Open access peer-reviewed chapter - ONLINE FIRST

Research Progress on Iron-Heart Cunninghamia lanceolate

By Ninghua Zhu, Xiaowei Yang, Zhiqiang Han and Xiao Can

Submitted: July 5th 2021Reviewed: October 19th 2021Published: December 8th 2021

DOI: 10.5772/intechopen.101286

Downloaded: 22

Abstract

Cunninghamia lanceolate (Lambert.) Hooker is one of the main fast-growing timber forest species in southern China which has a long history of cultivation and spreads across 28 provinces, cities, and regions. Recently, a variant of fir was discovered in the Xiaoxi National Nature Reserve in Hunan Province. The heartwood is hard as iron and its ratio is more than 80%, with the especial character of anti-corruption. It is a natural germplasm resource, called Iron-heart Cunninghamia lanceolate. Study on it is still in the stage of data accumulation. In this paper, we studied it from three points as follows: (1) Plus tree selection and construction of germplasm resources nursery. (2) Study on cone and seed quality. (3) Genetic structure analysis of natural population. The research of Iron-heart Cunninghamia lanceolate lays a theoretical foundation for the protection, development, and utilization of the black-heart wood germplasm resources of Iron-heart Cunninghamia lanceolate in the future.

Keywords

  • germplasm collection
  • plus tree selection
  • seed and cone quality
  • genetic diversity

1. Introduction

The Chinese fir, Cunninghamia lanceolate(Lambert) Hooker, belongs to the Cupressaceaefamily, which is the family with the largest number of genera among Gymnospermae and includes a number of other significant species in particular, Taiwania Hayata, Cryptomeria D. Don, Glyptostrobus Endl, etc. [1, 2]. As an evergreen coniferous tree species, C. lanceolateis native to northern Vietnam and southern China. Because of its desirable wood properties, fast growth, and high disease resistance, C. lanceolatehas been widely grown in China for 3000 years [3, 4, 5]. Recently, a unique natural wild variety of Chinese fir with a high ratio of heartwood and high wood quality was inadvertently found in provenance. Importantly, this Chinese fir has a high corrosion prevention property compared to other species, its wood is dark, and native people use it to make furniture, buildings, and even coffins [6, 7].

The study of cone and seed morphological characteristics of Iron-heart Cunninghamia lanceolateis helpful to master phenotypic diversity and formulate population protection strategies [8]. Selecting the best family for seed collection and seedling breeding has a key impact on improving the quality of Iron-heart China fir seedlings [9, 10]. Wild plants are important gene resources for breeding excellent varieties, so it is more important to study the genetic diversity and variation of wild populations [11].

For the germplasm resources of Cunninghamia lanceolate, the most common way is to preserve them by ex-situ conservation [12], and the establishment of germplasm collection area of Cunninghamia lanceolateis usually realized by grafting. Combining the conservation and application of germplasm resources in the nursery, on the one hand, the improved varieties were screened and preserved by selecting the best in the experimental area, on the other hand, the germplasm resources bank was enriched and high-quality breeding materials were provided. At present, in the field of science, the conservation and application of germplasm resources have been adopted by seed banks and gene banks in most countries, which can be summarized as “two less and one rich”, with less use area, less funds, and rich germplasm resources [13]. In addition, the rapid development of modern biotechnology makes it possible to use tissue culture in vitro preservation of Cunninghamia lanceolate. In a word, we can take a variety of forms to achieve the preservation of Chinese fir germplasm resources, but we should consider different places, depending on the situation, choose the best way to collect and preserve high-quality resources.

Determining genetic diversity and population structure, which are important for characterizing germplasm under investigation, constitute important steps in plant breeding [14, 15]. However, due to the impact of agricultural climate change, morphological characteristics provide limited genetic information [16]. Therefore, molecular markers unaffected by environmental changes are necessary to estimate genetic diversity and population structure [17, 18]. Based on molecular markers, genetic diversity analysis, germplasm characterization and evolution studies have been possible in the last 30 years [19, 20]. Molecular markers, such as restriction fragment length polymorphism (RFLP), random-amplified polymorphic DNA (RAPD), amplified fragment length polymorphism (AFLP), inter-simple sequence repeat (ISSR) and simple sequence repeat, microsatellite (SSR), have previously been used to study the genetic diversity and population structure of cultivated and natural breeding populations of many conifers [21]. SSR markers, which are relatively abundant, inexpensive, and provide more informative than bi-allelic markers, have been used to detect the genetic diversity, population structure, and even genetic relationships among landraces and cultivars of Cunninghamia lanceolate[22, 23, 24]. Single-nucleotide polymorphisms (SNPs), as a type of third-generation molecular marker with high stability and diversity, are expensive to analyze compared with SSR and AFLP markers [25, 26, 27].

Advertisement

2. Research contents

2.1 Area sampled

Xiaoxi National Nature Reserve is located in Yongshun County, Western Hunan Province, at the western end of Wuling Mountain. It is located at 110°6′50″–110°21′35″ E and 28°42′15″–28°53′55″ N. The annual average temperature is between 11 and 12°C, the frost-free period is 250 days, the annual precipitation is between 1300 and 1400 mm, the parent material of soil is sand shale, the soil fertility is high, the total forest storage is 2,223,500 cubic meters, the area has high mountains, dense forests, crisscross valleys, a wide variety of rare plants, rare birds and wild animals, with more than 1000 species of plants in 94 families. There are nearly 200 species of wild animals in the original secondary forest, including 68 species of national key protected animals such as leopard, clouded leopard, and white-necked long-tailed pheasant [28], which are rare in the world and unique in China. The only surviving evergreen broad-leaved primary secondary forest in the 13 provinces of central and southern China is protected from Quaternary glaciers.

2.2 Sampling design

The Iron-heart Cunninghamia lanceolatewas listed and numbered. According to the principle of uniform dispersion and a random selection, 33 cones of mother trees (52 years old) were collected in the mother forest in mid-October 2019 and were brought back to Central South University of Forestry and Technology to dry naturally for later use in 10, 2019.

About 35 plus trees of Iron-heart Cunninghamia lanceolatewere selected. Fresh cuttings are collected and used as materials for the establishment of a germplasm resource nursery. See Appendix Table S1 for the basic information. The germplasm resource nursery is set up in the Chinese fir test demonstration forest base in Xichong Village, Majiang Town, Chaling County, Zhuzhou City, Hunan Province. It has red soil and good site conditions. The demonstration forest has Guangxi provenance seedlings (Guangxi-2.5) and Fujian provenance vegetative Line cutting seedlings-020 (Fujian-020) and Fujian clone Zhongyuan cutting seedlings-061 (Fujian-061) pure forest of young Chinese fir, and grow well.

In total, 548 Iron-heart Cunninghamia lanceolatefrom nine plots (CTY, JZW-1, JZW-2, JZW-3, LYP-1, LYP-2, LYP-3, LYP-4, and XNC) were collected, covering the entire range of Iron-heart Cunninghamia lanceolatefrom (Appendix Table S2) (According to the natural distribution of the natural population of iron-heart Cunninghamia lanceolate, we found that it is concentrated in 9 mountains. Therefore, we divided it into 9 plots for population genetic structure analysis). Growth indexes and morphological parameters were considered as selection criteria for the sampled trees, which were chosen by a dominant comparative and comprehensive evaluation method in typical natural forests. The longitude, latitude, and altitude of each sample were determined using a handheld GPS (WGS-84) (Garmin eTrex Handheld GPS; Garmin). Fresh leaves of each voucher sample were collected in a 10 ml freezing tube, transported back to the laboratory in a liquid nitrogen tank, and deposited at −80°C.

2.3 Data sampled

2.3.1 Quality determination of cones and seeds

  1. Take 10 kg fresh cones from each plant and dry them. Test the quality of cones and seeds. Repeat for 3 times in each family. The cone length, cone width, seed length, and seed width are measured with a vernier caliper. The total cone quality and seed quality are weighed with an electronic balance (accurate to 0.01 g) to calculate the cone seed extracting percentage. Cone seed extracting percentage = total seed quality ÷ total cone quality × 100%.

  2. About 1000 seeds were randomly selected, and the quality of 1000 seeds (g) was measured in the air-dry state, repeated 3 times.

  3. Seed goodness test. Seed goodness = real number of good seeds ÷ real number of tested seeds.

  4. The seed germination rate was determined by the standard germination method. Take 150 seeds from each plant family, sterilize with 10% antifomin for 15 min, wash 3 times with sterile water, and soak in sterile water at 25°C for 24 h. Take a sterile petri dish, spread it with sterile filter paper, and moisten it with sterile water; spread the soaked seeds on the filter paper, and place them in a 25°C light incubator for cultivation. Repeat 3 times each, observe and count the germination situation once every 5 days, and count the real number of germinated species after 15 days to calculate the germination rate (%). Germination rate = real number of germinated seeds ÷ real number of initial seeds × 100%.

2.3.2 DNA extraction, amplification, and microsatellite genotyping

A Plant Genomic DNA Kit (TIANGEN Biotech, Beijing, China) was used to extract total genomic DNA. Genomic-SSR polymerase chain reaction (PCR) was performed in a 20 μl reaction volume containing 4.0 μl double-distilled water, 4.0 μl genomic DNA, 10.0 μl 2× Taq Plus PCR MasterMix (TIANGEN, Beijing, China), 1.0 μl forward primer and 1.0 μl reverse primer. The PCR conditions included denaturation for 5 min at 95°C, 30 cycles of 30 s at 94°C, 90 s at the annealing temperature for each SSR marker in the reaction, 1 min at 72°C, and 10 min at 60°C for a final extension. In total, 15 primer pairs with highly polymorphic loci (Table 1), for which the clarity and reproducibility of the DNA fragments were amplified, were selected from published papers [29, 30, 31].

