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Article

Spatial Pattern of Genetic Diversity and Demographic History Revealed by Population Genomic Analysis: Resilience to Climate Fluctuations of Acer truncatum Bunge

by
Jia Liao
1,†,
Xuedan Yu
1,†,
Yuxia Wu
1,
Shunxiang Pei
2,
Xuebing Xin
2,
Xinhe Xia
1,
Shan Mao
1,
Xinyue Pan
1,
Yongqi Zheng
1 and
Chuanhong Zhang
1,*
1
State Key Laboratory of Tree Genetics and Breeding, Research Institute of Forestry, Chinese Academy of Forestry, Beijing 100091, China
2
Beijing Jiulong Mountain National Long-Term Scientific Research Base of Warm Temperate Forests, Experimental Center of Forestry in North China, Chinese Academy of Forestry, Beijing 102300, China
*
Author to whom correspondence should be addressed.
†
These authors contributed equally to this work.
Forests 2024, 15(4), 639; https://doi.org/10.3390/f15040639
Submission received: 26 February 2024 / Revised: 20 March 2024 / Accepted: 29 March 2024 / Published: 31 March 2024
(This article belongs to the Section Forest Biodiversity)
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Abstract

:
Whole genome sequencing techniques are capable of providing insights into plant genetic adaptation to climate oscillations. Acer truncatum Bunge is a new resource tree for food with ornamental, timber and medicinal value. However, it has been listed as a near-threatened species because of the decreasing number of natural populations. In order to develop conservation strategies and sustainable innovative utilization for genetic resources, spatial pattern of genetic diversity and demographic history of A. truncatum from 13 natural populations, which cover the entire range, were analyzed by 9,086,353 single nucleotide polymorphisms (SNPs) through whole genome resequencing. The genetic diversity of natural populations was high (He = 0.289, I = 0.449), and genetic variations mainly resided within populations (82.47%) by AMOVA analysis. Cluster analysis showed that 13 natural populations mainly originated from three common gene pools. Therefore, it is recommended that the natural populations (LBGM, BTM, WLS and DQT) with high genetic diversity in different groups were given priority for in situ conservation and the genetic resources from these populations were collected for ex situ conservation. The effective population size of A. truncatum experienced two large-scale sharp contractions and currently decreased to its bottom in history. Nonetheless, A. truncatum could have expanded its effective population size to its historical peak after the last glacial period, indicating that it is highly resilient to fluctuations of temperature and humidity.

1. Introduction

As functional units of heredity, plant genetic resources are genetic materials of actual or potential value [1] and are important basic materials for genetic breeding [2]. Better understanding of the genetic diversity and spatial pattern of a species is useful for evaluating its genetic resources and provides a theoretical basis for development of conservation strategies and sustainable innovative utilization of genetic resources. Global climate oscillations and geological events have a crucial impact on the distribution pattern of species, further driving genetic differentiation and shaping current spatial patterns [3,4,5,6]. Many paleo-species disappeared during and following the Pliocene (5–1.7 Million years ago) as a result of climatic deterioration. Plants in central Europe had little opportunity to migrate southward due to the east–west structure of the mountains. In contrast, vast areas in China and wide-open plains of eastern Asia offered plants the opportunity to retreat before the advancing ice sheets [7]. During the Quaternary glaciation, extreme low temperature forced some species to survive in some refugia [8,9], while sheltered plants could expand and resettled under more favorable conditions during the inter-glacial or post-glacial warming. Ginkgo biloba L. survived in three refugia located in eastern, southern and southwestern China during the glacial period and expanded towards the northern regions during the post-glacial periods [10]. Loropetalum chinense var. rubrum Yieh contracted within the refuge in Nanling of China during the last glacial maximum and then expanded northward [11]. Therefore, the current distribution pattern of species does not represent their historical distribution. Inferring the demographic history of species based on genetic information can provide insights into important historical events, including population bottlenecks, expansions and contractions. The unique evolutionary history of each species affects the level and distribution of genetic diversity [12,13]. Thus, understanding the demographic history of species and exploring the mechanisms of the spatial patterns of genetic diversity are essential to the development of conservation strategies for plants’ genetic resources.
Acer truncatum Bunge, a deciduous tree of the genus Acer in Sapindaceae, is widely distributed in northern China, as well as in Russia, Japan and Korea [7,14]. A. truncatum is not only of ornamental value but also of timber and medicinal value. With its beautiful crown shape and autumn foliage color, it is an excellent landscape species suitable for use as a shade and street tree [15]. The wood of A. truncatum is of good quality and can be used in construction, furniture and sculpture, etc., and its bark fiber can also be used in papermaking and replacing cotton [16,17]. The leaves are rich in flavonoids, chlorogenic acid, vitamin E and tannins [18,19,20] and the bark contains anti-tumor active substances such as catechin, procyanidin B2/B3, and procyanidin C1/C2 [21]. Furthermore, the seed of A. truncatum contains 5%–6% nervonic acid [22], which is utilized to treat various brain diseases, such as Zellweger syndrome, Adrenoleukodystrophy and Alzheimer [23,24,25,26]. The discovery of nervonic acid in A. truncatum was regarded as an epoch-making outstanding achievement in the field of human brain medicine.
A. truncatum has been planted on a large scale as an economic tree species since 1970 and was approved as a new resource for food by the National Ministry of Health in 2011 (http://www.nhc.gov.cn/sps/s7891/201103/cffd9def6007444ea271189c18063b54.shtml, access on 18 March 2024). In 2020, A. truncatum was listed as an important species in the National Reserve Forest Project for development and utilization. At present, nearly 80 institutes have carried out research on A. truncatum, including cultivation, breeding and active substance extraction [27]. A. truncatum is a national treasure species in China, which is highly favored by the market, with increasing demand and expanding planting bases. However, the natural populations of A. truncatum have been seriously threatened due to anthropogenic interference and habitat degradation, and it has been listed as a near-threatened species in China Species Red List [28]. Recent studies reported the genetic diversity of A. truncatum is high. Qiao et al. [29] revealed a high genetic diversity in 15 populations of A. truncatum (H = 0.252, I = 0.394) from eight provinces, using 240 sequence-related amplified polymorphism (SRAP) markers. The study of 250 individuals in A. truncatum from nine different regions using 11 simple sequence repeat (SSR) markers revealed a high genetic diversity of population (He = 0.719, I = 2.05) [30]. However, as one of the Acer species distributed in the northern margin, it is unclear that how A. truncatum has responded to climate oscillations through genetic diversity and demographic history of natural populations over its long evolutionary history.
Single nucleotide polymorphism (SNP) markers developed through whole genome re-sequencing have abundant loci and present a high level of genetic stability [31,32,33], so they are suitable to study population genetics [34]. Meanwhile, the first genome assembly of A. truncatum was in 2020, with 13 chromosomes and a genome size of 633.28 Mb [35] to provide a basis for studying the population genetic structure of A. truncatum. Consequently, the spatial pattern of genetic diversity and demographic history of A. truncatum were analyzed by the explored SNP using whole genome re-sequencing to provide a theoretical basis for developing conservation strategies and exploiting excellent germplasm and innovative utilization of germplasm.

