A cost-effective sequencing method for genetic studies combining high-depth whole exome and low-depth whole genome

Whole genome sequencing (WGS) at high-depth (30X) allows the accurate discovery of variants in the coding and non-coding DNA regions and helps elucidate the genetic underpinnings of human health and diseases. Yet, due to the prohibitive cost of high-depth WGS, most large-scale genetic association studies use genotyping arrays or high-depth whole exome sequencing (WES). Here we propose a cost-effective method which we call "Whole Exome Genome Sequencing" (WEGS), that combines low-depth WGS and high-depth WES with up to 8 samples pooled and sequenced simultaneously (multiplexed). We experimentally assess the performance of WEGS with four different depth of coverage and sample multiplexing configurations. We show that the optimal WEGS configurations are 1.7-2.0 times cheaper than standard WES (no-plexing), 1.8-2.1 times cheaper than high-depth WGS, reach similar recall and precision rates in detecting coding variants as WES, and capture more population-specific variants in the rest of the genome that are difficult to recover when using genotype imputation methods. We apply WEGS to 862 patients with peripheral artery disease and show that it directly assesses more known disease-associated variants than a typical genotyping array and thousands of non-imputable variants per disease-associated locus.

Organic cation transporter 2 contributes to SSRI antidepressant efficacy by controlling tryptophan availability in the brain

Selective serotonin reuptake inhibitors (SSRI) are common first-line treatments for major depression. However, a significant number of depressed patients do not respond adequately to these pharmacological treatments. In the present preclinical study, we demonstrate that organic cation transporter 2 (OCT2), an atypical monoamine transporter, contributes to the effects of SSRI by regulating the routing of the essential amino acid tryptophan to the brain. Contrarily to wild-type mice, OCT2-invalidated mice failed to respond to prolonged fluoxetine treatment in a chronic depression model induced by corticosterone exposure recapitulating core symptoms of depression, i.e., anhedonia, social withdrawal, anxiety, and memory impairment. After corticosterone and fluoxetine treatment, the levels of tryptophan and its metabolites serotonin and kynurenine were decreased in the brain of OCT2 mutant mice compared to wild-type mice and reciprocally tryptophan and kynurenine levels were increased in mutants' plasma. OCT2 was detected by immunofluorescence in several structures at the blood-cerebrospinal fluid (CSF) or brain-CSF interface. Tryptophan supplementation during fluoxetine treatment increased brain concentrations of tryptophan and, more discreetly, of 5-HT in wild-type and OCT2 mutant mice. Importantly, tryptophan supplementation improved the sensitivity to fluoxetine treatment of OCT2 mutant mice, impacting chiefly anhedonia and short-term memory. Western blot analysis showed that glycogen synthase kinase-3β (GSK3β) and mammalian/mechanistic target of rapamycin (mTOR) intracellular signaling was impaired in OCT2 mutant mice brain after corticosterone and fluoxetine treatment and, conversely, tryptophan supplementation recruited selectively the mTOR protein complex 2. This study provides the first evidence of the physiological relevance of OCT2-mediated tryptophan transport, and its biological consequences on serotonin homeostasis in the brain and SSRI efficacy.

Customization of the translational complex regulates mRNA-specific translation to control CNS regeneration

In the adult mammalian central nervous system (CNS), axons fail to regenerate spontaneously after injury because of a combination of extrinsic and intrinsic factors. Despite recent advances targeting the intrinsic regenerative properties of adult neurons, the molecular mechanisms underlying axon regeneration are not fully understood. Here, we uncover a regulatory mechanism that controls the expression of key proteins involved in regeneration at the translational level. Our results show that mRNA-specific translation is critical for promoting axon regeneration. Indeed, we demonstrate that specific ribosome-interacting proteins, such as the protein Huntingtin (HTT), selectively control the translation of a specific subset of mRNAs. Moreover, modulating the expression of these translationally regulated mRNAs is crucial for promoting axon regeneration. Altogether, our findings highlight that selective translation through the customization of the translational complex is a key mechanism of axon regeneration with major implications in the development of therapeutic strategies for CNS repair.

Evoked responses to single pulse electrical stimulation reveal impaired striatal excitability in a rat model of Parkinson's disease

BACKGROUND

Sensorimotor beta oscillations are increased in Parkinson's disease (PD) due to the alteration of dopaminergic transmission. This electrophysiological read-out is reported both in patients and in animal models such as the 6-OHDA rat model obtained with unilateral nigral injection of 6-hydroxydopamine (6-OHDA). Current treatments, based on dopaminergic replacement, transiently normalize this pathological beta activity and improve patients' quality of life.

