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Article

The Molecular Evidence for Invasive Climber Echinocystis lobata (Michx.) Torr. & A. Gray in Eastern and Central Europe

by
Lina Jocienė
1,*,
Edvina Krokaitė
1,
Tomas Rekašius
2,3,
Erika Juškaitytė
1,
Irina Ielciu
4,
Olga Galanina
5,6 and
Eugenija Kupčinskienė
1
1
Department of Biology, Faculty of Natural Sciences, Vytautas Magnus University, K. Donelaičio Str. 58, 44248 Kaunas, Lithuania
2
Department of Mathematics and Statistics, Faculty of Informatics, Vytautas Magnus University, K. Donelaičio Str. 58, 44248 Kaunas, Lithuania
3
Department of Mathematical Statistics, Faculty of Fundamental Sciences, Vilnius Gediminas Technical University, Saulėtekio Ave. 11, 10223 Vilnius, Lithuania
4
Department of Pharmaceutical Botany, Cell Biology and Pharmacogenetics, Faculty of Pharmacy, “Iuliu Hatieganu” University of Medicine and Pharmacy Cluj-Napoca, Strada Victor Babeș 8, 400337 Cluj-Napoca, Romania
5
Department of Biogeography and Nature Protection, St. Petersburg State University, 7-9 Universitetskaya Embankment, St. Petersburg 199034, Russia
6
Department of General Geobotany, Komarov Botanical Institute RAS, Professor Popov Str. 2, St. Petersburg 197022, Russia
*
Author to whom correspondence should be addressed.
Diversity 2023, 15(10), 1084; https://doi.org/10.3390/d15101084
Submission received: 1 August 2023 / Revised: 2 October 2023 / Accepted: 10 October 2023 / Published: 13 October 2023
(This article belongs to the Section Plant Diversity)
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Abstract

:
The climbing cucurbit Echinocystis lobata, native to North America and alien to many European countries, was assessed for its genetic diversity and differentiation across its introduced range of populations by applying markers of amplified fragment length polymorphism (AFLP). Various tests, including an evaluation of the intrapopulation diversity, principal coordinate, and molecular variance analyses, showed that the Central and Eastern European populations differing in geography and arrival history are also distinct in the genetic parameters. Genetic diversity, defined as the percentage of polymorphic AFLP loci, ranged within 28–62% (on average 51%) at the regional scale (in Romanian, Baltic State, and Central Russian populations), and was very similar to this parameter at the local scale (on average 52% for Lithuanian populations). The differentiation was significant among the populations of the regions (Ф = 0.125, p = 0.001) and at the local scale (among the Lithuanian populations of the different river basins, Ф = 0.058, p = 0.010). The Bayesian results suggested the presence of three genetic clusters among the 29 sites, with populations from Romania, Latvia, Estonia, and the northern part of Lithuania comprising one prevailing cluster, populations from the Nemunas river basin of Lithuania comprising either the former mentioned cluster or the second cluster, and populations of Central Russia comprising the third genetic cluster. Overall, E. lobata in Europe has probably originated from multiple introductions. The intentional anthropogenic seed dispersal by marketing accompanied by hydrochory might have an impact on such a profile of genetic clusters.

