Several populations of Coho salmon have been maintained in aquaculture, but the extent of the genetic diversity in these strains is unknown. This paper describes the genetic status of several aquaculture strains of Coho salmon from North America, Chile, and Japan and a wild-type hatchery strain from the Pacific Northwest of North America. The Chilean strains in particular have been subject to changes in population sizes attributable to their establishment, reductions due to disease outbreaks, and maintenance of small population sizes in culture. An assumption-free method for estimating the changes in genetic diversity showed that many aquaculture strains had reduced variability. These results highlight the importance of monitoring the genetic diversity of aquaculture species from the start of breeding programs to secure their future genetic variation, particularly in challenging environments such as those expected from climate change.Understanding the genetic status of aquaculture strains is essential for developing management guidelines aimed at sustaining the rates of genetic gain for economically important traits, as well as securing populations that will be robust to climate change. Coho salmon was the first salmonid introduced to Chile for commercial purposes and now comprises an essential component of the country’s aquaculture industry. Several events, such as admixture, genetic bottlenecks, and rapid domestication, appear to be determinants in shaping the genome of commercial strains representing this species. To determine the impact of such events on the genetic diversity of these strains, we sought to estimate the effective population size (Ne) of several of these strains using genome-wide approaches. We compared these estimates to commercial strains from North America and Japan, as well as a hatchery strain used for supportive breeding of wild populations. The estimates of Ne were based on a method robust to assumptions about changes in population history, and ranged from low (Ne = 34) to relatively high (Ne = 80) in the Chilean strains. These estimates were higher than those obtained from the commercial North American strain but lower than those observed in the hatchery population and the Japanese strain (with Ne over 150). Our results suggest that some populations require measures to control the rates of inbreeding, possibly by using genomic information and incorporating new genetic material to ensure the long-term sustainability of these populations. Oncorhynchus kisutch) is one of the key salmonids contributing to aquaculture production in Chile. The species was first introduced to Chile from the west coast of North America in 1930, and since then, additional introductions have taken place from North America and Asia [Coho salmon  are expected in commercial salmonid aquaculture due to inadequate management of broodstock. The establishment of breeding populations might not have been accompanied by methods to prevent genetic bottlenecks and high rates of inbreeding. Such events might have led to sudden changes in effective population sizes . Salmonire began . The disre began ,9.It is essential to understand the status and genetic sustainability of commercial populations of Coho salmon. This situation is critical since Coho salmon is not native to Chile, but genetic rescue using introductions from outside the country has not been permitted to prevent large-scale disease outbreaks resulted in significant losses to the Atlantic salmon industry. Local feral strains might serve a role in enhancing strains, but it is not known to what extent such a step is necessary. Thus, understanding the current genetic status of these populations can help develop plans for increasing the genetic sustainability of the commercial aquaculture of this species. In this paper, we present estimates of recent and historical effective population sizes obtained from different strains of Chilean Coho salmon and compare these with commercial strains in North America and Japan. We also include a source population that has not been subject to deliberate domestication selection. The use of both contemporary and historical measures across study populations provides an understanding of the dynamics of effective population size throughout the management history of each strain.Samples from 5 Chilean strains that belong to individual companies  . This poThe North American reference, the Domsea strain, was initially derived from wild Skykomish Coho salmon returning to the Wallace hatchery in 1971, followed by three generations of mass selection by the Washington Department of Fish and Wildlife (WDFW) in 1971 and 1972 . The fouA summary of the data describing the different populations is presented in After sampling of fin tissue, DNA was extracted using the DNeasy Blood & Tissue Kits  from fin clips obtained from broodstock from the Chilean and North American strains. The Affymetrix SNP-chip used for genotyping contained 220,001 SNPs, as described previously . Thermo The ddRAD sequences from the Japanese Coho salmon strain  were map2 [e estimated at different inter-marker physical distances, from 0.1 to 2 Mb and using a minimum allele frequency (MAF) of 0.05. Bins of physical distance (every 10 kilobases) were constructed using the “content” method as implemented in the software ONeR [Estimates of the extent of linkage disequilibrium (LD), r2 , were ob2 , using tare ONeR .d2 . These values are obtained as the average of r2 [d2 of the bins, and those predicted considering different demographic histories. Notably, the temporal estimates of Ne are not modelled with the underlying assumption that there is a linear relationship between Ne and generation time, the main assumptions associated with other estimation methods [kosambi mapping function over short distances (c = 0.05). The position of the SNPs was obtained by aligning the harbouring sequence of each SNP with the Coho salmon genome version 2 (CF_002021735.2) using BWA [Estimates of Ne were obtained using the software GONE . The appge of r2  between ge of r2 . The met methods . The ana CF_0020235.2 usinFor comparison purposes, estimates of Ne were also obtained from an approach that assumes a constant linear relationship between Ne and the number of generations. The method used the derivations of ,28 and hAfter final filtering, a set of 189,501 segregating SNPs with a minor allele frequency (MAF) over 0.01 and below 0.49 across all screened populations was selected from the Coho salmon genotyping array. The median minor allele frequency was 0.24. A total of 147,349 SNPs were mapped to the 30 autosomes and used for the final analysis. The median marker spacing was 4.4 kilobases. Missing values were imputed using Beagle version 5.2 .In comparison, the median of the SNP marker distance for the ddRAD data on the Japanese population was 8.0 kilobases. The average number of markers per chromosome for the ddRAD dataset was 1727, giving a total of 51,794 across the Coho salmon genome. A description of sample size, number of polymorphic SNPs genotyped, and minimum allele frequencies are presented in 2) decay was most pronounced between SNPs separated within 0.15 Mb  is presented within each population over distances up to 2 Mb . In gene 0.15 Mb . This reThe Chilean commercial strains showed a non-linear pattern of change in Ne across time , reflectChanges in Ne in the commercial Domsea lines of North America were smaller across time. However, the relationship between Ne and the generations was not linear. There was a tendency towards decreased Ne values from 20 generations until nine generations in the past, after which there was a greater rate of decline from nine to four generations ago. This change is very similar between both lines  could nin Chile .Ne seen here [The results of this study also provide information relevant to conservation management. The Wallace River hatchery population has been maintained over time to support returning wild salmon and, as such, has incorporated locally derived wild fish in the hatchery . This poeen here . To our 2 values reported for other aquaculture species, such as rainbow trout lines raised in France [2 decreased from 0.34 at 10 kb to 0.23 at 100 kb) [The LD values estimated between markers at short distances provide insight into the possible effects of selection. Here, the values obtained for the commercial populations (≤0.1 Mb) is very similar to rn France . In this 100 kb) . At long 100 kb) .The small effective population sizes observed here are relevant to understanding future scenarios in aquaculture. For example, the ability to adapt to climate change can impact the future viability of aquaculture and natural populations ,40,41. TConcerns have been raised when applying Ne estimation methods to populations created by admixture, or when generating synthetic populations. The method of estimating Ne used here  has been. Here, we used more than 147 thousand SNPs within relatively small recombination rates (c = 0.05), providing sufficient power to obtain relatively accurate estimates. This large number of marker pairs at different distances was combined with relatively large sample sizes, gave enough power to estimate Ne. Estimates with as few as 32 haplotypes (n = 16) appear to be sufficient to recover population history, particularly recent events, as demonstrated using simulations and real data [An important issue is how accurate the estimates of Ne are when considering different methods. Estimates from GONE are proportional to the sample size, the square root of the number of pairs of SNPs included in the analysis, and the inverse of the effective population size . The sameal data . The loweal data .It is necessary to point out that any estimation method of Ne has several assumptions. In many instances, these assumptions may not be fully met in practice. For example, the estimates obtained from ,29 assumCommercial Coho salmon strains have undergone a series of events leading to contemporary values of Ne below 50 in some populations, which is the minimum value recommended for short-term sustainability of selection programs and avoiding genetic risks associated with inbreeding ,32. The


