Rubus takesimensis on Ulleung Island, Korea, we compared the genetic diversity and population structure of R. takesimensis with those of its continental progenitor R. crataegifolius. We broadly sampled a total of 315 accessions in 35 populations and sequenced five noncoding regions of chloroplast DNA. Rubus takesimensis emerged as nonmonophyletic and several geographically diverse continental populations were likely responsible for the origin of R. takesimensis; the majority of R. takesimensis accessions were sisters to the clade containing accessions of R. crataegifolius, primarily from the Korean peninsula, while rare accessions from three populations shared common ancestors with the ones from the southern part of the Korean peninsula, Jeju Island, and Japan. A few accessions from the Chusan population originated independently from the Korean peninsula. Of 129 haplotypes, 81 and 48 were found exclusively in R. crataegifolius and R. takesimensis, respectively. We found unusually high genetic diversity in two regions on Ulleung Island and no geographic population structure. For R. crataegifolius, two major haplotype groups were found; one for the northern mainland Korean peninsula, and the other for the southern Korean peninsula and the Japanese archipelago. Compared with populations of R. crataegifolius sampled from Japan, much higher haplotype diversity was found in populations from the Korean peninsula. The patterns of genetic consequences in R. takesimensis need to be verified for other endemic species based on chloroplast DNA and independent nuclear markers to synthesize emerging patterns of anagenetic speciation on Ulleung Island.To determine the origin and genetic consequences of anagenesis in  On oceanic islands, approximately 75% of the insular endemic plant species have originated presumably via cladogenesis, which is typically associated with the term adaptive radiation in insular setting ,2. This Dystaenia takesimana  . Our preliminary study based on limited insular derivative populations provided some possibilities of multiple introductions of R. takesimensis on Ulleung Island [R. takesimensis  and one variable noncoding region of cpDNA . The initial sampling strategy of the previous study was to broadly sample the continental progenitor species, R. crataegifolius, to determine the source populations of R. takesimensis. Therefore, in this study, we made special efforts to broadly sample R. takesimensis on Ulleung Island  and also to sample other highly variable noncoding sequences of cpDNA . Specifically, we attempted to (1) determine the geographic origin of R. takesimensis, (2) compare levels of genetic diversity between continental progenitor and insular derivative species and the degree of genetic differentiation between them, and finally (3) examine population genetic structures within insular derivative species. The results are expected to allow us to synthesize any emerging patterns in the genetic consequences of anagenetic speciation on Ulleung Island.Of nearly 40 endemic species on Ulleung Island, the family Rosaceae  includes the greatest number of endemic species  . Rubus tR. takesimensis and reveal the genetic structure among populations on Ulleung Island, we sampled the continental progenitor species R. crataegifolius throughout East Asia  and the insular derivative species R. takesimensis throughout its entire range on Ulleung Island. There were no permit requirements to collect both species in east Asia. For R. crataegifolius, we sampled a total of 23 populations , including 14 populations  from Korea, 6 populations  from Japan, 1 population  from China, and 2 populations  from the Russian Far East  throughout Ulleung Island. The number of individuals per population ranged from 7 (THR) to 13 (JR). All individuals were sampled at least 10 m apart after considering the possibility of clonal reproduction in two species. Thus, we sampled a total of 35 populations  for our study species, and R. trifidus  was also sampled as an outgroup for phylogenetic analysis . PCR conditions were an initial denaturation of 95°C for 2 min, 35 cycles of 95°C denaturation for 20 s, 56°C annealing for 40 s, 72°C extension for 1 min, and a final extension at 72°C for 5 min. PCR products were purified using the InCloneTM gel & PCR purification kit . Sequencing reactions were performed for the purified PCR products using BigDye Terminator V3.1 Cycle Sequencing Kit  at the GenoTech Corp. .Total genomic DNA was extracted from dried leaves using a DNeasy plant mini kit . After screening several noncoding regions of chloroplast DNA, we selected five highly variable intergenic spacers, i.e., rnL/trnF ,38. PCR Rubus in Korea and phylogeographic analysis, R. trifidus was selected as an outgroup [R. takesimensis on Ulleung Island. All gaps were treated as missing data or coded as simple binary characters [All sequences were assembled and edited using Sequencher 4.2.2. . Sequences were aligned using Clustal W version 2 , and minoutgroup ,34,36. Woutgroup  and IQ-Toutgroup , respectaracters . All chaaracters .R. crataegifolius and R. takesimensis, we used the haplotype network program TCS version 1.21 [R. crataegifolius, using three groups from Korea, China and Russia, and Japan; and (3) the insular derivative, R. takesimensis. The significance of the variance components was calculated using 1,023 permutations. For demographic history, we used mismatch distribution analysis using Arlequin 3.5 [D [R. takesimensis on Ulleung Island and compared two coefficients for gene differentiation, GST and NST, with 1,000 permutations. Nine populations with less than 3 individuals  were excluded for the mismatch distribution, PERMUT analysis, and in the distribution of chloroplast haplotypes among populations.For DNA polymorphism, the number of haplotype, nucleotide diversity (π), gene diversity, and θπ were estimated by Arlequin version 3.5 . To deteion 1.21 . Gaps weion 1.21 . An analion 1.21  was perfquin 3.5  and DnaSquin 3.5 . The gooquin 3.5 ) and Harquin 3.5 . A neutrn 3.5 [D , and Fu n 3.5 [D ,53 were n 3.5 [D  to test accD/psaI intergenic region was 706 bp long, including nine single nucleotide polymorphisms  and four indels, while the atpH/atpI region was 576 bp . The psbD/trnT region was 1,430 bp , trnG/trnS was 560 bp , and trnL/trnF was 940 bp . Of 4,212 total aligned sites, 4,017 (95.37%) were constant, 57 (1.35%) were variable but parsimony-uninformative, and 138 (3.28%) were parsimony-informative characters. The MP analysis found 605 equally most parsimonious trees with a tree length (TL) of 296, a consistency index (CI) of 0.67, and a retention index (RI) of 0.96. Similar tree topology was found when the gaps were treated as either missing data or coded as binary characters, and thus, the strict consensus tree based on the treatment of gaps as missing data is shown , Seokpo (SP), and Dodong  populations closely related to R. crataegifolius individuals. The group containing the most R. takesimensis individuals throughout the entire range of Ulleung Island shared the most recent common ancestor with populations of R. crataegifolius sampled from the northern part of the Korean peninsula, China, and the Russian Far East . The other group  included R. crataegifolius, primarily sampled from the southern part of the Korean peninsula, Jeju Island, and Japan. Within this group, southern populations sampled from Jeju Island , Korea, were closely related to the ones sampled from Hiroshima (Hiro) and Yamagata (Yama) prefectures in Japan. In group A, some individuals sampled from China (YR1), were closely related to the ones from Russia (Rus1), while other individuals were closely related to populations sampled from Korea . Some individuals from Russia (Rus2) were more closely related to the ones from the mountains of Seolak (SA) and Hambaek (HB) in the Gwangwoan-do province of Korea. It was noticeable that some individuals of R. takesimensis were more closely related to R. crataegifolius than to other conspecific populations on the island; three of eight individuals sampled from Dodong (DDHN), two of ten individuals sampled from Jeodong (DDR16), and two of eight individuals from Seokpo (SP). Furthermore, five of eight individuals of R. takesimensis from the Chusan population (CS) were closely related to group A of R. crataegifolius; two individuals, 217 and 218, were closely related to populations sampled from Gwangwon-do province (DH) and Gwangwon-do/Gyeongsangbuk-do province , respectively.The combined aligned sites of the five intergenic spacers were 4,212 base pairs (bp). The is shown . The ML simensis . Rubus tR. crataegifolius and the insular-derived R. takesimensis. Of 129 haplotypes, 81 and 48 haplotypes were found exclusively in R. crataegifolius and R. takesimensis, respectively. Most haplotypes were found at low frequency, and no haplotype was shared between the two species pair. For the insular derivative R. takesimensis, most haplotypes, except for individuals sampled from Chusan , were connected by one mutational step from major haplotypes, suggesting recent origins from the ancestral haplotype. Haplotypes H1 , H24 , and H29  showed high frequency in R. takesimensis on Ulleung Island.The TCS haplotype network  showed eR. crataegifolius sampled from the northern part of the Korean peninsula. Two haplotypes found in Dodong-ri (DDHN), H103 and H119, were also closely related to R. crataegifolius sampled from the southern part of the Korean peninsula. Of seven haplotypes found in Seokpo (SP), two haplotypes (H108 and H109) were closely connected to haplotypes of R. crataegifolius sampled from Jeju Island, Korea (H105 and H114). These cases represent several rare haplotypes on the island more closely related to those of R. crataegifolius, indicating their independent origins from different continental source areas.In most cases, each haplotype was represented by one individual, but rarely by two to three individuals. Eight haplotypes, each one represented by a single individual, were found in the Chusan population (CS). Specifically, haplotypes H43 and H58 were more closely related to the haplotype found in R. crataegifolius shown in the phylogenetic tree, we found two divergent clusters: group A included major haplotypes sampled from the northern part of the Korean peninsula, while group B included major haplotypes from the southern part of the Korea peninsula, Jeju Island, and Japan. Higher haplotype diversity was found in populations sampled from the Korean peninsula compared with the ones in Japan. The population sampled from Baekryeong Island (BR) in the Yellow Sea contained two divergent haplotype groups, one with H40 and H41, and the other with H97 and H98, and two somewhat divergent haplotypes (H40 and H41) were connected to the most common haplotype (H1) of R. takesimensis. The most common haplotype within this group was H42 , which was found in Gwangwon-do province (HB and DH), Gyeonggi-do province (CB), and Gyeongsangbuk-do province (BS) in Korea. Unlike haplotypes found in R. takesimensis, haplotypes found in this group A were connected by one to seven missing or inferred haplotypes, suggesting the divergent nature of the haplotype group. Of the five haplotypes found in one population from China (YR1), three  were connected to the haplotype H59 sampled from Russia (Rus1), while the remaining two (H46 and H84) were related to the southern part of the Korean peninsula (H47 from SC and H82 from BS). Most haplotypes found in Russia, except for two haplotypes, were connected to the ones from the northern part of the Korean peninsula (SA and BS). Two haplotypes (H43 and H58) of R. takesimensis sampled from Chusan (CS) on Ulleung Island were connected to the ones from Gangwon-do province .In the case of the continental progenitor R. takesimensis were connected to these southern populations via several missing haplotypes. The haplotype found in Jeju Island (H105) showed regional sharing across the Halla Mountains between the northern and southern parts of the island. Two haplotypes (H108 and H109) of R. takesimensis found from Seokpo (SP) on Ulleung Island were connected to H105 and H114 found on the northern part of Jeju Island.The group B included haplotypes found primarily in the southern part of the Korean peninsula (Gyeongsangnam-do and Jeollanam-do province), Jeju Island, and Japan. The most common haplotype was H105 , which occurred in the southern part of Korea (YS and BU), Jeju Island, and Japan (Hiro and Miya). The haplotypes found in R. takesimensis on Ulleung Island ranged from four  to nine (JR)  . Some poobserved . Group AContrary to group A, with its diverse haplotypes, group B included populations primarily from the southern part of the Korean peninsula and Japan. For the six populations sampled from Japan, all but two populations (Oita and TK) contained two haplotypes, showing highly reduced haplotype diversity. Two populations, Oita and TK, contained H123 (shared with the nearby Naga population) and H104 (specific to the TK population), respectively.R. crataegifolius and the insular derivative R. takesimensis), the majority of variations (73%) existed within populations, while