Probe combination and gene chip for predicting corn starch content and application of probe combination and gene chip

Abstract

The invention belongs to the technical field of molecular marker-assisted breeding, and particularly relates to an SNP (Single Nucleotide Polymorphism) combination for predicting corn starch content, a gene chip and application of the SNP combination. According to the invention, the SNP positioned in the upstream and downstream 2kb range of starch functional genes is screened out through collection of known corn starch synthesis regulation genes and excavation of potential related genes; further identifying the SNP sites associated with the corn starch content in a non-starch functional gene region by using whole genome association analysis, and adding and supplementing the starch functional SNP sites in reported research; and finally, the high-confidence SNP site associated with the corn starch content is obtained. The gene chip for detection is developed, the typing accuracy and the detection rate of SNP loci are high, the consistency rate of repeated sample genotypes is good, the gene chip has the advantages of low cost, high specificity, high stability of detection results and good accuracy, and a reliable molecular detection tool is provided for corn whole genome selective breeding application.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of molecular marker assisted breeding, in particular to a probe combination for corn starch content prediction, a gene chip and application thereof. BACKGROUND

[0002] Corn is an important food and feed crop. Because its kernels are rich in starch (>60%), corn is usually used as an energy source for feed. Therefore, identifying and breeding high-starch corn varieties has important social value. Corn is one of the most successful crops in which heterosis is applied. The selection of parents is the core of heterosis breeding. In the past, parent selection mostly relied on the experience of breeders and phenotypic selection, which consumed a large amount of human cost and had the disadvantages of long breeding cycle and low efficiency. With the development of genomics, molecular biology and high-throughput sequencing technology, molecular marker assisted selection breeding technology based on single nucleotide polymorphism (SNP) can screen plants with genotypes or alleles associated with superior traits by detecting SNP molecular markers, so as to realize the exploration and breeding of excellent germplasm resources. This technology has the advantages of short breeding cycle, low cost, high genetic stability and good application prospect in corn hybrid breeding.

[0003] SNP is the most widely distributed genetic marker in the genome, with high density and high genetic stability, and has become the most commonly used molecular marker for studying plant genetic variation. The gene chip designed and prepared based on SNP is an array of dense oligonucleotide probes formed by fixing the probes for detecting SNP molecular markers on a carrier. Through the allelic specific hybridization reaction between the probes and the target genome, the polymorphism and genotype of SNP sites can be determined according to the presence or absence and strength of the signal after the reaction. SNP chip has good detection rate and stability in sample site detection. Developing efficient and low-cost corn SNP chip is an important means of molecular breeding.

[0004] Currently, several SNP chips have been developed for maize. For example, the Crop Science Institute of Chinese Academy of Agricultural Sciences used 1604 maize inbred lines resequencing data to select representative SNPs, and integrated other specific markers, successfully developed a SNP liquid chip MaizeGerm50K (Guan et al., Development of a MaizeGerm50K array and application to maize genetic studies and breeding. The Crop Journal, 12(6): 1686-1696); Beijing Academy of Agriculture and Forestry Sciences Maize Institute developed a high-density chip Maize 6H-60K based on whole genome resequencing data of 388 representative maize inbred lines at home and abroad (Tian et al., New resources for genetic studies in maize (Zea mays L.): a genome-wide Maize 6H-60K single nucleotide polymorphism array and its application. Plant J, 105(4): 1113-1122). Although chip technology has been applied in many crop breeding fields, the currently developed gene chips are mainly high-density and medium-high-density, and the cost of genotyping is high when selecting genotypes for specific or certain agronomic traits, which limits its wide application in maize breeding. Starch is the main storage material in maize kernels, not only an important energy source for humans and animals, but also an important industrial raw material. However, a chip specifically used for genotyping maize starch traits has yet to be developed. Current gene chips often have problems of marker redundancy and poor specificity when used for starch phenotype prediction. Therefore, it is of important application value to develop a low-density, specific and / or low-cost maize starch trait genotyping chip. SUMMARY

