Genetic Constraints, Transcriptome Plasticity, and the Evolutionary Response to Climate Change

Logan, Michael L.; Cox, Christian L.

doi:10.3389/fgene.2020.538226

Cited by 54 publications

(64 citation statements)

References 120 publications

(97 reference statements)

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“…Evolutionary change in trait means is better understood and does provide evidence for local adaptation (e.g., Hoffmann et al, 2002;Kellermann et al, 2012). However, upper thermal limits seem to be evolutionary constrained in some small ectothermic insects (particularly studied in Drosophila) (Kellermann et al, 2012;Schou et al, 2014; but see discussion in Logan and Cox, 2020), while not in some species of phytoplankton (Kontopoulos et al, 2020). The constraint among species of Drosophila is not founded in an apparent lack of additive genetic variation, as significant levels of genetic variation for heat tolerance in the same species of Drosophila have been documented (Williams et al, 2012;Castaneda et al, 2019).…”

Section: Introductionmentioning

confidence: 99%

Pronounced Plastic and Evolutionary Responses to Unpredictable Thermal Fluctuations in Drosophila simulans

et al. 2020

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Organisms are exposed to temperatures that vary, for example on diurnal and seasonal time scales. Thus, the ability to behaviorally and/or physiologically respond to variation in temperatures is a fundamental requirement for long-term persistence. Studies on thermal biology in ectotherms are typically performed under constant laboratory conditions, which differ markedly from the variation in temperature across time and space in nature. Here, we investigate evolutionary adaptation and environmentally induced plastic responses of Drosophila simulans to no fluctuations (constant), predictable fluctuations or unpredictable fluctuations in temperature. We whole-genome sequenced populations exposed to 20 generations of experimental evolution under the three thermal regimes and examined the proteome after short-term exposure to the same three regimes. We find that unpredictable fluctuations cause the strongest response at both genome and proteome levels. The loci showing evolutionary responses were generally unique to each thermal regime, but a minor overlap suggests either common laboratory adaptation or that some loci were involved in the adaptation to multiple thermal regimes. The evolutionary response, i.e., loci under selection, did not coincide with induced responses of the proteome. Thus, genes under selection in fluctuating thermal environments are distinct from genes important for the adaptive plastic response observed within a generation. This information is key to obtain a better understanding and prediction of the effects of future increases in both mean and variability of temperatures.

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Section: Introductionmentioning

confidence: 99%

Pronounced Plastic and Evolutionary Responses to Unpredictable Thermal Fluctuations in Drosophila simulans

et al. 2020

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“…Additionally, tropical forests may buffer changes in temperature to some extent, reducing the magnitude of change experienced by slender anoles relative to brown anoles (De Frenne et al, 2019). Our analyses also ignore other variables that are likely to change as a result of climate change, including precipitation, cloud cover, wind dynamics, and the frequency of extreme weather events (Bonebrake & Deutsch, 2012; Bonebrake & Mastrandrea, 2010; Campbell‐Staton et al, 2017; Clusella‐Trullas et al, 2011; Grant et al, 2017; Logan & Cox, 2020). Finally, although we used an integrative, data‐rich approach, our study consisted of a comparison of only two species, and as such, our results should be interpreted with caution.…”

Section: Discussionmentioning

confidence: 99%

Habitat structure mediates vulnerability to climate change through its effects on thermoregulatory behavior

et al. 2021

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Tropical ectotherms are thought to be especially vulnerable to climate change because they are thermal specialists, having evolved in aseasonal thermal environments.However, even within the tropics, habitat structure can influence opportunities for behavioral thermoregulation. Open (and edge) habitats likely promote more effective thermoregulation due to the high spatial heterogeneity of the thermal landscape, while forests are thermally homogenous and may constrain opportunities for behavioral buffering of environmental temperatures. Nevertheless, the ways in which behavior and physiology interact at local scales to influence the response to climate change are rarely investigated. We examined the thermal ecology and physiology of two lizard species that occupy distinct environments in the tropics. The brown anole lizard (Anolis sagrei) lives along forest edges in The Bahamas, whereas the Panamanian slender anole (Anolis apletophallus) lives under the canopy of mature forests in Panama. We combined detailed estimates of environmental variation, thermoregulatory behavior, and physiology to model the vulnerability of each of these species.Our projections suggest that forest-dwelling slender anoles will experience severely reduced locomotor performance, activity time, and energy budgets as the climate warms over the coming century. Conversely, the forest-edge-dwelling brown anoles may use behavioral compensation in the face of warming, maintaining population viability for many decades. Our results indicate that local habitat variation, through its effects on behavior and physiology, is a major determinant of vulnerability to climate change. When attempting to predict the impacts of climate change on a given population, broad-scale characteristics such as latitude may have limited predictive power.

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“…Thermal adaptation is a complex polygenic trait well-described in terms of its genetic architecture and selection footprints across a wide range of phylogenetically diverse taxa (Way and Oren, 2010;Valladares et al, 2014;López-Hernández and Cortés, 2019). While genomics has enabled these achievements that rely on past events of thermal variation, forward predictions remain one step behind partly because (1) disentangling selective and demographic drivers of the genomic landscape from fortuitous genomic constrains (Logan and Cox, 2020) is puzzling (Ellegren and Galtier, 2016) and (2) merging these heterogeneous signatures and data sources into a cohesive predictive framework was unfeasible, until recently. In this mini-review, we advocated for novel approaches that may enhance our understanding of the genetic consequences of past climate change, while offering new avenues to calibrate more accurate predictive models of the thermal adaptive potential.…”

Section: Discussionmentioning

confidence: 99%

Predicting Thermal Adaptation by Looking Into Populations’ Genomic Past

2020

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Molecular evolution offers an insightful theory to interpret the genomic consequences of thermal adaptation to previous events of climate change beyond range shifts. However, disentangling often mixed footprints of selective and demographic processes from those due to lineage sorting, recombination rate variation, and genomic constrains is not trivial. Therefore, here we condense current and historical population genomic tools to study thermal adaptation and outline key developments (genomic prediction, machine learning) that might assist their utilization for improving forecasts of populations’ responses to thermal variation. We start by summarizing how recent thermal-driven selective and demographic responses can be inferred by coalescent methods and in turn how quantitative genetic theory offers suitable multi-trait predictions over a few generations via the breeder’s equation. We later assume that enough generations have passed as to display genomic signatures of divergent selection to thermal variation and describe how these footprints can be reconstructed using genome-wide association and selection scans or, alternatively, may be used for forward prediction over multiple generations under an infinitesimal genomic prediction model. Finally, we move deeper in time to comprehend the genomic consequences of thermal shifts at an evolutionary time scale by relying on phylogeographic approaches that allow for reticulate evolution and ecological parapatric speciation, and end by envisioning the potential of modern machine learning techniques to better inform long-term predictions. We conclude that foreseeing future thermal adaptive responses requires bridging the multiple spatial scales of historical and predictive environmental change research under modern cohesive approaches such as genomic prediction and machine learning frameworks.

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Genetic Constraints, Transcriptome Plasticity, and the Evolutionary Response to Climate Change

Cited by 54 publications

References 120 publications

Pronounced Plastic and Evolutionary Responses to Unpredictable Thermal Fluctuations in Drosophila simulans

Pronounced Plastic and Evolutionary Responses to Unpredictable Thermal Fluctuations in Drosophila simulans

Habitat structure mediates vulnerability to climate change through its effects on thermoregulatory behavior

Predicting Thermal Adaptation by Looking Into Populations’ Genomic Past

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