Plant Gene and Trait 2026, Vol.17 http://genbreedpublisher.com/index.php/pgt © 2025 GenBreed Publisher, registered at the publishing platform that is operated by Sophia Publishing Group, founded in British Columbia of Canada. All Rights Reserved.
Plant Gene and Trait 2026, Vol.17 http://genbreedpublisher.com/index.php/pgt © 2025 GenBreed Publisher, registered at the publishing platform that is operated by Sophia Publishing Group, founded in British Columbia of Canada. All Rights Reserved. GenBreed Publisher is an international Open Access publisher specializing in plant protection, plant breeding, molecular genetics, proteomics and genetic diversity registered at the publishing platform that is operated by Sophia Publishing Group (SPG), founded in British Columbia of Canada. Publisher GenBreed Publisher Edited by Editorial Team of Plant Gene and Trait Email: edit@pgt.genbreedpublisher.com Website: http://genbreedpublisher.com/index.php/pgt Address: 11388 Stevenston Hwy, PO Box 96016, Richmond, V7A 5J5, British Columbia Canada Plant Gene and Trait (ISSN 1925-2013) is an open access, peer reviewed journal published online by GenBreed Publisher. The journal publishes articles that address the fundamental nature of genes and genomes at any level, either experimental or computational approaches, in plants as well as algae, including applications of novel techniques to plant biology and plant trait improvement. All papers chosen for publishing should be innovative research work in fields of plant genes or traits, plant protection, plant breeding, particular in the areas of functional genomics, genomic tools, genome technologies, transgene, genome sequencing analysis, molecular genetics, proteomics, genetic diversity, heterosis, genetic characteristics, genetic modification, genotype-phenotype relationships, stress resistance characteristics, QTL analysis, biochemistry, physiology and morphology. All the articles published in Plant Gene and Trait are Open Access, and are distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. GenBreed Publisher uses CrossCheck service to identify academic plagiarism through the world’s leading plagiarism prevention tool, iParadigms, and to protect the original authors’ copyrights.
Plant Gene and Trait (online), 2026, Vol. 17 ISSN 1925-2013 http://genbreedpublisher.com/index.php/pgt © 2025 GenBreed Publisher, an online publishing platform of Sophia Publishing Group. All Rights Reserved. Sophia Publishing Group (SPG), founded in British Columbia of Canada, is a multilingual publisher Latest Content Genetic Diversity and Genetic Relationship Analysis of Platycladus orientalis Germplasm Based on SSR Markers Jilei Zhou, Liudong Zhang, Yinyin Fu, Yong Chen, Jingtao Li Plant Gene and Trait, 2026, Vol. 17, No. 1, 1-11 Regulatory Effects of Nursery Mode and Canopy Closure on the Establishment Survival Rate of Tetrastigma hemsleyanum and Delineation of the Optimal Closure Range Jianhui Li, Yehua Zhang, Yumin Fang, Jianzhong Fan, Yonghong Xu Plant Gene and Trait, 2026, Vol. 17, No. 1, 12-19 The Genetic Basis of Maple Leaf Color and Its Application in Landscape Design Huiyi Kuang Plant Gene and Trait, 2026, Vol. 17, No. 1, 20-35 Trait Basis and Management Strategies for Stable High Yield in Greenhouse Tomato Production Xiaxia Lin, Mengting Luo Plant Gene and Trait, 2026, Vol. 17, No. 1, 36-55 Trait Basis and Breeding Strategies for the Coordinated Improvement of Yield and Sugar Content in Sugarcane Jiong Fu, Zhongmei Hong Plant Gene and Trait, 2026, Vol. 17, No. 1, 56-73
Plant Gene and Trait 2026, Vol.17, No.1, 1-11 http://genbreedpublisher.com/index.php/pgt 1 Research Report Open Access Genetic Diversity and Genetic Relationship Analysis of Platycladus orientalis Germplasm Based on SSR Markers Jilei Zhou 1, Liudong Zhang 1, Yinyin Fu 2, Yong Chen 3, Jingtao Li 1 1 Forestry Protection and Development Service Center of Shandong Province, Ji’nan, 250014, Shandong, China 2 Shandong Academy of Forestry Sciences/ Key Laboratory for Genetics and Breeding in Forest Trees of Shandong, Ji’nan, 250014, Shandong, China 3 Ji’nan Forestry and Fruit Technology Promotion and Industrial Service Center, Ji’nan, 250102, Shandong, China Corresponding email: lzh529@163.com Plant Gene and Trait, 2026, Vol.17, No.1 doi: 10.5376/pgt.2026.17.0001 Received: 26 Dec., 2024 Accepted: 26 Jan., 2026 Published: 10 Feb., 2026 Copyright © 2026 Zhou et al., This is an open access article published under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Preferred citation for this article: Zhou J.L., Zhang L.D., Fu Y.Y., Chen Y., and Li J.T., 2026, Genetic diversity and genetic relationship analysis of Platycladus orientalis germplasm based on SSR markers, Plant Gene and Trait, 17(1): 1-11 (doi: 10.5376/pgt.2026.17.0001) Abstract To investigate the genetic diversity and phylogenetic relationships among Platycladus orientalis germplasm resources in Zaozhuang City, simple sequence repeat (SSR) molecular markers were used to analyze genetic diversity and relatedness in 100 P. orientalis accessions collected from four regions. The results showed that a total of 32 allelic loci were detected using seven pairs of SSR primers, with an average of 6.571 alleles per primer pair. The mean number of alleles (Na) was 3.714, the mean effective number of alleles (Ne) was 1.900, the mean Shannon’s information index (I) was 0.818, and the mean expected heterozygosity (He) was 0.440, indicating relatively high genetic diversity among the 100 sampled P. orientalis accessions. The Fst value was 0.0371, suggesting a high degree of similarity among populations, small genetic distances, and low genetic differentiation. Cluster analysis based on the estimation of the optimal K value showed that the maximum △K occurred at K=3, indicating that the 100 P. orientalis accessions could be divided into three groups rather than clustering strictly according to geographic origin, which implies the existence of gene flow among the sampled populations. Through preliminary screening and repeated validation, seven pairs of SSR primers with clear gel electrophoresis profiles were obtained, which showed stable amplification across all populations and yielded