Independently evolved pollution resistance in four killifish populations is largely explained by few variants of large effect.

The genetic architecture of phenotypic traits can affect the mode and tempo of trait evolution. Human-altered environments can impose strong natural selection, where successful evolutionary adaptation requires swift and large phenotypic shifts. In these scenarios, theory predicts that adaptation is due to a few adaptive variants of large effect, but empirical studies that have revealed the genetic architecture of rapidly evolved phenotypes are rare, especially for populations inhabiting polluted environments. Fundulus killifish have repeatedly evolved adaptive resistance to extreme pollution in urban estuaries. Prior studies, including genome scans for signatures of natural selection, have revealed some of the genes and pathways important for evolved pollution resistance, and provide context for the genotype-phenotype association studies reported here. We created multiple quantitative trait locus (QTL) mapping families using progenitors from four different resistant populations, and using RAD-seq genetically mapped variation in sensitivity (developmental perturbations) following embryonic exposure to a model toxicant PCB-126. We found that one to two large-effect QTL loci accounted for resistance to PCB-mediated developmental toxicity. QTLs harbored candidate genes that govern the regulation of aryl hydrocarbon receptor (AHR) signaling. One QTL locus was shared across all populations and another was shared across three populations. One QTL locus showed strong signatures of recent natural selection in the corresponding wild population but another QTL locus did not. Some candidate genes for PCB resistance inferred from genome scans in wild populations were identified as QTL, but some key candidate genes were not. We conclude that rapidly evolved resistance to the developmental defects normally caused by PCB-126 is governed by few genes of large effect. However, other aspects of resistance beyond developmental phenotypes may be governed by additional loci, such that comprehensive resistance to PCB-126, and to the mixtures of chemicals that distinguish urban estuaries more broadly, may be more genetically complex.

Independently evolved pollution resistance in four killifish populations is largely explained by few variants of large effect.

The genetic architecture of phenotypic traits can affect the mode and tempo of trait evolution. Human-altered environments can impose strong natural selection, where successful evolutionary adaptation requires swift and large phenotypic shifts. In these scenarios, theory predicts the influence of few adaptive variants of large effect, but empirical studies that have revealed the genetic architecture of rapidly evolved phenotypes are rare, especially for populations inhabiting polluted environments. Fundulus killifish have repeatedly evolved adaptive resistance to extreme pollution in urban estuaries. Prior studies, including genome scans for signatures of natural selection, have revealed some of the genes and pathways important for evolved pollution resistance, and provide context for the genotype-phenotype association studies reported here. We created multiple quantitative trait locus (QTL) mapping families using progenitors from four different resistant populations, and genetically mapped variation in sensitivity (developmental perturbations) following embryonic exposure to a model toxicant PCB-126. We found that a few large-effect QTL loci accounted for resistance to PCB-mediated developmental toxicity. QTLs harbored candidate genes that govern the regulation of aryl hydrocarbon receptor (AHR) signaling, where some (but not all) of these QTL loci were shared across all populations, and some (but not all) of these loci showed signatures of recent natural selection in the corresponding wild population. Some strong candidate genes for PCB resistance inferred from genome scans in wild populations were identified as QTL, but some key candidate genes were not. We conclude that rapidly evolved resistance to the developmental defects normally caused by PCB-126 is governed by few genes of large effect. However, other aspects of resistance beyond developmental phenotypes may be governed by additional loci, such that comprehensive resistance to PCB-126, and to the mixtures of chemicals that distinguish urban estuaries more broadly, may be more genetically complex.

To stripe or not to stripe: the origin of a novel foliar pigmentation pattern in monkeyflowers (Mimulus).

The origin of phenotypic novelty is one of the most challenging problems in evolutionary biology. Although genetic regulatory network rewiring or co-option has been widely recognised as a major contributor, in most cases how such genetic rewiring/co-option happens is completely unknown. We have studied a novel foliar pigmentation pattern that evolved recently in the monkeyflower species Mimulus verbenaceus. Through genome-wide association tests using wild-collected samples, experimental crosses of laboratory inbred lines, gene expression analyses, and functional assays, we identified an anthocyanin-activating R2R3-MYB gene, STRIPY, as the causal gene triggering the emergence of the discrete, mediolateral anthocyanin stripe in the M. verbenaceus leaf. Chemical mutagenesis revealed the existence of upstream activators and repressors that form a 'hidden' prepattern along the leaf proximodistal axis, potentiating the unique expression pattern of STRIPY. Population genomics analyses did not reveal signatures of positive selection, indicating that nonadaptive processes may be responsible for the establishment of this novel trait in the wild. This study demonstrates that the origin of phenotypic novelty requires at least two separate phases, potentiation and actualisation. The foliar stripe pattern of M. verbenaceus provides an excellent platform to probe the molecular details of both processes in future studies.

