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CN-122024829-A - Construction method and application of chrysanthemum aphid resistance prediction system based on whole genome selection

CN122024829ACN 122024829 ACN122024829 ACN 122024829ACN-122024829-A

Abstract

The invention provides a construction method and application of a chrysanthemum aphid resistance prediction system based on whole genome selection. According to the method, SNP loci which are obviously related to the chrysanthemum aphid resistance are identified through whole genome association analysis, the influence of different statistical models and SNP markers with different densities on the whole genome prediction precision is compared, a method for quickly, efficiently and accurately predicting the chrysanthemum aphid resistance based on the GWAS auxiliary whole genome selection is established, and the prediction precision can reach 0.882. The whole genome selection system constructed based on the method can realize early selection of the aphid resistance of the chrysanthemum, accelerate the breeding process of new good varieties of the aphid resistance of the chrysanthemum, save the breeding cost, effectively overcome the technical problems of complicated field aphid resistance identification work, long period, easy influence by environmental factors and artificial subjective factors, and the like, and has important theoretical and practical significance.

Inventors

  • CHEN SUMEI
  • CHEN FADAI
  • YIN XIANCAI
  • SU JIANGSHUO
  • ZHANG XINYI
  • Wan Wenyang
  • DONG ZIYI
  • SHI ZHONGCHENG
  • LING QIN
  • ZHANG FEI

Assignees

  • 南京农业大学

Dates

Publication Date
20260512
Application Date
20260116

Claims (10)

  1. 1. The construction method of the chrysanthemum aphid resistance prediction system based on whole genome selection is characterized by comprising the following steps: (1) Selecting a plurality of representative chrysanthemum germplasm resources which are different in sources and have no direct relationship, and carrying out seedling aphid resistance identification on the chrysanthemums to obtain the average value of the aphid quantity ratio of each chrysanthemum; (2) Performing genome resequencing on the chrysanthemum germplasm resources selected in the step (1), and obtaining high-quality SNP loci by using chrysanthemum 'Zhenshan purple cinnamon' as a reference genome and performing sequence comparison, mutation detection, annotation and screening; (3) Analyzing the high-quality SNP locus obtained in the step (2) to obtain a characteristic value PCs matrix and a kinship K matrix; (4) Based on the high-quality SNP loci obtained in the step (2), combining the chrysanthemum aphid quantity ratio average value obtained in the step (1), and carrying out whole genome association analysis by taking the PCs matrix and the K matrix in the step (3) as covariates to obtain the P value of each SNP locus; (5) Setting a molecular marker data set according to the P value of the SNP locus obtained in the step (4), sequencing the SNP locus according to the P value from small to large, and setting a significant SNP set containing different numbers of loci; (6) Preparing phenotype data and genotype data files required by whole genome selection by using the aphid amount ratio average value obtained in the step (1) and the remarkable SNP set and the random SNP set obtained in the step (5) respectively; (7) And (3) respectively carrying out whole genome selection analysis based on different statistical models and the phenotype data and the genotype data in the step (6) by using a 5-fold cross verification method, dividing the data into a training set and a test set, using the phenotype data and the genotype data of the training set for establishing a whole genome selection model, using the Pearson correlation coefficient r 2 of the actual aphid quantity ratio of the test set and the genome estimated breeding value as indexes for evaluating the whole genome selection prediction accuracy, and selecting and determining an optimal whole genome statistical model and an optimal molecular marker dataset according to the maximum principle of r 2 to obtain an optimal prediction system of chrysanthemum aphid resistance whole genome selection.
  2. 2. The method of claim 1, wherein the seedling stage in step (1) is a 6-8 leaf age stage.
  3. 3. The method of claim 1, wherein the seedling aphid resistance identification in the step (1) adopts an aphid quantity ratio method, and the average pest sensing quantity of each material at 21 days is counted through the inoculation of a pest sensing belt, so that the ratio of the average aphid quantity to the average aphid quantity of all individuals is calculated.
  4. 4. The method of claim 1, wherein the high quality SNPs in step (2) are screened for a sequencing depth greater than 6×, an integrity greater than 0.80, and a minor allele frequency MAF greater than 0.05.
  5. 5. The method according to claim 1, wherein the set of the number of different SNP sites in step (5) is 23 significantly associated SNP sets and the first 200, 500, 1000, 2000, 3000, 4000, 5000 SNP sites are ordered from small to large in P-value, respectively.
  6. 6. The method of claim 1, wherein step (6) further comprises the step of filling in missing values.
  7. 7. The method of claim 1, wherein the whole genome selection statistical model in step (7) comprises bayesian model a, bayesian model BL, random forest RF, ridge regression best linear unbiased prediction rrBLUP, support vector machine SVM.
  8. 8. The method of claim 1, wherein the statistical model and molecular marker dataset of the chrysanthemum aphid resistance whole genome selection optimal prediction system in step (7) are rrBLUP and 23 significantly associated SNP sets, respectively.
  9. 9. The method of claim 5, wherein SNP sites in the 23 set of significantly associated SNPs comprise Chr1__341107915、Chr3__68969696、Chr6__160603126、Chr8__237463465、Chr9__113977500、Chr9__148660626、Chr10__147077153、Chr10__212391937、Chr12__124599771、Chr12__129189145、Chr16__173012402、Chr16__294739630、Chr17__14461593、Chr17__315633045、Chr20__54716376、Chr21__221997442、Chr23__110542759、Chr23__279138954、Chr23__287266773、Chr24__79742681、Chr24__284703360、Chr25__100041366 and Chr27__129357806.
  10. 10. Use of a system predicted based on the method of claims 1-9 in the breeding of chrysanthemum aphid resistance, characterized in that after step (7) of claim 1, it further comprises the steps of: (8) Estimating breeding values GEBV of aphid resistance of each material by using a formula of Y=mu+Xg+e, wherein Y is a predicted phenotype value, mu is a training group phenotype mean value, X is a test group marking matrix, g is a marking effect matrix, and e is a random effect matrix; (9) And (3) screening the chrysanthemum with the breeding value GEBV less than 0.1 to be used as an excellent material for breeding aphid-resistant chrysanthemum.