OBJECTIVES

We wanted to assess in vivo whether the abnormal beta oscillations can be correlated with impaired striatal or cortical excitability of the sensorimotor system and modulated by the pharmacological manipulation of the dopaminergic system.

METHODS

In the unilateral 6-OHDA rat model and control animals, we used intra-striatal and intra-cortical single-pulse electrical stimulation (SPES) and concurrent local field potentials (LFP) recordings. In the two groups, we quantified basal cortico-striatal excitability from time-resolved spectral analyses of LFP evoked responses induced remotely by intracerebral stimulations. The temporal dependance of cortico-striatal excitability to dopaminergic transmission was further tested using electrophysiological recordings combined with levodopa injection.

RESULTS

LFP evoked responses after striatal stimulation showed a transient reduction of power in a large time-frequency domain in the 6-OHDA group compared to the sham group. This result was specific to the striatum, as no significant difference was observed in cortical LFP evoked responses between the two groups. This impaired striatal excitability in the 6-OHDA group was observed in the striatum at least during the first 3 months after the initial lesion. In addition, the striatum responses to SPES during a levodopa challenge showed a transient potentiation of the decrease of responsiveness in frequencies below 40 Hz.

CONCLUSION

The spectral properties of striatal responses to SPES show high sensitivity to dopaminergic transmission in the unilateral 6-OHDA rat model. We thus propose that this approach could be used in preclinical models as a time-resolved biomarker of impaired dopaminergic transmission capable of monitoring progressive neurodegeneration and/or challenges to drug intake.

Application of Genomic Sequencing to Refine Patient Stratification for Adjuvant Therapy in Renal Cell Carcinoma

PURPOSE

Patients with resected localized clear-cell renal cell carcinoma (ccRCC) remain at variable risk of recurrence. Incorporation of biomarkers may refine risk prediction and inform adjuvant treatment decisions. We explored the role of tumor genomics in this setting, leveraging the largest cohort to date of localized ccRCC tissues subjected to targeted gene sequencing.

EXPERIMENTAL DESIGN

The somatic mutation status of 12 genes was determined in 943 ccRCC cases from a multinational cohort of patients, and associations to outcomes were examined in a Discovery (n = 469) and Validation (n = 474) framework.

RESULTS

Tumors containing a von-Hippel Lindau (VHL) mutation alone were associated with significantly improved outcomes in comparison with tumors containing a VHL plus additional mutations. Within the Discovery cohort, those with VHL+0, VHL+1, VHL+2, and VHL+≥3 tumors had disease-free survival (DFS) rates of 90.8%, 80.1%, 68.2%, and 50.7% respectively, at 5 years. This trend was replicated in the Validation cohort. Notably, these genomically defined groups were independent of tumor mutational burden. Amongst patients eligible for adjuvant therapy, those with a VHL+0 tumor (29%) had a 5-year DFS rate of 79.3% and could, therefore, potentially be spared further treatment. Conversely, patients with VHL+2 and VHL+≥3 tumors (32%) had equivalent DFS rates of 45.6% and 35.3%, respectively, and should be prioritized for adjuvant therapy.

CONCLUSIONS

Genomic characterization of ccRCC identified biologically distinct groups of patients with divergent relapse rates. These groups account for the ∼80% of cases with VHL mutations and could be used to personalize adjuvant treatment discussions with patients as well as inform future adjuvant trial design.

The RSK2-RPS6 axis promotes axonal regeneration in the peripheral and central nervous systems

Unlike immature neurons and the ones from the peripheral nervous system (PNS), mature neurons from the central nervous system (CNS) cannot regenerate after injury. In the past 15 years, tremendous progress has been made to identify molecules and pathways necessary for neuroprotection and/or axon regeneration after CNS injury. In most regenerative models, phosphorylated ribosomal protein S6 (p-RPS6) is up-regulated in neurons, which is often associated with an activation of the mTOR (mammalian target of rapamycin) pathway. However, the exact contribution of posttranslational modifications of this ribosomal protein in CNS regeneration remains elusive. In this study, we demonstrate that RPS6 phosphorylation is essential for PNS and CNS regeneration in mice. We show that this phosphorylation is induced during the preconditioning effect in dorsal root ganglion (DRG) neurons and that it is controlled by the p90S6 kinase RSK2. Our results reveal that RSK2 controls the preconditioning effect and that the RSK2-RPS6 axis is key for this process, as well as for PNS regeneration. Finally, we demonstrate that RSK2 promotes CNS regeneration in the dorsal column, spinal cord synaptic plasticity, and target innervation leading to functional recovery. Our data establish the critical role of RPS6 phosphorylation controlled by RSK2 in CNS regeneration and give new insights into the mechanisms related to axon growth and circuit formation after traumatic lesion.

