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Journal of Resources and Ecology >

2020 , Vol. 11 >Issue 5: 466 - 474

DOI: https://doi.org/10.5814/j.issn.1674-764x.2020.05.004

Forest Ecosystem

Genetic Diversity of Toona ciliata Populations based on SSR Markers

  • WANG Yang ,
  • YUE Dan , * ,
  • LI Xinzhi , *
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  • Hubei Ecology Polytechnic College, Wuhan 430200, China
*, YUE Dan, E-mail:;
LI Xinzhi, E-mail:

Received date: 2020-02-19

  Accepted date: 2020-06-03

  Online published: 2020-09-30

Supported by

Foundation: The Public Welfare Research Project of Department of Science and Technology in Hubei Province(402012DBA40001)

The Scientific Research Project of Department of Education in Hubei Province(B20160555)

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Abstract

In order to provide a theoretical basis for the protection and development of T. ciliata germplasm resources, we studied the genetic diversity of T. ciliata by using SSR (Simple Sequence Repeat) primers to evaluate the genetic diversity of 192 T. ciliata germplasm samples from 24 populations of 5 provinces. DataFormater, Popgene, NTSYS, TFPGA and other software were used for genetic data conversion, genetic parameter estimation, dendrogram construction and genetic variation analysis. The results showed that: 1) a total of 17 alleles (Na) were detected in seven pairs of primers, with an average of 2.260 for each primer. Among them, the highest numbers of alleles (4) were detected in primers S11 and S422.The mean value of Nei’s genetic diversity index (H) was 0.4909, the mean value of Shannon information index (I) was 0.7321, and the mean value of polymorphic information content (PIC) was 0.5182. The mean expected heterozygosity (He) and observed heterozygosity (Ho) were 0.1055 and 0.4956, respectively. The Nei°s genetic distances of the populations ranged between 0.0002 and 2.6346, and the mean was 0.5477. The average genetic diversity level (H=0.1044) of the 24 populations was lower than that of the species (H=0.4909). 2) The genetic differentiation coefficients (Fst) varied from 0.2374 to 0.9148, with an average value of 0.7727. The mean of population gene flow (Nm) was 0.0735, indicating a low level of genetic exchange between populations, and suggesting that the genetic variation mainly came from within populations. 3) With the UPGMA method, the 24 populations were clustered into 3 groups at Nei’s genetic identity (0.99): the populations from Guizhou Province and Guangxi Zhuang Autonomous Region were clustered into one group, the populations from Hunan Province were in another group, and the populations from Hubei Province were in the third group. The Mantel test analysis showed a significant correlation between Nei’s genetic distance and geographic distance (r=0.6318, P=0.009˂0.05). The genetic diversity of the 24 populations of T. ciliata was at a low level. Geographic isolation was the main reason for genetic differentiation among T. ciliata provenances. In the protection of germplasm resources of T. ciliata, emphasis should be placed on breeding genetic resources from the populations with higher genetic diversity (P14, for example). As for the populations with low genetic diversity, an ex-situ protection strategy as well as ecological and timber objectives, should be taken into account to maximize the conservation and utilization of the diversity of T. ciliata.

Key words： Toona ciliata; SSR marker; natural population; genetic diversity; genetic differentiation

Cite this article

WANG Yang , YUE Dan , LI Xinzhi . Genetic Diversity of Toona ciliata Populations based on SSR Markers[J]. Journal of Resources and Ecology, 2020 , 11(5) : 466 -474 . DOI: 10.5814/j.issn.1674-764x.2020.05.004

