Rosa chinensis petal outer edge notching whole genome snp molecular marker combination and application thereof

Abstract

The application discloses a full-genome SNP molecular marker combination of petal edge notching of Rosa chinensis and application thereof, and aims at the deficiency of the prior art.The application fuses 358 full-genome resequencing data of Rosa chinensis and petal edge notching phenotype correlation analysis, and uses a multi-model joint screening technology to identify 879 SNP markers which are significantly related to petal edge notching, and to establish a full-genome selection model with high prediction accuracy.These markers are distributed on 14 chromosomes, high-throughput and rapid detection can be realized, the detection period is shortened, the petal wave trait is directly predicted by using seedling genotype data, and the breeding process is accelerated.The application has low cost, high-throughput and industrialization potential, and provides key data support for genetic rule analysis and molecular marker assisted breeding of petal edge notching of Rosa chinensis, and significantly improves breeding efficiency and precision.

Description

Technical Field

[0001] This invention relates to the field of molecular breeding technology, and in particular to a genome-wide SNP molecular marker combination for notches on the outer edge of rose petals and its application. Background Technology

[0002] As a world-renowned flower, the serrated edge of the rose petals is one of its key aesthetic features. The morphology, depth, and distribution pattern of these serrations are rich and diverse, significantly impacting the overall ornamental value of the rose. This trait is controlled by multiple genes, making its inheritance complex. Traditional breeding methods rely heavily on phenotypic selection, requiring multiple generations of field planting and observation, typically 3-5 years. Furthermore, it is easily affected by environmental factors such as light and temperature, making the assessment of the trait's genetic stability difficult and resulting in a slow breeding process.

[0003] In recent years, the rise of genome-wide association studies (GWAS) and genome-wide selection (GS) technologies has brought new opportunities for marker-assisted breeding. While SNPs, as high-density molecular markers, are widely used in the genetic analysis of traits such as flower shape and color, there is a gap in the research of refined marker systems for the complex morphological feature of petal notches. Existing SNP screening methods are mostly based on single-model association analyses, resulting in marker redundancy, insufficient specificity, and a lack of genome-wide selection models adapted to complex phenotypes, making it difficult to meet breeding requirements in terms of predictive accuracy. Furthermore, probe and microarray technologies for petal notches are not yet mature, limiting the application of molecular markers in early-stage breeding. Currently, there is no effective marker-assisted selection method that can accurately predict and screen rose individuals with the target petal notch trait, which makes the genetic improvement of petal notches a persistent challenge in rose breeding.

[0004] Currently, there is a lack of a genome-wide SNP molecular marker combination for notches on the outer edge of rose petals and its application. Summary of the Invention

[0005] To address the problems of existing technologies, the purpose of this invention is to provide a genome-wide SNP molecular marker combination for notches on the outer edge of rose petals and its application.

[0006] To achieve the above objectives, the present invention adopts the following technical solution: Firstly, this application provides a genome-wide SNP molecular marker combination for notches on the outer edge of rose petals.

[0007] Secondly, this application provides a predictive probe for notches on the outer edge of rose petals.

[0008] Thirdly, this application provides a predictive chip for notches on the outer edge of rose petals.

[0009] Fourthly, this application provides an application of SNP molecular marker combinations, probes, or chips in the prediction of notches on the outer edge of rose petals.

[0010] Fifthly, this application provides a method for predicting the outer edge notches of rose petals based on SNP molecular marker combinations.

[0011] Sixthly, this application provides an application of SNP site combinations, probes, chips, or prediction methods in the molecular breeding of roses.

[0012] Seventhly, this application provides a molecular breeding method for roses based on SNP markers.

[0013] The first aspect of this application provides a genome-wide SNP molecular marker combination for rose petal notches, comprising 879 SNP loci distributed on the 14 chromosomes of the rose; the specific information of the SNP loci is represented in the structure of chromosome number_physical location_allele type, and the SNP loci contain dominant alleles that are positively and significantly associated with rose petal notches, as shown in Table 1.