2. Materials and Methods

2.1. Sampling Collection

A total of 140 individuals from 13 natural populations were collected across the entire distribution range at the longitude of 106°17′34″–122°45′44″ and the latitude of 34°20′17″–45°12′54″ of A. truncatum from six provinces (Liaoning, Hebei, Henan, Shanxi, Shaanxi and Gansu), a municipality (Beijing) and an autonomous region (Inner Mongolia) in China (Figure 1). An overview of the collected A. truncatum individuals in Figure 2.
To understand how many individuals would be appropriate to be used to capture the majority of genetic diversity for one population by SNP marker, 20 individuals from WDT were used for sampling strategy.
According to the results of sampling strategy, 130 individuals from 13 populations with ten individuals for each population were for genetic diversity. The distance among the individuals was more than 50 m, and the longitude, latitude and altitude of the collection sites were recorded (Table 1). The leaf tissues of each individual were dried with silica gel and then stored in the refrigerator at −80 °C.

2.2. Whole Genome Sequencing

Total genomic DNA was extracted from 25 mg leaf tissues of each individual by the standard Cetyl Trimethyl Ammonium Bromide (CTAB) method [36]. DNA quality was checked by 1% agarose gel electrophoresis. DNA quantity was measured by the Qubit Fluorometer. DNA fragments were selected to construct libraries for Illumina by fragment end reparation, dual-index paired-end adapter ligation, PCR amplification, and target fragment selection. Then, re-sequencing was carried out on a HiSeqTM 2500 high-throughput platform by a commercial service (Biomarker Technologies, Beijing, China).

2.3. SNP Calling and Quality Filtering

Raw image data files were converted into Raw reads by base calling and stored in FASTQ (fq) file format. The method of fq data was filtered to filter the low-quality data and obtain high-quality data with reference to Jing et al. [37]. Clean reads were mapped to the A. truncatum reference genome [35] using bwa-meme [38]. SNP mutation detection and annotation were conducted based on the alignment results using GATK [39].
Dataset I was obtained by mapping sequences with the reference genome. Based on dataset I, dataset II was obtained by removing a missing rate > 0.2, integrity < 0.8, and minor allele frequency (MAF) < 0.05 for sampling strategy, genetic diversity and linkage disequilibrium (LD) decay. The sequencing information of the percentage of bases with mass values greater than or equal to 30 in the total number of bases (Q30), the percentage of G and C types of bases in the total base (CG) and the SNP ratio of base conversion to base transversion type (Ti/Tv) were calculated based on dataset II. Based on dataset II, Dataset III was obtained by filtering significant deviation (p < 10−4) from Hardy-Weinberg equilibrium (HWE) for gene flow, analysis of molecular variance (AMOVA), divergence times, demographic history and Mantel test. Based on dataset III, dataset IV was obtained by filtering linkage sites (r2 < 0.2) for admixture, principal component analysis (PCA) and phylogenetic tree.

