Spatial variation in high temperature‐regulated gene expression predicts evolution of plasticity with climate change in the scarlet monkeyflower

Abstract

A major way that organisms can adapt to changing environmental conditions is by evolving increased or decreased phenotypic plasticity. In the face of current global warming, more attention is being paid to the role of plasticity in maintaining fitness as abiotic conditions change over time. However, given that temporal data can be challenging to acquire, a major question is whether evolution in plasticity across space can predict adaptive plasticity across time. In growth chambers simulating two thermal regimes, we generated transcriptome data for western North American scarlet monkeyflowers (Mimulus cardinalis) collected from different latitudes and years (2010 and 2017) to test hypotheses about how plasticity in gene expression is responding to increases in temperature, and if this pattern is consistent across time and space. Supporting the genetic compensation hypothesis, individuals whose progenitors were collected from the warmer‐origin northern 2017 descendant cohort showed lower thermal plasticity in gene expression than their cooler‐origin northern 2010 ancestors. This was largely due to a change in response at the warmer (40°C) rather than cooler (20°C) treatment. A similar pattern of reduced plasticity, largely due to a change in response at 40°C, was also found for the cooler‐origin northern versus the warmer‐origin southern population from 2017. Our results demonstrate that reduced phenotypic plasticity can evolve with warming and that spatial and temporal changes in plasticity predict one another.

Testing for genetic assimilation with phylogenetic comparative analysis: Conceptual, methodological, and statistical considerations

“…Motivated by current debate surrounding the Trade-off Hypothesis and increasing interest in the evolution of phenotypic plasticity and genetic assimilation under global change (Gunderson and Stillman 2015;Kelly 2019;Sasaki and Dam 2019;van Heerwaarden and Kellermann 2020;Barley et al 2021;Sasaki and Dam 2021;Preston et al 2022), we used simulations to explore the more general consequences of regression to the mean for tests of genetic assimilation at the macroevolutionary level. We conducted simulations that assumed mechanistically different models for plasticity evolution, as well as different experimental sampling designs for measuring species phenotypic traits.…”

“…2021; Sasaki and Dam 2021; Preston et al. 2022), we used simulations to explore the more general consequences of regression to the mean for tests of genetic assimilation at the macroevolutionary level. We conducted simulations that assumed mechanistically different models for plasticity evolution, as well as different experimental sampling designs for measuring species phenotypic traits.…”

Complex eco‐evolutionary responses of a foundational coastal marsh plant to global change

“…Our results underscore that the evolution of phenotypic plasticity can be an important, though somewhat underexplored empirically, driver of trait change on decadal to centennial timescales. Appreciation for its potential importance has likely been limited in part because the evolution of plasticity can be challenging to assess, which can be overcome by leveraging ‘resurrection ecology’ approaches (Preston et al ., 2022; Rauschkolb et al ., 2022; Zhang & Jiang, 2022). We found that the stimulating effect of elevated CO 2 on aboveground biomass at high levels of inundation was conditional on an additional environmental factor (salinity) and age cohort (Fig.…”

“…It would be worthwhile, for example, to illustrate how the spatial and temporal scales of environmental change align with genetic and phenotypic variation observed within and among populations of S. americanus (Summers et al ., 2018; Vahsen et al ., 2023). Conducting further empirical work using pedigreed full‐sib and half‐sib families generated from controlled crosses would offer a stronger basis for drawing inferences about the mechanisms underlying patterns of phenotypic variation by, for example, accounting for factors like maternal effects and epigenetic variation ( sensu Preston et al ., 2022) and allowing for further exploration of responses to selection in a quantitative genetics framework.…”

Testing for genetic assimilation with phylogenetic comparative analysis: Conceptual, methodological, and statistical considerations

“…Motivated by current debate surrounding the Trade-off Hypothesis and increasing interest in the evolution of phenotypic plasticity and genetic assimilation under global change (Gunderson and Stillman 2015; Kelly 2019; Sasaki and Dam 2019; van Heerwaarden and Kellermann 2020; Barley et al 2021; Preston et al 2021; Sasaki and Dam 2021), we used simulations to explore the more general consequences of regression to the mean for tests of genetic assimilation at the macroevolutionary level. We conducted simulations that assumed mechanistically different models for plasticity evolution, as well as different experimental sampling designs for measuring species phenotypic traits.…”