Developing a High-Quality Linkage Map for the Atlantic Killifish Fundulus heteroclitus.

Killifish (Fundulus heteroclitus) are widely distributed among different aquatic environments where they demonstrate an impressive range of highly-plastic and locally adaptive phenotypes. High-throughput sequencing has begun to unravel the mechanisms and evolutionary history of these interesting features by establishing relationships in the genotype-phenotype map. However, some genotype-phenotype analyses require a higher order of contiguity than what initial scaffolded (fragmented genome assembly where contigs have been assemble into scaffolds) genome assemblies can provide. Here, we used 5,685 high-quality RAD-Seq markers from a single mapping family to order 84% of the scaffolded genome assembly to 24 chromosomes. This serves to: 1) expand the killifish genomic toolkit, 2) estimate genome-wide recombination rates, and 3) compare genome synteny to humans and other fishes. After initially building our map, we found that the selection of thresholds for sequence data filtration highly impacted scaffold placement in the map. We outline each step of the approach that dramatically improved our map to help guide others toward more effective linkage mapping for genome assembly. Our final map supports strong conservation of genomic synteny among closely related fish species and reveals previously described chromosomal rearrangements between more distantly related clades. However, we also commonly found minor scaffold misorientations in F. heteroclitus and in other assemblies, suggesting that further mapping (such as optical mapping) is necessary for finer scale resolution of genome structure. Lastly, we discuss the problems that would be expected from misoriented/unplaced scaffolds and stress the importance of a quality mapped genome as a key feature for further investigating population and comparative genomic questions with F. heteroclitus and other taxa.

Adaptive introgression enables evolutionary rescue from extreme environmental pollution.

Radical environmental change that provokes population decline can impose constraints on the sources of genetic variation that may enable evolutionary rescue. Adaptive toxicant resistance has rapidly evolved in Gulf killifish (Fundulus grandis) that occupy polluted habitats. We show that resistance scales with pollution level and negatively correlates with inducibility of aryl hydrocarbon receptor (AHR) signaling. Loci with the strongest signatures of recent selection harbor genes regulating AHR signaling. Two of these loci introgressed recently (18 to 34 generations ago) from Atlantic killifish (F. heteroclitus). One introgressed locus contains a deletion in AHR that confers a large adaptive advantage [selection coefficient (s) = 0.8]. Given the limited migration of killifish, recent adaptive introgression was likely mediated by human-assisted transport. We suggest that interspecies connectivity may be an important source of adaptive variation during extreme environmental change.

Phylogenomic analysis of Fundulidae (Teleostei: Cyprinodotiformes) using RNA-sequencing data.

Fishes of the New World cyprinodontiform family Fundulidae display a wide variety of tolerance to environmental conditions, making them a valuable model system for comparative, evolutionary, and environmental studies. Despite numerous attempts to resolve the phylogenetic relationships of family Fundulidae, the basal structure of the phylogeny remains unresolved. The lack of a robust and fully resolved phylogeny for family Fundulidae and its most speciose genus Fundulus is an impediment to future research. This study utilized novel RNA-sequencing data for phylogenetic inference among16 members of Fundulidae to better refine the basal nodes of the family and confront long-standing questions regarding (1) the monophyletic status of genus Fundulus, and validity of the Lucania and recently synonymized Adinia genera; (2) the relationship of the west coast endemic Fundulus parvipinnis and F. lima to other Fundulus species; and (3) the validity of subgeneric classifications. In addition, previously published nuclear gene sequences for 32 Fundulidae species were re-analyzed in combination with novel RNA-sequencing data. Maximum likelihood and Bayesian analyses generated identical phylogenies with strong statistical support at nearly all nodes, demonstrating the utility of RNA-sequencing data in constructing robust phylogenies not achievable by previous methods. While many past hypothesized evolutionary relationships for Fundulidae were reinforced, several alternative relationships are hypothesized at basal nodes resulting in a re-analysis of the deeper structure of family Fundulidae. These results reveal family Fundulidae as a paraphyletic grouping of members of genus Fundulus and Lucania and supports the previous synonymy of genus Adinia with genus Fundulus.

When evolution is the solution to pollution: Key principles, and lessons from rapid repeated adaptation of killifish (Fundulus heteroclitus) populations.

