can shift expression as organisms evolve, but how ancestral expression influences altered descendant expression is not well understood. To examine this, we amalgamate 1,903 RNA-seq datasets from 182 research projects, including 6 organs in 21 vertebrate species. Quality control eliminates project-specific biases, and expression shifts are reconstructed using gene-family-wise phylogenetic Ornstein–Uhlenbeck models. Expression shifts following gene duplication result in more drastic changes in expression properties than shifts without gene duplication. The expression properties are tightly coupled with protein evolutionary rate, depending on whether and how gene duplication occurred. Fluxes in expression patterns among organs are nonrandom, forming modular connections that are reshaped by gene duplication. Thus, if expression shifts, ancestral expression in some organs induces a strong propensity for expression in particular organs in descendants. Regardless of whether the shifts are adaptive or not, this supports a major role for what might be termed preadaptive pathways of gene expression evolution.
Highlights
The origins of multicellular physiology are tied to evolution of gene expression
Gene duplication is well-known to play an important role in expression pattern shifts, the evolutionary dynamics of expression patterns with and without gene duplication remain poorly understood
Our results suggest that the landscape of expression evolution is strongly shaped by mechanisms of gene birth
Summary
The origins of multicellular physiology are tied to evolution of gene expression. Genes can shift expression as organisms evolve, but how ancestral expression influences altered descendant expression is not well understood. A possible theoretical basis for such predisposition is the idea that certain preexisting adapted states are more conducive to evolution of specific new traits than other preexisting states This is known as preadaptation, and when a trait makes such a shift it is referred to as exaptation[12]. Protein sequence evolution generally involves highly epistatic interactions and context-dependent changes[15,16] that affect preadaptation, but the modular nature of expression regulation[17] makes it unclear whether preexisting expression patterns constrain evolutionary outcomes. Phylogenetic approaches model gene expression dynamics and infer ancestral expression patterns in the context of gene phylogenies. Each gene family has a distinct evolutionary history, a species phylogeny is often used for the sake of simplicity Because such approximations cannot be applied to gene families with lineage-specific gene duplications and losses, its application has mostly been limited to single-copy genes. We develop a curation pipeline to amalgamate large amounts of transcriptome data from many studies for a better phylogenetic resolution
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