Heliconius erato and H. melpomene, which have repeatedly and independently adapted to montane habitats on either side of the Andes. We sequenced 518 whole genomes from altitudinal transects and found many regions differentiated between highland (~ 1200 m) and lowland (~ 200 m) populations. We show repeated genetic differentiation across replicate populations within species, including allopatric comparisons. In contrast, there is little molecular parallelism between the two species. By sampling five close relatives, we find that a large proportion of divergent regions identified within species have arisen from standing variation and putative adaptive introgression from high-altitude specialist species. Taken together our study supports a role for both standing genetic variation and gene flow from independently adapted species in promoting parallel local adaptation to the environment.Repeated evolution can provide insight into the mechanisms that facilitate adaptation to novel or changing environments. Here we study adaptation to altitude in two tropical butterflies,  Here, the authors study adaptation to altitude in 518 whole genomes from two species of tropical butterflies. They find repeated genetic differentiation within species, little molecular parallelism between these species, and introgression from closely related species, concluding that standing genetic variation promotes parallel local adaptation. On the other hand, these scenarios can allow us to test whether the same loci are repeatedly targeted across populations and species2. Despite many studies reporting repeated adaptation involving the same genes or alleles across lineages5, which we here term ‘molecular parallelism’, we know relatively little about the evolutionary mechanisms that facilitate this process.Understanding how organisms adapt to the environment is a central goal of evolutionary biology and highly relevant given the pace of global change. One approach is to explore the repeatability of local adaptation in the wild in order to understand whether phenotypic and genetic changes are predictable. On the one hand, repeated adaptation to similar environments can act as a ‘natural experiment’ and provide the means to identify the targets of selection, by distinguishing locally adaptive from neutral or globally beneficial changes6. Beneficial variants may be recruited from ancestral standing variation7 or shared across populations of the same species via migration and gene flow8. Lastly, gene flow between species can facilitate the introgression of adaptive alleles11. A combination of these mechanisms may also be at play, for instance the high altitude adaptation Tibetan-EPAS1 haplotype was introgressed from Denisovan hominins but remained as neutral standing variation before positive selection occurred12.Three main mechanisms can give rise to molecular parallelism in repeated adaptation Fig. . Genetic3. For instance, populations that diverged recently and retain a large pool of standing genetic variation tend to reuse pre-existing alleles during repeated adaptation, as seen in freshwater adaptation in sticklebacks13, crypsis in beach mice14, or coastal ecotypes of bottlenose dolphins7. Similarly, organisms that readily hybridise in the wild are more likely to share beneficial alleles via adaptive introgression. This allows populations to rapidly adapt to, for instance, novel anthropogenic stressors such as pollutants15 or insecticides16.The likelihood of molecular parallelism and the relative importance of each mechanism may be largely dependent on the divergence between the lineages under study Fig. , but thi17. We know very little about the genomics or predictability of adaptation to altitude, especially in the tropical insects despite making up about half of all described species (but see)20. The type and genomic architecture of the trait under study may also determine its predictability21. Phenotypes controlled by few, large-effect loci typically show predictable genetic paths of evolution, such as melanic colouration in mammals, fish, and birds25, perhaps due to selective constraints on genetic pathways27. Organisms adapting to complex environmental challenges that face multifarious selective regimes may show less predictable patterns, with functional redundancy among genes allowing for different combinations of alleles to achieve similar phenotypes29. Thus, understanding the relative importance of these mechanisms in determining the predictability of adaptation to the environment could inform future research into conservation strategies to protect biodiversity30.Anthropogenic change is forcing organisms to move, adapt, or die, with many predicted to expand their ranges towards the highlands to escape warming and degrading lowland habitatsHeliconius tropical butterflies, H. erato and H. melpomene. These aposematic, toxic species have very wide ranges and co-mimic each other across South America, commonly found from sea level to around 1600 m on both sides of the Andes31. In contrast, most other species in this genus have specialised to either highland Andean or lowland Amazonian habitats, with topography and climate shown to correlate with speciation rates across the clade32. The biogeography of these species’ ancestral ranges across the Andes is uncertain, with multiple plausible adaptive histories: ancestral adaptation to the highlands on one side of the Andes followed by expansion, gene flow of adaptive alleles between sides of the Andes, or fully independent in situ adaptation to altitude on either side of the Andes.Here, we study the genetic basis of repeated adaptation to altitude in two divergent 33. Phenotypic differences between highland and lowland populations of Heliconius have recently been identified, such as in wing shape35 and heat tolerance33, and are of similar magnitude in H. erato and H. melpomene. Thus, the observed environmental and phenotypic differences point towards an important role of local adaptation enabling these two species to inhabit wide altitudinal ranges.A recent study in this system showed that even a modest 800 m change in elevation in the Ecuadorian Andes leads to strong environmental differences, with temperatures in the lowlands more variable and, on average, 4 °C hotter, as well as threefold increase in the ‘drying power of the air’ (Vapour Pressure Deficit) which correlates with desiccation risk in ectothermsWe search for signatures of local adaptation to montane habitats with extensive sampling that harnesses the power of natural spatial replication within and across sides of the Andes, to assess the extent of molecular parallelism in adaptation to montane habitats at the upper end of the species altitudinal range (∼1200 m). We quantify parallelism at multiple levels of divergence: (i) replicate three-population transects within sides of the Andes connected via gene flow, (ii) trans-Andean allopatric three-population transects with no gene flow at these latitudes , and (iii) two species that diverged 12 million years ago Fig. . FurtherH. erato and H. melpomene, we used whole-genome data from 518 re-sequenced individuals, 444 of which were sequenced for this study. Samples were collected from 111 different locations, which we grouped into 30 populations, corresponding to four three-population transects: Colombia West/East, and Ecuador West/East  between elevations  for three transects in each species, and FH. erato had a consistently longer high-altitude branch compared to the lowland, but geographically nearby population, which could be indicative of increased drift or extensive local adaptation to altitude throughout the genome. Indeed, we detected many regions across the genome strongly differentiated in the highland populations across transects and species  or zFst values above 4 , and merging overlapping intervals into discrete regions. The transects for which only two populations were sampled (Fst), had a higher number of HDRs: 400 and 405 HDRs, covering 11.4% and 17.1% of the genome for H. erato and H. melpomene, respectively  and 38% (±4.4 SD) of HDRs overlapped between replicate transects within the Western and the Eastern Andes, respectively , but very few shared across sides of the Andes . We then tested if the observed level of sharing was higher than expected under a null distribution of genomic regions, obtained by assessing sharing in randomly placed blocks across the genome of the same size and number as observed HDRs per transect. H. erato HDR sharing was higher than predicted under a null distribution in all three comparisons , whereas the low levels of allopatric parallelism did not differ from the null distribution  or allopatric (opposite side of the Andes) transects within each species Fig. . In H. eion Fig. , red. On53, indicating a large pool of shared variants upon which selection can repeatedly act. Furthermore, recurrent gene flow between replicate populations could facilitate the recruitment of new or standing adaptive alleles, as expected from theory54 and seen in other systems such as maize, Arabidopsis, or sticklebacks55. The reduced parallelism observed between allopatric populations of H. melpomene could be due to lower standing variation or less gene flow across the Andes, compared to H. erato.In summary, we show that levels of parallelism are highest between populations of the same species connected by gene flow or sharing considerable ancestral variation, but low between species. Molecular parallelism within species could be facilitated by the high levels of nucleotide diversity observedH. erato and H. melpomene, whose clades diverged 12 million years ago38, is in stark contrast with colour patterns56, where near-perfect local Müllerian mimics have arisen repeatedly in both species through independent mutations at a handful of conserved loci58. This difference in the extent of molecular parallelism might be explained by the nature of the trait under study: adaptation to altitude is multifarious and, as shown here, involves many genes. Genetic redundancy in polygenic adaptation may lead to evolution taking different paths to reach similar solutions, as shown for quantitative iridescent colouration in these two Heliconius species59 or in recent experimental evolution of thermal adaptation in Drosophila60. In contrast, the major effect loci that underlie switches in discrete colour patterning may favour genetic predictability even across divergent taxa, especially when selection is strong and reaching adaptive peaks requires large phenotypic shifts.The lack of significant molecular parallelism in altitude candidate loci between high− πlow), deviation from neutrality in site frequency distributions (Tajima’s D), and absolute divergence (Dxy) for the same 5 kb windows. Processes other than positive selection, such as background selection, can decrease within-population diversity and thus lead to increased relative differentiation (Fst), especially in the absence of gene flow between populations62. Thus, it is important to test for enrichment of different selection statistics to strengthen our inference of locally adaptive loci. A reduced Δπ compared to the background would indicate that a selective sweep in the highlands reduced nucleotide diversity compared to the lowlands. In selective sweep regions, Tajima’s D is expected to be low, as regions with selected haplotypes that rapidly increased in frequency would have an excess of rare alleles. Finally, absolute sequence divergence (Dxy), is expected to be high in old selective sweeps or variants, and less affected by genetic variation within populations than relative measures of differentiation such as Fst63.We tested whether highly differentiated genomic regions shared across transects (SHDRs) showed additional evidence of positive selection by computing difference in nucleotide diversity (π) across elevations  of the simulated values, obtained from 10000 permutations that randomly placed blocks of equal number and size to observed HDRs across the genome. Of the SHDRs differentiated on both Ecuadorian and Colombian transects but in