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Article

Genetic Diversity and Population Structure of Corylus yunnanensis (Franch.) A. Camus Using Microsatellite Markers in Sichuan Province

by
Zeliang Wang
1,*,
Yi Lin
2,
Xiongcai Gou
1,
Jincheng Du
1 and
Maolin Wang
1
1
Sichuan Academy of Forestry, Chengdu 610081, China
2
Beijing Key Laboratory of Spatial Information Integration and Its Applications, Institute of Remote Sensing and Geographic Information Systems, School of Earth and Space Sciences, Peking University, Beijing 100871, China
*
Author to whom correspondence should be addressed.
Forests 2023, 14(5), 932; https://doi.org/10.3390/f14050932
Submission received: 30 March 2023 / Revised: 26 April 2023 / Accepted: 27 April 2023 / Published: 1 May 2023
(This article belongs to the Special Issue Advances in Hazelnut Germplasm and Genetic Improvement)
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Abstract

:
Corylus yunnanensis (Franch.) A. Camus is a deciduous shrub, native to the Hengduan Mountain of Qinghai–Tibetan Plateau, and is an economically and ecologically important woody crop species. In the present study, one hundred and fifty trees sampled from ten populations of C. yunnanensis in Sichuan Province were investigated to assess the population genetic variation using nine SSR markers. The results revealed that C. yunnanensis has an average value of 12.111 alleles, 3.376 effective alleles, an expected heterozygosity of 0.648, and an observed heterozygosity of 0.630, presenting a relatively high level of genetic diversity. The C. yunnanensis populations in Maoxian and Wenchuan of Aba Prefecture expressed the highest value of genetic diversity, whereas the Hanyuan and Muli populations showed the lowest. Moreover, the genetic differentiation of ten C. yunnanensis populations averaged to 0.106. Correspondingly, AMOVA revealed that 87% of the total variance was accounted for the variation within populations, and only 13% was among the populations. Both UPGMA and Bayesian STRUCTURE clustering suggested that the ten C. yunnanensis populations could fall into three clusters: the Aba Prefecture population, the Ya’an population, and the population of Ganzi and Liangshan Prefecture, indicating a significant geographic distribution, which was also confirmed by the Mantel test. Our study could provide a better understanding of population genetic diversity, and serve valuable information for the genetic improvement of C. yunnanensis.

1. Introduction

The genus Corylus L. (commonly known as hazel plants), belonging to the family Betulaceae, are deciduous shrubs or small trees, native to the northern temperate zone. The genus contains about twenty species, among which eight species and two varieties are naturally occurring in China, mainly distributed in the north–east, north, and south–west of China [1,2,3]. Hazelnuts, one of the four major nuts in the world, are abundant in microelements, widely used in food processing and in the manufacture of confectionery products, including chocolate, biscuits, candy, dairy products, and so on. In addition, hazelnuts contain a higher overall proportion of fatty acids (~60% of the hazelnut kernel), mostly oleic acid (~80% of the fatty acids), and other unsaturated fatty acids, which could reduce the risk of cardiovascular disease by reducing blood pressure, thereby inhibiting cholesterogenesis and the atherosclerotic process [4,5,6]. Therefore, its economic value is growing increasingly of great concern.
Sichuan province is an important distribution region for the genus Corylus, and most domestic hazelnut resources in China are distributed here, including C. yunnanensis, C. heterophylla var. sutchuenensis Franch., C. ferox Wall., C. ferox var. thibetica (Batal.) Franch., C. mandshurica Maxim., C. chinensis Franch., and C. fargesii Schneid. [1]. These resources are mainly distributed in Aba Prefecture, Liangshan Prefecture, and Ganzi Prefecture, as well as the Qinba mountains in northern Sichuan. Due to the characteristics of their root systems, the hazelnut plants easily form continuous shrubs, and the hazelnuts are also important food sources for squirrels and other small wild animals, thereby being an important part of the mountain ecosystem. At present, the hazelnut resources in the above-mentioned region have not yet been bred effectively.
To utilize these wild hazelnut resources, it is necessary to clarify their population genetic variation. Microsatellites, or simple sequence repeats (SSRs) markers, are present in eukaryotic genomes extensively, and are suitable for automated allele sizing, exhibit co-dominant inheritance, and are highly polymorphic, and therefore have been widely used in studying population genetic diversity and structure. The SSR markers applied in the study of hazelnut plants were first developed by the laboratory of Mehlenbacher in Oregon State University, which constructed three microsatellite enrichment libraries of C. avellana (GAA, CA, and GA), and Bassil et al. (2003) screened fifty-three polymorphic loci from these libraries at first [7]. Thereafter, in 2005, 51 SSR markers in total were identified to dissect the population genetic diversity of C. avellana, and interspecific amplification was also successfully carried out [8,9,10]. So far, more than 200 SSR markers have been screened from the above three libraries, and are widely used in current times [11,12,13,14]. In China, SSR markers have been also successfully used in the study of genetic diversity, population structure, and relationship of hazelnut plants in C. mandshurica, C. heterophylla Fisch. ex Trautv., and C. heterophylla var. sutchuenensis, and so on, and this guided further hazelnut genetic improvements [15,16,17,18,19,20].
In this study, the genetic diversity, genetic structure, and variation patterns of the natural populations of C. yunnanensis in Sichuan province were investigated using SSRs, with the eventual aim to provide valuable information for the conservation strategy and utilization of C. yunnanensis.