For most species, evolutionary adaptation is not expected to be sufficiently rapid to buffer the effects of human-mediated environmental changes, including environmental pollution. Here we review how key features of populations, the characteristics of environmental pollution, and the genetic architecture underlying adaptive traits, may interact to shape the likelihood of evolutionary rescue from pollution. Large populations of Atlantic killifish (Fundulus heteroclitus) persist in some of the most contaminated estuaries of the United States, and killifish studies have provided some of the first insights into the types of genomic changes that enable rapid evolutionary rescue from complexly degraded environments. We describe how selection by industrial pollutants and other stressors has acted on multiple populations of killifish and posit that extreme nucleotide diversity uniquely positions this species for successful evolutionary adaptation. Mechanistic studies have identified some of the genetic underpinnings of adaptation to a well-studied class of toxic pollutants; however, multiple genetic regions under selection in wild populations seem to reflect more complex responses to diverse native stressors and/or compensatory responses to primary adaptation. The discovery of these pollution-adapted killifish populations suggests that the evolutionary influence of anthropogenic stressors as selective agents occurs widely. Yet adaptation to chemical pollution in terrestrial and aquatic vertebrate wildlife may rarely be a successful "solution to pollution" because potentially adaptive phenotypes may be complex and incur fitness costs, and therefore be unlikely to evolve quickly enough, especially in species with small population sizes.

Ryanodine receptor and FK506 binding protein 1 in the Atlantic killifish (Fundulus heteroclitus): A phylogenetic and population-based comparison.

Non-dioxin-like polychlorinated biphenyls (NDL PCBs) activate ryanodine receptors (RyR), microsomal Ca2+ channels of broad significance. Teleost fish may be important models for NDL PCB neurotoxicity, and we used sequencing databases to characterize teleost RyR and FK506 binding protein 12 or 12.6kDa (genes FKBP1A; FKBP1B), which promote NDL PCB-triggered Ca2+ dysregulation. Particular focus was placed on describing genes in the Atlantic killifish (Fundulus heteroclitus) genome and searching available RNA-sequencing datasets for single nucleotide variants (SNV) between PCB tolerant killifish from New Bedford Harbor (NBH) versus sensitive killifish from Scorton Creek (SC), MA. Consistent with the teleost whole genome duplication (tWGD), killifish have six RyR genes, corresponding to a and b paralogs of mammalian RyR1, 2 and 3. The presence of six RyR genes was consistent in all teleosts investigated including zebrafish. Killifish have four FKBP1; one FKBP1b and three FKBP1a named FKBP1aa, FKBP1ab, likely from the tWGD and a single gene duplicate FKBP1a3 suggested to have arisen in Atherinomorphae. The RyR and FKBP1 genes displayed tissue and developmental stage-specific mRNA expression, and the previously uncharacterized RyR3, herein named RyR3b, and all FKBP1 genes were prominent in brain. We identified a SNV in RyR3b encoding missense mutation E1458D. In NBH killifish, 57% were heterozygous and 28% were homozygous for this SNV, whereas almost all SC killifish (94%) lacked the variant (n≥39 per population). The outlined sequence differences between mammalian and teleost RyR and FKBP1 together with outlined population differences in SNV frequency may contribute to our understanding of NDL PCB neurotoxicity.

The genomic landscape of rapid repeated evolutionary adaptation to toxic pollution in wild fish.

Atlantic killifish populations have rapidly adapted to normally lethal levels of pollution in four urban estuaries. Through analysis of 384 whole killifish genome sequences and comparative transcriptomics in four pairs of sensitive and tolerant populations, we identify the aryl hydrocarbon receptor-based signaling pathway as a shared target of selection. This suggests evolutionary constraint on adaptive solutions to complex toxicant mixtures at each site. However, distinct molecular variants apparently contribute to adaptive pathway modification among tolerant populations. Selection also targets other toxicity-mediating genes and genes of connected signaling pathways; this indicates complex tolerance phenotypes and potentially compensatory adaptations. Molecular changes are consistent with selection on standing genetic variation. In killifish, high nucleotide diversity has likely been a crucial substrate for selective sweeps to propel rapid adaptation.

Community trees: Identifying codiversification in the Páramo dipteran community.

