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Population genetic structure of Sagittaria natans (Alismataceae), an endangered species in China, revealed by nuclear SSR loci analyses
Biochemical Systematics and Ecology 39 (2011) 412–418
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Biochemical Systematics and Ecology journal homepage: www.elsevier.com/locate/biochemsyseco
Population genetic structure of Sagittaria natans (Alismataceae), an endangered species in China, revealed by nuclear SSR loci analyses Xiaoli Yue a,1, Jinming Chen b, c,1, Youhao Guo a, Qingfeng Wang b, c, * a
Laboratory of Plant Systematics and Evolutionary Biology, College of Life Sciences, Wuhan University, Wuhan 430072, Hubei, PR China Key Laboratory of Aquatic Botany and Watershed Ecology, The Chinese Academy of Sciences, Wuhan 430074, Hubei, PR China c Wuhan Botanical Garden, The Chinese Academy of Sciences, Wuhan 430074, Hubei, PR China b
a r t i c l e i n f o
a b s t r a c t
Article history: Received 9 January 2011 Accepted 28 May 2011 Available online 24 June 2011
Sagittaria natans (Alismataceae) is an endangered aquatic herb in China. The nuclear microsatellite (SSR) loci variation of the 11 extant populations of S. natans was investigated in the present study. A relative high level of genetic diversity was found in this species. The Wilcoxon’s signed rank tests did not indicate a recent bottleneck in any of the populations. The Analysis of molecular variance (AMOVA) showed a low level of population differentiation (FST ¼ 0.284) among the populations of S. natans. This result was supported by STRUCTURE analysis (K ¼ 1), the NJ analyses and Mantel test (r ¼ 0.0221, p > 0.5). The genetic structure could be contributed to an earlier period of more pronounced gene flow when the species had a more continuous distribution. The results of this study could be used as the basis for conservation guidelines for the management of this endangered species in China. Ó 2011 Elsevier Ltd. All rights reserved.
Keywords: Aquatic herb Endangered Genetic diversity Microsatellite Sagittaria natans
1. Introduction Sagittaria natans Pall., a member of the aquatic family Alismataceae, is a float-leaved clonal plant species (Chen, 1989). The distribution range of S. natans is confined to bogs, rivers, and streams in Northeast Europe and Northeast Asia (Chen, 1989). In China, S. natans has been reported from Liaoning, Jilin, Heilongjiang, and Xinjiang provinces and also in Inner Mongolia (Chen, 1989). However, most S. natans populations in China have presently been extirpated largely due to increased human activity associated with the rise in human population and industrialization. Its distribution in China started to decrease during the latest thirty years, and populations continue to decline dramatically. Presently, it lives only in Jilin, Heilongjiang provinces and the Inner Mongolia. S. natans is now listed among the second category of the key protected wild plants of China (Yu, 1999). The genetic diversity of a species is often associated with population viability and the evolutionary potential (Reed and Frankham, 2003). Characterizing genetic diversity at the molecular level has been applied to S. natans to elucidate appropriate management unit. Based on inter-simple sequence repeat (ISSR) molecular markers, Chen et al. (2007) investigated the genetic diversity and population genetic structure of five populations of S. natans and found a relative higher levels of genetic variation resided within populations and lower level of genetic differentiations exist among populations. In our latest further investigations of S. natans populations in China, six populations that were not included in the previous genetic study (Chen et al., 2007) were found including three populations in Jilin province and three populations in Heilongjiang province. Each of the six newly discovered populations is occurring as small population and several populations were isolated from each other. What is the level of genetic diversity currently retained in these populations? And what is the pattern of the genetic structure * Corresponding author. Wuhan Botanical Garden, The Chinese Academy of Sciences, Wuhan 430074, Hubei, PR China. Tel./fax: þ86 27 87510526. E-mail address: [email protected] (Q.F. Wang). 1 These two authors contributed equally to this paper. 0305-1978/$ – see front matter Ó 2011 Elsevier Ltd. All rights reserved. doi:10.1016/j.bse.2011.05.022
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when the newly discovered populations were included in further genetic study. These questions still remain unanswered. In addition, due to the limited utility in inferring population genetic variability of ISSR markers, e.g., a dominant mode of inheritance and the occurrence of size homoplasy, with consequent co-migration of bands representing different alleles, our understanding of the genetic variability and heterozygosity in S. natans are still limited. Microsatellites are applied widely in conservation genetic studies of endangered species because of the typically high levels of variability detected, the co-dominant inheritance in a Mendelian fashion, reliable scoreability, coupled with applicability to rigorous statistical approaches (Beaumont and Bruford, 1999; Zhang and Hewitt, 2003). In the present study, we use microsatellite markers that developed by Yakimowski et al. (2009) for Sagittaria latifolia to investigate the level and distribution of the genetic variation in the extant S. natans populations in China. The results gained in this study could be used to inform the gene conservation and management program of this species in China. 2. Materials and methods 2.1. Plant materials A total of 269 individuals from 11 extant populations of S. natans, which representing all the populations discovered in recent years in China, were included in this study. The eleven populations were distributed in the three provinces of China, i.e., Jilin (AT-1, AT-2, DH-1 and DH-2), Heilongjiang (YL, XKH, SQ, QQHA, WSL and LHP), and Inner Mongolia (EKH) (Fig. 1). Among the 11 extant populations, six were the newly discovered populations in this study (AT-1, AT-2, QQHA, YL, XKH, and DH-2). Details on collection sites are given in Table 1. The distance between plants collected within an individual population was at least 1 m. About 5 g of fresh leaves per plant was collected from each plant and immediately dried with silica gel. Voucher specimens from all populations were deposited in the herbarium of Wuhan Botanical Garden (WBG). 2.2. DNA extraction and microsatellite genotyping Total genomic DNA was isolated from 0.5 g of silica-dried leaf tissue following the procedure described by Chen et al. (2007). Forward and reverse primers of eleven microsatellite loci described by Yakimowski et al. (2009) for S. latifolia were tested for PCR amplification. PCR reactions were performed in a reaction volume of 25 mL containing 0.25 mM of each dNTP, 2.5 mL of 10Taq buffer [10 mM Tris–HCl (pH 8.3), 1.5 mM MgCl2 and 50 mM KCl], 1 mM of each of the fluorescently
Fig. 1. Locations of 11 natural Sagittaria natans populations sampled from China. Population codes are the same as in Table 1.