2. Materials and Methods

2.1. Population Sampling

A total of 150 trees of C. yunnanensis were collected from ten populations in Sichuan province (Figure 1, Table 1). Fresh young leaves from individual trees were collected, promptly dried with silica gel in a non-woven bag, and then transported to the laboratory and stored at −70°C for DNA extraction.

2.2. DNA Extraction and Microsatellite Analysis

Extraction of genomic DNA was performed with a gDNA extraction kit (Tiangen, Beijing, China). A total of 9 primer pairs (Table 2) presenting higher levels of polymorphism were screened from published papers for hazel plants [8,10,21]. The forward primer was fluorescently labelled with 6-FAM, and PCR and genotyping analysis were executed as described previously by Guo et al. [22].

2.3. Data Analysis

Micro-Checker 2.2.3 software was used to check the SSR loci for null alleles and possible misprints [23]. The parameters of genetic diversity (number of different alleles (Na), effective number of alleles (Ne), Shannon’s information index (I), observed heterozygosity (Ho), expected heterozygosity (He), inbreeding coefficient at the population level (Fis), inbreeding coefficient at the total sample level (Fit), genetic differentiation coefficient (Fst), and gene flow (Nm)) were calculated using the GenAlEx 6.51 Toolkit [24]. Nei’s genetic distance (1978) was calculated using Popgene 1.32 software [25], which was then used to construct the UPGMA tree with the NTSYS-pc 2.10s software [26,27], and to implement the PCoA analysis using GenAlEx 6.51. In addition, Nei’s genetic distance and geographic distance were analyzed for correlation with the Mantel test by NTSYS-pc 2.10s using 1000 random permutations [28].
STRUCTURE 2.3.4 was used to analyze the population structure with 10 times and 500,000 Markov Chain Monte Carlo (MCMC) repetitions following a burn-in period of 100,000 interactions for each group number K from 1 to 10 [29]. The optimal K value was determined by the method from Evanno [30,31]. After repeated sampling analysis with Clumpp 1.1.2 [32], the inferred clusters were visualized using Distruct 1.1 [33].

3. Results

3.1. Microsatellite Variation andPopulation Genetic Diversity

Micro-Checker analysis indicated that one microsatellite marker (Ch02) presented null alleles at high frequencies, which were therefore excluded from further analysis. Amplification of one hundred and fifty C. yunnanensis individuals representing the ten populations with the remaining nine markers generated a total of one hundred and nine alleles, with an average of 12.111 alleles at each locus (Table 2). The observed heterozygosity (Ho) and expected heterozygosity (He) ranged from 0.351 (Ch08) to 0.808 (Ch06), and from 0.387 (Ch08) to 0.836 (Ch07), and averaged 0.630 and 0.648, respectively (Table 2). Among all nine SSR loci, Ch06 and Ch09 had lower He values than Ho, whereas the rest had higher He values compared to Ho.
Among the ten populations, Na and Ne ranged from 4.222 (E) to 8.000 (C), and 2.666 (E) to 4.360 (B), and averaged 5.667 and 3.376, respectively. Ho ranged from 0.519 (F) to 0.757 (C), and He ranged from 0.549 (E) to 0.758 (C), and averaged 0.630 and 0.758, respectively (Table 3).
Thus, the C. yunnanensis populations showed a relatively high degree of genetic diversity. In addition, among the ten populations, populations C (Maoxian), B (Luding), and H (Wenchuan) exhibited a higher diversity, while populations E (Hanyuan) and F (Muli) showed a lower level of genetic diversity by comparison, which was also revealed from the Shannon’s information index (I values are as shown in Table 3).

3.2. Population Genetic Differentiation

As shown in Table 2, the inbreeding coefficient (Fis) per locus ranged from −0.109 (Ch09) to 0.059 (Ch07), and averaged −0.019 per locus, while the genetic differentiation (Fst) ranged from 0.064 (Ch03) to 0.208 (Ch09) across the nine loci, and averaged 0.106, indicating that the average genetic differentiation among the ten C. yunnanensis populations was 10.6%, and that genetic variation within the populations (89.4%) accounted for the main source of variation. In addition, gene flow (Nm) ranged from 0.952 (Ch09) to 3.655 (Ch03), and averaged 2.452 (Table 2), indicating that the gene flow among the ten populations of C. yunnanensis was relatively frequent. Similarly, the results of the AMOVA analysis showed that genetic variation occurred mostly within the populations (87%), with only 13% being among the populations (Table S1). Additionally, both results indicated that the genetic variation of the C. yunnanensis populations mainly resides within the populations.