1. Introduction

The number of new invasive and potentially invasive alien plant species in European countries has been increasing from the end of the 18th century to the present day, and the expansion of such plants has accelerated especially over the last few decades of the last century [1,2,3,4,5,6]. At the same time, threats to the environment imposed by invasive species are rising [1]. Due to the intensive penetration of foreign plants into pristine communities, the number of local species decreases, ecosystem functioning is distorted, and ecosystems lose their beauty and economic value [7]. As invasions intensify, so do the economic costs of eradicating invasive alien species [8]. Considering the invaders’ impacts on the environment on one side and the economic losses on the other side, there is a need for wise, comprehensive management of the environment by limiting and eradicating widely spread adverse alien plants. Such visions were [9] and remain [10] an important part of the EU strategy. The successful implementation of management policies first requires a comprehensive scientific knowledge of each new unwanted species.
The early European conquerors of the last century such as Impatiens parviflora DC. [11,12,13,14] or Elodea canadensis Michx. [15,16,17,18] were comprehensively analyzed in terms of both the temporal and spatial scale and methods. Much less is known about the most recent invasive alien plants which started to intensively grow and spread in the last few decades of the previous century. By trailing to the canopy of local species and blocking the sunlight to the plants growing below, the three-dimensional invasion of climbers may cause damage to vegetation, reducing the genetic and species diversity, productivity, and altering the circulation of nutrients in the ecosystem [19]. In the analysis of invasive plants, the group of climbing plants has rarely been considered separately [20]. Following the generally accepted approaches to life form classification [21], most former EU surveys of invasive plants did not separate climbing plants as a group, and only recently performed analyses of the life forms of invaders have distinguished the branches of herbaceous climbers and woody climbers from the other types of life forms [22]. Only a few trailing canopy species, Parthenocissus quinquefolia (L.) Planch., Lonicera japonica Thunb. and Vitis vinifera L. met the selection criteria for the most widespread alien plants in Europe [1]. Four climbing plants including Humulus scandens (Lour.) Merr., Celastrus orbiculatus Thunb., Persicaria perfoliate (L.) H.Gross, and Pueraria montana var. lobata (Willd.) Ohwi, are considered as invasive alien species of concern to the European Union [23]. Although not listed in the aforementioned catalogs of invasive plants, in recent decades, the foreign ornamental climbers Sicyos angulatus L., Bryonia spp., and Echinocystis lobata (Michx) Torr. & A.Gray (Cucurbitaceae) are demonstrating exceptional growth and conquering some areas of Europe [24,25,26,27,28,29,30]. Among these cucurbits, the greatest expansion along Central and Eastern Europe is documented for E. lobata [1,2,5,24,31,32].
Echinocystis lobata, commonly called wild cucumber, is a species of the genera Echinocystis in the Rosids, Fabids clades [33], Cucurbitales order, and Cucurbitaceae family [33,34]. This species name has many scientific synonyms: Echinocystis echinata (Muhl.) Vassilcz.; Echinocystis echinata Britton, Sterns & Poggenb.; Hexameria echinata Torr. & A.Gray; Micrampelis lobata (Michx.) Greene; Momordica echinata Muhl.; Sicyos lobatus Michx. (basionym); and some English synonyms such as wild balsam apple and prickly cucumber. It is a high-climbing (2–6 m, up to 12 m) [35,36,37] monoecious protandrous annual herb with racemes of nectary staminate flowers and several or solitary white or greenish-yellow pistillate flowers [34,38,39], it is 2n = 32, self-pollinated or cross-pollinated by wasps, beetles [40], with one individual producing up to several hundred seeds enclosed into spiny capsules (with four seeds in each capsule), which can be spread over short distances (2–5 m) by autochory (one case of blastochory) and over long distances by hydrochory (cases of bythisohydrochory and nautohydrochory), zoochory (by birds and rodents), intentional anthropochory [41,42,43,44], establishing arbuscular mycorrhiza [45], containing polyphenols (p-coumaric acid, isoquercitrin, rutin, quercitrin) [46,47]. Among the various aspects of the invader’s biology (morphology, growth and development, and sociology) comprehensively reviewed for E. lobata [24,41,48,49], almost every country’s research has been dominated by ecological-geographic topics.
Within its native range of distribution, E. lobata is growing in lowland forests and thickets, riparian woods, marshes, fencerows, ditches, lake shores, railroad banks, and dunes [34]. In New York State, E. lobata was briefly described as a plant of damp places, rarely occurring in the dense stands typical for other annuals [35]. As defined by EUNIS codes [50], the invasive European habitats of the species are attributed to littoral zones of inland surface water bodies (C3), woodland fringes (E5), riverine and fen scrubs (F9), broad-leaved deciduous woodlands (G1), and cultivated areas of gardens (I2) [40]. It is thought that E. lobata may have escaped from gardens by natural dispersal (autochory and hydrochory) [41], and by deliberate human activity (gardeners discarding viable plants or seeds in wastelands and landfills). Among the frequent habitats of invasive E. lobata, most researchers indicate disturbed, ruderal sites: fences, around cottages, abandoned gardens, wastelands and garbage dumps, as well as roadsides with ditches [24,48,51]. The characteristics of the most typical environment of E. lobata, as defined by the Ellenberg indicatory values (EIV) on the scale of 1 to 9 [52], combines three extreme factors—very moist soil (F = 9), very rich soil (N = 8), and high temperature (T = 8). There are no other factors of a wider range. In support of the high EIV of soil richness were findings of the other E. lobata studies [2,41,48,53,54]. Therefore, it is not surprising that this species was not included into the list of 1071 invasive organisms of the Global Invasive Species Database [55], which is of worldwide importance. This is also an explanation of why this species was not detected as an invader in more than 25 regions of Europe (criteria used to select the 150 most widespread alien species in Europe) [1].
Phytogeographical analyses provided evidence about the time of arrival of E. lobata to Europe, including its introduction and escape from cultivation to pristine nature. E. lobata arrived in Europe between the end of the 19th century and the beginning of the 20th century as an ornamental species [56] in particular suitable for the design of covering fences and for designing arbors and summerhouses. The species was assumed by ethnopharmacologists to be a medicine for all diseases [41]. The first case of escape of this species from cultivation in Europe was registered in Derestje (Southern Transylvania, Romania), in 1904 (the species was identified as Sicyos at that time) [41]. In 1906, self-spreading individuals were found in the Czech Republic [57]. Later, the species was documented as an escapee from gardens in Hungary (1913), Austria, Germany, and Switzerland (1922) [41,58,59] (there are assumptions that E. lobata become naturalized in Austria and Germany most likely during the First World War), Ukraine (1929), Slovakia (1933), Slovenia (1945) [41], and Poland (1937 [24] or 1954 [41]). In the 1960s, E. lobata was cultivated in Central Russia and in the 1970s it was observed that the species had spread to natural areas [31,60,61,62]. There has been increasing invasion of E. lobata during the last 40 years along ruderal and riparian habitats from Western to Eastern Europe. In addition to the mentioned regions, some other countries have also reported a recent spread of E. lobata in Moldavia [63], Bulgaria [64], Greece [65], Croatia [66], Serbia [32,67], Bosnia and Herzegovina [68], and Belorussia [51]. Some countries have provided numerical evidence about the frequency of populations of the species: E. lobata was registered in 8.4% of all sites in Romania [6], in 19.4% of all sites in Poland [24], in 2.5% of all sites and 80% of riparian sites in Latvia [2], in 43.2% of riparian plots in Slovenia [69], in 34 geographic regions out of 45 regions of Russia (accounting for 83% of the territory of country) [31]. In the Baltic countries, the cultivation and subsequent naturalization of E. lobata started later compared to Poland [25] and other aforementioned countries of more southern locations. In Estonia, E. lobata was described as a rare species [70,71]. In Latvia, the cultivation of the species started in the 1960s and its naturalization started in the 1980s [2,53]. The cultivation of E. lobata in Lithuania was first documented in 1960 in a book about Lithuanian climbing plants [72]. Echinocystis lobata was described as a popular ornamental plant, in addition, it was mentioned that the species was exceptionally abundant in some areas, especially in Kaunas, Kaišiadorys, and Druskininkai [72]. The large number of individuals could not be explained solely by human-mediated dispersal, and the idea of birds as seed distributors of E. lobata was documented in this book. Therefore, it is suggested that the naturalization of E. lobata in Lithuania might have already started by the end of the 1950s. The first herbarium specimen of Lithuanian E. lobata growing as an escapee from cultivation was collected much later, in 1987, and at the end of the previous century, the species had become common throughout Lithuania [73].
Many Lithuanian invasive plant species have been examined using molecular markers: Impatiens parviflora DC. [14,74], Erigeron annuus (L.) Pers. [75], Impatiens glandulifera Royle [76,77,78], Lupinus polyphyllus Lindl. [79], Bunias orientalis L. [80], and Medicago sativa L. [81]. To our knowledge, neither in Lithuania nor in any other country have molecular markers been applied to study E. lobata populations. The use of the most advanced molecular markers, such as microsatellites/simple sequence repeats (SSRs) [82] and amplified fragment length polymorphic DNA (AFLP) [83], has provided valuable data concerning the invasion processes of the most aggressive climbing aliens in the world, such as Mikania micrantha Kunth [84] or Pueraria montana var. lobata (Willd.) Ohwi [85].
A variety of molecular markers—Restriction Fragment Length Polymorphism (RFLP), Critical Assessment of Structure Prediction (CAPS), Simple Sequence Repeat (SSR), and Single Nucleotide Polymorphisms (SNPs)—are used in agronomy and forestry, especially in phytopathology [86,87]. Although, in the research of invasive plant populations the most often-used markers are SSR and AFLP. Microsatellites exhibit codominance and are usually highly polymorphic [88,89], and although they are species-specific markers, their development requires a significant investment, and their cross-species transferability is limited [14,90,91]. Until now, simple sequence repeat markers have not been developed for E. lobata. AFLP has become a very popular method globally to probe organisms (including invasive plants) for genetic diversity without any prior knowledge of the genome; these are dominant, cost-effective, reproducible, and hypervariable markers that randomly target sequences scattered all over the genome and are transferable between distantly related plant taxa [92,93].
Taking all this into consideration, our study aimed at an evaluation of AFLP loci diversity and differentiation of Echinoctis lobata populations in Lithuania and other Baltic States, Romania, and Central Russia with the purpose of finding out the possible ways of species invasion in Europe.

2. Materials and Methods

2.1. Sites and Sample Collection

Sampling was performed in five countries: Lithuania, Latvia, Estonia, Central Russia (henceforth titled as Russia), and Romania. Twenty-nine populations of Echinocystis lobata were chosen (Table 1). Plant populations were named after river names and were given abbreviations with numbers, where the lowest represented the highest position of the population in relation to the river flow.
Geographical coordinates of E. lobata populations ranged from 53°59′50.5″ to 58°28′01.6″ latitude (N) and from 21°07′34.6″ to 42°18′21.6″ longitude (E) (Figure 1).
A total of 143 individuals were collected for molecular analysis (five individuals from each population, except for the Estonian Ema population where three individuals were taken) [94]. Sampling was carried out at the flowering stage of the plants following distances between plants described in the former research [95,96]. Leaves for DNA extraction were taken from healthy plants with no visible mechanical, fungal, or bacterial damage.