1 Introduction

Toona ciliata Roem. is a tall deciduous or semi-evergreen tree, and a precious timber species belonging to genus Toona (Meliaceae). T. ciliata was listed as a wild endangered species under secondary national protection (Yu, 1999). The natural distribution area of T. ciliata is limited to East Asia, South Asia and Australia. In China, T. ciliata is mainly distributed in South China, Central China, East China and Southwest China, and the natural population has sporadic distribution characteristics (Long et al., 2011; Li et al., 2016; Wang et al., 2018). In these areas, it is known as “Chinese mahogany” (Long et al., 2011; Wang et al., 2018) due to its high timber quality, so it has been overexploited and its natural regeneration is slow, leading to the reduction of its natural distribution (Wen et al., 2012; Chen et al., 2014).
So far, studies on T. ciliata at home and abroad have mainly focused on plant physiology and biochemistry, ecology, plant introduction and breeding, and related topics (Malairajan et al., 2007; Duan et al., 2015; Wang et al., 2016a; Wang et al., 2016b; Wang et al., 2016c; Huang et al., 2017; Wang et al., 2018). Genetic studies on T. ciliata have been reported with respect to phenotypic variation (Cai et al., 2018; Wang et al., 2018; Wang et al., 2019) and molecular markers (SRAP) (Li et al., 2016; Zhan et al., 2016). The SSR (Simple Sequence Repeat) molecular marker is a neutral molecular marker randomly distributed in the genome (Zietkievicz et al., 1994). Due to its advantages of co-dominant inheritance, wide distribution, good stability and repeatability (Powell et al., 1996), SSR technology has become an ideal genetic marker technology. It has been widely used in the genetic studies of some endangered and rare tree species, such as Eucommia ulmoides (Miao et al., 2017), Taxus wallichiana var. mairei (Yi et al., 2013), Parashorea chinensis (Zhang and Li, 2011), Pteroceltis tatarinowii (Fan et al., 2018) and Phoebe bournei (Liu et al., 2019). However, the application of SSR markers in the study of genetic diversity in genus Toona is seldom reported. Liu et al. (2013) compared the genetic diversity of central and peripheral populations of Toona ciliata var. pubescens by using SSR markers. Zhan et al. (2016) established an optimal reaction system of SSR-PCR and screened the highly polymorphic primers fitted for the SSR analysis of T. ciliata, which laid an academic foundation for genetic research on natural populations of T. ciliata.
Studies of the genetic characteristics of T. ciliata should consider the selection of provenances in different geographical distribution areas and the use of different molecular marker technologies in the investigation and evaluation of T. ciliata resources. We studied 192 germplasm samples from 24 natural T. ciliata populations from five provinces using SSR markers. Through the analyses of genetic diversity, population genetic differentiation, clustering and correlations between geographic distance and genetic distance, we aimed to reveal the genetic diversity level of T. ciliate, and the cause of that diversity, to provide a theoretical basis for the protection and development of T. ciliata germplasm resources.

2 Materials and methods

2.1 Testing materials

In May 2016, experimental samples were collected based on the investigation of 14 naturally-distributed populations of T. ciliata in the provinces of Hubei, Hunan, Jiangxi, Guizhou and Guangxi Zhuang Autonomous Region (Table 1). Eight samples were collected for each population and the distances between sampled plants were all greater than 40 m. Small healthy leaflets on adult plants without pests and diseases were collected for a total of 192 testing samples. All leaflets were rapidly dehydrated with a large amount of color-changing silica gel and then kept at low temperature for subsequent DNA extraction. See Table 1 for specific sampling data for each population.
Table 1 Locations and altitudes of the 24 sampled populations of Toona ciliata
Population Location East
longitude		 North latitude Altitude (m) Population Location East
longitude		 North latitude Altitude (m)
P1 Xingyi of Guizhou 105°02°08 24°58°03 779 P13 Laifeng of Hubei 109°15°57 29°25°58 521
P2 Changde of Hunan 111°31°08 29°18°54 399 P14 Hefeng of Hubei 110o12°29 30o10°12 559
P3 Ceheng of Guizhou 105°52°38 24°52°16 972 P15 Enshi of Hubei 109°14°51 30°01°13 738
P4 Tianlin of Guangxi 106°39°08 24°02°12 311 P16 Xuan’en of Hubei 109°41°59 30o02°26 1013
P5 Shaoyang of Hunan 111°22°15 27°22°30 540 P17 Lichuan of Hubei 108°33°49 29°51°22 521
P6 Jinggangshan of Jiangxi 114°09°37 26°39°20 907 P18 Zhushan of Hubei 110°01°59 31°39°58 660
P7 Zhenfeng of Guizhou 105°46°17 25°22°46 477 P19 Gucheng of Hubei 111°15°49 32°01°36 402
P8 Huaihua of Hunan 110°05°14 27°31°47 613 P20 Badong of Hubei 110°23°44 30°36°49 720
P9 Anlong of Guizhou 105°26°25 25°06°23 1377 P21 Chongyang of Hubei 113°46°25 29°26°37 338
P10 Youmai of Guizhou 105°59°41 25°03°19 695 P22 Tongshan of Hubei 114°38°39 29°24°18 567
P11 Xian°an of Hubei 114°19°18 29°45°42 356 P23 Huangshi of Hubei 115°04°51 30°11°26 356
P12 Xianfeng of Hubei 109°00°07 29°47°59 806 P24 Jianshi of Hubei 110°05°59 30°19°26 541

