Patterns of genetic variation in the Chinese endemic Psilopeganum sinense (Rutaceae) as revealed by nuclear microsatellites and chloroplast microsatellites

Biochemical Systematics and Ecology 55 (2014) 190e197

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Patterns of genetic variation in the Chinese endemic Psilopeganum sinense (Rutaceae) as revealed by nuclear microsatellites and chloroplast microsatellites Feiyan Tang, Qigang Ye, Xiaohong Yao* Key Laboratory of Plant Germplasm Enhancement and Specialty Agriculture, Wuhan Botanical Garden, The Chinese Academy of Sciences, Wuhan 430074, Hubei, China

a r t i c l e i n f o

a b s t r a c t

Article history: Received 20 January 2014 Accepted 29 March 2014 Available online

Psilopeganum sinense is a perennial herb endemic to Three-Gorges Reservoir Area (TGRA) in China. Genetic diversity of this endangered species was assessed by using 11 nuclear microsatellites and three chloroplast microsatellite (cpSSR) markers. A total of 8 haplotypes were identified in a survey of 212 individuals sampled from nine populations encompassing most of the natural range of the species. A low level of genetic diversity was detected: HE ¼ 0.301 for SSR and HE ¼ 0.28 for cpSSR. Populations were highly differentiated from one another: an AMOVA analysis that showed that 56.3% and 68.2% genetic variation resided between populations based on SSR and cpSSR analysis, respectively, and FST and FSTc (0.467 for SSR and 0.644 for cpSSR, respectively) were high. Significant differences were found between estimates of haplotypic differentiation calculated by using unordered alleles (GSTc ¼ 0.857) and ordered alleles (NSTc ¼ 0.728), which indicated the existence of phylogeographical structure in P. sinense. The indirect ratio of pollen flow/seed flow derived from estimates of haplotypic and nuclear DNA differentiation indicated that gene flow via pollen is less efficient than via seed. Two distinct evolutionary lineages (evolutionary significant units, ESUs) were recognized for P. sinense on the basis of both the PCoA and NCA analysis. Sampling strategies for conserving this endangered plant were discussed. Ó 2014 Elsevier Ltd. All rights reserved.

Keywords: Psilopeganum sinense Microsatellites Chloroplast microsatellites Genetic diversity Gene flow ESU

1. Introduction Psilopeganum sinense Hemsl. is a perennial plant endemic to China and the only member of its genus (Psilopeganum Hemsl.) in the family Rutaceae (Wu et al., 2003). This species is typically distributed sporadically in the brushwood of hillsides or under roadside trees at altitudes from 100 to 320 m along the Yangtze River from Yichang, Hubei to Wuling, Chongqing, centre-west China, a biodiversity hotspot in China (Wang et al., 1995). Due to its wide usage as a traditional medicinal herb and spiceberry, P. sinense has suffered severe over-collection by local residents. Furthermore, because the natural distribution of P. sinense is located in the core area of the Three Gorges Reservoir (TGR) along the Yangtze River, the natural habitat of P. sinense below 145 m above sea level has been inundated since 2003, and the inundated range has extended to 175 m above sea level in 2009 when the Three-Gorges Dam (TGD) was fully completed. The TGD has increased the isolation of remaining

* Corresponding author. E-mail address: [email protected] (X. Yao). http://dx.doi.org/10.1016/j.bse.2014.03.034 0305-1978/Ó 2014 Elsevier Ltd. All rights reserved.

