Introduction
Betula luminifera, a fast-growing deciduous tree of family Betulaceae, is a typical species of genus
Betula in the subtropical zone of central China and an important broad-leaved plant endemic to China (
Zheng et al., 1985;
Wu and Wang, 1996).
B.
luminifera has many merits, such as fast growth, good wood quality, strong adaptive capacity, large amount of leaf-fall, and so on. Therefore, it is not only a superior material in the industries of furniture, decoration and pulpwood making, but also plays an important role in improving soil and environment. In recent years,
B.
luminifera has been widely cultivated in southern China, especially in the barren mountains which need ecological recovery. Previous studies on
B.
luminifera focused mostly on its growth characteristics (
Dong et al., 2000), seedlings and afforestation (
Xie and Li, 2000), community characteristics (
Li, 2000) and comprehensive utilization (
Zhou et al., 2003). Few molecular ecology studies have been reported yet. The objectives of this study were to use random amplified polymorphic DNA (RAPD) technique to detect the genetic diversity of wild
B.
luminifera populations at different elevations in the National Nature Reserve of the Wuyi Mountain, Fujian, China, to discuss the variation of genetic diversity, and then to disclose ecological factors related to genetic diversity and factors which play an important role in the genetic differentiation of
B.
luminifera. We trust that the study could provide some molecular information to understand the genetic background and further help to make some effective strategies for the germplasm resources conservation, genetic improvement and sustainable utilization of the species.
Materials and methods
Plant materials
The samples were collected from four wild populations of
B.
luminifera at different elevations in the National Nature Reserve of Wuyi Mountain (27°51′42″N, 117°47′18″E), Fujian, China. The ecological factors of different samples are shown in Table 1. Among which, the soil total nitrogen and C/N ratio were tested by the NC-80 Analysis Instrument (made in Japan), soil organic matters was measured by volumetric method, elevations were detected by GPS, and the meteorological data were provided by the meteorological observation station of the Nature Reserve. The distance among individuals sampled in the same subpopulation was kept more than 30 m to avoid deviation produced by sampling within the same family. The fresh leaves for DNA extraction from 20-29 trees in each wild population were collected and stored with improved saturated NaCl-CTAB solution (
Li et al., 2006).
RAPD analysis
Genomic DNA was extracted with reference to the method of Zeng et al. (
2002) with a minor modification for
B.
luminifera from the leaves which were stored in the improved saturated NaCl-CTAB solution (
Xie et al., 2006). PCR amplifications were performed on a DNA thermal cycler (Applied Biosystems 2720 Thermal Cycler, USA). The amplifications were carried out in a volume of 20 µL containing 2 µL 10×PCR buffer, 2.5 mmol/L MgCl
2, 0.2 mmol/L dNTP, 0.4 µmol/L 10-base RAPD primer, 30 ng of DNA template, 1 U
Taq DNA polymerase (produced by TaKaRa of China). PCR conditions were as follows: initial denaturation at 95°C for 5 min, followed by 40 cycles consisting of denaturation at 94°C for 30 s, annealing at 40°C for 1 min and extension at 72°C for 2 min, with a final extension at 72°C for 5 min, and then storing at 4°C. In order to obtain reliable and reproducible data, the primers (produced by Shanghai Sangon of China) which produced clear and reproducible fragments needs to be selected. Amplification products were analyzed by electrophoresis on 1.5% agarose gels. DNA bands were visualized by staining with ethidium bromide, and observed under UV light and photography.
Data analysis
RAPD data analysis
RAPD bands were scored as binary presence (1) or absence (0) characters to assemble the matrix of the RAPD phenotypes. Then, the indices of genetic diversity, such as the percentage of polymorphic loci (
PPL), observed number of alleles (
Na), number of effective alleles (
Ne), Nei’s gene diversity (
h), Shannon information index (
I), the coefficient for gene divergence (
Gst) and gene flow (
Nm), were calculated using POPGENE 32 the software (
Yeh et al., 1999) on the basis of gene frequencies. At the same time, the genetic structure within and among populations were detected using the software AMOVA-PREP1.01 (
Miller, 1997) and WINAMOVA (
Excoffier, 1995).
Correlation analysis
The Pearson correlation between the genetic index within population and ecological factors was analyzed using the SPSS 11.0 software. Meanwhile, the Mantel test was applied to estimate the associations between genetic distance and elevation distance among populations, and between the matrix of Nei’s unbiased genetic distances and matrixes of divergence of ecological factors at different elevations of B. luminifera.
