Analysis of genetic diversity of ancient Ginkgo populations using SSR markers

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Analysis of genetic diversity of ancient Ginkgo populations using SSR markers Qi Zhoua,b, Kemin Mua, Zhouxian Nia, Xinhong Liub, Yingang Lib, Li-an Xua,* a b

Co-Innovation Center for Sustainable Forestry in Southern China, Nanjing Forestry University, 159 Longpan Road, Nanjing, 210037, China Zhejiang Academy of Forestry, 399 Liuhe Road, Hangzhou, 310023, China

A R T I C LE I N FO

A B S T R A C T

Keywords: Ginkgo biloba L. Refuge Genetic diversity Genetic structure SSR

Ginkgo biloba L., a famous relict plant, is the only surviving species of Ginkgopsida. To explore the genetic variation of geographic populations and possible refuges of Ginkgo during the glacial period, 216 samples from 6 ancient populations and 2 cultivated populations were analyzed using 22 simple sequence repeat (SSR) markers. A total of 231 alleles were detected at the 22 SSR loci, and the average expected heterozygosity (He) was 0.808, indicating a high level of genetic diversity. The STRUCTURE, phylogenetic tree and principal coordinate analysis (PCoA) results showed that the 8 populations could be divided into 2 groups, namely, the eastern group (TM, NJ and PZ) and southwestern group (PX, DY, MJ, FG and WC). The eastern and southwestern groups had 15 and 14 unique alleles, respectively. Among the populations, population TM from the east had the highest genetic diversity and allelic richness, and 9 rare alleles and 8 unique alleles were detected in this population. Although the genetic diversity of population WC from the southwest was lower than that of population TM, 8 rare alleles and 2 unique alleles were detected in WC. It was speculated that the areas of population TM in the east and population WC in the southwest were refuges during the glacial period. In addition, a total of 7 unique alleles were detected in the 2 cultivated populations from the east, suggesting that there may have been other refuge areas during the glacial period.

1. Introduction As a “living fossil”, Ginkgo biloba L. is a unique speciesin Ginkgopsida. Ginkgo not only is a very important medicinal plant but also has wood and ornamental uses. Furthermore, due to its early origin and strong vitality, Ginkgo is very valuable for scientific research on the origin and evolution of plant species. However, there is no conclusive evidence for or acknowledged conclusion about the origin of Ginkgo. Fossils of Ginkgo showed that the plant existed during the early Permian (270 million years ago; Zhou and Zheng, 2003). During the early Permian period, some early gymnosperms experienced a decline, and gymnosperms with strong adaptability, such as Ginkgoales and conifers, developed rapidly. Until the Jurassic period (190 million years ago), the Ginkgoales species were distributed almost globally, indicating a “golden age” of Ginkgopsida, and fossil evidence has shown that there were at least 16 genera in Ginkgoaceae at that time (Willis and McElwain, 2002). However, with the sharp climatic variations of the earth in the Late Cretaceous period (144 million years ago), the Ginkgopsida species began to decline, and angiosperms, which were

highly evolutionarily adaptable and widely adapted to the ecological environment, appeared. By the beginning of the Quaternary glaciation period, glacial movements had driven all of the Ginkgoales to extinction in North America and Europe (Zhou, 2003). Fortunately, due to special terrain characteristics, some places in China were little affected by glaciers and became unique refuges of Ginkgo. However, the number and locations of these refuges have not yet been confirmed. Investigations of the main Ginkgo resources and their habitats within the distribution area have shown that there were at least two possible refuge areas in China located in southwestern and eastern mountainous areas (Tang et al., 2012; Xiang and Xiang, 2000). Of these two places, the mountainous areas in southwestern China not only were among the 34 biodiversity hotspots in the world (Myers et al., 2000) but also contained several ancient populations of Ginkgo, which were still in a wild or semiwild state (Xiang et al., 2006, 2007). Mt. Tianmu in northern China contained many relict species of the Paleogene glaciation and had an ancient Ginkgo population (Xiang and Xiang, 2000). Variations among ancient populations from the two areas have been uncovered, including the concentrations of secondary metabolites in

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Corresponding author. E-mail addresses: [email protected] (Q. Zhou), [email protected] (K. Mu), [email protected] (Z. Ni), [email protected] (X. Liu), [email protected] (Y. Li), [email protected] (L.-a. Xu). https://doi.org/10.1016/j.indcrop.2019.111942 Received 8 August 2019; Received in revised form 30 October 2019; Accepted 4 November 2019 0926-6690/ © 2019 Elsevier B.V. All rights reserved.

