Cuba is the most populated country in the Caribbean and has a rich and heterogeneous genetic heritage. Here, we take advantage of dense genomic data from 860 Cuban individuals to reconstruct the genetic structure and ancestral origins of this population. We found distinct admixture patterns between and within the Cuban provinces. Eastern provinces have higher African and Native American ancestry contributions  than the rest of the Cuban provinces . Furthermore, in the Eastern Cuban region, we identified more intense sex-specific admixture patterns, strongly biased towards European male and African/Native American female ancestries. Our subcontinental ancestry analyses in Cuba highlight the Iberian population as the best proxy European source population, South American and Mesoamerican populations as the closest Native American ancestral component, and populations from West Central and Central Africa as the best proxy sources of the African ancestral component. Finally, we found complex admixture processes involving two migration pulses from both Native American and African sources. Most of the inferred Native American admixture events happened early during the Cuban colonial period, whereas the African admixture took place during the slave trade and more recently as a probable result of large-scale migrations from Haiti. According to archaeological evidence, two groups of hunter-fisher-gatherers associated with different cultures (Ortoiroid and Casimiroid), entered the archipelago at different times. The first group originated from northern South America (Venezuela and Guyana), settled in Trinidad around 6,000 BCE, and then expanded to the north along the Lesser Antilles2. The second group moved around 4,500–4,000 BCE from the Yucatan Peninsula to Hispaniola and Cuba—the largest island of the Greater Antilles2. Around 350 BCE, the arrival of Arawak-speaking people from Venezuela, associated with the horticulturalist Saladoid culture, changed the anthropological landscape in the Caribbean, and became the major group3. At the time of the first contacts with European settlers, Cuba was inhabited by three autochthonous groups: the “Guanahatabey”; the “Ciboney” or “Western Taíno”; and the “Classic Taíno” 3.The islands of the Caribbean were one of the last regions of the Americas to be colonized by anatomically modern humans4. The indigenous Cuban population was decimated during the early colonial period6. The Spanish settlers then started to bring sub-Saharan enslaved Africans8. During the transatlantic slave trade (TAST) from 1526 to 1875, approximately 853,000 enslaved Africans were forcibly deported to Cuba10. The vast majority (92%) arrived during the last phase of the TAST from 1801 to 187511. The most important embarkation regions were West-Central Africa , the Bight of Biafra , the Bight of Benin , Southeast Africa , Sierra Leone , the Gold Coast (4.0% from modem Ghana), the Senegambia , and the Windward Coast (1.2% from modem Liberia and Ivory Coast)11. While broad embarkation regions can be identified based on historical evidence12, the geographical origins of enslaved Africans forcibly displaced during the TAST remain unclear.Late in the fifteenth century, the arrival of Spanish settlers had a profound impact on the indigenous population of the Caribbean12. The nineteenth century witnessed the arrival of over 125,000 contract workers from China, almost exclusively males (99%), to work in the sugar plantations13. Although archaeologists and historians have reconstructed the migratory processes underlying Cuban demographic history, a number of long-standing questions remain unsolved, mostly due to the patchy archaeological and historical records6, and the incomplete and biased information regarding the illegal slave trade12.Throughout the colonial and post-colonial periods, European migrations coming to Cuba primarily originated from different regions of the Iberian Peninsula16. Based on a limited set of mitochondrial DNA (mtDNA) and Y-chromosome markers from 254 Cuban individuals, Mendizabal et al.14 highlighted a strong sex-bias in the admixture process, with male lineages mostly tracing to Europe and female lineages to Africa. Cintado et al.15 employed a small panel of seventeen ancestry informative markers (AIMs) to characterize admixture proportions in 206 individuals from Havana—the largest city in Cuba. Marcheco-Teruel et al.16 carried out admixture analyses using around 1,000 individuals from all the fifteen Cuban provinces, and a panel of 128 AIMs as well as diagnostic mtDNA and Y-chromosome markers. These authors reported extensive variation in admixture proportions in different Cuban regions. The studies highlighted above were hampered by the relatively small number of genetic markers considered. More recently, Moreno-Estrada et al.17 used genome-wide microarray data to study a diverse set of Caribbean populations, including 80 individuals from Cuba. They were able to investigate distinct subcontinental source populations. Likewise, other recent studies20 have employed dense genomic datasets to provide insights into the genetic structure of the Cuban population. However, the sample sizes of these studies were relatively small and did not capture well the demographic composition of the present Cuban population. Additionally, the number of continental reference populations considered in these studies was also quite limited.Previous genetic studies have provided relevant insights into the population history and admixture dynamics in Cuba16 to explore Cuba’s population structure and demographic history, by using a dense genome-wide SNP dataset of 860 individuals born in Cuba. Importantly, this Cuban sample covers all the fifteen Cuban provinces and is an excellent representation of the current distribution of the Cuban population in terms of sex, age, and population density. Based on both non-parametric and haplotype-based methods, we first describe genetic diversity patterns in the present-day Cuban population in relation to other worldwide populations, including Hispanic/Latino populations in the Americas. The inferred distributions of continental ancestries reflect broad-scale geographic admixture patterns across Cuba, and unravel regional differences within and between Cuban provinces. We then evaluate whether there are differences in patterns of sex-specific admixture in Cuba. To delve deeper into the founding of the Cuban population, we address hypotheses regarding the Cuban putative ancestral source populations by analysing genetic affinities with populations from specific regions in Africa, Europe, and the Americas. Furthermore, we address whether gene flow in the Cuban population has been the result of recent multiway migration events involving different continental sources. We applied a model-testing approach to infer and reconstruct admixture histories across Cuba in the context of the TAST and after its abolition. Overall, our research emphasizes finer-scale aspects of genetic diversity patterns in the current Cuban population, provides new insights on the geographical origins of enslaved Africans forced to move to Cuba, and highlights complex demographic histories during and after the slave trade period.Here, we substantially expand our previous research21 across all pairs of individuals in the dataset of Cuban and worldwide populations ter Fig. . These p26. Across Cuban provinces   results at the individual, municipal, and provincial scales were largely in agreement with the supervised and unsupervised ADMIXTURE results at K = 3 and K = 4  into two categories: short (between 5 and 50 cM) and long ancestry tracts (>50 cM). For each continental ancestry in each Cuban province, we then performed two types of analyses based on these data  between pairs of individuals from the Cuban population. This analysis highlights that individuals from the Eastern provinces  share more IBD segments than individuals from other Cuban provinces . For example, the differences estimated based on both sexes for European ancestry are highest in Granma (−17.7%), the differences for African ancestry are highest in Santiago de Cuba (7.8%), and the differences for Native American ancestry are highest in Las Tunas (7.9%) . The first principal component (PC1) separates the Southern and Northern European populations, while the PC2 splits the French Basque population from other European populations. In agreement with the known historical sources of European migrations to Cuba9, the Cuban haplotypes of European ancestry overlap with Southern European populations from Spain and Italy rather than with Northern or Central European populations. This result is supported by analyses indicating that, when comparing the Cuban haplotypes of European ancestry with haplotypes from European populations, the lowest ancestry-specific Weir and Cockerham’s weighted FST (WC-FST) values (0.0037) are observed between the Cuban and Iberian population  estimated between the Cuban Native American haplotypes and Native American haplotypes from different regions in South America  and more intense (17%) than in the rest of Cuba (range 6–7%)  migration pulse(s) for European, Native American, and African ancestries . Thus, supporting that a carefully selected AIM panel is an efficient tool to capture continental admixture proportions40.Cuba has a complex history of population migrationscas Fig. . Our stucas Fig. . We founcas Fig. . The admet al.16, the observed geographic admixture patterns in Cuba are fully consistent with archaeological and historical sources41. Estimates dating back to 1510 indicate that most of the indigenous groups in Cuba were located in the Eastern part of Cuba42, in which the most populated areas correspond to the present-day Holguin and Granma provinces, and where there is the highest concentration of Taíno archaeological sites43. Currently, both Eastern provinces have the highest Native American ancestry in Cuba  of the shared IBD between pairs of individuals 11, and more Spanish men than women migrating to that region (81% of Spanish immigrants)7. However, Marcheco-Teruel et al.16 showed that the Native American and African ancestry proportions in Cuba were higher in maternally-inherited mtDNA haplogroups  than in autosomal AIMs , and in turn, the autosomal AIMs estimates were higher than the paternally-inherited Y-chromosome haplogroups . Based on much denser autosomal and X-chromosome SNP data, we also find significant African/Native American contributions from the maternal side and European contributions from the paternal side in the current Cuban population 10. Our results indicate that the African ancestral component of Cuban individuals falls between Benin, Nigeria, Cameroon, Gabon, and Angola  in these two regions, which is notably earlier than in the Eastern region (1631–1660 CE)  Fig. .10, the slave trade in Eastern Cuba was less intensive and delayed compared to the rest of Cuba. For instance, in Santiago de Cuba, over 55,000 enslaved Africans disembarked from 1701 to 1875 (6.5% of the slave population in Cuba)10. However, our estimated ancestry fractions highlight stronger African ancestry and haplotype heterozygosities in the Eastern Cuban provinces such as Santiago de Cuba and Guantanamo  of African ancestry in the Caribbean17. Between 1913 and 1931, legal migration from Haiti to Cuba was estimated to be over 189,000 migrants, and illegal migration further brought in 450,000–600,000 migrants55. Our admixture dates (3–4 generations ago) evidence a recent second African migration pulse in Cuba that is especially high (15%) in the Eastern region, consistent with the expected impact of these Haitian large-scale migrations.According to historical