Skip to main content
Advertisement
Browse Subject Areas
?

Click through the PLOS taxonomy to find articles in your field.

For more information about PLOS Subject Areas, click here.

  • Loading metrics

Genetic Variability and Population Divergence in the Rare Fritillaria tubiformis subsp. moggridgei Rix (Liliaceae) as Revealed by RAPD Analysis

Abstract

Fritillaria tubiformis subsp. moggridgei Rix. is a rare alpine geophyte with shiny yellow flowers. This plant is sporadically distributed across the southwestern Alps where it is biogeographically close to F. tubiformis var. burnatii Planch. The latter has dark purple flowers and ranges in the majority of the Western and Central Alps. In order to develop appropriate strategies of conservation, a RAPD based analysis was conducted to study the genetic status of these taxa and the distribution of genetic variability of the subspecies by sampling seven populations distributed across the subspecies' range. Four populations of var. burnatii were chosen within this range and included in the genetic analysis. Some 264 individuals were analysed and 201 polymorphic loci were scored. Genetic diversity scored in the subspecies was in line with expectations for endemic species (He  = 0.194). F. tubiformis var. burnatii showed lower intraspecific diversity (He  = 0.173), notwithstanding a wider range than the subspecies. Most of the total phenotypic variation (about 83%) was allocated within populations, and significant lower proportions between taxa (6.45%) and between populations of the same taxon (10.64%). Moreover, PCoA analysis and Bayesian clustering separated populations into two genetically differentiated groups corresponding with the subspecific taxa. However, three populations ascribed to the subsp. moggridgei repeatedly showed genetic admixture with var. burnatii populations. Our findings suggest that: i) although the different flower colour, the two taxa are genetically very similar and share a consistent part of their gene pool, ii) the majority of genetic variability is allocated within populations rather than among them, iii) a representative amount of genetic diversity can be preserved by sampling from a restricted number of populations. The efficacy of RAPD markers in analysing genetic variation, and the contribution of the results to the preservation of biodiversity of the species, are discussed.

Introduction

Genetic erosion is one of the most important threats to the survival of many wild species. Nowadays these species are subjected to many stress factors, most of which are due to human activities: namely environment alteration, habitat fragmentation, urbanisation, pollution, irrational forest management and the introduction of allochthonous species. Current climate changes will probably determine a decline in growth and survival, and an alteration of genetic structure and diversity for many wild species. This pressure may be strengthened in marginal and peripheral populations of the species distribution, mainly in European southern populations of plants [1]. In order to survive these threats, and to persist over time, a high adaptive potential is fundamental: this is mainly determined by the within-species genetic diversity [2]. Genetic differentiation derives from several evolutionary forces, among which selection pressure as a response to different ecological conditions and genetic drift are the most important. Gene flow, in contrast to this pattern, leads to homogenisation of allelic frequencies [3].

The characterisation of patterns of genetic diversity within species, and among populations, is a fundamental necessity to establish any program aimed at preservation of biodiversity. Genetic markers are basic for supplying information on the genetic structure of populations, to analyse the pattern of within-species variability distribution [4] and to support the management of seed supply [5]. In particular, knowledge of genetic variation should be the basis for actions of ecological restoration [6]. This is even more important where the preservation of local, marginal and probably well adapted and/or differentiated gene pools must be achieved, through the management of small, marginal and inbreed populations [7], [8]. As a consequence, the goal is to focus not only on scattered and rare species, but also on those characterised by wide distribution that could appear to be less sensitive to genetic erosion [9].

Fritillaria tubiformis subsp. moggridgei (Boiss. & Reut. ex Planchon) Rix (Liliaceae) is a rare taxon sporadically distributed along the Ligurian and Maritime Alps. The species is limited to a few main sites within the Parc National du Mercantour in France (Muséum National d'Histoire Naturelle. National inventory of natural heritage. Website: http://inpn.mnhn.fr [accessed 17 04 2014]), and to seven populations of no more than 1000–10000 individuals found across Piedmont and Liguria, in Italy.

Conversely, Fritillaria tubiformis Gren. var. burnatii Planch. has a wider range, including the majority of the Western and Central Alps [10]. In the past, the two taxa have been confused and often fully synonymised by Italian botanists with F. tubiformis Gren. & Godr. [11], from which they differ by leaf morphology and the colour of tepals, which in moggridgei are yellow instead of dark purple. Results of a phylogenetic analysis carried on combined DNA sequences of the partial matK gene and the rpl16 intron supported this view, and showed that subsp. moggridgei is genetically more closely related to var. burnatii than to any other species in the genus. However, in the same study, using plastid length-variable microsatellites a number of plastid haplotypes were found to be differently fixed in the two subspecies [12].