Description

Construction method and application of chrysanthemum aphid resistance prediction system based on whole genome selection Technical Field The invention relates to a construction method and application of a chrysanthemum aphid resistance prediction system based on whole genome selection, and belongs to the field of plant molecular breeding. Background Aphids (Aphids) are one of the most damaging pests in plants, which are able to penetrate plant tissues with a mouth piece, to extract large quantities of phloem juice and thus plant photosynthetic assimilates, and are also a transmission vector for large quantities of plant viruses (Nalam et al., 2019). Chrysanthemum (Chrysanthemum morifolium ramat.) is one of the ten traditional famous flowers in China and the four cut flowers in the world, and has extremely high ornamental and economic values (Song et al, 2023). However, the growth and development process of chrysanthemum is often suffered from aphids, and the growth, yield and quality of chrysanthemum are greatly limited. Therefore, the cultivation of new varieties of aphid resistance is always one of the important targets of chrysanthemum breeding work. Currently, a plurality of excellent allelic variation sites which are obviously related to chrysanthemum aphid resistance have been mined through QTL (quantitative trait loci) positioning analysis based on traditional PCR molecular markers, and the genetic basis of the chrysanthemum aphid resistance is primarily analyzed (Wang et al 2014, fu et al 2018). However, because chrysanthemum aphid resistance belongs to complex quantitative traits influenced by micro-effect polygene control and environment, genetic improvement of chrysanthemum aphid resistance by molecular marker assisted selection (Molecular assisted selection, MAS) breeding has little effect. In addition, the field screening and identifying work of the aphid resistance of the chrysanthemum is time-consuming and labor-consuming by the traditional aphid quantity ratio method and the aphid damage index method, and the inaccuracy of the identifying result is easily caused by the influence of environment and human factors. Therefore, establishing a chrysanthemum aphid resistance efficient prediction system aiming at complex quantitative characters and low genetic force characters is indistinct. The whole genome selection (Genomic selection, GS) is a novel breeding technology (Alemu et al 2024) which is used for predicting the estimated genome breeding value (GEBV, genomic estimated breeding value) of candidate individuals by covering a high-density marker of the whole genome, can greatly shorten the breeding period, improve the accuracy of predicting the low-genetic trait and reduce the phenotype determination cost. Although whole genome selective breeding has been studied to some extent in breeding of main grain crops such as rice, corn, wheat, etc., it has little application in flower breeding. At present, GS breeding technology systems related to chrysanthemum aphid resistance are not reported at home and abroad. Disclosure of Invention The invention aims to provide a construction method and application of a chrysanthemum aphid resistance prediction system based on whole genome selection, which provides a new means for chrysanthemum aphid resistance breeding, accelerates the genetic improvement process of chrysanthemum aphid resistance and improves the selection efficiency and accuracy of breeding. The technical scheme is that the method for constructing the chrysanthemum aphid resistance prediction system based on whole genome selection comprises the following steps: (1) Selecting a plurality of representative chrysanthemum germplasm resources which are different in sources and have no direct relationship, and carrying out seedling aphid resistance identification on the chrysanthemums to obtain the average value of the aphid quantity ratio of each chrysanthemum; (2) Performing genome resequencing on the chrysanthemum germplasm resources selected in the step (1), and obtaining high-quality SNP loci by using chrysanthemum 'Zhenshan purple cinnamon' as a reference genome and performing sequence comparison, mutation detection, annotation and screening; (3) Analyzing the high-quality SNP locus obtained in the step (2) to obtain a characteristic value PCs matrix and a kinship K matrix; (4) Based on the high-quality SNP loci obtained in the step (2), combining the chrysanthemum aphid quantity ratio average value obtained in the step (1), and carrying out whole genome association analysis by taking the PCs matrix and the K matrix in the step (3) as covariates to obtain the P value of each SNP locus; (5) Setting a molecular marker data set according to the P value of the SNP locus obtained in the step (4), sequencing the SNP locus according to the P value from small to large, and setting a significant SNP set containing different numbers of loci; (6) Preparing phenotype data and genotype data files required