Hyalesthes obsoletus is generally considered as a polyphagous species associated with numerous wild and cultivated plants. However, recent research in southeastern Europe, the distribution centre of H. obsoletus and the area of most stolbur-inflicted crop diseases, points toward specific host-plant associations of the vector, indicating specific vector-based transmission routes. Here, we study the specificity of populations associated with four host-plants using mitochondrial and nuclear genetic markers, and we evaluate the evolution of host-shifts in H. obsoletus. Host-plant use was confirmed for Convolvulus arvensis, Urtica dioica, Vitex agnus-castus and Crepis foetida. Mitochondrial genetic analysis showed sympatric occurrence of three phylogenetic lineages that were ecologically delineated by host-plant preference, but were morphologically inseparable. Nuclear data supported the existence of three genetic groups (Evanno’s ΔK(3) = 803.72) with average genetic membership probabilities > 90%. While populations associated with C. arvensis and U. dioica form a homogenous group, populations affiliated with V. agnus-castus and C. foetida constitute two independent plant-associated lineages. The geographical signal permeating the surveyed populations indicated complex diversification processes associated with host-plant selection and likely derived from post-glacial refugia in the eastern Mediterranean. This study provides evidence for cryptic species diversification within H. obsoletus sensu lato: i) consistent mitochondrial differentiation (1.1–1.5%) among host-associated populations in syntopy and in geographically distant areas, ii) nuclear genetic variance supporting mitochondrial data, and iii) average mitochondrial genetic distances among host-associated meta-populations are comparable to the most closely related, morphologically distinguishable species, i.e., Hyalesthes thracicus (2.1–3.3%).The stolbur phytoplasma vector  Knowledge of changes in insect genetic structure and the possibility of cryptic divergence are particularly important for pest populations because management strategies must be adapted to the ecological diversity of the pest –6. SeverHyalesthes obsoletus Signoret, 1865 (Hemiptera: Cixiidae) rose to prominence as an important pest vector, inducing biomass losses exceeding agroeconomic thresholds, its role in the dissemination of stolbur phytoplasma  [H. obsoletus feeds, developments, reproduces or even on which it is accidentally hosted—has led to a general acceptance of H. obsoletus being highly polyphagous  and Urtica dioica (stinging nettle), both recognized as dual host-plants of primary importance in stolbur phytoplasma epidemiology [tuf-a (type I) in U. dioica and tuf-b (type II) in C. arvensis, which lead to two independent plant-based epidemiologies [H. obsoletus populations affiliated with these plants are well studied in central Europe [Ever since ubgroup)  has beenubgroup) , 20–25. emiology , 25–27. iologies . H. obsol Europe , 25, 28,l Europe , 29. Recl Europe , 30.H. obsoletus as a vector of stolbur [Vitex agnus-castus as a common host-plant in the European Mediterranean has been neglected for a full century after being reported by Horváth [H. obsoletus associated with V. agnus-castus being a vector in the Montenegrin littoral, and the elucidation of stolbur epidemiological routes commencing from different dual host-plants, has encouraged further research to understand the genetic relationships among diverse host-associated populations [Following the experimental verification of  stolbur , researc stolbur  remains  Horváth , even af Horváth . One rea Horváth . Recent ulations , 34.V. agnus-castus in the eastern Mediterranean where adult presence on co-occurring U. dioica and C. arvensis was either lacking or very rare, respectively. Orenstein et al. [H. obsoletus' host-plant associations across a wide distribution is the fact that it represents only one of the seven species constituting the Hyalesthes obsoletus species group: identical outer morphology, similarities of male genital structures and sympatric occurrences as well as the circum-Mediterranean distribution range of H. obsoletus that overlaps with H. lacotei  in south France, H. thracicus Hoch, 1986 in north Greece and Turkey, H. yozgaticus Hoch, 1986 in central Turkey (Anatolia), H. hani Hoch, 1986 in Lebanon, H. verticillatus Dlabola, 1994 in Israel and Syria, and H. flavovarius Kusnezov, 1935 in Uzbekistan [H. obsoletus and its developmental host plants difficult.Sympatric co-occurrence of populations feeding on (a combination of) the three aforementioned host-plants is often observed, even in strict syntopy , 13, 30.n et al.  explainebekistan , 36, hasH. obsoletus were initiated after severe outbreaks of stolbur-mediated Bois Noir disease of grapevine occurred in Germany, Austria and Switzerland. These outbreaks were linked to the recent northward colonization of new habitats by populations affiliated with U. dioica and the in situ formation of U. dioica and C. arvensis associated host-races among the peripheral populations on the species’ northernmost distribution range [H. obsoletus population expansion and genetic structure has identified an Israeli population comprised of individuals collected on Vitex sp. and Olea europaea (used as an outgroup for genetic comparison) as seemingly different from the central and west European populations associated with the traditional hosts C. arvensis and U. dioica [H. obsoletus populations in Serbia lead to the discovery of a new host association with Crepis foetida, stinking hawk’s-beard [H. obsoletus aggregation on C. foetida was made in 2006 on fallow meadows and recently abandoned arable land in east Serbia, near the Bulgarian border . The association was confirmed in the following years over a wider geographic range and preliminary data showed genetic differentiation of C. foetida populations relative to the C. arvensis- and U. dioica-associated populations [V. agnus-castus–affiliated populations raised questions regarding the cryptic differentiation potential of H. obsoletus [Studies of the genetic structure of plant-associated populations of on range , 28, 37.. dioica . In addi’s-beard . The firulations . Subsequbsoletus .H. obsoletus plant associations [C. arvensis both as a suitable adult host-plant and as the source of the vectored pathogen (at that time known as the stolbur virus). During the following half century, according to faunistic records and summarized data from museum collections for this region, occurrence of H. obsoletus was indicated primarily on Vitex sp., less frequently Quercus sp. and only sporadically Urtica sp. and Convolvulus sp. [H. obsoletus and its developmental host-plants in southeastern Europe, the surmised origin of the recent colonization of western Europe [H. obsoletus populations affiliated with C. arvensis and U. dioica at the northwestern edge of the range in western Europe, specific stolbur strains, different adult flight periods and the existence of two plant-based host races [On the Balkan Peninsula, the first reliable data regarding ciations  designatulus sp. . The epin Europe , 15. Thest races , 14, 39,st races .H. obsoletus from southeastern Europe with the aim of delineating population (host-plant) specialization and possible cryptic speciation. Using previously published genetic data analyzing the same mtDNA and microsatellite loci as the present study [sensu [The present study evaluates genetic differentiation and demographic history in four plant-associated populations of nt study , 11, 15,nt study , 41–44. y [sensu ) are higy [sensu .Hyalesthes obsoletus populations associated with four target plants previously identified as preferred plants for this planthopper in southeastern Europe and eastern Mediterranean [Convolvulus arvensis (Ca), Urtica dioica (Ud), Vitex agnus-castus (Vac) and Crepis foetida (Cf) [H. obsoletus by white collar and male genital morphology according to the taxonomic key provided by Hoch and Remane [H. obsoletus populations collected from crop plants in Romania and Russia  . To evald Remane . In addi-1. After removing the insect, chloroform was added to the homogenate. The mixture was centrifuged at 4°C on 11000 rpm for 10 min. The chloroform step was repeated, after which the upper aqueous supernatant was precipitated with ice-cold isopropanol. This mixture was centrifuged at maximum speed for 15 min. The resulting DNA pellet was washed with 96% ethanol, air dried and re-suspended in 50 μl TE buffer . To achieve a higher rate of DNA recovery for the dry museum specimen, and for specimens from localities in Turkey, Greece and Serbia with only few individuals, we used the Qiagen Dneasy Blood & Tissue Kit  in accordance with the manufacturer’s instructions. Both extraction methods allowed us to preserve morphological features of specimens for later analyses. After DNA extraction, insect specimens were prepared as voucher dry specimens. They are housed at the Institute for Plant Protection and Environment collection . Extracted DNA was kept at -20°C.Total DNA was extracted from each individual insect specimen using a non-destructive, partly modified sodium dodecyl sulfate (SDS) extraction method , 47. BriH. obsoletus were based on two concatenated gene regions (markers) previously characterized by Johannesen et al. [COI-tRNA(Leu)-COII) and (ii) 16S ribosomal RNA, tRNA-Leu and reduced nicotinamide adenine dinucleotide (NADH) dehydrogenase subunit I region (16S-tRNA(Leu)-ND1). Amplifications were performed using primers S2792 and A3661 for the first gene region [COI-tRNA(Leu)-COII and 1.5 mM for 16S-tRNA(Leu)-ND1, 0.5 mM of each dNTP, 0.4 μM of each primer, 1 U of KAPA Taq DNA polymerase  and 1 μL of template DNA. Amplification was conducted in a Mastercycler ep gradient S  using the following thermal profile for both markers: 95°C for 2 min, 35 cycles at 95°C for 30 s, 48°C for 1 min, 72°C for 1 min 30 s, and a final extension at 72°C for 10 min. Sequencing was performed on an ABI Prism 3700 automated sequencer . Sequences were edited using FinchTV v.1.4.0 (http://www.geospiza.com) and aligned with ClustalW [H. obsoletus population were genotyped for mitochondrial markers, (COI-tRNA(Leu)-COII and KY368692-8 for 16S-tRNA(Leu)-ND1 e region  and LR-Ne region  -ND1 .Considering that orthology is of primary importance for phylogenetic studies, especially when cryptic speciation events are possibly involved , we perfH. obsoletus host-plant associated haplotype groups, we supplemented our study with Hyalesthes thracicus genetic data, morpho-phylogenetically the closest member of the same species group [COI-tRNA(Leu)-COII and 16S-tRNA(Leu)-ND1 gene regions, respectively , R. melanochaetus , R. cuspidatus  and Setapius apiculatus . Six newly designed primers were combined with standard ones [H. thracicus COI-tRNA(Leu)-COII and 16S-tRNA(Leu)-ND1 gene regions were deposited in GenBank under the numbers KY368725 and KY368726, respectively.To achieve a better resolution for the evolutionary relations between and among es group , 54. We ectively . Newly dard ones , 49, proF-statistics [Arlequin v.3.5.1.2 [H. obsoletus populations (number and frequency of haplotypes). Standard molecular diversity indices (FST and θ) were calculated for the three metapopulations that were grouped according to the host-plant association and the cluster sharing between the populations associated with C. arvensis and U. dioica as host-plants: 1) C. arvensis + U. dioica, 177 individuals; 2) V. agnus-castus, 56 individuals; and 3) C. foetida, 83 individuals. To estimate the amount of genetic diversity within the selected groups (metapopulations) we calculated the population genetic parameter theta (θ) estimated from the number of alleles (θk), expected homozygosity (θH), segregating sites (θS) and pairwise differences (θπ). Theta (θ) represents the distribution of variation within or among populations when samples are considered to represent characteristics of the higher rank group from which they are sampled, in this case, the host-plant association [Genetic variations within and among host-plant associations were estimated with pairwise atistics  implemen.3.5.1.2 . Mitochoociation , 58.D [FS neutrality statistics [Arlequin v.3.5.1.2 [U. dioica-associated populations are known to be undergoing demographic expansion in western Europe [C. arvensis and U. dioica were treated both separately and as a meta-group to deduce the source of a departure from neutrality. Fu’s simulations are based on the infinite sites model of mutation. Negative values of Fu’s FS parameter indicate an excess in allele numbers as expected from a recent population expansion, while a positive value is evidence of an allele deficiency, as expected from a recent population bottleneck [D test measures a difference in the number of pairwise differences and the number of segregating sites scaled to be the same in a neutrally evolving population. A negative Tajima’s D parameter signifies an excess of low frequency polymorphisms. A significant negative departure from these tests has been explained mainly as an excess of new mutations as a result of evolutionary forces, such as selective sweeps or population growth (signature of population expansion), while positive departure indicate a balancing selection.To study whether genetic diversity of each of the four host-plant associated groups depart from neutrality and to detect genetic signals of the demographic and/or spatial growth we calculated Tajima’s D  and Fu’satistics . Neutral.3.5.1.2 . Becausen Europe , 37, indttleneck . Tajima’FST) values and the Nei’s average number of pairwise differences [Arlequin, to measure differentiation between all population pairs sorted according to host-plant association  to 1, with 0 indicating no divergence between the populations, and 1 indicates that two populations are completely separate [The pairwise fixation index  were aligned and treated as a single locus. The maximum parsimony and neighbor-joining trees were generated in PAUP* v.4.0b10 [COI-COII genes, which was proven to be the most phylogenetically informative of the analyzed mtDNA markers for species-level identification and differentiation, e.g., [Phylogenetic reconstruction and haplotype networks were based on newly identified haplotypes (this study) and all previously published plotypes , 15, 37.v.4.0b10  using thv.4.0b10  under unv.4.0b10 , 66. We v.4.0b10  to ensurv.4.0b10 . Averagen, e.g., –71.H. obsoletus host-associated haplogroups were inferred employing two software packages with different network construction approaches. The software TCS v.1.21 [www.fluxus-engineering.com) keeping the parameter ε = 0. This method adds median vectors as uncollected or possibly extinct ancestral genotypes in order to reduce tree length to the minimum spanning trees combined within a single network [Phylogenetic relationships between closely related species and such resulting from population-level processes  are often better visualized in reticulated graphs or networks . MtDNA gS v.1.21  was usedS v.1.21  with 95% network .H. obsoletus individuals originating from 50 populations  and allele frequencies per locus were estimated in FSTAT v.2.9.3 [FIS). The mean expected heterozygosity per population (HE) was calculated in Arlequin v.3.5.1.2 [HE and AR per group of the host-plant associated populations were tested with t-tests using Statistica v.5.1 . Because sample sizes varied, we performed a linear regression analyses to test sample the dependency of sample size and genetic diversity measures.The presence of null alleles was evaluated using the EM algorithm (FreeNa) , 78. Nul-checker . Linkage [enepop  using th [enepop . The all v.2.9.3  using al.3.5.1.2 . DiffereStructure v.2.3.3) [Vitex agnus-castus from Israel [Structure analysis for each test was repeated 20 times for each K with 50,000 burn-ins followed by 200,000 MCMC (Markov chain Monte Carlo) iterations using the admixture model and correlated allele frequencies. The web-based program Structure harvester [Structure was estimated with the molecular variance analysis (Amova) in Arlequin v.3.5.1.2 [Analyses of the influence of host-plant affiliation and geographic separation on population structure were estimated using Bayesian clustering (v.2.3.3) . Followiv.2.3.3) , we firsm Israel . Based oarvester  was usedarvester . Additio.3.5.1.2 .H. obsoletus populations associated with the four host-plants were further inferred with a maximum-likelihood phenogram using the Contml algorithm in Phylip v.3.69 [Hyalesthes luteipes individuals sampled on Ulmus minor in Serbia were used as an outgroup root. This analysis was based on four loci  that amplified successfully in both species. The phenogram was visualized using FigTree v.1.4 [H. thracicus. In contrast, microsatellite analysis (H. luteipes) relies on allele frequencies for which estimate several individual are required.Genetic clustering and identity among p v.3.69 . Hyalestee v.1.4 . It shouH. obsoletus populations across the surveyed area (H. obsoletus populations in southeastern Europe are i) high density and very common in association with Ud; ii) rare and low density in association with Ca; iii) usually very common and in high density in association with Vac, however, it is restricted to the coastal distribution of the host-plant; and iv) high in number and very common in association with Cf in the eastern parts of the surveyed area but absent in the south , Romania (Ca and Cf), Montenegro , Macedonia (Ca and Ud), Greece  and Turkey (Ca and Cf). In addition to these locations, a single locality with Cf as a tentative host-plant was surveyed at a Danube locality in Bulgaria , and from the Aegean islands Thasos and Lesbos 10 km from the nearest Greek or Turkish mainlands, respectively. The affiliation of H. obsoletus populations with C. foetida was observed mainly in eastern and southeastern Serbia, with a western limit along the river Morava (N = 11). The association with C. foetida was confirmed along the Danube in Bulgaria and Romania , held a syntopic C. arvensis population.A total of 718 d Turkey , Fig 1. Ca-Ud, Vac and Cf metapopulations), with 88% of genetic variance derived from host-plants  and 12% attributed to within-group variations. Diversity estimates within and among host-associated metapopulations , and 26 with Cf . OverallH. obsoletus populations collected on crop plants in Romania and Russia  and Cf (JH and MH), while the Russian had a single haplotype , the Rotype QB,  derived Ca-Ud H. obsoletus metapopulation  could be a result of low-frequency alleles left over from geographical expansion [U. dioica association with a highly significant negative value of neutrality indices , with 75% of the divergence deriving from the inner host-plant associated variance. A very low genetic polymorphism was detected in the genetic structure of the C. foetida metapopulation, while the V. agnus-castus association expressed the highest level of inner divergence , corresponding to 90.5% (p < 0.001) of the genetic variation observed between the Montenegrin and Greek haplogroups.Comparison among the theta (θ) values of molecular diversity in these three host-plant associations revealed the highest mtDNA diversity estimates of number of alleles and segregating sites in the pulation . The obsC. foetida = 2, C. arvensis = 6, V. agnus-castus = 9 and U. dioica = 11. The highest number of private alleles within a single sample population was 7, occurring within V. agnus-castus association (Pop36 and 37), while 11 (7%) were private relative to a host-plant association (V. agnus-castus = 5 and U. dioica = 6). No significant linkage disequilibrium was detected for any locus pair in any population after Bonferroni’s correction [Microsatellite analyses were performed on 702 individuals from 50 populations . Fifteenrrection .C. arvensis and U. dioica had an approximate null allele frequency of 0.05 , followed by E96 and G85 (0.10) and should not bias the following analyses. The frequencies of null alleles correlated with mtDNA divergence are as follows: ulation; ), V. agnHE was independent of sample size . Hereafter we treated this parameter as an unweighted estimate. The mean genetic diversity estimates HE and AR did not differ significantly among populations affiliated with C. arvensis (HE = 0.777 and AR = 4.567), U. dioica (HE = 0.765 and AR = 4.455) and V. agnus-castus (HE = 0.785 and AR = 4.523), all p > 0.05 (H. obsoletus populations associated with C. foetida (p < 0.05) than in the other host-associations (HE = 0.651 and AR = 3.449). The observed signal is attributed to the Serbian, Romanian and Bulgarian populations, while the Turkish population had much higher values of diversity indices comparing to the European metapopulation  and bootstrap support values (87–98%), while values for the Vac lineage were lower  probably due to geographic diversity. In addition, the Vac and Cf lineages formed a joint branch, but with low support values  due to high inner-branch diversity. However, the bifurcations were supported using genealogical network analysis (see below).The obtained tree’s topology revealed a clear segregation of the H. obsoletus haplotypes  and an Eastern European haplogroup (EC-derived haplotypes). An exception to this geographic based distribution was the Russian haplotype QB, which belonged to the western haplogroup. It implicates a common host-plant association older than the phylogeographic division. V. agnus-castus haplotypes were paraphyletic, being divided into three subgroups consisting of the monophyletic Greek YM and Montenegrin ZN haplotype clades  and a paraphyletic Israeli clade (two haplotypes). The two Israeli Vac haplotypes (GE and HE) were positioned closest to the C. foetida network branch as well as in the evolutionary tree  were higher, 2.5%  as well as Nei’s pairwise differences among and within populations clearly showed the existence of three genetically separate groups associated with different host-plants: 1) C. arvensis and U. dioica, 2) V. agnus-castus and 3) C. foetida  and within the Vac group.The measure of pairwise population differentiation due to genetic structure  and significant (p < 0.01) when the populations associated with Ca-Ud, Vac and Cf were compared to each other , while differentiation among the Greek populations was