LociForward primerReverse primerRepetitive unitProduct size (bp)Ta°C
contig476_526DTTTGGGACCTTATGGAGGTGGAGAAACCACCAGGTTGAGAAGCAGC(GGA)9153–15957.10
contig7616_683BGAGCCGTGAAGAACGAAGGTCTCACGATCGGATTGTCTCAGAAACG(GAA)12260–28157.05
contig4728_384BATTATCCGAGGCAGATACGCACCTTCTCCGTATTTGATCCATCGC(GGA)10336–35455.05
contig5410_1886AGGCTCGAGTTTGCATCTCACACCACATCCAATCCATACAGGAGGG(TC)9210–32056.70
contig16181_1285CGGTACTGCGAATCTTCAAATCCTGTTCAAGAAAGGAAGCAAACGG(TC)9293–29753.25
contig406_1209CTCATCAGCCTCAGTTTGTACTTGCGCAATCATGGGCTCTCTGCAC(AT)9348–38456.00
Unigene685CCTTTCTTTTCTGCACCAGCCTGTGCCTGATGGCTAAACA(GGT)5190–28456.90
Unigene754AGACGGTCGTTGACGAAAAACTCTTTTCCACACACGCAAA(GCA)4124–29855.35
Unigene840CAGGACGCCTGAGAATTGTTTCATCGGTAGAAGGAATGGC(AAG)5162–16956.65
Unigene1061GAAACAAACAAGGGAGGCAAAGGTCCAAATCCACCTGGTC(AGG)9150–27657.70
Unigene491TGGAAATGGCTGTAAAGGAGTGTGCTGAGCCATATTCACA(GAAG)3120–16855.30
contig6319_250CGCGGCCATTTATATCATCTTCCACGCCTGTAATTCATCTCCGTC(GAA)9126–13557.30
contig1560_1789DTTTCGGCTCTCCGACTCCTTAACAGAATCGCGTCCAGAACACAGAG(CT)11129–14759.45
CLSSR6ATTTCAAACACCTCTCCTTTCGGAATTCCTAGACAAAGATGG(CTTC)4136–26852.35
CLSSR8ATCGTTGCTTTCAATCTTATGATCCAACTGACACACAAAATC(CTTT)3143–16551.80
Ta°C represent annealing temperature of PCR cycles

Table 1.

Primary simple sequence repeat primers used in the study.

The forward primer had a universal M13 primer tail and a universal M13 primer fluorescently labeled with 6-carboxy-x-rhodamine, tetramethyl-6-carboxyrhodamine, 6-carboxy-fluorescein, or 5-hexachlorofluorescein. The final PCR products were separated based on capillary electrophoresis fluorescence using an ABI3730xl DNA Analyzer (Genewiz Inc., Beijing, China). The results were analyzed using GeneMarker 1.75 software (SoftGenetics LLC, State College, PA, USA).

2.4 Statistical analyses

Excel 2019 and R4.0.3, Rstudio software were used for summary processing and nested analysis of variance, Pearson correlation analysis, and principal component analysis. Among them, R4.0.3 calculates the mean value, standard deviation, and coefficient of variation of the seed and cone traits; based on the nest’s linear model variance analysis between and within groups differences, and Tukey HSD test; using R package Hmisc 4.4.2 [32] to calculate Pearson Correlation coefficient and p-value, use corrplot 0.84 [33] to draw the correlation graph.

The polymorphism information content (PIC) was used to estimate the allelic variation of SSR by applying the formula PIC = 1-i=0nPi2, where Pi is the frequency of the ith allele and n is the number of alleles detected for given SSR markers. GenALEx 6.5 [34] was used to estimate the genetic diversity indices of each locus and population.

The genetic diversity and population structure of the accessions were further investigated by analysis of molecular variance (AMOVA) using GenAlEx 6.5. The program STRUCTURE v2.3.4 [35] was used to analyze the genetic structure by employing Bayesian clustering analysis with the admixture model of independent allele frequencies. STRUCTURE HARVESTER (http://taylor0.biology.ucla.edu/structureHarvester/) was used to evaluate the most likely number (K) of genetic clusters. The data derived from the STRUCTURE analysis were visualized as bar charts and pie charts using ArcMap v10.0 and DISTRUCT v1.1 software [36, 37]. Interpolation of ArcGIS was used to forecast the expected heterozygosity (He) and the private allele frequency (Fp) of all Chinese firs included. The ArcGIS (Esri) program was used to map the distribution of the He of populations and Fp by employing a kriging spherical interpolation method.

Advertisement

3. Results

3.1 Cone and seed quality

In this study, we use 12 traits (germination rate, seed quality, seed length-width ratio, seed length, cone seed extracting percentage, seed width, total cone quality, goodness, cone length, Seed quality (1000), cone length-to-width ratio, cone width) to assess the of quality of cones and of seeds.

3.1.1 Differences in seed quality of different families

The results in Table 2 (code is the number of different mother trees) show that the variation range of the cone length of Iron-heart Cunninghamia lanceolateis 3.15–6.13 cm, the average is 4.66 cm, and the coefficient of variation is 18.97%; the variation range of cone width is 3.56–2.15 cm, the coefficient of variation is 12.18%, and the average is 2.95 cm; the variation range of the total quality of the cone is 1.15–2.40 kg, with an average value of 1.66 kg. The variation range of seed quality is large, between 0.09–0.33 kg, the coefficient of variation is 36.50%, and the average value is 0.20 kg; the cone seed extracting percentage is 5.59–19.02%, and the coefficient of variation is 24.42%, but the overall cone seed extracting percentage is low. Seed quality of Iron-heart Cunninghamia lanceolatefrom different families is quite different. The largest seed length, seed width, and seed length-to-width ratio are 9.77 mm, 5.75 mm, and 3.03 respectively; the smallest ones are 4.36 mm, 2.05 mm, and 1.16 mm, respectively; the average value are 6.31 mm, 2.35 mm, and 2.69 mm; the coefficients of variation are 26.02%, 22.15%, and 26.91%, respectively. The average seed quality of 1000 seeds is 7.06 g, the maximum is 10.54 g; the average of goodness is 67.65%, and the coefficient of variation is 20.53%. The variation range of seed germination rate is 5.33% ∼ 63.00%, the coefficient of variation is 52.34%; the seed germination rate of TXS-256 and TXS-234 families is the highest, TXS-29 and TXS -30 is the next; TXS-205, TXS-265, TXS-16 germination rates are all lower than 10%. The quality of cones and seeds of families is different in different traits, so it is impossible to evaluate the quality of cones and seeds from a single character.

CodeCone length (cm)Cone width (cm)Length/widthCone quality (kg)Seed quality (kg)Cone seed extracting percentage (%)
TXS-163.29 ± 0.032.66 ± 0.021.24 ± 0.011.34 ± 0.010.12 ± 0.029.22 ± 1.34
TXS-174.08 ± 0.052.54 ± 0.021.60 ± 0.031.93 ± 0.070.22 ± 0.0211.25 ± 1.43
TXS-183.77 ± 0.023.07 ± 0.031.23 ± 0.031.32 ± 0.080.14 ± 0.0110.63 ± 0.62
TXS-195.49 ± 0.023.09 ± 0.011.77 ± 0.031.86 ± 0.030.21 ± 0.0111.12 ± 0.52
TXS-295.76 ± 0.033.17 ± 0.021.82 ± 0.022.21 ± 0.020.32 ± 0.0514.33 ± 0.13
TXS-305.76 ± 0.033.17 ± 0.021.82 ± 0.022.21 ± 0.020.32 ± 0.0814.33 ± 0.13
TXS-2024.12 ± 0.022.36 ± 0.011.74 ± 0.011.56 ± 0.010.17 ± 0.0110.89 ± 0.55
TXS-2053.15 ± 0.002.15 ± 0.031.46 ± 0.021.55 ± 0.010.09 ± 0.085.59 ± 0.31
TXS-2175.24 ± 0.012.98 ± 0.051.76 ± 0.011.61 ± 0.010.21 ± 0.0713.04 ± 0.07
TXS-2195.95 ± 0.043.25 ± 0.011.83 ± 0.021.75 ± 0.040.33 ± 0.0119.02 ± 0.74
TXS-2244.57 ± 0.053.46 ± 0.011.32 ± 0.041.22 ± 0.060.19 ± 0.0815.34 ± 0.42
TXS-2285.85 ± 0.042.97 ± 0.011.97 ± 0.011.93 ± 0.050.25 ± 0.0313.08 ± 1.19
TXS-2345.84 ± 0.033.09 ± 0.061.89 ± 0.052.16 ± 0.040.33 ± 0.0115.42 ± 0.84
TXS-2365.02 ± 0.023.56 ± 0.021.41 ± 0.011.81 ± 0.020.22 ± 0.0411.95 ± 0.31
TXS-2373.66 ± 0.012.88 ± 0.011.27 ± 0.011.45 ± 0.010.15 ± 0.0110.12 ± 0.37
TXS-2384.61 ± 0.013.18 ± 0.011.45 ± 0.021.77 ± 0.010.19 ± 0.0110.71 ± 0.39
TXS-2394.35 ± 0.032.47 ± 0.011.76 ± 0.011.15 ± 0.010.15 ± 0.0912.76 ± 0.34
TXS-2565.89 ± 0.013.56 ± 0.001.66 ± 0.012.40 ± 0.010.31 ± 0.0213.00 ± 0.76
TXS-2595.64 ± 0.023.24 ± 0.041.74 ± 0.011.56 ± 0.010.28 ± 0.0117.74 ± 0.38
TXS-2643.27 ± 0.012.35 ± 0.011.39 ± 0.061.18 ± 0.010.09 ± 0.077.34 ± 0.36
TXS-2653.45 ± 0.032.79 ± 0.031.24 ± 0.021.16 ± 0.010.12 ± 0.0710.06 ± 0.35
TXS-2673.89 ± 0.022.89 ± 0.051.35 ± 0.041.34 ± 0.010.16 ± 0.0611.94 ± 0.07
TXS-2685.10 ± 0.023.16 ± 0.011.62 ± 0.012.14 ± 0.010.25 ± 0.0411.53 ± 1.74
TXS-2704.03 ± 0.022.91 ± 0.021.39 ± 0.011.39 ± 0.040.13 ± 0.099.38 ± 0.03
TXS-2763.91 ± 0.012.69 ± 0.021.45 ± 0.011.57 ± 0.050.13 ± 0.028.05 ± 0.29
TXS-3494.99 ± 0.002.98 ± 0.011.67 ± 0.001.84 ± 0.030.23 ± 0.0212.32 ± 1.29
TXS-3633.88 ± 0.002.34 ± 0.021.66 ± 0.021.62 ± 0.010.17 ± 0.0110.29 ± 0.25
TXS-3655.03 ± 0.012.92 ± 0.451.77 ± 0.031.18 ± 0.010.18 ± 0.0515.54 ± 0.5
TXS-3663.94 ± 0.062.68 ± 0.011.47 ± 0.031.24 ± 0.040.13 ± 0.0210.17 ± 1.58
TXS-3704.87 ± 0.023.12 ± 0.011.56 ± 0.011.64 ± 0.030.18 ± 0.0111.22 ± 1.00
TXS-4006.03 ± 0.113.23 ± 0.011.87 ± 0.032.40 ± 0.160.27 ± 0.0211.40 ± 0.37
TXS-5784.64 ± 0.023.06 ± 0.021.52 ± 0.011.67 ± 0.040.19 ± 0.0111.58 ± 0.75
TXS-6664.75 ± 0.033.06 ± 0.011.55 ± 0.011.94 ± 0.020.21 ± 0.0110.80 ± 0.36
CV/%18.9712.1813.5921.6236.5024.42
SD0.880.360.210.360.070.03
Range3.001.480.981.420.30.14
Mean4.662.951.581.660.211.91

Table 2.

