Method for identifying index genes of tea tree tolerance to poor soil based on WGCNA analysis and application

Abstract

The present application belongs to the field of plant molecular biology and functional genomics, and particularly relates to a method for identifying index genes of tea tree tolerance to poor soil based on WGCNA analysis and application. The present application discloses a method for identifying tea tree genes related to poor soil tolerance. The method first selects tea tree varieties with different growth potentials, and measures root biomass under the same conditions. After low-nitrogen treatment of seedlings, root tissues are taken to extract RNA, build a cDNA library and perform high-throughput sequencing. Based on the sequencing data, a gene set with high expression and large variation coefficient is screened, a gene co-expression network is constructed by using WGCNA, and a "green" module highly related to root biomass is identified. Fourteen core candidate genes stably highly expressed in the strong growth potential variety are screened out as potential candidate molecular indexes of poor soil tolerance, which are used for germplasm resource evaluation, early screening of low-fertilizer-tolerant varieties and molecular marker-assisted breeding, and have important theoretical value and application prospect.

Description

Technical Field

[0001] This invention belongs to the field of plant molecular biology and functional genomics, specifically relating to a method and its application for identifying tea plant barrenness tolerance index genes based on WGCNA analysis. Background Technology

[0002] tea tree( Camellia sinensis Tea is an important perennial economic crop in my country, with a long growth cycle and a high dependence on soil nutrients, especially nitrogen. In actual production, a large number of tea gardens are distributed in hilly and mountainous areas with poor soil and nitrogen deficiency, which seriously restricts the growth of tea trees and the yield and quality of tea. Therefore, breeding new tea varieties that are tolerant to low nitrogen and poor soil has become one of the core objectives of current breeding work.

[0003] Traditional breeding relies primarily on field phenotypic screening, which has limitations such as long cycles, low efficiency, and susceptibility to environmental interference. In recent years, the development of high-throughput sequencing technology has promoted the widespread application of transcriptomics in plant stress response research. Weighted co-expression network analysis (WGCNA), as a systems biology method, can identify functionally synergistic gene modules from large-scale expression data, revealing the regulatory networks of complex traits.

[0004] However, systematic exploration of genes related to tolerance to poor soil conditions remains relatively weak in tea plant research. Existing work largely focuses on the cloning and validation of individual functional genes, lacking a holistic strategy for analyzing the genetic mechanisms of tolerance to poor soil conditions at the "gene network-phenotype" level. In particular, it lacks a research system that effectively integrates root biomass—a key stress-resistance phenotype—with co-expression networks. Therefore, there is an urgent need to establish an efficient, reproducible, and universally applicable method for identifying genes related to tolerance to poor soil conditions in tea plants, providing theoretical support and technical tools for molecular breeding.

[0005] This study utilizes root biomass phenotypic data and root transcriptome sequencing data under low nitrogen stress, combined with weighted co-expression network analysis (WGCNA), to systematically identify key gene modules and core candidate genes related to the tolerance of tea to poor soil conditions. This method can be used for tea germplasm resource evaluation, early screening of low-fertility tolerant varieties, and molecular design breeding. Summary of the Invention

[0006] To address the problems existing in the prior art, this invention provides a method and application for identifying tea plant tolerance to poor soil conditions based on WGCNA analysis. This method compares the root transcriptomes of tea plant varieties with different growth vigors under low nitrogen stress, combines root biomass phenotypic data to construct a gene co-expression network, identifies gene modules significantly related to growth vigor, and further screens out core candidate genes as molecular evaluation indicators of tea plant tolerance to poor soil conditions.

[0007] The present invention is specifically implemented using the following technical solutions:

[0008] The first aspect of this invention provides a method for identifying genes related to tolerance to poor soil in tea trees, comprising the following steps:

[0009] (1) Select tea varieties with strong and weak growth potential and measure their root biomass under the same cultivation conditions.

[0010] (2) The seedlings of the tea tree variety were subjected to low nitrogen treatment, root tissues were collected, total RNA was extracted, a cDNA library was constructed and high-throughput transcriptome sequencing was performed.