2.2 Experimental method

2.2.1 DNA extraction
Genomic DNA was extracted from leaflets of T. ciliata using the CTAB method. Purity and quality of extracted DNA were measured with 1.0% agarose gel electrophoresis (AGE), and the DNA concentration was measured with a UV spectrophotometer.
2.2.2 SSR-PCR amplification
Based on the published literatures (Liu et al., 2009; Liu et al., 2013; Liu et al., 2016; Zhan et al., 2016), 29 pairs of primers with good polymorphism were selected. The SSR- PCR (polymerase chain reaction) was performed on the Bio-Rad ptc-200 PCR apparatus (Bio-Rad Laboratories, USA). The reaction system was amplified in 19 μl PCR molecular marker solutions, the specific components of which (after being optimized) were: 12.1 μl dd H2O, 2 μl template DNA, 0.1 μl Taq enzyme, 2.0 μl 10×PCR buffer, 1.8 μl MgCl2 (25 mmol L-1) and 1.0 μl primer mixture (10 μmol).
The PCR thermal cycling was: pre-denaturation at 94 ℃ for 5 min, denaturation at 94 ℃ for 45 s, annealing at 55 ℃ for 45 s, with a total of 30 cycles, and extension at 72 ℃ for 45 s. Then, the sequences amplified by PCR were extended at 72 ℃ for 10 min and maintained at 4 ℃ for 5 min. At the end of PCR, the amplified solutions were stored in the refrigerator at 4 ℃ for future use. A total of seven pairs of primers with stable amplification and good repeatability were selected for SSR analysis using the T. ciliata samples. Primer information is shown in Table 2.
Table 2 Primer sequences used in the SSR analysis of T. ciliata
Primer Primer combination sequences
S5 F: GTGGCGTAACAGACCAAAAC R: CCAGAGATACTCCATTCCAG
S11 F: AGTAATAGCCTGTAGAGCAG R: GAAGAAGGGTGAGCGAGA
S22 F: GAAACCAGCAGGCAGAGC R: ACCGCATTAGTACCAGTAG
T02 F: TAGGAAAGGCAAGGTGGG R: GGGTGGTCGATGAGGGTT
T05 F: AGTAATAGCCTGTAGAGCAG R: AGAGTGGGGTGGTCGATGAG
T07 F: ATGGATGAGTGTGCGATAGG R: TGTGATGTAGGAGTCTGAAC
S422 F: ATGGATGAGTGTGCGATAGG R: TGTGATGTAGGAGTCTGAAC

2.3 Data analysis

The amplified banding patterns were recorded as 0 or 1. In the positions with the same mobility rate, each position with a band was denoted as 1, while positions without a band were denoted as 0. DataFormater software (Fan et al., 2016) was used to transform the data to meet the input requirements of the different analysis software programs. POPGENE 1.32 was employed to obtain the required genetic parameters, including observed number of alleles (Na), effective number of alleles (Ne), observed heterozygosity (Ho), expected heterozygosity (He), Shannon information index (I), polymorphism information content (PIC), population inbreeding coefficient (Fis), genetic differentiation coefficient (Fst), the number of migrants per generation (Nm) and Nei’s genetic distance (Nei et al., 1983). NTSYS-pc 2.10s was used to draw the UPGMA-based dendrogram. TFPGA software was used to conduct the Mantel test for geographical distance and Nei’s genetic distance (Mantel, 1967). SPSS 22 and Excel 2013 were applied for data processing.