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habitat patches of P. sinense. Although this has prompted urgent conservation plans to protect P. sinense, any effective conservation programmes will require population genetic analysis of extant populations to help manage this species in both insitu and ex-situ conditions. Genetic variation in natural populations is important for a species to maintain evolutionary potential to cope with environmental change (Frankham et al., 2002). As a result, information on the genetic diversity of endangered species will be fundamental to the development of long-term conservation strategies. The evolutionary significant unit (ESU) is usually defined as independently evolved and genetically isolated populations and devised as a practical way to approach the conservation management of endangered species. ESU has been defined as monophyly characterized by organelle haplotypes and significant divergence of allele frequencies at nuclear loci (Moritz, 1994). Recently, microsatellites, or tandem Simple Sequence Repeats (SSRs) have been effectively utilized in population genetic studies of plant species as they are highly abundant and polymorphic, co-dominantly inherited, analytically simple and readily transferable (e.g. Zhang et al., 2013). Due to a uniparental mode of inheritance, chloroplast genome-based population genetic studies provide a means for evaluating the relative roles of seed vs. pollen movement as sources of gene flow by comparison of chloroplast and nuclear data (Ennos, 1994; Ebert and Peakall, 2009) and identifying ESUs for rare or endangered species. The combined analysis may provide insights into the relative contribution of nuclear and organelle genomes to population structure (e.g. Muller et al., 2009) and therefore is a prerequisite to understanding the species survival possibility in the short term, so that an effective conservation strategy for long-term survival can be formulated and implemented. The genetic diversity of P. sinense at the level of nuclear DNA has been recently evaluated with RAPD markers (Song et al., 2004). The results showed that the species-level genetic diversity of P. sinense was high whereas the genetic diversity within each population was low. In the present study, nuclear and chloroplast microsatellites were used to examine the level and pattern of genetic diversity in natural populations of P. sinense. We also combined the chloroplast genome diversity and the SSR-based nuclear genome diversity to estimate the relative contributions of seed dispersal and pollen dispersal to population structure. The data should be also valuable, in terms of practical conservation, to formulate appropriate ESUs for longterm conservation of P. sinense. 2. Materials and methods 2.1. Study species Psilopeganum sinense Hemsl. has a mixed mating system, with predominant autogamy (Ye et al., 2014), but vegetative reproduction can occur as a result of adventitious rooting of fractured branches (Wang et al., 1995). The hermaphrodite flowers are pollinated by small insects. Large quantities of very small seeds are produced. Seeds are shaken out of the capsule when mature and dispersed by gravity. 2.2. Plant materials Psilopeganum sinense was collected from nine sites (referred to as populations, Table 1 and Fig. 1). Up to 31 individuals were collected from each population. Sample collections cover most of the species’ range in the Three-Gorges Reservoir Area. Fresh leaves were randomly collected from adult individuals and dried immediately by using silica gel, and stored at room temperature until DNA extractions were completed. 2.3. DNA extraction and genotyping DNA was extracted by using a modified CTAB protocol (Doyle and Doyle, 1987). The extraction buffer consisted of 2% CTAB, 100 mM TriseHCl pH 8.0, 20 mM EDTA pH 8.0, 1.4 M NaCl, 1% w/v polyvinylpyrrolidone, to which b-mercaptoethanol was Table 1 Geographic locations, habitats and sample sizes for the nine P. sinense populations sampled. Population

Code Locality

Wuling1 Wuling2 Wuxi

WL1 WL2 WX

Wushan Badong

WS BY

Badong

BX

Xingshan XS Changyang CY Yichang YC

Coordinates

Altitude (m)

Habitat

30 320 N/108 160 E 170e180 Farmland side of brae; clumped 30 310 N/108 160 E 150e160 Farmland side of brae; sporadic 31 250 N/109 360 E 250e280 Hillside or fieldside; cespitose or sporadic Shuanglong Town, Wushan County, Chongqing City 31 060 N/109 520 E 110e150 Hillside; sporadical or cespitose Yanduhe Town, Badong County, Hubei Province 31 150 N/110 170 E 170e200 Riverside or ditchside; cespitose or sporadical Xinling Town, Badong County, Hubei Province 31 010 N/110 240 E 200e220 Roadside, hillside; sporadic or cespitose Gaoyang Town, Xingshan County, Hubei Province 31 150 N/110 430 E 180e250 Hillside of road; sporadic  0  0 Gaojiayan Town, Changyang County, Hubei Province 30 36 N/111 03 E 185e210 Brae bottom, ditchside; sporadic Yiling District, Yichang City, Hubei Province 30 470 N/111 150 E 170e190 Roadside of ravine; cespitose Wuling Town, Wanzhou District, Chongqing City Wuling Town, Wan County, Chongqing City Chengxiang Town, Wuxi County, Chongqing City

Sampling size 25 15 24 24 30 31 22 17 24

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Fig. 1. Distribution of 12 chloroplast haplotypes detected in P. sinense.

