Tahina spectablis in 2008 and 2016. Our 2016 study included newly discovered populations and added to our genetic study. We incorporated these new populations into species distribution niche model (SDM) and projected these onto maps of the region. We developed population matrix models based on observed demographic data to model population change and predict the species vulnerability to extinction by undertaking population viability analysis (PVA). We investigated the potential conservation value of reintroduced planted populations within the species potential suitable habitat. We found that the population studied in 2008 had grown in size due to seedling regeneration but had declined in the number of reproductively mature plants, and we were able to estimate that the species reproduces and dies after approximately 70 years. Our models suggest that if the habitat where it resides continues to be protected the species is unlikely to go extinct due to inherent population decline and that it will likely experience significant population growth after approximately 80 years due to the reproductive and life cycle attributes of the species. The newly discovered populations contain more genetic diversity than the first discovered southern population which is genetically depauperate. The species appears to demonstrate a pattern of dispersal leading to isolated founder plants which may eventually lead to population development depending on local establishment opportunities. The conservation efforts currently put in place including the reintroduction of plants within the species potential suitable habitat if maintained are thought likely to enable the species to sustain itself but it remains vulnerable to anthropogenic impacts.Madagascar is home to 208 indigenous palm species, almost all of them endemic and >80% of which are endangered. We undertook complete population census and sampling for genetic analysis of a relatively recently discovered giant fan palm, the Critically Endangered  Tahina spectabilis a critically endangered palm from Madagascar to assess its long term viability. We found that current conservation measures may enable the species to persist. Its endangerment is not due to intrinsic population decline.We studied the genetics, population ecology and suitable habitat for  The GPS location was taken at the start and finish of each transect as well as the compass direction. These data were later used to construct georeferenced maps of the relative locations of each plant by using trigonometry to adjust for variable transect direction. For each plant, the following data were recorded: height of the trunk to the base of the lowest leaf sheath or if no trunk, the total height of the plant; diameter or number of fronds if larger than seedling and lacking a trunk. The locations of three adult plants that had flowered and died in previous years  were also recorded. Samples from mature leaves were collected from every plant above 15 cm height except one for genetic analysis. Samples were collected from a subsample of seedlings <15 cm. Samples were surface cleaned with paper towel, cut into smaller pieces, and stored in individually labelled sealed plastic bags with silica gel. In addition, silica gel‐dried leaf material from 25 seedlings propagated at RBG Kew from seed collected from the 2006 mother tree was also obtained to be included in the genetic analysis.All known populations of The original three populations were relocated in 2016 and resurveyed using the same systematic belt‐transect methods as used previously , and the geographic distances between the populations were then determined using the ruler function The area occupied by each population was determined either directly from transect data or by constructing perimeter polygons in Google Earth Pro and using the area calculator. This enabled the expansion of the area of the TS1 population from 2008 to 2016 to be determined. The estimations of extent of occurrence (EOO) and area of occupancy (AOO) were made using the original 2008, new 2016 as well as planted populations as of 2019 with the GeoCat Geospatial Conservation Assessment Tool  of one species in each pixel of 30 m × 30 m resolution throughout the study area. At the same time, it identifies the most important factors governing the distribution of one taxon by giving a training gain for each variable selected; one factor is considered as important if the species displays a strong sensibility in relation to it, that is, a high value of the test gain  and transition probabilities (stage‐transition survivorship iS) between development stages based on methods of Akçakaya, Burgman, and Ginzbur  and was given as the estimated average number of seedlings produced per reproductive tree based on field data. As these data are based on seedling numbers per reproductive tree after seed harvesting has taken place, all models incorporate seed harvesting. We used the number of known trees that did or did not fruit successfully over the total time period since record keeping began for this species, to estimate the average frequency of reproduction.The time spent in each stage class was estimated based on changes in abundance of plants over the 8 year time frame and the ability to track individual plants growth between the two time periods due to our detailed mapping of plants. This was used to estimate the mean residential time in each stage class (MRT) which allowed the mean life span (Mlf) of the species to be estimated  was set at 1.5 based on the observed overall population growth rate of 1.47 over the eight year time period at TS1. A 10 percent standard deviation in the stage matrix  was used to account to sampling error in calculations and is the program default.A baseline Lefkovitch stage matrix was developed based on the parameters determined from the life history model developed above from field observations and input into RAMAS GIS v5.0 , and average dispersal distances and rates are based on the observation of within population dispersal/expansion at TS1. This was then modelled for 25 time steps (200 years) and 15 time steps (120 years).The model trajectories including population growth, final stage structure, and extinction probabilities and trajectories were plotted in RAMAS GIS v5.0  to determine the genotype of each individual at each locus. GENEMAPPER v4.1 software (Applied Biosystems) was used to score fragments according to alleles and loci, double checked manually to ensure accuracy to expected banding size. The repeated samples from the 2008 collections that were run with the 2016 collection were used to confirm consistency of genetic scoring to alleles, and adjustments were made to bp size of alleles present due to the different machine runs between original 2008 and 2016 samples. Of the nine loci tested only four were polymorphic within the species Pd15, Ob11, Aacu07, Pd32 and these were used for further analysis. We acknowledge the limited resolution of so few variable loci and results need to viewed with caution.A), the percentage of polymorphic loci (P), mean expected heterozygosity (He), mean observed heterozygosity (Ho), and the fixation index (F) was also calculated using GenAlEx 6.4  at three locations in close proximity , and further searches in 2016 documented 774 wild growing T. spectabilis plants  at a total of seven sites including the original three locations  but climatically the species requires low temperature seasonality (contribution 48%), that is, where there is little variation in the mean monthly temperature (difference of 10–14°C between warmer and colder season) throughout the year and relatively high precipitation during the wettest month .The revised SDM indicates that the potential areas suitable for the species remain restricted to coastal areas in small parts of the northwest of Madagascar, between Analalava in the north and to the southern part of the Antsanifera peninsula Figure . Of the 2 and the AOO based on a 2 km grid is 24 km2; there is a considerable disjunction between the two known areas of occurrence  to 1 > 2 m tall .The average distance to nearest neighbor population is 1.9 km and the presence of single plants at several sites suggests successful seed dispersal within a 3 km range Table . Our mets Figure . It is ps Figure . Under tT. spectabilis range. The combined wild and planted T. spectabilis populations, extends the EOO by 3.5 times to approx. 763,994 km2 and nearly doubles the AOO in size from 24 to 44 km2  has approximately doubled its area between 2008 and 2016. However, it is important to notice that all known habitats are susceptible to degradation and decline in quality since the natural ecosystems in the area are generally threatened by the seasonal use of fire  cycle and possibly the interaction of this and the Indian Ocean Dipole (IOD)  throughout the year emphasizes the role played by the heat in the growth physiology of palms by the absence of dormancy during the dry season  during the wettest month (February) when T. spectabilis population growth, they also show that this seems unlikely to lead to its extinction. Previous demographic studies have shown that changes in individual palm growth rates and fecundity must be large and persistent to affect population growth rates  and Extent of occurrence has expanded (EOO) since its discovery the number of plants of a size capable of reproduction has declined since 2008 and remains at a critically small size thus the species remains Critically Endangered according to the IUCN criteria (D). Our modelling shows that if the current known populations remain protected by local customs and new conservation practices (Gardiner, Rabehevitra, Letsara, et al., T. spectabilis populations are expected to maintain themselves and eventually expand and we expect to see a recovery in the next 100 years. If new populations are discovered as a result of recent searches this will assist to ensure the species long‐term viability if new discoveries are accompanied by local conservation security actions. However, the species appears sensitive to seasonal rainfall with this predicting its distribution and potentially its reproductive events and thus may be impacted by climate change in the longer term.This study has found that while the total number of There are no competing interests.AS lead the collection of field data in 2008 and 20,016, analyzed the final genetics, and demographic data undertook demographic modelling, supervised student HJ and was principal manuscript writer. HJ undertook initial genetic and demographic analysis and contributed to writing especially methods.LS undertook second genetic analysis and contributed to PVA model methods and critical review and editing manuscript. YS contributed to developing demographic models and PVA and critical review of the manuscript. LG obtained funding and lead the 2016 field trip conceptual design as well as contributing to critical manuscript writing and revision. DR organized local field logistics and contributed to the field work in the 2016 trip as well as developing conservation priorities for the species and contributed to manuscript writing. RL participated in the 2016 field trip and liased with local authorities and Botanic Gardens to obtain permits as well as contributing to the critical manuscript revision. SC was responsible for the Kew logistics team and both grant and permit and contributed to critical manuscript editing and who has been key in the establishing of the species conservation program. JD provided ongoing taxonomic, observational and logistical advice and was responsible for making the original connection to Xavier Metz who discovered the species, assisted with the establishment of the species conservation program and C de Foucault who has conserved the species in planted population as well as contributing to the critical review of interpretation of results and manuscript. WB has supported this project in his lead role at RBGKEW from its inception and had contributed critical review of all versions of manuscripts and data interpretation from the original Honours thesis to this final paper. MR assisted with permits and logistical support for the 2008 trip, developed SDM models and made a major contribution to the manuscript writing and editing. All listed authors have read and approved the final submitted manuscript.