[0005] In view of the problems in the prior art, the present application provides a SNP combination for corn starch content prediction, a detection probe and a gene chip thereof and application thereof. The present application screens out SNPs located in the range of 2 kb upstream and downstream of a starch function gene by collecting known corn starch synthesis regulation genes and mining potential related genes. Further, the SNPs sites associated with corn starch content are identified by using whole genome association analysis (GWAS) on the non-starch function gene region. In addition, the starch function SNP sites reported in the research are added as supplements. Finally, the high confidence SNP sites associated with corn starch content are obtained, which provides new genetic resource information for the breeding work of high starch content corn varieties. The genotype of the aforementioned SNP sites is detected, so that the starch content of corn inbred lines or hybrid harvest materials can be efficiently predicted, the predicted value is highly consistent with the true value, which is beneficial to the breeder to make reasonable parent combination strategy and accelerate the breeding progress.

[0006] The present application is implemented by the following technical solutions:

[0007] Therefore, the first aspect of the present application provides a SNP molecular marker combination for corn starch content detection, which includes 850 SNP variation sites, respectively named SNP1-SNP850, the physical positions of the 850 SNP variation sites are determined by sequence alignment based on a corn reference genome, the version number of the corn reference genome is Zm-B73-REFERENCE-GRAMENE-4.0; wherein the corresponding chromosome physical positions and base polymorphisms of SNP1-SNP850 are shown in Table 1 of the specification.

[0008] The second aspect of the present application provides a probe combination, which is used for identifying the SNP molecular marker combination as described above.

[0009] Further, the CG content of each probe in the probe combination is 20%-80%, the theoretical melting temperature is greater than or equal to 65℃, there is no N base in the sequence of the probe, the sequence complexity is greater than or equal to 0.9, the maximum homopolymer length is less than or equal to 6, and the maximum number of consecutive base repeats is less than or equal to 3.

[0010] Further, the sequence length of the probe is 110 bp.

[0011] Further, the probe combination includes 853 probes, and the nucleotide sequences of the 853 probes correspond to the chromosome positions shown in Table 2 of the specification.

[0012] The third aspect of the present application provides a gene chip, which includes the probe combination as described above.

[0013] Optionally, the gene chip is a liquid chip.

[0014] The fourth aspect of the present application provides an application of the probe combination or gene chip as described above, which is selected from at least one of the following: (1) corn genetic diversity analysis; (2) corn starch content molecular marker assisted selection breeding; (3) whole genome selection breeding; (4) corn germplasm resource identification; (5) corn genotyping; (6) corn population structure analysis.

[0015] The fourth aspect of the present application provides a method for predicting the starch content of corn, comprising the following steps:

[0016] S1, extracting the genomic DNA of the corn to be tested;

[0017] S2, constructing a library from the genomic DNA and hybridizing with probes, and sequencing the captured library;

[0018] S3, quality control and data analysis of the sequencing data to obtain genotyping results;

[0019] S4, performing excellent allele analysis on the genotyping results to predict the starch content of corn.

[0020] Further, the standard for judging the starch content of corn by excellent allele analysis on the genotyping results in step S4 is as follows:

[0021] The genotyping results of each SNP of the corn material are compared with excellent allele types, and the number of excellent allele types is counted; the fewer the number of excellent allele types, the lower the starch content, and vice versa, the more the number of excellent allele types, the higher the starch content.

[0022] The advantages and positive effects of the present application are as follows:

[0023] The SNP molecular marker combination provided by the present application is developed for corn starch traits, has the advantages of strong correlation, high specificity, low density, small cost, etc., and provides high-quality molecular markers for efficient prediction or detection of the starch content of corn germplasm resources and selection breeding. The detection probe combination and gene chip developed based on the foregoing molecular markers have the advantages of high specificity, high stability of detection results, high accuracy, and the consistency between the predicted starch content predicted based on the SNP molecular marker combination and the true value is high, which provides a reliable molecular detection tool for the breeding application of corn whole genome selection, and is beneficial to accelerating the breeding process of high-starch-content corn and other excellent varieties. BRIEF DESCRIPTION OF DRAWINGS

[0024] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the following briefly describes the drawings needed in the embodiment description.