[0011] (3) Based on sequencing data, a set of genes with high expression levels and large coefficient of variation was screened, and a gene co-expression network was constructed using weighted gene co-expression network analysis to divide the gene into multiple gene modules;

[0012] (4) Correlation analysis was performed on the characteristic genes of each gene module and the root biomass to screen out gene modules that are significantly positively correlated with root biomass;

[0013] (5) In the gene modules that are significantly positively correlated, several core genes are selected based on gene connectivity or weight values ​​as candidate molecular indicators of tea tree tolerance to poor soil.

[0014] Furthermore, the low-nitrogen treatment conditions described in step (2) are: the ammonium nitrate concentration is not higher than 0.1 mM, other nutrients are maintained at normal levels, and the treatment time is not less than 21 days.

[0015] Furthermore, the gene module that is significantly positively correlated with root biomass in step (4) is the "green" module, which contains 1387 genes.

[0016] Furthermore, the core gene mentioned in step (5) is the core gene identified in the "green" module, and its average expression level in tea tree varieties with strong growth potential is higher than that in varieties with weak growth potential, with a difference of ≥2 times.

[0017] Furthermore, the core genes include, but are not limited to, the following 14 genes: CSS0032724, CSS0035356, CSS0027956, CSS0030718, CSS0022852, CSS0010822, CSS0029967, CSS0021338, CSS0022715, CSS0002800, CSS0026315, CSS0036601, CSS0003724, and CSS0030991.

[0018] The second aspect of the present invention provides a molecular marker combination for evaluating the tolerance of tea trees to poor soil, characterized in that it includes the expression profiles of the 14 core genes described in the first aspect.

[0019] The third aspect of this invention provides the application of the aforementioned molecular marker combinations in the discovery of barrenness-tolerant genes, molecular marker development, or molecular breeding.

[0020] A fourth aspect of the present invention provides a method for screening new tea tree varieties tolerant to poor soil conditions, comprising:

[0021] (1) Determine the root transcriptome of the tea plant material under low nitrogen conditions;

[0022] (2) Detect the expression level of the core genes described in the first aspect;

[0023] (3) If the overall expression level of the core gene is significantly higher than that of the control weak growth vigor variety, then the material is judged to have strong potential to tolerate poor soil.

[0024] Compared with the prior art, the beneficial effects of the present invention are:

[0025] This invention is the first to systematically identify the "green" co-expression module and a set of core candidate genes closely related to tea plant tolerance to poor soil conditions, providing an efficient and accurate method for identifying genes related to tea plant tolerance to poor soil conditions, and offering an efficient technical path for tea plant molecular breeding.

[0026] (1) Multi-variety comparative design: Tea tree materials with contrasting growth vigor are used to enhance the detectability of gene expression differences;

[0027] (2) Realistic environmental simulation: Low-nitrogen hydroponic treatment simulates barren soil conditions, enhancing the biological relevance of the results;

[0028] (3) Systems biology approach: Using WGCNA to mine gene modules rather than single genes, which is closer to the regulatory nature of complex traits;

[0029] (4) Phenotypic-omics integration: Root biomass is used as a key phenotype and associated with gene networks to ensure the functional relevance of screening results;

[0030] (5) Core genes are verifiable: The expression patterns of the 14 core genes selected have been verified and have the potential for widespread application. Attached Figure Description

[0031] Figure 1 For different tea tree resources, the fresh weight of the root system is considered;

[0032] Figure 2 Construction of a root gene clustering and co-expression module for different tea tree resources;

[0033] Figure 3This section associates samples with WGCNA modules; each row corresponds to a module, each column corresponds to a specific sample, and the color of each cell at the intersection of rows and columns represents the correlation coefficient between the module and the sample. Detailed Implementation

[0034] The following will describe the concept and technical effects of the present invention clearly and completely with reference to the embodiments, so as to fully understand the purpose, features and effects of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, not all embodiments. Other embodiments obtained by those skilled in the art based on the embodiments of the present invention without creative effort are all within the scope of protection of the present invention. The tea plant genes involved in the embodiments can all be found in the Tea Plant Information Archive.

