A wheat ultra-high density gene chip probe and its preparation method

Abstract

This invention discloses a wheat ultra-high-density gene chip probe and its preparation method, belonging to the fields of plant functional genomics, population genetics, and molecular breeding technology. Based on wheat pan-genome information, this invention uses resequencing data and exon capture sequencing data from large-scale natural wheat populations to perform variation analysis and obtain ultra-large-scale whole-genome variation information. High-quality SNPs and INDEL loci with population and individual representativeness are obtained through filtering and screening. Simultaneously, harmful mutation sites are identified, and publicly published genetic loci related to important wheat yield and quality traits are integrated and extracted. Polymorphic loci regions are determined by combining genome annotation and variation annotation. Finally, ultra-high-density liquid-phase probes are synthesized at the pan-genome level. Because this invention only sequences target gene regions, it reduces sequencing costs by more than 90% for the same gene sequencing depth.

Description

Technical Field

[0001] This invention relates to the fields of plant functional genomics, population genetics and molecular breeding technology, and in particular to a wheat ultra-high density gene chip probe and its preparation method. Background Technology

[0002] High-density single nucleotide polymorphism (SNP) markers have been widely used in molecular marker-assisted selection, backcross breeding and background selection, multigene aggregation breeding, genome-wide association analysis, QTL mapping, genome-wide selection, species evolution analysis, and germplasm resource identification.

[0003] Currently, obtaining genome-wide variant genotypes mainly relies on resequencing and custom gene chips. However, the wheat genome is enormous (16GB), making the cost of obtaining variant information through whole-genome or simplified genome sequencing methods too high. This results in significant site omissions, a relatively large sequencing data volume, and demanding requirements for data storage and analysis hardware and software. The detection quality of variant sites heavily depends on the quality of the reference genome. Furthermore, existing wheat transcriptome sequencing BSR-seq is based on gene expression data, which is significantly influenced by factors such as sample tissue, sampling period, and environment, leading to substantial data bias. Since gene expression data itself is not genetic information, it carries a certain risk of false positives.

[0004] SNP chips offer greater flexibility in sample and detection site preparation, and boast higher detection rates and stability compared to sequencing. Currently, several chips have been developed in the field of wheat molecular breeding to characterize the variation information of tested materials, including the Illumina Wheat 90K iSelect SNP genotyping array (90K), Axiom® Wheat 660K SNP array (660K), Wheat 55K SNP array (55K), Axiom® HD Wheat genotyping (820K) array (820K), and Wheat 50K Triticum TraitBreed array (50K). Significant research progress has been made in wheat molecular breeding based on these chips, but they also have the following drawbacks: First, the preparation of the above chips requires specialized supporting detection equipment and specific analysis software to analyze genotype results, which has many limitations and is inconvenient. Second, the probes of the current chips are mostly located in non-gene coding regions such as chromosomal repetitive regions with more variation information, while the marker distribution is less in chromosomal regions with more gene distribution. Third, the current chips do not have high coverage of functional genes and are mostly located in non-coding regions of genes. Taking the 660K chip, which is currently a representative chip in the field of wheat molecular breeding, as an example, probe sites are designed near only 66,834 HC genes, accounting for 63.52% of all genes (Sun et al., Plant Biotechnology Journal, 2020, 18(6): 1354-1360). Summary of the Invention

[0005] The purpose of this invention is to provide a wheat ultra-high density gene chip probe and its preparation method, which addresses the problem of low coverage of gene coding regions by existing chip-designed probes, and the high cost of obtaining gene information using whole-genome sequencing due to the large size of the wheat genome. Because sequencing is performed only on the target gene region, sequencing costs are reduced by more than 90% for the same gene sequencing depth.

