A multigenerational study can detect the evolutionary response to BaP exposure in the non-biting freshwater midge Chironomus riparius

The release of polycyclic aromatic hydrocarbons (PAHs) into the environment is posing a threat to ecosystems and human health. Benzo(a)pyrene (BaP) is considered a biomarker of PAH exposure and is classified as a Group 1 carcinogen. However, it was not known whether BaP is mutagenic, i.e. induces inherited germline mutations. In this study, we used a recently established method, which combines short-term mutation accumulation lines (MAL) with whole genome sequencing (WGS) to assess mutagenicity in the non-biting midge Chironomus riparius. The mutagenicity analysis was supplemented by an evaluation of the development of population fitness in three successive generations in the case of chronic exposure to BaP at a high concentration (100 μg/L). In addition, the level of ROS-induced oxidative stress was examined in vivo. Exposure to the higher BaP concentration led to an increase in germline mutations relative to the control, while the lower concentration showed no mentionable effect. Against expectations, BaP exposure decreased ROS-level compared to the control and is thus probably not responsible for the increased mutation rate. Likewise, the higher BaP concentration decreased fitness measured as population growth rate per day (PGR) significantly over all generations, without signs of rapid evolutionary adaptations. Our results thus highlighted that high BaP exposure may influence the evolutionary trajectory of organisms.

Genomics for monitoring and understanding species responses to global climate change

All life forms across the globe are experiencing drastic changes in environmental conditions as a result of global climate change. These environmental changes are happening rapidly, incur substantial socioeconomic costs, pose threats to biodiversity and diminish a species' potential to adapt to future environments. Understanding and monitoring how organisms respond to human-driven climate change is therefore a major priority for the conservation of biodiversity in a rapidly changing environment. Recent developments in genomic, transcriptomic and epigenomic technologies are enabling unprecedented insights into the evolutionary processes and molecular bases of adaptation. This Review summarizes methods that apply and integrate omics tools to experimentally investigate, monitor and predict how species and communities in the wild cope with global climate change, which is by genetically adapting to new environmental conditions, through range shifts or through phenotypic plasticity. We identify advantages and limitations of each method and discuss future research avenues that would improve our understanding of species' evolutionary responses to global climate change, highlighting the need for holistic, multi-omics approaches to ecosystem monitoring during global climate change.

Characterization and expression of heat shock and immune genes in natural populations of Prodiamesa olivacea (Diptera) exposed to thermal stress

This paper characterizes the heat stress response (HSR) and explores the impact of temperatures on the immune response of larvae from two chironomid species, Prodiamesa olivacea and Chironomus riparius. Genes involved in crucial metabolic pathways were de novo identified in P. olivacea: Hsp27, Hsp60, Hsp70, Hsc70, Cdc37, and HSF for the heat stress response (HSR) and TOLL, PGRP, C-type lectin, and JAK/hopscotch for the immune system response (ISR). Quantitative real-time PCR was used to evaluate the expression levels of the selected genes in short-term treatments (up to 120') at high temperatures (35 °C and 39 °C). Exposing P. olivacea to elevated temperatures resulted in HSR induction with increased expression of specific heat shock genes, suggesting the potential of HSPs as early indicators of acute thermal stress. Surprisingly, we found that heat shock represses multiple immune genes, revealing the antagonist relation between the heat shock response and the innate immune response in P. olivacea. Our results also showed species-dependent gene responses, with more significant effects in P. olivacea, for most of the biomarkers studied, demonstrating a higher sensitivity in this species to environmental stress conditions than that of C. riparius. This work shows a multi-species approach that enables a deeper understanding of the effects of heat stress at the molecular level in aquatic dipterans.