Abstract LB113: Genomic classification to refine prognosis in clear cell renal cell carcinoma

Renal cell carcinomas (RCC) are characterized by their heterogenous clinical outcomes, and due to their indeterminate behavior and the absence of routine biomarkers, it is difficult to identify patients who are at high-risk for relapse after curative nephrectomy. To identify genomic biomarkers for clear cell RCC (ccRCC) risk-stratification we interrogated somatic mutation status of 12 RCC-relevant genes using next-generation sequencing (NGS) in tumor-normal pairs from 943 patients with matched follow up data from the Cancer Genomics of the Kidney (CAGEKID) study. We examined associations between genomically-defined patient groups, explained below, and disease-free as well as RCC-specific survival independently in two cohorts of patients (N=469 for cohort 1; 474 for cohort 2). We used the Kaplan-Meier method with log-rank tests to compare survival functions, and Cox proportional hazards models to stratify for patient stage and age to estimate association of each group with survival. RCC-specific survival was assessed with a competing-risks method to include deaths from other causes. Within these cohorts, 76.4% of patients harbored somatic mutations in VHL, the most common driver gene in ccRCC. The most commonly mutated genes within VHL-mutated tumors were PBRM1 (39.7%), SETD2 (19%), BAP1 (14.3%), and KDM5C (8.3%). Less frequently mutated genes included ATM, COL11A1, DMD, TP53, and TRRAP (~3-5%).Among VHL-driven tumors, we identified a new genomic classifier on the basis of the number of mutations in additional RCC driver genes in the panel examined. Patients were classified based on the presence of mutations only in VHL (VHL+0), those with mutations in VHL and one other driver gene (VHL+1), two other driver genes (VHL+2), and 3 or more other driver genes (VHL≥3). We observed within both cohorts that both the risk of disease recurrence as well as RCC-specific death were associated with an increased number of mutations within this classification. When stratified for patient stage and age, the hazard-ratio for 5-year disease-free survival for VHL≥3 patients was 6.69 (p=0.000212), 4.31 for VHL+2 (p=0.000862), and 2.43 for VHL+1 (p=0.035662), compared to patients with only mutations in VHL. These observations were replicated in the second patient cohort, with hazards ratios of 4.55, 2.49, and 1.40, for VHL≥3, VHL+2, and VHL+1 classified patients respectively, indicating that risk of disease recurrence increases with the number of driver mutations. Notably, tumor mutational burden (TMB) was not significantly different between the aforementioned groups, demonstrating that our classifier is independent of TMB. We created a model based on a set of 12 RCC-relevant genes, which can predict risk of relapse for the ~80% of patients with ccRCC that are VHL-driven. This classification can be defined based on a small panel of genes, making it easily applicable to the clinic, in the context of tumor or liquid biopsy analysis.

Citation Format: Kate I. Glennon, Naveen S. Vasudev, Ghislaine Scelo, Michelle Wilson, Louis Letourneau, Robert Eveleigh, Nazanin Nourbehesht, Madeleine Arseneault, Antoine Paccard, Lars Egevad, Juris Viksna, Edgars Celms, Sharon M. Jackson, Behnoush Abedi-Ardekani, Anne Y. Warren, Peter J. Selby, Sebastian Trainor, Michael Kimuli, Naeem Soomro, Adebanji Adeyoju, Poulam Patel, Magdalena B. Wozniak, Ivana Holcatova, Antonin Brisuda, Vladimir Janout, Estelle Chanudet, David Zaridze, Anush Moukeria, Oxana Shangina, Lenka Foretova, Marie Navratilova, Dana Mates, Viorel Jinga, Ljiljana Bogdanovic, Bozidar Kovacevic, Anne Cambon-Thomsen, Guillaume Bourque, Alvis Brazma, Jörg Tost, Paul Brennan, Mark Lathrop, Yasser Riazalhosseini, Rosamonde E. Banks. Genomic classification to refine prognosis in clear cell renal cell carcinoma [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr LB113.