sourcesamo Fig. . Furtheramo Fig. , suggest6. Nevertheless, this perspective has been challenged in recent studies56, which report the presence of indigenous communities living in Cuba long after the end of the seventeenth century. Our results support this latter perspective, since we evidenced a Native American genetic admixture pulse in the post-contact Cuban population form Western and Central Cuba, albeit of small absolute magnitude, between 7 and 8 generations ago.For the Native American ancestry, the first migration pulse occurred with a high intensity early during the colonial period, around 15 generations ago Fig. . This is57. For the African gene-flow, our subcontinental ancestry analyses point to populations from West-Central Africa and the Bights of Benin and Biafra regions as the major source populations of the African ancestral gene pool in Cuba. In addition, our results provide evidence of a strong and recent second African migration pulse in Eastern Cuba, most probably reflecting recent Haitian large-scale migrations. Overall, these new findings expand our understanding of the impact of demographic events associated with mass migrations and population admixture in Cuba, as well as the ancestral origins of the Cuban source populations, with unprecedented geographic resolution.In conclusion, Cuba has experienced major demographic migrations involving multiple indigenous groups, European settlers, and enslaved Africans, as well as recent intracontinental large-scale population movements in the Americas. The current Cuban population has different genetic patterns of admixture than other Hispanic/Latino populations, and there is also evidence of population structure across the island. European ancestry is higher in Western than in Eastern provinces, except for La Havana. Conversely, Eastern provinces have higher Native American and African ancestries, though there is also evidence of strong genetic differentiation within this region . Therefore, the extensive genetic structure observed within and between Cuban regions emphasizes the need to ensure appropriate representation of ancestrally diverse individuals in future biomedical and genetic association studies in Cuba47 was published elsewhere16.The original sample size comprised 1,019 voluntary participants born in Cuba representing all fifteen Cuban provinces  (Supplementary Methods). During the genome-wide quality control (QC) procedure, 97 samples were removed due to their high missing call rate (i.e. >1%). After some basic filtering based on Hardy-Weinberg (p < 10−6) and minor allele frequency (i.e. <1%), we created an initial dataset that includes 432,138 polymorphic autosomal SNP markers. We estimated genetic relatedness for all pairs of individuals using KING58 and PC-Relate59, and no first-degree or second-degree relatives were found , the remaining linkage disequilibrium (LD-) unpruned dataset includes 292,549 SNPs genotyped in 860 unrelated Cuban individuals . In addition, we assembled another LD-unpruned dataset only for X-chromosome SNP markers that includes 5,060 SNPs genotyped in 860 Cuban individuals.A total of 957 DNA samples were genotyped using the Infinium PsychArray v1.0 and v1.1 BeadChips (Illumina Inc.) at Statens Serum Institut, Denmark  to compute ASD between all pairs of individuals separately21. We represent the respective inter-individual pairwise ASD distance matrix into two- or three-dimensional metric MDS projections using the cmdscale function in R25. We then estimated genome-wide heterozygosities for the Cuba-World dataset. To avoid SNP-chip geographical ascertainment bias when calculating population SNP-by-SNP heterozygosities, we employed a haplotype heterozygosity approach following Verdu et al.25, which was derived from the method developed by Li et al.26, and using the recombination map from the HapMap Phase 2 project Build GRCh37/hg19.To better understand the genetic contribution from each continental source population to the genetic landscape of present-day Cuba, we merged our Cuban dataset with other datasets comprising 1,353 unrelated individuals from continental reference populations in Europe, Africa, America, and Asia . We first used SHAPEIT263 to generate haplotypic phased data for each assembled dataset, and then we ran RFMix in “PopPhased” mode using two steps of Expectation-Maximization algorithm (EM = 2)62. We collapsed inferred ancestry calls to calculate the average ancestry proportions for each individual haploid genome, Cuban municipality, and Cuban province. We focused on average ancestry proportions across all, short (between >5 and ≤50 cM), and long (>50 cM) ancestry tracts28.To estimate three- and four-way continental ancestry for each individual, we first used the clustering algorithm implemented in the software ADMIXTURE v1.3064 tool implemented in the software BEAGLE v4.165. The minimum length threshold was set to 3 cM66. We then estimated the total length of IBD segments (in Mb) shared IBD between pairs of individuals from the same province and different provinces in Cuba.To investigate the distribution of genomic IBD segments shared between pairs of individuals from the Cuba-World dataset, we use the Refined-IBDet al.29 to calculate the ΔAdmix ratio. We expect ΔAdmix ratios to be positive when there is an excess of female-specific admixture contributions from one specific ancestry; or negative when there is an excess of male-specific admixture instead29. Second, we applied Wilcoxon signed-rank two-sided unpaired test to assess the difference between the paired X-chromosome and autosomal ancestry proportions of individuals from each Cuban province17. Third, we estimated sex-specific admixture under the sex-specific admixture mechanistic modelling framework developed in (p. 271 in30), with a fixed number of 15 generations67.To explore if there is evidence of sex-specific admixture patterns in Cuba, we estimated admixture proportions in the X-chromosome dataset using RFMix (EM = 2), and compared them to the estimates based on autosomal data using three approaches. First, we applied the method proposed by Rishishwar asd v1.0 to compute ASD between all pairs of individuals separately for each assembled SNP dataset and visualize them in the MDS based on ASD, as described above. Second, we analysed ancestry calls estimated for each haploid individual in the RFMix analysis, to generate new datasets with non-masked reference haplotypes and masked Cuban haplotypes with different thresholds for each continental ancestry . The only exception was the analysis of Native American ancestry, in which we only used a 15% cutoff due to the fact that only one Cuban sample has more than 30% Native American ancestry. For each dataset, we used the MDS approach described in Browning et al.18, to perform MDS-based ASPCA for within-continental ancestry inference28. We found better overlapping for non-masked reference haplotypes and masked Cuban haplotypes with at least 40% of European ancestry, or 75% of African ancestry, or 15% of Native American ancestry, and plots from those thresholds were included in the manuscript  shared between Cuban individuals and individuals from different European, African and Native American populations.To investigate the ancestral origins of the Cuban population, we used haplotype-based methods for individual Cuban haploid genomes masked for one specific ancestry. To do so, we merged our Cuban dataset with publicly available whole-genome and genome-wide SNP datasets for European, African, and Native American ancestries  , to infer the admixture parameters (timing and intensity of admixture events) underlying the observed data37. We first pooled Cuban individuals into the three historical regions  that have administratively structured Cuba from 1827 to 187834. For each historical department, we then tested five admixture models with different admixture pulses. We started the first model with a founding admixture event between European and indigenous groups fifteen generations ago followed by a pulse of African admixture . Separately, we evaluated models adding an additional: African pulse , Native American pulse ; Native American and African pulse , and Native American, African, and European pulse . To identify the best-fitting model, we first fit each model with 1,000 starting parameter randomizations, and then evaluated the magnitude of log-likelihood of each competing model24. Finally, we calculated the dates of the admixture event assuming 29 years per generation70.To explore the recent migration history in Cuba, we applied the model-testing approach implemented in the TRACTS softwarecngm@infomed.sld.cu). Requests should be addressed to Dr. Hilda Roblejo, vice-president of the CNGM Research Ethics Committee (hilda.roblejo@infomed.sld.cu).The data that support the findings of this study are available from the Cuban Government but restrictions apply to the availability of these data, which were used under license for the current study, and so are not publicly available. Data are however available from the authors upon reasonable request and with permission of the Cuban Government. For accessing the data, within Cuban legal framework, contact the Cuban Centre of Medical Genetics (CNGM) Research Ethics Committee at Medical University of Havana (This study was conducted following the ethical principles for medical research included in the World Medical Association Declaration of Helsinki, and was approved by the CNGM Research Ethics Committee at Medical University of Havana, Cuba. Collected human DNA samples were obtained in Cuba, and each voluntary participant gave written informed consent prior to the private interview, physical examination, and blood sample collection.Supplementary MethodsAll supplementary Tables and supplementary FiguresSupplementary Tables S1-S10 in Excel


In addition, we successfully tested an approach to detect polygenic adaptation in biological pathways, allowing us to identify the flavonoid biosynthesis pathway as a candidate stress‐response pathway that deserves further attention in other plants. Finally, our study contributes to the emerging view that explaining contemporary standing genetic variation requires considering adaptation to past climates, especially for long‐lived trees.Detecting the molecular basis of local adaptation and identifying selective drivers is still challenging in nonmodel species. The use of purely population genetic approaches is limited by some characteristics of genetic systems, such as pleiotropy and polygenic control, and parallel evidence from phenotypic‐based experimental comparisons is required. In long‐lived organisms, the detection of selective pressures might also be precluded by evolutionary lag times in response to the environment. Here, we used the English yew to showcase an example of a multiscale integrative approach in a nonmodel species with limited plant and genomic resources. We combined information from two independent sources, phenotypes in a common environment and genomic data in natural populations, to investigate the signature of selection. Growth differences among populations in a common environment, and phenological patterns of both shoot elongation and male strobili maturation, were associated with climate clines, providing evidence for local adaptation and guiding us in the selection of populations for genomic analyses. We used information on over 25,000 SNPs from c. 1,200 genes to infer the demographic history and to test for molecular signatures of selection at different levels: SNP, gene, and biological pathway. Our results confirmed an overall demographic history of population decline, but we also found evidence for putative local adaptation