3.3. Population Genetic Structure

The generated UPGMA tree showed that the C. yunnanensis populations were grouped into three clusters (C and H, K and M, and others). Interestingly, populations C and H were from Aba Prefecture, populations K and M were from Ya’an, and the others were populations from Liangshan Prefecture and Ganzi Prefecture (Figure 2A), indicating that the C. yunnanensis populations in Sichuan province exhibited a geographic distribution.
The STRUCTURE analysis showed that the ΔK gave a clear maximum for K = 3 (ΔK = 10.843), also suggesting that the ten C. yunnanensis populations could be classified into three groups (Supplementary Figure S1). The cluster membership proportions of each individual are presented in Figure 3, and the cluster membership proportions of each population were also graphed (as shown in Figure 4), revealing a clear geographic distribution of the original populations. In the Aba populations, the first cluster (green) had a larger proportion. For populations from the Liangshan and Ganzi, the third cluster (blue) or the second cluster (red) showed a bigger portion, with a very small portion of the first cluster. In comparison with the Liangshan and Ganzi populations, the first cluster (green) was slightly larger for the Ya’an populations. This result is consistent with the UPGMA tree (Figure 2A). Similarly, the PCoA between either populations or individuals also revealed that the ten C. yunnanensis populations could be classified into three main groups (Figure 2B,C).
The Mantel test revealed a significant correlation [r = 0.715 (p = 0.002)] (Figure 5) between Nei’s genetic distance among populations and geographic distance, suggesting that the geographic distance presumably gives rise to the genetic differentiation observed of the ten C. yunnanensis populations.

4. Discussion

4.1. Population Genetic Diversity in C. yunnanensis

Overall, our SSR data indicates that all ten populations of C. yunnanensis have relatively higher genetic diversity, with the highest level of genetic diversity occurring in Aba Prefecture populations (Maoxian, Wenchuan).The genetic diversity of C. yunnanensis (Na = 12.111, He = 0.648) in this study is higher than that of C. heterophylla (Na = 5.125, He = 0.553) [17], and C.cornuta var. californica (Na = 6.496, He = 0.619) [34]. Meanwhile, the C. yunnanensis genetic diversity is lower than that of C. mandshurica (Na = 15.3, He = 0.777) [15], C. avellana (Na = 6.325, He = 0.709) [35], and C. americana (Na = 10.90, He = 0.74) [36]. This may be related to the sampling range of the hazelnut plant. For example, the C. mandshurica populations were sampled from several provinces, including Heilongjiang, Liaoning, Beijing, Hebei, and Shanxi in north and north–east China [15], while the C. avellana plants were collected from many countries or regions in Europe [35]. Alternatively, this might be attributed to the different SSR markers used in these studies. In accordance with the biological characteristics of C. yunnanensis, its population genetic diversity in this study was similar with what is typical for species that are perennial (He = 0.68), outcrossed, and regionally distributed (He = 0.65), and higher than that of species with a narrow distribution (He = 0.56), early succession (He = 0.42), wind- or water-dispersed (He = 0.61), and endemism (He = 0.46) [37].

4.2. Population Genetic Structure and Geographic Variation in C. yunnanensis

The genetic differentiation coefficient among the C. yunnanensis populations was relatively small (Fst = 0.106), lower than that of C. mandshurica (Fst = 0.122) [15], similar to that of C. avellana (Fst = 0.097) [35], but higher than those of C. cornuta var. californica (Fst = 0.012–0.054) [34], C. heterophylla (Fst = 0.058), and C. heterophylla var. sutchuenensis (Fst = 0.090) [16]. As according to Wright’s consideration [38], the genetic differentiation among C. yunnanensis populations was moderate, which suggests that gene flow among the populations of C. yunnanensis was relatively frequent, preventing the impact of genetic drift and weakening genetic differentiation among the C. yunnanensis populations [39], conforming to the gene flow value (Nm = 2.452).
Nevertheless, both UPGMA and STRUCTURE analyses showed that the ten C. yunnanensis populations could be divided into three clusters: Aba Prefecture populations, Ya’an populations, and Liangshan and Ganzi Prefecture populations, suggesting that the population genetic variation in C. yunnanensis presents a clear characteristic geographic distribution. On the other hand, Ya’an populations with the lowest distribution altitude are differentiated from the Liangshan and Ganzi populations, although the Ya’an populations are closer to the Ganzi populations in geographic distance, meaning that the genetic structure of C. yunnanensis is affected by the elevation gradient to some extent.
The plants of the genus Corylus and the genus Alnus Mill., both of which belong to the family Betulaceae, are widely distributed in the Hengduan mountain, but there is a significant difference in Sichuan basin. No wild hazelnut resources have been found in this area, whereas A. cremastogyne Burk. is widely distributed here [22]. The two genera were considered to have originated early from southwestern China. The fossil of A. ferdinandi-coburgii Schneid. was discovered in Mangkang of Tibet (~34.6Ma) [40,41], and the recent common ancestor of Corylus was also considered to occur in southwestern China using genome-wide SNPs (~36.38 Ma) [42], when major parts of Hengduan mountains of the Qinghai–Tibetan Plateau were being established [43]. For their distribution difference, we speculate that there are two possibilities. First, both were only distributed in the Hengduan mountain historically. However, accompanied with the uplift of the Qinghai–Tibetan Plateau, regional drainage systems such as the Daduhe river, Minjiang river, and Fujiang river were established, and the lightweight alder nutlets were easily dispersed into Sichuan Basin. While hazelnuts are large and heavy, they were presumably unaffected by the drainage systems. Second, both were historically distributed in both the Hengduan mountain and Sichuan Basin. However, with the climatic environmental changes resulting from the uplift of the Qinghai–Tibetan Plateau, hazelnut plants in Sichuan Basin might therefore become extinct due to flower abortion or flowering asynchronism. For example, the catkins of C. heterophylla × C. avellana introduced into Sichuan Basin tend to abortion (data not shown). Of course, these speculations need further study.