[0014] Furthermore, the SNP loci were determined through genome-wide association analysis of 358 rose resequencing materials, and were screened using multiple software and models.

[0015] The second aspect of this application provides a predictive probe for notches on the outer edge of rose petals. The selection principles for the probe include: it is designed from a combination of SNP sites, can specifically bind to the SNP sites, is used to capture target DNA regions, and realizes the detection of specific SNP sites. Its sequence information is associated with the combination of SNP sites and meets the various selection principles of probe design, including no Indel markers within 50 bp upstream and downstream of the SNP site, only one copy number of the sequence within 100 bp upstream and downstream of the whole genome, GC content of 40-60%, no short repetitive sequences in the sequence, and no N bases.

[0016] A third aspect of this application provides a prediction chip for the outer edge notch of rose petals. The prediction chip includes probes for detecting the 879 SNP sites. By detecting the genotype of the SNP sites in the genomic DNA of the rose sample to be tested, and using a pre-constructed whole-genome selection model, the accurate prediction of the outer edge notch trait of rose petals can be achieved.

[0017] The fourth aspect of this application provides an application of SNP molecular marker combinations, probes, or chips in the prediction of outer edge notches in rose petals, by extracting genomic DNA from rose plants and using SNP site combinations, probes, or chips for detection.

[0018] The fifth aspect of this application provides a method for predicting the outer edge notch of rose petals based on SNP molecular marker combinations, including the following steps: (1) Extract genomic DNA from the rose plants to be tested; (2) Constructing a library from genomic DNA; (3) Use probes to hybridize and capture DNA fragments in the library to enrich DNA fragments containing the target SNP site; (4) Perform high-throughput sequencing on the captured DNA fragments; (5) Compare and analyze the sequencing data with the rose reference genome to determine the genotype of the SNP loci; (6) Input the genotype data of SNP loci combination into the whole genome selection model to obtain the prediction results of the notched petal trait of the rose to be tested.

[0019] Furthermore, the establishment of a genome-wide selection model includes the following steps: SNP genotypic data and corresponding petal outer edge notch phenotypic data were collected from 358 rose samples; Phenotypic data of petal outer edge notch characteristics were recorded according to a standardized scoring system, BLUP values ​​were calculated, and GWAS analysis was performed in conjunction with five phenotypic indicators. Six models, including EMMAX, GEMMA, and TASSEL, were used to screen the GWAS analysis results, and a significance threshold (p < 1 × 10⁻⁻⁶) was set. 4 ), identify SNP markers that are significantly associated with the notch feature on the outer edge of the petals; Candidate SNPs were evaluated for probe feasibility, and highly specific SNP sites were screened out. Highly specific SNP sites were ranked based on the multi-model association strength, and 879 core SNP sites spanning 14 chromosomes were selected. The genotype data of the selected core SNP loci and the corresponding phenotypic data of the outer edge of the petals were used as the training set and input into the Bayesian ridge regression model for training to obtain the trained whole genome selection model.

[0020] The sixth aspect of this application provides an application of SNP site combinations, probes, chips, or prediction methods in the molecular breeding of roses, which is used to predict and screen the petal outer edge notch characteristics of breeding materials in an early, accurate, and efficient manner during the rose breeding process, thereby shortening the breeding cycle, improving selection efficiency, and cultivating new rose varieties with excellent petal outer edge notch characteristics.

[0021] Furthermore, a genome-wide selection model constructed based on SNP site combinations can predict the notches on the outer edge of rose petals with a prediction accuracy greater than 0.541.

[0022] The seventh aspect of this application provides a molecular breeding method for roses based on SNP markers, comprising the following steps: (1) obtaining the genomic DNA of rose seedlings; (2) using the method to predict the phenotypic value of the outer edge wavy trait of the petals of the rose seedlings; (3) screening out rose seedlings with the target outer edge wavy trait of the petals according to the predicted phenotypic value, and performing subsequent breeding operations.