Owing to this taxonomic uncertainty, our genetic analysis has been focused on the seven Italian populations of subsp. moggridgei. In addition, we have used a data set based on DNA from four populations of F. tubiformis var. burnatii, sampled at the periphery of the subspecies distribution. A biosystematic study is also underway aimed at clarifying the exact phylogenetic relationships between the two taxa and their distribution range.

Random Amplified Polymorphic DNA (RAPD) technology is based on the amplification, using the Polymerase Chain Reaction (PCR), of short segments of DNA randomly chosen by the use of arbitrary, usually short (8–12 base pairs) primers. Despite having some drawbacks, the most important of which are the dominant expression and the low level of reproducibility [13], [14], the RAPD technique analyses a larger number of loci, and thus provides a more general evaluation of the genome with a high potential for detecting polymorphism. Furthermore, the technique has a low cost, and can give a large amount of data in a short time; it requires small amounts of DNA and there is no requirement of prior knowledge of the genome being studied.

The aims of the present research were to estimate the amount and distribution of genetic diversity within and among Fritillaria tubiformis subsp. moggridgei populations from north-western Italy using RAPDs, and to evaluate possible effects of habitat fragmentation on genetic variation. The genetic relationship between the subspecies and Fritillaria tubiformis var. burnatii has also been investigated. Spatial structure and the expected association between genetic and geographical distances among populations were assessed, in order to provide recommendations for in situ preservation of the species.

Materials and Methods

Plant material

Seven populations of F. tubiformis subsp. moggridgei were considered in the study, distributed across the Maritime and Ligurian Alps, which represent the natural range of the subspecies in Italy. In general, populations were of small size and individuals therein limited to several hundreds. In addition, four populations of F. t. var. burnatii were also considered and were sampled within an area that partly overlaps the distribution range of the former subspecies. Figure 1 and Table 1 summarise names and locations of the populations analysed. Ente di gestione del Parco naturale del Marguareis (Chiusa di Pesio, province of CN) issued the permit for leaf sampling within PLU, MAR and SER populations (see Table 1 for their location). For the remaining locations (Table 1) specific permission was not required since these locations are outside protected areas and leaf collection does not represent a threat to the sampled individuals.

thumbnail
Figure 1. Geographical distribution of the Italian populations of Fritillaria tubiformis subsp. moggridgei (circles) and Fritillaria tubiformis var. burnatii (stars) analysed in this study.

https://doi.org/10.1371/journal.pone.0101967.g001

thumbnail
Table 1. Details of the site characteristics of Fritillaria tubiformis populations from Italy which were sampled for the study.

https://doi.org/10.1371/journal.pone.0101967.t001

Leaves were sampled from about 30 non-adjacent blooming individuals in each population, in order to avoid selection of clonal individuals. In total, 264 individuals were analysed. After collection, the vegetative material was frozen at −20°C until DNA extraction.

Molecular analysis

Total DNA was extracted from frozen tissue using E.Z.N.A. SP Plant DNA Kit (Omega Bio-Tek, Norcross, GA), and purified on columns following the manufacturer's protocol. Amplifications were carried out in a Perkin Elmer DNA thermal cycler (PE 9600). The optimal reaction for RAPD analysis was set using the following conditions: 25 µl volume containing 1× reaction buffer, 1 unit of Taq DNA polymerase (Promega), 2.5 mM magnesium chloride, 0.2 µM decamer primers, dNTPs mix 0.2 mM and 20 ng DNA. The amplification conditions were as follows: the first step at 95°C for 5 min., followed by 40 cycles of 1 min. at 94°C, 1 min. at 36°C and 2 min. at 72°C. The reaction was completed with a final run at 72°C for 8 min. We screened a total of 16 primers from Life Technologies. The amplification products were separated in 1.5% agarose gel with ethidium bromide in 0.5× TBE buffer. The banding patterns were visualised under UV light and acquired using a fluorimeter linked with a gel documentation system (GelDoc 2000). The bands were scored visually, and those of similar molecular size, scored for the same primer, were assumed to be homologous. Since RAPD markers are dominant it was assumed that each band was an independent locus with two alleles: presence or absence of the band. The reproducibility of the amplification products was tested twice for each sample and each primer.

