A constitutive QTL for maize mesocotyl length and its molecular marker and application

Abstract

The present invention belongs to the field of molecular biology, and specifically relates to a constitutive QTL for regulating the length of the mesocotyl of corn, named cQMES4, and its molecular markers and applications. The molecular marker of this cQMES4 is composed of two pairs of SSR molecular marker primers, umc1869 and umc1775. When the SSR molecular markers of the present invention are used to assist in the selection of deep-sowing-resistant corn materials with long mesocotyl characteristics, it is only necessary to detect the characteristic bands of the SSR molecular markers to predict the deep-sowing resistance of the corn material. The identification method is easy to operate, simple and feasible, and has high selection efficiency. It has great application potential in the field of deep-sowing-resistant corn breeding, thereby ensuring the safety of corn production in arid areas.

Description

Technical Field

[0001] The present invention belongs to the field of maize molecular genetic breeding, and specifically relates to a maize mesocotyl length constitutive QTL (cQTL), namely cQMES4, and its molecular marker and application. Background Art

[0002] Low soil moisture and precipitation during corn sowing prevent the seeds from absorbing soil moisture and germinating quickly. This significantly prolongs the emergence time, reduces the emergence rate, and even causes seed dust. This leads to severe seedling shortages and broken ridges during the seedling stage, ultimately severely reducing corn yields. In long-term agricultural practice, Native Americans in arid regions of western Mexico and the southwestern United States have widely cultivated the corn variety "P1213733 (Komona)" (Zhao et al., 2021), which can be sown at a depth of 30 cm. The corn variety "40107" (Zhao Xiaoqiang and Zhong Yuan, 2021), which can be sown at a depth of 26 cm, has also been promoted in arid regions of northwest my country. These deep-sowing corn varieties offer numerous advantages, including high emergence rates, good plant growth, strong drought resistance, and high yields, effectively ensuring corn production safety in arid and semi-arid regions.

[0003] Deep sowing tolerance in different crops is determined by the elongation of different tissues and organs. For example, wheat (Triticum aestivum L.) and barley (Hordeum vulgare L.) achieve seedling after deep sowing primarily through elongation of the coleoptile and first internode (Takahashi et al., 2001; Mohan et al., 2013), while maize (Zea mays L.) and rice (Oryza sativa L.) primarily rely on significant elongation of the mesocotyl (Zhao et al., 2021; Lee et al., 2012). Furthermore, deep sowing tolerance in different crops is an extremely complex quantitative genetic trait, regulated by multiple microgenes and interactions with the environment (Zhang et al., 2012). Due to limitations in the genetic background, size, and type of mapping populations, high-throughput sequencing technology, molecular markers, and molecular marker density, the number of constitutive QTL (cQTL) loci for deep-sowing tolerance that have high contribution rates and breeding application value is currently very limited in these crops. This restricts the development and application of molecular marker-assisted selection (MAS) breeding for deep-sowing tolerance and drought resistance in crops, thereby significantly extending the breeding cycle of new excellent deep-sowing-tolerant and drought-resistant varieties. Summary of the Invention

[0004] The present invention aims to provide a method using conventional QTL mapping and bulked-segregation analysis (BSA) technology, combined with molecular bioinformatics methods, to explore the regulation of maize deep sowing tolerance traits, especially cQMES4 and its SSR molecular markers for regulating maize mesocotyl length, in different genetic background populations under multiple sowing depth environments. Furthermore, the present invention provides a method for assisting the selection of excellent deep sowing tolerance maize with long mesocotyl characteristics. In addition, the present invention also provides an application of a molecular marker for regulating mesocotyl length cQMES4 in maize deep sowing tolerance breeding.

[0005] In order to solve the above technical problems, the present invention adopts the following technical solutions:

[0006] 1. SSR molecular marker primers for maize mesocotyl length cQMES4, including two pairs of SSR molecular marker primers umc1869 and umc1775. The sequences of SSR molecular marker primers are as follows:

[0007] As shown in the sequence listing SEQ ID NO: 1 and SEQ ID NO: 2, the sequence of the SSR molecular marker primer umc1869 is:

[0008] Forward:5'-CGAGCGCTCTAGACACGATTTT-3';

[0009] Reverse:5'-GAACTGGAGGAGCGAGCATGTAT-3';

[0010] As shown in the sequence listing SEQ ID NO: 3 and SEQ ID NO: 4, the sequence of the SSR molecular marker primer umc1775 is:

[0011] Forward:5'-GGAACTCCGTCAAAATCCCATC-3';

[0012] Reverse:5'-GAGGACAACGCTGCTATTCTCG-3';

[0013] The above-mentioned SSR molecular marker of maize mesocotyl length cQMES4 regulates maize mesocotyl length under different sowing depth environments.

[0014] 2. Application of the SSR molecular marker cQMES4 for maize mesocotyl length in maize deep sowing tolerance breeding, to assist in the selection of deep sowing tolerance maize materials with long mesocotyl characteristics for application in maize deep sowing tolerance breeding; can be amplified by PCR with primers umc1869 and umc1775; and obtain amplification products with lengths of 232bp and 249bp, then the maize to be tested is a deep sowing tolerance maize variety or line with long mesocotyl characteristics.

