Quantitative Genetic Analysis Indicates Natural Selection on Leaf Phenotypes Across Wild Tomato Species (Solanumsect.Lycopersicon; Solanaceae)

Abstract

Adaptive evolution requires both raw genetic material and an accessible path of high fitness from one fitness peak to another. In this study, we used an introgression line (IL) population to map quantitative trait loci (QTL) for leaf traits thought to be associated with adaptation to precipitation in wild tomatoes (Solanum sect. Lycopersicon; Solanaceae). A QTL sign test showed that several traits likely evolved under directional natural selection. Leaf traits correlated across species do not share a common genetic basis, consistent with a scenario in which selection maintains trait covariation unconstrained by pleiotropy or linkage disequilibrium. Two large effect QTL for stomatal distribution colocalized with key genes in the stomatal development pathway, suggesting promising candidates for the molecular bases of adaptation in these species. Furthermore, macroevolutionary transitions between vastly different stomatal distributions may not be constrained when such large-effect mutations are available. Finally, genetic correlations between stomatal traits measured in this study and data on carbon isotope discrimination from the same ILs support a functional hypothesis that the distribution of stomata affects the resistance to CO 2 diffusion inside the leaf, a trait implicated in climatic adaptation in wild tomatoes. Along with evidence from previous comparative and experimental studies, this analysis indicates that leaf traits are an important component of climatic niche adaptation in wild tomatoes and demonstrates that some trait transitions between species could have involved few, large-effect genetic changes, allowing rapid responses to new environmental conditions. T HE course of phenotypic evolution depends upon both the genetic basis of functionally important traits and the mechanistic relationship between traits. All else being equal, traits governed by mutations of large phenotypic effect with low pleiotropy can respond to selection more readily than traits that are complex, highly pleiotropic, and/or strongly correlated with other traits. Hence, the genetic basis of trait differences and covariation influences which phenotypic axes are most likely to respond to selection in new environmental conditions; understanding this underlying architecture therefore provides insight into the genetic mechanisms constraining or facilitating phenotypic evolution (Lee et al. 2014). It can also indicate which evolutionary forces are responsible for trait differences within and between species. When adaptation to a complex ecological niche involves many traits, for example, genetic analysis can determine whether correlations between traits are caused by a shared genetic basis (pleiotropy) or whether natural selection favors trait combinations because they function well together (coselection). The magnitude and direction of allelic effects between phenotypically divergent genotypes can also be used to infer whether this divergence is consistent with directional natural selection (Orr 1998b;Rieseberg et al. 2002)...

Making pore choices: repeated regime shifts in stomatal ratio

“…However, there is little evidence for non-selective constraints on SR, whereas selection explains the precise position of modes in the trait distribution and the association with growth form. Although the molecular mechanisms have not been identified, plants exhibit the ability to fine-tune SR through independent control of upper and lower stomatal densities: loci capable of generating intermediate SR phenotypes occur spontaneously during mutagenesis [45], segregate among natural populations [24,46,47] and are fixed between closely related species [25,48]. That such intermediate phenotypes are rare in nature implicates selective constraint.…”

“…If it is generally true that multimodal traits are associated with rapid regime shifts, then one way forward is to look for signatures of such shifts in closely related species that sit astride different regimes. For example, Muir et al [25] recently identified two large effect loci that together account for the phenotypic difference between hypostomatous and amphistomatous species, perhaps suggesting that these loci enabled a regime shift. Integrating comparative biology, mechanistic studies of organismal function and the genetics of adaptation points to a general approach for evaluating the common features of macroevolutionary adaptive landscapes and, hence, the role of selection in constraining phenotypic evolution.…”

“…SR varies widely, but non-randomly [13,17,19,[21][22][23] and evolves rapidly in some taxa, possibly owing to selection [24,25]. Several environmental and anatomical factors have been hypothesized to favour amphistomy (table 1).…”

eQTL Regulating Transcript Levels Associated with Diverse Biological Processes in Tomato

“…Previous phenotypic and QTL analyses identified many ILs, such as IL4.3, IL8.1.5, IL8.1.1, and IL8.1, harboring loci regulating leaf and plant developmental traits (Holtan and Hake, 2003;Muir et al, 2014). IL4.3, which harbors loci with the largest contribution to leaf shape and shows larger epidermal cell sizes , exhibited decreased steady-state transcript levels for many genes associated with cell division, such as Cyclin-dependent protein kinase regulator-like protein (CYCA2;3), Cyclin A-like protein (CYCA3;1), and F-box/LRR-repeat protein 2 SKP2A (Supplemental Data Sets S1 and S10).…”

“…ILs developed from the wild desert-adapted species Solanum pennellii and domesticated Solanum lycopersicum cv M82 have proved to be a useful genetic resource (Eshed and Zamir, 1995;Liu and Zamir, 1999). This population has been successfully used to map numerous QTL for metabolites, enzymatic activity, yield, fitness traits, and developmental features, such as leaf shape, size, and complexity (Frary et al, 2000;Holtan and Hake, 2003;Fridman et al, 2004;Muir et al, 2014). Comparative transcriptomics for the two parents enabled identification of transcript abundance variation potentially underlying trait differences between species .…”