low (FST = 0.00–0.30). Differentiation among most Ca and Ud population, regardless of geographic origin, was low, FST = 0.00 to 0.20. Nevertheless, three populations associated with Ca in Montenegro and Greece . This finding was caused by the presence of the AB-group haplotypes in these populations  only in comparison with the Ud-associated Pop30  because of the mixed presence of the AB- and EC-group haplotypes in this population.Genetic differentiation among the 51 host-associated  to 0.20 . Within ulations , while ECa-Ud and the Cf-associated populations (12–15) as well as between the Ca-Ud and Vac-associated populations (9–12). Within host-plants, pairwise genetic distances were 0.0–4.0 for the Ca-Ud associated populations, 0.0–1.2 for the Vac-associated populations in Montenegro and 0.0–2.1 in Greece (4–8 in between), and 0.0–1.0 for the Cf-associated populations. The within-population genetic distances were found for those associated with Cf, and were caused by the number and frequency of haplotypes  specificity to host-plant.In syntopy, i.e., co-occurrence of two host-plants harboring Structure based on the 50 H. obsoletus populations  from southeastern Europe and Turkey, and a single Vac-associated population from Israel  [Ca- and Ud-associated individuals formed Cluster 1, Vac association formed Cluster 2, and the Cf-associated individuals formed Cluster 3  showed that 77% of the total genetic variance was host-plant affiliated  = 0.06–11.14) nor Cluster 3  = 0.18–5.32) showed signals of geographic differentiation, and for Ca and Ud there was no significant host-plant differentiation. In contrast, genetic variance in Cluster 2 (Vac) was divided between Montenegrin and the Greek metapopulations (approx. 400 km), geography explaining 60% of the total variance  = 80.45; Amova of Montenegrin vs. Israel and Greek populations estimated 42% of the total genetic variance was caused by differentiation between the two clusters , syntopic with the C. foetida-associated population (Pop54), was removed from the analyses because the number of collected individuals was low (3 specimens). In three of the four analyzed syntopic Ca-Ud sites  no differentiation between host associations was found, agreeing with the general absence of the host-driven diversification signal for all Ca-Ud populations. However, in one Ca-Ud syntopic site (Podgorica), Evanno’s ΔK(2) = 76.94 suggested the existence of two clusters, hence showing a signal similar of host races as in southwest Germany (Ca-associated population (Pop 6) and eastern EC-group haplotypes were found in the Ud-association (Pop25). In all other syntopic localities , clear population-based host-plant affiliation were evident (population membership asignment 68–99%), but not for all individuals of the affiliated host-plant  C. arvensis and U. dioica, 2) V. agnus-castus and 3) C. foetida show much higher segregation on an evolutionary time-scale compared with the previously identified C. arvensis and U. dioica host races in south Germany [Salvia sclarea- and Lavandula angustifolia-associated host-race formation in south France [Hyalesthes thracicus (2.1–3.3%).In recent years, several studies have documented specialized plant-associated life cycles of bsoletus , 33, 38.bsoletus  to hypot Germany  or that h France . The folH. obsoletus’ affiliation with C. arvensis and U. dioica, the traditional host plants in southeastern Europe. Relations between these two associations were expected to be complex. Evidence for host races in the western European mtDNA sub-haplolineage (AB) was found in an area of recent immigration in Germany and northern France, but not in Western Europe south thereof [Ca-Ud-associated individuals belong to the EC mtDNA sub-haplolineage also suggest a lack of host races associated with C. arvensis and U. dioica there. Combined data indicate an innate capability of H. obsoletus to utilize both plants in the ancestral distribution range. However, the finding of the core populations’ single syntopic locality with clear genetic differentiation on the host-plant level , require further investigation. One reason for differentiation here may be phylogeographic bias rather than host-plant specialization. Individuals associated with the two plants belonged to the sub-lineages AB and EC, respectively. These sub-lineages are also genetically diverged for microsatellite loci [This study was initially started as a survey to verify  thereof , 15, 28.V. agnus-castus was described by Hoch and Remane [H. obsoletus with V. agnus-castus in Montenegro and Greece (mainland and islands) and we believe that the association will be affirmed along the coast of the Adriatic Sea, as well as in other parts of the Mediterranean basin—such as the coastal regions of the Iberian, Apennine and Anatolian peninsula—as outlined in Hoch and Remane [V. agnus-castus association was confirmed in habitats surrounding vineyards along Bosnia and Herzegovina’s coastal area [H. obsoletus associated with V. agnus-castus on the Balkan Peninsula consists of two geographically separated genotype groups (Greek YM and Montenegrin ZN), which are linked genealogically by the haplotype ηM. The spatial separation between the groups is approximately 250 km along the coastline with suitable habitats for V. agnus-castus growth. Whether the two V. agnus-castus sub-lineages of H. obsoletus represent two subspecies separated by the Pindus mountain range as a barrier that prevents between-group interaction, or simply are phylogeographic variants, may be assessed by sampling in the intermediate range along the Albanian coastline.The association with d Remane  and needd Remane . Prior td Remane . In our d Remane . Recentltal area , while ital area , but sinV. agnus-castus haplotypes to the C. foetida-associated haplo-group than to the Montenegrin and Greek haplotypes , but that are linked to other association according to mtDNA genetic markers , as a relic from their host-shift past.One of the most interesting findings is a closer mtDNA genealogical relatedness of Israeli pes Figs  and 5. Cbarriers . Populatbarriers , 90, 91.H. obsoletus populations to C. foetida across a vast area ranging from east Turkey up to the Danube and Morava rivers on the Balkans . This association could have entered the European continent by crossing the Bosphorus and the Dardanelles or by following the Danube valley, like many other taxa that share this Balkan-Anatolian and Ponto-Panonian chorotype [C. foetida collected on crop plants in Radovanu (south Romania) and the presence of this association on both sides of the Danube in Bulgaria and Romania  emphasizes a need for genetic analysis of this archival material (if located) and its mere importance for resolving H. obsoletus taxonomic and nomenclature status.Due to its significance as a vector of plant pathogenic phytoplasma, e failed , leadinge failed , the typy Fieber ) collecty Fieber . Hence, Hyalesthes [H. obsoletus and its closest relative H. thracicus. These subtle phenotypic differences, and an average genetic distance of 2.6% (3.3% on COI-COII), suggest a recent common ancestor not older than the Quaternary glacial cycles [Hyalesthes [H. obsoletus in the eastern Mediterranean. Micro-refugia as well as host-plant specialization likely expanded the distribution range of H. obsoletus westwards  but morphological differences were not evident among them . This lack of morphological difference may imply intense specialization to specific plant metabolites that rapidly separated the incipient species. Berlocher and Feder [Ca/Cf, three Ud/Cf and two Ud/Vac) where plant-associated populations lacked genetic exchange. Hence, we view H. obsoletus as a species complex, for which cladogenesis is linked to morphological stasis [Haplotype divergence among the three host-plant associated nd Feder  argued fl stasis . The decl stasis , 104.H. obsoletus, requires an integrative taxonomic approach. If the type material of H. obsoletus is considered lost, then the designation of a neotype, following the International code of Zoological nomenclature (ICZN), can lead to stabilization of the taxonomic and nomenclature ambiguity within the H. obsoletus species complex.Following genetic and ecological (host-plant) differentiation of three entities within, what is up-to-date considered a single unique species under the name H. obsoletus, which acquires stolbur phytoplasma in the larval stage [H. obsoletus. First, the genetic homogeneity of H. obsoletus utilizing C. arvensis and U. dioica is opposed by two distinct plant associations of the pathogen, tuf-b and tuf-a, respectively [V. agnus-castus and C. foetida cryptic species transmit only tuf-b [C. arvensis, V. agnus-castus and C. foetida indicate the existence of intersections or meeting points in the epidemiological pathways of tuf-b strains associated with different host-plants and plant-specialized vector populations  [H. obsoletus polyphagy. Although we do not exclude the possibility that H. obsoletus belonging to a specific association (e.g. C. arvensis) feeds on erroneous plants of another association (e.g. V. agnus-castus) within the same epidemiological cycle (tuf-b), this event is unlikely in many habitats of the species range due to differences in micro-geography, micro-climate and vegetation composition. Survival tests of genetic host-races on alternative plants [H. obsoletus is more dependent on the host-plant than was previously thought. Hence, host-plant preference, which is proven to be a crucially important trait for this insect, requires special attention in all further studies delimiting epidemiological cycles. Therefore, to verify that plants currently found in the literature are actual hosts for development, we encourage careful population sampling in the entire distribution range and molecular confirmation of larval presence on the plants’ roots to determine true host suitability and association. Only precise identification of dual hosts enables detecting pathogen transmission routes and epidemiological cycles for relevant management strategies, e.g., [Clarifying the true relationships of host associations of insect vectors is of particular epidemiological importance because these associations determine the breadth of pathogen transmission. For al stage , knowledal stage , 14, 37.ly tuf-b , 38, 40.ed data) , 10, 13,e plants  show thaH. obsoletus occurs in natural ecosystems, unlike the majority of economically important insects, for which cryptic differentiation is usually attributed to survival and reproductive pressures in agro-ecosystems, e.g., [H. obsoletus support the notion that specialization and possibly cryptic species is more common than often appreciated in "generalist" insects [This thrilling evolutionary story of s, e.g., –107. The insects . It poseS1 Appendix(TXT)Click here for additional data file.S1 Fig(PDF)Click here for additional data file.S1 Table(PDF)Click here for additional data file.S2 Table(PDF)Click here for additional data file.S3 Table(PDF)Click here for additional data file.S4 Table(PDF)Click here for additional data file.S5 Table(PDF)Click here for additional data file.S6 Table(PDF)Click here for additional data file.