Data processing

Amplified fragments were scored as presence or absence of bands, and a binary matrix of RAPD phenotypes was assembled. Only polymorphic loci were used. The data analysis were further restricted to bands whose observed frequencies in each population were less than 1 – (3/N), where N is the number of plants analysed [14] to avoid significant bias in estimates of population genetic parameters. Non-random associations between pairs of loci were investigated using the Spearman rank correlation, with the SPSS 12.0 computer package. Intrapopulational genetic diversity was assessed as the proportion of polymorphic loci (P, using the 95% criterion), mean number (N) and effective number (Ne) of alleles per locus, Nei's gene diversity [15] (He, that was adopted assuming the populations to be in Hardy-Weinberg equilibrium, although we were not able to investigate this since dominant markers were used), and Shannon's information index. The latter can be considered a measure of phenotypic diversity (I =  −Σpilog2pi, where pi is the frequency of presence or absence of a given RAPD fragment; [16]), assuming that populations are not in Hardy-Weinberg equilibrium. This index is frequently used in RAPD analysis because it is insensitive to bias that may be introduced into data owing to undetectable heterozygosity [17]. Calculations were performed using the GENALEX 6.5 software package [18].

The distribution of genetic diversity within and among populations was assessed using Nei's genetic differentiation degree (GST) [19]. Analysis of Molecular Variance (AMOVA), based on squared Euclidean distances between all pairs of RAPD phenotypes [20], was employed using the Arlequin software [21]. The AMOVA procedure was performed in order to further partition the total genetic variation among taxa, among population within subspecies and within populations, and to compute a pairwise population FST value matrix according to Weir and Cockerham [22]. The statistical significance of the covariance components was estimated by nonparametric randomisation tests using 10000 permutations. The null distribution of pairwise FST values under the hypothesis of no differences between the populations was also tested by using a permutational approach (10000 replicates).

Cluster analysis was performed on pairwise FST distances using the Unweighted Pair Group Method with Arithmetic Averages (UPGMA; [23]) with the SAHN program in NTSYS-pc 2.10j [24]. A cophenetic value matrix (COPH in NTSYS) was produced from the dendrogram and compared with the genetic distance matrix by using the MXCOMP program in NTSYS to estimate the goodness of fit of the cluster analysis. Principal coordinate analysis (PCoA) was also performed, based on pairwise FST distances matrix (DCENTER and EIGEN procedures in NTSYS), to better understand genetic relationships among populations.

The genetic structure of the populations was also explored using Bayesian clustering, performed using the software Structure [25]. The program uses a Markov chain Monte Carlo (MCMC) algorithm to cluster individuals into populations on the basis of multilocus genotypic data. Individual multilocus genotypes are first assigned probabilistically to genetic clusters (K) without considering sampling origins. Admixed or hybrid individuals can be identified as they will have a fraction of their alleles derived from each genetic cluster. Posterior probabilities of K were calculated from the means of 20 runs for each value of K (from 1 to 6), and the optimum K determined using the method of Evanno et al. [26].

Results

Variation of RAPD loci

Among the primers tested, OPA01, OPA02, OPA03, OPA4, OPA6, OPAF04, OPAF12 and OPAS18 gave non-reproducible amplification products and were therefore excluded from the analysis. The remaining eight selected primers showed reliable banding patterns and generated a total of 204 consistent and differential amplification products, ranging in size from 170 to 990 bp. Each primer amplified between 15 (OPA10) and 30 (OPA19) fragments, with a mean number of scored bands per primer of 25.5 (Table 2). Almost all these bands were polymorphic, being monomorphic only three, OPA10-4, OPA12-1 and OPA19-1. Many of the bands were fixed at the population level, and several even at the subspecific level (16 within subsp. moggridgei and 4 within var. burnatii). Five bands were unique to a single population: OPA05-19, OPA05-30, OPA05-21 and OPA09-27 in GAL, OPA05-22 in ROS. All bands fulfilled the Lynch and Milligan criterion [14], and were therefore included in further analyses. No band pair showed any correlation with any other, as indicated by Spearman's rho correlation coefficients (data not showed). Therefore, each of the 201 polymorphic bands was considered as an independent locus.

thumbnail
Table 2. Characteristics of fragments generated by the 8 primers selected for the genetic analysis.