Cone characteristics (average ± standard deviation value) of different iron-heart Cunninghamia lanceolate.

The coefficient of variation is the comprehensive performance of the discrete characteristics of phenotypic traits. The greater the coefficient of variation, the greater the degree of dispersion of traits. The coefficient of variation of seed traits of 33 families is between 12.18% and 51.34%, and the coefficient of variation of each trait has a certain difference. From large to small, it is germination rate > seed quality >seed length-width ratio > seed length > cone seed extracting percentage > seed width > total cone quality> goodness> cone length > seed quality(1000) > cone length-to-width ratio > cone width (Tables 2 and 3).

codeSeed length (mm)Seed width (mm)Length/widthSeed quality (1000) (g)Goodness (%)Germination rate (%)
TXS-164.36 ± 0.043.75 ± 0.011.16 ± 0.017.65 ± 0.0576.67 ± 1.258.67 ± 1.25
TXS-176.11 ± 0.504.90 ± 0.091.25 ± 0.088.57 ± 0.0177.67 ± 2.3624.67 ± 2.05
TXS-185.41 ± 0.033.46 ± 0.011.56 ± 0.056.47 ± 0.0362.67 ± 0.4718.67 ± 0.47
TXS-197.86 ± 0.083.33 ± 0.032.36 ± 0.036.82 ± 0.0173.33 ± 3.6845.67 ± 4.11
TXS-299.77 ± 0.023.78 ± 0.032.59 ± 0.027.81 ± 0.0275.67 ± 3.461.33 ± 1.25
TXS-309.77 ± 0.023.78 ± 0.032.59 ± 0.027.81 ± 0.0375.67 ± 3.461.33 ± 1.25
TXS-2024.41 ± 0.033.56 ± 0.011.24 ± 0.016.12 ± 0.0548.67 ± 0.4714.33 ± 0.47
TXS-2054.44 ± 0.012.53 ± 0.031.76 ± 0.025.67 ± 0.0747.33 ± 4.115.33 ± 0.47
TXS-2178.09 ± 0.043.24 ± 0.012.50 ± 0.016.75 ± 0.0274.33 ± 3.0950.33 ± 0.47
TXS-2199.47 ± 0.064.34 ± 0.012.18 ± 0.018.1 ± 0.0275.67 ± 1.2557.67 ± 2.62
TXS-2246.49 ± 0.023.12 ± 0.052.08 ± 0.016.68 ± 0.0569.33 ± 1.2535.00 ± 0.82
TXS-2288.42 ± 0.023.47 ± 0.012.43 ± 0.016.85 ± 0.0376.67 ± 3.6856.00 ± 2.16
TXS-2349.43 ± 0.023.67 ± 0.022.57 ± 0.017.24 ± 0.0375.00 ± 4.9763.00 ± 2.83
TXS-2366.45 ± 0.083.56 ± 0.031.81 ± 0.026.60 ± 0.0266.33 ± 1.8941.00 ± 0.82
TXS-2375.39 ± 0.022.05 ± 0.062.63 ± 0.084.91 ± 0.0542.67 ± 0.4716.00 ± 0.01
TXS-2386.31 ± 0.032.35 ± 0.012.69 ± 0.014.83 ± 0.0733.67 ± 0.9438.00 ± 0.82
TXS-2395.35 ± 0.023.25 ± 0.041.64 ± 0.076.61 ± 0.0572.00 ± 0.8218.33 ± 0.47
TXS-2569.68 ± 0.024.87 ± 0.031.99 ± 0.028.83 ± 0.0181.00 ± 1.4163.00 ± 5.10
TXS-2598.74 ± 0.102.89 ± 0.013.03 ± 0.036.11 ± 0.0547.33 ± 0.4754.33 ± 0.47
TXS-2644.60 ± 0.073.67 ± 0.061.25 ± 0.026.40 ± 0.0363.33 ± 0.4710.67 ± 5.91
TXS-2654.74 ± 0.053.08 ± 0.011.54 ± 0.026.15 ± 0.0353.33 ± 0.478.67 ± 1.25
TXS-2676.06 ± 0.043.25 ± 0.011.86 ± 0.016.53 ± 0.0564.67 ± 0.4725.67 ± 0.47
TXS-2686.21 ± 0.024.84 ± 0.061.28 ± 0.028.72 ± 0.0183.33 ± 3.6844.67 ± 3.09
TXS-2705.02 ± 0.052.98 ± 0.051.68 ± 0.016.32 ± 0.0558.67 ± 0.4718.00 ± 0.82
TXS-2764.78 ± 0.012.77 ± 0.021.73 ± 0.025.94 ± 0.0451.33 ± 0.4713.33 ± 0.47
TXS-3496.77 ± 0.014.33 ± 0.011.56 ± 0.008.32 ± 0.0181.00 ± 2.9434.00 ± 2.16
TXS-3634.88 ± 0.023.04 ± 0.041.60 ± 0.025.35 ± 0.0550.00 ± 0.8228.67 ± 0.47
TXS-3656.23 ± 0.023.56 ± 0.031.75 ± 0.016.63 ± 0.0566.00 ± 0.8231.67 ± 0.47
TXS-3665.74 ± 0.183.56 ± 0.051.62 ± 0.077.13 ± 0.0574.00 ± 3.5628.67 ± 0.47
TXS-3706.36 ± 0.024.88 ± 0.001.30 ± 0.008.21 ± 0.0081.33 ± 3.3035.33 ± 0.94
TXS-4008.83 ± 0.045.75 ± 0.041.54 ± 0.0110.54 ± 0.0287.67 ± 1.8959.33 ± 1.25
TXS-5786.67 ± 0.024.68 ± 0.021.43 ± 0.058.31 ± 0.0185.33 ± 2.0538.00 ± 2.45
TXS-6665.96 ± 0.043.80 ± 0.021.57 ± 0.027.76 ± 0.0478.00 ± 2.1635.33 ± 0.47
CV/%26.0222.1526.9117.2320.5352.34
SD1.720.810.51.220.140.18
Range5.483.781.925.740.560.63
Mean6.623.641.877.0667.65%34.80%

Table 3.

Seed characteristics (average ± standard deviation value) of different iron-heart Cunninghamia lanceolate.

The P value associated with total cone quality, seed quality, seed germination rate, seed goodness, seed quality (1000), seed width, and cone length-width ratio was less than 0.001 (see the Table 4, variance analysis of 33 iron-heart Cunninghamia lanceolate), indicating that these traits varied greatly among families; the P value associated with of the cone-length factor is less than 0.01, and the P values associated with other factors of other characteristics were less than 0.1. There are minor differences, and differences mainly exist between individuals. The F value of 12 seed characteristics varies from 0.757 to 965.1 between families, and the order of size is cone seed extracting percentage (0.757) < cone width (1.591) < seed length to width ratio (1.704) < seed length (1.91) < germination rate (2.87) < cone length (2.885) < seed quality (3.221) < cone length-to-width ratio (3.845) < total cone quality (5.454) < seed width (14.8) < goodness (22.39) < seed quality (1000, 965.1).

Source of variationDfSSMSF
Total cone quality618078132.425.454 ***
Total seed quality264827185.643.221 ***
Cone seed extracting percentage87769288.410.757
Germination rate456364141.422.87 ***
Goodness398408215.5922.39 ***
Seed quality(1000)93897696.51965.1 ***
Seed width728762121.714.8 ***
Seed length808030100.381.91.
Length/width(seed)687130104.851.704.
Cone length707883112.612.885 **
Cone width596341107.471.591.
Length/width(cone)537353138.733.845 ***

Table 4.

Variance analysis of 33 iron-heart Cunninghamia lanceolate*.

Note: “***”: P < 0.001; “**”: P < 0.01; “*”: P < 0.05; “.”: P < 0.1; “”: P < 1.

3.1.2 Correlation analysis of seed traits of iron-heart Cunninghamia lanceolate

It can be seen from the Figure 1 that the seed germination rate of iron-heart Cunninghamia lanceolateis positively correlated with the other 8 characteristics except for the total cone quality, seed quality, and cone seed extracting percentage. Among them, the germination rate is positively correlated with the cone length, seed quality, seed length-to-width ratio, and seed length are extremely significantly positively correlated at the level of P < 0.001, and are more correlated with seed width, seed length-to-width ratio, seed quality (1000), and goodness at P < 0.01; There was a very significant negative correlation (r = −0.56, P < 0.001) between cone seed extracting percentage and total cone quality, and a very significant positive correlation (r = 0.84, P < 0.001) with seed quality, and the correlation between these three traits and the other eight traits was not significant.

Figure 1.

Correlation analysis of seed and cone characters of iron-heartCunninghamia lanceolate. Note: A–L are: cone length, cone width, cone length-width ratio, total cone quality, seed quality, cone seed extracting percentage, seed length, seed width, seed length-width ratio, seed quality (1000), goodness, and germination rate.

3.1.3 Comprehensive evaluation of seed quality of iron-heart Cunninghamia lanceolate

Analyzing the various characteristics that affect the quality of the cones and seeds of the Iron-heart Cunninghamia lanceolate, it can be seen from the figure that principal components 1 and 2 can explain 65.8% of the variation (Figure 2). Among them, traits A, B, C, G, L has a greater contribution rate to principal component 1, and most of them are cone traits; traits H, J, K, I has a large contribution rate to principal component 2, and most of them are seed traits. The principal component dimensionality reduction method is used to comprehensively evaluate the 12 cones and seed traits of iron-heart Cunninghamia lanceolate. It can be seen from the Table 5 that the cumulative variance contribution rate of the first three main factors can reach 82.30%, which can satisfy the traits of each half-sibling progeny. Therefore, the first three main factors are selected to make a comprehensive evaluation score for iron-heart Cunninghamia lanceolate. Take the characteristic value of the main factor as the weight of each index, and multiply each index to obtain the calculation formula of the main factor comprehensive evaluation score:

Figure 2.