4.3. Genetic Improvement of C. yunnanensis

In Sichuan province, C. yunnanensis is mainly distributed in the alpine valley region of western Sichuan, which belongs to parts of the Hengduan mountain of the Qinghai–Tibetan Plateau. Compared to the smaller area, a relatively high genetic variation was accumulated in the populations of C. yunnanensis, which could be presumably attributed to the diverse habitats resulting from the historically geological and climatic changes across the Qinghai–Tibetan Plateau [43]. However, ongoing expanding human activities, and increasingly severe climatic changes, are resulting in the loss of germplasm resources of C. yunnanensis. Therefore, one effective way to protect the germplasms of C. yunnanensis and its population genetic diversity is to screen some core populations for in situ conservation [16,44]. Thus, C. yunnanensis populations C, H, and B with the highest genetic diversity should be considered priorities for in situ conservation in future.
In addition, C. yunnanensis has a smaller nut and thicker shell, so it could not be directly used as a commercial variety. To cross with C. heterophylla × C. avellana, or with C. avellana for regional suitable varieties, or to directly breed the pollinating varieties, are two ways for their utilization. In this respect, it is necessary to select suitable populations for ex situ conservation, such as a larger hazelnut size, a thin nut shell, sufficient catkins, and appropriate blooming time. These are what we are currently designing and working towards.
In addition to C. yunnanensis, C. heterophylla var. sutchuenensis, C. ferox, C. mandshurica, C. chinensis, and C. fargesii are also distributed in the alpine valley region of western Sichuan [1,2]. Among these, some occupy the same ecological niches with C. yunnanensis, whereas some show differences with C. yunnanensis. The differentiation and evolution of these hazelnut plants deserve further study. Moreover, compared to C. yunnanensis, C. ferox, with some unique characteristics, such as spiny husks and arbor tree, show a wider distribution range, and also deserves further investigation.

5. Conclusions

In summary, our studies showed that the ten C. yunnanensis populations show a relatively high degree of genetic diversity. There was moderate genetic differentiation among the C. yunnanensis populations, and the majority of variation occurred within the populations. Gene flow among C. yunnanensis populations was relatively frequent, which reduced the population variation. These ten C. yunnanensis populations could be classified into three groups, and exhibited a significant geographic distribution. Taken together, the findings of our studies may provide valuable information for conservation management, genetic improvement, and utilization of C. yunnanensis.

Supplementary Materials

The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/f14050932/s1, Figure S1: Estimated population structure (K = 3) by STRUCTURE; Table S1: Molecular variance analysis among and within C. yunnanensis populations using 9 SSR loci.

Author Contributions

Conceptualization, experimental, data analysis, and writing—original draft preparation, Z.W.; writing—review and editing, Y.L.; investigation and resources, X.G. and J.D.; experimental, data analysis, and visualization, M.W.; funding acquisition, Z.W. and Y.L. All authors have read and agreed to the published version of the manuscript.

Funding

This research was funded by the Fundamental Research Funds for Provincial Research Institutes in Sichuan (no. 2023JBKY07), the National Key Research and Development Program of China (no. 2022YFE0112700), and the National Natural Science Foundation of China (no. 32171782).

Data Availability Statement

Data are contained within the article.

Conflicts of Interest

The authors declare no conflict of interest.