2.4. Sampling Strategy for One Population

Through computer simulation, different sample sizes (3, 6, 9, 12, 15, and 18) were randomly selected from 20 individuals in WDT and each sample size was simulated 10 times. The parameters of genetic diversity of different sample sizes and the total sample size (20) were determined using the Perl scripts in R [40]. The parameters included expected heterozygosity (He), Shannon’s index (I), polymorphic index content (PIC) and minor allele frequency (MAF), as well as the mean and standard deviation of 10 times. The values of genetic diversity parameters of different sample sizes were calculated separately as a percentage of the values of genetic diversity parameters for the total sample size and then fitting curves with the sample size were analyzed.

2.5. Genetic Diversity and Linkage Disequilibrium (LD) Decay

Genetic diversity parameters of 13 populations with 10 individuals of each population were calculated by Perl scripts in R, such as the number of observed alleles (Na), effective number of alleles (Ne), observed heterozygosity (Ho), expected heterozygosity (He), Nei’s diversity index (Nei), polymorphic index content (PIC) and Shannon’s index (I). Tajima’s D and genetic differentiation coefficient (Fst) were determined by VCF tools v0.1.15 [41]. He in relation with latitude was calculated by SPSS 26 [42]. Mantel test was analyzed by Mega X [43]. The LD was calculated by PopLD decay (v3.41) [44] between pairs of SNP sites within 1000 kb on the same chromosome.

2.6. Genetic Structure Analysis

The genetic structure of 13 populations in A. truncatum was analyzed using Admixture v1.22 [45]. The number of groups (K value) was preset to be 1–10 for clustering. The clustering results are cross validated, and the optimal number of gene pools is determined according to the valley value of the cross validation error rate. Use the Pophelper package in R to generate a Q matrix stack diagram for each K value (http://royfrancis.github.io/pophelper, accessed on 18 March 2024). PCA was carried out by the smart pca program in EIGENSOFT v6.0 [46]. The maximum-likelihood (ML) phylogenetic tree was analyzed by Iqtree 2.2.0 [47] and Acer griseum (Franch.) Pax (XS04) was taken as an outgroup. The phylogenetic tree was recorded and modified by ITOL (https://itol.embl.de/login.cgi, accessed on 18 March 2024).
AMOVA and inbreeding coefficient (Fis) were calculated by Arlequin 3.5 [48]. The migration and splits among populations were determined by Treemix v1.12 [49], and gene flow was calculated according to Fst [50] as follows:
Nm = (1 − Fst)/4Fst

2.7. Inference of Demographic History

The divergence time of natural populations in A. truncatum was estimated by MCMCTREE in PAML v4.8 [51]. The fossil-calibrated divergence time between A. griseum and A. truncatum was collected from TimeTree (http://www.timetree.org/, accessed on 18 March 2024). The demographic history was inferred by SMC++ v1.12.1 [52] with the neutral mutation value of Acer yangbiense Y. S. Chen & Q.E. Yang as a reference [53].

3. Results

3.1. Identification and Characterization of SNPs

A total of 997.74 Gbp of high-quality clean data from 130 individuals in 13 natural populations of A. truncatum and one individual of A. griseum were identified, with an average Q30 of 90.26% and an average GC content of 36.63% (Table 2). The average alignment rate of the individuals to the reference genome was 96.38%, with an average sequencing depth was 10× and the average genome coverage was 90.03%. A total of 9,086,353 SNPs (dataset I) and 3,129,131 indels were detected in 130 individuals. The number of SNP base transitions was 1.78 times higher than the number of SNP base transversions, indicating that most of the SNPs were of the base transition type. After filtering the different parameters, a total of 1,751,584 SNPs were obtained for dataset II, 676, 68 SNPs for dataset III and 115,622 SNPs for dataset IV.

3.2. Sampling Strategy for Analysis of Genetic Diversity of Population

A total of 154.34 G of clean data were obtained from 20 individuals in WDT, with a Q30 of 90.33% and a GC content of 36.63% (Table 2). The average alignment rate of the individuals to the reference genome was 95.20%, and a total of 15,686,473 SNPs and 35,666,813 InDels were detected.
The genetic diversity parameters of each sample population increased with the increase of sample size, and the standard deviation decreased with the increase of sample size (Table S1). The percentage of genetic diversity index values (He, I, MAF and PIC) accounting for the total genetic diversity parameter values was analyzed by fitted curve analysis. The R2 was high, as seen by the values of 0.998, 0.999, 0.997 and 0.999, respectively. The inverse function of He was as follows:
Y = 103.193 − 62.486/x
The S function of I was as follows:
Y = e4.655 − 0.984/x
The cubic function of MAF was as follows:
Y = 82.790 + 3.682 × x − 0.278 × x2 + 0.007 × x3
The inverse function of PIC was as follows:
Y = 103.635 − 75.218/x
When He accounted for 95% of the total genetic diversity in each population, the fit curves showed that the sample size was eight. When I accounted for 95% of the total genetic diversity in each population, the fit curves showed that the sample size was ten. When MAF accounted for 95% of the total genetic diversity in each population, the fit curves showed sample size was five. When PIC accounted for 95% of the total genetic diversity in each population, the fit curves showed that the sample sizes were nine (Figure 3). Therefore, we select ten individuals in each population to analyze genetic diversity and genetic structure.

