Molecular markers and gene combination related to salt-alkali tolerance of alfalfa based on pot phenotype

Abstract

The present application relates to the technical field of genetic engineering, and more particularly to a salt-tolerant and alkali-tolerant alfalfa related molecular marker and gene combination based on a potted phenotype, wherein the gene is selected from any one or more of the following genes: Msa.H. 0273230 , Msa.H. 0273240 The present application provides a gene or expression product kit that can be directly used for detection, and a matching molecular marker, which greatly simplifies the identification process of the salt-tolerant and alkali-tolerant alfalfa germplasm, and accelerates the breeding process of the salt-tolerant and alkali-tolerant alfalfa new variety. The core innovation of the present application is to establish a system screening method of potted phenotype precise evaluation-full genome correlation analysis-linkage disequilibrium segment haplotype typing, through the collaborative evaluation of multiple traits such as relative plant height and relative branch number, the limitations of traditional methods relying on single index and random combination are broken through, and the positioning accuracy and screening efficiency of the salt-tolerant and alkali-tolerant gene site are significantly improved.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of genetic engineering, and particularly relates to a salt-tolerant and alkali-tolerant molecular marker and gene combination of Medicago sativa based on a pot phenotype. BACKGROUND

[0002] As one of the most important legume forages in the world, the yield and quality of Medicago sativa are deeply affected by soil salinization. With the increasing problem of global land salinization, it has become an urgent need to breed new varieties of salt-tolerant and alkali-tolerant M. sativa to ensure the sustainable development of animal husbandry. However, the salt-tolerance and alkali-tolerance of M. sativa is a typical quantitative trait controlled by multiple genes, which is significantly affected by the interaction of genetic background and environmental factors. Traditional phenotype screening and conventional breeding methods have great limitations in genetic analysis and breeding efficiency. Therefore, it is of great significance to use genome-wide association analysis (GWAS) to systematically mine salt-tolerance and alkali-tolerance related molecular markers and key genes for accelerating the molecular breeding process of salt-tolerant and alkali-tolerant M. sativa.

[0003] In order to accurately evaluate the salt-tolerance and alkali-tolerance differences of M. sativa germplasm resources, a systematic evaluation system based on pot seedling phenotype was established. 196 M. sativa germplasm resources from 50 countries around the world were used as materials. The genetic background differences between individuals were overcome by using uniform cutting and cloning methods. Salt stress (100 mM NaCl solution, final salt concentration 0.41%) and alkali stress (50 mM NaHCO3 solution, final alkali concentration 0.31%, pH value 8.9) treatments were set up respectively. By accurately measuring key growth traits such as plant height, branch number, fresh weight and dry weight at seedling stage, salt tolerance index and alkali tolerance index were calculated. The phenotypic variation rules of each trait under salt and alkali stress were systematically revealed. It was found that relative fresh weight was the most sensitive to stress response, and there were significant differences in salt-tolerance and alkali-tolerance among different improvement types (wild species, cultivated species, etc.), which provided a high-quality phenotypic data basis for subsequent genetic analysis.

[0004] On the basis of phenotype evaluation, combined with high-throughput genotyping data, genome-wide association analysis was carried out on the above traits using FarmCPU model. It was found that the growth traits of M. sativa at seedling stage under salt stress and alkali stress were all controlled by multiple genes. Under the condition of significant threshold, 223 and 139 SNP sites significantly associated with target traits were detected respectively. These sites were distributed on all 8 chromosomes, the phenotypic variation explanation rate (PVE) was high, and some significantly associated sites showed co-localization among different traits, revealing the possible "one cause multiple effects" or synergistic genetic mechanism of salt-tolerance and alkali-tolerance traits. The results clearly showed the distribution of important genetic loci of salt-tolerance and alkali-tolerance of M. sativa, and provided reliable target sites for molecular marker-assisted selection.

[0005] Based on linkage disequilibrium characteristics, this study further screened candidate genes in genomic regions 20 kb upstream and downstream of significantly associated loci. Combined with functional annotation, a total of 116 salt stress-related candidate genes and 96 alkali stress-related candidate genes were obtained, suggesting that these genes may play key co-regulatory roles in alfalfa's response to cross-stress of salt and alkali. The screening of these candidate genes and the localization of molecular markers not only systematically elucidated the genetic basis of alfalfa's salt and alkali tolerance but also provided important genetic resources and theoretical basis for subsequent gene cloning, functional verification, and molecular design breeding of superior salt- and alkali-tolerant varieties. Summary of the Invention

[0006] The purpose of this invention is to provide molecular markers and gene combinations related to salt and alkali tolerance in alfalfa based on potted plant phenotypes.

[0007] To achieve the above-mentioned objectives, the present invention provides the following technical solution: This invention provides the application of reagents for detecting genes or their expression products in the preparation of kits for identifying or assisting in the identification of alkali tolerance in alfalfa, wherein the gene is selected from any one or more of the following genes: Msa.H.0273230 , Msa.H.0273240 .

[0008] Preferably, the Msa.H.0273230 and Msa.H.0273240 The gene showed a significant association with the relative plant height and relative branch number of alfalfa under alkaline stress, demonstrating pleiotropic regulatory function and participating in the synergistic regulation of multiple aboveground growth traits of alfalfa under alkaline stress.

[0009] This invention provides the application of the gene in the genetic improvement or molecular breeding of alkali tolerance in alfalfa.

[0010] Preferably, the application is: using molecular markers closely linked to the gene to conduct alkali-tolerant marker-assisted selection breeding of alfalfa germplasm resources.

[0011] Preferred, with Msa.H.0273230 or Msa.H.0273240 The tightly linked molecular markers are located on chromosome 5 of alfalfa, and their physical locations are selected from any one or more of the following sites: chr5_35227094, chr5_35229849, and chr5_35230451.

[0012] Preferably, the application is: to overexpress, silence, or edit the gene in alfalfa using genetic engineering methods to improve the agronomic traits of alfalfa under alkaline stress.

[0013] This invention provides a method for screening alkali-tolerant alfalfa germplasm, comprising the following steps: (1) Extract genomic DNA from the alfalfa sample to be tested; (2) Detect the presence and / or genotype of the gene in the sample to be tested; (3) Based on the test results, select alfalfa plants carrying the aforementioned gene and / or specific genotype.

[0014] Preferably, the method further includes: conducting pot phenotypic verification of the selected candidate germplasm under alkaline stress conditions, and measuring at least one trait among relative plant height and relative number of branches.

[0015] This invention provides a method for screening salt-alkali tolerance-related markers and genes in alfalfa based on potted plant phenotypes, comprising the following steps: The alfalfa germplasm resources to be tested were cloned by cuttings and transplanted into flower pots for pot cultivation. Salt stress treatment group, alkali stress treatment group and control group were set up, and potted plants were subjected to stress treatment respectively. Phenotypic traits of alfalfa plants in the stress treatment group and the control group were determined. Calculate the relative values ​​of each phenotypic trait, where the relative values ​​are the ratios of the phenotypic trait measurements of the stress treatment group to those of the control group. Based on the relative values, salt tolerance of alfalfa germplasm resources was evaluated, and SNP markers and candidate genes related to salt tolerance were screened by combining genome-wide association analysis.