References

  1. Chen, Z.D. Phylogeny and phytogeography of the Betulaceae (cont.). Acta Phytotax. Sin. 1994, 32, 101–153. (In Chinese) [Google Scholar]
  2. Kuang, K.; Li, P.; Cheng, S.; Lu, A. Flora Reipublicae Popularis Sinicae; Science Press: Beijing, China, 1979; Volume 21, pp. 93–103. (In Chinese) [Google Scholar]
  3. Ma, Q.H.; Wang, G.X.; Liang, W.J.; Chen, X.; Liang, L.S.; Zhao, T.T. Progress on pollen–stigma compatibility in Corylus (hazelnuts): A review. J. For. Res. 2013, 24, 397–402. [Google Scholar] [CrossRef]
  4. Wang, G.X. Progress in cultivation and utilization of Corylus L. resources in China (IV)–Nutrition, comprehensive utilization and industry development. For. Res. 2018, 31, 130–136. (In Chinese) [Google Scholar]
  5. Terés, S.; Barceló-Coblijn, G.; Benet, M.; Alvarez, R.; Bressani, R.; Halver, J.E.; Escribá, P.V. Oleic acid content is responsible for the reduction in blood pressure induced by olive oil. Proc. Natl. Acad. Sci. USA 2008, 105, 13811–13816. [Google Scholar] [CrossRef] [PubMed]
  6. Perdomo, L.; Beneit, N.; Otero, Y.F.; Escribano, Ó.; Díaz-Castroverde, S.; Gómez-Hernández, A.; Benito, M. Protective role of oleic acid against cardiovascular insulin resistance and in the early and late cellular atherosclerotic process. Cardiovasc Diabetol. 2015, 14, 75. [Google Scholar] [CrossRef] [PubMed]
  7. Bassil, N.V.; Botta, R.; Mehlenbacher, S.A. Microsatellite markers of the european hazelnut. Hort. Sci. 2003, 38, 740–741, (Abstr). [Google Scholar]
  8. Bassil, N.V.; Botta, R.; Mehlenbacher, S.A. Microsatellite markers in the hazelnut: Isolation, characterization and cross–species amplification in Corylus. J. Am. Soc. Hort. Sci. 2005, 130, 543–549. [Google Scholar] [CrossRef]
  9. Boccacci, P.; Akkak, A.; Bassil, N.V.; Botta, R. Characterization and evaluation of microsatellite loci in European hazelnut (Corylus avellana L.) and their transferability to other Corylus species. Mol. Ecol. Notes 2005, 5, 934–937. [Google Scholar] [CrossRef]
  10. Bassil, N.V.; Botta, R.; Mehlenbacher, S.A. Additional microsatellites of the European hazelnut. Acta Hortic. 2005, 686, 105–110. [Google Scholar] [CrossRef]
  11. Boccacci, P.; Botta, R.; Rovira, M. Genetic diversity of hazelnut (Corylus avellana L.) germplasm in northeastern Spain. HortScience 2008, 43, 667–672. [Google Scholar] [CrossRef]
  12. Gökirmak, T.; Mehlenbacher, S.A.; Bassil, N.V. Characterization of European hazelnut (Corylus avellana) cultivars using SSR markers. Genet. Resour. Crop Evol. 2009, 56, 147–172. [Google Scholar] [CrossRef]
  13. Boccacci, P.; Botta, R. Investigating the origin of hazelnut (Corylus avellanaL.) cultivars using chloroplast microsatellites. Genet. Resour. Crop Evol. 2009, 56, 851–859. [Google Scholar] [CrossRef]
  14. Gürcan, K.; Mehlenbacher, S.A.; Botta, R.; Boccacci, P. Development, characterization, segregation, and mapping of microsatellite markers for European hazelnut (Corylus avellana L.) from enriched genomic libraries and usefulness in genetic diversity studies. Tree Genet. Genomes 2010, 6, 513–531. [Google Scholar] [CrossRef]
  15. Zong, J.W.; Zhao, T.T.; Ma, Q.H.; Liang, L.S.; Wang, G.X. Assessment of genetic diversity and population genetic structure of Corylus mandshurica in China using SSR markers. PLoS ONE 2015, 10, e0137528. [Google Scholar] [CrossRef] [PubMed]
  16. Zhao, T.; Ma, W.; Ma, Q.; Yang, Z.; Liang, L.; Wang, G. Genetic diversity and population structure of Chinese Corylus heterophylla and Corylus kweichowensis using simple sequence repeat markers. J. Amer. Soc. Hort. Sci. 2020, 145, 289–298. [Google Scholar] [CrossRef]
  17. Wang, Y.M.; Liu, Z.; Ma, T.X.; Zhai, M.P. Preliminary study on population structure and genetic diversity of Corylus heterophylla Fisch. J. Henan Agric. Univ. 2009, 45, 497–500, 505. (In Chinese) [Google Scholar]
  18. Li, X.; Li, X.; Wang, Z.; Xue, C.; Zhang, L.; Guo, Y. Study on phylogenetic analysis of Corylus germplasm resouces with SSR molecular markers for Corylus avellana. J. Northeast Agric. Univ. 2011, 42, 129–136. (In Chinese) [Google Scholar]