[0006] To achieve the above objectives, the present invention provides the following solution: One of the technical solutions of this invention is a method for preparing wheat ultra-high density gene chip probes, comprising the following steps: S1. Based on the Chinese spring reference genome, variation analysis was performed using wheat natural population resequencing data and exon capture sequencing data to obtain high-quality SNP and INDEL sites. S2. Extract the sequencing reads that failed to be aligned to the Chinese spring reference genome in step S1 and the low-quality aligned reads, and perform sequence alignment analysis and variant site screening and filtering again using other wheat reference genomes in the pan-genome. S3. Construct a Chinese spring and pan-genome SNP annotation database and perform functional annotation of variant sites; S4. SNPs / Indels within a 2K range upstream and downstream of the gene coding sequence are screened. SNPs / Indels within the gene coding sequence region are preferentially retained, followed by SNPs / Indels within a 1K range upstream and downstream of the gene coding sequence, and then SNPs / Indels within a 2K range upstream and downstream of the gene coding sequence. S5. The discovered variant sites were predicted as harmful mutation sites using PROVEAN software and SIFT 4G software, respectively, and harmful mutation sites were screened out. S6. Integrate and extract genetic loci related to important yield and quality traits in wheat; S7. High-density probes are designed and synthesized for the regions covered by the SNP / Indel sites, harmful mutation sites, and trait-related sites obtained in steps S4, S5, and S6 to obtain an ultra-high-density SNP chip for wheat exon sequencing gene localization.

[0007] The second technical solution of the present invention is a wheat ultra-high density SNP chip, which is prepared by the method described above.

[0008] The third technical solution of the present invention is a method for detecting wheat genotypes, which uses the ultra-high density SNP chip to scan wheat germplasm resources to obtain genotype information of variant sites.

[0009] Based on the above technical solution, the present invention has the following technical effects: (1) The present invention has obtained an ultra-high density wheat gene chip; compared with other wheat chips, especially the wheat 660K SNP chip which is currently the most widely used in the field of wheat breeding and has a better gene detection effect, the chip of the present invention has a higher SNP density and a better gene detection effect.

[0010] (2) Under the same gene sequencing depth, sequencing costs are reduced by more than 90%. Attached Figure Description

[0011] Figure 1 This is a flowchart illustrating the preparation process of the wheat ultra-high density gene chip of the present invention.

[0012] Figure 2 This is a diagram showing the coverage of the wheat ultra-high density gene chip on the genome according to the present invention.

[0013] Figure 3 This is a density comparison diagram of the wheat ultra-high density gene chip and the wheat 660K chip of the present invention.

[0014] Figure 4 This is a Manhattan plot of a genome-wide association study of wheat plant height performed using the wheat ultra-high density gene chip of this invention. Detailed Implementation

[0015] Unless otherwise specified, the technical solutions described in this invention are all conventional solutions in the field, and the reagents or raw materials used are all purchased from commercial channels or are publicly available unless otherwise specified.

[0016] This invention provides a method for preparing wheat ultra-high density gene chip probes, comprising the following steps: S1. Based on the Chinese spring reference genome, variation analysis was performed using wheat natural population resequencing data and exon capture sequencing data to obtain high-quality SNP and INDEL sites. S2. Extract the sequencing reads that failed to be aligned to the Chinese spring reference genome in step S1 and the low-quality aligned reads, and perform sequence alignment analysis and variant site screening and filtering again using other wheat reference genomes in the pan-genome. S3. Construct a Chinese spring and pan-genome SNP annotation database and perform functional annotation of variant sites; S4. SNPs / Indels within a 2K range upstream and downstream of the gene coding sequence are screened. SNPs / Indels within the gene coding sequence region are preferentially retained, followed by SNPs / Indels within a 1K range upstream and downstream of the gene coding sequence, and then SNPs / Indels within a 2K range upstream and downstream of the gene coding sequence. S5. The discovered variant sites were predicted as harmful mutation sites using PROVEAN software and SIFT 4G software, respectively, and harmful mutation sites were screened out. S6. Integrate and extract genetic loci related to important yield and quality traits in wheat; S7. High-density probes are designed and synthesized for the regions covered by the SNP / Indel sites, harmful mutation sites, and trait-related sites obtained in steps S4, S5, and S6 to obtain an ultra-high-density SNP chip for wheat exon sequencing gene localization.

[0017] In some specific implementation schemes, step S1 includes the following specific procedures for the variation analysis: The raw data from resequencing and exon capture sequencing are filtered using the default parameters of the FASTP software. The filtered sequencing data were compared with the Chinese spring reference genome using the default parameters of BWA software to obtain the bam file; PCR repetitive sequences were removed using the default parameters of Picard software, and the Indel region was re-aligned and baseline corrected. The haplotypecaller tool in GATK software was used to mine variant sites, with the standard being MQ≥50 and BQ≥20, to obtain GVCF files. Picard software was used for VCF quality filtering, with the standard being QUAL≥100 or DP≥5, to obtain high-quality SNP and INDEL sites. The filtering criteria for reference genome variant sites in the Chinese spring genome in the population are: MF>0.005 and MISSING≤0.3.