approximately 27% of the variations existed among populations  occurred among populations, while the remaining 17% and 26.5% of the variations existed among countries and within populations, respectively. In the case of the insular derivative species R. takesimensis, total variations were partitioned more-or-less equally among populations (57%) and within populations (43%).With regard to the partitioning of genetic variations between the two taxa , nucleotide diversity (π) (0.015951 vs. 0.007045), and θπ (65.0013 vs. 27.67857)  . HoweverR. crataegifolius had multimodal distributions with an SSD of 0.007 (P<0.05) and RI of 0.0074 (P<0.05)  and an RI of 0.0355 (P<0.05). Therefore, it is likely that the population of R. takesimensis did not undergo recent population expansion or a bottleneck after introduction to Ulleung Island [Fs and Tajima’s D test . The Harpending’s raggedness index (RI) derived from the mismatch distribution was significant , based on cp DNA data across all populations, was much higher than the average within the population diversity (hS = 0.701). The GST value (0.208) of R. takesimensis on Ulleung Island was higher than its corresponding NST (0.139), suggesting no significant genetic structure in R. takesimensis on Ulleung Island.Mismatch distributions showed that (P<0.05) . Also, pg Island ,54. Demos D test , with sinificant . In R. tAcer takesimensis and Acer okamotoanum) and the Apiaceae (Dystaenia takesimana), primarily utilizing nuclear markers  with complimentary use of a chloroplast marker (trnL-F) [Rubus species.This study represents the first attempt to utilize chloroplast DNA based on extensive sampling  and sequence data  to characterize the genetic consequences of anagenetic speciation in one endemic species-rich group, Rosaceae, on Ulleung Island, Korea. Previous studies were limited to the Sapindaceae  –25,55. IR. takesimensis on Ulleung Island are not the result of a single colonization event. Rather, several geographically diverse continental source populations were likely involved in the origin of R. takesimensis. As shown in the phylogenetic tree  and Seokpo (SP) most likely originated from the southern part of the Korean peninsula, Jeju Island, and Japan. Furthermore, even within a population, especially Chusan (CS) in the north-facing part of the island, we found evidence for a few accessions originating separately from the Korean peninsula. These populations are located either nearby a harbor used for commercial fishing and passenger ferries or near typical bird nesting sites, thus increasing the likelihood of anthropogenic or natural independent colonization events from different source populations. It seems less likely though that human-mediated colonization is responsible for the origin of some accessions in those populations because the archaeological evidence indicates that the island has been inhabited since the 1st millennium BC, with the first confirmed historical reference for the year of 512 CE [A. okamotoanum on Ulleung Island, but later suggested a single origin from the continental progenitor A. mono based on microsatellite or SSR markers [R. takesimensis back to the southern part of the Korean peninsula. However, current studies  involving extensive sampling from southern areas did not find any haplotype sharing between continental and insular species, suggesting Ulleung Island as a primary sink area for plant colonization despite its geographical proximity to the continent. Nevertheless, this study raises the possibility of multiple introductions for Ulleung Island endemics from nearby source areas, and additional investigations on diverse phylogenetic lineages with different seed dispersal modes will be helpful to determine the evolutionary history of each group.First of all, we found that endemic species of tic tree  and the tic tree , a majorf 512 CE –58. Consf 512 CE . Pfosserf 512 CE , based o markers . This di markers –62. It m markers  also raiR. takesimensis, the insular derivative, compared with its continental progenitor R. crataegifolius (Rubus takesimensis harbors unique and diverse chlorotypes despite its occurrence in a young (<1.8 million years old) and small isolated island . Although we used five highly variable noncoding regions of cpDNA in our study, this level of haplotype diversity  contrasts with that of other endemic species, such as Fagus multinervis (one haplotype based on the psbA-trnH noncoding region) [Sedum takesimense (two haplotypes based on the trnL-F noncoding region) [R. takesimensis is genetically unique and contains comparable genetic diversity relative to its continental progenitor species.Based on the few available studies of anagenetically derived species on Ulleung Island, some emerging patterns of the genetic consequences include a clear genetic distinction between continental progenitor and island-derived species and high levels of genetic variation within the island population with no geographic genetic partitioning ,24,63. Fgifolius . This fi region)  and Sedu region) . TherefoR. takesimensis on Ulleung Island was estimated to be 1.7 ± 3.02 million years old, suggesting its origin soon after the formation of the island . In addition, species of Rubus are known for bird-mediated seed dispersal, employ diverse modes of reproduction , and play as early forest succession frontiers. When a single individual of Rubus is transplanted into a bare and open area, it expands quickly as a population with asexual creeping stems and roots in less than five years and undergoes sexual reproduction with the production of flowers and fruits . In addition, Rubus species can utilize both asexual (obligate apomixes to facultative apomixes) and sexual  reproductive modes as the population expands [Populus tremuloidess [Rubus takesimensis can vigorously expand its habitat to open areas as frontier plants, accumulate mutations in its populations, and receive a continuous supply of new genetic materials from continental progenitors through migrating birds. A combination of these factors, i.e., large population size, dual mode of reproduction, bird-mediated seed dispersal, and the long presence on the island likely resulted in high genetic diversity and no geographical genetic structuring in R. takesimensis.As suggested by Takayama et al. , several expands . As a co expands –72. Highuloidess . Sarhanouloidess  pointed R. ulmifolius and a southern Spanish population of blackberry. The Ulleung and Dok-do Islands are known as refuge islands for migratory birds [Columba janthina) is one notable bird species, and several other birds have also been reported; the black-tailed gull (Larus crassiroostris), the russet sparrow (Passer rutilans), the barn swallow (Hirundo rustica), and the oriental greenfinch (Carduelis sinica) [Hypsipetes amaurotis), the great tit (Parus major), the pheasant (Phasianus colchicus), and the blue rock thrush (Monticola solitarius) [R. takesimensis on Ulleung Island. Considering the habit of R. takesimensis , it is plausible that species belonging to the order Passeriformes could feed on aggregate druplets of R. takesimensis. The Passeriformes, suborders Passeri are small or medium-sized birds, mostly insectivorous or omnivorous, and known raspberry feeding birds include the catbird, the mocking bird, the robin, the tanager, the thrasher, the turkey, and the warbler [Carduelis sinica , Passer rutilans (russet sparrow), and Zosterops japonicas (warbling white-eye) are found on Ulleung Island. Carduelis sinica is assumed to be a permanent resident on the island, while Zosterops japonicas occur in southern coastal areas of the Korean peninsula, Jeju Island, and Ulleung Island. Passer rutilans, a winter migratory bird that visits southern parts of the Korean peninsula for the summer, occurs much more broadly in eastern Asia, Sakhalin, Jeju Island, and Ulleung Island. Considering some R. takesimensis haplotypes  are closely related to R. crataegifolius haplotypes from the northern part of the Korean peninsula, China, and Russian Far East and others  to the southern part of the Korean peninsula, Jeju Island, and Japan, it is conceivable that such migratory birds are responsible for introducing a diverse pool of R. crataegifolius haplotypes to Ulleung Island, eventually evolving into R. takesimensis.As for bird-mediated seed dispersal, variations in fruit and seed size have potential effects on seed dispersal. For example, it has been demonstrated that frugivory of many passerine birds is limited by their gape width ,76. Birdry birds . In the  sinica) . Other pitarius) . Althougitarius) , little R. crataegifolius, we found that populations sampled from the inland part of the Korean peninsula showed much higher haplotype diversity compared with those from Japan. In addition, haplotype composition among the populations from Japan was very simple, i.e., just one fixed haplotype, or up to two closely related haplotypes (except for H123). In Korea, R. crataegifolius frequently occurs in lowland open habitats and along mountainous trail edges all over the Korean peninsula, while it is rarely found in the mountainous areas of Japan. Considering the wide geographic natural distribution of R. crataegifolius in Japan, it was interesting to find very low genetic variation within populations and differentiation among populations compared with conspecific populations on the continent. Several factors  likely contribute to neutral genetic diversity within populations and genetic differentiation among populations. In particular, vegetative propagation and the selfing rate have profound outcomes for the genetic diversity of species [Rubus, it has been demonstrated that sexual R. ideanus has much higher genetic variation than apomictic R. nessensis [R. crataegifolius is unknown, it is conceivable that populations in Korea are sexual reproducing diploid or facultative apomictic, while those in Japan are predominantly obligate apomictic. The breeding system of R. crataegifoloius and other possible factors for shaping genetic variation and differentiation requires further investigation.For the patterns of genetic variation in the continental progenitor species  species ,85. In tessensis . AlthougR. crataegifolius from the Korean peninsula to the Japanese archipelago via land bridges, which existed during the last glacial maximum  and served as a dispersal corridor during that time [R. crataegifolius colonized Japan via long-distance dispersal most likely by birds during or even before the Quaternary climatic oscillation, and survived during the LGM. Given all other haplotypes are confined within each region (the Korean peninsula and the Japanese archipelago), the Korean/Tsushima Strait served as an effective barrier to seed-mediated gene flow [Given the rarity of sharing certain haplotypes between and among populations, it was noticeable to find the haplotype H105, which occurs commonly in the southern part of the Korean peninsula , is shared with populations (northern Miya and southern Hiro) throughout the Japanese archipelago. Three derived haplotypes from H105 by one mutational step, i.e., H104, H106, and H107, were shared among populations (H107) or unique (H104 and H106) to a specific population. Therefore, the sharing of haplotype H105 between southern Korea and Japan may suggest a recent migration of hat time ,87–89. Aene flow –93.R. takesimensis on Ulleung Island from the continental progenitor R. crataegifolius based on chloroplast DNA sequences. The insular derivate endemic species, R. takesimensis on Ulleung Island, originated multiple times from diverse geographical source populations. A distinct pool of chlorotypes was found between the progenitor and derivative species, suggesting significant genetic divergence between the two species. A highly diverse haplotype composition within the population and a lack of significant geographic structuring of R. takesimensis were found. Two major groups of chlorotypes in R. crataegifolius were found, with high diversity in the mainland continent populations than in the Japanese archipelago. Based on the results of anagenetic speciation of R. takesimensis, it seems necessary to test rigorously the monophyly of diverse insular endemic lineages on Ulleung Island based on extensive sampling strategy  and sequence data  and compare and contrast the emerging patterns in the genetic consequences of anagenetic speciation shaped by different types of molecular markers. In addition, the discovery of cryptic species on oceanic archipelagos in collaboration with others in the botanical disciplines is critical to the discovery and conservation of the subtle diversity in oceanic island flora [We provided the first comprehensive results regarding the genetic consequences of the anagenetic speciation of nd flora .S1 TableRubus crataegifolius and R. takesimensis.Accession numbers for haplotype sequences of (DOCX)Click here for additional data file.S2 TableRubus takesimensis identifying 48 haplotypes.Variable sites found in (XLSX)Click here for additional data file.S3 TableRubus crataegifolius identifying 81 haplotypes.Variable sites found in (XLSX)Click here for additional data file.