  19. Wang, Z.L.; Zheng, Y.Q.; Su, L.; Liu, Q.; Yu, M.Z. Screening of SSR markers in Corylus yunnanensis. J. Sichuan For. Sci. Tech. 2017, 34, 55–58. (In Chinese) [Google Scholar]
  20. Wang, Z.L.; Wu, B.; Xing, W.X.; Zheng, C.W.; Li, P.J. Study on genetic Relationship of genus Corylus resources in Sichuan province based on SSR markers. J. Sichuan For. Sci. Tech. 2021, 42, 78–82. (In Chinese) [Google Scholar]
  21. Gökirmak, T.; Mehlenbacher, S.A.; Bassil, N.V. Investigation of genetic diversity among European hazelnut (Corylus avellana) cultivars using SSR markers. Acta Hort. 2005, 686, 141–149. [Google Scholar] [CrossRef]
  22. Guo, H.Y.; Wang, Z.L.; Huang, Z.; Chen, Z.; Yang, H.B.; Kang, X.Y. Genetic diversity and population structure of Alnus cremastogyne as revealed by microsatellite markers. Forests 2019, 10, 278. [Google Scholar] [CrossRef]
  23. Van, O.C.; Hutchinson, W.F.; Wills, D.P.; Shipley, P. MICRO-CHECKER: Software for identifying and correcting genotyping errors in microsatellite data. Mol. Ecol. Notes 2004, 4, 535–538. [Google Scholar]
  24. Peakall, R.; Smouse, P.E. GenAlEx 6.5: Genetic analysis in Excel. Population genetic software for teaching and research–an update. Bioinformatics 2012, 28, 2537–2539. [Google Scholar] [CrossRef]
  25. Yeh, F.; Yang, R.; Boyle, T. Popgene Version 1.32. Microsoft Windows–Based Freeware for Population Genetic Analysis; University of Alberta: Edmonton, AB, Canada, 1999. [Google Scholar]
  26. Nei, M. Estimation of average heterozygosity and genetic distance from a small number of individuals. Genetics 1978, 89, 583–590. [Google Scholar] [CrossRef] [PubMed]
  27. Rohlf, F.J. NTSYS–pc numerical taxonomy and multivariate analysis system. Am. Stat. 1987, 41, 330. [Google Scholar] [CrossRef]
  28. Mantel, N. The detection of disease clustering and generalized regression approach. Cancer Res. 1967, 27, 209–220. [Google Scholar]
  29. Pritchard, J.K.; Stephens, M.; Donnelly, P. Inference of population structure using multilocus genotype data. Genetics 2000, 155, 945–959. [Google Scholar] [PubMed]
  30. Evanno, G.; Regnaut, S.; Goudet, J. Detecting the number of clusters of individuals using the software structure: A simulation study. Mol. Ecol. 2005, 14, 2611–2620. [Google Scholar]
  31. Earl, D.A.; vonHoldt, B.M. Structure Harvester: A website and program for visualizing STRUCTURE output and implementing the Evanno method. Conserv. Genet. Res. 2012, 4, 359–361. [Google Scholar] [CrossRef]
  32. Jakobsson, M.; Rosenberg, N.A. CLUMPP: A cluster matching and permutation program for dealing with label switching and multimodality in analysis of population structure. Bioinformatics 2007, 23, 1801–1806. [Google Scholar]
  33. Rosenberg, N.A. Distruct: A program for the graphical display of population structure. Mol. Ecol. Notes 2004, 4, 137–138. [Google Scholar] [CrossRef]
  34. Fine, P.V.; Misiewicz, T.M.; Chavez, A.S.; Cuthrell, R.Q. Population genetic structure of California hazelnut, an important food source for people in Quiroste Valley in the Late Holocene. Calif. Archaeol. 2013, 5, 353–370. [Google Scholar] [CrossRef]
  35. Boccacci, P.; Aramini, M.; Valentini, N.; Bacchetta, L.; Rovira, M.; Drogoudi, P.; Silva, A.P.; Solar, A.; Calizzano, F.; Erdoğan, V.; et al. Molecular and morphological diversity of on–Farm hazelnut (Corylus avellana L.) landraces from southern Europe and their role in the origin and diffusion of cultivated germplasm. Tree Genet. Genomes 2013, 9, 1465–1480. [Google Scholar] [CrossRef]
  36. Sathuvalli, V.R.; Mehlenbacher, S.A. Characterization of American hazelnut (Corylus americana) accessions and Corylus americana × Corylus avellana hybrids using microsatellite markers. Genet. Resour. Crop Evol. 2012, 59, 1055–1075. [Google Scholar] [CrossRef]
  37. Nybom, H. Comparison of different nuclear DNA markers for estimating intraspecific genetic diversity in plants. Mol. Ecol. 2004, 13, 1143–1155. [Google Scholar] [CrossRef] [PubMed]