Please cite this article as: Qi Zhou, et al., Industrial Crops & Products, https://doi.org/10.1016/j.indcrop.2019.111942

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2.3. Genotyping with SSR markers

leaves (Zhou et al., 2017). Moreover, molecular marker research conducted on the Ginkgo resources distributed in the two areas has provided some evidence for the existence of a refuge in the southwest. However, there are conflicting conclusions about the existence of refuges in the Mt. Tianmu area (Fan et al., 2004; Shen et al., 2005; Gong et al., 2008a, b). On the one hand, the molecular markers used in Ginkgo research on refuges, such as amplified fragment length polymorphisms (AFLPs; Gong et al., 2008a), random amplification polymorphic DNA (RAPD; Fan et al., 2004) and Inter simple sequence repeats (ISSRs; Ge et al., 2003), were dominant markers, which may have resulted in the loss of genetic information due to the inability of these markers to distinguish alleles. On the other hand, the materials used in these studies were unrepresentative, and the sample sizes of the individual studies were small (Gong et al., 2008a) and did not contain comprehensive genetic information. In contrast, as an efficient tool for population genetics studies (Ellis and Burke, 2007), simple sequence repeats (SSRs) are more consistent than RAPD, easier to use than AFLPs and more polymorphic than ISSRs and have been used in many species (Addisalem et al., 2016; Cortés et al., 2014; Ma et al., 2017; Shi et al., 2017). Several nuclear genomic and chloroplast SSR loci of Ginkgo were identified (Li et al., 2009; Xu et al., 2015; Yan et al., 2006, 2009; Zhou et al., 2016). However, only 14 nuclear genomic SSR markers and some ancient Ginkgo resources distributed in the two refuges were applied in population dynamics and gene flow studies, and the sample size varied greatly among populations (Zhao et al., 2016). There is still much genetic information about Ginkgo resources distributed in the two areas to be revealed. In this study, we surveyed Ginkgo resources distributed in the two potential refuges and collected ancient populations. Combined with two plantations, SSR markers were used to (i) understand the genetic diversity and relationships between populations in these two potential refuges and (ii) explore the possible origins and speculate on possible refuge areas of Ginkgo in China.

According to the polymorphism, stability and clarity of the amplifications, 22 SSR markers, including 8 expressed sequence tag (EST) SSR (E-SSR) and 14 genomic SSR (G-SSR) markers, were selected from 556 SSR markers developed by our laboratory (Table 2). PCR amplification for all markers was carried out using an ABI Veriti 96 PCR system (Thermo Fisher Scientific, MA, USA). The reaction mixtures of 10 μl contained 1 x buffer, 0.2 mM dNTPs, 2.5 mM MgCl2, 0.2 μM each SSR forward and reverse primer, 30 ng of genomic DNA and 1 U of Taq polymerase (Thermo Scientific). The PCR program involved an initial denaturation step of 5 min at 94℃, followed by 30 cycles at 94℃ for 30 s, the appropriate annealing temperature for 30 s, and 72℃ for 40 s and an extension cycle of 1 min at 72℃. The PCR products were separated using a 96-capillary 3730xl DNA Analyzer (Thermo Fisher Scientific, MA, USA). 2.4. Analysis of data For each marker, the genotyping results were analyzed using Peak Scanner v1.0 software (Thermo Fisher Scientific, MA, USA), and the bands with the same base size were represented by the same capital letter. The number of observed alleles (Na), the number of efficient alleles (Ne), the observed heterozygosity (Ho), the expected heterozygosity (He), Nei’s diversity index (H), the genetic differentiation index (Fst), gene flow (Nm) and adherence to Hardy-Weinberg equilibrium (assessed via a chi-square test) were determined using POPGENE version 1.32 software. The determination of the polymorphism information content (PIC) and the construction of phylogenetic trees based on the neighbor-joining method were carried out using PowerMarker version 3.25 software (Liu and Muse, 2005). With FSTAT version 2.9.3 software, allelic richness (AR) was analyzed. Analysis of molecular variance (AMOVA) and principal coordinate analysis (PCoA) were carried out using GenAlEx version 6 software (Peakall and Smouse, 2006). To estimate individual ancestry, we subjected eight sample sets (DY, MJ, FG, WC, PX, TM, NJ, and PZ) to Bayesian clustering analysis using STRUCTURE version 2.3.1 software (Evanno et al., 2005). For each value of K (number of potential ancestral populations, which ranged from 1 to 9 (number of populations + 1)), the genetic ancestry of each individual was estimated based on the admixture model; estimates were obtained with the Markov chain Monte Carlo (MCMC) method with 100,000 iterations followed by a burn-in period of 100,000 iterations. The best K values were identified based on the Evanno method (Evanno et al., 2005) implemented in STRUCTURE HARVESTER (Earl and VonHoldt, 2012). The results were plotted using CLUMPP (Jakobsson and Rosenberg, 2007) and DISTRUCT (Rosenberg, 2004).

