Anopheles coluzzii is a major malaria vector throughout its distribution in west-central Africa. Here we present a whole-genome study of 142 specimens from nine countries in continental Africa and three islands in the Gulf of Guinea. This sample set covers a large part of this species’ geographic range. Our population genomic analyses included a description of the structure of mainland populations, island populations, and connectivity between them. Three genetic clusters are identified among mainland populations and genetic distances (FST) fits an isolation-by-distance model. Genomic analyses are applied to estimate the demographic history and ancestry for each island. Taken together with the unique biogeography and history of human occupation for each island, they present a coherent explanation underlying levels of genetic isolation between mainland and island populations. We discuss the relationship of our findings to the suitability of São Tomé and Príncipe islands as candidate sites for potential field trials of genetic-based malaria control strategies. Campos, Lanzaro and colleagues use whole-genome sequencing and population genomic analyses to infer connectivity between mainland and island mosquito populations in West Africa. The unique biogeographic history for each island population is reported, and the findings highlight potential candidate sites for genetic-based malaria control strategies. Island remoteness is an obvious barrier for migration and one of the key factors in the theory of island biogeography, which relates island size and distance from the mainland to species richness2. Migration between related populations allows the exchange of heritable information and enhances genetic diversity, which is generally lower in island populations compared to mainland ones3.From Darwin’s early work to the present, oceanic islands have served as model systems for the development of evolutionary theory. Attributes such as small size, distinct boundaries, and simplified biotas, together with relative youth and geographical isolation, have made islands a focus for the study of biological diversity6. Malaria is a life-threatening parasitic disease, that in 2018 resulted in an estimated 405,000 deaths, of which 94% occurred in Africa7. Anopheline mosquitoes are responsible for transmitting malaria parasites to humans. In Africa, Anopheles gambiae s.s (hereafter A. gambiae) and A. coluzzii are among the principal vector species10. Malaria elimination strategies and interventions greatly rely on vector control methods11. However, modelling studies have shown that conventional vector control is insufficient for endemic malaria elimination13, which reinforces the conclusion that new methods, which may include GEM, are urgently needed17.From an applied perspective, geographically isolated sites are being considered for initial field trials of new genetic technologies applied to mosquito populations with the goal of malaria elimination. Isolation of a field site from non-target sites is generally considered a pivotal criterion in genetically engineered mosquitoes (GEM) field site selection. Emigration of GEMs out of the field trial site into neighboring, non-target sites on the mainland pose a problem especially as it relates to risk and regulatory concerns. Equally important is immigration of wild type individuals from neighboring sites into the trial site. Immigration in this case will confound efforts to measure GEM invasiveness and could potentially render the gene drive inefficient or even ineffective18. This archipelago consists of two small oceanic islands in the Gulf of Guinea (West Africa), about 250 and 225 km, respectively, off the coast of Gabon. Anopheles coluzzii is thought to be the only malaria vector present on these islands20. Previous studies have shown genetic isolation between A. coluzzii populations from São Tomé and Príncipe islands, as well as between the island and mainland22 reinforcing the choice of STP as a suitable location for initial release of GEM. STP has recently reached the pre-elimination malaria level as defined by the World Health Organization11, due to the success of a combination of interventions, including indoor residual spraying, insecticide-treated nets, and artemisinin-based combination therapy25. Sustainability of these malaria vector control methods are challenged by limited financial support and decreased mosquito susceptibility to insecticides25.A thorough study of islands off the coast of Africa with the aim of identifying candidate sites for initial field trials of GEM has identified the country of São Tomé and Príncipe (STP) as a strong candidateA. coluzzii populations by applying analyses of 142 individual mosquito genomes. Using these data, we test the prediction that island populations are less genetically diverse than their mainland counterparts3, conduct an analysis of historical demography and assess ancestral patterns using cross-coalescence. We present genome resequencing data from three island populations: São Tomé, Príncipe and Bioko  and continental populations from nine African countries . This sampling scheme covers the majority of A. coluzzii’s geographic distribution26. This is the first study using whole-genome sequencing to assess connectivity of conspecific populations on islands in the Gulf of Guinea with populations on the mainland and to explore the consequences of geography and geology on the genetics of these island populations. In addition, we consider our results as they relate to current and future vector control methods on the islands.Here we extend earlier studies describing genetic isolation between island and mainland A. gambiae 1000 Genomes project phase 2  dataset included 78 sequenced genomes. In total 2.4 billion reads were sequenced with a mean genome coverage of 12.6x per sample , and southern. The same clustering pattern was derived using biallelic SNPs on the mitochondrial genome of these samples . Tajima’s D statistic for A. coluzzii sequence from STP was D > 0, indicating a scarcity of rare alleles consistent with a population bottleneck which most likely occurred during the initial introduction of this species into the islands (founder event) and continued maintenance of small population size relative to populations on the mainland  and lower FIS (p < 0.001). The results for STP populations are consistent with the hypothesis of reduced genetic diversity in remote oceanic island populations due to inbreeding and smaller population sizes.Mean nucleotide diversity (π) was measured over the euchromatic regions of chromosome 3. Specimens from STP populations carried significantly less nucleotide diversity compared with mainland populations  analysis applied to our genome sequence data. The MSMC model uses large numbers  of SNPs, each with its own coalescent i.e., time since the most recent common ancestor between the two alleles carried by an individual. The method reconstructs a demographic history from patterns in local density of heterozygous sites across the genome. As with other coalescence-based methods, MSMC can only infer scaled times using assumptions about numbers of generations/year (in our case we assume this is ten) and population sizes. These limitations are implicit where we refer to “years ago” and “effective population size (Ne)”. Prior to about 900,000 years ago the effective population size of a putative ancestral population was relatively large (Ne~107) and stable , which likely occurred during the process of colonizing the islands. Approximately 25,000 years ago, the STP populations reached their nadir, followed by steady increase, however, their Ne remained lower than any other population in this study.A reconstruction of the demographic history of ble Fig. . From thShared population history was estimated using cross-coalescence. A higher relative cross-coalescence (RCC) indicates less time to the last common ancestor shared by the two populations in a specific pair-wise comparison Fig. . Heurist29. Mosquito dispersal can be measured by conventional mark–release-recapture experiments for short range movement31, directly by air-borne insect sampling for long distances29 or through estimation of gene flow between populations applied at various scales. Here we describe important aspects of A. coluzzii dispersal and historical phylogeography using a population genomics approach. This is the first whole-genome resequencing study covering a large part of this species’ range focusing on island as well as mainland populations.Dispersal of malaria vector species has been extensively explored because it directly affects disease transmission, the spread of insecticide resistance and the development of control strategiesAnopheles coluzzii samples from mainland populations were consistently divided into three geographically related population groups: (i) Benin, Burkina Faso, Cotê d’Ivoire, Ghana, Guinea, and Mali forming a western group, (ii) Cameroon and Gabon forming a central group and (iii) Angola representing a southern group , whereas A. gambiae populations experience local extinctions followed by reestablishment via long-distance migration45. These observations suggest that A. gambiae has a greater capacity for dispersal compared with its sister species A. coluzzii.nce Fig. , corroboA. gambiae46 the geographical origin of A. coluzzii was from a west African ancestral population represented by populations in Mali (largest in size), Burkina Faso, Benin, Cotê d’Ivoire, and Ghana ; and admixture analysis (K = 5) assigned each island to a distinct genetic cluster  insertion site polymorphisms22. Collectively these works revealed genetic isolation between populations