  38. Wright, S. Evolution and the Genetics of Population, Vol. 4. Variability within and among Natural Populations; University of Chicago Press: Chicago, IL, USA, 1978; pp. 97–159. [Google Scholar]
  39. Wright, S. Evolution in Mendelian populations. Genetics 1931, 16, 97–159. [Google Scholar] [CrossRef] [PubMed]
  40. Xu, H.; Su, T.; Zhou, Z.K. Leaf and infructescence fossils of Alnus (Betulaceae) from the late Eocene of the southeastern Qinghai–Tibetan Plateau. J. Syst. Evol. 2019, 57, 105–113. [Google Scholar] [CrossRef]
  41. Su, T.; Spicer, R.A.; Li, S.H.; Xu, H.; Huang, J.; Sherlock, S.; Huang, Y.J.; Li, S.F.; Wang, L.; Jia, L.B.; et al. Uplift, climate and biotic changes at the Eocene–Oligocene transition in south–eastern Tibet. Nat. Sci. Rev. 2019, 6, 495–504. [Google Scholar] [CrossRef]
  42. Yang, Z.; Zhao, T.-T.; Ma, Q.-H.; Liang, L.-S.; Wang, G.-X. Resolving the Speciation Patterns and Evolutionary History of the Intercontinental Disjunct Genus Corylus (Betulaceae) Using Genome-Wide SNPs. Front. Plant Sci. 2019, 9, 1386. [Google Scholar]
  43. Wu, S.; Wang, Y.; Wang, Z.; Shrestha, N.; Liu, J. Species divergence with gene flow and hybrid speciation on the Qinghai–Tibet Plateau. New Phytol. 2022, 234, 392–404. [Google Scholar] [CrossRef]
  44. Tijerino, A.; Korpelainen, H. Molecular characterization of Nicaraguan Pinus tecunumanii Schw. ex Eguiluz et Perry populations for in situ conservation. Trees 2014, 28, 1249–1253. [Google Scholar] [CrossRef]
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Figure 1. Locations of the 10 sampled populations of C. yunnanensis in Sichuan Province.
Figure 1. Locations of the 10 sampled populations of C. yunnanensis in Sichuan Province.
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Figure 2. Genetic structure of the 10 C. yunnanensis populations. (A) UPGMA (Unweighted pair-group method with arithmetic means) cluster analysis based on Nei’s genetic distance. (B) PCoA (Principal Coordinate Analysis) between populations. (C) PCoA between individuals.
Figure 2. Genetic structure of the 10 C. yunnanensis populations. (A) UPGMA (Unweighted pair-group method with arithmetic means) cluster analysis based on Nei’s genetic distance. (B) PCoA (Principal Coordinate Analysis) between populations. (C) PCoA between individuals.
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Figure 3. The cluster membership proportions of the 10 C. yunnanensis populations at the individual level with STRUCTURE (K = 3). Each bar representing one individual was partitioned into three different colored segments, showing the individual’s estimated ancestry proportion of the genetic clusters.
Figure 3. The cluster membership proportions of the 10 C. yunnanensis populations at the individual level with STRUCTURE (K = 3). Each bar representing one individual was partitioned into three different colored segments, showing the individual’s estimated ancestry proportion of the genetic clusters.
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Figure 4. Mean cluster membership proportions of the 10 C. yunnanensis populations with STRUCTURE (K = 3).
Figure 4. Mean cluster membership proportions of the 10 C. yunnanensis populations with STRUCTURE (K = 3).
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Figure 5. Mantel test for matrix correlation between Nei’s genetic distance and geographic distance for the 10 C. yunnanensis populations.
Figure 5. Mantel test for matrix correlation between Nei’s genetic distance and geographic distance for the 10 C. yunnanensis populations.
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Table
Table 1. Location and number of trees of the 10 C. yunnanensis populations in Sichuan Province.
Table 1. Location and number of trees of the 10 C. yunnanensis populations in Sichuan Province.
Population CodeLocationNumber of SamplesLongitude (E)Latitude (N)Altitude (m)
AMianning (Liangshan)2528.534102.2141768–2224
BLuding (Ganzi)1429.916102.2361788–2573
CMaoxian (Aba)2531.756103.9171430–2336
EYanyuan (Ya’an)1027.568101.4702563–3184
FMuli (Liangshan)1627.960101.2522279–3230
