Maize ear row number-related molecular marker gene Zm00001eb072850 and its application

Abstract

The present invention belongs to the field of molecular marker-assisted breeding technology, and specifically discloses a molecular marker gene Zm00001eb072850 related to the number of corn ear rows and its application, 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. Through multi-year multi-point experiments, the present invention co-localizes SNP: 2-15316355 and its associated gene Zm00001eb072850 on corn chromosome 2. The SNP can be located in three different environments, and its associated candidate functional gene mainly encodes corn histones and is related to corn ear development. The molecular marker provided by the present invention can effectively shorten the breeding period, accelerate the breeding process, improve breeding efficiency, and accelerate the process of screening excellent germplasm resources.

Description

Technical Field

[0001] The invention belongs to the technical field of molecular marker-assisted breeding, and particularly relates to application of a corn ear row number molecular marker SNP:2-15316355 and its associated 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), which refers to the number of rows of kernels per ear, is a yield component directly related to maize yield. ERN is a complex quantitative trait controlled by multiple genes. Although it is closely related to maize yield, the mechanisms underlying the formation of ear row number remain relatively understudied. Therefore, identifying candidate functional genes associated with ERN has become an essential component of molecular breeding programs to improve maize yield.

[0003] The number of rows of ears is determined by the development of the maize inflorescence. The maize axillary meristem (AM) transforms into the inflorescence meristem (IM), which produces spikelet pair meristems (SPMs) in the peripheral region. Each SPM produces two spikelet meristems (SMs), which further develop into two floret meristems. Existing studies have identified several candidate genes related to ERN using methods such as GWAS. However, most of the maize genes related to the number of rows of ears that have been cloned so far are from mutant studies, and the practical application of these functional genes in maize breeding is still limited. There is still little work on the discovery of key genes with high utilization value for breeding practice obtained using map-based cloning methods. The present invention selected six recombinant inbred line populations, totaling 780 recombinant inbred lines, and used three years of ERN phenotypic data for GWAS analysis to discover candidate functional genes, in order to provide a new method for breeding new high-yield maize varieties with multiple rows of ears using modern molecular breeding techniques. Summary of the Invention

[0004] This study confirms that SNP 2-15316355 on maize chromosome 2 and its associated gene, Zm00001eb072850, have a significant positive effect on the number of rows per ear. Maize ERN (ear row number) is a quantitative trait regulated by multiple genes. The technical solutions provided by this invention offer a new method for cultivating new high-yield maize varieties using modern molecular breeding techniques. 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 rows of corn ears, 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 rows of ears.

[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 the 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 products include 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; f) Genome-wide selection breeding for corn ear row number; g) Gene editing breeding for corn ear row number.

[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 is tested. 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 used tropical maize inbred lines (YML226, Q11, R-2-1-1, YML1218, Chang7-2, and Shen137) as resistant parents and hybridized them with the temperate susceptible elite inbred line Ye107. After six consecutive generations of single-seed self-pollination, six F9 recombinant inbred lines (RILs) were selected. These RILs were planted in Yanshan County, Yunnan Province in 2021 and in Jinghong City, Yunnan Province in 2022 and 2023. Through ERN phenotype identification in three environments and combined with high-quality SNPs in the RIL population, GWAS analysis identified SNPs that were consistently significantly associated with the number of corn ear rows in multiple environments: 2-15316355 molecular markers and the functional gene Zm00001eb072850. The nucleotide sequence of the Zm00001eb072850 gene is shown in SEQ ID NO: 1. This gene is related to the development of corn ear primordium. The molecular markers provided by the present invention can effectively shorten the breeding period, accelerate the breeding process, improve breeding efficiency, and speed up the process of screening excellent and high-yield germplasm resources. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] Figure 1 Figure 2: Population structure and changes in ear row number across six subpopulations. a. Schematic diagram of multi-parent population (MPP) construction. Six parents (YML222, Q11, R-2-1-1, YML1218, Chang7-2, and Shen137) were crossed with Ye107 to generate F1 hybrids. Six generations of self-pollination were performed on the F1 progeny to generate F7 recombinant inbred lines (RILs). b. Changes in the mean and minimum / maximum number of ear rows across six subpopulations (pop1-pop6). (c) Frequency distribution of the number of ear rows across the six subpopulations.