reliable, easily interpretable results. These microsatellite markers provide a useful reference for future studies on the origin and evolution of P. orientalis varieties, molecular identification and classification, hybrid breeding, and parental selection for genetic mapping. Keywords Platycladus orientalis; SSR; Fingerprinting; Cluster analysis 1 Introduction Platycladus orientalis, belonging to the family Cupressaceae, subfamily Cupressoideae, genus Platycladus (Fu, 1982), is the coniferous tree species with the widest natural distribution in China. It has a broad ecological amplitude, strong tolerance to drought and poor soils, vigorous vitality, and a long lifespan. It is one of the most commonly used pioneer tree species for afforestation of barren mountains in northern China, possessing extremely high economic and medicinal value, and it is also an important component of historical and cultural landscapes (Wu, 1986; Yang et al., 2014a). With global climate change, under the combined effects of natural disasters, deterioration of site conditions, pests and diseases, as well as subjective factors such as human disturbance and poor management, P. orientalis populations have shown varying degrees of decline, including weakened growth and even near death. The conservation and utilization of P. orientalis germplasm resources are facing great challenges, and its ecological value has not been effectively utilized (Su, 2003; Wang et al., 2004; Yang et al., 2014b). Since the 1970s, extensive provenance trials have been carried out for P. orientalis, making it one of the earliest tree species in China to undergo such trials. In recent years, many scholars have conducted substantial research on provenance testing and patterns of genetic variation in P. orientalis (Wang, 2011). Numerous studies have also investigated and discussed the pharmacologically active components in different parts of P. orientalis (Miao Hui, 2018). During cultivation, a number of regional cultivars have been formed. Due to its wide distribution, wild populations of P. orientalis possess rich genetic resources. By studying the genetic variation and distribution patterns of P. orientalis, analyzing its genetic diversity and phylogenetic relationships, further revealing kinship
Plant Gene and Trait 2026, Vol.17, No.1, 1-11 http://genbreedpublisher.com/index.php/pgt 2 and evolutionary relationships, and evaluating its genetic potential and value, a theoretical foundation can be established for the construction of core germplasm collections and the screening of superior genes. This is of great significance for the selection and utilization of elite germplasm. With continuous advances in science and technology, methods for studying genetic diversity have also been constantly updated. Molecular marker techniques, owing to their advantages of being unaffected by environmental factors, developmental stage, or gene expression, have become important tools in genetic research (Liu et al., 2012). Geographic population variation in P. orientalis has shown significant effects on population selection and improvement (Jin, 2020). There is an urgent need to improve the genetic quality and adaptability of superior P. orientalis varieties through molecular marker technologies and to carry out research on the genetic basis of breeding populations. Among these methods, microsatellite markers (simple sequence repeats, SSRs), because of their high level of genetic information, good reproducibility and stability, and codominant inheritance (Maroof et al., 1994; Guichoux, 2011), have been widely used in studies of genetic diversity and phylogenetic relationships in forest trees (Reisch et al., 2007; Kalia, 2011; Lin et al., 2013; Huang et al., 2018). At present, sequenced genomes are mainly concentrated in cultivated plants and species with important economic value. Meanwhile, the development of new microsatellite primers is difficult and costly. However, species derived from a common ancestor often exhibit high sequence homology. Therefore, screening SSR primers required for the target species from closely related species with well-developed microsatellite primers has been widely adopted (Barbara, 2007). In this study, SSR molecular markers were used to analyze the genetic diversity and kinship relationships of 100 P. orientalis samples collected from four regions. Through preliminary screening and repeated validation, seven pairs of microsatellite primers were selected from all synthesized SSR primers. These primers produced clear gel electrophoresis patterns, could be stably amplified in each population, showed relatively ideal performance, and were easy to score and statistically analyze, and were thus used for subsequent analyses. 1 Results and Analysis 1.1 PCR amplification and primer polymorphism Through primer screening and repeated validation, seven polymorphic microsatellite primers were successfully selected from 45 pairs of SSR primers. These primers produced clear gel electrophoresis profiles, could be stably amplified in all populations, showed relatively ideal performance, and were easy to score and statistically analyze. A total of 26 allelic loci were detected by the seven SSR primers, mainly distributed in the range of 125–309 bp (Table 1). On average, each SSR primer detected 3.714 alleles. The number of effective alleles (Ne) ranged from a minimum of 1.317 for primer 18 to a maximum of 2.819 for primer SF13, with a mean of 1.9. The observed heterozygosity (Ho) of Platycladus orientalis populations ranged from 0.140 to 0.610, with an average of 0.406. The expected heterozygosity (He) varied from 0.241 to 0.645, with a mean value of 0.440. The polymorphic information content (PIC) ranged from 0.212 to 0.579. Highly polymorphic primers (PIC>0.5) accounted for 28.6% of the total, primers with moderate polymorphism (0.25<PIC<0.5) accounted for 57.1%, and primers with low polymorphism (PIC<0.25) accounted for 14.3%, with an average PIC value of 0.398. The Shannon information index (I) ranged from 0.405~1.194, with an average of 0.818, indicating that the genetic diversity of the population of 100 P. orientalis accessions was relatively low. Table 1 Genetic diversity characteristics of different SSR loci Locus Genotype No. Na Ne I Ho He uHe PIC 4 3 2 1.688 0.598 0.350 0.408 0.410 0.325 18 3 2 1.317 0.405 0.140 0.241 0.242 0.212 SF3 5 3 1.595 0.685 0.380 0.373 0.375 0.341 SF14 12 5 2.441 1.194 0.610 0.590 0.593 0.557 SF4 7 5 1.894 0.955 0.490 0.472 0.475 0.441 SF12 6 4 1.551 0.703 0.370 0.355 0.357 0.330 SF13 10 5 2.819 1.188 0.505 0.645 0.649 0.579 Mean 6.571 3.714 1.900 0.818 0.406 0.440 0.442 0.398