GXide (Liangshan)1428.349102.4852085–2226
HWenchuan (Aba)1231.523103.5942239–2389
KHanyuan (Ya’an)929.572102.6441700–1920
LKangding (Ganzi)1430.475102.2882220–2388
MShimian (Ya’an)1129.451102.2301254–1593
Note: The text in the parentheses indicates the prefecture for the corresponding population in the location column.
Table
Table 2. Characterization of 9 SSR loci in C. yunnanensis based on 150 trees representing 10 populations in Sichuan Province.
Table 2. Characterization of 9 SSR loci in C. yunnanensis based on 150 trees representing 10 populations in Sichuan Province.
LocusPrimers (5′-3′)Size Range (bp)Annealing Temperature (°C)NaNeHoHeIFisFitFstNmPrimer Source
Ch01F: CAAACTTATGATAGGCATGCAA
R: TGTCACTTTGGAAGACAAGAGA		270–30055173.3960.6990.7181.436−0.0270.0910.1151.930CAC-B005 [10]
Ch03F: AGCAACAGAGGTTAGGTGTG
R: GCCCCATTAGCCTTCTTA		164–1855562.4610.5950.6050.982−0.0270.0380.0643.655CAC-C118 [10]
Ch04F: GTAGGTGCACTTGATGTGCTTTAC
R: ACACCATATTGAGTCTTTCAAAGC		107–16155184.7730.7920.8181.734−0.0130.0640.0773.004CaDCAT28 [21]
Ch05F: GGTTTGTTACAGAAATTCAGACG
R: GCGTGTGGTTAATGTTTTCTTT		208–22855104.2090.7630.7901.542−0.0110.0570.0673.496CAC-A14a [8]
Ch06F: ATGGACGAGGAATATTTCAGC
R: CCTGTTTCTCTTTGTTTTCGAG		254–28055144.3420.8080.7791.623−0.0850.0470.1221.802CAC-B028 [8]
Ch07F: AAAGGAGCAAGCATGTTAGG
R: GTTTGTACGGATGATCCACTGAG		138–16655155.3460.7510.8361.7790.0590.1270.0723.201CAC-B105 [10]
Ch08F: GGTCTCCTTCGCTAACATAACCAA
R: GTTGCCCTCGAGTTGTAGTA		151–1755681.6730.3510.3870.6950.0510.1380.0922.474CaDCAT6 [21]
Ch09F: CTAAGCTCACCAAGAGGAAGTTGAT
R: GCTTCTGGGTCTCCTGCTCA		180–20055122.1330.4940.4680.902−0.1090.1220.2080.952CaDCAT10 [21]
Ch10F: CTTCCAAGGATGGCTCAG
R: TTTCAGGACGAGGACTCTG		179–1975892.0490.4150.4290.837−0.0130.1270.1391.553CAC-B014 [10]
Mean 12.1113.3760.6300.6481.281−0.0190.0900.1062.452
Na, Number of different alleles; Ne, Number of effective alleles; Ho, Observed heterozygosity; He, Expected heterozygosity; I, Shannon’s information index; Fis, inbreeding coefficient at the population level; Fit, inbreeding coefficient at the total sample level; Fst, genetic differentiation coefficient among populations; Nm, gene flow.
Table
Table 3. Genetic diversity within the 10 C. yunnanensis populations in Sichuan Province.
Table 3. Genetic diversity within the 10 C. yunnanensis populations in Sichuan Province.
Population CodeNaNeIHoHeF
A7.1113.2431.2650.5800.586−0.018
B7.2224.3601.5190.6670.702−0.001
C8.0004.2421.6270.7570.758−0.019
E4.2222.6661.0230.5220.549−0.002
F4.3332.9891.0850.5190.5770.048
G6.1112.8921.2200.6110.590−0.076
H4.8893.4331.3560.7430.753−0.055
K4.7783.0001.1950.6570.638−0.106
L5.5563.7841.3220.6670.656−0.076
M4.4443.1491.1970.5740.6680.067
Mean5.6673.3761.2810.6300.648−0.024
Na, Mean number of different alleles; Ne, Number of effective alleles; I, Shannon’s information index; Ho, Observed heterozygosity; He, Expected heterozygosity; F,Fixation index.
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Wang, Z.; Lin, Y.; Gou, X.; Du, J.; Wang, M. Genetic Diversity and Population Structure of Corylus yunnanensis (Franch.) A. Camus Using Microsatellite Markers in Sichuan Province. Forests 2023, 14, 932. https://doi.org/10.3390/f14050932

AMA Style

Wang Z, Lin Y, Gou X, Du J, Wang M. Genetic Diversity and Population Structure of Corylus yunnanensis (Franch.) A. Camus Using Microsatellite Markers in Sichuan Province. Forests. 2023; 14(5):932. https://doi.org/10.3390/f14050932

Chicago/Turabian Style

Wang, Zeliang, Yi Lin, Xiongcai Gou, Jincheng Du, and Maolin Wang. 2023. "Genetic Diversity and Population Structure of Corylus yunnanensis (Franch.) A. Camus Using Microsatellite Markers in Sichuan Province" Forests 14, no. 5: 932. https://doi.org/10.3390/f14050932

APA Style

Wang, Z., Lin, Y., Gou, X., Du, J., & Wang, M. (2023). Genetic Diversity and Population Structure of Corylus yunnanensis (Franch.) A. Camus Using Microsatellite Markers in Sichuan Province. Forests, 14(5), 932. https://doi.org/10.3390/f14050932

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