[0015] 3. A method for assisting in the selection of deep-sowing-resistant corn materials with long mesocotyl characteristics, comprising the following steps: extracting genomic DNA of the corn material to be tested; performing PCR amplification using SSR molecular marker primers umc1869 and umc1775; when amplification products of 232 bp and 249 bp in length are obtained, the corn to be tested is deep-sowing-resistant corn with long mesocotyl characteristics.

[0016] 4. A method for obtaining molecular markers for maize mesocotyl length cQTL, the specific detailed steps are as follows: (1) F 2:3 (1) QTL mapping of maize mesocotyl length in a population; (2) BSA-Seq analysis of maize mesocotyl length in a BSA pool; (3) Collection and organization of QTL information for deep sowing tolerance in maize; (4) Localization of cQTL for maize mesocotyl length using a combination of multiple methods; (5) Screening of candidate genes for the cQTL interval for maize mesocotyl length.

[0017] The present invention has the following beneficial effects: Using conventional QTL mapping and BSA technology, combined with molecular bioinformatics methods, the present invention discovered a gene, cQMES4, that regulates deep sowing tolerance in maize, specifically mesocotyl length, across multiple genetic backgrounds under various sowing depth environments. The gene is located at 160,984,132 bp to 176,222,964 bp in the Bin 4.06-4.07 interval of chromosome 4, and has a high phenotypic contribution rate (cumulative contribution rate of 554.58%). Further analysis showed that PCR amplification of the test maize materials using two pairs of SSR molecular marker primers, umc1869 and umc1775, within the cQMES4 interval, can rapidly, objectively, and accurately predict the mesocotyl length of the test maize.

[0018] When molecular marker-assisted selection of corn materials with long mesocotyl characteristics is performed using the SSR molecular markers disclosed in the present invention, the mesocotyl length of the corn material can be predicted by simply detecting the characteristic amplified bands of the corresponding SSR molecular markers. This identification method is easy to operate, simple and feasible, and has high selection efficiency. Deep-sowing-resistant corn plants with long mesocotyl characteristics can be quickly identified and eliminated. The selection target is clear and is not affected by the environment, effectively improving the breeding utilization value of candidate corns. It has huge breeding application potential. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] Figure 1 The results of the parental K12 and W64A and their F1 hybrid and F1 hybrid were analyzed under the sowing depth of 3 cm, 15 cm and 20 cm. 2:3 Mesocotyl length phenotype analysis of segregating populations;

[0020] Different lowercase letters represent significant differences at the P<0.05 level between different sowing depth treatments of the same corn material;

[0021] Figure 2 and 3 Compared with the normal sowing depth treatment, the average change rate of the mesocotyl length of different maize materials under the 15cm and 20cm sowing depth stress treatments was analyzed;

[0022] Where MRC represents the mean rate of change of mesocotyl length, F is the F-value in ANOVA analysis, and ** represents a significant difference at the P < 0.01 level in ANOVA analysis;

[0023] Figure 3 Genetic mapping of F2 segregating populations and composite interval mapping (CIM) method for maize F2 in a single environment 2:3 Results of QTL mapping for cotyledon length in segregating populations;

[0024] Among them, 3cm represents the detection of mesocotyl length QTL under the normal sowing depth of 3cm, 15cm represents the detection of mesocotyl length QTL under the stress sowing depth of 15cm, and 20cm represents the detection of mesocotyl length QTL under the stress sowing depth of 20cm.

[0025] Figure 4 The growth of mesocotyls under the stress of extreme mixed pond sowing at 20 cm depth in maize;

[0026] LM-pool represents the 30 progeny pools with the longest mesocotyls, and SM-pool represents the 30 progeny pools with the shortest mesocotyls;

[0027] Figure 5 Box plot analysis of mesocotyl length under extreme maize mixed pond 20 cm deep sowing stress treatment;

[0028] LM-pool represents the 30 progeny pools with the longest mesocotyls, and SM-pool represents the 30 progeny pools with the shortest mesocotyls; ** represents the difference in mesocotyl length between LM-pool and SM-pool at the P < 0.01 level;

[0029] Figure 6 Distribution of maize mesocotyl length SNP-index (A) and InDel-index (B) obtained by BSA-Seq analysis;

[0030] Figure 7 Bins location distribution on maize chromosome 4 (A), related QTL location distribution detected in the cMES4 interval (B), and their BSA distribution and candidate gene location distribution (C);

[0031] Among them, MES is mesocotyl length, COL is coleoptile length, SDL is seedling length, VI is seed vigor index, and MGT is mean seed germination time. Specific implementation methods

[0032] To make the purpose, technical solutions and advantages of the present invention more clear, the specific implementation methods of the present invention are described in detail below with reference to specific examples. Unless otherwise specified, the experimental methods in the following examples are all conventional experimental methods. Unless otherwise specified, the experimental reagents and consumables described in the following examples are all from conventional biochemical reagent companies. To make the purpose, technical solutions and advantages of the present invention more clear, the specific implementation methods of the present invention are described in detail below with reference to specific examples. Examples of these preferred embodiments are illustrated in the specific examples.