2. Materials and methods 2.1. Plant material The potential refuge areas of Ginkgo in southwestern and eastern China were investigated. Five ancient populations were found in southwestern China (populations PX, DY, MJ, FG and WC), while only one ancient population was found in eastern China (population TM). Among these populations, the ratio of males to females were close to 1:1 only in populations FG and TM, and that in the other populations was 2:1∼6:1, suggesting a lack of male trees. Samples of the six populations were mainly collected from ancient trees more than 200 years old to ensure that the trees were indigenous. The distance between sampled trees was more than 50 m to reduce the probability of sampling trees that were closely related (except in small populations). To compare the genetic differences between ancient and cultivated populations, two cultivated populations (populations NJ and PZ) were collected from eastern China. Of the 2 plantations, population PZ mainly included seedlings 20–30 years old, and trees from population NJ were 20–50 years old. A total of 216 individuals were collected from the 6 ancient populations and 2 plantations. Young leaves were collected and desiccated by silica gel and stored at -80℃ for later use. The detailed information for each population is shown in Table 1 and Fig. 1.

3. Results 3.1. Genetic diversity A total of 231 alleles were obtained at 22 SSR loci based on 216 samples from six ancient and two cultivated populations (Fig. 2). The number of alleles per SSR locus varied from 5 to 20, with an average of 10.5 alleles per locus (Table 3). In general, the average Ne, He and PIC were 6.104, 0.808 and 0.781, respectively, indicating that the 216 samples contained high levels of genetic diversity. Among the 22 SSR loci, the E-SSR32 locus had the lowest level of genetic diversity, smallest Ne (2.386), lowest He (0.582) and lowest PIC (0.565). In contrast, the G-SSR38 locus showed the highest diversity, as this locus had the largest Ne (12.130), He (0.920) and PIC (0.912). However, all the frequencies of alleles at the 22 SSR loci significantly deviated from Hardy-Weinberg equilibrium (P < 0.05). In general, the genetic diversities of the six ancient and two cultivated populations showed little difference, and the populations ranked

2.2. DNA extraction Total genomic DNA was extracted using the hexadecyl trimentyl ammonium bromide (CTAB) method (Cota-Sánchez et al., 2006). The DNA concentrations were estimated with a NanoDrop-1000 spectrophotometer (Nano Drop Technologies, Wilmington, DE, USA) and were normalized to 30 ng/μl for polymerase chain reaction (PCR). 2

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Table 1 Accession data for the populations of Ginkgo. Population code

Southwest PX DY MJ FG WC East TM PZ NJ

Location

Longitude (E)

Latitude (N)

Altitude (m a.s.l.)

Sample size

Age (years)

Panxian, Guizhou Duyun, Guizhou Majiang, Guizhou Fenggang, Guizhou Wuchuan, Guizhou

104°32′ 107°23′ 107°31′ 107°45′ 108°1′

25°36′ 26°21′ 26°29′ 27°48′ 28°41′

1619 1054 1053 836 994

37 14 12 17 45

400-1000 300-1000 500-1000 200-1200 300-500

Mt. Tianmu, Zhejiang Pizhou, Jiangsu Nanjing, Jiangsu

119°26′ 117°35′ 118°79′

30°19′ 34°1′ 32°6′

481 22 13

43 24 24

300-1600 20-30 20-50

a.s.l.: above sea level.

from the southwest were 0.792 and 0.796, respectively (not listed), while those from the east were 0.779 and 0.788, respectively. Therefore, the ancient trees in southwestern China as a whole showed slightly more genetic diversity than those in eastern China. The genetic diversity of the two cultivated populations was intermediate among those of the eight populations and higher than that of populations MJ, FG and DY.

from highest to lowest in terms of genetic diversity as TM, WC, PX, NJ, PZ, MJ, FG, and DY. Within the eight populations, the He values were higher than the Ho values, suggesting a lack of heterozygotes (Table 4). Of the six populations, population TM showed the highest level of genetic diversity, with the largest Na (8.591), H (0.779), AR (6.679) and He (0.788), followed by population WC. In contrast, population DY showed the lowest genetic diversity, as DY had the smallest Na (5.591), H (0.674) and He (0.699), followed by population FG, which had the lowest AR (5.384). The genetic diversity of ancient trees from the southwest (populations WC, PX, FG, DY, and MJ) was also different from that of ancient trees from the east (population TM). The H and He of the ancient trees

3.2. Genetic variation and genetic structure The F-statistic (Fst) of the eight Ginkgo populations was 0.093, indicating that there was little genetic variation between the populations,