Groups of codistributed species that responded in a concerted manner to environmental events are expected to share patterns of evolutionary diversification. However, the identification of such groups has largely been based on qualitative, post hoc analyses. We develop here two methods (posterior predictive simulation [PPS], Kuhner-Felsenstein [K-F] analysis of variance [ANOVA]) for the analysis of codistributed species that, given a group of species with a shared pattern of diversification, allow empiricists to identify those taxa that do not codiversify (i.e., "outlier" species). The identification of outlier species makes it possible to jointly estimate the evolutionary history of co-diversifying taxa. To evaluate the approaches presented here, we collected data from Páramo dipterans, identified outlier species, and estimated a "community tree" from species that are identified as having codiversified. Our results demonstrate that dipteran communities from different Páramo habitats in the same mountain range are more closely related than communities in other ranges. We also conduct simulation testing to evaluate this approach. Results suggest that our approach provides a useful addition to comparative phylogeographic methods, while identifying aspects of the analysis that require careful interpretation. In particular, both the PPS and K-F ANOVA perform acceptably when there are one or two outlier species, but less so as the number of outliers increases. This is likely a function of the corresponding degradation of the signal of community divergence; without a strong signal from a codiversifying community, there is no dominant pattern from which to detect an outlier species. For this reason, both the magnitude of K-F distance distribution and outside knowledge about the phylogeographic history of each putative member of the community should be considered when interpreting the results.

Functional genomics to assess biological responses to marine pollution at physiological and evolutionary timescales: toward a vision of predictive ecotoxicology.

Marine pollution is ubiquitous, and is one of the key factors influencing contemporary marine biodiversity worldwide. To protect marine biodiversity, how do we surveil, document and predict the short- and long-term impacts of pollutants on at-risk species? Modern genomics tools offer high-throughput, information-rich and increasingly cost-effective approaches for characterizing biological responses to environmental stress, and are important tools within an increasing sophisticated kit for surveiling and assessing impacts of pollutants on marine species. Through the lens of recent research in marine killifish, we illustrate how genomics tools may be useful for screening chemicals and pollutants for biological activity and to reveal specific mechanisms of action. The high dimensionality of transcriptomic responses enables their usage as highly specific fingerprints of exposure, and these fingerprints can be used to diagnose environmental problems. We also emphasize that molecular pathways recruited to respond at physiological timescales are the same pathways that may be targets for natural selection during chronic exposure to pollutants. Gene complement and sequence variation in those pathways can be related to variation in sensitivity to environmental pollutants within and among species. Furthermore, allelic variation associated with evolved tolerance in those pathways could be tracked to estimate the pace of environmental health decline and recovery. We finish by integrating these paradigms into a vision of how genomics approaches could anchor a modernized framework for advancing the predictive capacity of environmental and ecotoxicological science.

Posterior predictive checks of coalescent models: P2C2M, an R package.

Bayesian inference operates under the assumption that the empirical data are a good statistical fit to the analytical model, but this assumption can be challenging to evaluate. Here, we introduce a novel r package that utilizes posterior predictive simulation to evaluate the fit of the multispecies coalescent model used to estimate species trees. We conduct a simulation study to evaluate the consistency of different summary statistics in comparing posterior and posterior predictive distributions, the use of simulation replication in reducing error rates and the utility of parallel process invocation towards improving computation times. We also test P2C2M on two empirical data sets in which hybridization and gene flow are suspected of contributing to shared polymorphism, which is in violation with the coalescent model: Tamias chipmunks and Myotis bats. Our results indicate that (i) probability-based summary statistics display the lowest error rates, (ii) the implementation of simulation replication decreases the rate of type II errors, and (iii) our r package displays improved statistical power compared to previous implementations of this approach. When probabilistic summary statistics are used, P2C2M corroborates the assumption that genealogies collected from Tamias and Myotis are not a good fit to the multispecies coalescent model. Taken as a whole, our findings argue that an assessment of the fit of the multispecies coalescent model should accompany any phylogenetic analysis that estimates a species tree.

Poor fit to the multispecies coalescent is widely detectable in empirical data.

Model checking is a critical part of Bayesian data analysis, yet it remains largely unused in systematic studies. Phylogeny estimation has recently moved into an era of increasingly complex models that simultaneously account for multiple evolutionary processes, the statistical fit of these models to the data has rarely been tested. Here we develop a posterior predictive simulation-based model check for a commonly used multispecies coalescent model, implemented in *BEAST, and apply it to 25 published data sets. We show that poor model fit is detectable in the majority of data sets; that this poor fit can mislead phylogenetic estimation; and that in some cases it stems from processes of inherent interest to systematists. We suggest that as systematists scale up to phylogenomic data sets, which will be subject to a heterogeneous array of evolutionary processes, critically evaluating the fit of models to data is an analytical step that can no longer be ignored.

How to fail at species delimitation.