The combined power of discrimination, combined power of exclusion and cumulative probability of matching were 0.999999999999999978430815060354, 0.999995039393942 and 2.15692 × 10−17, respectively. On the bases of genetic distances, PCA, phylogenetic and structure analysis Lahore-Christians appeared genetically more associated to south Asian particularly Indian populations like Tamil, Karnataka, Kerala and Andhra Pradesh than rest of global populations.Phylogenetic relationship and the population structure of 500 individuals from the Christian community of Lahore, Pakistan, were examined based on 15 autosomal short tandem repeats (STRs) using the AmpFℓSTR Identifiler Plus PCR Amplification Kit and our previously published Y-filer kit data (17 Y-STRs) of same samples. A total of 147 alleles were observed in 15 loci and allele 11 at the TPOX locus was the most frequent with frequency value (0.464). The data revealed that the Christian population has unique genetic characteristics with respect to a few unusual alleles and their frequencies relative to the other Pakistani population. Significant deviations from Hardy–Weinberg equilibrium were found at two loci  after Boneferroni’s correction ( Minority religious affiliates residing in Pakistan include Hindus, Christians, Ahmedis, Baha'is, Sikhs, Parsis, and Buddhists, amongst others. The Christian population comprises of 2.5 million (1.6%), making it the second largest religious minority of Pakistan2. Lahore, the capital of the Pakistani province of Punjab, is the second-most populous city in Pakistan (11.13 million) with a Muslim majority (97%) and a Christian minority (2%). Christianity was initially imported by Reverend Thomas Valpy who was appointed as the first Bishop of Lahore in 18773. Christians are considered to be descendants of a caste population of India4 and while they are thought to be a relatively closed population because of religious constraints, yet amiable relations are sustained with the majority population.Pakistan is a multiethnic country, harboring 217 million people, of whom the majority is Muslim according to the Pakistan Burea of Statistics6 Although their mutation rates are significantly higher than those for single nucleotide polymorphisms (SNPs)7, they are none the less useful as genetic markers for population genetic studies, especially more recent genetic history8.Short tandem repeats (STRs), also known as microsatellites, are repetitive sequences of DNA with a repeat motif of four to six base pairs and are almost universally employed as forensic identity markers because they are highly polymorphic and heterozygous, have short sequence lengths and are distributed throughout the human genome9 on 17 YSTRs , Y-GATA-H4, DYS19, DYS390, DYS439, DYS456, DYS448). To affirm phylogenetic affiliations of this population, data sets were compared with referenced populations as given in Table There have been many earlier studies of 15 autosomal STRs in various Pakistani populations except Christians. We emphasize that this population must be targeted as a whole, to understand the genetic context of Christians and its connection to the greater Eurasian continent. Hence, Lahore-Christian samples were evaluated based on fifteen autosomal STRs of Identifiler Plus Kit (Applied Biosystems) and already published data set of same male samples (YA004381)About 3 mL blood was collected in EDTA vacutainer tubes from 500 unrelated Christian individuals residing Lahore, capital city of the Punjab province in Pakistan. Whatman blood stain cards were prepared for each sample with a unique sample ID that was henceforth used for processing.10 and quantified on ABI7500 Real-Time PCR instrument (Applied Biosystems) using the Quantifiler Human DNA Quantification Kit (Applied Biosystems) following the recommended protocol11.Genomic DNA was isolated by an organic-extraction procedure described by Signer et al. (1988)12. The DNA template (1 ng) was added to 2.4μL of Master Mix and 1.2μL Primer Set in a total reaction volume of 6 µL. PCR was performed in a GeneAmp9700 PCR System (Applied Biosystems). Thermal cycler conditions included an initial incubation for 11 min at 95 °C; 28 cycles of denaturation for 20 s at 94 °C, annealing/extension for 3 min at 59 °C and final extension for 10 min at 60 °C; and a final hold at 4 °C.DNA samples were diluted to the concentration of 1 ng/μL for PCR according to the recommended protocol for the AmpFℓSTR Identifiler Plus PCR Amplification Kit (Applied Biosystems)To perform genotyping on an ABI3730xl Genetic Analyzer (Applied Biosystems), 1µL of amplified product was added to 0.35µL GeneScan 500 LIZ size standard (Applied Biosystems) and 13µL highly deionized (Hi-Di) formamide. Data was analyzed using GeneMapper ID v3.2 to designate alleles in accordance with the Kit allelic ladder.13. The dataset was evaluated by the STRidER database13 with QC report reference number STR000284.The efficiency of the PCR amplification was monitored using Identifiler Plus Control DNA 9947A as a positive control and all reagents except DNA template as negative control. The STR analysis was conducted following the nomenclature recommendations of the DNA Commission of the International Society for Forensic Genetics (ISFG)The STR data of Lahore-Christians was compared with the available data of indigenous and global populations (supplementary Table HO) and expected (HE) heterozygosities, polymorphism information content (PIC), typical paternity index (TPI), power of exclusion (PE) and allele frequencies were determined using modified Powerstats1.2 software30. A Hardy Weinberg equilibrium (HWE) test was performed using PowerMarker3.2531. The exact test for population differentiation was carried out by Arlequin3.5.2.2 software32. Phylogenetic and Principal Component analysis were executed using POPTREE33, MEGA-X34, Structure2.3.435 and PAST3.2636. Y-DNA haplogroups were also predicted by Whit Athey’s Haplogroup Predictor (https://www.hprg.com/hapest5/index.html)37 for the purpose of Y-lineage identification.Statistical parameters of forensic interest including power of discrimination (PD), matching probability (MP), observed .−17, respectively. Significant deviations from Hardy–Weinberg equilibrium (p < 0.05) were observed at two loci  after Boneferroni’s correction (p ≤ 0.003).A total of 147 alleles were observed over all loci and allele 11 at the TPOX locus was found to have the highest frequency of 0.46. Allelic frequencies at each locus are shown in Supplementary Table p ≤ 0.0002) at 15/15 loci with Mongol, 14/15 African American27, Caucasian (12/15)27, Uganda Yousafzai and Kashmiri (11/15)28, Balochi, Punjabi, central India (7/15)38. While differences at small numbers of loci for Nepalese, Sindhi (3/15), Karnataka and Bangladeshi (2/15)39 were observed. However, there were no significant differences at any loci for the Tamil, Balmiki, and Kerala populations22.The allele frequencies at the 15 autosomal STRs in the Lahore-Christian population were compared with those from 16 other populations using population differentiation test as shown in Supplementary Table 9 of studied population and 16 reference populations based upon RST p-values. Pairwise RST p-values were calculated through AMOVA using online YHRD tool. As illustrated in Fig. (1B) paternal lineage of Lahore-Christians shared branch with South Indian-Karnataka adjoining roots with Tamils, Andhra Pradesh and Bangladeshi followed by Punjabi. While Sindhi, Yousafzai and Balochi shared genetic association with Caucasians at the top. However, Madhya Pradesh  appeared distantly. Phylogenetic analysis shows Lahore-Christians population has a close genetic distance with the south Indian populations.The neighbour-joining phylogenetic tree Fig. A illustr40. Historically, the Tamil, Kerala and Karnataka populations belonged to the southern part of India and their culture is deeply rooted in Christians and Muslims41. Kerala is home to 22.07% of the total Christians in the country, followed by Tamil Nadu with 15.88%42. According to a 2011 census, Christians represent about 6% of the Tamil Nadu state population43 which also proclaim our phylogenetic analysis and migration history of Lahore-Christians. Moreover, it suggests that while South Indians and Pakistani Christians are geographically isolated, they have similar genetic origins.South India accounts for 21.47% of the community. It experienced a range of cross-cultural challenges between missionary Christianity and local convertsAlthough 15 autosomal STR markers have limited differentiation power to detect population structure but are efficient to some extent in differentiating Lahore-Christians from 9 other reference populations. Structure analysis was conducted employing Structure2.3.4 software using the admixture model with correlated allele frequencies without prior population information (USEPOPINFO = 0). Number of inferred clusters varied from 1 to 6 with three repetitions using 50,000 burnin and 100,000 MCMC simulation for each K. Results are intuitively depicted by bar plot as illustrated in Fig. 44 as depicted in Fig. Whereas, K = 3 was the most suitable configuration based upon output posterior probability results inferred using the Structure HarvesterA PCA plot was constructed from autosomal STR allele frequencies  based on 17 –YSTRs using Whit–Athey’s algorithm were assigned to 7 haplogroups . Other haplogroups like I1, G2c, I2a1, J2a1h I2b1, N and T were not observed in our samples. Whereas, L(40%), RIa(38%), E1b1b(25%), Q(23%) were found the most common haplogroups and accounted for most of its Y-lineage from south Asians. Our results also corroborated with the past reportings of the most frequent haplotypes from South Asia46.The outcomes of phylogenetic analysis presented that Lahore Christians are most closely related to Indians particularly Tamil and might share common ancestors. Moreover, there are clear genetic variations between Christians and rest of the populations. It also supports historical records that, following the geographical migration from India to Pakistan, this population got eventually recognized as Christians47.Lahore-Christians are primarily nomadic, poses conservative lifestyle, religious practices, extremely endogamous culture and traditional occupation as compared to other Pakistani population. Tracing their trail of migration and relatedness with world populations would provide a glimpse of primordial trajectory. Genetic affinity of Lahore-Christians to South Asian Indian populations and their common nomadic practices indicates historical genetic relatedness. Migratory events lead to subsequent separation of both populations. Relatively higher genetic distance to other Pakistani population were observed in our current study. Previous reports have also suggested genetic similarities of Tamils representing their common origin but minimal signature of gene exchange with other nomadic groups48.However there were certain inconsistencies seen in side by side comparison at fewer population groups based on autosomal and YSTRs due to limited availability of their respective samples data. However, all these analyses clearly indicate that Lahore-Christian population has close genetic affiliation to South Indian population. Moreover, significant differences were observed between Lahore-Christians and other Pakistani populations except Punjabi that seems bit closer. This might also indicate that Lahore-Christians and Pakistani Punjabi diverged gradually from native South Indians following its geographical migration, which also corresponded with historical records49. Results of inter-population differentiations, PCA, phylogenetic and structure analysis revealed that Lahore Christians have relatively close genetic relationships with south Asians particularly Indians. Being closely related to South Indians therefore it showed close resemblance to Tamil, Kerala, Andhra Pradesh and Karnataka populations. In this population, the 15 autosomal STRs and 17 YSTRs provide ample information for lineage characterization. This data would be useful for studies of genealogy, historical migration of Pakistani populations and database development. Genetic data obtained from autosomal and YSTR are in accord with human migration history of Indo-Pak populations. However, there is need of a detailed mitochondrial study to assign them mitochondrial haplogroups for maternal lineage identification.We have provided evidence that the Christian population in Lahore, Pakistan, forms a sub-population among Asian groups and has some unique genetic characteristicsSupplementary Information 1.Supplementary Information 2.Supplementary Information 3.Supplementary Information 4.Supplementary Information 5.