Fig. 1. Geographical distribution of the 8 populations of Ginkgo. Populations PX, DY, MJ, FG, WC, and TM are ancient populations, and populations NJ and PZ are cultivated populations. Codes for the populations are given in Table 1. 3

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origin of the two cultivated populations (NJ and PZ) was closely related to population TM. However, genetic differences were detected between the five ancient populations in the southwest. Of the five ancient populations, populations WC and PX had abundant genetic variations and genetic information with different origins. Most genetic information within populations DY and MJ had similar origins, which were also closely related to populations WC and P X . In addition, the genetic information within population FG was a mixture of the genetic information within populations WC and PX, suggesting that the formation of population FG was influenced by the two ancient populations. The phylogenetic tree based on the neighbor-joining method is shown in Fig. 4-B. The results showed that the 216 samples from 8 populations could be divided into 2 groups (Ⅰ and Ⅱ), which was consistent with the pattern from the population structure analysis. Most of the genetic information within populations TM, NJ, and PZ from the east was in group Ⅰ, while most of the genetic information within the five ancient populations from the northwest was in group Ⅱ. In addition, the results of PCoA further verified the phylogenetic tree and population structure analysis results (Fig. 4-C). In summary, the origins of the six ancient and two cultivated populations were obviously different according to genetic data, and these populations were divided into a southwestern group (PX, WC, DY, MJ, and FG) and an eastern group (TM, NJ, and PZ).

Table 2 Repeat motif, primer sequence, fragment size and Tm information for 22 microsatellite loci. Locus code

Repeat motif

Primer sequence (5′∼3′)

Fragment size (bp)

Tm (℃)

E-SSR32

(TA)11

196

57

E-SSR91

(AAC)8

297

57

E-SSR120

(CA)11

234

55

E-SSR202

(AG)14

267

55

E-SSR214

(AT)11

341

53

E-SSR354

(TG)11

295

55

E-SSR440

(AT)10

287

57

E-SSR538

(CT)11

103

55

G-SSR8

183

58

238

58

G-SSR38

(AC) 9ataagc (AT)9 (TG) 14(AG)9 (TG)10

TTCGCTGTAGCATTTGTG GCAGGTTGTATTTCGGAG ACCCTCCCAGAAAAAGTC AGGTTGGCAATGTTAGCA AAGTCATAAGCGACAGTG CCGTCTTTCAGATCAATA CCCTTGTTTCTCCATAAT TGCTCATATAGGTGCTCT TTTGGGAGTAGTGTGTTGT CTGGATTGCATTTGAAGTC GATGAAGTGTGAAGAGAATG AACTACGATGACGATGGA GGTTTTGGAAATGGAGTA TGTGGAAGAGAATTGGAT AGAGATTTTGCGACAGAGC GGTAGCAGTTGAACCGTTA CACACGCACATACACATACA ATTCCCTCCCCAATACTCTT

372

60

G-SSR101

(TC)10

160

55

G-SSR117

(CT)9

297

55

G-SSR151

202

53

G-SSR183

(TC) 11(AC)12 (ATAG)11

304

55

G-SSR246

(ATAG)9

362

55

G-SSR252

(CA)18

286

55

G-SSR258

(TA)11

225

57

G-SSR269

(TG)12

193

55

G-SSR279

(TG)12

202

55

G-SSR448

(TC)10

156

55

G-SSR578

(CA)11

307

58

G-SSR12

AGGGAAAAAGTGAAAGAGAGAG CTAGTCAAGGCGAGGTTAAAGA GGGGTTGGGAATGAGATG CTTAAATTGAAGGCCGGT AGTTGTTCACGGTTAGGA CCATTAGGGTTTAGGGAT TGGACTTATTTCTCACAC GATGACCTTCTACAACAG GACCATAGCCAATCATAA CTCTTTGCATCTCACTCA GGTTTTGTACTGGAGCATA GGATTGGTAATAACTTTGTC TGGTGCTTTGGATGATGA TGTTTTGCAGGAATAGGC ACACCTATTGATGAACCA TAACAAGACCTTTGCACA GACTTTTGGCACTATCGT GTCAATGGGAGACAGGTT AAGTGGTCACGCACAAGA GCATATGGGATCCAAGGT TTGATTTTTCTCTCCGTC CCTTTAGCACATTTCCAT GTTCAAGGTCCTCATAG TAGCCTCTTCTTTACTG TGTGTCTACTTGTCTCTCC AGGACTTACCCAATGAAC