[0016] Preferably, the phenotypic traits include plant height, number of branches, fresh weight, and dry weight; before the stress treatment, all plants are uniformly cut and stubble height is retained; the salt stress treatment is performed by watering with NaCl solution in several stages, and the alkali stress treatment is performed by watering with NaHCO3 solution in several stages; the calculation of the relative values ​​includes relative plant height, relative number of branches, relative fresh weight, and relative dry weight, wherein, relative plant height = plant height measurement under salt / alkali stress treatment ÷ plant height measurement of the control group, relative number of branches = number of branches measurement under salt / alkali stress treatment ÷ number of branches measurement of the control group, relative fresh weight = fresh weight measurement under salt / alkali stress treatment ÷ fresh weight measurement of the control group, and relative dry weight = dry weight measurement under salt / alkali stress treatment ÷ dry weight measurement of the control group.

[0017] Preferably, the genome-wide association analysis uses the FarmCPU model to screen out SNP markers and candidate genes that are significantly associated with the relative plant height, relative number of branches, relative fresh weight, and relative dry weight, within a set significance threshold. The SNP markers include: SNP markers under salt stress: chr1_111187521, chr1_42960696, chr1_68814409, chr1_68823954, chr2_62791415, chr2_70493601, chr3_27432527, chr4_21658074, chr4_63050214, chr4_6500 associated with relative plant height. 4751, chr5_76203165, chr6_11960006, chr6_181638646, chr7_28602740, chr7_28603276, c hr7_28603449, chr7_28604344, chr7_28604369, chr7_28605835, chr7_28606770, chr7_2860 7260; chr2_14149227, chr3_49984825, chr4_22665207, chr6_13793180, chr6_12379936, chr8_74992195 associated with relative branch number; chr1_49709706, chr1_56318618, chr2_55107523, chr2_58 associated with relative fresh weight 572467, chr4_87591526, chr6_14357008; chr1_28520170, chr1_56995013, chr2_55739393, chr3_70547956, chr4_12989127, chr6_43339873, chr8_57312295, chr8_57314077 associated with relative dry weight; SNP markers under alkaline stress: chr5_35229849, chr7_20985207, chr8_30398564, chr8_52127072, associated with relative plant height; chr1_37554368, chr1_78319110, chr1_85563336, chr3_11723989, chr3_18354369, chr3_18354842, chr3_18355035, chr3_18356082, chr3_18356144, chr3_18356664, chr3_18357339, chr3_50157262, chr4_35008892, associated with relative branch number. chr5_35227094, chr5_35230451, chr6_13640447, chr6_29514421, chr7_75610213; and chr1_64378663, chr2_70477781, chr3_10472645, chr3_10476122, which are associated with relative fresh weight. chr3_10476280, chr3_10476482, chr3_10478356, chr3_10480333, chr4_15062825, chr6_18155523, chr6_3686004, chr8_54253289; chr3_89298267 associated with relative dry weight; The candidate genes include: Candidate genes under salt stress: Msa.H.0009590, Msa.H.0009600, Msa.H.0009610, Msa.H.0028680, Msa.H.0044820, Msa.H.0044830, Msa.H.0044840, Msa.H.0102230, Msa.H.0102240, Msa.H.0102250, Msa.H.0107550, Msa.H.0107560, Msa.H.0107570, Msa.H.0107580, Msa.H.0132350, Msa.H.0132360, Msa.H.0132370, Msa.H.0197740, Msa.H.0197750, Msa.H.0197760, Msa.H.0197770, Msa.H.0187950, Msa.H.0187960, Msa.H.0187970, Msa.H.0187980, Msa.H.0220560, Msa.H.0220570, Msa.H.0220580, Msa.H.0220590, Msa.H.0295920, Msa.H.0295930, Msa.H.0295940, Msa.H.0295950, Msa.H.0295960, Msa.H.0295970, Msa.H.0295980, Msa.H.0307090, Msa.H.0307100, Msa.H.0307110, Msa.H.0318560, Msa.H.0318570, Msa.H.0386400, Msa.H.0386410, Msa.H.0386420, Msa.H.0386430 that are associated with relative plant height; Msa.H.0077240, Msa.H.0077250, Msa.H.0139460, Msa.H.0139470, Msa.H.0139480, Msa.H.0198350, Msa.H.0198360, Msa.H.0198370, Msa.H.0368430, Msa.H.0368440, Msa.H.0360920, Msa.H.0360930, Msa.H.0360940, Msa.H.0481120, Msa.H.0481130, Msa.H.0481140, Msa.H.0481150, Msa.H.0481160, Msa.H.0481170 that are associated with relative branch number; Msa.H.0031710, Msa.H.0031720, Msa.H.0031730, Msa.H.0035900, Msa.H.0035910, Msa.H.0035920, Msa.H.0035930, Msa.H.0035940, Msa.H.0035950, Msa.H.0097900, Msa.H.0097910, Msa.H.0097920, Msa.H.0097930, Msa.H.0100070, Msa.H.0100080, Msa.H.0100090, Msa.H.0100100, Msa.H.0239800, Msa.H.0239810, Msa.H.0239820, Msa.H.0239830, Msa.H.0316450, Msa.H.0316460, Msa.H.0316470, Msa.H.0316480; Msa.H.0020910, Msa.H.0036300, Msa.H.0036310, Msa.H.0036320, Msa.H.0036330, Msa.H.0036340, Msa.H.0036350, Msa.H.0098160, Msa.H.0098170, Msa.H.0098180, Msa.H.0151100, Msa.H.0151110, Msa.H.0151120, Msa.H.0151130, Msa.H.0151140, Msa.H.0151150, Msa.H.0192630, Msa.H.0192640, Msa.H.0192650, Msa.H.0192660, Msa.H.0330480, Msa.H.0330490, Msa.H.0330500, Msa.H.0330510, which are associated with relative dry weight. Candidate genes under alkali stress: Msa.H.0273230, Msa.H.0273240, Msa.H.0382150, Msa.H.0382160, Msa.H.0382170, Msa.H.0382180, Msa.H.0454660, Msa.H.0454670, Msa.H.0464210, Msa.H.0464220 associated with relative plant height; Msa.H.0026180, Msa.H.0026190, Msa.H.0026200, Msa.H.0052010, Msa.H.0052020, Msa.H.0052030, Msa.H.0052040, Msa.H.0052050, Msa.H.0058220, Msa.H.0058230, Msa.H.0058240, Msa.H.0058250, Msa.H.0058260, Msa.H.0058270, Msa.H.0124780, Msa.H.0124790, Msa.H.0124800, Msa.H.0128220, Msa.H.0128230, Msa.H.0128240, Msa.H.0139580, Msa.H.0139590, Msa.H.0139600, Msa.H.0139610, Msa.H.0205440, Msa.H.0273230, Msa.H.0273240, Msa.H.0367620, Msa.H.0325090, Msa.H.0325100, Msa.H.0409580, Msa.H.0409590, Msa.H.0409600, Msa.H.0409610, Msa.H.0409620 associated with relative branch number; Msa.H.0041250, Msa.H.0041260, Msa.H.0041270, Msa.H.0041280, Msa.H.0107550, Msa.H.0107560, Msa.H.0178590, Msa.H.0178600, Msa.H.0178610, Msa.H.0178620, Msa.H.0178630, Msa.H.0178640, Msa.H.0178650, Msa.H.0178660, Msa.H.0178670, Msa.H.0178680, Msa.H.0178690, Msa.H.0178700, Msa.H.0178710, Msa.H.0193880, Msa.H.0193890, Msa.H.0193900, Msa.H.0318540, Msa.H.0318550, Msa.H.0318560, Msa.H.0328190, Msa.H.0465750, Msa.H.0465760, Msa.H.0465770, Msa.H.0465780; and Msa.H.0166130, Msa.H.0166140, Msa.H.0166150, and Msa.H.0166160, which are associated with relative dry weight.