one side of the Andes only, i.e. across replicate transects, on average 74% and 48% of H. erato and H. melpomene SHDRs, respectively, were outliers for at least one other statistic, in addition to zPBS/zFst , 94% and 86% had at least one additional outlier statistic, respectively . In contrast, H. melpomene SHDRs were rarely outliers for Tajima’s D, whereas 22-33% of them were outliers for both Δπ and Dxy. This could point towards different selection histories in each species, with H. erato showing signatures of recent or ongoing selective sweeps leading to an excess of rare alleles (negative Tajima’s D). The Andean split is dated ~0.8 million years older in H. melpomene populations37 and their altitudinal range is wider than that of H. erato, which is rarely found > 1500 m at these latitudes. Thus, it is possible that H. melpomene SHDRs represent more ancient sweeps, reflected in the high prevalence of SHDRs outliers for Dxy. Alternatively, high absolute sequence divergence (Dxy) between elevations could be indicative of selected haplotypes arising through adaptive introgression from other species into the highland populations.SHDRs were considered outliers for Δπ, Tajima’s D, or DFst Fig.  grey. Ofely Fig. . In H. e64. We found that, on average, 59% ( ± 10 SD) of Eastern SHDRs of each species overlapped with at least one additional outlier selection statistic estimated with the haplotagging dataset, whereas, as expected, fewer Western SHDRs did  or maladaptive introgressionH. erato and H. melpomene, respectively. Adaptation to altitude is likely driven by a suite of selective factors such as temperature, air pressure, or habitat changes. Here, we do not distinguish among individual selective pressures, as these are often correlated and we do not have the power to tease them apart. Additionally, populations adapting to new or changing environments are unlikely to univariately respond to these pressures, with adaptive walks in the wild predicted to be as complex as the environments themselves. Nevertheless, future studies should test different selective pressures in laboratory settings and look for overlaps between genes of interest and SHDRs.We retrieved 908 and 747 genes overlapping with SHDRs in H. erato and H. melpomene35. Rounder wings are generally associated with the highlands across 13 species of Heliconius34. There is also subtle but highly heritable variation in wing shape associated with altitude along the Ecuadorian Eastern transect here studied35. We found that five out of 12 previously identified candidate wing shape loci35, overlapped with SHDRs in H. erato, three of which corresponded to SHDRs detected in all transects. In contrast, only two wing shape loci (out of 16) overlapped with H. melpomene SHDRs, one of which was a SHDR shared by all transects. The number of overlaps between candidate wing shape loci and SHDRs in H. erato (n = 5) was higher than the 90th quantile of 10,000 permutations, but not in H. melpomene  with outlier windows of each SHDR  could be significantly explained by altitude while accounting for genome-wide  structuring . Local PCAs at SHDRs often showed individual clustering that differed from the neutral geographic expectations  standing variation being repeatedly selected in the highlands or shared via intraspecific gene flow, or (ii) recruitment of adaptations from other high-altitude adapted species through introgression. With five high-depth individuals per population of dM statistic in 50 kb windows across the genome82. For each test, we used a tree with four populations , P3), O), where P1/P2 reflect the lowland and highland populations, respectively, and P3 is an allopatric high-altitude population of the same species or a sympatric high-altitude specialist species , and negative values indicate excess allele sharing between P3 and P1 , using the distribution of absolute negative FdM across SHDRs as a null (see Methods for details). This specifically tests whether genomic regions that are differentiated in high-altitude populations (SHDRs) are systematically enriched for alleles shared with allopatric high-altitude populations of the same species or with sympatric specialist high-altitude species.To test for excess allele sharing at SHDR, we calculated the Fies Fig. . PositivH. erato and H. melpomene, respectively37. Signatures of allele sharing likely represent shared ancestral standing variation that pre-dates the Andean split  and ~1.7 Mya in lit Fig. , but we did Fig. . Both coato Fig. . OverallH. erato and H. melpomene and five sympatric high-altitude specialist relatives  strong signatures of high-altitude differentiation in narrow regions across the genome, consistent with positive selection, (ii) high levels of molecular parallelism between transects of the same species but no sharing across species, and (iii) an important role of standing variation and adaptive introgression from high-altitude specialist species in adaptation to these montane environments. The overall lack of molecular parallelism across species points towards genetic redundancy of polygenic evolution that allows different combinations of alleles to confer adaptation to the same environments or may reflect variation in the importance of specific selection pressures across speciesOur study did not require ethical approvals. In Colombia, field collections were conducted under permit no. 530 issued by the Autoridad Nacional de 539 Licencias Ambientales of Colombia (ANLA). In Ecuador, collections during November-December 2011, and September-October 2012, were done under permit 0033-FAU-MAE-DPO-PNY and exported under permits 001-FAU-MAE-DPO-PNY and 006-EXP-CIEN-FAU-DPO-PNY. Permits were obtained from Parque Nacional Yasuní, Ministerio Del Ambiente, La Dirección Provincial de Orellana. Collections in Ecuador during 2017-2019 were conducted under the permit provided by the Ministerio del Ambiente, Ecuador (MAE-DNB-CM-2017-0058).H. erato and H. melpomene can be found across most of the Neotropics and have Müllerian aposematic mimicry to advertise their toxicity to predators, thus share colour pattern when inhabiting the same areas94. They can be found continuously coexisting across altitudinal transects ranging from sea level up to 1600 m along the Andean mountains, and H. melpomene can be found across elevations up to 1800 m. Butterflies were collected from 111 different locations, which we grouped into 30 populations, corresponding to four transects Colombia West/East, and Ecuador West/East  had the same subspecies, i.e., geographic colour morph, in the three altitudes, to avoid differentiation due to highly divergent colour pattern loci . Of the individuals sequenced for this study 365 were sequenced at low-medium depth with BGI (~6X), and 79 were sequenced at high depth with Novogene (~18X-30X), at least 5 per population. For the high-altitude specialist species dataset and outgroup species, we obtained high-depth whole genome sequencing data for 116 individuals, 63 of which were sequenced for this study at ~20X depth with BGI. A full list of individuals, localities, and accession numbers can be found in the Supplementary Data H. melpomene malleti phenotypes  using Qubit. DNA samples were stored at −20 °C until library preparation. For the individuals that were sequenced with low-medium depth, a secondary purification was performed with magnetic SpeedBeadsTM (Sigma) and we prepared Nextera DNA libraries  with purified Tn5 transposase96. PCR extension with an i7-index primer (N701–N783) and the N501 i5-index primer was performed to barcode the samples. Library purification and size selection was done using magnetic SpeedBeadsTM (Sigma). We confirmed adaptor lengths through TapeStation High sensitivity T1000  and gel electrophoresis. Pooled libraries were sequenced by The Beijing Genomics Institute (China) using HiSeq X Ten (Illumina). Library preparation and sequencing of the high-depth H. erato and H. melpomene individuals was carried with HiSeq X platform (150 bp paired-end) by Novogene.Whole genome sequence data from 518 individuals was analysed in this study, 444 were sequenced for this study, while the rest were obtained from published studies  and graphics were generated with the package H. melpomene version 2.599 or H. erato demophoon58, obtained from Lepbase98, using bwa mem (v 0.7.15100). We used samtools (v 1.9101) to sort and index the alignment files. Duplicates were removed using the MarkDuplicates program in Picard tools . Genome-wide mean sequencing depth was calculated with samtools (v 1.9101). Mean sequencing depth was very similar across areas of H. erato , but more variable, especially in Colombia where many sequences were obtained from published studies , and sites with more than 50% missing data.However, for our phylogenetic datasets combining our samples with other species for phylogenetic tree reconstruction and tests of admixture, we restricted the H. erato west (npopulation = 7), H. erato east (npopulation = 11), H. melpomene west (npopulation = 7), H. melpomene east (npopulation = 9), hereafter side-species replicate  heavily filtering 10 random individuals and obtaining minor allele frequencies (-doMaf 1) by forcing the major allele to match the reference state, so that it is the same across all populations (-doMajorMinor 4) (ii) extracting the sites and the major/minor allele frequencies, (iii) creating an indexed sites file (angsd sites index), (iv) subsetting so that sites are at least 2 kb apart, to prune for linkage disequilibrium. This list of sites and regions was then used to obtain minor/major allele frequency counts with all individuals per population and forcing the major/minor allele to match the ones given by the sites file (-doMajorMinor 3). From the resulting allele frequencies per population, we calculated allele counts, by multiplying by the number of individuals per population and the number of chromosomes samples . We obtained the required allele count matrix by concatenating all populations per side-species replicate, and only keeping loci with allele counts for all populations.To study Isolation by Distance (IBD) and Isolation by Environment (IBE), we first calculated all pairwise genetic differentiation (Fst) between all populations on each side of the Andes that had at least 5 individuals each, i.e., topodistance. With historical records from the Earthcape database106, we created a binary habitat suitability raster based on the altitudinal range of each species, so that least cost paths between populations never included elevations that these butterflies do not inhabit. Then we used the function topoLCP to get the least cost path distance between populations , and use this distance as a proxy of isolation by distance between populations.Geographical distance between populations measured as a straight line through the landscape is not biologically representative of organisms moving through space. To account for topographic complexity, we obtained topographic least cost paths with the R package 44. PBS is a summary statistic based on pairwise genetic differentiation (Fst) among three populations, two of which are located