Method for mining core hotspot genes based on population transcriptome and application of method in plant molecular breeding

Abstract

The invention discloses a method for mining a core hot spot gene based on a population transcriptome and application of the method in plant molecular breeding, and the method comprises the following steps: S1, processing and sampling a rice population under different nitrogen conditions to obtain a rice sample; and S2, carrying out differential expression gene analysis on the rice sample to obtain the group nitrogen response gene. And S3, carrying out correlation analysis on the expression level of the group nitrogen response gene as a molecular phenotype and genetic variation to obtain an expression quantitative character site of the group nitrogen response gene. And S4, screening out eGWAS hot spot regions according to expression quantitative character sites. And S5, performing eTWAS analysis on the group nitrogen response gene to obtain an eTWAS result. And step S6: screening out an eTWAS hot spot gene from an eTWAS result. And step S7, taking the intersection of the eTWAS hot spot gene and the gene in the eGWAS hot spot region to obtain a core hot spot gene. Through eGWAS-eTWAS conjoint analysis, core hotspot genes for regulating and controlling important biological pathways can be efficiently and accurately mined.

Description

Technical Field

[0001] The present invention belongs to the technical field of plant molecular breeding, and specifically relates to a method for mining core hotspot genes based on population transcriptome and an application thereof in plant molecular breeding. Background Art

[0002] GWAS (Genome-Wide Association Studies) and eGWAS (Gene expression-based genome-wide association study) mainly locate related sites and regions by analyzing the statistically significant association between SNP (Single Nucleotide Polymorphism) linkage blocks and traditional phenotypes or gene expression levels. However, due to the linkage between variants, it is difficult to accurately and efficiently locate the causal gene.

[0003] Therefore, a method is needed to quickly mine hotspot regulatory regions and genes and analyze causal regulatory networks. Summary of the invention

[0004] In view of the above problems, the first object of the present invention is to provide a method for mining core hotspot genes based on population transcriptome, and the second object is to provide an application of plant molecular breeding. The present invention takes rice as the research object, performs whole genome resequencing and root transcriptome sequencing under different nitrogen conditions, and can quickly mine the hotspot regulatory regions and genes of rice and analyze the causal regulatory network of rice. To achieve the above objects, the technical solution adopted by the present invention is:

[0005] Methods for mining core hotspot genes based on population transcriptomes include:

[0006] Step S1: treating and sampling a rice population under different nitrogen conditions to obtain a rice sample;

[0007] Step S2: performing differentially expressed gene analysis on the rice sample to obtain population nitrogen response genes;

[0008] Step S3: using the expression level of the population nitrogen response gene as a molecular phenotype, and performing association analysis with genetic variation to obtain the expression quantitative trait loci of the population nitrogen response gene;

[0009] Step S4: Screening out eGWAS hotspot regions based on the expression quantitative trait loci;

[0010] Step S5: Perform transcriptome-wide association analysis on the expression of nitrogen response genes in the population to obtain eTWAS results;

[0011] Step S6: screening out eTWAS hotspot genes from the eTWAS results;

[0012] Step S7: taking the intersection of the eTWAS hotspot genes and the genes in the eGWAS hotspot region to obtain core hotspot genes; the core hotspot genes are used to regulate multiple population nitrogen response genes.

[0013] Preferably, the differentially expressed gene analysis of the rice sample to obtain population nitrogen response genes comprises:

[0014] DESeq2 software was used to analyze the differentially expressed genes in response to nitrogen for each sample, and the analysis parameters included fo l dchange and p value;

[0015] Summarize nitrogen-responsive differentially expressed genes in rice samples;

[0016] Genes showing differential expression in more than 25% of the rice samples are screened out from the nitrogen-responsive differentially expressed genes to obtain population nitrogen-responsive genes.

[0017] Preferably, the expression level of the population nitrogen response gene is used as a molecular phenotype, and an association analysis is performed with genetic variation to obtain the expression quantitative trait loci of the population nitrogen response gene, including:

[0018] Performing eGWAS analysis on the nitrogen response genes of the population to obtain eGWAS results;

[0019] Extracting SNPs with a p-value less than 1e-05 from the eGWAS results, merging sets of continuous SNP points with a distance less than 10 kb, and obtaining expression quantitative trait loci of population nitrogen response genes;

[0020] Linkage disequilibrium analysis was performed on multiple expression quantitative trait loci of the same gene, retaining r 2 <0.1 for expression quantitative trait loci;

[0021] The total number and average length of the expression quantitative trait loci of nitrogen-responsive genes in multiple populations were counted;

[0022] The rice genome was divided into multiple windows, and the number of expressed quantitative trait loci in each window was counted.