Results
Genetic diversity of B. luminifera populations
Eighteen ideal primers (Table 2) which produced clear and reproducible fragments were selected from 139 random primers for further study. The 18 primers generated a total of 199 RAPD bands (loci), 11.1 bands per primer on average. The number of amplification products per primer varied from 8 to 14, and these primers produced fragments ranging from 200 to 3000 bp in size.
The genetic diversity of
B.
luminifera (such as
PPL, total genetic diversity (
IT) and total gene diversity (
hT), 87.74%, 0.4899 and 0.3442, respectively) was in accordance with that of
B. alnoides which has similar life histories (
Zeng et al., 2003) (Table 3), but was higher than that of the coniferous or broad-leaved trees (
Ge, 1988), which indicated that there was a relatively high genetic diversity in
B.
luminifera at different elevations in the National Nature Reserve of Wuyi Mountain. Biological characteristics and life habits of
B.
luminifera might contribute to its high genetic diversity. As a long-lived, hermaphroditic individual and outcrossing tree,
B.
luminifera can maintain its genetic diversity over a very long time. Moreover,
B.
luminifera itself maybe has high genetic diversity because the populations had been protected effectively.
The genetic diversity among populations of B. luminifera from different elevations had obvious differences, and the genetic parameters (PPL, I, h) at mean population level were PPL=60.05%, I=0.3181, h=0.2242, Na=1.6339, Ne=1.3893 (Table 3), respectively. According to the genetic diversity parameters, we found that the genetic variation of B. luminifera increased with the drop of elevations, i.e., the genetic variation level of the population at the elevation of 580 m (population 1) was the highest, and it became low at the elevation of 750 m (population 2), 980 m (population 3) and 1 250 m (population 4).
Genetic structure among populations
The analysis by AMOVA implied that only 32.74% of genetic variation occurred among populations and most of the variation (67.21%) occurred within population (Table 4), which was in accordance with the
Gst (34.86%) based on the Nei’s gene diversity index and the genetic diversity among populations (35.07%) based on the Shannon information index. Based on the above results, we concluded that about 1/3 of the genetic variations existed among populations, and most of genetic variation resided within population, which was similar to some endangered species of China, such as
Liriodendron chinense(
Li et al., 2002) and
Cathaya argyrophylla (
Wang et al., 1997), but dissimilar to the ubiquitous species. Table 4 also shows that
Nm based on
Gst was 0.9343, which indicated that the estimate of gene flow among populations was lower.
Table 5 shows the genetic distance and genetic identity among populations. The variation of the genetic distance ranged from 0.0836 (between population 1 and population 2) to 0.1748 (between population 1 and population 4). The mean distance was 0.1284. The analysis of the genetic identity among populations of B. luminifera indicated that the largest genetic identity occurred between population 1 and population 2 (0.8897) and the least between population 1 and population 4 (0.7120). The above results shows that there was higher genetic difference among populations of B. luminifera at different elevations, which became obvious with the increasing distance of elevation.
Correlation between genetic structure and ecological factors
The correlation analysis (Table 6) indicated that the five diversity indices of different subpopulations had significantly (
p<0.05) or very significantly (
p<0.01) negative correlation with elevation distance and soil C/N ratio. Some genetic diversity indices had also significant correlation with climate factors (annual average temperature and annual precipitation), the content of soil total nitrogen and organic matter. Among them, all the diversity indices had a positive correlation with annual average temperature, but had a negative correlation with the other ecological factors. There was no significant correlation between the genetic diversity parameters and pH of soil. The above correlations implied that the genetic diversity of
B.
luminifera might be the result from the joint effects of one or several ecological factors, i.e., the ecological factors play an important role in influencing the RAPD polymorphism of
B.
luminifera, which are in accordance with the results of the study on
Stipa grandis (
Zhao et al., 2004) and
Triticum dicoccoides (
Fahima et al., 1999).
Table 7 shows the relationships between the divergence ecological factors of different elevations and genetic distances of
B.
luminifera populations. From Table 7, we knew that there were significant correlation between Nei’s unbiased genetic distances and elevation-distance among populations, which indicated that elevation had influenced on the genetic differentiation of
B.
luminifera among populations, which is similar to the results of Liu et al. (
2003) and Li and Peng (
2001). Furthermore, the genetic distance among populations had obvious correlation with the soil factors, such as C/N ratio, the content of total nitrogen, and organic matter, which indicated that the ecological factors might significantly affect the differentiation in population. The above results indicated that the genetic differentiation of
B.
luminifera among populations was actually influenced by the joint effects of many ecological factors.