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

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

[0019] Figure 4 Haplotype analysis of the candidate gene Zm00001eb072850. (a) The 13 SNPs 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 (Arabidopsis thaliana); maize histone H4 genes are represented in blue, and Arabidopsis in red. b: Expression patterns of H4 genes in 2-4 mm ear primordia, 6-8 mm ear primordia, 16-19 day old female flower spikelets, and vegetative meristems. Darker colors and larger circles indicate higher gene expression. DETAILED DESCRIPTION

[0021] Below in conjunction with accompanying drawing and embodiment, technical scheme of the present invention is described in detail, but therefore the present invention is not limited among described embodiment scope.Unless otherwise specified, otherwise basically according to conventional method well known in the art and described in various references, carry out the experiment and method described in embodiment, and reagent and raw material used in the present invention are all commercially available.Unindicated specific conditions in embodiment, carry out according to conventional conditions or the condition of manufacturer's suggestion.Unindicated manufacturer for reagent or instrument, all are conventional products that can be obtained by commercial.Those skilled in the art know that embodiment describes the present invention by way of example, and can not limit the scope of protection claimed in the present invention with this.

[0022] Based on genome-wide association analysis, the present invention used tropical maize inbred lines (YML226, Q11, R-2-1-1, YML1218, Chang7-2, and Shen137) as resistant parents and hybridized them with the temperate susceptible elite inbred line Ye107. After six consecutive generations of single-seed self-pollination, six F7 recombinant inbred lines (RILs) were selected. These RILs were planted in Jinghong City, Yunnan Province in 2021 and in Yanshan County, Yunnan Province in 2022 and 2023. Through ERN phenotype identification in three environments and combined with high-quality SNPs in the RIL population, GWAS analysis identified SNPs that were significantly correlated with the number of corn ear rows, including the 2-15316355 molecular marker and the functional gene Zm00001eb072850, which showed consistent performance in multiple environments. The nucleotide sequence of the Zm00001eb072850 gene is shown in SEQ ID NO: 1. The molecular markers provided by the present invention can be used in molecular breeding for high-yield corn.

[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 rows of ears and wide genetic variation were selected as female parents. They were crossed with the high-combining-ability, excellent temperate maize inbred line Ye107 as a common parent (the pedigrees, heterotic groups, and ecological groups of the seven parents are detailed in Table 1). Through single-seed descent, nine consecutive generations of self-pollination were performed to generate 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). Initially, each population contained 200 RIL lines, but due to environmental selection, inbreeding depression and other factors, the final number of RIL lines used in the present invention was 780. 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 4 m, and a plant spacing of 25 cm, and was carried out according to standard farmland management.

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

[0027]

[0028] 2. Phenotypic Identification and Statistical Analysis

[0029] Descriptive analyses of phenotypic data were performed using SPSS Statistics and ORIGIN (Origin 2022) software. Mean, minimum, maximum, standard deviation (SD), coefficient of variation (CV), skewness, and kurtosis were calculated. Frequency distributions of phenotypic data were analyzed 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 methods 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 the restriction enzymes PstI and MspI (New England BioLabs, Ipswich, MA, USA) and ligated to barcoded adapters using T4 ligase (New England BioLabs).