[0025] Figure 1 Distribution map of SNP variation sites in the whole genome of the embodiment of the present application in the genome;

[0026] Figure 2 Starch content prediction value based on the number of SNP advantageous alleles of corn material BY815, DAN340 and K22 and the real value correlation diagram of the embodiment of the present application;

[0027] Figure 3 Starch content prediction value based on the number of SNP advantageous alleles of corn association population material and the real value correlation diagram of the embodiment of the present application;

[0028] Figure 4 Starch content prediction value based on the number of SNP advantageous alleles of corn B73 and BY804 recombinant inbred line population material and the real value correlation diagram of the embodiment of the present application;

[0029] Figure 5 Starch content prediction value based on the number of SNP advantageous alleles of corn commercial hybrid material and the real value correlation diagram of the embodiment of the present application. DETAILED DESCRIPTION

[0030] In order to make the objects, technical solutions and advantages of the present application clearer, the following further describes the present application in combination with embodiments. The embodiments described herein are only used to explain the present application, and are not used to limit the present application. In the present application, all numbers and other numerical values used to express amount and percentage should be understood as being modified by the word "approximately" in all cases. Therefore, unless specifically stated otherwise, the numerical parameters listed in the specification and attached claims are approximations. They can vary somewhat depending on desired properties sought to be obtained from the ideal properties. Each numerical parameter should be considered as a minimum and maximum value, obtained from the reported significant digits and rounded off by the conventional rounding-off method. The meaning of the terms "comprise", "contain", "include", "have" and the like are non-restrictive, i.e. other steps and other components can be added without affecting the results. "And / or" should be considered as a specific disclosure of each of the two specified features or components with or without the other. For example, "A and / or B" should be considered as including the following cases: (i) A, (ii) B, and (iii) A and B.

[0031] The experimental methods in the following embodiments, if not otherwise specified, are usually carried out according to conventional conditions, for example, the conditions described in "Molecular Cloning: A Laboratory Manual (Fourth Edition)" published by Cold Spring Harbor Laboratory, or the conditions recommended by the manufacturer.

[0032] 1. Development of SNP molecular markers associated with starch content in maize parent kernels

[0033] 1.1. Collect genes related to corn starch synthesis metabolism and regulation.

[0034] The literature search was performed by using the key words "Maize starch; Maize endosperm; Maize seed development" in the biomedical literature retrieval system (NCBI PubMed) developed by the National Center for Biotechnology Information to obtain the review literature related to the research of maize starch synthesis and metabolism in the past ten years. The starch synthesis and metabolism pathway genes and related regulatory genes were collected, and the genes were verified by using the related research literature cited in the review literature. In the PATHWAY module of the Kyoto Encyclopedia of Genes and Genomes (KEGG) database, the Metabolism option was selected to retrieve the starch synthesis and metabolism pathway (map00500: Starch and sucrose metabolism) and select the species as maize (zma) to obtain all genes involved in the starch synthesis and metabolism pathway. In the maize genome database MazieGDB (https: / / www.maizegdb.org / ), the genes retrieved by KEGG were annotated and analyzed to remove genes without starch-related annotation information. A total of 50 maize starch synthesis and metabolism genes and 23 related transcription factors were screened. The gene IDs are as follows: Zm00001d000002, Zm00001d000021, Zm00001d002256, Zm00001d003817, Zm00001d004438, Zm00001d005546, Zm00001d010821, Zm00001d011301, Zm00001d013428, Zm00001d014150, Zm00001d014844, Zm00001d015200, Zm00001d015746, Zm00001d016684, Zm00001d018033, Zm00001d019266, Zm00001d019479, Zm00001d020799, Zm00001d022206, Zm00001d022510, Zm00001d026337, Zm00001d027242, Zm00001d029087, Zm00001d029091, Zm00001d032385, Zm00001d033746, Zm00001d033910, Zm00001d033937, Zm00001d034074, Zm00001d034256, Zm00001d035037, Zm00001d037234, Zm00001d038121, Zm00001d039131, Zm00001d042536, Zm00001d042842, Zm00001d044129, Zm00001d044211,Zm00001d045042, Zm00001d045261, Zm00001d045462, Zm00001d047253, Zm00001d049753, Zm00001d050032, Zm00001d051976, Zm00001d052263, Zm00001d051837, Zm00001d035038, Zm00001d020771, Zm00001d005925, Zm00001d011712, Zm00001d018971, Zm00001d005100, Zm00001d029512, Zm00001d008403, Zm00001d005028, Zm00001d040189, Zm00001d021537, Zm00001d026447, Zm00001d003677, Zm00001d002654, Zm00001d026113, Zm00001d041781, Zm00001d038001, Zm00001d020043, Zm00001d009646, Zm00001d031620, Zm00001d000361, Zm00001d043131, Zm00001d010730, Zm00001d032095, Zm00001d036298, Zm00001d045026.