[0018] In some specific implementations, in step S1, before performing alignment analysis using GATK software, the sequencing data needs to be segmented because GATK software is incompatible with chromosome genome files longer than 512M. The split points were selected in regions of the genome with a large number of "N"s or near the centromere in repetitive sequence clusters. The whole genome "N" regions were scanned and screened using seqtk, and the split sites were selected by combining the regions marked by RepeatMask.

[0019] In some specific implementations, in step S2, other wheat reference genomes in the pangenome include the wheat 10+ genome and / or the fielder genome; The wheat 10+ genome includes at least one of ArinaLrFor_v3, Cadenza_v1, CDC_Landmark_v1, CDC_Stanley_v1, Claire_v1, Jagger_v1, Julius_v1, LongReach_Lancer_v1, Mace_v1, Norin61_v1, SY_Mattis_v1, and PI190962_v1; The filtering criterion for other reference genomic variant sites in the population is: MF>0.001.

[0020] In some specific implementation schemes, step S3 involves using snpEff software to perform functional annotation on the variant sites.

[0021] In some specific implementation schemes, in step S4, 706,912 probe regions with 1,738,820 variant sites in the Chinese Spring 2.1 reference genome, 1,096,869 probe regions with 5,041,140 variant sites in the Chinese Spring 1.1 reference genome, and 196,943 high-confidence probe regions from other genomes were finally screened.

[0022] In some specific implementations, in step S5, mutation sites with a PROVEAN score less than or equal to -2.5 and a SIFT value less than 0.05 are defined as harmful mutation sites.

[0023] In some specific implementations, step S6 involves 3418 genetic loci associated with 22 important wheat yield and quality traits.

[0024] This invention also provides a wheat ultra-high density SNP chip, which is prepared by the method described above.

[0025] This invention also provides a method for detecting wheat genotypes, which uses the ultra-high density SNP chip to scan wheat germplasm resources and obtain genotype information of variant sites.

[0026] The variation data in the examples comes from: 652One set of wheat resequencing data is from (Hao C, Jiao C, Hou J, et al. Resequencing of 145 landmark cultivars reveals asymmetric sub-genome selection and strong founder genotype effects on wheat breeding in China[J]. Molecular plant, 2020, 13(12): 1733-1751( 145 copies ); Zhou Y, Zhao X, Li Y, et al. Triticum population sequencing provides insights into wheat adaptation[J]. Nature genetics, 2020, 52(12): 1412-1422( 414 copies ); Cheng H, Liu J, Wen J, et al. Frequent intra-and inter-species introgression shapes the landscape of genetic variation in bread wheat[J]. Genome biology, 2019, 20(1): 1-16( 93 copies ); 1390 copies The wheat exons are from (Pont C, Leroy T, Seidel M, et al. Tracing the ancestry of modern bread wheats[J]. Nature genetics, 2019, 51(5): 905-911 (500 copies) ; He F, Pasam R, Shi F, et al. Exome sequencing highlights the role of wild-relative introgression in shaping the adaptive landscape of the wheat genome[J]. Nature Genetics, 2019, 51(5): 896-904 (890 copies);Sequencing data and samples cover major domestic varieties, core parent lines, local varieties, major foreign varieties, breeding materials, and other resources. Redundant parts have been removed, and all data are second-generation sequencing data.

[0027] This invention, based on pan-genome information, utilizes resequencing data and exon capture sequencing data from large-scale natural populations for variation analysis to obtain large-scale genome-wide variation information. High-quality SNPs and INDEL loci, representative of both the population and individuals, are filtered and screened. Polymorphic loci regions are identified by combining genome annotation and variation annotation. Simultaneously, the importance of gene function changes caused by variation sites is predicted, i.e., harmful mutation site prediction, to assess the importance of variation sites. Finally, by integrating the genetic loci previously associated by the applicant that regulate important agronomic and quality traits, the above genetic information is synthesized at the pan-genome level to synthesize an ultra-high-density liquid-phase probe. The specific implementation is as follows: Step 1: Based on the Chinese spring reference genome, variant analysis was performed using wheat natural population resequencing data and exon capture sequencing data.

