A method for detecting single-cell gene sequence variation in rice and its application

Abstract

The present invention provides a method for detecting single-cell gene sequence variation in rice and its application, which belongs to the field of agricultural technology. The method of the present invention mainly includes three aspects: sampling, sequencing and bioinformatics analysis, wherein the sampling is to obtain a single rice microspore sex cell. The present invention successfully isolates a single rice microspore sex cell, and improves the defects of the existing rice single-cell variation detection technology process, such as weak integrity and detection consistency that need to be improved. In addition, the authenticity of the mutation site is identified and confirmed by heavy ion mutagenesis technology. The method of the present invention broadens the source range of rice single-cell mutagenic materials, and provides new ideas and methods for creating more diverse breeding materials and conducting more efficient mutagenic breeding. At the same time, microspore sex cells serve as male gametes, and the mutations carried in the genome can be passed into the offspring through hybridization, which can realize the inheritance and fixation of mutations, and also provide a way to quickly utilize excellent mutant genes.

Description

Technical Field

[0001] The present invention belongs to the field of agricultural technology, and in particular relates to a method for detecting single-cell gene sequence variation in rice and an application thereof. Background Art

[0002] Mutation breeding is a common crop breeding approach, offering significant advantages in creating superior new genes with high biosafety that can be directly used in germplasm selection. Traditional mutagenesis breeding approaches focus on plant mutagenic materials at the tissue and organ level. This traditional sequencing approach only reflects average cell data and fails to provide information on heterogeneity between individual cells. This hinders detailed, targeted cellular-level variation discovery and utilization, and may overlook unique site-specific variation in single cells.

[0003] The rapid development of genome sequencing technology and bioinformatics has greatly facilitated research into the mechanisms of variation. Whole-genome resequencing is most widely used in plant mutation breeding, significantly reducing the barriers to identifying important gene sequences with unknown functions, enabling the full exploration and utilization of mutagenic gene resources and providing technical support for related research. Single-cell whole-genome sequencing (scWGS) reveals genomic heterogeneity in biological samples at single-cell resolution, addressing the shortcomings of traditional sequencing methods and helping us understand the unique functions of cells during plant development.

[0004] Compared to animal cells, single-cell sequencing has been less widely used in plant research. The presence of plant cell walls complicates the isolation and acquisition of single cells. Currently, single-cell sequencing can only be performed through protoplast isolation. This significantly impacts species where protoplast isolation is difficult, potentially leading to biased sequencing results and hindering the widespread adoption of single-cell sequencing in plants. Consequently, single-cell sequencing has been limited to a few crops, such as corn.

[0005] As one of the most important food crops, rice is crucial for ensuring food security in my country and globally through the creation of new variant genes and germplasm resources through mutagenesis breeding. Innovative technologies for isolating single cells, such as rice microspores, sequencing rice single-cell genomes, and detecting single-cell gene sequence variation are crucial for further exploring and utilizing gene sequence variation sites in single-cell rice cells subjected to mutagenesis. Summary of the Invention

[0006] In order to solve the above technical problems, the present invention provides a method for detecting single-cell gene sequence variation in rice and its application. The method of the present invention mainly includes three aspects: sampling, sequencing and bioinformatics analysis, wherein the sampling is to obtain a single rice microspore sex cell. The present invention successfully isolates a single rice microspore sex cell, and improves the defects of the existing rice single-cell variation detection technology process, such as weak integrity and detection consistency that need to be improved. In addition, the authenticity of the variation site is identified and confirmed by heavy ion mutagenesis technology. The method of the present invention broadens the source range of rice single-cell mutagenic materials, and provides new ideas and methods for creating more diverse breeding materials and conducting more efficient mutagenesis breeding. At the same time, microspore sex cells serve as male gametes, and the mutations carried in the genome can be passed into the offspring through hybridization, which can realize the inheritance and fixation of the variation, and also provide a way to quickly utilize excellent variant genes.