3.3. Genetic Diversity of Populations

Different populations presented different levels of genetic diversity (Table 3). The range of Na and Ne were 1.348 (TSX)–1.717 (ZW) and 1.179 (TSX)–1.321 (ZW), respectively. The range of Ho and He were 0.243 (PQ)–0.329 (LBGM) and 0.255 (SSS and PQ)–0.336 (LBGM), respectively. The range of PIC and I were 0.212 (SSS and PQ)–0.270 (LBGM) and 0.407 (SSS and PQ)–0.506 (LBGM), respectively. The average number of Nei ranged from 0.269 to 0.356, with an average value of 0.305. Remarkably, He of each population was higher than Ho, which resulted in a positive inbreeding coefficient value (Fis = 0.013), indicating that there may be heterozygosity deficiency within populations. Ranking by He is as follows: LBGM > BTM > XLM > TSX > WLS > ZTS > ZW > JY > XLS > DQT > WDT > PQ > SSS. Except for JY, XLS, and ZW, the values of Tajima’s D of other populations were positive, which reflected that most of them may have a large number of medium-frequency alleles and have experienced bottleneck events and/or balanced selection.
LD decay is crucial to forward genetics studies in plant. The LD values reached half of maximum average r2 at a minimum of 261 kb in TSX and a maximum of more than 1000 kb in ZW (Figure S1). The order of LD values in 13 natural populations is as follows: ZW > ZTS > SSS > WLS > PQ > DQT > BTM > XLS > WDT >JY > XLM > LBGM > TSX. A binomial fit of He with latitude indicated that the genetic diversity of populations did not show a significant decrease with the increase of latitude (Figure S2). However, the genetic diversity of populations in the subtropical zone was higher than that of populations in the middle temperate zone.

3.4. Genetic Structure and Gene Flow

Admixture analysis showed that when K = 3, the cross validation error was the lowest (Figure 4a), indicating that 13 natural populations originated from three common gene pools. Group I (red color) consisted of BTM and TSX in the subtropical zone. Group II (green color) consisted of WDT, DQT and SSS in the middle temperate zone, and PQ, WLS, XLS, JY and ZTS in the warm temperate zone (Figure 4b). Group III (blue color) consisted of LBGM and XLM in the warm temperate zone, and ZW in the middle temperate zone. The genetic components of Group I and Group III were homogeneous, while Group II was heterogeneous.
The results of PCA revealed that the 13 natural populations were roughly divided into three groups (Figure 4c), which was concordant with the results of Admixture. Individuals in the same population are all clustered into the same group, while one individual of ZTS in Group II was clustered into Group I and one individual of ZW in Group III was clustered in Group II. This result was further verified by the ML phylogenetic tree (Figure 4d). Similar to Admixture and PCA, 130 individuals of 13 natural populations were divided into three groups: Group I (N = 21), Group II (N = 80) and Group III (N = 29). Mantel test showed that there was no significant correlation between genetic distance and geographical distance among populations (Figure S3).
The result of AMOVA analysis showed that the genetic variation was mainly within populations, accounting for 82.47% of the total variation (Table 4). The pairwise Fst ranged from 0.032 to 0.569, showing different levels of genetic differentiation among populations [54] (Figure 5). The genetic differentiation among groups was high, and genetic differentiation within groups was low. Nine migration events among populations in Treemix (Figure S4) indicated that frequent gene flow was observed among populations. The highest gene flow was from TSX to ZW, followed by XLS to JY. Nm ranged from 0.189 to 7.632, indicating that there were different levels of gene flow among populations (Figure 5).

3.5. Inference of Demographic History

The divergence time of A. truncatum showed that Group I was initially divided from other populations at 21.24 Ma and further diverged into BTM and TSX at 20.58 Ma (Figure 6). The other populations diverged into Group II and Group III at 18.86 Ma. Group II further diverged into ZTS, JY, PQ, XLS, SSS, WDT, WLS and DQT at 15.27 Ma. Group III further diverged into XLM, LBGM and ZW at 13.76 Ma.
Population demographic history provided evidence that A. truncatum experienced bottleneck events in the long term of the evolution process (Figure 7). There was a sharp contraction around 40,000 to 60,000 years ago, and the northern population especially is in severe decline. Then, A. truncatum began to expand and reach its historical peak about 1500 years ago. Subsequently, the number of individuals underwent a severe decline between 500 and 300 years ago. Since then, the effective populations have been maintained at a low level until now.