[0023] Beneficial effects: This invention enables high-throughput and rapid detection, shortens the detection cycle, and directly predicts petal wavy traits using seedling genotype data without waiting for the plant to flower, thus accelerating the breeding process. It has low cost, high throughput, and industrialization potential, and provides key data support for the analysis of the genetic rules of rose petal notches and molecular marker-assisted breeding. It has significant theoretical significance and application prospects for improving breeding efficiency and accuracy.

[0024] Compared with the prior art, the present invention has the following advantages: (1) Precise prediction and efficient screening: This invention uses multi-model joint screening technology to accurately identify 879 SNP molecular markers that are significantly associated with the notch trait of the outer edge of rose petals from a large number of SNP sites. The established whole-genome selection model (especially the Bayesian Ridge regression model) has high prediction accuracy (R²>0.541) and can accurately predict the notch trait of the outer edge of petals. It effectively solves the problem of insufficient prediction accuracy of existing technologies and provides a high-precision molecular marker-assisted screening tool for rose breeding.

[0025] (2) Shorten the breeding cycle: By using the genotype data of rose seedlings to directly predict the petal notch characteristics, there is no need to wait for the plant to bloom. This can shorten the breeding cycle by 3-5 years, greatly improve breeding efficiency, accelerate the process of rose variety improvement, and help to launch superior varieties with the target petal notch characteristics more quickly, so as to meet the market demand for ornamental roses.

[0026] (3) High-throughput and low-cost detection: Combining specific probes and liquid-phase chip technology, high-throughput and rapid detection is achieved, with high detection efficiency and low cost. Evaluation showed that 879 SNP molecular markers had good capture efficiency for 12 seasonal varieties, with a detection rate of 97.55%-98.85% and a high coverage depth (374.50-556.80), providing strong technical support for large-scale sample detection and reducing breeding costs.

[0027] (4) Overcoming environmental interference: Existing methods rely on manual observation of phenotypes, which are easily affected by environmental factors such as light and temperature, resulting in unstable results. This invention is based on genotype prediction, is not affected by the environment, and provides more reliable test results, providing a more stable and accurate selection basis for breeding work.

[0028] (5) Provides new insights into genetic laws: The identified SNP molecular marker combinations are distributed on 14 chromosomes, providing key data for analyzing the genetic laws of the outer edge notch of rose petals, filling the research gap in this field, and having important theoretical significance. It provides a reference for a deeper understanding of the genetic basis of rose petal morphological development and promotes the development of rose genetics research.

[0029] (6) Wide applicability and industrial potential: Applicable to different rose varieties, it can be widely used in the field of rose breeding, promote the improvement of rose varieties, enhance the market value and ornamental value of roses, and has significant industrial application prospects, which helps to improve the economic benefits and market competitiveness of the rose industry. Attached Figure Description

[0030] To more clearly illustrate the technical solutions in the embodiments of this application, 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 some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0031] Figure 1 The distribution map of whole chromosome markers in the notches on the outer edge of rose petals provided by this invention.

[0032] Figure 2 Allele frequency diagram of notches on the outer edge of rose petals provided by the present invention.

[0033] Figure 3 The missing rate diagram of the outer edge notch of rose petals provided by the present invention.

[0034] Figure 4 This is a diagram showing the heterogeneity of the notched outer edge of a rose petal provided by the present invention.

[0035] Figure 5 The image shows the results of whole-genome selection evaluation of the notches on the outer edge of rose petals provided by this invention. Detailed Implementation

[0036] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0037] In this application, the term "and / or" describes the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent: A existing alone, A and B existing simultaneously, or B existing alone. A and B can be singular or plural. The character " / " generally indicates that the preceding and following related objects have an "or" relationship.

[0038] In this application, "-one less" means one or more, and "more than" means two or more. "-one less item (item) below" or similar expressions refer to any combination of these items, including any combination of single or multiple items. For example, "-one less item (item) in a, b, or c", or "-one less item (item) in a, b, and c", can all mean: a, b, c, ab (i.e., a and b), ac, bc, or abc, where a, b, and c can be single or multiple.

[0039] It should be understood that in the various embodiments of this application, the order of the above processes does not imply the order of execution. Some or all steps may be executed in parallel or sequentially. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of this application.