3.3. Rare alleles and unique alleles During population expansion, low-frequency alleles are more likely to be lost than high-frequency alleles, which makes the former an important basis for population origin research. In general, origin populations contain more rare alleles and (or) unique alleles than normal populations. The frequencies of 231 alleles detected in 216 samples ranged from 0.0023 to 0.6319, with an average of 0.0952. The minimum allele frequencies of 22 SSR loci ranged from 0.0023 to 0.0370, with an average of 0.0144. To study the genetic variation between populations, rare alleles detected within two populations and unique alleles detected within only one population were analyzed (Fig. 5). Eighteen rare alleles and seventeen unique alleles were detected at 22 SSR loci. Eight SSR loci had rare alleles, and G-SSR 279, GSSR 183 and G-SSR 354 contained more rare alleles than the other loci. Unique alleles were distributed among 10 SSR loci, and 4 and 3 alleles were detected at the E-SSR 32 and G-SSR 8 loci, respectively (not listed). Except for population DY, the populations contained rare alleles, and populations WC (8) and TM (9) contained more rare alleles than the other populations (3–4). Four populations (WC, TM, PZ, and NJ) had unique alleles, and population TM had the most unique alleles (8), followed by populations NJ (6), WC (2) and PZ (1). Notably, although population WC from the southwest had few unique alleles, the five populations from the southwest had 14 alleles that were not detected within populations from the east (Table 6), suggesting that ancient populations from the southwest contained unique genetic information.

which might have been due to high average gene flow between populations (Nm = 2.427, Table 3). The results of the AMOVA revealed significant genetic differences between regions (southwest and east), between populations within regions and within populations (Table 5), but the variation was concentrated within the populations. In total, 3% of the variation was between geographic regions (southwest and east, P = 0.001), and 10% and 87% of the variation was between populations within regions and within populations, respectively (P = 0.001). To analyze the genetic structure of Ginkgo populations, the coancestry relations of the populations were analyzed based on a Bayesian clustering model. According to the ΔK results, the optimal K value was 2, when the ΔK was at a maximum (Fig. 3). When K was 2, the genetic information of 216 samples from the six ancient populations and two cultivated populations came from two different ancestral populations (Fig. 4-A). At K = 2, most of the genetic information for the five ancient populations (PX, DY, MJ, FG, and WC) in southwestern China came from the same ancestral population (green), and the genetic information for TM and the two cultivated populations (NJ and PZ) in eastern China mainly came from another ancestral population (red). At K = 3 and 4, most genetic information for the three populations from the east still came from the same ancestral population, suggesting that the

4. Discussion 4.1. Genetic diversity and genetic structure As an important index used to measure a species’ ability to adapt to changing environments, genetic diversity is influenced by many factors, such as selection, genetic drift, migration, and breeding system. Studying the genetic diversity of Ginkgo populations provides a theoretical reference for the protection and utilization of Ginkgo resources. The genetic diversity of Ginkgo populations was analyzed using dominant markers (RAPD and AFLPs), and the resulting genetic diversity index (H) values were 0.3159 and 0.191, respectively (Fan et al., 2004; Gong et al., 2008a). In this study, the average He of the 22 SSR loci was 0.808, which indicated a high level of genetic diversity in Ginkgo. On 4

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Fig. 2. Maps of PCR product separation for E-SSR 32 loci. The first four individuals (A to D) were from population WC, and the last four individuals (E to H) were from population TM.

the one hand, as codominant markers, SSR markers are more polymorphic than dominant markers; on the other hand, the samples used in our study were distributed in two potential refuges and contained more diversity than other populations in China. Moreover, 14 SSR markers were also applied in genetic studies of Ginkgo populations based on a previous report (Zhao et al., 2016), and the He (0.710) was lower than that in this study, which may be due to differences in markers and samples. Compared to the results for other gymnosperms obtained using SSR markers, Ginkgo has a higher level of genetic diversity than Cupressus funebris (He = 0.520; Yang et al., 2016), Abies fabri (He = 0.739; Wang et al., 2014), and Taxus chinensis (He = 0.261; Cheng et al., 2015), which are relict species. However, the diversity of Ginkgo was lower than that of Pinus densiflora (Iwaizumi et al., 2007), which may be because Pinus densiflora is a widespread species. Among the 8 studied populations (6 ancient populations and 2 cultivated populations), population TM from the east had the highest level of genetic diversity (H = 0.779, He = 0.788), and the genetic diversity of the 2 cultivated populations was intermediate among those of the 8 populations. The ancient populations DY, MJ and FG had lower levels of genetic diversity than the two cultivated populations, which may have been due mainly to human influences (female trees are mainly reserved for fruit production, and most male trees are removed). In general, the genetic variation in perennial cross-pollinated woody plants is small between populations, while that within populations is relatively high. In our study, the genetic variation between Ginkgo populations was low (Fst = 0.093), which indicated that 90.7% of the genetic variation was within populations, and only 9.3% of the genetic variation was between populations. Fan et al. (2004) analyzed 9 Ginkgo populations in China using RAPD markers, and the results were similar