[0023] Preferably, performing eGWAS analysis on the nitrogen response genes of the population to obtain eGWAS results comprises:

[0024] Performing Box-Cox normal transformation on the expression level of the nitrogen response gene in the population to obtain a transformation result;

[0025] The conversion result is used as a phenotype and an association analysis is performed with the SNP to obtain an eGWAS result.

[0026] Preferably, the whole transcriptome association analysis of the expression of nitrogen response genes in the population is performed to obtain eTWAS results, including:

[0027] The expression of all rice genes was decomposed into cis-expression components and trans-expression components based on the genetic variation upstream and downstream of the genes using GCTA software;

[0028] The expression levels of nitrogen-responsive genes in the population were used as molecular phenotypes, and the mixed linear model of EMMAX in the R package was used for association analysis with the cis- and trans-expression components of all rice genes to obtain the eTWAS results.

[0029] Preferably, screening out eTWAS hotspot genes from the eTWAS results comprises:

[0030] From the eTWAS results, significantly associated genes with a p-value of the cis-expression component less than 0.01 and a q-value of the trans-expression component less than 0.01 were screened to obtain eTWAS hotspot genes.

[0031] Preferably, the step of processing and sampling the rice population under different nitrogen conditions to obtain the rice sample comprises:

[0032] N rice materials were treated with normal nitrogen and low nitrogen for 2 weeks respectively;

[0033] The roots of different rice varieties were sampled to obtain rice samples.

[0034] Preferably, after obtaining the rice sample, the method further comprises:

[0035] extracting total RNA from each of the rice samples;

[0036] The total RNA is sequenced to obtain an RNA sequence.

[0037] Preferably, the step of taking the intersection of the eTWAS hotspot genes and the genes in the eGWAS hotspot region to obtain core hotspot genes comprises:

[0038] The eTWAS hotspot genes are selected in the hotspot regions of the expression quantitative trait loci to obtain core hotspot genes.

[0039] A plant molecular breeding application, the application is based on any of the above methods for mining core hotspot genes based on population transcriptome.

[0040] The beneficial effects of the present invention are as follows: the present invention provides a method for mining core hotspot genes based on population transcriptome, comprising step S1: treating and sampling a rice population under different nitrogen conditions to obtain rice samples; step S2: performing differential expression gene analysis on the rice samples to obtain population nitrogen response genes; step S3: using the expression level of the population nitrogen response gene as a molecular phenotype, performing association analysis with genetic variation, and obtaining expression quantitative trait loci of the population nitrogen response gene; step S4: screening out eGWAS hotspot regions according to the expression quantitative trait loci; step S5: performing expression whole transcriptome association analysis on the population nitrogen response gene to obtain eTWAS results; step S6: screening out eTWAS hotspot genes from the eTWAS results; step S7: taking the intersection of the eTWAS hotspot genes and the genes in the eGWAS hotspot region to obtain core hotspot genes; the core hotspot genes are used to regulate multiple population nitrogen response genes. SNP-GWAS and eGWAS can locate associated sites or regions, but further analysis is required to locate key genes, and the accuracy and efficiency of gene mining need to be improved. By combining whole genome expression association analysis and whole transcriptome expression association analysis, the present invention can efficiently and accurately mine core hotspot genes that regulate important biological pathways and analyze causal regulatory networks. BRIEF DESCRIPTION OF THE DRAWINGS

[0041] The drawings herein are incorporated into and constitute a part of the specification, illustrate embodiments consistent with the present invention, and together with the specification are used to explain the principles of the present invention. In order to more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings required for use in the embodiments or the prior art description will be briefly introduced below. Obviously, for ordinary technicians in this field, other drawings can be obtained based on these drawings without creative labor.

[0042] In the attached figure:

[0043] Figure 1 This is the root eGWAS result of the population nitrogen response gene Os11t0620400-01 under low nitrogen;

[0044] Figure 2 It is the root eGWAS result of the population nitrogen response gene Os04t0269600-01 under low nitrogen;

[0045] Figure 3 It is the root eGWAS result of the population nitrogen response gene Os01t0541800-01 under low nitrogen;

[0046] Figure 4 is with Figure 1-3The eGWAS hotspot region corresponding to the eQTL hotspot on chromosome Chr11. DETAILED DESCRIPTION

[0047] The following examples are used to illustrate the present invention, but are not intended to limit the scope of the present invention. Without departing from the spirit and essence of the present invention, modifications or substitutions made to the methods, steps or conditions of the present invention all belong to the scope of protection of the present invention. Unless otherwise specified, the experimental materials, reagents, instruments, etc. used in each embodiment are commercially available; unless otherwise specified, all technical means in the embodiments of the present invention are conventional means well known to those skilled in the art.