4. Discussion

4.1. Sampling Strategy for Genetic Diversity of Populations

In general, the sample size of each population is about 30 individuals when the genetic background and biological characteristics of a species are unknown [55]. There is a debate about whether the small sample size (<10) for each population can capture the high genetic diversity of populations by SNPs. The He, I, MAF and PIC in this study captured more than 95% of the total genetic diversity of the population when the sample size of the population in A. truncatum was at least 10. Similarly, the results of 20 individuals in Amphirrhox longifolia (A.St.-Hil.) Spreng. using SNP markers, that is, 94% of the total genetic diversity of the population, could be achieved when the sample size was greater than eight with 1000 or more SNPs [56]. In addition, the same conclusion was found for SSR markers. The individual number of 17 and 15 for the population in Liquidambar formosana Hance and Toona ciliata Roem based on SSR markers captured more than 95% of genetic diversity, respectively [57,58]. Therefore, SNP markers with a small sample size can be used to analyze genetic diversity.

4.2. Maintaining Mechanism of Genetic Diversity within Populations

A. truncatum currently maintains a high genetic diversity (He = 0.289), compared with other species, such as Vatica guangxiensis S. L. Mo (He = 0.181) [59], Pinus densiflora Siebold & Zucc. (He = 0.253) [37] and Cunninghamia lanceolata (Lamb.) Hook. (He = 0.233) [60]. A. truncatum is a duodichogamous tree [61] that can promote cross-pollination among individuals by avoiding self-fertilization [62] and high gene flow (average Nm = 1.984) among populations. A. truncatum, like other Acer species, such as A. grosseri (H = 0.35, I = 0.5) [63] and A. monspessulanum (H = 0.325, I = 0.46) [64], is sufficiently outcrossing with high genetic diversity. Moreover, it is widely distributed geographically, ranging from the north subtropical to the middle temperate zone and from the humid mountainous area to the arid desert area. A. truncatum is a tall perennial tree with a long lifespan and some of the trees can be more than 200 years old [22]. Therefore, All the above biological characteristics of A. truncatum may contribute to maintaining its high genetic diversity. This supports the view of Hamrick and Godt [65] that woody plants with wide geographical ranges, continuous distributions, long lifespans and cross-pollination generally exhibit high genetic diversity.

4.3. Genetic Differentiation among Populations

Thirteen natural populations were divided into three genetic groups by cluster analysis. The Fst coefficient showed that low genetic differentiation within groups was in line with AMOVA analysis, while high genetic differentiation among groups was not. Mountain barriers may reinforce genetic differentiation among genetic groups [66]. There were two possible alternative scenarios of population barriers to interpret the observed differentiation. First, the uplift of Mt. Qinling (2.4 Ma) was later than the divergence time of A. truncatum (21.24 Ma). Group I (BTM and TSX) and partial populations (XLS, JY and ZTS) of Group II were separated by a huge body of Mt. Qinling during the gradual uplifting process. Moreover, long geographical distances among groups also can strengthen genetic differentiation. Group I is located in the subtropical zone, and Group III and the remaining populations of Group II are located in the temperate zone. Extremely long geographical distances among those groups may hinder the gene flow among populations, resulting in high genetic differentiation.
Group III (XLM, LBGM and ZW) and Group II (PQ, WLS, WDT, SSS and DQT) are geographically close in this study, but there is high genetic differentiation. This is inconsistent with the fact that the closer the geographical distance among populations is, the lower the genetic differentiation is [67]. Flora of China showed that A. truncatum and A. pictum subsp. mono H. Ohashi have overlapped distribution areas in Group III (LBGM, XLM and ZW), and there is natural hybridization between the two species [68]. Although samples were collected as far as possible from the morphological judgment to ensure that it was A. truncatum, the morphology of the hybrid offspring was not only intermediate type but also parent-like [69]. It is not guaranteed that all individuals in this study were A. truncatum, and there may also be some individuals of A. truncatum genetic introgressed by A. pictum subsp. mono. Therefore, gene introgression may lead to high genetic differentiation among geographically close groups. In the future, the two closely related species may be studied together to explore the gene flow between them and the influence on the genetic structure of the two species to better understand the genetic structure of A. truncatum.
The analysis of divergence time of populations showed that BTM diverged earliest in all populations, suggesting that it was the origin center. This is also supported by Treemix results, which showed that the northward migration events occurred among populations and gene flow mainly spread from the subtropical population (BTM) to the middle temperate zone (WDT). However, the correlation analysis of He and latitude in A. truncatum indicated that the genetic diversity of populations did not show a significant decreasing trend with the increase of latitude. The high genetic diversity in LBGM and XLM in the center area of the distribution may be interfered with by gene introgression and artificial introduction. Compared to nuclear DNA (nDNA), chloroplast DNA (cpDNA) can produce clearer traces of the population history and better predict ancient haplotypes [70]. It is possible to conduct the phylogeography study based on cpDNA to identify its refuge during the ice age and to trace the origin center of A. truncatum.