added just before use. Extracted DNA was assessed by running on a 0.8% agarose mini-gel, and then diluted to 10 ng/mL with autoclaved deionized water before use in PCRs. Eleven microsatellite primers developed by Tang et al. (2008) were used to genotype all the sampled individuals. Polymerase chain reaction (PCR) was performed as described by Tang et al. (2008). A set of ten conserved chloroplast microsatellite primers (ccmp1 to ccmp10) reported by Weising and Gardner (1999) were used to screen variation. The amplifications were carried out in a PTC-200 thermal cycler (MJ Research, MA, USA) as described by Weising and Gardner (1999). PCR products were run on 1.5% agarose gels to verify the reproducibility of the amplifications. An initial screening to look for variation was carried out by using 12 individuals from six populations and polymorphic primer pairs were then used to screen all P. sinense individuals. Amplified products were separated on a 6% denaturing polyacrylamide gel by using silver staining. A 25-bp DNA ladder (Promega, USA) was used to identify alleles. 3. Data analysis 3.1. Genetic analysis of SSR data Observed heterozygosity (HO) and expected heterozygosity (HE) for each locus and population, and inbreeding coefficient (FIS) for each population were calculated with CERVUS 2.0 (Marshall et al., 1998). Allele richness (AR) and mean number of alleles per locus (A) were estimated with FSTAT software (Goudet, 2001). HardyeWeinberg and linkage disequilibrium between microsatellites were tested by Fisher’s exact tests (GENEPOP, version 3.4; Raymond and Rousset, 1995). Null alleles were checked in MICRO-CHECKER 2.2 (Van Oosterhout et al., 2004). Recent reduction in effective population size for each sample was tested with the program BOTTLENECK (Piry et al., 1999). We used the Wilcoxon sign-rank test of heterozygosity of excess under three different models, i.e., the infinite allele model (IAM), the stepwise mutation model (SMM) and the two-phase model (TPM). Ten thousand simulations for each mutational model were performed. Principal coordinate analysis (PCoA) was performed on the basis of the resulting distance matrices of squared Euclidean distances between all pairs of genotypes by using GENALEX 6.1. (Peakall and Smouse, 2006). 3.2. Genetic analysis of chloroplast microsatellite data The total number of haplotypes (No), effective number of haplotypes (Ne), and unbiased haplotype diversity (He) were estimated by using the software SPAGeDi ver.1.2 (Hardy and Vekemans, 2002). The software ARLEQUIN 2.000 (Schneider P 2 et al., 2000) was used to estimate the haplotype diversity He ¼ [n/(n  1)][1  pi ] (where n is the number of individuals analyzed and pi is the frequency of the i-th haplotype in a population). Levels of differentiation in chloroplast genome for unordered alleles (GST) and ordered alleles (NST) were calculated by using the program PERMUT (Pons and Petit, 1996). Significantly higher NST versus GST values indicate that genealogically close related haplotypes tend to occur together within populations, suggesting the existence of phylogeographical structure (Pons and Petit, 1996). The ratio of pollen to seed flow (r ¼ mp/ms) was calculated with a modified equation of Ennos (1994): r ¼ mp/ms ¼ [(1/FSTn 1)-2(1/FSTc 1)]/(1/FSTc 1), in which FST is substituted by GST (Fineschi et al., 2000). The equation is used to estimate the