[0018] Preferably, after screening SNP markers and candidate genes, a haplotype analysis step is also included: Haplotypes were constructed for linkage disequilibrium segments containing significantly associated SNP sites, and the performance of different haplotypes under saline-alkali stress conditions was evaluated in combination with phenotypic data. The haplotype analysis specifically included: in the 28.583-28.623Mb region of chromosome 7, which is the relative plant height trait under salt stress, seven haplotypes HAP1 to HAP7 were formed by eight SNP loci: chr7_28602740, chr7_28603276, chr7_28603449, chr7_28604344, chr7_28604369, chr7_28605835, chr7_28606770 and chr7_28607260. Alfalfa individuals carrying haplotypes HAP3, HAP4 or HAP5 were identified as having higher salt tolerance. In the 18.334-18.374Mb region of chromosome 3, which is the relative branching trait under alkaline stress, six haplotypes HAP1 to HAP6 are formed by seven SNP loci: chr3_18354369, chr3_18354842, chr3_18355035, chr3_18356082, chr3_18356144, chr3_18356664, and chr3_18357339. It was found that alfalfa individuals carrying the HAP1 haplotype have higher alkaline tolerance.

[0019] Compared with the prior art, the present invention has the following beneficial effects: First, this invention is the first to identify the alfalfa gene. Msa.H.0273230 and Msa.H.0273240 Under alkaline stress, these genes showed significant associations with two key agronomic traits: relative plant height and relative branching number, revealing that these two genes have typical pleiotropic regulatory functions. This invention identifies them as core molecular targets that can be used to regulate multiple aboveground growth traits of alfalfa under alkaline stress, overcoming the technical bottleneck of single-trait selection being unable to comprehensively improve alkali tolerance.

[0020] Secondly, this invention provides diverse pathways for genetic improvement of alkali tolerance. On one hand, based on specific SNP molecular markers (chr5_35227094, chr5_35229849, and chr5_35230451) on chromosome 5 closely linked to the aforementioned genes, precise marker-assisted selection breeding for alkali tolerance in alfalfa germplasm resources can be achieved. On the other hand, the aforementioned target genes can be overexpressed, silenced, or edited through genetic engineering, thereby directionally improving the overall agronomical traits of alfalfa under alkaline stress, providing a flexible technical solution for molecular design breeding of alkali tolerance.

[0021] Third, the gene identification results of this invention are based on rigorous, large-scale scientific experiments. Based on a GWAS genome-wide association analysis covering 196 alfalfa germplasm resources from 50 countries worldwide, combined with high-throughput sequencing and the FarmCPU model, SNP loci significantly associated with alkaline stress were systematically screened and candidate genes were located. Phenotypic distribution, analysis of variance, and linkage disequilibrium assessment confirmed that these gene loci have a high explanatory power for phenotypic variation, and the results also suggest the co-regulatory role of some genes in salt-alkali cross-stress, providing solid data support and theoretical basis for genetic analysis.

[0022] Fourth, this invention innovatively establishes a three-pronged systematic screening method: "precise evaluation of potted plant phenotypes—FarmCPU model GWAS—linkage-disequilibrium haplotype typing," effectively overcoming the shortcomings of traditional phenotypic screening in the breeding of multi-gene controlled traits, which is characterized by low efficiency and long cycles. By providing gene or expression product kits and matching molecular markers that can be directly used for detection, the identification process of alkali-tolerant alfalfa germplasm is greatly simplified. This technical solution not only accelerates the breeding process of salt-alkali tolerant new varieties but also provides genetic resources and tools of great industrial value for addressing global soil salinization, ensuring the sustainable development of animal husbandry, and improving forage production capacity. Attached Figure Description

[0023] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on the provided drawings without creative effort.

[0024] Figure 1 This is a photograph of alfalfa cuttings grown in pots in a greenhouse.

[0025] Figure 2The table shows the frequency distribution histograms and normal fitting curves of four phenotypic traits at the seedling stage of 196 alfalfa materials under salt stress. Figures A to D correspond to relative plant height, relative number of branches, relative fresh weight, and relative dry weight, respectively.

[0026] Figure 3 The table shows the frequency distribution histograms and normal fitting curves of four phenotypic traits in 196 alfalfa seedlings under alkali stress. Figures A to D correspond to relative plant height, relative number of branches, relative fresh weight, and relative dry weight, respectively.

[0027] Figure 4 : Box plots showing the differential distribution of four phenotypic traits in the seedling stage of alfalfa of three improved types (cultivated, local, and wild varieties) under salt stress (S) and alkali stress (A) treatments. Figures A to D correspond to relative plant height, relative number of branches, relative fresh weight, and relative dry weight, respectively.

[0028] Figure 5 Pearson correlation matrix diagram of four phenotypic traits among 196 alfalfa seedlings under salt stress.

[0029] Figure 6 Pearson correlation matrix diagram of four phenotypic traits among 196 alfalfa seedlings under alkali stress.

[0030] Figure 7 The Manhattan plot and corresponding QQ plots of genome-wide association analysis (GWAS) for four phenotypic traits in potted seedlings under salt stress are shown. Figures A to D correspond to relative plant height, relative number of branches, relative fresh weight, and relative dry weight, respectively.

[0031] Figure 8 The Manhattan plot and corresponding QQ plot of the genome-wide association analysis (GWAS) of four phenotypic traits in potted seedlings under alkaline stress are shown. Figures A to D correspond to relative plant height, relative number of branches, relative fresh weight, and relative dry weight, respectively.

[0032] Figure 9 Figure 1 shows the local association, candidate genes, and haplotype analysis of regions with significant correlation to relative plant height under salt stress. Figure A shows the local Manhattan plot and LD heatmap (including candidate gene localization), Figure B shows the frequency distribution of the 7 haplotypes, and Figure C shows the relative plant height phenotype distribution corresponding to different haplotypes.

[0033] Figure 10 Figure 1 shows the local association, candidate gene and haplotype analysis of the regions with significant correlations in relative branch number under alkaline stress. Figure A is a local Manhattan map and LD heatmap (including candidate gene localization), Figure B is the frequency distribution of the 6 haplotypes, and Figure C is the phenotypic distribution of relative branch number corresponding to different haplotypes. Detailed Implementation

[0034] The technical solutions provided by the present invention will be described in detail below with reference to the embodiments, but they should not be construed as limiting the scope of protection of the present invention.