Plant Gene and Trait 2026, Vol.17, No.1, 1-11 http://genbreedpublisher.com/index.php/pgt 3 1.2 Genetic diversity and kinship analysis of Platycladus orientalis Genetic variation among Platycladus orientalis populations was analyzed using seven SSR markers. Based on GenAlEx analysis, the results (Table 2) showed that at the population level, the observed number of alleles per population ranged from 2.571 to 3.571, with an average of 3.071. The effective number of alleles ranged from 1.865 to 1.987, with an average of 1.909. The Shannon information index ranged from 0.725 to 0.807, with a mean of 0.766. Observed heterozygosity ranged from 0.393 to 0.492, with an average of 0.423, while expected heterozygosity ranged from 0.431 to 0.452, with a mean of 0.439. The fixation index (Fst), which reflects the level of allelic heterozygosity among populations and is used to measure the degree of population differentiation, was 0.0371. This value falls within the range of 0–0.05, indicating a high degree of similarity among populations, small genetic distances, and very low genetic differentiation. Population A exhibited the highest values of polymorphism rate, Na, and I, indicating that this population had the highest genetic diversity. It is therefore inferred that population A represents the center of genetic diversity of P. orientalis among the four sampling regions. Table 2 Genetic diversity of Platycladus orientalis Population N Na Ne I Ho He uHe a 68 3.571 1.902 0.807 0.394 0.431 0.434 b 9 2.857 1.883 0.761 0.492 0.452 0.479 c 4 2.571 1.987 0.725 0.393 0.433 0.495 d 19 3.286 1.865 0.771 0.414 0.438 0.450 Mean 25 3.071 1.909 0.766 0.423 0.439 0.464 1.3 Genetic Differentiation Analysis of Platycladus orientalis Analysis of variance (ANOVA) was used to assess genetic variation in Platycladus orientalis. The results (Table 3) showed that genetic variation in P. orientalis was mainly derived from within populations, accounting for 91% of the total variation, while genetic variation among populations accounted for 9%. This indicates that the genetic variation of P. orientalis is predominantly distributed within populations. Table 3 Molecular variance analysis of P. orientalis germplasm Sources of variation df SS MS Est. Var. Percentage of variation Among Pops 3 4.36 1.45 0 0% Among Indiv 96 165.74 1.73 0.15 9% Within Indiv 100 143 1.43 1.43 91% Total 199 313.10 1.58 100% 1.4 Genetic structure analysis of Platycladus orientalis Bayesian clustering analysis of 100 individuals from four populations was performed using STRUCTURE software. The number of subpopulations (K) was preset from 2 to 10, with 10 independent runs for each K value. The value of LnP(D) continuously decreased with increasing K. When K=3, ΔK reached its maximum peak, indicating that division of the experimental materials into three clusters was the most appropriate (Figure 1; Figure 2). The distribution of individuals among the three clusters (Table 4) showed a relatively even composition, with mean Q values of 0.619, 0.476, and 0.461, respectively. When Q≥0.6, the genetic background of a sample is considered relatively pure, whereas when Q<0.6, the genetic background is considered complex (Falush et al., 2003). In this study, the Q value of Subpopulation 1 was≥0.6, indicating a relatively homogeneous genetic background. In contrast, Subpopulations 2 and 3 had Q values<0.6, suggesting that these two subpopulations integrated genetic components from multiple clusters and exhibited evident gene flow. The first cluster contained 39 individuals, including 27 from Shanting District, 2 from Yicheng District, 2 from Shizhong District, and 7 from Tengzhou City. The second cluster comprised 28 individuals, including 18 from Shanting District, 2 from Yicheng District, and 5 from Tengzhou City. The third cluster contained 23 individuals,
Plant Gene and Trait 2026, Vol.17, No.1, 1-11 http://genbreedpublisher.com/index.php/pgt 4 including 68 from Shanting District, 9 from Yicheng District, 4 from Shizhong District, and 19 from Tengzhou City. Using the method for estimating the optimal K value, Structure clustering analysis based on microsatellite data showed that ΔK reached its maximum at K=3; therefore, the optimal K value was 3. The studied populations were divided into three genetic clusters rather than being grouped according to sampling regions. This indicates the presence of gene flow among different regions, which is consistent with the results of the UPGMA clustering analysis. Figure 1 The deltaK (ΔK) values of structure output Figure 2 The structure output at K=3 Table 4 Distribution of P. orientalis germplasm subpopulations when K=3 Sub-population Shanting Yicheng Shizhong Tengzhou Total Q-Value Sub-population 1 27 3 2 7 39 0.619 Sub-population 2 18 5 0 5 28 0.476 Sub-population 3 23 1 2 7 33 0.461 Total 68 9 4 19 100 0.5187 Using PowerMarker software, UPGMA clustering based on Nei’s genetic distance was performed on 100 samples from four populations. The clustering results showed both similarities and differences compared with the three clusters identified by STRUCTURE. The main difference was that the proportions of samples from each provenance differed among the clusters. The similarity was that germplasm from the Shanting provenance was distributed across all three clusters. Based on the clustering outcomes from both methods, further analyses of kinship relationships among germplasm accessions can be conducted. To some extent, the clustering results indicate that genetic relatedness among populations is associated with geographic distribution; however, most samples did not cluster strictly according to their sampling regions, suggesting that there is a certain level of gene flow among different regions.