Detection of Temozolomide-Induced Hypermutation and Response to PD-1 Checkpoint Inhibitor In Recurrent Glioblastoma

Background

Despite aggressive upfront treatment in glioblastoma (GBM), recurrence remains inevitable for most patients. Accumulating evidence has identified hypermutation induced by temozolomide (TMZ) as an emerging subtype of recurrent GBM. However, its biological and therapeutic significance has yet to be described.

Methods

We combined GBM patient and derive GBM stem cells (GSCs) from tumors following TMZ to explore response of hypermutant and non-hypermutant emergent phenotypes and explore the immune relevance of hypermutant and non-hypermutant states in vivo.

Results

Hypermutation emerges as one of two possible mutational subtypes following TMZ treatment in vivo and demonstrates distinct phenotypic features compared to non-hypermutant recurrent GBM. Hypermutant tumors elicited robust immune rejection in subcutaneous contexts which was accompanied by increased immune cell infiltration. In contrast, immune rejection of hypermutant tumors were stunted in orthotopic settings where we observe limited immune infiltration. Use of anti-PD-1 immunotherapy showed that immunosuppression in orthotopic contexts was independent from the PD-1/PD-L1 axis. Finally, we demonstrate that mutational burden can be estimated from DNA contained in extracellular vesicles (EVs).

Conclusion

Hypermutation post-TMZ are phenotypically distinct from non-hypermutant GBM and requires personalization for appropriate treatment. The brain microenvironment may be immunosuppressive and exploration of the mechanisms behind this may be key to improving immunotherapy response in this subtype of recurrent GBM.

Evolution of thermal physiology alters the projected range of threespine stickleback under climate change

Species distribution models (SDMs) are widely used to predict range shifts but could be unreliable under climate change scenarios because they do not account for evolution. The thermal physiology of a species is a key determinant of its range and thus incorporating thermal trait evolution into SDMs might be expected to alter projected ranges. We identified a genetic basis for physiological and behavioural traits that evolve in response to temperature change in natural populations of threespine stickleback (Gasterosteus aculeatus). Using these data, we created geographical range projections using a mechanistic niche area approach under two climate change scenarios. Under both scenarios, trait data were either static ("no evolution" models), allowed to evolve at observed evolutionary rates ("evolution" models) or allowed to evolve at a rate of evolution scaled by the trait variance that is explained by quantitative trait loci (QTL; "scaled evolution" models). We show that incorporating these traits and their evolution substantially altered the projected ranges for a widespread panmictic marine population, with over 7-fold increases in area under climate change projections when traits are allowed to evolve. Evolution-informed SDMs should improve the precision of forecasting range dynamics under climate change, and aid in their application to management and the protection of biodiversity.

Rational Development of Liquid Biopsy Analysis in Renal Cell Carcinoma

Simple Summary

Among patients affected by renal cell carcinoma (RCC), the most common type of kidney cancer, it remains difficult to identify those who are at high risk for relapse or metastasis. This is in part due to the absence of reliable clinical biomarkers and robust methods to capture them. The aim of our study was to develop an improved assay to capture prognostic genomic biomarkers in circulating tumor DNA (ctDNA) in RCC. For this purpose, we first established a next generation sequencing (NGS) assay, targeting genes that are tailored for RCC and that are largely excluded from commercially available assays. Next, we showed the reliable performance of this assay to detect prognostic gene mutations in tumor DNA isolated from plasma, and from extracellular vesicles. Thus, our study provides a resource to facilitate ctDNA analysis for precision medicine in RCC.