https://doi.org/10.1371/journal.pone.0101967.t002

Genetic variation within populations

Genetic variation within populations was estimated for the 11 populations using various methods (Table 3). The mean number of alleles per locus ranged from 1.48 (PRA) to 1.72 (GAL), with a mean value of 1.59 (standard error, SE  = 0.017). The mean effective number of alleles per locus was 1.29 (SE  = 0.006), and the range was from 1.25 (ROS) to 1.32 (MAR). The percentage of polymorphic loci ranged from 72 (PRA) to 85 (GAL), with a mean value of 77.5 (SE  = 1.19), and the expected heterozygosity was on average 0.187 (SE  = 0.003), ranging from 0.165 (ROS) to 0.206 (CRA). Lastly, the Shannon diversity index, based on phenotype frequency, ranged from 0.268 (ROS) to 0.327 (GAL), with a general mean of 0.299 (SE  = 0.005). In general, populations belonging to Fritillaria tubiformis subsp. moggridgei showed an amount of internal genetic variability slightly higher than those of Fritillaria tubiformis var. burnatii.

thumbnail
Table 3. Genetic variation within populations of Fritillaria tubiformis from Italy, based on 201 RAPD markers.

https://doi.org/10.1371/journal.pone.0101967.t003

Genetic variation among populations and groups

Partitioning of the total gene diversity (HT  = 0.293), following Nei's statistics [19], revealed that about 12.9% of the total variation was allocated among taxa and 4.5% among populations belonging to the same taxon. The remaining genetic variation was due to differences between individuals within populations. Within taxa, F. tubiformis subsp. moggridgei showed a genetic differentiation slightly higher than F. tubiformis var. burnatii (values of GST respectively of 0.135 and 0.117). The hierarchical analysis of molecular variance (AMOVA) confirmed these findings, demonstrating that about 83% of the variation was within populations and the remaining variance was attributable partly to differences between groups (6.45%) and partly among populations (10.64%), providing corroborating evidence for the genetic structure predicted by the Nei's indices analysis (Table 4).

thumbnail
Table 4. Analysis of molecular variance (AMOVA) within and among the populations studied.

https://doi.org/10.1371/journal.pone.0101967.t004

Cluster analysis, based on pairwise FST distances between all pairwise combinations of individuals, was used to generate an UPGMA dendrogram in order to examine relationships between populations (Figure 2). Populations clustered thoroughly in two distinct main groups, showing low geographical correspondence. The first cluster contained all the four populations of var. burnatii but with intermixed populations of subsp. moggridgei. The DRO and PRA populations (both sampled in Maira Valley) clustered together as a sister group to ROS (Tanaro Valley) but also to SAC and SAM belonging to subsp. moggridgei. The second cluster grouped together the remaining populations belonging to subsp. moggridgei and precisely CRA and MAR (from Pesio Valley) as a sister group to the populations FRO and PLU. No precise assignation was possible for the remaining two populations, SER and GAL, belonging respectively to var. burnatii and subsp. moggridgei.

thumbnail
Figure 2. Dendrogram based on UPGMA of RAPDs profiles, showing relationships among the 11 populations of Fritillaria tubiformis considered in the study.

M =  Fritillaria tubiformis subsp. moggridgei, B =  Fritillaria tubiformis var. burnatii.

https://doi.org/10.1371/journal.pone.0101967.g002

The PCoA analysis was performed to visualise the grouping of populations more clearly, providing a graphical representation of the relationships between them (Figure 3). Calculated pairwise Euclidean distances were used as an input for PCoA. The first two principal coordinate axes accounted for 49.76% and 21.35% of the total variation (cumulative value 71.11%). The first principal coordinate clearly distinguished subspecific taxa, but when referred to the second coordinate, populations were broadly scattered and clustered independently of each other (Figure 3).

thumbnail
Figure 3. PCoA plot based on RAPDs variation, with the first two principal components showing relationships among the 11 populations of Fritillaria tubiformis studied.

https://doi.org/10.1371/journal.pone.0101967.g003

Following the method of Evanno et al. [26], the Bayesian clustering results obtained with STRUCTURE indicate that K = 2 clusters represents the most informative representation of the overall genetic structure that we analysed (Figure 4). We found that most individuals from subsp. moggridgei (CRA, FRO, GAL, MAR, and PLU) clearly belong to cluster 1, whereas var. burnatii populations (DRO, PRA, ROS and SER) are primarily composed by individuals from cluster 2. Exceptions are represented by two admixed populations belonging to subsp. moggridgei (SAC and SAM), that already in the UPGMA analysis were shown to be more similar to var. burnatii than to other populations of the same taxon.

thumbnail
Figure 4. Probability of assignment of 264 plants of Fritillaria tubiformis from Italy to the two genetic clusters identified by hierarchical STRUCTURE analysis, and corresponding with subspecific taxa.