Phytophthora cactorum was performed using ddRADseq sequence variation analysis completed by the analysis of effector genes—RXLR6, RXLR7 and SCR113. The population structure was described by F-statistics, heterozygosity, nucleotide diversity, number of private alleles, number of polymorphic sites, kinship coefficient and structure analysis. The population of P. cactorum in Europe seems to be structured into host-associated groups. The isolates from woody hosts are structured into four groups described previously, while isolates from strawberry form another group. The groups are diverse in effector gene composition and the frequency of outbreeding. When populations from strawberry were analysed, both asexual reproduction and occasional outbreeding confirmed by gene flow among distinct populations were detected. Therefore, distinct P. cactorum populations differ in the level of heterozygosity. The data support the theory of the mixed-mating model for P. cactorum, comprising frequent asexual behaviour and inbreeding alternating with occasional outbreeding. Because P. cactorum is not indigenous to Europe, such variability is probably caused by multiple introductions of different lineages from the area of its original distribution, and the different histories of sexual recombination and host adaptation of particular populations.A population study of  Phytophthora cactorum (Lebert and Cohn) J. Schröt. has a cosmopolitan distribution [Phytophthora pathogens [P. cactorum, especially on strawberry production, has been repeatedly reported [Phytophthora species [P. cactorum, despite its wide host spectrum [P. cactorum isolates to cause crown rot in strawberry plants. Isolates obtained from other hosts were unable to cause the disease in this crop. Similar conclusions were also revealed by other authors; an association between the host specificity and genetic differences of strawberry crown rot isolates and those from other hosts was discovered [P. cactorum [P. hedraiandra [P. × serendipita [P. cactorum was repeatedly confirmed, the genetic background of host specificity remains unclear, although some works indicate genes of virulence as being responsible for host specificity in other Phytophthora species [Phytophthora [ribution  and the ribution . It is cathogens , the subreported ,4,5. The species ,7, as wespectrum . Van Derspectrum  reportedscovered ,10,11,12cactorum , which araiandra  and P. ×endipita ,16 previ species . The smaophthora ,18,19,20P. cactorum is not likely to be in agreement with the considered low genetic diversity of a homothalic oomycete [Phytophthora can be changed. Examples of isolates with homothallic behaviour belonging to heterothallic species have been reported [Phytophthora is considered to be “hormonal homo/heterothallism”, where the sexual behaviour of the isolate depends on the production of one of two sexual hormones [P. infestans [P. ramorum [P. sojae and P. porri. In homothallic Phytophthora spp., outbreeding was reported as a possible mechanism generating new pathotypes able to overcome host resistance [The occurrence of multiple genetic lineages and the host specificity in oomycete ,21,22. Hreported ,24,25,26hormones . Homothahormones ,28. Prefhormones , therefonfestans ,31,32 or ramorum , or in hsistance ,35,36,37sistance .P. cactorum, as a homothallic species with described host specificity, a wide host spectrum, worldwide distribution and well-documented interspecific hybridisation, is an interesting model for a genotyping study. The aims of this study were to analyse the genetic structure and sequence variation in P. cactorum populations from strawberry fields in the Czech Republic and from other hosts, and to evaluate the relationships between these populations, as well as their relationships with the genetic groups defined earlier. We also related the population structure to the host specificity and related this specificity to particular arrangements of some avirulence gene groups. We inferred those conclusions on the basis of SNP (single nucleotide polymorphism) markers generated using high-throughput sequencing with the ddRADseq method of gene library preparation, enabling us to calculate many population characteristics. The ascertained structure was confirmed by phylogeny based on the sequences of three cytoplasmic effector genes.P. cactorum isolates, 24 strawberry plantations in the Czech Republic were sampled. Most of the isolates were isolated from symptomatic strawberry plants in 2017–2019 using the baiting method with subsequent cultivation on a selective V8 PARPNH medium [P. cactorum isolates originating from the same strawberry plantation were considered a single population and, similarly, each previously defined group  was considered a separate population. The species identity of the newly acquired isolates was preliminarily morphologically determined according to the shape and size of reproductive organs.To obtain H medium . Except H medium  were alsAll isolates were cultivated on V8 agar plates covered by a cellophane membrane in Petri dishes. After a colony was developed, the mycelium was harvested and homogenised in a 1.5 Eppendorf tube by a mixer mill . The extraction of DNA was performed using a DNeasy Power Plant Pro Kit  according to the manufacturer’s instructions.P. cactorum was confirmed by the BLAST algorithm of the NCBI database.Isolates were identified according to DNA barcoding based on the sequences of the ITS region of the ribosomal DNA. The PCR was processed using ITS1 and ITS4 primers designed by White et al. , accordiP. cactorum isolate was: 300 ng of sample DNA, 5 U of MspI and 7 U of Sau3AI endonucleases and 1 × Tango buffer , added to nuclease-free water to 30 µL. The reaction was performed in a thermocycler at 37 °C for three hours. Single-stranded oligos for the adapter were synthesised by the MilliporeSigma according to a template proposed by Peterson et al. [The ddRADseq DNA library was prepared according to the method of Peterson et al. . The comn et al. , of whicn et al. . The adaThe sequencing on an Illumina MiSeq device was processed by the Biotechnology and Biomedicine Centre of the Academy of Sciences and Charles University  using a MiSeq Reagent Kit v3 .P. cactorum isolates were used in this part of the whole study (TM). The concentration of primers in RXLR6 and RXLR7 was 0.2 mM, and in SCR113 it was 1.32 mM. The reaction conditions in the thermocycler  were identical for all three DNA regions except for the annealing phase. The cycling conditions were as follows: 98 °C for 5 min; 35 cycles of 98 °C for 30 s, annealing −54 °C for 15 s for both RXLRs and 55 °C for 30 s for SCR113, 72 °C for 60 s, then 72 °C for 5 min. The PCR product was sequenced by MacroGen Inc. .Three effector gene regions that are potentially polymorphic were chosen: RXLR6, RXLR7  and SCR1le study . Primer The quality of data in all 2 × 12 individual runs of sequencing on an Illumina MiSeq device was evaluated using FastQC software  ; in partst statistics were calculated according to Excoffier et al. [st according to Meirmans [st according to Weir and Cockerham [st according to Jost [is” and its variance were calculated. Since the heterozygosity is strongly influenced by the reproduction behaviour of the population, heterozygosity reveals the sexual or asexual nature of the population. Briefly, heterozygosity is increased by clonal reproduction and by outbreeding [The subsequent data processing was carried out using seven modules of Stacks software  ,45. The r et al.  and, as Meirmans , Fst accockerham  and Dst  to Jost  were calbreeding ,51, whilbreeding . SimilarP. cactorum and the number of discrete genetic groups (K-numbers), the Structure analysis  [is), also by VcfTools. The indication of population exposition to some evolutionary pressure was tested by the exact test for Hardy–Weinberg equilibrium [To more reliably deduce the structuring of the population of ia, USA)  was procia, USA) . VcfToolia, USA)  was usedilibrium , calculailibrium , which eilibrium . The thrhttps://bioedit.software.informer.com/7.2/; accessible 9 February 2021). The phylogenetic analysis was performed for all three loci, which were concatenated into one dataset and analysed using maximum likelihood and a Bayesian approach. A partitioning scheme and the best-fit model of evolution were selected in PartitionFinder 2  [st [To reveal the relation between the host specificity, the population structuring and the presence of the specific group of effector genes in different parts of population, the sequence analysis of three of effector genes was conducted. The DNA sequences were manually aligned using the software BioEdit 7.1   using thstralia) , and a sstralia) . The constralia) . Bayesiastralia)  using thstralia)  using 20stralia) . The minstralia)  was calclia) [st  between lia) [st .6 reads. The error rate of sequencing was 0.16% in run 1 and 0.23% in run 2. In all reads, the average percentage of GC content was 52.78%, and the average percentage of target sequence length (80 bp) was between 95.3 and 98.4% for all reads. Both the median and lower quartiles of per-base sequence quality were higher than 34, which means a very good quality of reads. During data processing, 7.25% of reads were discarded because of the low barcode quality, 1.34% of reads were of poor sequence quality and in 0.78%, no restriction enzyme cut site was found, thus, 3.05 × 107 (90.64%) reads were retained for further processing. After the processing of all data and SNP calling, the mean number of identified sites per individual was 3943.37 and the average depth of sites per individual was 5.69.Illumina MiSeq sequencing and data processing: The sequencing on an Illumina MiSeq device resulted in a total of 33.6 × 10Structure: According to structure analysis, the most probable model appears to be K = 5, with the highest value of ΔK = 677.6, followed by a considerably less