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Table 1 Geological and voucher information relating to the studied Sagittaria natans populations and their genetic parameters revealed by nuclear microsatellite markers. Population AT-1 AT-2 EKH SQ DH-1 WSL LHP QQHA YL XKH DH-2 Mean a b c d e f g
Localities Antu, Jilin Antu, Jilin Erkahe, Inner Mongolia Siquan, Heilongjiang Dunhua, Jilin Wusuli, Heilongjiang Lianhuapao, Heilongjiang Qiqihaer, Heilongjiang Yilan, Heilongjiang Xingkaihu, Heilongjiang Dunhua, Jilin
Longitude/latitude
0
0
128 28 E/42 56 N 128 290 E/42 580 N 117 450 E/49 300 N 120 400 E/49 320 N 128 130 E/43 190 N 134 00’E/46 480 N 134 010 E/46 440 N 123 560 E/47 230 N 129 500 E/45 500 N 132 160 E/45 270 N 128 150 E/43 220 N
Na
Aab
ARc
Hod
Hee
FISf
Voucher no.
24 18 24 24 19 48 23 24 24 20 21
3.8 2.6 2.8 2.2 2.4 3.6 3.2 2.6 2.4 2.6 2.2 2.8
2.7 2.4 2. 1 1.9 2.0 2.5 2.6 2.3 2.0 2.1 1.9 2.2
0.383 0.578 0.275 0.292 0.368 0.375 0.374 0.417 0.300 0.370 0.333 0.370
0.407 0.412 0.307 0.284 0.264 0.420 0.386 0.364 0.272 0.340 0.280 0.340
0.059 0.420g 0.105 0.029 0.409 0.109 0.032 0.148 0.105 0.090 0.195 0.099
WH0901 WH0908 WH0604 WH0613 WH0618 WH0621 WH0625 WH0926 WH0913 WH0915 WH0920
Sample size. Average number of alleles per locus. Allele richness. Observed heterozygosity. Expected heterozygosity. Inbreeding coefficient and deviation from HWE tests. Significant at 0.01
labeled reverse and forward primer, 1 U Taq Polymerase (Tian Yuan Biotech) and 40 ng of DNA template. Primers were synthesized by Shanghai SBS Biotech Ltd., China. Amplification of genomic DNA was performed on a PTC-100Ô thermocycler (MJ Research, Waltham, MA, USA), and commenced with 3 min at 94 C, followed by 35 cycles of 30 s at 94 C, 30 s annealing at 52–54 C and 45 s extension at 72 C, and a final extension step of 7 min at 72 C. After amplification, the fragments of each microsatellite marker were separated using ABI 3730 automated sequencer in Beijing Genomics Institute, the Chinese Academy of Sciences and visualized using the GeneScan system (Applied Biosystems, USA). 2.3. Data analysis For each nuclear microsatellite locus, the total number of alleles detected (A), the observed heterozygosity (Ho), the unbiased expected heterozygosity (He), and the FST value (Weir and Cockerham, 1984) were calculated using the FSTAT program (Goudet, 2001). For each population, the average number of alleles per locus (Aa), the observed heterozygosity (Ho), the unbiased expected heterozygosity (He), and the inbreeding coefficient (FIS) were estimated using POPGENE (Yeh et al., 1999). The allelic richness (AR) for each population, which was calculated using a fixed sample size of 18 individuals, and the pairwise FST between each pair of populations were estimated using FSTAT program (Goudet, 2001). Gene flow (Nm) among populations was estimated using the expression Nm ¼ (1 FST)/4FST (Slatkin and Barton, 1989). The deviation from Hardy–Weinberg equilibrium (HWE) at each population was investigated using Weir and Cockerham (1984) inbreeding coefficient (FIS) calculated by GENPOPE 3.4 (Raymond and Rousset, 1995), with 1000 allelic permutations among individuals. Population structure was inferred using a Bayesian clustering approach, which implemented in the program STRUCTURE 2.3.2 (Pritchard et al., 2007). The approach was used to determine the optimal number of genetic clusters (K) in the datasets without prior information on the sampling locations, under the admixture model with the option of correlated allele frequencies between populations. A total of 10 independent runs (K ¼ 1–14) were performed with 105 Markov chain Monte Carlo (MCMC) repetitions after a burn-in period of 104 interactions. The optimal value of K was estimated by calculating DK values to identify the top level in the hierarchical structure, according to Evanno et al. (2005). The genetic variations were also evaluated by analysis of molecular variance (AMOVA, Excoffier et al., 1992) using ARLEQUIN ver. 2.001 (Schneider et al., 2000). Variance was apportioned to the following components: among individuals within population and among populations. The significance of differentiation between populations was tested by examining 1000 permutations. The BOTTLENECK program (Piry et al., 1999) was used to assess the possible impact of recent demographic changes on genetic diversity. Wilcoxon’s signed rank tests (Piry et al., 1999) under the infinite allele mutation model (IAM), the twophased model of mutation (TPM) and the stepwise mutation model (SMM) assumptions were employed. Under the TPM, 70% of the mutations were assumed to occur under the SMM and 30% assumed to occur under the IAM. For each mutational model, 10,000 replicates were performed. Mode shift away from an L-shaped distribution of allelic frequencies was also tested using BOTTLENECK (Piry et al., 1999). Nei’s genetic distance (DA, Nei et al., 1983) between each pair of populations was calculated using the POPULATIONS program (Langella, 2007). Neighbor-joining (NJ) tree based on the DA distance matrix for the genetic relationships between the 11 studied populations was performed using the POPULATIONS (Langella, 2007). To assess the confidence limits associated with the topology of the NJ tree, 1000 replicates of bootstrap analysis (Felsenstein, 1985) were performed.
