DOI: 10.5061/dryad.j6q573nj8
title: Origin and genetic variability of populations of the invasive plant Rumex alpinus L. in the Giant (Krkonoše) Mountains

description: Monk's rhubarb, Rumex alpinus L. (R. alpinus), is a perennial plant
 native to the mountains of Central and Southern Europe. Currently, the
 distribution of R. alpinus has been partly affected by its utilization as
 a vegetable and a medicinal herb. In the mountains of the Czech Republic,
 it is considered an invasive plant, probably introduced into the Krkonoše
 Mountains by colonists from the Alps. This study's main aim was to
 verify whether R. alpinus was introduced into the Krkonoše Mountains by
 alpine colonists or whether it was anthropogenically introduced from the
 Carpathians. Furthermore, the genetic structure of native and introduced
 populations of R. alpinus was determined. For the evaluation of genetic
 structure, 417 samples of R. alpinus were collected from the Alps,
 Carpathians, Balkan, Pyrenees, and Czech Mountains. In total, 12 simple
 sequence repeat (SSR) markers were applied. The results of AMOVA showed a
 high 60% variation within populations, 27% variation among groups, and 13%
 among the population within groups. The overall unbiased gene diversity
 was high (ĥ = 0.55). The higher level of genetic differentiation among
 populations (FST = 0.35; p &lt; 0.01) indicated restricted gene flow
 between populations. Compared to native populations, limited genetic
 variability was observed in the nonnative populations. It was concluded
 that local adaptation, low gene exchange, and genetic drift affected the
 genetic diversity of nonnative R. alpinus. The results support a genetic
 link between Alpine and Czech genotypes of R. alpinus, while the
 Carpathians genotypes corresponded to the Balkan genotype.
description: Description of
 localities Between 2017 and 2020, plant samples of
 <em>R. alpinus</em> were collected from different locations in
 Europe (Table 1, Figure 1). According to Professor Klimeš research´s
 focused on ancestors of the original alpine colonists and individual
 families, <em>R. alpinus</em> was collected in the exact
 places (Krkonoše) where the colonists lived and <em>R.
 alpinus</em> probably occurred. Equally, individual plants of
 <em>R. alpinus</em> were collected in Tyrol and Styria in
 Austria. As control samples, <em>R. alpinus </em>samples were
 collected from other mountain localities in the Alps (Lombardy, and
 Graubünden) and the Pyrenees. Finally, to determine the true origin of
 <em>R. alpinus </em>were collected samples representing plant
 populations in the East and West Carpathians, and then in the mountainous
 regions of the Balkans. Populations from other mountainous regions of the
 Czech Republic (Jizera and Eagle Mountains) were collected for comparison
 and possible exclusion of other origins of <em>R.
 alpinus</em>.   In total, 417 individual leaf samples were collected,
 representing 31 populations with 9–20 individual plants per
 population. The 329 plant
 samples were collected in the European Mountains, Alps, West and East
 Carpathians, Pyrenees, and Balkan Peninsula, which represent areas where
 <em>R. alpinus</em> is a native
 species. In the Czech Mountains, represented by Eagle
 Mountains, Jizera Mountains, and Krkonoše (Giant) Mountains where
 <em>R. alpinus</em> is considered a nonnative/invasive plant
 (Kopecký, 1973; Lokvenc, 1978; Kubát, 1990; Šťastná et al., 2010; Pyšek et
 al., 2012), overall88 plant samples were collected (Table 1 and Figure
 1). Population sampling and DNA
 extraction At each locality, leave samples were collected
 in plants separated approximately 200 m apart to avoid collecting the same
 plant because <em>R. alpinus</em> also reproduces vegetatively
 and to ensure a representative sample of the population. Samples were
 dried on silica gel and stored in a collection at the Faculty of
 Environmental Sciences, Czech University of Life Sciences
 Prague. Total genomic DNA was extracted from silica
 gel-dried leaves of <em>R. alpinus</em> in two repetitions
 using the protocol of Doyle & Doyle (1978) with a minor
 modification that involved the addition of 10 mg of polyvinylpyrrolidone
 (PVPP) (Carl Roth, Germany) and 5 µl of 10 mg/µl RNase A (Thermo
 Scientific, Czech Republic) during the initial phase prior to incubation.
 The quality and yield of isolated DNA were assessed on a 0.8% agarose gel
 in 1× TAE buffer. The concentration and quality of DNA were measured using
 a spectrophotometer UVS-99/UVIS Drop (Avans Biotech, Taiwan). The
 extracted DNA samples were diluted to the concentration of 20 ng/μl for
 subsequent analysis and stored at - 20°C.