3 Results and analyses

3.1 Polymorphism of SSR loci

From 29 pairs of SSR primers, seven pairs of markers were obtained which had stable amplification, effective polymorphic information content and uniform genome-wide distribution (Table 2). A total of 17 alleles (Na) was detected, yielding a mean value of 2.7143 alleles for each marker, with the variation ranging from 2 to 4, as can be seen in Table 3. The number of detected effective alleles (Ne) was 15.8214, for an average of 2.2602 alleles for each marker. The percentage of polymorphic bands (PPB) ranged from 49.92%-93.70%, and the mean was 78.82%, indicating that there was little difference between Na and Ne, and that the detected loci were evenly distributed in each population. The average polymorphism information content (PIC) of each marker was 0.5182 and the arrangement of loci by PIC values was: S11 (0.7473) > T07 (0.5789) > S5 (0.5340) > T05 (0.5211) > S422 (0.5122) > S22 (0.4429) >T02 (0.2909). Shannon indexes (I) varied from 0.1447 to 1.2094, with an average of 0.7321. The observed heterozygosity (Ho) spanned 0.0000 to 0.5965, with an average value of 0.1055. The expected heterozygosity (He) ranged from 0.4266 to 0.6749, with an average of 0.4956. Nei’s genetic diversity index (H) values were between 0.4228 and 0.6675, with a mean of 0.4909. These results showed that the polymorphism of the seven pairs of SSR primers in the populations of T. ciliata was lower but effective, so these primers could be applied to provide a good analysis of the genetic diversity of T. ciliata.
Table 3 Summary of genetic variation statistics of the seven Loci
Locus Na Ne PPB (%) PIC Ho He H I
S5 2 2.1460 89.30 0.5340 0.0000 0.4444 0.4401 0.6603
S11 4 3.9574 75.20 0.7473 0.0870 0.6749 0.6675 1.2094
S22 2 1.7950 86.63 0.4429 0.0000 0.4266 0.4228 0.6205
T02 2 1.4102 93.53 0.2909 0.5965 0.4695 0.4654 0.1447
T07 3 2.3750 63.50 0.5789 0.0192 0.4796 0.4750 0.8395
T05 2 2.0880 93.70 0.5211 0.0000 0.4708 0.4664 0.6757
S422 4 2.0498 49.92 0.5122 0.0357 0.5037 0.4992 0.9745
Mean 2.7143 2.2602 78.82 0.5182 0.1055 0.4956 0.4909 0.7321

Note：Na: the number of alleles; Ne: the number of effective alleles; PPB: the percentage of polymorphic bands; PIC: the polymorphic information content; Ho: the observed heterozygosity; He: the expected heterozygosity; H: Nei’s genetic diversity index; I: Shannon diversity index.

3.2 Genetic diversity of the population

The analyses of the genetic diversity parameters of the 24 populations showed that the number of alleles (Na) varied between 1.0000 and 2.4286, with an average of 1.2629. The number of effective alleles (Ne) ranged from 1.0000 to 2.2286, with an average of 1.2081. The polymorphic in- formation content (PIC) was 0‒100.00%, and the mean was 19.05%. The observed heterozygosity (Ho) was between 0.0000 and 0.2857, with an average of 0.1136. The expected heterozygosity (He) spanned 0.0000 to 0.6190, with a mean of 0.1493, indicating that the diversity level of all populations was lower. Nei’s genetic diversity index (H) was between 0.0000 and 0.5159, with an average of 0.1044. Only P16 had a higher genetic diversity than that of the species level (H = 0.4909) while the other populations with H > 0.1000 were ranked in value as: P16 > P6 > P13 > P15 > P10 > P22 > P8. Shannon information indexes (I) were in the range of 0.0000‒0.8015, with a mean of 0.1546, indicating a low level of genetic diversity (Table 4).
Table 4 Genetic diversity parameters of 24 T. ciliata populations
Population Na Ne PIC Ho He H I
P1 1.1429 1.1429 14.29% 0.1429 0.1429 0.0714 0.0990
P2 1.1429 1.1429 14.29% 0.1429 0.1429 0.0714 0.0990
P3 1.1429 1.1429 14.29% 0.1429 0.1429 0.0714 0.0990
P4 1.1429 1.1429 14.29% 0.1429 0.1429 0.0714 0.0990
P5 1.1429 1.1429 14.29% 0.1429 0.1429 0.0714 0.0990
P6 2.2857 1.8138 100.00% 0.0714 0.4481 0.4107 0.6533
P7 1.1429 1.1429 14.29% 0.1429 0.0952 0.0714 0.0990
P8 1.2857 1.1829 28.57% 0.0357 0.1310 0.1027 0.1528
P9 1.1667 1.1000 14.29% 0.0833 0.0714 0.0625 0.0937
P10 1.2857 1.2101 28.57% 0.0857 0.1302 0.1171 0.1705
P11 1.1429 1.1429 14.29% 0.1429 0.1429 0.0714 0.0990
P12 1.1429 1.1213 14.29% 0.1020 0.0706 0.0656 0.0931
P13 1.4286 1.2527 42.86% 0.2381 0.1810 0.1508 0.2278
P14 1.0000 1.0000 0.00% 0.0000 0.0000 0.0000 0.0000
P15 1.2857 1.2857 28.57% 0.2857 0.2857 0.1429 0.1980
P16 2.4286 2.2286 0.00% 0.1429 0.6190 0.5159 0.8015
P17 1.0000 1.0000 0.00% 0.0000 0.0000 0.0000 0.0000
P18 1.1429 1.1143 14.29% 0.0952 0.0762 0.0635 0.0909
P19 1.1429 1.1429 14.29% 0.1429 0.1429 0.0714 0.0990
P20 1.1429 1.1429 14.29% 0.1429 0.1429 0.0714 0.0990
P21 1.0000 1.0000 0.00% 0.0000 0.0000 0.0000 0.0000
P22 1.2857 1.1708 28.57% 0.0857 0.1175 0.1057 0.1588
P23 1.1429 1.0857 14.29% 0.0714 0.0714 0.0536 0.0803
P24 1.1429 1.1429 14.29% 0.1429 0.1429 0.0714 0.0990
Mean 1.2629 1.2081 19.05% 0.1136 0.1493 0.1044 0.1546

