Drift and Directional Selection Are the Evolutionary Forces Driving Gene Expression Divergence in Eye and Brain Tissue of Heliconius Butterflies

By Catalán, Ana; Briscoe, Adriana D. et al. | Genetics, October 2019 | Go to article overview

Drift and Directional Selection Are the Evolutionary Forces Driving Gene Expression Divergence in Eye and Brain Tissue of Heliconius Butterflies


Catalán, Ana, Briscoe, Adriana D., Höhna, Sebastian, Genetics


Species and populations diverge through the accumulation of genetic changes that affect coding or non-coding genomic regions that Genetic variation affecting gene expression has the potential of changing gene expression patterns in a spatiotemporal manner by changing gene expression profiles in specific organs and cell types at particular developmental stages (Carroll 2005; Signor and Nuzhdin 2018). This spatiotemporal attribute of gene expression might enable evolutionary change in a compartmentalized manner, allowing for change where it is required but also allowing for the needed processes to remain conserved. Phenotypic diversity caused by changes in gene expression encompasses a great variety of traits, including changes affecting an organism's coloration (Nadeau 2016), size, and shape (Ahi et al. 2017), as well as sensory perception and behavior, among other phenotypes (Lee et al. 2000; Wanner et al. 2007). Even though major advances have been made in linking gene expression variation to a phenotype (Catalán et al. 2016; Glaser-Schmitt and Parsch 2018), discerning the evolutionary forces that shape gene expression level variation among closely related species is an area that needs further research.

To understand the evolutionary forces acting on gene expression it is necessary to model within- and between-species gene expression variance. Neutral gene expression divergence between species leads to gene expression differences through divergence alone. Thus, neutral changes in gene expression provide a null hypothesis to detect deviations from the expected neutral gene expression divergence. A linear relationship between divergence time and gene expression variance has been proposed for closely related species, assuming a clock-like (i.e., constant through time) rate of gene expression divergence (Khaitovich et al. 2004, 2005a). Another approach to study the evolutionary forces shaping gene expression evolution, which is motivated by statistical phylogenetics, is fitting Brownian motion (BM) models. BM models are often used to describe the rate of change of continuous traits through time taking into account the known phylogeny of the taxa of interest (Felsenstein 1985). Thus, in a BM context, the parameter s2 is often described as the volatility parameter that determines the rate at which a trait's value diffuses away from its current state (Bedford and Hartl 2009). Fitting BM models to investigate gene expression evolution has shown that stabilizing selection and evolution through drift can be readily characterized (Kalinka et al. 2010; Wong etai. 2015).

Ornstein-Uhlenbeck (OU) models have also been used to study continuous trait evolution in a phylogenetic context (Hansen 1997; Butler and King 2004). OU models, an extension to BM models, include two extra parameters, a and 0. As in a BM context, s2 is the rate at which a trait changes through time and the parameter a is the force pulling back the diffused trait to an optimum state. This is analogous to stabilizing selection pulling back a trait to its optimum value after having experienced a departure from it. 0 is described as the trait's optimum state at a particular time point toward which the pull of a is aimed (Hansen 1997; Butler and King 2004). OU models offer a useful framework to generate hypotheses about the evolutionary forces acting on transcriptome levels, whether it is drift, stabilizing selection, or directional selection (Bedford and Hartl 2009; Rohlfs and Nielsen 2015; Wong et al. 2015; Chen et al. 2017; Stern and Crandall 2018).

In this study, we used five closely related species of Heliconius butterflies to explore the evolutionary forces shaping gene expression variation in combined eye and brain tissue. Heliconius charithonia, H. sara, H. erato, H. melpomene, and H. doris (Figure 1) belong to four of the seven distinct Heliconius phylogenetic clades with divergence times ranging from 5.5 to 11.8 MYA. Beside showing great diversity in wing color patterns (Kronforst and Papa 2015), Heliconius butterflies also show diversity in life history traits (Salcedo 2010; Merrill et al. …

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