Elaeis oleifera genetic materials were assembled from its center of diversity in South and Central America. These materials are currently being preserved in Malaysia as ex situ living collections. Maintaining such collections is expensive and requires sizable land. Information on the genetic diversity of these collections can help achieve efficient conservation via maintenance of core collection. For this purpose, we have applied fourteen unlinked microsatellite markers to evaluate 532 E. oleifera palms representing 19 populations distributed across Honduras, Costa Rica, Panama and Colombia.The In general, the genetic diversity decreased from Costa Rica towards the north (Honduras) and south-east (Colombia). Principle coordinate analysis (PCoA) showed a single cluster indicating low divergence among palms. The phylogenetic tree and STRUCTURE analysis revealed clusters based on country of origin, indicating considerable gene flow among populations within countries. Based on the values of the genetic diversity parameters, some genetically diverse populations could be identified. Further, a total of 34 individual palms that collectively captured maximum allelic diversity with reduced redundancy were also identified. High pairwise genetic differentiation (Fst > 0.250) among populations was evident, particularly between the Colombian populations and those from Honduras, Panama and Costa Rica. Crossing selected palms from highly differentiated populations could generate off-springs that retain more genetic diversity.The results attained are useful for selecting palms and populations for core collection. The selected materials can also be included into crossing scheme to generate offsprings that capture greater genetic diversity for selection gain in the future.The online version of this article (doi:10.1186/s12863-017-0505-7) contains supplementary material, which is available to authorized users. Elaeis consists of two important species, namely E. guineensis Jacq. and E. oleifera (HBK) Cortes. Both species yield oil used for food and non-food applications. In terms of their habitats, E. guineensis is endemic to the tropical lowlands of West and Central Africa, spreading from 16°N in Senegal to 15°S in Angola E. oleife= 0.644) , indicat= 0.644)  in a stu content  can be eoleiferas in Cerete was removed to give way to agriculture [oleifera fruits by the locals. Oleifera bunches may have been transported from far for oil extraction at these mills. It has been shown that oil palm seeds from the processed bunches preserve germination ability thus, unrelated palms from these bunches could have been established in areas near the mills in Cerete. Hence, the genetic materials assembled from this area possess dissimilar genotypes, introduced by the unrelated palms, which is reflected in higher Ho value. This leads to the negative F value, as seen for the population from Cerete (C6).At the population level, one of the populations from Colombia (C6) possessed negative fixation index (F) value (-0.030). This population was located at Cerete, Colombia. Bulk of the natural groves of iculture . The remiculture  indicatiE. oleifera. Analysis carried out on the E. oleifera remains across an area between the southern part of the United States and the south of Uruguay [E. oleifera populations in Colombia was more recent. This archaeological evidence further supports the low Na(rar) and genetic diversity among the Colombia populations. Similarly, populations from Honduras also exhibited low diversity. However, the low diversity observed among the genetic materials from Honduras is probably due to founder effect. Here, we only investigated small number of populations ie. two from this country thus, limited diversity was captured.Allelic richness is a useful estimate for evaluating population diversity. The plot of allelic richness Na(rar) of each population against position Fig.  indicate Uruguay  concludeE. oleifera is higher than that reported in E. guineensis (0.206) [E. guineensis wild groves was reported along the oil palm belt stretching from the west to the central Africa. However, unlike E. guineensis, the natural distribution of E. oleifera was highly discontinuous [The AMOVA revealed that 29% of the variation observed in this study was attributed by the genetic differentiation between the populations. The differences between the populations are considered extensive, thus sampling a limited number of individuals from many populations should be implemented for future collection and establishment of core collection. Our results are in agreement with that reported by , based o (0.206) . Extensintinuous . In suchThe phylogenetic tree presented in Fig. E. oleifera seeds from natural populations in Panama, Colombia, Suriname, Honduras, Nicaragua and Brazil [Between 1967 and 1976, a private company in Costa Rica initiated collections of d Brazil . These gd Brazil . This poex situ living collection of E. oleifera occupies approximately 18 hectares of land, accommodating approximately 2,500 palms. Maintaining living collection for large crop like oil palm is expensive. Nonetheless, field evaluation of the collection revealed some interesting traits useful for oil palm genetic improvement [The current rovement . AchieviThe results presented above facilitate the identification of unique populations or rich allelic individual palms as well as populations that exhibit high genetic variation. These results are useful for selecting genetic materials for establishing the core collection. Some genetically variable populations were identified based on the genetic diversity parameters estimated in this study. Among the interesting populations are C5, C8, P5, P12, K4, K14 and K15, as they exhibited genetic diversity estimates higher than the mean. The results from AMOVA indicated greater diversity between populations which suggests that sampling limited individuals from many populations should capture maximum diversity. Previous analysis  revealedOur results also revealed high pairwise genetic differentiation (Fst) between populations from Colombia and those from other countries. This can be visualized in Fig. E. guineensis SSRs tested showed cross amplification in E. oleifera. Of these, 40% showed discriminative power among populations thus, proving to be a reasonably useful marker resources for genetic studies of E. oleifera. The genetic diversity estimates indicated high genetic variability among the populations from Costa Rica. This result suggests that the country may serve as the centre of diversity of E. oleifera. This study also provides valuable information that help oil palm breeders and germplasm manager in identifying individual palms and populations for establishment of core collection. Implementing the suggestions described above would result in comprehensive genetic collection that retains genetic diversity as well as valuable traits for selection gains and access in the future.From the current work, 77% of the ex situ living collection of E. oleifera. These populations were selected based on their geographic distribution, microclimates, altitudes and rainfalls in Colombia, Panama, Costa Rica and Honduras , 0.1% TritonTMX-100), 1.5 mM Mg2Cl, 200 μM dNTPs mix, 1.0 U Taq DNA polymerase , 0.25 μM of each primer, 0.38 μM fluorescent dye  and 50 ng of DNA template. The PCR conditions included initial denaturation at 94 °C for 5 min, followed by 35 cycles of denaturation at 94 °C for 30 s, annealing at 52 °C for 1 min and elongation at 72 °C for 2 min, then final elongation step of 72 °C for 10 min. The M13-tailed forward primer was labeled with 4-colour fluorescent dyes. The fluorescent dyes used in the study were FAM (blue), PET (red), VIC (green) and NED (yellow). The sample set was subdivided into four panels and each of them consisted of four microsatellite primers labeled with four fluorescent dyes, respectively.Prior to fragment analysis, PCR products from four different SSR primers were combined at 1:1:1:1 ratio. The multiplex (2.0 μl) was pretreated by adding 7.80 μl of Hi-DiTM Formamide  and 0.20 μl of GeneScanTM-500 LIZTM Size Standard  to make up 10.0 μl of the final volume. The mixture was vortexed thoroughly and followed by denaturation at 95 °C for 5 min. The plate was then placed on the ice immediately for another 5 min before capillary electrophoresis using ABI PRISM® 3100 Genetic Analyzer . The raw reads were retrieved and exported to GeneMapper V3.1 software. The genotype profiles were finally generated and displayed in the software for scoring purpose.a), number of effective alleles (Ne), Shannon Information Index (I), observed heterozygosity (Ho), unbiased expected heterozygosity (He) and fixation index (F) were also estimated for each population.Marker informativeness was evaluated based on the G”st values determined in GenAlex version 6.5 , 42. Thehttp://www.nhc.noaa.gov/gccalc.shtml).Allelic richness (Na (rar)) for each population was estimated using HP-Rare 1.1 software , 46. Genhttp://itol.embl.de/upload.cgi) [GenAlex version 6.5 was also applied in determining the genetic relatedness among the individual palm in the form of Principle Component Analysis (PCoA) plot. AMOVA was carried out to generate the overall partitioning of the genetic variation within and between the populations. Fst values and genetic distances (GD)  were estoad.cgi)  using thStructure V2.2 program  was applE. oleifera analyzed in this study. The software was developed using a heuristic algorithm that retained all different alleles and the results were highly reproducible.We applied PowerCore software  to shortAdditional file 1:Log probability data (LnP(D)) as function of k (number of clusters) from the STRUCTURE. (DOCX 2712 kb)Additional file 2:Information of country, collection sites and population size included in the study. (DOCX 16 kb)Additional file 3:Details of the 18 microsatellite markers used in the study. (DOCX 16 kb)


Gst = 0.05 ± 0.049). The smallest divergence is among African populations (Gst = 0.0081 ± 0.0025), with increased divergence among non-African populations (Gst = 0.0217 ± 0.0109) and then among African and non-African populations (Gst = 0.0324 ± 0.0064). Genetic diversity is high in African populations (~0.13), low in Asian populations (~0.11), and intermediate in the remaining 11 populations. Few significant linkage disequilibria (LDs) occur between the genome-wide CNV loci. Patterns of gametic and zygotic LDs indicate the absence of epistasis among CNV loci. Mutation rate is about twice as large as the migration rate in the non-African populations, suggesting that the high mutation rates play dominant roles in producing the low population genetic divergence at CNV loci.Copy-number-variable (CNV) loci differ from single nucleotide polymorphic (SNP) sites in size, mutation rate, and mechanisms of maintenance in natural populations. It is therefore hypothesized that population genetic divergence at CNV loci will differ from that found at SNP sites. Here, we test this hypothesis by analysing 856 CNV loci from the genomes of 1184 healthy individuals from 11 HapMap populations with a wide range of ancestry. The results show that population genetic divergence at the CNV loci is generally more than three times lower than at genome-wide SNP sites. Populations generally exhibit very small genetic divergence ( Understanding human population genetic structure remains important for gaining insights into human history and demography, as well as for investigating genetic diseases in relation to geography and ancestry124671012Homo sapiens and other species has been extensively reviewed from a number perspectives12101112151612et al.Drosophila melanogaster. Sjödin and Jakobsson21Genetic variation at CNV loci in In comparison with variation at SNP sites, variants at CNV loci have several distinct features. First, CNV variants often differ in length by 1kbp or more2427To test this hypothesis, we employ genotype data at CNV loci from the HapMap Phase III populations. This has two advantages. The first is that genetic divergence among these populations has been fully investigated at genome-wide SNP sites1834In this study we analyze genetic divergence at the genome-wide CNV loci and compare it with that at the genome-wide SNP sites in exactly the same populations. To further address the population genetic properties of CNV loci and reinforce our explanations of evolution at CNV loci, we test LDs at both gametic and zygotic levels among all pairs of CNV loci. We compare the patterns of gametic and zygotic LDs at CNV loci with those previously reported at SNP sites363838Maximum likelihood estimates (MLEs) of allele frequencies are summarized in Na = 1.6–1.66). Similarly, African populations have high gene diversity over all CNV loci (He = ~0.13) and small standard deviations (~0.15); while Asian populations have low gene diversity (~0.11) but large standard deviations (~0.16) over all CNV loci. The rest of the 11 populations have intermediate gene diversity and standard deviations  to 0.0421 ± 0.0001 (JPT-LWK), with the mean of 0.0255 ± 0.0114 over all pairs (Gst in African populations ranges from 0.0059 ± 0.00001 (LWK-YRI) to 0.0128 ± 0.00002 (MKK-YRI), with