closely geographically  and one distant outgroup (low distant). For each population trio  per population. Then, we computed 2D-SFS for each population pair  with the function realSFS. We then used the 2D-SFS as a prior for the joint allele frequency probabilities at each site, which are used to compute per-site pairwise Hudson’s Fst108 as interpreted by Bhatia  among the three populations  and PBS per population . This is achieved by first transforming pairwise Fst values into relative divergence times with Eq. To then obtain PBS for a given population (here the highlands) with Eq. :2\documeH. erato and Ecuador west for H. melpomene Fig. This quantifies the magnitude of allele frequency change in the highland lineage since its divergence from the lowland and lowland distant populations. Regions of the genome with large PBS values represent loci that have undergone population-specific sequence differentiation consistent with positive selection. We computed weighted Fst and PBS averages per 5 kb window size and 1 kb steps , with the same window centres across datasets (-type 0). For transects where only two out of three populations had any individuals . We then expanded outlier window positions 50 kb upstream and 50 kb downstream from the window centre (HDR) and checked for overlaps with other transects, either within or across sides of the Andes for each species, to highlight parallelism when visualizing patterns of genome-wide divergence. High-differentiation regions with any overlap with other transects are termed shared HDRs (SHDRs). To check for HDR overlaps between species, we mapped the H. melpomene windows (starts and end positions) to the H. erato reference genome using a chainfile64 and the liftover utility .To measure genetic parallelisms in adaptation to the highlands, we quantified overlap of outlier windows and adjacent regions, i.e. high differentiation regions (HDR), across replicate and allopatric transects and species. We considered outlier windows to be those with values above 4 standard deviations from their mean , by obtaining the start and end positions of continuous blocks of outlier windows ( ± 50 kb buffers) with the function Intervals . We obtained the observed proportion of total intervals that overlapped, at any of their positions, with outlier intervals in the other transect within sides of the Andes, or with outlier intervals in both, the other transect within the same side of the Andes and the two transects on the other side of the Andes . We then simulated 10,000 randomized distributions of outlier-window intervals across the genome per transect, per species (n = 8). In each simulation set, we randomly placed the same number of HDR intervals and of the same size as the observed outlier-window intervals for those transects. With these, we estimated the proportion of simulated intervals that overlapped with observed HDR outlier intervals within and across sides of the Andes, obtaining as a result a null distribution of interval overlap proportions. This approach does not account for the possibility that different parts of the genome may be more readily involved in local adaptation. Finally, to determine whether the level of overlap was significantly greater than expected by chance alone, we performed jackknife block resampling across the genome to estimate the 95% CI for the observed proportion of overlapping intervals and then assessed whether this interval included the expected value, which was computed as the mean of 10,000 random permutations described above.To test whether the level of parallelism observed between transects within and across sides of the Andes was higher than expected by chance, we used the R package 103, Tajima’s D, which estimates the deviation of a sequence from neutrality, nucleotide diversity , and Dxy or absolute divergence, which calculates pairwise differences between sequences of two populations excluding differences between sequences within populations. ANGSD has been found to be an accurate estimator of nucleotide diversity because it includes invariant sites111. Firstly, we obtained folded global site-frequency spectra for each population. Then we calculated pairwise nucleotide diversity per site . Finally, we performed sliding window analysis of 5 kb window size and 1 kb steps (thetaStat do_stat) to obtain sum of pairwise differences, Tajima’s D, and total effective number of sites per window. Nucleotide diversity (pi) was obtained by dividing the sum of pairwise differences by the total number of sites per window. For all transects, we calculated the difference in nucleotide diversity per window between highland and lowland distant populations , which is expected to be negative if a selective sweep led to locally reduced diversity in highland populations. Absolute divergence  between high (population A) and low/low distant (population B) populations was estimated by additionally obtaining pairwise nucleotide diversity per site (thetaD) for all individuals pooled from populations A and B (population AB), and then per-site Dxy obtained with Eq.  estimated for 13 H. erato populations from across the range in a recent study113 and for 100 kb windows of four H. melpomene populations71. Note that the H. erato genome is larger than H. melpomene , hence the difference in window sizes.With n being the number of individuals per population  and thetaD obtained from realSFS saf2theta. Mean Dhigh− πlow), and absolute divergence (Dxy) within SHDRs and compared values to simulated distributions. We used the same permutation approach described for assessing HDR parallelism, by randomly placing the same number of intervals and of the same size as the observed HDRs for each transect 10000 times. We then obtained minimum Tajima’s D and Δπ and maximum Dxy within each simulated SHDR and permutation, and only considered a SHDR to be an outlier for a given selection statistic if the observed maximum  or minimum (Dxy) value was above the 90th or below the 10th percentile of simulated values. Number of outlier selection statistics per SHDR was tallied and compared across replicate or allopatric sharing in each species.To test for positive selection we assessed Tajima’s D, difference in nucleotide diversity across elevations Δπ  to obtain genotype likelihoods in beagle format (-doGlf 2) for all individuals. In H. erato, we excluded chromosome 2 as it contains a large inversion which could distort the neutral differentiation landscape. Genotype likelihoods were used as input for PCAngsd114, which incorporates genotype uncertainty from genotype likelihoods to obtain a covariance matrix across all individuals.To assess neutral genetic variation between individuals and populations, we performed principal component analysis (PCA) in the eastern and western transects separately for each species, i.e., two transects per PCA Fig. . We firs2) for each SHDR local PCA and the relative contributions of each explanatory variable , estimated with the package relaimpo115.To assess whether the same haplotypes were involved in adaptation to altitude across replicate transects (within sides of the Andes), we performed local PCAs with outlier windows  of each SHDR . All individuals from replicate transects were included, leading to local PCAs for all Western and Eastern SHDRs of each species that included Colombia and Ecuador samples. We obtained genotype likelihoods in beagle format (-doGlf 2) as input for PCAngsd, similarly to the population structure analysis. We then assessed whether altitude was a significant predictor of individual clustering in each SHDR by building a linear model where local PCA PC1 was the response variable, and altitude and global (genome wide) PCA PC1 the predictors, to account for population structure. We considered that individuals in each replicate transect had the same haplotypes in SHDRs if altitude was a significant predictor of local PCA PC1, while controlling for global PC1 Fig. . We addiABBA-BABA-related statistics to examine patterns of allele sharing between closely or distantly related high-altitude species and our study H. erato and H. melpomene populations. These statistics test for an excess of shared derived variation between lineages to distinguish gene flow or ancestral population structure from the incomplete lineage sorting (ILS) that can occur during a simple tree-like branching process. To examine genome-wide patterns of excess allele sharing between populations and species, we obtained F branch statistics implemented with the package Dsuite86. Fbranch summarises and visualises patterns of excess allele sharing across phylogenetic datasets. We performed linkage-pruning to obtain a genome-wide average of excess allele sharing. Using a custom script (https://github.com/joanam/scripts/blob/master/ldPruning.sh) we removed sites above an LD-threshold of R2 > 0.1 with plink v. 1.07116. To reconstruct the backbone phylogeny for excess allele sharing tests, we extracted for each population or species the individual with highest sequencing depth from the vcf file using vcftools v. 0.1.15105. The vcf file was then converted to phylip with a custom script (https://github.com/joanam/scripts/blob/master/vcf2phylip.py). We reconstructed the phylogeny of the melpomene and erato clade separately with RAxML v. 8.2.9 using the GTRGAMMA model117. Using this backbone tree, we used the LD-pruned vcf files of all melpomene/erato clade individuals to computed f statistics  across all possible sets of three populations or species with Dsuite Dtrios. Next, we summarized these statistics with Dsuite Fbranch118. The extent of gene flow in the eastern Andes between H. melpomene and H. timareta can skew genome-wide trees. Thus, to assess the levels of gene flow, we constrained the H. melpomene clade to be monophyletic following the species tree. In order to remove spurious signatures of excess allele sharing that are not significant, we set Fbranch values to 0 if the z-score was greater than 3 with a custom script (https://github.com/joanam/scripts/blob/master/removeNonsignDsuite.r). Lastly, we plotted the Fbranch statistics along the phylogeny with dtools.py of the Dsuite package.We used H. erato and H. melpomene highland populations, we computed fdM, a statistic of excess allele sharing suitable for small genomic regions. This test is based on a set of four populations, including two sister taxa (P1 & P2), a close relative (P3) that may have admixed with one of these sister taxa and an outgroup (O). Here, the sister taxa represent the H. erato or H. melpomene lowland (P1) and highland populations (P2), whereas P3 represents a highland specialist species that may have contributed beneficial gene variants to the H. erato and H. melpomene highland populations. fdM quantifies gene flow between P3 and P2 or between P3 and P1. In addition, we ran these tests with the allopatric erato/melpomene populations as P3, to test if at SHDRs, the same haplotypes are found in high-altitude populations on both sides of the Andes, potentially due to parallel selection on the same haplotypes. We estimated fdM for non-overlapping 50 kb windows across the genome with the ABBABABAwindows.py script by  from https://github.com/simonhmartin/genomics_general. We considered individual SHDRs as fdM outliers if their observed maximum fdM value was > 90th percentile of the absolute minimum fdM values across all SHDRs. Additionally, we tested for overall enrichment of excess allele sharing between P3 and P2  across all SHDRs, by testing with a two-sample Kolmogorov-Smirnov tests if the distribution of maximum fdM values across all SHDRs  was significantly higher than the absolute minimum fdM values across all SHDRs . This was repeated for each Colombia/Ecuadorian clines with their respective potential donors (P3).To test for adaptive introgression from high-altitude specialist species into Further information on research design is available in the Supplementary InformationDescription of Additional Supplementary FilesSupplementary Data 1Reporting Summary