[0007] To achieve the above object, the present invention adopts the following technical solutions:

[0008] The present invention provides a method for detecting single-cell gene sequence variation in rice, comprising the following steps:

[0009] (1) Single cell isolation and DNA amplification:

[0010] First, a simple single-cell isolation device made by connecting a pointed glass capillary to a microsyringe was used to aspirate a single surviving uninucleate early microspore. Then, single-cell DNA was amplified using a single-cell whole genome amplification kit based on the MDA Phi29 DNA polymerase isothermal amplification system.

[0011] (2) Whole genome sequencing and data filtering:

[0012] First, the genomic DNA is fragmented and blunt-end repaired. Then, dA tails are attached to both ends of the DNA fragments and sequencing adapters are connected. Then, the fragments are purified using magnetic beads. Then, fragments in the range of 300-400bp are selected for PCR amplification, purification, quality control, and sequencing. Finally, the fragments are filtered using the fastp software.

[0013] (3) Identification of true variants in single-cell genomes:

[0014] GATK software was used for mutation detection. SNP sites were obtained according to the haplotype method. The software was then used to directly determine the base type of the site based on the sequencing reads and output the base type of the site. Sites with a heterozygous rate of 0.4-0.6 at a sequencing depth of 100× were considered heterozygous mutation sites. Sites outside this range were corrected to homozygous sites with the corresponding high-frequency bases. False positive data caused by genomic background differences and mismatches during DNA amplification were also removed during this process. Heavy ion or gamma-ray mutagenesis techniques were also used to verify microspore gene sequence variations.

[0015] (4) Bias analysis of single-cell genome variations:

[0016] Highly mutated genes (HMG), low-frequency mutated genes (LMG), and non-mutated genes (NMG) were screened from single-cell sequencing results. In HMG, the number of SNPs and gene length have a highly significant positive correlation. To eliminate the influence of gene length on the number of SNPs, the SNP ratio was used as a screening indicator. The SNP ratio is the number of SNPs per unit length (bp).

[0017] (5) Bioinformatics analysis of single-cell genome variations:

[0018] Includes a. GO enrichment analysis and b. data analysis and plotting.

[0019] Preferably, the single cell isolation method is specifically as follows: first, the microspores are stained with FDA-PI, then the cell activity is observed under a fluorescence microscope with a 20x objective lens, and finally, a single surviving uninucleate early microspore is aspirated through a simple single cell isolation device made by connecting a pointed glass capillary to a microsyringe.

[0020] Preferably, the single-cell DNA amplification method is specifically as follows: adding 3 μL of Buffer D2 to the single-cell sample, gently tapping the tube wall to mix, and briefly centrifuging to collect; incubating at 65°C for 10 minutes; adding 3 μL of Buffer N, gently tapping the tube wall to mix, and briefly centrifuging to collect; adding 40 μL of the reaction mixture to the prepared 10 μL DNA sample, gently tapping the tube wall to mix, and briefly centrifuging to collect, and incubating at 30°C for 3-4 hours; incubating at 65°C for 5 minutes to inactivate Discover-sc DNA Polymerase; performing 1% agarose gel electrophoresis on the amplified DNA sample, and storing the DNA sample with a clear and bright main band at -80°C for later use.

[0021] Preferably, the magnetic beads used in the purification are AMPure XP magnetic beads.

[0022] Preferably, the method for removing false positive data caused by genomic background differences is as follows: if the sequencing variety is inconsistent with the reference genome variety used for GATK comparison, the genomic background of the material itself is different. 10 blank control samples are set up, and the sequenced variant sites of the blank control samples are counted and compared with the irradiated samples. The same sites are considered to be derived from the differences in genomic background and are screened out.