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To test the significance of “isolation by distance” between populations, the Mantel test was performed using IBDWS ver. 3.1 (Bohonak, 2002). Matrices of genetic distances using FST/(1 FST) (Raymond and Rousset, 1995) and geographical distances (logarithm of the shortest geographical distance, km) were constructed for pairwise comparison and tests were based on 10,000 randomizations. 3. Results 3.1. Microsatellite variation and genetic diversity within populations For the eleven microsatellites identified for S. latifolia (Yakimowski et al., 2009), five produced reproducible, and scorable polymorphic primer pairs (SL09, SL21, SL31, SL65 and SL75) were used in this study (Table 2). The five microsatellite loci generated a total of 32 alleles across the 269 individuals from 11 populations analyzed. The total number of alleles (A) detected at each locus ranged from 3 at locus SL21 to 15 at locus SL75, with an average of 6.4 alleles per locus (Table 2). The observed heterozygosity (Ho) ranged from 0.086 to 0.770 (average over all loci was 0.366) and the unbiased expected heterozygosity (He) ranged from 0.097 to 0.778 (average over all loci was 0.471). The FST values ranged from 0.035 to 0.573 with a mean of 0.297 (Table 2). The intra-population genetic diversity measures are presented in Table 1. The mean number of alleles per locus varied from 2.2 to 3.8 (average 2.8). The Ho and He values ranged from 0.275 to 0.578 (average 0.370) and from 0.264 to 0.412 (average 0.340), respectively. The AR ranged from 1.9 to 2.7 (average 2.2). The FIS values obtained for the populations were negative in most of the cases (7/11) (FIS values ranged from 0.420 to 0.105, with an average of 0.099). One population (AT-2) showed significant deviation from HWE. The Wilcoxon sign-rank tests indicated that there had been no significant bottlenecks in any population under the IAM, SMM or TPM assumptions. No population displayed a shifted distribution of allelic frequencies. 3.2. Genetic differentiation between populations The AMOVA results showed that variation within populations accounted for most (71.6%) of the genetic variation. Variation among populations accounted for only 28.4% of the total genetic variation (Table 3). The global genetic differentiation across all populations estimated as FST was 0.284. The FST values for each pair of populations varied between 0.009 and 0.493 (Table 4). All the pairwise FST values were statistically significant with the exception of that between the WSL population and LHP populations. The inferred Nm values were ranged from 0.257 to 27.53 (data not show). In the STRUCTURE analysis, a value of K ¼ 1 resulted in the highest log-likelihood value. This result suggests that there were probably one original population, from which the 269 individuals in the current 11 populations were derived, and there were no strong differentiation existed among the current populations of S. natans. Nei et al. (1983) DA distances ranged from 0.022 to 0.482 (Table 4). The NJ tree based on the DA distance indicated that there was not clear geographical structure among populations: pairs of populations from geographically close locations not always clustered together (Fig. 2). A Mantel test also showed no significant correlation between genetic distance and geographic distance for the 11 populations of S. natans (r ¼ 0.0221, p > 0.5). 4. Discussion Microsatellite loci in S. latifolia have relatively high numbers of alleles (Yakimowski et al., 2009) making them useful for studying the genetic diversity among populations of S. natans. The genetic variations among populations (mean value of He ¼ 0.340) of S. natans revealed in this study were low in comparison to the general trend of high average microsatellite heterozygosity found in long-lived perennial species (mean He ¼ 0.68) or the species with narrow distribution (mean He ¼ 0.56) (reviewed in Nybom, 2004). However, as an aquatic clonal plant, S. natans is characterized by high levels of genetic diversity among populations (the He ranged from 0.264 to 0.412, with an average of 0.340) comparing the genetic diversity
Table 2 Characteristics of five nuclear microsatellite loci. Locus
Aa
Hob
Hec
FSTd
SL09 SL21 SL31 SL65 SL75 Mean
5 3 4 5 15 6.4
0.770 0.279 0.093 0.086 0.602 0.366
0.581 0.461 0.438 0.097 0.778 0.471
0.159 0.387 0.573 0.035 0.222 0.297
a b c d
Total number of detected alleles. Observed heterozygosity. Expected heterozygosity. Fixation index (Weir and Cockerham, 1984).
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Table 3 Analysis of molecular variance (AMOVA) for populations of Sagittaria natans based on nuclear microsatellite loci. Source of variation
d.f.a
SSDb
Variance component
Percentage of variation
Fixation index
Among populations Within populations Total
10 527 537
173.228 459.499 632.727
0.3398 0.8719 1.2117
28.4 71.6
FST ¼ 0.284
a b
Degree of freedom. Sum of squares.
values obtained in studies on several other aquatic plants using SSR markers, e.g., the He values among populations of Typha latifolia ranged from 0.18 to 0.31 with a mean value of 0.29 (Tsyusko et al., 2005); the He among populations of Posidonia aceanica ranged from 0.190 to 0.380 (Procaccini and Mazzella, 1998); The He averaged over all analyzed loci ranged from 0.324 to 0.607 per population for Zostera marina (Reusch et al., 2000). The level of within population genetic variations of the newly discovered populations (AT-1, AT-2, QQHA, YL, XKH, and DH-2; the He ranged from 0.272 to 0.412 with an average of 0.332) was similar to that of the previous found populations (EKH, SQ, DH-1, WSL, and LHP; the He ranged from 0.264 to 0.420 with an average of 0.346). As suggested by Chen et al. (2007) in their ISSR molecular markers based genetic diversity study, the outcrossing may have played an important role in generating the high levels of genetic diversity in S. natans. For S. natans, the species is an insect pollinated species, although it is self-compatible species and can reproduce selfed seeds, the characteristics of dichogamy of this species limited the selfing within the individual. The selfing between ramets of the same genet could happen within populations of the clonal species S. natans, however, the clonal orgasm of this species is corm and the dispersals of the corms are difficult because it commonly grows only near the roots in the substrate sludge. In this study, we sampled the individuals in a large distance and the genetic identified individuals produced by selfing between the ramets could be avoided. The inbreeding coefficient (FIS values) obtained for the populations were negative in most of the populations also suggesting outcrossing in S. natans populations was predominant. Several previous surveys of genetic variation in plants with narrow distribution or small population size tend to maintain low degree of genetic variability due to the impact of genetic drift, the founder effect, and directional selection with high levels of