DPYD gene. Their prevalence and allelic frequencies vary considerably worldwide, so their description in heterogeneous groups such as the Ecuadorian population will allow for the description of pharmacogenetic variants and proper characterization of this population. Thus, we genotyped all the molecular variants with a predictive value for DPYD in a total of 410 Ecuadorian individuals belonging to Mestizo, Afro-Ecuadorian, and Indigenous ethnic groups. Moreover, we developed a genetic ancestry analysis using 46 autosomal ancestry informative markers. We determined 20 genetic variations in 5 amplified regions, including 3 novel single nucleotide variants. The allele frequencies for DPYD variants c.1627G>A , c.1129-15T>C (rs56293913), c.1218G>A (rs61622928), rs1337752, rs141050810, rs2786783, rs2811178, and g.97450142G>A  are significantly related to Native American and African ancestry proportions. In addition, the FST calculated from these variants demonstrates the closeness between Indigenous and Mestizo populations, and evidences genetic divergence between Afro-Ecuadorian groups when compared with Mestizo and Indigenous ethnic groups. In conclusion, the genetic variability in the DPYD gene is related to the genetic component of ancestral populations in different Ecuadorian ethnic groups. The absence and low frequency of variants with predictive value for fluoropyrimidine toxicity such as DPYD *2A, HapB3, and c.2846A>T  is consistent with the genetic background found.Dihydropyrimidine dehydrogenase is one of the main pharmacological metabolizers of fluoropyrimidines, a group of drugs widely used in clinical oncology. Around 20 to 30% of patients treated with fluoropyrimidines experience severe toxicity caused by a partial or total decrease in enzymatic activity. This decrease is due to molecular variants in the  Dihydropyrimidine dehydrogenase (DPD) is a metabolic enzyme in the pyrimidine catabolic pathway, responsible for the conversion of thymine or uracil to 5,6-dihydrothymine or 5,6-dihydrouracil, respectively . As a phDPYD gene that result in partial or total loss of DPD activity [A decrease in the enzymatic activity of DPD is associated with the development of toxicity in patients treated with chemotherapeutic schemes based on fluoropyrimidines. Several studies have shown a partial deficiency of DPD in 3–8% of patients who develop toxicity. Of these, 50% showed a reduction in their enzymatic activity . Moleculactivity , and theactivity .DPYD is one of the most studied genes in clinical oncology [DPYD single nucleotide variant (SNV) c.1905+1G>A  was the first to be described as functionally relevant [DPYD variants such as c.2846A>T (rs67376798), c.1679T>G , and c.1236G>A  were later identified as pharmacogenetic markers with clinical relevance [oncology ,17,18, woncology ,20. The relevant . Its allrelevant ,23,24,25relevant ,27. OtheDPYD c.1905+1G>A , c.1898del , c.1679T>G  and c.1156G>T , and variants associated with a decreased function for the enzyme, such as c.2846A>T (rs67376798) and c.1236G>A , are related to toxicity in carrier individuals that lies in a significant reduction in the enzymatic activity of DPD [DPYD c c.1905+1G>A, c.1679T>G, c.2846A>T and c.1236G>A variants, an initial half dose of 50% of fluoropyrimidines is recommended [Considering all this evidence, the Clinical Pharmacogenetics Implementation Consortium (CPIC) and the Dutch Pharmacogenetics Working Group (DPWG) ,31 descrl *3, rs749303, c.y of DPD ,35,36,37ommended ,38,39, tDPYD in Ecuadorian heterogeneous populations will let us study both their genetic characterization, and above all, the implementation of personalized oncological therapies. The Ecuadorian population studied comprises three main ethnic groups: Mestizos, Afro-Ecuadorian, and Indigenous, distributed throughout the country. The genetic background for each group is different, hence it is paramount to consider their ancestry proportions and establish an association with the frequencies of the predictive variants. In fact, by determining the frequencies of these molecular variants in a healthy population, it will be possible to evaluate the usefulness of screening tests in the routine pretreatment of patients undergoing chemotherapy based on fluoropyrimidines, or will allow proposing alternative strategies for avoiding toxicity. The study population of this work represents the heterogeneity of the Ecuadorian people.Population genetic diversity is related to the inter-individual response to drugs used in pharmacological therapy . One of A total of 410 unrelated Ecuadorian individuals (men and women) aged 18 and over were included in the study. Blood samples and buccal swabs were collected with written informed consent. The project was approved by the Ethical Committee in Human Research from the Universidad de las Américas (CEISH-UDLA 2017-0301).The population studied consisted of Ecuadorian individuals from the 3 main geographic regions of the country: Coast (CO), Andes/Highlands (HG), and the Amazon Region (AZ). The ethnic self-denomination of the participants was also considered, namely Mestizo groups (MEZ), Afro-Ecuadorian (AFE), and Indigenous (IND). The MEZ groups inhabit the CO , HG , and AZ ; the AFE inhabit the CO  and HG ; and IND groups inhabit the CO , HG , and AZ .Genomic DNA extraction from blood samples was performed using the standard phenol–chloroform method . For bucGenotyping was determined using Sanger sequencing, where the amplified PCR products were subsequently purified, analyzed, and aligned with the RefSeq NC_000001.11 (GRCh38.p13).https://www.ncbi.nlm.nih.gov/tools/primer-blast/, accessed on 10 November 2022). We considered the default parameters and contemplated the inclusion of DPYD variants with clinical significance in oncological practice [DPYD c.1905+1G>A , c.1898del , c.1679T>G  and c.1156G>T ; (2) variants associated with a decreased function for the enzyme: c.2846A>T (rs67376798) and c.1236G>A ; and (3) variants described as fully functional for DPD: c.1896T>C (rs17376848), c.1627G>A , c.1601G>A , and c.85T>C .In order to design the primers, we used the Primer-BLAST tool  according to the manufacturer’s instructions. Within the reaction, we used ~50 ng of DNA, 1x GoTaq Green Master Mix, and 0.3 µM of each primer, in a final volume of 25 µL. Following the amplification, the PCR products were purified using AMPure XP magnetic purification beads , following the manufacturer’s directions, and were eluted in an elution buffer  for a final volume of 20 µL.The PCR reaction was performed using the GoTaq® Terminator v3.1 Cycle Sequencing Kit  following the manufacturer’s instructions. Within the reaction, a final concentration of 1 µM of primer was used in a volume of 20 uL. The amplicons were purified using Agencourt CleanSEQ chemistry , following the standard protocol, and ran in an ABI 3130 Genetic Analyzer 142 . The sequences were visualized using the GeneMapper software version 3.2  and aligned in the Geneous program with the reference sequence NC_000001.11.Next, the amplicons were sequenced using the BigDyeDNA samples were genotyped for a set of 46 autosomal ancestry informative markers (AIM-INDELs) in a single PCR multiplex reaction, applying the same previously described PCR conditions and primer concentrations [Ancestry inferences were obtained using the admixture model with K = 3 (based in trihybrid historic admixture) on STRUCTURE V2.3.4 software . Runs cop-values < 0.01 were considered highly significant. Numeric variables were described using arithmetic means and standard deviations (SD). These statistical analyses were performed using the IBM SPSS Statistics 22 software .The estimated proportions of ancestral populations for each participant were compared with the genotyping results and geographic background using non-parametric tests . The ST), and analysis of molecular variance (AMOVA), were estimated using Arlequin software v.3.5.2.2 [DPYD genotyping, p-values > 0.0025 show no significant deviations from HWE. For the analysis of pairwise, based on the classification proposed by Ballaux et al. (2002) FST values of 0–0.05 were interpreted as having little genetic distance between analyzed groups, values of 0.05–0.15 as moderate differentiation, and 0.15–0.25 as great differentiation [ST matrix was represented in multidimensional scaling (MDS) using the multidimensional scaling (PROXSCAL) of the IBM SPSS Statistics 22 software .Finally, the population genetic parameters, such as allele frequencies, Hardy–Weinberg equilibrium (HWE), pairwise genetic distances , g.97450088T>G, and g.97082286A>C. The frequency of these SNVs for the minor allele was 0.001, except for the variant g.97450142G>A (0.059). The SNVs g.97450142G>A and g.97450088T>G are placed in the exonic region . Although g.97450142G>A is a synonymous variant (NP_000101.2:p.Leu608=), g.97450088T>G induces a change of threonine to proline at position 626 (NP_000101.2:p.Thr626Pro). The SNV at position g.97082286A>C is placed in the intronic region (NM_000110.3:c.2907+43T>G). All the allelic and genotypic frequencies, as well as the p-values calculated for HWE are described in Interestingly, we detected undescribed SNVs for p < 0.0025). Nevertheless, when developing this analysis by grouping the individuals by ethnic self-denominations, only SNVs rs1337752 and rs2811178 did not meet the equilibrium in the MEZ and AFE groups, respectively. No statistically significant deviations from HWE expectations were detected for the 20 loci in the population under study when considering the groups by ethnic self-denominations and geographic location  predominates, followed by AFR (0.228) and EUR (0.124) contributions. Considering ethnic groups, the self-proclaimed IND people show a high percentage of NAM ancestry (0.906), while in MEZ, the NAM and EUR proportions predominate in their genetic background . As expected, AFE populations show a high proportion of AFR ancestry (0.768) A.The inference of ancestry proportions also describes the genetic composition of the ethnic groups throughout the three geographic regions studied. As can be seen in We compared the estimated proportions of each participant with the genotypes found for all SNVs with allele frequencies > 0.001 for the minor allele. We