No Expression Divergence despite Transcriptional Interference between Nested Protein-Coding Genes in Mammals

Nested protein-coding genes accumulated throughout metazoan evolution, with early analyses of human and Drosophila microarray data indicating that this phenomenon was simply due to the presence of large introns. However, a recent study employing RNA-seq data uncovered evidence of transcriptional interference driving rapid expression divergence between Drosophila nested genes, illustrating that accurate expression estimation of overlapping genes can enhance detection of their relationships. Hence, here I apply an analogous approach to strand-specific RNA-seq data from human and mouse to revisit the role of transcriptional interference in the evolution of mammalian nested genes. A genomic survey reveals that whereas mammalian nested genes indeed accrued over evolutionary time, they are retained at lower frequencies than in Drosophila. Though several properties of mammalian nested genes align with observations in Drosophila and with expectations under transcriptional interference, contrary to both, their expression divergence is not statistically different from that between unnested genes, and also does not increase after nesting. Together, these results support the hypothesis that lower selection efficiencies limit rates of gene expression evolution in mammals, leading to their reliance on immediate eradication of deleterious nested genes to avoid transcriptional interference.

Tempo and mode of gene expression evolution in the brain across Primates

Primate evolution has led to a remarkable diversity of behavioral specializations and pronounced brain size variation among species 1,2. Gene expression provides a promising opportunity for studying the molecular basis of brain evolution, but it has been explored in very few primate species to date e.g. 3,4. To understand the landscape of gene expression evolution across the primate lineage, we generated and analyzed RNA-Seq data from four brain regions in an unprecedented eighteen species. Here we show a remarkable level of variation in gene expression among hominid species, including humans and chimpanzees, despite their relatively recent divergence time from other primates. We found that individual genes display a wide range of expression dynamics across evolutionary time reflective of the diverse selection pressures acting on genes within primate brain tissue. Using our sample that represents an unprecedented 190-fold difference in primate brain size, we identified genes with variation in expression most correlated with brain size and found several with signals of positive selection in their regulatory regions. Our study extensively broadens the context of what is known about the molecular evolution of the brain across primates and identifies novel candidate genes for study of genetic regulation of brain development and evolution.

Amalgamated cross-species transcriptomes reveal organ-specific propensity in gene expression evolution

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.

Modeling gene expression evolution with EvoGeneX uncovers differences in evolution of species, organs and sexes

While DNA sequence evolution has been well studied, the expression of genes is also subject to evolution. Yet the evolution of gene expression is currently not well understood. In recent years, new tissue/organ specific gene expression datasets spanning several organisms across the tree of life, have become available providing the opportunity to study gene expression evolution in more detail. However, while a theoretical model to study evolution of continuous traits exist, in practice computational methods often cannot distinguish, with confidence, between alternative evolutionary scenarios. This lack of power has been attributed to the modest number of species with available expression data.To solve this challenge, we introduce EvoGeneX, a computationally efficient method to uncover the mode of gene expression evolution based on the Ornstein-Uhlenbeck process. Importantly, EvoGeneX in addition to modelling expression variations between species, models within species variation. To estimate the within species variation, EvoGeneX formally incorporates the data from biological replicates as a part of the mathematical model. We show that by modelling the within species diversity EvoGeneX significantly outperforms the currently available computational method. In addition, to facilitate comparative analysis of gene expression evolution, we introduce a new approach to measure the dynamics of evolutionary divergence of a group of genes.We used EvoGeneX to analyse the evolution of expression across different organs, species and sexes of the Drosophila genus. Our analysis revealed differences in the evolutionary dynamics of male and female gonads, and uncovered examples of adaptive evolution of genes expressed in the head and in the thorax.

Non-parallel transcriptional divergence during parallel adaptation

How underlying mechanisms bias evolution toward predictable outcomes remains an area of active debate. In this study, we leveraged phenotypic plasticity and parallel adaptation across independent lineages of Trinidadian guppies (Poecilia reticulata) to assess the predictability of gene expression evolution during parallel adaptation. Trinidadian guppies have repeatedly and independently adapted to high- and low-predation environments in the wild. We combined this natural experiment with a laboratory breeding design to attribute transcriptional variation to the genetic influences of population of origin and developmental plasticity in response to rearing with or without predators. We observed substantial gene expression plasticity as well as the evolution of expression plasticity itself across populations. Genes exhibiting expression plasticity within populations were more likely to also differ in expression between populations, with the direction of population differences more likely to be opposite those of plasticity. While we found more overlap than expected by chance in genes differentially expressed between high- and low-predation populations from distinct evolutionary lineages, the majority of differentially expressed genes were not shared between lineages. Our data suggest alternative transcriptional configurations associated with shared phenotypes, highlighting a role for transcriptional flexibility in the parallel phenotypic evolution of a species known for rapid adaptation.

Drift and directional selection are the evolutionary forces driving gene expression divergence in eye and brain tissue ofHeliconiusbutterflies

Investigating gene expression evolution over micro- and macroevolutionary timescales will expand our understanding of the role of gene expression in adaptation and speciation. In this study, we characterized which evolutionary forces are acting on gene expression levels in eye and brain tissue of fiveHeliconiusbutterflies with divergence times of ~5-12 MYA. We developed and applied Brownian motion and Ornstein-Uhlenbeck models to identify genes whose expression levels are evolving through drift, stabilizing selection, or a lineage-specific shift. We find that 81% of the genes evolve under genetic drift. When testing for branch-specific shifts in gene expression, we detected 368 (16%) shift events. Genes showing a shift towards up-regulation have significantly lower gene expression variance than those genes showing a shift leading towards down-regulation. We hypothesize that directional selection is acting in shifts causing up-regulation, since transcription is costly. We further uncover through simulations that parameter estimation of Ornstein-Uhlenbeck models is biased when using small phylogenies and only becomes reliable with phylogenies having at least 50 taxa. Therefore, we developed a new statistical test based on Brownian motion to identify highly conserved genes (i.e., evolving under strong stabilizing selection), which comprised 3% of the orthoclusters. In conclusion, we found that drift is the dominant evolutionary force driving gene expression evolution in eye and brain tissue inHeliconius. Nevertheless, the higher proportion of genes evolving under directional than under stabilizing selection might reflect species-specific selective pressures on vision and brain necessary to fulfill species-specific requirements.