Abstract

Renal cell carcinoma (RCC) is known for its variable clinical behavior and outcome, including heterogeneity in developing relapse or metastasis. Recent data highlighted the potential of somatic mutations as promising biomarkers for risk stratification in RCC. Likewise, the analysis of circulating tumor DNA (ctDNA) for such informative somatic mutations (liquid biopsy) is considered an important advance for precision oncology in RCC, allowing to monitor molecular disease evolution in real time. However, our knowledge about the utility of ctDNA analysis in RCC is limited, in part due to the lack of RCC-appropriate assays for ctDNA analysis. Here, by interrogating different blood compartments in xenograft models, we identified plasma cell-free (cf) DNA and extracellular vesicles (ev) DNA enriched for RCC-associated ctDNA. Additionally, we developed sensitive targeted sequencing and bioinformatics workflows capable of detecting somatic mutations in RCC-relevant genes with allele frequencies ≥ 0.5%. Applying this assay to patient-matched tumor and liquid biopsies, we captured tumor mutations in cf- and ev-DNA fractions isolated from the blood, highlighting the potentials of both fractions for ctDNA analysis. Overall, our study presents an RCC-appropriate sequencing assay and workflow for ctDNA analysis and provides a proof of principle as to the feasibility of detecting tumor-specific mutations in liquid biopsy in RCC patients.

Repeatability of Adaptive Radiation Depends on Spatial Scale: Regional Versus Global Replicates of Stickleback in Lake Versus Stream Habitats

The repeatability of adaptive radiation is expected to be scale-dependent, with determinism decreasing as greater spatial separation among "replicates" leads to their increased genetic and ecological independence. Threespine stickleback (Gasterosteus aculeatus) provide an opportunity to test whether this expectation holds for the early stages of adaptive radiation-their diversification in freshwater ecosystems has been replicated many times. To better understand the repeatability of that adaptive radiation, we examined the influence of geographic scale on levels of parallel evolution by quantifying phenotypic and genetic divergence between lake and stream stickleback pairs sampled at regional (Vancouver Island) and global (North America and Europe) scales. We measured phenotypes known to show lake-stream divergence and used reduced representation genome-wide sequencing to estimate genetic divergence. We assessed the scale dependence of parallel evolution by comparing effect sizes from multivariate models and also the direction and magnitude of lake-stream divergence vectors. At the phenotypic level, parallelism was greater at the regional than the global scale. At the genetic level, putative selected loci showed greater lake-stream parallelism at the regional than the global scale. Generally, the level of parallel evolution was low at both scales, except for some key univariate traits. Divergence vectors were often orthogonal, highlighting possible ecological and genetic constraints on parallel evolution at both scales. Overall, our results confirm that the repeatability of adaptive radiation decreases at increasing spatial scales. We suggest that greater environmental heterogeneity at larger scales imposes different selection regimes, thus generating lower repeatability of adaptive radiation at larger spatial scales.

Using seasonal genomic changes to understand historical adaptation to new environments: Parallel selection on stickleback in highly-variable estuaries

Parallel evolution is considered strong evidence for natural selection. However, few studies have investigated the process of parallel selection as it plays out in real time. The common approach is to study historical signatures of selection in populations already well adapted to different environments. Here, to document selection under natural conditions, we study six populations of threespine stickleback (Gasterosteus aculeatus) inhabiting bar-built estuaries that undergo seasonal cycles of environmental changes. Estuaries are periodically isolated from the ocean due to sandbar formation during dry summer months, with concurrent environmental shifts that resemble the long-term changes associated with postglacial colonization of freshwater habitats by marine populations. We used pooled whole-genome sequencing to track seasonal allele frequency changes in six of these populations and search for signatures of natural selection. We found consistent changes in allele frequency across estuaries, suggesting a potential role for parallel selection. Functional enrichment among candidate genes included transmembrane ion transport and calcium binding, which are important for osmoregulation and ion balance. The genomic changes that occur in threespine stickleback from bar-built estuaries could provide a glimpse into the early stages of adaptation that have occurred in many historical marine to freshwater transitions.

Understanding Maladaptation by Uniting Ecological and Evolutionary Perspectives

Evolutionary biologists have long trained their sights on adaptation, focusing on the power of natural selection to produce relative fitness advantages while often ignoring changes in absolute fitness. Ecologists generally have taken a different tack, focusing on changes in abundance and ranges that reflect absolute fitness while often ignoring relative fitness. Uniting these perspectives, we articulate various causes of relative and absolute maladaptation and review numerous examples of their occurrence. This review indicates that maladaptation is reasonably common from both perspectives, yet often in contrasting ways. That is, maladaptation can appear strong from a relative fitness perspective, yet populations can be growing in abundance. Conversely, resident individuals can appear locally adapted (relative to nonresident individuals) yet be declining in abundance. Understanding and interpreting these disconnects between relative and absolute maladaptation, as well as the cases of agreement, is increasingly critical in the face of accelerating human-mediated environmental change. We therefore present a framework for studying maladaptation, focusing in particular on the relationship between absolute and relative fitness, thereby drawing together evolutionary and ecological perspectives. The unification of these ecological and evolutionary perspectives has the potential to bring together previously disjunct research areas while addressing key conceptual issues and specific practical problems.