inbreeding (Franklin, 1980; Ellstrand and Elam, 1993; Hamrick and Godt, 1996). However, no significant bottlenecks in any population under the IAM, SMM or TPM assumptions were revealed in this study, suggesting that the S. natans populations might have not suffered heavy losses of genetic diversity from a recent habitat loss and/or a decline in population size. This confirmed the supposes of Chen et al. (2007) that erosion of genetic diversity in the species may, however, have not been readily discernible due to initial high levels of diversity in the species arising from frequent recombination, given the frequent sexual reproduction in the life history of this species. The clonal habit of this species may also have contributed to retention of genetic diversity in the remnant populations of S. natans by “fixing” some of the genetic variation (Chen et al., 2007). A low level of population differentiation (FST ¼ 0.284) among the populations of S. natans in China was observed in the AMOVA analysis. No strong differentiation existed among the current populations of S. natans was also indicated by STRUCTURE analysis. The STRUCTURE analysis assigned all the 269 individuals from the extant 11 populations into one cluster (K ¼ 1). The weak population genetic differentiation of S. natans was also supported by the NJ analyses and Mantel test. The NJ tree based on the DA distance indicated that there was not clear geographical structure among populations. A Mantel test also showed no significant correlation between genetic distance and geographic distance (r ¼ 0.0221, p > 0.5). These results were agreed with the previous findings on five populations of S. natans using ISSR molecular markers (Chen et al., 2007). The high intra-population genetic diversity and low inter-population genetic differentiation of S. natans may be due to gene flow among their populations. The inferred gene flow values between populations based on the FST values were shown to be high (Nm values ranged from 0.257 to 27.53). However, here we would not propose efficient ongoing gene flow between extant populations of S. natans, considering the fragmentation of its modern habitats; instead, we suggest that the considerably high gene flow might be indicative of an earlier period of more pronounced gene flow when the species had a more continuous distribution. Table 4 Nei’s DA distance (Nei et al., 1983) between populations (above the diagonal) and FST (Weir and Cockerham, 1984) between populations (below the diagonal). Population AT-1 AT-2 EKH SQ DH-1 WSL LHP QQHA YL XKH DH-2
AT-1 0.261 0.373 0.401 0.352 0.148 0.153 0.167 0.410 0.191 0.412
AT-2
EKH
SQ
DH-1
WSL
LHP
QQHA
YL
XKH
DH-2
0.151
0.188 0.1188
0.2418 0.2308 0.046
0.275 0.361 0.258 0.266
0.151 0.307 0.151 0.153 0.218
0.147 0.298 0.159 0.162 0.200 0.022
0.179 0.407 0.272 0.284 0.345 0.156 0.166
0.384 0.482 0.293 0.280 0.275 0.246 0.241 0.239
0.162 0.320 0.210 0.246 0.252 0.115 0.148 0.175 0.285
0.227 0.208 0.104 0.097 0.247 0.254 0.260 0.310 0.333 0.243
0.219 0.322 0.453 0.335 0.351 0.409 0.493 0.392 0.247
0.082 0.397 0.255 0.265 0.400 0.383 0.352 0.061
0.418 0.245 0.273 0.406 0.397 0.408 0.144
0.226 0.245 0.350 0.247 0.314 0.408
0.009 0.090 0.188 0.097 0.327
0.144 0.226 0.113 0.349
0.276 0.154 0.440
0.289 0.429
0.418
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417
DH-1 SQ EKH YL DH-2
81
WSL
AT-2
LHP
AT-1
XKH
QQHA
0.1 Fig. 2. Unrooted neighbor-joining tree of 11 sampled populations based on the Nei’s DA distance (Nei et al., 1983) using microsatellite data. Only bootstrap values 50% are presented. Population codes are the same as in Table 1.
In summary, the present-day S. natans populations still maintain high degree of intra-population genetic diversity and exhibit low levels of inter-population differentiation as evidenced by both the present microsatellite analysis and previous ISSR analysis (Chen et al., 2007). The results from both studies indicate that the S. natans populations might have not suffered heavy losses of genetic diversity from a recent habitat loss and/or a decline in population size. However, if it is continue to decline in numbers of individuals or populations for this endangered species, it is quite possible that the process of habitat isolation will lead to a loss of genetic diversity by dramatically increasing mating opportunities between relatives and intraclones within small populations. Appropriate conservation strategies are required for the long-time survival of this species. Protecting more habitats should be considered as prior since damage to the habitats is the prevalent causative factor for the decline in populations and number of individuals. Considering the current situation of rapid decline of populations and the endangered natural habitats of S. natans, we also recommend to carry out ex situ conservation of this species. Acknowledgments The authors thank Chun-Feng Yang, Fan Liu and Zhi-Yuan Du for their help in fieldwork, Yi-Ying Liao and Shu-Ying Zhao for their assistance in the laboratory. This study was supported by grants from One Hundred Person Project of the Chinese Academy of Sciences granted to WQF (KSCX2-YW-Z-0805) and from the National Natural Science Foundation of China (No. 30800061 and No. 30970195). References Beaumont, M.A., Bruford, M.W., 1999. Microsatellites in conservation genetics. In: Goldstein, D.B., Schlotterer, C. (Eds.), Microsatellites: Evolution and Applications. Oxford University Press, pp. 165–182. Bohonak, A.J., 2002. IBD (isolation by distance): a program for analyses of isolation by distance. J. Hered. 93, 153–154. Chen, J.K. (Ed.), 1989. Systematic and Evolutionary Biology Studies on Chinese Sagittaria. Wuhan University Press, Wuhan. Chen, J.M., Gituru, W.R., Wang, Q.F., 2007. A comparison of the extent of genetic variation in the endangered Sagittaria natans and its widespread congener S. trifolia. Aquat. Bot. 87, 1–6. Ellstrand, N.C., Elam, D.R.,1993. Population genetic consequences of small population size: implications for plant conservation. Ann. Rev. Ecol. Syst. 24, 217–242. 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. Excoffier, L., Smouse, P.E., Quattro, J.M., 1992. Analysis of molecular variance inferred from metric distances among DNA haplotypes: application to human mitochondrial DNA restriction data. Genetics 131, 479–491. Felsenstein, J., 1985. Confidence limits on phylogenies: an approach using the bootstrap. Evolution 39, 783–791. Franklin, I.R., 1980. Evolutionary changes in small populations. In: Soule, M.E., Wilcox, B.A. (Eds.), Conservation Biology. Sinauer, Sunderland, MA, pp. 135–149. Goudet, J., 2001. FSTAT, Ver 2.9.3, a Program to Estimate and Test Gene Diversities and Fixation Indices Available from. http://www.unil.ch/izea/softwares/ fstat.html. Hamrick, J.L., Godt, M.J.W., 1996. Effects of life history traits on genetic diversity in plant species. Philos. Trans. R Soc. Lond. B 351, 1291–1298. Langella, O., 2007. Populations (Version 1.2.30) Available from. http://bioinformatics.%20org/populations/.