[0023] Preferably, the method for removing false positive data caused by mismatches during the DNA amplification process is as follows: high-fidelity Phi29 DNA polymerase performs multiple cycles of replication of the entire rice genome, and each sample will still produce thousands of mismatch sites. However, the later the mismatch occurs during the cyclic amplification process, the lower the detected heterozygosity rate. The limit value of the first mismatch is taken, and sites with a heterozygosity rate below 25% are corrected and changed to the corresponding high-frequency base genotype, thereby screening out false positives generated during the amplification process.

[0024] Preferably, when the heavy ion or gamma ray mutagenesis technique is used to verify the microspore gene sequence variation, the heavy ions used are 3-5 Gy heavy ions, and the gamma rays used are 9-11 Gy gamma rays.

[0025] More preferably, the heavy ions used are 4 Gy heavy ions, and the gamma rays are 10 Gy gamma rays.

[0026] Preferably, the GO enrichment analysis method is: mapping the target gene to each term in the GO database, and calculating the number of genes for each term, thereby obtaining a gene list with a certain GO function and a gene number statistic; using a hypergeometric test, finding the GO terms that are significantly enriched in the target gene compared with the entire genome background; associating the target gene set with the GO database, performing GO enrichment analysis on the target gene, and obtaining the GO terms with significant gene enrichment; the data analysis and drawing method is: Microsoft Excel 2016 and SPSS19.0 are used for the collation and analysis of bioinformatics-related data, and Origin 2022 is used for drawing graphics.

[0027] The invention also provides application of the method in rice breeding.

[0028] The beneficial effects of the present invention are:

[0029] Aiming at the defects and deficiencies in existing technologies:(1) Cells are the most basic structural units of living organisms. Traditional sequencing methods can only reflect the average data of cells and cannot provide heterogeneity information between individual cells. Single-cell sequencing technology can make up for the shortcomings of traditional sequencing methods, but it is currently less used in crop research. In rice, the methods of sampling, sequencing and data analysis for single-cell sequencing need to be improved. The existence of plant cell walls increases the difficulty of isolating and obtaining single cells. The thickness of cell walls varies among different species, tissues and developmental stages, and the separation process of protoplasts will cause changes in cell state. However, single cells can only be sequenced by isolating protoplasts. This has a great impact on some species materials where protoplast isolation is difficult, and may cause deviations in sequencing results, which also creates certain difficulties for the popularization of plant single-cell sequencing. (2) The full-process operation steps of sampling, sequencing and data analysis of rice sex cells at the single-cell level are not perfect.

[0030] The innovation of the present invention is mainly reflected in Based on the emerging single-cell sequencing technology, this study uses uninucleated early microspores as the sample, improving the sampling, sequencing, and data analysis processes of rice sex cells. This establishes a comprehensive system for detecting mutations in rice microspore sex cells at the single-cell level, which is validated by case studies. This system offers clear technical specifications, strong operability, and the ability to perform batch mutation detection, providing a technical system supporting efficient batch mutation detection of rice sex cell mutants.

[0031] It is specifically reflected in the following aspects :

[0032] (1) In terms of material sources, the mutagenic materials currently used in rice research are mostly concentrated at the tissue and organ levels, making it difficult to conduct detailed mutation studies at the single-cell level.

[0033] The present invention successfully isolated single rice microspore cells, subjected them to heavy ion mutagenesis, and identified and confirmed the authenticity of the mutation sites. This invention broadens the sources of single-cell rice mutagenesis materials, providing new ideas and methods for creating more diverse breeding materials and conducting more efficient mutagenesis breeding. Furthermore, since microspore cells serve as male gametes, mutations carried in their genomes can be passed on to progeny through hybridization, achieving inheritance and fixation of the mutations, providing a pathway for the rapid utilization of superior mutant genes.

[0034] (2) In terms of detection process, the existing single-cell variation detection technology process of rice is not complete, and the consistency of detection needs to be improved.