[0028] Following the recommended practices for Germline SNP & Indel Discovery in WholeGenome and Exome Sequence in the GATK software developed by the Broad Institute (https: / / gatk.broadinstitute.org / hc / en-us), this study performed alignment analysis and variant site screening and filtering on the reference genome of the filtered wheat natural population resequencing data and exon capture sequencing data. Specifically, this included using BWA software to align the sequencing data to the Chinese spring reference genome, using Picard software to remove repetitive sequences, re-align indel regions, and perform baseline correction, using GATK software for population variant site screening (variant calling), and using Picard software for filtering.

[0029] The Chinese Spring reference genome includes the Chinese Spring RefSeq v1.1 version and the Chinese Spring RefSeq v2.1 version.

[0030] Step 2: Extract the reads that failed to align to the Chinese spring reference genome in Step 1, as well as the low-quality reads that did align to the Chinese spring reference genome. Use a pangenome composed of several recently published wheat reference genomes, including fielder (Sato et al., DNA Research, 2021, 28(3): dsab008), dsab008 (Jia et al., Molecular Plant, 2023, 16, 1893-1910), dsab008 (Shi et al., Molecular Plant, 2022, 15, 1440-1456), and dsab008 (Li et al., Plant Communication, 2025). Genomes of ArinaLrFor_v3, Cadenza_v1, CDC_Landmark_v1, CDC_Stanley_v1, Claire_v1, Jagger_v1, Julius_v1, LongReach_Lancer_v1, Mace_v1, Norin61_v1, SY_Mattis_v1, PI190962_v1, BJ8, MZM, XN6028, Abo, NC4, YM158, XY6, AMN, JM47, S4185, CM42, JM22, KF11, ZM366, ZM16, ZM22, and HD6172 (Walkowiak et al., Nature, 2020, 588, 277-283; Jiao et al., Nature, 2025, 637). (384-393), and perform comparative analysis of variants and variant site screening and filtering again. Step two is repeated in multiple different reference genomes. The Chinese spring reference genome in step one and the wheat genome in step two form a wheat pangenome. In this step, reads that failed to align to the Chinese spring reference genome are extracted to align them with multiple other wheat genomes, with the aim of mining variant sites and avoiding the problem of insufficient detection by a single reference genome; low-quality reads that align to the Chinese spring reference genome are extracted to obtain more accurate variant location information in the pangenome.

[0031] The aforementioned variant sites include SNP sites and INDEL sites.

[0032] Step 3: Construct a pan-genome SNP annotation database and use snpEffv4.3 (Cingolani et al. A program for annotating and predicting the effects of single nucleotide polymorphisms, SnpEff: SNPs in the genome of Drosophila melanogaster strainw1118; iso-2; iso-3[J]. Fly, 2012, 6(2): 80-92) software to perform functional annotation on variant sites.

[0033] Step 4: Perform site screening on SNPs / Indels within a 2K range upstream and downstream of all annotated genes, prioritizing them as follows: SNPs / Indels within the CDS region > SNPs / Indels within 1K upstream and downstream of the CDS > SNPs / Indels within 2K upstream and downstream of the CDS. The genes listed above are all annotated genes from the Chinese Spring reference genome (V1.1 and V2.1), including both high-confidence and low-confidence genes (HC+LC).

[0034] Step 5: Detrimental mutation sites were predicted using PROVEAN (V1.1.4) software (Choil et al., PloSONE, 2012, 7, e46688) and SIFT 4G software (Vaser et al., Nature Protocols, 2016, 11, 1-9). Detrimental mutation sites were defined as those with a PROVEAN score of less than or equal to -2.5 and a SIFT value of less than 0.05.

[0035] Step 6: Based on the applicant's two previously published SCI papers (Sun et al., Genome-wide association study for 13 agronomic traits reveals distribution of superior alleles in bread wheat from the Yellow and Huai Valley of China, 2017, PlantBiotechnology Journal, 15, 953–969.; Sun et al., Reconciliation of wheat 660K and 90K SNP arrays and their utilization in dough rheological properties of bread wheat, 2025, Journal of Advanced Research, 1-13), 22 genetic loci related to important yield and quality traits of wheat were integrated and extracted.