[0035] Example 1: Determination of growth vigor phenotype in tea plant materials

[0036] Eight tea varieties were selected: a group with weak growth vigor (ZM6, 1620, SY1, WNZ) and a group with strong growth vigor (ZC99, 3006, 1902, ZM7). The varieties were derived from Longjing 43 (LJ43), Zhongming 6 (ZM6), Shiyan 1 (SY1), Wuniuzao (WNZ), Zhongcha 99 (ZC99), Zhongming 7 (ZM7), and Zhongcha 9 (ZC9). 1620, 3006, and 1902 were tea varieties bred by the Tea Research Institute of the Chinese Academy of Agricultural Sciences, all obtainable from the institute. 1620 and 1902 are hybrids of 'Longjing 43' and 'Baihaozao', while 3006 is a hybrid of 'Wuniuzao' and 'Longjing 43'. All varieties were propagated by cuttings under identical field conditions and cultivated using conventional management methods for 14 months. At harvest, the entire root system was removed, washed with clean water, and the surface moisture was dried. The fresh weight of the roots was immediately measured (10 biological replicates per variety). Results are as follows: Figure 1 As shown, the average root biomass of the high-growth-potential group was 1.97 times that of the low-growth-potential group, a highly significant difference. p <0.01).

[0037] Example 2: Low-nitrogen treatment and transcriptome sequencing

[0038] Healthy tea seedlings of the above eight varieties were transplanted into a hydroponic system. They were first acclimatized for 7 days with a 1 / 4 complete nutrient solution, then transferred to a low-nitrogen nutrient solution (0.1 mM ammonium nitrate, other nutrients remained unchanged) for 21 days. After treatment, root tissues were collected, immediately flash-frozen in liquid nitrogen, and stored at -80°C. Total RNA was extracted, a cDNA library was constructed, and RNA-seq sequencing was performed. After quality control, the raw data were aligned to the tea reference genome using HISAT2. Camellia sinensis (var. sinensis genome v2.0), StringTie calculates gene expression levels (TPM values).

[0039] Example 3: WGCNA analysis to identify root growth potential-related modules

[0040] The top 25,000 genes with high expression levels (FPKM>1) and large coefficients of variation were selected for WGCNA analysis. A co-expression network was constructed using the WGCNA package in R, and a soft threshold β = 9 was determined based on the scale-free topology criterion (R²>0.8). An anisotropy matrix was constructed based on the Pearson correlation coefficients between genes, and the genes were hierarchically clustered into 39 co-expression modules (named by color). Figure 2 ).

[0041] Correlation analysis was performed between the characteristic genes of each module and the fresh weight of the root system. Figure 3 The results showed that the "green" module was the gene module most significantly associated with root biomass in this study (this module contains 1387 genes).

[0042] Example 4: Screening of candidate core genes

[0043] To further explore key regulatory genes in the "green" module, genes with kME > 0.8 and the top 300 connectivity were selected based on module membership degree (kME) and gene connectivity within the module, and a gene network was constructed. The network was visualized using Cytoscape software, and 20 candidate core genes were initially selected based on "weight" scores (combining connectivity strength and expression stability) (Table 1).

[0044] Table 1. Top 20 candidate core genes with the highest degree values ​​in the Green module

[0045] .

[0046] Further analysis of their expression profiles in eight varieties revealed that the average expression levels of these core genes in tea varieties with strong growth potential (Table 2) were significantly higher than those in tea varieties with weak growth potential (Table 3), with an average difference of 5-fold. Among them, genes CSS0021338 and CSS0030718 showed the most significant differences, with the strong group expressing 30.5 and 10.6 times more genes than the weak group, respectively (Table 4). After removing genes with a fold change ≤2, 14 core genes were finally identified as potential indicator genes for tolerance to poor soil conditions in tea plants.

[0047] Table 2. Expression levels (TPM values) of 20 candidate core genes in the roots of four vigorous tea plant species.

[0048] .

[0049] Table 3. Expression levels (TPM values) of 20 candidate core genes in the roots of four weak tea plant species.

[0050] .

[0051] Table 4. Mean TPM expression ratio of 20 candidate core genes in the roots of vigorous and weak tea trees

[0052] .

