SSR molecular markers closely related to the growth traits of jinyunluo and their application
By applying SSR molecular markers to Dalbergia odorifera, high-yielding and fast-growing germplasm was screened out at an early stage, solving the problem of low breeding efficiency in traditional methods and achieving efficient breeding and resource protection.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Patents(China)
- Current Assignee / Owner
- INST OF MEDICINAL PLANT DEV CHINESE ACADEMY OF MEDICAL SCI HAINAN BRANCH
- Filing Date
- 2025-08-01
- Publication Date
- 2026-06-16
AI Technical Summary
Traditional methods are inefficient in screening high-yielding and fast-growing Dalbergia odorifera germplasm, as they cannot accurately measure heartwood yield and growth traits in a short period of time, resulting in low breeding efficiency.
Using SSR molecular markers, target germplasm was screened early by detecting molecular markers such as 34a-241, S03-265, JXHT097-252, JXHT136-270, and 96c-345, combined with specific amplification reaction systems and conditions.
This enables the early screening of high-yield and fast-growing germplasm, shortens the breeding cycle, improves breeding efficiency, meets market demand, and protects wild resources.
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Abstract
Description
Technical Field
[0001] This invention belongs to the field of biotechnology, specifically relating to SSR molecular markers closely related to the growth traits of Dalbergia odorifera and their applications. Background Technology
[0002] Dalbergia odorifera (scientific name: Dalbergia odorifera) Dalbergia odorifera Dalbergia chenschenensis (T. Chen) is a tree belonging to the genus Dalbergia in the legume family. It not only possesses excellent medicinal, timber, and fragrance value but also carries profound cultural connotations. The dried heartwood of its trunk and roots is known as "Jiangxiang" (a traditional Chinese medicine). This precious medicine can combat myocardial ischemia and possesses pharmacological activities such as anti-oxidation, anti-inflammation, liver protection, anti-atherosclerosis, and anti-cancer properties. Due to its unique aroma and exquisite grain, Dalbergia chenschenensis heartwood ranks among the world's top-grade woods.
[0003] High yield and rapid growth are important goals in the breeding of superior varieties of Dalbergia odorifera. Traditional methods for screening Dalbergia odorifera germplasm mainly rely on phenotypic observation of tree growth traits and direct harvesting and measurement of heartwood after the trees have matured. However, Dalbergia odorifera has a long growth cycle, and heartwood yield and some important growth traits can only be accurately measured over many years, which makes the breeding efficiency low.
[0004] With the development of molecular biology techniques, molecular marker-assisted breeding technology has provided new methods for screening and identifying superior plant germplasm resources. Simple sequence repeats (SSRs), also known as microsatellite DNA technology, has advantages such as broad genome coverage, high polymorphism, ability to distinguish heterozygous genotypes, ease of operation, and reproducible results, making it a reliable tool for assessing plant genetic diversity and identifying superior varieties. However, its application in Dalbergia odorifera is rarely reported, and its use in screening high-yielding and fast-growing germplasm of Dalbergia odorifera has not been documented. Summary of the Invention
[0005] In view of the shortcomings of existing technologies, the purpose of this invention is to provide the application of SSR molecular markers in predicting the heartwood yield of Dalbergia odorifera and screening high-yielding and fast-growing germplasm. It aims to overcome the deficiencies of traditional breeding methods, achieve efficient screening of superior Dalbergia odorifera germplasm, and provide technical support for the cultivation of superior varieties of Dalbergia odorifera.
[0006] The technical solution of this invention mainly includes the following:
[0007] The application of SSR molecular markers in screening high-yielding and / or fast-growing germplasm of Dalbergia odorifera, wherein the molecular markers include at least one of 34a-241, S03-265, JXHT097-252, JXHT136-270, and 96c-345, wherein the upstream and downstream primer sequences of 34a are shown in SEQ ID NO.1 and SEQ ID NO.2, respectively; the upstream and downstream primer sequences of S03 are shown in SEQ ID NO.39 and SEQ ID NO.40, respectively; the upstream and downstream primer sequences of JXHT097 are shown in SEQ ID NO.15 and SEQ ID NO.16, respectively; the upstream and downstream primer sequences of JXHT136 are shown in SEQ ID NO.47 and SEQ ID NO.48, respectively; and the upstream and downstream primer sequences of 96c are shown in SEQ ID NO.41 and SEQ ID NO.42, respectively.