the mean of 0.0081 ± 0.0025 over population pairs. The average pairwise multilocus Gst in non-African populations ranges from 0.0038 ± 0.00001(CHB-CHD) to 0.0352 ± 0.0001(TSI-JPT), with the mean of 0.0212 ± 0.0109 over population pairs. The average pairwise multilocus Gst among African and non-African populations ranges from 0.0206 ± 0.00004 (MKK-TSI) to 0.0421 ± 0.0001 (JPT-LWK), with the mean of 0.0324 ± 0.0064. over population pairs.The average pairwise multilocus ll pairs . The aveFst previously reported at the genome-wide SNP sitesGst at the genome-wide CNV loci is generally more than three times lower (average ratio of Fst(SNP)/Gst(CNV) = 3.3081 ± 1.1837; Fst(SNP)/Gst(CNV) range from 1.3481 ± 0.0171 (LWK-YRI) to 2.1023 ± 0.0087 (MKK-LWK) in African populations, with the mean of 1.6849 ± 0.3294 over population pairs; from 0.2649 ± 0.0265 (CHB-CHD) to 3.6545 ± 0.0253 (CEU-CHD) in non-African populations, with the mean of 2.5048 ± 0.9240 over population pairs; and from 3.3.5497 ± 0.0200 (ASW-GIH) to 4.8624 ± 0.0258 (CHD-MKK) among African and non-African populations, with the mean of 4.2584 ± 0.3548 over population pairs  to 0.0241 ± 0.0001 (CHD-YRI), with a mean of 0.0124 ± 0.0067 over all pairs . The ave−5 at a CNV locusV(t), the population isolation time is generally about t = 0.0124 × 5 × 104 × 25 ± 0.0067 × 5 × 104 × 25 = 15500 ± 8375 years among populations, t = 3625 ± 1250 years among African populations, about t = 10625 ± 6125 years among non-African populations, and about t = 21750 ± 5000 years among African and non-African populations.Consider an average mutation rate of the order 10Statistical tests indicate that very few pairs of CNV loci, 0.027~0.073%, exhibit significant gametic LDs in the 11 populations . The avePatterns of gametic LDs are different among populations. African populations have more significant gametic LDs from different chromosomes than from the same chromosomes, while non-African populations except CEU and MEX have more significant gametic LDs from the same chromosomes than from different chromosomes. No common pairs of CNV loci have significant gametic LDs on different chromosomes among 11 populations, but twelve common pairs from overlapped CNV loci (except one on Chr 7) exist, with 1 on Chrs 1, 7,9,11, and 12, 3 on Chr 5, and 4 on Chr 6 .Dij  except D3j . There are twenty-two common pairs of CNV loci (mostly overlapped) of significant zygotic LDs in 11 populations, with 1 pair on Chr 1, 3 on Chr 5, 7 on Chr 6, 3 on Chr 7, 1 on Chr 9, 2 on Chr 10, 2 on Chr 11, 1 on Chr 12, 1 on Chr 13, and 1 on Chr 20  (Fst(SNP)7mc + 3μc/2) to those at SNP sites (ms + 2μs) are estimated according to From the pairwise multilocus Gst(CNV)  and the Fst(SNP) = 0.0956 ± 0.05677Gst(CNV) = 0.0255 ± 0.0114 across all population pairs, we obtain (mc + 3μc/2)/(ms + 2μs) = 4.0396 ± 3.2341, where a large standard deviation arises from the variation among populations. The above estimates indicate that the joint migration and mutation rates are generally much greater at the genome-wide CNV loci than at the genome-wide SNP sites.Using the average pairwise μc/m are summarised in The ratio of the mutation rate to the migration rate at CNV loci can be approximately quantified. According to μc/m is 2.0264 ± 2.1561 from the rate (mc + 3μc/2)/(ms + 2μs) = 4.0396 ± 3.2341 in the 11 populations, and 2.0352 ± 2.0909 from (mc + 3μc/2)/(ms + 2μs) = 4.0529 ± 3.1364 in four populations 7Fst(SNP) = 0.1265 ± 0.0675; average pairwise Gst(CNV) = 0.0354 ± 0.0158 in the present study). These estimates indicate that the mutation rate at CNV loci is generally about twice as large as the migration rate.Estimate of Fst = ~0.11 at the genome-wide SNP sites)Fst < 5% where negative selection is thought to be involvedOur results indicate a closer population genetic relationship at CNV loci than at SNP sites among 11 HapMap Phase III populations. Previous reports indicate a similar pattern at specific loci among African, European and East Asian populations (HapMap Phase II data)Note that our analyses are based on the three-allele system for describing the evolution at a CNV locus because the maximum number of allele copies is four in a diploid genotype. These 856 CNV loci are shown to exhibit neutrality among 1184 healthy individualsμt4345Nei’s genetic distance at the genome-wide CNV loci is generally comparable to those between human populations at the common protein or blood group lociPatterns of genetic divergence at CNV loci may reflect the historical divergence in forming modern human origins. The common pattern at both CNV and SNP loci is that the smallest genetic divergence is present among African populations, followed by among non-African populations, and then among African and non-African populations. Polymorphisms at CNV loci decrease from African to non-African populations. More alleles per CNV locus in African populations suggest a longer-term accumulation of mutants. These patterns are consistent with the Out of African model rather than with the multiregional model for modern human origins4737−6 to 1.0 × 10−4, about 100~10000 times of the point mutation rate at SNP sites (1.8–2.5 × 10−8). Fu et al.−5 per CNV locus per generation. On average, a mutation rate of the order 10−5 at the 856 CNV loci could be inferred from the estimate of the population-scaled mutation rate θ (=4 Nμ) = 0.1415 ± 0.0144N ~ 3000μc/mestimates suggest a dominant role that the mutation process plays in shaping population genetic divergence at CNV loci, especially in the non-African populations  at a few CNV locin = 270 in total) or at the locus of a specific gene CCL4LGst = 0.0345 ± 0.0158; Fst across chromosomes at the genome-wide SNP sites : 0 for the genotype without any allele copy in both gametes, 1 for the genotype with one allele copy in one gamete but without any copy in the other gamete, 2 for the genotype with one allele copy in each gamete, 3 for the genotype with one allele copy in one gamete and two allele copies in the other gamete, and 4 for the genotype with two allele copies in each gamete. From the individual IDs in the HapMap project, eleven populations were extracted from the pooled data (hm3_cnv_submission.txt): ASW (African ancestry in Southwest USA), CEU (Utah residents with Northern and Western European ancestry from the CEPH collection), CHB , CHD , GIH , JPT , LWK , MEX , MKK , TSI , and YRI . Sample size for each population is shown in A0, A1, and A2 be the alleles with 0-, 1-, and 2-copies at a CNV locus, respectively. Allele A1 may be the most abundant variant in a population (the segment on the reference genome), while alleles A0 and A2 are likely less abundant at a CNV locus. Owing to lack of information needed to separate distinct genotypes with the same copy numbers in diploids, allele frequencies under Hardy-Weinberg equilibrium (HWE) were estimated using the expectation-maximization (EM)232959Na), the percentage of polymorphic loci, P(99%), and the genetic diversity in a population  which is equal to the expected heterozygosity (He) under HWE.Because the maximum number of allele copies is four at a CNV locus in the diploid genotype dataset of HapMap Phase III populations, a three-allele system is used to describe the genotype composition. Note that a system of more than three alleles is needed if the number of allele copies is more than 4 in a diploid genotype23GstGst = 1 − Hs/Ht where Hs is the mean of the expected heterozygosity (He) per locus over all populations and Ht is the expected heterozygosity per locus in the pooled population. The 95% confidence intervals (CIs) for Gst was derived using the bootstrapping approach. To relate the population genetic differentiation to the time since the populations diverge from a single ancestral population, genetic distance was measuredD = −ln(I) where plu1 and plu2 are the frequencies of alleles u1 and u2 at the lth locus from populations 1 and 2, respectively. Under the neutral process (mutation and genetic drift), Nei’s genetic distance is linearly related to the time since divergence (t), i.e. V(t) = V(D)/4μ2, given a mutation rate μ. Standard deviations for Gst and Nei’s genetic distance were calculated using the jackknife methodPopulation genetic differentiation was measured by dij  be the gametic LD between allele i at the first locus and allele j at the second locus, and pij be the gametic frequency in the population. MLE of the frequency of a genotype pair, s, t = 0, 1, 2, 3, 4), can be obtained using the direct counting method. An EM method is used to estimate the gametic frequency through an iterative calculation, which is described below:To assess the properties of CNV loci relevant for interpreting population genetic divergence, both the gametic and zygotic LDs were tested in each population. Assuming that CNV loci are involved in fitness, a comparison of gametic LD with the maximum zygotic LD in value can be used to determine whether epistasis occurs or not among loci3738δij, a Kronecker delta variable, is equal to 1 when i = j, and 0 when i≠j. Note that the E- and M-steps are combined into one formula in pij , the gametic frequency at the next step p′uv can be calculated using pij in p′uv and recalculate p′uv at the next step. This iterative calculation is repeated until the convergence of gametic frequencies is attained.where dij, is then estimated as i at the first locus and allele j at the second locus, respectively. A chi-square statistic with 1 degree of freedom (df) is used to test H0: dij = 0 The gametic LD, 0 or 1 (dij ≠ 0) has a maximum value at the intermediate allele frequencies. A large variance increases the uncertainty and hence reduces the power, given a sample size (n), a significance level (α), and gametic LD. The power also increases as the sample size or the gametic LD increases.R-square, Dij be the zygotic LD between genotypes i at the first locus and j at the second locus  in the population. The MLE of zygotic LD, n can be obtained by i at the first locus and j at the second locus, and i (or j). To test H0: Dij = 0, a chi-square statistic with 1 df is set asLet The normalized r-square is set as −7~6.91 × 10−7 owing to different numbers of polymorphic loci in the 11 populations. To minimize the impacts of minor allele frequency (MAF) on amplifying gametic LD test or on increasing false-positive errors, those alleles with their frequencies being out of the range  in the samples were excluded in testing gametic LD. For the same reason, those genotypes with genotypic frequencies beyond the range  in the samples were excluded in testing zygotic LD. Sample sizes ranging from 77 to 171 can provide appropriate statistical power for genotypic frequencies within the range   for the allele frequency under an equilibrium among genetic drift, mutation, and migration effects can be approximated by synthesizing Kimura’sConsider a neutral CNV locus with three alleles. Let N is the effective population size, mc is the migration rate per generation for an allele at a CNV locus, Q is the migrant allele frequency, and θc (aka “population diversity”) is the population-scaled mutation rate (=4Nμc). Fst per locus is derived aswhere FstGstThe practical population differentiation with Similarly, the pdf of allele frequency at a bi-allelic SNP locus under an equilibrium among genetic drift, mutation, and migration effects can be approximated by synthesizing Kimura’sms is the migration rate per generation, Q is the migrant allele frequency, and θs is equal to 4Nμs in which μs is the mutation rate at an SNP locus. Fst per locus is derived aswhere Fst(SNP)/Gst(CNV), and its standard deviation can be estimated from the variance approximation:The relative extent of genetic divergence at the genome-wide SNP sites versus at the genome-wide CNV loci is measured by the ratio of Fst(SNP) and Gst(CNV), respectively, and cov(Fst(SNP), Gst(CNV)) is the covariance between Fst(SNP) and Gst(CNV). The above expression is derived by the delta methodFst(SNP), Gst(CNV)) is negligible at the genome-wide scale. Correlations between CNV and SNP loci are weak, which could arise from the effects of transposition events, recurrent mutation/reversions, or the preference of CNV loci at the low density of SNP sites on chromosomes12where From X = Fst(SNP)(1 − Gst(CNV)) and Y = Gst(CNV)(1 − Fst(SNP)). Again, assume that cov(Fst(SNP), Gst(CNV)) is neglected at the genome-wide scale. The variance V(X) is given bySimilarly, the variance of this ratio can be estimated using the delta methodV(Y) can be obtained by replacing Fst(SNP) and 1 − Gst(CNV) in Gst(CNV) and 1 − Fst(SNP), respectively. Similarly, V(XY) can be obtained by replacing 1 − Gst(CNV) in Gst(CNV). The covariance cov is given byV(X/Y) can be estimated from the following expression,The variance of the ratio V(X/Y) in The variance mc = ms = m) although local variation might occur among loci . Also, compared with the migration rate, the point mutation rate at the SNP sites can be neglected. Thus, the ratio of the mutation rate to the migration rate at CNV loci can be estimated:It is appropriate to assume that the migration rate is the same, on average, at the neutral CNV and SNP loci .Publisher's note: Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.