Each vertical bar corresponds with a distinct genotype and different colours indicate the part of its genome assigned to each cluster. M =  Fritillaria tubiformis subsp. moggridgei, B =  Fritillaria tubiformis var. burnatii.

https://doi.org/10.1371/journal.pone.0101967.g004

Discussion

This study investigated genetic variation of Fritillaria tubiformis subsp. moggridgei endemic of the South-Western Alps. Genetic structure in this subspecies was compared with four populations of Fritillaria tubiformis var. burnatii sampled within the range of the subspecies.

RAPD markers proved to be an efficient tool to analyse genetic variation both within and among populations. However, it must be underlined that RAPD variation cannot be linked with variation in adaptive genes [27], so that further research is needed to better understand the relationship between the observed variation and the adaptive potential of these taxa. The use of RAPD markers to estimate genetic parameters in outcrossing populations has been questioned: since RAPDs are dominant markers, null alleles present only in heterozygous genotypes cannot be detected, thus underestimating gene diversity [14].

In species with complex life histories, the choice of appropriate techniques of genetic analysis is not obvious. In a previous analysis run on chloroplast DNA with different type of sequence repeats, we showed that only insertion/deletion events were effective in discriminating genetically between yellow and dark purple flowered-morphotypes of F. tubiformis [12]. In the present study, RAPDs amplified mostly non-coding nuclear DNA sequences, which are subject to weaker selection pressures, thereby allowing the scoring of a higher amount of genetic variation.

F. tubiformis subsp. moggridgei displayed a level of genetic diversity in line with expectations. Expected heterozygosity (He  = 0.194) (Table 3) was similar to the average value of Hpop reported by Nybom [28] for endemic species (0.20), and for species with seeds dispersed by gravity (Hpop  = 0.19).

The average percentage of polymorphic loci (75–85%) (Table 3) and total gene diversity (0.293) were in the range previously reported with RAPDs for other endemic or endangered species [17], [29], [30], [31]; in contrast, percent polymorphism was higher in subsp. moggridgei than in the Iranian endemic F. imperialis L. a much more widespread congeneric [32].

Despite the relatively restricted geographical range covered by this investigation, F. tubiformis populations exhibited genetic divergence. Using the AMOVA procedure, we showed that although most of the phenotypic variation was allocated within populations (82.91%), a significant proportion was attributable to genetic differences between intraspecific taxa (6.45%), as well as between populations (10.64%) (Table 4).

The overall FST value (0.171) was significantly different from zero (P<0.001) (Table 4), providing evidence for a strong genetic structuring among populations. This pattern of differentiation is expected for species pollinated by insects, and with scattered distribution. In this case genetic differentiation is generally higher than that occurring in wind-pollinated species with a more continuous distribution [33], [34]. Significant levels of variation among populations were also observed by partitioning of variability based on Nei's gene diversity (GST  = 17.4%), confirming the existence of a genetic structuring among populations.

The results also indicate that most of the total genetic variation was present within populations. Patterns of high genetic diversity at both the species' and local population levels have already been documented in other mountain plants [35] and critically endangered species [36], [37], especially when relatively large populations have been considered [38]. Our findings, however, were in contrast with two studies on F. imperialis and F. camschatcensis using RAPD markers, where variation within populations accounted for only 54% and 35.7% of the total variation, respectively [32], [39]. As stressed in the study with chloroplast DNA, when molecular variation is based on allele frequencies, a slight over-estimation of the within population component of variation is possible [12]. This is likely to have occurred in the present study. Moreover, other ecological and demographical characteristics are likely to have promoted the maintenance of high levels of genetic variation in subsp. moggridgei populations. This is supported by previous RAPD-based analyses which showed that long-lived, outcrossing or late successional species retain most of their genetic variability within populations [35], [40]; and by contrast, annual, selfing and/or early successional plants allocate most of the genetic variability among populations [28]. The results stress that F. tubiformis subsp. moggridgei has not experienced population bottlenecks, and the general low levels of inbreeding likewise suggest a predominantly outcrossing mating system for this taxon [40], in accordance with field surveys and breeding features of related species [41].