India, known for its rich cultural, linguistic and ethnic diversity, has attracted the attention of population geneticists to understand its genetic diversity employing autosomal, Y-chromosomal and mitochondrial DNA markers. Y-chromosomal short tandem repeats (Y-STRs) are useful in understanding population substructures and reveal the patrilineal affinities among populations. Previous studies on Indian populations based on Y-STR markers were either limited to restricted number of markers or focused on few selected populations. In this study we genotyped 407 unrelated male individuals from 12 states in India employing the suite of Y-STRs present in PowerPlex Y23 . These populations clustered genetically close to each other irrespective of their geographic co-ordinates and were characterized primarily by R1a, H and L haplogroups. Interestingly, comparison with 129 worldwide populations showed genetic affinity of the Indian populations with few populations from Europe and Levantine. This study presents the first pan-Indian landscape of 23 Y-STRs and serves as a useful resource for construction of an Indian Y-STR database. Y-chromosomal markers provide interesting insights into the past demographic events of a population as illustrated by several studies examining the patrilineal affinities among different world populations, including India4.The male-specific human Y chromosome follows a strict mode of paternal inheritance and major portion comprises the non-recombining region (NRY). Y-chromosome is also widely acknowledged for its utility in providing one of the highest resolution tools for studying human population genetics owing to the aforementioned features of uniparental inheritance and non-recombining nature6. It is believed that the genetic diversity exhibited by Indian populations may be because India along with other regions of South Asia served as an important corridor for ancient human migrations7. Genealogical studies have discerned that the Indian subcontinent was not only a recipient but also a donor of the genetic material to the world6. A report by Indian Genome Variation Consortium suggests that though India harbors higher genetic diversity compared to various worldwide populations, Indian populations exhibit low levels of genetic differentiation8. In the past, several studies have already addressed the genetic affinities among Indian populations employing autosomal markers10 and the uniparentaly inherited molecular markers located on mitochondria and Y-chromosome12.Contemporary human populations in India exhibit rich social, cultural and linguistic diversity. Multiple archeological, palaeoanthropological, linguistic and genetic studies highlight India as an interesting vault of ancient genetic pool13. However, few haplogroups (e.g. haplogroup J) that were reported to be frequent in India are also traced to outside of the Indian sub-continent3. Studying the Indian population history has always been a challenging task owing to its past demographic events and the complex organization of the extant human populations. Although, studies based on autosomal data reported a North to South genetic cline for non-tribal Indian populations14; other studies with Y-chromosomal markers were unable to corroborate such a cline15. Y-chromosome based worldwide comparisons of Indian populations showed their closest affinities with some European populations3.Y-chromosomal studies in various populations of India show that the few Y-haplogroups (group of similar haplotypes derived from a common ancestor) were autochthonous in nature and dated back to the late Pleistocene epoch 18. However, similar studies in Indian populations were confined to small restricted groups of India, which do not truly represent the genetic diversity possessed by them19. To the best of our knowledge, a comprehensive analyses representing populations from widely distributed geographical regions of India has not been attempted earlier employing 23 set of Y-STRs. In this study, we have genotyped 407 samples sourced from 12 different states (administrative provinces) representing North, South, East and West India using a multiplex of 23 Y-STR loci present in PowerPlex Y23 (PPY23)  system, to infer genetic relationship among the populations from different regions of the country. Our results show that these populations illustrated a closer genetic relationship among themselves, irrespective of their geographic distance. Moreover, while investigating the genetic relationship with populations from other regions of the world20, these populations interestingly showed greater genetic affinity with few populations from Europe and Levantine. Additionally, since this chemistry was reported to be forensically potent in various worldwide populations21; this panel was evaluated to gauge its forensic efficacy in Indian populations as well. This study apart from providing a comprehensive picture of Y-STR-based diversity of Indian populations, would also be of great utility for the development of a Y-STR database for forensic investigation purposes in India.In addition to playing an instrumental role in elucidating human population history; Y-STR markers were also widely used to study patrilineal diversity in various populationsIn order to obtain an estimate of molecular genetic diversity for the target STRs in Indian populations, we calculated genetic diversity (GD) values (a measure of the polymorphism at a locus) for each locus incorporated in the panel. After discarding four samples due to presence of more than one allele, we observed a total of 397 unique profiles with four haplotypes present in duplicates and one in triplicate which can be visualized through minimum spanning network (MSN) plot depicted in Supplementary Fig. 19. Even though the populations were sourced from 12 different geographic locations in India, this set of STRs in PPY23 system did not show much variation in allelic distribution across the populations (RST~0.02).To evaluate the distribution of Y-STR alleles, GD of the panel was calculated separately for each of the 12 populations. Higher values of GD (≥0.64) were observed for each of the populations indicating the polymorphic nature of the panel of markers . Only 3.6% of the variation based on genetic distance could be explained by geographic distance, which was not statistically significant (p = 0.07). The correlation between geographic distance and genetic distance was also low (0.22) and statistically insignificant. Even after grouping the locations on the basis of geographic regions, none of the populations were found to be isolated as evident from the spatial analysis of AMOVA (SAMOVA), wherein only a small genetic variance was observed among the groups (FCT~0.02) .The principal coordinate analysis (PCoA) plot based on the pairwise Nei’s genetic distance among the 12 populations showed small genetic distance among them Fig. , althoug23 was used to assess the pattern of clustering in the Indian populations. It was observed that not only individuals belonging to the same geographic region were closely spaced in their individual cluster, but each of the 12 clusters were also closely overlapping and occupying central position in the plot. Thus, based on the 23 Y-STRs, only a subtle genetic variation was observed between populations. Previous studies had suggested a genetic cline from North to South for non-tribal populations in India9, however the same was not observed with the current set of Y-chromosome markers, which also corroborates the finding of Mondal et al.3.Similarly, discriminant analysis of principal components (DAPC) , R1b, E1b1b, E1b1ba and T) were observed in this study, whereas 7 other haplogroups , I2b1, J2a1h and N) mentioned in the haplogroup assigning tool were not observed in these samples. R1a (51.5%), H (16.2%) and L (15.8%) were the major haplogroups present throughout the country and accounted for more than three-fourths of the Y lineages. Figure 24. R1a haplogroup is reported to be the most frequent haplogroup present in Eurasia25 and was also observed to be the most abundant in all the major geographic regions of India in this study.The occurrence of R1a was observed to decrease from north to south, while the haplogroup L displayed the opposite trend. In contrast to R1a and L haplogroups, haplogroup H was found to be distributed uniformly across the country. In a previous study, clades of R1a, J2, H and R2 were observed to be centered in North, Northwest, South and East India, respectively and R haplogroup and its clades were amongst the most frequent Y lineages found throughout India, East Europe and Central Asia12 and is known to be widely distributed in North Eurasia and in some Siberian groups26, with lower representation in populations of Europe, Middle East and East Asia25. Haplogroup H, which was suggested to be restricted mainly to Indian subcontinent25, was observed in 16.2% of individuals in the current study  in South India. Haplogroup L is thought to be associated with the expansion of farming% in Sout24 whereas the occurrence of J1 haplogroup is believed to be rare4 and its presence was mainly attributed to the paternal gene pool contribution during Islamic expansion from Iranians and/or Arabians in the past27. Haplogroups J2a1b and J1 were represented by only one individual in the present study. G2a, another rare haplogroup was observed in only 3 individuals (1.3%) and was absent in individuals from western and eastern parts of India. Since these haplogroups were based on predictor algorithm, caution has to be exercised while drawing interpretations based on these tools. Nevertheless, the use of large number of STRs (>17 loci), which was the case in this work, is able to provide a reasonable estimate of haplogroup prediction28, as is being supported by earlier studies based on Y-chromosomal STRs29.Haplogroups J2b and J2a1 x J2a1-bh were the most prominent among the other branches of J2 in the Indian populations observed in the current study. The presence of J2 clades in India was suggested primarily due to the demic diffusion from West Asia20. The multidimensional scaling (MDS) plot  and Baltic  populations as well, which needs further investigations involving Y-SNPs and other ancestry informative markers to better understand the significance of this finding.Our findings are in agreement with previous anthropological and linguistic reports supporting genetic similarity of Romanis and IndiansST based genetic relationship with other neighboring as well as few European countries was visualized in the heatmap presented in Supplementary Fig. 36.To examine the genetic relationship of the populations tested in the current study with the Indian populations reported previously in Y Chromosome Haplotype Reference Database (YHRD), MDS analysis was performed, which showed very low genetic distance between them. Further, R19.On a different perspective, the utility of the 23 Y-STR chemistry for its forensic applicability in India populations was also investigated. High haplotype diversity (HD) (0.9948793876) and discrimination capacity (DC) (0.98511166253) values demonstrated its informativeness in the Indian populations. As expected, this panel exhibited a low combined match probability (CMP) (0.00264578799), which was comparable to the previously published