2.2. Molecular Analysis

Total genomic DNA was extracted using the universal genomic DNA extraction kit (#K0512; Thermo Fisher Scientific, Vilnius, Lithuania). Dried leaf tissue was ground in liquid nitrogen and used for DNA extraction according to the manufacturer’s protocol, with some modifications as described previously [76]. Agarose gel electrophoresis and UV spectrophotometry (BioSpec-Nano, Shimadzu, Kyoto, Japan) were used to assess DNA quality and quantity.
Amplified fragment length polymorphism analysis was performed according to the protocols of Voss et al. [84] with some modifications [96,97,98]. Restriction and ligation reactions were carried out for 2 h at 37 °C in a final volume of 11 µL containing 200 ng of DNA, 0.05 mg/mL BSA, 1X T4 DNA ligase buffer, 0.05 M NaCl (Invitrogen by Thermo Fisher Scientific, Vilnius, Lithuania), 5 U EcoRI and 1 U MseI of restriction enzymes (New England BioLabs, Ipswich, MA, USA), 67 U T4 DNA ligase, 0.45 pmol/µL EcoR I adapter (F: 5′CTCTGACTGCGTACC3′, R: 5′AATTGGTACGCAGTA3′) and 4.5 pmol/µL MseI adapter (F: 5′GACGATGAGTCCTGAG3′, R: 5′CTACTCAGGACTCAT3′) (Invitrogen by Thermo Fisher Scientific, Vilnius, Lithuania). Restriction–ligation products were diluted 1:1 with deionized H2O.
The polymerase chain reaction (PCR) mix for pre-selective amplification was performed in a final volume of 20 µL containing 4 µL of restriction–ligation product, 1.5 ng/µL of each EcoRI A (5′TACTGCGTACCAATTCA3′) and MseI C (5′GATGAGTCCTGAGTAAC3′) pre–selective primers (Metabion International AG, Planegg, Germany), 200 µM dNTPs, 2 µL, 1X Dream Taq buffer, 0.8 U DreamTaq polymerase (Thermo Fisher Scientific, Vilnius, Lithuania). The PCR was performed in a Mastercycler® EP Gradient S (Eppendorf, Hamburg, Germany), using the following program: 72 °C for 2 min, 20 cycles of 94 °C for 20 s, 56 °C for 30 s, 72 °C for 2 min, followed by 60 °C for 30 min, as it was used earlier [98]. Pre-selective amplification products were diluted 1:5 with deionized H2O.
For the final selective AFLP amplification, 8 selective primer pairs were used (Table 2). The PCR mix was performed in a final volume of 4.4 µL containing 1 µL of pre-selective amplification product, 1X Green PCR Buffer, 1.5 mM MgCl2, 0.2 mM dNTPs, 0.105 µL KB Extender, 0.7 U Platinum Taq DNA Polymerase (Invitrogen by Thermo Fisher Scientific, Vilnius, Lithuania), and 1.8 pmol/µL of each forward and reverse selective primer (Metabion International AG, Planegg, Germany). EcoR I primers were labeled with a fluorescent dye. The following PCR program was used for selective amplification: 95 °C for 15 min, followed by 10 cycles of 94 °C for 20 s, 66 °C for 30 s (decreasing by 1 °C per cycle), 72 °C for 2 min, followed by 20 cycles of 94 °C for 20 s, 56 °C for 30 s, 72 °C for 2 min, followed by 60 °C for 30 min.
Selective amplification products were mixed with Hi-Di Formamide and GeneScanTM 500 LIZ size standard (Applied Biosystems, Foster, CA, USA) and denatured at 95 °C for 3 min. Capillary gel electrophoresis was performed on an ABI Prism 3130 × L Genetic Sequencer (Applied Biosystems, Foster, CA, USA). Analyses of 10 randomly selected samples were repeated to check the reproducibility of the data. Patterns of AFLP peak rows were visualized by GeneMapper v. 4.0 (Applied Biosystems, Foster, CA, USA). AFLP peaks were recorded manually in the range of 50–500 bp. A binary matrix indicating the presence (1) or absence (0) of the AFLP fragments was constructed and used for further analysis.

2.3. Statistical Data Analysis

Genetic diversity statistics (%P—percentage of polymorphic loci; h—Nei’s [99] gene diversity, I—Shannon’s information index) and principal coordinate analyses (PcoA) were performed using GenAlEx v. 6.5 [100]. An analysis of molecular variance (AMOVA) based on Nei’s [99] genetic distances was performed, using the same software. Genetic variation among and within populations (two-level analysis) also among regions/groups, among populations, and within populations (three-level analysis) were calculated. A Mantel test (with 9999 permutations) was performed to examine the correlation between genetic and geographic distances of populations employing GenAlEx v. 6.5. Population relationships were examined by constructing a dendrogram based on Nei’s [99] genetic distances and an unweighted pair group method with arithmetic mean (UPGMA) in PopGene v. 1.32 [101]. Bootstrap analysis of 1000 iterations was applied to evaluate the clusters generated by UPGMA with TFPGA [102]. The genetic structure of E. lobata populations was assessed by Bayesian clustering analysis in Structure v.2.3.3. [103]. The number of genetically homogeneous clusters (K) was determined following the methodology of Evanno et al. [104]. Twenty replicate simulations were run for each K ranging from 1 to 29. The analysis was performed using an admixture model with 105 burn-in periods and 106 Markov chain Monte Carlo simulations. The log probability of the data between successive likelihood values was estimated to identify the most relevant number of K.