in STP and Gabon and little isolation between populations on Bioko and the mainland.The results we report here are consistent with and extend earlier work on the genetic structure of mainland and island populations of A. coluzzii populations from those on the African mainland and suggests that these populations were diverged about ~25,000 years ago (RCC = 0). Analysis of populations on Bioko indicate recent , whereas the population size trajectory on Bioko is similar to the mainland  collected from field sites using standard methods  and archived at the VGL, UC Davis, and at the Instituto de Higiene e Medicina Tropical (IHMT), Universidade Nova de Lisboa, Portugal , four Gulf of Guinea coastal mainland sites  and one inland site . Species diagnostics was performed using species-specific markers included in the divergence island SNPs (DIS) assay as described in Lee et al.57. In addition to these 78 samples, we included genome sequence data from 64 individuals taken from the publicly available Ag1000 database (The Anopheles gambiae 1000 Genomes Consortium—phase227). These included samples of A. coluzzii from five countries: Angola, Burkina Faso, Cotê d’Ivoire, Ghana, and Guinea. Analysis was performed with 15 samples from each country except for N = 4 from Guinea  at UC Davis. These samples included adult and larval stage 58. DNA yield was measured using a dsDNA high sensitivity assay kit on a Qubit instrument . The KAPA HyperPlus Kit  was used for individual genomic DNA libraries using 10 ng DNA as input, as described in Yamasaki, et al.59. Size selection of the libraries and clean-up was performed using AMPure SPRI beads . Individual library concentrations were measured using Qubit and then pooled in equal amounts for sequencing using an Illumina HiSeq 4000 instrument at the UC Davis DNA Technologies Core facility. Methods used for genome sequencing of individuals from the Ag1000 samples are described elsewhere .Individual mosquito DNA from the VGL samples was extracted using a Qiagen Biosprint following our established protocol60, the VGL sample reads were mapped to the reference AgamP462 using BWA-MEM v0.7.1563 with default settings. Duplicate reads were removed using Sambamba markdup64. Freebayes v1.2.065 was used for variant calling, with standard filters and the “-no-population-priors”, “theta = 0.01”, and “max-comple-gap = 0” options. Variants were normalized with vt normalize v0.566 and those without support from both overlapping forward and reverse reads were removed using vcffilter v1.0.0rc2 (https://github.com/vcflib/vcflib). Only biallelic SNPs with minimum depth of 8 and maximum of 5% of missing data were used for further analysis.After filtering and trimming demultiplexed raw reads using Trimmomatic v0.3667. A neighbor-joining tree was constructed with Nei’s distance matrix and 1000 bootstrap replicates using the R package ape 5.468.Mitogenome variant calling were generated assuming single ploidy using Freebayes v1.2.0. Singletons and SNPs in an AT-rich region were removed from further analysis due to low coverage69 followed by restrictive filtering. We removed any SNP that did not pass the accessibility filter of the Ag1000G dataset, any SNPs with >10% missingness, and SNPs with minor allele frequency (MAF) < 1%. Also, population structure analysis was based on chromosome 3 SNPs only. This was done to avoid confounding signals from polymorphic inversions on chromosomes 2 and X62. Heterochromatic regions on chromosome 3 R  and 3 L  were also filtered out62.The VGL dataset was merged with biallelic SNP data from Ag1000G using BCFtools v1.970. Hudson’s estimator72 was used for pairwise fixation indices FST calculation implemented in scikit-allel v1.2.0. Isolation-by-distance was tested using the regression of FST/(1−FST) estimates against the logarithm of geographical distance73 in R. Population structure was also explored by assignment of individual genomes to ancestry components using ADMIXTURE v1.3.074. A total of three independent replicate samples of 100,000 SNPs (<10% of the full dataset) from chromosome 3 were submitted for admixture analysis. For each replicate, ten iterations were performed for values of K clusters from 1 to 10, resulting in 30 estimates per K. The results were compiled using the online version of CLUMPAK and plotted in R. Best-fitting K was determined by the lowest cross-validation error values.Principal component analysis (PCA) was performed after pruning for LD using scikit-allel v1.2.075. VCFtools was also used for the calculation of inbreeding statistics (FIS) using the method-of-moments approach. Runs of homozygosity (ROH) within each individual were inferred outside inversions and heterochromatic regions and LD-pruned SNPs on chromosome 3 set using PLINK v1.976, requiring 10 homozygous SNPs spanning a distance of 100 kb and default parameters. The results were grouped by population and significance tests performed between the islands of São Tomé and Príncipe (STP) and the remaining populations under study or Bioko and mainland categories using a Wilcoxon rank-sum test in R.Nucleotide diversity (π) and Tajima’s D were calculated in nonoverlapping windows of 20 kb on euchromatic regions of chromosome 3 using VCFtools77 following the author’s protocol (https://github.com/stschiff/msmc2). For this analysis, SNPs on chromosome 3 R and 3 L were phased with SHAPEIT2 v2.978 using an A. gambiae recombination map39. Heterochromatic regions on chromosome 3 R and 3 L were removed after phasing. Four samples per population were randomly selected and used for population size and two per population or genetic cluster for cross-coalescence inter-population with 20 Baum–Welch iterations each. The results were plotted in R, converting the results to real time in years and assuming 10 generations per year and mutation rate of 2.85 × 10−9 .Population size estimation and cross-coalescence analyses were performed using the multiple sequentially Markovian coalescent (MSMC) pipeline MSMC2 v2.0.2A. coluzzii from 12 populations from Africa were used for this study. Statistical analyses were performed in R and corresponding p values are reported in the text and/or figures.One hundred and forty-two specimens of Further information on research design is available in the Supplementary InformationReporting Summary


The production of domestic geese in Egypt depends mainly on small-sized flocks reared by smallholder farmers in villages, and until now, there have been no intensive or commercial goose farms in Egypt. The objective of this study was to characterize three domestic Egyptian goose populations  phenotypically and genetically in order to identify the populations with the highest diversity to establish a large base population with a broad variation. Phenotypic characterization of 402 domestic mature geese included morphological measurements such as head length, culmen length, bill width, tarsus length, sternum length and chest circumference. Genetic characterization of 173 individuals was performed based on mutations in the mitochondrial D-loop region and the genotyping of 12 microsatellite markers. The results showed low population differentiation based on morphological measurements and low genetic differentiation based on the two used genetic markers. The low differentiation between the three investigated goose populations implies their suitability for aggregation and formation of a large founder population with high genetic variation. The information from this study could be useful for further investigation in order to develop a convenient conservation program for this important species.AN) and effective (EN) number of alleles and observed (OH) and expected heterozygosity (EH) , and a high inbreeding coefficient (ISF = 0.203) across the three Egyptian goose populations. The high inbreeding and low genetic and morphological differentiation of Egyptian geese could be corrected by establishing a large base population through capturing small populations with the highest genetic variation. The findings of the current study can therefore serve as an initial guide to design further investigations for developing conservation programs of Egyptian geese genetic resources.The objectives of this study were to achieve phenotypic characterization of three domestic Egyptian goose populations collected from three different geographical zones  and to perform genetic characterization of these three populations based on mtDNA D-loop and 12 microsatellite markers. The body measurements of 402 domestic mature geese belonging to these three governorates showed that the lengths of the head, culmen and tarsus and the live body weight varied significantly among the three studied Egyptian goose populations. After alignment of a 710-base-pair segment of the goose mtDNA control region, there was a single haplotype in the three Egyptian goose populations, indicating the same maternal origins. The genotyping of the 12 microsatellite markers showed low diversity indices, including average observed ( Anser anser), a progenitor of many domestic breeds, including the current native geese in Egypt; and (2) the swan goose (Anser cygnoides), an ancestor of the Chinese and African goose breeds [Globally, domesticated geese were derived from two wild species: 1) the greylag goose  [Alopochen genus [Anser anser) [The drawings of geese on the walls of ancient Egyptian temples showed the two types of domesticated geese in Egypt . The firyptiaca) ,9,10, a en genus . The secr anser) . It is kr anser) ,8,10,11.Considering the established goose breeding and production practices in ancient Egypt, some authors ,5 singleThe domestic Egyptian geese are characterized by barred