[0048] Example 1

[0049] This embodiment provides a method for mining core hotspot genes based on population transcriptome, including:

[0050] (1) Treatment and sampling: Rice populations (159 materials) were grown under normal nitrogen (2 mM NO3 - ) and low nitrogen (0.2 mM NO3 - ) for 2 weeks. Roots of different rice varieties were then collected and total RNA from each sample was extracted for sequencing.

[0051] (2) Differential expression analysis: Salmon software was used to quantify transcriptome sequencing data based on the RAP-DB annotation version, and DESeq2 software was used to analyze differentially expressed genes for each sample, with the threshold set to fo ld change>1.2 and q<0.05. The nitrogen-responsive differentially expressed genes in the samples were summarized, and genes showing differential expression in more than 25% of the samples were retained for subsequent analysis. Finally, a set of population differentially expressed genes (DEGs) under different nitrogen treatment conditions was obtained, which was defined as population nitrogen-responsive genes.

[0052] Follow change refers to the relative change in the expression level of a gene or protein under two different conditions. In biological research, it is necessary to compare the expression changes of genes or proteins under different physiological or experimental conditions, and follow change is an indicator used to describe such changes.

[0053] The method for calculating the fo ld change is to compare the expression levels under different conditions to obtain the relative change fold, and use the following formula to calculate the fo ld change:

[0054] fo ld change = expression value of target gene in experimental group / expression value of target gene in control group;

[0055] If the expression level of the target gene in the experimental group is higher than that in the control group, the fo ld change will be greater than 1, indicating that the target gene has an up-regulated trend in the experimental group; if the expression level of the target gene in the experimental group is lower than that in the control group, the fo ld change will be less than 1, indicating that the target gene has a down-regulated trend in the experimental group; when the fo ld change is equal to 1, it means that the expression level of the target gene has not changed under the two conditions.

[0056] Combining fo ld change and p-value for differential analysis, p-value is an indicator used to determine whether there is a statistically significant difference between two sets of data, while fo ld change can be used as a supplement to p-value to quantitatively describe the magnitude of the difference. If the fo ld change of a gene or protein is greater than 2 or less than 0.5, and the p-value is less than 0.05, it can be considered that its expression is statistically significantly different.

[0057] (3) eQTL hotspot analysis: Figure 1-Figure 3 As shown, the expression levels of these genes were used as molecular phenotypes using gemma software to perform association analysis with genetic variation (SNP), namely expression genomic association study (eGWAS), to identify the expression quantitative trait loci (eQTL) regulating the nitrogen response genes of each population. The eQTLs of the nitrogen response genes of the population were summarized, including the following steps (i)-(iii):

[0058] (i) The expression levels of the nitrogen response genes in the population obtained in step (2) are subjected to Box-Cox normal transformation, and the transformation results are used as phenotypes for association analysis with SNPs, namely, expression genomic association study (eGWAS).

[0059] (ii) For the above eGWAS results, SNPs with p<1e-05 were extracted, and the continuous SNP point sets with a distance less than 10kb were merged as expression quantitative trait loci (eQTLs). The SNP with the lowest p value was taken as the leading SNP of the eQTL (l eadSNP).

[0060] (iii) Linkage disequilibrium (LD) analysis was performed on multiple eQTLs of the same gene, and r 2 <0.1 eQTL; if r 2 >0.1, the eQTL with a lower p-value of the dominant SNP is retained.

[0061] (4) The total number and average length of eQTLs for nitrogen-responsive genes in all populations were counted, the rice genome was divided into windows of 100 kb, and the number of eQTLs in each window was counted. Through 1000 permutation tests, the threshold of whether the actual window was a hotspot interval was determined to obtain the eQTL hotspot (eGWAS hot-spot).

[0062] By the above method, hotspot eQTLs regulating nitrogen response genes in multiple populations are obtained, namely eGWAS hot-spot regions. eGWAS hot-spot regions are intervals of a certain length, containing multiple genes. For example, Figure 4 The representative eGWAS hotspot region (chr11: 24175000-24195000) contains 5 genes, and the detailed information is shown in Table 1. It is necessary to further identify the hotspot genes that regulate nitrogen response genes in multiple populations in this region through eTWAS.