3. Results

The eight pairs of AFLP primers generated 328 polymorphic fragments. The length of the fragments ranged from 50 to 496 bp (Table 2). The lowest number of fragments (21) was generated by the EcoRI AGC + MseI CAC primer pair and the highest (62) generated by the EcoRI AAC + MseI CTG primer pair, the average number of fragments per primer was 41.1. The total number of fragments per population ranged in the interval of 306–326, with an average value of 317.6 (Table 3). The number of polymorphic fragments per population ranged in the interval of 93–205, with an average value of 167.8. The lowest number of polymorphic loci was found in the Estonian population Ema and the highest number was found in the Lithuanian population Lei. The percentage of polymorphic fragments per population ranged from 28.27% to 62.31%, with a mean of 51.00%. The lowest level of polymorphic fragments was found in the Estonian population Ema. A relatively low level of polymorphism was also found in the Lithuanian populations Ven2 (38.6%) and Šyš (43.47%). The Lithuanian population Lei had the highest level of polymorphism, and a similar level of polymorphism was found in the Lithuanian populations Ner3 and Nem4 (58.36%). The Nei [99] gene diversity and Shannon index values of the populations ranged from 0.120 to 0.272 and from 0.173 to 0.390, respectively. The lowest and highest values of these indices belonged to the same populations, as in the case of the percentage of polymorphic fragments. The mean gene diversity between the populations was 0.218 and the Shannon index was 0.313; the most extreme values of these parameters differed 2.3 times.
The geographical distances between E. lobata populations ranged from 3 to 1784 km (upper triangle of Table 4). The shortest geographical distances were between the Lithuanian populations Mer1 and Mer2 (3 km) and the Lithuanian populations Nem1 and Nem2 (4 km), while the longest geographical distances were between the Russian and Romanian populations (1431–1784 km).
Nei’s [99] genetic distances between pairs of E. lobata populations varied between 0.034 and 0.322 (lower triangle of Table 4), the most contrasting pairs of populations differed 9.5 times, and the average distance between pairs of populations was 0.187. The smallest genetic distances were determined for the Romanian population pairs Som1 and Som2 (0.034), for the Russian population pairs Dbn and Gal (0.074), and for the Lithuanian population pairs Ven1 and Ven2 (0.086). The largest genetic distances were found between the Lithuanian Ner1 and the Russian Dbn populations (0.322), between the Lithuanian Jūr and the Russian Dbn populations (0.316), and between the Lithuanian Atm and the Russian Dbn (0.313).
Mantel’s [105] test (Figure 2) revealed a significant (p = 0.01) relationship between the geographic distances and Nei’s [99] genetic distances of E. lobata populations.
A dendrogram based on Nei’s [99] genetic distances using the UPGMA population clustering method showed that the populations fell into two main clusters. The first one consisted of the Romanian and Russian populations and the second one of the Lithuanian, Latvian, and Estonian populations (Figure 3). In the first cluster, the Romanian populations Som1 and Som2 (cluster Ia) were separated from the Russian populations Dbn and Gal (cluster Ib), while in the second cluster, the Estonian Ema, and the Lithuanian and Latvian populations of the Venta and Lielupė basins (Ven1, Ven2, Ven3, Kul; cluster Iia) were separated from the Lithuanian Nemunas basin populations (cluster Iib).
The principal coordinate analysis subdivided the populations of E. lobata into four groups (Figure 4), corresponding to the second-order branches Ia, Ib, Iia and Iib of the population dendrogram (Figure 3): Ia—Romanian population group (Som1, Som2), Ib—Russian population group (Dbn, Gal), Iia—Estonian (Ema) and the population groups of the Venta and Lielupė basins (in Latvia and Lithuania) (Ven1, Ven2, Ven3 and Kul) and Iib—population group of the Nemunas basin (in Lithuania). The first axis of the principal coordinates explained 16.1%, the second axis explained 8.8%, the third axis explained 8.6%, the first two axes explained 24.9%, and all three axes explained 33.5% of the total genetic variability of the populations.
According to the two-level AMOVA, the intrapopulation variance of all E. lobata populations was significantly higher (89%) than the interpopulation variance (11%; Ф = 0.109, p = 0.001; Table 5 (section A). Very similar results (90% and 10%, respectively; Ф = 0.095, p = 0.001; Table 5B) were obtained when only the populations of the Baltic States were assessed for molecular variance. No significant differences were found in the molecular variance of the Russian and Romanian populations (Ф = 0.044, p = 0.057; Table 5 (section C). The three-level AMOVA analysis showed that when the populations were grouped by country (Baltic States, Russia, and Romania), the intrapopulation variance (81%; Ф = 0.192, p = 0.001; Table 5 (section D) was also significantly higher, and the interregional variance (12%; Ф = 0.125, p = 0.001) was higher than the interpopulation variance (7%; Ф = 0.077, p = 0.001). When the populations were grouped by river basin, the intrapopulation variance was significantly highest (86%; Ф = 0.144, p = 0.001; Table 5 (section E), and diversity between the river basin populations was higher (9%; Ф = 0.089, p = 0.001) than the interpopulation diversity (6%; Ф = 0.061, p = 0.001).
The Bayesian analysis of the highest ΔK values showed that the E. lobata populations formed 26, 28, or 3 genetic clusters (Figure 5). The probability plot showed that the lowest dispersion and most stable results were obtained at K = 3.
Genetic clusters on the map are shown in blue, yellow, and red colors (Figure 6) and are referred to by these colors in the following text.
Among the Lithuanian populations, the blue cluster was prevailing in some populations (Ven1, Ven2, Kul, Šyš, Nem4, Lok, Dub1, Dub2, Nev1, Ner3, Nev2, Mer2, Nem1, Nem2, Kia), and the yellow cluster in others (Mar, Atm, Lei, Jūr, Ner1, Ner2, Nem3, Mer1). In the Latvian and Estonian populations (Ven3 and Ema) the blue cluster was dominating—96.3%. In the Romanian populations (Som1 and Som2) the blue cluster also dominated—96.3–98.2%, and in the Russian populations (Gal and Dbn) the red cluster was dominating—99.2–99.4%.

4. Discussion

4.1. Genetic Diversity of Populations

Adaptation processes are crucial when a species occupies new areas, and they might be reflected in the gene pool of invasive plants. To date, we are unaware of any molecular analysis of E. lobata populations within either the natural or invasive range of distribution. Therefore, the only evaluations of our data might be made in comparison of E. lobata to the other alien species tested by DNA markers.
A significant bottleneck effect was recorded for all South China populations of invasive Mikania micrantha with both low and high percentage polymorphism (P%) (ranging within 11–93%, on an average 41.84%) [84], so the possibility that European populations of Echinocystis Lobata have also experienced a bottleneck effect cannot be ruled out when interpreting the results of our investigation. Studies of some other invasive species such as Mikania micrantha [84], Lythrum salicaria [106], Phragmites australis [107], Impatiens glandulifera [108], and Alliaria petiolata [109] have shown significantly lower genetic diversity in populations of the invasive distribution range compared to the populations of the natural distribution range. Based on these facts, it was most likely that the populations of E. lobata in Central and Eastern Europe would not exhibit high genetic diversity. The evaluation of 29 European populations of E. lobata revealed a P% ranging within 28–62% (on an average value 51%) (Table 3). The polymorphism of European E. lobata might be considered moderate compared to the P% found in Ambrosia artemisiifolia (ranging within 76–81%) [110].
A recent comparative study of different invasive species did not show that the genetic diversity of the invasive populations is significantly lower than that of the pristine populations [111]. The conclusions of such analyses are not of great value due to the use of different molecular markers and different genetic parameters in various studies: in some investigations, intrapopulation indices, such as the percentage of polymorphic loci in populations (P%), Nei‘s index of the genetic diversity, h, the content of polymorphic information, PIC [84,106,110], while some other studies emphasize interpopulation data by presenting kinship dendrograms, differentiation (by AMOVA), and Bayesian gene clustering [112,113]. In addition, the species itself may be an important factor in determining the course of the invasion. It is well-known fact that cross-pollinating species exhibit a higher genetic diversity compared to self-pollinated species [114]. Cross-pollination is the predominant mode of pollen transfer in E. lobata [34,35,39].
The polymorphism of Lithuanian E. lobata populations (%P ranged within 39–62%, on an average 52%) differed little form the polymorphism of all populations studied by us (%P ranged within 28–62%, on average 51%). In terms of the number of populations, similarly to this study conducted on E. lobata, there was an analysis of the populations of another invasive Lithuanian species, Impatiens parviflora, evaluated with the same eight AFLP markers [98]. The average P% value (20%) of the Impatiens parviflora populations was significantly lower than that of the Echinocystis lobata populations. The average %P of the Impatiens parviflora populations was also low when evaluated by other molecular markers: 21% at randomly amplified polymorphic DNA (RAPD) loci [73] and 16.5% at inter-simple sequence repeat (ISSR) loci [14]. The invasion of I. parviflora in Lithuania started much earlier [14] compared to Echinocystis lobata invasion. The average polymorphism of populations of other Lithuanian invasive species was as follows: 65% at SSR loci [78] and 21% at RAPD loci for Impatiens glandulifera [76], 15% at ISSR loci for Bunias orientalis [80], 46% at ISSR loci and 50% at RAPD loci for Erigeron annuus [75], and 29% at ISSR loci for Bidens frondosa [115]. By comparing the Lithuanian data on the amount of polymorphism in populations of various alien invasive species, it might be concluded that the Echinocystis lobata P% was among the highest. It is worth nothing that E. lobata filled an “empty” niche, since it is the only climbing invader among 18 invasive alien species in Lithuania [116].
The lowest P% of E. lobata (28%; Table 3) was found in the northernmost Baltic site (Ema), where individuals grew on the edge of a house plot (Table 1, Figure 1), among the possible reasons for the low genetic diversity may be the later introduction of this species in Estonia. E. lobata is rare in Estonia [71]. A small genetic polymorphism (P%) was also found in some Lithuanian E. lobata populations (Šyš—43%, Ven2—39%; Table 3), while polymorphisms in other populations geographically close to Šyš or Ven2 was high (Lei—62%, Ven3—51%). Thus, on a local scale, the differences in polymorphism between the Lithuanian populations could not be linked to the geographical location. The E. lobata study sites in Lithuania differed in terms of the anthropogenic load and natural environmental conditions, and we detailed these differences in a previous study by examining the leaf nitrogen concentrations of E. lobata populations [54]. The leaf nitrogen concentrations of the different populations were not significantly associated with land use and agricultural pollution by nitrogen. Compared to other studied species of Lithuanian riverbanks, E. lobata populations were not found near small streams; they grew along rivers with natural riverbeds [117] and the water condition of the sites was defined as 3rd–5th class (5th as the best quality) using the 5-level classification of the Water Framework Directive [118]. The genetic diversity at the AFLP loci of the Lithuanian E. lobata populations had no significant relationship with the leaf nitrogen concentration. According to our findings and studies in Slovenia [69], the spread of E. lobata within non-native areas may have been influenced by the natural characteristics of the rivers.
Despite the large geographical differences in longitudes and latitudes (Table 1, Figure 1), the percentage of polymorphism between the Romanian and Central Russian populations of E. lobata was very similar (Table 3). In addition to the genetic level, the diversification of populations might also occur at the transcriptome level. Valuable information elucidating the adaptive potential and rapid growth has been obtained by analyzing the epigenetic differentiation of other invasive climbers and creepers Mikania micrantha, Pueraria montana var. lobata, and Fallopia japonica [84,119,120,121]. The coverage was a more important variable of the Lithuanian populations of Impatiens parviflora compared to the AFLP and other molecular data or parameters of the abiotic environment [98].