probable K = 2 with ΔK = 360.9 . Since tPrivate sites: The numbers of private sites in S group populations were mainly between 0 and 54, which supports the close relations of all populations of the S group, and the numbers of private sites of other groups confirm the dissimilarity of this genetic group from the others. Population 45 was exceptional, with 403 private sites, which places this population outside the S group. The numbers of private sites in the C1, C2, F and H groups were as follows: C2-728, C1-4651, H-3700 and F-8962. These values  support p ≤ 0.05), therefore, 61.2% of loci are in HW equilibrium. Such a result means deviation from HW equilibrium, which indicates the presence of some evolutionary forces influencing the P. cactorum population. The deviation from HW equilibrium as such does not explain the type of these forces, but supports conclusions about the presence of some of these forces.Hardy–Weinberg (HW) equilibrium: Hardy–Weinberg equilibrium was confirmed in 14,928 positions of all 24,412 : The basic structure is similar in all four matrices displaying the differentiation among populations calculated according to various methods. The separation of all groups identified by structure analysis is apparent in the results of Fst according to Weir and Cockerham [st [st [ST [Genetic differentiation between populations ; the substantially different values of other populations are 0.819 in C2 and 0.744 in F. The ascertained values mean rather high homozygosity in all groups, with mentioned exceptions. The reduced values in those populations means a decrease in their homozygosity in comparison to others, which can be interpreted as being a consequence of increased outbreeding. Detailed information is in P—mean frequency of the most frequent allele in each population: This characteristic is in close association with the homozygosity. In variant positions, the values of the mean frequency of the most frequent alleles in the Heterozygosity: The heterozygosity values at the population level ranged from 0.060 to 0.465; in all cases, the observed heterozygosity was higher than the expected heterozygosity . The higis—inbreeding coefficient: The inbreeding coefficient Fis [is = 1 − HI/HS, where HI means individual heterozygosity and HS means the subpopulation heterozygosity [is indicates asexual reproduction. The ascertained values thus indicate at least occasional outbreeding; only the C1 (0.001) and H (0.043) groups had slightly positive values. These results suggest that outbreeding occurs with a different frequency in each group, which is also implied by the variability of individual Fis values. The values of population and individual Fis are summarised in Fient Fis  was sligzygosity , values Nucleotide diversity Π and proportion of polymorphic sites: Nucleotide diversity is a measure of genetic variation, which is similar to expected heterozygosity. The values of nucleotide diversity Π are given in Relations between isolates: The kinship coefficient (Φ) values among all isolates, calculated according to Manichaikul et al. , are sumPhylogeny: The phylogenetic analysis based on DNA sequences of RXLR6, RXLR7 and SCR113 effector genes resulted in a phylogenetic tree . The maist values congruently put the C2, F and H groups mutually rather close. The locus SCR113 clustered together the S and C1 groups, while the locus RXLR6 clustered the S group together with the C2 group.AMOVA: The results of AMOVA based on DNA sequence data of the three examined effector genes are not in complete concordance . The resHeterozygosity (effector genes): Values of heterozygosity (as nucleotide diversity) calculated for each group based on data for three effector genes are summarised in st  and group S specific to strawberry plants; this result is also supported by the numbers of private alleles . The S gst .st or Dst values  is distant from the members of the S group according to kinship coefficient Φ , and isost value . These tis  and the F group includes exclusively Finnish isolates, also considered to be of a probable hybrid origin. Isolates of the F group were considered as specific to birch [P. cactorum from strawberry plants do not belong to the C1 group, as expected in [st, Φst, Dst) and the numbers of private sites of each group.Historically, two host-specific types of he world ,5,8,9,69innamomi  or P. ra ramorum . Intrasprasitica ,73. On tlanaceae . In P. crecently . The linto birch  and theyto birch . Althougected in , but forP. cactorum population structure, which is primarily determined by the mode of reproduction. Three basic modes of reproduction are known for homothallic Phytophthora species: Asexual clonal reproduction driven by the production of zoospores and chlamydospores, homothallic sexual reproduction (selfing) represented by the production of oogonia and antheridia by a single strain [Phytophthora and only under high concentrations of strong mutagens [st) among populations increases to 1 [st) and inbreeding (Fis) indices [P. andina, inbreeding coefficient Fis values between −0.13 and −0.07 were considered to be associated with outbreeding, or an isolation-breaking effect, which is congruent with the low revealed rate of clones in those populations [P. cactorum are rather low. Anyway, in all cases, the observed heterozygosity was slightly higher than expected, which indicates outbreeding and an isolation-breaking effect [is are slightly negative in most groups, with the exception of slightly positive values for C1 and H, while the variance of Fis is rather low. The revealed proportion of clones (1.2%) and the proportion of genetically distant individuals in populations of the S group are low ); its level varies among loci . The hetonfirmed ,91,92, aonfirmed .P. cactorum populations. The development of such resistance has been repeatedly evidenced in this pathogen [P. cactorum plays an important role in the spread of this pathogen to new host species and environments; outbreeding is equally important in chemical plant protection as well.Since the allele composition of virulence genes probably determines the host specificity, their change by outbreeding carries the risk of changes of pathogenicity  and has pathogen ,96,97, apathogen ,98. Ther


Nitraria tangutorum, a drought-tolerant desert shrub that is distributed in the EAMS zone and has substantial ecological and economic value, was profiled to better understand the influence of EAMS evolution on its biogeographical patterns and demographic history. Thus, the phylogeographical structure and historical dynamics of this plant species were elucidated using its five chloroplast DNA (cpDNA) fragments. Hierarchical structure analysis revealed three distinct, divergent lineages: West, East-A, and East-B. The molecular dating was carried out using a Bayesian approach to estimate the time of intraspecies divergence. Notably, the eastern region, which included East-A and East-B lineages, was revealed to be the original center of distribution and was characterized by a high level of genetic diversity, with the intraspecific divergence time dated to be around 2.53 million years ago (Ma). These findings, combined with the data obtained by ecological niche modeling analysis, indicated that the East lineages have undergone population expansion and differentiation, which were closely correlated with the development of the EAMS, especially the East Asian winter monsoon (EAWM). The West lineage appears to have originated from the migration of N. tangutorum across the Hexi corridor at around 1.85 Ma, and subsequent colonization of the western region. These results suggest that the EAWM accelerated the population expansion of N. tangutorum and subsequent intraspecific differentiation. These findings collectively provide new information on the impact of the evolution of the EAMS on intraspecific diversification and population demography of drought-tolerant plant species in northwest China. The influence of Quaternary climate fluctuation on the geographical structure and genetic diversity of species distributed in the regions of the Qinghai–Tibet Plateau (QTP) has been well established. However, the underlying role of the East Asian monsoon system (EAMS) in shaping the genetic structure of the population and the demography of plants located in the arid northwest of China has not been explored. In the present study,  Geological events and climate fluctuations play a major role in shaping the distribution of plant species and their genetic diversity worldwide ,2. A morThe impact of climate oscillations, especially climate fluctuations during the Pleistocene, on species distribution patterns has attracted increasing research interest due to the predominant effects of climatic factors on plant adaptation to local habitats ,13. FurtReaumuria soongarica and Agriophyllum squarrosum, appear to have been driven by the onset and stabilization of the EAMS   indicated that the molecular variation among the three groups (51.96%) was notably higher than the variation within the populations (17.45%) , support < 0.05] .In addition, the molecular variation among populations in the East-A group (47.77%) was estimated to be slightly higher than what was present within both the East-B (43.50%) and West (33.07%) groups, suggesting that a higher degree of genetic differentiation exists in the Eastern populations compared with the West populations.The phylogenetic relationship constructed with all the 33 haplotypes revealed that the East-B lineage was first diverged from the ancestral haplotype H31, followed by the divergence of East-A lineage from the East-B lineage. The West lineage (4 haplotypes) was monophyletic and separated from the Eastern lineages, because it was derived the haplotype H19 that exists in the JQ population located in the eastern regions .N. roborowskii , and that the East-A lineage possessed the highest level of genetic diversity  