reportslSTR Yfiler, Thermo Fisher Scientific, Waltham, USA) are shown in Supplementary Fig. Allelic distribution of the six newly incorporated Y-STRs, which were introduced in PPY23 system and were not part of the previous panel of 17 Y-STRs  and data was analyzed using the GeneMapper ID version 3.2.1 (Thermo Fisher Scientific). The control DNA 2800M was genotyped for quality control purposes. A certificate for quality assurance was obtained from the Department of Forensic Genetics at the Charite´–Universitätsmedizin, Berlin, Germany, which is a mandatory criterion for submitting the Y-STR data to the YHRD. The data was submitted to YHRD and 12 accession numbers were obtained, which are mentioned in Supplementary Table Individuals were genotyped for 23 Y-STR markers incorporated in PowerPlex Y23 (PPY23) system . The Y-STRs were amplified according to the manufacturer’s instructions in a GeneAmp 9700 thermal cycler  followed by capillary electrophoresis on the ABI Prism 3130pi is the frequency of i-th allele) and HD (HD = hi is the haplotype frequency) were calculated as per previous reports20. MSN was generated using poppr39 package implemented in R v3.1.2 to visualize the number of unique and redundant haplotypes. Arlequin40 was used to perform locus-wise AMOVA. For comparison of the genetic distance among the current populations as well as with that of the other populations reported in YHRD, DYS385a/b locus and the samples with micro-variants were omitted. GenALEx v6.542 was used to assess the molecular diversity of the Y-STR panel and to test the performance of the panel in each population. PCoA (based on the pairwise Nei’s genetic distance), to visualize genetic relationship among the populations was performed using GenALEx. Poppr package in R v3.1.2 was also used to perform DAPC.Four samples that were found to be biallelic at few loci were discarded and further analyses were performed on the remaining 403 samples. Allele and haplotype frequencies were calculated by counting method. GD (GD = ST and MDS was performed using YHRD-based online tool (http://www.yhrd.org) to infer the genetic relationship among populations. To test whether there was any association between the genetic and geographic distances among these populations, SAMOVA was performed43. RST values derived from pairwise comparison with other populations of the world were also inferred employing the YHRD tool. To investigate if the population substructure affects the Y-STR distribution, the geographic locations were considered as its representative and regression analysis was performed using the geographic distance between sampling locations as a covariate for the genetic distance (pairwise RST). The correlation between the geographic distance and the RST across all pairs of populations was also tested using R v3.1.2. Further, MDS plots were drawn using the sammon function from MASS package implemented in R v3.1.2 to visualize the genetic relationship between the populations in the current study with those reported earlier. Individuals were assigned respective haplogroups derived from Y-STRs using Whit Athey’s haplogroup predictor44. As recommended in the instructions for users in the Whit Athey’s haplogroup predictor tool’s website, minimum score and minimum probability to assign an individual to a particular haplogroup was set to 40 and 95 percent, respectively.AMOVA based on R45. The network analyses were carried out for the three most abundant lineages observed in this study. The variance at each locus for the haplogroups was calculated in the whole dataset using R v3.1.2. The weights assigned to each locus were inversely proportional to the observed variance as reported previously46. Briefly, weights for a range of variance were assigned as follows: for variance 0.0–0.2, weight = 10; for variance 0.2–0.4, weight = 8; for variance 0.4–0.6, weight = 6; for variance 0.6–0.8, weight = 4 and for variance >0.8, weight = 2. To view the spatial distribution of the major haplogroups, Surfer15 of Golden Software  was used to generate iso-frequency maps. To investigate the forensic applicability of the multiplex in the Indian populations, the sum of squared haplotype frequencies was calculated to obtain CMP of the panel of markers. DC i.e. the ratio between the number of unique haplotypes to the total number of haplotypes was calculated.Median joining (MJ) networks for Y-STR haplotypes within specific Y-haplogroups were constructed using the software NETWORK 5.0.0.1Supplementary Information


Prosopis alba Griseb. (Leguminosae), is a resource  that is strongly affected by changes in land use. A gradient in the level of disturbance is found moving away from the La Paz city toward less altitude areas. The main objective of this study was to characterize genetically three P. alba populations with different levels of human disturbance located at different altitudes in Bolivia, in order to provide some guidelines for management and conservation of these species. Based on 10 SSR loci, the populations showed high level of genetic diversity in comparison with other forest species. The population less disturbed and situated at the lowest altitude was the most variable (He = 0.51–0.42), whereas the less variable was the most disturbed and situated at the highest altitude. Heterozygote excess was observed in all populations. Most of genetic diversity (99%) is contained within populations. Genetic differentiation among populations is low (1%), suggesting low gene flow among populations. No evidence of recent bottlenecks events was detected. The estimates of the effective population size were low in all populations. The results are in agreement with the hypothesis that genetic diversity is reduced by the impact of anthropic disturbance in the population located at higher altitude in comparison with the lightly disturbed situated at lower altitude and farther from urban settlements.The fast expansion of human population around La Paz, Bolivia  triggered new suburban settlements in nearby areas in valleys and mountain feet. The white mesquite,  Tahuapalca , about 18 km SE of Mecapaca, is accessed following a hard‐winding road and shows almost no evidence of anthropic activities and environmental disturbance.We collected fresh young leaves samples from three populations of a Figure . Vouchera Figure  and eachP. alba Argentinean populations, these authors recommend sampling trees separated more than 50 m from each other in order to avoid collecting genetically related material. From 15 to 30 adult individuals adult trees were sampled in each location. The two populations closest to La Paz were relatively small and sampling size corresponded to the highest possible following the criteria applied. Population size in Tahuapalca was grater but trees were located on the slope of the mountain making collection very difficult. A total of 61 adult individuals were studied from the three populations.Collection method followed Bessega et al. , Bessegawww.softGenetics.com).Total genomic DNA was extracted using the Qiagen DNeasy Plant kit  from leaf material that was collected and stored in silica gel. The samples were genotyped at 10 microsatellite markers described by Mottura, Finkeldey, Verga, and Gailing , Mo05, M2.2Ia) and a slightly modified statistic which is independent of the number of loci (rd) , allelic richness (rA), the number of private alleles (aP), observed heterozygosity (Ho) and expected (He) and unbiased Nei's gene diversity (uHe) . Diversity measures and FIS were compared among populations and considering nonoverlapping 95% confidence intervals as significance criterion. The possibility that heterozygotes deficiency may be due to null alleles was tested by Monte Carlo with 1,000 randomizations as described by Guo and Thompson  Nei,  using the) Nei,  for R soe) Nei,  using thThompson  and the Thompson  with 10,Thompson .2.3GST  was partitioned into among populations (GST × TH) and within population (SH) using Nei and Chesser  of software R , using the Jombart,  (functio2.4k) given the sample size (n) under the assumption of mutation‐drift equilibrium. To determine whether populations exhibit a significant number of loci with gene diversity excess we used a sign test, the standardized difference  of Hill  as θNe = 0.5/θ  than in the remaining populations (aP = 2). The allelic richness (rA) also differs significantly between Tahuapalca and the remaining populations as the 95% confidence intervals do not overlap. Mean rAin Tahuapalca was 3.9 [CI95% = 3.1–4.2], 2.99 [CI95% = 2.6–3] in Mecapaca, and 2.99 [CI95% = 2.4–3] in Huajchilla. The mean expected heterozygosity (He) was similar in Mecapaca and Huajchilla (He = 0.44 and 0.42) but higher in Tahuapalca (He = 0.51).The 10 loci analyzed were variable with 2–9 alleles in Tahuapalca population and 1–5 alleles in Mecapaca and Huajchilla (Table Ho) was similar to He in Mecapaca (Ho = 0.44) and Tahuapalca (Ho = 0.51) whereas in Huajchilla Ho (0.52) was higher than He. Average FIS estimates were negative in all populations as well as their weighted mean (Table FIS estimates.Observed heterozygosity (Ho = 0.5 whereas p = 0.04), which are attributable to Tahuapalca only (p = 0.026), as in the other two populations the association index was non‐significant. However, after applying Bonferroni correction for multiple tests linkage disequilibrium was not significant in any case.The analysis of linkage disequilibrium in the whole sample yielded significant results (3.2GST = 0.029 and G'STH = 0.068 (Table GST = 0.209 and G'STH = 0.523)  and the remaining variation by the among population component (1%). The global estimations of genetic differentiation were K = 1, ln P(X/K) = −1,160.00 and −1,160.02, respectively). The lack of evidence of genetic discontinuities suggests no influence of historical events for these populations. When the analysis is performed adding the Argentinean populations, the number of clusters identified was K = 3 (ln P(X/K) = −3,098.00 and −3,087.06 for admixture and no‐admixture models). One of these clusters is represented by the trees collected in the three Bolivian populations, Tahuapalca, Huajchilla, and Mecapaca , whereas Huajchilla is differentiated from Mecapaca by the second PC (p = 1.15 × 10−7). The correspondence between the prior and the posterior classification of individuals in their respective populations varied from 93% in Huajchilla to 96% in Tahuapalca. The Canonical discriminant analysis based on the presence and absence of alleles was consistent with those of the DAPC . When DAPC is performed adding the Argentinean population, the tendency observed by global differentiation estimators  Figure a. The scC Figure . The fir3.3NeLD) showed low values in Tahuapalca (NeLD = 38) and Mecapaca (NeLD = 88), but failed to yield an estimate in Huajchilla based on the SSR analyzed loci (Table Ne based on group coancestry (θNe) was only possible in Huajchilla where θ resulted positive. The effective size estimation in this population is small, θNe = 72.9 (Table eN estimated from FIS (NeF) was 35.71, 17.85, and 2.39 for Tahuapalca, Mecapaca, and Huajchilla, respectively.The results of the analysis of recent bottleneck were not significant for the three populations according to any of the tests used, indicating that the loci analyzed do not depart from