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Biochemical Systematics and Ecology journal homepage: www.elsevier.com/locate/biochemsyseco
Population genetic structure of Sagittaria natans (Alismataceae), an endangered species in China, revealed by nuclear SSR loci analyses Xiaoli Yue a,1, Jinming Chen b, c,1, Youhao Guo a, Qingfeng Wang b, c, * a
Laboratory of Plant Systematics and Evolutionary Biology, College of Life Sciences, Wuhan University, Wuhan 430072, Hubei, PR China Key Laboratory of Aquatic Botany and Watershed Ecology, The Chinese Academy of Sciences, Wuhan 430074, Hubei, PR China c Wuhan Botanical Garden, The Chinese Academy of Sciences, Wuhan 430074, Hubei, PR China b
a r t i c l e i n f o
a b s t r a c t
Article history: Received 9 January 2011 Accepted 28 May 2011 Available online 24 June 2011
Sagittaria natans (Alismataceae) is an endangered aquatic herb in China. The nuclear microsatellite (SSR) loci variation of the 11 extant populations of S. natans was investigated in the present study. A relative high level of genetic diversity was found in this species. The Wilcoxon’s signed rank tests did not indicate a recent bottleneck in any of the populations. The Analysis of molecular variance (AMOVA) showed a low level of population differentiation (FST ¼ 0.284) among the populations of S. natans. This result was supported by STRUCTURE analysis (K ¼ 1), the NJ analyses and Mantel test (r ¼ 0.0221, p > 0.5). The genetic structure could be contributed to an earlier period of more pronounced gene flow when the species had a more continuous distribution. The results of this study could be used as the basis for conservation guidelines for the management of this endangered species in China. Ó 2011 Elsevier Ltd. All rights reserved.
Keywords: Aquatic herb Endangered Genetic diversity Microsatellite Sagittaria natans
1. Introduction Sagittaria natans Pall., a member of the aquatic family Alismataceae, is a float-leaved clonal plant species (Chen, 1989). The distribution range of S. natans is confined to bogs, rivers, and streams in Northeast Europe and Northeast Asia (Chen, 1989). In China, S. natans has been reported from Liaoning, Jilin, Heilongjiang, and Xinjiang provinces and also in Inner Mongolia (Chen, 1989). However, most S. natans populations in China have presently been extirpated largely due to increased human activity associated with the rise in human population and industrialization. Its distribution in China started to decrease during the latest thirty years, and populations continue to decline dramatically. Presently, it lives only in Jilin, Heilongjiang provinces and the Inner Mongolia. S. natans is now listed among the second category of the key protected wild plants of China (Yu, 1999). The genetic diversity of a species is often associated with population viability and the evolutionary potential (Reed and Frankham, 2003). Characterizing genetic diversity at the molecular level has been applied to S. natans to elucidate appropriate management unit. Based on inter-simple sequence repeat (ISSR) molecular markers, Chen et al. (2007) investigated the genetic diversity and population genetic structure of five populations of S. natans and found a relative higher levels of genetic variation resided within populations and lower level of genetic differentiations exist among populations. In our latest further investigations of S. natans populations in China, six populations that were not included in the previous genetic study (Chen et al., 2007) were found including three populations in Jilin province and three populations in Heilongjiang province. Each of the six newly discovered populations is occurring as small population and several populations were isolated from each other. What is the level of genetic diversity currently retained in these populations? And what is the pattern of the genetic structure * Corresponding author. Wuhan Botanical Garden, The Chinese Academy of Sciences, Wuhan 430074, Hubei, PR China. Tel./fax: þ86 27 87510526. E-mail address: [email protected] (Q.F. Wang). 1 These two authors contributed equally to this paper. 0305-1978/$ – see front matter Ó 2011 Elsevier Ltd. All rights reserved. doi:10.1016/j.bse.2011.05.022
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when the newly discovered populations were included in further genetic study. These questions still remain unanswered. In addition, due to the limited utility in inferring population genetic variability of ISSR markers, e.g., a dominant mode of inheritance and the occurrence of size homoplasy, with consequent co-migration of bands representing different alleles, our understanding of the genetic variability and heterozygosity in S. natans are still limited. Microsatellites are applied widely in conservation genetic studies of endangered species because of the typically high levels of variability detected, the co-dominant inheritance in a Mendelian fashion, reliable scoreability, coupled with applicability to rigorous statistical approaches (Beaumont and Bruford, 1999; Zhang and Hewitt, 2003). In the present study, we use microsatellite markers that developed by Yakimowski et al. (2009) for Sagittaria latifolia to investigate the level and distribution of the genetic variation in the extant S. natans populations in China. The results gained in this study could be used to inform the gene conservation and management program of this species in China. 2. Materials and methods 2.1. Plant materials A total of 269 individuals from 11 extant populations of S. natans, which representing all the populations discovered in recent years in China, were included in this study. The eleven populations were distributed in the three provinces of China, i.e., Jilin (AT-1, AT-2, DH-1 and DH-2), Heilongjiang (YL, XKH, SQ, QQHA, WSL and LHP), and Inner Mongolia (EKH) (Fig. 1). Among the 11 extant populations, six were the newly discovered populations in this study (AT-1, AT-2, QQHA, YL, XKH, and DH-2). Details on collection sites are given in Table 1. The distance between plants collected within an individual population was at least 1 m. About 5 g of fresh leaves per plant was collected from each plant and immediately dried with silica gel. Voucher specimens from all populations were deposited in the herbarium of Wuhan Botanical Garden (WBG). 2.2. DNA extraction and microsatellite genotyping Total genomic DNA was isolated from 0.5 g of silica-dried leaf tissue following the procedure described by Chen et al. (2007). Forward and reverse primers of eleven microsatellite loci described by Yakimowski et al. (2009) for S. latifolia were tested for PCR amplification. PCR reactions were performed in a reaction volume of 25 mL containing 0.25 mM of each dNTP, 2.5 mL of 10Taq buffer [10 mM Tris–HCl (pH 8.3), 1.5 mM MgCl2 and 50 mM KCl], 1 mM of each of the fluorescently
Fig. 1. Locations of 11 natural Sagittaria natans populations sampled from China. Population codes are the same as in Table 1.