at the molecular level. We identified or confirmed several candidate genes for positive and negative selection in forest trees, including the  We first addressed the phenotypic variability and potential adaptive responses of trees from a reduced but climatically heterogeneous part of the species range (Iberian Peninsula) growing in a common environment. From the results obtained, we designed an independent geographic sampling to enable a rangewide genomic analysis. Taking advantage of the recently available T. baccata transcriptome  was collected in 26 native populations from one‐year‐old shoots located on terminal branches. Due to the patchy distribution of the species, populations are easily defined as a group of reproducing individuals growing along ravines or hillsides and readily identified in the landscape. Clones were propagated through stem cuttings in growth chambers and later transferred outdoors. Plants were planted 2–3 m apart in a row and column layout without following any particular randomized design, replaced when dead, and watered if needed during summer. After accounting for ramets failing to establish, the available plant material included a total of 254 uneven aged (10–15 year old) clones  belonging to 108 genets (1–9 genets per population) distributed across six contrasted geographic regions in the Iberian Peninsula  of the leading current‐year shoot located in the two dominant (longest) stems in four consecutive years (2009–2012). We used the average value of both leading shoots as the response variable. According to the number of replicates available, the variability in growth was assessed using a Gaussian mixed model with Population, Sex, Year, and Population by Year interaction as categorical fixed factors. We used stem length at the beginning of our follow‐up study (2009) as a covariate. Genet and individual within genet were treated as random factors. Stem length and shoot volume were log‐transformed after residual analyses.First, we measured shoot growth, which is often considered as a fitness proxy in forest trees  to the total shoot length attained at the end of the growing season (October‐November). Measures of length were taken on the leading current‐year shoot of two dominant stems per individual and averaged before analyses. Male strobili maturation was assessed in two consecutive samplings (early and mid/late March) on tagged apical shoots and was estimated as the proportion of strobili shedding pollen using pooled data from both samplings. In both cases, we used mixed models to determine the effects of Population, Sex and Year, using genet and individual within genet as random effects. In the analysis of shoot elongation, we also tested for Sex by Year and Population by Year interactions. Models were conducted on the original scale assuming a Gaussian distribution of residuals. Strobili maturation was assessed in a subsample of 21 populations. Since several individuals and genets failed to reproduce every year, we performed 2 analyses. In the first, we used 14 populations allowing us to test for the effect of Population, Year, and their interaction. In the second, we tested only for Population and Year main effects using all populations. Models of the proportion of mature strobili were run assuming binomial random errors.lme4 package  and the last interglacial , in agreement with Mayol et al. .Phenotypic variability in the common garden suggested a potential cline of adaptation from cold, inland, continental climates to milder, temperate, and coastal ones (see Results). Based on these results, we sampled 12 populations throughout the European distribution of English yew spanning a range of variation from cold continental to milder temperate conditions Figure . Since wl et al. . Ten ind2.3T. baccata transcriptome  focused on the characterization of loci putatively involved in the adaptation of tree species to environment  and obtained a list of 344 genes of interest Table . Then, wT. baccata  were used to compute Ka/Ks and detect additional potential candidates under moderate/high positive evolution . From this approach, we obtained 345 candidate genes with > 450 bp length and functional annotation available, so the final number of candidate genes obtained from literature and sequence divergence ratios was 618 .Second, the transcriptomes of Finally, we completed our design including 516 genes with > 450 bp length for which functional annotation was available , despite not being selected as candidates initially by any of the two approaches. Thus, the final number of genes included in the study was 1,134 .2.4cutadapt  followed by next‐generation sequencing of captured regions on an Illumina platform. Probes were designed by Roche Tech‐Support in Madison  starting from the selected 1,134 gene sequences . Library preparation and targeted sequencing were outsourced to IGA Technology Services . Libraries were constructed by using KAPA DNA Library Preparation Kit  following the manufacturer's protocol and enrichment performed using NimbleGen solution‐based SeqCap EZ probe libraries kit. Cluster generation, template hybridization, isothermal amplification, linearization, blocking and denaturization, and hybridization of the sequencing primers were then performed on Illumina cBot and flow cell HiSeq SBS V4 50 cycle kit, loaded on HiSeq 2500 Illumina sequencer producing 50 bp single reads. The CASAVA version of the Illumina Pipeline 1.8.2 was used for base calling and de‐multiplexing. Adapters were masked using  Martin, . Masked The GATK pipeline was used for SNP calling, following GATK best practices for SNP filtering (–filterExpression “MQ0> = 4 && ((MQ0/(1.0 * DP)) > 0.1) || DP < 10.0 || Q < 50.0 || QD < 1.5 || FS > 60.0”), which allowed the initial identification of 52,904 SNPs. SNP data were further filtered using VCFtools v0.1.14 , the efficacy of selection evaluated as the ratio of nonsynonymous to synonymous nucleotide diversity (πa/πs), and neutrality tests  were computed using mstatspop (https://bioinformatics.cragenomica.es/numgenomics/people/sebas/software/software.html) on concatenated sequence files, both considering all populations together and separately for distinct geographic regions  and pairwise relatedness  to K = 12 . Runs were repeated three times, and averaged Q‐values  were used to draw pie charts in Figure stairway plot approach on unphased SNP data , the last glacial maximum  and the last interglacial  periods. We obtained data for eight climatic variables for each period: annual mean temperature, temperature seasonality (standard deviation), maximum temperature of the warmest month, minimum temperature of the coldest month, annual precipitation, precipitation of the wettest month, precipitation of the driest month, and precipitation seasonality (coefficient of variation). bayescenv was run for each of the standardized climatic variables with general default parameters. After 20 pilot runs of 2,000 iterations and a burn‐in of 50,000 iterations, 5,000 MCMC samples were taken with 10 steps between each sample. For baypass runs, standardized variables were run using default parameters under the standard model   and/or Bayes Factor > 30 (baypass).We combined several approaches to investigate the contribution of natural selection to genetic adaptation in English yew. First, we searched for signals of selection at the single‐locus (SNP) level using two environmental association approaches that take into account population genetic structure to avoid false positives: Gautier, . For eacGautier,  for the p < 0.01. For each gene, we then counted the total number of SNPs (n) and the number of SNPs with significant climate correlations (a). Then, to identify candidate genes potentially under selection, we compared the number of SNPs related to climate in each gene to the 0.9999 quantile of its binomial expectation, considering the expected frequency of SNPs related to climate per gene to be P = ∑iai/in (summation over i genes), and calculating P separately for each climatic variable. Following Yeaman et al. , we performed a gene set enrichment approach as in Daub et al. . Briefly, the genes belonging to the highest scoring gene set were removed, iteratively, from the remaining gene sets and the testing procedure was re‐run until no gene sets large enough to be tested were left. When following this procedure, tests are not independent and biased toward low P‐values , and thus, we estimated the false discovery rate (FDR) empirically using 300 iterations.Third, we used a complementary, independent, procedure to investigate the potential joint effect of selection acting on multiple loci (polygenic adaptation) instead of on single genes. This procedure was, in turn, independent of the environmental variables chosen, allowing the detection of potential signatures of selection in response to other drivers apart from climate. For this purpose, we used KEGG Automatic Annotation Server to map our 1,128 genes and retained 75 pathways that included at least five genes. We refined this pathway list by retaining only known pathways in plants, most of them having an b et al. , using p33.1F1, 66.03 = 4.65; p < 0.05). Males showed higher annual growth than females . However, relative differences among populations were quite consistent across years .The analysis of growth showed significant differences between sexes . However, differences among populations and sexes were highly consistent across years , although the overall pattern of differentiation among populations was also similar across years . We also found a significant negative correlation between strobili maturation and temperature, particularly mean and maximum temperature during winter and spring  varied among populations and between sexes, but such differences were also dependent on the year considered  and efficacy of selection  produced the same results, that is, the separation of Swiss populations as a third independent pool and, in some instances, Bosnia‐Herzegovina and Slovakia were split into two different genetic pools (data not shown).Population genetic structure showed an optimal partition into two genetic pools located at the eastern  and western  parts of the distribution Figure , with a stairway plot revealed a decrease in effective population size for all populations starting around 400,000–600,000 years ago , but most of them involved single SNPs per gene. The number of significant associations with at least two different SNPs on the same gene was lower, involving 212/293 SNPs located on 72/111 genes for bayescenv and baypass, respectively. However, only 11 SNPs located on 7 genes had significant associations with the same climatic variables using both methods. At gene level, we found 60 genes with a significantly higher proportion of SNPs associated with climate than expected by chance. Combining these results with those obtained at the SNP level , a total of 11 top candidate genes for climate adaptation were retained (Table We detected a similar number of significant associations between SNPs and climate with pseudo‐response regulator 7 gene (PRR7), a significant higher frequency  of the minor allele of SNP5227 was found in those populations with annual mean precipitation below 1,000 mm, irrespectively of their geographic location  increased with precipitation of the driest month, being significantly higher in those populations with minimum precipitation above 60 mm . Minor allele frequencies of SNP19480 (acetyl‐CoA carboxylase 1) and SNP346 (senescence‐associated E3 ubiquitin ligase 1) increased significantly in those populations with annual mean temperature above 8ºC  and minimum temperature of the coldest month above −3°C , respectively . Regarding