[0063] Table 1 Candidate genes in eGWAS hotspot regions

[0064] Gene name chromosome Starting position End position Os11g0620100 Chr11 24170641 24175621 Os11g0620200 Chr11 24178808 24179250 Os11g0620300 Chr11 24180905 24181434 Os11g0620400 Chr11 24184610 24191330 Os11g0620500 Chr11 24192113 24195295

[0065] (5) eTWAS analysis: GCTA software was used to decompose the expression of all rice genes into cis-expression components (cis-EC) and trans-expression components (trans-EC) based on the genetic variation 100k upstream and downstream of the gene. The expression of the nitrogen response gene in the population was used as the molecular phenotype, and the mixed linear model of the R package EMMAX was used to perform association analysis (eTWAS) with the cis- and trans-expression components of all rice genes to identify potential upstream regulatory genes.

[0066] (6) eTWAS hotspot genes: Perform transcriptome-wide association analysis (eTWAS) on the nitrogen response genes in the population, and screen out significantly associated genes with a p-value of less than 0.01 for the cis-expression component and a q-value of less than 0.01 for the trans-expression component from the eTWAS results. Summarize all eTWAS results to identify eTWAS hotspot genes that regulate multiple nitrogen response genes in the population.

[0067] (7) Integrated analysis: Considering that there are certain degrees of false positives in eGWAS and eTWAS analysis, the accuracy of gene mining can be significantly improved by combining the two. The candidate genes in the above eGWAS hotspot regions are intersected with the hotspot genes identified by eTWAS to obtain the eTWAS hotspot genes in the eGWAS hotspot regions, that is, the core hotspot genes that regulate nitrogen response genes in multiple populations. For example, Figure 4Among them, gene Os11 g0620400 was also identified as a hotspot gene by eTWAS, which regulated the expression of 2511 population nitrogen-responsive genes, thus confirming that this gene was an eGWAS-eTWAS hotspot gene (Table 2).

[0068] Table 2 Summary of eTWAS results

[0069]

[0070] (8) The advantages of the invention are: SNP-GWAS and eGWAS can locate associated sites or regions, but further analysis is needed to locate key genes, and the accuracy and efficiency of gene mining need to be improved. Through eGWAS-eTWAS joint analysis, the present invention can more efficiently and accurately mine core hotspot genes that regulate important biological pathways.

[0071] This embodiment also provides an application of plant molecular breeding based on the above-mentioned method of mining core hotspot genes based on population transcriptome.

[0072] This embodiment provides a method for mining core hotspot genes based on population transcriptome, including step S1: treating and sampling a rice population under different nitrogen conditions to obtain rice samples; step S2: performing differentially expressed gene analysis on the rice samples to obtain population nitrogen response genes; step S3: using the expression level of the population nitrogen response gene as a molecular phenotype, performing association analysis with genetic variation, and obtaining expression quantitative trait loci of the population nitrogen response gene; step S4: screening out eGWAS hotspot regions based on the expression quantitative trait loci;

[0073] Step S5: Perform expression-wide transcriptome association analysis on population nitrogen response genes to obtain eTWAS results; Step S6: Screen out eTWAS hotspot genes from the eTWAS results; Step S7: Take the intersection of the eTWAS hotspot genes and the genes in the eGWAS hotspot region to obtain core hotspot genes; the core hotspot genes are used to regulate multiple population nitrogen response genes. SNP-GWAS and eGWAS can locate associated sites or regions, but further analysis is needed to locate key genes, and the accuracy and efficiency of gene mining need to be improved. The present invention combines expression-wide genome association analysis and expression-wide transcriptome association analysis to efficiently and accurately mine core hotspot genes that regulate important biological pathways and analyze causal regulatory networks.

[0074] It can be understood that the above embodiments only express the preferred implementation modes of the present invention, and the descriptions thereof are relatively specific and detailed, but they cannot be understood as limiting the patent scope of the present invention. It should be pointed out that, for ordinary technicians in this field, the above technical features can be freely combined without departing from the concept of the present invention, and several deformations and improvements can be made, which all belong to the protection scope of the present invention. Therefore, all equivalent changes and modifications made to the scope of the claims of the present invention should belong to the coverage of the claims of the present invention.