[0033] It should also be noted here that, in order to avoid obscuring the technical solution of the present invention due to unnecessary details, only the technical solutions and / or processing steps closely related to the solution of the present invention are shown in the embodiments, while other details that are not very relevant are omitted.

[0034] Example 1

[0035] The present invention provides a method for mapping a maize mesocotyl length QTL, and the specific detailed steps are as follows:

[0036] 1.F2 and F 2:3 Construction of segregating population: short mesocotyl inbred line K12 (male parent) and long mesocotyl inbred line W64A (female parent) were planted in the field, and hybridized during flowering to obtain their F1 hybrids. The F1 hybrids were continued to be planted in the field the following year, bagged and pollinated during flowering, and self-pollinated to obtain an F2 segregating population containing 346 grains. In April 2020, the seeds of the F2 segregating population containing 346 grains and the seeds of its two parent inbred lines were continued to be sown at a planting density of 4500 plants / mu in Longxi, Gansu (34.97°N; 104.40°E; 2074m above sea level). Before sowing, the plants were uniformly covered with film (film length 120cm, film thickness 0.02mm), and other management measures were the same as local general field management. When the corn seedlings grew to the three-leaf and one-heart stage, the leaves of each F2, K12 and W64A plant were cut and stored in liquid nitrogen at -80℃. During flowering, the F2 single plant was strictly bagged and pollinated by self-pollination to derive the F 2:3 Separate the group. Harvest F at the end of September 2:3 Separate the clusters, dry them naturally and test them for seeds.

[0037] 2. Extraction and quality testing of genomic DNA from both parents and F2 segregating populations: The genomic DNA from the parental inbred lines K12 and W64A and each F2 seedling sample from step 1 above was extracted using the CTAB method. The DNA quality of each sample was tested using 1% agarose gel electrophoresis using a NanoDrop TMThe DNA concentration of each sample was analyzed using a One / OneC (Thermo Fisher Scientific) ultraviolet spectrophotometer, and the DNA concentration was diluted to 50 ng / μL for later use.

[0038] 3. SSR Molecular Marker Primer Design and Synthesis: First, 1000 pairs of SSR molecular marker primers uniformly distributed across the ten maize chromosomes were downloaded from the Maize Genome Database (MaizeGDB) public website (http: / / www.maizegdb.org / ). These molecular marker primers were synthesized by Sangon Biotech (Shanghai) Co., Ltd. These SSR molecular marker primers were synthesized using the HAP purification method. Finally, these SSR molecular marker primers (each SSR molecular marker primer consists of Primer 1 and Primer 2) were diluted to a concentration of 1 mmol / L and set aside.

[0039] 4. Selection of primers for parental polymorphic SSR markers: Using the genomic DNA from the two parental samples extracted in step 2 above as templates and the SSR markers designed and synthesized in step 3 above as primers, PCR amplification was performed using a German-made Biometra-T1 PCR instrument. A 20 μL reaction system was used: 0.6 μL of Primer 1 (1 mmol / L), 0.6 μL of Primer 2 (1 mmol / L), 1.4 μL of DNA (50 ng / μL), 10.0 μL of 2× Power Taq PCR Master Mix, and 7.4 μL of UPH2O. The PCR protocol was as follows: 1 cycle of initial denaturation at 95°C for 5 min; 36 cycles of denaturation at 94°C for 0.5 min, annealing at 50.0-60.3°C for 0.5 min, and extension at 72°C for 0.5 min; a final extension at 72°C for 1 min, followed by storage at 4°C for 60 min. The DNA genomic PCR amplification products of K12 and W64A were run on 8% non-denaturing polyacrylamide gel electrophoresis and silver stained to identify SSR markers of polymorphism between parents K12 and W64A for subsequent whole genome scanning and genetic map drawing of F2 segregating populations.

[0040] 5. Whole genome scanning of SSR molecular markers and drawing of genetic maps of F2 segregating populations: Select the genomic DNA of individual seedlings of the F2 segregating population and the seedlings of parents K12 and W64A extracted in step 2 above, and perform whole genome scanning with polymorphic SSR molecular markers between the parents according to the method in step 4 above, and analyze the genotype of the F2 population at each SSR molecular marker site. The distribution of the genotype of each SSR molecular marker in the F2 segregating population was subjected to a chi-square test, and the SSR molecular marker information with a segregation ratio of maternal genotype: heterozygous genotype: paternal genotype that met 1:2:1 was obtained. The genetic map drawing software JoinMap4.0 (http: / / www.kyazma.nl / index.php / mc.JoinMap / sc.Evaluate / ) was used to draw the genetic map of the F2 segregating population, and the genetic distance (centimorgan, cM) of the genetic map was set to be calculated using the Kosambi function method. This drawn genetic map is used for subsequent F 2:3 QTL mapping analysis of embryonic axis length in segregating populations.