neutrality and the populations have not undergone a recent bottleneck Table . The res NeLD = 8 and Mec NeLD = 8 and Mec4P. alba forests which are overexploited for wood and nonwood (edible pods) resources. As original local communities are still dependent on the native resources, they are strongly affected by the expansion of urban boundaries and the change of human habits. Forest fragmentation is expected to yield geographic isolation and decline of genetic diversity within populations associated with genetic drift or inbreeding   . LDNe method is considered very robust  is small relative to Ne    studied by Bessega et al.  generations after the population size reduction . That means that in Tahuapalca the number of generations required to detect the maximum heterozygosity excess would be between 35–38 generations (based on Ne estimates obtained for this population from FIS and with NeEstimator). As P. alba trees of more than 300 years old have been recorded, it is not unexpected that possible bottlenecks produced by human disturbance are too early to be detected.In recent bottleneck, the rare alleles are the first to be lost diminishing the mean number of alleles per locus. In contrast, heterozygosity is less affected generating a transient excess of heterozygosity compared to that expected given the resulting numbers of alleles . The percent of genetic variance associated with among population differentiation, although significant, was low (1%). The genetic differentiation among populations was significant and both DAPC and canonical discriminant analysis clearly differentiate the individuals from different populations. On the other hand, the STRUCTURE analysis showed no structure for these populations and admixture within populations was only observed in Tahuapalca. The analysis with the admixture model shows some genetic similarity of Tahuapalca with the Argentinean populations studied by Bessega et al.  in the Valley of La Paz are able to disperse seeds in dungs  were described as possible disperser of P. flexuosa and P. chilensis . In  Bolgeri , the guaPicea glauca, where insufficient time for evolutionary forces to differentiate populations was proposed  among Bolivian populations. As these values are higher than 10% of Ne estimates, they may be considered as belonging to a single management unit. By contrast, gene flow between Bolivian and Argentinean populations would be less than one migrant per generation suggesting that each area should be treated as different MUs.The identification of management units (MU) from genetic data was reviewed by Palsbøll, Berube, and Allendorf , and the5Ne) of 70 has been suggested to avoid inbreeding depression for in situ conservation (Caballero, Bravo, & Wang, P. alba in Bessega et al. (Prosopis forest historically provide resources used by native communities, protection policies should be recommended applying monitoring strategies to ensure the rationale use of P. alba avoiding non‐sustainable harvesting for immediate economic benefits or habitat destruction for construction purposes which might jeopardize the ecosystems as a whole.The information obtained here has important implications for conservation and management purposes. Tahuapalca, the population situated at lower altitude and the minimal disturbance by anthropic activities has the higher diversity, what makes it worth protecting. Recently, a minimum effective population size (a et al. . As ProsThe authors declare that they have no conflict of interest.Conception or design of the work: C. Bessega, B. Saidman, J.C. Vilardi. Formal analysis and Methodology: C. Bessega, C. Pometti, J.C. Vilardi. Funding acquisition: C. Bessega, B. Saidman, J.C. Vilardi. Investigation: C. Bessega. Resources: C. Bessega, C. Pometti, R. Fortunato, RP Lopez, DM Larrea Alcazar. Interpretation of data for the work: C. Bessega, C. Pometti, R.P. López, D.M. Larrea‐Alcázar, R. Fortunato, B.O. Saidman, J.C. Vilardi. Writing—original draft: C. Bessega, C. Pometti, R.P. López, D.M. Larrea‐Alcázar, R. Fortunato, B.O. Saidman, J.C. Vilardi.Upon article acceptance, original data including sampling locations, and microsatellite genotypes will be archived in the public repository Dryad.


Liriomyza is a large genus that includes polyphagous and invasive species , and oligophagous species such as L. Chinensis in China. Effective control of these invasive and oligophagous species is not easy due to the fast invasion rate, interspecific competition, and pesticide resistance. In this study, we investigated population genetics of five Liriomyza species L. trifolii, L. sativae, L. huidobrensis, L. bryoniae, and L. chinensis based on COI and EF-1a genes, and microsatellite DNA. These five Liriomyza species revealed highly conservative characteristics in the COI gene among populations collected from different geographical regions and host plants. By contrast, the mutation rate of the EF-1a gene was higher than COI, and phylogenetic tree based on EF-1a showed that haplotypes of L. trifolii and L. sativae were not distinguished well. Genetic differentiation in microsatellite loci was obvious among the five species. Our results also indicated that geographic isolation had a greater impact on genetic differentiation in L. trifolii than the host plant. Populations of L. trifolii in China showed a high to moderate level of genetic differentiation and they had divided into two groups representing the coastal areas of southern China and northern regions. The genetic diversity of the southern group was higher than the northern group. We speculated that the invasion of L. trifolii likely occurred in southern regions of China and then spread northward. Bottleneck analyses revealed that the L. trifolii population in China was in a steady growth period. Liriomyza is one of the largest genera belonging to the subfamily Phytomyzidae, family Agromyzidae, and order Diptera, consisting 330 described species12. Among these, 160 species are harmful in field crops or ornamental plants13, and 23 species are of great economic significance8.16. It has been speculated that host specialization has resulted in many new species in polyphagous Liriomyza that are highly adaptable to environmental stress18. To determine population genetic structure and migration patterns in L. sativae, several research groups analyzed different populations in China using fragments of ITS1 and β-tubulin genes and microsatellites20. In a study of Wang21, nuclear rDNA-ITS2 and mitochondrial COI sequences were used to analyze population differentiation in several invasive leafminer populations. It has been showed that populations of L. trifolii had separated into one clade representing the United States populations and a second clade for Asia-Europe populations, and a low level of differentiation was observed in domestic populations. However, mtDNA and ITS may not be the most suitable molecular markers for genetic differentiation analysis, because mitochondrial genes are highly conserved among intraspecific populations of insects and ITS is not suitable for analysis of intrageneric populations20. Microsatellites marker is a highly polymorphic co-dominant molecular marker with many characteristics, such as low requirements for DNA quality, good repeatability, simple detection methods, etc., and therefore it has been well applied in studies on population genetic structure, genetic relationship identification, genetic map construction and gene mapping to explore the population genetics, molecular systematics and ecology22. But there were a few researches using microsatellite marker technology to unfold the population genetic structure in Liriomyza especially for these invaded species14.Due to the small size, rapid interspecific competition, invasion rates, and adaptability, insects are sensitive to geographic isolation, hosts and phenological niches that cause species differentiationLiriomyza have generally involved only a single species14, with only a few comparative studies on genetic relationships among species21. In this study, we investigated intraspecies genetic differentiation in L. trifolii and interspecies variations among five species in Liriomyza in order to understanding better the species diversity during the geographic isolation and population expansion. Five species, namely L. trifolii, L. sativae, L. huidobrensis, L. bryoniae, and L. chinensis, were collected from 38 cities in 11 provinces of China. Population genetics differentiations of Liriomyza from different regions of China and host plants were evaluated using COI, EF-1a and microsatellite polymorphisms.Previous studies on the population genetic structure of COI in L. trifolii populations was conserved with consistent characteristics among populations from different geographical regions and host plants. The maximum haplotype number among L. trifolii populations was three, and most haplotypes had only a single base difference. L. sativae populations showed slightly more diversity, and the maximum number of haplotypes among three L. sativae populations was six. The populations of L. huidobrensis, L. bryoniae and L. chinensis showed relatively low diversity (Table Haplotype and nucleotide diversity of ty Table .EF-1a was relatively high among intraspecies (e.g. L. trifolii) as compared with COI. Ten haplotypes were found in the ZZJD, HLJD and HSFQ populations of L. trifolii, and the CSJD population had the highest nucleotide diversity. The other four Liriomyza spp. also showed relatively high diversity in EF-1a (Table Haplotype and nucleotide diversity of 1a Table .L. trifolii populations ranged from 6.625 (DGJD) to 3.37 (HLJD). The average effective number of alleles (Ne) of L. trifolii populations ranged from 4.3885 (CXJD) to 1.9154 (SQNGMZ). The observed heterozygosity (Ho) values of ten L. trifolii populations were greater than 0.5, and the highest Ho was 0.6771 in the BLJD population; the remaining nine populations had Ho values less than 0.5 and the lowest was 0.3125 in the HLJD population. L. huidobrensis, L. bryoniae and L. chinensis had a low heterozygosity. Populations of different hosts in the same geographic region  showed a great degree of similarity in Na and Ho. Most populations were deviated from the Hardy-Weinberg equilibrium  in um Table .COI haplotypes  were compared based on 8 microsatellite loci  had high levels of interspecific genetic differentiation in microsatellite loci, although the species were similar in terms of morphology, niche occupation and feeding habits , and there were only six populations  and nine populations with a statistically significant heterozygotes under the two-phase model (TPM) and the infinite allele model (IAM)  Table , respect23. In this study, the phylogenetic tree, pairwise FST, and STRUCTURE analysis indicated that the degree of differentiation and direction of nuclear and mitochondrial genes were not completely consistent. COI in the five species of Liriomyza showed very conservative characteristics, but the mutation rate of EF-1a gene was relatively higher, and phylogenetic tree results showed that haplotypes of L. trifolii and L. sativae were not distinguished well. The results of microsatellite analysis showed that genetic distances among the five species of Liriomyza were significantly much longer than those within L. trifolii