grey and white feathers, with the legs, feet and beaks ranging from orange to pink colors . Geese iHigh genetic variation is a very important factor for establishing a successful base population as the response due to selection depends mainly on additive genetic variation. One method for maximizing the genetic variation in the base population is to aggregate and capture small-sized populations with the highest genetic diversity from different breeders into a large founder breeding population ,16,17. PThere are several methods used to characterize poultry diversity, ranging from assessment and linear measurement of morphological traits ,19,20,21Anser anser) populations collected from three different geographical zones and also to perform genetic characterization of these three populations based on the mtDNA D-loop and 12 microsatellite markers. This information will help in optimizing the contribution of each population while creating a large base population of Egyptian geese.Therefore, the objectives of this study were to perform phenotypic characterization of three domestic Egyptian goose .This study was carried out in three geographical zones: the Upper, Middle and Delta Egypt regions, as shown in Upper Egypt was represented by 12 villages located in the Luxor governorate, Middle Egypt was represented by 13 villages located in the Fayoum governorate and Delta Egypt was represented by 13 villages located in the Kafr El-Sheikh governorate, as shown in The body weight and body measurements of 402 domestic mature geese with an equal sex ratio were estimated according to the procedures of . Body meAnser cygnoides) in the zoos located in the Kafr El-Sheikh and Giza governorates were collected. Collected photos for the three studied Egyptian and Chinese goose populations are shown in Blood samples were taken from 173 individuals selected randomly out of the above 402 domestic geese belonging to the three governorates . In addition, 31 samples from Chinese geese (Anser cygnoides) was sequenced for comparison. PCR was performed in a total volume of 15 µL, containing 20 ng of mtDNA, 2× PCR buffer, 400 μM of each dNTP, 0.3 μM of each primer and LA-Taq polymerase at 0.5 U . PCR amplification was performed for 35 cycles after initial incubation at 95 °C for 5 min. Each PCR cycle consisted of 95 °C for 45 s, an annealing temperature of 56 °C for 45 s, 72 °C for 60 s, followed by a final extension of 72 °C for 10 min. A PCR purification kit  was used for purification of the amplified products; then, the purified products were sequenced using the same primers with the Big Dye Terminator ver. 3.1 Cycle sequencing kit  and electrophoresed on an ABI PRISM 3130xl DNA sequencer . BLAST software [PCR was performed to amplify a 710-base-pair segment of the goose mitochondrial control region (D-loop) by using the primer pair F: 5′-CCTCTGGTTCCTCGGTCA-3′ and R: 5′-CAACTTCAGTGCCATGCTTT-3′ . Two samsoftware  was usedsoftware  was usedZAAS006, ZAAS013, ZAAS018, ZAAS035, ZAAS038, ZAAS015, ZAAS060, ZAAS064, ZAAS152, ZAAS041, ZAAS175 [ANS025 [Twelve microsatellite markers, namely,  ZAAS175  and ANS0 [ANS025 , with mip < 0.05) and partial R2 values of ≥0.01 were used to evaluate the relative importance of the morphometric variables in discriminating the three populations of geese.The statistical difference between the three studied goose populations was assessed using a one-way analysis of variance (ANOVA), with the population of geese included in the model as the source of variation using the PROC GLM procedure in the SAS v9.1.3 statistical package . We conducted a principal component analysis (PCA) using R software version 3.6 . A stepwise discriminant analysis was conducted using PROC STEPDISC to investigate which morphological traits have more discriminant power than others. The level of significance (AN) and effective (EN) number of alleles, the observed (OH) and expected (EH) heterozygosity and the Hardy–Weinberg equilibrium using GENALEX version 6.0 [PIC) was estimated using CERVUS version 3 [STF), fixation coefficient of an individual within a subpopulation (ISF) and fixation coefficient of an individual within the total population (ITF)) per locus and deviation from the Hardy–Weinberg equilibrium (HWE) were estimated by the GENEPOP version 3.4 program [http://bioinformatics-org/~tryphon/populations/ /accessed on 26 June 2021) was used to construct the microsatellite phylogenetic tree of the three studied populations based on the Reynolds and Nei genetic distance (AD) by using the neighbor-joining (NJ) method [Genetic diversity parameters were evaluated by calculating the observed (sion 6.0 . Polymorersion 3 . F-stati program . The POP) method .K, we conducted 50 runs with 50,000 iterations following a burn-in period of 20,000. CLUMPP software [K and outputted a mean of the permuted matrices across replicates after aligning the cluster membership coefficients of these replicates. Finally, the clustering pattern with the best ∆K value was graphically displayed for the selected K value using DISTRUCT software [The clustering pattern and the genetic structure of the studied populations were investigated using STRUCTURE software . For eacsoftware  was usedsoftware .p < 0.05 to p < 0.001). However, chest circumference chronologically followed by body weight, sternum length and head length had more discriminant power than the others, as revealed by their higher R2 and F-values.The mean values of live body weight and other body measurements in the three evaluated Egyptian goose populations are presented in The principal component analysis (PCA) of the body measurements showed that the first principal component (Dim1) accounts for 99.9% of the variation, while the second one (Dim2) accounts for 0.0% of the variation, as shown in Anser anser sequence retrieved from GenBank (accession number EU583734.1), and the Chinese sample was clustered with the Anser cygnoides sequence retrieved from GenBank (accession number KU211647.1), as shown in We obtained a sequence of 710 bp for two samples of each of the three Egyptian populations in addition to one sample of Chinese geese acting as an outgroup population. After alignment, there were no substitution sites among the three Egyptian goose populations, indicating a single haplotype and the same maternal origins. In the NJ phylogenetic tree, these three populations clustered into the same clade with the AN) ranged between 2  and 7 (ZAAS006 and ZAAS018), with an average of 3.333 alleles. The locus ZAAS035 showed a monomorphic pattern across the three Egyptian and Chinese goose populations and was excluded. The effective number of alleles (EN) ranged from 1.024 (ZAAS175) to 2.748 (ZAAS038), with an average of 1.760 alleles.The genetic diversity of the 11 microsatellite loci across the three Egyptian goose populations is shown in OH, EH) were 0.277 and 0.352, respectively. The ZAAS152, ZAAS041 and ZAAS175 loci showed very low observed  and expected  heterozygosity (ISF) and the mean fixation coefficient of a subpopulation within the total population (STF) were 0.203 and 0.045, respectively, across the eleven studied loci.The averages of the observed and expected heterozygosity , the mean PIC value was 0.307. Significant deviations from the Hardy–Weinberg equilibrium (HWE) in allele frequencies were recorded for all markers except the ZAAS015, ZAAS060 and ANS025 loci  to 0.277 (Fayoum), with a mean of 0.213.The lowest value of expected heterozygosity (0.308) was obtained for the Kafr El-Sheikh population, and the highest value (0.343) was recorded for the Fayoum population. The overall expected heterozygosity of the three Egyptian populations was 0.325. The AD) value between the four studied goose populations was recorded between Fayoum and Luxor (0.023) and the highest value between the Kafr El-Sheikh and Luxor populations (0.071). Similarly, the genetic differentiation indicated by the pairwise STF values was the lowest between Fayoum and Luxor (0.022) and the highest between Kafr El-Sheikh and Luxor (0.044), as shown in K = 2, where the four studied goose populations showed the most probable structure clustering, the Fayoum, Kafr El-Sheikh and Luxor populations were clustered together, while the Chinese population was assigned independently into its respective cluster  could be more important in differentiating between the three Egyptian goose populations than other measurements. The plot of the principal component analysis (PCA) for the body measurements showed large overlaps, indicating that there are small differences in the measured variables between the three populations.Anser anser confirms that all of these samples belong to the same species (Anser anser), and the mtDNA D-loop sequence divergence is more suitable for the analysis of interspecies divergence than intraspecies divergence [The six sequenced individuals were found to be monomorphic in the amplified fragment of the D-loop, providing a single haplotype in the three Egyptian goose populations, thus indicating the same maternal origins. The low sequence divergence among the Egyptian geese from the GenBank sequence of vergence .AN, OH and EH across ten of the studied microsatellite loci  in the three studied populations were comparable with those described by Li et al. [AN, OH and EH of the ANS025 locus of this study were comparable with those described by Mindek et al. [The average values of i et al. , who reck et al. , who reck et al. , who recZAAS175, ZAAS152 and ZAAS041 loci showed low EN values  across the three studied Egyptian populations, they showed moderate values  across the Chinese population, as shown in EN) is an importance diversity index as it gives an indication