[0035] Example 1

[0036] 1. Materials and Methods

[0037] 1.1 Plant materials

[0038] One representative plant from each of the 196 field samples was selected for cutting cloning. After successful cutting, the plants were transplanted into pots for salt-alkali stress treatment. Salt-alkali tolerance phenotyping of the potted plants was then conducted in a greenhouse at the experimental base of the High-tech Industrial Park of the Chinese Academy of Agricultural Sciences in Langfang City, Hebei Province. Figure 1 ).

[0039] 1.2 Genotype Analysis

[0040] One plantlet from each material was selected, and young leaves were used for genome resequencing. Genomic DNA was extracted from the young leaves using a plant genomic DNA extraction kit (Beijing Kangwei Century Biotechnology Co., Ltd.). The purity and concentration of the DNA were assessed using a NanoDrop spectrophotometer to ensure compliance with the requirements for genome resequencing library construction and sequencing. DNA library construction and high-throughput sequencing were performed by Berry Genomics (Beijing, China). Genome resequencing was conducted using the Illumina NovaSeq 6000 sequencing platform, with approximately 30 Gb of raw data per material. Quality control of the raw data was performed using FastP (v0.23.4) software, and the main steps included removing adapter sequences and filtering low-quality bases.

[0041] Using the haploid genome of 'Zhongmu 4' alfalfa (approximately 826 Mb in size) as a reference, the quality-controlled sequencing data were aligned to the reference genome using BWAMEM software. After alignment, SAMtools (v1.18) was used to sort and filter the alignment results, removing multiple alignments and low-quality alignment sequences. To further improve the accuracy of variant detection, the MarkDuplicates module in the GATK (v4.3.0.0) toolset was used to mark and remove PCR repetitive sequences, followed by single nucleotide polymorphism (SNP) detection and preliminary identification using the HaplotypeCaller module.

[0042] To obtain a high-confidence SNP marker set, this study followed the GATK best practice guidelines and population genetics standards, employing VCFtools (v0.1.16) for multi-level rigorous filtering of the original variants. First, hard filtering thresholds were set based on quality parameters: Quality Depth (QD) < 2.0, Fisher's test chain bias (FS) > 60.0, Mapping Quality Rank Sum Test (MQ Rank Sum Test) < -12.5, Read Pos Rank Sum Test (Read Pos Rank Sum Test) < -8.0, Chain Bias Ratio (SOR) > 3.0, and Mapping Quality (MQ) < 40.0. Subsequently, further quality control was performed using population genetics indicators, specifically including: removing variants significantly deviating from Hardy-Weinberg equilibrium (HWE). P <1×10 -6 The selection process involved multiple screening steps: a minimum allele frequency (MAF) of at least 0.05 was set to exclude interference from low-frequency variants; the maximum missing rate (Max Missing) was limited to no more than 0.1 to ensure that the locus was genotyped in over 90% of individuals; and a minimum sequencing quality score (MinQ) of at least 30 was required. Through these multiple screening methods, high-quality SNP loci were obtained, providing a reliable data foundation for subsequent genome-wide association studies and genetic diversity analysis.

[0043] 1.3 Phenotypic Index Measurement and Analysis

[0044] (1) Phenotypic index determination

[0045] Clonal plants with consistent growth after successful cutting were selected and transplanted into pots for a pot experiment. One plant was transplanted into each pot. Three treatment groups were set up: salt stress, alkali stress, and normal growth, with three replicates in each group. The pots used in the experiment were 12 cm in diameter and filled with potting soil. The bottom of the pots was designed to be fully sealed to prevent soil leakage, and each pot contained 1000 g ± 10 g of potting soil. After transplanting, the alfalfa plants were initially managed with normal watering to promote seedling establishment and growth. During the growing season, weeding and pruning were carried out regularly. Before the salt and alkali stress treatment, all plants were homogenized by uniformly cutting them, leaving a 3 cm stubble. After a period of growth, the plants were watered with 100 mM NaCl solution and 50 mM NaHCO3 solution seven times, with an interval of two days between each watering, to implement salt stress and alkali stress treatment (the final soil salt concentration in the salt treatment group was 0.41%; the final soil alkali concentration in the alkali treatment group was 0.31%, and the soil pH was 8.9). After the salt and alkali stress treatment lasted for four weeks, the various phenotypic indicators were measured.

[0046] Plant height: Randomly select 3 representative branches from each pot and measure their height with a ruler.

[0047] Branch count: The total number of branches in each pot is counted using manual techniques.

[0048] Fresh weight: Cut the whole plant, leaving a stubble height of 3 cm, then use an electronic scale to weigh the fresh weight of the cut part and bag it.

[0049] Dry weight: After weighing the fresh plants, put them into envelopes and dry them, then weigh them using an electronic scale.

[0050] (2) Phenotypic index analysis

[0051] Salt tolerance index (ST) and alkali tolerance index (SA) were calculated for phenotypic traits in potted seedlings. The specific calculation formulas are: Salt tolerance index (ST) = Phenotypic value of trait under salt treatment conditions ÷ Phenotypic value of trait under control conditions; Alkali tolerance index (SA) = Phenotypic value of trait under alkali treatment conditions ÷ Phenotypic value of trait under control conditions. The distribution range, phenotypic mean, coefficient of variation, and correlation analysis of each phenotypic trait (including the seedling salt and alkali tolerance index) were statistically analyzed using R- (version 4.10) software; trait correlation was analyzed using R package... ggplot Visualization plots were created, and the normal distribution of each phenotypic trait was analyzed using SPSS (version 26) statistical software.

[0052] 1.4 Genome-wide association analysis

[0053] High-quality single nucleotide polymorphisms (SNPs) obtained using VCFtools (v0.1.16) were used to screen for significant SNPs associated with salt tolerance in alfalfa. Genome-wide association analysis was performed using R software. gapit This R package analyzes the salt tolerance traits of alfalfa based on the FarmCPU model; the results are visualized using Manhattan plots and QQ plots. CMplot Complete the drawing.

[0054] 1.5 Candidate Gene Analysis

[0055] Based on the linkage disequilibrium (LD) analysis results, all genes within a 20kb range upstream and downstream of significantly associated loci (total 40kb) were delineated and screened. Subsequently, the EggNOG database was used to perform functional annotation and enrichment analysis on the above gene set, and potential candidate genes closely related to salt tolerance in alfalfa were further screened.