relative to the other lineages. An analogous phylogeographical genetic structure has been found in other xerophytes, such as R. soongarica, Ephedra sinica, E. intermedia, A. squarrosum, and Panzerina lanata , and population haplotype diversity  with 1000 random permutations. The genetic differentiation among groups (FCT), populations within group, and within populations (FST) were determined by conducting a hierarchical analysis of molecular variance (AMOVA) using Arlequin v.3.1156 software with default parameters. The pairwise differentiations (ΦST) between all pairs of three groups were also estimated using 1000 permutations.Nucleotide diversity parameters, including segregating sites . To predict the potential distribution range of N. tangutorum in response to glacial climatic oscillations, Maxent v.3.3 software was used to construct ecological niche modeling (ENM) under the maximum entropy algorithm using the WorldClim database from the years 1955–2000 (http://www.worldclim.org/) as described in our previous study [The predicted demographic expansion of populations was estimated through neutrality tests with Tajima’s us study .Nitraria tangutorum that bears important economic and ecological values is a drought-tolerant shrub widely distributed in a broad range of sensitive zones of EAMS, especially the EAWM, in the northwest China. However, its genetic geographical patterns and demographic history under the EAWM were largely elusive. In this study, we profiled the genetic structure and population dynamic history of N. tangutorum using five cpDNA fragments of 161 individuals in a total of 21 populations. Three distinct lineages, including East-A, East-B, and West, were identified through the phylogenic analysis. Furthermore, the eastern regions were suggested to be the ancestral areas, wherein the split of East-A and -B lineages was significantly earlier than that of the West lineage. The higher level of genetic diversity among all populations than within populations was proposed to be closely linked to intensifying aridification of the northwest China induced by geological and paleoclimate scenarios, while the EAWM with characteristics of cold and drought enhanced the regional aridification. According to the results of ENM analysis, the potential distributions of N. tangutorum were predicted to contract and expand during the LGM and LIG periods, respectively, when the EAMS controlling two bioclimate factors, precipitation and temperature, predominantly influenced the surrounding environments for plant survival and led to inter- and intra-specific differentiation. Intriguingly, the West lineage was suggested to have resulted from the dispersal of N. tangutorum located in the eastern regions through the Hexi corridor under the strengthened EAWM during the mid-Pleistocene. Thus, EAWM was regarded as a major trigger of regional diversification and population expansion of drought-tolerant N. tangutorum. This study will therefore deeply facilitate our understanding of the development of EASM and its influences on phylogeographic structures and demography of drought-tolerant plants distributed in northwest China.The past climate oscillation and geological events have been considered as important drivers to trigger the diversification, population expansion, and speciation of plant species, especially those distributed in the QTP and adjacent regions. The evolution of EAMS, closely correlated with the multiple uplift of the QTP, has been found to result in the aridification of the central Asia interior, including the northwest China.


Podarcis lilfordi) using double digest restriction-site associated DNA sequencing. The objectives were to establish levels of divergence among populations, investigate the impact of population size on genetic variability and to evaluate the role of different environmental factors on local adaptation. Analyses of 72,846 SNPs supported a highly differentiated genetic structure, being the populations with the lowest population size  the most divergent, indicative of greater genetic drift. Outlier tests identified ~ 2% of loci as candidates for selection. Genomic divergence-Enviroment Association analyses were performed using redundancy analyses based on SNPs putatively under selection, detecting predation and human pressure as the environmental variables with the greatest explanatory power. Geographical distributions of populations and environmental factors appear to be fundamental drivers of divergence. These results support the combined role of genetic drift and divergent selection in shaping the genetic structure of these endemic island lizard populations.Genomic divergence was studied in 10 small insular populations of the endangered Balearic Islands lizard ( Their characteristic isolation leads to a reduction in gene flow and generates population divergence and speciation2. High levels of genetic structuring also result from frequent physical events combined with the impact of rapid fixation rates in often small populations subject to genetic drift and selection4.Insular populations are naturally isolated systems that harbour high levels of biodiversity and endemism7. Nonetheless, morphological divergence and environmental heterogeneity between islands suggests that divergent selection may also play a key role10. The interplay between local adaptation and genetic drift in moulding variation in these environments is often not clear and requires more research13. Genetic and genomic approaches provide additional value as an important basis for conservation decisions15.Understanding the relative roles of selection and drift are key to understanding the divergence of insular populations. Drift is expected to be considerable due to low migration rates and small population sizesPodarcis lilfordi, as an insular endemism inhabiting a large group of coastal islands and islets of Mallorca and Menorca , provides a suitable system for studying selection and genetic drift as mechanisms of evolution. Podarcis lilfordi likely became extinct from the main islands of Mallorca and Menorca during the Holocene (~ 2000 years ago), presumably as a consequence of the introduction of foreign terrestrial predators by humans who arrived 2000–3000 years prior to this17. Small populations managed to survive on the coastal islands and islets situated around Menorca and Mallorca, as well as the uninhabited Cabrera archipelago . Subsequently, the P. lilfordi populations of the islands of Menorca began to diverge from the populations of the islands of Mallorca at the beginning of the Quarternary period, ~ 2.6 Ma ago21. Despite subsequent glacial events causing sea-level fluctuations22, no evidence of historical gene flow or migration can be detected between present-day Mallorcan (including the Cabrera archipelago), and Menorcan populations20. Within Mallorca, the earliest split (~ 2 Ma ago) separates the populations of the islands of Western Mallorca from the other populations. The next split within the latter group occurred 1.2 Ma ago and separates northern, southern Mallorcan and northern Cabrera populations from other Cabrera populations. Splits within the latter Cabrera populations are also quite old, with the first estimated at 0.8 Ma19. Changes in sea level during the Quarternary were apparently insufficient to reconnect the main islands  but would have allowed connections between islets and islands within groups20. It is particularly interesting the phylogenetic position of the Colomer Island, an isolated population in northern Mallorca with a steep orography and almost inaccessible nature, that make introductions extremely unlikely. Its closer relationship with populations from the south of Mallorca and Cabrera archipelago seems more probable to be explained by the recent extinction of populations that once inhabited the main island of Mallorca.Previous phylogeographical analyses using mitochondrial DNA (mtDNA) have indicated that P. lilfordi populations have led to the proposal that they should each be recognized as Evolutionarily Significant Units (ESUs). The range of this species is restricted to a limited geographical area within the Western Mediterranean basin, across which climatic and altitude characteristics vary only slightly23. Nonetheless, other environmental traits, such as food availability, habitat structure, orography, predation pressure, the presence of potential competitors and human pressure or some parameter correlated with it, show substantial differences across populations. Here, we aimed to reveal whether these aspects of the environment had led to population divergence.The extensive genetic, morphological, ecological and behavioural differences between 25. In addition, it is clear that most of the selective pressures associated with humans can be extremely strong and microevolutionary changes can occur on time frames comparable to human disturbance and anthropogenic changes. Such knowledge is crucial to the conservation of biodiversity26.These well-known populations provide us with a rare opportunity to obtain insight on the effect of short-term environmental changes, most of them driven by humans, in adaptive traits of individuals from a common origin, but now living in different environmental conditions. There are several examples of rapid evolution of species, quickly responding to new selective pressures as human pressure29. This enabled us to reexamine the population history of P. lilfordi, previously described using mtDNA20, and explore the roles of genetic drift and divergent selection in shaping genome diversity among these endangered populations.We used double digest restriction-site associated DNA sequencing (ddRADseq), to obtain single-nucleotide polymorphims (SNP) data from across the genomedenovo_map.pl and described filtering steps, 288,286 SNPs were called from 80,091 ddRAD contigs, with a mean coverage of 28.6 per site. The first