[0008] Furthermore, the application is as follows: using the upstream and downstream primers to detect the molecular markers, if at least one of the following alleles is detected, a higher yield of Dalbergia odorifera heartwood is predicted: 241 bp allele detected by the upstream and downstream primers of 34a, 265 bp allele detected by the upstream and downstream primers of S03, 252 bp allele detected by the upstream and downstream primers of JXHT097, and 270 bp allele detected by the upstream and downstream primers of JXHT136.
[0009] If the upstream and downstream primers of 96c detect a 345bp allele, then rapid growth of Dalbergia odorifera is predicted.
[0010] High yield refers to a high yield of heartwood. Fast growth refers to a large diameter at breast height (DBH) and ground diameter (DBC).
[0011] Furthermore, the application is as follows: using the upstream and downstream primers to detect the molecular marker, if at least one of the other four alleles is detected in addition to the detection of 96c-345, then the Dalbergia odorifera is a high-yielding and fast-growing germplasm.
[0012] Furthermore, the amplification reaction system for detecting the molecular marker using the upstream and downstream primers is as follows: 5.0 μL 2×Taq PCR premix, 1.0 μL genomic DNA, 0.5 μL each of the upstream and downstream primers, and 3.0 μL ddH2O.
[0013] Furthermore, the concentration of the genomic DNA is 20-50 ng / μL.
[0014] Furthermore, the concentration of the primer is 10 pmol / μL.
[0015] Furthermore, the conditions for the amplification reaction are as follows:
[0016] Pre-denaturation at 95℃ for 5 min; denaturation stage: 10 cycles, 95℃ for 30 s, annealing at 62℃~52℃ for 30 s / cycle, 72℃ for 30 s; amplification stage: 25 cycles, 95℃ for 30 s, 52℃ for 30 s, 72℃ for 30 s; final extension at 72℃ for 20 min.
[0017] The beneficial effects of this invention are:
[0018] By detecting SSR molecular markers such as 34a-241, S03-265, JXHT097-252, JXHT136-270, and 96c-345, target germplasm can be screened out at an early stage in Dalbergia odorifera. There is no need to wait for the trees to grow for many years before judging their heartwood yield and growth potential. Compared with traditional phenotypic screening methods, this significantly shortens the selection and breeding cycle and helps to improve breeding efficiency.
[0019] Accurately selecting high-yielding and fast-growing Dalbergia odorifera varieties can help accelerate the artificial afforestation and breeding of improved varieties, increase the timber production of Dalbergia odorifera, meet market demand, and also help protect the wild resources of Dalbergia odorifera and achieve sustainable use of resources. Detailed Implementation
[0020] To better understand the technical content of this invention, the invention will be further described below with reference to specific embodiments.
[0021] Experimental Example
[0022] 1. Materials and Methods
[0023] 1.1 Plant materials
[0024] A total of 380 Dalbergia species were collected from five locations in China: Dongfang (DF), Ledong (LD), Xinglong (XL), and Haikou (HK) in Hainan Province, and Xishuangbanna (BN) in Yunnan Province. Fifteen fresh leaves were collected from each plant and immediately dried in sealed plastic bags with silica gel desiccant to facilitate subsequent DNA extraction, species genetic diversity testing, and the success rate of SSR molecular marker amplification and polymorphism detection. For the 70 plants from Haikou and Xinglong, growth cores were drilled at the diameter at breast height (DBH) (1.3 m) to measure heartwood percentage (HWR). In addition, leaves were collected from 13 outgroups (including 8 Dalbergia and 5 Pterocarpus species) to verify the species differentiation capability of the SSR markers.
[0025] 1.2 Phenotypic Characteristic Measurement
[0026] Phenotypic traits of 70 plants from HK and XL were quantitatively analyzed, including diameter at breast height (DBH), ground diameter (GD), rachis length (RL), number of leaflets (LN), leaflet length (LL), leaflet width (LW), leaflet length-to-width ratio (LWR), leaflet area (LA), and heartwood percentage (HWR). DBH refers to the diameter of the tree at a height of 1.3 m above the ground, GD refers to the diameter of the tree at a height of 30 cm above the ground, and HWR is the ratio of heartwood length at DBH to the diameter after debarking. These trait data were used for association analysis with SSR molecular markers.