[0035] Based on the above collected 50 maize starch synthesis metabolism genes and 23 transcription factors, the potential candidate genes were identified by gene co-expression network, protein interaction network analysis and other methods. The steps include: (1) In the previous study (Xu et al., DNA demethylation affects imprinted gene expression in maize endosperm. Genome Biol. 23:77) of the application, the maize DNA demethylase mutant was obtained, and through the phenotype detection of multiple years and multiple points, it was found that the starch content of the mutant grain was reduced, and the whole genome methylation sequencing and transcriptome sequencing showed that the wide DNA methylation variation caused by the mutant disturbed the expression of the starch synthesis pathway genes. Further, the transcriptome sequencing of the wild type and the DNA demethylase mutant maize grain endosperm at different development stages was carried out, and the expression level of the genes at different development stages of the endosperm was identified. The DESeq2 R package was used for differential expression gene analysis, and the expression level of the above collected 50 maize starch synthesis metabolism genes and 23 transcription factors was analyzed, and 13 maize starch synthesis metabolism genes and 10 transcription factors were identified to be differentially expressed in the wild type and the DNA demethylase mutant. (2) The co-expression network of the differentially expressed genes and the annotated differentially expressed transcription factors of maize was constructed by using GENIE3 software, and the TOP 100000 genes were selected for the analysis of the constructed co-expression network. Based on the co-expression network, the 13 maize starch synthesis metabolism genes and the 10 transcription factors were used as target genes, and the gene pairs with weight value greater than or equal to 0.01 were used as potential candidate genes, and the DNA methylation level of the potential candidate genes in the wild type and the DNA demethylase mutant was analyzed. The maize genome was divided into discontinuous 100bp windows, and the CG and CHG methylation levels of the 100bp windows in the wild type and the DNA demethylase mutant at different development stages were counted. The 100bp window with differential DNA methylation level CG greater than or equal to 50% or CHG greater than or equal to 50% was the differential methylation segment, and based on the above analysis results, the genes with differential methylation segments in the range of 2kb upstream and downstream of the genes were selected as the candidate genes related to maize starch synthesis metabolism; 99 candidate transcription factor genes were identified. (3) The MaizeNetome database (http: / / minteractome.ncpgr.cn / ) developed by the Li Lin research group of Huazhong Agricultural University was used to identify the candidate genes. The gene IDs of the collected 50 maize starch synthesis metabolism genes and 23 transcription factors were entered for retrieval, and 99 candidate genes associated with the 50 maize starch synthesis metabolism genes and 23 transcription factors were retrieved.Combining the aforementioned candidate genes, 196 genes related to corn starch synthesis metabolism were screened, including 102 transcription factors and 94 non-transcription factor genes.