found that the variants c.1627G>A, c.1129-15T>C, c.1218G>A, rs1337752, rs141050810, rs2786783, rs2811178, and the SNV g.97450142G>A are significantly correlated with AFR ancestry. Similarly, these loci (except for c.1129-15T>C and c.1218G>A) show statistically significant differences with proportions calculated for NAM populations. None of the cases presented statistical differences when comparing the genotypes found with EUR ancestry .DPYD genotyping in the Ecuadorian population were used to estimate the FST genetic distances between all population pairs.The data obtained from the genetic ancestry analysis and ST genetic distances between all pairs of ancestral populations and Ecuadorian ethnic groups from the 46 AIM-INDELs showed statistically significant differences (p < 0.00000). Despite this, the low FST values indicate the closeness of IND and MEZ populations to NAM ancestral populations  and AFE groups to AFR ancestral populations (FST = 0.019). These values increase when comparing the ethnic groups with the EUR reference, having an FST of 0.275 with IND, 0.242 with AFE, and 0.145 with MEZ , while the AFE population shows moderate differentiation . No intra-ethnic variation is shown when taking into account the geographical origin of the groups. The FST obtained in the IND of the three regions is low in all pairwise comparisons (FST < 0.0445). Likewise, the values obtained between the AFE groups of CO and HG, and the MEZ of the three regions are minimal   A. This sST values (ST) and the corresponding non-differentiation p-values are shown in AFR, EUR, and NAM continental ancestry groups are separated as three poles of diversity on the MDS plot of the pairwise FT values B. MEZ grDPYD gene, we estimated the FST genetic distances between all population pairs. Similar to what was found with the 46 AIM-INDELs, the FST values showed little genetic distance between MEZ and NAM populations ; while comparing AFE groups with MEZ and IND, these values indicated moderate differentiation . When evaluating the ethnic groups by geographic origin, there is no great divergence, especially between MEZ groups of the three regions studied , and in AFE groups of CO and HG . The comparison of IND groups from the HG region with CO and AZ had low divergence ; however, this index increased between IND groups from CO and AZ  (ST) and the corresponding non-differentiation p-values are shown in ST values, the distribution of the points revealed that AFE populations (from HG and CO) have distinctive genetic profiles to both MEZ and IND geographic groups. Interestingly, IND groups from CO showed moderate differentiation with IND groups from AZ  C. All th from AZ D.p < 0.001), while MEZ and IND groups did not show a statistically significant difference (p = 0.35860).Lastly, the differentiation test between all pairs of samples  showed significant differences when comparing AFE with MEZ and IND groups , c.1898del , c.1679T>G , and c.1156G>T . The frequencies for the variants associated with a decreased function for the enzyme c.1236G>A  and c.2846A>T (rs67376798) are low (0.001). Conversely, the fully functional variants c.1896T>C (rs17376848), c.1627G>A , and c.85T>C  are the most prevalent, with a frequency for the minor allele of 0.045, 0.301, and 0.194, respectively. Only the fully functional c.1601G>A  registers a low frequency (0.002) in the tested population.The genotypic analysis applied to participants describes an Ecuadorian population that does not carry the nonfunctional variants DPYD suggests that genetic screening in Ecuadorian cancer patients treated with 5-Fu would not be the best strategy for avoiding toxicity. Alternative tests, such as measuring endogenous plasma dihydrouracil/uracil (UH2/U) ratios or measuring the DPD enzyme activity in peripheral blood mononuclear cells (PBMCs) [The prevalence of variants with phenotypic consequence in DPD or variants that are clinically associated with 5-FU toxicity are of very low frequency worldwide ,51,52,53 (PBMCs) ,55,56, cDespite the fact that fully functional variants were dismissed as having too low a penetrance to be of pharmacological importance, one should consider the reports in which a degree of association was found with secondary events during chemotherapeutic schemes based on fluoropyrimidines, especially with c.85T>C. The effect of c.85T>C on fluoropyrimidine treatment-related toxicity was initially reported in DPD deficient patients ; nonetheThe Ecuadorian population shows a complex demographic history, for it is defined as multiethnic and multicultural. From the Spanish colonization onwards, the continuous admixture between Europeans, Native Amerindians , and peop-value for the FST index is statistically significantly different (p = 0.0000), suggesting that the NAM component for an admixed population is heterogeneous [ST (0.0348) show little genetic distance with IND groups, indicating a low degree of divergence between both groups and evidencing a high Native American contribution to their genetic ancestry.The IND groups show a high proportion of NAM ancestry (0.906), denoting their low degree of admixture with EUR and AFR populations. Ecuadorian MEZ groups evidence their history of admixture with the Spanish population, where the percentages of EUR (0.265) and NAM (0.636) ancestral proportions are prevalent in the individual genotypes. Although the largest contribution in MEZ is NAM, the ogeneous ,73. The DPYD. The global frequencies for each of those nonfunctional and decreased variants, based on data from the Allele Frequency Aggregator (ALFA) project [While the NAM ancestry is the main composition of the MEZ, IND, and the Ecuadorian population considered as a whole, the AFR component is the predominant background for AFE groups (0.768). Afro-descendent populations in Ecuador have a discrete distribution, allocated along the Ecuadorian coastline, and mainly in the provinces of Esmeraldas and Imbabura. The estimated membership coefficients for AFR are in line with this, showing a higher frequency for this ancestral population in a relatively small territory in the north of the country B. This g project , ranges DPYD is heterogeneous and has a close relationship with biogeographical ancestry [DPYD and the proportion of ancestry with ancestral reference populations, especially with NAM and AFR populations. DPYD variants c.1627G>A , rs1337752, rs2786783, and rs2811178 have a statistically significant association with NAM ratio in genotyped individuals. Their frequency in individuals with MEZ and IND is higher than in AFE individuals. On the other hand, the c.1129-15T>C (rs56293913), c.1218G>A (rs61622928), rs141050810, and g.97450142G>A SNVs have an association with AFR ancestry, which shows differences in the genetic landscape and variant frequencies between ethnogeographic groups.The genetic variability reported in ancestry ,76,77,78DPYD describe genetic divergences between AFE populations when compared to NAM and MEZ. It is interesting to note that, as observed in the ancestry analysis estimation with the 46 AIM-INDELs, DYPD variants demonstrate the genetic closeness between MEZ and IND groups and show a divergence when compared to AFE populations.The mapping of variant frequencies in different ethnogeographic groups can provide important information about genetic structure, enabling better characterization of heterogeneous populations. In the HWE analysis, the loci c.85T>C , rs1337752, rs2786783, and rs2811178 showed statistically significant deviations; nevertheless, when stratifying the sample by considering ethnic self-identification and geographical origin, no statistically significant deviations from HWE expectations were detected. This imbalance can occur possibly due to geographic barriers that limit gene flow (migration) or genetic drift in subpopulations. Another possibility that cannot be ruled out is non-random mating or the existence of selection processes . The excDPYD within a healthy Latin American population where their frequencies were not previously reported. One of the main limitations of this study is the lack of association between molecular variants in DPYD and toxicity in the cancer population treated with fluoropyrimidines. Since clinical and genetic factors can develop toxicity events to fluoropyrimidine-based chemotherapy, it is recommended to develop a prospective study on Ecuadorian patients treated with fluoropyrimidines and apply a more robust genetic screening using next generation sequencing. So far, the functional impact of several additional DPYD SNVs remains unknown, so a study in different ethnic groups may yield important results on molecular variants associated with decreased or lost function in DPD. On the other hand, even though they were included individuals belonging to the three main ethnic groups of Ecuador, distributed throughout the CO, HG and AZ regions, the number of participants studied does not allow for the evaluation of the intra-ethnic variation that exists in the Ecuadorian population. It is therefore necessary to increase the study population to evaluate minority groups within the ethnic groups analyzed.It is important to note that the main objective of this study is to describe the prevalence and frequency of predictive variants in DPYD gene is heterogeneous within a multicultural and multiethnic Ecuadorian population. The frequency of the SNVs c.1627G>A , c.1129-15T>C (rs56293913), c.1218G>A (rs61622928), rs1337752, rs141050810, rs2786783, rs2811178, and g.97450142G>A  has a significant association with the genetic profile of Ecuadorian ethnic groups, especially with the component of ancestral NAM and AFR populations. The pairwise genetic distances calculated, both with variants in DPYD and with the 46 AIM-INDELs, demonstrate the closeness between IND and MEZ populations, and evidence genetic divergence between AFE groups when compared with MEZ and IND ethnic groups. In a trihybrid population where the NAM ancestry is the main genetic component, the absence and low frequency of predictive variants prevalent in European populations  is consistent with the genetic profile found. Therefore, a genetic screening of variants with predictive value in DPYD would not be informative in Ecuadorian cancer patients treated with fluoropyrimidines. The use of alternative tests, for instance measuring endogenous plasma dihydrouracil/uracil (UH2/U) ratios or measuring the DPD enzyme activity in peripheral blood mononuclear cells (PBMCs), may be better strategies in order to avoid such toxicity.In conclusion, the genetic diversity of the