PCA analysis. Note: A–L are: cone length, cone width, cone length-width ratio, total cone quality, seed quality, cone seed extracting percentage, seed length, seed width, seed length-width ratio, seed quality (1000), goodness and germination rate.

TraitsComp.1Comp.2Comp.3Comp.4Comp.5
A0.4080.156
B0.3080.142−0.456−0.511
C0.3080.1040.4070.598
D−0.1240.441−0.6220.486
E0.145−0.541−0.4590.313
F0.1060.130−0.668
G0.3890.1910.1520.105
H0.286−0.453
I0.1350.5730.161
J0.315−0.417
K0.310−0.369−0.135
L0.4030.160
λ2.3341.5641.4080.9720.896
Contribution rate0.4540.2040.1650.0790.067
Total contribution rate0.4540.6580.8230.9020.969

Table 5.

PCA analysis of iron-heart Cunninghamia lanceolate.

F1=0.408X1+0.308X2+0.308X3+0.145X5+0.106X6+0.389X7+0.286X8+0.135X9+0.315X10+0.310X11+0.403X12×2.334E1
F2=0.156X1+0.142X2+0.104X30.124X4+0.130X6+0.191X70.453X8+0.573X90.417X100.369X11+0.160X12×1.564E2
F3=0.441X40.541X50.668X6+0.152X7+0.161X9×1.408E3

The variance contribution rates of the first three main factors are different. In the comprehensive evaluation of growth traits, the focus of each factor needs to be coordinated. The contribution rates of the three factors are 45.4%, 20.4%, and 16.5% as weights, combined with 3 common factors. The contribution rate and factor score Fi, refer to the calculation formula of the comprehensive score, the mathematical model of the comprehensive score of seed traits of iron-heart Cunninghamia lanceolatecan be established:

Dn=F1×45.4%+F2×20.4%+F3×16.5%E4

Using the comprehensive ranking as an indicator, a total of 14 excellent Iron-heart Cunninghamia lanceolate were selected with a 40% selection rate (Table 6).

CodeF1F2F3ScoreRanking
TXS-1613.878−3.0741.5815.93428
TXS-1715.059−4.1922.0676.32322
TXS-1813.916−1.641.86.2823
TXS-1915.962−0.6232.647.55510
TXS-2917.937−0.833.0988.4853
TXS-3017.846−1.2482.9768.3394
TXS-20212.952−2.0231.6465.73932
TXS-20512.394−0.8591.5175.70233
TXS-21715.963−0.3852.5237.5859
TXS-21918.056−1.5912.6788.3155
TXS-22414.879−0.8511.9576.90416
TXS-22816.393−0.562.7217.7778
TXS-23417.425−0.593.0068.2866
TXS-23615.077−1.2692.2576.95914
TXS-23712.6260.832.0816.24524
TXS-23813.4471.0042.3736.70119
TXS-23913.838−1.6121.6856.23225
TXS-25619.568−2.2553.0828.9321
TXS-25915.9820.8172.6267.8567
TXS-26413.25−2.1741.5795.83331
TXS-26513.06−1.3881.6135.91230
TXS-26714.314−1.1951.9436.57520
TXS-26816.472−3.7452.2267.08213
TXS-27013.361−1.3251.7886.09126
TXS-27612.877−1.0631.865.93627
TXS-34916.23−2.9212.2827.14911
TXS-36312.779−0.9211.8445.91829
TXS-36514.714−1.3651.8446.70618
TXS-36614.65−1.9331.8596.56321
TXS-37016.1−3.4052.0526.95315
TXS-40020.197−4.2342.8798.7812
TXS-57816.309−3.1822.1417.10912
TXS-66615.245−2.4752.1726.77517

Table 6.

Comprehensive score and ranking of principal components of 33 black-heart wood Chinese fir.

3.2 Seed garden construction

3.2.1 Grafting and management of the germplasm resource nursery of Iron-heart Cunninghamia lanceolate

3.2.1.1 Seedling grafting

Before grafting, we selected high-quality rootstocks to mark and hang tags. The height of the rootstocks was uniformly about 15.6 cm. The rows are 2 m × 2 m, and at least 10 plants should be planted for each clone. After grafting, apply an appropriate amount of organic fertilizer according to the standard of 30–60 t per hectare to promote the growth and development of Iron-heart Cunninghamia lanceolateand improve the survival rate, stress resistance, cold resistance, and adaptability of grafted seedlings. The trails are set up in Iron-heart Cunninghamia lanceolategermplasm resource nursery, which is mainly used for convenient work such as planting, cultivation, observation, management, and protection. At present, 35 genotypes of superior trees selected from nature reserves are still preserved in the germplasm resource nursery (Table 7). In May of the same year, the research team conducted statistics and surveys on the survival rate of grafting.

CodeBreast diameter/cmAltitude/mGPS(E,N)
TXS-172.0895110.246958, 28.835133
TXS-248.2899110.247068, 28.835290
TXS-341.1845110.247144, 28.833239
TXS-443.2505110.260574, 28.814858
TXS-529.5560110.260804, 28.814984
TXS-644.1563110.260804, 28.814984
TXS-763.0813110.246442, 28.822674
TXS-825.3804110.246186, 28.822969
TXS-951.5800110.247032, 28.823265
TXS-1047.0807110.247682, 28.823303
TXS-1143.0894110.245943, 28.834792
TXS-1235.51000110.242849, 28.834510
TXS-1337.41010110.243119, 28.835489
TXS-1447.0904110.245980, 28.835239
TXS-1546.0894110.246676, 28.834436
TXS-1643.2648110.268425, 28.798110
TXS-1726.9632110.268312, 28.797980
TXS-1827.7648110.268386, 28.798233
TXS-1940.6632110.267831, 28.797993
TXS-2034.4629110.267767, 28.796707
TXS-2154.7902110.247119, 28.835550
TXS-2254.2901110.246885, 28.835296
TXS-2373.0895110.246958, 28.835133
TXS-2448.2899110.247968, 28.835290
TXS-2541.1845110.247444, 28.833239
TXS-2643.2505110.260574, 28.814858
TXS-2729.5560110.260804, 28.814984
TXS-2852.3490110.261149, 28.814843
TXS-2938.7514110.261320, 28.814457
TXS-3027.3511110.261126, 28.814625
TXS-3129.4524110.260469, 28.814065
TXS-3229.0502110.259730, 28.813559
TXS-3337.7494110.269097, 28.814165
TXS-3428.0525110.259179, 28.814850
TXS-3531.8523110.250914, 28.814820

Table 7.

The information of the 35 Iron-heart Cunninghamia lanceolate.

3.2.1.2 Statistics of graft survival rate

The construction of iron-heart Cunninghamia lanceolategermplasm resource nursery was uniformly carried out by splitting, and from the results (Table 8), the average survival rate of grafting was 83%, among which the minimum survival rate of grafting with number TXS-35 was 50%, and the number TXS-30, the highest survival rate of grafting is 96%. It shows that TXS-30 has a high degree of adherence to the test forest fir, and it is suitable as a material for remote preservation of iron-heart Cunninghamia lanceolategermplasm. Experiments have proved that it is feasible and suitable to use the test forest of Chinese fir in Majiang Town as a place where the iron-heart Cunninghamia lanceolateis preserved in a different place, and the method of splitting can realize the clonal reproduction of iron-heart Cunninghamia lanceolateand has a higher survival rate.

CodeGraft survival rate (%)Average number of branchesRootstock trail (cm)Rootstock height (cm)Average total growth (cm)
TXS-18873.5032.1053.40
TXS-26762.1819.0038.68
TXS-37072.7640.1141.59
TXS-46982.4719.4519.83
TXS-56951.5034.0017.00
TXS-68562.7728.2524.93
TXS-78071.8716.6727.67
TXS-88081.9012.3024.50
TXS-99092.3519.3538.50
TXS-107052.0920.3628.00
TXS-119562.5936.8823.90
TXS-128553.2335.6333.75
TXS-138662.7433.9943.91
TXS-148872.8534.6128.35
TXS-158983.5131.6635.55
TXS-169572.4032.0025.30
TXS-177962.8335.0049.13
TXS-188972.4034.3334.67
TXS-199382.1028.0016.00
TXS-208892.1531.0030.03
TXS-218793.0026.0049.75
TXS-228772.0020.8728.82
TXS-239272.5935.5936.88
TXS-249162.7741.0442.34
TXS-259572.4621.1525.35
TXS-268983.4623.6626.50
TXS-278993.0327.0035.57
TXS-289371.9020.5051.30
TXS-299262.6532.3522.34
TXS-309673.1034.5031.55
TXS-319482.1320.8527.15
TXS-327692.7421.7018.58
TXS-3377102.5630.3824.16
TXS-346583.4541.9028.55
TXS-355091.8621.0028.92

Table 8.

Statistics of grafting survival rate of iron-heart Cunninghamia lanceolate.