the climatic period, most of the significant correlations detected involved current climate, although a few were also detected for the last glacial maximum and the last interglacial ones Table .pseudo‐response regulator 7 gene was part of the circadian rhythm‐plant pathway, and the putative acetyl‐CoA carboxylase 1 gene was shared between four different pathways, that is, fatty acid biosynthesis, pyruvate metabolism, propanoate metabolism, and AMPK signaling pathway. Interestingly, although the remaining 388 genes that could be mapped on the pathways showed no signs of selection when analyzed individually at the SNP or the gene level, we were able to detect a total of seven pathways that were globally enriched for signals of selection after removing gene redundancy  showed significantly lower values of πa/πs relative to the total number of pathways analyzed, indicating constrained adaptive evolution  suggests the existence of local adaptations at the Iberian scale, and this assumption is reinforced by the detection of similar signatures at the European scale, both at the single‐locus (SNP) and multilocus  levels. Our results also show that polygenic approaches can provide useful and simple tools for detecting signatures of “soft” selection . Using this polygenic approach, we were able to identify one biological pathway as potentially under the effect of diversifying selection, when individual approaches such as those focused on single loci failed to detect the signature of selection for any of the genes in this pathway. Finally, our study provides some evidence supporting the contribution of past climate to the potentially adaptive genetic variation observed. Below we discuss these findings within the context of the demography of the species while considering their potential limitations and caveats.4.1c. 115,000–130,000 year BP; Turner, Using extensive genetic resources , we confirmed previous demographic studies on English yew that supported the existence of two main Eastern and Western genetic pools across the whole species range  and the putative pseudo‐response regulator 7 gene (PRR7). In A. thaliana, PRR7 is an essential component of the circadian clock that is directly associated with developmental transitions such as flowering  Karst. : Alves & Fietto, acetyl‐CoA carboxylase 1 (ACC1): Amid, Lytovchenko, Fernie, Warren, & Thorlby, Alternative oxidase 1A (AOX1A): Fiorani, Umbach, & Siedow, Putrescine‐binding periplasmic protein‐related (ENF2): Cuevas et al., Modifier of SNC1 (MOS1): Li, Tessaro, Li, & Zhang, senescence‐associated E3 ubiquitin ligase 1 (SAUL1): Lee et al., Apart from PRR7, several other candidate genes relevant for forest tree adaptation were detected in our study Table . Some ofAlthough most of the variation found for these candidate genes was correlated to present climate, we also were able to detect significant associations with past climate for a few genes Table . It must4.2phagosome), genetic information processing  or environmental information processing , were characterized by highly conserved genes . In fact, many of the constituent genes of these pathways showed no variation for nonsynonymous mutations (Table Oxidative phosphorylation), showed significant lower overall values of nucleotide diversity. These results are consistent with the expected prevalence of purifying selection for genes and/or genomic regions of functional relevance, especially for nonsynonymous sites .In addition to single‐locus methods, we also applied a gene set enrichment test that has been used successfully to detect polygenic adaptation in the human genome  pathway  was 3‐fold that of the remaining genes (π = 0.0011). In addition, the ratio of nonsynonymous to synonymous variation for the PRR7 gene was between 5–30 times greater than that of the other genes in this pathway, suggesting that functional constraints for this particular gene might be much more relaxed .Within this group, however, the n Figure . Despiteta Table , where ted Table . In factflavonoid biosynthesis pathway had significantly higher values for overall nucleotide diversity (π) and Fu & Li's D*, pointing to divergent selection acting across English yew's geographic range. Flavonoids are plant secondary metabolites that are involved in a wide array of biological functions, including protection against ultraviolet (UV) radiation and phytopathogens, signaling during nodulation, pollen fertility, auxin transport and coloration of flowers, fruits and seeds  are still large in this long‐lived tree. Several new candidate genes for positive and negative selection in forest trees were identified or confirmed in this study, and an approach to detect potential polygenic selection in biological pathways was successfully tested. In particular, we identified the flavonoid biosynthesis pathway as a general stress‐response pathway that deserves further attention, including genomic studies in other plant systems. Our study also suggests that the integration of complementary information coming from different sources could be useful to detect selection in nonmodel species for which common gardens and genomic resources are limited. Such an approach can also help the field to advance beyond correlational “black‐box” methods  to systems biology‐driven ones, which are more informative in terms of drivers and mechanisms of adaptation. Finally, our study also contributed to the emerging view that while adaptation to current climates explains part of the contemporary distribution of standing genetic variation, it is also essential to consider adaptation to past climates, especially for long‐lived forest trees. Understanding the drivers and mechanisms of adaptation is particularly relevant for highly threatened species such as the English yew, which is protected by environmental laws in several European countries, and may help to develop sound conservation programs and reforestation schemes.Our rangewide study in English yew using a large number of SNP markers allowed us to confirm an overall demographic history characterized by two gene pools in Western and Eastern Europe, with an admixture zone in Central Europe, and population decline in most populations, extending initial evidence based on nuSSRs in Burgarella et al. . InteresNone declared. Click here for additional data file. Click here for additional data file.


Examples of rapid evolution are common in nature but difficult to account for with the standard population genetic model of adaptation. Instead, selection from the standing genetic variation permits rapid adaptation via soft sweeps or polygenic adaptation. Empirical evidence of this process in nature is currently limited but accumulating.Fundulus heteroclitus populations subjected to recently elevated temperatures due to coastal power station thermal effluents using 5449 SNPs across two effluent-affected and four reference populations. Bayesian and multivariate analyses of population genomic structure reveal a substantial portion of genetic variation that is most parsimoniously explained by selection at the site of thermal effluents. An FST outlier approach in conjunction with additional conservative requirements identify significant allele frequency differentiation that exceeds neutral expectations among exposed and closely related reference populations. Genomic variation patterns near these candidate loci reveal that individuals living near thermal effluents have rapidly evolved from the standing genetic variation through small allele frequency changes at many loci in a pattern consistent with polygenic selection on the standing genetic variation.We provide genome-wide analyses of rapid evolution in While the ultimate trajectory of selection in these populations is unknown and we survey only a minority of genomic loci, our findings suggest that polygenic models of adaptation may play important roles in large, natural populations experiencing recent selection due to environmental changes that cause broad physiological impacts.The online version of this article (10.1186/s12862-019-1392-5) contains supplementary material, which is available to authorized users. Understanding the population genetic basis of local adaptation is one of the principal goals of evolutionary biology. Historically, theoretical models of adaptation have focused on selection on one or a few genetic loci and populations that are mutationally limited. Under these assumptions, a typical adaptive walk is a long process characterized by successive fixations of large effect alleles that arise via mutation after the onset of selection . FixatioWhile this standard hard sweep model is often invoked to explain the genetic basis of adaptation among species that diverged millions of generations ago or populations that diverged thousands of generations ago, many of the most salient evolutionary questions today, and perhaps historically, occur on much more rapid time scales, e.g. adaptation to novel environments during species introductions  and in sSoft sweeps appear to have driven local adaptation in a number of empirical examinations –16. Yet,In the case of local adaptation, these predictions regarding the nature of adaptive genetic variants are additionally complicated by the influence of gene flow . Gene flFundulus heteroclitus exposed to the thermal effluents of coastal power stations. We sampled F. heteroclitus populations near the effluents of two power stations: Oyster Creek nuclear generating station in New Jersey and Brayton Point generating station in Massachusetts. Thermal effluents produced by coastal power stations provide a recent source of environmental variation that is both localized and well quantified. Effluents from both power plants have produced significant thermal impacts since the beginning of their operation in the late 1960s. The Oyster Creek thermal effluent is discharged along a modified river for approximately 3 km into the intracoastal Barnegat Bay. Temperatures range from 10 to 13 °C above ambient at the discharge site and 4–5 °C above ambient where Oyster Creek joins Barnegat Bay. Beyond this point, the effluent’s thermal influence is limited to a ~ 2 km radius from the mouth of Oyster Creek . Wh. Wh52]. k was 1. Similarly, no structure was observed when using a putatively neutral set of SNPs created by excluding outliers. STRUCTURE detected population structure within the Brayton Point triad after thinning the full dataset for SNPs in linkage disquilibrium (r2 > 0.5)  and Tajima’s D , STRUCTURE estimates the probability that an individual derives its ancestry from a particular genetic cluster at the loci provided. DAPC maximizes among population differences while minimizing within group variation by combining principal components of genetic variation.Genetic structure potentially resulting from varying selection among populations within a triad was inferred using two methods: a model-based Bayesian approach (STRUCTURE) using the most differentiated loci and a non-model-based multivariate approach ) using the full SNP dataset  among differentiated SNPs. Submitting an LD-thinned set of outlier SNPs to STRUCTURE produces qualitatively similar results  at a range of putative population clusters between 1 and 6. Thus these results do not reflect population genetic structure genome-wide (see above for these results); rather they reflect differences among the populations at the most differentiated loci. These STRUCTURE analyses produced different results between the two triads. For the Oyster Creek triad, p = 0.038, and p = 2.2 × 10− 16, for BP and OC respectively). To investigate the possibility that the population genetic structure described above varies from structure at loci in the neutral SNP