[0040] The terminology used in the embodiments of this application is for the purpose of describing particular embodiments only and is not intended to be limiting of this application. The singular forms “a,” “the,” and “the” used in the embodiments of this application and the appended claims are also intended to include the plural forms unless the context clearly indicates otherwise.

[0041] The weights of the relevant components mentioned in the embodiments of this application can refer not only to the specific content of each component, but also to the proportional relationship between the weights of the components. Therefore, any scaling up or down of the content of the relevant components according to the embodiments of this application is within the scope disclosed in the embodiments of this application. Specifically, the mass described in the embodiments of this application can be a mass unit known in the chemical industry, such as µg, mg, g, or kg.

[0042] The terms "first" and "second" are used for descriptive purposes only, to distinguish objects, such as substances, from one another, and should not be construed as indicating or implying relative importance or implicitly specifying the diameter of the indicated technical features. For example, without departing from the scope of the embodiments of this application, "first XX" may also be referred to as "second XX," and similarly, "second XX" may also be referred to as "first XX." Thus, features defined with "first" and "second" may explicitly or implicitly include one or more of that feature.

[0043] The first aspect of this application provides a genome-wide SNP molecular marker combination for rose petal notches. The SNP molecular marker combination includes 879 SNP loci distributed on the 14 chromosomes of the rose. The specific information of the SNP loci is represented in the structure of chromosome number_physical location_allele type. The SNP loci contain dominant alleles that are positively and significantly associated with rose petal notches. The specific locus information is shown in Table 1.

[0044] SNP loci were identified through genome-wide association analysis of 358 rose resequencing materials, and were screened using multiple software and models.

[0045] The second aspect of this application provides a predictive probe for notches on the outer edge of rose petals. The selection principles for the probe include: it is designed from a combination of SNP sites, can specifically bind to SNP sites, is used to capture target DNA regions, and realizes the detection of specific SNP sites. Its sequence information is associated with the combination of SNP sites and meets the various selection principles of probe design, including no Indel markers within 50 bp upstream and downstream of the SNP site, only one copy number of the sequence within 100 bp upstream and downstream of the whole genome, GC content of 40-60%, no short repetitive sequences in the sequence, and no N bases.

[0046] The third aspect of this application provides a prediction chip for the outer edge notch of rose petals. The prediction chip includes probes for detecting the 879 SNP sites. By detecting the genotype of the SNP sites in the genomic DNA of the rose sample to be tested, and using a pre-constructed whole-genome selection model, the accurate prediction of the outer edge notch trait of rose petals can be achieved.

[0047] The fourth aspect of this application provides an application of SNP molecular marker combinations, probes, or chips in the prediction of outer edge notches in rose petals. This involves extracting genomic DNA from rose plants and detecting the SNP sites using the SNP site combinations, probes, or chips.

[0048] The fifth aspect of this application provides a method for predicting the outer edge notch of rose petals based on SNP molecular marker combinations, including the following steps: (1) Extract genomic DNA from the rose plants to be tested; (2) Construct a library from the genomic DNA; (3) Use probes to hybridize and capture DNA fragments in the library to enrich DNA fragments containing the target SNP site; (4) Perform high-throughput sequencing on the captured DNA fragments; (5) Compare and analyze the sequencing data with the rose reference genome to determine the genotype of the SNP loci; (6) Input the genotype data of SNP loci combination into the whole genome selection model to obtain the prediction results of the notched petal trait of the rose to be tested.

[0049] In some embodiments, the establishment of a genome-wide selection model includes the following steps: SNP genotypic data and corresponding petal outer edge notch phenotypic data were collected from 358 rose samples; Phenotypic data of petal outer edge notch characteristics were recorded according to a standardized scoring system, BLUP values ​​were calculated, and GWAS analysis was performed in conjunction with five phenotypic indicators. Six models, including EMMAX, GEMMA, and TASSEL, were used to screen the GWAS analysis results, and a significance threshold (p < 1 × 10⁻⁻⁶) was set. 4 ), identify SNP markers that are significantly associated with the notch feature on the outer edge of the petals; Candidate SNPs were evaluated for probe feasibility, and highly specific SNP sites were screened out. Highly specific SNP sites were ranked based on the multi-model association strength, and 879 core SNP sites spanning 14 chromosomes were selected. The genotype data of the selected core SNP loci and the corresponding phenotypic data of the outer edge of the petals were used as the training set and input into the Bayesian ridge regression model for training to obtain the trained whole genome selection model.