[0035] This invention improves the relevant detection process, which mainly includes three aspects: sampling, sequencing and bioinformatics analysis:

[0036] a. The innovation in sampling primarily lies in the innovation of single-cell isolation and DNA amplification technology. This invention utilizes a simple single-cell isolation device to aspirate a single, surviving, uninucleate early microspore. The single-cell DNA is then amplified using an MDA-based Phi29 DNA polymerase isothermal amplification system, confirming that it meets the quality requirements for subsequent single-cell sequencing.

[0037] b. For sequencing, magnetic beads were used for DNA purification, and fragments in the 300-400bp range were targeted for PCR amplification. This improved sequencing quality and enabled the successful acquisition of the microspore single-cell genome, preparing basic data for subsequent mutations.

[0038] c. The innovation in the analytical step primarily involves the identification of authentic mutation sites. Confirming that microspore cells undergo authentic mutations detectable at the genomic level following heavy ion mutagenesis is of great significance. Only by identifying and confirming that authentic mutations have been induced can the present method for inducing microspore genomic mutations be considered effective.

[0039] In addition, in terms of technical analysis, variant site detection and true variant identification clearly state that false positive data comes from two aspects: "genomic background differences" and "false positive variant sites introduced by DNA amplification mismatches", and carry out targeted filtering steps to effectively ensure the authenticity of the data and lay the foundation for subsequent gene function analysis. BRIEF DESCRIPTION OF THE DRAWINGS

[0040] Figure 1 This is a flow chart of single cell separation in Example 1 of the present invention;

[0041] Figure 2 Schematic diagram of the true variant screening strategy in Example 1 of the present invention;

[0042] Figures 3 and 4 The tool used in making the simple single cell separation device in Example 1 of the present invention;

[0043] Figure 5 This is the distribution of cluster damage after heavy ion and gamma ray radiation in Example 2 of the present invention;

[0044] Figure 6 is the Sanger sequencing verification result of the mutation site of the single-cell sequencing in Example 2 of the present invention, wherein: C is a high-quality sample obtained by heavy ion radiation, rC is a high-quality sample obtained by gamma-ray radiation; hom is a homozygous site, and het is a heterozygous site;

[0045] Figure 7 This is a correlation diagram between radiation-mutated gene features in Example 3 of the present invention;

[0046] Figure 8This is the GO enrichment result of genes with different mutation frequencies in Example 4 of the present invention. DETAILED DESCRIPTION

[0047] The following examples are intended 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 are intended to fall within the scope of the present invention. The products, reagents, instruments, and equipment used in the following examples are all commercially available, and the methods used are consistent with conventional methods unless otherwise specified.

[0048] The technical solution of the present invention is further elaborated in detail below in conjunction with embodiments.

[0049] Example 1 A method for detecting single-cell gene sequence variation in rice

[0050] (1) Single cell isolation and DNA amplification:

[0051] After staining the microspores with FDA-PI, the cell activity was observed under a fluorescence microscope with a 20x objective lens. A simple single-cell isolation device made by connecting a pointed glass capillary to a microsyringe was used to aspirate a single surviving uninucleate early microspore ( Figure 1 ), placed in a 200 μL centrifuge tube, and placed on ice to prevent DNA degradation.

[0052] Single-cell DNA amplification was performed using the Phi29 DNA polymerase isothermal amplification system (MDA) using the Novozymes Single-Cell Whole Genome Amplification Kit (N-603). First, 3 μL of Buffer D2 was added to the single-cell sample, mixed by gently tapping the tube, and collected by brief centrifugation. The sample was incubated at 65°C for 10 minutes. Then, 3 μL of Buffer N was added, mixed by gently tapping the tube, and collected by brief centrifugation. 40 μL of the reaction mixture was added to the prepared 10 μL DNA sample, mixed by gently tapping the tube, and collected by brief centrifugation. The sample was incubated at 30°C for 3-4 hours, and incubated at 65°C for 5 minutes to inactivate the Discover-scDNA Polymerase. The amplified DNA sample was subjected to 1% agarose gel electrophoresis. DNA samples with a clear, bright main band were stored at -80°C until further use.