dataset because of differences in site frequency spectrum rather than high differentiation, e.g. STRUCTURE is more sensitive when using more or less common alleles, we bootstrap sampled the neutral dataset to match the outlier dataset analyzed above with respect to minor allele frequency. This site frequency spectrum matched neutral dataset did not demonstrate any evidence of structure within a triad suggesting that the structure identified using differentiated loci is not an artifact arising from the use of STRUCTURE on datasets that varied in their site frequency spectra.For both the Oyster Creek and Brayton Point triads we conducted an additional analysis. The most differentiated loci among populations within a triad are not representative of the genome-wide site frequency spectrum. Pairwise outliers are enriched for among loci with lower minor allele frequency  for the triads . In contp = 0.001, 1000 permutations). Variance partitioning revealed that 0.51% of the total genetic variation was attributable to spatial variation alone (27.9% of FST), 0.49% attributable to effluents (26.8% of FST) and no variation explained jointly   and partial redundancy analysis (pRDA)  to examip = 0.001, 1000 permutations) with 0.86% of the genetic variation attributable to spatial variation alone (13.5% of FST), 0.89% attributable to effluents (13.9% of FST) and no variation explained jointly   among all SNPs occurred on a similar spatial scale to the decay in FSTvalues for both triads, with smooth mean R2 falling to 50% of its maximum within ~ 30 bp , we also conducted a similar analysis at larger genomic scales  in F. heteroclitus collected from Oyster Creek and its northern reference population after acclimation to laboratory conditions. Oyster Creek individuals demonstrated a significant, but minor increase in thermal tolerance relative to the northern reference population . The critical thermal maximum for Oyster Creek was 39.7 ± 0.07 °C (mean ± s.e.) while the critical thermal maximum for the northern reference was 39.5 ± 0.07. °C. These differences correspond to a PST (phenotypic divergence in a trait across populations) value of 0.67, which exceeds FST among these populations (FST = 0.01), suggesting that selection may drive this difference in thermal tolerance. However, divergence in genetic architecture and narrow-sense heritability for this trait may also drive the observed divergence. To examine the robustness of the PST-FST comparison to these effects, we bootstrapped sampled the data according to [To assess whether exposure to thermal effluents has led to an increase in thermal tolerance, we measured critical thermal maxima  applied to the loci identified as outliers in any one of the pairwise comparisons within a triad. Thus we use the most differentiated loci to reveal subtle population genetic structure at loci whose differentiation is potentially influenced by selection . Such anFor the Oyster Creek triad there are two genetic clusters among outliers inferred by STRUCTURE. Individuals from the two reference populations primarily derive their ancestry at the most differentiated loci from one cluster, while the TE population is dominated by a second cluster. This pattern is consistent across the range of ancestral genetic clusters that we model and leads us to reject the neutral hypothesis for genetic variation among the most differentiated loci. The DAPC analyses support this finding. The second axis in DAPC using the full SNP dataset indicates a non-neutral pattern where the TE population is distinct from both reference populations with little distinction between the two reference populations. This divergence in the TE population in the second axis is different from the primary axis of genetic variation that follows a neutral pattern, where the position along the genetic axis of a population correlates with its geographic distribution. These patterns among all SNPS are expected if selection is occurring at the effluent site; we expect a mosaic of historic evolutionary forces to drive the differences observed among SNPs randomly sampled along the genome, with older, neutral forces shaping the majority of variation, but recent selection unique to the effluent site driving differentiation at some loci in the standing genetic variation.ST values ~ 0.03) than the Oyster Creek triad , and STRUCTURE analysis using the most differentiated loci suggests that each population is unique. When we examine all loci for the Brayton Point triad using DAPC, however, we find a similar pattern as in the Oyster Creek triad. The major axis of genetic variation separates each of the populations in a pattern consistent with its geographic position, but the two reference populations are more similar to each other along the second major axis of genetic variation than either is to the TE population. In both the Oyster Creek triad and Brayton Point triad, the second largest component of genetic variation among the populations occurs in a pattern that is not consistent with neutral evolution. Therefore, we interpret the DAPC results as evidence of selection in both TE populations but caution that the STRUCTURE results do not corroborate this interpretation for Brayton Point where population differentiation is stronger.In the Brayton Point triad, populations are more strongly differentiated  capable of determining the portion of overall genetic differentiation potentially explained by demography and selection at the effluent site through variance partitioning and (ii) provides a statistically robust framework to infer whether these patterns might arise by chance alone.max) of individuals from the effluent impacted habitat was significantly higher than that of individuals from the northern reference population. Assuming a correlation between CTmax performance in the laboratory and thermal tolerance in the wild, these data suggest that Oyster Creek individuals are phenotypically adapted to the effluent impacted environment. F. heteroclitus populations separated by 1000 s of kilometers demonstrate compensatory variation in CTmax  when individuals are acclimated to similar temperatures as those used in our analysis [F. heteroclitus population is expected to be marginally more thermally tolerant due to its location ~ 30 km kilometers south along the coast from the reference population. Additionally, our analysis cannot rule out irreversible thermal acclimation or developmental plasticity. Nor did we conduct a similar analysis within the Brayton Point triad, where population genomic evidence of possible selection at the effluent site is weaker. However, it seems unlikely that clinal adaptation would lead to the observed variation between the Oyster Creek TE and the northern reference population, which is only separated by ~ 30 Km, when the magnitude of this difference is approximately one third of the difference among populations separated by thousands of kilometers. Instead, we suggest that the Oyster Creek population difference is more likely due to adaptive genetic or non-reversible plastic responses to the thermal effluent. PST-FST comparisons support this conclusion. The degree of phenotypic divergence among populations exceeds that expected that might arise solely due to drift given the extent of genome-wide divergence among the populations across a wide parameter space of potentially varying genetic architecture [Although the three populations within the Oyster Creek triad demonstrate little genetic divergence, critical thermal maximum  are adaptive shifts in allele frequency between reference and effluent-affected populations large or small, (ii) are adaptive alleles common or rare in the standing genetic variation, and (iii) are candidate loci embedded in extended genomic regions of elevated differentiation and linkage disequilibrium, or are these islands of differentiation near candidate loci limited to the scale of ancestral linkage disequilibrium?, directional selection in favor of the triad minor allele). Furthermore, in the minority of cases where the minor allele is putatively advantageous in the TE environment , it is rarely a private allele among all six populations in both triads, and is therefore likely available in the standing genetic variation either below our minor allele frequency filtering cutoff, or low enough in frequency that it is not included in our sample by chance, given the only moderate genetic distance between populations in different triads and large population sizes. We conclude that at the majority (98%) of candidate loci, the adaptive allele is likely present in the standing genetic variation, either because it is the major allele overall or it is present at an appreciable frequency in populations with appreciable gene flow (ΦCT = 0.096).In the classical paradigm, adaptation proceeds through selective sweeps that drive an advantageous allele from low to very high frequency. However, evidence from quantitative genetics , 70, 71,ST embedded in the shoulders surrounding a hard sweep. We expected that if variation at candidate loci is due to a selective sweep, candidates would lie in large regions with elevated FST values due to the fixation of rare haplotypes bearing the adaptive allele, and that LD would be high along these regions [ST and LD decay fully to genome wide averages within very short scales. The region surrounding a candidate where the FST value exceeds the genome-wide average extends less than 50 bp, a similar scale to the decay of LD (R2) for the full SNP dataset  . Both re regions . Our datST value region due to a hard sweep in F. heteroclitus to compare our results to, but observations in other species suggest that the LD distance we find is orders of magnitude shorter than any predicted unit of adaptive hitchhiking due a recent selective sweep. An empirical estimate of the average unit of adaptive hitchhiking in humans is 20 kb, where FST values are highly significantly correlated [ST values commonly utilize windows of 100 kb or more . Taken on sizes , 82.ST values surrounding these alleles decay at a distance on a similar scale to genome-wide average patterns of linkage disequilibrium suggesting they are derived from the standing genetic variation borne on several haplotypes. Therefore, if our candidate loci contain SNPs in LD with the true targets of selection, recent thermal adaptation in these populations is consistent with polygenic adaptation in that adaptive alleles are borne on multiple haplotypes that coalesce before the onset of selection (as is the case under a soft sweep), but the adaptive alleles themselves are not swept to high frequency.Under polygenic adaptation, selection drives many subtle shifts in allele frequency until a new phenotypic optimum is reached. Our data implicate a model of the early stage of adaptive evolution where selection acts on previously segregating mutations to produce small changes in allele frequency at many loci: putatively adaptive alleles are present at appreciable frequency in nearby populations, adaptive variation in allele frequency is small, and regions of elevated FFundulus heteroclitus effective population sizes are large, ranging from 2X104 [5 [eμa (where μa is adaptive mutation rate) and therefore the probability of adaptation from the standing genetic variation, is increased in the case of thermal adaptation [While the parameter space selection on the standing genetic variation producing soft sweeps become feasible may be narrow , there aom 2X104  to 3X1052X104 [5 . Effecti2X104 [5 . Most of2X104 [5 , 47, the2X104 [5 , 49. Conaptation .F. heteroclitus (~ 1.26 Mb) [It is important to also emphasize that our data do not preclude the possibility of sweeps, hard or soft, as