Different Genomic Changes Underlie Adaptive Evolution in Populations of Contrasting History

Artificial selection reveals complex genetic architecture of shoot branching and its response to nitrate supply in Arabidopsis

Quantitative traits may be controlled by many loci, many alleles at each locus, and subject to genotype-by-environment interactions, making them difficult to map. One example of such a complex trait is shoot branching in the model plant Arabidopsis, and its plasticity in response to nitrate. Here, we use artificial selection under contrasting nitrate supplies to dissect the genetic architecture of this complex trait, where loci identified by association mapping failed to explain heritability estimates. We found a consistent response to selection for high branching, with correlated responses in other traits such as plasticity and flowering time. Genome-wide scans for selection and simulations suggest that at least tens of loci control this trait, with a distinct genetic architecture between low and high nitrate treatments. While signals of selection could be detected in the populations selected for high branching on low nitrate, there was very little overlap in the regions selected in three independent populations. Thus the regulatory network controlling shoot branching can be tuned in different ways to give similar phenotypes.

Population History Shapes Responses to Different Temperature Regimes in Drosophila subobscura

Drosophila subobscura is considered a good model species for investigation of a population's ability to adapt and cope with climate changes. Decade long research has shown that inversion frequencies change in response to environmental factors indicating their role in adaptation to novel environments. The mechanisms behind organisms' responses to temperature are complex, involving changes in physiology, behavior, gene expression and regulation. On the other hand, a population's ability to respond to suboptimal conditions depends on standing genetic variation and population history. In order to elucidate the role of local adaptation in population response to the changing temperature, we investigated the response to temperature in D. subobscura individuals originating from two different altitudes by combining traditional cytogenetic techniques with assessing the levels of Hsp70 protein expression. Inversion polymorphism was assessed in the flies sampled from natural populations and in flies reared in laboratory conditions at three different temperatures after five and sixteen generations and Hsp70 protein expression profile in 12th generation flies at the basal level and after heat shock induction. Our results indicate that local adaptation and population history influence population response to the changing temperature.

How predictable is adaptation from standing genetic variation? Experimental evolution in Drosophila highlights the central role of redundancy and linkage disequilibrium

Experimental evolution is well-suited to test the predictability of evolution without the confounding effects of inaccurate forecasts about future environments. Most of the literature about parallel (and thus predictable) evolution has been carried out in asexual microorganisms, which adapt by de novo mutations. Nevertheless, parallel evolution has also been studied in sexual species at the genomic level. Here, I review the evidence for parallel evolution in Drosophila, the best-studied obligatory outcrossing model for adaptation from standing genetic variation in the laboratory. Similar to asexual microorganisms, evidence for parallel evolution varies between the focal hierarchical levels. Selected phenotypes consistently respond in a very predicable way, but the underlying allele frequency changes are much less predictable. The most important insight is that the predictability of the genomic selection response for polygenic traits depends highly on the founder population and to a much lesser extent on the selection regime. This implies that predicting adaptive genomic response is challenging and requires a good understanding of the adaptive architecture (including linkage disequilibrium) in the ancestral populations. This article is part of the theme issue 'Interdisciplinary approaches to predicting evolutionary biology'.

Resequencing of a Pekin duck breeding population provides insights into the genomic response to short-term artificial selection

BACKGROUND

Short-term, intense artificial selection drives fast phenotypic changes in domestic animals and leaves imprints on their genomes. However, the genetic basis of this selection response is poorly understood. To better address this, we employed the Pekin duck Z2 pure line, in which the breast muscle weight was increased nearly 3-fold after 10 generations of breeding. We denovo assembled a high-quality reference genome of a female Pekin duck of this line (GCA_003850225.1) and identified 8.60 million genetic variants in 119 individuals among 10 generations of the breeding population.

RESULTS

We identified 53 selected regions between the first and tenth generations, and 93.8% of the identified variations were enriched in regulatory and noncoding regions. Integrating the selection signatures and genome-wide association approach, we found that 2 regions covering 0.36 Mb containing UTP25 and FBRSL1 were most likely to contribute to breast muscle weight improvement. The major allele frequencies of these 2 loci increased gradually with each generation following the same trend. Additionally, we found that a copy number variation region containing the entire EXOC4 gene could explain 1.9% of the variance in breast muscle weight, indicating that the nervous system may play a role in economic trait improvement.

CONCLUSIONS

Our study not only provides insights into genomic dynamics under intense artificial selection but also provides resources for genomics-enabled improvements in duck breeding.