Selective effects of a short transient environmental fluctuation on a natural population

Natural populations experience continuous and often transient changes of environmental conditions. These in turn may result in fluctuating selection pressures leading to variable demographic and evolutionary population responses. Rapid adaptation as short-term response to a sudden environmental change has in several cases been attributed to polygenic traits, but the underlying genomic dynamics and architecture are poorly understood. In this study, we took advantage of a natural experiment in an insect population of the non-biting midge Chironomus riparius by monitoring genome-wide allele frequencies before and after a cold snap event. Whole genome pooled sequencing of time series samples revealed 10 selected haplotypes carrying ancient polymorphisms, partially with signatures of balancing selection. By constantly cold exposing genetically variable individuals in the laboratory, we could demonstrate with whole genome resequencing (i) that among the survivors, the same alleles rose in frequency as in the wild, and (ii) that the identified variants additively predicted fitness (survival time) of its bearers. Finally, by simultaneously sequencing the genome and the transcriptome of cold exposed individuals we could tentatively link some of the selected SNPs to the cis- and trans-regulation of genes and pathways known to be involved in cold response of insects, such as cytochrome P450 and fatty acid metabolism. Altogether, our results shed light on the strength and speed of selection in natural populations and the genomic architecture of its underlying polygenic trait. Population genomic time series data thus appear as promising tool for measuring the selective tracking of fluctuating selection in natural populations.

Population Genomic Time Series Data of a Natural Population Suggests Adaptive Tracking of Fluctuating Environmental Changes

Natural populations are constantly exposed to fluctuating environmental changes that negatively affect their fitness in unpredictable ways. While theoretical models show the possibility of counteracting these environmental changes through rapid evolutionary adaptations, there have been few empirical studies demonstrating such adaptive tracking in natural populations. Here, we analyzed environmental data, fitness-related phenotyping and genomic time-series data sampled over 3 years from a natural Chironomus riparius (Diptera, Insecta) population to address this question. We show that the population's environment varied significantly on the time scale of the sampling in many selectively relevant dimensions, independently of each other. Similarly, phenotypic fitness components evolved significantly on the same temporal scale (mean 0.32 Haldanes), likewise independent from each other. The allele frequencies of 367,446 SNPs across the genome showed evidence of positive selection. Using temporal correlation of spatially coherent allele frequency changes revealed 35,574 haplotypes with more than one selected SNP. The mean selection coefficient for these haplotypes was 0.30 (s.d. = 0.68). The frequency changes of these haplotypes clustered in 46 different temporal patterns, indicating concerted, independent evolution of many polygenic traits. Nine of these patterns were strongly correlated with measured environmental variables. Enrichment analysis of affected genes suggested the implication of a wide variety of biological processes. Thus, our results suggest overall that the natural population of C. riparius tracks environmental change through rapid polygenic adaptation in many independent dimensions. This is further evidence that natural selection is pervasive at the genomic level and that evolutionary and ecological time scales may not differ at all, at least in some organisms.

Polyamide microplastic exposure elicits rapid, strong and genome-wide evolutionary response in the freshwater non-biting midge Chironomus riparius

Susceptibility to hazardous materials and contamination is largely determined by genetic make-up and evolutionary history of affected organisms. Yet evolutionary adaptation and microevolutionary processes triggered by contaminants are rarely considered in ecotoxicology. Using an evolve and resequencing approach, we investigated genome-wide responses of the midge C. riparius exposed to virgin polyamide microplastics (0-180 μm size range, at concentration 1 g kg^-1) during seven consecutive generations. The results were integrated to a parallel life-cycle experiment ran under the same exposure conditions. Emergence, life-cycle trait, showed first a substantial reduction in larval survival, followed by a rapid recovery within three generations. On the genomic level, we observed substantial selectively driven allele frequency changes (mean 0.566 ± 0.0879) within seven generations, associated with a mean selection coefficient of 0.322, indicating very strong selection pressure. Putative selection targets were mainly connected to oxidative stress in the microplastics exposed C. riparius population. This is the first multigenerational study on chironomids to provide evidence that upon exposure to polyamide microplastic there are changes on the genomic level, providing basis to rapid adaptation of aquatic organisms to microplastics.

