Gibberellic disease resistance association interval Meta analysis method based on wheat natural population whole genome association analysis and application of Gibberellic disease resistance association interval Meta analysis method

Abstract

The invention discloses a gibberellic disease resistance correlation interval Meta analysis method based on wheat natural population whole genome correlation analysis and application, and 64 gibberellic disease resistance related Meta intervals are obtained by integrating multiple gibberellic disease resistance whole genome correlation analysis results through Meta analysis. Compared with the Meta research result of an amphiphilic parent derived wheat genetic population in the prior art, 54.7% of the new QTL loci are new QTL loci, and the rest 45.3% of the new QTL loci are consistent with the research result of the wheat amphiphilic parent genetic population. The Meta analysis method provided by the invention can provide more accurate targets and associated markers for breeding of wheat varieties resistant to gibberellic disease, and is expected to further improve the efficiency of molecular marker-assisted selection breeding resistant to gibberellic disease. And the Meta analysis method can be expanded and applied to GWAS analysis results of importance characters of different crops, and has a wide application prospect.

Description

Technical Field

[0001] The present invention belongs to the technical field of data analysis, and in particular relates to a meta-analysis method and application of association intervals of fusarium head blight resistance based on whole genome association analysis of natural wheat populations. Background Art

[0002] Wheat (Triticum aestivum L.) is one of the world's major food crops, and its yield and quality have an important impact on global food security. However, wheat production is often attacked by a variety of diseases, and Fusarium head blight (FHB) is one of the most destructive diseases. Fusarium head blight not only causes a significant decrease in wheat yield, but also produces fungal toxins (such as vomitoxin), which endangers the health of humans and animals. Therefore, cultivating wheat varieties resistant to Fusarium head blight is one of the important goals of wheat breeding research.

[0003] The core of wheat disease resistance breeding lies in accurately identifying and utilizing quantitative trait loci (QTLs) associated with disease resistance traits. Traditional QTL mapping methods rely on genetic populations derived from two parents. Such populations are limited by the genetic background of the parents and the few polymorphic sites of the parents, so the research results often vary greatly between different populations. To solve this problem, genome-wide association studies (GWAS) have been widely used in recent years. They can efficiently screen genetic variations associated with target traits in many breeding populations with different genetic backgrounds. However, GWAS results are often inconsistent due to differences in population source, size, experimental conditions and environment, making it difficult to compare and utilize the research results.

[0004] In order to improve the accuracy and stability of the results of association interval positioning, Meta-analysis has become an effective solution. Meta-analysis improves the credibility of QTL positioning results by integrating published research results. This method has been widely used in genetic populations derived from parents of various crops, but there is no precedent for its application in natural populations of crops (including wheat). The main reason is that the results of GWAS analysis give associated molecular marker sites rather than intervals.

[0005] CN113113086A discloses a dsMQTL analysis method for wheat resistance to Fusarium fusarium head blight. However, the identification of Fusarium fusarium head blight (FHB) resistance loci in this method is mainly concentrated on a specific wheat genetic population derived from two parents, and its scope is limited to a very small number of specific varieties. Due to the limited DNA differences between the two parents and the narrow genetic background, more stable genetic loci cannot be discovered. Summary of the invention

[0006] In view of the shortcomings of the prior art, the present invention provides a Meta-analysis method and application of association intervals for fusarium spp. resistance based on whole-genome association analysis of wheat natural populations. The results of multiple whole-genome association analyses of fusarium spp. resistance are integrated through Meta-analysis, and new association intervals that are different from those reported in parental mapping populations and stably associated with fusarium spp. resistance are screened and mined, thereby providing new target sites for improving fusarium spp. resistance and providing important information for genetic research on fusarium spp. resistance and precision breeding.

[0007] The present invention is achieved through the following technical solutions:

[0008] A meta-analysis method for association intervals of fusarium head blight resistance based on whole genome association analysis of natural wheat populations, comprising the following steps:

[0009] Step 1) searching in the data knowledge service platform based on key search terms to screen out corresponding literature, wherein the key search terms are: wheat, fusarium head blight, and whole genome association analysis;

[0010] Step 2) The screened literature was collected, and the titles, years, SNP names, left position of the association interval, right position of the association interval, peak position of the association interval, SNP P value and PVE value of the collected literature were sorted and summarized to obtain the original association interval; for the original association interval whose physical position on one side was unclear or only the SNP position was known, the association interval position was derived using the wheat linkage disequilibrium decay distance; the sorted data was converted to physical position according to the wheat variety Chinese Spring sequencing map IWGSC RefSeqv2.1;

[0011] Step 3) Import the sorted data into amMQTL software, and use the least squares method to build a model to obtain four models: Model1-amMQTL, Model2-amMQTL, Model3-amMQTL, and Model4-amMQTL. There will be 1, 2, 3, and 4 amMQTL on each chromosome;

[0012] Step 4) Perform fitting tests on the four models respectively, select the model that best fits the QTL reliability accumulation curve, and screen the final output Meta QTL to obtain the Meta analysis results.

