Genetic diversity and population structure of the endangered endemic species Paeonia decomposita from China and implications for its conservation

Paeonia decomposita, endemic to China, has important ornamental, medicinal and economic value and is regarded as a threatened endangered plant. The genetic diversity and structure have seldom been described. A conservation management plan is not currently available. In present study, 16 pairs of SSR primers were used to evaluate genetic diversity and population structure. A total of 122 alleles were obtained with a mean of 7.625 alleles per locus. The expected heterozygosity (He) varied from 0.043 to 0.901 (mean 0.492). Moderate genetic diversity (He=0.405) among populations were revealed, with Danba identified as the center of genetic diversity. Mantel tests revealed a significant positive correlation between geographic and genetic distance among populations (r=0.592, P=0.0001), demonstrating consistency with the isolation by distance model. Analysis of molecular variance (AMOVA) results indicated that the principal genetic variation existed within populations (73.48%) rather than among populations (26.52%). Bayesian structure analysis and principal coordinate analysis (PCoA) supported classification of the populations into three clusters. Based on the level of observed genetic diversity, three management unints were proposed as conservation measures. The results will be beneficial for the conservation and exploitation of the species, providing a theoretical basis for further research on its evolution and phylogeography. Hightlights Genetic diversity among populations was moderate in Paeonia decomposita There is significant positive correlation between geographic and genetic distance among populations, consistent with the isolation by distance model Principal genetic variation existed within populations rather than among populations. The populations divided into three clusters. Three management unints were proposed as conservation measures.

deviation between microsatellites was tested using GenAlEx 6.5. A Mantel test was 1 3 9 conducted to check correlations between matrices of genetic distances (GD) and geographic 1 4 0 distances using GenAlEx 6.5. Population genetic structure was analyzed using a Bayesian 1 4 1 clustering analysis method conducted in Structure 2.3.4 software (Pritchard et al., 2000). A 1 4 2 total of ten independent runs (K=2-10) were performed with a run length of 1 × 10 5 Markov (PCoA) was used with GenAlEx 6.5 to evaluate the genetic relationships between demonstrated that 81.7% of the total molecular variation was due to differences within (all P<0.001). When total variation was grouped into three hierarchical components, <0.001) and 16% (P <0.001) of total genetic variation resulted from genetic differentiation 2 2 3 among regions and among populations within regions, respectively (Table 7). Therefore, 2 2 4 significant differences in genetic differentiation existed among the 11 populations (Table 7). The MCMC algorithm of reconstruction of SSR markers is displayed in Fig. 2 between populations revealed a genetic structure that is presented in Fig. 4 axis 2 -16.95% and axis 3 -9.00%). All populations were represented by the three groups. indicated that the 11 populations could be divided into two major clades: 1 and 2 (Fig. 5).

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Clade 1 included two populations, namely DB1 and DB2, with clade 2 consisting of the 2 4 8 remaining 9 populations, which were further divided into two small branches: five other, for example, JC1/JC2 and M2/M3 were closely related and clustered together because 2 5 3 they were closest in terms of genetic distance. In recent years, an increasing number of researchers have realized that it is important to 2 5 6 maintain the genetic diversity of natural populations to ensure the continuing survival, fitness and potential for evolution of a species (Frankham et al., 2002). Traditionally, analysis of investigating population structure. In general, higher genetic diversity existed within populations with less genetic Godt , 1996). In this study, the 16 SSR primers demonstrated a higher genetic diversity level 2 9 0 (He=0.492) and lower genetic differentiation (Fst=0.193) than those in the ISSR study  life-history traits or geographic traits of a species (Nybom, 2004). In general, less genetic 2 9 5 diversity exists in an endemic species that is not widely distributed compared with that 2 9 6 found in a widespread species (Hamrick and Godt, 1996;Huh and Huh, 1999), usually because their population numbers are limited, and as they are isolated from other 2 9 8 populations they adapt to their particular habitat (Barrett and Kohn, 1991).

