Corn ear row number related molecular marker gene Zm00001eb072850 and application thereof

Abstract

The invention belongs to the technical field of molecular marker assisted breeding, and particularly discloses a molecular marker gene Zm00001eb072850 related to the row number of corn ears and application of the molecular marker gene Zm00001eb072850 related to the row number of the corn ears, the molecular marker is the Zm00001eb072850 gene or protein for encoding the gene, the nucleotide sequence of the gene is shown as SEQ ID NO: 1, and the expression quantity of the Zm00001eb072850 gene or the protein for encoding the gene is in positive correlation with the row number of the corn ears. According to the molecular marker, SNP: 2-15316355 and a related gene Zm00001eb072850 are jointly positioned on a corn chromosome 2 through multi-point experiments for many years, the SNP can be positioned in three different environments, a related candidate functional gene mainly encodes corn histone and is related to corn ear development, the molecular marker provided by the invention can effectively shorten the breeding period, and the breeding cost is reduced. The breeding process is accelerated, the breeding efficiency is improved, and the process of screening excellent germplasm resources is accelerated.

Description

Technical Field

[0001] The invention belongs to the technical field of molecular marker-assisted breeding, and specifically relates to application of a corn ear row number molecular marker SNP:2-15316355 and a related gene Zm00001eb072850 in assisted breeding for increasing corn ear row number. Background Art

[0002] Maize (Zea mays) is the most important dual-purpose grain and feed crop. Ear row number (ERN) refers to the number of kernel rows on a maize ear and is a yield component directly related to maize yield. ERN is a complex quantitative trait controlled by polygenic inheritance. Although it is closely related to maize yield, little research has been conducted on the mechanism of maize ear row number formation. Therefore, identifying candidate functional genes related to ERN has become an important part of molecular breeding programs to improve maize yield.

[0003] The number of rows of ears is determined by the development of corn inflorescence. The corn axillary meristem (AM) is transformed into the inflorescence meristem (IM), and the spikelet pair meristem (SPM) is produced in the peripheral area. Each SPM produces two spikelet meristems (SM), which further develop into two floret meristems. Existing studies have identified several candidate genes related to ERN by methods such as GWAS. However, most of the cloned corn ear row number-related genes are from mutant studies, and the practical application of these functional genes in corn breeding is still limited, and there is still little work on key gene mining with high utilization value for breeding practice obtained by using the map-based cloning method. The present invention selects six recombinant inbred line populations with a total of 780 recombinant inbred lines, uses three years of ERN phenotypic data for GWAS analysis, and mines candidate functional genes, in order to provide a new method for breeding new high-yield corn varieties with multiple ear rows using modern molecular breeding technology. Summary of the invention

[0004] The present invention confirms through research that SNP: 2-15316355 of corn chromosome 2 and its associated gene Zm00001eb072850 have a significant positive effect on the number of corn ear rows. Corn ERN (ear row number) is a quantitative trait regulated by multiple genes. The technical solution provided by the present invention provides a new method for breeding new high-yield corn varieties using modern molecular breeding technology. Specifically, the present invention provides the following technical solutions:

[0005] On the one hand, the present invention provides a molecular marker related to the number of corn ear rows, wherein the molecular marker is the Zm00001eb072850 gene or a protein encoding the gene, and the nucleotide sequence of the gene is shown in SEQ ID NO: 1. The expression level of the Zm00001eb072850 gene or the protein encoding the gene is positively correlated with the number of corn ear rows.

[0006] On the other hand, the present invention provides molecular markers related to the number of corn ear rows, wherein the molecular markers are SNP sites, the reference genome version is B73_V4 (B73RefGen_v4), and the marker SNP sites are 15316067, 15316076, 15316100, 15316136, 15316202, 15316214, 15316241, 15316274, 15316346, 15316355, 15316361, 15316367 and 15316370 sites on corn chromosome 2. When the bases at the sites are GACGGGGACTCGT in sequence, the corn exhibits the trait of multiple ear rows.