4.4. Demographic History

Our study showed that the effective population size of A. truncatum decreased sharply from 60,000 to 40,000 years ago, which may be caused by the sudden drop in temperature during the last glacial period (during 70,000–11,500 years ago). This is in line with the results of studies on the historical dynamics of other plants. Both Malus sieversii Roem. and Thuja sutchuenensis Franch. were affected by the Quaternary glaciation, which led to severe population contraction of the two species starting 900,000 and 110,000 years ago, respectively, and a decrease in effective population size [71,72].
From 11,500 to 5000 years ago after the end of the last glacial period, the population of A. truncatum was in a relatively slow recovery period, until the population expanded greatly from 5000 to 300 years ago. The endangered species of the same genus, A. griseum, did not expand during the last inter-glacial period (unpublished data). In contrast, A. truncatum has a wide geographic distribution (about 105°–126° E and 32°–45° N), with a broad range of temperature and humidity (from humid, semi-humid, and semi-arid to arid regions) [73], indicating that it is highly adaptive. Mature trees of A. truncatum exhibit easy natural regeneration with high seed setting rate and seed germination rate [74]. It also has a thin, non-woody seed shell, which can spread over a long distance by wind [75]. There are many factors affecting the expansion and reconstruction of species after the Quaternary glacial period, including the adaptability to low temperature and drought, as well as the ability of natural reproduction and dispersal [76]. Therefore, the excellent biological characteristics of A. truncatum led to its rapid expansion during the last inter-glacial period and successful resettlement in new areas. This demonstrates that A. truncatum is of strong resilience to harsh habitat or climate fluctuations.
In addition to climate change, the shrinking of the effective population size may be related to anthropogenic interference. The effective population size of A. truncatum was observed as a second sharp contraction roughly 300 years ago. China was in the Ming Dynasty at that time, and there were many border wars in the north of China. A. truncatum, as a hardwood tree, was frequently cut down for weapons and utensils, resulting in a decline in its population. After liberation in China, the rapid development of industry also led to a large number of A. truncatum being cut down for use. The shrinkage of effective population size may be caused by anthropogenic activities. This may be another bottleneck event, which reminds us to take some genetic rescue to stop this trend.

5. Conclusions

The genetic diversity of natural populations in A. truncatum was high, and the genetic variation mainly resided within populations. Thirteen natural populations primarily originated from three gene pools. Geographic isolation for gene flow led to high genetic differentiation among groups. The effective population size of A. truncatum declined sharply during the last glacial period in the long-term historical evolution. Its good biological characteristics of reproduction and dissemination allow it to expand rapidly after the last glacial period. So, A. truncatum has a strong ability to adapt to climate fluctuations and is a pioneer tree for vegetation recovery for degraded arid sandy land. However, the effective population size of A. truncatum sharply shrank again and remained at a low level until now due to the influence of extreme weather and anthropogenic interference. Therefore, it is necessary to give priority to in situ and ex situ conservation of natural populations with high genetic diversity.
As a new resource tree for food, A. truncatum has been greatly exploited and utilized. Considering the effective population size of A. truncatum is currently at the lowest level in its evolutionary history, it is necessary to conserve genetic resources and avoid the destruction of its natural population. Analysis of the population demography and exploration of the causes of change suggest that the current population size is much lower than that at the peak period of its evolutionary history. Therefore, corresponding promotion measures should be taken to restore its population size to cope with future climate change.

Supplementary Materials

The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/f15040639/s1, Figure S1: Delay of linkage disequilibrium of populations in A. truncatum; Figure S2: The variation of He with the latitude of populations in A. truncatum (R2 = 0.437); Figure S3: The correlation between the genetic distance matrix and the corresponding geographic distance of populations in A. truncatum (y = −(1 × 10−6x) + 0.0896, r = 0.193, p > 0.05); Figure S4: Population splits and migrations among populations of A. truncatum. Table S1: Effects of different number of samples (N) on genetic diversity parameters of populations in A. truncatum.

Author Contributions

Conceptualization, J.L. and X.Y.; methodology, J.L. and X.Y.; software, J.L., Y.W. and X.X. (Xinhe Xia); validation, J.L., X.Y. and C.Z.; formal analysis, S.M., X.P. and Y.Z.; investigation, J.L., X.Y., S.P. and X.X. (Xuebing Xin); resources, S.P. and X.X. (Xuebing Xin); writing—original draft preparation, J.L.; writing—review and editing, X.Y., Y.W., X.X. (Xinhe Xia), S.M., X.P., Y.Z. and C.Z.; visualization, J.L.; supervision, C.Z.; project administration, C.Z.; funding acquisition, S.P. and X.X. (Xuebing Xin). All authors have read and agreed to the published version of the manuscript.