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Our study demonstrated that the genetic diversity level of P. decomposita was moderate Levels of genetic diversity in P. decomposita (He = 0.405) were lower than both 3 1 0 "endemic" species (He=0.420) and "widespread" species (He=0.620) (Nybom, 2004). This between populations. In this study, genetic diversity (I, Ho, He, PIC) at a population level self-compatibility system of this species (Table 3).
The results strengthened the assumption that endangered plants with a narrow distribution 3 3 1 are generally aplastic. A reduction in genetic variation might suggest a decline in adaptation 3 3 2 to a changing environment, leading to increased danger of extinction and increased 3 3 3 inbreeding (Tansley and Brown, 2000;Frankham et al., 2002;Frankham et al., 2010). flow and the genetic differentiation coefficient are negatively correlated (Grant, 1986).
Gene flow is a basic micro-evolutionary phenomenon that destroys genetic differentiation Though diversity has mostly occurred within populations, the majority of genetic  The Fst value observed among the 11 populations might result from isolation of the 3 5 7 populations, geographic distance and environmental adaptation. The AMOVA results (P<0.001) also support population differentiation. AMOVA The genetic differentiation level observed in the present study was lower than that to differences in population numbers studied, or molecular markers investigated. Increasing numbers of methods are being used to detect genetic diversity and population combination of PCoA, Structure and UPGMA analysis is able to produce reliable results. produce plans for breeding. Therefore, this method was regarded as the most suitable to 3 7 8 categorize populations.

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There was a clear genetic structure among the P. decomposita populations, and the In the present study, UPGMA cluster analysis grouped 11 populations collected from 3 8 4 three different regions into two clades (Fig. 5), demonstrating that there were two distinct were three distinct clusters. This suggests that analyses by Structure software were reliable.

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Furthermore, the PCoA results were identical to those from Structure and inconsistent with 3 9 0 1 6 the UPGMA clustered tree.

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In addition, the genetic relationships among populations reflected those populations' 3 9 2 natural geographical locations which were supported by an IBD (isolation-by-distance) 3 9 3 model constructed using a Mantel test. This IBD model for P. decomposita indicated a 3 9 4 significantly positive correlation (r=0.592, P<0.001) between geographic distance and 3 9 5 genetic distance between populations. The closer the populations were geographically, the 3 9 6 lower the genetic differentiation. Thus, the genetic differentiation among populations 3 9 7 increased as distance among populations increased, and so Mantel test analysis suggested 3 9 8 that the genetic clusters were significantly related to the populations' geographic origins. The Genetic distance is highly significant in every population relationship study. In general, It is essential to understand the genetic diversity of a population, its structure and gene germplasm must be optimal in terms of genetic variation, with low levels of inbreeding that 4 1 0 restrains the growth of a population.

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The management of collections and conservation of genetic resource must guarantee that diversity is not lost due to genetic drift (Namkoong, 1988). In the case of P. decomposita, 4 1 6 conservation must consider not only geographic distance between populations, but also the pool, which could embrace the uniqueness and diversity that exists in all populations.

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Genetic diversity is especially important in a species in order to preserve the latent suggest that three natural distribution areas should correspond to three management units. In and populations in situ for the sake of preserving genetic variation as far as possible.

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Traditional methods of protection that primarily concentrate on in situ conservation, such as previous research has demonstrated that heterozygosity is the best way to ensure a 4 4 6 populations' fitness and potential for adaptation (Reed and Frankham, 2003). However, The populations are facing problems of habitat destruction, loss or fragmentation as a Genetic information from this detailed study has provided first-hand data of the genetic beneficial for developing measures to conserve and manage endangered and endemic plants. into three groups by PCA cluster analysis, which should possibly be considered as three over those with genetic diversity and differentiation. This is the first time that the genetic 4 8 0 1 9 diversity of P. decomposita has been studied using SSR, the results representing a reference 4 8 1 for improving the germplasm and parental selection for breeding strategy plans.

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In this study, the markers used allowed investigation of population structure, genetic 4 8 3 diversity and proposed germplasm collection and a conservation strategy for P. decomposita. Important information about genetic structure was provided by these markers, through SSR analysis will be helpful for crop breeding, germplasm management and 4 8 8 conservation. To conclude, these results provide value as an important resource to study 4 8 9 genetic diversity and assist conservation and research plans in the future.

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Grant V. 1986. The evolutionary process: a critical study of evolutionary theory. Studies in 5 3 9 History and Philosophy of Science 17, 65-98.     HWE: loci showing a significant departure from Hardy-Weinberg equilibrium with a global test at 5% level and after a sequential Bonferroni correction (** P < 0.05. ** P < 0.01. *** P < 0.001. indicates loci with heterozygote deficit). 6    Branch length represents genetic distance, and the value on the branch is support rate.    Branch length represents genetic distance, and the value on the branch is support rate.