 Microsatellite (SSR)
 analysis Based on the test, 12 polymorphic primer pairs
 were selected from the 15 primer pairs according to Šurinová et al. (2018)
 and used (Table S1). DNA amplification was performed in 5 μl reactions
 consisting of 2.5 μl QIAGEN Multiplex PCR Master Mix; 0.125 μl of each
 M13-labelled forward, reverse, and fluorolabelled (<em>NED</em>™, <em>PET</em>®,
 <em>6-FAM</em>™, <em>VIC</em>® – Table
 S1) M13 primers (10 μM
 each in initial volume); 20 ng of DNA dissolved in 0.5 μl TE buffer; and
 1.625 μl dH2O. The PCR protocol was performed according to Schuelke
 (2000). PCR was performed using an Applied Biosystem Thermal Cycler
 (Applied Biosystems, USA) as follows: an initial denaturation step at 95°C
 for 15 min followed by 25 cycles of denaturation (95°C for 20 s),
 annealing (59°C for 30 s) and extension (72°C for 20 s), followed by 10
 cycles of denaturation (95°C for 30 s), annealing (53°C for 45 s) and
 extension (72°C for 45 s) and a final extension at 72°C for 15 min. During
 the first 25 cycles, specific PCR products are produced, and in the
 following 10 cycles, the fluorescent M13 tag is ligated to the M13 forward
 primer. The quality of PCR products has been verified on 2% agarose gels.
 Three multiplexes were built (Table S1).
 Fragment analyses were
 performed using capillary electrophoresis in an ABI PRISM 3500 Genetic
 Analyser automated sequencer (Applied Biosystems, USA). Electropherograms
 were analysed and scored using GeneMarker ver. 1.8 (SoftGenetics,
 USA).
description: Statistical
 analysis Analysis of the molecular variance test (AMOVA)
 with 1 000 permutations was calculated in ARLEQUIN software ver. 3.5.2
 (Excoffier & Lischer, 2010). The degree of genetic differentiation
 among populations was also evaluated using ARLEQUIN software using the
 distance matrix based on the fixation index
 (<em>F</em><sub>ST</sub>) generated by the
 program. Further, a distance matrix based on geographical distances was
 calculated for <em>R. alpinus</em> populations within R
 program (R development core team, 2021) version 4.0.3 using the routines
 in geosphere (Hijmans, 2021) library. These were subsequently
 logarithmically transformed and correlated
 with <em>F</em><sub>ST</sub> distance matrix using
 the Mantel test and 9999 permutations.
 Nei’s genetic distance was
 employed to obtain a UPGMA dendrogram after 1,000 bootstrap samplings in
 TFPGA software (Miller, 1997). The diversity indices for each population
 included the percentage of polymorphic loci, the average diversity of the
 loci using Nei's unbiased gene diversity ĥ (Nei, 1973), and the
 Shannon information index (Lewontin, 1972; Shannon & Weaver, 1949)
 were calculated using the POPGENE, version 1.32 (Yeh et al.,
 1999). To assess the Hardy-Weinberg equilibrium, we
 used the ARLEQUIN software
 ver. 3.5.2 (Excoffier & Lischer, 2010). Was conducted an exact
 test using a Markov chain with a forecasted chain length of 1,000,000 and
 100,000 dememorization steps (Guo & Thompson, 1992). Deviation
 from HWE was assessed at a significance level of
 <em>p</em> &lt; 0.05. The results were interpreted
 according to established guidelines (Levene, 1949).
 Another approach to studying
 population structure analysis is based on Bayesian statistics STRUCTURE,
 version 2.3.4 (Pritchard et al., 2000) was used to determine the genetic
 architecture of the <em>R. alpinus</em> populations. Ten
 independent runs of 1–20 groups (<em>K</em> = 1–20) were
 performed using the locprior model with admixture and correlated allele
 frequency (Falush et al., 2003; Hubisz et al., 2009) with the recommended
 200,000 Markov chain iterations after a burn-in period of 100 000
 iterations. The optimal value of K was estimated based on
 ln(<em>K</em>) and on the Δ<em>K</em> calculation,
 which considers the rate of change in the ln <em>P(D)</em>
 values among successive <em>K</em> runs to account for
 patterns of dispersal that are not homogeneous among populations (Evanno
 et al., 2005). The number (<em>K</em>) of clusters into which
 the sample data (<em>X</em>) were fitted with posterior
 probability Pr<em> (X</em>|<em>K</em>) was
 estimated using the same model with 1,000,000 Markov chain iterations
 after a burn-in period of 100,000 iterations (Evanno et al.,
 2005). An exact test for population differentiation was
 calculated using the Tools for Population Genetic Analyses (TFPGA; version
 1.3; Miller, 1997) with 100 000 recommended permutation
 steps. To identify potential bottleneck events in the
 populations under investigation, we employed BOTTLENECK 1.2.02 software
 (Cornuet & Luikart, 1996; Piry et al., 1999) and heterozygosity
 excess resulting from population reduction was examined. We utilized three
 models of mutational equilibrium: the infinite allele model (IAM), the
 stepwise mutation model (SMM), and the two-phase mutation model (TPM),
 with the latter being the most appropriate for microsatellites. For the
 TPM, we employed the default settings, which assumed that 70% of mutations
 occur in a single step, with a variance of 30 among multiple steps. The
 significance of these models was assessed using a one-tailed Wilcoxon rank
 test, which is suitable for dataset analysis with less than 20
 microsatellite loci (Piry et al., 1999). A population was deemed to have
 experienced a bottleneck event only if all three models produced
 significant results (<em>p</em>-value ≤
 0.05).