[0053] (2) Whole genome sequencing and data filtering:

[0054] Genomic DNA was randomly enzymatically fragmented into short DNA fragments, followed by blunt-end repair. DNA fragments were ligated with dA tails at both ends and then ligated with sequencing adapters. The adapter-attached DNA fragments were purified using AMPure XP magnetic beads (Beckman Coulter, CA, USA), and fragments in the 300-400 bp range were selected for PCR amplification. The resulting library was purified and quality-checked before sequencing using a HiSeq X10 PE150 (Illumina Inc, USA). Raw reads were filtered using fastp software to obtain clean data.

[0055] (3) Identification of true variants in single-cell genomes:

[0056] GATK software was used for mutation detection. SNP sites were identified using the haplotype method. The software then determined the base type of each site based on the sequencing reads (number of supported reads, sequencing quality, etc.) and output the base type. Sites with a heterozygous rate of 0.4-0.6 at a sequencing depth of 100× were considered heterozygous mutation sites. Sites outside this range were corrected to homozygous sites with the corresponding high-frequency bases.

[0057] Remove false positive data in two aspects:

[0058] a. Genomic background differences: If the sequencing species and the reference genome species used for GATK alignment are inconsistent, the genomic background of the material itself is different. Set up 10 blank control samples (CK), count the sequenced variant sites of the CK samples, and compare them to the irradiated samples. Identical sites are considered to be caused by genomic background differences and are screened out.

[0059] b. Mismatches during DNA amplification: High-fidelity Phi29 DNA polymerase replicates the entire rice genome multiple times, resulting in tens of thousands of mismatches in each sample. However, the later a mismatch occurs during the amplification cycle, the lower the heterozygosity rate detected. By taking the first mismatch threshold, sites with a heterozygosity rate below 25% are corrected and replaced with the corresponding high-frequency base genotypes, thus eliminating false positives generated during the amplification process. Figure 2 ).

[0060] (4) Bias analysis of single-cell genome variations:

[0061] High-frequency mutant genes (HMG), low-frequency mutant genes (LMG), and no mutation genes (NMG) were screened from single-cell sequencing results. In HMG, the number of SNPs and gene length have a highly significant positive correlation. To eliminate the influence of gene length on the number of SNPs, the SNP ratio (SNP ratio) was used as a screening indicator. The SNP ratio is the number of SNPs per unit length (bp) (SNP ratio = SNP count / Length).

[0062] (5) Bioinformatics analysis of single-cell genome variations:

[0063] a. GO enrichment analysis: Map target genes to terms in the GO (Gene Ontology) database and calculate the number of genes associated with each term to obtain a list of genes with a specific GO function and a gene count. Use a hypergeometric test to identify GO terms that are significantly enriched in the target genes compared to the entire genomic context. Link the target gene set to the GO database and perform GO enrichment analysis on the target genes to identify GO terms that are significantly enriched in the genes.

[0064] b. Data analysis and drawing: Bioinformatics-related data were organized and analyzed using Microsoft Excel 2016 and SPSS 19.0 (IBM, SPSS Inc, USA), and graphics were drawn using Origin 2022 (OriginLab Crop, Northampton, MA, USA).

[0065] Among them, the simple single cell separation device made by connecting the pointed glass capillary to the micro syringe in this embodiment is made using tools such as Figures 3 and 4 The specific steps are as follows:

[0066] 1. Purchase:

[0067] (1) Commercially available borosilicate glass spotting capillary tube, 0.1 mm in diameter and 10 mm in length (referred to as “capillary tube”).

[0068] (2) 10mL plastic syringe. (Referred to as "syringe")

[0069] (3) The stainless steel metal needle that comes with the WPI zebrafish manual microinjection pump DMP injector (Wuhan Gairdner Tech Co., Ltd.) and the rubber tube and white plastic connector connected to the needle.