Plant Gene and Trait 2026, Vol.17, No.1, 1-11 http://genbreedpublisher.com/index.php/pgt 5 The clustering analysis of Platycladus orientalis (Figure 3) showed that red represents Cluster I, blue represents Cluster II, and yellow represents Cluster III. Cluster I contained 13 individuals, including 7 from Shanting District, 4 from Tengzhou City, and 1 from Yicheng District. Cluster II contained 23 individuals, including 21 from Shanting District and 2 from Shizhong District. Cluster III contained 64 individuals, including 40 from Shanting District, 15 from Tengzhou City, 8 from Yicheng District, and 1 from Shizhong District. Figure 3 Phylogenetic tree of Platycladus orientalis based on SSR data Using NTSYS software, UPGMA clustering analysis based on Nei’s genetic distance was performed on 100 samples from four populations (Figure 4). Coefficient 0.69 0.77 0.85 0.92 1.00 118 118 66 102 117 161 24 75 196 4 135 81 116 167 3 72 119 43 169 185 28 176 8 63 5 78 11 76 96 199 200 150 168 158 47 120 170 178 2 25 35 36 52 103 157 113 179 37 187 145 27 64 89 148 83 98 182 59 80 85 122 183 39 193 156 155 166 13 74 100 137 197 159 10 56 109 53 68 99 106 107 54 127 124 152 189 141 49 50 7 70 174 26 32 55 38 144 151 9 115 195 Figure 4 Dendrogram of Platycladus orientalis based on SSR data At a similarity coefficient of approximately 0.69, the samples were divided into two clusters. Samples 135, 137, 141, and 145 collected from Shizhong District, which showed relatively close kinship, were grouped together with samples from other regions, while samples from the remaining regions were not strictly clustered according to their geographic origins. At a similarity coefficient of approximately 0.70, four clusters were identified, and the collected samples still did not cluster according to the four sampling regions. When the genetic similarity coefficient reached 0.77, the 100 Platycladus orientalis accessions were divided into eight clusters.
Plant Gene and Trait 2026, Vol.17, No.1, 1-11 http://genbreedpublisher.com/index.php/pgt 6 2 Discussion In this study, seven polymorphic microsatellite primers with clear gel electrophoresis patterns and stable amplification across all populations were successfully selected, and corresponding DNA fingerprint profiles were established. These markers provide a valuable reference for future studies on the origin and evolution of Platycladus orientalis varieties, molecular-level identification and classification, hybrid breeding, and parental selection for genetic mapping. As an ideal type of molecular marker, microsatellites exhibit advantages such as good reproducibility, simplicity, efficiency, and high primer transferability in the identification of P. orientalis varieties. However, because the detection and application of SSR polymorphism largely depend on PCR amplification efficiency, different primers may require different reaction conditions. Therefore, it is essential to conduct preliminary optimization experiments for each primer and adopt appropriate strategies to maintain PCR reaction conditions at an optimal level. In plant variety identification and classification studies, a more scientific approach is to integrate multiple methods and use them to complement and validate one another (Yuan et al., 2014). Identification results based on morphological traits and molecular markers are not always completely consistent. For example, some morphologically similar P. orientalis individuals were identified as hybrids in STRUCTURE clustering analyses. This phenomenon may be attributed to genetic variation caused by backcrossing and introgression, or to morphological variation resulting from convergent evolution and environmental selection (Rieseberg et al., 1999; Schwarzbach et al., 2001; Lexer et al., 2003). Similar patterns have also been observed in other populations exhibiting natural hybridization (Rieseberg, 1995). Any single method has inherent limitations, and relying on a single approach for species identification and classification makes it difficult to ensure the scientific rigor and reliability of the results. Numerous studies have shown that factors such as genetic drift and gene flow have a substantial impact on population genetic structure. In recent years, parameters such as genetic differentiation coefficients have been widely used as important indicators for evaluating population genetic structure and kinship relationships among varieties (Song et al., 2011; Xu et al., 2014). Genetic variation analysis of P. orientalis populations using seven SSR markers showed that the average number of alleles (Na) among the 100 samples from four sampling regions was 3.714, the average effective number of alleles (Ne) was 1.900, the average Shannon index (I) was 0.818, and the average expected heterozygosity (He) was 0.440. These results indicate that the 100 sampled accessions possessed relatively rich genetic diversity. The fixation index (Fst), which reflects the level of allelic heterozygosity among populations and is used to measure the degree of population differentiation, was 0.0371. This value falls within the range of 0–0.05, indicating high similarity among populations, small genetic distances, and very low genetic differentiation. Results from principal coordinate analysis (PCoA), UPGMA clustering, and STRUCTURE clustering based on microsatellite data consistently showed that the 100 P. orientalis accessions were not strictly clustered according to their geographic