Discussion
The results determined by RAPD markers show that there was a relative high genetic diversity of wild B. luminifera populations at different elevations in the National Nature Reserve of Wuyi Mountain. At the species level, the genetic diversity indices PPL, I and h were 87.44%, 0.4899 and 0.3442, respectively. However, according to field investigation, we found that it was difficult for seedlings of B. luminifera to survive in the natural forest and most of B. luminifera trees were mature ones. From these, we presumed that the high genetic diversity of B. luminifera in Wuyi Mountain might be only a temporary phenomenon. Consequently, if we cannot take effective and timely measures of breeding and protection, the genetic diversity of B. luminifera will decline in the long run. At the population level, the genetic variation level of B. luminifera varied regularly with elevations. That is, the genetic variation of the population at the elevation of 580 m (population 1), in which soil, moisture and light environments were well was the highest, and it became low at the elevation of 750 m (population 2), 980 m (population 3) and 1250 m (population 4), which shows that elevation had a close relation to genetic variation of B. luminifera, and the genetic variation level increased with the decrease of elevations. In this study, the change of genetic diversity B. luminifera may be a consequence of adaptation to the microtopography. And the effects of geographical distances and elevations on the genetic variation of B. luminifera might increase if we enlarge the study area. Of course, further experiments are needed to support this hypothesis.
Pearson correlation analysis further revealed that the change rule of genetic diversity had a close relation to the ecological factors of B. luminifera at different elevations. The genetic diversity within population was significantly or very significantly related to elevation, climate factors (annual average temperature and annual precipitation) and soil nutrient factors (total nitrogen, C/N ratio and organic matter), which suggested that the elevation, soil nutrient and climatic factors might play an important role in maintaining the genetic diversity of B. luminifera. In our study, the genetic differentiation B. luminifera among populations was also significantly correlated to the elevation and climate factors. Therefore, the divergence of elevation and microenvironments influenced not only the genetic diversity of B. luminifera, but also the genetic differentiation.
Genetic structure analysis shows that the genetic differentiation percentage of
B.
luminifera at different elevations in Wuyi Mountain was relatively high. Only about 1/3 of genetic variations occurred among populations and most of the variations occurred within populations. The genetic structure among populations of a species was affected by many factors, such as gene mutation, geographic distance, gene flow, genetic drift, natural selection and its biological characteristics (
Schaal et al., 1998;
Volis et al., 2001). Among them, gene mutation was not often considered as the factor that induced genetic differentiation among populations. To avoid the effect of community edges and gaps, the samples were randomly collected in the
B.
luminifera community, and there were no obvious difference on the geographic distances among the four samples. So, geographic distance was also not the reason that caused the genetic differentiation of
B.
luminifera among populations. Secondly,
B.
luminifera is a heliophilous tree species. Most of them are situated in upper canopy layers of natural community and their seedlings had difficulty surviving in the natural forest, which lead to the fact that most
B.
luminifera were mature trees. Furthermore, the
B.
luminifera natural forests have been seriously destroyed and disappeared from many sites as a result of over utilization and invasion of other species. Therefore, the biological characteristics of
B.
luminifera might be a potential reason that affected the genetic difference of this species. Meanwhile, Volis et al. (
2001) pointed out that if the genetic differentiation was caused by genetic drift among populations, then there would be no correlation between genetic differentiation and ecological factors. However, in our study, the genetic variation of
B.
luminifera among populations had significant correlation with ecological factors, which meant that the genetic differentiation of
B.
luminifera could not be affected by genetic drift, but by the natural selection pressure from the microenvironment at different elevations. As a result, except for the biological characteristics, natural selection and the lack of effective gene flow might also affect the genetic difference of
B.
luminifera among populations. Further studies are needed to reveal whether there are some other factors which cause the genetic variation of
B.
luminifera.
Although B. luminifera had not been listed as a top conservation plant in China, it is an important economic tree species endemic to China. Therefore, the conservation and further reasonable utilization of the germplasm resources of this species are an urgent task for us. Our results demonstrated that the divergence of elevation and microenvironments had an obvious effect on the genetic diversity and genetic structure of B. luminifera in Wuyi Mountain. Consequently, major attention should be paid to the scientific conservation for wild populations of B. luminifera at different elevations when strategies for breeding and germplasm conservation will be implemented in the future. Meanwhile, introduction, cultivation and genetic improvement should be carried out for the wild germplasm resources of different elevations, and the new varieties which can adapt to all kinds of ecological environments should be cultivated.
Higher Education Press and Springer-Verlag Berlin Heidelberg
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