[0036] 1.2, SNP site analysis associated with corn starch synthesis

[0037] The location information of the 50 corn starch synthesis metabolism genes, 23 transcription factors and 196 potential genes related to corn starch synthesis metabolism collected in the corn reference genome (Zm-B73-REFERENCE-GRAMENE-4.0 (B73 v4), Assembly accession: GCF_000005005.2) was obtained. Based on the SNP information identified by the corn association population (Gui et al., ZEAMAP, a Comprehensive Database Adapted to the Maize Multi-Omics Era. iScience. 2020 Jun 26;23(6):101241.), SNPs located within 2 kb upstream and downstream of the genes were screened, and only SNPs with only two alleles and a minimum allele frequency (MAF) greater than 0.1 were retained. The starch content of the corn association population material was determined (Zhou and Bao, High throughput method for measuring total fermentables in small amount of plant part. U.S. Patent 8, 329,426 P. 201212-11), the retained SNPs were genotyped, the starch content of corn plants with different genotypes was subjected to T test, and SNPs with P<0.05 were selected. Then, PLINK was used to calculate the LD (Linkage Disequilibrium) between SNPs, and SNPs with LD≥0.1 were combined, and finally 325 SNPs associated with starch content synthesis were identified.

[0038] Based on the published 756,806 corn association population material SNP molecular markers (Gui et al., ZEAMAP, a Comprehensive Database Adapted to the Maize Multi-Omics Era. iScience. 2020 Jun 26; 23(6): 101241.) and the measured grain starch content information. Using the mixed linear model (Mixed Linear Model, MLM) of tassel5 software for whole genome association analysis (GWAS), removing the SNP with more than 10% missing, retaining 574 SNPs with threshold p < 0.0001, LD ≥ 0.1. Further from the related research of Professor Yang Xiaohong of China Agricultural University (Hu et al., Genetic basis of kernel starch content decoded in a maize multi-parent population. Plant Biotechnol J. 2021, 19(11): 2192-2205, which uses 6 recombinant inbred line (RIL) populations to analyze the genetic variation of corn kernel starch content traits, adds the QTL effect analyzed to the conventional linear model to form a new modified model for GWAS, and uses the residual of the model to test all SNPs on the current chromosome), using forward and backward regression method for variable screening, the P value threshold is determined by 500 times permutation test, finally 137 SNPs significantly related to variation of corn kernel starch content are collected.

[0039] After the above analysis, a total of 1036 SNPs were collected, then the SNPs located in the same gene (2kb upstream and downstream of the gene) with LD ≥ 0.1 were combined, and 951 SNPs related to corn kernel starch content were retained, which were evenly distributed on the genome as a whole (see Figure 1 ).

[0040] 2. Liquid probe design for SNP molecular marker detection

[0041] According to the position information of 951 SNP sites on the corn B73 v4 version genome, liquid probe design was carried out with SNP as the center, the probe sequence length was 110 bp, the CG content was between 20%-80%, the theoretical melting temperature of the probe was ≥ 65℃, the number of N bases in the sequence was 0, the sequence complexity was ≥ 0.9, the maximum homopolymer length (continuous repetition of the same base) was ≤ 6, and the maximum number of continuous repetition of multiple bases was ≤ 3. The liquid probe was prepared by Beijing Baividai Biotechnology Co., Ltd., and the liquid probe combination was the gene chip.

[0042] Finally, 853 probes with 110 bp in length were designed to cover 850 SNPs (some SNPs contain two probes, such as SNP324, SNP498 and SNP542), among which 83 SNPs are from 50 functional genes related to starch synthesis in maize and 23 transcription factors, 216 SNPs are from genes related to starch synthesis in maize, 421 SNPs are from GWAS analysis of association population, and 130 SNPs are from previous literature reports. Table 1 shows the physical location information of 850 SNP (SNP1 to SNP850) molecular markers, as well as their base polymorphisms and dominant alleles. Table 2 shows the physical location information of 853 probes for detecting SNP molecular markers in the genome.

[0043] Table 1 Physical location and allele information of SNP1 to SNP850 molecular markers

[0044]

[0045]

[0046]

[0047]

[0048]

[0049]

[0050]

[0051]

[0052]

[0053]

[0054]

[0055]

[0056] In the table, chr represents the chromosome, the data before the s_number represents the chromosome number, and the number after the s_number represents the physical location of the base on the chromosome. Polymorphism represents the base type of the SNP site; for example, Chr1.s_2154074 represents that SNP1 is located at the 2154074th base on chromosome 1, and the base type is C or G, and the dominant allele is C, that is, the corn plants containing this allele (including homozygous genotype CC and heterozygous genotype CG) are related to high starch content.