of the difference in allele frequency in a population. When most alleles have a low frequency and few of them have a high frequency, we expect low values of EN, OH and EH [OH and EH in the current study might be attributed to the fact that most of the alleles of those loci have a low frequency and few of them have a high frequency. The relatively high and positive ISF average in this study (0.203), in addition to the seven loci showing a deficit of heterozygosity, might indicate non-random mating and inbreeding.In the present study, although the O and HE . The lowSTF), it has been suggested that values in the ranges of 0.00–0.05, 0.05–0.15, 0.15–0.25 and above 0.25 indicate little, moderate, high and very high genetic differentiation, respectively [STF value (0.045) indicated little genetic differentiation between the three studied Egyptian populations. The estimated STF value of the current study was lower than that measured between Chinese goose populations, which showed a value of 0.242 [STF value (0.343) recorded after adding the Chinese population indicated that there is high genetic differentiation between this population and the three Egyptian goose populations.For interpretation of the fixation coefficient of a subpopulation within the total population  than those reported by Moniem et al. [EN = 3.166, OH = 0.482, EH = 0.615, PIC = 0.565), the ISF value (0.213) was comparable to that of Moniem et al. [Regarding the within-population genetic diversity, although the three goose populations of this study showed lower genetic diversity parameters , suggesting their potential endangerment [Lower genetic diversity reduces individuals’ fitness and limits their ability to adapt to environmental change, consequently increasing their risk of extinction . Moreovepriority . Therefongerment .AD) and pairwise STF, might be attributed to the high social connection between the Luxor and Fayoum governorates, where human activities, such as marketing, can shape the goose population structure, as the genetic diversity in its domestic distribution is the result factors such as geography, ecology, behavior and molecular aspects, which hierarchically interact through time and space [STF (0.11) between two Egyptian goose populations (black variety and grey variety) based on nine microsatellite loci. The pairwise STF value between Suchovska and Slovak geese was 0.58 [The close relationship between the Fayoum and Luxor populations indicated by the clustering pattern of the neighbor-joining phylogenetic tree and STRUCTURE, in addition to the low values of pairwise genetic distance , Middle (Fayoum) and Delta (Kafr El-Sheikh) Egypt showed a high inbreeding level and low genetic differentiation based on mitochondrial D-loop and microsatellite markers, suggesting their potential endangerment. Moreover, they showed low differentiation based on morphological measurements. The high inbreeding and low genetic and morphological differentiation could be corrected by establishing a large base population through capturing small populations with the highest genetic variation. The


Eriophorum vaginatum L.) is a foundation species of the moist acidic tundra, whose potential decline due to competition from shrubs may affect ecosystem stability in the Arctic. We used double-digest Restriction Site-Associated DNA sequencing to identify genomic variation in 273 individuals of E. vaginatum from 17 sites along a latitudinal gradient in north central Alaska. These sites have been part of 30 + years of ecological research and are inclusive of a region that was part of the Beringian refugium. The data analyses included genomic population structure, demographic models, and genotype by environment association. Genome-wide SNP investigation revealed environmentally associated variation and population structure across the sampled range of E. vaginatum, including a genetic break between populations north and south of treeline. This structure is likely the result of subrefugial isolation, contemporary isolation by resistance, and adaptation. Forty-five candidate loci were identified with genotype-environment association (GEA) analyses, with most identified genes related to abiotic stress. Our results support a hypothesis of limited gene flow based on spatial and environmental factors for E. vaginatum, which in combination with life history traits could limit range expansion of southern ecotypes northward as the tundra warms. This has implications for lower competitive attributes of northern plants of this foundation species likely resulting in changes in ecosystem productivity.Global climate change has resulted in geographic range shifts of flora and fauna at a global scale. Extreme environments, like the Arctic, are seeing some of the most pronounced changes. This region covers 14% of the Earth’s land area, and while many arctic species are widespread, understanding ecotypic variation at the genomic level will be important for elucidating how range shifts will affect ecological processes. Tussock cottongrass ( Investigating the adaptive constraints of plants is critical to better determine how different species and communities may respond to an altered climate  and how Among geological events with lasting effects on populations, glaciation events often serve as a major factor leading to genetic divergence . In factRefugia like the Beringian region had a heterogeneous landscape , and locEriophorum vaginatum L.; Cyperaceae), a sedge that exemplifies arctic plant distribution across tundra and taiga biomes and occurs throughout the Beringian region, to investigate landscape genomic patterns.Landscape-scale genetic constraints for arctic plant species have been proposed, especially for ecotypic specialization and adaptational lag . Local aEriophorum vaginatum is a wind-pollinated and wind-dispersed sedge, and a foundation species of the moist acidic tundra (MAT). It has a circumarctic and circumboreal distribution and is a common component of taiga forest in muskeg and bogs  Is population structure delimited at the ecosystem level among these populations? (2) Is there evidence of genetic structure linked to adaptation for latitude of origin? We hypothesize that the Brooks Range glaciation within the Beringian refugium effectively isolated populations to the north and south and that this resulted in the confinement of E. vaginatum to putative subrefugia as glaciers expanded before the LGM. When separated for a sufficient amount of time, genetic drift and/or divergent selection should have altered the genomes of the isolated E. vaginatum populations, and population structure analyses should demarcate these isolated populations as unique. More recently, treeline may be expected to pose an important barrier to gene flow for contemporary populations of E. vaginatum, as the treeline ecotone represents the current boundary between glacially isolated habitats. Finally, we hypothesize that genetic correlation associated with environmental predictors will be uncovered along the stable arctic latitudinal cline corresponding to local niche dynamics that have resulted in the ecotypic variation identified through 30 + years of reciprocal transplant garden studies.Here we use thousands of double-digest Restriction Site-Associated DNA sequencing (ddRAD-seq) single nucleotide polymorphisms (SNPs) to investigate broad patterns of population structure, gene flow, and associations with landscape variables in The study area consisted of a latitudinal gradient covering ∼426 km in north central Alaska , from noE. vaginatum from 16–18 individuals at each of 17 sites (273 accessions) along the latitudinal gradient following the Dalton Highway  and 5 μL of 10 × NEBuffer 4  in a thermocycler at 37°C for 30 min followed by enzyme deactivation at 65°C for 20 min. Custom barcodes and indices were ligated to digested DNA, with the addition of 50 nM of custom EcoRI and MspI adapters , 2 μL of 10 × NEBuffer , 0.6 μL of rATP , 0.4 μL of ddH2O, and 1 μL of T4 DNA ligase  to each 50 μL sample of digested DNA. Ligation was completed in the thermocycler (22°C for 30 min), followed by enzyme deactivation (65°C for 20 min). Adapter-ligated DNA fragments were then double-side size selected with a 0.8 × SPRI bead clean up. Right-sided selection for large fragments was done with AMPure XP beads  added at 0.55 × volume of the starting ligated DNA solution, and the supernatant transferred to new tubes. Subsequently, a left-sided size selection was done with 0.25 × volume AMPure XP beads added to the supernatant. The supernatant was then discarded and the beads were washed twice with 80% ethanol and air-dried. DNA was re-suspended with 25 μL ddH2O and eluted for a minimum of 30 min.To assemble ddRAD libraries, 43 μL of each ∼25 ng/μL DNA sample was digested with 20 U of 2O and 3 μL of each 10 μM primer specific to sequences at the ends of each custom barcode and index  and Qubit 3.0 Fluorometer . Additionally, samples were visualized with gel electrophoresis to ensure that all were similarly size-selected. Equimolar concentrations of samples with unique barcode combinations were pooled. Multiplexed libraries were sequenced at the Center for Genome Research and Biocomputing at Oregon State University on an Illumina HiSeq 3000.To amplify size-selected DNA fragments, PCR was performed with a solution of 15 μL template DNA, 30 μL of Phusion High-Fidelity PCR Master Mix , 9 μL of ddHndex see . PCR wasde novo assembly method in STACKS 2.41 . In addition, prior odds settings were increased to 500 for the comprehensive dataset, as recommended for candidate loci identification in large datasets  of 5%]. Additionally, SNPs deviating from Hardy-Weinberg