[0050] The sixth aspect of this application provides an application of SNP site combinations, probes, chips, or prediction methods in rose molecular breeding, which is used to predict and screen the petal outer edge notch characteristics of breeding materials in an early, accurate, and efficient manner during the rose breeding process, thereby shortening the breeding cycle, improving selection efficiency, and cultivating new rose varieties with excellent petal outer edge notch characteristics.

[0051] In some embodiments, a genome-wide selection model based on SNP site combinations can predict the notches on the outer edge of rose petals with a prediction accuracy greater than 0.541.

[0052] The seventh aspect of this application provides a molecular breeding method for roses based on SNP markers, comprising the following steps: (1) obtaining the genomic DNA of rose seedlings; (2) using the method to predict the phenotypic value of the outer edge wavy trait of the petals of the rose seedlings; (3) screening out rose seedlings with the target outer edge wavy trait of the petals according to the predicted phenotypic value, and performing subsequent breeding operations.

[0053] Example 1

[0054] This invention discloses a genome-wide SNP molecular marker combination for rose petal outer margin notches. The SNP molecular marker combination includes 879 SNP loci distributed across the 14 chromosomes of the rose. The specific information of the SNP loci is represented using a chromosome number_physical location_allele structure. Each SNP locus contains a dominant allele that is positively and significantly associated with rose petal outer margin notches. Specific locus information is shown in Table 1. Table 1

[0055] SNP loci were identified through genome-wide association analysis of 358 rose resequencing materials, and were screened using multiple software and models.

[0056] Example 2 This invention discloses a predictive probe for notches on the outer edge of rose petals. The selection criteria for the probe include: it is designed from a combination of SNP sites, capable of specifically binding to SNP sites, used to capture target DNA regions, and enabling the detection of specific SNP sites. Its sequence information is associated with the combination of SNP sites and meets various selection criteria for probe design, including no Indel markers within 50 bp upstream and downstream of the SNP site, only one copy number of the sequence within 100 bp upstream and downstream of the SNP site in the whole genome, GC content of 40-60%, no short repetitive sequences in the sequence, and no N bases.

[0057] Example 3 The present invention provides a prediction chip for the outer edge notch of rose petals. The prediction chip includes probes for detecting the 879 SNP sites. By detecting the genotype of the SNP sites in the genomic DNA of the rose sample to be tested, and using a pre-constructed whole-genome selection model, the accurate prediction of the outer edge notch trait of rose petals can be achieved.

[0058] Example 4 The present invention relates to the application of a combination of SNP molecular markers, probes, or chips in the prediction of notches on the outer edge of rose petals. This involves extracting genomic DNA from rose plants and then using the SNP site combination, probes, or chips for detection.

[0059] Example 5 The present invention provides a method for predicting the outer edge notch of rose petals based on SNP molecular marker combinations, comprising the following steps: (1) Extract genomic DNA from the rose plants to be tested; (2) Constructing a library from genomic DNA; (3) Use probes to hybridize and capture DNA fragments in the library to enrich DNA fragments containing target SNP sites; (4) Perform high-throughput sequencing on the captured DNA fragments; (5) Compare and analyze the sequencing data with the rose reference genome to determine the genotype of the SNP loci; (6) Input the genotype data of SNP locus combinations into the whole-genome selection model to obtain the predicted results of the notched petal trait of the rose to be tested. The establishment of the whole-genome selection model includes the following steps: SNP genotypic data and corresponding petal outer edge notch phenotypic data were collected from 358 rose samples; Phenotypic data of petal outer edge notch characteristics were recorded according to a standardized scoring system, BLUP values ​​were calculated, and GWAS analysis was performed in conjunction with five phenotypic indicators. Six models, including EMMAX, GEMMA, and TASSEL, were used to screen the GWAS analysis results, and a significance threshold (p < 1 × 10⁻⁻⁶) was set. 4 ), identify SNP markers that are significantly associated with the notch feature on the outer edge of the petals; Candidate SNPs were evaluated for probe feasibility, and highly specific SNP sites were screened out. Highly specific SNP sites were ranked based on the multi-model association strength, and 879 core SNP sites spanning 14 chromosomes were selected. The genotype data of the selected core SNP loci and the corresponding phenotypic data of the outer edge of the petals were used as the training set and input into the Bayesian ridge regression model for training to obtain the trained whole genome selection model.