[0007] Furthermore, the present invention provides a product for detecting any of the molecular markers, wherein the product detects the genotype of the molecular marker, or detects the expression level of the Zm00001eb072850 gene or a protein encoding the gene, and the nucleotide sequence of the gene is shown in SEQ ID NO:1.

[0008] Furthermore, the product includes a reagent, a kit or a gene chip.

[0009] Furthermore, the product includes products prepared by PCR, qPCR, Sanger sequencing, high-throughput sequencing, fluorescence in situ hybridization, TaqMan probe method, ARMS-PCR method or KASP method.

[0010] Furthermore, the present invention provides any of the following applications of any of the molecular markers or any of the products:

[0011] a) Analysis of genetic diversity of corn ear row number; b) Construction of molecular genetic map of corn ear row number; c) Genome-wide association analysis of corn ear row number; d) Identification of corn varieties with multiple ear rows; e) Molecular marker-assisted selection breeding for corn ear row number trait; f) Genome-wide selection breeding for corn ear row number trait; g) Gene editing breeding for corn ear row number trait.

[0012] Furthermore, the present invention provides a method for screening corn with a large number of ear rows, characterized in that a corn sample to be tested is taken, and any of the molecular markers described is detected. If the molecular marker type is met, a corn variety with a large number of ear rows is obtained.

[0013] Furthermore, the present invention provides a method for increasing the number of corn ear rows, which comprises overexpressing the Zm00001eb072850 gene or the expression level of a protein encoding the gene, wherein the nucleotide sequence of the gene is shown in SEQ ID NO:1.

[0014] The technical effects achieved by the present invention are:

[0015] Based on genome-wide association analysis, the present invention uses tropical maize inbred lines (YML226, Q11, R-2-1-1, YML1218, Chang7-2, Shen137) as resistant parents and hybridizes them with temperate susceptible excellent inbred line Ye107. After six consecutive generations of single-seed self-pollination, six F 9 Recombinant inbred lines (RIL). These RILs were planted in Yanshan County, Yunnan Province in 2021, and in Jinghong City, Yunnan Province in 2022 and 2023. Through ERN phenotypic identification in three environments, combined with high-quality SNPs of the RIL population, GWAS analysis identified SNPs that were significantly correlated with the number of corn ear rows in multiple environments: 2-15316355 molecular markers and functional genes Zm00001eb072850, the nucleotide sequence of the Zm00001eb072850 gene is shown in SEQ ID NO: 1, and the gene is related to the development of corn ear primordium. The molecular markers provided by the present invention can effectively shorten the breeding period, speed up the breeding process, improve the breeding efficiency, and speed up the process of screening excellent and high-yield germplasm resources. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] Figure 1 : The population structure and ear row number of the six subpopulations. a. Schematic diagram of the construction of the multi-parent population (MPP). The six parents (YML222, Q11, R-2-1-1, YML1218, Chang7-2 and Shen137) were crossed with Ye107 to obtain F 1 Hybrid. 1 After 6 generations of self-pollination, the offspring obtained F 7 recombinant inbred lines (RILs). b. Changes in the mean and minimum / maximum values ​​of the number of ear rows in the six subpopulations (pop1-pop6). (ch) Frequency distribution of the number of ear rows in the six subpopulations.

[0017] Figure 2 Manhattan plot (left) and QQ plot (right) of GWAS analysis of corn ear row number.

[0018] Figure 3 Relative position map of significant SNP 2-15316355 and its corresponding gene Zm00001eb072850.

[0019] Figure 4 Haplotype analysis of candidate gene Zm00001eb072850. (a) 13 SNP loci included in the haplotype, (b) Hap2 can significantly increase the number of corn ear rows.