Conservation through the lens of (mal)adaptation: Concepts and meta-analysis

Evolutionary approaches are gaining popularity in conservation science, with diverse strategies applied in efforts to support adaptive population outcomes. Yet conservation strategies differ in the type of adaptive outcomes they promote as conservation goals. For instance, strategies based on genetic or demographic rescue implicitly target adaptive population states whereas strategies utilizing transgenerational plasticity or evolutionary rescue implicitly target adaptive processes. These two goals are somewhat polar: adaptive state strategies optimize current population fitness, which should reduce phenotypic and/or genetic variance, reducing adaptability in changing or uncertain environments; adaptive process strategies increase genetic variance, causing maladaptation in the short term, but increase adaptability over the long term. Maladaptation refers to suboptimal population fitness, adaptation refers to optimal population fitness, and (mal)adaptation refers to the continuum of fitness variation from maladaptation to adaptation. Here, we present a conceptual classification for conservation that implicitly considers (mal)adaptation in the short-term and long-term outcomes of conservation strategies. We describe cases of how (mal)adaptation is implicated in traditional conservation strategies, as well as strategies that have potential as a conservation tool but are relatively underutilized. We use a meta-analysis of a small number of available studies to evaluate whether the different conservation strategies employed are better suited toward increasing population fitness across multiple generations. We found weakly increasing adaptation over time for transgenerational plasticity, genetic rescue, and evolutionary rescue. Demographic rescue was generally maladaptive, both immediately after conservation intervention and after several generations. Interspecific hybridization was adaptive only in the F1 generation, but then rapidly leads to maladaptation. Management decisions that are made to support the process of adaptation must adequately account for (mal)adaptation as a potential outcome and even as a tool to bolster adaptive capacity to changing conditions.

Causes of maladaptation

Evolutionary biologists tend to approach the study of the natural world within a framework of adaptation, inspired perhaps by the power of natural selection to produce fitness advantages that drive population persistence and biological diversity. In contrast, evolution has rarely been studied through the lens of adaptation's complement, maladaptation. This contrast is surprising because maladaptation is a prevalent feature of evolution: population trait values are rarely distributed optimally; local populations often have lower fitness than imported ones; populations decline; and local and global extinctions are common. Yet we lack a general framework for understanding maladaptation; for instance in terms of distribution, severity, and dynamics. Similar uncertainties apply to the causes of maladaptation. We suggest that incorporating maladaptation-based perspectives into evolutionary biology would facilitate better understanding of the natural world. Approaches within a maladaptation framework might be especially profitable in applied evolution contexts - where reductions in fitness are common. Toward advancing a more balanced study of evolution, here we present a conceptual framework describing causes of maladaptation. As the introductory article for a Special Feature on maladaptation, we also summarize the studies in this Issue, highlighting the causes of maladaptation in each study. We hope that our framework and the papers in this Special Issue will help catalyze the study of maladaptation in applied evolution, supporting greater understanding of evolutionary dynamics in our rapidly changing world.

Rapid evolution of cold tolerance in stickleback

Climate change is predicted to lead to increased average temperatures and greater intensity and frequency of high and low temperature extremes, but the evolutionary consequences for biological communities are not well understood. Studies of adaptive evolution of temperature tolerance have typically involved correlative analyses of natural populations or artificial selection experiments in the laboratory. Field experiments are required to provide estimates of the timing and strength of natural selection, enhance understanding of the genetics of adaptation and yield insights into the mechanisms driving evolutionary change. Here, we report the experimental evolution of cold tolerance in natural populations of threespine stickleback fish (Gasterosteus aculeatus). We show that freshwater sticklebacks are able to tolerate lower minimum temperatures than marine sticklebacks and that this difference is heritable. We transplanted marine sticklebacks to freshwater ponds and measured the rate of evolution after three generations in this environment. Cold tolerance evolved at a rate of 0.63 haldanes to a value 2.5°C lower than that of the ancestral population, matching values found in wild freshwater populations. Our results suggest that cold tolerance is under strong selection and that marine sticklebacks carry sufficient genetic variation to adapt to changes in temperature over remarkably short time scales.