[0056] 2 Results and Analysis

[0057] 2.1 Phenotypic analysis and salt tolerance evaluation

[0058] To systematically evaluate the differences in the degree of inhibition of seedling growth by salt-alkali stress on different alfalfa germplasm resources, this study measured the relative values ​​of four seedling growth-related traits under salt-alkali treatment conditions, including plant height (PH), branch number (BN), fresh weight (FW), and dry weight (DW). Subsequent analyses in this chapter will use relative plant height (RPH), relative branch number (RBN), relative fresh weight (RFW), and relative dry weight (RDW), where the relative values ​​were calculated as the ratio of the measured values ​​of the treatment group to those of the control group. The descriptive statistical results of the relative values ​​of the four phenotypic traits under salt stress are shown in Table 1. All four phenotypic traits exhibited relatively wide phenotypic variation, reflecting significant differences in salt tolerance among germplasm. The mean values ​​were generally less than 1, indicating that salt stress had varying degrees of inhibitory effect on the growth of different materials. The median relative values ​​of the four phenotypic traits were 0.80 (RPH), 0.79 (RBN), 0.48 (RFW), and 0.81 (RDW), respectively. RBN and RDW both had a mean of 0.80, indicating relatively small variations. RFW showed the largest variation range, between 0.01 and 1.16, with a mean of 0.48, indicating that this trait was most sensitive to salt stress and exhibited the most significant inter-germline differences. Skewness coefficients ranged from -1.03 to 0.34, and kurtosis coefficients ranged from -0.05 to 1.39, indicating that the data distribution generally conformed to a normal distribution. The coefficient of variation (CV), as an important indicator of the degree of individual variability within a population, indicates that a larger value indicates a higher degree of dispersion of the trait within the population. The coefficients of variation for the four phenotypic traits were 0.41 (RPH), 0.13 (RBN), 0.19 (RFW), and 0.14 (RDW), respectively, indicating that the phenotypic variations of the four traits under salt stress were relatively rich, providing a good material basis for subsequent genetic analysis. The heritability of the four phenotypic traits was 33.2% (RPH), 53.1% (RBN), 33.1% (RFW), and 70.5% (RDW), respectively. Further analysis of the phenotypic distribution of each trait was conducted, and frequency distribution histograms of the four phenotypic traits were plotted. Figure 2 The results showed that the relative values ​​of the four traits all exhibited a typical continuous distribution, consistent with a normal distribution. Overall analysis indicated that under salt stress, the four phenotypic traits in alfalfa seedlings exhibited wide phenotypic variation and high heritability, with a reasonable population structure and reliable data quality, laying a solid foundation for subsequent screening of salt tolerance-related loci and candidate genes.

[0059] Table 1. Statistical analysis of four phenotypic variations at the seedling stage in 196 alfalfa materials under salt stress.

[0060] Note: RPH (Relative Plant Height); RBN (Relative Branch Number); RFW (Relative Fresh Weight); RDW (Relative Dry Weight). All values ​​are ratios of the treatment group to the control group, and statistical analysis was performed using a t-test.

[0061] Table 2 shows the descriptive statistical results of the relative values ​​of the four phenotypic traits under alkaline stress. All four phenotypic traits exhibited relatively wide phenotypic variation, reflecting significant differences in alkali tolerance among germplasms. The means of the four phenotypic traits were generally less than 1, indicating that alkaline stress inhibited the growth of different materials to varying degrees. The median relative values ​​of the four phenotypic traits were 0.76 (RPH), 0.77 (RBN), 0.37 (RFW), and 0.66 (RDW), respectively. Among them, RFW was the most sensitive to alkaline stress and showed the most significant inhibition. RDW had the smallest range of variation, ranging from 0.22 to 1.03, with an average of 0.65; RPH had the largest range of variation, ranging from 0.21 to 1.66, with an average of 0.78, indicating that relative plant height showed the most diverse responses to alkaline stress and a high degree of differentiation among germplasms. The skewness coefficients ranged from -0.25 to 1.00, and the kurtosis coefficients ranged from -0.48 to 4.10, indicating that the data distribution basically conformed to a normal distribution, suitable for subsequent genetic analysis. The coefficients of variation for the four phenotypic traits were 0.48 (RPH), 0.19 (RBN), 0.20 (RFW), and 0.17 (RDW), respectively, indicating relatively rich phenotypic variation under alkaline stress, providing a good material basis for subsequent genetic analysis. The heritability of the four phenotypic traits was 66.7% (RPH), 79.3% (RBN), 33.1% (RFW), and 71.1% (RDW), respectively, which was at a relatively high level overall.

[0062] To further analyze the differences in salt tolerance among different improved types of alfalfa germplasm resources under salt-alkali stress, this study conducted a normality test on the relative values ​​of four seedling growth-related traits. The results showed that the relative values ​​of plant height, number of branches, fresh weight, and dry weight all exhibited a continuous distribution, conforming to a normal distribution. Figure 3 This indicates that the above traits are typical quantitative traits, and their genetic basis is regulated by multiple genes in a synergistic manner, making them suitable for genome-wide association analysis. To visually compare the differences in phenotypic distribution among different improved germplasm types under salt stress, this study plotted box plots for four phenotypic traits (…). Figure 4The results showed that under salt-alkali stress, most cultivated and wild species outperformed local varieties in the relative values ​​of various traits, demonstrating stronger salt-alkali tolerance. Further comparison of the phenotypic distribution characteristics of cultivated and wild species revealed that the relative values ​​of wild varieties in various traits were generally slightly higher than those of cultivated varieties, indicating that wild germplasm resources may contain richer allelic variations in salt-alkali tolerance, exhibiting stronger growth maintenance capabilities under salt-alkali stress. These findings suggest that wild alfalfa germplasm is an important genetic resource for discovering salt-alkali tolerance genes and improving the salt-alkali tolerance of cultivated varieties.

[0063] Table 2. Phenotypic variation of relevant traits in 196 alfalfa materials during the seedling stage under alkali stress.

[0064] Note: RPH (Relative Plant Height); RBN (Relative Branch Number); RFW (Relative Fresh Weight); RDW (Relative Dry Weight). All values ​​are ratios of the treatment group to the control group.

[0065] Under saline-alkali stress, the overall growth and development of alfalfa is significantly inhibited, with obvious stress responses observed in plant vigor, biomass accumulation, and morphogenesis. To systematically analyze the intrinsic correlations and synergistic changes among four phenotypic traits in alfalfa seedlings under saline-alkali stress, this study conducted Pearson correlation analysis on seedling phenotypic traits under both salt and alkali stress. Figure 5 , Figure 6 The results showed that under salt stress, except for the lowest correlation between relative plant height and relative branch number, all other growth traits exhibited significant positive correlations, indicating a strong synergistic trend among traits. The correlation between relative branch number and relative fresh weight was significant, with a correlation coefficient of 0.25, indicating a relatively stable positive association between branching development and aboveground fresh biomass accumulation. Under alkaline stress, the correlation patterns among traits differed slightly. Except for a relatively weak correlation between relative plant height and relative dry weight, relative branch number, relative fresh weight, and all other traits showed high correlations, indicating that the branch number and fresh weight phenotypes have a more prominent indicative role in overall growth under alkaline stress. In summary, the correlation analysis results show that under salt-alkali stress, the various growth traits of alfalfa seedlings do not change independently, but are closely related and synergistically regulated, jointly determining the overall growth performance of the plant during the seedling stage.