[0036] Step 7: Design and synthesize probe sequences for the regions covered by the SNP / Indel sites selected in Steps 4, 5, and 6.

[0037] Based on the aforementioned wheat ultra-high density microarray fabrication method, 800,000 probes were designed within the gene and upstream / downstream regions. To avoid skewed label distribution, 50,000 probes were designed in the intergenic region. Through sequencing interval fusion, a total of 706,912 probes were finally obtained, including those based on the Chinese Spring 2.1 reference genome (https: / / www.wheatgenome.org / Resources / Sequences / RefSeq-v2.1-Assembly-and-Annotation-now-freely-available-at-URGI-and-NCBI) and annotation files. The study included 1,096,869 probe regions from the Chinese Spring 1.1 version (https: / / www.wheatgenome.org / Resources / Sequences / All-IWGSC-data-related-to-IWGSC-RefSeq-v1.0-publicly-available-at-URGI); among them, 702,503 (99.3763%) probe regions based on the Chinese Spring 2.1 version reference genome were 120bp sequencing intervals, and the remaining 4,409 probe regions were sequencing intervals smaller than 120bp. All variant sites within these intervals could be obtained through sequencing.

[0038] Example 1 The method for preparing wheat ultra-high density gene chip probes includes the following steps: S1. Based on the Chinese Spring reference genome, variation analysis was performed using 652 wheat natural population resequencing data and 1390 exon capture sequencing data. The raw data of resequencing and exon capture sequencing were filtered using the default parameters of FASTP software (Shifu Chen, Yanqing Zhou, Yaru Chen, Jia Gu, fastp: an ultra-fast all-in-one FASTQ preprocessor, Bioinformatics, 2018, 34(17), i884–i890).

[0039] This step specifically uses the recommended practices for Germline SNP & Indel Discovery in Whole Genome and Exome Sequence from the GATK software developed by the Broad Institute (https: / / gatk.broadinstitute.org / hc / en-us) to perform alignment analysis of the filtered wheat natural material resequencing and exon capture sequencing data with the reference genome. The procedure is as follows: (1) Resequencing data and exon capture sequencing data file segmentation of natural wheat populations Because GATK software is incompatible with chromosome genome files longer than 512M, resequencing data and exon capture sequencing data from a natural wheat population need to be segmented before alignment analysis can begin. The principle of segmentation is that the segmentation point should not be near genes, ideally near the centromere in a set of repetitive sequences or in a region with a large number of "N"s in the genome. When selecting a segmentation point in a region with a large number of "N"s in the genome, seqtk (https: / / github.com / lh3 / seqtk) is used to scan and screen for "N" regions throughout the genome, and the segmentation site is selected in conjunction with the regions marked by RepeatMask. To further accelerate the process, this embodiment selects a segmentation point in a region with a large number of "N"s in the genome. For the segmented resequencing and exon capture sequencing data, a target is provided to output the specified region, resulting in a segmented genome FASTA file.

[0040] (2) Map to reference: Aligning sequencing data to the Chinese spring reference genome Using the default parameters of BWA software (https: / / github.com / lh3 / bwa), the filtered wheat natural material resequencing and exon capture sequencing data were compared with the Chinese Spring 1.1 and Chinese Spring 2.1 reference genomes to obtain bam files.

[0041] (3) Mark Duplicates: Remove duplicate sequences The PCR repetitive sequences were removed using the default parameters of the Picard software (https: / / broadinstitute.github.io / picard / ) to obtain a PCR-free BAM file.

[0042] (4) Realign Indels: Realign Indels The Indel region was re-aligned using the default parameters of the Picard software to obtain the score file.

[0043] (5) Recalibrate Base: Baseline Correction Baseline correction was performed using the default parameters of the Picard software to obtain the corrected BAM file.

[0044] (6) Use GATK software to perform population variation site mining (variant calling) and filtering: ①Call Variants: Discovering variant sites The haplotypecaller tool in GATK software is used to generate call variants, with the standard being MQ>=50 && BQ>=20, resulting in a GVCF file.

[0045] MQ is a score given to reads that are aligned to the reference genome, with a maximum score of 60.

[0046] BQ is a quality score for sequencing reads.

[0047] ②VCF Quality filter: Quality control The VCF Quality filter was performed using Picard software, with the standard being QUAL>=100 || DP>=5, resulting in the hp.vcf.gz file.