SNP for each locus was retained leaving 72,846 SNPs for analysis .A total of 6.8 billion paired-end reads of 101 bp length were generated from the 91 individuals. Following application of FIS) were low (less than 10%)  and 0.182 (Cabrera harbour). Foradada, Esclatasang and Porros presented the highest number of private alleles  indicating considerable genetic divergence, with little or no gene flow between them and the other populations, probably due to their strong geographical isolation. In general, inbreeding coefficients  or K = 6 (CV = 0.388) for the first single SNPs dataset. The divergent positions of Porros, Foradada and Esclatasang islets was corroborated by these results; Dragonera and Colomer grouped with Cabrera main island with K = 5 or formed an independent group with K = 6 . When K = 6 (CV = 0.294), Porros, Aire and Foradada were revealed as independent groups  for 10 clusters. Cross-validation showed that use of the first 15 PCs (55.3% of variance) provided higher assignment rates (99.5%) and the lowest root mean squared error (RMSE) (0.016), justifying the use of this subset of PCs in the analysis. The first PC (51.2% of variance) separated all populations into two major groups: Menorcan populations and all the remaining populations from Mallorca and Cabrera. All lizard populations were grouped by island , except for Rei and Colom islets in Menorca that grouped together. Ten clusters were also favored when analyses were carried out using only SNPs that were candidates for selection, and variance was best explained by 25 PCs (90.2% of variance). In this case, the first PC (91.4%) reinforced the clear separation between Menorca islands and Mallorca islands and Cabrera populations. The populations grouped geographically , except for Porros islet which continued showing a divergent position  and Ne and pi. Negative correlations had been achieved between mean FST and N, but not with Ne (data not shown). Migration rates (estimated by divMigrate) did not show gene flow between Menorca islands and Mallorca islands and Cabrera populations  was lower than the unexplained variance (79.9%) Fig. . However31. Population structure analysis revealed a clear genetic structure among all the populations of P. lilfordi, independent of whether we used SNPs from all RAD tags or just candidates for selection32. Major genetic structuring mirrors that found using mtDNA, with high levels of divergence between Menorca islands and Mallorca islands/Cabrera populations20. However, analyses of outlier SNPs revealed greater similarity between the northern Mallorca Colomer population and other Mallorca islands (Dragonera), which differs from the pattern found in mtDNA20. These results together with the high migration rate detected between Mallorca islands and the Cabrera archipelago populations supports a previous proposal20 that the Colomer Island could be home of a relict population representative of the early population that once colonized Mallorca Island.The RADseq methodology has been applied in other studies of squamate (lizards and snakes), increasing understanding of the processes related to genetic divergence and the identification of genomic regions of interest. The total number of SNPs obtained in this study  agree with the SNP density found in other RADseq studies of reptiles, with relatively high levels of diversity detectedFST values and the greatest number of private alleles relative to other populations, which supports previous findings33 and is suggestive of genetic drift. Long-term isolation and small population size should lead to decreased genetic diversity and increased inbreeding coffecients37. While nucleotide diversity was low38, inbreeding values were under 10%40 which is not indicative of an inbreeding effect.The populations with the smallest population sizes  were most divergent with highest FST outlier tests. Almost 2% of total SNPs were candidates for selection. These loci were related to several functions with direct survival value such as tail regeneration, reproduction, lipid metabolism and circadian rhythm. Nonetheless, the still incomplete annotation of the available Podarcis genome makes necessary a more in-depth analysis to elucidate the molecular mechanisms of adaptation in this genus. Other studies of lizards have revealed links between genetic variation of candidate genes and geographical distributions, patterns of colonization and/or landscapes gradients43.It is worth highlighting evidence of adaptive divergence among lizard populations based on 47.We show that environmental variables appear to be an important driver of divergence between lizard populations after taking into account the effect of historical divergence. The RDA analysis revealed most SNPs that were influenced by the environment were associated with levels of predation and human pressure. These SNPs were involved in diverse functions most notably with feeding and locomotory behavior. The explanatory power of the remaining environmental predictors, such as the biotic capacity of islands, the presence of rats, or the existence of breeding colonies of gulls, is negligible. Some behavioral and physiological differences between populations can be related to differences in predation and human pressures, as in the case of escape behavior in lizard populations with or without terrestrial predators. For example, predation pressure has previously been shown to influence flight initiation distance, distance fled, or hiding time in Balearic lizard populations48. Unlike many terrestrial vertebrates that have evolved in the presence of these selection pressures over millions of years, P. lilfordi has evolved for ~ 5.3 Ma in a pristine environment, free from terrestrial predators16. The subsequent arrival of humans ~ 5000 years ago caused a major change as allochthonous predators were introduced. Hence there is a strong association between indices of human pressure and predation pressure as a result of this Holocenic arrival49.Predation has traditionally been identified as a major selective factor shaping the morphological and demographic evolution of animal species52. However, to our knowledge, this is the first case where predator and human pressures have been functionally linked with possible selection on loci involved in physiological functions that are directly involved with locomotor and escape behaviors. Same human-driven factors are often responsible of rapid adaptation and current extinction crisis53. This fact implies that the study of rapid adaptation to novel environment changes, especially those related with humans, has an inmediate relevance to conservation biology. For this reason, the study of adaptive evolution need to be incorporate into conservation strategies of insular terrestrial vertebrates populations and specifically in the Balearic lizard. In this way, Ashley et al.25 proposed the promotion of an evolutionary enlightened management in which conservation decisions need to take into account the evolutionary effects of anthropogenic changes.It is interesting that this selection has had a strong and detectable effect on the genomic structure of these populations in a relatively short time. This has been described in a few other studiesOverall, our results reveal that both evolutionary processes, associated with isolation and small population size, and selective factors, related to environmental patterns  have played a role in shaping divergence between Balearic lizard populations.P. lilfordi) from 10 different sampling locations across the Balearic archipelago  of individuals  was performed using the R package adegenet59 to obtain an overall representation of the divergence between populations and Neighbor-Joining (NJ) trees were inferred using Mega 760 based on pairwise FST distances.Several analyses were used to characterize population structure of island lizard populations based on all RAD-tag information  for each population has been estimated with the software NeEstimator v2.0.161 using the molecular coancestry method. Linear regression analyses between N and Ne, pi and N, pi and Ne, and FST with N and with Ne, was performed with Pearson correlation. To investigate migration rates between each locality and between each island , migration networks were generated usind divMigrate function62 in the R package diveRsity63 based on GST genetic distance64 with 1000 bootstrap repetitions and a filter threshold of 0.25. More information is provided in the Effective population size  was used as a GEA method to identify adaptive loci based on associations between genetic data and environmental predictors68. See Genome-environment association (GEA) is an important tool for the examination of local adaptation to heterogeneous landscapeshttp://www.usal.es. According to these Guidelines, only the requirements applicable to our study were implemented simply because we did not perform any experiment with lizards in captivity. Field protocols for the capture, handling and release of lizards (which was done at the site of capture a few minutes after the sampling of tail tips) were approved by the competent authority: the Nature Conservation Agency (Conselleria de Medi Ambient) of the Government of Balearic Island (permits: CEP 02/2018 and CEP 10/2016 to V.P.-M. and A. P.-C.).All tail tips samples used in this study were obtained in accordance with Ethical Guidelines of the Universities of Balearic Islands and Salamanca, particularly, following the Bioethics Committee Guidelines of the University of Salamanca. The Ethical Committee from the University of Salamanca publishes general Guidelines concerning the experimental protocols with laboratory animals. These general Guidelines for laboratory animals can be read in Supplementary Appendix S1.Supplementary Appendix S2.Supplementary Figure 1.Supplementary Figure 2.Supplementary Figure 3.Supplementary Figure Legends.Supplementary Information.