Note：Na: the number of alleles; Ne: the number of effective alleles; PIC: the polymorphic information content; Ho: the observed heterozygosity; He: the expected heterozygosity; H: Nei’s genetic diversity index; I: Shannon diversity index.

3.3 Population genetic differentiation

The coefficient of inbreeding (Fis) reveals the deletion or excess of heterozygous genotypes in the total group of samples (Table 5). Among the seven loci, there were excess hybrid genes in five of them, and deleted hybrid genes in two loci (S11 and T02); overall, the mean heterozygosity of the populations was higher, indicating an inbreeding phenomenon of T. ciliata. This inbreeding phenomenon might be related to the characteristics of a small population or a high degree of geographic or environmental isolation (Wang et al., 2016a).
Table 5 Coefficients of genetic differentiation and gene flow between T. ciliata populations
Locus Fis Fst Nm
S5 1.0000 0.9148 0.0233
S11 -0.1232 0.8288 0.0516
S22 1.0000 0.9148 0.0233
T02 -0.7084 0.2374 0.8029
T07 0.7857 0.8233 0.0537
T05 1.0000 0.8921 0.0302
S422 0.6548 0.7914 0.0659
Mean -0.0096 0.7727 0.0735

Note：Fis: population inbreeding coefficient; Fst: genetic differentiation coefficient; Nm: number of migrants per generation.

The genetic differentiation index (Fst) is an important indicator of inter-population genetic differentiation. The mean value of Fst was 0.7727, indicating a high degree of genetic differentiation among the populations. The Fst of T02 (0.2374) was the lowest, but even it reached a high level of genetic differentiation, while the Fst of S5 (0.9148) and S22 (0.9148) were both at the highest value. Gene flow (if Nm > 1) can play a homogenizing role, that is, it can effectively inhibit the differentiation between populations. But when Nm ˂ 1, genetic differentiation between populations definitely occurs (Wright, 1951). The mean Nm of the 24 T. ciliata populations was 0.0735, showing a low level of genetic exchanges between the populations, which inevitably resulted in the higher Fst.