[0032] GBS DNA libraries were constructed and sequenced according to 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 to obtain high-quality reads 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 criterion for SNPs was set to MAF ≥ 0.05 to screen for 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 spikelets

[0035] GWAS analysis was performed on the average number of spikelets 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 was 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 labeled and unlabeled effects, respectively, and m represents an 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 a 20 kb region upstream and downstream of consistently significant SNPs across different environments. SNPs derived from the GWAS results were annotated using ANNOVAR software (v2013-05-20). The identified SNPs were searched and compared with the MaizeGDB (https: / / www.maizegdb.org) and NCBI (http: / / www.ncbi.nlm.nih.gov / ) databases to identify candidate genes and perform functional annotation. Furthermore, expression data for candidate genes regulating ERN at different time points were extracted from the MaizeGDB database, and 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. Box plots were generated to represent the relationship between haplotypes and phenotypes.

[0042] 7 Homology analysis of candidate genes

[0043] The protein domains of the 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 / ). A neighbor-joining phylogenetic tree with 1000 bootstrap replicates and complete deletion of gaps / missing data was 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 / ). The expression profiles of the identified genes were obtained and visualized using online qTeller (https: / / qteller.maizegdb.org).

[0044] result

[0045] 1. Phenotypic Data Analysis

[0046] This study used a multiparent population (MPP) consisting of 780 families from six recombinant inbred line populations 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 the number of ear rows in the six subpopulations follows a normal distribution ( Figure 1 ch).

[0047] Descriptive statistical analysis of the number of ear rows was performed on 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 used for subsequent analyses. Significant differences in ERN expression 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 ERN-related loci.

[0048] Table 2 Descriptive statistical analysis of the number of ear rows in 6 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 performed using the MLM model in the GEMMA software package using phenotypic and BLUP values ​​and genotypic data in three environments. A 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 was consistent in all environments (21JH, 22YS, 23YS and BLUP) ( Figure 2 ).

[0054] The candidate gene Zm00001eb072850 associated with SNP2-15316355 was found in the 20kb region upstream and downstream of SNP2-15316355. The relative positions of the significant SNP2-15316355 and the candidate gene Zm00001eb072850 are as follows: Figure 3 As shown. Zm00001eb072850 is 690 bp long, and SNP2-15316355 is located at 518 bp within the gene, with 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 780 RIL families, four different haplotypes were found 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 noteworthy that compared with Hap1, Hap3 and Hap4, Hap2 (GACGGGGACTCGT) significantly increased the number of ear rows in maize 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. Histone variants, as carriers of key genetic and epigenetic information, play a crucial role in gene expression, contributing significantly 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 across plant species and are divided into five subfamilies: core histones (H2A, H2B, H3, and H4) and linker histones (H1 / H5). Homology to histone 4 (H4) genes in the maize genome identified 13 genes containing the H4 protein domain. A phylogenetic tree was constructed using these 13 maize histone genes and eight histone genes from Arabidopsis thaliana, revealing that the maize H4 proteins exhibit 100% identity 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 at 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 at 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 its involvement in the regulation of maize ERN.

[0060] The foregoing description shows and describes several preferred embodiments of the present invention. However, as previously stated, it should be understood that the present invention is not limited to the forms disclosed herein and should not be construed as excluding other embodiments. Rather, the present invention is applicable to various other combinations and modifications and can be modified within the scope of the present invention through the above teachings or the skills or knowledge in the relevant field. Modifications and variations made by those skilled in the art that do not depart from the spirit and scope of the present invention are intended to be protected by the appended claims.

Claims

1. Application of a product for detecting molecular markers related to the number of corn ear rows in molecular marker-assisted selection breeding for the number of corn ear rows trait, characterized in that: The molecular marker is a SNP site, the genome version is B73_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 of the sites are GACGGGGACTCGT in sequence, the corn exhibits the trait of multiple ears and rows; the product detects the genotype of the molecular marker.

2. The use according to claim 1, characterized in that The products include reagents, kits or gene chips.

3. A method for screening 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 claim 1 is tested. If the sample meets the molecular marker type, a corn variety with a large number of ear rows is obtained.

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