populations. In short, the five Liriomyza species showed high levels of genetic differentiation in mitochondrial and nuclear genes, and the interspecies differentiation in nuclear genes was obvious. COI and EF-1a gene were suitable molecular markers for interspecies genetic differentiation analysis and not for intraspecies of Liriomyza species, because COI as a mitochondrial gene and EF-1a as a reference gene are highly conserved among intraspecific populations of the five Liriomyza species. Microsatellites marker were suitable molecular markers for both interspecies and intraspecific genetic differentiation analysis of the five Liriomyza species, because microsatellite analysis showed both interspecies and intraspecific genetic differentiations among the five species of Liriomyza.Population genetic structure and diversity are important factors affecting the survival and adaptability of invasive species. Population genetics in many pests were studied to find out their invasion and transmission routes5. We found that geographic isolation had a greater influence on genetic differentiation within L. trifolii, which is consistent with previous results for L. Sativae14, but we did not find obvious influence of host plants on genetic differentiation in these species. We hypothesize that host plants have not yet driven reproductive isolation among populations, so the gene exchange among populations on different hosts occurs frequently.Spencer (1964) suggested that host specialization caused the development of many new speciesL. trifolii in China were in a high or moderate degree of genetic differentiation. Populations of L. trifolii could be divided into two groups, one from coastal areas of southern China and the other from northern China including Jiangsu and Zhejiang provinces. The genetic diversity of the southern group was higher than the other group, so the invasion of L. trifolii likely occured in southern regions of China and then spread toward northward. Bottleneck test analysis showed that the L. trifolii population in China was in a steady growth period, which was similar as L. sativae14. Genetic variation may lead to the rapid adaptation of insects to new environments and contributes to population establishment and spread. Our study has produced information on the geographical distribution of genetic variation of five Liriomyza species in China that may also help in management programs of these important pests.The results of genetic differentiation and structure analysis showed that most populations of Liriomyza individuals , nucleotide diversity (p), and the mean number of pairwise differences were calculated to estimate DNA polymorphism using DnaSP 5.026. Analysis of F-statistics (Fst) and genetic differentiation were performed using Arlequin v. 3.527 with 10,000 permutations. Phylogenetic relationships were deduced by Bayesian inference (BI) and maximum likelihood (ML). Phylogenetic trees were constructed using MrBayes v. 3.1.128 and a PHYML online web server29. For BI, nucleotide alignments were constructed using the MrBayes program with 20,000,000 generations and with the first 5000 discarded as burn-in. Support values for trees generated by BI were expressed as Bayesian posterior probabilities in percentages. ML analysis was performed by Mega 6.030. Tree information was visualized and edited using Treeview. The haplotype network was performed using NETWORK v. 4.632.The 33 including the number of alleles (Na), the effective number of alleles (Ne), and observed (Ho) and expected heterozygosity (HE), as well as Nei’s genetic distance and genetic similarity. Deviation from Hardy-Weinberg equilibrium and linkage disequilibrium at each locus were calculated using GenePop v. 4.0 (http://wbiomed.curtin.edu.au/genepop/). The polymorphic information content (PIC) was calculated using Cervus 2.034. Differentiation indices (FST) were calculated using ARLEQUIN 3.527. A phylogenetic tree based on Nei’s genetic distance was constructed using the unweighted pair group with the arithmetic mean (UPGMA) method of PHYLIP v. 3.6935. Bootstrap values were calculated using 1000 replicates. To assess the population genetic structure, we used Bayesian model-based clustering analysis with STRUCTURE v. 2.3.336. We specified an initial range of potential genotype clusters (K) from 1 to 10 under the admixed model and the assumption of correlated allele frequencies among populations. For each value of K, ten runs were performed with 100,000 iterations discarded as burn-in followed by an additional 10,000 iterations. The most probable number of K values in the data was detected by comparing the log probability of the data lnP (D) for each value of K across all ten runs of Structure and by examining the standardized second-order change of lnP (D) and ΔK37. For selected K values, CLUMPP v 1.1.238 was used to align cluster membership coefficients from ten replicates of cluster analyses using the Greedy algorithm with 10,000 random input orders; the results were then graphically displayed with DISTRUCT v. 1.139. We also analyzed our data with the GENELAND package40 to further investigate the number of populations and the spatial location of genetic discontinuities between them. K was allowed to vary (1 to 10) with 100,000 MCMC iterations, and uncertainty was attached to spatial coordinates fixed to 1 km, and then the fixed modal K was obtained with the other parameters unchanged. A potentially significant heterozygosity excess (the signature of a bottleneck) was detected using a Wilcoxon signed rank test, as implemented in Bottleneck v. 1.241. When a population experiences a reduction of its effective size, it generally develops a heterozygosity excess at selectively neutral loci. Previous analyses have shown that the most useful markers for bottleneck detection are those evolving under IAM, and they provide guidelines for selecting sample sizes of individuals and loci44; meanwhile, the TPM is thought to more closely simulate microsatellite mutation45. Unlike the SMM, which predicts all mutations corresponding to the increment or decrement of a single base-pair repeat, the TPM predicts the occurrence of an occasional multiple base-pair repeat42. The strict SMM is obviously the most conservative model for testing for a significant heterozygosity excess caused by bottlenecks, because in some conditions it can produce a heterozygosity deficiency, and due to the heterozygosity excess it is always lower than other mutation models. Because the actual mutation model followed by our microsatellites is unknown, we ran the program Bottle neck under the IAM, SMM, and TPM to determine whether these populations recently experienced a population decline or not.Fundamental genetic parameters were calculated for all eight loci using POPGENE v. 3.2Supplementary Tables


Coregonus albula), sympatric to common autumn‐spawners, have declined or disappeared; for example, three out of four known spring‐spawning populations in Sweden are regarded as extinct. Over the same period, the climate has changed and populations have been subject to other anthropogenic stressors. We compared historic (1960s) and recent (1990–2000s) morphological data from the still‐existent sympatric cisco populations in Lake Fegen, Sweden. Phenotypic changes were found for spring‐spawners making them more similar to the sympatric autumn‐spawners that had remained virtually unchanged. Based on results for other salmoniform fishes, a phenotypically plastic response to increased temperature during early development appears unlikely. The recent material was also analyzed with microsatellite markers; long‐term effective population size in spring‐spawners was estimated to be about 20 times lower than autumn‐spawners, with signs of long‐term gene flow in both directions and a recent genetic bottleneck in spring‐spawners. We suggest the change toward a less distinct phenotype in spring‐spawners to reflect a recent increase in gene flow from autumn‐spawners. Time since divergence was estimated to only c. 1,900 years , but still the Fegen populations represent the most morphologically and genetically distinct sympatric populations studied. Consequently, we hypothesize that less distinct population pairs can be even younger and that spring‐spawning may have repeatedly evolved and disappeared in several lakes since the end of the last glaciation, concurrent with changed environmental conditions.During the past 50 years, Fennoscandian populations of spring‐spawning Baltic cisco ( We compared historic (1960s) and recent (1990–2000s) morphological data from the still‐existent sympatric cisco populations in Lake Fegen, Sweden. Phenotypic changes were found for spring‐spawners making them more similar to the sympatric autumn‐spawners . The recent material was also analyzed with microsatellite markers. There were signs of ongoing gene flow in both directions, and the change toward a less distinct phenotype in spring‐spawners likely reflects increased gene flow from autumn‐spawners. In these cases, a common autumn‐spawner typically coexists with a spring‐ or winter‐spawning population  lakes compared with other parts of Sweden, regardless of spawning time  have been explained by extrinsic factors such as pollutants, eutrophication, and introduction of non‐native fish species , only some 2%–4% of the 2014 catch were classified as spring‐spawners . There are also some records  and more recent (1990–2000s) morphological data from Fegen to changes in local temperatures over the same period, discussing a possible eco‐phenotypic response directly or indirectly related to temperature by means of plasticity and (or) microevolution. Microsatellites markers were used to study genetic structure and amounts of gene flow. We further estimated effective population sizes, and searched for signs of genetic bottlenecks, to investigate whether elevated gene flow could potentially explain observed phenotypic changes. The time since divergence between the two Fegen populations was also estimated. By combining data from detailed morphological and genetic analyses with results from previous studies of other sympatric Baltic cisco populations, an overall aim was to gain further understandings of the evolution, maintenance, and possible reasons for recent collapses of these two‐population systems.22) is situated 132 m above the sea level in Southern Sweden  was included in the genetic study by Delling et al. (SS) and 100 autumn‐spawners (AS) from Fegen collected in 1960–1969  individuals that could be strictly classified as AS or SS , but also specimens found to be ripe but not running (SSr and ASr), and some fish with unknown or uncertain gonadal status that were immature and/or collected outside the spawning seasons  and time of capture, or from DNA (microsatellites) and morphology with the suffix mg (morphometry and genetics).The historical material was collected during spawning from “ripe and running” , eye diameter (Ed), and head length (Hl), with SS possessing fewer vertebrae, a proportionally larger head and larger eye.Based on Svärdson , the maiTl) and standard length (Sl) were measured . Sex for mature specimens (rr or r) was determined in the field or at the laboratory shortly after capture. For the remaining unclassed specimens, sex was determined during final morphological