4.2. Interpopulation Variability

Large geographical distances separate the populations of Romania, the Baltic States, and Central Russia from each other: the distance between the study sites in Romania and the Baltic States was 1400–1800 km; between the Baltic States and Central Russia, 900–1300 km; and between Romania and Central Russia, 700–1300 km (exact numbers are given in Table 4 and locations in Figure 1 and Figure 6). According to Nei‘s genetic distances between the populations of the different regions, the highest values were between the populations of the Baltic States and Central Russia (0.231–0.322), the lower values were the genetic distances between the populations in Romania and Central Russia (0.212–0.250), and the lowest values were the genetic distances between the populations in Romania and the Baltic States (0.164–0.227). Nei‘s genetic distances between the regions corresponded, to some extent, to the differences in the genetic clusters of the Bayesian analysis (Figure 6).
The pattern of population isolation by distance was significant (Figure 2), providing evidence that the E. lobata populations in the Central and Eastern European regions are geographically structured and differentiated. Nei‘s genetic distance-based dendrogram divided the European populations hierarchically into the regions of the Baltic States and the regions of Romania and Central Russia (Figure 3). Within the next-order branching of the dendrogram, the Baltic State sites were subdivided into the Nemunas River Basin and the more northern sites in Lithuania, Latvia, and Estonia, and the second branch divided the populations into Romania and Central Russia. The genetic variation of the E. lobata populations explained by the principal coordinate analysis (PCo) was not large: The principal coordinate axes PC1 and PC2 together explained 24.9% of the total variation and the first three axes explained 33.5% of the total variation (Figure 4). The unweighted pair group method with the arithmetic mean (UPGMA) dendrogram data matched with the PCo scatterplot information, both revealing clear differentiation between the populations of Romania, the Baltic States, and Central Russia.
The explanations of the molecular ways by which populations differentiate at distinct spatial and time scales is an essential topic in invasion biology [122]. For E. lobata, the two-level AMOVA (i.e., within and among populations) partitioned 90% of the molecular variance within populations and 10% among populations (Table 5). Our data support the fact that in outcrossing species, most of the total genetic diversity is retained within populations [106]. Very similar data were also obtained for the Lithuanian populations of Impatiens parviflora examined at the AFLP loci (within-population genetic variability was 91%) [98]. The hierarchical AMOVA of Echinocystis lobata revealed significant variation at the regional scale (among the population groups of Romania, Central Russia and the Baltic States) (12% of the total genetic variability). The molecular variation between populations belonging to the different river basins of Lithuania was also significant (6% of the total genetic variability). The Lithuanian populations of Echinocystis lobata were more differentiated, compared to the Lithuanian populations of Impatiens parviflora, for which the hierarchical AMOVA did not reveal significant differences between the population groups according to geographical zones.
The Bayesian results show that there are three genetic clusters in the 29 E. lobata populations: populations from Romania, Latvia, Estonia, and the northern part of Lithuania are dominated by one cluster; populations from the Nemunas River Basin in Lithuania are dominated by either the already mentioned cluster or the second cluster; and the third cluster is dominating in Central Russian populations (Figure 6a,b). According to the dominant gene cluster (blue cluster in Figure 6), the Romanian E. lobata differed little from the northern Baltic populations. Based on this, it might be assumed that the plants arrived in the Baltic region only as a result of intentional activities of people in transporting seeds along trade routes, or the exchanges of plants between scientists and/or ornamental gardeners, since the probability of a species spontaneously spreading over greater distances while maintaining a very similar genetic structure is not high.
Among the Lithuanian populations, the second cluster (yellow cluster in Figure 6), is especially prevalent among the populations of the Nemunas basin, located near the Kaliningrad Oblast of Russia, until 1945 known as the Prussian Free State of the Weimar Republic. It is highly probable that a part of the Lithuanian E. lobata come directly from Kaliningrad blast, Russia, or through Poland. In Poland, two possible routes of introduction of E. lobata have been discussed: from Ukraine and from Germany [24]. Differences in the time of arrival of E. lobata in the discussed regions are not reflected either in Nei‘s genetic distances (Table 3), nor in the cladogram or Bayesian gene clustering (Figure 3 and Figure 6). This indicates that E. lobata arrived in Romania and Central Russia via different routes. Two different Eurasian regions of E. lobata were mentioned in the USSR Flora of the 1960s [38]: Ukraine and the Vladivostok area (East Asia). A completely different dominant gene cluster of the Central Russian populations (red cluster in Figure 6) could have originated from the Far East or other regions not closely related to the studied Romanian sites of E. lobata.
The differences in the proportions of the genetic clusters in the neighboring populations of the Nemunas basin (blue and yellow clusters in Figure 6) could not be explained without the participation of human intervention by throwing away, trading, or gifting seeds over all directions and distances. The hydrochorous spread of E. lobata along the rivers in both the downstream and upstream directions have been analyzed [41]. Hydrochory appears to be a sink for large-seeded species [123] to which E. lobata belongs. Hereby, the spread of E. lobata along the Nemunas basin mainly took place in two ways; hydrochory and anthropochory.
The populations of the Baltic States and Central Russia differ from the Romanian populations by more than half a century according to their time of introduction to these regions [2,39,41,53,60,61,71,72,124]. The distinctiveness of Romania as the region of the earliest naturalization of E. lobata was not reflected in our genetic analysis, once more suggesting that the Central Russian populations of E. lobata might originate from somewhere other than the Romanian geographical areas. Summarizing, it could be stated that E. lobata has been introduced to Central and Eastern Europe several times. Our data on multiple introductions are in support of the AFLP data for Heracleum mantegazzianum, H. sosnowskyi, and H. persicum [125] and some other invaders reviewed by Dormontt et al. [126].
Compared to other invasive species, the delay of the spread of E. lobata in the Baltic States could be due to various reasons. In recent decades, the increased transport and tourism in the Baltic States has accelerated the dissemination of small-seeded invaders such as Heracleum sosnowskyi, Impatiens glandulifera, and I. parviflora [14,74,76,77,78,98]; they can be easily transported by humans accidentally (by bicycle, car tires, or shoe soles), but E. lobata could not spread in this way because of their relatively large seeds.
The climate of the Baltic States or Central Russia is cooler than that of Central Europe, so climate change in recent decades may open up more opportunities for introducing new plants, many of which are more thermophilic than the local vegetation of the Baltic region. Climate change may have a dual effect on plant communities, weakening the less temperature-demanding native species and strengthening more thermophilic aliens [127,128]. Perhaps the most important factor limiting the introduction and subsequent spontaneous spread of E. lobata in the Baltic States and Central Russia was the very low winter temperatures [60,61]. Echinocystis lobata is a thermophilic species; among the 18 invasive Lithuanian plant species, it is the only one with a temperature EIV of 8, while the EIV of the other two species is 7 and the EIV of all the rest is 5–6 [41,52].
In Lithuania, there are many ornamental climbing or creeping cucurbits, especially Sicyos sp., Bryonia sp., which are popular among gardeners. Their cultivation has been described in Lithuanian Floras since the first half of the last century [129,130,131]. This suggests that attempts to cultivate E. lobata may have started much earlier than documented, but were unsuccessful.
The nitrogen abundance has been associated with the spread of some invasive plants in North America [106]. The spread of E. lobata in Europe may also have been promoted by anthropogenic nitrogen pollution. Our previous studies of the nitrogen concentrations in leaves showed that E. lobata is among the most nitrophilous invasive and native riparian plants in Lithuania [54]. The fact that the habitats of E. lobata are very rich in nutrients is also indicated in many studies from other countries [2,41,52,53].
Our study of the genetic diversity of E. lobata populations provided preliminary insights into potential sources and routes of spread of E. lobata in Central and Eastern Europe and into the viability of the current invasive populations. The obtained data are important for understanding the molecular mechanisms of invasion, for the development of molecular eradication methods [132,133] and for the use of invasive plants in biotechnology [134].
Our study is limited in sites, and future investigations should be directed towards the analysis of wider invasive areas, including a larger number of European populations from different regions, as well as E. lobata from a native distribution range. Further evaluations should also consider the applications of other molecular methods and analysis of the interaction of E. lobata with the biotic and abiotic environment.
In conclusion, our study of the genetic diversity of E. lobata populations provided preliminary insights into the viability of the current invasive populations and the possible routes of spread of E. lobata in Central and Eastern Europe. The percentage of polymorphic AFLP loci in the populations of Romania, Lithuania, Latvia, Estonia, and Central Russia (a total of 29 sites) varied within 28–62% (51% on average). Differentiation was significant among the populations of the regions accounting for 12% of the total genetic variability. The Bayesian results show the presence of three genetic clusters. The European populations of E. lobata, including those from the Baltic States, Romania, and Central Russia, may have originated from different sources, so E. lobata may have been introduced to Europe multiple times.