Tawantinsuyu, including Kañaris, a Quechua-speaking community located at the highlands of the Province of Ferreñafe, Lambayeque (Peru). Other families were probably taken from the Central Andes to a place close to Kañaris, named Inkawasi. Evidence of this migration comes from the presence near the Kañaris–Inkawasi communities of a village, a former Inka camp, which persists until the present day. This scenario could explain these toponyms, but it is still controversial. To clarify this historical question, the study presented here focused on the inference of the genetic relationship between ‘Cañaris’ populations, particularly of Cañar and Ferreñafe, compared to other highland populations. We analysed native patrilineal Y chromosome haplotypes composed of 15 short tandem repeats, a set of SNPs, and maternal mitochondrial DNA haplotypes of control region sequences.According to history, in the pre-Hispanic period, during the conquest and Inka expansion in Ecuador, many Andean families of the Cañar region would have been displaced to several places of n = 376) indicated that individuals from the Cañar region do not share Y haplotypes with the Kañaris, or even with those of the Inkawasi. However, some Y haplotypes of Ecuadorian ‘Cañaris’ were associated with haplotypes of the Peruvian populations of Cajamarca, Chivay (Arequipa), Cusco and Lake Titicaca, an observation that is congruent with colonial records. Within the Kañaris and Inkawasi communities there are at least five clans in which several individuals share haplotypes, indicating that they have recent common ancestors. Despite their relative isolation, most individuals of both communities are related to those of the Cajamarca and Chachapoyas in Peru, consistent with the spoken Quechua and their geographic proximity. With respect to mitochondrial DNA haplotypes (n = 379), with the exception of a shared haplotype of the D1 lineage between the Cañar and Kañaris, there are no genetic affinities.After the genetic comparisons of local populations—three from Ecuador and seven from Peru—, Y chromosome analyses (Although there is no close genetic relationship between the Peruvian Kañaris (including Inkawasi) and Ecuadorian Cañar populations, our results showed some congruence with historical records. Inka rulers imposed an important socio-political system of forced displacement and resettlement of people called tinsuyu) , 2. Duritinsuyu) –4. Largetinsuyu) , 6. One ern Peru , 8. Suppern Peru , 8.Reducciones (Spanish mission reductions) under the political and administration control of Piura. Later, in 1756, some of the Kañaris, Penachí and Salas communities passed into the jurisdiction of the current Inkawasi administration [By 1572, Kañaris was a place of stration . Accordistration . Meanwhistration .mitmakuna ‘Cañaris’ indicate a very complicated scenario [The general scenario on migration of the people from Cañar region could explain the toponymy in the Province of Ferreñafe (Peru), but this is still controversial . To clarscenario , 11, butscenario –16.Fig.n = 376) [A total of 140 individuals were genotyped and compared with other highland populations of the South American Genographic Project database and published data (n = 376) –15, 17. e) closely related to some from Cajamarca, Chivay (Arequipa), Cusco and Lake Titicaca, an association supported by colonial records. Individuals from the Inkawasi and Kañaris communities are a conglomerate of at least five clans, and most of their haplotypes are shared. Some haplotypes from both localities are more related to those from Cajamarca and Chachapoyas, congruent with the results from linguistic analyses and their geographical proximity [mitmakuna, brought from the north of Peru to Ecuador, including the individuals labelled with the letter c  and 0.047 (p = 0.0053), respectively  . There is also a genetic difference between Kañaris and Inkawasi . A high level of difference is observed between Cañar_EC and Inkawasi  , a small difference  results , despite its geographical isolation on an island located in the Lake Titicaca. Part of the male population of Amantani is associated with the populations of Ecuador, Cajamarca, Chachapoyas and Cusco, suggesting that considerable gene flow took place among the Andean communities. However, the macro regional scenario depicted in the PCoA space, with the exception of Amantani, reflects a genetic gradient according to geographic location.n = 379). A list of the mtDNA control region data according to the rCRS is presented in Additional file A total of 182 mitochondrial DNA (mtDNA) control region haplotypes were assigned to four Native American maternal lineages  and compared with other highland populations as done previously with the STR haplotypes. Genetic analysis was carried out using only the autochthonous lineages   from Tawantinsuyu, especially from Cañar, returned to their original regions. It is known that a proportion of the Ecuadorian Cañaris, including other groups subjugated by the Inkas, were allied with the Spaniards. This situation would have offered a chance to free them from the Inkas, and also to reintegrate the mitmakuna Cañaris and return them to their old home [With respect to the historical association of the Cañar region (Ecuador) with Kañaris of Lambayeque (Peru), it is likely that at the beginning of the colonial period and after the collapse of the Inka Empire, most old home . This coTo clarify a historical controversy on displacements of the people during the Inka Empire, we inferred the genetic history of the ‘Cañaris’ populations. Although there is no close genetic relationship between the Peruvian Kañaris (including Inkawasi) and Ecuadorian Cañar populations, our results showed some congruence with historical records.Ethical consent for the project (Genographic Project –South America) was obtained from the Ethics Committees of the following institutions: Universidade Federal de Minas Gerais and CONEP (Brazil), Universidad de las Americas (Ecuador) and Universidad de San Martín de Porres (Peru). The project was previously explained to the confederations, authorities or leaders, as well as to the participants. After informed consent was obtained, saliva samples from each volunteer from different families was collected using buccal swabs. Subsequently, in the laboratory, DNA extraction was performed following standard procedures .n = 376), we tested the following 10 populations , from the Sisid, Zhud and Cuchucun communities, Province of Cañar, Ecuador; Pastos_EC (n = 6), from the Province of Carchi, Ecuador; Kañaris (n = 16) and Inkawasi (n = 39) from the Province of Ferreñafe, Lambayeque, Peru and Chivay (n = 17) from of Province of Caylloma, Arequipa, Peru. For comparison, individuals from Chachapoyas (n = 115) [n = 36) [n = 11 in the present study, Quichua_EC (n = 37) [n = 4 new samples, Cusco (n = 38) [n = 2 in the present study, and Amantani (n = 26) [For the STR haplotype analysis ,[n = 36) , 17, inc(n = 37) , includi(n = 38) , includi(n = 26)  were incn = 379), we considered the following populations/languages: Cañar_EC , Pastos_EC , Quichua_EC (n = 62) [n = 36) [n = 38), Kañaris (n = 21), Chivay (n = 30), Cusco (n = 33), Amantani (n = 26) [n = 82) [For mtDNA analysis ((n = 62) , includi[n = 36) , includi(n = 26)  and Chac[n = 82) .http://www.fluxus-engineering.com) with the single-stepwise mutation model and median joining algorithm as well as the maximum parsimony approach [ST (RST for STRs and ϕst for mtDNA) and genetic distances between the 10 populations of Peru and Ecuador were evaluated using the AMOVA algorithm, implemented in Arlequin 3.5.1.2. program [http://biology.anu.au/GenAlEx) was used, considering the genetic distance indices transformed by the Reynolds formula in the Arlequin program.For the Y chromosome, five SNPs were genotyped, corresponding to the C-M130, Q-M242, Q-M346, Q-L54 and Q-M3 markers, which characterise the autochthonous lineages of America , using aapproach , 24. A wapproach . To infe program . The hapAdditional file 1: Table S1. Y-STR data and AMOVA results. (a) List of 17 Y-STRs among Peruvian and Ecuadorian populations; (b) AMOVA results for the 10 Peruvian and Ecuadorian populations using 15 STR haplotypes of Y chromosome (n = 376).Additional file 2: Table S2. The RST matrix  and their statistical probabilities  among the 10 populations, according to Arlequin v3.5.1.2 program, based on the 15 Y-STR haplotypes.Additional file 3: Table S3. Diversity indices for 15 the Y-STR haplotypes among 10 populations studied. n = sample size; K = number of haplotypes; N Y-15 STRs = number of 15 Y-STR polymorphic markers; h = haplotypic diversity; MPD = mean number of pairwise differences; SD = standard deviation.Additional file 4: Table S4. MtDNA SNPs data, AMOVA results and mtDNA haplogroup frequencies. a List of mtDNA SNPs according to rCRS among the Peruvian and Ecuadorian populations. The mitochondrial haplogroups were determined using MitoTool program (http://mitotool.kiz.ac.cn/); b AMOVA results for the 10 Peruvian and Ecuadorian populations using the control region mtDNA sequences (n = 379); c Distribution of mtDNA haplogroup frequencies among Ecuadorian and Peruvian populations.Additional file 5: Table S5. The ϕst matrix  and their statistical probabilities  among 10 populations, according to Arlequin v3.5.1.2. program, based on control region mtDNA analysis.Additional file 6: Table S6. Diversity indices and neutrality tests for each population using 379 mitochondrial sequences of the control region for the four maternal lineages . n = sample size; K = number of haplotypes; h = haplotypic diversity; S = number of polymorphic sites; π = nucleotide diversity ; D = Neutrality Tajima’s D test; Fs = Fu’s Fu test; p = probability.