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relative ratio of pollen to seed flow in different angiosperm species for which FST values are available from both biparentally and maternally inherited markers (Fineschi et al., 2000). FSTn and FSTc indicate the level of population subdivision based on nuclear and cytoplasmic markers, respectively. A minimum spanning network was computed with MINSPNET (Excoffier and Smouse, 1994), proved with the software ARLEQUIN. To test for a significant association between haplotypes and their geographical distribution, and to separate population structure from population history (Templeton et al., 1995), a nested clade analysis (NCA) was conducted with the program GEODIS 2.5 (Posada et al., 2000). Statistically significant large or small values of DC (clade distances) and DN (nested clade distances) (Templeton et al., 1995) were interpreted by using the inference key given by Templeton (2004). 3.3. General analysis We evaluated pairwise genetic differentiation among populations (FST) using FSTAT. The association between the genetic distance matrices (GST) and pairwise geographic distances (Isolation by Distance) was analyzed with a Mantel test (Mantel, 1967). Hierarchical tests of population structure were performed by using the AMOVA function in ARLEQUIN 2.000 (Schneider et al., 2000). 4. Results 4.1. Genomic SSR analysis The 11 microsatellite loci used in this study generated a total of 75 alleles, ranging from two alleles at locus Psh1, Psh2 and Psh10 to 17 alleles at loci Psh5. Expected heterozygosity per locus from ranged from 0.302 to 0.874 and observed heterozygosity ranged from 0.043 to 0.339 (Table S1). Most of microsatellite markers failed to amplify successfully for the WS population due to its poor DNA quality. Hence the WS population was removed from further analysis. Across eight populations, the average expected heterozygosity (HE) per population is 0.301, the average observed heterozygosity (HO) per population is 0.193, and the average number of alleles per population is 2.5 (Table 2). Null alleles were not detected at any loci. The level of inbreeding (FIS) for each population ranges from 1.000 to 0.719. All populations were observed to deviate from HardyeWeinberg equilibrium when all loci were combined and Bonferroni-type correction applied (Table 2). Significant linkage disequilibrium between SSR loci within each population was detected for 22 out of 440 comparisons at the 5% significance level, but no linkage disequilibria were detected for any locus pair in any population after Bonferroni-type correction was applied. The Wilcoxon’s statistical test revealed a demographic bottleneck in three populations under the IAM model, but only in two populations under the TMP and SMM models. In addition, three out of the remnant eight populations displayed a shifted distribution of allele frequencies. All pairwise values of FST (0.200e0.870) were highly significant (P < 0.0001, Table S2). At the population level, 56.3% of the total molecular variation was attributed to inter-population differentiation, and 43.7% to individual differentiation within populations. Principal coordinate axes 1 and 2, explaining 21.7% and 15% of the variation, respectively, revealed two distinct groups of genotypes (Fig. 2). 4.2. Chloroplast SSR analysis Of the 10 primer pairs screened, seven (ccmp1, ccmp2, ccmp4, ccmp5, ccmp8, ccmp9, ccmp10) generated successful amplifications and thus were used to fingerprint all individual plants. Three (ccmp3, ccmp6 and ccmp7) of the seven primers used were found to be polymorphic. Two length variants (103, 104 bp) were detected in ccmp3, three length variants (124, 125, 126 bp) in ccmp6 and four length variants (138, 139, 140, 142 bp) in ccmp7 (Table S3). Table 2 Genetic diversity statistics for the nine populations of P. sinense. Population

N

nSSR

cpSSR

A

AR

HE

HO

FIS

No

Ne

He

D2sh

WL1 WL2 WX WS BY BX XS CY YC Mean

25 15 24 24 30 31 22 17 24 23.6

1.7 1.1 2.2 e 1.9 4.4 2.2 2.4 3.9 2.5

1.6 1.1 2.1

0.089 0.050 0.283 e 0.216 0.454 0.228 0.552 0.539 0.301

0.116 0.100 0.179 e 0.110 0.265 0.123 0.332 0.325 0.193

0.284* 1.000* 0.384* e 0.504* 0.431* 0.480* 0.719* 0.415* 0.527

1 1 1 2 2 2 3 2 4 2

1 1 1 1.80 1.07 1.72 2.35 1.84 2.55 1.58

0 0 0 0.53 0.07 0.40 0.60 0.49 0.63 0.28

0 0 0 0.15 0.02 0.13 1.09 1.46 1.53 0.49

1.8 3.8 2.1 2.4 3.7 2.3

N, Sample size; A, mean number of alleles per locus; AR, allele richness; HE, expected heterozygosity; HO, observed heterozygosity; FIS, inbreeding coefficient; indicates significant deviation from HardyeWeinberg equilibrium (P < 0.05); No, total number of haplotypes; Ne, effective number of haplotypes; He, unbiased haplotype diversity; D2sh, mean pairwise haplotype distance. *

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Fig. 2. Principal components analysis computed on the 188 individuals from eight populations of P. sinense based on microsatellite data.