Whole genome sequencing and RNA-seq evaluation allowed to detect Cd adaptation footprint in Chironomus riparius

Evolutionary adaptation and phenotypic plasticity are important processes on how organisms respond to pollutant exposure. We dissected here the contribution of both processes to increased tolerance in Chironomus riparius to cadmium (Cd) exposure in a multi-generation experiment and inferred the underlying genomic basis. We simulated environmentally realistic conditions by continuously increasing contaminant concentration in six replicates initiated with 1000 larvae each, three pre-exposed to Cd and three not exposed to Cd (no-Cd) over eight generations. We measured life-cycle traits, transcriptomic responses and genome-wide allele frequency changes from this evolve and resequencing (E&R) experiment. Overall, life cycle tests revealed little phenotypic adaptation to Cd exposure, but a slightly increase in survival in the first larval stage was observed. Population genomic analyses showed a strong genome-wide selective response in all replicates, highlighting two main biological functions involved in development and growth of the chironomids. Emphasizing that laboratory conditions continually exert selective pressure. However, the integration of the transcriptomic to the genomic data allowed to distinguish pathways specifically selected by the Cd exposure related to microtubules and organelles and cellular movement. Those pathways could be functionally related to an excretion of metals. Thus, our results indicate that genetic adaptation to Cd in C. riparius can happen within few generations under an environmentally relevant exposure scenario, but substantial phenotypic tolerance might take more time to arise. With our approach, we introduce an experimental setup to fill the existing gap in evolutionary ecotoxicology to investigate these early signs of genetic adaptation.

Photoperiod is an important seasonal selection factor in Chironomus riparius (Diptera: Chironomidae)

Most organisms respond and can adapt to photoperiodic changes. This affects measurable end points like developmental time, survival and fertility. For ectotherms like Chironomus riparius, temperature is the most studied environmental cue regulating their life cycle, whereas photoperiodic influence is neglected. However, the developmental speed between summer and winter seasons of a field population could not be explained solely by temperature variations. Therefore, to have a comprehensive view on how photoperiods influence chironomid’s life cycle, we investigated if it plays a role in their development and if it acts as an important selective pressure on developmental time speed. To this end, first emerged C. riparius were artificially selected for seven generations. Pre-selected and unselected organisms could develop and breed independently under three light regimes: constant light (24:0 L:D), long days (16:8 L:D) and short days (8:16 L:D). Adult emergence, mean and median emergence time and fertility were integrated into the population growth rate to compare fitness. Our findings show that although developmental time is extended under short days, this same condition may exert a selective pressure towards a shorter development. Moreover, by also using photoperiodic clues to anticipate environmental changes, chironomids can potentially adapt to alterations in climate.

Altered gene expression in Chironomus riparius (insecta) in response to tire rubber and polystyrene microplastics

The extent until which plastics are present in our surrounding environment completely exceeds our expectations. Plastic materials in the form of microplastics have been found in terrestrial, freshwater and marine environments and are transported through the atmosphere even to remote locations. However, we are still far from understanding the effects that they may have caused and are causing to biota. In the present study, we investigated the alterations in the expression of twelve genes in the aquatic insect Chironomus riparius after 36 h exposures to polystyrene and tire rubber microplastics at nominal concentrations of 1 and 10 mg L^-1. The results indicated that several genes encoding for heat shock proteins (hsp90, Glycoprotein 93 (Gp93), hsc70, hsp60, hsp40, and the small HSP hsp17) were overexpressed respect to the control. In addition, the genes coding for manganese superoxide dismutase (SOD Mn, related to alleviation of oxidative stress) and for the FK506-binding protein of 39 kDa. (FKBP39, related to development and pupation) showed altered expression. Most of the alterations on gene expression level occurred at a concentration of 10 mg L^-1 of tire rubber microplastics, although specific modifications arose at other concentrations of both rubber and polystyrene. On the contrary, one hsp gene (hsp10) and genes related to biotransformation and detoxification (Cyp9f2, Cyp12a2, and ABCB6) did not alter their expression in any of the treatments. Overall, the results of the gene expression indicated that microplastics (especially tire rubber) or their additives caused cellular stress that led to some alterations in the normal gene expression but did not cause any mortality after 36 h. These results highlight the need for more studies that describe the alterations caused by microplastics at the molecular level. Additionally, it opens questions about the effects caused to aquatic fauna in environmental realistic situations, especially in hot spots of microplastic contamination (e.g., tire rubber released in storm water runoff discharge points).