Past history shapes evolution of reproductive success in a global warming scenario

Adaptive evolution is critical for animal populations to thrive in the fast-changing natural environments. Ectotherms are particularly vulnerable to global warming and, although their limited coping ability has been suggested, few real-time evolution experiments have directly accessed their evolutionary potential. Here, we report a long-term experimental evolution study addressing the evolution of Drosophila thermal reaction norms, after ∼30 generations under different dynamic thermal regimes: fluctuating (daily variation between 15 and 21 °C) or warming (daily fluctuation with increases in both thermal mean and variance across generations). We analyzed the evolutionary dynamics of Drosophila subobscura populations as a function of the thermally variable environments in which they evolved and their distinct background. Our results showed clear differences between the historically differentiated populations: high latitude D. subobscura populations responded to selection, improving their reproductive success at higher temperatures whereas their low latitude counterparts did not. This suggests population variation in the amount of genetic variation available for thermal adaptation, an aspect that needs to be considered to allow for better predictions of future climate change responses. Our results highlight the complex nature of thermal responses in face of environmental heterogeneity and emphasize the importance of considering inter-population variation in thermal evolution studies.

Hybrid evolution repeats itself across environmental contexts in Texas sunflowers (Helianthus)

To what extent is evolution repeatable? Little is known about whether the evolution of hybrids is more (or less) repeatable than that of nonhybrids. We used field experimental evolution in annual sunflowers (Helianthus) in Texas to ask the extent to which hybrid evolution is repeatable across environments compared to nonhybrid controls. We created hybrids between Helianthus annuus (L.) and H. debilis (Nutt.) and grew plots of both hybrids and nonhybrid controls through eight generations at three sites in Texas. We collected seeds from each generation and grew each generation × treatment × home site combination at two final common gardens. We estimated the strength and direction of evolution in terms of fitness and 24 traits, tested for repeated versus nonrepeated evolution, and assessed overall phenotypic evolution across lineages and in relation to a locally adapted phenotype. Hybrids consistently evolved higher fitness over time, while controls did not, although trait evolution varied in strength across home sites. Repeated evolution was more evident in hybrids versus nonhybrid controls, and hybrid evolution was often in the direction of the locally adapted phenotype. Our findings have implications for both the nature of repeatability in evolution and the contribution of hybridization to evolution across environmental contexts.

Highly Parallel Genomic Selection Response in Replicated Drosophila melanogaster Populations with Reduced Genetic Variation

Many adaptive traits are polygenic and frequently more loci contributing to the phenotype are segregating than needed to express the phenotypic optimum. Experimental evolution with replicated populations adapting to a new controlled environment provides a powerful approach to study polygenic adaptation. Because genetic redundancy often results in nonparallel selection responses among replicates, we propose a modified evolve and resequence (E&R) design that maximizes the similarity among replicates. Rather than starting from many founders, we only use two inbred Drosophila melanogaster strains and expose them to a very extreme, hot temperature environment (29 °C). After 20 generations, we detect many genomic regions with a strong, highly parallel selection response in 10 evolved replicates. The X chromosome has a more pronounced selection response than the autosomes, which may be attributed to dominance effects. Furthermore, we find that the median selection coefficient for all chromosomes is higher in our two-genotype experiment than in classic E&R studies. Because two random genomes harbor sufficient variation for adaptive responses, we propose that this approach is particularly well-suited for the analysis of polygenic adaptation.

No evidence for short-term evolutionary response to a warming environment in Drosophila

Adaptive evolution is key in mediating responses to global warming and may sometimes be the only solution for species to survive. Such evolution will expectedly lead to changes in the populations' thermal reaction norm and improve their ability to cope with stressful conditions. Conversely, evolutionary constraints might limit the adaptive response. Here, we test these expectations by performing a real-time evolution experiment in historically differentiated Drosophila subobscura populations. We address the phenotypic change after nine generations of evolution in a daily fluctuating environment with average constant temperature, or in a warming environment with increasing average and amplitude temperature across generations. Our results showed that (1) evolution under a global warming scenario does not lead to a noticeable change in the thermal response; (2) historical background appears to be affecting responses under the warming environment, particularly at higher temperatures; and (3) thermal reaction norms are trait dependent: although lifelong exposure to low temperature decreases fecundity and productivity but not viability, high temperature causes negative transgenerational effects on productivity and viability, even with high fecundity. These findings in such an emblematic organism for thermal adaptation studies raise concerns about the short-term efficiency of adaptive responses to the current rising temperatures.

Evolution of a neuromuscular sexual dimorphism in the Drosophila montium species group

While epigamic traits likely evolve via sexual selection, the mechanism whereby internal sexual dimorphism arises remains less well understood. Seeking clues as to how the internal sexual dimorphism evolved, we compared the abdominal musculature of 41 Drosophila montium group species, to determine whether any of these species carry a male-specific muscle of Lawrence (MOL). Our quantitative analysis revealed that the size of a sexually dimorphic MOL analog found in 19 montium group species varied widely from species to species, suggesting the gradual evolution of this sexually dimorphic neuromuscular trait. We attempted the ancestral state reconstitution for the presence or absence of the neuromuscular sexual dimorphism in the A5 segment; the neuromuscular sexual dimorphism existed in an old ancestor of the montium group, which was lost in some of the most recent common ancestors of derived lineages, and subsequently some species regained it. This loss-and-gain history was not shared by evolutionary changes in the courtship song pattern, even though both traits were commonly regulated by the master regulator male-determinant protein FruM. It is envisaged that different sets of FruM target genes may serve for shaping the song and MOL characteristics, respectively, and, as a consequence, each phenotypic trait underwent a distinct evolutionary path.