[0070] (referred to as "connection device")

[0071] 2. Heat the capillary tube under the outer flame of an alcohol lamp. Once the capillary tube softens, slowly stretch it outwards from both ends until it breaks at the heated part. The pore size at the break is very small, much smaller than 0.1mm, making it suitable for aspirating single cells.

[0072] 3. Take one of the two broken sections, insert the thick end (hand-held end) into the metal mouth of the needle of the "connecting device", and insert the white plastic connector of the "connecting device" into the suction port of the "syringe".

[0073] 4. Use one hand to move the needle of the "connecting device" so that the thin end (melted end) of the capillary connected to it is aligned with the single cell to be separated in the microscope field of view. With the other hand, gently pull the piston of the syringe to draw the single cell into the capillary, and the separation is successful.

[0074] Example 2: Identifying single-cell genome sequencing and true variation

[0075] a. Isolation of uninucleate early microspores for single-cell sequencing:

[0076] Rice (japonica rice variety 02428) male gametes (uninucleate early microspores) were irradiated with heavy ions (4 Gy) and gamma rays (10 Gy). Fifty microspores were isolated from each treatment group by microscopy, and 10 unirradiated unnucleate early microspores were isolated as a control. Single-cell DNA was extracted and amplified using the MDA method. The amplified DNA quality was tested by 1% agarose gel electrophoresis. Forty-seven high-quality samples (C) with bright, clear main bands and ten blank control samples (CK) were selected for single-cell sequencing. The reference genome for sequencing was Nipponbare (Ensembl_release45). For microspore isolation and DNA amplification methods, see Example 1.

[0077] b. Perform single-cell genome cluster damage structure analysis:

[0078] Cluster damage refers to the presence of two or more DNA damage sites within one or two DNA helices. It is characterized by complex damage and difficulty in repair, and is an important characteristic for measuring genomic damage. Statistics on the distribution of cluster damage under the two irradiation methods found that the total number of cluster damage caused by heavy ions was as high as 35,632, with an average of 758 per cell; while gamma rays only caused 6,744 cluster damage, with an average of 135 per cell, indicating that heavy ion irradiation causes more intensive, severe and difficult to repair damage to the genome ( Figure 5 ).

[0079] c. Verify the reliability of the variant site:

[0080] The number of mutation sites in the microspores treated with the two radiations was detected to clarify the molecular characteristics of the mutations and verify the reliability of the mutation sites. The mutation sites of the microspores treated with the two radiations were randomly selected for Sanger sequencing verification. The Sanger sequencing results were compared with the mutation sites of the single-cell sequencing. The results showed that the detection results of the two were consistent, especially the Sanger results of the heterozygous sites showed a double peak, which confirmed the reliability of the detected mutation sites ( Figure 6 ).

[0081] Example 3: Exploring the Preference of Genomic Variation

[0082] According to the method in step (4) of Example 1, HMG (C-HMG for heavy ions and rC-HMG for gamma rays), LMG (C-LMG for heavy ions and rC-LMG for gamma rays), and NMG were screened from the single-cell sequencing results of Example 2. Analysis of variant preferences revealed correlations between various gene structural features, indicating that multiple features significantly influence the proportion and number of SNPs.

[0083] In HMG, the SNP ratio and SNP number were highly significantly positively correlated, and in heavy ion exposure, they were significantly negatively correlated with UTR5 length and UTR3 GC content. In gamma ray exposure, they were highly significantly negatively correlated with exon length, gene length, and UTR5 length. The SNP number was highly significantly positively correlated with gene length, exon number, exon length, intron number, intron length, intron GC content, UTR5 length, UTR3 length, and UTR3 GC content, and inversely correlated with total GC content and exon GC content. In heavy ion exposure, the SNP number was also highly significantly positively correlated with the GC content of UTR5.