[0027] 1.3 Genomic DNA extraction and PCR amplification
[0028] Genomic DNA was extracted from 380 samples using a modified CTAB plant DNA extraction kit (Aidlab, China). DNA concentration and purity (OD) were determined using a NanoDrop 2000c spectrophotometer. 260 / 280 ≥1.8), and integrity was assessed by 1% agarose gel electrophoresis (80V, 45 min). Amplification of 24 SSR loci was performed in a Veriti™ 384-well thermal cycler (Applied Biosystems). The reaction mixture consisted of 5.0 μL 2×Taq PCR premix, 1.0 μL genomic DNA (20–50 ng / μL), 0.5 μL each of forward and reverse primers (10 pmol / μL), and 3.0 μL ddH₂O. The thermal cycling program was as follows: 95℃ pre-denaturation for 5 min; 10 cycles of denaturation (95℃ 30 s → 62℃–52℃ annealing 30 s / cycle → 72℃ 30 s); 25 cycles of amplification (95℃ 30 s → 52℃ 30 s → 72℃ 30 s); and a final extension at 72℃ for 20 min. After the PCR products were separated by fluorescent capillary electrophoresis (ABI 3730xl), genotyping analysis was performed using GeneMarker® v2.7.0 software (SoftGenetics) to obtain allele size, peak shape characteristics, and biallelic genotype information.
[0029] Table 1 SSR Molecular Marker Information
[0030]
[0031] 1.4 Data Analysis
[0032] Genotypic data were analyzed using POPGENE v1.32 software to estimate genetic diversity parameters: allele frequencies, observed and effective allele counts (…). N a and Ne ), expected heterozygosity ( H e and H o ) and Wright's fixed index ( F Polymorphic information content () PIC The F-statistic was calculated using CERVUS v3.0.7. Subsequently, the F-statistic (including...) was calculated using GenAlEx v6.5. F is , F it , F st , N m The Hardy-Weinberg equilibrium test, molecular variance analysis (AMOVA), and principal coordinate analysis (PCoA) were performed. Phylogenetic reconstruction was performed using UPGMA clustering (R v4.2.0) and population structure inference (STRUCTURE v2.3.4; K=3-10, 20 replicates), with the optimal K value determined by the ΔK method (STRUCTURE HARVESTER v0.6.94).
[0033] For phenotypic traits, we calculated the minimum / maximum values, range, mean, standard deviation (SD), and coefficient of variation for samples from different regions and for all samples. CV Following this, trait correlation analysis and regional difference analysis were performed. Linkage disequilibrium (LD) analysis was conducted using PLINK v1.9, and trait-marker association analysis was performed using TASSEL v5.0 under generalized linear model (GLM) and mixed linear model (MLM), with population structure (Q) and kinship (K) matrices as covariates. Significance thresholds were set at P ≤ 0.05 (significant) and P ≤ 0.01 (highly significant).
[0034] 2. Results
[0035] 2.1 Genotyping Data Analysis
[0036] 2.1.1 Polymorphism of 124 SSR loci
[0037] We performed genotyping on 24 polymorphic SSR markers in 380 Dalbergia odorifera samples.
[0038] As shown in Table 2, the effective number of individuals (N) for the 24 primer pairs ranged from 365 to 380, with an average of 376.5, indicating that these 24 polymorphic primer pairs were successfully amplified in the vast majority of samples; a total of 128 alleles were observed for the 24 primer pairs, and the observed allele count ( N aThe range of alleles was 2-12, with an average of 5.33; the effective number of alleles ( N e The range of the Shannon diversity index was 1.391 to 6.543, with an average of 2.514; I The range of heterozygosity was 0.546–2.023, with an average of 1.030, falling between 1 and 2 but close to 1, indicating that species diversity was at a moderately high level; the observed heterozygosity ( H o The range of ) is 0.274~0.712, with an average of 0.518, and the expected heterozygosity ( H e The range of variation was 0.281 to 0.847, with an average value of 0.545. H o and H e The values are not significantly different, indicating that this small population follows Hardy-Weinberg equilibrium. Both values are greater than 0.5, indicating that the population's genetic diversity is moderately high; the fixation index ( F The range of heterozygosity was -0.061 to 0.327, with an average of 0.0409, indicating low heterozygosity and a slight loss of heterozygotes in the population; the genetic diversity within the population ( H s The variation range of the polymorphism information index (PI) was 0.639–0.884, with an average of 0.752, indicating good genetic diversity within the population; PIC The range of ) is 0.269~0.829, with an average of 0.49, and 2.5 < PIC A value <5 indicates that the SSR molecular marker has moderate polymorphism. PIC A value ≥5 indicates that the SSR molecular marker is highly polymorphic. The data shows that the selected 24 SSR pairs exhibit moderate to high levels of polymorphism, making them suitable for population analysis. Genetic differentiation coefficient ( F st The variation range of gene flow (GFR) was 0.013–0.212, with an average of 0.061, indicating a moderate degree of genetic differentiation within the population; gene flow (GFR) N m The variation range of the genetic diversity coefficient (GDC) was 0.931–19.458, with an average of 6.344, indicating frequent gene exchange within the population and weak geographical isolation; the genetic diversity coefficient (GDC) was also high. G st The range of variation was 0.004~0.205, with an average value of 0.053, compared to... F st The results echo this, implying that the species diversity of Dalbergia odorifera is at a moderate level.