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Table 1 Geological and voucher information relating to the studied Sagittaria natans populations and their genetic parameters revealed by nuclear microsatellite markers. Population AT-1 AT-2 EKH SQ DH-1 WSL LHP QQHA YL XKH DH-2 Mean a b c d e f g
Localities Antu, Jilin Antu, Jilin Erkahe, Inner Mongolia Siquan, Heilongjiang Dunhua, Jilin Wusuli, Heilongjiang Lianhuapao, Heilongjiang Qiqihaer, Heilongjiang Yilan, Heilongjiang Xingkaihu, Heilongjiang Dunhua, Jilin
Longitude/latitude
0
0
128 28 E/42 56 N 128 290 E/42 580 N 117 450 E/49 300 N 120 400 E/49 320 N 128 130 E/43 190 N 134 00’E/46 480 N 134 010 E/46 440 N 123 560 E/47 230 N 129 500 E/45 500 N 132 160 E/45 270 N 128 150 E/43 220 N
Na
Aab
ARc
Hod
Hee
FISf
Voucher no.
24 18 24 24 19 48 23 24 24 20 21
3.8 2.6 2.8 2.2 2.4 3.6 3.2 2.6 2.4 2.6 2.2 2.8
2.7 2.4 2. 1 1.9 2.0 2.5 2.6 2.3 2.0 2.1 1.9 2.2
0.383 0.578 0.275 0.292 0.368 0.375 0.374 0.417 0.300 0.370 0.333 0.370
0.407 0.412 0.307 0.284 0.264 0.420 0.386 0.364 0.272 0.340 0.280 0.340
0.059 0.420g 0.105 0.029 0.409 0.109 0.032 0.148 0.105 0.090 0.195 0.099
WH0901 WH0908 WH0604 WH0613 WH0618 WH0621 WH0625 WH0926 WH0913 WH0915 WH0920
Sample size. Average number of alleles per locus. Allele richness. Observed heterozygosity. Expected heterozygosity. Inbreeding coefficient and deviation from HWE tests. Significant at 0.01
labeled reverse and forward primer, 1 U Taq Polymerase (Tian Yuan Biotech) and 40 ng of DNA template. Primers were synthesized by Shanghai SBS Biotech Ltd., China. Amplification of genomic DNA was performed on a PTC-100Ô thermocycler (MJ Research, Waltham, MA, USA), and commenced with 3 min at 94 C, followed by 35 cycles of 30 s at 94 C, 30 s annealing at 52–54 C and 45 s extension at 72 C, and a final extension step of 7 min at 72 C. After amplification, the fragments of each microsatellite marker were separated using ABI 3730 automated sequencer in Beijing Genomics Institute, the Chinese Academy of Sciences and visualized using the GeneScan system (Applied Biosystems, USA). 2.3. Data analysis For each nuclear microsatellite locus, the total number of alleles detected (A), the observed heterozygosity (Ho), the unbiased expected heterozygosity (He), and the FST value (Weir and Cockerham, 1984) were calculated using the FSTAT program (Goudet, 2001). For each population, the average number of alleles per locus (Aa), the observed heterozygosity (Ho), the unbiased expected heterozygosity (He), and the inbreeding coefficient (FIS) were estimated using POPGENE (Yeh et al., 1999). The allelic richness (AR) for each population, which was calculated using a fixed sample size of 18 individuals, and the pairwise FST between each pair of populations were estimated using FSTAT program (Goudet, 2001). Gene flow (Nm) among populations was estimated using the expression Nm ¼ (1 FST)/4FST (Slatkin and Barton, 1989). The deviation from Hardy–Weinberg equilibrium (HWE) at each population was investigated using Weir and Cockerham (1984) inbreeding coefficient (FIS) calculated by GENPOPE 3.4 (Raymond and Rousset, 1995), with 1000 allelic permutations among individuals. Population structure was inferred using a Bayesian clustering approach, which implemented in the program STRUCTURE 2.3.2 (Pritchard et al., 2007). The approach was used to determine the optimal number of genetic clusters (K) in the datasets without prior information on the sampling locations, under the admixture model with the option of correlated allele frequencies between populations. A total of 10 independent runs (K ¼ 1–14) were performed with 105 Markov chain Monte Carlo (MCMC) repetitions after a burn-in period of 104 interactions. The optimal value of K was estimated by calculating DK values to identify the top level in the hierarchical structure, according to Evanno et al. (2005). The genetic variations were also evaluated by analysis of molecular variance (AMOVA, Excoffier et al., 1992) using ARLEQUIN ver. 2.001 (Schneider et al., 2000). Variance was apportioned to the following components: among individuals within population and among populations. The significance of differentiation between populations was tested by examining 1000 permutations. The BOTTLENECK program (Piry et al., 1999) was used to assess the possible impact of recent demographic changes on genetic diversity. Wilcoxon’s signed rank tests (Piry et al., 1999) under the infinite allele mutation model (IAM), the twophased model of mutation (TPM) and the stepwise mutation model (SMM) assumptions were employed. Under the TPM, 70% of the mutations were assumed to occur under the SMM and 30% assumed to occur under the IAM. For each mutational model, 10,000 replicates were performed. Mode shift away from an L-shaped distribution of allelic frequencies was also tested using BOTTLENECK (Piry et al., 1999). Nei’s genetic distance (DA, Nei et al., 1983) between each pair of populations was calculated using the POPULATIONS program (Langella, 2007). Neighbor-joining (NJ) tree based on the DA distance matrix for the genetic relationships between the 11 studied populations was performed using the POPULATIONS (Langella, 2007). To assess the confidence limits associated with the topology of the NJ tree, 1000 replicates of bootstrap analysis (Felsenstein, 1985) were performed.