[0048] The SNPs and INDEL sites obtained after screening with GATK software and filtering with Picard software are high-quality SNPs and INDEL sites.

[0049] S2. Extract the reads that could not be mapped to the Chinese Spring reference genome and low-quality mapped reads (MQ < 10) in S1, and use other wheat reference genomes, such as the wheat 10+ genome, including ArinaLrFor_v3, Cadenza_v1, CDC_Landmark_v1, CDC_Stanley_v1, Claire_v1, Jagger_v1, Julius_v1, LongReach_Lancer_v1, Mace_v1, Norin61_v1, SY_Mattis_v1, PI190962_v1 (Walkowiak S, Gao L, Monat C, et al. Multiple wheat genomes reveal global variation in modern breeding[J]. Nature, 2020, 588(7837): 277-283.); and the fielder genome (Sato K, Abe F, Mascher M, et al. Chromosome-scale genome assembly of the transformation-amenable common wheat cultivar ‘Fielder’[J]. DNA Research, 2021, 28(3): dsab008.) to perform sequence alignment analysis, variant site screening and filtering again for Aikang 58, Kenong 9204, Zhou 8425B, BJ8, MZM, XN6028, Abo, NC4, YM158, XY6, AMN, JM47, S4185, CM42, JM22, KF11, ZM366, ZM16, ZM22 and HD6172. Repeat this step in the pan-genome composed of the above genomes to obtain the uni.vcf.gz file.

[0050] S3. Construct a Chinese spring and pan-genome SNP annotation database. Use snpEffv4.3 (Cingolani P,Platts A, Wang LL, et al. A program for annotating and predicting the effects of single nucleotide polymorphisms, SnpEff: SNPs in the genome of Drosophila melanogaster strain w1118; iso-2; iso-3[J]. Fly, 2012, 6(2): 80-92.) software to perform functional annotation on variant sites and obtain the ann.vcf.gz file.

[0051] S4. Site screening was performed on SNPs / Indels within a 2K range upstream and downstream of the gene, with the priority order as follows: SNPs / Indels within the CDS region > SNPs / Indels within 1K upstream and downstream of the CDS > SNPs / Indels within 2K upstream and downstream of the CDS. Ultimately, 706,912 probe regions with 1,738,820 variant sites were identified in the Chinese Spring 2.1 reference genome; 1,096,869 probe regions with 5,041,140 variant sites were identified in the Chinese Spring 1.1 reference genome; other genomes, including ArinaLrFor_v3, Cadenza_v1, CDC_Landmark_v1, CDC_Stanley_v1, Claire_v1, Jagger_v1, and Julius_... The targets.bed file was obtained from 196,943 HC probe regions, including v1, LongReach_Lancer_v1, Mace_v1, Norin61_v1, SY_Mattis_v1, PI190962_v1, fielder, Aikang58, Kenong9204, Zhou8425B, BJ8, MZM, XN6028, Abo, NC4, YM158, XY6, AMN, JM47, S4185, CM42, JM22, KF11, ZM366, ZM16, ZM22, and HD6172.

[0052] S5. The extracted variant sites were predicted as harmful mutation sites using PROVEAN (V1.1.4) software and SIFT 4G software, respectively. Variants with a PROVEAN score of less than or equal to -2.5 and a SIFT value of less than 0.05 were defined as harmful mutation sites, and the harmful mutation map deleteerious.map file was obtained, yielding 329,008 harmful mutation sites.