[0041] 6. Identification of maize mesocotyl length phenotype under different sowing depths: Each F 2:3 20 seeds of each of the segregating population, F1 hybrid, and its parents K12 and W64A were weighed in sequence, and then the seeds were sterilized by shaking continuously for 10 minutes at a ratio of 1 g seed mass to 10 mL of NaClO solution (0.5% by volume), and then the seeds were rinsed three times with 100 mL of ddH2O water with shaking continuously. Finally, the sterilized seeds were placed in a dark environment at 20±1°C indoors and soaked in a ratio of 1 g seed mass to 8 mL of ddH2O water for 24 hours to obtain soaked seeds. Before sowing, the sterilized vermiculite mass and 5 g ddH2O water volume were stirred evenly to prepare a cultivation medium. A seed deep sowing test device with an inner diameter of 17 cm and a height of 50 cm was selected (authorization announcement number: CN 209768182U) was used as a sowing device. When sowing, the sowing device was first loaded with cultivation substrate in layers. Then, 30 soaked seeds were evenly sown on the surface of the cultivation substrate. Then, the surface of the seeds was covered with 3 cm, 15 cm, and 20 cm of cultivation substrate, respectively, until the cultivation substrate just filled the sowing device. The device was then placed in an intelligent artificial climate chamber (65% relative humidity, 12 h / 12 ​​h light / dark, 600 μmol / (sm 2) light intensity and cultured in a constant temperature environment of 22 ± 1°C. Every two days, 20 mL of ddH2O was added to each sowing container. This experiment included three sowing depth treatments: 3 cm (normal sowing depth), 15 cm (15 cm deep sowing stress), and 20 cm (20 cm deep sowing stress). Three biological replicates were used for each sowing depth treatment. 2:3 Ten days after germination of seeds of segregating populations, F1 hybrids, parents K12, and W64A, the culture medium at the roots of the seedlings was quickly washed off with clean water, and ten seedlings with overall uniform growth were selected to measure their mesocotyl length (MES).

[0042] 7. Analysis of the average change rate and kurtosis / skewness of maize mesocotyl length under different sowing depths: The F values ​​measured under the three sowing depths in step 6 above were 2:3 The mesocotyl length phenotypes of the population, F1 hybrids, and parents K12 and W64A were calculated according to the following formula to calculate the mean rate of change (MRC) of mesocotyl length of corn materials in different populations under the treatments of 15 cm and 20 cm sowing depth, namely: MRC i =[MES CK -MES DS(i) ] / MES CK × 100%. Where MRC i is the average change rate of mesocotyl length under the i-th deep sowing stress treatment (15 cm or 20 cm), MES CK The length of the mesocotyl under the normal sowing depth of 3 cm, MES DS(i) is the mesocotyl length under the deep sowing stress treatment of type i (15 cm or 20 cm). The statistical analysis software IBM-SPSS 19.0 (SPSS Inc., Chicago, IL, USA) was used to calculate F 2:3 Kurtosis and skewness of hypocotyl length in segregating populations under three sowing depth treatments.

[0043] 8. F under different sowing depths 2:3 QTL mapping of mesocotyl length in segregating populations: Combined with step 6 above, F 2:3The mesocotyl length phenotype of the segregating population and the genome-wide scanning results of SSR molecular markers of the F2 segregating population in step 5 were analyzed using the composite interval mapping (CIM) method in Windows QTL Cartographer version 2.5 software (http: / / statgen.ncsu.edu / qtlcart / WQTLcart.htm) to analyze the F length of the segregating population under single sowing depth treatment. 2:3 QTL mapping for mesocotyl length was performed in segregating populations. For CIM, the Zmapqtl program module Model 6 was used with a 10.0 cM window size. Genotypes for mesocotyl length were scanned every 0.5 cM. The LOD threshold (LOD > 3.0) was determined by sampling 1000 times. The genetic effect of mesocotyl length QTLs was estimated based on the absolute value of the ratio of the dominant effect (d) to the additive effect (a): |d / a| = 0.00-0.20 indicates an additive effect (A), |d / a| = 0.21-0.80 indicates a partial-dominance effect (PD), |d / a| = 0.81-1.20 indicates a dominant effect (D), and |d / a| > 1.20 indicates an over-dominance effect (OD). Major QTLs with a contribution of > 10% to the mesocotyl phenotype were identified.