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To test the significance of “isolation by distance” between populations, the Mantel test was performed using IBDWS ver. 3.1 (Bohonak, 2002). Matrices of genetic distances using FST/(1 FST) (Raymond and Rousset, 1995) and geographical distances (logarithm of the shortest geographical distance, km) were constructed for pairwise comparison and tests were based on 10,000 randomizations. 3. Results 3.1. Microsatellite variation and genetic diversity within populations For the eleven microsatellites identified for S. latifolia (Yakimowski et al., 2009), five produced reproducible, and scorable polymorphic primer pairs (SL09, SL21, SL31, SL65 and SL75) were used in this study (Table 2). The five microsatellite loci generated a total of 32 alleles across the 269 individuals from 11 populations analyzed. The total number of alleles (A) detected at each locus ranged from 3 at locus SL21 to 15 at locus SL75, with an average of 6.4 alleles per locus (Table 2). The observed heterozygosity (Ho) ranged from 0.086 to 0.770 (average over all loci was 0.366) and the unbiased expected heterozygosity (He) ranged from 0.097 to 0.778 (average over all loci was 0.471). The FST values ranged from 0.035 to 0.573 with a mean of 0.297 (Table 2). The intra-population genetic diversity measures are presented in Table 1. The mean number of alleles per locus varied from 2.2 to 3.8 (average 2.8). The Ho and He values ranged from 0.275 to 0.578 (average 0.370) and from 0.264 to 0.412 (average 0.340), respectively. The AR ranged from 1.9 to 2.7 (average 2.2). The FIS values obtained for the populations were negative in most of the cases (7/11) (FIS values ranged from 0.420 to 0.105, with an average of 0.099). One population (AT-2) showed significant deviation from HWE. The Wilcoxon sign-rank tests indicated that there had been no significant bottlenecks in any population under the IAM, SMM or TPM assumptions. No population displayed a shifted distribution of allelic frequencies. 3.2. Genetic differentiation between populations The AMOVA results showed that variation within populations accounted for most (71.6%) of the genetic variation. Variation among populations accounted for only 28.4% of the total genetic variation (Table 3). The global genetic differentiation across all populations estimated as FST was 0.284. The FST values for each pair of populations varied between 0.009 and 0.493 (Table 4). All the pairwise FST values were statistically significant with the exception of that between the WSL population and LHP populations. The inferred Nm values were ranged from 0.257 to 27.53 (data not show). In the STRUCTURE analysis, a value of K ¼ 1 resulted in the highest log-likelihood value. This result suggests that there were probably one original population, from which the 269 individuals in the current 11 populations were derived, and there were no strong differentiation existed among the current populations of S. natans. Nei et al. (1983) DA distances ranged from 0.022 to 0.482 (Table 4). The NJ tree based on the DA distance indicated that there was not clear geographical structure among populations: pairs of populations from geographically close locations not always clustered together (Fig. 2). A Mantel test also showed no significant correlation between genetic distance and geographic distance for the 11 populations of S. natans (r ¼ 0.0221, p > 0.5). 4. Discussion Microsatellite loci in S. latifolia have relatively high numbers of alleles (Yakimowski et al., 2009) making them useful for studying the genetic diversity among populations of S. natans. The genetic variations among populations (mean value of He ¼ 0.340) of S. natans revealed in this study were low in comparison to the general trend of high average microsatellite heterozygosity found in long-lived perennial species (mean He ¼ 0.68) or the species with narrow distribution (mean He ¼ 0.56) (reviewed in Nybom, 2004). However, as an aquatic clonal plant, S. natans is characterized by high levels of genetic diversity among populations (the He ranged from 0.264 to 0.412, with an average of 0.340) comparing the genetic diversity
Table 2 Characteristics of five nuclear microsatellite loci. Locus
Aa
Hob
Hec
FSTd
SL09 SL21 SL31 SL65 SL75 Mean
5 3 4 5 15 6.4
0.770 0.279 0.093 0.086 0.602 0.366
0.581 0.461 0.438 0.097 0.778 0.471
0.159 0.387 0.573 0.035 0.222 0.297
a b c d
Total number of detected alleles. Observed heterozygosity. Expected heterozygosity. Fixation index (Weir and Cockerham, 1984).
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Table 3 Analysis of molecular variance (AMOVA) for populations of Sagittaria natans based on nuclear microsatellite loci. Source of variation
d.f.a
SSDb
Variance component
Percentage of variation
Fixation index
Among populations Within populations Total
10 527 537
173.228 459.499 632.727
0.3398 0.8719 1.2117
28.4 71.6
FST ¼ 0.284
a b
Degree of freedom. Sum of squares.
values obtained in studies on several other aquatic plants using SSR markers, e.g., the He values among populations of Typha latifolia ranged from 0.18 to 0.31 with a mean value of 0.29 (Tsyusko et al., 2005); the He among populations of Posidonia aceanica ranged from 0.190 to 0.380 (Procaccini and Mazzella, 1998); The He averaged over all analyzed loci ranged from 0.324 to 0.607 per population for Zostera marina (Reusch et al., 2000). The level of within population genetic variations of the newly discovered populations (AT-1, AT-2, QQHA, YL, XKH, and DH-2; the He ranged from 0.272 to 0.412 with an average of 0.332) was similar to that of the previous found populations (EKH, SQ, DH-1, WSL, and LHP; the He ranged from 0.264 to 0.420 with an average of 0.346). As suggested by Chen et al. (2007) in their ISSR molecular markers based genetic diversity study, the outcrossing may have played an important role in generating the high levels of genetic diversity in S. natans. For S. natans, the species is an insect pollinated species, although it is self-compatible species and can reproduce selfed seeds, the characteristics of dichogamy of this species limited the selfing within the individual. The selfing between ramets of the same genet could happen within populations of the clonal species S. natans, however, the clonal orgasm of this species is corm and the dispersals of the corms are difficult because it commonly grows only near the roots in the substrate sludge. In this study, we sampled the individuals in a large distance and the genetic identified individuals produced by selfing between the ramets could be avoided. The inbreeding coefficient (FIS values) obtained for the populations were negative in most of the populations also suggesting outcrossing in S. natans populations was predominant. Several previous surveys of genetic variation in plants with narrow distribution or small population size tend to maintain low degree of genetic variability due to the impact of genetic drift, the founder effect, and directional selection with high levels of inbreeding (Franklin, 