[0020] Figure 5a: Phylogenetic tree of H4 genes in maize (Zea mays) and Arabidopsis thaliana; maize histone H4 genes are represented in blue, and Arabidopsis thaliana are represented in red. b: Expression pattern of H4 genes in 2-4 mm ear primordium, 6-8 mm ear primordium, 16-19 day female flower spikelet and vegetative meristem. Darker colors and larger circles indicate higher gene expression. DETAILED DESCRIPTION

[0021] The technical scheme of the present invention is described in detail below in conjunction with the accompanying drawings and Examples, but the present invention is not therefore limited to the scope of the embodiments described. Unless otherwise specified, the experiments and methods described in the embodiments are carried out substantially according to conventional methods well known in the art and described in various references, and reagents and raw materials used in the present invention are all commercially available. If specific conditions are not specified in the embodiments, they are carried out according to conventional conditions or conditions recommended by the manufacturer. If the reagents or instruments are not specified by the manufacturer, they are all conventional products that can be obtained commercially. Those skilled in the art will appreciate that the embodiments describe the present invention by way of example, and the scope of protection claimed in the present invention cannot be limited thereto.

[0022] Based on genome-wide association analysis, the present invention uses tropical maize inbred lines (YML226, Q11, R-2-1-1, YML1218, Chang7-2, Shen137) as resistant parents and hybridizes them with temperate susceptible excellent inbred line Ye107. After six consecutive generations of single-seed self-pollination, six F 7 Recombinant inbred lines (RIL). These RILs were planted in Jinghong City, Yunnan Province in 2021, and in Yanshan County, Yunnan Province in 2022 and 2023. Through ERN phenotypic identification in three environments, combined with high-quality SNPs of the RIL population, GWAS analysis identified SNPs that were significantly correlated with the number of corn ear rows in multiple environments: 2-15316355 molecular markers and functional genes Zm00001eb072850, the nucleotide sequence of the Zm00001eb072850 gene is shown in SEQ ID NO: 1, and the molecular markers provided by the present invention can be applied to high-yield molecular breeding of corn in molecular breeding.

[0023] Example 1

[0024] 1. Experimental Materials and Design

[0025] In this experiment, six tropical maize inbred lines (YML226, Q11, R-2-1-1, YML1218, Chang7-2, and Shen137) with significant variation in the number of corn ear rows and wide genetic variation were selected as female parents. The high-combining ability and excellent temperate maize inbred line Ye107 were used as common parents for hybridization (the pedigrees, heterotic groups, and ecological groups of the seven parents are detailed in Table 1). Through the single-seed transmission method, nine consecutive generations of self-pollination were performed to produce six recombinant inbred line (RIL) populations: po p1 (YML226 × Ye107), pop2 (Q11 × Ye107), pop3 (R-2-1-1 × Ye107), pop4 (YML1218 × Ye107), pop5 (Chang7-2 × Ye107) and pop6 (Shen137 × Ye107), each population initially contained 200 RIL lines, but due to environmental selection, inbreeding depression and other factors, 780 RIL lines were ultimately used for the present invention. These RIL lines were planted in Yanshan County, Yunnan Province (23 ° 19'-23 ° 59'N, 103 ° 35'-104 ° 45'E) in 2021, and in Jinghong City, Yunnan Province (100 ° 78'E, 22 ° 00'N) in 2022 and 2023. The experimental design adopted a completely randomized block design, with 14 plants per row, a row length of 4m, and a plant spacing of 25cm, and was carried out according to standard farmland management.

[0026] Table 1. Pedigrees, ecotypes and white spot resistance of the seven parents used in the experiment

[0027]

[0028] 2. Phenotypic Identification and Statistical Analysis

[0029] Phenotypic data were analyzed descriptively using SPSS (SPSS Statistics) and ORIGIN (Origin 2022) software. Mean, minimum, maximum, standard deviation (SD), coefficient of variation (CV), skewness, and kurtosis were calculated. Frequency distribution of phenotypic data was performed using SPSS software. Kurtosis and skewness were used to assess the normality of the frequency distribution. The coefficient of variation (CV%) was calculated using the following formula: CV = (standard deviation SD / mean) × 100%. Broad-sense heritability was calculated according to the method outlined by Knapp et al.

[0030] 3. DNA Extraction and Sequencing Genotyping

[0031] Genotyping of parental lines and recombinant inbred lines (RILs) was performed using genotyping by sequencing (GBS). Genomic DNA was extracted from seedling leaves of 780 RILs using the cetyltrimethylammonium bromide (cTAB) method described by Elshire et al. (2011). DNA concentration was quantified using Qubit and diluted to 20 ng / μL for library preparation. The extracted DNA was digested with restriction enzymes PstI and MspI (New England BioLabs, Ipswich, MA, USA) and ligated to barcode adapters using T4 ligase (NewEngland BioLabs).