[0013] Preferably, the criteria for literature screening in step 1) are: ① only natural populations are selected for wheat populations; ② wheat fusarium head blight resistance traits only focus on wheat resistance to expansion and antitoxin accumulation; ③ only SNP results are focused on in GWAS articles; ④ reproducible SNP association results are selected.

[0014] Preferably, the literature in step 1) is 11 domestic and foreign publicly published literature on GWAS research on natural populations of wheat fusarium wilt, excluding literature on linkage analysis and QTL verification.

[0015] Preferably, the screening criteria in step 4) are: ① the accumulation curve of QTL confidence is clustered into peaks and the model can be fitted; ② an amMQTL has at least 2 original physical intervals that are completely or partially overlapped.

[0016] Preferably, the Meta-analysis results of step 4) include 64 Meta-association intervals, 35 of which are new stable Meta-association intervals associated with wheat resistance to ergot, and the remaining 29 are consistent with the Meta-study results of genetic populations derived from wheat parents.

[0017] Preferably, the information of the 35 new stable Meta association intervals associated with wheat resistance to scab is as follows:

[0018]

[0019] The application of the above-mentioned meta-analysis method of association intervals for fusarium wilt resistance based on whole-genome association analysis of natural wheat populations in wheat breeding for fusarium wilt resistance: the obtained meta-analysis results are used for molecular marker-assisted selection in wheat breeding for fusarium wilt resistance.

[0020] The beneficial effects of the present invention are as follows:

[0021] (1) Compared with CN113113086A, the invention provides a meta-analysis method for association intervals of fusarium head blight resistance based on whole-genome association analysis of natural wheat populations. The innovation lies in utilizing natural wheat populations from published literature, involving 2,672 wheat varieties, and with a wide range of sources. By integrating and meta-analyzing fusarium head blight resistance loci in these diverse genetic backgrounds, the reliability of loci-association loci is improved, providing more available reliable target loci for breeding wheat varieties resistant to fusarium head blight.

[0022] (2) The Meta-analysis method of association intervals of resistance to fusarium head blight based on whole-genome association analysis of natural wheat populations provided by the present invention collects and integrates 11 literatures on whole-genome association analysis of natural wheat fusarium head blight populations, performs Meta-analysis on the association intervals located in these studies, and obtains 64 Meta-intervals related to resistance to fusarium head blight. Compared with the results of the Meta-study of wheat genetic populations derived from two parents in the prior art, 4.7% are new QTL loci, and the remaining 45.3% are consistent with the research results of wheat genetic populations with two parents. The Meta-analysis method of the present invention can provide more accurate targets and their associated markers for the breeding of wheat varieties resistant to fusarium head blight, and is expected to further improve the efficiency of molecular marker-assisted selection breeding for resistance to fusarium head blight. In addition, the Meta-analysis method of the present invention can be extended to the GWAS analysis results of important traits of different crops, and has broad application prospects. DETAILED DESCRIPTION

[0023] The present invention is further described in detail below with reference to specific embodiments.

[0024] Example 1

[0025] A meta-analysis method for association intervals of fusarium head blight resistance based on genome-wide association analysis of natural wheat populations, the specific steps are as follows:

[0026] 1. Data collation

[0027] This example retrieved relevant literature from 2001 to the present from English literature websites such as Google scholar and Pubmed using "wheat, Fusarium head blight (FHB), genome-wide association analysis (GWAS)" as key search terms. Literature screening criteria: ① Only natural populations were selected for wheat populations; ② Only wheat anti-expansion and antitoxin accumulation were focused on for wheat Fusarium head blight resistance traits; ③ Only SNP results were focused on in GWAS articles; ④ Reproducible SNP association results were selected.

[0028] Based on the above screening criteria, 11 articles were finally included. Microsoft Excel 2021 software was used to sort out the titles, years, SNP names, left position of the association interval, right position of the association interval, Peak position of the association interval, SNP P value, and PVE value of the included articles, and finally 107 original association intervals were summarized. For the original association intervals where the physical position on one side is unclear or only the SNP position is known, the wheat linkage disequilibrium (LD) decay distance is used to derive the association interval position. According to the wheat variety Chinese Spring sequencing map IWGSC RefSeq v2.1, the sorted data were physically converted.

[0029] 2. Meta-analysis

[0030] This embodiment uses amMQTL 1.1 analysis software developed based on python language. In the software, it is assumed that QTL is normally distributed with peak as the center, and its variance is estimated by QTL data of the same chromosome, and the model is constructed by least square method. The data sorted and summarized in Excel are input into the program, and the four models Model1-amMQTL, Model2-amMQTL, Model3-amMQTL, and Model4-amMQTL are obtained in the preliminary operation of the program. There will be 1, 2, 3, and 4 amMQTL on each chromosome.