the final outcome of selection in these effluent populations, nor do they preclude a role for genomic islands of differentiation. Absence of evidence is not evidence of absence. We surveyed the genetic variation at a small subset of the total polymorphisms present and cannot refute other patterns of variation at loci that our dataset does not query. In fact, moderate genome size in 1.26 Mb) , coupled1.26 Mb) . Also, i1.26 Mb) –91.There is a fundamental disconnect between the time scale of common models of molecular evolution and rates of phenotypic adaptation observed in natural populations  and in eST-based outlier scans. We used this approach to assess the hypothesis that populations exposed to thermal effluents near coastal power stations experience recent selection and then examined the genomic signature of this putative recent selection to investigate the evolutionary history of adaptive alleles. We conclude that fish living near thermal effluents have rapidly evolved from the standing genetic variation through small allele frequency changes at many loci in a pattern consistent with a polygenic model of evolution. Overall, we suggest that evolution through these mechanisms may be a common feature early in the adaptive process in large, outbred, natural populations exposed to environmental changes with broad physiological impacts, but caution that our low resolution genomic dataset may not tell the full story in these populations and that polygenic effects are likely to be only transient in nature.We combined a population sampling regime that allows us to identify potentially adaptive variation with an analysis of population genetic structure at varying levels of differentiation and FF. heteroclitus were collected from six sites. The six locations form two triads, where a triad contains a single population subjected to thermal effluents (TE) as well as northern and southern reference populations ; these samples were stored at 4 °C prior to processing. Genomic DNA was isolated from fin clips using an Epoch Life Sciences silica column [Fin clips from the terminal margin of the caudal fin approximately 5 mma column . DNA quaFundulus heteroclitus genome [Genomic DNA (gDNA) was isolated from 296 individuals. These gDNA samples were individually barcoded and used to create a reduced representation library for genotyping by sequencing (GBS)  was useds genome ; SNPs wes genome . A log oAseI cut site. Bowtie aligned 1,142,340 (78.7%) of these tags to unique loci in the F. heteroclitus genome [F. heteroclitus genome, we identified 314,746 SNPs.We found 1,451,801 unique sequence tags that contained both the barcode and s genome ; 159,591s genome . Among to) was significantly greater than the expected heterozygosity (He) [o > He that exceeded Hardy-Weinberg equilibrium at p < 0.01 were removed. Thus, the fully filtered SNP dataset consisted of 5449 SNPs among 239 individuals. Mean read depth per SNP per individual was 26.29 ± 0.43 for the full SNP dataset , we then filtered the SNP dataset by coverage, minor allele frequency and whether observed heterozygosity (Hity (He) , 100. Reity (He)  using 10ST values  and used the bisection approximation algorithm to estimate mean FST values (force mean FST option). After these steps, we conducted 50 k simulations. To control for multiple comparisons, we adjusted empirical p-values provided by LOSITAN with a modified FDR of 5% [Outlier scans were conducted with FDIST2  as impleDR of 5% , 55. The2) and sliding window nucleotide diversity was calculated in the tassel GUI. Smoothing conditional mean r2 and FST along the genome was accomplished using LOESS. The span for each fit was chosen using the bias-corrected Akaike information criterion [Population genetic parameters were calculated in a variety of statistical packages. Isolation by distance was tested using a Mantel test (9999 simulations) in the ade4 R package . Arlequiriterion .2 > 0.5 (c) a “neutral” SNP dataset with both potential directional and balancing selection outlier loci  excluded, (d) a SNP dataset consisting of all pairwise directional selection outliers within a triad, i.e. the most differentiated loci among the population within a triad and (e) a minor allele frequency matched neutral dataset. For (e), we bootstrap sampled the “neutral” dataset for each triad, so that the allele frequency distribution matched that of the dataset composed of the most differentiated loci. For all analyses, we used a burn in of 10 k steps and MCMC of 20 k steps with at least 7 replicates for each k value and varied k from 1 to 6. In all replicates, burn in was sufficient for convergence in the STRUCTURE parameters: α, F, D and likelihood. We specified an admixture model with correlated allele frequency to improve clustering among closely related populations within a triad [k runs were merged and the ΔK method for identifying the optimal number of clusters [K = 2 increase at a decreasing rate ) plateau at K = 3  separated the southern reference population  from both the TE and the northern reference populations .Population genetic structure inference was made using STRUCTURE  and DAPC a triad . Replicaclusters  was calcclusters . For OysK = 1–12 demonstrated an inflection point at K = 3  . We conducted the RDA using the R package vegan [rda command and the anova.cca command to test its significance. dbMEMs are calculated using a distance matrix of alongshore (5 m depth constrained) distances among sampling locations and the dbmem command from the R package adespatial [varpart command of vegan in R. Because variation in PCA is equivalent to FST [ST as the denominator [vegan using the rda and anova commands. We conducted three RDAs with pRDAs: a global RDA of both triads, and each triad separately.We also examined the extent to which spatial and environmental (effluent) variables could be used to explain genetic variation among populations using redundancy analysis (RDA) and partial redundancy analysis (pRDA). RDA is a form of constrained ordination that can be used to describe linear relationships among components of multivariate response and multiple multivariate explanatory variables . In pRDAge vegan , using tespatial . To calcespatial  implement to FST , we usedominator . To testF. heteroclitus genome [F. heteroclitus gene annotations using the “high” classification stringency. DAVID’s Functional Annotation Clustering Tool groups similar functional annotations and collectively evaluates their enrichment. The statistical significance of annotation clusters is evaluated on the basis of DAVID’s EASE score: the mean value of the negative log-transformed, FDR corrected p-values of enrichment for all genes included in that cluster [Functional enrichment among candidate loci was assessed with DAVID v6.7 . Candidas genome  where ge cluster . ClusterF. heteroclitus collections from the Oyster Creek TE population (n = 51) and its northern reference population  (n = 47), we measured upper thermal tolerance with the critical thermal methodology [Using separate hodology . Fish weST) relative to overall genetic divergence (FST). We bootstrapped these data to produce confidence intervals for PST across varying degrees of heritability and among population changes in genetic architecture using the R package Pstat [The experimental chamber consisted of a 20 L aquarium within an insulated 40 L aquarium. Both chambers were filled with acclimation temperature water (28 °C), then 70 °C water was introduced from a header tank to the outer aquarium at a controlled rate to maintain heating at 0.28–0.30 °C/min in the inner tank throughout the experiment. The inner chamber was aerated to reduce thermal stratification and maintain oxygen saturation during trials. After acclimation, groups of six fish were introduced to the inner aquarium. Critical thermal maxima were determined based on continuous loss of equilibrium for 5 s. 99% of individuals survived the critical thermal maximum trial after 1 week. CTmax measurements were used to calculate the degree of phenotypic divergence among the populations  Mean depth across individuals represented by red line. (B) Frequency histogram of reads per SNP per individual. (PDF 1857 kb)Additional file 2:Table S1. AMOVA results for neutral dataset. (DOCX 38 kb)Additional file 3:Figure S8. STRUCTURE results for after LD thinning the full dataset. STRUCTURE plots for LD thinned dataset  among (A) Brayton Point triad, best k = 3, and (B) Oyster Creek triad, best k = 1. (PDF 1589 kb)Additional file 4:Figure S3. Supporting population genetic structure data. (PDF 820 kb)Additional file 5:Figure S2. Outlier Scans. Lositan output with distributions of FST values and observed H for all within triad pairwise comparisons. (PDF 1080 kb)Additional file 6:Figure S9. STRUCTURE results for after LD thinning the outlier dataset. STRUCTURE plots at best k for the most differentiated SNPs, LD thinned (r2 < 0.5) among (A) Brayton Point and (B) Oyster Creek triads. (PDF 1141 kb)Additional file 7:Figure S5. Decay of FST away from candidate SNPs. Mean reference vs. effluent FST values at SNPs with 1mb and 100 kb from candidate SNPs for the Oyster Creek triad (a) and Brayton Point triad (b). Distance is presented in base pairs from candidate SNP, smoothing line is the Loess-smoothed mean FST value with 95% confidence intervals, dashed line is the mean genome-wide FST value estimate (dashed black line) for both reference vs effluent comparisons within the triad, dashed smoothing line (blue) is Loess-smoothed mean of a random permutation of distance vs. mean reference vs. effluent FST values, red SNPs are candidate loci. (PDF 3502 kb)Additional file 8:Figure S4. Long Range LD Decay. R2 among single SNP pairs across the full dataset, with loess smoothing line for SNP pairs that contain a candidate (red) and those that do not (black). (PDF 649 kb)Additional file 9:Table S2. Functional annotation clusters for Oyster Creek (top) and Brayton Point (below). For each cluster the EASE score, functional annotation terms, gene identifiers, p-value for individual annotation terms, and fold enrichment relative to the F. heteroclitus background are presented. (DOCX 26 kb)Additional file 10:Figure S7. PST-FST Comparison. PST and it’s 95% confidence interval for critical thermal maximum differences among F. heteroclitus from Oyster Creek and its northern reference population. PST is estimated for a range of c/h2, where c is proportion of the total variance that is presumed to be because of additive genetic effects across populations and h2 is narrow sense heritability. FST is plotted in green. PST exceeds FST for the majority of the parameter space, suggesting that the degree of phenotypic divergence exceeds that expected given the extent of genome-wide divergence alone. (PDF 194 kb)Additional file 11:Figure S6. Filtering impacts on coverage summary. (A) Density plot of reads per SNP per individual for the filtered (green) and raw (purple) datasets. (B) Density plot of non-zero reads per unique tag per individual for filtered dataset (purple) and the raw dataset (green). (C) Density plot of reads per SNP per individual for the filtered (green) dataset and the raw dataset excluding with SNPs where > 75% of individuals demonstrate zero reads (blue). Summary: There are large differences in coverage between our filtered (5.4 k) and raw SNP (314 k) datasets. The median read depth per SNP per individual of the raw dataset  is 0 . The mean read depth per SNP per individual of the raw dataset is ~ 4.4 (filtered data mean = ~ 26.3). While we base our filtering on missingness across SNPs and individuals , the majority of SNPs we filter out have zero reads in the majority of individuals, but coverage similar to our filtered dataset in the remaining individuals (panel B and C). (PDF 746 kb)