Table 3 Polymorphism information for 22 microsatellite loci. Locus

Na

Ne

He

PIC

Fst

Nm

HWE

E-SSR32 E-SSR91 E-SSR120 E-SSR202 E-SSR214 E-SSR354 E-SSR440 E-SSR538 G-SSR8 G-SSR12 G-SSR38 G-SSR101 G-SSR117 G-SSR151 G-SSR183 G-SSR246 G-SSR252 G-SSR258 G-SSR269 G-SSR279 G-SSR448 G-SSR578 Mean

12 6 11 14 6 14 9 20 18 11 18 6 6 7 11 5 6 8 8 17 9 9 10.5

2.386 3.525 6.856 6.862 3.450 5.149 4.298 11.423 9.326 5.455 12.130 3.859 4.971 5.106 4.578 3.359 4.325 7.104 6.044 8.857 7.642 7.592 6.104

0.582 0.718 0.856 0.856 0.712 0.808 0.769 0.915 0.895 0.819 0.920 0.743 0.801 0.806 0.783 0.704 0.771 0.861 0.837 0.889 0.871 0.870 0.808

0.565 0.669 0.839 0.838 0.661 0.780 0.728 0.906 0.885 0.795 0.912 0.670 0.769 0.777 0.751 0.643 0.733 0.843 0.813 0.877 0.855 0.854 0.781

0.076 0.154 0.094 0.106 0.089 0.086 0.072 0.089 0.073 0.128 0.064 0.166 0.176 0.062 0.086 0.096 0.097 0.054 0.116 0.055 0.067 0.074 0.093

3.055 1.377 2.407 2.118 2.573 2.675 3.217 2.573 3.173 1.707 3.672 1.257 1.172 3.760 2.656 2.356 2.319 4.388 1.905 4.304 3.500 3.136 2.427

** * ** ** ** ** ** ** ** ** ** ** ** ** ** ** ** ** ** ** ** ** –

Na: number of alleles, Ne: effective number of alleles, He: expected heterozygosity, PIC: polymorphism information content, Fst: F-statistic, Nm: gene flow, HWE: Chi-square test for Hardy-Weinberg equilibrium. * significant deviation (P < 0.05). ** very significant deviation (P < 0.01).

5

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eastern region, the cultivated populations NJ and PZ had genetic correlations with the ancient population (TM). However, the 7 unique alleles detected in the 2 cultivated populations indicated that the origin of the 2 populations not only was closely related to population TM but also may have had other sources. Of the 5 ancient populations in the southwestern group, DY, MJ and FG had few existing trees, and the genetic information for DY, MJ and FG was closely related to that for WC and PX, suggesting that the origin of populations DY, MJ and FG was related to populations WC and P X .

Table 4 Mean values of the genetic diversity statistics for 22 microsatellite loci in 8 populations.