Measuring mutagenicity in ecotoxicology: A case study of Cd exposure in Chironomus riparius

Existing mutagenicity tests for metazoans lack the direct observation of enhanced germline mutation rates after exposure to anthropogenic substances, therefore being inefficient. Cadmium (Cd) is a metal described as a mutagen in mammalian cells and listed as a group 1 carcinogenic and mutagenic substance. But Cd mutagenesis mechanism is not yet clear. Therefore, in the present study, we propose a method coupling short-term mutation accumulation (MA) lines with subsequent whole genome sequencing (WGS) and a dedicated data analysis pipeline to investigate if chronic Cd exposure on Chironomus riparius can alter the rate at which de novo point mutations appear. Results show that Cd exposure did not affect the basal germline mutation rate nor the mutational spectrum in C. riparius, thereby arguing that exposed organisms might experience a range of other toxic effects before any mutagenic effect may occur. We show that it is possible to establish a practical and easily implemented pipeline to rapidly detect germ cell mutagens in a metazoan test organism. Furthermore, our data implicate that it is questionable to transfer mutagenicity assessments based on in vitro methods to complex metazoans.

Genomic divergence landscape in recurrently hybridizing Chironomus sister taxa suggests stable steady state between mutual gene flow and isolation

Divergence is mostly viewed as a progressive process often initiated by selection targeting individual loci, ultimately resulting in ever increasing genomic isolation due to linkage. However, recent studies show that this process may stall at intermediate stable equilibrium states without achieving complete genomic isolation. We tested the extent of genomic isolation between two recurrently hybridizing nonbiting midge sister taxa, Chironomus riparius and Chironomus piger, by analyzing the divergence landscape. Using a principal component-based method, we estimated that only about 28.44% of the genomes were mutually isolated, whereas the rest was still exchanged. The divergence landscape was fragmented into isolated regions of on average 30 kb, distributed throughout the genome. Selection and divergence time strongly influenced lengths of isolated regions, whereas local recombination rate only had minor impact. Comparison of divergence time distributions obtained from several coalescence-simulated divergence scenarios with the observed divergence time estimates in an approximate Bayesian computation framework favored a short and concluded divergence event in the past. Most divergence happened during a short time span about 4.5 million generations ago, followed by a stable equilibrium between mutual gene flow through ongoing hybridization for the larger part of the genome and isolation in some regions due to rapid purifying selection of introgression, supported by high effective population sizes and recombination rates.

Parallel gene expression evolution in natural and laboratory evolved populations

Ecological adaptation is frequently inferred by the comparison of natural populations from different environments. Nevertheless, inference of the selective forces suffers the challenge that many environmental factors covary. With well-controlled environmental conditions, experimental evolution provides a powerful approach to complement the analysis of natural populations. On the other hand, it is apparent that laboratory conditions differ in many ways from natural environments, which raises the question as to what extent selection responses in experimental evolution studies can inform us about adaptation processes in the wild. In this study, we compared the expression profiles of replicated Drosophila melanogaster populations which have been exposed to two distinct temperature regimes (18/28 and 10/20°C) in the laboratory for more than 80 generations. Using gene-wise differential expression analysis and co-expression network analysis, we identified 541 genes and three coregulated gene modules that evolved in the same direction in both temperature regimes, and most of these changes probably reflect an adaptation to the space constraint or diurnal temperature fluctuation that is common in both selection regimes. In total, 203 genes and seven modules evolved temperature-specific expression changes. Remarkably, we detected a significant overlap of these temperature-adaptive genes/modules from experimental evolution with temperature-adaptive genes inferred from natural Drosophila populations covering two different temperature clines. We conclude that well-designed experimental evolution studies are a powerful tool to dissect evolutionary responses.