1980; Ellstrand and Elam, 1993; Hamrick and Godt, 1996). However, no significant bottlenecks in any population under the IAM, SMM or TPM assumptions were revealed in this study, suggesting that the S. natans populations might have not suffered heavy losses of genetic diversity from a recent habitat loss and/or a decline in population size. This confirmed the supposes of Chen et al. (2007) that erosion of genetic diversity in the species may, however, have not been readily discernible due to initial high levels of diversity in the species arising from frequent recombination, given the frequent sexual reproduction in the life history of this species. The clonal habit of this species may also have contributed to retention of genetic diversity in the remnant populations of S. natans by “fixing” some of the genetic variation (Chen et al., 2007). A low level of population differentiation (FST ¼ 0.284) among the populations of S. natans in China was observed in the AMOVA analysis. No strong differentiation existed among the current populations of S. natans was also indicated by STRUCTURE analysis. The STRUCTURE analysis assigned all the 269 individuals from the extant 11 populations into one cluster (K ¼ 1). The weak population genetic differentiation of S. natans was also supported by the NJ analyses and Mantel test. The NJ tree based on the DA distance indicated that there was not clear geographical structure among populations. A Mantel test also showed no significant correlation between genetic distance and geographic distance (r ¼ 0.0221, p > 0.5). These results were agreed with the previous findings on five populations of S. natans using ISSR molecular markers (Chen et al., 2007). The high intra-population genetic diversity and low inter-population genetic differentiation of S. natans may be due to gene flow among their populations. The inferred gene flow values between populations based on the FST values were shown to be high (Nm values ranged from 0.257 to 27.53). However, here we would not propose efficient ongoing gene flow between extant populations of S. natans, considering the fragmentation of its modern habitats; instead, we suggest that the considerably high gene flow might be indicative of an earlier period of more pronounced gene flow when the species had a more continuous distribution. Table 4 Nei’s DA distance (Nei et al., 1983) between populations (above the diagonal) and FST (Weir and Cockerham, 1984) between populations (below the diagonal). Population AT-1 AT-2 EKH SQ DH-1 WSL LHP QQHA YL XKH DH-2
AT-1 0.261 0.373 0.401 0.352 0.148 0.153 0.167 0.410 0.191 0.412
AT-2
EKH
SQ
DH-1
WSL
LHP
QQHA
YL
XKH
DH-2
0.151
0.188 0.1188
0.2418 0.2308 0.046
0.275 0.361 0.258 0.266
0.151 0.307 0.151 0.153 0.218
0.147 0.298 0.159 0.162 0.200 0.022
0.179 0.407 0.272 0.284 0.345 0.156 0.166
0.384 0.482 0.293 0.280 0.275 0.246 0.241 0.239
0.162 0.320 0.210 0.246 0.252 0.115 0.148 0.175 0.285
0.227 0.208 0.104 0.097 0.247 0.254 0.260 0.310 0.333 0.243
0.219 0.322 0.453 0.335 0.351 0.409 0.493 0.392 0.247
0.082 0.397 0.255 0.265 0.400 0.383 0.352 0.061
0.418 0.245 0.273 0.406 0.397 0.408 0.144
0.226 0.245 0.350 0.247 0.314 0.408
0.009 0.090 0.188 0.097 0.327
0.144 0.226 0.113 0.349
0.276 0.154 0.440
0.289 0.429
0.418
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417
DH-1 SQ EKH YL DH-2
81
WSL
AT-2
LHP
AT-1
XKH
QQHA
0.1 Fig. 2. Unrooted neighbor-joining tree of 11 sampled populations based on the Nei’s DA distance (Nei et al., 1983) using microsatellite data. Only bootstrap values 50% are presented. Population codes are the same as in Table 1.
In summary, the present-day S. natans populations still maintain high degree of intra-population genetic diversity and exhibit low levels of inter-population differentiation as evidenced by both the present microsatellite analysis and previous ISSR analysis (Chen et al., 2007). The results from both studies indicate that the S. natans populations might have not suffered heavy losses of genetic diversity from a recent habitat loss and/or a decline in population size. However, if it is continue to decline in numbers of individuals or populations for this endangered species, it is quite possible that the process of habitat isolation will lead to a loss of genetic diversity by dramatically increasing mating opportunities between relatives and intraclones within small populations. Appropriate conservation strategies are required for the long-time survival of this species. Protecting more habitats should be considered as prior since damage to the habitats is the prevalent causative factor for the decline in populations and number of individuals. Considering the current situation of rapid decline of populations and the endangered natural habitats of S. natans, we also recommend to carry out ex situ conservation of this species. Acknowledgments The authors thank Chun-Feng Yang, Fan Liu and Zhi-Yuan Du for their help in fieldwork, Yi-Ying Liao and Shu-Ying Zhao for their assistance in the laboratory. This study was supported by grants from One Hundred Person Project of the Chinese Academy of Sciences granted to WQF (KSCX2-YW-Z-0805) and from the National Natural Science Foundation of China (No. 30800061 and No. 30970195). References Beaumont, M.A., Bruford, M.W., 1999. Microsatellites in conservation genetics. In: Goldstein, D.B., Schlotterer, C. (Eds.), Microsatellites: Evolution and Applications. Oxford University Press, pp. 165–182. Bohonak, A.J., 2002. IBD (isolation by distance): a program for analyses of isolation by distance. J. Hered. 93, 153–154. Chen, J.K. (Ed.), 1989. Systematic and Evolutionary Biology Studies on Chinese Sagittaria. Wuhan University Press, Wuhan. Chen, J.M., Gituru, W.R., Wang, Q.F., 2007. A comparison of the extent of genetic variation in the endangered Sagittaria natans and its widespread congener S. trifolia. Aquat. Bot. 87, 1–6. Ellstrand, N.C., Elam, D.R.,1993. Population genetic consequences of small population size: implications for plant conservation. Ann. Rev. Ecol. Syst. 24, 217–242. 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. Excoffier, L., Smouse, P.E., Quattro, J.M., 1992. Analysis of molecular variance inferred from metric distances among DNA haplotypes: application to human mitochondrial DNA restriction data. Genetics 131, 479–491. Felsenstein, J., 1985. Confidence limits on phylogenies: an approach using the bootstrap. Evolution 39, 783–791. Franklin, I.R., 1980. Evolutionary changes in small populations. In: Soule, M.E., Wilcox, B.A. (Eds.), Conservation Biology. Sinauer, Sunderland, MA, pp. 135–149. Goudet, J., 2001. FSTAT, Ver 2.9.3, a Program to Estimate and Test Gene Diversities and Fixation Indices Available from. http://www.unil.ch/izea/softwares/ fstat.html. Hamrick, J.L., Godt, M.J.W., 1996. Effects of life history traits on genetic diversity in plant species. Philos. Trans. R Soc. Lond. B 351, 1291–1298. Langella, O., 2007. Populations (Version 1.2.30) Available from. http://bioinformatics.%20org/populations/.
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