Southwest

East

PX DY MJ FG WC TM NJ PZ

Na

Ne

H

AR

Ho

He

6.364 5.591 6.727 5.909 8.227 8.591 7.273 6.727

4.545 3.853 4.530 3.461 5.284 5.224 4.620 4.338

0.744 0.674 0.727 0.682 0.766 0.779 0.735 0.734

5.494 5.435 6.227 5.384 6.546 6.679 6.343 5.914

0.724 0.640 0.644 0.562 0.640 0.650 0.604 0.650

0.754 0.699 0.758 0.703 0.774 0.788 0.751 0.750

4.2. Refuge Mt. Tianmu, located in eastern China, has intact native vegetation, a typical forest community and a relatively complete forest community structure (Xiang and Xiang, 2000). In addition to Ginkgo, there are tertiary relic species, such as Pseudolarix amabilis, Torreya grandis, Cunninghamia lanceolata, and Nyssa sinensis, in this region, which indicates that this region may have acted as a refuge (Lou et al., 2004). Generally, an important feature of refuge populations is that these populations have a higher level of genetic diversity than other populations (Comes and kadereit, 1998). In addition, a high allele abundance and large number of rare alleles may support the survival of species in a refuge because alleles with a low frequency are easily lost during population expansion after an ice age. Shen et al. (2005) found only one haplotype in the TM population, while Gong et al. (2008b) detected a high level of genetic diversity in this population when using the same chloroplast region. In this study, ancient population TM, located on Mt. Tianmu, had the highest H (0.779) and AR (6.679) and the most rare alleles (9) and unique alleles (8), which accounted for 50% and 47% of the total number of rare and unique alleles, respectively. Gong et al. (2008a) also provided some molecular evidence for the existence of a Ginkgo refuge in the West Tianmu Mountains. Therefore, it was verified that the Mt. Tianmu area in eastern China may have been part of the refuge area of Ginkgo during the Quaternary glacial period. Southwest China is located on the southeastern Qinghai-Tibet Plateau and Yunnan-Kweichow Plateau, and the plateaus form a natural barrier, effectively slowing down the impact of the Siberian cold current on this region during the ice age. Due to its stable environment and diverse landforms, this region had the richest biodiversity in China. In addition to Ginkgo, which grew in a wild state in southwestern China, Mt. Dalou in Guizhou Province, which runs through southwestern China, had many rare relict species, such as Cathaya argyrophylla and Glyptostrobus pensilis (Tang et al., 2012). In our study, ancient population WC was located in the Mt. Dalou area. The H (0.766) and AR (6.546) ranked second (lower than those of population TM), and WC had 8 rare alleles and 2 unique alleles. In a previous investigation, Xiang et al. (2006) also found a typical wild Ginkgo forest in this region and speculated that a mixed deciduous broad-leaved forest dominated by Ginkgo existed there a hundred years ago, which might have been cut down by humans. Moreover, a large number of haplotypes and high genetic diversity were found in population WC, which indicated that the center of genetic diversity of Ginkgo was mainly in southwestern China (Gong et al., 2008b). In conclusion, the area of population WC is believed to have acted as a refuge during the recent ice age. In addition, Shen et al. (2005) detected some haplotypes and 1 unique haplotype in population PX and believed that this area was a potential refuge of Ginkgo. Gong et al. (2008b) also detected high genetic diversity for population P X . In our study, the AR (5.494) of population PX was not high, and unique alleles were not detected in this population, which was not enough to justify the area as a refuge. Populations NJ and PZ, as cultivated populations, had medium levels of genetic diversity and AR among the 8 populations, with 6 and 1 unique alleles, respectively, accounting for 41% of the total. China has built many artificial forests in recent decades, and the sources of Ginkgo plantations are various and unknown. The samples in this study came from the two recognized potential refuge regions in China, and it can be

H: Nei’s diversity index, AR: allelic richness, Ho: observed heterozygosity. Table 5 Analysis of molecular variance (AMOVA) in 216 individuals from 8 populations. Source of variance

Variance component

Percentage of total

P-value

Between regions Between populations within regions Within populations Total

0.576 2.235

3% 10%

0.001 0.001

19.155 21.965

87% 100%

0.001

Fig. 3. Relationships between the number of clusters (K) and the corresponding ΔK statistics calculated according to ΔK (Evanno et al., 2005) based on STRUCTURE analysis.

to those in our study (Fst = 0.110). However, Gong et al. (2008a) studied the genetic variation in 92 samples from 13 Ginkgo populations in China using AFLP markers and detected more genetic variation within populations than our study did (Fst = 0.288), mainly due to a difference in the markers used and a lack of samples within populations. In addition, gene flow greatly reduces the genetic variation between populations. The average Nm in this study was 2.427, which was high enough to resist the effect of genetic drift and reduce the genetic variation between populations. Cluster analysis was performed with STRUCTURE software on all individuals based on a Bayesian model, and the determination of the optimal K value was the most critical part of the analysis. Evanno et al. (2005) showed that it was difficult to obtain the correct K value with Ln P (D) and that the Δ K value was more reliable. In this study, the K value was 2 when Δ K was the highest, suggesting that the 8 populations were genetically divided into two groups (the eastern group, containing populations TM, NJ, and PZ, and the southwestern group, containing populations PX, DY, MJ, FG, and WC). The phylogenetic tree and PCoA results further verified the clustering. Of the 3 populations in the

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Fig. 4. (A) Population genetic structure based on the Bayesian clustering model among 216 samples at K = 2-4. B) Neighbor-joining tree based on Nei’s genetic distances. C) Score plot generated using PCoA. All the results showed that the samples could be divided into two clusters. Table 6 The frequency of 14 alleles in each of 5 populations from the southwest. Allele

PX

DY

MJ

FG

WC

E-SSR 32-C E-SSR 202-A E-SSR 440-H E-SSR 538-M E-SSR 538-T G-SSR 8-E G-SSR 8-F G-SSR 12-G G-SSR 101-A G-SSR 183-A G-SSR 279-C G-SSR 279-F G-SSR 279-G G-SSR 279-J

/ / / / / 0.1486 0.0811 / 0.0135 / / 0.1216 / 0.027

/ / / / 0.0357 0.2143 0.1786 / / / / 0.1786 0.0714 /

/ / 0.0417 0.125 0.125 0.25 / / 0.125 0.0417 0.0833 0.1667 / /

0.0294 / / 0.0294 0.5294 0.0882 0.0294 / 0.0294 / 0.0294 0.1176 0.0294 /

0.0222 0.0111 0.0222 / 0.2222 0.0111 / 0.0111 0.0778 0.0111 / 0.0111 0.0111 0.1444

/: not detected in the population.