[0039] Table 2. Genetic diversity statistics of 24 SSR loci in 380 Dalbergia odorifera samples.
[0040]
[0041] 2.1.4 Cross-amplification of SSR markers with other species
[0042] SSR marker technology is commonly used for identifying species genetic diversity and distinguishing closely related species. To verify whether the 24 pairs of polymorphic SSR markers used in this study are species-specific, we analyzed eight species of Dalbergia genus (…). Dalbergia oliveri , Dalbergia bariensis , Dalbergia cultrata , Dalbergia benthamii , Dalbergia sissoo , Dalbergia cochinchinensis , Dalbergia balansae , Dalbergia hainanensis ) and five species of Pterocarpus genus ( Pterocarpus marsupium , Pterocarpus macarocarpus , Pterocarpus northern , Pterocarpus indicus , Pterocarpus echinatus Cross-amplification experiments were conducted. The results showed that most SSR loci did not distinguish well between *Dalbergia* species and *Dalbergia odorifera*. Only two markers, JXHT136 and JXHT062, showed a low amplification rate (12.5%) for *Dalbergia* plants, indicating high distinguishability. Most SSR loci could distinguish well between *Pterocarpus* species and *Dalbergia odorifera*. The amplification rate of 10 markers (JXHT129, S10, S03, S24, S01, S08, 34a, JXHT022, JXHT136, 33c, and S11) was 0%, completely distinguishing *Pterocarpus* species from *Dalbergia odorifera*. The amplification rate of 4 markers (JXHT025, JXHT004, S04, and 96c) was 100%, completely failing to distinguish *Pterocarpus* species from *Dalbergia odorifera*. JXHT136 showed the best species differentiation among external populations. Phylogenetic trees of outgroups and five Dalbergia odorifera populations were constructed using the neighbor-joining (NJ) method. The results showed that 380 Dalbergia odorifera samples could cluster into one large branch, and the five species of Dalbergia could cluster into one small branch, all of which were distinguishable from the eight species of Dalbergia.
[0043] 2.2 Phenotypic Data Analysis
[0044] 2.2.1 Analysis of the diversity of phenotypic traits in different regions
[0045] coefficient of variation ( CV ( ) is a relative index that measures the dispersion of phenotypic data. It eliminates differences in units and means, facilitating comparisons of the degree of variation between different samples or groups. Therefore, we calculated the phenotypic traits of different groups. CV Values (see Table 3), the average of the nine phenotypic traits across all samples. CV The percentage was 22.78%, with the maximum being heartwood percentage (HWR, 60.04%) and the minimum being leaf number (LN, 11.40%). The heartwood percentage (HWR) showed a high... CV High phenotypic value, high phenotypic diversity, and unstable genetic characteristics; moderate diameter at breast height (DBH) and diameter at ground level (GD). CV High values and high phenotypic diversity; while, apart from leaf area (LA), leaf-related indicators (RL, LN, LL, LW, LWR, and LA) CV The values were all at low to medium levels, indicating low phenotypic diversity and relatively stable genetic characteristics. The average values for the XL and HK groups were... CV The percentages were 20.50% and 22.90% respectively, which were not significantly different from the overall sample, indicating that the differences in phenotypic diversity among different groups were not significant.
[0046] Table 3. Descriptive statistics of 70 Dalbergia genotypes on the studied traits.
[0047]
[0048] Note: Min: minimum value; Max: maximum value; SD: standard deviation; CV: coefficient of variation; DBH: diameter at breast height; GD: diameter at ground level; RL: rachis length; LN: number of leaflets; LL: leaflet length; LW: leaflet width; LWR: leaflet length-to-width ratio; LA: leaflet area; HWR: heartwood ratio.