[0053] Example 5: Validation and Application Evaluation of Core Genes

[0054] To verify the universality and predictive ability of the aforementioned core genes, two tea varieties that were not involved in the modeling, LJ43 (weak growth potential) and ZC9 (strong growth potential), were selected for verification. The fresh weight of their roots was measured according to the method in Example 1, with ZC9 weighing 7.98 g and LJ43 weighing 2.96 g. The fresh weight of ZC9 roots was 2.7 times that of LJ43 (Table 5).

[0055] Table 5. Expression levels (TPM values) of 14 core genes in ZC9 and LJ43

[0056] gene LJ43 ZC9 ZC9 / LJ43 CSS0032724 78.21 139.73 1.8 CSS0035356 137.26 422.99 3.1 CSS0027956 71.08 265.15 3.7 CSS0030718 14.39 46.87 3.3 CSS0022852 248.15 445.14 1.8 CSS0010822 1.31 4.35 3.3 CSS0029967 10.32 51.15 5.0 CSS0021338 3.33 4.83 1.5 CSS0022715 3.26 8.06 2.5 CSS0002800 33.09 83.03 2.5 CSS0026315 4.54 10.00 2.2 CSS0036601 4.38 9.97 2.3 CSS0003724 49.82 160.06 3.2 CSS0030991 5.79 24.13 4.2

[0057] Low nitrogen treatment was performed as described in Example 2, and the root transcriptome was measured. The results showed that the expression levels of all 14 core genes in ZC9 were higher than those in LJ43, with an average expression level 2.9 times that of LJ43, and 11 genes were upregulated by more than 2-fold, with a highly consistent overall expression trend.

[0058] The results confirm that the core gene can effectively distinguish tea plant materials with different tolerance to poor soil conditions, and has the potential to be used as a combination of molecular markers.

Claims

1. A method for identifying genes related to tolerance to poor soil in tea trees, characterized in that, Includes the following steps: R.1 Select tea varieties with strong and weak growth potential and measure their root biomass under the same cultivation conditions. R.2 The seedlings of the tea variety were subjected to low nitrogen treatment, root tissues were collected, total RNA was extracted, a cDNA library was constructed, and high-throughput transcriptome sequencing was performed. R.3, based on sequencing data, screens gene sets with high expression levels and large coefficients of variation, constructs gene co-expression networks using weighted gene co-expression network analysis, and divides them into multiple gene modules; R.4 Correlation analysis was performed between the characteristic genes of each gene module and root biomass to screen out gene modules that were significantly positively correlated with root biomass. R.5 In the significantly positively correlated gene modules, based on gene connectivity or weight values, several core genes are screened as candidate molecular indicators of tea tree tolerance to poor soil conditions; the core genes include, but are not limited to, the following 14 genes: CSS0032724, CSS0035356, CSS0027956, CSS0030718, CSS0022852, CSS0010822, CSS0029967, CSS0021338, CSS0022715, CSS0002800, CSS0026315, CSS0036601, CSS0003724, and CSS0030991.

2. The method as described in claim 1, characterized in that, The low-nitrogen treatment conditions described in step R.2 are: ammonium nitrate concentration not higher than 0.1 mM, other nutrients maintained at normal levels, and treatment time not less than 21 days.

3. The method as described in claim 1, characterized in that, The core gene mentioned in step R.5 has an average expression level in tea varieties with strong growth potential that is higher than that in varieties with weak growth potential, with a difference of ≥2 times.

4. A molecular marker combination for evaluating the tolerance of tea plants to poor soil, characterized in that, It includes the 14 core genes described in claim 1.

5. The application of the molecular marker combination as described in claim 4 in the discovery of low-nitrogen and barren soil tolerance genes in tea trees, molecular marker development, or molecular breeding.

6. A method for screening new tea varieties tolerant to low nitrogen and poor soil conditions, characterized in that, include: S.1 Determination of root transcriptome of the tea plant material under low nitrogen conditions; S.2 Detect the expression level of the core gene described in claim 1; S.3 If the overall expression level of the core gene is significantly higher than that of the control weak growth vigor variety, then the material is judged to have strong potential for tolerance to poor soil.

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