origins. This suggests that the genetic backgrounds of the germplasm resources are relatively similar and that varying degrees of natural hybridization may occur among P. orientalis germplasm from different sampling regions. Hybridization promotes gene flow among populations and contributes to genetic evolution, thereby influencing population genetic structure and altering its overall pattern. The formation of this spatial genetic variation pattern may be the result of the combined effects of long-distance gene flow, natural climatic conditions, and geographic isolation. In theory, geographically proximate regions tend to have similar soil conditions and environmental climates, resulting in less pronounced differences in natural selection pressures and increased opportunities for interpopulation gene exchange. Consequently, populations located closer to each other tend to have smaller genetic distances and higher genetic similarity. At present, only a portion of P. orientalis resources has been collected, and the limited sample size may introduce bias into the analyses. Therefore, a more comprehensive evaluation and utilization of P. orientalis germplasm resources will require further investigation and research. To adapt to diverse ecological conditions and geographic environments, wild plant resources have undergone prolonged evolutionary processes involving intense survival
Plant Gene and Trait 2026, Vol.17, No.1, 1-11 http://genbreedpublisher.com/index.php/pgt 7 competition and extensive natural selection, resulting in extremely rich genetic diversity. These resources constitute complex natural gene pools that harbor many superior genes for disease resistance, pest resistance, and drought tolerance that are often absent in cultivated varieties, and thus can be used to improve the genetic basis of cultivated varieties (Tao et al., 2010; Jing et al., 2020). Influenced by artificial cultivation practices and breeding strategies, cultivated varieties have undergone substantial evolutionary changes; however, the patterns and directions of their evolution show considerable similarity to those of wild populations under natural conditions (Xu, 2005). The construction of genetic populations of P. orientalis and the exploration of their genetic diversity are therefore of great significance for the conservation and utilization of P. orientalis germplasm resources (Lei, 2018). 3 Materials and Methods 3.1 Overview of experimental material collection In March 2021, a total of 100 Platycladus orientalis samples were collected from four regions in Zaozhuang City (Table 5): Shanting District (a68), Yicheng District (b9), Shizhong District (c4), and Tengzhou City (d19). A sampling strategy of collecting one mature individual at intervals of 10 m was adopted to avoid repeated sampling. Healthy upper leaves free of insect damage were collected as samples whenever possible. After collection, the samples were thoroughly dried using color-indicating silica gel, and DNA was subsequently extracted. Table 5 Geographical location of Platycladus orientalis sampling sites No. Group Region Locality Longitude Latitude Elevation (m) Aspect 2 a Shanting District Huameizhuang 117°32′24″ 35°01′05″ 360 South 3 a Shanting District Shifosi 117°36′26″ 35°01′38″ 360 South 4 a Shanting District Shifosi 117°36′28″ 35°01′39″ 370 South 5 a Shanting District Shifosi 117°36′28″ 35°01′40″ 370 Southwest 7 a Shanting District Shifosi 117°36′28″ 35°01′40″ 384 Southeast 8 a Shanting District Shifosi 117°36′31″ 35°01′39″ 360 Southeast 9 a Shanting District Shifosi 117°36′22″ 35°01′42″ 410 East 10 a Shanting District Shifosi 117°36′37″ 35°01′36″ 330 South 11 a Shanting District Shifosi 117°36′22″ 35°01′42″ 390 South 13 a Shanting District Shifosi 117°36′29″ 35°01′34″ 380 South 24 a Shanting District Shifosi 117°36′32″ 35°01′49″ 326 Southwest 25 a Shanting District Glass Walkway South Mountain 117°35′27″ 35°02′04″ 340 Northeast 26 a Shanting District Glass Walkway South Mountain 117°35′25″ 35°02′12″ 330 North 27 a Shanting District Glass Walkway South Mountain 117°35′24″ 35°02′01″ 360 Northwest 28 a Shanting District Glass Walkway South Mountain 117°35′31″ 35°02′01″ 360 Northeast 32 a Shanting District Glass Walkway South Mountain 117°35′35″ 35°01′54″ 390 East 35 a Shanting District Mujia Cave West Mountain 117°35′54″ 35°02′36″ 270 Southwest 36 a Shanting District Mujia Cave West Mountain 117°35′55″ 35°01′52″ 280 West 37 a Shanting District Mujia Cave West Mountain 117°35′03″ 35°02′19″ 270 Southwest 38 a Shanting District Mujia Cave West Mountain 117°33′57″ 35°02′02″ 270 Northwest 39 a Shanting District Mujia Cave West Mountain 117°34′54″ 35°02′36″ 270 Southwest 43 a Shanting District Mujia Cave West Mountain 117°34′54″ 35°02′36″ 280 Southwest 47 a Shanting District East Dami Mountain 117°34′26″ 35°03′00″ 370 Southeast 49 a Shanting District East Dami Mountain 117°38′27″ 35°02′59″ 360 Southeast 50 a Shanting District East Dami Mountain 117°38′26″ 35°03′04″ 390 Northwest 52 a Shanting District Dajiao Mountain 117°38′27″ 35°03′38″ 390 West 53 a Shanting District East Dajiao Mountain 117°38′26″ 35°02′51″ 400 Southeast 54 a Shanting District Dajiao Mountain 117°38′27″ 35°03′10″ 246 Southwest 55 a Shanting District East Dajiao Mountain 117°38′25″ 35°02′50″ 400 East 56 a Shanting District Dajiao Mountain 117°38′15″ 35°03′29″ 400 West 59 a Shanting District East Dajiao Mountain 117°38′25″ 35°02′48″ 400 East 63 a Shanting District East Dajiao Mountain 117°38′25″ 35°02′47″ 410 Southeast 64 a Shanting District Northwest Mountain 117°36′31″ 35°03′45″ 280 East