Population size and geographical separation may be strong determinants of the spatial distribution of genetic variation in populations of neighboring species with fragmented distributions [42][43]. These conditions, in combination with life-history features such as growth form, mating system and seed dispersal mechanisms [44], may have conditioned the genetic history of F. tubiformis subsp. moggridgei populations. SAM, for example, has little chance of gene flow. This is in fact a very small population at a relatively low altitude, which has suffered the impact of agricultural activities and human settlements. GAL and SAC populations, on the contrary, are isolated populations, which nevertheless might receive frequent visits of pollinators thanks to their position on the very summit of two mountains.

Analyses of population genetic structure (UPGMA, PCoA and Structure) showed that the studied populations belonged to two distinct genetic pools corresponding to the subspecific taxa. The varied geological, topographical and climatic conditions of the Alpine chain can boost isolation and divergence of populations even over short geographical distances, thus explaining the fragmented distribution and genetic complexity of some endemic species of the Maritime Alps [45]. This genetic separation, however, was never rigorous, and three populations of subsp. moggridgei showed repeated admixture with var. burnatii, leaving open the problem of their exact taxonomic attribution. The profile of the UPGMA tree supported a certain degree of genetic admixture across SAC and SAM populations, which positioned in the tree within populations of var. burnatii (Figure 2). When analyzed by Structure, genetic admixture was present to some extent also in GAL population (Figure 4). These findings are in accordance with a previous phylogenetic analysis, where we showed that subsp. moggridgei was more phylogenetically related to var. burnatii (matK and rpl16 genes) than to any other Fritillaria species considered in the study [12].

If the ambiguous positioning of GAL population in these analysis can be explained by its geographical position and low demographic size, no explanations seems possible for the other two populations. Moreover, clustering of apparently distant populations as SAC (Val Tanaro, Ligury) and SAM (Val Stura, Piedmont) demonstrated that population positioning in the UPGMA tree was almost geographically unrelated. In support of this finding, it has been observed that when analysed by RAPD markers, population diversity is little affected by geographical range [28]. The UPGMA results were supported by PCoA that showed that populations were distributed along the first coordinate according to the intraspecific taxa (almost 50% variation), but showed admixture according to the second coordinate (SAC and SAM in subspecies moggridgei and SER in the variety burnatii) (Figure 3).

The position of the three populations of subsp. moggridgei is ambiguous and it remains unclear whether they are a hybrid of recent origin between subsp. moggridgei and var. burnatii [46] or whether they represent a separate evolutionary lineage. The low levels of genetic divergence among populations encountered in this study, seem to support the first hypothesis. However, broader taxon sampling in the territory of France might shed more light on this interesting problem.

F. tubiformis sensu lato is increasingly rare in the wild, due to habitat loss, and some populations are already under threat because of human activities. In conclusion, this study has shown that F. tubiformis subsp. moggridgei has a substantial degree of genetic diversity, which may counteract genetic erosion and maintain high adaptive potential in the subspecies. Indeed, this potential is mainly determined by the species genetic diversity [2]. The results show that despite being a narrow endemic with a relatively small distribution and fragmented, isolated populations, F. tubiformis subsp. moggridgei exhibits high level of genetic diversity and, in the perspective of a long-term conservation, a restricted number of its populations would be variable enough to represent the genetic variability of the subspecies.

A literature and herbarium-based survey of subsp. moggridgei and var. burnatii has shown that the taxonomic status of the Italian populations is uncertain [11]. A thorough phylogenetic analysis aiming at assessing their genetic relationships with respect to other widespread congeneric taxa of the Alpine chain (for example F. tubiformis Gren. & Godr.), will provide information essential for the formulation of appropriate management strategies for the conservation of all these populations.

Supporting Information

Dataset S1.

Fritillaria tubiformis subsp. moggridgei RAPD profile and Analysis of Molecular Variance (AMOVA). The pairwise FST matrix of all population comparisons and step by step pairwise distances along with population labels are also given and can be used to manually calculate AMOVA results.

https://doi.org/10.1371/journal.pone.0101967.s001

(XLSX)

Acknowledgments

Thanks are due to colleagues from “Translations Group” for the language revision of the manuscript (www.translation-group.com/).

Author Contributions

Conceived and designed the experiments: MM PB. Performed the experiments: DF MM. Analyzed the data: PB DF. Contributed reagents/materials/analysis tools: PB MM. Contributed to the writing of the manuscript: PB MM.