[0084] In LMG, the SNP ratio was significantly negatively correlated with gene length, number of exons, number of introns, and intron length, and significantly positively correlated with total GC content and exon GC content. In addition, in γ-rays, it was significantly positively correlated with the number of SNPs and UTR5 length, and extremely significantly negatively correlated with intron GC content. The number of SNPs was significantly positively correlated with gene length, intron length, and intron GC content. The number of SNPs in heavy ion exposure was also significantly positively correlated with exon length, and the number of SNPs in γ-rays was significantly negatively correlated with the GC content of UTR3 ( Figure 7 ).

[0085] Example 4 Bioinformatics Analysis of Single Cell Genomic Variant Sites

[0086] Bioinformatics analysis was performed on the genes in the five gene sets of C-HMG, rC-HMG, C-LMG, rC-LMG and NMG in Example 3, focusing on studying the functions of the genes where the mutation sites are located through GO enrichment and motif analysis.

[0087] GO enrichment was performed on the five gene sets mentioned above, and the top 10 pathways with the largest -log(p-value) were selected. C-HMG was significantly enriched in processes such as protein modification, response to stimuli, stress, and chemicals, and organ organization; C-LMG was significantly enriched in nucleic acid and RNA metabolism, organic compound synthesis, and metabolism; rC-HMG was significantly enriched in multi-organism processes, defense responses, response to heat, stimuli, and reactive oxygen species, jasmonic acid metabolism, and biological reproduction; rC-LMG was significantly enriched in organic matter, macromolecular metabolism, and single-organism processes; and NMG was enriched in the assembly, disassembly, and processing of cellular components, as well as anther dehiscence.

[0088] HMG, LMG, and NMG show opposite trends in the functions of mutant genes. Heavy ion-induced high-frequency mutant genes have some special functions, such as responses to pressure and stimulation, while low-frequency mutant genes have conservative biological functions, such as metabolism. γ-rays show a similar trend, that is, high-frequency mutant genes have some special functions, such as responses to heat and reactive oxygen species, while low-frequency mutant genes have more conservative functions, and most of them are also enriched in metabolic processes. At the same time, the functions of non-mutated genes are also relatively conservative, and most of them are enriched in processes such as chromatin, nucleosomes, and other cell component processing. The correlation between gene mutation frequency and biological function is consistent with the trend of non-mutated gene function, that is, in order to maintain the stability of basic life activities, functionally conservative genes are less likely to mutate, while genes with special functions are more likely to mutate ( Figure 8 ).

[0089] The embodiments described above are merely descriptions of preferred embodiments of the present invention and are not intended to limit the scope of the present invention. Without departing from the spirit of the present invention, various modifications and improvements made to the technical solutions of the present invention by persons skilled in the art should fall within the scope of protection defined by the claims of the present invention.

Claims

1. A method for detecting single-cell gene sequence variation in rice, characterized in that: The following steps are involved: (1) Single cell isolation and DNA amplification: First, a simple single-cell isolation device made by connecting a pointed glass capillary to a microsyringe was used to aspirate a single surviving uninucleate early microspore. Then, a single-cell DNA amplification kit was used based on the MDAPhi29 DNA polymerase isothermal amplification system. (2) Whole genome sequencing and data filtering: First, the genomic DNA is fragmented and blunt-end repaired. Then, dA tails are attached to both ends of the DNA fragments and sequencing adapters are connected. Then, the fragments are purified using magnetic beads. Then, fragments in the range of 300-400bp are selected for PCR amplification, purification, quality control, and sequencing. Finally, the fragments are filtered using the fastp software. (3) Identification of true variants in single-cell genomes: GATK software was used for mutation detection. SNP sites were obtained according to the haplotype method. The software was then used to directly determine the base type of the site based on the sequencing reads and output the base type of the site. Sites with a heterozygous rate of 0.4-0.6 at a sequencing depth of 100× were considered heterozygous mutation sites. Sites outside this range were corrected to homozygous sites with the corresponding high-frequency bases. False positive data caused by genomic background differences and mismatches during DNA amplification were also removed during this process. Heavy ion or gamma-ray mutagenesis techniques were also used to verify microspore gene sequence variations. (4) Bias analysis of single-cell genome variations: Highly mutated genes (HMG), low-frequency mutated genes (LMG), and non-mutated genes (NMG) were screened from single-cell sequencing results. In HMG, the number of SNPs and gene length have a highly significant positive correlation. To eliminate the influence of gene length on the number of SNPs, the SNP ratio was used as a screening indicator. The SNP ratio is the number of SNPs per unit length (bp). (5) Bioinformatics analysis of single-cell genome variations: Includes a. GO enrichment analysis and b. data analysis and plotting.