[0053] S6. Based on the applicant's two previously published SCI papers (Sun et al., Genome-wide association study for 13 agronomic traits reveals distribution of superior alleles in bread wheat from the Yellow and Huai Valley of China, 2017, PlantBiotechnology Journal, 15, 953–969.; Sun et al., Reconciliation of wheat 660K and 90K SNP arrays and their utilization in dough rheological properties of bread wheat, 2025, Journal of Advanced Research, 1-13.), 22 genetic loci related to important yield and quality traits in wheat were integrated and extracted, including 13 yield-related traits and 9 quality-related traits.The genetic loci for yield-related traits were obtained from the literature (Sun et al., Genome-wide association study for 13 agronomic traits reveals distribution of superior alleles in bread wheat from the Yellow and Huai Valley of China, 2017, Plant Biotechnology Journal, 15, 953–969.), namely 89 loci for flag leaf direction, 86 loci for flag leaf angle, 112 loci for grain length, 161 loci for number of spikelets per spike, 167 loci for grain weight per spike, 238 loci for grain width, 143 loci for plant height, 129 loci for spike length, 159 loci for number of fertile spikelets, 81 loci for number of sterile spikelets, 116 loci for total number of spikelets, 121 loci for 1000-grain weight, and 167 loci for length of internode below spike. The genetic loci for quality-related traits were obtained from the literature (Sun et al., Reconciliation of wheat 660K and 90K SNP arrays and their utilization in dough rheological properties). (ofbread wheat, 2025, Journal of Advanced Research, 1-13.), which identified 178 genetic loci for dough stability time, 111 genetic loci for water absorption, 640 genetic loci for C1, 55 genetic loci for C2, 28 genetic loci for C3, 66 genetic loci for C4, 27 genetic loci for C5, 446 genetic loci for C2-C1, and 98 genetic loci for C4-C3, totaling 3418 genetic loci. This yielded the trait.bed file, and these genetic loci will significantly improve the detection reliability of the designed chip.

[0054] S7. High-density probes are designed and synthesized for the regions covered by the SNP / Indel sites, harmful mutation sites, and trait-related sites selected in S4, S5, and S6 to obtain probes for wheat exon sequencing gene localization, i.e., ultra-high-density gene chips.

[0055] It should be noted that: (1) Use the standard variation analysis procedure to perform variation analysis on the Chinese Spring reference genome or other genomes. The first analysis can be performed according to the MQ>=30 standard.

[0056] (2) Filtering of variant sites in the Chinese spring reference genome, filtering in the population: MF>0.005&MISSING<=0.3.

[0057] (3) Other reference genomic variant sites are filtered in the population: MF>0.001.

[0058] Example 2 Genotypes of wheat germplasm resources from the Huang-Huai wheat region were obtained by scanning the gene chip prepared in Example 1, followed by population analysis and gene mapping analysis. (1) Selection of test materials To obtain extensive genetic variation information, 131 (ZZ1~ZZ131) important genetic resource materials from the Yellow and Huai Valley of China were selected based on the genetic background, kinship, approval date, planting area, and agronomic traits of the varieties. For details of the materials, please refer to (Sun C, Zhang F, Yan X, et al. Genome‐wide association study for 13agronomic traits reveals distribution of superior alleles in bread wheat from the Yellow and Huai Valley of China[J]. Plant biotechnology journal, 2017, 15(8): 953-969.).

[0059] (2) Genotyping Using the 706,912 probe regions of the Chinese Spring 2.1 version reference genome obtained in Example 1, variant sites were detected in 131 genetic resource materials. The distribution density of variant sites per 1 MB interval on the chromosome is shown in [Figure 1]. Figure 2 .

[0060] (3) Comparison of ultra-high density SNP chip and wheat 660K chip The Wheat 660K chip is currently the most widely used wheat SNP chip in the field of wheat breeding. A density comparison between the ultra-high density SNP chip obtained in Example 1 and the Wheat 660K chip is shown below. Figure 3 .Depend on Figure 3 It can be concluded that the probe density of the wheat ultra-high density gene chip prepared in Example 1 is significantly higher than that of the 660K chip.

[0061] (4) Application of high-density probes in gene localization The plant height phenotype of 131 tested materials in Example 2 was investigated, and genome-wide association analysis was performed using the detected genotype information to identify important genetic loci regulating plant height. Figure 4 Manhattan plots of plant height for 131 tested materials. SNP loci significantly associated with the target trait (plant height) were detected on chromosomes 2B, 3B, and 7D.

[0062] Obviously, the above embodiments of the present invention are merely examples for clearly illustrating the present invention, and are not intended to limit the implementation of the present invention. For those skilled in the art, other variations or modifications can be made based on the above description. It is neither necessary nor possible to exhaustively describe all embodiments here. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of the present invention should be included within the scope of protection of the claims of the present invention.