[0057] Table 2 Physical position information of SNP1 to SNP850 molecular marker probes

[0058]

[0059]

[0060]

[0061]

[0062]

[0063]

[0064]

[0065] 3. Detection effect evaluation of corn starch content breeding gene chip

[0066] Genome extraction was performed on corn B73 inbred line leaf tissue (named B73) using 2% CTAB method, and corn inbred line B73 was detected and analyzed by Beijing Biomed Company using a gene chip; including: library construction of genomic DNA, hybridization with probes, sequencing of captured library; quality control and data analysis of sequencing data to obtain genotyping results.

[0067] The raw sequencing data was quality controlled and adapter removed using SOAPnuke filter to obtain Clean data, and the parameters were set as -n 0.1 -q 0.5 -l 20 -Q 2 -G -f AAGTCGGAGGCCAAGCGGTCTTAGGAAGACAA -r AAGTCGGATCGTAGCCATGTCGTTCTGTGAGCCAAGGAGTTG. The Clean data was aligned to the maize reference genome B73 v4-like (951 SNPs in B73 v4 genome were replaced by non-B73 type bases, for example, the base at SNP1 position was C in B73 v4 genome, and was replaced by G in B73 v4-like) using BWA mem mode, and the parameters were set as default parameters. The repeated data in the aligned file due to PCR amplification in the library construction process was removed using SortSam.jar and MarkDuplicates.jar in picard-tools-1.119 package. Further, the annotation of AddOrReplaceReadGroups was performed using picard.jar in picard-tools-1.124 package. Finally, the SNP sites between all samples were identified using GenomeAnalysisTK.jar in GenomeAnalysisTK-3.7, and the parameters were set as -T HaplotypeCaller -nct 6 -dontUseSoftClippedBases -stand_call_conf 20.0. The obtained SNP file was quality controlled, and the file was filtered using vcftools tool, and the parameters were set as --minDP 10 --minQ 30. The genotypes were extracted using vcftools tool, and the parameters were set as --extract-FORMAT-info GT. The results are shown in Table 3. The results show that the genotyping accuracy, detection rate and genotype consistency rate of the repeated samples of the probe combination are all good.

[0068] Table 3 Effect of probe combination on detection of SNP molecular markers

[0069]

[0070] 4. Effect evaluation of gene chip for predicting corn starch phenotype

[0071] The number of excellent alleles of each material is counted based on the SNP molecular marker information of the published maize association population materials. Among them, the reported recombinant inbred population parent materials BY815, DAN340, K22 for genetic analysis of kernel starch content have 403, 430, 474 excellent allele numbers respectively (Hu et al., Genetic basis of kernel starch content decoded in a maize multi-parent population. Plant Biotechnol J. 2021 Nov; 19(11): 2192-2205), according to the number of excellent alleles, BY815, DAN340, K22 are predicted to be low, medium and high starch content materials respectively. The prediction results are consistent with the starch content measured values of BY815, DAN340, K22, which are 54.0%, 63.8%, 67.9% respectively (see Figure 2 , the horizontal coordinate of the figure is the number of excellent alleles of the plant, and the vertical coordinate is the starch content (%)). Further evaluate the correlation between the prediction results and the true phenotype values of all materials in the population, the results are as follows Figure 3 , the horizontal coordinate value is the number of excellent alleles, and the vertical coordinate is the true starch content. Specifically, the number of excellent alleles <=200, 201-250, 251-300, 301-350, 351-400, 401-450, 451-500, 501-550, the average number of excellent alleles is 192, 228, 279, 330, 377, 424, 470, 518, and the average true phenotype value is 61.47%, 61.61%, 63.39%, 63.98%, 65.54%, 66.67%, 67.91%, 69.38%, and the correlation coefficient R 2 =0.99, indicating that the prediction results have good accuracy.