Combining polymorphic fragments from cpSSR analyses allowed eight haplotypes (H1 to H8) to be identified (Table S3). The haplotype diversity per population ranged from 0 to 0.63. The average haplotype diversity of intra-population and total haplotype diversity were 0.28 and 0.83, respectively (Table 2). Except haplotype H6, which was found in a single population (XS), all other haplotypes were found in two or more populations (Fig. 1 and Table 3). H2 was the most frequent haplotype (26.4%), followed by haplotype H1 (20.3%) and H4 (19.3%), whereas the frequencies of other four haplotypes were less than 10% (Table 3). Three populations were fixed for a single haplotype: WL1, WL2 were fixed for a single haplotype H1, whereas WX was fixed for haplotype H2. Thus no cpDNA haplotype diversity was detected in these populations (HE ¼ 0). Two haplotypes were detected in populations BX, BY, CY and WS, and three and five haplotypes in population XS and YC, respectively. Global haplotype differentiation values of GST and NST were 0.857 and 0.728, respectively. The permutation test revealed a significant difference between GST and NST (P < 0.05), suggesting phylogeographic structure in cpDNA diversity. Moreover, a significant correlation was detected between genetic distances and geographical distances (r ¼ 0.52, P ¼ 0.012), indicating that gene flow was geographically limited among populations. This is in agreement with the result obtained by the PERMUT analysis. Only one of the 36 pairwise FST comparisons was not significant at the 5% level (Table S2). Of the total genetic variation, 68.2% was attributed to differences among populations and 31.8% to differences among individuals within populations. The result of nested design for the NCA is shown in and Table 5. Two distinct evolutionary lineages (ESUs) were recognized. At the one-step-level, restricted gene flow with isolation by distance was inferred for derived haplotypes in clades 1e1 and 1e 4. For the second clade level, NCA inferred restricted gene flow and dispersal but with some long-distance dispersal in clade 2e4. At the level of the entire cladogram, NCA revealed allopatric fragmentation (Table 5). The subdivision value FST among populations was calculated as FSTc ¼ 0.644 and FSTn ¼ 0.467 for chloroplast and nuclear markers, respectively. The ratio pollen flow/seed flow, calculated according to the FST value, was 0.065. 5. Discussion This study represents the first P. sinense investigation that has compared genomic and chloroplast microsatellite markers. Our results revealed low genetic diversity within each population and high levels of genetic differentiation among populations, which is consistent with results obtained in a previous study with RAPD markers (Song et al., 2004). 5.1. Genetic diversity A low level of genetic variation was detected in eight extant populations of P. sinense based on the SSR markers. Moreover, the number of haplotypes (eight) is quite low, with seven of nine populations harboring only one or two haplotypes. Consequently, three of nine populations have no haplotype diversity and a relatively low average intra-population haplotype Table 3 Chloroplast DNA haplotype frequencies for P. sinense. Population

Na

Haplotype frequency

WL1 WL2 WX WS BY BX XS CY YC Overall

25 15 24 24 30 31 22 17 24 212

1.000 (25) 1.000 (15)

H1

a

H2

1.000 0.333 0.033 0.742

H3

(24) (8) (1) (23)

0.189 (40)

0.264 (56)

H5

H6

H7

H8

0.647 (11) 0.417 (10) 0.100 (21)

0.353 (6) 0.042 (1) 0.033 (7)

0.667 (16) 0.967 (29) 0.258 (8) 0.409 (9)

N sample size for analysis.

H4

0.083 (2) 0.127 (27)

0.500 (11)

0.189 (40)

0.091 (2) 0.458 (11) 0.090 (19)

0.001 (2)

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Table 4 Tests for mutationedrift equilibrium. Probabilities from Wilcoxon sign-rank tests and mode shift as inferred by the program BOTTLENECK. Population

Mutation-drift test IAM

SMM

TPM

Mode shift

WL1 WL2 WX BY BX XS CY YC

0.0625 0.2500 0.0547 0.1875 0.1875 0.0313* 0.0010*** 0.0034**

0.0313* 0.2500 0.2891 0.4688 0.8838 0.4375 0.0186** 0.2158

0. 0625 0.2500 0.1484 0.3438 0.3477 0.0625 0.0010*** 0.0161**

Normal Shifted Shifted Normal Normal Normal Shifted Normal

*P

< 0.05;