Funding

This research was funded by the Fundamental Research Fund of Chinese Academy of Forestry, grant number CAFYBB2020ZB005-01.

Data Availability Statement

Data are contained within the article.

Acknowledgments

The authors are grateful to associated researcher Wenhua Yang, who is from Research Institute of Forestry, Chinese Academy of Forestry, for her language polishing.

Conflicts of Interest

The authors declare no conflicts of interest.

References

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Figure 1. The geographic distribution of sampling populations in Acer truncatum Bunge. Pie charts represent three genetic groups that were divided by Admixture. BTM, DQT and LBGM, etc., were shown in Table 1.
Figure 1. The geographic distribution of sampling populations in Acer truncatum Bunge. Pie charts represent three genetic groups that were divided by Admixture. BTM, DQT and LBGM, etc., were shown in Table 1.
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Figure 2. An overview of the collected A. truncatum individuals. (a) A tree of A. truncatum. (b) The sampling environment in DQT. (c) The leaves of A. truncatum. (d) The leaf tissues of each individual were dried with silica gel.
Figure 2. An overview of the collected A. truncatum individuals. (a) A tree of A. truncatum. (b) The sampling environment in DQT. (c) The leaves of A. truncatum. (d) The leaf tissues of each individual were dried with silica gel.
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Figure 3. The percentage of genetic diversity index values accounting for the total genetic diversity parameter. (a) expected heterozygosity (He). (b) Shannon’s index (I). (c) minor allele frequency (MAF). (d) polymorphic index content (PIC). N, number of samples in each population.
Figure 3. The percentage of genetic diversity index values accounting for the total genetic diversity parameter. (a) expected heterozygosity (He). (b) Shannon’s index (I). (c) minor allele frequency (MAF). (d) polymorphic index content (PIC). N, number of samples in each population.
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Figure 4. Genetic structure of 130 individuals in A. truncatum output from Admixture based on neutral loci. (a) Cross validation errors. The x−axis represents the K value, while the y-axis indicates the cross validation errors. The red dot shows K = 3 with the lowest cross validation errors. (b) Population structure of A. truncatum. The clustered populations are depicted with different colors representing different gene pools. (c) PCA plot of populations of A. truncatum based on neutral loci. PC1, the first principal component; PC2, the second principal component. (d) A maximum likelihood phylogenetic tree of populations of A. truncatum. A. griseum (XS04) is the outgroup species, BTM2201 is named as population code plus the sampling year.
Figure 4. Genetic structure of 130 individuals in A. truncatum output from Admixture based on neutral loci. (a) Cross validation errors. The x−axis represents the K value, while the y-axis indicates the cross validation errors. The red dot shows K = 3 with the lowest cross validation errors. (b) Population structure of A. truncatum. The clustered populations are depicted with different colors representing different gene pools. (c) PCA plot of populations of A. truncatum based on neutral loci. PC1, the first principal component; PC2, the second principal component. (d) A maximum likelihood phylogenetic tree of populations of A. truncatum. A. griseum (XS04) is the outgroup species, BTM2201 is named as population code plus the sampling year.
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Figure 5. Genetic differentiation and gene flow among populations of A. truncatum.
Figure 5. Genetic differentiation and gene flow among populations of A. truncatum.
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Figure 6. Divergence time of populations in A. truncatum with A. griseum (XS04), as the outgroup species. The number represents the divergence time.
Figure 6. Divergence time of populations in A. truncatum with A. griseum (XS04), as the outgroup species. The number represents the divergence time.
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Figure 7. Demographic history of populations in A. truncatum. Ne, Effective population size.
Figure 7. Demographic history of populations in A. truncatum. Ne, Effective population size.
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Table 1. Geographical locations and number of samples (N) of populations in A. truncatum.
Table 1. Geographical locations and number of samples (N) of populations in A. truncatum.