[0060] Example 6 The present invention relates to the application of an SNP site combination, probe, chip, or prediction method in the molecular breeding of roses, which is used to predict and screen the petal outer edge notch characteristics of breeding materials in an early, accurate, and efficient manner during the rose breeding process, thereby shortening the breeding cycle, improving selection efficiency, and cultivating new rose varieties with excellent petal outer edge notch characteristics.

[0061] A genome-wide selection model based on SNP site combinations can predict the notches on the outer edge of rose petals with an accuracy greater than 0.541.

[0062] Example 7 The present invention provides a method for molecular breeding of roses based on SNP markers, comprising the following steps: (1) obtaining genomic DNA of rose seedlings; (2) The method was used to predict the phenotypic value of the outer edge wavy trait of the petals of the rose seedlings; (3) Based on the predicted phenotypic values, select rose seedlings with the wavy outer edge of the target petals for subsequent breeding operations.

[0063] Example 8 (1) Genome-wide association analysis of petal outer margin notches was performed on 358 rose whole-genome resequencing data. The procedure is as follows: (2) Collected 358 rose leaf samples, extracted genomic DNA using magnetic bead adsorption, selected DNA fragments that met the length requirements, and performed whole genome resequencing using the DNBSEQ-T7 platform after fluorescence quantitative analysis.

[0064] (3) The raw sequencing data (in fq.gz format) was compared with the modern rose 'Samantha' genome v2 version (https: / / figshare.com / articles / dataset / _i_R_hybrida_i_Samantha_genome_v2_ / 28738781?file=53454104) using BWA software. Variation detection was performed using the GATK workflow, and 115,219,112 high-quality SNP sites were initially identified.

[0065] (4) These loci were quality filtered to select those with an allele frequency (MAF) greater than 0.01 ( Figure 2 And the missing rate is less than 0.2%. Figure 3The SNPs were analyzed, and a total of 35,335,433 high-quality SNP loci were obtained.

[0066] (5) Collect petal outer edge notch phenotypic data, record three repeated observations according to the standardized scoring system (0 indicates none, 1 indicates present), calculate BLUP value, and combine with 5 phenotypic indicators for GWAS analysis.

[0067] (6) Six models (including FARMCPU, GLM, and MLM algorithms) were used, and a significance threshold (p < 1 × 10⁻⁻⁶) was set. 4 ), 268,779 associated SNP markers were selected, and after removing duplicates, 134,868 SNP sites were retained.

[0068] (7) The feasibility of probes was evaluated for candidate SNPs. Sites containing InDel, repetitive sequences or N bases within 50 bp upstream and downstream were excluded. SNPs with GC content between 40% and 60% and located in single copy regions were screened out. Finally, 5710 highly specific sites were retained.

[0069] (8) Based on the multi-model association strength, 879 core SNPs spanning 14 chromosomes were selected. Figure 1 ), used for probe synthesis and model building.

[0070] (9) Based on 13 whole-genome selection models, including LightGBM (lgb), Random Forest (RF), SVR (svr), Lasso Regression (Lasso), Ridge Regression (Ridge), rrBLUP (rrblup), Reproducing Kernel HilbertSpace (RKHS), Bayes Ridge Regression (BRR), Bayesian Lasso (BL), BayesC, BayesB, BayesA, and GBLUP, the genotype and phenotype data of 348 samples were used for model training.