[0032] GBS DNA libraries were constructed and sequenced following the GBS protocol outlined by Poland et al. (2012). Sequencing was performed on an Illumina NovaSea 6000 platform with a read length of 2 × 150 bp. Low-quality reads and reads containing adapters were removed, and high-quality reads were obtained and used for further analysis.

[0033] Single nucleotide polymorphisms (SNPs) and insertions / deletions (InDels) were generated by alignment with the B73 maize reference genome (B73_V4, ftp: / / ftp.ensemblgenomes.org / pub / plants / release-37 / fasta / zea_mays / DNA) using GATK software (v4.1.4.0). The quality of SNPs was assessed based on minor allele frequency (MAF), percentage of missing data points, and linkage disequilibrium. The filtering criteria for SNPs was set as MAF ≥ 0.05 to screen high-quality SNPs. A total of 638,646 high-quality SNPs were identified and annotated using the ANNOVAR software tool (v2013-05-20).

[0034] 4. Whole-genome resequencing of ear rows

[0035] GWAS analysis was performed on the average number of ear rows of 780 RILs from multi-parent populations in three different environments. Best linear unbiased prediction (BLUP) was also used in GWAS to identify SNPs significantly associated with ERN. GWAS analysis was performed using a mixed linear model (MLM) in the EMMAX software package (vintel 64-20,120,205) (Jiang et al., 2023). Plink (v1.9) was used to determine the significance threshold for identifying SNPs associated with ERN. Manhattan plots were used to display marker distributions and QQ plots were used to visualize the results to assess the accuracy of the association analysis. A significance threshold of log10(p)=6 was applied to identify significant SNPs (Purcell et al., 2007). The mixed linear model used for GWAS is based on the following formula:

[0036] y=Xa+Sb+Km+e

[0037] Where y represents the phenotype, a and b are fixed effects representing the marked and unmarked effects respectively, and m represents the unknown random effect. The association matrices a, b, and m are represented by X, S, and K respectively, and e is the vector of random residual effects.

[0038] 5. Candidate gene screening and expression analysis

[0039] GWAS was used to screen candidate genes within the 20 kb region upstream and downstream of the consistent significant SNPs in different environments. The SNPs obtained from the GWAS results were annotated using ANNOVAR software (v2013-05-20). The identified SNPs were searched and compared in the maizeGDB (https: / / www.maizegdb.org) and NCBI (http: / / www.ncbi.nlm.nih.gov / ) databases to identify candidate genes and perform functional annotations. In addition, the expression data of candidate genes regulating ERN at different time points were extracted from the MaizeGDB database, and the FPKM (fragments per kilobase of transcript per million mapped reads) values ​​were obtained for further analysis.

[0040] 6. Haplotype Analysis

[0041] Haplotype analysis of candidate genes was performed by extending the upstream and downstream regions of the selected genes by 1 Mb. Haplotype block values ​​were calculated using Haploview (v4.2) software and visualized as heat maps, and box plots were generated to represent the relationship between haplotypes and phenotypes.

[0042] 7 Homology analysis of candidate genes

[0043] Protein domains of candidate genes were extracted and homologous sequences were identified using BLAST (v2.2.26) against Arabidopsis thaliana. Homologous gene sequences were confirmed by comparison with orthologs available on the OrthoMCL database (http: / / orthomcl.org / orthomcl / ). Neighbor-joining phylogenetic trees with 1000 bootstrap replicates and complete deletion of gap / missing data were constructed using MEGA11 (version 11.0.13). The phylogenetic tree was visualized, annotated, and adjusted in iTOL (interactive tree of life, https: / / itol.embl.de / ). Expression profiles of identified genes were obtained and visualized using online qTeller (https: / / qteller.maizegdb.org).