**P

< 0.01;

***P

< 0.001.

diversity compared with other angiosperm species (Petit et al., 2005). The low level of genetic diversity found in the current study is most likely explained by the predominantly selfing breeding system, narrow distribution and population bottleneck. Predominantly selfing species such as P. sinense (Ye et al., 2014) tend to have less genetic diversity within populations, as well as greater genetic differentiation among populations (Hamrick and Godt, 1989). Furthermore, narrowly distributed or endemic species possess lower genetic diversity than their widespread congeners (Hamrick and Godt, 1989). P. sinense is a relict species mainly distributed in the Three-Gorges Reservoir Area, which belongs to the East Sichuan-West Hubei distribution center, one of the biodiversity hotspots with high endemism in China (Wu et al., 2003). However, all populations of P. sinense occur in human-managed lands and are thus prone to extirpation caused by local agricultural activities. As a traditional herb, the over-collection by local residents has further placed this species as risk of local extinction. Another possible explanation for low diversity found within populations is that extant populations have experienced repeated bottlenecks caused by anthropogenic activities. Though the Wilcoxon test performed in BOTTLENECK is not considered a very rigorous test with less than 10 loci and 30 individuals per population (Piry et al., 1999), bottleneck analyses revealed that four populations may have experienced population bottlenecks (Table 4). Hence, for a short-lived perennial species, genetic bottlenecks could have contributed to the genetic impoverishment of this endangered species. 5.2. Genetic differentiation As expected for a selfing species (Hamrick and Godt, 1989), high genetic differentiation was observed among populations of P. sinense. Microsatellite analysis showed great genetic differentiation among the populations. Moreover, the high level of differentiation measured for cpDNA variation in P. sinense (FSTc ¼ 0.644) was similar to that of other angiosperm species, considering their pattern of inheritance (GSTc ¼ 0.637, reviewed by Petit et al. (2005)). Strong genetic divergence among

Table 5 Results of the nested clade analysis for P. sinense haplotypes. Dca

Dna

Inferenceb

Nesting clade

Clades

1e1

H2 (I) H4 I-T

39 18S 20L

43L 28S 15L

Restricted gene flow with isolation by distance

1e2

H5 (I) H6 I-T

39 0 39

40 42 2

Inconclusive outcome

1e4

H3 (I) H7 I-T

45S 13S 32L

63L 52S 11L

Restricted gene flow with isolation by distance

2e2

1e1 (I) 1e2 1e3 1e4 I-T

37S 41S 5S 58L 11S

43S 53 78L 63L 18S

Restricted gene flow/dispersal but with some long distance dispersal

Total

2e1 2e2 (I) I-T

1S 53S 52L

167L 69S 99S

Allopatric fragmentation

a Statistical significance of Dc and Dn determined by 1000 random permutations of clades against sampling location. Superscript S/L corresponds to significantly small distance/large distance at P  0.05 level. Interior clades are labeled with “(I)”. b Inferences were made following the updated version (11-Nov-2005) of the inference key provided in Templeton (2004).