Fig. 5. Number of rare and unique alleles within 8 Ginkgo populations.

4.3. Disturbance status of ancient populations inferred from the unique alleles detected within the 2 cultivated populations that there were other refuge areas in addition to the southwestern and eastern areas. However, the specific number and location of these refuges and whether they were artificially damaged remain to be further studied.

Ginkgo is an important species with economic and medicinal value, and one of its important uses is the extraction of secondary metabolites contained in leaves. In general, abundant germplasm resources are an important foundation for the breeding success and guaranteed continuation of this species. The ancient Ginkgo resources distributed in the two refuges not only differed significantly in the concentration of the secondary metabolites (Zhou et al., 2017) but also had a high level of 7

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genetic diversity and possessed rare and unique alleles. Hence, these trees are important genetic resources that can be used in the process of tree breeding for secondary metabolite products. However, except for populations FG and TM, the populations showed different degrees of imbalance in the proportions of male and female trees, and the number of female trees was 2∼6 times that of male trees within each population. There were fewer than 20 ancient trees in populations DY, FG and MJ, and the number of ancient trees in these populations was much lower than that in the other ancient populations. In addition, all the alleles at the 22 SSR loci showed significant deviation from HardyWeinberg equilibrium, and all ancient populations showed homozygote excess. Therefore, the ancient populations in the southwest and east were influenced by human activities and natural factors, and more attention should be paid to the protection of ancient Ginkgo trees in these two places.

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5. Conclusion The findings of this study confirmed that ancient Ginkgo populations distributed in two potential refuge areas (southwest and east) contain a high level of genetic diversity. Genetic variation was also detected between samples from the two places, and the origin of the populations in the southwest was obviously different from that of the populations in the east. Population TM in the east and population WC in the southwest were two separate refuges during the ice age, and there may have been other refuges in China. In addition, the ancient populations have been influenced by human activities and natural factors and should be protected further. This research will provide not only molecular evidence for the study of Ginkgo refuges but also theoretical guidance for the development and utilization of ancient trees. Author contributions LX, QZ and XL conceptualized the study. YL, ZN and QZ contributed to the investigation. QZ and KM were in charge of data curation. QZ wrote the original draft, and LX reviewed. Declaration of Competing Interest The authors declare that they have no conflicts of interest. Acknowledgements This study was supported by the Special Fund for Forest Scientific Research in the Public Welfare (201404312; 201504105) and the Priority Academic Program Development of Jiangsu Higher Education Institutions (PAPD). References Addisalem, A.B., Bongers, F., Kassahun, T., Smulders, M.J.M., 2016. Genetic diversity and differentiation of the frankincense tree (Boswellia papyrifera (Del.) Hochst) across Ethiopia and implications for its conservation. For. Ecol. Manage. 360, 253–260. https://doi.org/10.1016/j.foreco.2015.10.038. Cheng, B.B., Zheng, Y.Q., Sun, Q.W., 2015. Genetic diversity and population structure of Taxus cuspidata in the Changbai Mountains assessed by chloroplast DNA sequences and microsatellite markers. Biochem. Syst. Ecol. 63, 157–164. https://doi.org/10. 1016/j.bse.2015.10.009. Comes, H.P., Kadereit, J.W., 1998. The effect of Quaternary climatic changes on plant distribution and evolution. Trends Plant Sci. 3 (11), 432–438. https://doi.org/10. 1016/S1360-1385(98)01327-2. Cortés, A.J., Waeber, S., Lexer, C., Sedlacek, J., Wheeler, J.A., Kleunen, M.V., Bossdorf, O., Hoch, G., Rixen, C., Wipf, S., Karrenverg, S., 2014. Small-scale patterns in snowmelt timing affect gene flow and the distribution of genetic diversity in the alpine dwarf shrub Salix herbacea. Heredity 113 (3), 233–239. https://doi.org/10. 1038/hdy.2014.19. Cota-Sánchez, J.H., Remarchuk, K., Ubayasena, K., 2006. Ready-to-use DNA extracted with a CTAB method adapted for herbarium specimens and mucilaginous plant tissue. Plant Mol. Biol. Rep. 24 (2), 161. https://doi.org/10.1007/BF02914055. Earl, D.A., VonHoldt, B.M., 2012. STRUCTURE HARVESTER: a website and program for

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