[0044] result

[0045] 1. Phenotypic Data Analysis

[0046] In this study, a multiparent population (MPP) consisting of 780 families from six recombinant inbred line populations was used to investigate the genetic structure of ear row number in maize ( Figure 1 a). Significant differences in ear row number were observed among the six subpopulations. Pop3 had the highest ear row number of 13.99, while the lowest ERN for ear row number was 12.48 ( Figure 1 b). The frequency distribution of ear row numbers in the six subpopulations follows a normal distribution ( Figure 1 ch).

[0047] Descriptive statistical analysis of the number of ear rows was performed for six RIL populations in three different environments, Jinghong (2021, 21JH) and Yanshan (2022 and 2023, 22YS and 23YS) (Table 1). The results showed that pop3 consistently showed the highest number of ear rows in all environments, while pop5 showed the lowest mean number of ear rows (Table 1). The coefficient of variation (CV%) of the number of ear rows between the six subpopulations in each environment ranged from 9.83% to 16.20%, indicating significant differences in the number of ear rows between subpopulations. The absolute values ​​of the skewness and kurtosis of the number of ear rows in different environments were generally less than 1, except for pop5 in 22YS and pop6 in 21JH and 22YS (Table 1). The broad-sense heritability (H2) of the number of ear rows in the six subpopulations ranged from 75.96% to 88.21%, indicating a strong genetic influence on this trait. The consistency of phenotypic variation in different environments highlights the reliability of the phenotypic data for subsequent analysis. Significant differences in ERN were observed among subpopulations, influenced by both genetic and environmental factors. This variability provides a solid foundation for further GWAS analysis and identification of important loci associated with ERN.

[0048] Table 2 Descriptive statistical analysis of the number of ear rows in the six RIL groups.

[0049]

[0050]

[0051] *Note: JH stands for Jinghong and YS stands for Yanshan

[0052] Genome-wide association analysis of 2ERN

[0053] GWAS analysis was performed using 638,646 high-quality SNP data to identify candidate genes associated with ERN. GWAS analysis was implemented using the MLM model in the GEMMA software package using phenotypic and BLUP values ​​and genotypic data in three environments. The minimum threshold of -log10p>6.0 was applied to identify significant associations. 80 SNPs significantly associated with ERN were identified in the three environments and BLUP. Among them, 21JH detected 26 significant SNPs, 22YS detected 19 significant SNPs, 23YS detected 21 significant SNPs, and BLUP detected 14 significant SNPs. These significant SNPs are distributed on all maize chromosomes. Among them, SNP2-15316355 is consistent in all environments (21JH, 22YS, 23YS and BLUP) ( Figure 2 ).

[0054] The candidate gene Zm00001eb072850 associated with SNP2-15316355 was mined in the 20kb region upstream and downstream of SNP2-15316355. The relative positions of the significant SNP2-15316355 and the candidate gene Zm00001eb072850 are shown in Figure 2. Figure 3 As shown. Zm00001eb072850 is 690 bp in length, SNP2-15316355 is located at 518 bp in its gene, and has a T / G mutation ( Figure 3 ).

[0055] 3. Haplotype analysis

[0056] Haplotype analysis of candidate genes was performed to identify dominant haplotypes associated with ERN. The Zm00001eb072850 gene corresponds to positions 15315838-15316527 from the 5' end of maize chromosome 2. Among the 780 RIL families, there were four different haplotypes at positions 15316067, 15316076, 15316100, 15316136, 15316202, 15316214, 15316241, 15316274, 15316346, 15316355, 15316361, 15316367 and 15316370 (Hap1: ACGGGGAGCTCAT; Hap2: GACGGGGACTCGT; Hap3: GCGGGGGGCTCGT; Hap4: ACGGGGAGAGCGC)( Figure 4 a). It is worth noting that compared with Hap1, Hap3 and Hap4, Hap2 (GACGGGGACTCGT) significantly increased the number of ear rows in corn ears, that is, Hap2 is a favorable haplotype ( Figure 4 b).