[0066] 2.2 Genome-wide association analysis

[0067] To elucidate the genetic basis of seedling growth-related traits under salt-alkali stress, this study employed the FarmCPU model, with a significance threshold of log... 10 Under the condition of (p)=5, genome-wide association analysis (GWAS) was performed on the relative values ​​of four traits: plant height, number of branches, fresh weight, and dry weight. A total of 223 SNP loci significantly associated with the target traits were detected under salt stress, distributed across all eight chromosomes, with a phenotypic variance explained (PVE) ranging from 9.33% to 58.47%. Figure 7 From the perspective of individual traits, the trait of relative plant height had the largest number of significantly associated loci, totaling 133, distributed across all 8 chromosomes, with an explanatory power of 10.31%–48.70%. A total of 36 SNP loci were detected that were significantly associated with the trait of relative branching number, distributed across all chromosomes except chromosome 7, with an explanatory power of 10.57%–41.35%. A total of 31 SNP loci were detected that were significantly associated with the trait of relative fresh weight, distributed across all chromosomes except chromosome 7, with an explanatory power of 10.09%–58.47%. A total of 25 SNP loci were detected that were significantly associated with the trait of relative dry weight, distributed across all 8 chromosomes, with an explanatory power of 9.33%–50.40%. The results showed that the genetic basis of various growth-related traits in alfalfa seedlings under salt stress exhibited significant polygenic control characteristics, and significant SNP loci among different traits were co-located in some chromosomal regions, suggesting the possible existence of a pleiotropic or synergistic regulatory genetic mechanism. The 223 significantly associated SNP loci and their candidate regions identified provide important genetic evidence for subsequent exploration of salt-tolerant candidate genes, construction of molecular marker-assisted breeding systems, and systematic analysis of salt tolerance mechanisms.

[0068] The results of genome-wide association analysis (GWAS) of the relative values ​​of four phenotypic traits under alkaline stress are as follows: Figure 8As shown, a total of 139 SNP loci significantly associated with the target trait were detected, distributed across all 8 chromosomes, with a phenotypic variation explanation rate (PVE) ranging from 10.08% to 56.20%. Looking at individual traits, the trait with the highest number of significantly associated loci (51) was associated with relative branching number, distributed across all 8 chromosomes, with a phenotypic variation explanation rate ranging from 10.19% to 53.22%, indicating that relative branching number is most significantly regulated by multiple genes under alkaline stress. A total of 39 SNP loci significantly associated with relative fresh weight were detected, distributed across all 8 chromosomes, with an explanation rate ranging from 10.12% to 35.33%. A total of 24 SNP loci significantly associated with relative dry weight were detected, distributed across all chromosomes except chromosome 1, with an explanation rate ranging from 10.76% to 56.20%. A total of 25 SNP loci significantly associated with plant height were detected, distributed across all eight chromosomes, with an explained value ranging from 10.08% to 56.17% (Table A-3). These results indicate that the genetic basis of various growth-related traits in alfalfa seedlings under alkaline stress exhibits clear polygenic control characteristics, and significant SNP loci among different traits are co-located in some chromosomal regions, suggesting the possible existence of pleiotropic or synergistic regulatory mechanisms. The 139 significantly associated SNP loci and their candidate regions identified provide important genetic evidence for subsequent exploration of salt-alkali tolerance candidate genes, construction of molecular marker-assisted breeding systems, and systematic analysis of alkaline stress adaptation mechanisms.

[0069] To further elucidate the molecular regulatory mechanisms of these sites under salt-alkali stress, using the genome of alfalfa 'Zhongmu 4' as a reference and combining the linkage disequilibrium (LD) characteristics of associated populations, candidate genes were screened in genomic regions 20 kb upstream and downstream of each significant site (totaling 40 kb). The initially screened alfalfa candidate genes, combined with functional annotation, were further screened to identify 116 candidate genes related to salt stress response, which will be the focus of subsequent functional analysis and mechanism elucidation (Tables 3-5). These genes were screened upstream and downstream of 41 associated SNP sites, distributed across all 8 chromosomes. The phenotypic variation explained (PVE) at each significant site ranged from 9.33% to 48.70%, indicating that the contribution of the located sites to the traits is relatively stable and has certain major effects. Figure 8(See Tables 3-5). Forty-five candidate genes were screened upstream and downstream of 21 SNPs significantly associated with relative plant height, distributed across all chromosomes except chromosome 8, with an explained phenotypic variation ranging from 10.77% to 48.70%. Nineteen candidate genes were screened upstream and downstream of six SNPs significantly associated with relative branching number, distributed across chromosomes 2, 3, 4, 6, and 8, with an explained phenotypic variation ranging from 11.49% to 41.35%. Twenty-five candidate genes were screened upstream and downstream of six SNPs significantly associated with relative fresh weight, distributed across chromosomes 1, 2, 4, and 6, with an explained phenotypic variation ranging from 12.06% to 36.09%. Twenty-seven candidate genes were screened upstream and downstream of eight SNPs significantly associated with relative dry weight, distributed across chromosomes 1, 2, 3, 4, 6, and 8, with an explained phenotypic variation ranging from 9.33% to 41.07% (Tables 3-5).

[0070] To address the linkage disequilibrium characteristics of candidate regions, this study performed LD analysis on the regions containing significant SNPs across the entire genome to define the physical regions where candidate genes are located. Within the 28.583–28.623 Mb region of chromosome 7, a total of 8 SNP loci significantly associated with the relative plant height (RPH) trait were detected, with a phenotypic variance explained (PVE) ranging from 31.94% to 40.40%. Figure 9 A) indicates that there may be one or more major loci regulating plant height development in this region. To further identify candidate genes, fine mapping was performed using high-density SNP information. Four candidate genes, Msa.H.0386400, Msa.H.0386410, Msa.H.0386420 and Msa.H.0386430, were identified in this LD region, suggesting that they play an important role in regulating plant height development under salt stress. Haplotype analysis showed that the above eight significant SNPs constituted seven major haplotypes in the associated population: HAP1 (C / G), HAP2 (A / G), HAP3 (G / A), HAP4 (C / T), HAP5 (G / T), HAP6 (T / C) and HAP7 (A / C). Figure 9 B). Further evaluation of the performance of different haplotypes under salt stress using phenotypic data showed that alfalfa individuals carrying haplotypes HAP3, HAP4, and HAP5 exhibited better plant height maintenance under salt stress and higher salt tolerance. Figure 9 C).

[0071] Table 3. Screening of candidate genes near GWAS-associated loci for four phenotypes in potted seedlings under salt stress.

[0072] Table 4. Screening of candidate genes near GWAS-associated loci for four phenotypes in potted seedlings under salt stress (continued)

[0073] Table 5. Screening of candidate genes near GWAS-associated loci for four phenotypes in potted seedlings under salt stress (continued)

[0074] Note: RPH (Relative Plant Height); RBN (Relative Branch Number); RFW (Relative Fresh Weight); RDW (Relative Dry Weight).

[0075] Table 6. Screening of candidate genes near GWAS-associated loci for four phenotypes in potted seedlings under alkaline stress.

[0076] Table 7. Screening of candidate genes near GWAS-associated loci for four phenotypes in potted seedlings under alkali stress (continued)

[0077] Table 8. Screening of candidate genes near GWAS-associated loci for four phenotypes in potted seedlings under alkali stress (continued)

[0078] Note: RPH (Relative Plant Height); RBN (Relative Branch Number); RFW (Relative Fresh Weight); RDW (Relative Dry Weight).