[0044] Example 2

[0045] The present invention provides a method for BSA-Seq analysis of corn mesocotyl length, and the specific detailed steps are as follows:

[0046] 1. Construction of BSA extreme progeny mixed pool and parent pool: Each F 2:3 20 seeds of each isolated population were weighed in sequence, and then the seeds were shaken continuously for 10 minutes according to the ratio of seed mass to NaClO solution (0.5% by volume) of 1g:10mL, and then the seeds were washed 3 times with 100mL of ddH2O water by shaking continuously. Finally, the sterilized seeds were placed in the dark and soaked for 24 hours at a ratio of seed mass to ddH2O water volume of 1g:8mL at a temperature of 20±1℃. Seed F was obtained. 2:3 Separate the group seeds; before sowing, first mix the sterilized vermiculite mass and ddH2O water volume at a ratio of 5g:1mL to prepare a cultivation medium; select a seed deep sowing test device with an inner diameter of 17cm and a height of 50cm (authorization announcement number: CN209768182U) as a sowing device, first load the cultivation medium into the sowing device in layers, and then soak the seeds in the F2:3 Thirty seeds of each isolated population were evenly sown on the surface of the cultivation substrate, and then the surface of the seeds was covered with 20 cm of cultivation substrate until the cultivation substrate just filled the sowing device, thus obtaining the 20 cm deep sowing stress treatment. 2:3 The seeds of the isolated population were placed in an intelligent artificial climate chamber (65% relative humidity, 12h / 12h light / dark, 600μmol / (sm 2 ) light intensity, and culture in a constant temperature environment of 22±1℃ for 10 days. Every 2 days, add 20mL of ddH2O water to each sowing container. After 10 days, select each F with the same overall growth. 2:3 The mesocotyl length (MES) of 10 seedlings from the segregating population was measured. 2:3 The mesocotyl length phenotype of the isolated population under the 20 cm deep sowing treatment was screened out, and the 30 F clones with the longest mesocotyl length were selected. 2:3 Separating families and 30 F with the shortest mesocotyl length 2:3 Families were isolated and corresponding F2 individual seedling leaves were found. Equal amounts of 0.1 g of leaves were evenly mixed to form the long mesocotyl progeny pool (LM-pool) and the short mesocotyl progeny pool (SM-pool). The pool sizes for these two extreme progeny were 30 + 30. 1.0 g of leaves from the parents K12 and W64A were also selected to serve as the paternal and maternal pools, respectively, for subsequent BSA-Seq sequencing.

[0047] 2. BSA-Seq Sequencing of Extreme Progeny and Parental Pools: Genomic DNA from the two extreme progeny pools (LM-pool and SM-pool) constructed in Step 1 above, as well as leaves from the paternal pools K12 and maternal pools W64A, was extracted using the CTAB method and sequenced using the Illumina NovaSeq 6000 platform (Illumina, San Diego, CA). Reads were cleaned and filtered using Illumina Casava 1.8. After filtering out low-quality and short reads, they were mapped to the Zea_maysB73_V4 reference genome (ftp: / / ftp.ensemblgenomes.org / pub / plants / release-46 / fasta / zea_mays / dna / ). Single nucleotide polymorphisms (SNPs) and insertions and deletions (InDels) were identified using GATK software. The obtained SNPs / small InDels were then annotated and predicted using snpEff software (http: / / snpeff.sourceforge.net / SnpEff_manual.). BSA-Seq sequencing was performed by Nanjing Jisi Huiyuan Biotechnology Co., Ltd.

[0048] 3. Detection of the BSA region linked to maize mesocotyl length: In order to more intuitively reflect the distribution of SNP-index on maize chromosomes, the SNP-index and ΔSNP-index in the two mixed pools LM-pool and SM-pool were calculated respectively. The window was set to 1Mb and the step size was set to 100Kb. The mean of the SNP-index in each window was calculated to reflect the SNP-index distribution of the LM-pool and SM-pool, and the difference was used to obtain the ΔSNP-index. 1000 permutation tests were performed, and a 99% confidence level screening threshold was selected to obtain the distribution of the ΔSNP-index of the two mixed pools LM-pool and SM-pool on maize chromosomes. The BSA region linked to maize mesocotyl length was determined using the QTL-Seq method with a confidence level of ΔSNP-index>99% and a q-value<0.01.

[0049] 4. Screening of candidate genes in the BSA interval linked to maize mesocotyl length: The genes in the BSA interval linked to maize mesocotyl length detected in step 3 above were analyzed using Blast software for Nr (http: / / www.ncbi.nlm.nih.gov / pubmed), GO (http: / / bioinfo.cau.edu.cn / agriGO / ), KEGG (http: / / www.genome.jp / kegg / ), Swiss-Prot (https: / / web.expasy.org / docs / swiss-prot_guideline.html), and COG (https: / / www.ncbi.nlm.nih.gov / COG / ). Based on gene function, candidate genes regulating maize mesocotyl length were screened.

[0050] Example 3

[0051] The present invention provides a method for locating a constitutive QTL (cQTL) for maize mesocotyl length, and the specific detailed steps are as follows:

[0052] 1. Collection and organization of QTL information for deep seeding tolerance in maize: First, QTL information for deep seeding tolerance in maize was collected from databases such as NCBI (https: / / blast.ncbi.nlm.nih.gov / ), MaizeGDB (http: / / www.MaizeGDB.org / ), and CNKI (http: / / epub.cnki.net / ). This included QTL location, contribution rate, regulatory traits, detection environment, QTL mapping method, marker type and physical location, mapping population type and size, and literature source.