Author Contributions

Conceptualization, E.K. (Eugenija Kupčinskienė); data curation, L.J., E.K. (Eugenija Kupčinskienė) and E.K. (Edvina Krokaitė); software, T.R. and L.J.; funding acquisition, E.K. (Eugenija Kupčinskienė); investigation, L.J., E.J., E.K. (Edvina Krokaitė), T.R.; methodology, E.K. (Eugenija Kupčinskienė), L.J., E.J., E.K. (Edvina Krokaitė), I.I., and O.G.; project administration, L.J. and E.K. (Edvina Krokaitė); visualization, L.J., T.R., E.J., and E.K. (Edvina Krokaitė); writing—original draft, E.K. (Eugenija Kupčinskienė), L.J., E.K. (Edvina Krokaitė), E.J., T.R., I.I., and O.G.; writing—review and editing, E.K. (Eugenija Kupčinskienė), L.J., E.K. (Edvina Krokaitė), T.R., and E.J. All authors have read and agreed to the published version of the manuscript.

Funding

This study was funded by the Research Council of Lithuania, Grant No. SIT-02/2015.

Institutional Review Board Statement

Not applicable.

Data Availability Statement

Not applicable.

Acknowledgments

Artem Leostrin for their assistance in the collection of the plant material, Jūratė Šikšnianienė for their technical assistance in the capillary electrophoresis.

Conflicts of Interest

The authors declare no conflict of interest.