Climatic ZoneProvinceLocationCodeLongitude (E)Latitude (N)Altitude (m)N
Middle temperate zoneInner MongoliaDai Qin Ta LaDQT121°30′41″45°12′54″33210
Song Shu ShanSSS119°33′23″43°1′27″77310
Wu Dan Ta LaWDT122°45′44″42°59′45″22020
LiaoningZhang WuZW122°32′38″42°50′24″25910
Warm temperate zoneBeijingLa Ba Gou MenLBGM116°27′81″40°57′18″131310
Xiao Long MenXLM115°25′57″39°57′59″118810
GansuXiao Long ShanXLS106°17′34″34°20′17″132210
HenanPing QuanPQ118°46′1″40°50′33″115010
Ji YuanJY112°8′0.6″35°9′39″70010
HebeiWu Ling ShanWLS117°47′41″40°57′1″133410
ShannxiZhong Tiao ShanZTS112°1′34″35°30′12″137910
Subtropic zoneHenanBao Tian ManBTM111°52′46″33°28′57″101710
ShaanxiTian Shu XiaTSX109°17′18″31°59′51″180410
Table 2. Sequencing information of populations in A. truncatum.
Table 2. Sequencing information of populations in A. truncatum.
Location CodeTotal ReadsSNP Num.Alignment Rate (%)Average Q30 (%)Average CG (%)Ti/Tv
WDT *1,054,174,48815,686,47395.2090.3336.632.02
BTM511,807,66210,313,73897.6190.0335.952.03
DQT511,057,6525,989,63897.7088.8836.171.93
JY495,467,7305,320,38595.3893.6036.041.92
LBGM502,797,72011,099,54096.8589.2835.941.94
PQ474,844,2345,503,80994.5193.4936.501.92
SSS503,270,7925,866,08397.9788.7436.451.94
TSX511,075,07610,485,16996.0989.2236.702.01
WDT519,997,9085,454,95495.1689.7436.501.91
WLS513,698,8806,143,75997.3989.0936.641.95
XLM500,572,49011,008,00695.9089.0936.631.94
XLS541,715,6865,388,34995.7993.3336.211.91
ZTS509,314,2746,476,08697.6089.0136.371.96
ZW510,144,56410,685,34297.1489.2736.191.94
XS0447,801,750905,84874.7096.0940.281.52
Note: * 20 individuals in WDT; XS04, Acer griseum is an outgroup species; Q30, the percentage of bases with mass values greater than or equal to 30 in the total number of bases; CG, the percentage of G and C types of bases in the total base; Ti/Tv, SNP ratio of base conversion to base transversion type.
Table 3. Parameter values of genetic diversity of populations in A. truncatum.
Table 3. Parameter values of genetic diversity of populations in A. truncatum.
Location CodeNaNeHoHePICINei’sTajima’DFis
BTM1.4391.2460.2660.3320.2670.5010.3510.9490 0.058
DQT1.5111.2150.2670.2670.2210.4230.2810.2386 0.007
JY1.4231.1910.2620.2800.2310.4390.296−1.0122 0.074
LBGM1.4291.2440.3290.3360.2700.5060.3561.0783 −0.068
PQ1.5131.2050.2430.2550.2120.4070.2690.4044 0.034
SSS1.5091.2040.2540.2550.2120.4070.2690.1223 0.013
TSX1.3481.1790.2990.3100.2510.4750.3281.2503 −0.058
WDT1.4591.1920.2500.2660.2200.4210.2801.0854 0.073
WLS1.4901.2220.2840.2860.2360.4470.3010.6191 0.008
XLM1.4341.2440.3220.3310.2660.5000.3510.8866 −0.054
XLS1.4391.1880.2560.2690.2230.4250.284−0.7118 0.057
ZTS1.5721.2550.2680.2840.2350.4460.2991.4664 0.026
ZW1.7171.3210.2800.2820.2330.4430.299−0.5777 0.001
Mean1.4831.2240.2750.2890.2370.4490.3050.44600.013
Note: Na, number of observed alleles; Ne, number of effective alleles; Ho, observed heterozygosity; He, expected heterozygosity; PIC, Polymorphic index content; I, Shannon’s information index; Nei’s, Nei’s genetic diversity; Tajima’D, a test statistic for neutral evolutionary; Fis, inbreeding coefficient.
Table 4. Analysis of molecular variance (AMOVA) of populations in A. truncatum.
Table 4. Analysis of molecular variance (AMOVA) of populations in A. truncatum.
Source of VariationDfSSVCPV (%)
Among Pops121,587,760.905346.2354417.53%
Within Pops2476,210,342.3525,155.367182.47%
Total2597,798,103.2530,501.60254100%
Note: Df, Degree of freedom; SS, Sum of squares; VC, Variance components; PV, Percentage of variation.
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Liao, J.; Yu, X.; Wu, Y.; Pei, S.; Xin, X.; Xia, X.; Mao, S.; Pan, X.; Zheng, Y.; Zhang, C. Spatial Pattern of Genetic Diversity and Demographic History Revealed by Population Genomic Analysis: Resilience to Climate Fluctuations of Acer truncatum Bunge. Forests 2024, 15, 639. https://doi.org/10.3390/f15040639

AMA Style

Liao J, Yu X, Wu Y, Pei S, Xin X, Xia X, Mao S, Pan X, Zheng Y, Zhang C. Spatial Pattern of Genetic Diversity and Demographic History Revealed by Population Genomic Analysis: Resilience to Climate Fluctuations of Acer truncatum Bunge. Forests. 2024; 15(4):639. https://doi.org/10.3390/f15040639

Chicago/Turabian Style

Liao, Jia, Xuedan Yu, Yuxia Wu, Shunxiang Pei, Xuebing Xin, Xinhe Xia, Shan Mao, Xinyue Pan, Yongqi Zheng, and Chuanhong Zhang. 2024. "Spatial Pattern of Genetic Diversity and Demographic History Revealed by Population Genomic Analysis: Resilience to Climate Fluctuations of Acer truncatum Bunge" Forests 15, no. 4: 639. https://doi.org/10.3390/f15040639

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