References

  1. 1. Reich PB, Oleksyn J (2008) Climate warming will reduce growth and survival of Scots pine except in the far north. Ecol Lett 11: 588–597.
  2. 2. Kramer AT, Havens K (2009) Plant conservation genetics in a changing world. Trends Plant Sci 14: 599–607.
  3. 3. Jump AS, Peñuelas J (2006) Genetic effects of chronic habitat fragmentation in a wind-pollinated tree. Proc Natl Acad USA 103: 8096–8100.
  4. 4. Pautasso M (2009) Geographical genetics and the conservation of forest trees. Perspect Plant Ecol 11: 157–189.
  5. 5. Escudero A, Iriondo JM, Torres ME (2003) Spatial analysis of genetic diversity as a tool for plant conservation. Biol Conserv 113: 351–365.
  6. 6. Väli Ü, Einarsson A, Waits L, Ellegren H (2008) To what extent do microsatellite markers reflect genome-wide genetic diversity in natural populations? Mol Ecol 17: 3808–3817.
  7. 7. Rice KJ, Emery NC (2003) Managing microevolution: restoration in the face of global change. Front Ecol Environ 1: 469–478.
  8. 8. Frankham R (2005) Genetics and extinction. Biol Conserv 126: 131–140.
  9. 9. Eckert CG, Samis K, Lougheed SC (2008) Genetic variation across species' ranges: the central-marginal hypothesis and beyond. Mol Ecol 17: 1170–1188.
  10. 10. Conti F, Abbate G, Alessandrini A, Blasi C (2005) An annotated checklist of the Italian vascular flora. Roma: Palombi.
  11. 11. Bartolucci F, Peruzzi L (2012) Typification of Fritillaria tubiformis Gren. & Godr., Fritillaria delphinensis f. moggridgei Planch. and Fritillaria delphinensis var. burnatii Planch. (Liliaceae) from SW Europe. Candollea 67: 23–29.
  12. 12. Mucciarelli M, Fay M (2013) Plastid DNA fingerprinting of the rare Fritillaria moggridgei (Liliaceae) reveals population differentiation and genetic isolation within the Fritillaria tubiformis Complex. Phytotaxa 91: 1–23.
  13. 13. MacPherson J, Eckstein P, Scoles G, Gajadhar A (1993) Variability of the random amplified polymorphic DNA assay among thermal cyclers, and effects of primer and DNA concentration. Mol Cell Probes 7: 293–299.
  14. 14. Lynch M, Milligan BG (1994) Analysis of population genetic structure with RAPD markers. Mol Ecol 3: 91–99.
  15. 15. Nei M (1973) Analysis of gene diversity in subdivided populations. Proc Nat Acad Sci USA 70: 3321–3323.
  16. 16. Lewontin RC (1972) The apportionment of human diversity. Evol Biol 6: 381–398.
  17. 17. del Hoyo A, López-Pujol J, Chung MY, Lasso de la Vega B (2012) Population genetics and conservation of the extremely narrow Pyrenean palaeoendemic Glandora oleifolia (Boraginaceae). Plant Ecol Divers 4: 501–511.
  18. 18. Peakall R, Smouse PE (2006) GENALEX 6: genetic analysis in Excel. Population genetic software for teaching and research. Mol Ecol Notes 6: 288–295.
  19. 19. Nei M (1987) Molecular evolutionary genetics. New York, NY: Columbia Univ Press.
  20. 20. Excoffier L, Smouse PE, Quattro JM (1992) Analysis of molecular variance inferred from metric distances among DNA haplotypes: application to human mitochondrial DNA restriction data. Genetics 131: 479–491.
  21. 21. Schneider S, Roessli D, Excoffier L (2000) Arlequin ver. 2.000: a software for population genetics data analysis. University of Geneva, Switzerland: Genetics and Biometry Laboratory.
  22. 22. Weir BS, Cockerham CC (1984) Estimating F-statistics for the analysis of populations structure. Evolution 38: 1358–1370.
  23. 23. Sneath PHA, Sokal RR (1973) Numerical Taxonomy: The principles and practice of numerical classification. San Francisco, CA: Freeman, WH and Co.
  24. 24. Rohlf FJ (2001) NTSYS-pc Numeral Taxonomy and Multivariate Analysis System, version 2.10j. New York, NY: Exeter Publications.
  25. 25. Pritchard JK, Stephens M, Donnelly P (2000) Inference of population structure using multilocus genotype data. Genetics 155: 945–959.
  26. 26. Evanno G, Regnaut S, Goudet J (2005) Detecting the number of clusters of individuals using the software structure: a simulation study. Mol Ecol 14: 2611–2620.