Claims

1. A method for mining core hotspot genes based on population transcriptome, characterized in that: include: Step S1: treating and sampling a rice population under different nitrogen conditions to obtain a rice sample; Step S2: performing differentially expressed gene analysis on the rice sample to obtain population nitrogen response genes; Step S3: using the expression level of the population nitrogen response gene as a molecular phenotype, and performing association analysis with genetic variation to obtain the expression quantitative trait loci of the population nitrogen response gene; Step S4: Screening out eGWAS hotspot regions based on the expression quantitative trait loci; Step S5: Perform transcriptome-wide association analysis on the expression of nitrogen response genes in the population to obtain eTWAS results; Step S6: screening out eTWAS hotspot genes from the eTWAS results; Step S7: taking the intersection of the eTWAS hotspot genes and the genes in the eGWAS hotspot region to obtain core hotspot genes; the core hotspot genes are used to regulate multiple population nitrogen response genes.

2. The method for mining core hotspot genes based on population transcriptome according to claim 1, characterized in that: The differentially expressed gene analysis of the rice sample to obtain the population nitrogen response gene includes: DESeq2 software was used to analyze the differentially expressed genes in response to nitrogen for each sample, and the analysis parameters included fo ldchange and p value; Summarize nitrogen-responsive differentially expressed genes in rice samples; Genes showing differential expression in more than 25% of the rice samples are screened out from the nitrogen-responsive differentially expressed genes to obtain population nitrogen-responsive genes.

3. The method for mining core hotspot genes based on population transcriptome according to claim 1, characterized in that: The expression level of the group nitrogen response gene is used as a molecular phenotype, and an association analysis is performed with genetic variation to obtain the expression quantitative trait loci of the group nitrogen response gene, including: Performing eGWAS analysis on the nitrogen response genes of the population to obtain eGWAS results; Extracting SNPs with a p-value less than 1e-05 from the eGWAS results, merging sets of continuous SNP points with a distance less than 10 kb, and obtaining expression quantitative trait loci of population nitrogen response genes; Linkage disequilibrium analysis was performed on multiple expression quantitative trait loci of the same gene, retaining r 2 <0.1 for expression quantitative trait loci; The total number and average length of the expression quantitative trait loci of nitrogen-responsive genes in multiple populations were counted; The rice genome was divided into multiple windows, and the number of expressed quantitative trait loci in each window was counted.

4. The method for mining core hotspot genes based on population transcriptome according to claim 3, characterized in that: The step of performing eGWAS analysis on the nitrogen response genes of the population to obtain eGWAS results comprises: Performing Box-Cox normal transformation on the expression level of the nitrogen response gene in the population to obtain a transformation result; The conversion result is used as a phenotype and an association analysis is performed with the SNP to obtain an eGWAS result.

5. The method for mining core hotspot genes based on population transcriptome according to claim 1, characterized in that: The whole transcriptome association analysis of the expression of the nitrogen response genes in the population is performed to obtain the eTWAS results, including: The expression of all rice genes was decomposed into cis-expression components and trans-expression components based on the genetic variation upstream and downstream of the genes using GCTA software; The expression levels of nitrogen-responsive genes in the population were used as molecular phenotypes, and the mixed linear model of EMMAX in the R package was used for association analysis with the cis- and trans-expression components of all rice genes to obtain the eTWAS results.

6. The method for mining core hotspot genes based on population transcriptome according to claim 1, characterized in that: The step of screening out eTWAS hotspot genes from the eTWAS results comprises: From the eTWAS results, significantly associated genes with a p-value of the cis-expression component less than 0.01 and a q-value of the trans-expression component less than 0.01 were screened to obtain eTWAS hotspot genes.

7. The method for mining core hotspot genes based on population transcriptome according to claim 1, characterized in that: The rice population is processed and sampled under different nitrogen conditions to obtain rice samples including: N rice materials were treated with normal nitrogen and low nitrogen for 2 weeks respectively; The roots of different rice varieties were sampled to obtain rice samples.

8. The method for mining core hotspot genes based on population transcriptome according to claim 7, characterized in that: After obtaining the rice sample, the method further includes: extracting total RNA from each of the rice samples; The total RNA is sequenced to obtain an RNA sequence.

9. The method for mining core hotspot genes based on population transcriptome according to claim 1, characterized in that: The step of taking the intersection of the eTWAS hotspot genes and the genes in the eGWAS hotspot region to obtain core hotspot genes includes: The eTWAS hotspot genes are selected in the hotspot regions of the expression quantitative trait loci to obtain core hotspot genes.

10. An application of plant molecular breeding, characterized in that: A method for mining core hotspot genes based on population transcriptome according to any one of claims 1 to 9.

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