The genetic architecture of temperature adaptation is shaped by population ancestry and not by selection regime

Background

Understanding the genetic architecture of temperature adaptation is key for characterizing and predicting the effect of climate change on natural populations. One particularly promising approach is Evolve and Resequence, which combines advantages of experimental evolution such as time series, replicate populations, and controlled environmental conditions, with whole genome sequencing. Recent analysis of replicate populations from two different Drosophila simulans founder populations, which were adapting to the same novel hot environment, uncovered very different architectures—either many selection targets with large heterogeneity among replicates or fewer selection targets with a consistent response among replicates.

Results

Here, we expose the founder population from Portugal to a cold temperature regime. Although almost no selection targets are shared between the hot and cold selection regime, the adaptive architecture was similar. We identify a moderate number of targets under strong selection (19 selection targets, mean selection coefficient = 0.072) and parallel responses in the cold evolved replicates. This similarity across different environments indicates that the adaptive architecture depends more on the ancestry of the founder population than the specific selection regime.

Conclusions

These observations will have broad implications for the correct interpretation of the genomic responses to a changing climate in natural populations.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13059-021-02425-9.

Predicting Thermal Adaptation by Looking Into Populations' Genomic Past

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.

The Effects of Quantitative Trait Architecture on Detection Power in Short-Term Artificial Selection Experiments

Evolve and resequence (E&R) experiments, in which artificial selection is imposed on organisms in a controlled environment, are becoming an increasingly accessible tool for studying the genetic basis of adaptation. Previous work has assessed how different experimental design parameters affect the power to detect the quantitative trait loci (QTL) that underlie adaptive responses in such experiments, but so far there has been little exploration of how this power varies with the genetic architecture of the evolving traits. In this study, we use forward simulation to build a more realistic model of an E&R experiment in which a quantitative polygenic trait experiences a short, but strong, episode of truncation selection. We study the expected power for QTL detection in such an experiment and how this power is influenced by different aspects of trait architecture, including the number of QTL affecting the trait, their starting frequencies, effect sizes, clustering along a chromosome, dominance, and epistasis patterns. We show that all of these parameters can affect allele frequency dynamics at the QTL and linked loci in complex and often unintuitive ways, and thus influence our power to detect them. One consequence of this is that existing detection methods based on models of independent selective sweeps at individual QTL often have lower detection power than a simple measurement of allele frequency differences before and after selection. Our findings highlight the importance of taking trait architecture into account when designing and interpreting studies of molecular adaptation with temporal data. We provide a customizable modeling framework that will enable researchers to easily simulate E&R experiments with different trait architectures and parameters tuned to their specific study system, allowing for assessment of expected detection power and optimization of experimental design.

Benchmarking software tools for detecting and quantifying selection in evolve and resequencing studies

BACKGROUND

The combination of experimental evolution with whole-genome resequencing of pooled individuals, also called evolve and resequence (E&R) is a powerful approach to study the selection processes and to infer the architecture of adaptive variation. Given the large potential of this method, a range of software tools were developed to identify selected SNPs and to measure their selection coefficients.

RESULTS

In this benchmarking study, we compare 15 test statistics implemented in 10 software tools using three different scenarios. We demonstrate that the power of the methods differs among the scenarios, but some consistently outperform others. LRT-1, CLEAR, and the CMH test perform best despite LRT-1 and the CMH test not requiring time series data. CLEAR provides the most accurate estimates of selection coefficients.

CONCLUSION

This benchmark study will not only facilitate the analysis of already existing data, but also affect the design of future data collections.

Widespread gene duplication and adaptive evolution in the RNA interference pathways of the Drosophila obscura group

BACKGROUND

RNA interference (RNAi) related pathways provide defense against viruses and transposable elements, and have been implicated in the suppression of meiotic drive elements. Genes in these pathways often exhibit high levels of adaptive substitution, and over longer timescales show gene duplication and loss-most likely as a consequence of their role in mediating conflict with these parasites. This is particularly striking for Argonaute 2 (Ago2), which is ancestrally the key effector of antiviral RNAi in insects, but has repeatedly formed new testis-specific duplicates in the recent history of the obscura species-group of Drosophila.

RESULTS

Here we take advantage of publicly available genomic and transcriptomic data to identify six further RNAi-pathway genes that have duplicated in this clade of Drosophila, and examine their evolutionary history. As seen for Ago2, we observe high levels of adaptive amino-acid substitution and changes in sex-biased expression in many of the paralogs. However, our phylogenetic analysis suggests that co-duplications of the RNAi machinery were not synchronous, and our expression analysis fails to identify consistent male-specific expression.

CONCLUSIONS

These results confirm that RNAi genes, including genes of the antiviral and piRNA pathways, have undergone multiple independent duplications and that their history has been particularly labile within the obscura group. However, they also suggest that the selective pressures driving these changes have not been consistent, implying that more than one selective agent may be responsible.