[0053] 2. Mapping of maize mesocotyl length cQTL: Based on the maize mesocotyl length QTL and linked BSA interval information detected by conventional QTL mapping and BSA analysis in this study, and combined with the maize deep sowing tolerance QTL information collected in step 1, QTLs regulating multiple maize deep sowing tolerance traits across different populations under multiple environments were detected. Intervals that highly overlapped with the major QTL regulating mesocotyl length (contribution rate >10%) and linked BSA located in this study were considered as one cQTL interval. BioMercator v.4.2 software (http: / / www.bioinformatics.org / mqtl / wiki / ) was used to construct a physical map of the cQTL interval. Patentin version 3.5 software was used to generate a list of SSR molecular marker sequences at both ends of the cQTL (as shown in the sequence listing).

[0054] 3. Screening of candidate genes within the cQTL interval for maize mesocotyl length: Based on the cQTL information for mesocotyl length detected in step 2 above, genes within the cQTL interval were identified. Based on the functional annotations of the corresponding genes using the Nr (http: / / www.ncbi.nlm.nih.gov / pubmed), GO (http: / / bioinfo.cau.edu.cn / agriGO / ), KEGG (http: / / www.genome.jp / kegg / ), Swiss-Prot (https: / / web.expasy.org / docs / swiss-prot_guideline.html), and COG (https: / / www.ncbi.nlm.nih.gov / COG / ) phylogenetic tree, important candidate genes regulating maize mesocotyl length within the cQTL interval were screened.

[0055] Example 4

[0056] The present invention provides a result of QTL mapping for maize mesocotyl length, and the specific results are as follows:

[0057] 1. Identification of maize mesocotyl length phenotypes under different sowing depths: F containing 346 families under 3 cm, 15 cm, and 20 cm sowing depths 2:3 The mesocotyl lengths of the isolated groups were 3.74 cm, 10.95 cm and 13.09 cm respectively ( Figure 1 ), and its skewness and kurtosis were 0.112 and 0.110, 0.450 and 0.301, and 0.982 and 0.337, respectively, showing typical quantitative genetic characteristics. This indicates that maize mesocotyl length is a quantitative genetic trait. Therefore, further conventional QTL mapping and detection are feasible. In addition, compared with the normal sowing depth of 3 cm, the sowing depth of 15 cm stress treatment showed that the length of the mesocotyl in K12, W64A, F1 hybrids and F 2:3 The average mesocotyl length of the segregating populations was 41.4%, 169.1%, 233.8% and 192.8%, respectively. Under the 20 cm sowing depth stress treatment, the average mesocotyl length of K12, W64A, F1 hybrid and F 2:3 The average mesocotyl length of the isolated groups was extended by 124.1% / 232.5% / 293.8% and 250.0% ( Figure 2 This indicates that deep sowing stress treatments can promote maize mesocotyl elongation to varying degrees. Therefore, mesocotyl length is an important indicator of maize tolerance to deep sowing, and QTL analysis of this trait can lay the foundation for marker-assisted selection (MAS) breeding of maize for deep sowing tolerance.

[0058] 2. Screening of polymorphic SSR molecular marker primers between parents and mapping of F2 segregating population genetics: 1000 pairs of SSR molecular marker primers were designed and synthesized from the maize GDB database. These primers were used to screen for polymorphic SSR molecular marker primers between parents K12 and W64A. 254 pairs of SSR molecular marker primers with obvious polymorphism were screened. These polymorphic SSR molecular marker primers were further used to perform a genome-wide SSR molecular marker scan on an F2 segregating population containing 346 individual plants, and a genetic map of this population was finally mapped ( Figure 3 ) for subsequent maize mesocotyl length QTL mapping analysis.

[0059] 3. F under different sowing depths 2:3 QTL mapping of mesocotyl length in segregating populations: Using the CIM method, this set of F 2:3 A total of seven QTLs significantly regulating maize mesocotyl length were detected in the segregating population under 3 cm, 15 cm, and 20 cm seeding treatments (P < 0.05). These QTLs were distributed on chromosomes 1, 3, 4, 6, and 7 (Table 1; Figure 3 ). 68.75%, 6.25%, 6.25% and 18.75% of the QTLs were controlled by additive (A), partial dominance (PD), dominant (D) and overdominant (OD) effects of the genes, respectively (Table 1). In addition, four major QTLs regulating mesocotyl length were detected (phenotypic contribution [PVE] of QTL > 10%), namely, qMES1-1 (Bin 1.09; interval umc2047-bnlg1597), which explained 2.89%, 8.34% and 10.01% of the phenotypic contribution at 3 cm, 15 cm and 20 cm sowing depths, respectively; qMES3-1 (Bin 3.04; interval umc1527-umc2261), which explained 11.60% and 4.94% of the phenotypic contribution at 15 cm and 20 cm sowing depths, respectively; and qMES4-1 (Bin The major QTLs (bin 4.06-4.07; umc1869-umc1775 interval) explained 3.81%, 9.46%, and 13.97% of the phenotypic contribution at 3 cm, 15 cm, and 20 cm sowing depths, respectively. qMES6-1 (bin 6.01; umc2311-umc2196 interval) explained 8.11%, 5.06%, and 10.03% of the phenotypic contribution at 3 cm, 15 cm, and 20 cm sowing depths, respectively (Table 1). Furthermore, the alleles promoting mesocotyl elongation in these four major QTLs all originated from the long mesocotyl parent, W64A (Table 1). Therefore, these major QTLs may provide important reference and QTL molecular marker information for future maize breeding programs focused on deep sowing tolerance using marker-assisted selection (MAS).