[0049] 2.2.1 Correlation analysis between pairs of phenotypic traits
[0050] Correlation among phenotypic traits: DBH showed a highly significant positive correlation with GD and RL; RL showed extremely significant positive correlations with LN and LW, LL with LW, LWR, and LA, and LW with LA (P≤0.01); DBH showed significant positive correlations with HWR, GD with RL, LW, HWR, and RL with LA (P≤0.05). However, RL showed significant negative correlations with LWR, LN with LW and LA, and LW with LWR and LWR with HWR (P≤0.05).
[0051] 2.3 Correlation Analysis
[0052] Linkage disequilibrium (LD) refers to the non-random association of alleles on the same chromosome or between different chromosomes. A higher degree of linkage disequilibrium indicates a stronger genetic connection, requiring fewer molecular markers. In this study, 276 combinations of 24 SSR loci were included in the linkage disequilibrium analysis. At a p-value ≤ 0.01, significant linkage disequilibrium was found in 97 SSR loci combinations, accounting for 35.14% of all combinations; 111 SSR loci showed rD ≥ 0.3 (strong linkage disequilibrium), accounting for 40.22%; and 168 SSR loci showed rD ≥ 0.1 (moderate linkage disequilibrium), accounting for 60.87%. This indicates that the SSR markers used in this study exhibited disequilibrium and could be used for association analysis with phenotypic traits.
[0053] Table 4 presents the association analysis results with phenotypic traits. Generalized linear model (GLM) analysis showed that 8 traits were significantly associated with 16 SSR loci (P≤0.05), of which 7 traits were highly significantly associated with 12 SSR loci (P≤0.01). Explained R0.05 2 The percentages ranged from 3.85% (RL and JXHT136-253) to 18.97% (GD and 96c-345). Multivariate model (MLM) analysis showed that nine traits were significantly associated with 17 SSR loci, including highly significant associations at 15 loci, with R... 2 The percentages ranged from 6.69% (HWR and 96c-340) to 21.41% (LW and 96c-348). Cross-analysis of the results from the two analytical models revealed significant associations between four traits and seven SSR loci: DBH with 96c-345, RL with 58b-159, LN with S09-220, HWR with 34a-241, and JXHT097-252, JXHT136-270, and S03-265 all showed highly significant associations. Furthermore, seven traits showed relatively significant associations with nine SSR loci (one model showed a highly significant association, and the other showed a significant association).
[0054] Analysis revealed that GLM and MLM analyses showed that 34a-241 and HWR, 58b-159 and RL, and 34a-241, JXHT097-252, JXHT136-270, and S03-265 were significantly associated with HWR in a one-to-one correspondence. The remaining loci were significantly associated with multiple traits. Notably, 96c-345 was significantly associated only with diameter at breast height (DBH), ground diameter (GD), and HWR.
[0055] Table 4 shows the SSR locus analysis of traits in 70 individuals using GLM and MLM models.
[0056]
[0057] Note: The table shows SSR loci that are highly significantly associated with the phenotypic trait when the detection threshold P≤0.01. If one association analysis model shows a highly significant association, while another shows only a significant association (P≤0.05), the results of these two analyses are combined and listed in the table; if not listed, it means that the association between the locus and the trait is not significant (P>0.05).
[0058] 3. Conclusion Analysis
[0059] SSR analysis of 380 samples from five populations showed that plantations ( I =1.030、 H o =0.518、 H e =0.545、 PIC The genetic diversity of the population (=0.490) is at a moderate level, comparable to that of wild resources, and the degree of population differentiation is also at a moderate level. F st =0.061), confirming that plantations retain a large amount of wild genetic variation and are not affected by bottleneck effects, making them an effective alternative resource for wild germplasm. Pairwise correlation analysis of phenotypic traits showed a significant positive correlation (P≤0.05) between diameter at breast height (DBH), ground diameter (GD), and heartwood yield (HWR), indicating that growth-related processes may be involved in heartwood formation, and these phenotypes should be used as the basis for screening high-yielding germplasm. Furthermore, the 96c-345 locus was found to be specifically associated with DBH, GD, and HWR, and can serve as an early screening marker for fast-growing germplasm; the 34a-241, JXHT097-252, JXHT136-270, and S03-265 loci were also found to be highly significantly correlated with HWR (P≤0.01), laying the foundation for marker-assisted breeding of high-yielding heartwood in Dalbergia odorifera.
[0060] This study is the first to systematically demonstrate the properties of Dalbergia odorifera (Dalbergia odorifera). D. odorifera The study explored the role of plantations in resource conservation and genetic breeding, and identified molecular marker sites that can be used for assisted breeding. This provided a scientific basis for the breeding of rare species and afforestation, and set a model for the protection and utilization of genetic resources of rare species, thus possessing significant scientific and applied value.