[0072] Maize B73 and BY804 are two inbred lines with obvious difference in starch content. The genomic DNA of B73 × BY804 recombinant inbred line population (71) is extracted by 2% CTAB method, and is detected and analyzed by Beijing Biomed Company using gene chip. The number of excellent alleles contained in each material (heterozygous sites are recorded as excellent alleles) is counted, and they are classified according to the number of excellent alleles, as follows Figure 4Horizontal coordinate. The starch content of the population material was determined by polarimetry (GB / T 20378-2006 “Raw starch Starch content determination Polarimetry”), and the consistency of the prediction results and the true phenotype values was evaluated, and the results are as follows Figure 4 . Correlation coefficient R 2 =0.89, indicating that the prediction results have good accuracy.

[0073] Corn commercial hybrids are the source of corn application, and the accurate prediction of the starch content of the harvested material according to the genotype of the hybrid is of great significance to breeding and application. The genomic DNA of the collected commercial hybrid population (66) was extracted by 2% CTAB method, and was detected and analyzed by Beijing Baividai Biotechnology Co., Ltd. using a gene chip. The number of excellent alleles (heterozygous sites are recorded as excellent alleles) contained in each material was counted, and they were classified according to the number of excellent alleles, such as Figure 5 Horizontal coordinate. The starch content of the population material was determined by polarimetry, and the correlation coefficient R 2 =0.95 between the prediction results and the true phenotype values Figure 5 , indicating that the prediction results have good accuracy.

[0074] The above only describes the preferred embodiments of the present application and does not limit the present application. Any modification, equivalent replacement and improvement made within the spirit and principle of the present application shall be included in the protection scope of the present application.

Claims

1. A probe assembly, characterized in that, The probe combination is used to identify SNP molecular marker combinations for corn starch content detection. The SNP molecular marker combination includes 850 SNP variant sites, named SNP1-SNP850 respectively. The physical locations of the 850 SNP variant sites are determined by sequence alignment based on the corn reference genome, and the version number of the corn reference genome is Zm-B73-REFERENCE-GRAMENE-4.

0. The chromosomal physical locations and base polymorphisms corresponding to SNP1-SNP850 are shown in the table below: 。 2. The probe assembly according to claim 1, characterized in that, The probe combination has a CG content of 20%-80% for each probe, a theoretical melting temperature greater than or equal to 65℃, no N bases in the probe sequence, a sequence complexity greater than or equal to 0.9, a maximum homopolymer length less than or equal to 6, and a maximum number of consecutive repetitions of multiple bases less than or equal to 3.

3. The probe assembly according to claim 1, characterized in that, The probe has a sequence length of 110 bp.

4. The probe assembly according to claim 1, characterized in that, The probe array comprises 853 probes, and the chromosomal positions corresponding to the nucleotide sequences of the 853 probes are shown in the table below: 。 5. A gene chip, characterized in that, Includes the probe combination as described in any one of claims 1-4.

6. The gene chip according to claim 5, characterized in that, The gene chip is a liquid-phase chip.

7. The application of the probe combination as described in any one of claims 1-4 or the gene chip as described in any one of claims 5-6, characterized in that, The application is selected from at least one of (1)-(6): (1) Analysis of genetic diversity in maize; (2) Marker-assisted selection breeding based on corn starch content; (3) Whole-genome selection breeding; (4) Identification of maize germplasm resources; (5) Maize genotyping; (6) Analysis of maize population structure.

8. A method for predicting corn starch content, characterized in that, Includes the following steps: S1. Extract genomic DNA from the maize to be tested; S2. Construct a library of genomic DNA, hybridize it with probes, and sequence the captured library; S3. Perform quality control and data analysis on sequencing data to obtain genotyping results; S4. Perform superior allele analysis on the genotyping results to predict corn starch content.

9. The method for detecting corn starch content according to claim 8, characterized in that, In step S4, the criteria for determining the corn starch content by performing superior allele analysis on the genotyping results are as follows: The genotyping results of each SNP in maize materials were compared with the superior alleles, and the number of superior alleles was counted. The fewer the number of superior alleles, the lower the starch content, and vice versa.

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