Festuca rubra situated along crossed gradients of temperature and moisture using molecular markers and phenotypic measurements, respectively. By comparing population differentiation in putatively neutral molecular markers and phenotypic traits (QST-FST comparisons), we show the existence of adaptive differentiation in phenotypic traits and their plasticity across the climatic gradient. The observed patterns of differentiation are due to the high genotypic and phenotypic differentiation of the populations from the coldest (and wettest) environment. Finally, we observe statistically significant covariation between markers and phenotypic traits, which is likely caused by isolation by adaptation. These results contribute to a better understanding of the current adaptation and evolutionary potential to face climate change of a widespread species. They can also be extrapolated to understand how the studied populations will adjust to upcoming climate change without going through the lengthy process of phenotyping.Species response to climate change is influenced by predictable (selective) and unpredictable (random) evolutionary processes. To understand how climate change will affect present-day species, it is necessary to assess their adaptive potential and distinguish it from the effects of random processes. This will allow predicting how different genotypes will respond to forecasted environmental change. Space for time substitution experiments are an elegant way to test the response of present day populations to climate variation in real time. Here we assess neutral and putatively adaptive variation in 11 populations of  Understanding how climate change will affect the evolution of existing populations is one of the greatest challenges of evolutionary ecology at present. Climate change will result in novel environments but also increased environmental variation, both of which will generate new selective pressures . ExistinThree mechanisms are commonly distinguished as possible responses to climate change–migration, genetic adaptation and adaptive plasticity –5. In plQST) with that based on putatively neutral molecular markers (FST) [FST is the neutral baseline against which population differentiation is measured. If QST = FST, then the observed differentiation in phenotypic traits is solely due to random evolutionary processes, whereas if QST > FST, then the phenotypic traits have likely differentiated under the effects of divergent selection, which were higher than random evolutionary processes.When the existing populations encounter novel climates, the new selective pressures to which they will have to adapt will result in population divergence from their current structure . Understrs (FST) –24. FST F. rubra for phenotypic traits and their plasticity, which are putatively under selection, and for molecular markers, which are supposedly not under selection. Our model species is a perennial grass, Festuca rubra, which has shown significant differentiation in traits and their plasticity on various spatial scales [F. rubra in western Norway to sustain future climate change.In this study, we estimated population differentiation along a temperature and precipitation gradient of eleven populations of l scales –27. We ul scales ,28. We eFestuca rubra L. is a common perennial grass species of temperate grasslands in Europe. F. rubra ssp. rubra used in the experiment is a widespread hexaploid type from the F. rubra complex. It reproduces sexually through outcrossing [F. rubra possess considerable genetic variability and plasticity [crossing  as well asticity –27.F. rubra density, plot morphology and vegetation homogeneity . Theogeneity . Transecribed in . In locaIn March 2015, four single young ramets originating from the maternal ramets were taken from each plant, and each was placed in a different growth chamber. Each growth chamber simulated the spring and summer conditions in one of the four most extreme natural environments observed in the climate grid . The temperature in the growth chamber differed between the cold and warm treatments and changed over the growing season following the course of temperature at the natural localities . Soil moAt the end of August 2015 (21 weeks after placement in the growth chamber) we assessed photosynthetic activity, water potential and stomatal density and size as physiological traits. Photosynthetic activity was assessed through the measurements of the maximum quantum yield of primary PS II and the performance index for energy conservation from photons absorbed by PS II antenna . These tAt the end of the experiment, the number of intravaginal and extravaginal ramets and the plant height were assessed. The total number of ramets was calculated as the sum of intravaginal and extravaginal ramets. Finally, the plants were harvested, dried at 60°C to constant weight, and the aboveground (cut at the 3 cm height above the soil surface), and belowground (rhizome and root separately) biomasses were weighed. We calculated the below:aboveground biomass ratio.MAX−traitmin|)/traitMAX where traitMAX and traitMIN were respectively the maximal and minimal value of the trait measured on the same genotype across the four growth chambers [We calculated the plasticity of all of the measured traits within each genotype as . Quality and quantity of extracted DNA were measured by NanoDrop 2000 , and all the samples were normalized to 20 ng/μl for subsequent PCR. Four microsatellite loci were amplified using and HVM3  and B4-Dand HVM3 . MultiplAll analyses were done in R 3.2.5 . The effQST), we first estimated additive genetic variance and between population variance following a similar approach as in [y = Xβ + Zp + Za + ε where X and Z–incidence matrices assigning fixed and random effects to measurements in vector y, β –the vector of the fixed effects of growth chamber climate and any other unspecific chamber effects, p~N–the vector of random population effects, with σp2 –between population variance and I is identity matrix, a~N–the vector of random individual plant genetic effects, with σa2—within population (additive genetic) variance and G–Loisselle’s kinship coefficient [y = Xβ + Zp + Za + ε Narrow-sense QST was then calculated for trait values and plasticity as To estimate the population quantitative genetic differentiation (ch as in  using thch as in . Within ch as in  as follofficient  matrix efficient  using thQST. We thus estimated the lower bound of QST through the population phenotypic differentiation index (PST) as defined in [y = β + b + ε, where β –the vector of the fixed effects of growth chamber and any other unspecific chamber effects, b~N–the vector of random population effects, with σb2 the variance of random population effects, and ε~N–the vector of residuals, with σw2 the residual population variance. We then calculated PST for trait values and plasticity as c the proportion of between population variance that is due to additive genetic factors only, and h2 trait heritability, or the proportion of within-population genetic variance that is due to additive genetic factors. We assume c = h2= 1, meaning that all of the observed phenotypic variance is due to additive genetic factors only [c = 1 plausible in our study, given that all populations are grown in a common environment, which reduces between population differences that can be due to environmental factors. Assuming h2= 1 is clearly an overestimate of the additive genetic component of σw2, but it is relevant in our case because we want to estimate the lower boundary of PST, which is done by maximising the within-population variance.Kinship coefficient estimates based on four loci could be imprecise and downwardly bias the estimates of within-population variance, resulting in an overestimate of fined in . Within ors only . The assQST-FST (PST-FST) distribution was simulated using the Lewontin-Krakauer distribution [FST (from molecular markers), and of QST (of PST). The quantile of the observed QST (PST) equals FST. This method was particularly suitable for our data set, as it gives reliable results when used with relatively few neutral molecular markers, when population differentiation in molecular markers is low, and when the number of populations is relatively high (ten or higher). Given that microsatellite data can have mutation rates that are higher than migration rates, microsatellite based FST can be downwardly biased. To avoid this, we also made QST—RST comparisons, with RST being an FST analogue based on allele size, calculated following [RST should not be affected by the microsatellite mutation rate, provided that microsatellite size variance is proportional to their genetic distance [To test for the effects of selection on population divergence in quantitative traits, we used the method described in  as impleribution , and theollowing . RST shodistance ,50.Coinertia analysis is a multivariate ordination method that measures the concordance between two data sets. The goal of a COA is to find a multidimensional projection of the two data sets which is a compromise between the maximal variance of each data set and the maximal covariance between the two data sets ,52. COA COA was made using the projections of the first two axes of Principal Component Analysis (PCA) for trait values (or plasticity) and molecular markers. For phenotypic trait values PCA we used the Euclidian distance matrices based on the trait values averaged across growth chambers calculated by the R package ade4 , and forIf significant coinertia was detected between trait values (or plasticities) and molecular markers, we then tested how are the individual projections on the main COA axis (COA axis 1) affected by climate variation. For this, we used ANOVA with temperature and precipitation of origin and their interaction as fixed, quantitative, explanatory variables. Significance levels were estimated using Fisher’s F statistic. A significant ANOVA result meant that the molecular marker variation which was associated with variation of trait value (or plasticity) was also influenced by climate variation. If such a relationship existed, we further tested for alleles that were associates with specific trait values, or which were characteristic for some populations (see below). Note that if allelic frequencies were influenced by phenotypic trait values and/or environmental variables, it does not mean that they were under selection, as microsatellite loci are by default considered to be neutral markers. This association could have been caused by pure genetic drift, or non-random mating patterns. Independent of the causes of the association, the alleles associated with phenotypic traits and climatic variables could further be used to identify individuals with specific phenotypes or thriving in specific climates.We tested for isolation by distance (IBD) and isolation by adaptation (IBA) by estimating the proportion of genetic differentiation between populations explained by geographical