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Figure 1. Geographical location of Baltic countries (on the left), Romania (in the middle below), Central Russia (on the right), and sites with populations of Echinosytis lobata evaluated by AFLP. Note: full names of populations are provided in Table 1.
Figure 1. Geographical location of Baltic countries (on the left), Romania (in the middle below), Central Russia (on the right), and sites with populations of Echinosytis lobata evaluated by AFLP. Note: full names of populations are provided in Table 1.
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Figure 2. Correlations of geographic and AFLP loci based on Nei’s [99] genetic distances between populations of Echinocystis lobata (Mantel test [105]).
Figure 2. Correlations of geographic and AFLP loci based on Nei’s [99] genetic distances between populations of Echinocystis lobata (Mantel test [105]).
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Figure 3. Dendrogram (based on Nei’s [99] genetic distances, clustered by UPGMA method) of genetic relationships among populations of Echinocystis lobata. Branches of order 1 are named I and II, branches of orders 2 are named Ia, Ib, Iia, and Iib. Populations are named after abbreviations provided in Table 1; the numbers on branches represent bootstrap values generated from 1000 replicates; scale bar represents the genetic distance.
Figure 3. Dendrogram (based on Nei’s [99] genetic distances, clustered by UPGMA method) of genetic relationships among populations of Echinocystis lobata. Branches of order 1 are named I and II, branches of orders 2 are named Ia, Ib, Iia, and Iib. Populations are named after abbreviations provided in Table 1; the numbers on branches represent bootstrap values generated from 1000 replicates; scale bar represents the genetic distance.
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Figure 4. Principal coordinate analysis (PcoA) based on Nei’s [99] genetic distances for populations of Echinocystis lobata. The encircled populations correspond to four groups of the dendrogram (Figure 3): Ia—Romanian populations, Ib—Central Russian populations, Iia—Estonian population, and populations of Venta and Lielupė basins (in Latvia and Lithuania), Iib—populations of Nemunas basin (in Lithuania). The populations are named according to the abbreviations given in Table 1.
Figure 4. Principal coordinate analysis (PcoA) based on Nei’s [99] genetic distances for populations of Echinocystis lobata. The encircled populations correspond to four groups of the dendrogram (Figure 3): Ia—Romanian populations, Ib—Central Russian populations, Iia—Estonian population, and populations of Venta and Lielupė basins (in Latvia and Lithuania), Iib—populations of Nemunas basin (in Lithuania). The populations are named according to the abbreviations given in Table 1.
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Figure 5. Mean values of the log likelihood of K values (a) and the plot of ΔK values (b) (Bayesian cluster analysis implemented in STRUCTURE) for Echinocystis lobata populations examined by AFLP markers. Note. Red lines—mean values.
Figure 5. Mean values of the log likelihood of K values (a) and the plot of ΔK values (b) (Bayesian cluster analysis implemented in STRUCTURE) for Echinocystis lobata populations examined by AFLP markers. Note. Red lines—mean values.
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Figure 6. Location of populations (more detailed in Figure 1) and the proportional membership of the three genetic clusters (Bayesian cluster analysis implemented in STRUCTURE) in (a) individuals of populations (x axis –denote the populations, where white lines separate bars of different individuals, black lines separate bars of different populations, y axis—estimated membership of gene clusters of individuals/ populations in K clusters) and in (b) populations (x axis—geographical longitude, y axis—geographical latitude) of Echinocystis lobata. Each color (blue, yellow, red) represents one cluster (abbreviations of populations are explained in Table 1).
Figure 6. Location of populations (more detailed in Figure 1) and the proportional membership of the three genetic clusters (Bayesian cluster analysis implemented in STRUCTURE) in (a) individuals of populations (x axis –denote the populations, where white lines separate bars of different individuals, black lines separate bars of different populations, y axis—estimated membership of gene clusters of individuals/ populations in K clusters) and in (b) populations (x axis—geographical longitude, y axis—geographical latitude) of Echinocystis lobata. Each color (blue, yellow, red) represents one cluster (abbreviations of populations are explained in Table 1).
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Table 1. Titles and geographical location of Echinocystis lobata populations evaluated by AFLP markers.
Table 1. Titles and geographical location of Echinocystis lobata populations evaluated by AFLP markers.
River
Basin		Title of
Population		Abbreviation
of the Title		CountryGeographical
Latitude		Geographical Longitude
NemunasNemunas1Nem1LT53°59′50.5″23°55′49.1″
NemunasNemunas2Nem2LT54°01′12.5″23°58′53.5″
NemunasMerkys1Mer1LT54°8′36.38″24°12′49.98″
NemunasMerkys2Mer2LT54°9′26.29″24°10′57.36″
NemunasNemunas3Nem3LT54°31′49.78″23°53′15.88″
NemunasKiaunaKiaLT55°16′08.41″25°56′11.9″
NemunasNeris1Ner1LT54°41′19.9″25°24′26.1″
NemunasNeris2Ner2LT54°56′55.89″24°40′28.02″
NemunasNeris3Ner3LT54°58′46.2″24°01′37.7″
NemunasNevėžis1Nev1LT55°17′58.3″23°59′46.3″
NemunasNevėžis2Nev2LT54°55′46.4″23°47′26.0″
NemunasDubysa1Dub1LT55°31′10.69″23°4′46.68″
NemunasDubysa2Dub2LT55°25′31.91″23°13′30.12″
NemunasNemunas4Nem4LT55°03′18.2″22°41′02.0″
NemunasLokystaLokLT55°29′12.5″22°10′06.1″
NemunasJūraJūrLT55°06′26.6″22°10′23.6″
NemunasŠyšaŠyšLT55°19′54.51″21°36′13.3″
NemunasLeitėLeiLT55°15′57.63″21°27′18.38″
NemunasAtmataAtmLT55°20′42.47″21°17′42.8″
Curonian lagoon 1Kuršių mariosMarLT55°33′06.7″21°07′34.6″
LielupėKulpėKulLT56°00′51.7″23°24′58.9″
VentaVenta1Ven1LT56°00′16.3″22°55′49.7″
VentaVenta2Ven2LT56°11′09.5″22°41′07.9″
VentaVenta3Ven3LV56°58′58.9″21°57′19.5″
-Emajõgi 2EmaEE58°28′01.6″26°37′34.8″
VolgaDubna 3DbnRU56°40′32.0″37°48′39.2″
-Galichskoye 4GalRU58°22′30.4″42°18′21.6″
DanubeSomeşul MicSom1RO47°01′55.6″23°54′02.7″
DanubeSomeşul MicSom2RO46°48′43.7″23°44′43.1″
Notes. 1 The Curonian Lagoon is an inland freshwater body into which the Nemunas flows, 2 on the edge of the house plot, close to the river Emajõgi, 3 by the ditch that flows into the river Dubna, 4 shore of the lake Galicskhoye, LT—Lithuania, LV—Latvia, EE—Estonia, RU—Russia, RO—Romania.
Table 2. Characteristics of 8 amplified fragment length polymorphism (AFLP) primers.
Table 2. Characteristics of 8 amplified fragment length polymorphism (AFLP) primers.
Selective Primers PairsSequence (5′–3′)Fluorescent DyeLength of the Fragments (bp)Total Number of the Fragments
EcoRI AAC + MseI CTCGACTGCGTACCAATTCAAC
GATGAGTCCTGAGTAACTC		6-FAM50–49631
EcoRI ACC + MseI CTGGACTGCGTACCAATTCACC
GATGAGTCCTGAGTAACTG		6-FAM51–49062
EcoRI ACG + MseI CACGACTGCGTACCAATTCACG
GATGAGTCCTGAGTAACAC		VIC51–45641
EcoRI ACG + MseI CATGACTGCGTACCAATTCACG
GATGAGTCCTGAGTAACAT		VIC53–47931
EcoRI AAG + MseI CAGGACTGCGTACCAATTCAAG
GATGAGTCCTGAGTAACAG		NED51–46655
EcoRI ACC + MseI CACGACTGCGTACCAATTCACC
GATGAGTCCTGAGTAACAC		NED51–47349
EcoRI AGC + MseI CACGACTGCGTACCAATTCAGC
GATGAGTCCTGAGTAACAC		PET54–39621
EcoRI AGG + MseI CACGACTGCGTACCAATTCAGG
GATGAGTCCTGAGTAACAC		PET54–49230
Table 3. Genetic diversity parameters (%P—percentage of polymorphic loci; h—Nei’s [99] gene diversity, I—Shannon’s information index) of Echinocystis lobata populations based on 8 AFLP markers.
Table 3. Genetic diversity parameters (%P—percentage of polymorphic loci; h—Nei’s [99] gene diversity, I—Shannon’s information index) of Echinocystis lobata populations based on 8 AFLP markers.