[0060] Table 1. F values ​​at 3cm, 15cm and 20cm sowing depths using the CIM method. 2:3 QTL mapping results for mesocotyl length in segregating populations

[0061]

[0062] Note: MES stands for mesocotyl length, PVE stands for phenotypic contribution of QTL.

[0063] Example 5

[0064] The present invention provides the results of a BSA-Seq analysis of corn mesocotyl length, and the specific results are as follows:

[0065] 1. Phenotypic analysis of mesocotyl length in mixed pools of progeny under 20 cm deep sowing stress: Under 20 cm deep sowing stress, the average mesocotyl lengths of 30 LM-pools and 30 SM-pools were 16.2 cm and 5.5 cm, respectively, which were significantly different at the P < 0.01 level ( Figure 4 and Figure 5 ). Therefore, it can be used for subsequent BSA-Seq sequencing analysis.

[0066] 2. BSA-Seq Results: Resequencing was performed on the LM-pool and SM-pool progeny pools, as well as the K12 and W64A parental pools. After filtering and removing low-quality reads, clean reads of 59.62 Gb and 65.17 Gb were obtained for the K12 and W64A parental pools, respectively (Table 2). Furthermore, clean reads of 84.71 Gb and 102.90 Gb were obtained for the LM-pool and SM-pool progeny pools, respectively (Table 2). Further mapping of the clean reads from the four mixed pools to the Zea_mays B73_V4 reference genome (ftp: / / ftp.ensemblgenomes.org / pub / plants / release-46 / fasta / zea_mays / dna / ) revealed that the genome coverage of the LM-pool and SM-pool progeny pools was 41.10× and 50.10×, respectively (Table 2).

[0067] Table 2 Statistics of sequencing data volume and data quality of different mixed pool samples

[0068]

[0069] Note: W64A is the maternal pool, K12 is the paternal pool, LM-pool is the pool of 30 progeny with the longest mesocotyls, and SM-pool is the pool of 30 progeny with the shortest mesocotyls.

[0070] 3. SNP and InDel Variability Detection: A total of 1,091,0818 and 11,030,104 SNPs were detected in the W64A and K12 parental pools, respectively, of which 119,191 and 118,942 were non-synonymous. A total of 15,382,895 and 15,604,761 SNPs were detected in the LM-pool and SM-pool progeny pools, respectively, of which 174,520 and 176,522 were non-synonymous (Table 3). Furthermore, 2,454,187, 2,473,420, 2,664,711, and 2,663,176 small InDels were identified in the W64A, K12, LM-pool, and SM-pool pools, respectively (Table 4).

[0071] Table 3 Annotation statistics of SNPs sites after sequencing of different pooled samples

[0072]

[0073] Note: W64A is the maternal pool, K12 is the paternal pool, LM-pool is the pool of 30 progeny with the longest mesocotyls, and SM-pool is the pool of 30 progeny with the shortest mesocotyls.

[0074] Table 4 Annotation statistics of InDels sites after sequencing of different pooled samples

[0075]

[0076]

[0077] Note: W64A is the maternal pool, K12 is the paternal pool, LM-pool is the pool of 30 progeny with the longest mesocotyls, and SM-pool is the pool of 30 progeny with the shortest mesocotyls.

[0078] 4. Detection of BSA intervals linked to mesocotyl length and analysis of genes within the intervals: By calculating the pooled ΔSNP- / InDel-index, three significantly linked SNP-region intervals and four significantly linked InDel-region intervals were found to be closely associated with maize mesocotyl length (Table 5; Figure 6 The BSA-SNP1-1 interval is located at 243,149,664 bp to 251,888,006 bp on chromosome 1 and contains 169 genes. The remaining six BSA intervals (BSA-SNP4-1, BSA-SNP4-2, BSA-InDel4-1, BSA-InDel4-2, BSA-InDel4-3, and BSA-InDel4-4) are all located at 160,984,132 bp to 176,222,964 bp on chromosome 4 and contain a total of 329 genes (Table 5).

[0079] Table 5. BSA intervals of maize mesocotyl length located

[0080]

[0081] In this study, conventional QTL mapping and BSA-Seq analysis of maize mesocotyl length revealed that the major effect qMES4-1, located at Bin 4.06-4.07 of chromosome 4, highly overlapped with six BSA intervals spanning 160,984,132 bp to 176,222,964 bp on chromosome 4 (Tables 1 and 5). This interval may be an important cQTL locus regulating maize mesocotyl length. This also provides a theoretical basis for the application of SSR markers umc1869 and umc1775, which are associated with the major effect qMES4-1, in marker-assisted selection (MAS) breeding.