[0079] The initially screened alfalfa candidate genes, combined with functional annotation, were further screened to identify 96 candidate genes related to alkali stress response, which will be the focus of subsequent functional analysis and mechanism elucidation (Tables 6-8). Genes were screened from 40 SNP loci significantly associated with the target trait, distributed across all 8 chromosomes. The phenotypic variation explained (PVE) at each locus ranged from 10.08% to 52.30%, indicating that the contribution of the located loci to the trait is relatively stable and has certain major effects. Looking at individual traits, 34 candidate genes were screened upstream and downstream of 18 SNP loci significantly associated with the relative branching number trait, distributed across chromosomes except chromosomes 2 and 8, with an PVE ranging from 11.79% to 52.30%. 32 candidate genes were screened upstream and downstream of 13 SNP loci significantly associated with the relative fresh weight trait, distributed across chromosomes except chromosomes 5 and 7, with an PVE ranging from 10.12% to 30.35%. Twenty-two candidate genes were screened upstream and downstream of five SNP loci significantly associated with relative dry weight, distributed on chromosomes 3, 4, and 5, with an explained value ranging from 11.89% to 28.48%. Eight candidate genes were screened upstream and downstream of four SNP loci significantly associated with relative plant height, distributed on chromosomes 5, 7, and 8, with an explained value ranging from 10.08% to 48.76% (Tables 6-8). Among the candidate genes, two genes were found to be (…). Msa.H.0273230 and Msa.H.0273240 These two genes were screened for in both relative plant height (RPH) and relative branch number (RBN) traits, indicating that they may have pleiotropic regulatory functions and participate in the synergistic regulation of multiple aboveground growth traits of alfalfa under alkaline stress. In addition, three candidate genes screened under alkaline stress... Msa.H.0107550 , Msa.H.0107560 and Msa.H.0318560 These genes were also screened under salt stress, suggesting that they may be involved in the cross-adaptation mechanism of alfalfa to salt and alkali stress and play a co-regulatory role in response to different abiotic stresses.

[0080] To address the linkage disequilibrium characteristics of candidate regions, this study performed linkage disequilibrium analysis (LD) on the region containing the significant SNP chr3_18356144 across the entire genome to define the physical regions where candidate genes are located. Within the 18.334–18.374 Mb region of chromosome 3, a total of 7 SNPs significantly associated with the relative branch number (RBN) trait were detected, with a phenotypic variance explained (PVE) ranging from 17.28% to 33.97%. Figure 10This indicates that a major site regulating branching development may exist in this region. To further identify candidate genes, fine mapping was performed using high-density SNP information. One candidate gene, Msa.H.0128230, was identified in this LD region, suggesting that it plays an important role in regulating branching development under alkaline stress. Haplotype analysis showed that the above seven significant SNPs constituted six major haplotypes in the associated population: HAP1 (A / T), HAP2 (T / A), HAP3 (C / T), HAP4 (G / A), HAP5 (T / C), and HAP6 (G / T). Figure 10 B). Further evaluation of the performance of different haplotypes under alkaline stress using phenotypic data showed that alfalfa individuals carrying the HAP1 haplotype exhibited better branching maintenance under alkaline stress and higher alkali tolerance. Figure 10 C).

[0081] The above description is only a preferred embodiment of the present invention. It should be noted that for those skilled in the art, several improvements and modifications can be made without departing from the principle of the present invention, and these improvements and modifications should also be considered within the scope of protection of the present invention.

Claims

1. The application of reagents for detecting genes or their expression products in the preparation of kits for identifying or assisting in the identification of alfalfa alkali tolerance, characterized in that, The gene is selected from any one or more of the following genes: Msa.H.0273230, Msa.H.0273240.

2. The application according to claim 1, characterized in that, The Msa.H.0273230 and Msa.H.0273240 genes showed significant association with the relative plant height and relative branch number of alfalfa under alkaline stress, demonstrating pleiotropic regulatory functions and participating in the synergistic regulation of multiple aboveground growth traits of alfalfa under alkaline stress.

3. The application of the gene described in claim 1 or 2 in the genetic improvement or molecular breeding of alkali tolerance in alfalfa.

4. The application according to claim 3, characterized in that, The application is as follows: using molecular markers closely linked to the gene described in claim 1 to conduct alkali-tolerant marker-assisted selection breeding of alfalfa germplasm resources.

5. The application according to claim 3, characterized in that, Molecular markers closely linked to the Msa.H.0273230 or Msa.H.0273240 genes are located on chromosome 5 of alfalfa, and their physical locations are selected from any one or more of the following loci: chr5_35227094, chr5_35229849, and chr5_35230451.

6. The application according to claim 3, characterized in that, The application is to overexpress, silence, or edit the gene described in claim 1 in alfalfa using genetic engineering methods to improve the agronomic traits of alfalfa under alkaline stress.

7. A method for screening salt-alkali tolerance-related markers and genes in alfalfa based on potted plant phenotypes, characterized in that, Includes the following steps: The alfalfa germplasm resources to be tested were cloned by cuttings and transplanted into flower pots for pot cultivation. Three groups were set up: a salt stress treatment group, an alkali stress treatment group, and a control group. Potted plants were subjected to stress treatments. Phenotypic traits of alfalfa plants in the stress treatment group and the control group were determined. Calculate the relative values ​​of each phenotypic trait, where the relative values ​​are the ratios of the phenotypic trait measurements of the stress treatment group to those of the control group. Based on the relative values, salt tolerance of alfalfa germplasm resources was evaluated, and SNP markers and candidate genes related to salt tolerance were screened by combining genome-wide association analysis.

8. The method according to claim 7, characterized in that, The phenotypic traits include plant height, number of branches, fresh weight, and dry weight. Before the stress treatment, all plants were uniformly cut and stubble height was retained. The salt stress treatment was performed by watering with NaCl solution in several stages, and the alkali stress treatment was performed by watering with NaHCO3 solution in several stages. The calculation of the relative values ​​includes relative plant height, relative number of branches, relative fresh weight, and relative dry weight, wherein, relative plant height = plant height measurement under salt / alkali stress treatment ÷ plant height measurement under control group, relative number of branches = number of branches measurement under salt / alkali stress treatment ÷ number of branches measurement under control group, relative fresh weight = fresh weight measurement under salt / alkali stress treatment ÷ fresh weight measurement under control group, and relative dry weight = dry weight measurement under salt / alkali stress treatment ÷ dry weight measurement under control group.