3.3 Analysis of sub-populations genetic structure

3.3.1 Genetic diversity

The evolutionary potential and adaptation of a species are reflected by its genetic diversity, the more genetic variation a species has, the more adaptive it is. The study of the genetic diversity of iron-heart Cunninghamia lanceolateis necessary to understand its biological characteristics. In total, 133 alleles were observed among all samples for 15 polymorphic loci, which is higher than the amount previously reported. This difference may have been caused by the sample size, reproductive properties, and molecular marker characteristics of the species. The microsatellites used in the study yielded moderately to highly variable allele numbers per locus, in which 15 SSR primer pairs generated a total of 133 alleles, with a mean of 8.87 alleles at each locus, ranging from 5 for the contig5410_1886A locus to 18 for the contig406_1209 locus, except the two loci CLSSR6 and CLSSR8. Both the CLSSR6 locus and CLSSR8 locus had only 2 alleles, producing the lowest Ne (0.641, 0.691). The expected and observed heterozygosity of all the loci ranged from 0.442 to 0.870 and from 0.270 to 0.700, with averages of 0.654 and 0.474, respectively (Table 9). As an important index for measuring the genetic diversity of a population, the He of the SSRs was 0.654, which indicated that a higher genetic diversity existed in the population, suggesting that these accessions varied with high genetic diversity. The high genetic diversity may be due to being a predominantly outcrossing species. Meanwhile, the Ne was significantly smaller than the Na for each loci, which may be because the natural ecological conditions became severe suddenly during the process of alternation generation because of the high altitude of the site, and collapse of the large population occurred, leading to the loss of rare alleles in the population and the bottleneck effect. The results also revealed a range of PIC values from 0.348 (CLEER6) to 0.858 (contig406_1209C), and among these, the values of three loci (contig476_526D, 0.421; CLSSR6, 0.348; and CLSSR8, 0.374) were less than 0.5, indicating that the other 12 primers were accessible for identifying the genetic diversity of Chinese fir in Xioxi, Hunan Province. The average Shannon’s Information Index (I) value was 1.350, with a minimum of 0.285 (contig 406_1209C) and a maximum of 0.641 (CLSSR8). However, the effective number of alleles (Ne) ranged from 1.792 to 7.677 per locus for all accessions, and the mean value was 3.325. Overall, the mean values of Ne, He, Ho, PIC, Fst, and Gst were 1.933, 0.654, 0.474, 0.566, 0.090, and 0.076, respectively.

LocusNaNeIHoHeG’stNPICNmFisFitFstGst
contig476_526D61.7920.9480.4290.4420.0090.42111.8120.0370.0570.0210.008
contig7616_683B164.0881.6800.7000.7550.0150.7249.1610.0310.0570.0270.013
contig4728_384B142.3041.3400.5480.5660.0090.54812.039−0.0020.0180.0200.008
contig5410_1886A53.8791.3890.5920.7420.0420.6954.6000.1930.2340.0520.038
contig16181_1285C72.8111.2200.5980.6440.0020.57716.0980.0370.0510.0150.002
contig406_1209C187.6772.2850.6570.8700.0190.8587.2110.1990.2250.0340.017
Unigene63373.8781.4880.3910.7420.2060.7010.9970.3040.4440.2000.187
Unigene75453.1481.2820.4220.6820.2320.6260.8660.2010.3800.2240.212
Unigene84073.0811.3400.6440.6750.0750.6302.948−0.0270.0530.0780.067
Unigene1061104.5041.6910.3690.7780.1060.7461.9610.5140.5690.1130.095
Unigene491123.2081.5910.2700.6880.1600.6521.2980.5270.6030.1620.145
contig6319_250C72.3351.1050.4480.5720.2590.5240.751−0.0820.1890.2500.237
contig1560_1789D153.3681.5510.4230.7030.1310.6611.6140.3970.4780.1340.119
CLSSR621.8150.6410.3320.449−0.0010.34817.0260.2380.2490.014−0.001
CLSSR821.9930.6910.2900.498−0.0140.37449.0570.4130.4160.005−0.012
Mean8.873.3251.3500.4740.6540.0830.5669.1630.1990.2680.0900.076

Table 9.

Characterization of 15 simple sequence repeat loci in iron-heart Cunninghamia lanceolatebased on 548 accessions representing 9 sampling sites.

There were high levels of differentiation and genetic diversity at these loci. The 15 polymorphic loci showed that the G’stN value was between 0.259 (contig6319_250C) and −0.001 (CLSSR6), with an average value of 0.083. This finding shows that the genetic difference among populations was 8.3%, and 91.7% of the genetic difference existed among individuals in the population. The average Nm of 15 SSR loci in nine populations was 9.163, indicating that gene exchange was frequent.

Na: Number of alleles; Ne: effective number of alleles; I: shannon’s Information Index; Ho: Observed heterozygosity; He: Expected heterozygosity with populations; G’stN: Nei’s standardized Gst; PIC: The polymorphism information content; Nm = [(1/Fst)-1]/4; Fis (Inbreeding coefficient within individuals) = (Hs-Ho)/Hs; Fst (Inbreeding coefficient within subpopulations) = (Ht-Hs)/Ht; Gis (Analog of Fst, adjusted for bias) = (cHs-Ho)/cHs; Gst (Analog of Fst, adjusted for bias) = (cHt-cHs)/cHt.***

The highest number of alleles was observed in population JZW-3 (Na = 8), and three populations (LYP-2, LYP-3, and LYP-4) had the lowest number of alleles, which was only 4. The observed heterozygosity within a population ranged from 0.416 to 0.506, varying little. The mean of the expected heterozygosity within populations was significantly higher than the observed heterozygosity (Ho) within populations, while the highest value was found for population LYP-1 (He = 0.637), and the lowest value of 0.524 was found in LYP-4 (Table S2). LYP-4 was the least diverse population (I = 0.997 and He = 0.524) of all the sites sampled. The highest genetic diversity was recorded for sites located in JWZ-2, JWZ-3, and LYP-1 (I = 1.244, 1.294, and 1.241 and He = 0.622, 0.636, and 0.637, respectively). In Figure 3, the geographic distribution of the population diversity based on Fp and He is presented, which indicated that JZW- (1,2,3) was likely the center of genetic diversity of this Chinese fir variety.

Figure 3.

Distribution of population diversity based on the expected heterozygosity and private allele frequency. (A) The private allele frequency (Fp) in all populations. (B) The expected heterozygosity (He) in all populations.

Molecular variance analysis was used to assess the population differentiation among 9 subgroups, which demonstrated that approximately 11% of the total variance was explained among the groups and 89% of the total variance was explained within accessions (Table 10). The population differentiation study that included red-heartwood Chinese fir and clones from six different provinces produced similar results to our study and identified a slightly higher genetic variance in subgroups. However, a moderate degree of variability was present among some populations. Previous studies [38] have shown that severe genetic drift, which might be intensified by long-term habitat isolation, is widespread in small populations. This effect will result in a low level of genetic diversity within a population and genetic differentiation among populations. Meanwhile, the results were almost consistent with G’stN = 0.083, indicating that variation mainly existed between individuals, so it was unreasonable to divide the groups according to geographical locations and administrative boundaries.

Source of variationDegree of freedomSum of squaresVariance component estimatesPercentage of variation (%)
Among populations9804.9001.54111
Between samples within populations5396443.89411.95589
Total5487248.79413.496100

Table 10.

Analysis of molecular variance (AMOVA) among populations of iron-heart Cunninghamia lanceolate.

3.3.2 Genetic structure and divergence

The study of population structure is important for the formulation of strategies utilizing special germplasms for breeding objectives and conserving species effectively. Meanwhile, the genetic structure largely determines the evolutionary potential of a species or population. To verify the results of the neighbor-joining cluster analysis and PCA principal component analysis, the results of 15 pairs of SSR primer polymorphisms of 548 wild germplasm resources in Xiaoxi, Hunan Province, were further analyzed by STRUCTURE v2.3.4. The results showed that L(K) increased with the increase of K. A clear peak appeared at the value of ΔK at K = 2 (Figure 4A and B). When k = 2, ΔK reached the peak value, which indicated that the 548 accessions were clearly differentiated into two clusters according to STRUCTURE analysis (Figure 4). All the accessions from JZW-2, JZW-3, and LYP-1 were present in two clusters, with approximately one-half of each population in each cluster, which can be considered admixed. Materials from different sources were distributed in the populations, there was no obvious regional differentiation, and the results of the population structure analysis were consistent with the results of SSR genetic diversity clustering. According to previous research, in the genetic structure analysis of a structured population, when the genetic component (Q value) of material is ≥0.6, the genetic background of the material is relatively simple, and when the Q value is <0.6, the genetic background of the material is relatively complex. With the increase of the K value (k = 3, k = 4), a new gene classification appeared in the wild Chinese fir population, but the high variance was inconsistent (Figure 4D). The clustering of CTY, JZW-1, JZW-2, JZW-3, and XNC showed some evidence that these populations can be broken down into further clusters, while LYP-1, LYP-2, LYP-3, and LYP-4 were relatively stable for higher K values. Excluding the CTY and JZW-1 populations, a new gene classification appeared in the other seven populations, which showed that there were significant differences among other populations. This finding suggested that the heterozygosity and genetic background of the wild Chinese fir are higher. When K = 4, the population was divided into four groups. The accessions that originated from the same population, including JZW-1, JZW-3, and XNC, were divided into different clusters. This result indicated that the four clusters are not geographically independent. Several populations (i.e., the LYP-3 and LYP-4 populations) that consisted of a single genetic component might have experienced founder effects or significant bottlenecking. The results also show low levels of mixing, which account for the hybridization or outcrossing of individuals between populations. Classifying accessions according to administrative boundaries and geographical distributions is very subjective, and it is very difficult to grade traits accurately in the provenance of this specific Chinese fir. In some cases, the population structure may not be predicted via administrative boundaries and geographical distributions. Therefore, the relationship between the population structure and phylogenetic clustering is not obvious, which is consistent with previous research results [22] for the Chinese fir. Wind pollination and a high natural outcrossing frequency among the species may lead to inconsistencies in population classifications and geographical locations. As a result, the geographical origin and genetic structure of a population should be simultaneously considered for the screening of this special germplasm breeding material. That is, geographical features are not obvious among distribution regions. From the principal component analysis results, we were able to identify two main populations with some sub-populations in each group. Obviously, the distributions of accessions from the same location in the two groups were not concentrated and scattered in each group. Additionally, one group contained all the individuals from JZW-1 and approximately 60% of the accessions from the other three locations (ZJW-2, JZW-3, and LYP-1), which occupied approximately 40% in the other group.

Figure 4.

Population classification based on the consensus of STRUCTURE analysis across 10 replications for per K clusters. (A) Circles with standard deviations represent the average log-likelihoods across per K runs independently. (B) Solid circles indicate the values of Evanno’s ΔK based on the rate of change of the log-likelihood. (C) Bar plots express the population structure. The number of clusters is shown from K = 2 to K = 4. Vertical bars represent each genotype, and the length of each colored bar represents the proportion of membership for each cluster. (D) the distribution of 2 to 4 clusters of 9 populations is visualized as a pie chart, with each population divided into colored segments based on the proportion of its members in a given cluster.

The lowest Gst and Fst values between populations JWZ-2 and LYP1 were 0.004 and 0.010, respectively (Table S3). The highest values, which were 0.104 for Fst and 0.093 for Gst, were observed between populations CTY and LYP-2. Most of the values for both parameters were within the limits of moderate genetic differentiation between populations (Table S3).