Can laboratory evolution experiments teach us about natural populations?

The ability to predict how natural populations will evolve and adapt to major changes in environmental conditions has long been of interest to evolutionary biologists and ecologists alike. The reality of global climate change has also created a pressing need for advancement in this particular area of research, as species are increasingly faced with rapid shifts in abiotic and biotic conditions. Evolutionary genomics has the potential to be incredibly useful as we move forward in addressing this need and in particular, evolve and resequence (E&R) studies-where researchers combine experimental evolution with whole-genome sequencing-have an important role to play. However, while E&R studies have shown a great deal of promise in tackling fundamental questions regarding the genetics of adaptation (Long et al., 2015; Schlötterer et al., 2014), it is unclear whether results from laboratory experiments can be directly translated to natural populations. In a From the Cover article in this issue of Molecular Ecology, Hsu et al. (Mol Ecol, 29, 2020) explicitly contend with this issue by examining the overlap between genes implicated in thermal adaptation in a Drosophila melanogaster E&R study and genes identified by comparing natural populations from different latitudinal clines. They report significant correlations between the two sets of temperature-adaptive genes and ultimately conclude that E&R studies can indeed generate insights applicable to populations inhabiting complex natural environments. While more work is needed to assess the generality of these conclusions, Hsu and Belmouaden (Mol Ecol, 29, 2020) contribute an important precedent.

A multigenerational approach can detect early Cd pollution in Chironomus riparius

Cadmium (Cd) is a non-essential highly toxic metal and its presence in the environment has been a concern over the years. On the present study we adopt the spiked water exposure scenario to study early Cd contamination across five generations of the model organism Chironomus riparius. Animals were, at the beginning of each generation, submitted to 0, 1, 3.2, 10, 32 and 100 μg/L of Cd. Classical endpoints like total emergence, EmT50, fertility and the integrative fitness measure, population growth rate (PGR), were calculated at each generation. Results could demonstrate that exposure to brief and low Cd concentrations can affect all the measured endpoints and, therefore, initial Cd pollution in previously unpolluted sites can be detected after just five consecutive generations. Importantly, at 100 μg/L of Cd fertility was greatly impaired after three generations. Also, PGR calculation is a sensitive tool for monitoring early pollution of Cd. Yet, no adaptation to Cd over five generations could be observed on the present experimental setup.

Multi-Level Gene Expression in Response to Environmental Stress in Aquatic Invertebrate Chironomids: Potential Applications in Water Quality Monitoring

In freshwater ecosystems, aquatic invertebrates are influenced continuously by both physical stress and xenobiotics. Chironomids (Diptera; Chironomidae), or non-biting midges, are the most diverse and abundant invertebrates in freshwater habitats. They are a fundamental link in food chains of aquatic ecosystems. Chironomid larvae tolerate stress factors in their environments via various physiological processes. At the molecular level, environmental pollutants induce multi-level gene responses in Chironomus that regulate cellular protection through the activation of defense processes. This paper reviews literature on the transcriptional responses of biomarker genes to environmental stress in chironomids at the molecular level, in studies conducted from 1991 to 2020 (120 selected literatures of 374 results with the keywords "Chironomus and gene expression" by PubMed search tool). According to these studies, transcriptional responses in chironomids vary depending on the type of stress factor and defensive responses associated with antioxidant activity, the endocrine system, detoxification, homeostasis and stress response, energy metabolism, ribosomal machinery, apoptosis, DNA repair, and epigenetics. These data could provide a comprehensive overview of how Chironomus species respond to pollutants in aquatic environments. Furthermore, the transcriptomic data could facilitate the development of genetic tools for water quality and environmental monitoring based on resident chironomid species.

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.