Claims

1. A method for preparing a probe for a wheat ultra-high density gene chip, characterized by, Includes the following steps: S1. Based on the Chinese spring reference genome, variation analysis was performed using wheat natural population resequencing data and exon capture sequencing data to obtain high-quality SNP and INDEL sites. S2. Extract the sequencing reads that failed to be aligned to the Chinese spring reference genome in step S1 and the low-quality aligned reads, and perform sequence alignment analysis and variant site screening and filtering again using other wheat reference genomes in the pan-genome. S3. Construct a Chinese spring and pan-genome SNP annotation database and perform functional annotation of variant sites; S4. SNPs / Indels within a 2K range upstream and downstream of the gene coding sequence are screened. SNPs / Indels within the gene coding sequence region are preferentially retained, followed by SNPs / Indels within a 1K range upstream and downstream of the gene coding sequence, and then SNPs / Indels within a 2K range upstream and downstream of the gene coding sequence. S5. The discovered variant sites were predicted as harmful mutation sites using PROVEAN software and SIFT 4G software, respectively, and harmful mutation sites were screened out. S6. Integrate and extract genetic loci related to important yield and quality traits in wheat; S7. High-density probes are designed and synthesized for the regions covered by the SNP / Indel sites, harmful mutation sites, and trait-related sites obtained in steps S4, S5, and S6 to obtain an ultra-high-density SNP chip for wheat exon sequencing gene localization.

2. The production method according to claim 1, characterized by, In step S1, the specific procedure for the variation analysis includes: The raw data from resequencing and exon capture sequencing are filtered using the default parameters of the FASTP software. The filtered sequencing data were compared with the Chinese spring reference genome using the default parameters of BWA software to obtain the bam file; PCR repetitive sequences were removed using the default parameters of Picard software, and the Indel region was re-aligned and baseline corrected. The haplotypecaller tool in GATK software was used to mine variant sites, with the standard being MQ≥50 and BQ≥20, to obtain GVCF files. Picard software was used for VCF quality filtering, with the standard being QUAL≥100 or DP≥5, to obtain high-quality SNP and INDEL sites. The filtering criteria for reference genome variant sites in the Chinese spring genome in the population are: MF>0.005 and MISSING≤0.

3.

3. The production method according to claim 2, characterized by, In step S1, before performing alignment analysis using GATK software, the sequencing data needs to be segmented because GATK software is incompatible with chromosome genome files longer than 512M. The split points were selected in regions of the genome with a large number of "N"s or near the centromere in repetitive sequence clusters. The whole genome "N" regions were scanned and screened using seqtk, and the split sites were selected by combining the regions marked by RepeatMask.

4. The preparation method according to claim 1, characterized in that, In step S2, other wheat reference genomes in the pan-genome include wheat 10+ genome, fielder genome, dwarf 58, Kenong 9204, Zhou 8425B, BJ8, MZM, XN6028, Abo, NC4, YM158, XY6, AMN, JM47, S4185, CM42, JM22, KF11, ZM366, ZM16, ZM22 and HD6172; The wheat 10+ genome includes ArinaLrFor_v3, Cadenza_v1, CDC_Landmark_v1, CDC_Stanley_v1, Claire_v1, Jagger_v1, Julius_v1, LongReach_Lancer_v1, Mace_v1, Norin61_v1, SY_Mattis_v1, and PI190962_v1; The filtering criterion for other reference genomic variant sites in the population is: MF>0.

001.

5. The preparation method according to claim 1, characterized in that, In step S3, snpEff software is used to perform functional annotation on the variant sites.

6. The method of claim 1, wherein, In step S4, 706,912 probe regions with 1,738,820 variant sites in the Chinese Spring 2.1 reference genome, 1,096,869 probe regions with 5,041,140 variant sites in the Chinese Spring 1.1 reference genome, and 196,943 high-confidence probe regions from other genomes were finally screened.

7. The preparation method according to claim 1, characterized in that, In step S5, mutation sites with a PROVEAN score less than or equal to -2.5 and a SIFT value less than 0.05 are defined as harmful mutation sites.

8. The preparation method according to claim 1, characterized in that, In step S6, 3418 genetic loci related to 22 important wheat yield and quality traits were identified.

9. A wheat-based ultra-high density SNP chip, characterized in that, Prepared by the method described in any one of claims 1-8.

10. A method for detecting wheat genotypes, characterized in that, The ultra-high density SNP chip described in claim 9 was used to scan wheat germplasm resources to obtain genotype information of variant sites.

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