Advertisement

4. Discussion

Seed yield and quality are the basis for the collection and preservation of improved seeds and the construction of seed orchards, which has a great impact on the efficiency of plantation and industrial development in the later stage [39, 40]. It is found that the variation range of seed and cone traits is 12.18–51.34%, among which the variation of cone length, cone width, cone length-width ratio, seed length, seed width, and seed length-width ratio is relatively small, indicating that these seed traits of iron-heart Cunninghamia lanceolateare relatively stable [41, 42]. The order of coefficient of variation from large to small is: seed germination rate > seed quality > seed length to width ratio > seed length > cone seed yield > seed width > total cone mass > seed goodness > cone length > seed quality (1000) > cone length to width ratio > cone width. The results of the analysis of variance showed that among families, the differences of total cone quality, seed quality, seed germination rate, seed goodness, seed quality (1000), seed width, and cone length-width ratio were very significant (P < 0.001), the differences of cone length were significant (P < 0.01), and the differences of the other four traits were not significant. The results showed that the phenotypic characters of different Iron-heart Cunninghamia lanceolatefamilies had high diversity and rich variation.

Genetic diversity of a species reflects its evolutionary potential and allows for evolution and adaptation. The more abundant the genetic variation of a species is, the more adaptable it is. Thus, it is necessary to study the genetic diversity of a species to understand its biological properties [43]. All previous studies on this species revealed a relatively high level of genetic diversity [22]. In the current study, 15 SSR markers were used to evaluate the population genetics of a large number of specific Chinese fir individuals across its distribution range in Xiaoxi Hunan. Amplification results of the 548 germplasms only existed Hunan Xiaoxi gave a total of 133 alleles with a mean of 8.87 at each locus, a value higher than those in previous reports [1, 22]. The difference may relate to the reproductive attributes of this species, the sample size, and/or the characteristics of the molecular markers. Understanding population structure is useful for developing strategies for the conservation of new species and effectively utilizing genotypes for breeding purposes. Genetic distance is commonly used to describe the genetic structure of a population and the differences among populations [44]. The evolutionary potential of a species or population depends to a large extent on the genetic structure of the population [45]. The results of the STRUCTURE analysis performed for this study indicate that the most likely genetic structure of the 548 studied accessions is two clusters.

Advertisement

5. Conclusions

Through this study, we constructed a germplasm resource nursery of Iron-heart China fir, and the grafting survival rate was as high as 83%. 27 families of iron-heart Cunninghamia lanceolateseeds were collected, and the highest germination rate was 68%; 15 highly polymorphic and stable SSR markers were selected to analyze the genetic structure of the natural population of iron-heart Cunninghamia lanceolate. In total, the study got 133 alleles, and the GestN’s = 0.083. AMOVA analysis showed that the variation among populations was only 11%, and 89% of the variation came from individuals. In addition, STRUCTURE analysis showed that the whole samples could be divided into two groups, and there was no correlation between population division and geographical location. This study will lay a foundation for the protection of the new species of Iron-heart Cunninghamia lanceolate. In this study, only the genetic structure of its natural population was analyzed, but the heartwood variation was not deeply discussed. In addition, we only used the single method of STRUCTURE to analyze its genetic structure and did not use PCA, neighbor-joining (NJ) cluster analysis, and other methods to analyze its genetic structure. This will be what we will study in the next step.

Advertisement

Acknowledgments

I would like to thank all the scholars for their monographs and their research achievements for their inspiration and help. Secondly, I would like to express my heartfelt thanks to the colleagues who provided help in this work was funded by Hunan Provincial Forestry Science and Technology Innovation Project (Project No. XLK201921).

Advertisement

Gst values above the diagonal; Fst values below the diagonal.

CodeDBH (cm)Altitude (m)GPS(E,N)
TXS-172.00895110.246958, 28.835133
TXS-248.20899110.247068, 28.835290
TXS-341.10845110.247144, 28.833239
TXS-443.20505110.260574, 28.814858
TXS-529.50560110.260804, 28.814984
TXS-644.10563110.260804, 28.814984
TXS-763.00813110.246442, 28.822674
TXS-825.30804110.246186, 28.822969
TXS-951.50800110.247032, 28.823265
TXS-1047.00807110.247682, 28.823303
TXS-1143.00894110.245943, 28.834792
TXS-1235.501000110.242849, 28.834510
TXS-1337.401010110.243119, 28.835489
TXS-1447.00904110.245980, 28.835239
TXS-1546.00894110.246676, 28.834436
TXS-1643.20648110.268425, 28.798110
TXS-1726.90632110.268312, 28.797980
TXS-1827.70648110.268386, 28.798233
TXS-1940.60632110.267831, 28.797993
TXS-2034.40629110.267767, 28.796707
TXS-2154.70902110.247119, 28.835550
TXS-2254.20901110.246885, 28.835296
TXS-2373.00895110.246958, 28.835133
TXS-2448.20899110.247968, 28.835290
TXS-2541.10845110.247444, 28.833239
TXS-2643.20505110.260574, 28.814858
TXS-2729.50560110.260804, 28.814984
TXS-2852.30490110.261149, 28.814843
TXS-2938.70514110.261320, 28.814457
TXS-3027.30511110.261126, 28.814625
TXS-3129.40524110.260469, 28.814065
TXS-3229.00502110.259730, 28.813559
TXS-3337.70494110.269097, 28.814165
TXS-3428.00525110.259179, 28.814850
TXS-3531.80523110.250914, 28.814820

Table S1.

The information of the 35 Iron-heart Cunninghamia lanceolate.