Equilibrium  were identified with PLINK1 v.1.07  and expected (He)], allelic richness (Ar) and the inbreeding coefficient (FIS) were estimated across all loci and for each population with the divBasic function in the diveRsity R package v.1.9.90 (PopGenReport package v.3.0.4 (Ne) was estimated with NeEstimator v.2.1 . The analysis was comprised of 20,000 burn-in iterations followed by 50,000 replicates of each population value (K = 1–10), and each run was conducted 10 times  via k-means clustering of principal components and the Bayesian Information Criterion (BIC)  .poppr.amova function with 99 permutations in the poppr R package v.2.8.0   using th v.2.8.0 , 2015. Tv.1.9.90  was usedntervals .E. vaginatum suitable habitats past and present within the range of the Beringian refugium. To build an ENM, the species distribution was modeled for the present and projected into climate scenarios of the mid-Holocene (∼6 kyr BP), and the LGM (∼20 kyr BP). The initial ENM was built with 19 bioclimatic variables obtained from the WorldClim 2.0 Bioclimatic database  was used to create environmental suitability maps, to test various demographic models, and predict the geographical distribution of database  and deridatabase . MaxEnt Database , adding r ≥ 0.75 and r ≤ −0.75) was applied to remove variables for the final MaxEnt run  ABoVE: Landsat-derived Annual Dominant Land Cover Across ABoVE Core Domain, 1984–2014 dataset . The 15-E. vaginatum, resistance due to forest land cover in the Arctic landscape is expected to be a primary physical factor limiting gene flow. As the extent to which land cover types affect gene flow is unknown, we tested a series of resistance surfaces for Forest, Woodland, and Shrubland categories, assigning combinations of low resistance (2 or 5), medium resistance , and high resistance (100 or 500). Landscape classes in the Other category were assigned a resistance of 1, or lack of resistance. An ENM model based on habitat suitability using MaxEnt output was used to examine IBE. To create a null model, all cells were assigned a resistance cost value of 1, equivalent to an IBD scenario. Pairwise landscape resistance matrices were calculated between sites for 11 different models.A series of models was designed to examine the effects of isolation by distance (IBD), resistance (IBR), and environment (IBE) on genetic distance and run in CIRCUITSCAPE following FST genetic distances as response variables and pairwise resistance matrices as explanatory variables. MLPE models implement a type of linear regression on distance matrices while accounting for random effects of pairwise data  models to test the IBD, IBE, or IBR models with pairwise ise data . MLPE mo1.1.27.1 . Best su.1.43.17  was usedadespatial v.0.0–7 (spdep v.0.6–9 (p < 0.05) allele frequency variance.As geographic and landscape variables often influence patterns of genomic variation and spatial distribution of plants , genotyp v.0.0–7  and spde v.0.6–9  packagesR2 > 0.7) of predictor variables (see section “Results”), a principal components analysis (PCA) was conducted with the prcomp function of the R stats package v.3.6.0 . Significance of the final models and constrained axes were identified with 999 permutations and a p-value of 0.05 .After removal of low-quality reads and reads without radtags, a total of 546,642,395 single-end sequences were retained for 273 individuals, with an average of 2,002,353 sequencing reads per individual. All samples had a coverage depth > 13×. The comprehensive SNP data set contained 3,879 loci and 10,734 SNPs. Twenty-one outlier loci, each with a single SNP, were identified using BayeScan, and these were removed to create a putatively neutral dataset. The neutral data set was comprised of 2,776 loci, each represented by a single SNP, after filtering out SNPs deviating from HWE (FIS = −0.003 (SE = ± 0.001). Ho  and He  varied little among sites  than below treeline . Eagle Creek had relatively high FST values in all pairwise comparisons . While all pairwise comparisons were significant (p < 0.01) between sites below treeline, this was not true between some sites above treeline  were found between sites north of treeline  and between CC, EL, NN, GO, and CF south of treeline  showed evidence of admixture based on both STRUCTURE and DAPC results  identified suitable habitat throughout the Beringian refugium for aginatum  outside aginatum . IncludiTwo environmental PCAs were run: (1) temperature and (2) precipitation. PC1 and PC2 explained 90.5% of the total variation of the temperature PCA and 96.0% of the precipitation PCA. All predictors strongly influenced both PC1 and PC2, so environmental predictors were not grouped into summarized environmental variables. The retained variables explaining significant allelic variation for the RDA analysis were: (1) isothermality , (2) mean temperature of the driest quarter , (3) mean temperature of the warmest quarter , (4) precipitation of the driest month , (5) precipitation seasonality , (6) MEM1, and (7) MEM2 .p = 0.001), and predictor variables explained 13.2% of the total genetic variance. The RDA1 discriminant axis was significant (p = 0.001), and explained 30.1% of the constrained variation. The RDA2 axis was not significant (p = 0.070). There were 165 candidate SNPs identified and detected on the RDA1 axis and 162 candidate SNPs with high correlations (R2 ≥ 0.7) to predictor variables, which were retained to further investigate local adaptation . The remaining candidate SNPs were correlated with tdq (11 SNPs) and twq (10 SNPs). Gene Ontology annotations were found for 45 candidate loci after a search against the E. vaginatum transcriptome  clusters with north slope populations while south slope treeline adjacent populations ST (south of treeline) and TB (north of treeline) show evidence of an admixture zone only at treeline. While treeline in the Arctic signifies a contemporary ecosystem change, the arctic flora was also shaped in part by patterns of glaciation and distribution of refugia. The Beringian refugium was an important source for post-glaciation vegetation, but in Alaska it was divided by glaciation over the Brooks Range  had the opportunity to adapt to contrasting abiotic and biotic factors reflecting the contemporary ecosystems that now have a transition zone at the treeline ecotone.Post-glaciation, the Brooks Range could have provided an allopatric barrier for ks Range  that hasaciation , with eal cycles , creatin the LGM . Likewis the LGM . Demogra as well . As suchAdaptive variation is supported by GEA analyses that indicate environmental predictors  contribudivMigrate analyses indicate gene flow to the southernmost site above treeline  on the south slope of the Brooks Range coming from SG, which is located just beyond the northern extent of the LGM  had similar migration values from North and South clusters  and it is not uniquely isolated among southern populations. Thus, we alternatively posit that EC may represent a population adapted to alternative niche space as supported by GEA analyses that uncovered association between allelic turnover and precipitation variables (iso and prs) for this population relative to others  relate to spring and summer conditions, which encompass the limited growing season of gradient . The shogradient . Consequaginatum , 2021. Saginatum ; thus, sR2 ≥ 0.7) were identified with GEA methods. MEM1, tdq, and twq, in succession, were the predictors for the 45 loci identified to gene and function (Several potentially adaptive SNPs (162 candidate SNPs and 131 loci with high correlations to predictor variables; function . MEM varfunction , and profunction  includedfunction . These tfunction . These ifunction . The impfunction  and shouE. vaginatum sites along a ∼426 km latitudinal gradient in north central Alaska, which was within the boundary of the Beringian refugium. A major genetic boundary was found at the treeline ecotone. Strong evidence of IBR was found across the study region, highlighting the influence of vegetation type and density on E. vaginatum neutral genetic structure. Importantly, IBR due to forest cover can signify a major obstacle for gene flow of potentially better-adapted genotypes northward with rapid climate change. GEA results support ecotypic adaptations elucidated over decades of ecological studies for this arctic foundation species and suggest potential important environmental variables along with candidate loci, many of which are associated to abiotic stress gene pathways. These results are consequential for increasing predictive accuracy of distribution changes under climate change. An understanding of adaptive variation should be incorporated into developing hybrid environmental niche and species distribution models (In summary, genomic structure and differentiation were identified across 17 n models . The comhttps://www.ncbi.nlm.nih.gov/, BioProject PRJNA803172, accession numbers SAMN25639742–SAMN25640014. The STACKS pipeline Python script, Redundancy Analysis R code, and ENMEVAL R code can be found at https://github.com/estunz/EvLG2022.The datasets presented in this study can be found in online repositories. The names of the repository/repositories and accession numbers can be found below: MM, NF, and JT designed the study. MM, ES, and NF organized and performed field collections. ES and MM wrote the manuscript. ES performed lab research and analyzed the data. JM contributed bioinformatic analytical tools and training and assisted with data analyses. PL provided ddRAD data collection techniques, lab resources, and assistance. All authors reviewed and approved the final manuscript.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.