analyses.Both total length (Tl was measured to the nearest 1.0 mm from the anterior tip of the head (tip of lower jaw in the case of ciscoes) to the posterior tip of the caudal fin, with both fin lobes folded back. Sl was measured with a digital caliper to the nearest 1.0 mm from the anterior tip of the snout to the end of the caudal peduncle. Head length (Hl) was measured point to point with a digital caliper to the nearest 0.1 mm from the tip of the snout (upper jaw) to the posterior margin of the operculum .The majority of recent specimens were analyzed in a frozen (slightly thawed), fresh condition. Measuring the size of the eye  is notoriously tricky, and repeated trials often result in deviations. However, using X‐ray, the sclera of the eyeball in the anterior and posterior margin of the eye is clearly visible, and the horizontal eye diameter can be measured with a high degree of accuracy, using a reference length for calibration Figure . The numNo documentation seems to exist on how morphological measurements and counts were obtained for the historical materials, and no such specimens from Fegen have been preserved. Thus, only original protocols with individual data have been available for the purpose of this study. Besides the variables measured for the recent specimens, the historical materials also included data on gill raker and scale counts, snout length, body depth, snout to dorsal origin distance, and snout to pelvic origin distance  in the historic data. The relation between Vc and Hl was also investigated to confirm that the larger head in SS was not the result of a proportionally shorter body due to fewer vertebrae  using the software SYSTAT13. Comparing the resulting principal components to standard lengths, showed that the second component (PC II) could be treated as a size‐independent morphometric “shape” variable  from Svärdson .We compared historic data on eye diameter  was performed with  Goudet,  was usedstructure 2.3.4  in the total material. K was increased from 1 to 5, with true K inferred following Evanno, Regnaut, and Goudet  based on their closeness to the observed data at a set of 17 “summary statistics”  computed within subpopulations and for the total material. Posterior parameter estimates with associated probability densities were assessed using nonlinear regression . Notably, only three out of 248 specimens sampled as ripe and running (rr) or ripe (r) deviated from its expected group, according to the division based on independent morphologic–genetic data  spawning time, (b) morphology, and (c) nuclear genetic markers, but none of these independent data sets can alone be used to divide all fish into well‐separated groups. Combining morphologic and genetic data, however, significantly enforced the distinction between the two forms Figure , and sin3.1SS have significantly fewer vertebrae than AS, with just minor year‐to‐year variation within each group . Comparing vertebral counts from several lakes showed that SS often have lower counts compared with sympatric AS, but that this difference was most prominent in Fegen , and there exists an apparent correlation between the increase in air temperature and that for SS vertebral counts , that is, more commonly in SS (13.1%) compared with AS (3.5%) (Fisher's exact test: two‐sided p < .001).The average number of vertebrae in S Figure . As a coS Figure . Over ths Figure . AnomaliHl against Tl and Ed against Hl) for the recent and historical materials separately showed a trend toward less distinction between SS and AS for Ed over time, particularly in females  for both sexes combined revealed a marked temporal difference in SS but just a minor difference in AS . Parallelism in the AS data set, allowing for ANCOVA, indicated a small but significant difference in Ed over time (p = .006). It is, however, hard to judge whether this is a true difference or an artifact related to the adjustment needed for the historical Hl data  revealing a true change in SS eye diameter over time.A series of biplots Figure  on morphs Figure . PlottinS Figure . Tests fS Figure a preclud3.2structure based only on microsatellite genotypes yielded highest likelihood for two genetic clusters . Significant allele frequency differences among SSmg and ASmg occurred at all but one locus and in total, with an overall FST of 0.07 .The average number of alleles observed, allelic richness, and expected heterozygosity was higher in BWF1) was identified as a putative outlier, displaying higher differentiation between SSmg and ASmg than expected under selective neutrality . Observed gene diversity (HE) in both populations was found to be lower than the levels expected under mutation‐drift equilibrium (HEQ), that is, a pattern in the opposite direction as anticipated for populations following a genetic bottleneck where HEQ is expected to be reduced faster than HE , whereas HE and HEQ were not significantly different in SSmg , is a general pattern in Swedish ciscoes , the observation of HE ≈ HEQ is actually in line with what to be expected following a recent bottleneck.Signs of a genetic bottleneck were seen for spring‐spawners. The Garza–Williamson M‐ratio Table  was consg et al.  revealeds Figure . Thus, ibayesass (8 loci) yielded almost identical parameter estimates and Bayesian deviances, and all chains were therefore merged before final analysis using tracer v. 1.6  being twice as high as in the opposite direction (0.008 vs. 0.004) although with highly overlapping probability intervals (Table The five runs with ls Table .popabc (8 loci) under an isolation with migration model were almost identical to the contemporary estimates  compared to ASmg . Time since divergence was estimated to 486 generations  corresponding to 1,944 years  estimates of immigration rates obtained with es Table . The est4SS) Fegen population, manifested as an increased number of vertebrae and a decreased relative eye size from the 1960s to the 1990s. In contrast, the sympatric autumn‐spawning (AS) population has remained virtually unchanged. Analyses of microsatellite data show lower allelic richness and signs of a genetic bottleneck in the SS population. The same genetic data further reveal a clear difference in long‐term average effective population size (NE) between the sympatric populations (SS < AS) and low levels of gene flow in both directions.Our results reveal rapid phenotypic change in the spring‐spawning , it is striking that after 1990 there are no annual means below 6°C  in relation to temperature . Tånig's results showed that it required an increase of as much as 5°C to increase the average Vc in trout by one. Lowest counts were found around 6°C, and a decrease in temperature also resulted in a slight increase of vertebral counts in six out of eight crosses, that is, a so‐called V‐shaped response  rather showed a negative response.Although fluctuations between years in average air temperature close to Fegen Figure  have beeC Figure  reviewed Tåning, , are proLindsey, . HoweverAS spawned at around 6°C during the autumn circulation whereas SS spawned at about the same temperature during early stratification after the spring circulation. Early development and hatching take place in late spring and early summer in both forms, although a narrower first growth zone on the scales indicates that SS hatch somewhat later than AS . Furthermore, assuming that Vc in C. albula responds to temperature much more strongly than in S. trutta, one would also have expected larger variation between years within both populations. In conclusion, when comparing to studies of other species, the increase seen for Vc in Fegen SS (c. 1.8) appears much too large to be explained by an increase in air temperature of just about one degree .Runnström  studied 4.2SS is microevolution involving natural selection, random genetic drift, and/or increased gene flow from AS into SS. Leary, Allendorf, and Knudsen (Vc and other meristic traits in rainbow trout (Onchorynchus mykiss), suggesting that genetic change could indeed explain the increase in Vc for C. albula. However, we are not aware of any similar heritability studies with respect to eye diameter (Ed).The alternative to effects of temperature on phenotypic traits in Fegen  Knudsen  reportedGasterosteus aculeatus, evolutionary rapid phenotypic changes explained by altered natural selection regimes have been documented  led to breakdown of reproductive isolation between the two whitefish forms that collapsed into a more morphologically and genetically homogenous population within just 15 years. Thus, some kind of microevolutionary explanation to the present observations appears feasible.For three‐spined stickleback, SS and AS are in fact adaptive and related to ecological niche separation. There is a tendency with lower vertebrae counts in SS for all studied population pairs  into a larger head and feeding apparatus might give an advantage for the offspring when competing with AS that hatches somewhat earlier in spring. According to Figure SS in Lake Ännättijärvi had larger heads than their sympatric AS, even though not clearly stated by the author. Among the four known population pairs in Sweden, however, a larger head in SS is only found in Fegen, whereas SS in Ören and Åsunden (no data for St Hålsjön) on average displayed c. 1% smaller heads in relation to Tl, compared with their sympatric AS  in only two cases (Fegen and Ännättijärvi) . Taken together, however, even if natural selection could be responsible for the phenotypic differences between SS and AS, it seems unlikely that a marked and sudden change in the selection regime may have caused the observed rapid retrogression of SS into a more AS‐like morphology.A negative relationship between relative eye size and individual growth rate has been reported for SS  in both directions, despite a larger than 20‐fold difference in long‐term average effective population sizes  including SS and AS from Fegen  than observed herein . The allozyme data were collected in 1986 and 1989, that is, between the presently analyzed historical and recent materials, where the latter was collected mainly in 2007–2008 . However, so far pikeperch appears to be relatively scarce, especially in the deeper NE lake basin where the SS population resides  during the warmer Eemian interglacial period. However, supported by genetic and geological data, Delling et al. . In German Lake Stechlin, only subtle morphological differences were found among the sympatric ciscoes and FST estimated across six microsatellites was just 0.004  should be done with caution, and so far few such cases in SS populations in recent decades represent a rapid loss of biodiversity within the far from fully understood C. albula complex. Further studies of ciscoes from additional Fennoscandian lakes, that is, in Finland, possibly still inhabited by sympatric C. albula populations, appear urgently needed to gain further knowledge on these interesting populations.Even though we suggest that these sympatric cisco populations could appear almost ephemeral in evolutionary terms, the extinction and decline of None declared.B.D. and S.P. designed the study. B.D performed the morphological work, whereas S.P. analyzed molecular data. B.D. and S.P. performed joint analyses of morphologic–genetic data and drafted the manuscript.