[0061] Example 1
[0062] A method for screening high-yielding and fast-growing Dalbergia odorifera germplasm using SSR molecular markers, the specific steps of which are as follows:
[0063] Genomic DNA was extracted from the sample to be tested, and the molecular marker 96c-345 was detected using the upstream and downstream primers and detection system described in Table 1. If the molecular marker was detected, it was predicted that the Dalbergia odorifera sample would grow relatively fast and that the sample was a potential fast-growing germplasm.
[0064] Example 2
[0065] This embodiment proposes a method for predicting the heartwood yield of Dalbergia odorifera using SSR molecular markers. The specific steps are as follows:
[0066] Genomic DNA was extracted from the sample to be tested. Molecular markers 34a-241, JXHT097-252, JXHT136-270, and S03-265 were detected using the upstream and downstream primers and detection system described in Table 1. If at least one of the molecular markers was detected, it was predicted that the heartwood yield of the Dalbergia odorifera sample was high, and the sample was a potential high-heartwood-yield sample.
[0067] Example 3
[0068] This embodiment proposes a method for predicting the heartwood yield of Dalbergia odorifera using SSR molecular markers. The specific steps are as follows:
[0069] Genomic DNA was extracted from the sample to be tested. Molecular markers 34a-241, JXHT097-252, JXHT136-270, S03-265, and 96c-345 were detected using the upstream and downstream primers and detection system described in Table 1. If at least one of the other four molecular markers is detected in addition to 96c-345, it is predicted that the heartwood yield of the Dalbergia odorifera sample is high and it can be used as excellent germplasm for subsequent breeding.
[0070] The above description is only a part of the embodiments of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention shall fall within the protection scope of the present invention.
Claims
1. The application of the primer for detecting SSR molecular marker in screening Dalbergia odorifera high-yield germplasm, characterized in that, The molecular markers include at least one of 34a-241, S03-265, JXHT097-252, JXHT136-270, and 96c-345. The upstream and downstream primer sequences of 34a-241 are shown in SEQ ID NO.1 and SEQ ID NO.2, respectively; the upstream and downstream primer sequences of S03-265 are shown in SEQ ID NO.39 and SEQ ID NO.40, respectively; the upstream and downstream primer sequences of JXHT097-252 are shown in SEQ ID NO.15 and SEQ ID NO.16, respectively; the upstream and downstream primer sequences of JXHT136-270 are shown in SEQ ID NO.47 and SEQ ID NO.48, respectively; and the upstream and downstream primer sequences of 96c-345 are shown in SEQ ID NO.41 and SEQ ID NO.42, respectively. High yield of Dalbergia odorifera is predicted if at least one of the following alleles is detected: 241 bp allele detected by primers 34a-241, 265 bp allele detected by primers S03-265, 252 bp allele detected by primers JXHT097-252, 270 bp allele detected by primers JXHT136-270, and 345 bp allele detected by primers 96c-345. The high yield refers to a high heartwood percentage.
2. Use according to claim 1, characterized in that, If the upstream and downstream primers of 96c-345 detect a 345bp allele, it predicts high yield and fast growth of Dalbergia odorifera; fast growth is defined as large diameter at breast height (DBH) and ground diameter (DBD).
3. The application according to claim 1, characterized in that, Using the upstream and downstream primers to detect the molecular marker, if at least one of the other four alleles is detected in addition to 96c-345, then the Dalbergia odorifera is a high-yielding and fast-growing germplasm; fast-growing means having a large diameter at breast height (DBH) and ground diameter (DBD).
4. Use according to claim 1, characterized in that, The amplification reaction system for detecting the molecular marker using the upstream and downstream primers is as follows: 5.0 μL 2×Taq PCR premix, 1.0 μL genomic DNA, 0.5 μL each of the upstream and downstream primers, and 3.0 μL ddH2O.
5. Use according to claim 4, characterized in that, The concentration of the genomic DNA is 20-50 ng / μL.
6. Use according to claim 4, characterized in that, The concentration of the primers was 10 pmol / μL.
7. Use according to claim 4, characterized in that, The conditions for the amplification reaction are as follows: Pre-denaturation at 95℃ for 5 min; denaturation stage: 10 cycles, 95℃ for 30 s, annealing at 62℃~52℃ for 30 s / cycle, 72℃ for 30 s; amplification stage: 25 cycles, 95℃ for 30 s, 52℃ for 30 s, 72℃ for 30 s; final extension at 72℃ for 20 min.