Dolichophis caspius), populations have become increasingly disconnected due to habitat alteration. To understand population dynamics and this widespread but locally endangered snake’s adaptive potential, we investigated population structure, admixture, and effective migration patterns. We took a landscape-genomic approach to identify selected genotypes associated with environmental variables relevant to D. caspius. With double-digest restriction-site associated DNA (ddRAD) sequencing of 53 samples resulting in 17,518 single nucleotide polymorphisms (SNPs), we identified 8 clusters within D. caspius reflecting complex evolutionary patterns of the species. Estimated Effective Migration Surfaces (EEMS) revealed higher-than-average gene flow in most of the Balkan Peninsula and lower-than-average gene flow along the middle section of the Danube River. Landscape genomic analysis identified 751 selected genotypes correlated with 7 climatic variables. Isothermality correlated with the highest number of selected genotypes (478) located in 41 genes, followed by annual range (127) and annual mean temperature (87). We conclude that environmental variables, especially the day-to-night temperature oscillation in comparison to the summer-to-winter oscillation, may have an important role in the distribution and adaptation of D. caspius.Across the distribution of the Caspian whipsnake ( Adaptation to a changing environment is a growing challenge that populations face in the era of “Anthropocene”, marked by significant human impact on the Earth’s geology and ecosystems, including human-mediated climate change . PopulatDolichophis caspius , is a large-bodied colubrid species with a distribution covering large parts of eastern Europe including the Balkans, Turkey, and regions around the Caspian and the Black Sea [Dolichophis caspius also inhabits the Croatian islands, Olib and Lastovo [The Caspian whipsnake, lack Sea ,11,12. T Lastovo , where t Lastovo ,16,17,18 Lastovo . Accordi Lastovo ,19, its In the northern parts of its distribution range, the Caspian whipsnake is under strict protection in Croatia , HungaryD. caspius. Genetic studies of D. caspius have been scarce, and the existing morphological studies focused either on separating D. caspius from the jugularis species complex [b gene and was a phylogeographic analysis of samples from South-East Europe  and Frontier Asia [While evolutionary forces such as gene flow , founder complex  or were  complex ,29. The ier Asia . ResultsD. caspius, as a representative organism for reptiles across eastern Europe and western Asia. To investigate local adaptation, we investigated D. caspius (i) population structure, (ii) genetic diversity, and (iii) adaptive evolution to local habitat types throughout its distribution, applying genome-wide double-digest restriction-site associated DNA sequencing (ddRAD-seq) data and a landscape-genomic approach.Genetic variation is essential for a population to respond to changing environments  and to emerging infectious diseases  effectiExtracted from carcass tissue, shed skin and blood, and buccal swabs originating from 8 countries, 124 DNA samples were collected for this study  and depoSphI and HindIII. The ddRAD library preparation following Peterson et al. [https://doi.org/10.5061/dryad.mgqnk98xmfor description of the Stacks pipeline).DNA concentrations were normalized prior to the library preparation to ensure homogeneous sequencing results followed by double restriction enzyme digestion with n et al.  and sequn et al.  using den = 19) from the dataset. SNPs were then filtered for 1% minor allele frequency (maf). Duplicated samples and highly-related individuals (parent-offspring or siblings) were identified by calculating pairwise identity-by-state (IBS) values using the distance matrix function within Plink. From the resulting matrix, pairs of individuals with an allele identity (IBS) higher than 0.95  of 5%, interpreted as a pairwise match [D. caspius species conservation program, the high number of samples with IBS > 0.95 likely reflect the recapture of snakes or re-sampling of shed skins. In the Croatian islands, the snakes were surveyed annually, individually recognizing each specimen, thus re-sampling or recapture can be excluded. Despite the removal of samples, the remaining dataset included individuals from each sampled locality (The functions geno and mind within Plink 1.07  were usese match ) were relocality . The finlocality .HE) and observed heterozygosity (HO), which were compared using a parametric Welch’s t-test implemented in R statistical environment v.3.5.1. [t-test function. We explored the initial population structure with a Principal Component Analysis (PCA) implemented in Adegenet v.2.1.0 [D. caspius populations—Admixture v.1.3 [D. caspius. Arlequin was also used to estimate hierarchical F-statistics as well as nucleotide diversity (π) within each subpopulation using 10,000 permutations to determine significance in all Arlequin based analyses. Subpopulations containing fewer than 4 individuals  were excluded from the analysis.The package pegas  within Rv.3.5.1.  using th v.2.1.0 . Phyloge v.2.1.0  based onre v.1.3  was run,re v.1.3  to asseshttp://www.birdtheme.org/useful/v3tool.html), and results were plotted using the R package rEEMSplots as suggested in Petkova et al. [The software EEMS (Estimated Effective Migration Surfaces)  was useda et al. .−1), water vapor pressure (kPa), solar radiation (kJ·m−2·day−1), and the 19 WorldClim bioclimatic variables at 30 arc-second resolutions (We used current climate data (1970–2000) from the WorldClim Version 2 dataset . The envolutions . The valBecause multicollinearity of variables can result in erroneous modeling , we remoP, including the population variables and genotype data, was computed for each genotype. To describe the population variables, we used the eigenvalues of the PCA’s first 3 principal components (PC1-3), explaining 41.05% of the total variation in the D. caspius dataset. The effect of each environmental variable was tested by adding one environmental variable at a time to the population variables (dimension P + 1) and assessing which of the 2 models  was more likely.Samßada (v. 0.6.0) modeled the probability of a genotype occurrence in an individual according to its habitat’s environmental composition using logistic regressions while taking population structure into account . First, P and P + 1 (G = 2 × (lP+1 − lP)). Finally, p-values (P) were calculated and corrected for multiple comparisons using the Benjamini and Hochberg procedure [Thamnophis sirtalis 6.0 genome assembly (GenBank: GCF_001077635.1). Protein-coding genes containing SNPs were determined by using the NCBI Eukaryotic Genome Annotation pipeline’s annotation release 100 for the T. sirtalis genome, which was based on sequence homology between a multitude of taxa (https://www.ncbi.nlm.nih.gov/genome/annotation_euk/process/) and also ab initio models and thus produced in silico functional annotations also for more distantly related (non-model) organisms. Similar annotation pipelines have been applied to a wide range of genetic distances, from distant members of the same clade to individualized assemblies of the same species [® database (www.genecards.org).For each tested model, Samßada created an output file, which contained the model parameters for each genotype, including log-likelihood values. Following the Samßada user manual’s instructions, we calculated a G-score for each tested model from the log-likelihoods of dimensions rocedure . The worrocedure  to the T species . DescribHE) estimated across all 53 individuals was significantly higher than the observed heterozygosity (HO) under Hardy–Weinberg equilibrium: 0.204 (±0.177) and 0.107 (±0.106), respectively. The overall average inbreeding coefficient across all individuals was FIS = 0.132.The expected heterozygosity , second (11.9%), and third (6.9%) principal components clustered the D. caspius in eight different groups . These results indicated that most admixture was observed in the populations from C-BAL and BALK-ANAT. C-BAL showed substantial admixture between the N-HU and I-CR populations and a limited amount from the DAN and CRI-BES populations. BALK-ANAT harbored a mixed genetic make-up sharing genetic ancestry with the DAN and CRI-BES populations and to a limited extent also with N-HU, SAM, and S-HU. The results for K = 6 or 7 were similar to those for K = 5 but with relatively small changes in the proportions of admixture. However, increasing the number of potential ancestral populations to K = 8 resulted in the same eight groups identified by the PCA analysis  were significantly different than zero only in the DAN population  and in the C-BAL population , albeit the latter was small , with the highest differentiation levels observed between S-HU and N-HU population, followed by S-HU and C-BAL, while moderate pairwise genetic distances were found between the N-HU and DAN, BALK-ANAT and C-BAL populations (FST = 0.261–0.420). The lowest differentiation was found between BALK-ANAT and DAN or CRI-BES , followed by variation between populations (41.5%) and then among individuals within populations (7.7%). The mean nucleotide diversity (π) within the different populations ranged from 0.067 (S-HU) to 0.168 (BALK-ANAT) , we selected the least correlated ones  associated with one of the seven environmental variables, and of these 65 were located within coding regions predicted in T. sirtalis  and alterations. To understand the population dynamics and adaptation potential of this widespread but locally endangered snake, we investigated population structure, admixture, and effective migration patterns across its distribution range. Moreover, we also implemented a landscape-genomic approach to identify genotypes associated with environmental variables across the species distribution range.Rapid climate change and habitat fragmentation can have negative impacts on populations and be responsible for significant biodiversity loss, making them important concerns in the field of conservation biology ,55. In cGenetic structuring of reptiles in Europe follows a well-known North-South pattern, with the highest genetic differentiation observed in southern Europe and the Mediterranean peninsulas, while the lowest genetic differentiation is observed in northern Europe . The ‘soD. caspius  and showed genetic separation from the spatially closest Hungarian populations  occupied northern central Europe from a Balkan refugium only during the Holocene climatic optimum, and has low genetic variation across the whole area [Coronella austriaca) dominates central Europe; another clade occupies the Balkans, while high diversity can be found in Anatolia and Transcaucasia [Natrix natrix) shows a complex genetic pattern across Central Europe and the Balkans. One genetic lineage distributed from Scandinavia to the Balkan Peninsula survived glaciations in two distinct refugia in the southern Balkan Peninsula and in Central Europe, while the second genetic lineage colonized Central Europe recently from a structured refugia in the Balkan Peninsula [Snake species with similar geographic distribution show only a partially concordant pattern. The eastern genetic clade of the Aesculapian snake  associated with one of the seven environmental variables. Furthermore, the clustering of the environmental variables did not overlap with the genetic clustering  body temperature in ectotherms might be correlated as habitats with high rainfall provide worse conditions for behavioral thermoregulation . Howeverky areas ,18,21 anD. caspius populations , e.g., including locations north of the Danube River in southern Romania and along the Mediterranean coast, which might help us to understand the current high differentiation of the northern Hungarian (N-HU) population and to systematically follow the (re-) colonization routes of D. caspius into Central Europe after the last glacial period. This will also have an impact on conservation management recommendations: The results obtained here are indicative of a strong fragmentation in the species distribution range that has rendered the D. caspius populations relatively isolated from each other. It is important for this to be accounted for when considering moving animals across populations to reduce the effect of inbreeding or to increase population numbers. Furthermore, we found that 4.3% of the genotypes are associated with certain environmental variables and that the genetic diversity connected with such variation is widely distributed across the species range, thus suggesting that all populations harbor relevant adaptive genetic variation.With a comprehensive data set of 17K genome-wide SNPs and samples covering a significant part of its global distribution range, we investigated phylogeography, gene flow, and adaptive selection in