and environmental distances, respectively, using Mantel tests (R package vegan). The genetic distance matrix was based on Bruvo distances , and thWe also tested the relationship between population genetic diversity and population trait means or plasticity using Pearson’s product moment correlations. Since the estimate of genetic diversity in hexaploid organisms is not straightforward because complete information about allelic frequencies cannot be obtained ,58, seveThe statistical significance of the association between specific molecular marker alleles and phenotypic traits was tested with Multivariate Analysis of Variance (MANOVA). As the total number of alleles was higher than degrees of freedom associated with the phenotypic traits, we first selected the alleles that were most suitable for the analyses based on abundance criteria. We thus excluded rare or private alleles by selecting only alleles that were either present in seven or more populations, or alleles that were present in less than seven populations but they had population frequencies higher than 0.05. In locus HVM3 we excluded two alleles whose frequency was equal or close to 1 in all populations. Then we tested the effect of all alleles within each locus separately by using step-wise selection procedure within MANOVA. All alleles that were retained for each locus after the step-wise selection were combined together as explanatory variables in a new MANOVA. To make sure that the order of introduction of the alleles did not affect the MANOVA results, type 3 testing was carried out by permuting the introduction order of the alleles. To enable comparison between traits with different units, trait means were z-transformed using the scale function in R. Significance levels were assessed using the Pillai statistic. When a significant effect of at least one allele was observed, we performed individual ANOVAs for each trait separately in order to extract the coefficient of the slope associated with each of the tested alleles.FST: 0.039 ± 0.011 standard error, RST: 0.057 ± 0.047 standard error). QST estimates were obtained for ten out of the twelve phenotypic trait values. QST values for below:aboveground biomass and water potential could not be estimated with our model because their variance components were fixed at the boundary. QST estimates for trait values were generally low (0.072 ± 0.024). Six trait values showed QST-FST significantly different from the neutral QST-FST distribution , and close to 1 for stomatal density, water potential and number of ramets. However, the precision of the QST estimates for trait plasticity was lower than that for trait values , and between plasticity and molecular markers , even in partial tests taking into account environmental distances . Environmental distances showed significant correlation with genetic distances when tested alone  or in partial tests with geographic distances .All estimators of population genetic diversity  showed similar estimates, thus only the correlations with Pons and Petit’s index of population genetic diversity of non ordered alleles are shown . The corFSTand RST). These results need to be taken with precaution, as population genetic differentiation in this study can be somewhat underestimated. First, the of lack of exact allele frequency estimates due to the hexaploid status of F. rubra [RST [F. rubra populations due to neutral genetic processes.Overall, the population genetic differentiation estimated from molecular markers was very low  was overall very low, and did not differ significantly from FST, except for stomatal density. Stomatal density is a trait regulates carbon uptake and water use efficiency of the plant, and as such is highly responsive to environmental variation [PST−FST test, stomatal density shows patterns of adaptive differentiation in our study. For all the other traits, based on PST−FST comparisons, if the selection is acting on these populations, its effects cannot be disentangled from the effects of genetic drift. This result is contradictory to the findings of previous studies using the same approach to estimate the effects of divergent selection [PST estimates in the previous studies were made on traits measured in natural populations. Thus the observed variation between and within populations could include environmental effects, genotype x environment interactions, and non-additive genetic effects, which can inflate the estimated variances [PST.Population phenotypic differentiation , have more effective foraging abilities  and slower growth . Increased foraging and reduced size is a pattern commonly observed in plants in response to different types of unfavourable environments –76. In lF. rubra, it is necessary to relate the degree of plasticity of each individual to an estimate of its fitness [Interestingly, our results suggest that trait plasticity could also be under divergent selection. In our study, differentiation in plasticity is solely due to the higher plasticity of alpine populations according to the coinertia analyses, although alpine and boreal populations are facing the same absolute environmental distances (with opposing signs) in the growth chambers. This could be because alpine populations need to efficiently use the short ‘windows of opportunity’ when favourable conditions occur in the harsh alpine environment to rapidly increase their growth, and have thus evolved higher plasticity to cope with local, micro-environmental variations . This hy fitness ,10,78, w fitness ) makes t fitness .QST estimates have rather low precision and non-significant lower bound estimates (PST), and thus need to be considered with precaution. Only a few other studies have tested for among-population differentiation in phenotypic plasticity using QST-FST comparisons and have found low or non-significant QST for plasticity [The plasticity asticity ,81–83. Hasticity , and canasticity .FST below 5% can still generate strong biases in genetic association or environmental association analyses neglecting this structure [COA results showed significant positive covariation between molecular markers and phenotypic trait values; and between molecular markers and phenotypic plasticity. The association between molecular markers and phenotypes is a general tendency in studies of the divergence of neutral traits and traits under selection ,21,73. Itructure .Regardless of the causes of the observed associations, the information it provides can be used to identify individuals in the populations of this study bearing traits with specific values without going through the lengthy process of phenotyping. Since microsatellites are neutral molecular markers, a statistical association between adaptive traits and microsatellite markers is not informative about the genetic basis of the adaptive trait. However, establishing a relationship between molecular markers, phenotypic traits and environmental variation would help to easily identify genotypes and phenotypes in the studied populations that can be of interest for the future exploration of the response of the studied populations to climate change, by helping to select for appropriate genotypes  to test their response to climate variation. Although the observed marker-trait associations are only relevant for the populations of this study, the same methods can be used to identify analogous associations in other populations, and thus select for new genotypes that have comparable trait associations as those in our study.The alpine populations of this study were overall highly differentiated from boreal and subalpine populations, and among the alpine populations, the population from the wettest habitat was the most genetically and phenotypically distinct. These results are somewhat consistent with an adaptive response to climate, although other environmental factors should not be overlooked. Indeed, we showed that locality explains between 30 and 50% more of the shared inertia than temperature and precipitation combined, so other factors, unaccounted for in this study also contribute and can be more important for shaping the observed patterns.F. rubra will face an increasingly hotter and wetter environment [F. rubra has an upper limit tolerance of temperature and moisture given that the species grows in considerably more temperate environments than Norway, it is unlikely that the boreal populations will face climate restrictions in the foreseeable future. Nevertheless, to reliably predict the response of boreal populations, we need data of their performance in temperature and precipitation conditions that are warmer and wetter than those tested in our study.Finally, according to the climatic predictions for western Norway in the next century, the present populations of ironment , which bironment . Alpine F. rubra is consistent with the effect of divergent selection that is at least partly due to climate. The variation in adaptive traits and their plasticity is also correlated with variation in neutral molecular markers, and the covariation patterns are themselves influenced by variation in climate. Regardless of the causes of the statistical association between quantitative traits and molecular markers, the information it provides can be used to identify individuals bearing traits with specific values within our studied system without going through the lengthy process of phenotyping.In conclusion, quantitative genetic differentiation between populations of S1 Fig(PDF)Click here for additional data file.S2 FigA. and D. Population projection on the first two COA axes. The grey arrows represent the PCA projections of trait values (beginning of arrow) and molecular markers (end of arrow). B. and E. COA axes loadings for phenotypic variables. Black lines–growth related trait means, bold lines–resource acquisition trait means, dashed lines–physiological trait means.φP0– maximum quantum yield of primary PS II photochemistry, PIABS–performance index for energy conservation from photons absorbed by PS II antenna. C. and F. COA axes loadings for genotypic structure. For clarity of the representation, only 15 alleles that have the highest loadings for either axis are shown. Full black lines–locus HVM3, dotted black lines– B3-B8, full grey lines– B4-D9, dotted grey lines–HVM2.(PDF)Click here for additional data file.S3 Fig(PDF)Click here for additional data file.S1 TableThe dimensions are calculated as the distance between the most distant collecting points at two perpendicular directions.(PDF)Click here for additional data file.S2 TableA. MANOVA results of the multivariate analysis of variance of the effect of selected alleles on trait values and plasticities. B. Regression coefficients of individual ANOVAs testing the effect of allelic presence/absence on trait mean and on plasticity.(PDF)Click here for additional data file.S3 Table(PDF)Click here for additional data file.S4 Table(PDF)Click here for additional data file.S5 Table(XLSX)Click here for additional data file.