3.4 Genetic relationship and cluster analysis of the populations

Table 6 shows that the Nei’s genetic distances of the 24 T. ciliata populations were between 0.000 and 2.635, with an average of 0.548. The genetic distance between P9 and P18 was the longest, while the genetic distance between P1 and P3 was the shortest. The geographical distances among the 24 populations ranged from 20.202 to 1154.471 km. The geographical distance between P1 and P23 was the longest, while that between P14 and P24 was the shortest, with an average of 491.180 km. By using the UPGMA method, the genetic consistency among the populations of T. ciliata was clustered (Fig. 1). The populations of Guizhou Province and Guangxi Zhuang Autonomous Region were grouped together; while the populations of Hunan Province were clustered in another group; and the populations of Hubei were in a third group. The results showed that the 24 populations of T. ciliata were clearly clustered according to geographical distances.
The Mantel test (Mantel, 1967) was performed on the normalized logarithmic geographic distances between the different populations and Nei’s genetic distances (Fig. 2). The results revealed an extremely significant correlation between Nei’s genetic distance and geographic distance for the group of 24 T. ciliata populations (r=0.631, P=0.009 ˂0.05).
Table 6 Geographic distance and Nei’s measures of genetic distance between the different populations
Population P1 P2 P3 P 4 P5 P 6 P7 P8 P9 P10 P11 P12
P1 0.000 0.184 0.000 0.169 0.164 1.427 0.023 0.191 0.048 0.020 1.250 1.495
P2 813.899 0.000 0.502 0.284 0.224 0.000 0.253 0.136 0.321 0.355 0.151 0.397
P3 94.239 745.562 0.000 0.134 0.238 1.499 0.087 0.624 0.010 0.079 1.559 0.914
P4 200.399 764.182 121.327 0.000 0.261 0.379 0.357 0.191 0.321 0.251 0.679 0.759
P5 694.831 216.008 615.055 600.545 0.000 0.128 1.861 0.076 0.321 0.251 0.151 0.397
P6 942.630 394.233 854.178 809.441 288.084 0.000 0.594 0.220 1.261 1.101 0.100 0.317
P7 94.373 717.911 58.421 174.249 600.937 851.510 0.000 1.852 1.826 0.001 1.482 1.338
P8 588.999 244.576 513.711 518.222 128.105 415.348 491.837 0.000 0.273 0.250 0.150 1.033
P9 51.623 764.833 51.287 170.344 643.819 890.660 46.619 536.283 0.000 0.011 1.826 1.624
P10 105.825 719.245 28.112 130.579 595.541 937.695 43.327 491.987 56.546 0.000 1.378 1.329
P11 1102.194 295.379 1031.610 1033.003 438.119 409.258 1006.608 518.472 1051.834 1009.778 0.000 0.092
P12 667.923 249.735 627.351 679.819 354.799 614.673 584.291 273.074 628.524 603.785 518.927 0.000
P13 658.233 215.922 610.919 655.850 306.996 569.457 570.941 227.165 615.754 587.346 496.102 47.796
P14 784.345 155.414 734.238 772.719 331.558 547.032 685.329 297.541 740.855 710.735 390.338 131.978
P15 702.516 233.378 660.920 711.379 351.351 608.949 618.035 288.427 662.272 637.127 491.349 34.232
P16 731.596 193.604 686.204 730.671 337.601 576.007 645.371 280.881 690.102 662.422 447.588 32.267
P17 648.599 292.523 612.780 672.126 388.540 653.713 567.327 297.783 610.703 662.329 559.069 43.109
P18 896.381 298.413 859.041 911.302 494.726 686.210 814.512 460.657 858.245 835.246 435.728 231.839
P19 997.076 302.490 952.453 995.339 516.427 659.615 911.266 511.782 955.825 928.686 348.442 328.029
P20 824.102 180.008 777.377 817.424 371.063 572.418 737.151 343.091 782.254 753.221 379.222 161.860
P21 1004.299 222.903 932.128 926.337 329.956 305.026 910.554 418.748 955.163 910.704 117.445 467.081
P22 1078.720 303.619 1003.264 992.667 391.714 308.371 984.091 492.168 1028.344 982.642 108.409 548.314
P23 1154.471 357.847 1082.811 1077.884 477.909 401.988 1060.605 569.301 1105.364 1061.561 73.747 588.123
P24 789.9930 174.5340 742.3150 783.321 351.456 409.226 702.080 314.612 747.541 718.582 399.826 129.477
Population P13 P14 P15 P16 P17 P18 P19 P20 P21 P22 P23 P24
P1 1.321 1.320 1.411 1.550 1.398 1.254 1.283 1.279 1.264 1.260 1.339 1.269
P2 0.353 0.147 0.376 0.514 0.315 0.547 0.540 0.184 0.081 0.087 0.103 0.208
P3 1.506 1.234 1.006 0.503 1.075 1.176 0.903 0.645 0.549 0.504 0.538 0.527
P4 0.671 0.484 0.515 0.565 0.372 0.461 0.460 0.349 0.266 0.345 0.342 0.582
P5 1.321 0.670 0.716 0.565 0.996 0.893 0.789 0.338 0.166 0.139 0.136 0.423
P6 0.266 0.330 0.262 0.317 0.354 0.368 0.379 0.272 0.114 0.125 0.120 0.305
P7 0.172 1.322 1.322 0.249 1.349 1.338 1.337 1.337 1.349 2.305 1.340 1.337
P8 0.668 0.725 0.080 0.564 0.514 0.526 0.553 0.191 0.135 0.063 0.128 0.289
P9 2.477 1.784 2.050 1.641 1.636 2.635 2.624 1.672 1.636 1.670 1.839 0.981
P10 1.299 0.935 1.314 1.719 1.866 1.329 1.328 1.328 1.866 2.285 1.331 1.328
P11 0.100 0.103 0.096 0.092 0.093 0.097 0.123 0.138 0.156 0.087 0.093 0.092
P12 0.090 0.089 0.090 0.090 0.090 0.090 0.097 0.093 0.097 0.091 0.095 0.100
P13 0.000 0.097 0.097 0.090 0.091 0.092 0.089 0.102 0.107 0.111 0.103 0.091
P14 126.121 0.000 0.092 0.091 0.094 0.088 0.089 0.236 0.094 0.107 0.114 0.091
P15 62.808 43.537 0.000 0.091 0.094 0.092 0.093 0.236 0.094 0.093 0.100 0.090
P16 75.212 59.243 43.576 0.000 0.091 0.095 0.099 0.233 0.099 0.116 0.118 0.091
P17 84.077 111.518 68.878 111.545 0.000 0.096 0.090 0.232 0.100 0.115 0.095 0.094
P18 257.393 185.494 199.733 185.395 247.608 0.000 0.094 0.206 0.156 0.097 0.097 0.091
P19 341.271 266.155 293.889 266.143 352.536 121.514 0.000 0.154 0.024 0.018 0.029 0.009
P20 166.455 46.169 128.776 92.379 195.463 123.627 177.363 0.000 0.018 0.017 0.028 0.008
P21 437.295 352.559 446.745 404.053 510.539 441.607 381.901 355.899 0.000 0.100 0.090 0.094
P22 518.364 430.732 526.568 483.493 590.942 508.314 436.324 430.933 82.506 0.000 0.099 0.090
P23 564.382 461.774 562.455 518.883 629.691 508.818 418.347 452.369 152.414 101.020 0.000 0.096
P24 131.412 20.202 97.204 58.386 165.387 146.899 211.513 34.708 368.508 443.241 475.439 0.000