2. The method according to claim 1, characterized in that The single-cell isolation method specifically comprises the following steps: first, staining the microspores with FDA-PI, then observing the cell activity under a fluorescence microscope with a 20x objective lens, and finally, aspirating a single surviving uninucleate early microspore using a simple single-cell isolation device made by connecting a pointed glass capillary to a microsyringe.

3. The method according to claim 2, characterized in that The single-cell DNA amplification method specifically comprises: adding 3 μL of Buffer D2 to the single-cell sample, gently tapping the tube wall to mix, and briefly centrifuging to collect; incubating at 65°C for 10 minutes; adding 3 μL of Buffer N, gently tapping the tube wall to mix, and briefly centrifuging to collect; adding 40 μL of the reaction mixture to the prepared 10 μL DNA sample, gently tapping the tube wall to mix, and briefly centrifuging to collect, and incubating at 30°C for 3-4 hours; incubating at 65°C for 5 minutes to inactivate Discover-scDNA Polymerase; and subjecting the amplified DNA sample to 1% agarose gel electrophoresis. DNA samples with clear and bright main bands are stored at -80°C for later use.

4. The method according to claim 3, characterized in that The magnetic beads used in the purification are AMPure XP magnetic beads.

5. The method according to claim 4, characterized in that The method for removing false positive data caused by genomic background differences is as follows: if the sequencing variety is inconsistent with the reference genome variety used for GATK alignment, the genomic background of the material itself is different. 10 blank control samples are set up, and the sequenced variant sites of the blank control samples are counted and compared with the irradiated samples. The same sites are considered to be derived from the differences in genomic background and are screened out.

6. The method according to claim 5, characterized in that The method for removing false-positive data caused by mismatches during the DNA amplification process is as follows: High-fidelity Phi29 DNA polymerase performs multiple cycles of replication across the entire rice genome, generating thousands of mismatched sites for each sample. However, the later a mismatch occurs during the cyclic amplification process, the lower the detected heterozygosity rate. Using the first mismatch threshold, sites with a heterozygosity rate below 25% are corrected and replaced with the corresponding high-frequency base genotype, thereby eliminating false positives generated during the amplification process.

7. The method according to claim 6, characterized in that When the heavy ion or gamma ray mutagenesis technique is used to verify the microspore gene sequence variation, the heavy ions used are 3-5Gy heavy ions, and the gamma rays used are 9-11Gy gamma rays.

8. The method according to claim 7, characterized in that The heavy ions used were 4 Gy heavy ions, and the gamma rays used were 10 Gy gamma rays.

9. The method according to claim 8, characterized in that The GO enrichment analysis method is as follows: mapping the target gene to each term in the GO database and calculating the number of genes for each term, thereby obtaining a gene list with a certain GO function and a gene number statistics; Use the hypergeometric test to find GO terms that are significantly enriched in the target gene compared with the whole genome background; The target gene set was associated with the GO database, and GO enrichment analysis was performed on the target genes to obtain GO terms with significant gene enrichment. The data analysis and drawing methods were as follows: Microsoft Excel 2016 and SPSS19.0 were used for the collation and analysis of bioinformatics-related data, and Origin 2022 was used for the drawing of graphics.

10. Use of the method according to any one of claims 1 to 9 in rice breeding.

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