CodePlotPositionlongitudelatitudeAltitude(m)
11CTY110.26681228.793035534
21CTY110.26611528.794041541
31CTY110.26658228.795033544
41CTY110.26701128.794845551
51CTY110.26715428.795096514
61CTY110.26715428.795096561
71CTY110.268328.794092605
81CTY110.268328.794092596
91CTY110.26944628.794093602
101CTY110.26944628.794093616
141CTY110.27173928.793089654
154JZW3110.26371828.803132658
164JZW3110.26486328.804133655
171CTY110.26944628.792084660
184JZW3110.26486328.804133653
191CTY110.27403128.792087652
201CTY110.27403128.792087654
211CTY110.27403128.792087656
221CTY110.27403128.792087661
234JZW3110.26257228.804132660
241CTY110.27173928.794094659
251CTY110.27173928.794094644
261CTY110.27231128.793592646
271CTY110.27254928.79341664
281CTY110.27245528.793361650
291CTY110.27232228.793322651
301CTY110.27244628.793236645
311CTY110.27229328.793381642
321CTY110.27215928.793616623
331CTY110.27214128.793757653
341CTY110.2721528.793773654
351CTY110.27227628.793624663
361CTY110.27213228.79378658
371CTY110.27206128.793863668
381CTY110.27206128.793863663
391CTY110.27217828.793881655
401CTY110.27216228.793761661
411CTY110.27215128.796853666
421CTY110.27227628.794812657
431CTY110.26944528.788067650
441CTY110.27212328.794133657
451CTY110.27210128.793965645
461CTY110.2721528.794034646
471CTY110.27250928.794644630
481CTY110.27247328.794675627
491CTY110.27241928.794675625
501CTY110.27240128.794754630
511CTY110.27249128.794675632
521CTY110.27234728.794769635
531CTY110.27241928.794691645
541CTY110.27243728.794738645
551CTY110.27241928.794691650
561CTY110.27245628.794738651
571CTY110.27245628.794973650
581CTY110.27259928.79491653
591CTY110.27281328.794754653
601CTY110.27270628.794722638
611CTY110.27267528.794859675
621CTY110.27280428.794785655
631CTY110.27266628.794701673
641CTY110.2727428.794741675
651CTY110.27300328.794652676
661CTY110.27247328.794785677
671CTY110.27306428.794565711
681CTY110.27306428.794565680
691CTY110.27306428.794565688
701CTY110.27326128.794511681
711CTY110.27309728.794544674
721CTY110.27317828.794603668
731CTY110.27323128.794833655
741CTY110.27323128.948323671
751CTY110.27321428.794826668
761CTY110.27320828.794858658
771CTY110.2733428.794583667
781CTY110.2734428.794662663
791CTY110.27341528.794634662
801CTY110.27311928.794773660
811CTY110.27350128.794945679
821CTY110.27336928.794766675
831CTY110.27362628.795024613
841CTY110.2736528.795094630
851CTY110.27357328.795127657
861CTY110.27359828.795052665
871CTY110.27335728.79507653
881CTY110.27326128.795105789
891CTY110.2732728.794935870
901CTY110.27332728.794876759
911CTY110.27314728.795255667
921CTY110.27293528.795291682
931CTY110.27325328.795221660
941CTY110.2732828.795224674
951CTY110.27316728.795279655
971CTY110.2731128.795333666
981CTY110.27313928.79538691
991CTY110.27333728.795049653
1001CTY110.27332128.794943635
1012JZW-1110.25868828.811154486
1022JZW-1110.2589528.811245482
1033JZW-2110.26146828.812119496
1043JZW-2110.26147528.812175504
1073JZW-2110.26166328.81301549
1083JZW-2110.26150828.813028526
1093JZW-2110.2612228.813561527
1103JZW-2110.26122628.813602520
1123JZW-2110.26090428.81422509
1133JZW-2110.26099828.814105506
1143JZW-2110.26080328.814323497
1153JZW-2110.26072328.814317482
1173JZW-2110.2616928.815117507
1183JZW-2110.26211928.815117500
1193JZW-2110.2616928.815493510
1203JZW-2110.2616928.815493509
1213JZW-2110.2616928.815493515
1223JZW-2110.2616928.81474526
1233JZW-2110.26254928.81474539
1243JZW-2110.26254928.81474513
1253JZW-2110.26254928.81474519
1273JZW-2110.26340928.81474531
1283JZW-2110.2616928.81474534
1293JZW-2110.2616928.81474535
1303JZW-2110.26340928.81474537
1313JZW-2110.26340928.81474531
1323JZW-2110.26340928.81474552
1343JZW-2110.2616928.81474538
1363JZW-2110.2616928.81474525
1373JZW-2110.2616928.81474521
1383JZW-2110.2616928.81474537
1393JZW-2110.2616928.81474535
1403JZW2110.2616928.81474528
1413JZW-2110.2616928.81474519
1423JZW-2110.2616928.81474524
1433JZW-2110.2616928.81474523
1442JZW-1110.25653228.813234522
1453JZW-2110.2616928.81474514
1463JZW-2110.2616928.81474525
1473JZW2110.2616928.81474513
1483JZW-2110.2616928.81474510
1493JZW-2110.2616928.81474511
1503JZW-2110.2616928.81474512
1519XNC110.2580828.794866426
1529XNC110.25805728.794869425
1539XNC110.2580528.794869427
1549XNC110.25773428.792924352
1552JZW-1110.25592828.81311500
1562JZW-1110.25596128.812925513
1579XNC110.25794228.792232496
1589XNC110.25796328.792241499
1599XNC110.25803628.792211495
1609XNC110.25798328.792156492
1619XNC110.25632428.792974556
1629XNC110.2562628.793065554
1639XNC110.25617328.793191519
1649XNC110.25617328.793197547
1659XNC110.2561928.793335548
1669XNC110.25615928.7934545
1679XNC110.25614928.793409548
1689XNC110.25612928.793385548
1699XNC110.25611628.793521531
1709XNC110.25609628.793444543
1719XNC110.25609628.793556542
1729XNC110.25606928.793668533
1739XNC110.25608928.793644534
1749XNC110.25610928.793574530
1759XNC110.25612328.793633527
1769XNC110.25612928.793627523
1779XNC110.25609628.793739520
1789XNC110.25608228.793733515
1799XNC110.25597528.793344500
1809XNC110.25607628.79355526
1819XNC110.2566828.791991534
1829XNC110.25692828.792044542
1839XNC110.25681428.791926535
1849XNC110.25675428.791779527
1859XNC110.256728.791744524
1869XNC110.25667328.791732538
1879XNC110.25651228.791849526
1889XNC110.25645828.791808526
1899XNC110.25645828.79182532
1909XNC110.25651928.791908530
1919XNC110.25646528.791902540
1929XNC110.25637828.791745536
1949XNC110.25643828.791685542
1959XNC110.25637128.791633556
1969XNC110.25635828.791508553
1979XNC110.25644528.791402552
1989XNC110.25643828.79139552
1999XNC110.25599528.791137544
2009XNC110.2562128.790978545
2015LYP-1110.25167228.831943928
2025LYP-1110.25171628.83204920
2036LYP-2110.25176628.830129862
2046LYP-2110.25183828.830039882
2056LYP-2110.25195228.829865845
2066LYP-2110.25177628.829784872
2076LYP-2110.25168828.829844871
2086LYP-2110.25286128.829196796
2106LYP-2110.25368928.828283755
2116LYP-2110.25398528.827786749
2126LYP-2110.25350128.827892730
2136LYP-2110.25405828.827841738
2146LYP-2110.25372828.827494733
2156LYP-2110.25417828.827329733
2166LYP-2110.25416928.827263734
2176LYP-2110.25431828.827022728
2186LYP-2110.25470128.826678710
2207LYP-3110.25110228.819344879
2217LYP-3110.25092528.819311889
2227LYP-3110.25124728.819485860
2237LYP-3110.2508628.819912875
2247LYP-3110.25098928.820227878
2257LYP-3110.25096228.819546870
2267LYP-3110.25120428.819504840
2287LYP-3110.2511528.819278835
2297LYP-3110.25100528.81924837
2307LYP-3110.25135428.819156830
2327LYP-3110.25145128.819231830
2347LYP-3110.25126828.818977814
2367LYP-3110.251328.818902733
2377LYP-3110.25143428.818902678
2387LYP-3110.25136628.818901810
2397LYP-3110.25147228.818635807
2407LYP-3110.25136728.818623806
2418LYP-4110.25340328.814614785
2428LYP-4110.25346428.814627780
2438LYP-4110.25350428.814843780
2448LYP-4110.25330328.814612790
2458LYP-4110.25238128.814914787
2468LYP4110.25243128.814457787
2478LYP-4110.25256528.814573785
2488LYP-4110.25253128.814643770
2498LYP-4110.25241528.814638780
2508LYP-4110.2524928.81451790
2518LYP-4110.25238928.814524780
2528LYP-4110.25261728.814707780
2538LYP-4110.25246428.814759822
2548LYP-4110.25258628.814907823
2558LYP-4110.25248528.814505815
2568LYP-4110.25247428.81493825
2578LYP-4110.25244228.81495826
2588LYP-4110.25247428.81493825
2598LYP-4110.25243228.81475836
2602JZW-1110.25999128.808601830
2612JZW-1110.25999328.808731819
2638LYP-4110.25194728.814613824
2648LYP-4110.25190928.814514837
2658LYP-4110.25189628.814477840
2668LYP-4110.25181528.814618834
2678LYP-4110.2520728.81447825
2688LYP-4110.25228228.814319819
2698LYP-4110.25211828.814293821
2708LYP-4110.25217528.814322821
2718LYP-4110.25224428.814284815
2728LYP-4110.25136228.814845799
2738LYP-4110.25132228.814858808
2748LYP-4110.25159728.813805808
2758LYP-4110.251528.813742823
2763JZW-2110.26473728.810652525
2773JZW-2110.26007828.814223485
2783JZW-2110.26007828.814175488
2793JZW-2110.26002428.814317491
2803JZW-2110.2599728.814364509
2813JZW-2110.25986328.814599504
2823JZW-2110.25986328.814599504
2833JZW-2110.25980928.814646510
2843JZW-2110.25980928.814693514
2853JZW-2110.25970228.814787513
2863JZW-2110.25975628.814787513
2873JZW-2110.25970228.814787518
2883JZW-2110.25964828.814787520
2893JZW-2110.25964828.814882525
2913JZW-2110.25932628.814976535
2933JZW-2110.25921828.814882525
2953JZW-2110.25921828.814699523
2963JZW-2110.25921828.814599526
2973JZW-2110.25932628.814552516
2983JZW-2110.25943328.814458510
2993JZW-2110.25986328.813611464
3002JZW-1110.26301128.80788498
3012JZW-1110.26328.808087503
3022JZW-1110.26318328.808167506
3032JZW-1110.26357128.808077510
3043JZW-2110.26598928.811247545
3053JZW-2110.26600428.811278576
3063JZW-2110.26610328.811241523
3073JZW-2110.26615328.811309535
3083JZW-2110.26619928.811258537
3093JZW-2110.26619928.811259537
3103JZW-2110.26607928.811436520
3113JZW-2110.26602528.811335520
3123JZW-2110.26599628.811373532
3133JZW-2110.26599628.811372520
3143JZW-2110.26585828.811433528
3153JZW-2110.26595628.81142531
3163JZW-2110.26586328.811323529
3173JZW-2110.26550428.811433525
3183JZW-2110.26588928.81137529
3193JZW-2110.26593828.811365530
3203JZW-2110.26596828.81137531
3213JZW-2110.26588928.811301529
3233JZW-2110.26574528.81161526
3243JZW-2110.26587328.811646525
3253JZW-2110.26548528.811865536
3263JZW-2110.26552428.811862537
3273JZW-2110.26555628.811825537
3283JZW-2110.26561828.811889526
3303JZW-2110.26555428.811823530
3313JZW-2110.26565828.811802530
3323JZW-2110.26550328.811767535
3333JZW-2110.26529628.811861557
3343JZW-2110.26523428.811896539
3357LYP-3110.26513828.811964538
3353JZW-2110.26513828.811964538
3363JZW-2110.26490528.811888542
3373JZW-2110.26488628.811812535
3383JZW-2110.26490228.811727537
3393JZW-2110.26491828.811686543
3403JZW-2110.26519428.811692538
3413JZW-2110.26505528.811593540
3423JZW-2110.26512728.811549532
3433JZW-2110.26510328.811499532
3443JZW-2110.26503628.811453535
3453JZW-2110.26502128.811431540
3463JZW-2110.26505928.811403538
3473JZW-2110.26499628.811403535
3483JZW-2110.26591728.811525542
3493JZW-2110.26593728.811543525
3503JZW-2110.26590928.811615529
3513JZW-2110.26600328.811554530
3523JZW-2110.26626728.811835540
3533JZW-2110.26625528.811816533
3543JZW-2110.26627228.811721541
3553JZW-2110.26616428.811771538
3563JZW-2110.26599128.811558532
3573JZW-2110.26622828.811586540
3583JZW-2110.26619328.811927535
3593JZW-2110.26596328.811565545
3603JZW-2110.2660428.811553533
3623JZW-2110.26601228.811557537
3636LYP-2110.25227128.829358818
3646LYP-2110.25221928.829951854
3655LYP-1110.25134928.831102899
3665LYP-1110.25130428.831128899
3675LYP-1110.25094828.831558922
3685LYP-1110.25087428.831577930
3695LYP-1110.25068928.831557932
3705LYP-1110.25063428.832051900
3715LYP-1110.25047828.832025940
3725LYP-1110.25043428.832028940
3732JZW-1110.26391228.808815945
3745LYP-1110.25016328.832358945
3755LYP-1110.24956928.832626998
3765LYP-1110.24946628.8328621015
3775LYP-1110.24908828.8327241030
3785LYP-1110.24929728.8325141011
3795LYP-1110.24906628.8326261033
3805LYP-1110.24857528.832561035
3815LYP-1110.24859828.8324761040
3825LYP-1110.2487928.8320711050
3835LYP-1110.24835428.8320441028
3855LYP-1110.24828728.831451022
3865LYP-1110.24831828.8312741005
3895LYP-1110.24817328.831164990
3905LYP-1110.24831128.831247991
3925LYP-1110.24862928.830985980
3935LYP-1110.24857528.831086967
3945LYP-1110.24887328.831389950
3955LYP-1110.24958128.830962934
3965LYP-1110.24995428.831276938
3975LYP-1110.25005828.831746937
3985LYP-1110.25192928.832356921
3995LYP-1110.25177928.832887921
4005LYP-1110.25169328.832149921
4019XNC110.25628428.79092542
4029XNC110.25651928.79092542
4039XNC110.25648528.790973540
4049XNC110.25658628.791055539
4059XNC110.25658628.791043539
4069XNC110.25669328.790949538
4079XNC110.25668728.790949546
4089XNC110.25694228.790949540
4099XNC110.2572128.790172513
4109XNC110.25735128.790431492
4114JZW-3110.25782228.804113467
4124JZW-3110.25747228.804066477
4134JZW-3110.25747228.804066477
4144JZW-3110.25728428.803972491
4154JZW-3110.25712328.803996496
4164JZW-3110.25704328.804031498
4174JZW-3110.25692228.804561524
4184JZW-3110.25685528.804572508
4194JZW-3110.25676128.804631517
4204JZW-3110.2566828.804678494
4214JZW-3110.25666728.804702515
4224JZW-3110.25661328.804725519
4234JZW-3110.25651928.804737520
4244JZW-3110.25641128.804808512
4254JZW-3110.25630428.804878526
4264JZW-3110.2562528.804867520
4274JZW-3110.25626428.80486526
4284JZW-3110.25612928.80489528
4294JZW-3110.25603528.80489527
4304JZW-3110.25598228.804937530
4314JZW-3110.25590128.805067541
4324JZW-3110.2558228.805055536
4334JZW-3110.2557828.805043537
4344JZW-3110.25575328.805079542
4354JZW-3110.25567328.805149537
4364JZW-3110.25564628.805161538
4374JZW-3110.25548528.805196543
4384JZW-3110.25547128.805208550
4394JZW-3110.25521628.805302558
4404JZW-3110.25489428.805396559
4414JZW-3110.25469228.80542553
4424JZW-3110.25469228.805408565
4434JZW-3110.25457128.805396564
4444JZW-3110.2544528.805396568
4454JZW-3110.25431628.805361566
4464JZW-3110.25423628.805349567
4474JZW-3110.25415528.805337569
4484JZW-3110.25406128.80533570
4494JZW-3110.25395428.805349572
4504JZW-3110.25385928.805361576
4524JZW-3110.25309428.805585579
4534JZW-3110.25312128.805561599
4544JZW-3110.25301328.805632595
4554JZW-3110.25266428.805679611
4564JZW-3110.25255728.805655612
4574JZW-3110.25236928.805702618
4584JZW-3110.25231528.805702622
4594JZW-3110.25220828.805749626
4604JZW-3110.25188528.805843637
4614JZW-3110.25185828.805867642
4624JZW-3110.25172428.805867649
4634JZW-3110.2516728.805867652
4644JZW-3110.25156328.805941659
4654JZW-3110.25153628.805914654
4664JZW-3110.25142928.805891651
4674JZW-3110.25142928.805914650
4684JZW-3110.25140228.805914648
4694JZW-3110.25134828.805961644
4704JZW-3110.25118728.806008648
4714JZW-3110.2511628.806126652
4724JZW-3110.2511628.806126648
4734JZW-3110.2511628.806102644
4744JZW-3110.25102628.807115641
4754JZW-3110.25091828.807044660
4764JZW-3110.25086428.807185662
4774JZW-3110.25089128.807303658
4784JZW-3110.25089128.807303657
4794JZW-3110.25091828.807303656
4804JZW-3110.25089128.80735654
4814JZW-3110.25081128.80742658
4824JZW-3110.25083828.807444659
4832JZW-1110.25094528.81041671
4852JZW-1110.25105228.810457663
4862JZW-1110.25110628.81048662
4872JZW-1110.2511628.810504663
4882JZW-1110.25126728.810551659
4892JZW-1110.25132128.810551661
4902JZW-1110.25255728.810716629
4912JZW-1110.25263728.810833624
4922JZW-1110.25274528.810904624
4932JZW-1110.25301328.810951607
4942JZW-1110.25298628.81097601
4952JZW-1110.25312128.810998613
4962JZW-1110.25312128.81099612
4972JZW-1110.25317528.811092609
4982JZW-1110.25344328.811116613
4992JZW-1110.25360428.811116605
5002JZW-1110.25363128.811163603
5012JZW-1110.2539828.811092597
5022JZW-1110.25513528.810716574
5032JZW-1110.25524328.810669568
5042JZW-1110.25532328.810598550
5052JZW-1110.25604928.81041533
5064JZW-3110.25690828.80808519
5074JZW-3110.25690828.80808516
5084JZW-3110.25642528.80808526
5094JZW-3110.25569928.807938543
5104JZW-3110.25556528.807915549
5114JZW-3110.25556528.807915546
5124JZW-3110.2553528.807915555
5134JZW-3110.25537728.807915553
5144JZW-3110.2552728.807985553
5154JZW-3110.25492128.807891577
5164JZW-3110.25489428.807868579
5174JZW-3110.25489428.807868579
5184JZW-3110.25470628.807868572
5194JZW-3110.25470628.807821569
5204JZW-3110.25465228.807844563
5214JZW-3110.25465228.807844572
5224JZW-3110.25443728.807868573
5234JZW-3110.25443728.807821567
5244JZW-3110.25416828.807844588
5254JZW-3110.25411528.80775588
5274JZW-3110.25336328.807585609
5284JZW-3110.25314828.807562608
5294JZW-3110.25344328.807632604
5304JZW-3110.25309428.807632608
5314JZW3110.2529628.807656609
5324JZW-3110.2529628.807656608
5334JZW-3110.25293328.807679612
5344JZW-3110.2529628.807656612
5354JZW-3110.25287928.807656615
5364JZW-3110.25271828.807632620
5374JZW-3110.25269128.80775621
5384JZW-3110.25274528.807726611
5394JZW-3110.2526128.80775613
5404JZW-3110.25220828.807774612
5414JZW-3110.25220828.80775622
5424JZW-3110.25215428.807726619
5434JZW-3110.25201928.807797630
5444JZW-3110.25188528.807868634
5454JZW-3110.25177828.807821642
5464JZW-3110.25169728.807726650
5474JZW-3110.2516728.807891644
5484JZW-3110.25169728.807938651
5494JZW-3110.25156328.807962655
5504JZW-3110.2512428.807915659
5514JZW-3110.2512428.807915653
5524JZW-3110.25126728.807962656
5534JZW-3110.2512428.807962652
5544JZW-3110.25099928.80815662
5554JZW-3110.25099928.808197659
5564JZW-3110.25083828.808174664
5574JZW-3110.25078428.808197665
5584JZW-3110.25059628.808221606
5592JZW-1110.24855428.809421717
5602JZW-1110.24782928.810645756
5612JZW-1110.24777528.810692751
5622JZW-1110.24782928.810645750
5632JZW-1110.24777528.810692750
5642JZW-1110.24782928.810645749
5652JZW-1110.24777528.810692749
5662JZW-1110.2475628.811116754
5672JZW-1110.24782928.811728760
5682JZW-1110.24788328.811822762
5692JZW-1110.2479928.81187764
5702JZW-1110.24804428.811916759
5712JZW-1110.24815128.811916765
5722JZW-1110.24847428.81201752
5732JZW-1110.25008528.810127727
5742JZW-1110.250328.810221698
5752JZW-1110.25040828.810221684
5763JZW-2110.25975628.813516477
5773JZW-2110.25975628.813516497
5793JZW-2110.25954128.813611505
5803JZW-2110.25954128.813611501