[0071] (10) The results show that Bayesian Ridge Regression (BRR) has the highest prediction accuracy (R² > 0.541), which is significantly better than traditional linear models (such as Ridge Regression). Figure 5 Finally, the SNP sites selected in step (7) are used to synthesize probe sequences for capture sequencing.

[0072] Example 9 The method for detecting roses using liquid phase probe technology corresponding to 879 SNPs mentioned in Example 8 (1) Extraction of rose genomic DNA: Leaves were collected from roses and stored with ice packs and transported to the laboratory quickly. Total DNA of roses was extracted using the magnetic bead method.

[0073] (2) Library construction of rose genomic DNA: The genomic DNA was fragmented (200-300bp in length), the DNA fragments were repaired at the ends and ligated with adapters, and then Pre-PCR amplification was performed to construct the library.

[0074] (3) Hybridization of probes with target regions: The prepared SNP probes were hybridized with the Pre-PCR library. The streptomycin-modified probes specifically bound to the complementary DNA library to capture the target DNA library. Other non-target library DNA was washed away to obtain the enriched Pre-PCR library. Hybridization conditions: The streptomycin-labeled probes were hybridized with the target library at 50℃ for 16 h. Biotin-labeled magnetic beads were used to bind with the streptomycin-labeled probes at room temperature for 30 min to enrich the target library. After rinsing the non-target library regions with wash buffer, the library was eluted with nuclease-free water.

[0075] (4) After purification by magnetic beads, the enriched DNA is amplified to reach the concentration required for high-throughput sequencing, and then high-throughput sequencing is performed.

[0076] (5) High-throughput sequencing: The library obtained after capture and amplification in step (4) is subjected to high-throughput sequencing using the BGI Genomics DNBSEQ-T7 sequencing platform to obtain the sequencing results of genomic DNA, and the data is preliminarily cleaned.

[0077] (6) Evaluation of liquid phase probe capture efficiency: The cleaned sequencing data were compared with the reference sequence of the modern rose 'Samantha' genome v2 version using bwa software to evaluate the capture efficiency of the liquid phase probe.

[0078] Experimental Example 1

[0079] Experimental materials Twelve modern rose varieties with significant genetic background differences were selected for the experiment (such as White Rose and Zindella, numbered as shown in Table 2). Fresh leaves were immediately frozen in liquid nitrogen and stored at -80℃ after collection. Genomic DNA of each variety was extracted using the CTAB method (hexadecyltrimethylammonium bromide extraction method). The purity (OD260 / 280 between 1.8 and 2.0) and concentration (≥50 ng / μL) of the DNA were confirmed by agarose gel electrophoresis and Nanodrop spectroscopy.

[0080] Table 2

[0081] Variety representativeness: The selected materials cover red, white, and pink color groups, including red varieties such as Red Calm (Test6), Golden Back Red (Test7), and Fire Treasure (Test12); white varieties include White Médiland (Test1); and pink varieties include Pink Intuition (Test9), Darling (Test11), and Zindella (Test2). Commercial types include hybrid tea roses and floribunda roses. The experimental design leverages the genetic background differences across multiple color groups and commercial types to provide scientific support for validating the probe's universality across samples. All sample processing and DNA extraction followed standardized procedures to ensure data reliability.

[0082] Capture efficiency assessment Based on the evaluation results of the 12-month-old materials, the proportion of detectable SNPs ranged from 97.55% to 98.85%, with a coverage depth of 374.50% to 556.80%, indicating good overall capture efficiency. This data can be used for subsequent SNP detection and genome-wide selection evaluation of other samples. Table 3 shows the detection rate statistics of the captured sequencing samples from this invention. Hybridization capture was performed on the samples shown in Table 2 using the liquid-phase probe library designed in this invention (containing 528 target SNP sites), and 150bp paired-end sequencing was performed on the Illumina NovaSeq 6000 platform. Key indicators were calculated using bioinformatics workflows (including Trimmomatic quality control, BWA alignment, and GATK variant detection): Call Rate: the proportion of effectively detected target SNPs; Coverage Depth: the average sequencing depth of the target region.