Note: Nei’s genetic distance (above diagonal) and geographic distance (below diagonal) of the 24 T. ciliata populations.

Fig. 1 UPGMA dendrogram based on Nei’s genetic distance
Fig. 2 Spatial genetic correlation of the 24 T. ciliata populations

4 Discussion

4.1 Genetic diversity of T. ciliata

At the species level, Nei’s genetic diversity index (H = 0.4909) was consistent with (but slightly lower than) Shannon diversity index, indicating that the genetic diversity of populations was at a lower level. The level and distribution pattern of genetic diversity of a given plant species are the results of geographical distribution, breeding system, human interferences and many other factors (Wu et al., 2019), among which natural environmental differences can cause isolation between populations. Widely distributed in China, and adapted to complex and diverse environments, T. ciliata has derived rich genetic diversity. In this study, the latitudes of sampled T. ciliata populations spanned 24°02'12"- 32°01'36"N, and the difference between the flowering phases of the northernmost and southernmost distribution areas is greater than 30 d. Therefore, T. ciliata trees from the northern populations and the southern populations could not pollinate each other, resulting in reproductive isolation. Limited pollen and seed diffusion might contribute to a lower level of effective gene flow, and can easily cause a high proportion of self-pollination in a species (Liu et al., 2009). T. ciliata is mainly distributed in mountainous areas (at altitudes of 300-2260 m), and its sporadic distribution and small population together with overcutting, all add to the declines of its habitats and natural resources (Long et al., 2011), which contribute to the high degree of habitat isolation and obstruct the gene flow, resulting in the low genetic diversity of the T. ciliata populations. Except for P16, the genetic diversity levels of the other 23 populations were lower than that of the species level (H = 0.4909), which was higher than that found by Li et al. (2016) for the whole distribution area of T. ciliata in China (H = 0.3770). However, the average genetic diversity level of the populations in this study (H = 0.1044) was lower than that found by Li et al. (2016) (H = 0.1805), which might be related to the differences in sampling sites.
T. ciliata is a highly heliophilous species. So, if the plants in the forest cannot reach the canopy, then their competitiveness is insufficient, and the small-and medium-sized plants under the canopy often die (Wang et al., 2019). Therefore, the natural habitats of T. ciliata are along streams, rivers or narrow forest margins with optimal luminous conditions. When the suitable habitats shrink, the number of trees declines sharply, and smaller populations become more typical (Wang et al., 2016a). Meanwhile, species with diffusive incompetence are more susceptible to the influence of edge locations, compared with species which have long- distance diffusion competence (Lesica and Allendorf, 1995; Peakal and Smouse, 2012). A strategy of scattered survival would make it difficult for T. ciliata trees to maintain extensive gene exchanges, even within the populations, which may lead to low genetic diversity at the population level.