[0057] 4. Histone 4 gene regulation of maize ERN

[0058] The candidate gene Zm00001eb072850 was annotated as a histone superfamily protein H4 variant. As carriers of key genetic and epigenetic information, histone variants play a key role in gene expression and make significant contributions to plant growth and development and responses to biotic and abiotic stresses. However, their specific roles in maize remain largely unexplored. Histone variant genes are highly conserved among plant species and are divided into five subfamilies: core histones (H2A, H2B, H3, and H4) and linker histones (H1 / H5). Thirteen genes containing the H4 protein domain were identified in the maize genome based on homology to histone 4 (H4) genes. A phylogenetic tree was constructed using these 13 maize histone genes and eight histone genes from Arabidopsis thaliana, and it was found that the H4 protein in maize showed 100% consistency in gene length. It is noteworthy that most maize H4 genes are independent of Arabidopsis histones, while ZmHistone12, ZmHistone8, ZmHistone11, and ZmHistone10 are more closely related to Arabidopsis histones ( Figure 5 a).

[0059] The expression of maize H4 gene in four developmental stages of maize, namely ear primordium (2-4 mm), ear primordium (6-8 mm), female spikelet and vegetative meristem (16-19 days), was analyzed. The results showed that the candidate gene ZmHistone1 (i.e. Zm00001eb072850 of the present invention) showed the highest expression level in all tissue types, especially in the ear primordium stage ( Figure 5 b) This gene showed high FPKM values ​​in all tissues during the early stages of maize ear development, strongly suggesting that it is involved in the regulation of maize ERN.

[0060] The above description shows and describes several preferred embodiments of the present invention, but as mentioned above, it should be understood that the present invention is not limited to the form disclosed herein, and should not be regarded as excluding other embodiments, but can be used in various other combinations, modifications, and can be modified within the scope of the present invention through the above teachings or the technology or knowledge of the relevant field. And the changes and modifications made by those skilled in the art do not depart from the spirit and scope of the present invention, and should be within the scope of protection of the claims attached to the present invention.

Claims

1. A molecular marker associated with the number of corn ear rows, characterized in that: The molecular marker is the Zm00001eb072850 gene or a protein encoding the gene, the nucleotide sequence of the gene is shown in SEQ ID NO: 1, and the expression level of the Zm00001eb072850 gene or a protein encoding the gene is positively correlated with the number of corn ear rows.

2. A molecular marker associated with the number of corn ear rows, characterized in that: The molecular markers are SNP sites, the genome version is B73_V4, the marker SNP sites are 15316067, 15316076, 15316100, 15316136, 15316202, 15316214, 15316241, 15316274, 15316346, 15316355, 15316361, 15316367 and 15316370 sites on chromosome 2 of corn. When the bases at the sites are GACGGGGACTCGT in sequence, the corn exhibits the trait of multiple ears and rows.

3. Detection of a product labeled with a molecule according to any one of claims 1 to 2, characterized in that: The product detects the genotype of the molecular marker, or detects the expression level of the Zm00001eb072850 gene or the protein encoding the gene, and the nucleotide sequence of the gene is shown in SEQ ID NO:

1.

4. The product according to claim 3, characterized in that The products include reagents, kits or gene chips.

5. The product according to claim 3, characterized in that The products include those prepared by PCR, qPCR, Sanger sequencing, high-throughput sequencing, fluorescence in situ hybridization, TaqMan probe method, ARMS-PCR method or KASP method.

6. Any of the following applications of the molecular marker described in any of claims 1-2, or the product described in any of claims 3-5: a) genetic diversity analysis of corn ear row number; b) construction of molecular genetic map of corn ear row number; c) genome-wide association analysis of corn ear row number; d) identification of corn varieties with multiple ear rows; e) molecular marker-assisted selection breeding for corn ear row number trait; f) genome-wide selection breeding for corn ear row number trait; g) gene editing breeding for corn ear row number trait.

7. A method for selecting corn with a large number of ear rows, characterized in that: A corn sample to be tested is taken, and the molecular marker described in any one of claims 1-2 is tested. If the sample meets the molecular marker type, a corn variety with a large number of ear rows is obtained.

8. A method for increasing the number of corn ear rows, characterized in that: The overexpression Zm00001eb072850 gene or the expression level of the protein encoding the gene, wherein the nucleotide sequence of the gene is shown in SEQ ID NO: 1.

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