9. The method according to claim 7, characterized in that, The genome-wide association analysis used the FarmCPU model to screen out SNP markers and candidate genes that were significantly associated with the relative plant height, relative number of branches, relative fresh weight, and relative dry weight, within a set significance threshold. The SNP markers include: SNP markers under salt stress: chr1_111187521, chr1_42960696, chr1_68814409, chr1_68823954, chr2_62791415, chr2_70493601, chr3_27432527, chr4_21658074, chr4_63050214, chr4_6500 associated with relative plant height. 4751, chr5_76203165, chr6_11960006, chr6_181638646, chr7_28602740, chr7_28603276, c hr7_28603449, chr7_28604344, chr7_28604369, chr7_28605835, chr7_28606770, chr7_2860 7260; chr2_14149227, chr3_49984825, chr4_22665207, chr6_13793180, chr6_12379936, chr8_74992195 associated with relative branch number; chr1_49709706, chr1_56318618, chr2_55107523, chr2_58 associated with relative fresh weight 572467, chr4_87591526, chr6_14357008; chr1_28520170, chr1_56995013, chr2_55739393, chr3_70547956, chr4_12989127, chr6_43339873, chr8_57312295, chr8_57314077 associated with relative dry weight; SNP markers under alkaline stress: chr5_35229849, chr7_20985207, chr8_30398564, chr8_52127072, associated with relative plant height; chr1_37554368, chr1_78319110, chr1_85563336, chr3_11723989, chr3_18354369, chr3_18354842, chr3_18355035, chr3_18356082, chr3_18356144, chr3_18356664, chr3_18357339, chr3_50157262, chr4_35008892, associated with relative branch number. chr5_35227094, chr5_35230451, chr6_13640447, chr6_29514421, chr7_75610213; and chr1_64378663, chr2_70477781, chr3_10472645, chr3_10476122, which are associated with relative fresh weight. chr3_10476280, chr3_10476482, chr3_10478356, chr3_10480333, chr4_15062825, chr6_18155523, chr6_3686004, chr8_54253289; chr3_89298267 associated with relative dry weight; The candidate genes include: Candidate genes under salt stress: Msa.H.0009590, Msa.H.0009600, Msa.H.0009610, Msa.H.0028680, Msa.H.0044820, Msa.H.0044830, Msa.H.0044840, Msa.H.0102230, Msa.H.0102240, Msa.H.0102250, Msa.H.0107550, Msa.H.0107560, Msa.H.0107570, Msa.H.0107580, Msa.H.0132350, Msa.H.0132360, Msa.H.0132370, Msa.H.0197740, Msa.H.0197750, Msa.H.0197760, Msa.H.0197770, Msa.H.0187950, Msa.H.0187960, Msa.H.0187970, Msa.H.0187980, Msa.H.0220560, Msa.H.0220570, Msa.H.0220580, Msa.H.0220590, Msa.H.0295920, Msa.H.0295930, Msa.H.0295940, Msa.H.0295950, Msa.H.0295960, Msa.H.0295970, Msa.H.0295980, Msa.H.0307090, Msa.H.0307100, Msa.H.0307110, Msa.H.0318560, Msa.H.0318570, Msa.H.0386400, Msa.H.0386410, Msa.H.0386420, Msa.H.0386430, which are associated with relative plant height; Msa.H.0077240, Msa.H.0077250, Msa.H.0139460, Msa.H.0139470, Msa.H.0139480, Msa.H.0198350, Msa.H.0198360, Msa.H.0198370, Msa.H.0368430, Msa.H.0368440, Msa.H.0360920, Msa.H.0360930, Msa.H.0360940, Msa.H.0481120, Msa.H.0481130, Msa.H.0481140, Msa.H.0481150, Msa.H.0481160, Msa.H.0481170, which are associated with relative branch number; Msa.H.0031710, Msa.H.0031720, Msa.H.0031730, Msa.H.0035900, Msa.H.0035910, Msa.H.0035920, Msa.H.0035930, Msa.H.0035940, Msa.H.0035950, Msa.H.0097900, Msa.H.0097910, Msa.H.0097920, Msa.H.0097930, Msa.H.0100070, Msa.H.0100080, Msa.H.0100090, Msa.H.0100100, Msa.H.0239800, Msa.H.0239810, Msa.H.0239820, Msa.H.0239830, Msa.H.0316450, Msa.H.0316460, Msa.H.0316470, Msa.H.0316480; Msa.H.0020910, Msa.H.0036300, Msa.H.0036310, Msa.H.0036320, Msa.H.0036330, Msa.H.0036340, Msa.H.0036350, Msa.H.0098160, Msa.H.0098170, Msa.H.0098180, Msa.H.0151100, Msa.H.0151110, Msa.H.0151120, Msa.H.0151130, Msa.H.0151140, Msa.H.0151150, Msa.H.0192630, Msa.H.0192640, Msa.H.0192650, Msa.H.0192660, Msa.H.0330480, Msa.H.0330490, Msa.H.0330500, Msa.H.0330510, which are associated with relative dry weight. Candidate genes under alkali stress: Msa.H.0273230, Msa.H.0273240, Msa.H.0382150, Msa.H.0382160, Msa.H.0382170, Msa.H.0382180, Msa.H.0454660, Msa.H.0454670, Msa.H.0464210, Msa.H.0464220 associated with relative plant height; Msa.H.0026180, Msa.H.0026190, Msa.H.0026200, Msa.H.0052010, Msa.H.0052020, Msa.H.0052030, Msa.H.0052040, Msa.H.0052050, Msa.H.0058220, Msa.H.0058230, Msa.H.0058240, Msa.H.0058250, Msa.H.0058260, Msa.H.0058270, Msa.H.0124780, Msa.H.0124790, Msa.H.0124800, Msa.H.0128220, Msa.H.0128230, Msa.H.0128240, Msa.H.0139580, Msa.H.0139590, Msa.H.0139600, Msa.H.0139610, Msa.H.0205440, Msa.H.0273230, Msa.H.0273240, Msa.H.0367620, Msa.H.0325090, Msa.H.0325100, Msa.H.0409580, Msa.H.0409590, Msa.H.0409600, Msa.H.0409610, Msa.H.0409620 associated with relative branch number; Msa.H.0041250, Msa.H.0041260, Msa.H.0041270, Msa.H.0041280, Msa.H.0107550, Msa.H.0107560, Msa.H.0178590, Msa.H.0178600, Msa.H.0178610, Msa.H.0178620, Msa.H.0178630, Msa.H.0178640, Msa.H.0178650, Msa.H.0178660, Msa.H.0178670, Msa.H.0178680, Msa.H.0178690, Msa.H.0178700, Msa.H.0178710, Msa.H.0193880, Msa.H.0193890, Msa.H.0193900, Msa.H.0318540, Msa.H.0318550, Msa.H.0318560, Msa.H.0328190, Msa.H.0465750, Msa.H.0465760, Msa.H.0465770, Msa.H.0465780; and Msa.H.0166130, Msa.H.0166140, Msa.H.0166150, and Msa.H.0166160, which are associated with relative dry weight.

10. The method according to claim 9, characterized in that, After identifying SNP markers and candidate genes, the process also includes haplotype analysis. Haplotypes were constructed for linkage disequilibrium segments containing significantly associated SNP sites, and the performance of different haplotypes under saline-alkali stress conditions was evaluated in combination with phenotypic data. The haplotype analysis specifically included: in the 28.583-28.623Mb region of chromosome 7, which is the relative plant height trait under salt stress, seven haplotypes HAP1 to HAP7 were formed by eight SNP loci: chr7_28602740, chr7_28603276, chr7_28603449, chr7_28604344, chr7_28604369, chr7_28605835, chr7_28606770 and chr7_28607260. Alfalfa individuals carrying haplotypes HAP3, HAP4 or HAP5 were identified as having higher salt tolerance. In the 18.334-18.374Mb region of chromosome 3, which is the relative branching trait under alkaline stress, six haplotypes HAP1 to HAP6 are formed by seven SNP loci: chr3_18354369, chr3_18354842, chr3_18355035, chr3_18356082, chr3_18356144, chr3_18356664, and chr3_18357339. It was found that alfalfa individuals carrying the HAP1 haplotype have higher alkaline tolerance.

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