Plant Gene and Trait 2026, Vol.17, No.1, 1-11 http://genbreedpublisher.com/index.php/pgt 8 No. Group Region Locality Longitude Latitude Elevation (m) Aspect 66 a Shanting District Northwest Mountain 117°36′29″ 35°03′40″ 280 Southeast 68 a Shanting District Northwest Mountain 117°36′31″ 35°03′43″ 280 East 70 a Shanting District Northwest Mountain 117°36′38″ 35°03′22″ 280 South 72 a Shanting District Northwest Mountain 117°36′29″ 35°03′40″ 290 Southeast 74 a Shanting District Northwest Mountain 117°36′28″ 35°03′40″ 240 South 76 a Shanting District Northwest Mountain 117°36′27″ 35°03′39″ 280 Southwest 78 a Shanting District Northwest Mountain 117°36′40″ 35°03′09″ 280 South 80 a Shanting District Northwest Mountain 117°36′25″ 35°03′38″ 270 South 81 a Shanting District Yanggang Mountain 117°36′30″ 35°02′55″ 230 East 83 a Shanting District Yanggang Mountain 117°36′28″ 35°02′57″ 280 Southeast 85 a Shanting District Yanggang Mountain 117°36′10″ 35°03′21″ 300 Southwest 89 a Shanting District Yanggang Mountain 117°36′29″ 35°02′56″ 290 Southeast 96 a Shanting District Shengshan’an Pass 117°34′08″ 35°00′19″ 180 North 98 a Shanting District Shengshan’an Pass 117°34′10″ 34°59′38″ 290 Northwest 99 a Shanting District Yanggang Mountain 117°36′00″ 35°03′22″ 280 South 100 a Shanting District Shengshan’an Pass 117°34′10″ 34°59′38″ 216 Southwest 102 a Shanting District Shengshan’an Pass 117°34′10″ 34°59′39″ 213 Southwest 103 a Shanting District Jiguan Gu 117°36′57″ 34°58′15″ 270 Southwest 107 a Shanting District Jiguan Gu 117°37′09″ 34°58′09″ 260 Southwest 109 a Shanting District Jiguan Gu 117°36′46″ 34°58′37″ 300 Southwest 113 a Shanting District Baodu Gu 117°42′54″ 34°59′11″ 330 Northwest 115 a Shanting District Baodu Gu 117°42′55″ 34°59′08″ 340 Southwest 118 b Yicheng District Qingtan Temple 117°34′23″ 34°57′39″ 410 East 135 c Shizhong District Guishan Forest Farm 117°40′51″ 34°46′43″ 200 Northeast 151 d Tengzhou City East Mountain 117°23′13″ 34°55′51″ 120 East 155 d Tengzhou City Hutou Mountain 117°16′44″ 34°53′28″ 120 Northwest 166 d Tengzhou City Mushi Forest Farm 117°16′59″ 34°58′08″ 100 South 183 d Tengzhou City Hulutao 117°16′34″ 34°52′58″ 80 Northeast 200 a Shanting District Beiyu 117°25′53″ 35°08′46″ 360 Northeast 3.2 Experimental methods 3.2.1 Extraction and quality assessment of total plant DNA Genomic DNA was extracted from the leaves of 100 Platycladus orientalis samples using a modified cetyltrimethylammonium bromide (CTAB) method. After the extracted DNA was completely dissolved, its quality was assessed by electrophoresis on 2% agarose gels. 3.2.2 Primer screening In this study, SSR primers of Platycladus orientalis were developed based on the identification of SSR loci and primer screening from P. orientalis transcriptome sequences, and a total of 45 pairs of SSR primers were initially selected. Prior to large-scale PCR amplification and sequencing of all individuals, eight individuals were randomly selected for preliminary screening of the 45 microsatellite primers (Figure 5). Using the annealing temperature of 58 °C reported in the literature as a reference, PCR products were examined by 3% agarose gel electrophoresis and capillary sequencing. Primers with poor amplification efficiency or unclear banding patterns were discarded. Ultimately, seven pairs of SSR primers that produced clear gel electrophoresis profiles, could be stably amplified in all populations, showed satisfactory performance, and were easy to score and statistically analyze were selected for subsequent analyses. 3.2.3 SSR analysis In this study, seven pairs of polymorphic primers with clear and well-resolved DNA bands were selected (Table 6). Detailed information on the PCR reaction system (Table 7) and amplification program is provided below.
Plant Gene and Trait 2026, Vol.17, No.1, 1-11 http://genbreedpublisher.com/index.php/pgt 9 Figure 5 Amplification and detection of primers 4, 18, SF3, SF14, SF4, SF12 and SF13 Note: 1~8 The number of strains; M: 50bp DNA ladder Table 6 Information of microsatellite primers used in this study Locus name Dye Primer sequence (5´-3´) Tm (℃) Allele size (bp) Repeated motif SF12 5`6-FAM F:AAACGAATGAGGCTGAATGG 58 150-200 (AT)6 R:GGATGCACGCAATTTTCTTT SF3 5`6-FAM F:GAGAGCTCTGCTGCCATCTT 58 150 (TC)6 R:ATAACGTTCCCTGGCATCTG SF4 5`6-FAM F:ATAAAAAGTCCCCGGAGCAT 58 100-150 (AG)9 R:GCCAGTGAAATTGAGGTTGC 18 5`6-FAM F:ACATTGATTTGCATTGGGGT 58 200-250 (CA)6 R:AGAGCACATTCCGGTACCAC SF13 5`HEX F:ACGGCCTTTGTTTTCTCTCA 58 250-300 (GT)7 R:AAACCGCCAACACAGGTAAT SF14 5`HEX F:CTTCGTCCCCGATACAAGAG 58 200-300 (CAG)6 R:CATCATGCCCGATATCATCA 4 5`HEX F:AGTGAGAGCACCTGCTGGAT 58 300 (TTC)5/(GGGTAAA)3 R:AGCAGTGGGCTTTACCCTTT Table 7 The PCR reaction system of the microsatellite markers Component Volume (μL) (Vazyme)2×Taq Master mix 12.5 Forward primer 1.5 Reverse primer 1.5 ddH2O 6 DNA template 1.5 Total 20 The PCR reaction program was as follows: 94 °C for 3 min; 30 cycles of 94 °C for 30 s, 58 °C for 30 s, and 72 °C for 1 min; followed by a final extension at 72 °C for 5 min, and then held at 4 °C. After completion of the PCR reactions, the products were examined by electrophoresis on 3% agarose gels. Qualified PCR amplification products were sent to an automated sequencer (Applied Biosystems) for allele genotyping. GeneMarker software was used to read allele sizes, and genotyping results were obtained for 100 Platycladus orientalis individuals.