Coscinasterias tenuispina, an Atlantic-Mediterranean fissiparous starfish, focusing on the western Mediterranean, to investigate: the distribution and prevalence of genetic variants, the relative importance of asexual reproduction, connectivity across the Atlantic-Mediterranean transition, and the potential recent colonisation of the Mediterranean Sea. Individuals from 11 Atlantic-Mediterranean populations of a previous study added to 172 new samples from five new W Mediterranean sites. Individuals were genotyped at 12 microsatellite loci and their gonads histologically analysed for sex determination. Additionally, four populations were genotyped at two-time points. Results demonstrated genetic homogeneity and low clonal richness within the W Mediterranean, due to the dominance of a superclone, but large genetic divergence with adjacent areas. The lack of new genotypes recruitment over time, and the absence of females, confirmed that W Mediterranean populations were exclusively maintained by fission and reinforced the idea of its recent colonization. The existence of different environmental conditions among basins and/or density-depend processes could explain this lack of recruitment from distant areas. The positive correlation between clonal richness and heterozygote excess suggests that most genetic diversity is retained within individuals in the form of heterozygosity in clonal populations, which might increase their resilience. We here analysed the populations’ genetic structure of  Understanding how genetic diversity is distributed across populations, and how it arises and is lost, is relevant to estimate species’ resilience under changing conditions and to determine temporal trends of the populations2.Genetic diversity, needed for populations to adapt to environmental changes, has a profound influence on evolutionary and ecological processes of the species, and is one of the key components of ecosystems biodiversity6 due to the different interplay of biological characteristics  and past and contemporary oceanographic factors , which generates variable patterns of connectivity7.In marine organisms, spatial distribution of genetic diversity, and so populations’ genetic structure, can largely vary across similar spatial and temporal scales8. However, in others, such as some echinoderms, adults and/or larvae can divide into two new free-living individuals, yielding mobile ramets with considerable dispersal capability when the splitting happens at the larval stages10. In the latter heterogonic animal group, the balance between sexual and asexual reproduction within populations influence the prevalence of ramets and different genetic individuals (genets)12. This different proportion of ramets and genets can have a strong impact on the intra-population genetic diversity13, genetic drift, effective population size, and finally, populations’ divergence and evolutionary potential15. Theoretical and empirical approaches have suggested that long-term prevalence of asexual reproduction in diploids tends to drive populations to a deviation from the Hardy–Weinberg equilibrium, shifting the fixation coefficient (FIS) to negative values16, caused by heterozygotic excess due to the accumulation of somatic mutations in absence of recombination17. Additionally, sex-ratio bias in populations dominated by asexual reproduction can also occur if males and females have different energy demands during asexual reproduction18.Marine invertebrates, represented by an abundance of contrasted biological strategies, can have complex reproductive systems that combine sexual and asexual cycles and/or stages. In many benthic invertebrate groups, such as bryozoans, ascidians, or corals, among others, asexual reproduction during adulthood is mostly linked to colonial growing, generating colonies composed of immobile ramets 10. Within the latter class, we find the starfish genus Coscinasterias, with four species described, being all of them fissiparous10. In our study, we focus on Coscinasterias tenuispina , a subtropical species widely distributed across both sides of the Atlantic Ocean and the whole Mediterranean Sea20. Like all representatives of the genus, when C. tenuispina sexually reproduces releases a planktonic larva that can live and disperse in the water column for several weeks22. The most recent genetic analyses, based on both mitochondrial and nuclear markers, demonstrated the existence of two distant evolutionary lineages within C. tenuispina: one lineage distributed along the north Atlantic and Mediterranean Sea (hereafter named as C. tenuispina); and the south-western Atlantic lineage found along the coast of Brazil (hereafter named as C. tenuispina like)13. Population genetic analyses also highlighted the importance of asexual reproduction in C. tenuispina across the Cantabrian Sea and a some sites at the western Mediterranean, where monoclonal populations were found23, and also in C. tenuispina like along the coast of Brazil where a significant sex-ratio bias was observed19. The same studies suggested that the prevalence of asexual propagation is more frequent at the distribution edges of the species23, and likely related to the constrictions imposed by environmental factors. The temperature was also suggested as the most relevant physical factor correlated to asexual reproduction due to its impact during larvae development in tropical and sub-tropical echinoderms24. Additionally, significant genetic divergence in C. tenuispina among the northeast Atlantic, W Mediterranean, and east Mediterranean basins was detected. The same data suggested a relatively recent colonisation of the Mediterranean Sea from the Atlantic Ocean during one of the last interglacial periods of the Pleistocene23, but more data are required to confirm this hypothesis, including the role of the Atlantic-Mediterranean transition in the connectivity patterns between both basins.In echinoderms, asexual reproduction has been reported in three classes: Ophiuroidea, Holothuroidea, and Asterioidea26. Whereas for some species the oceanographic circulation system generates a strong genetic break due to a gene flow interruption28, for others, a smooth genetic transition (e.g.30), or even a null effect, was detected due to moderate levels of connectivity between basins (e.g.32). Additionally, the genetic structure of populations may not be stable over time and can rapidly vary over shorts periods of only a few years (see33); therefore considering temporal variability in genetic structure studies is desirable to better understand the potential plasticity of populations and to obtain more accurate estimates of gene flow.The role of oceanographic currents across the Gibraltar Strait and the Almeria-Oran front, which delimit the Alboran Sea, on genetic patterns has been explored in species with contrasting biological features, and a differential barrier effect among species demonstrated, although still poorly known in facultative asexual invertebratesC. tenuispina have shown unusual biological features in this predator species20. Although asexual reproduction can happen all over the year23, populations can preserve their potential for sexual reproduction, even when they have not sexually reproduced for long-time periods23. Another work performed by Garcia-Cisneros and coauthors34, in which telomere length of individuals from wild populations were measured, demonstrated that the clonality rate, at the population level, was significantly and positively correlated with telomere length average. Telomeres, which protect the extreme of the chromosome from DNA damage, shorten after each cellular cycle of mitosis and are routinely used as molecular markers for assessing aging and fitness36. Hence, higher fitness would be expected when telomeres remain longer during lifetime. The novel finding in C. tenuispina suggested that this starfish has a mechanism for telomere elongation during adulthood, never observed in wild animals before, associated with asexual reproduction, and likely related to overcome some of the negative effects related to prolonged periods of asexual reproduction, such as senescence (e.g.37).In general, studies on C. tenuispina seems to have a large biological and evolutionary plasticity. Based on its reproductive plasticity, and the long dispersal potential of its larva, some authors suggested that C. tenuispina could be an efficient colonizer of new areas9. Nevertheless, on the other hand, some partially clonal species, from different ecosystems, have suffered large demographic fluctuations and important geographic drifts. In this sense, genetics studies can be applied to indirectly identify major drivers and life history traits associated with populations’ fluctuations16 (and references herein). In C. tenuispina, there is still an important gap of knowledge related to the levels of genetic diversity and prevalence of clonality across the W Mediterranean area, the effect of the Atlantic-Mediterranean transition on the genetic divergence between basins, and the potential recent colonisation of the Mediterranean basin34; genetic features that could determine the long-term resilience of Mediterranean populations of C. tenuispina. In order to answer these previous questions, we here explore the populations’ genetic structure of C. tenuispina, over space and time, together with information on sex-ratios, focusing on the W Mediterranean area and the Atlantic-Mediterranean transition. Hence, our specific objectives for this study were:As presented above, C. tenuispina. Information obtained can help to unveil whether current larvae recruitment at some W Mediterranean populations occurs either from adjacent or distant geographical areas, as well as to estimate historical gene flow across the Alboran Sea. We will also determine the distribution limits and prevalence of the different genetic variants found. In Coscinasterias, dispersion mainly relies on larvae generated by sexual reproduction. Adults lack migratory behaviour and displacements during adulthood are limited39. Therefore, our initial hypothesis is that spatial spreading of clonal lineages by fission would be limited to short geographical distances of only a few kilometres and between close populations. (1) to investigate levels of genetic diversity, clonality, and structure of W Mediterranean populations of C. tenuispina fits within the theoretical models and empirical studies performed in other marine asexual species that relate significant HWE disequilibrium and increasingly deviation of FIS towards negative values, due to heterozygote excess, with modest and high clonality rates (see16 and references herein). Our hypothesis is that if those models also apply to C. tenuispina, we should observe a positive relationship between clonal diversity and FIS in the populations here analysed. This point is interesting because some authors consider that the heterozygote excess in clonal populations can be an evolutionary advantage to retain genetic diversity within individuals38, increasing the potential resilience of populations.