[0083] The detection rate of captured sequencing samples is shown in Table 3: Table 3

[0084] SNP locus detection data for 12 rose varieties (such as White Plum and Cocktail) showed that the detection rate of all samples was ≥97.55% (mean 98.21% ± 0.46%), indicating that ≥857 of the 879 SNP loci were effectively detected. The coverage depth ranged from 374.5X to 556.8X (mean 455.92X ± 72.34X), significantly exceeding the minimum depth threshold for SNP genotyping (≥30X). Among them, Jiawa (Test11) had the highest detection rate (98.85%), while Huobao (Test12) had the lowest (97.55%). Jiawa (Test11) also had the highest coverage depth (556.8X), while Huobao (Test12) had the lowest coverage depth (374.5X). The coefficient of variation (CV) for the detection rate was only 0.46%, confirming the excellent cross-varietal applicability of the probe.

[0085] From a technical perspective, this liquid-phase probe system achieves: ① a target SNP capture efficiency of ≥97.55%, meeting the requirements of genome-wide selection (GS) for genotyping accuracy (>95%); ② an average coverage depth of 455.92X, which effectively reduces the risk of allele dropout; and ③ stable performance across 12 diverse varieties (detection rate fluctuation range ≤1.30%), demonstrating the broad applicability of the probe design.

[0086] Conclusion: This liquid-phase probe system can be efficiently applied to SNP typing, population genetic structure analysis, and whole-genome selection breeding practices of rose germplasm resources.

[0087] The foregoing has shown and described the basic principles, main features, and advantages of the present invention. Those skilled in the art should understand that the present invention is not limited to the above embodiments. The embodiments and descriptions in the specification are merely illustrative of the principles of the invention. Various changes and modifications can be made to the invention without departing from its spirit and scope. The scope of protection of the present invention is defined by the appended claims, specification, and their equivalents.

Claims

1. A method for predicting the outer edge notch of rose petals based on SNP molecular marker combinations, characterized in that... Includes the following steps: (1) Extract genomic DNA from the rose plants to be tested; (2) Construct a library from the genomic DNA; (3) Use probes to hybridize and capture DNA fragments in the library to enrich DNA fragments containing combinations of target SNP molecular markers; (4) Perform high-throughput sequencing on the captured DNA fragments; (5) The sequencing data were compared and analyzed with the rose reference genome to determine the genotype of the SNP molecular marker combination; the SNP molecular marker combination includes 879 SNP molecular marker combinations distributed on the 14 chromosomes of rose; the specific information of the SNP molecular marker combination is represented in the structure of chromosome number_physical location_allele type, the SNP site contains the dominant allele that is positively and significantly associated with the outer edge notch of rose petals, and the specific site information is shown in Table 1; the reference genome of the SNP molecular marker combination is the modern rose 'Samantha' genome v2 version; (6) Input the genotype data of the SNP molecular marker combination into the whole genome selection model to obtain the prediction results of the notched petal trait of the rose to be tested.

2. The application of an SNP molecular marker combination in the molecular breeding of roses, characterized in that: Based on the SNP molecular marker combination described in claim 1, this method is used to predict and screen for the petal notch trait of breeding materials in an early, accurate, and efficient manner during rose breeding, thereby shortening the breeding cycle, improving selection efficiency, and cultivating new rose varieties with excellent petal notch traits. The SNP molecular marker combination includes 879 SNP loci distributed on the 14 chromosomes of rose. The specific information of the SNP loci is represented in the structure of chromosome number_physical location_allele type. The SNP loci contain dominant alleles that are positively and significantly associated with the petal notch of roses. The specific locus information is shown in Table 1. The reference genome for the SNP molecular marker combination is the v2 version of the modern rose 'Samantha' genome.

3. The application of the SNP molecular marker combination according to claim 2 in the molecular breeding of roses, characterized in that: The genome-wide selection model constructed based on the SNP molecular marker combination described in claim 1 can predict the outer edge notches of rose petals with a prediction accuracy greater than 0.541.

Images