Introduction
Phenotypic evolution is biased by the mechanisms that link genetic variation to phenotypic variation, i.e. the genotype-phenotype map (Alberch, 1991; Pigliucci, 2010). Mechanisms linking genotype to phenotype are characterized by both robustness and flexibility. Robust developmental processes buffer phenotypes from noise such that multiple transcriptional, biochemical, or cellular network configurations give rise to similar organismal phenotypes, while flexibility in these processes allows for phenotypic plasticity in response to environmental conditions (Marder & Goaillard, 2006; Siegal & Leu, 2014; Wagner, 2011). Though contrasting, both phenomena are ultimately bounded by phenotypic, developmental, genetic, and mechanistic constraints. The complex nature of the genotype-phenotype map and the existence of ‘many-to-one’ mappings across hierarchical levels of biological organization make it challenging to understand how mechanistic properties facilitate or constrain adaptive evolution. Here, we combine studies of phenotypic plasticity and parallel adaptation to assess how mechanistic biases shape evolutionary trajectories across timescales.
Studies of parallel adaptation can reveal biases in mechanisms of evolution by asking whether similar mechanism are associated with repeated, independent evolutionary transitions. Similar mechanisms underlying parallel evolutionary transitions suggest the genotype-phenotype map is constrained by limits on the possible ways to construct adaptive phenotypes (Losos, 2011). In contrast, non-shared mechanisms suggest that mechanistic flexibility may facilitate evolution by providing multiple alternative ‘solutions’ to a given adaptive problem and providing alternative paths by which organisms can reach adaptive peaks (Badyaev & Morrison, 2018; Drion, O’Leary, & Marder, 2015; Grashow, Brookings, & Marder, 2009). Such mechanistic flexibility may allow organisms to more easily reach the same adaptive peak from alternative starting points, and additionally buffer organisms from pleiotropic effects via compensatory mechanisms that rely on the many-to-one mappings created by these alternative paths.
One potential consequence of the biological robustness generated by many-to-one mappings is that variation in the function of only a small number of key genes will alter organismal phenotypes while variation in most genes has no phenotypic consequences (Yang, Maclean, Park, Zhao, & Zhang, 2017), either because variation does not propagate to higher levels of organization and/or because variation is compensatory. In this case, phenotypic evolution may rely on a limited number of mechanistic paths, repeatedly targeting those mechanisms that that yield the greatest phenotypic responses with the smallest pleiotropic costs. Indeed, compelling examples demonstrate that similar phenotypes share underlying neural, physiological, molecular, and/or genetic mechanisms, even across highly divergent taxa (e.g. Insel and Young, 2000; Manceau et al., 2010; Pankey et al., 2014; Rosenblum et al., 2010). In contrast, other studies demonstrate flexibility in underlying mechanisms suggesting that different mechanistic ‘solutions’ can give rise to shared phenotypes in closely related species, among populations of the same species, or even among individuals of the same population (e.g. Abouheif and Wray, 2002; Crawford and Oleksiak, 2007; Drion et al., 2015; Grashow et al., 2009; Mandic et al., 2018). Nevertheless, even if mechanistic flexibility is a common feature of robust biological networks, shared genetic background or patterns of pleiotropy in a lineage may still direct evolutionary paths toward predictable mechanistic pathways, especially at long evolutionary timescales (Gompel & Prud’homme, 2009; Stern & Orgogozo, 2008). Empirical evidence for both shared and distinct mechanisms underlying parallel phenotypic evolution leaves open the question of when and why either pattern dominates.
One feature of biological networks that may channel divergence into particular paths is environmentally induced plasticity. First, both plastic and evolutionary processes may rely on those mechanistic paths that yield the greatest phenotypic responses. In this case, we expect plastic and evolutionary responses to share underlying mechanisms, although they may not act in the same direction. Theory predicts that plastic and evolutionary changes will be in the same direction when plasticity in a novel environment is adaptative, increasing immediate survival and allowing time for evolutionary divergence via co-option of mechanisms involved in environmentally induced responses (Baldwin, 1896; Ghalambor, McKay, Carroll, & Reznick, 2007; Lande, 2009; West-Eberhard, 2003). In contrast, plastic and evolutionary changes will be in opposite directions when plasticity in a novel environment is non-adaptive thereby increasing the strength of selection or when plastic responses ‘overshoot’ adaptive optima and are compensated by selection (Conover, Duffy, & Hice, 2009; Ghalambor et al., 2007; Grether, 2005; Velotta & Cheviron, 2018). Importantly, plasticity may facilitate adaptation under either scenario and empirical studies document both patterns. In addition, plastic and evolutionary processes may rely on shared mechanistic paths because the mechanisms mediating phenotypic plasticity promote the accumulation of cryptic genetic variation that is released under new environmental conditions, thereby fostering associations between plasticity and divergence (Draghi & Whitlock, 2012; Espinosa-Soto, Martin, & Wagner, 2011). Finally, while associations between phenotypic plasticity and evolution have primarily been considered in the context of phenotypic change, associations between developmental plasticity and genetic divergence at the level of underlying mechanisms could also arise if initially plastic compensatory or homeostatic responses to maintain, rather than alter, organism level phenotypes become genetically fixed as adaptation proceeds (Velotta & Cheviron, 2018), in which case we may also expect the evolution of plasticity itself.
In the present study, we take advantage of parallel phenotypic evolution in independent lineages of Trinidadian guppies (Poecilia reticulata ) to explore patterns of flexibility and constraint in transcriptional mechanisms mediating repeated adaptation. We compare whole-brain gene expression patterns based on developmental experience and genetic background to test four hypotheses: (1) that genes with significant expression plasticity are more likely to show genetic divergence in expression, (2) that the direction of plastic responses predicts the direction of genetic divergence, (3) that gene expression plasticity itself evolves, and (4) that parallel phenotypic adaptation across independent lineages relies on shared gene expression changes.