(2) To explore whether C. tenuispina have an Atlantic origin from a relatively recent colonisation event. Information generated will contribute to better understand the poorly known genetic patterns of clonal marine invertebrates.The novelty of our study is combining both spatial and temporal genetic data, together with sex-ratio information, from distant and close populations, within the W Mediterranean, to measure clonality rates and genetic diversity . Genetic analyses of populations at two different years allow us to empirically measure the recruitment of new genotypes, and compare it with historical connectivity inferred from coalescence analyses. With all information retrieved, we will finally be able to determine whether Mediterranean populations of C. tenuispina for sexual reproduction, we investigated their sex-ratios. Over the 316 individuals of C. tenuispina analysed from five W Mediterranean localities , only 60 individuals from two localities, LLA and PAL, had developed gonads , Hardy Weinberg Equilibrium (HWE), number of multi locus genotypes (MLGs) and multi locus lineages (MLLs), and clonal richness from all eight W Mediterranean locations, including all individuals, are presented in Table p-value < 0.01) with negative FIS values due to an excess of heterozygotes, when all individuals were included , number of alleles, fixation index , and among them, 10 MLGs were located at the Alboran Sea. It is remarkable the different number of MLGs and MLLs in the W Mediterranean . Regarding private MLGs and MLLs, a higher frequency of private MLGs and MLLs was observed at the NE Atlantic, Alboran Sea, and E Mediterranean than in the W Mediterranean, being private genotypes at low frequency in the latter area  and GIJ , compared to NE Atlantic and E Mediterranean populations  and FAll population genetic analyses, based on different methods , showed the W Mediterranean  as the most homogeneous area across the species’ distribution range.FST and Jost’s Dest tests, displayed similar values of significance between both statistics. When all individuals were included, results were significant (p ≤ 0.01) for almost all pairwise comparisons, with the exception of the comparisons between W Mediterranean sites. Within the W Mediterranean, most sites demonstrated low and no significant values of divergence, with the exception of HER (at the Alboran Sea), ESC (at the Alboran Sea limit), and CAI  and ESC lightly different from the other W Mediterranean sites but still included in this cluster; a second cluster including HER from the Alboran Sea, E Mediterranean populations  and Atlantic populations from Canary Islands; and the last cluster including the distant population of GIJ, from the Cantabrian Sea  maintained, with the exception of Sicily that only showed significant genetic differences with HER from the Alboran Sea .AMOVA analyses also showed similar results for both databases, either including all individuals or only unique MLGs. In both analyses, significant differences among localities within geographical areas and among geographical areas  were obtained  lightly distant to other W Mediterranean localities, and HER, within the Alboran Sea, closely related to the Atlantic pool see Fig. . InteresThe Structure results reveal additional insides on the genetic structure across and within marine areas. The number of K was selected based on the ΔK and maximum likelihood results , showed limited historical genetic admixture among the NE Atlantic, the Alboran Sea, and the W Mediterranean see Fig. . In geneST < 0.01 and Dest = 0.00; and p-value > 0.1) or MLG frequencies . We also investigate the relationship between heterozygosity and clonality in this fissiparous starfish species.Our study explores in detail the distribution and frequency of C. tenuispina was characterised by large genetic distances between major oceanographic areas, NE Atlantic, W Mediterranean, and E Mediterranean, and across marine fronts, including the Gibraltar Strait, the Almeria-Oran front, and the Siculo-Tunisian front, as demonstrated by genetic distances, Bayesian clustering, and DAPC analyses. Significant differences were also evident between populations within major areas, in concordance with those observed by Garcia-Cisneros and coauthors13, with the exception of W Mediterranean localities, the main focus of our current study. Our results demonstrate the existence of a dominant clonal lineage (the superclone) widely spread across the W Mediterranean area studied, from Alicante (Spain) to Naples , covering over 2000 km along the coastline. Although this genetic variant was already detected from three sites by Garcia-Cisneros and coathors13, we now demonstrate that the superclone is the most frequent clonal lineage across the Mediterranean coast of the Iberian Peninsula and Naples , being the unique clonal lineage in most localities, but absent in the E Mediterranean, Atlantic Ocean, and Alboran Sea. This clonal dominance generates a pattern of genetic homogeneity within the W Mediterranean area studied that clearly contrasts with those observed from the adjacent areas, the NE Atlantic and E Mediterranean. The strong genetic break between the Alboran Sea  and the rest of the W Mediterranean, and the genetic homogeneity within the latter area, results from a combination of different biological and genetic features. Among the processes involved in this genetic pattern we can identify: (a) a prevalence of asexual reproduction and clonality within the W Mediterranean area studied, and (b) a lack of contemporary connectivity between the W Mediterranean and adjacent marine areas.The general genetic structure of 20, have been found in all species of the genus Coscinasterias42, and populations of C. tenuispina, and C. tenuispina like43. However, clonality, according to the number of shared genetic variants (MLGs and MLLs), clonal richness, heterozygote excess and negative FIS values16 (see the Discussion below) was more important in C. tenuispina at the W Mediterranean than in any other geographical area and/or species of the genus . The presence of the superclone in C. tenuispina is an extreme case of the clonality, with a unique clonal lineage widely distributed across a large geographical range. Although super-clones has been described in other marine invertebrates, such as corals, their presence was described at smaller spatial scales of only tens of kilometres44. In the mentioned cases, the wide expansion and dominance of a clone was attributed to the combination of asexual reproduction together with a well-adapted genotype to local environmental conditions (see44 and references herein).Evidences of clonality, even with populations mostly maintained by asexual rather than sexual reproduction and highly sex-ratio biased46. The combined information from both parameters together with a deviation from the HWE, negative and significant FIS values and heterozygote excess in C. tenuispina47, are unequivocal marks of long-term clonal reproduction13. Our results demonstrated that C. tenuispina fits on the expectations for clonal marine species16, with a positive relationship between genetic diversity within populations and the FIS coefficient. Actually, as observed for seagrass species, the correlation between these variables in C. tenuispina was weaker when only unique genotypes were considered16. Heterozygote excess, due to the accumulation of somatic mutations, was also common in populations of C. tenuispina with modest and high rates of asexual reproduction. Hence, the complementary use and interpretation of these genetic variables allowed us identifying clonal reproduction as the origin of the high prevalence of some clones in C. tenuispina, instead of inbreeding or methodological problems. The low genetic distances among genetic variants, by only one allele-variant among most low-frequent MLGs, as demonstrated from several analyses, point out their origin in somatic mutations rather than recombination and/or mutations during sexual events.The existence of shared MLGs and low genetic diversity values are genetic signs of asexuality but not exclusive of itC. tenuispina23. In a study monitoring the biological cycle of C. tenuispina from Llançà (NW Mediterranean), authors found that fission was very frequent all over the year, and although some individuals maintained their potential for gonadal maturation, sexual reproduction was also impeded by the absence of females, among other potential environmental factors such as the low winter temperatures in this area23. Studies of C. tenuispina like along the coast of Brazil also highlighted that some populations were mostly maintained by fission, which drove them to a strong sex-ratio imbalance, and recruitment from larvae negligible48.The genetic pattern and the extreme sex-ratio imbalance, with absence of females, found in the W Mediterranean localities, are in concordance with the biological features previously described for a population of C. tenuispina, genetic divergence among populations is drastically reduced. When strict asexual reproduction is maintained over evolutionary time periods, population size tends to infinite and genetic drift to zero, because genetic diversity cannot be lost in clonal lineages47, and therefore, homogeneity among populations increases. Our results from the temporal monitoring highlighted that contemporary recruitment of larvae from distant genetic pools is negligible in the W Mediterranean localities. The low levels of connectivity inferred from Migrate across the Alboran Sea likely result from past historical processes and/or shared ancestral polymorphisms rather than current immigration, suggesting a contemporary strong barrier effect to gene flow across this Atlantic-Mediterranean transition. Whereas the potential effect on gene flow across the Siculo-Tunisian Strait has been scarcely investigated in metazoans49, but already discussed in C. tenuispina13, a large body of literature has demonstrated a variety of genetic divergence patterns between Atlantic and Mediterranean populations. Those studied included species with large dispersal potential associated to a planktotrophic larva , as the one observed in C. tenuispina, but patterns inferred from other species contrast with the strong break found in C. tenuispina. The genetic patterns and biological information revealed in our study reinforces the idea of a relatively recent colonization of the W Mediterranean basin from the Atlantic during a Pleistocene interglacial period, as already suggested by Garcia-Cisneros and coauthors13. During this colonisation, the Alboran Sea might have been functioned as a stepping stone area with higher gene flow eastward, as observed in other species51 (and references herein), following the superficial and dominant current circulation across the Gibraltar Strait52. From our current data, we cannot determine whether major marine fronts prevent the planktotrophic larvae of C. tenuispina to pass across them, or contrary, larvae are able to disperse across marine fronts but recruitment is impeded by other additional factors. Forces impeding larvae and new genotypes recruitment might be varied, such as the existence of the different environmental conditions between basins and/or density-dependent processes after the initial colonisation53. The rapid colonisation of the W Mediterranean, potentially marked by a founder effect with a strong reduction of genetic diversity, could have also constrained the dispersal success of additional genotypes due to the exclusion of subsequent dispersers under conditions of high-density53.Under conditions of predominant asexual reproduction and absence of contemporary immigration, like those found at the W Mediterranean populations of superclone spread all across the W Mediterranean. The absence of sexual reproduction, and therefore, the subsequent spawning, and larvae development, restrict the dispersive potential of the species to the adult stage. Movement rates and migration behaviour are poorly understood in starfish species, but the few studies investigating patterns of adulthood movement in the genus Coscinasterias demonstrated that both vertical and horizontal displacement were mainly limited and related to the feeding behaviour39. Therefore, with the current data available, we assume that the colonization of the W Mediterranean area by the superclone happened by a stepping stone process over an evolutionary time period, and that contemporary migration of individuals is minimum among sites within the W Mediterranean.One question that remains open is how the C. tenuispina presents genetic homogeneity along the W Mediterranean