Sogatella furcifera (Horváth) (Hemiptera: Delphacidae), is a serious pest of rice in Asia. However, little is known regarding the migration of this pest insect from the Greater Mekong Subregion (GMS) including Cambodia, Laos, Myanmar (Burma), Thailand, and Vietnam, into China’s Yunnan Province. To determine the migration patterns of S. furcifera in the GMS and putative secondary immigration inside China’s Yunnan Province, we investigated the population genetic diversity, genetic structure, and gene flow of 42 S. furcifera populations across the six countries in the GMS by intensive sampling using mitochondrial genes. Our study revealed the potential emigration of S. furcifera from the GMS consists primarily of three major sources: 1) the S. furcifera from Laos and Vietnam migrate into south and southeast Yunnan, where they proceed to further migrate into northeast and central Yunnan; 2) the S. furcifera from Myanmar migrate into west Yunnan, and/or central Yunnan, and/or northeast Yunnan; 3) the S. furcifera from Cambodia migrate into southwest Yunnan, where the populations can migrate further into central Yunnan. The new data will not only be helpful in predicting population dynamics of the planthopper, but will also aid in regional control programs for this economically important pest insect.The white-backed planthopper,  Sogatella furcifera (Horváth) (Hemiptera: Delphacidae), is a serious pest of rice in Asia1S. furcifera can damage rice directly by feeding on the rice or indirectly by transmitting plant viruses such as southern rice black-streaked dwarf virus (SRBSDV)34S. furcifera overwinter in Vietnam and southern Hainan Province, and in spring migrate to eastern China, Japan, and Korea, then migrate back to their overwintering areas in autumn8The white-backed planthopper, Sogatella furcifera is one the most destructive pests of rice production in the GMS. The migration information of S. furcifera in the region, especially the immigration source into China’s Yunnan Province, has mainly been derived from trajectory analyses and migration simulations. Previous studies based on weather during the rice growth period and using the HYSPLIT method showed that although a small number of S. furcifera do successfully overwinter in China’s Yunnan Province, the immigrants from the spring migration are the major source of this pest. The source of the April to early May migration into Yunnan were estimated to have originated mainly in Myanmar, while immigrations occurring in mid-May were thought to have come from northern Vietnam1011S. furcifera from five disjunct localities in Korea, the Philippines, China (only two populations), Malaysia, and Vietnam using mitochondrial sequences. Genetic diversity of S. furcifera from Yunnan Province and three Southeastern Asia countries  was also demonstrated using the inter-simple sequence repeat (ISSR) techniqueIt is difficult to determine potential migration source of the insect using conventional approaches such as atmospheric current analysis, fluorescent marker dyes, and radar monitoring primarily due to the small size of the insects coupled with their relatively short lifespan131516171819S. furcifera populations from across the six countries in the GMS by intensive sampling using mitochondrial genes. The objective of this study was to reveal the migration pattern of S. furcifera in the GMS and putative secondary immigration in China’s Yunnan Province. These results will provide insight into migrations of S. furcifera in the GMS countries, and should also form a basis for sustainable management of this economically important pest insect in this region.In the present study, we investigated the genetic structure of 42 The haplotype network tree of mtCOI formed two major groups , which oAmong the 13 shared haplotypes, seven haplotypes were shared by different populations from China’s Yunnan and other GSM countries as follows: 1) Haplotypes H1 and H3 were the dominant shared haplotypes in every population, occupying 75–100% in each population; 2) H6 was shared by the populations from Laos (L2 and L5 populations), Vietnam (V3 population), and China’s Yunnan ; 3) H12 was shared by the populations from Vietnam (V3 population) and China’s Yunnan (JP population); 4) H57 was shared by the populations from Cambodia (C2 population), and China’s Yunnan (GM and BS populations); 5) H34 was shared by the populations from Myanmar (M1 population), and China’s Yunnan ; 6) H61 was shared by the populations from Myanmar (M4 population) and China’s Yunnan (GM population).Among the other six shared haplotypes, (except H73 which was only found in the M1 population from Myanmar), the remaining five haplotypes were shared only by populations within China’s Yunnan Province: 1) H30 was shared by Yunnan’s MS and SM populations; 2) H20 was shared by the province’s SJ and XP populations; 3) H5 was shared by the YUJ and YS populations; 4) H53 was shared by the JP and FN populations; and 5) H28 was shared by the ZY and KY populations.Hd of the populations from China’s Yunnan Province ranged from 0.297 to 0.725 while those from the other countries ranged from 0.173 to 0.830. The average Hd value from China’s Yunnan (0.5043) had no significant difference with those from the neighboring countries (0.4609) (P > 0.05). Thirty-one of the 38 populations had negative Fu’s F and Tajima’s D indices, suggesting a recent post-bottleneck population expansion21Genetic diversity analysis based on mtCOI varied among different populations . For exaFst difference based on mitochondrial genes showed significant differentiation in 74 of the 861 population pairs   , indicatM ranged from 28.6 (from M2 to T1) to 950.9 (from L4 to CX)  (Nem > 1000) in the GSM (excluding China’s Yunnan Province) were found in several populations, including L5 of Laos, C1-C3 of Cambodia, and V2 in Vietnam. The numbers of total migrants in Myanmar and other GSM localities, however, were relatively low.Analysis between each pair of the 42 populations showed the presence of high gene flow among different populations. Unidirectional estimates of 4 to CX) . When thon (Nem) , a high Nem > 1300) were found in a number of populations, including those from south Yunnan , southwest Yunnan , southeast Yunnan , and central Yunnan , although, the numbers in some of the populations from these areas in Yunnan were very low, including KY in south Yunnan (Nem = 0.4), FN in southeast Yunnan (Nem = 0.7), GM in southeast Yunnan (Nem = 0.7), and SM in central Yunnan (Nem = 1.3). A number of the populations from western and northeastern Yunnan were also relatively low. This was especially true in the majority of those from western Yunnan where the numbers were quite low (Nem < 1.8) except in the MS population (Nem = 320.3). Interestingly, the average value for number of migrants into south Yunnan was the highest of all areas while that of west Yunnan was the lowest among all of the Yunnan populations.In China’s Yunnan Province, a relatively high numbers of migrants  the S. furcifera populations from Myanmar, west Yunnan, central Yunnan, and northeast Yunnan; 3) and the S. furcifera populations from Cambodia and southwest Yunnan. According to the seasonal weather data, we can infer that potential immigrations into Yunnan, China may occur in at least three main potential sources: 1) a source from Laos and Vietnam into adjacent southeastern and southern Yunnan; 2) a source from Myanmar into the adjacent western Yunnan, with subsequent migrations into central and northeastern Yunnan; 3) a source from Cambodia into southwestern Yunnan. For the potential source populations from Myanmar or Cambodia, they may be introduced into China’s Yunnan indirectly because of the long geographical distance, which should be further explored in the future researches.Based on shared mtCOI haplotypes, a close association was found to exist between: 1) the In Yunnan Province, the haplotype composition of the populations in central Yunnan is closely linked with that from southeast Yunnan, west Yunnan, and southwest Yunnan since the H20, H30, and H5 haplotypes discovered in central Yunnan are also found in the latter three regions. When combined with the seasonal weather patterns, the populations in central Yunnan may have several sources such as from the neighboring regions. The haplotypes of the populations in south Yunnan are also closely associated with that found in northeast Yunnan, suggesting a potential immigration source from south Yunnan into northeast Yunnan.S. furcifera from the GMS consists primarily of three major sources: 1) the S. furcifera from Laos and Vietnam migrate into south and southeast Yunnan, where they proceed to further migrate into northeast and central Yunnan; 2) the S. furcifera from Myanmar migrate into west Yunnan, and/or central Yunnan, and/or northeast Yunnan; 3) the S. furcifera from Cambodia migrate into southwest Yunnan, where the populations can migrate further into central Yunnan.Based on the combined data mentioned above, the potential emigration of S. furcifera populations in Yunnan, China are consistent with previous studies. Based on their analysis using the HYSPLIT model, Shen et al.S. furcifera into Yunnan, China in 2009 were located in Myanmar, and that secondary source areas were in Laos and Vietnam, with a few coming from the Imphal area in Manipur, India. The frequent westerly winds coupled with the tremendous increase in rice production in the Myanmar source areas were considered to be the principal reasons causing the mass migration of S. furcifera into Yunnan Provinceet al.S. furcifera in May were located in the middle of Myanmar, and secondarily in northern Thailand and Vietnam. The westerly and southwesterly wind carried massive numbers of S. furcifera into Funing (FN), a site in southeastern Yunnan. Wind shear combined with the occurrence of threshold flying temperatures associated with rainfall, caused a mass descent of S. furcifera. An analysis by Zheng et al.These postulated multiple sources of the S. furcifera migrants. This data will be helpful in predicting the population dynamics of this economically important planthopper, and will aid in regional control of this major pest insect.Our study not only reveals the potential migratory sources from Myanmar, Vietnam, and Laos, but also adds Cambodia as another source of Bemisia tabaci biotype Q in Shandong, China, while the mitochondrial genetic diversity was considerably lowerThe genetic diversity of species is closely associated with their ecological adaptations, which have been explored in many species especially in invasive alien species1923Although, based on mtCOI data, it is apparent that migrations from and within the GMS consist of many sources, detailed migration patterns may be more complex than expected due to variations of yearly ecological factors occurring in this region. In addition, recent studies have revealed the differences resulting from using mitochondrial and nuclear markers18232527S. furcifera populations analyzed in this study enabled us to infer the planthopper’s migration sources. Based on our results, we can speculate that the potential migration of S. furcifera from the GMS consisted primarily of three major sources: 1) the S. furcifera from Laos and Vietnam migrate into southern and southeastern Yunnan. These populations can later migrate into northeast and central Yunnan; 2) the S. furcifera originating from Myanmar migrate into western Yunnan, and/or central Yunnan, and/or northeastern Yunnan; 3) the S. furcifera from Cambodia migrates into southeastern Yunnan, where the populations can further migrate into central Yunnan. Our study not only reaffirmed the detailed potential migration source from Myanmar, Vietnam, and Laos, but also demonstrated the migration of S. furcifera from Cambodia. The added data will be helpful in predicting the population dynamics of this pest insect, which, in turn will be useful in regional control programs for the planthopper.The genetic diversity and structures found in the S. furcifera samples were collected from 42 locations in the GMS during 2014–2015  and L2-N-3014 (5′-TCCAATGCACTAATC TGCCATATTA-3′) and then sequenced2, 0.2 μM dNTPs, 1 unit Taq DNA polymerase, 2 μL template DNA, and 0.2 μM of each primer. PCR amplification was carried out as follows: initial denaturation at 94 °C for 5 min, followed by 35 cycles each of 30 s at 94 °C, 30 s at 50 °C, and 60 s at 72 °C, and a final elongation step at 72 °C for 30 min.The cytochrome coxidase subunit I gene of the mitochondrial DNA (mtCOI) was used to determine the genetically distinct populations of These sequences of mtCOI were aligned with Clustal WS), the total number of mutations (η)K)Hd)π)π (JC))Da (JC)D (D)F testThe genetic diversity indices of each population which were analyzed based on mtCOI using DnaSP v.5.0FstThe Weir and Cockerham’s fixation index S. furcifera populations in the GMS, was determined by calculating the effective numbers of migrants per generation Nem using mitochondrial COI data. Nem is ϴM  calculated using Bayesian search strategies in MIGRATE v. 3.2.16 softwareThe dispersal of different How to cite this article: Li, X.-y. et al. Possible Source Populations of the White-backed Planthopper in the Greater Mekong Subregion Revealed by Mitochondrial DNA Analysis. Sci. Rep.6, 39167; doi: 10.1038/srep39167 (2016).Publisher's note: Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.