Charadrius alexandrinus and the enigmatic White-faced Plover C. dealbatus – which display strong plumage differentiation, yet show minimal genetic divergence based on previous mitochondrial and microsatellite work. Two scenarios may lead to this situation: (1) they represent clinal or poorly diverged populations with limited genomic differentiation despite substantial plumage variation, or (2) they are diverging taxa at the cusp of speciation, with ongoing limited gene flow obliterating signals of differentiation in traditional genetic markers. We compared the genotypes of 98 plovers  sampled in eastern Asia and Europe using ddRADSeq to harvest over 8000 genome-wide SNPs. In contrast to previous studies, our analyses revealed two well defined genomic clusters, with limited hybridization and a narrow contact zone. We also uncovered significant differences in bill length and further sex-specific differences in size, which may signal differences in mate choice between Kentish and White-faced Plovers. Our results support the hypothesis that this shorebird duo is on the verge of speciation.Genetic isolation of populations over evolutionary time leads to the formation of independent species. We examined a pair of shorebirds – the Kentish Plover  Firstly, why, if species have descended from other species by insensibly fine gradations, do we not everywhere see innumerable transitional forms? Why is not all nature in confusion, instead of the species being, as we see them, well defined?” – Darwin (1859)1“2, with allopatric barriers being its most well recognized driver3. However, there is now growing recognition that variation in intensity of sexual selection or preferences for different traits may also lead to species divergence5. Speciation can occur extremely rapidly over the course of a few generations6 or over long time scales, and may or may not be accompanied by gene flow from overlapping congenerics7. Consequently, young species can often be difficult to distinguish from divergent populations10. Biologists often conservatively use the term ‘taxon’ to refer to difficult cases in which there is no consensus on whether a lineage qualifies as a full species or is merely a divergent population.Speciation is the evolutionary process by which populations differentiate to become distinct species. The formation of barriers to gene flow plays an important role in the speciation process14. Charadrius plovers, one of the core clades and the name-sake group, have been an important study subject in evolutionary and ecological research given their unusual diversity in mating and parental care systems, even within a single species16. This variation in breeding behaviour has also been linked to population differentiation and diversification, whereby monogamous breeding systems in plovers are thought to be key promoters for population divergence whereas polygamous behaviour may instead slow down divergence5. The advent of Next-Generation Sequencing (NGS) technologies provides us with powerful tools to investigate differentiation across plovers from a genomic perspective17.Shorebirds (order Charadriiformes) are an old avian lineage with high behavioural and morphological diversityCharadrius as an extremely well-studied bird genus, the last few years have seen the discovery of novel populations and taxa18. Among these, Kennerley et al.19 documented the discovery of a distinctly-plumaged East Asian population of the Kentish Plover Charadrius alexandrinus complex that was shown to refer to the generally synonymized taxon name dealbatus. Several aspects regarding the breeding plumage of this rediscovered taxon, such as the extent of white on the face, and minor differences in morphology, render it as distinct as many universally recognized plover species20, which has led to its occasional recognition as an independent species named White-faced Plover C. dealbatus . However, a first molecular inquiry using mitochondrial DNA and microsatellites on museum specimens found no evidence of genetic differentiation between White-faced and Kentish Plovers20. While the two taxa overlap widely in their Southeast Asian winter distribution . Our taxon sampling covers a broad geographic range to investigate the magnitude of differentiation and dynamics of the contact zone, and includes a densely sampled coastal transect in China, a population from the western distribution end of Kentish Plovers in Spain, and a population from another East Asian subspecies nihonensis that inhabits island archipelagos at the northeastern end of the Kentish Plover breeding distribution. Our sampling incorporates a comprehensive dataset of body measurements to explore whether biometric changes correlate with the genomic clines. Our objective is to establish the nature of genomic connectivity between these two taxa to ascertain how and if two such divergent plumage phenotypes can be maintained in the presence of gene flow.Here we investigate the two possible scenarios by examining the patterns of genomic differentiation between plovers along the east coast of China. We used a genotyping-by-sequencing approachSTRUCTURE and PCA (see below).We recovered a total of 1,729,307,240 paired-end 150 bp reads from Illumina sequencing of 122 plover samples. Preliminary filtering of the sequencing data included manually removing seven individuals with poor sequencing coverage (less than one million reads). Each of the remaining 115 samples had a mean sequencing depth of 139x. A further nine individuals were removed in PLINK 2.0 as they exhibited more than 30% missing stack data, whilst eight additional individuals that showed evidence for first or second-order kinship with another individual were also pruned. This yielded a final dataset of 98 individuals and 8088 SNPs. The total genotyping rate was 0.990466. Of these 98 individuals, 59 were Kentish Plovers, 35 were White-faced Plovers and four consistently displayed genomic signatures intermediate between the two taxa in both STRUCTURE showed a primary division between Kentish Plovers and White-faced Plovers, and subsequent division between allopatric subspecies alexandrinus (the Chinese mainland and Taiwanese samples) and nihonensis  and the minority were Kentish Plovers . More importantly, when we considered only records from the breeding season . Conversely, in southern Zhejiang, 78% of breeders were Kentish and only 22% were White-faced Plovers  plovers sampled were Kentish Plovers Fig. . The remSTRUCTURE results. White-faced and Kentish Plovers separated along PC1, with White-faced Plovers forming a tight cloud, whereas Kentish Plovers were more broadly dispersed along both axes  were consistent with the xes Fig. . The disSTRUCTURE results, with White-faced Plovers displaying high genetic divergence and population differentiation from all Kentish Plover populations. Within the Kentish Plover populations, the Japanese population (nihonensis) consistently appeared to be the most distinct, whilst divergences of Spanish and Western Chinese populations mirrored their geographic distance from other populations.Our summary statistics also echoed the The results of all Shapiro-Wilk tests for normality of the morphological traits were non-significant . Two way ANOVAs showed that White-faced Plovers had longer bills than Kentish Plovers   hybrids among our samples of breeding birds, indicating that gene flow, while present, is rare between these two taxa. Our results favour a narrow contact zone resulting in two lineages with deep genomic differentiation, rather than a genetic cline from one form to the other Fig. .Their pronounced differences in breeding plumage coloration are matched by different bill sizes and sex-specific differences in tarsus, wing and full length measurements, hinting at differences in the intensity of sexual selection between the two taxa. Future research into differences in the reproductive behaviour of these two young taxa may shed light on the evolution of sexual traits in these two shorebirds.Charadrius alexandrinus complex , mainly in China across a coastal transect spanning the breeding distribution of the two forms (n = 87), but also including samples from Taiwan (n = 18), Japan (n = 10) and Spain (n = 7)  Table . We capt37. We used a Qubit® 2.0 Fluorometer to quantify DNA concentrations of extracts.The following procedures were approved by National University of Singapore’s Office of Safety, Health, and Environment. We extracted DNA either with DNEasy Blood & Tissue Kits (Qiagen) using the manufacturer’s recommended protocol or using an ammonium salt method38) as per Tang et al.23. We split samples into total DNA yield bands between 170–500 ng, based on post-extraction concentrations. We then calculated input volumes for the first restriction step based on these cut-off values. We used the restriction enzymes EcoRI and Msp1 (New England Biolabs Inc.) to double digest the samples for 3.5 hours at 37 °C, followed by clean up using a 1.1X ratio of Sera-Mag SpeedBead Carboxylate-Modified Magnetic Particles (Thermo Scientific). We then quantified samples again and ligated unique barcodes (PIE adaptors) to the fragments using T4 DNA Ligase (New England Biolabs Inc.) at 16 °C for 16 hours.We performed double digest restriction enzyme associated DNA sequencing  using a 1.5X bead ratio, and then carried out size selection for the seven pools using a Pippin Prep Gel Electrophoresis system (Sage Science) to isolate fragments for a sample peak of 420 base-pairs in length. After another subsequent AMPure XP clean up, we amplified size-selected fragments using a polymerase chain reaction (PCR) for 12 cycles, followed by a final AMPure XP clean up step. We screened pools for quality control on a Fragment Analyzer  and then quantified pools on a Qubit 2.0 Fluorometer before creating two final libraries of pools in equimolar proportions. We submitted the DNA libraries to Novogene  for 150 bp paired-end sequencing using the Illumina HiSeq X Ten platform.process_radtags command in STACKS v1.3439. We removed samples with less than one million reads from subsequent analysis. We aligned the sequence reads of the remaining 115 samples against the congeneric Killdeer (Charadrius vociferus) genome assembly40 using BWA-MEM41.We used FastQC (Babraham Bioinformatics) to analyze sequence quality across all base positions. Demultiplexing was then performed using the ref_map.pl in STACKS to call single nucleotide polymorphic markers (SNPs), employing a minimum stack depth of 10 in our analyses. We ran the ‘populations’ module to retain loci present in more than 90% of individuals, whilst assigning all individuals to a single population. To reduce the effects of linkage disequilibrium in subsequent analyses, we only accepted one SNP from each locus using the –write_single_snp option provided.We used the pipeline 42 to remove any individuals exhibiting more than 30% missing data, and then to further filter SNPs to account for missing data and linkage disequilibrium. We checked for SNPs under selection using BayeScan43.We ran PLINK 2.044 to estimate pairwise kinship coefficients using maximum likelihood estimation. We removed a single individual from each pair which displayed a kinship coefficient above 0.125 (second order kinship). We then re-ran the populations module in Stacks v1.34 and re-ran PLINK 2.0 without filtered individuals/loci to generate the final dataset.We used the R package, SNPRelateSTRUCTURE v2.3.445. First, we removed any singleton or doubleton alleles46 using a minimum allele count filter in PLINK 2.0. We then implemented STRUCTURE runs using the remaining 5639 SNPs without a priori hypotheses of cluster membership. We ran STRUCTURE from K = 1 to K = 10 with five iterations per K. For each iteration we implemented a burn-in of 100,000 generations and MCMC for 500,000 generations. We used STRUCTURE Harvester Web v0.6.9447 to process the output and subsequently averaged the results across replicates by evaluating individual ancestry coefficients  with CLUMPP v1.1.248. Averaged population subdivision over changing values of K is depicted in Fig. K = 3, the optimum K value as determined by the Evanno method, which calculates the most statistically likely number of genetic clusters47, are additionally incorporated into Fig. We assessed population subdivision using a model-based clustering approach implemented in 50. Different network topologies were explored by specifying different values of k, which dictates the number of genetically nearest neighbors each sample is connected to. We ran Netview for k values of 1–35, and plotted the resultant graphs using the Kamada-Kawai force-directed graph drawing algorithm51 as implemented in iGraph52. We explored population structure using a PCA in SNPRelate44 using a genetic covariance matrix calculated from genotypes.We then used Netview, a network theory-based approach, to construct networks of individuals illustrating the connectivity and information flow within and between populations based on genetic similaritySTRUCTURE and PCA analyses.Among our samples we identified hybrids between Kentish and White faced Plover based on their consistent genotypic assignment indicating mixed genotypes based on both 53 and Adegenet55. We divided our Kentish Plover samples into four populations  and retained White-faced Plovers as a single population. We excluded any hybrids we identified from this analysis. We utilized Nei’s genetic distance in Adegenet to calculate 56.We calculated pairwise population summary statistics for Kentish and White-faced Plover populations using the R packages HierfstatWe recorded morphological measurements for a total of 54 birds sampled along the Chinese coastline Table , includi57. For traits that adhered to a normal distribution we examined differences between sexes and taxa using two-way ANOVAs. We utilized the R package ggplot258 to generate boxplots comparing morphological measurements between the two genomically-prescribed groups for the measurements which showed significant interactions between taxa and sex, and plotted relevant significance bars with the R package ggsignif59. We used R version 3.4.1 for all statistical analyses60.We obtained ddRADSeq genotypes for 41 of the 54 measured individuals. These comprised 13 males and 28 females, of which we identified 11 birds based on their genotypes as Kentish Plovers, 29 as White-faced Plovers and one as a hybrid (see Results). We assessed normality of the morphological data using Shapiro-Wilk testsResearch protocols were approved by Jiangsu Normal University and National Natural Science Foundation of China. All lab work was conducted in accordance with regulations outlined by the National University of Singapore’s Office of Safety, Health, and Environment.Supplementary Information