Population genetic theory predicts that rapid adaptation is largely driven by complex traits encoded by many loci of small effect. Because large-effect loci are quickly fixed in natural populations, they should not contribute much to rapid adaptation.Drosophila simulans population. Transcriptome and respiration measurements reveal extensive metabolic rewiring after only approximately 60 generations in a hot environment. Analysis of genome-wide polymorphisms identifies two interacting selection targets, Sestrin and SNF4Aγ, pointing to AMPK, a central metabolic switch, as a key factor for thermal adaptation.To investigate the genetic architecture of thermal adaptation — a highly complex trait — we performed experimental evolution on a natural SNF4Aγ also exhibits clinal variation in various Drosophila species, we suggest that this large-effect polymorphism is maintained by temporal and spatial temperature variation in natural environments.Our results demonstrate that large-effect loci segregating at intermediate allele frequencies can allow natural populations to rapidly respond to selection. Because The online version of this article (10.1186/s13059-018-1503-4) contains supplementary material, which is available to authorized users. One of the major challenges in evolutionary genetics is to unravel the genetic architecture of phenotypic traits and how this affects the potential of natural populations to respond to selective forces. Theory predicts that evolution proceeds mainly through polygenic quantitative traits . Thus, aDrosophila an excellent model system to study the impact of large-effect alleles segregating in natural populations on rapid adaptation to novel thermal environments. Shared clinal polymorphisms between two sister species, D. melanogaster and D. simulans, suggest that genetic variants associated with thermal clines may have been segregating for long evolutionary times. Such alleles contributing to temperature adaptation could be readily selected, either in natural populations or in the laboratory, and mediate a fast adaptation to a new temperature regime.In the light of global warming, it is of key interest to understand how novel thermal environments can drive genetic adaptation and the true nature of the associated phenotypic changes , 18. TemD. simulans to investigate the genetic architecture of phenotypic adaptation to a novel thermal environment. Transcriptomic data suggest that the evolved populations underwent a massive metabolic rewiring, which was confirmed by resting metabolism measurements. Whole genomic resequencing after ~ 60 generations of evolution under our hot environment indicated that, despite temperature adaptation being a complex trait, only a small number of selection targets were identified across five replicate populations. Two interacting loci were associated with AMP-activated protein kinase (AMPK), a key metabolic switch driving the phenotypic changes observed in our experiment. We show that these alleles are segregating at intermediate frequency in a European population and show a latitudinal cline in North American populations. These results suggest that experimental evolution identified variants which play a key role in rapid spatial and temporal temperature adaptation in natural populations.Here we use experimental evolution in D. simulans population from Póvoa de Varzim, Portugal was selected for ~ 60 generations in a hot environment that fluctuated daily between 18 and 28 °C  than the ancestral population , collecting whole transcriptome data of young adult males (3–5 days old). Out of more than 9000 genes with reliable gene expression signals, 687 genes were differentially expressed  < 0.05) between hot-evolved and reconstituted ancestral populations. In contrast, the cold-evolved control populations were very similar to the ancestral ones, with only 60 genes differing significantly. Because 35 of these genes were also differentially expressed between ancestral and hot-evolved populations, we attributed them to non-temperature-specific adaptation. These genes are enriched for oxidoreductase activity  categories and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways contrasting hot-evolved with ancestral or with cold-evolved populations. Genes down-regulated in the hot-evolved populations were enriched for more GO categories than up-regulated ones  we identified the factors “population”  and “sex”  to have a significant effect on CO2 emission . “Body weight” was not significant , because the difference in weight between sexes was already explained by the factor “sex” and females produced significantly more CO2 than males. We found similar results in a second series of measurements between the ancestral and hot-evolved populations after 133 generations  of 219 individuals  showed a handful of pronounced peak structures  driving these changes. To map the targets of selection, we performed Pool-Seq  contrastuals see  in our pres Fig. . Each peres Fig. . While tDrosophila  studies in a e.g., –34). We . We Droselomeres –37. ThirSestrin is not very high .While the mapping precision of the genomic region containing  kb Fig. . We furt kb Fig.  and iden kb Fig. . These 2Sestrin locus, we found a higher number of SNPs (95) distributed over a broader genomic region (~ 60 kb) than for SNF4Aγ  based on Student’s t test for 10,000 random sets of SNPs generated by jackknifing 21 SNPs out of the 197 SNPs segregating in the region of interest  [SNF4Aγ and two other subunits. AMPK is a key player in energy homeostasis at the cellular and the organismal levels, and both SNF4Aγ and Sestrin are directly linked to AMPK activity [D. melanogaster, RNA interference-mediated down-regulation of SNF4Aγ increases glucose content of muscles and the fat body [Ilp6, InR, see Additional file D. melanogaster [SNF4Aγ [Sestrin is also connected with autophagy regulation in Drosophila, through its role in activating AMPK [Based on the genomic analyses alone, it is not possible to rule out other genes in the e (AMPK) , which iactivity –47. Low activity . Furtheractivity . Inactivfat body  and indufat body . Some ofnogaster  by invok [SNF4Aγ  that lining AMPK , 55.SNF4Aγ and interacting gene Sestrin in hot-evolved populations. Given the central role of SNF4Aγ and Sestrin for temperature-dependent metabolic rewiring, we reasoned that both genes should vary along temperature clines in natural populations. While we did not find evidence for clinality of Sestrin, the patterns for SNF4Aγ matched our expectations. A whole genome polymorphism analysis identified SNF4Aγ as one of the top candidates in clinal North American D. melanogaster populations [SNF4Aγ in D. melanogaster and D. simulans further implicate temperature as an adaptive driver [SNF4Aγ is among the 603 most differentiated genes shared by North American and Australian D. simulans populations. Gene expression of SNF4Aγ is clinal in European D. subobscura populations, with southern populations having lower expression levels [Thus, our results indicate that the activity of the key metabolic regulator AMPK is modulated through the differential regulation of the subunit ulations . Clinal e driver , 24. Reae driver , SNF4Aγ n levels , which pD. simulans population evolving in a new thermal environment identified two genes, both connected to AMPK, a central metabolic switch. While many possibilities exist as to how metabolism could be regulated, the strong selection response in all replicates suggests that two major-effect loci are driving the adaptive metabolic response in our populations. The observed selection signature clearly indicates that adaptation in our E&R study [The combined analysis of transcriptomic and whole genome resequencing data of a freshly collected &R study  is domin&R study –16.D. simulans [The two haplotypes driving the metabolic switch in our experimental populations segregate at intermediate frequencies in the founder population and show clinal variation. Thus, it is highly plausible that these genes contribute to similar adaptive processes in natural populations, which probably occur over very short time scales. Because temperature varies seasonally, it is possible that spatial and temporal heterogeneity maintains the selected alleles at intermediate frequency in simulans , 24.The fact that few large-effect loci resulted in a clear selection signature in our experiment does, however, not preclude that several minor effect loci also influence the metabolic rewiring in hot environments. Yet, our computer simulations suggest that these two loci probably explain more than 50% of the phenotypic change, even when minor effect loci are also contributing Fig. . PreviouWith the favored allele being fixed or close to fixation in southern populations in the USA, it would be interesting to study the adaptive response in these populations. Because AMPK will probably not further contribute to adaptation, such an experiment could reveal other adaptive signals that were not detected in this study. Would such populations be segregating for other major alleles or would a polygenic response detected?D. simulans, a species with lower transformation efficiency than D. melanogaster, is extremely challenging. Thus, the next steps would require some further fine mapping of the target of selection. We anticipate that adding chromosomes without the selected alleles during an extended experimental evolution will provide more opportunity in recombination to obtain a smaller candidate region. Once sufficiently small candidate regions are cloned, many follow-up experiments are conceivable, ranging from competition experiments of selected and non-selected alleles in an experimental evolution setting to detailed biochemical comparisons using metabolomics, transcriptomics, and proteomics.Experimental evolution provides an excellent framework for experimental testing of selected alleles. Allelic replacements with the CRISPR/Cas9 technology enable the direct comparison of selected and non-selected alleles in an otherwise homogeneous genetic background. Nevertheless, the mapping resolution in our study is still rather low. Replacing a genomic region of > 10 kb in We demonstrate with empirical data acquired at several biological levels  that rapid adaptation to novel thermal environment involves rapid evolution of metabolism regulation that can be explained by large-effect alleles rising in frequency. We suggest that these alleles are maintained at intermediate frequencies in natural populations by temporal and spatial variations. Finally, we propose that E&R studies using different founder populations are a very powerful approach to answer questions about the genetic architecture of rapid adaptation, which are difficult to infer from natural populations.Drosophila simulans  and distributed randomly to two different selective regimes: a hot treatment with 12 h at 18 °C (dark) and 12 h at 28 °C (light) and a cold treatment with 12 h at 10 °C (dark) and 12 h at 20 °C (light). The replicate populations were then propagated the same way with non-overlapping generations and a census population size of 1000. After 64 and 39 generations, respectively, in the hot and cold treatments, we assayed all ten populations together with five replicates of a reconstituted ancestral population at 23 °C in a common garden experiment. Males aged 3–5 days old were frozen in liquid nitrogen and stored at − 80 °C for RNA sequencing.A detailed description of the experimental procedures can be found in Additional file www.repeatmasker.org, file available on demand). While library preparation protocols do not affect allele frequency