Micromeria and six Clinopodium taxa (family Lamiaceae) distributed in the Balkan Peninsula was carried out. The phytochemicals detected in essential oils by gas chromatography, mass spectrometry, and molecular data amplified fragment length polymorphism were used to study the taxonomic relationships among the taxa and the correlations between phytochemical and molecular data. STRUCTURE analysis revealed three genetic groups, while Bayesian Analysis of Population Structure grouped the studied taxa into 11 clusters nested in the groups obtained by STRUCTURE. Principal components analysis performed with the 21 most represented compounds in the essential oils yielded results that were partly consistent with those obtained by STRUCTURE and neighbour-joining analyses. However, their geographic distributions did not support the genetic grouping of the studied taxa and populations. The Mantel test showed a significant correlation between the phytochemical and genetic data . Genetic distance explained 17.8% of the phytochemical distance between populations. The current taxonomic position of several of the studied taxa is yet to be satisfactorily resolved, and further studies are needed. Such future research should include nuclear and plastid DNA sequences from a larger sample of populations and individuals.A study of the phytochemical and molecular characteristics of ten  Micromeria Benth. (Lamiaceae) includes 54 [Micromeria species extends from the Mediterranean to South Africa and Madagascar and from China to the Macaronesian Archipelago. Chater and Guinea [Micromeria species for Europe, with more than half of these species occurring in the Balkan Peninsula. The genus Micromeria is part of a complex group of genera in the tribe Mentheae and subtribe Menthinae  and has often been considered part of the loosely defined “Satureja” complex [Micromeria species strictly as a distinct genus, and this opinion prevails today [Micromeria, while Doroszenko [Micromeria inhabiting the Balkan Peninsula, which are the focus of this article, belong to the sections Pseudomelissa and Micromeria [Micromeria is polyphyletic and that its revision is necessary. Based on this view, Bräuchler et al. [Micromeria to the genus Clinopodium L. Bräuchler et al. [Micromeria and closely related Clinopodium species support the recent transfer of the section Pseudomelissa into the genus Clinopodium [The genus ludes 54 , 70, or ludes 54  annual aludes 54 ,3, the d complex ,7. On th complex  acceptedls today ,10,11,12ls today  proposedcromeria  or Pseudcromeria . Bräuchlr et al.  transfernopodium .Micromeria is represented in the Balkan Peninsula by several species with narrow distribution ranges that are primarily included on local floras and lists [The genus nd lists ,21,22,23nd lists ,28,29,30Micromeria and Clinopodium species have been widely studied [Genetic studies can help reconstruct the evolutionary history and the delimitation of species or subspecies ,32. The  studied ,42,43,44 studied ,42 have Micromeria and closely related Clinopodium species recently transferred from the section Pseudomelissa that are widely distributed in the Balkan Peninsula. To achieve this goal, molecular and phytochemical studies were performed at the population level on 16 Balkan Micromeria and closely related Clinopodium taxa.This study aims to obtain additional knowledge about Clinopodium pulegium (Cp)  and the highest in Micromeria cristata ssp. cristata (population Mc3) . Of the 1694 polymorphic markers in 434 individuals, 19 were private (unique to a specific population). They were detected across 14 populations, most belonging to M. cristata ssp. cristata  and a single population of M. graeca ssp. fruticulosa , whereas no private alleles were detected in populations of M. kerneri. Of the 16 Clinopodium populations, private alleles were detected in only three. Frequency down-weighted marker values (DW) ranged from 1139.31  to 6622.21 (M. graeca ssp. fruticulosa). The highest values were detected in M. graeca and M. cristata, while much lower values were found in the other studied taxa. The expected heterozygosity (HE) levels ranged from 0.073 (populations Mcr1 and Mcr5 of M. croatica) to 0.130  and 0.131 (population Mj6 of M. juliana). With an average value of 0.114, M. cristata and M. juliana had the highest HE levels, while M. longipedunculata and M. croatica were on the other side of the spectrum, with an average HE value of 0.084. Of the total variability, 48.68% refers to variability between and 51.32% within populations, indicating significant differences between the studied populations. AMOVA analysis showed that intrapopulation variability was considerably higher than among populations (M. graeca ssp. graeca) to 34.45% (M. kerneri). For most species, interpopulation variability was approximately 10%. The exceptions were the populations of M. cristata (24.82%) and M. kerneri (34.45%), which had a higher and significant interpopulation distance (ΦST).Amplified fragment length polymorphism (AFLP) analysis revealed high contrasts in population–genetic parameters among the studied populations. The percentage of polymorphic fragments and Shannon’s index  varied aulations . VariabiMicromeria and Clinopodium are well-differentiated groups of closely related taxa. In addition, most individuals in both groups were well-supported, except for the M. juliana–M. kerneri–M. microphylla cluster, characterised by low differentiation among the adopted taxa. Individuals of M. juliana were grouped in the same cluster with M. kerneri from the Croatian population Gradina (Mk3). The population of M. microphylla (Mm) was divided into two clusters and associated with four populations of M. kerneri. The AMOVA results showed no statistically significant differences between M. microphylla and M. kerneri. Two populations of M. croatica, known from local Balkan literature as M. pseudocroatica (McrP), were separated from the remaining ten populations of M. croatica (Mcr) (M. graeca ssp. fruticulosa (MgF) was recognised as a distinct taxon, separated from the two populations of M. graeca ssp. graeca (Mg). In the NJ tree, the population of M. cristata ssp. kosaninii (McK) and two populations of M. cristata ssp. cristata  were also separated.The results of neighbour-joining (NJ) analysis are shown in ca (Mcr) , Table 3Clinopodium is complex. Clinopodium dalmaticum showed genetic differentiation into two subgroups. The first subgroup was formed by two Montenegrin populations (Cd), while the second was formed by three Bulgarian populations (CdB). Moreover, the Bulgarian populations were closer to C. frivaldszkyanum (Cf) than to the Montenegrin populations of the same species  were separated from the other taxa with high bootstrap support.The position of the studied taxa within the genus  species . Three oMicromeria cristata, M. croatica, M. graeca, and M. longipedunculata; the second included the populations of M. juliana and M. kerneri; the third included all Clinopodium populations studied. While low levels of admixture characterised most of the studied populations, this was not the case with the M. microphylla population that was positioned between the two Micromeria clusters with high admixture levels. The genetic clusters were not geographically defined, since representatives of each cluster are found throughout the studied area.In the STRUCTURE analysis, the highest K value was observed for K = 3 (K = 1394.43), indicating the presence of three genetic clusters . STRUCTUMicromeria and Clinopodium taxa to 11 clusters nested within the groups identified by the STRUCTURE analysis. The best partitions received log-likelihoods of −182,699.06 at P = 1 (without using geographic coordinates as informative priors) and −183,284.74 at P = 1 . In general, both methods produced nearly identical results. The first two groups of the BAPS analysis were formed by M. cristata ssp. cristata (Mc) and M. cristata ssp. kosaninii (McK); the third group was formed by M. croatica (Mcr); the fourth by two populations of M. croatica covered under the disputed name M. pseudocroatica (McrP); the fifth and sixth clusters were formed by M. graeca ssp. graeca (Mg) and M. graeca ssp. fruticulosa (MgF), respectively; the seventh by M. juliana (Mj) and one population of M. kerneri (Mk3); the eighth by M. microphylla (Mm) and four populations of M. kerneri ; the ninth by M. longipedunculata (Ml); the tenth by C. pulegium (Cp), C. serpyllifolium (Cs), C. dalmaticum (Cd), and C. thymifolium populations; the eleventh cluster was formed by C. frivaldszkyanum (Cf) and three C. dalmaticum (CdB) populations listed under the contested name M. bulgarica.On the other hand, BAPS analysis B revealeMicromeria and 15 samples from the genus Clinopodium , oxygenated monoterpenes (10.42–85.31%), sesquiterpene hydrocarbons (1.09–35.73%), oxygenated sesquiterpenes (0.25–39.39%), phenolic compounds (0–25.73%), carbonyl compounds (0–2.56%), and hydrocarbons (0.25–14.07%).The composition and yield of EO in this study included 41 oil samples from the genus nopodium . The yieMicromeria cristata ssp. cristata, the compounds borneol (14.11–26.28%) and α-cadinol (12.48–17.72%) were most abundant. The compounds α-muurolol (17.53%) and pulegone (8.91%) were detected only in M. cristata subsp. kosaninii. The detection of verbenone, camphene, bornyl acetate, and α-humulene in all populations of M. cristata but not in M. cristata subsp. kosaninii (E-caryophyllene (7.13–16.8%), caryophyllene oxide (10.92–15.75%), and germacrene D (2.95–14.12%) were the main components of EO extracted from all 12 samples of M. croatica  at both sites. In the EO of M. graeca subsp. fruticulosa, α-bisabolol was also abundant (11.92%), but the most representative compound was pinocarvone (17.39%) (M. juliana were E-caryophyllene (10.62–22.35%) and caryophyllene oxide (22.26–32.72%)  , while M. microphylla was rich in eudesem-7(11)-en-4-ol (22.91%)  . The mos–32.72%) . Caryoph–16.13%) . Isolate(22.91%) .Clinopodium dalmaticum showed the most significant differences in EO composition among the investigated Clinopodium taxa. The oil composition in the Montenegrin samples consisted mainly of piperitone (more than 30%). Two Bulgarian populations presented high concentrations of E-caryophyllene , while population CdB3 had the highest content of α-pinene (14.31%). Thymol was also prominent in Bulgarian populations of C. dalmaticum. Pulegone  and menthone  were dominant in the composition of C. frivaldszkyanum  the most abundant compounds were pulegone and piperitenone oxide, making these oils extremely rich in oxygenated monoterpenes (64.99–85.31%)  .Clinopodium species were mainly located in the negative region of PC1 and PC2, while Micromeria longipedunculata (Ml) was positioned among the Clinopodium species.PCA analysis  was perfClinopodium frivaldszkyanum  and C. thymifolium   had an unusual position among the Clinopodium species, positioned near M. kerneri and M. juliana in the negative region of PC1 and the positive region of PC2. The specific compounds for this phytochemical group were verbenone, caryophyllene oxide, and docosane, which were highest in three populations of M. juliana   . Only C.j8, Mj5) .Micromeria croatica  and the contested taxon M. pseudocroatica   .Mantel < 0.001). According to the same test, 17.8% (R = 0.178) of the phytochemical distance between populations could be explained by genetic distance  to the genus Clinopodium by Bräuchler et al. [Micromeria and Clinopodium groups, it is questionable whether it is substantial enough to label these groups as separate genera. STRUCTURE analysis indicated the presence of three genetic clusters: two within Micromeria and a third of Clinopodium