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populations was also revealed by the PERMUT analysis. In this present study, the difference between GSTc and NSTc was significant, which indicates the existence of a relationship between phylogeny and the geographical distribution of haplotypes (Pons and Petit, 1996). Significant genetic differentiation suggests that gene flow among P. sinense populations is likely to be restricted. Chloroplast and nuclear GST values are not independent and they may be used to derive the pollen/seed flow ratio (Ennos, 1994). Usually, insect-pollinated angiosperms show lower pollen/seed flow ratios than wind-pollinated (Squirrell et al., 2001). On the other hand, the pollen/seed flow ratio is low when calculated for plant species characterized by efficient seed dispersal mechanisms (e.g. Oddou-Muratorio et al., 2001). The pollen/seed flow ratio for P. sinense was low and lower than any reported from other plant species (Petit et al., 2005), suggesting that gene flow via pollen is not more efficient than via seed. Pollinators of P. sinense are mostly small insects whose flight distances are thought to be relatively short. Hence, for P. sinense, pollen-mediated gene flow is very limited. The low pollen/seed flow ratio for P. sinense could also be interpreted as being consistent with gene flow being predominantly by seed. Although seeds of P. sinense are primarily dispersed by gravity, a secondary dispersal mediated by wind, animals or water may occur. The natural germination ratio of seeds of P. sinense in the first year is quite low, mainly because of the hard seed capsule (Ye et al., unpublished data). We also speculate that there exists after-ripening and/or seed dormancy. Then it takes quite a long time for seeds to germinate because they fall from the maternal plant. Because seeds move to a final germination site during the secondary phase of dispersal, it may be relatively more important than primary dispersal in the patterns of plant distribution, especially when dispersed by animals and/or moving water (Johansson and Nilsson, 1993). However, most populations of P. sinense are separated by rivers or high mountains, and the complex land conditions of the TGR could have reduced seed flow among populations. Therefore, gene flow between sample populations tends to be restricted when the historical large continuous populations have been broken into small and isolated ones. 5.3. Conservation issues The genetic data obtained in the present study has important implications for conservation and management of the extant populations of P. sinense. The low level of intra-population diversity and high population differentiation were revealed within the extant populations of P. sinense. As most populations have been submerged due to the construction of the TGD, efficient in situ conservation measures should be taken to preserve the extant populations. Because substantial population differentiation was detected, all of the populations should be considered for protection to maintain the genetic diversity of this species. Moreover, because the habitat of P. sinense is restricted to a very small area in TGR, habitat loss or over-collecting by local farmers can cause crucial damage to population persistence of the species. Therefore, ex situ conservation and subsequent reestablishment of populations will be essential. Both microsatellites and current cpSSR markers provided convincing evidence of two ESUs within P. sinense. Thus, ex situ conservation measures should be taken to capture all haplotypes to maximize genomic representation of P. sinense. Considering its specific habitat, ex situ conservation site should be situated near natural populations of P. sinense. In addition, the uniformly positive FIS values across loci (Table S1) may be an indication of some population-level inbreeding. All remnant populations and the effect of inbreeding depression should be carefully monitored at all sites. Acknowledgments We thank Peter W. Fritsch and Ming Kang for insightful comments on the manuscript and Shusen Chen for his assistance in sample collections. This research was supported in part by National Sciences Foundation of China (30870241) and by the Key Project of the Chinese Academy of Sciences (KSCXZ-EW-J-20). Appendix A. Supplementary data Supplementary data related to this article can be found at http://dx.doi.org/10.1016/j.bse.2014.03.034. References Doyle, J.J., Doyle, J.L., 1987. A rapid DNA isolation procedure for small quantities of fresh leaf tissue. Phytochem. Bull. 19, 11e15. Ebert, D., Peakall, R., 2009. Chloroplast simple sequence repeats (cpSSRs): technical resources and recommendations for expanding cpSSR discovery and applications to a wide array of plant species. Mol. Ecol. Resour. 9, 673e690. Ennos, R.A., 1994. Estimating the relative rates of pollen and seed migration among plant populations. Heredity 72, 250e259. Excoffier, L., Smouse, P.E., 1994. Using allele frequencies and geographic subdivision to reconstruct gene trees within a species: molecular variance parsimony. Genetics 136, 343e359. Fineschi, S., Taurchini, D., Villani, F., Vendramin, G.G., 2000. Chloroplast DNA polymorphism reveals little geographical structure in Castanea sativa Mill. (Fagaceae) throughout southern European countries. Mol. Ecol. 9, 1495e1503. Frankham, R., Ballou, J.D., Briscue, D.A., 2002. Introduction to Conservation Genetics. Cambridge University Press, Cambridge. Goudet, J., 2001. FSTAT, A Program to Estimate and Test Gene Diversities and Fixation Indices (Version 2.9.3). Available from. http://www.unil.ch/izea/ softwares/fstat.html. Hamrick, J.L., Godt, M.J., 1989. Allozyme diversity in plant species. In: Brown, A., Clegg, M., Khaler, A., Weir, B. (Eds.), Plant Population Genetics, Breeding and Genetic Resources. Sinauer Press, Sunderland, MA.

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