area studied, dominated by a clonal lineage, and genetic divergence with the adjacent marine areas. This genetic pattern may respond to a relatively recent colonization of the W Mediterranean area during an interglacial period, coherent with an ancestral evolutionary gene flow eastward from the Atlantic, and current maintenance of W Mediterranean populations, exclusively, by asexual reproduction after a strong founder effect. In conclusion, our results do not validate our first hypothesis, since clonal lineages seem to be widely spread across broad geographical areas despite the limited dispersal potential of the adult ramets in Coscinasterias. On the other hand, despite the low inter- and intra-population diversity along the W Mediterranean area, genetic diversity seems to be retained within individuals, in the form of heterozygosity. Hence, our study confirms that C. tenuispina fits with the theoretical models and the empirical data obtained for other facultative asexual marine species. Whether retaining genetic diversity within individuals is evolutionarily advantageous in clonal species is something we cannot conclude from our data. However, if this hypothesis is true, C. tenuispina seems to be a resilient species, highly specialised in retaining evolutionary potential, since the species can also elongate its telomeres in absence of sexual reproduction34 to avoid processes of senescence.In conclusion, C. tenuispina were collected for spatial analyses at five new localities of the western Mediterranean (W Mediterranean) along the Iberian Peninsula: La Herradura , Los Escullos , Cunit , Palamós  and Cadaqués . These new samples were added to the collection already available from another study (see13), ranging across > 1200 km of the Iberian Peninsula coast, and Naples  and finally, a total of 316 individuals from five different sites were here included for sex determination . Dissection and visual inspection of all specimens were done to isolate the gonads from all arms. Gonads were then removed from the body and histologically analysed. Briefly, gonads were dehydrated, embedded in paraffin, cut in 5 μm sections using a Microm HM325 Microtome, and stained in haematoxylin–eosin. Sex, male (testis) or female (ovary), was then determined under the optical microscope from the histological preparations. Details are described in23.For sex determination, animals were collected as explained before, and the whole individuals were preserved in formalin . All specimens were genotyped by twelve polymorphic microsatellites previously described and applied in C. tenuispina54. Microsatellite loci were amplified in multiplex following the protocol described in13. Amplification products were analysed on an Applied Biosystems 3730xl DNA Analyzer (Applied Biosystems) at the Scientific-Technical Services of the University of Barcelona. Allele length was estimated relative to the internal GENESCAN 400HD ROX size standard (Applied Biosystems) using the software Peak-Scanner . Allele scoring was graphically performed using the R package MsatAllele55. To maintain consistency during the genotyping calling among studies, we used 10 individuals from the previous study13 for alleles size calibration. Additionally, the same researchers that scored alleles and genotyped in13, scored allele sizes in the present study.For genotyping, we used DNA extracted from tube feet preserved in ethanol at − 20 °C. Total DNA was extracted from 3 to 4 feet using the RedExtract-N-Amp™ Tissue PCR kit, and following the manufacturer’s protocol , and the exact test of departure from the Hardy Weinberg Equilibrium (HWE). Genetic descriptors potentially affected by the presence of clones  were also calculated considering only unique genotypes within the populations. These genetic descriptors were estimated in Genodive v 3.0.456 and R package hierfstat57.From the microsatellite dataset obtained, all individuals per locality and time  were used to determine the observed and expected heterozygosity , number of alleles, allele richness, fixation indexes (F13 (and references herein). We performed in Genodive the following descriptors, for both, the spatial and temporal analyses: number of multi locus genotypes (MLGs), number of multi locus lineages (MLL) and clonal richness (Eff-MLG).Genetic diversity descriptors and clonality levels were explored to infer the prevalence of asexual reproduction in the populations. We applied different statistics previously used in other studies for comparisonPsex) due to independent sexual events were used GENCLONE v 2.058. According to the p-values obtained (p = 0.00), the probability of a repeated MLG arising through sexual events was found negligible, hence we consider all repeat MLGs as a result of asexual events. We also determine the so-called multi locus lineages (MLLs), which are individuals with different MLGs potentially generated by somatic mutations. We detected them using the same method explained before for the MLGs but applying a threshold of only one potential allele of difference between MLGs. Since there is not a standard threshold to determine MLLs generated by somatic mutations, we conservatively allowed only one mutation.The different MLGs were determined using a distance matrix based on an Infinite Allele Model (IAM) for the whole dataset and locality. Missing data, which only represented 0.65%  and 0.11%  were not considered as genetic differences when performing the distance matrix. Therefore only the available scores were used for the identification of MLGs. To estimate the probability of having the same MLG  and the number of MLLs (relative to sample size), and clonal richness per locality. Additionally, since some studies have detected heterozygote excess and large deviation from the equilibrium of the FIS statistic towards negative values under conditions of clonal reproduction16, we also explored the correlation between FIS and the number of MLLs, and clonal richness. All correlations were computed with the lattice package in R59, and two different databases, one including all individuals per site and another only including unique genotypes.To explore the relationship between heterozygosity and clonality in C. tenuispina, with focus on the W Mediterranean area, and including and excluding individuals sharing MLGs.Different approaches were used to investigate spatial patterns of genetic structure and gene flow in FST statistics and Jost’s Dest in Genodive. Significant p-values were obtained after 10,000 permutations for both statistics. Genetic dissimilarity values for FST and Dest values were graphically represented with heatmaps obtained with the gplots v 3.0.3 package for R60. The FST genetic distances were also used to construct an unrooted neighbour-joining tree with the adegenet package v 2.1.3 in R61. Both statistics, FST and Jost’s Dest, were also calculated including unique MLGs, although values of the statistics could not be performed for monoclonal populations or dominated by only one MLG.Genetic distances between pairs of localities, including all individuals, were measured based on two different methods: the Analyses of the Molecular Variance (AMOVAs) were separately run for two databases, including all individuals or only unique genotypes (MLGs) per locality. We used an allele infinite model, and the significance of the tests was evaluated with 10,000 permutations per run in Genodive. We calculated genetic divergence at three hierarchical levels: individuals within localities, localities within different geographical areas and four geographical areas .Discriminant analyses of principal components (DAPC) were run for two datasets: one including the NE Atlantic and Mediterranean localities, and another only including western Mediterranean localities. Analyses were performed with adegenet. The optimal number of principal components (PC) was determined by the cross-validation method as implemented in this package, and comparison of a-scores for a set of increasing numbers of PCs and a spline interpolation using the a-score function. The number of genetic clusters that better explain our data was explored with the function find.clusters. DAPC analyses were performed grouping samples by actual localities (sampling sites) and also by the genetic clusters inferred from our data. Representing DAPC by clusters helps to determine how well the selected clusters retrieve the actual populations.62 was also used to infer an optimal number of homogeneous genetic units (K) based on Bayesian clustering analyses. We run two analyses, one included all individuals and another included only unique MLGs, with K numbers from 1 to 12 in both cases. For each K run, 200,000 Markov chain Monte Carlo (MCMC) steps were performed following 80,000 burn-in iterations. Ten independent replicates per run were computed under the “admixture model” implemented by the software. Convergence of the analyses was confirmed verifying that key statistical parameters  reached the equilibrium. The most likely value of clusters was identified comparing the rate of change in the likelihood of K. The optimal K values were determined using the ad hoc statistic ΔK63 and the maximum likelihood. The 10 independent replicates per run were averaged and aligned using the clumpak server64 and results graphically represented with the same software.The software STRUCTURE v 2.3.465 in R.Additionally to the previous analyses, minimum spanning networks based on dissimilarity , from both databases, one including all individuals and another including only unique MLGs, were constructed to visualise the relationships among genetic variants (MLGs) from the different geographical areas with the package poppr v 2.9.266. For migration analyses, we only considered unique MLGs per geographical area . Due to the computational intensity of analysis in Migrate, only the Alboran Sea and adjacent areas, the main focus of our paper, were included in the analysis. We estimate asymmetrical migration (M) among geographical areas based on Bayesian inference using coalescence. Migration per generation is expressed as 4Nm in nuclear markers, in which N is the effective population size, also estimated in Migrate, and m the immigration rate. Since the mutation model for our microsatellite loci is known, the Brownian motion mutation model, recommended for microsatellites65, with a constant mutation rate for all loci was used as implemented in the software. A custom-migration model of recurrent immigration among the three areas in absence of divergence was applied. A first preliminary run of our data was performed to infer the prior distribution of parameters and their boundaries. Three additional preliminary runs were also computed increasing the number of sampled steps and the increment between samples. After each run, histograms of the parameters obtained, as well as their Effective Sample Size (ESS), were explored to determine whether the length of the run was appropriate. For the definitive run, and considering all the parameters and boundaries obtained from the preliminary runs, we finally performed three different replicates of one long chain, with an increment between the samples (long-inc) of 1,600,000 and the number of sampled steps (long-sample) of 800,000, burning of 480,000, and an adaptive heating scheme of four different temperatures .To explore evolutionary or historical migration patterns between the NE Atlantic and W Mediterranean areas, and across the Alboran Sea, we used the software Migrate v 3.6.11FST and Jost’s Dest statistics. Diversity and clonality indexes were also calculated per site and year as explained before.The frequency of the MLGs and MLLs found per locality at t1 and t2 was calculated and represented as pie charts. Genetic distances between years, t1 and t2, for all four W Mediterranean sites were measured based on Supplementary Information.