Species delimitation is the act of identifying species-level biological diversity. In recent years, the field has witnessed a dramatic increase in the number of methods available for delimiting species. However, most recent investigations only utilize a handful (i.e. 2-3) of the available methods, often for unstated reasons. Because the parameter space that is potentially relevant to species delimitation far exceeds the parameterization of any existing method, a given method necessarily makes a number of simplifying assumptions, any one of which could be violated in a particular system. We suggest that researchers should apply a wide range of species delimitation analyses to their data and place their trust in delimitations that are congruent across methods. Incongruence across the results from different methods is evidence of either a difference in the power to detect cryptic lineages across one or more of the approaches used to delimit species and could indicate that assumptions of one or more of the methods have been violated. In either case, the inferences drawn from species delimitation studies should be conservative, for in most contexts it is better to fail to delimit species than it is to falsely delimit entities that do not represent actual evolutionary lineages.

Phylogenetic estimation error can decrease the accuracy of species delimitation: a Bayesian implementation of the general mixed Yule-coalescent model.

BACKGROUND: Species are considered the fundamental unit in many ecological and evolutionary analyses, yet accurate, complete, accessible taxonomic frameworks with which to identify them are often unavailable to researchers. In such cases DNA sequence-based species delimitation has been proposed as a means of estimating species boundaries for further analysis. Several methods have been proposed to accomplish this. Here we present a Bayesian implementation of an evolutionary model-based method, the general mixed Yule-coalescent model (GMYC). Our implementation integrates over the parameters of the model and uncertainty in phylogenetic relationships using the output of widely available phylogenetic models and Markov-Chain Monte Carlo (MCMC) simulation in order to produce marginal probabilities of species identities. RESULTS: We conducted simulations testing the effects of species evolutionary history, levels of intraspecific sampling and number of nucleotides sequenced. We also re-analyze the dataset used to introduce the original GMYC model. We found that the model results are improved with addition of DNA sequence and increased sampling, although these improvements have limits. The most important factor in the success of the model is the underlying phylogenetic history of the species under consideration. Recent and rapid divergences result in higher amounts of uncertainty in the model and eventually cause the model to fail to accurately assess uncertainty in species limits. CONCLUSION: Our results suggest that the GMYC model can be useful under a wide variety of circumstances, particularly in cases where divergences are deeper, or taxon sampling is incomplete, as in many studies of ecological communities, but that, in accordance with expectations from coalescent theory, rapid, recent radiations may yield inaccurate results. Our implementation differs from existing ones in two ways: it allows for the accounting for important sources of uncertainty in the model (phylogenetic and in parameters specific to the model) and in the specification of informative prior distributions that can increase the precision of the model. We have incorporated this model into a user-friendly R package available on the authors' websites.

An information-theoretical approach to phylogeography.

Data analysis in phylogeographic investigations is typically conducted in either a qualitative manner, or alternatively via the testing of null hypotheses. The former, where inferences about population processes are derived from geographical patterns of genetic variation, may be subject to confirmation bias and prone to overinterpretation. Testing the predictions of null hypotheses is arguably less prone to bias than qualitative approaches, but only if the tested hypotheses are biologically meaningful. As it is difficult to know a priori if this is the case, there is the general need for additional methodological approaches in phylogeographic research. Here, we explore an alternative method for analysing phylogeographic data that utilizes information theory to quantify the probability of multiple hypotheses given the data. We accomplish this by augmenting the model-selection procedure implemented in ima with calculations of Akaike Information Criterion scores and model probabilities. We generate a ranking of 17 models each representing a set of historical evolutionary processes that may have contributed to the evolution of Plethodon idahoensis, and then quantify the relative strength of support for each hypothesis given the data using metrics borrowed from information theory. Our results suggest that two models have high probability given the data. Each of these models includes population divergence and estimates of ancestral theta that differ from estimates of descendent theta, inferences consistent with prior work in this system. However, the models disagree in that one includes migration as a parameter and one does not, suggesting that there are two regions of parameter space that produce model likelihoods that are similar in magnitude given our data. Results of a simulation study suggest that when data are simulated with migration, most of the optimal models include migration as a parameter, and further that when all of the shared polymorphism results from incomplete lineage sorting, most of the optimal models do not. The results could also indicate a lack of precision, which may be a product of the amount of data that we have collected. In any case, the information-theoretic metrics that we have applied to the analysis of our data are statistically rigorous, as are hypothesis-testing approaches, but move beyond the 'reject/fail to reject' dichotomy of conventional hypothesis testing in a manner that provides considerably more flexibility to researchers.