Plant Gene and Trait 2026, Vol.17, No.1, 1-11 http://genbreedpublisher.com/index.php/pgt 10 PowerMarker V3.25 software was used to analyze the genotype data, including the number of alleles, number of genotypes, heterozygosity, and polymorphic information content (PIC) for different sample combinations. Genetic distances among varieties were also calculated, and clustering was performed using the unweighted pair-group method with arithmetic means (UPGMA) (Liu, 2005). Author Contributions Zhou Jilei and Li Jingtao were responsible for the experimental design and the execution of the experimental research. Zhou Jilei and Zhang Liudong carried out data analysis and prepared the first draft of the manuscript. Fu Yinyin completed the experimental design and analysis of the experimental results. Chen Yong participated in sample collection for the study. Li Jingtao conceived and led the project and provided guidance on experimental design, data analysis, and manuscript writing and revision. All authors read and approved the final manuscript. Acknowledgements This study was supported by the Shandong Provincial Forestry Science and Technology Innovation Project “Efficient Cultivation and Demonstration of Superior Native Tree Species,” under the subproject “Research on Key Technologies for the Establishment of Primary Seed Orchards of Platycladus orientalis and Pinus thunbergii” (2019LY001). References Barbara T., Palma-Silva C., GECELE M. Paggi G.M., Bered F., Fay M.F., and Lexer C., 2007, Cross-species transfer of nuclear microsatellite markers: potential and limitations, Molecular Ecology, 16(18): 3759-3767. https://doi.org/10.1111/j.1365-294X.2007.03439.x Falush D., Wirth T., Linz B., Pritchard J.K., Stephens M., Kidd M., Blaser M.J., Graham D.Y., Vacher S., Perez-Perez G., Yamaoka Y., Me’graud F., Otto K., Reichard U., Katzowitsch E., Wang X., Achtman M., and Suerbaum S., 2003, Traces of human migrations in Helicobacter pylori populations, Science, 299(5612): 1582-1585. https://doi.org/10.1126/science.1080857 Guichoux E., Lagache L., Wagner S., Chaumeil P., LÉGER P., Lepais O., Lepoittevin C., Malausa T., Revardel E., Salin F., and Petit R.J., 2011, Current trends in microsatellite genotyping, Molecular Ecology Resources, 11(4): 591-611. https://doi.org/10.1111/j.1755-0998.2011.03014.x Huang L.S., Song J., and Sun Y.Q., 2018, Pollination dynamics in a Platycladus orientalis seed orchard as revealed by partial pedigree reconstruction, Canadian Journal of Forest Research,48: 952-957. https://doi.org/10.1139/cjfr-2018-0077 Jin Y., 2020, Genetic evaluation of the breeding population of Platycladus orientalis and management strategies, Beijing Forestry University, Supervisors: Wang X. and Mao J., pp.79-80. Jing D., Luo X., Chen L., Li H., Tang L., and Cao S., 2020, Genetic diversity analysis of 78 walnuts based on SSR molecular marker, Acta Agriculturae Jiangxi, 32(6): 11-16. Kalia R.K. Rai R.K., Kalia S., Singh R., and Dhawan A.K., 2011, Microsatellite markers: an overview of the recent progress in plants, Euphytica, 177(3): 309-334. https://doi.org/10.1007/s10681-010-0286-9 Lei A.A. 2018, Genetic diversity of ancient Platycladus orientalis population in Qiao Mountain and DNA fingerprint of the old tree planted by Huang Di, Northwest A&F University, Supervisor: Li Z., pp.17-18. Lexer C., Welch M.E., Raymond O., and Rieseberg L.H., 2003, The origin of ecological divergence in Helianthus paradoxus (Asteraceae): selection on transgressive characters in a novel hybrid habitat, Evolution, 57(9): 1989-2000. https://doi.org/10.1111/j.0014-3820.2003.tb00379.x Lin Z., Anru L., and Vendramin G.G., 2013, Old-growth Platycladus orientalis as a resource for reproductive capacity and genetic diversity, PLoS One, 8(2): e56489. https://doi.org/10.1371/journal.pone.0056489 Liu K., and Muse S.V., 2005, PowerMarker: an integrated analysis environment for genetic marker analysis, Bioinformatics, 21(9): 2128-2129. https://doi.org/10.1093/bioinformatics/bti282 Liu Y., Yang S.X., Ji P.Z., and Gao L.Z., 2012, Phylogeography of Camellia taliensis (Theaceae) inferred from chloroplast and nuclear DNA: insights into evolutionary history and conservation, BMC Evolutionary Biology, 12(1): 92. https://doi.org/10.1186/1471-2148-12-92 Miao H., 2018, Studies on the chemical constituents and pharmacological activities of Platycladi cacumen, Jilin Agricultural University, Supervisor: Bao H., pp.49-51. Reisch C., Mayer F., Ruther C., and Nelle O., 2007, Forest history affects genetic diversity-molecular variation of Dryopteris dilatata (Dryopteridaceae) in ancient and recent forests, Nordic Journal of Botany, 25(5‐6): 366-371. https://doi.org/10.1111/j.0107-055X.2008.00188.x Rieseberg L.H., 1995, The role of hybridization in evolution: old wine in new skins, American Journal of Botany, 82(7): 944-953. https://doi.org/10.1002/j.1537-2197.1995.tb15711.x
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Plant Gene and Trait 2026, Vol.17, No.1, 12-19 http://genbreedpublisher.com/index.php/pgt 12 Research Report Open Access Regulatory Effects of Nursery Mode and Canopy Closure on the Establishment Survival Rate of Tetrastigma hemsleyanum and Delineation of the Optimal Closure Range Jianhui Li 1, Yehua Zhang 2, Yumin Fang 1, Jianzhong Fan 1, Yonghong Xu 1 1 Jiande Shouchang Forest Farm of Zhejiang, Jiande, 311600, Zhejiang, China 2 Jiande Forest Farm of Jiande City, Jiande, 311604, Zhejiang, China Corresponding email: 644295636@qq.com Plant Gene and Trait, 2026, Vol.17, No.1 doi: 10.5376/pgt.2026.17.0002 Received: 30 Dec., 2025 Accepted: 30 Jan., 2026 Published: 15 Feb., 2026 Copyright © 2026 Li et al., This is an open access article published under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Preferred citation for this article: Li J.H., Zhang Y.H., Fang Y.M., Fan J.Z., and Xu Y.H., 2026, Regulatory effects of nursery mode and canopy closure on the establishment survival rate of Tetrastigma hemsleyanum and delineation of the optimal closure range, Plant Gene and Trait, 17(1): 12-19 (doi: 10.5376/pgt.2026.17.0002) Abstract To clarify the regulatory factors affecting the establishment survival rate of Tetrastigma hemsleyanum, cutting propagation experiments and field establishment trials were conducted to compare survival performance under different nursery modes and canopy closure conditions. The results demonstrated significant differences in survival rates among the three nursery modes, with container substrate cultivation showing significantly higher survival than direct field cuttings. Establishment survival also differed significantly across canopy closure levels, exhibiting a unimodal response pattern along the closure gradient. Quadratic regression analysis indicated that the predicted maximum survival rate occurred at a canopy closure of approximately 