PopulationNumber of Total LociNumber of
Polymorphic Loci		%Ph ± CII ± CI
Nem1 *31017252.280.222 ± 0.0120.319 ± 0.017
Nem231715747.720.206 ± 0.0120.295 ± 0.018
Mer131716750.760.216 ± 0.0120.311 ± 0.017
Mer232016148.940.212 ± 0.0130.304 ± 0.018
Nem332318054.710.232 ± 0.0120.334 ± 0.017
Kia31916048.630.205 ± 0.0120.295 ± 0.017
Ner131416550.150.212 ± 0.0120.305 ± 0.017
Ner231017954.410.237 ± 0.0130.339 ± 0.018
Ner332519258.360.253 ± 0.0120.363 ± 0.017
Nev131915647.420.192 ± 0.0120.279 ± 0.017
Nev231919659.570.250 ± 0.0120.362 ± 0.017
Dub132117352.580.224 ± 0.0120.322 ± 0.018
Dub232118556.230.235 ± 0.0120.339 ± 0.017
Nem432219258.360.266 ± 0.0130.376 ± 0.018
Lok32517753.800.229 ± 0.0120.329 ± 0.017
Jūr31918857.140.233 ± 0.0120.338 ± 0.017
Šyš31714343.470.175 ± 0.0120.255 ± 0.017
Lei32020562.310.272 ± 0.0120.390 ± 0.017
Atm32117352.580.219 ± 0.0120.317 ± 0.017
Mar32417051.670.222 ± 0.0120.319 ± 0.018
Kul31114844.980.189 ± 0.0120.273 ± 0.017
Ven131715246.200.191 ± 0.0120.277 ± 0.017
Ven230812738.600.160 ± 0.0120.231 ± 0.017
Ven332016750.760.220 ± 0.0130.315 ± 0.018
Ema3069328.270.120 ± 0.0110.173 ± 0.016
Dbn32617753.800.249 ± 0.0130.353 ± 0.018
Gal32617151.980.242 ± 0.0130.341 ± 0.018
Som130717151.980.217 ± 0.0120.314 ± 0.017
Som230616951.370.219 ± 0.0120.316 ± 0.017
Mean317.6167.851.000.218 ± 0.0020.313 ± 0.003
Note: * full names of populations and locations are provided in Table 1; CI—interval of confidence; p < 0.05.
Table 4. AFLP markers based on Nei’s [99] genetic distances (below triangle) and geographic distances (above triangle) between populations of Echinocystis lobata.
Table 4. AFLP markers based on Nei’s [99] genetic distances (below triangle) and geographic distances (above triangle) between populations of Echinocystis lobata.
Nem1Nem2Mer1Mer2Nem3KiaNer1Ner2Ner3Nev1Nev2Dub1Dub2Nem4LokJūrŠyšLeiAtmMarKulVen1Ven2Ven3EmaDbnGalSom1Som2
Nem1x42524591911231161091451041781651412011682112132262492272322563515249251232775799
Nem20.154x2020571871191131071421021761641402001682112142272502252312553505219211228777802
Mer10.1770.161x348167989494129921691561391991702132172302522142222473435039021208791816
Mer20.1670.1520.163x46167999492128901671541361961672112142282502122202453415029031209793817
Nem30.1470.1220.1370.144x1559969518645121108941531271711761892091681751992954699051205834858
Kia0.1690.1570.1930.1530.123x73881261231421831722022392402742842943051792062283083587541051927953
Ner10.1360.1340.1320.1290.1040.123x55941131071751611742242122532602722891942142393304278071111858884
Ner20.1140.1340.1300.1390.1100.1620.113x4158561191061221701602002082192351431611862794098421139882907
Ner30.1880.1790.2030.1720.1930.1590.1860.186x36168571811311191591671781941211331582544198801174884908
Nev10.1480.1320.1680.1300.0990.1080.1140.1480.152x43635182117118151161171183871031282223878711161919944
Nev20.1340.1530.1630.1750.1470.1510.1520.1370.1800.145x8066671201051461531651831231311562524308961190878903
Dub10.1510.1310.1650.1400.1280.1350.1200.1380.1600.1150.147x14545873951061141235955781743929211204945969
Dub20.1600.1200.1420.1610.1230.1570.1210.1150.1780.1490.1570.160x4967751031131221336767911873969151200934958
Nem40.1830.1550.1870.1780.1720.1750.1930.1840.1620.1610.1790.1730.180x60387986981171131041242164459531242897921
Lok0.1810.1630.1780.1580.1440.1360.1430.1720.1930.1460.1740.1380.1820.174x42405157669875841644279771258948971
Jūr0.1880.2170.1630.2160.1470.1660.1460.1480.2350.1600.1760.1710.1870.2260.156x444962831281111242074619881275906929
Šyš0.1650.1290.1530.1440.1280.1120.1030.1470.1690.1180.1770.0950.1570.1880.1430.184x12203913711211718346310161298937959
Lei0.1800.1730.1320.2140.1680.1980.1630.1520.2080.2090.1730.1750.1650.1890.1890.1840.186x133814912412819247510271309931953
Atm0.1580.1620.1580.1590.1200.1600.1250.1230.2340.1400.1360.1400.1670.2160.1790.1590.1510.165x2515212612818547410351315942964
Mar0.1660.1590.1290.1710.1290.1490.1330.1510.1980.1600.1680.1670.1580.1750.1580.1600.1570.1480.169x15212412016646410391316967989
Kul0.1830.1880.1810.1830.1950.1990.1920.1880.2150.2080.2350.2040.1870.2090.2010.2420.2040.2070.2220.170x1141382344319161208888912
Ven10.1500.1640.1600.1680.1730.1610.1630.1650.1760.1500.2150.1740.1580.1720.1750.2030.1570.1910.2220.1560.119x25121353918119210001024
Ven20.1810.1720.1930.1650.1930.1880.1890.1980.2050.1820.2300.1770.1740.1960.1750.2560.1640.2190.2240.1600.1180.086x96347930120010211045
Ven30.1480.1500.1790.1700.1570.1750.1690.1570.1680.1680.1960.1620.1480.1630.1740.2170.1670.1840.2140.1530.1580.1230.113x321960121311121135
Ema0.2090.1960.2250.1850.2120.2380.2270.2100.2060.1920.2640.2050.2300.2020.2370.3050.2070.2370.2560.2020.2170.1740.1760.132x69591112841310
Dbn0.2660.2710.2960.2760.2680.2910.3220.2680.2560.2670.2950.2690.2750.2360.2760.3160.3000.2680.3130.2650.2510.2560.2780.2400.283x32814311457
Gal0.2420.2460.2570.2550.2450.2560.2730.2390.2250.2380.2830.2370.2470.2310.2360.2910.2510.2500.2760.2660.2450.2340.2440.2190.2560.074x17581784
Som10.2430.2390.2250.2470.2510.2620.2610.2420.2380.2450.2520.2380.2530.2400.2450.2770.2620.2430.2740.1990.2220.1940.1870.2100.2630.2310.212x27
Som20.2170.2140.2000.2230.2180.2330.2300.2100.2140.2150.2310.2130.2400.2220.2170.2430.2370.2220.2500.1830.2160.1640.1740.1880.2370.2500.2120.034x
Note: for geographic distances, colors range from greenish (<100 km) through green (100–500 km) to dark green (>500 km); for genetic distances, from brownish (<0.100) through brown (0.100–0.200) to dark brown (>0.200).
Table 5. AFLP markers-based analysis of molecular variance (AMOVA) for Echinocystis lobata populations. A–C—two-level analyses, D–E—three-level analyses.
Table 5. AFLP markers-based analysis of molecular variance (AMOVA) for Echinocystis lobata populations. A–C—two-level analyses, D–E—three-level analyses.
Sourcedf SS MS Est. Var.%Φp
Two level analysis
A. Populations of Romania, Baltic States, and Russia
Among populations281907.468.15.2110.1090.001
Within populations1144836.442.442.489
Total1426743.8 100
B. Populations of Baltic States
Among populations241518.263.34.4100.0950.001
Within populations984087.641.741.790
Total1225605.8 46.1100
Three level analysis
C. Populations of Romania, Baltic States, and Russia
Among regions2354.2177.16.5120.1250.001
Among populations261553.259.73.570.0770.001
Within populations1144836.442.442.4810.1920.001
Total1426743.8 52.5100
D. Populations of the different river basins
Among river basins7726.8103.84.490.0890.001
Among populations211180.656.22.860.0610.001
Within populations1144836.642.442.4860.1440.001
Total1426743.8 49.6100
E. Populations of Nemunas and other Lithuanian river basins
Among river basins1152.5152.52.860.0580.010
Among populations211245.659.33.570.0760.010
Within populations923861.642.042.0870.1300.010
Total1145259.7 48.3100
Note. df—degree of freedom, SS—sum of squares, MS—mean squares, Est. Var—estimated variability, %—percentage of variation, Φ—genetic differentiation, p—probability of differentiation.
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Jocienė, L.; Krokaitė, E.; Rekašius, T.; Juškaitytė, E.; Ielciu, I.; Galanina, O.; Kupčinskienė, E. The Molecular Evidence for Invasive Climber Echinocystis lobata (Michx.) Torr. & A. Gray in Eastern and Central Europe. Diversity 2023, 15, 1084. https://doi.org/10.3390/d15101084

AMA Style

Jocienė L, Krokaitė E, Rekašius T, Juškaitytė E, Ielciu I, Galanina O, Kupčinskienė E. The Molecular Evidence for Invasive Climber Echinocystis lobata (Michx.) Torr. & A. Gray in Eastern and Central Europe. Diversity. 2023; 15(10):1084. https://doi.org/10.3390/d15101084

Chicago/Turabian Style

Jocienė, Lina, Edvina Krokaitė, Tomas Rekašius, Erika Juškaitytė, Irina Ielciu, Olga Galanina, and Eugenija Kupčinskienė. 2023. "The Molecular Evidence for Invasive Climber Echinocystis lobata (Michx.) Torr. & A. Gray in Eastern and Central Europe" Diversity 15, no. 10: 1084. https://doi.org/10.3390/d15101084

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