species. If Clinopodium is treated as a separate genus, then the other two Micromeria groups should also be considered as such. Since the previous Clinopodium–Micromeria segregation was based on a small sample size and analysis of a single cpDNA region [Several phylogenetic conclusions can be drawn from the genetic diversity and STRUCTURE results. The NJ analysis separated r et al. . AlthougA region , the resClinopodium dalmaticum in the Montenegrin and Bulgarian populations. Regarding the EO composition, PCA also separated Montenegrin from Bulgarian populations of C. dalmaticum . Chater and Guinea [M. dalmatica : M. dalmatica ssp. dalmatica and M. dalmatica ssp. bulgarica (Velen.) Guinea. On the other hand, Bräuchler et al. [M. bulgarica is a synonym of C. dalmaticum. Since C. dalmaticum showed both molecular and phytochemical separation among its populations, research on this species should be continued. The Bulgarian population of C. dalmaticum was closer to C. frivaldszkyanum than to the Montenegrin populations of C. dalmaticum  and a single population of M. croatica (McrP2) from the southern Adriatic mainland. Populations characterised by moderately high levels of DW markers were more common than populations with highest values. They were also scattered over a large area, ranging from the eastern Adriatic coastal region to the eastern Balkans.In studies of individual species or groups of closely related species in the Balkan Peninsula, the question of the presence of (micro)refugial areas that protected local populations during unfavourable climatic conditions of glaciation cycles cannot be avoided. In the AFLP analyses, DW markers  are consSimilar to the STRUCTURE results, no spatial structuring was observed of populations characterised by high frequencies of DW markers, suggesting that no single refugial area can be identified within the Balkan Peninsula. Instead, there appear to have been numerous microrefugia scattered over large areas. The northern Adriatic coastal area does not harbour any of this microrefugia, as low levels of these markers characterised these populations.Micromeria species into several genetic groups and raised questions about the systematic position of certain taxa. Populations of M. cristata were separated into two statistically significant different subgroups  and M. cristata ssp. kosaninii (McK), while the second subgroup was formed by three eastern populations of M. cristata ssp. cristata . On the other hand, the PCA analysis based on phytochemical compounds separated M. cristata ssp. kosaninii from populations of M. cristata ssp. cristata , known in the Balkan literature [M. pseudocroatica (McrP), were separated from the remaining ten populations of M. croatica (Mcr1–Mcr10) with high bootstrap support. The PCA analysis of phytochemical traits also split M. croatica (Mcr) from the disputable taxon M. pseudocroatica (McrP)  . Additiotica McrP, McrP2, Micromeria microphylla (Mm) was divided into two clusters associated with four populations of M. kerneri, although the differences between the species were not statistically significant (M. microphylla (Mm) is quite different from populations of M. kerneri (M. kerneri (Mk3), which is divided into two clusters closely related to M. juliana , but the recognition of a few additional taxa is now possible, thus opening the possibility for systematic repositioning within the studied groups. Within the C. dalmaticum group, two well-supported taxa were identified, one formerly known as M. dalmatica and the second as M. bulgarica. Within the Micromeria group, a similar result was observed in three cases. Micromeria graeca ssp. fruticulosa, formerly known as M. fruticulosa, emerged as a well-supported taxon and not as a representative of M. graeca. Similarly, two populations of M. croatica, formerly recognised as M. pseudocroatica, were differentiated from any other taxon, thus confirming their status as a separate species. Within the M. cristata group, two taxa have emerged: one comprising populations Mc3, Mc5, and McK, and another comprising Mc1, Mc2, and Mc4. Micromeria cristata ssp. kosaninii (McK), formerly recognised as M. kosaninii, seems to lack the support needed for its recognition as either a species or subspecies. However, bearing in mind that Bräuchler et al. [M. cristata ssp. kosaninii, future research should also examine its taxonomic position and whether certain western populations of M. cristata ssp. cristata belong to a new combination, M. cristata ssp. kosaninii.Another set of results enabled a more straightforward conclusion. Not only were the majority of analysed taxa well-supported   was the most abundant in the sample collected in Serbia [M. cristata, namely M. cristata ssp. cristata, M. cristata ssp. phyrigia P. H. Davis, and M. cristata ssp. orientalis P. H. Davis. In all three subspecies, the main constituents of EO were borneol and camphor [M. cristata ssp. kosaninii  . Kostadin Serbia . The extn Serbia , who stu camphor . Thus, tosaninii  were notMicromeria croatica  -en-4-ol (22.91%)  . A previcompound . In this(22.91%) . The pec(22.91%) .Clinopodium dalmaticum is endemic to the Balkan Peninsula, and is widespread in Bulgaria, Montenegro, and Greece, including Crete [E-caryophyllene, α-pinene, and thymol   . Accordip < 0.001). The literature on this topic is diverse. According to Slavkovska et al. [Micromeria species distinguished section Pseudomelissa from Eumicromeria. The EO of species from the section Pseudomelissa was dominated by oxygenated monoterpenes of the menthane type, while various terpene compounds were dominant in species from the section Eumicromeria [M. kerneri and M. juliana separated the populations of these two species [p = 0.004) and individual level  in Sorbus taxa (family Rosaceae). Xavier et al. [Aniba Aubl. species in the Amazon region in Pará State (Brazil). Additionally, AFLP profiles of 11 Hypericum species and cultivars were correlated with their levels of phytochemical markers  determined in their methanolic extracts enabling true-to-type identification and marker-assisted breeding programmes [Thymus L. species native to Hungary found only partial similarities between dendrograms generated by hierarchical cluster analysis based on DNA patterns and EO samples [Ophrys L. taxa (Orchidaceae), Stökl et al. [Thymus caespititius Brot. from the Azores and molecular data sets. Volatile and molecular analysis of Juniperus brevifolia (Seub.) Antoine from the same archipelago also showed no correlation between chemical and molecular data sets [Lutea elbursensis Mozaff from northern Iran, concluding that the chemical composition of EO cannot be used as a reliable taxonomic tool.The Mantel test showed a significant correlation between the phytochemical and AFLP data , while a nanophotometer P330  was used to measure DNA concentrations and quality. The AFLP technique [EcoRI-ACG + Tru1I-CGA, NED-EcoRI-AGA + Tru1I-CGA, FAM-EcoRI-ACA + Tru1I-CGA, and PET-EcoRI-ACC + Tru1I-CGA.Genomic DNA was isolated using a commercial DNA isolation kit , the number of private markers (prN), and the frequency down-weighted marker values (DW) [I = −Σ (ip log2 ip), where ip is the phenotypic frequency [EH) was calculated using a Bayesian approach [ISF = 0) as implemented in AFLP-Surv v. 1.085  [To construct a binary matrix, the obtained AFLP fragments were scored as present (1) or absent (0). Diversity within populations was assessed by calculating the proportion of polymorphic markers (%ues (DW)  using thues (DW) . The Sharequency ,72. In aapproach , assuminBelgium) . The oveUsing the pairwise distance matrix based on the Dice coefficient , a neighAnalysis of molecular variance (AMOVA)  was usedPopulation structure was assessed using two Bayesian clustering approaches implemented in STRUCTURE v2.3.4   and BAPSMicromeria and Clinopodium sample obtained by hydro-distillation were collected for each sample in a pentane/diethyl ether mixture and analysed by gas chromatography and mass spectrometry (GC-MS). GC was performed using a gas chromatograph  and a mass spectrometer . The MS conditions were ion source temperature 200 °C, ionisation voltage 70 eV; mass scan range: 40–350 mass units. The carrier gas was helium. Two columns were used: nonpolar VF-5 ms and polar capillary columns CP Wax 52. The conditions for the VF-5 ms column were temperature 60 °C isothermal for 3 min, then increased to 246 °C at a rate of 3 °C min−1, and held isothermal for 25 min. The CP Wax 52 column conditions were: temperature 70 °C isothermal for 5 min, then increased to 240 °C at a rate of 3 °C-min−1, and held isothermal for 25 min. The injection volume was 2 μL and the split ratio was 1:20. The triplicate analyses of individual peaks were identified by comparing the retention indices of the n-alkanes with literature data and authentic standards [The EO of each tandards ,88.Principal component analysis (PCA) was based on 21 significant constituents of the EO. PCA was performed using the PRINCOMP procedure in SAS v9.3  , and theThe Mantel test  was usedMicromeria and six closely related Clinopodium taxa distributed in the Balkan Peninsula into three genetic groups. The first cluster included all Clinopodium taxa, while Micromeria species were divided into two clusters. In general, their geographic distributions did not support the genetic grouping of the studied taxa and populations. Numerous populations of genetically well-supported taxa were also found scattered over large areas with no evidence of spatial groupings. Such a result suggests that substantial gene flow barriers exist between closely related taxa, precluding any possibility for inter-species hybridisation and consequent fusion of these taxa into spatially structured clusters. An exception is the M. Juliana–M. kerneri–M. microphylla complex, where these barriers are weakest. Generally, groups of taxa were much less supported than individual taxa, indicating their concurrent dispersal and approximately the same time of origin.STRUCTURE analysis based on AFLP genetic data grouped the studied ten C. dalmaticum group, two well-supported taxa were identified, one formerly known as M. dalmatica and the second as M. bulgarica. The species M. graeca ssp. fruticulosa (formerly M. fruticulosa) emerged as a well-supported taxon and not a representative of M. graeca. Two populations of M. croatica, formerly recognised as M. pseudocroatica, were also clearly differentiated from any other taxon. Within the M. cristata group, the taxon M. cristata ssp. kosaninii (formerly M. kosaninii) lacks the needed support for its recognition as either a species or subspecies. Although further studies are needed on some species within the genera Clinopodium and Micromeria, the AFLP data obtained in this research provide a good starting point for future studies. Such a study should include nuclear and plastid DNA sequences on a larger sample of populations and individuals. Finally, the Mantel test showed a significant correlation between phytochemical and AFLP data.The results also showed that the current taxonomic position of certain species requires stronger resolution. Within the