Table S2.

Location and number of trees sampled for 9 populations in provenance.

PopNaNeIHoFpHeuHeF
CTY72.8701.1740.4970.5330.5940.5980.164
JZW-162.7551.1790.4520.0000.5990.6040.240
JZW-273.0701.2440.4550.2000.6220.6250.244
JZW-383.1831.2940.4970.2000.6360.6390.205
LYP-153.2721.2410.4520.1330.6370.6470.257
LYP-242.4631.0150.4420.0000.5360.5540.173
LYP-342.4521.0130.4160.0000.5380.5540.220
LYP-442.4530.9970.5060.0670.5240.5340.035
XNC52.7921.1080.4650.0000.5740.5790.181
Mean2.8121.1410.4650.1260.5840.5930.191

Table S3.

Genetic diversity parameters of 9 populations of Chinese fir. All values were multilocus estimates based on 15 microsatellite loci.

Na: number of different alleles; Ne: number of effective alleles; I: Shannon’s Information Index; Ho: observed heterozygosity; He: expected heterozygosity with populations; uHe: unbiased expected heterozygosity with populations; F: fixation Index; Fp: no. private alleles (no. of alleles unique to a single population).

CTYJZW-1JZW-2JZW-3LYP-1LYP-2LYP-3LYP-4XNC
CTY0.0880.0690.0380.0570.0930.0810.0800.052
JZW-10.0920.0140.0250.0130.0670.0640.0690.071
JZW-20.0720.0180.0180.0040.0510.0390.0490.037
JZW-30.0410.0290.0200.0100.0510.0380.0440.024
LYP-10.0630.0210.0100.0160.0450.0340.0410.043
LYP-20.1040.0800.0620.0620.0600.0060.0260.063
LYP-30.0910.0770.0500.0480.0490.0250.0160.049
LYP-40.0870.0770.0550.0510.0510.0400.0300.059
XNC0.0570.0760.0410.0270.0510.0760.0610.066

Table S4.

Pair-wise estimates of genetic differentiation between Chinese fir populations using Fst and Gst coefficients based on 15 SSR markers.

CTYJZW-1JZW-2JZW-3LYP-1LYP-2LYP-3LYP-4
JZW-10.357
JZW-20.2750.059
JZW-30.1440.1010.073
LYP-10.2420.0710.0350.059
LYP-20.3560.2550.1970.2010.192
LYP-30.3020.2440.1520.1480.1510.062
LYP-40.2730.2360.1640.1500.1530.0990.073
XNC0.1840.2660.1360.0880.1770.2280.1760.188

Table S5.

Genetic distance between the different population.

DOWNLOAD FOR FREE

chapter PDF

© 2021 The Author(s). Licensee IntechOpen. This chapter is distributed under the terms of the Creative Commons Attribution 3.0 License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

How to cite and reference

Link to this chapter Copy to clipboard

Cite this chapter Copy to clipboard

Ninghua Zhu, Xiaowei Yang, Zhiqiang Han and Xiao Can (December 8th 2021). Research Progress on Iron-Heart <em>Cunninghamia lanceolate</em> [Online First], IntechOpen, DOI: 10.5772/intechopen.101286. Available from:

chapter statistics

22total chapter downloads

More statistics for editors and authors

Login to your personal dashboard for more detailed statistics on your publications.

Access personal reporting

We are IntechOpen, the world's leading publisher of Open Access books. Built by scientists, for scientists. Our readership spans scientists, professors, researchers, librarians, and students, as well as business professionals. We share our knowledge and peer-reveiwed research papers with libraries, scientific and engineering societies, and also work with corporate R&D departments and government entities.

More About Us