estimates based on Pool-Seq [p values under a null hypothesis. Given a certain p value threshold, the false positive rate was computed as the fraction of simulated  and empirical loci. All simulations, sampling noise additions, and CMH tests were performed with the R package poolSeq [Genomic DNA for pooled sequencing of the ancestral and the hot-evolved flies from generation F59 was extracted from females only. For each evolved population, DNA was extracted from about 500 females. Since only two replicates of the founder females were frozen , we added one replicate from generation F2 as a substitute. Genomic DNA was extracted using either the DNeasy Blood and Tissue Kit   or a high salt extraction protocol  includinPool-Seq . TherefoPool-Seq  using thPool-Seq , bwa-memPool-Seq , and NovPool-Seq ). Using Pool-Seq . We filt poolSeq .SNF4Aγ was a good candidate to explain the observed phenotypic changes, we focused the subsequent analysis on a 200-kb region on chromosome 3R  using the method of Jonas et al. [s) based on an Ne estimate of 219 and mean allele frequency of the 28 SNPs across all three replicates at the start of the experiment and at generation 59 using the method of Taus et al. [We estimated the effective population size  based on these 95 SNPs .The same procedure was then repeated for the Since the results of our experimental evolution study may be affected by inadvertent migration events, we also tested whether migration may have resulted in false positives, but we consider this unlikely  with a virgin female from our reference 2713493, ). DNA ex2713493,  includin2 production (see the subsequent discussion) was tested at generation 74 of the cold-evolved flies, which roughly matches the generation at which the expression profile of the hot-evolved flies was determined (F64). Because CO2 production suggests no metabolic difference between the ancestral and cold-evolved flies, we conclude that the observed gene expression differences related to metabolism are unlikely to reflect only different generation numbers.We contrasted the phenotypes of hot-evolved, cold-evolved, and ancestral populations in a common garden setting, where all populations were maintained for two generations in the target temperature of 23 °C. We note that hot-evolved and cold-evolved populations were separated from the founder population by a different number of generations because of the faster development at warm temperatures. This may imply that the differences between hot- and cold-evolved flies may reflect different generation numbers, rather than a different selection response. While it is not possible to compare flies from the two temperature regimes at the same generation, we note that CODrosophila simulans reference genome using GSNAP  we generated two RNA-seq libraries, each from different sets of males. Total RNA was extracted from 25 to 30 males using the Qiagen RNeasy Universal Plus Mini protocol  with DNase I treatment according to the manufacturer’s instructions. Libraries were generated using the NEBNext® Ultra Directional RNA Library Prep Kit for Illumina . All replicates of evolved and ancestral populations were reared for two generations at 23 °C, controlling egg density (400 eggs per bottle). Flies were collected shortly after eclosion, and after 24 h males and females were separated and placed at low density in vials (25 flies/cm3) under CO2 anesthesia. After 48 h recovery, the CO2 emission of 3–5 day old males and females was measured. Each assay was conducted at 23 °C in the dark, overnight (at least 12 h). The flies from different replicates were randomly assigned to one out of eight chambers together with a small piece of fly food (2 cm3) to avoid starvation response and desiccation. Each chamber contained approximately 25–30 flies. During the assays, a multiplexer (RM8 Intelligent Multiplexer) was sequentially flushing the metabolic chambers. Each flushing cycle lasted 5 min at a constant flow rate of 50 μl/min. We obtained repeated measurements in 40-min intervals for each of the eight channels. After removal of water by passing through a magnesium perchlorate column, we measured CO2 in the flushed air with a CA-10A Carbon Dioxide Analyzer. For each flushing cycle we determined the total CO2 emission using the ExpeData software  with an in-house script (available on demand). At the end of each assay the flies were dried and weighed.Resting metabolism was determined by repeatedly measuring overnight CO2 levels in the empty chamber were always very low compared to the CO2 levels of chambers containing flies, we used all eight chambers with flies for the second set of measurements (generation 133). We analyzed the data with linear models. The most complete model included fixed effects of sex, mean dried weight, population identity , and interactions of these explanatory variables. Model comparison and selection of fixed effects occurred by stepwise removal of non-significant interactions and main effects, using analysis of variance (ANOVA) F tests. The assumptions of the models  were validated by visual inspection of the residuals.We conducted the assay after generation 127 (74) of the hot (cold) evolved populations contrasting all three populations , and a second time after 133 generations . We estimated the resting metabolism for each chamber as the average of the three lowest observations overnight . During We conducted fecundity assays of the cold- (F78) and hot- (F133) evolved populations in parallel with a reconstituted ancestral population using the same common garden design as described above. The only modifications were that we performed two generations of density control rather than a single one and that the ancestral population was reconstituted from ~ 90–100 lines only. In parallel, we set up another common garden experiment that differed only in the temperature regime, which was not constant but cycled between 28/18 °C light/dark conditions.2 anesthesia in separate bottles to estimate egg laying rates. We created two bottles for each replicate . Every day, all flies were transferred without CO2 anesthesia to fresh food, and the eggs laid were counted. We did not count the eggs laid during the first 24 h after anesthesia and recorded the next 5 consecutive days. After 6 days the flies were then sexed and counted. We determined the mean number of eggs per female in a 24-h interval for each replicated population and tested for differences between populations using linear models in R. Significance of the fixed effects was tested using ANOVA F tests and differences between populations using Tukey tests (using the multcomp library and appropriate contrasts). At 23 °C, we excluded the results of two hot-evolved replicates (the 3rd and 4th) due to problems with the density control, and the data from only three replicates were used.Flies were collected shortly after eclosion and allowed to mate within a 24-h period. Approximately 60 flies were placed under COSNF4Aγ and Sestrin, contribute to the trait proportionally to their coefficient of selection and modeled additional loci with an equal effect size. Because the effect sizes of all selected alleles are parameterized relatively to each other , we maintained the summed effect sizes of all alleles constant between simulations. Thus, the number of background loci is inversely proportional to their effect size. We randomly sampled their starting frequency in the distribution of initial allele frequency in our experimental population . The model assumes a Gaussian fitness function. We fixed the standard deviation (0.2) as well as the minimum and maximum fitness values  of the function and allowed the mean fitness optimum to vary.We used the framework of Franssen et al.  implemenSNF4Aγ and Sestrin (background loci) had about a four times larger effect size than SNF4Aγ and Sestrin together . We assume here that there could be ~ 8 additional loci of the same effect size of SNF4Aγ or Sestrin or ~ 80 loci with an effect size ten times smaller than that of SNF4Aγ or Sestrin.We conservatively assumed that all loci contributing to the adaptive phenotype in addition to SNF4Aγ and Sestrin are fixed (0.32) is then only 15% of the potential phenotypic increase . We performed computer simulations varying two parameters: the number of background loci (5 to 1000) and the phenotypic value that maximize fitness (0.3 to 0.7). For each parameter combination, we performed 50 independent simulations. For each simulation, we report the proportion of the observed phenotypic change explained by our two focal loci after 60 generations in five independent replicates. We used the allele frequency after one generation as the initial value to account for random variation between replicates. To compare these simulated results to our experiment, we also computed a CMH test. To match the experimental data for each simulated locus, we randomly sampled “reads” at F1 and F60 matching the coverage of a chosen SNP in the experimental data set. We then computed for each set of parameters the proportion of simulations in which at least one SNP was above our CMH cutoff. We matched the population size with the empirical estimate (Ne = 219).We computed the initial mean phenotypic value of the population (0.18) assuming that the frequency distribution of the background loci matches the one of all SNPs (mean frequency: 14%). The maximal phenotypic value when both D. simulans populations along a cline [FST to determine whether the SNF4Aγ and Sestrin regions were differentiated along the clines. Since FST values do not indicate the direction of allele frequency differences, we performed a second analysis testing specifically whether the difference in allele frequencies between northern and southern populations along a cline differs in the direction expected based on our experiment. Below, we describe the analysis for each of the two data sets separately.We analyzed two published data sets of  a cline , 23. FirSNF4Aγ occurring on a haplotype block in the Portugal population in each population. At all 21 positions, we classified each sample in four categories: homozygous for either allele, heterozygous, or unknown. As the coverage for each sample was relatively low (1.8-fold), all reads were used to determine the genotype of each individual. Based on this classification, we computed the frequency of all the rising SNF4Aγ variants along the cline for each position. Only SNPs were used for which we genotyped in at least half of the samples in each population, which reduced the number of SNPs to 20.We downloaded, trimmed, and mapped the raw data from Machado et al.  using thFST between populations at each polymorphic position using PoPoolation2 [FST values were computed for all positions individually while accounting for different numbers of chromosomes in each pool . Focusing on the SNPs with the strongest differentiation, we retained only the top 0.1% SNPs with the highest FST values, resulting in FST thresholds of 0.53 and 0.52 in the Australian and American populations, respectively. These SNPs mapped to 2053 and 1506 genes, out of which only 603 genes were shared. Additionally, we compared the allele frequencies of our SNPs of interest in the SNF4Aγ region across the two clines (Sestrin was not among the 603 shared genes). We called the SNPs on each cline separately and only retained SNPs with a minimum coverage of 30 in each of the sampled sites.We downloaded, trimmed, and mapped the raw data from Sedghifar et al.  using tholation2 . We filtAdditional file 1:Tables S1, S6, S7 and Figures S1–S17. (PDF 4847 kb)Contains Supplementary Methods, Supplementary Results, Additional file 2:Tables S2–S5. in separated sheets. (XLSX 83 kb)Contains