  27. 27. Bekessy SA, Ennos RA, Burgman MA, Newton AC, Ades PK (2003) Neutral DNA markers fail to detect genetic divergence in an ecologically important trait. Biol Conserv 110: 267–275.
  28. 28. Nybom H (2004) Comparison of different nuclear DNA markers for estimating intraspecific genetic diversity in plants. Mol Ecol 13: 1143–1155.
  29. 29. Li XJ, Yang HL, Liu JQ (2008) Genetic variation within and between populations of the Qinghai-Tibetan Plateau endemic Gentiana straminea (Gentianaceae) revealed by RAPD markers. Belg J Bot 141: 95–102.
  30. 30. Rustaiee AR, Hassani ME, Tabatabaei SMF, Omidbaigi R (2010) Evaluation of genetic diversity among some populations of Thymus daenensis Celak., a vulnerable medicinal plant from Iran. Hort Environ Biotechnol 51: 335–342.
  31. 31. Sözen E, Özaydın B (2010) A study of genetic variation in endemic plant Centaurea wiedemanniana by using RAPD markers. Ekoloji 19: 1–8.
  32. 32. Badfar-Chaleshtori S, Shiran B, Kohgard M, Mommeni H, Hafizi A, et al. (2012) Assessment of genetic diversity and structure of Imperial Crown (Fritillaria imperialis L.) populations in the Zagros region of Iran using AFLP, ISSR and RAPD markers and implications for its conservation. Biochem Syst Ecol 42: 35–48.
  33. 33. Hamrick JL, Godt MJW, Sherman-Broyles SL (1992) Factors influencing levels of genetic diversity in woody plant species. New Forest 5: 95–124.
  34. 34. Nybom H, Bartish IV (2000) Effects of life history traits and sampling strategies on genetic diversity estimates obtained with RAPD markers in plants. Perspect Plant Ecol Evol Syst 3: 93–114.
  35. 35. Medrano M, Herrera CM (2008) Geographical structuring of genetic diversity across the whole distribution range of Narcissus longispathus, a habitat-specialist, mediterranean narrow endemic. Ann Bot 102: 183–194.
  36. 36. Wang BY, Shi L, Ruan ZY, Deng J (2011) Genetic diversity and differentiation in Dalbergia sissoo (Fabaceae) as revealed by RAPD. Genet Mol Res 10: 114–120.
  37. 37. Liu J, Shi S, Chang E, Yang W, Jiang Z (2013) Genetic diversity of the critically endangered Thuja sutchuenensis revealed by ISSR markers and the implications for conservation. Int J Mol Sci 14: 14860–14871.
  38. 38. Ellstrand NC, Elam DR (1996) Population genetic consequences of small population size: implications for plant conservation. Annu Rev Ecol Syst 24: 217–242.
  39. 39. Yamagishi M, Nishioka M, Kondo T (2010) Phenetic diversity in the Fritillaria camschatcensis population grown on the Sapporo campus of Hokkaido. Landscape Ecol Eng 6: 75–79.
  40. 40. Barrett SCH, Cole WW, Herrera CM (2004) Mating patterns and genetic diversity in the wild daffodil Narcissus longispathus (Amaryllidaceae). Heredity 92: 459–465.
  41. 41. Zynch M, Stpiczyńska M (2012) Neither protogynous nor obligatory out-crossed: pollination biology and breeding system of the European Red List Fritillaria meleagris L (Liliaceae). Plant Biol 14: 285–294.
  42. 42. Young A, Boyle T, Brown T (1996) The population genetic consequences of habitat fragmentation. Trends Ecol Evol 11: 413–418.
  43. 43. Leimu R, Mutikainen P, Koricheva J, Fischer M (2006) How general are positive relationships between plant population size, fitness and genetic variation? J Ecol 94: 942–952.
  44. 44. Hamrick JL, Godt MJW (1996) Effects of life history traits on genetic diversity in plant species. Philos Trans R Soc Lond B Biol Sci 351: 1291–129.
  45. 45. Casazza G, Grassi F, Zecca G, Mariotti MG, Guerrina M, et al. (2013) Phylogeography of Primula allionii (Primulaceae), a narrow endemic of the Maritime Alps. Bot J Linn Soc 173: 637–653.
  46. 46. Wolf PG, Soltis PS, Soltis DE (1993) Phylogenetic significance of chloroplast DNA restriction site variation in the Ipomopsis aggregata complex and related species (Polemoniaceae). Syst Bot 18: 652–655.