4.2 Genetic differentiation of populations

The high degree of genetic differentiation indicates that the homologous probability of two gametes being randomly selected from any non-cohabitation populations is low, and, therefore, the homogeneity of genetic composition of the population is also low. The genetic differentiation coefficient (Fst = 0.7727) was higher than that found for T. ciliata var. pubescens (a T. ciliata variety) in central (0.1520) and peripheral populations (0.3045) (Liu et al., 2009), showing that at the species level, the genetic variation (77.27%) within T. ciliata populations was higher than the genetic variation between groups (22.73%), and that the genetic differentiation within populations was the main factor causing the genetic variation of T. ciliata. This result was consistent with Li’s finding that 79.26% of the genetic differentiation existed between populations through AMOVA analysis (Li et al., 2016).
Genetic differentiation is influenced by gene flow, natural selection and mutations (Schaal et al., 1998). Gene flow (Nm) is the flow of genes between populations and an important factor affecting the genetic differentiation of populations. A greater level of gene flow between populations causes more homogeneous populations (Slatkin, 1981). However, as long as the gene flow is in pleiotropy, it can prevent the genetic differentiation caused by genetic drift between populations when the inter-population migration per generation is Nm ≥ 1 (Hamrick et al., 1995). In this study, we found that gene exchange between populations was low (Nm = 0.0735 ˂ 1), and thus increasing the genetic differentiation between populations. Since gene flow mainly comes from seed flow or pollen flow, geographical isolation caused by mountains or rivers could block it (Nagel et al., 2015; Yi et al., 2018).
Nei’s genetic distance was significantly related to the geographical distance of the T. ciliata populations. First of all, there were six populations in one group, including P4 of Guangxi Zhuang Autonomous Region as well as P1, P3 P7, P9, and P10 from Guizhou Province. In addition, P2, P5 and P8 from Hunan Province were grouped together, while all 14 populations in Hubei were grouped together. Such a clustering reflected the differences in the geographical distribution areas of T. ciliata (both in the north and in the south), and, as a result, reproduction between the populations was almost completely isolated and the gene flow was greatly blocked.

4.3 Protection and utilization of germplasm resources of T. ciliata

As an important source of genetic diversity, wildlife may possess valuable genetic resources which can serve as the basis for resource utilization. Therefore, systematic research and scientific protection of wildlife should be emphasized (Wu et al., 2019). For protecting germplasm resources of T. ciliata, it is necessary to select and breed superior populations according to the higher genetic diversity of the species resources and their genetically-differentiated characteristics. P16, for example, has the highest genetic diversity (H = 0.5159), which is higher than that of the species level (H = 0.4909). As we observed in this investigation, the natural resources of T. ciliata in Xuan’en region were very rich. This might give rise to a higher probability of gene exchanges within the populations, which might help to effectively reduce the genetic differentiation.

5 Conclusions

We can generally conclude that the larger distribution area of T. ciliata results in the lower genetic diversity of the species, but the higher genetic diversity at the population level as a whole. The differences in the geographical distribution areas of T. ciliata can add to reproductive isolation. Furthermore, the geographical and environmental characteristics within smaller areas in each group coupled with the resource pressure from human activities have led to the unique clustering pattern. For example, terrain blockage, human interference, and frequent rainfall in the flowering period could bring the reduction of gene exchanges within the populations, resulting in lower genetic diversity within populations. Meanwhile, natural selection and genetic mutations may increase the genetic differentiation.
The key element of germplasm breeding of T. ciliata lies in the selection of families and plants with high genetic diversities within the different populations (Yang et al., 2017; Wu et al., 2019). The populations with the lowest genetic diversities, P14, P17 and P21, for example, might harbor higher potentials, so pursuing on-site protection together with ex-situ protection strategies is recommended (Yi et al., 2018). The selection of parents in crossbreeding, genetic relationships between individuals separated by geographical distances and the parent populations (or individuals) should all be taken into account (Yang et al., 2017), as well as the ecological and timber objectives, so as to maximize the preservation and utilization of the genetic diversity of T. ciliata.

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