[0031] The four models were fitted and tested respectively, and the model that best fits the QTL reliability accumulation curve was selected, and the final output Meta QTL was screened. The screening criteria were as follows: ① The accumulation curve of QTL confidence is clustered into a peak, and the model can be fitted; ② An amMQTL has at least two completely or partially overlapping original physical intervals.

[0032] 3. Meta-analysis results

[0033] This example systematically searches for literature related to wheat scab GWAS reported from 2001 to date, and retrieves 11 articles in total, involving 2672 resistant varieties or strains, and a total of 107 association intervals. After Meta-analysis, 64 Meta-association intervals were obtained, of which 35 were new stable Meta-association intervals associated with wheat scab resistance, and the remaining 29 were consistent with the results of the Meta study of genetic populations derived from wheat parents, proving the reliability of the method of the present invention.

[0034] The information of the new stable Meta association intervals of 35 wheat scab resistance associations based on IWGSC RefSeq v2.1 is shown in Table 1:

[0035] Table 1 Meta-analysis results

[0036]

[0037]

[0038] The above experimental results prove that the method of the present invention can provide accurate and reliable association intervals for resistance to scab, providing a reference for molecular marker-assisted selection in disease-resistant wheat breeding. At the same time, the method of the present invention can be extended to the GWAS analysis results of important traits of different crops, and has broad application prospects.

[0039] The embodiments described above are only some embodiments of the present invention, rather than all embodiments. The detailed description of the embodiments of the present invention is not intended to limit the scope of the invention claimed for protection, but merely represents selected embodiments of the present invention. The scope of protection of the present invention shall be subject to the scope required by the claims. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work shall fall within the scope of protection of the present invention.

Claims

1. A Meta-analysis method for association intervals of fusarium head blight resistance based on whole genome association analysis of natural wheat populations, characterized in that: The following steps are involved: Step 1) searching in the data knowledge service platform based on key search terms to screen out corresponding literature, wherein the key search terms are: wheat, fusarium head blight, and whole genome association analysis; Step 2) The screened literature was collected, and the titles, years, SNP names, left position of the association interval, right position of the association interval, peak position of the association interval, SNP P value and PVE value of the collected literature were sorted and summarized to obtain the original association interval; for the original association interval whose physical position on one side was unclear or only the SNP position was known, the association interval position was derived using the wheat linkage disequilibrium decay distance; the sorted data was converted to physical position according to the wheat variety Chinese Spring sequencing map IWGSC RefSeq v2.1; Step 3) Import the sorted data into amMQTL software, and use the least squares method to build a model to obtain four models: Model1-amMQTL, Model2-amMQTL, Model3-amMQTL, and Model4-amMQTL. There will be 1, 2, 3, and 4 amMQTL on each chromosome; Step 4) Perform fitting tests on the four models respectively, select the model that best fits the QTL reliability accumulation curve, and screen the final output Meta QTL to obtain the Meta analysis results.

2. The method of meta-analysis of association intervals of fusarium resistance based on genome-wide association analysis of natural wheat populations according to claim 1, characterized in that: The criteria for literature screening in step 1) are as follows: ① only natural populations are selected for wheat populations; ② wheat fusarium head blight resistance traits only focus on wheat resistance to expansion and toxin accumulation; ③ only SNP results are focused on in GWAS articles; ④ reproducible SNP association results are selected.

3. The method of Meta-analysis of association intervals of fusarium head blight resistance based on whole genome association analysis of natural wheat populations according to claim 2, characterized in that: The literature in step 1) is 11 domestic and foreign publicly published literature on GWAS research on natural populations of wheat fusarium wilt, excluding literature on linkage analysis and QTL verification.

4. The method of meta-analysis of association intervals of fusarium head blight resistance based on whole genome association analysis of natural wheat populations according to claim 1, characterized in that: Step 4) The screening criteria are: ① the accumulation curve of QTL confidence is clustered into a peak and the model can be fitted; ② an amMQTL has at least 2 original physical intervals that are completely or partially overlapped.

5. The method of Meta-analysis of association intervals of fusarium head blight resistance based on whole genome association analysis of natural wheat populations according to claim 4, characterized in that: Step 4) The meta-analysis results include 64 meta-association intervals, of which 35 are new stable meta-association intervals associated with wheat resistance to ergot, and the remaining 29 are consistent with the results of the meta-study of genetic populations derived from wheat parents.

6. The method of meta-analysis of association intervals of fusarium head blight resistance based on whole genome association analysis of natural wheat populations according to claim 5, characterized in that: The information of the 35 new stable Meta association intervals associated with wheat resistance to fusarium head blight is as follows:

7. The application of a meta-analysis method for association intervals of fusarium head blight resistance based on genome-wide association analysis of natural wheat populations as described in any one of claims 1 to 6 in wheat breeding for fusarium head blight resistance, characterized in that: The meta-analysis results obtained were used for molecular marker-assisted selection in wheat breeding for resistance to Fusarium fusarium.

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