0.67. Based on comprehensive statistical analyses and trend fitting, the optimal canopy closure range for the establishment of T. hemsleyanum was determined to be 0.6–0.7. These findings provide quantitative support for understory cultivation management of T. hemsleyanum. Keywords Tetrastigma hemsleyanum; Establishment; Nursery mode; Canopy closure; Survival rate 1 Introduction Tetrastigma hemsleyanum Diels et Gilg is a perennial climbing vine belonging to the Vitaceae family and is one of the important medicinal resource plants in southern China. Its tuberous roots are rich in polysaccharides, flavonoids, and various bioactive compounds, exhibiting considerable pharmacological potential in anti-inflammatory, antitumor, and immunomodulatory applications. With increasing market demand and continuous depletion of wild populations, artificial cultivation has become an essential approach for ensuring sustainable resource utilization. Within the cultivation system, establishment represents the critical transition from nursery production to subsequent field management. The survival rate during this stage directly affects planting costs, population structural stability, and future yield potential. Forest ecological studies have demonstrated that the seedling establishment phase often constitutes a demographic bottleneck in regeneration processes, where high mortality restricts the transition of individuals to stable populations (Chang-Yang et al., 2021; Stone et al., 2025). Under closed canopy conditions, seedlings may persist in the understory for extended periods, yet only a small proportion successfully overcome early survival constraints, thereby influencing community structure and regeneration trajectories (Lin et al., 2014). Therefore, improving establishment survival is a prerequisite for large-scale cultivation and stable production. T. hemsleyanum is commonly distributed along forest edges or in open woodland environments and is considered a typical understory-adapted species. Canopy closure, as a structural indicator of canopy coverage, directly regulates understory light intensity, light quality, and microclimatic conditions. Under closed canopies, light availability may decline to 10%~15% of full sunlight, substantially affecting seedling photosynthetic performance and carbon balance (Zhou et al., 2023). Shade-tolerant or semi-shade-tolerant species generally exhibit higher light-use efficiency under moderate diffuse light, whereas excessive irradiance may induce photoinhibition and severe shading may reduce net photosynthetic rates due to insufficient light availability (George and Bazzaz, 1999; De Lombaerde et al., 2020). Variations in canopy gap size and openness can markedly alter early seedling survival conditions; however, increased light availability may simultaneously promote rapid expansion of
Plant Gene and Trait 2026, Vol.17, No.1, 12-19 http://genbreedpublisher.com/index.php/pgt 13 understory vegetation, generating an ecological filtering effect (Lu et al., 2021; Liu et al., 2022). Thus, canopy closure not only determines the light environment but also indirectly influences water balance and neighborhood competition intensity, thereby jointly affecting establishment survival. Nevertheless, quantitative studies examining the gradient response of T. hemsleyanum establishment survival to canopy closure and delineating an optimal closure range remain limited. In addition to light conditions, nursery mode constitutes a key technical factor influencing establishment success. Global-scale restoration studies have shown that seedling size and root development quality significantly affect post-transplant survival (Andivia et al., 2021). Larger seedlings or those with well-developed root systems typically exhibit enhanced water uptake capacity and carbon reserves, thereby improving tolerance to drought or low-light stress (Wu et al., 2024). Container cultivation can improve substrate structure and rhizosphere aeration, contributing to root integrity and facilitating recovery after transplanting, whereas direct field cuttings are more susceptible to soil compaction and pathogen pressure. The degree of matching between seedling quality and stand conditions is therefore critical for successful establishment. However, in the cultivation practice of T. hemsleyanum, the combined regulatory effects of nursery mode and canopy closure have not yet been systematically compared or ecologically interpreted. The present study focuses on the establishment survival rate of T. hemsleyanum, systematically comparing responses under different nursery modes and canopy closure conditions. By analyzing their regulatory effects and delineating the optimal canopy closure range, this study aims to provide a scientific basis for large-scale understory cultivation of T. hemsleyanum and offer reference insights for ecological suitability studies of other understory medicinal plants. 2 Materials and Methods 2.1 Study area The experimental site was located in the Lühetang forest region of Shouchang Forest Farm, Zhejiang Province, China. The area is characterized by a subtropical humid monsoon climate, with a mean annual temperature of 16 °C~18 °C and abundant annual precipitation. The terrain consists primarily of low mountains and hills, with elevations ranging from 200 to 400 m above sea level. The soil type is red soil with slightly acidic properties and a soil depth generally exceeding 30 cm. The dominant forest types include Cunninghamia lanceolata plantations, Phyllostachys edulis (Moso bamboo) forests, natural broadleaf forests, and Metasequoia glyptostroboides stands, providing suitable ecological conditions for understory cultivation experiments. 2.2 Cutting propagation experiment design 2.2.1 Nursery mode settings Cutting propagation experiments were conducted in spring 2021. Cuttings were collected from healthy 1-3-year-old mother plants. Each cutting contained 2-3 nodes, with a length of 10-15 cm and at least two retained leaves. Three nursery modes were established: (1) Mode I: Container cultivation in a greenhouse using a self-formulated substrate composed of peat (20%), organic fertilizer (20%), rice husk powder (10%), yellow subsoil (48%), and calcium–magnesium phosphate fertilizer (2%). Container size was 6.5 cm ×6.5 cm. (2) Mode II: Non-woven fabric container cultivation. The substrate consisted of peat (40%), rice husk powder (10%), organic fertilizer (10%), vermiculite (10%), and perlite (25%). Container size was 5 cm ×8 cm. (3) Mode III: Direct cutting insertion in prepared field beds in the forest, with trenches 30 cm wide and 30 cm deep. Each nursery mode included 50 randomly assigned cuttings per replicate, with three replicates per treatment, totaling 450 cuttings.
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