[0082] Example 6

[0083] The present invention provides a maize mesocotyl length cQMES4 localization result and its molecular marker, and the specific results are as follows:

[0084] 1. Collection and organization of QTL positioning information for deep sowing tolerance in maize: We focused on collecting QTL information regulating deep sowing tolerance in maize near the main effect region qMES4-1 (Bin 4.06-4.07) of this study. In addition to the QTLs or linked BSA intervals for maize mesocotyl length identified in this study, including qMES4-1, BSA-SNP4-1, BSA-SNP4-2, BSA-InDel4-1, BSA-InDel4-2, BSA-InDel4-3, and BSA-InDel4-4, we also identified six QTLs for deep sowing tolerance in maize: qMES4-2 and qMES4-3, which regulate mesocotyl length; qCOL4-1, which regulates coleoptile length; qSDL4-1, which regulates seedling length; qVI4-1, which regulates seed vigor index; and qMGT4-1, which regulates average seed germination time. The cumulative phenotypic contribution rate was 54.58% (Table 6). This indicates that the major effect qMES4-1 at bin 4.06-4.07 and the other six BSA intervals identified in this study are reliable genetic loci for deep sowing tolerance in maize, particularly mesocotyl length.

[0085] Table 6 Statistics of maize mesocotyl length QTLs and BSA information collected at Bin4.06-4.07 on chromosome 4

[0086]

[0087] Note: MES is mesocotyl length, COL is coleoptile length, SDL is seedling length, VI is seed vigor index, MGT is mean seed germination time, PVE is phenotypic contribution rate of QTL.

[0088] 2. Mapping of maize mesocotyl length cQMES4: Since the six QTLs for maize deep sowing tolerance obtained by previous studies highly overlap with the main effect qMES4-1 (Bin 4.06-4.07) and six BSA intervals detected in this study ( Figure 7 A-7C). Therefore, this Bin4.06-4.07 region is an important cQTL locus for regulating maize mesocotyl length, which is named cQMES4 ( Figure 7 A-7C).

[0089] 3. Prediction of candidate genes in the cQMES4 interval: By annotating the functions of all genes in the cQMES4 interval, 15 candidate genes were found to be important candidate genes for regulating maize mesocotyl length, which are involved in maize cell wall structure, lignin biosynthesis, plant hormone (auxin, abscisic acid, brassinolide) signal transduction, circadian clock, and plant organ formation and development ( Figure 7 The stable cQMES obtained in this study across multiple maize populations under various sowing depths provide precise QTL information for future marker-assisted selection (MAS) breeding of maize for deep sowing tolerance and significantly enhance breeders' understanding of maize deep sowing tolerance.

[0090] 4. Molecular Markers for Maize Mesocotyl Length cQMES4: Further research revealed that the SSR molecular marker primers umc1869 and umc1775 within the maize mesocotyl length cQMES4 region obtained in this study were closely associated with maize mesocotyl length. The main effect qMES4-1, encompassing the umc1869-umc1775 region, also had a significant phenotypic contribution. Furthermore, the characteristic bands of the SSR molecular marker primers umc1869 and umc1775 accurately and objectively identified the genetic alleles of maize with long mesocotyls and deep sowing tolerance (Tables 1 and 6). Therefore, the umc1869 and umc1775 SSR molecular marker primer pairs are important indicators of maize mesocotyl length cQMES4.

[0091] Example 7

[0092] The present invention provides a method for applying a molecular marker cQMES4 for maize mesocotyl length in maize deep sowing tolerance molecular marker-assisted selection breeding, which specifically comprises the following steps:

[0093] 1. A method for applying a molecular marker for maize mesocotyl length cQMES4 in deep sowing tolerance molecular marker-assisted selection breeding of maize: The maize mesocotyl length cQMES4, the SSR molecular marker primers for cQMES4, are composed of two pairs of SSR molecular marker primers, umc1869 and umc1775, wherein the sequence of the SSR molecular marker primer umc1869 is:

[0094] Forward:5'-CGAGCGCTCTAGACACGATTTT-3';

[0095] Reverse:5'-GAACTGGAGGAGCGAGCATGTAT-3';

[0096] The sequence of the SSR molecular marker primer umc1775 is:

[0097] Forward:5'-GGAACTCCGTCAAAATCCCATC-3';

[0098] Reverse:5'-GAGGACAACGCTGCTATTCTCG-3';

[0099] It can be seen from the above embodiments that the method of using the SSR molecular marker cQMES4 that regulates the length of the corn mesocotyl to assist in selecting deep-sowing-resistant corn materials with long mesocotyl characteristics includes: extracting the genomic DNA of the corn to be tested, and performing PCR amplification using the SSR molecular marker primers umc1869 and umc1775; when amplification products with lengths of 232 bp and 249 bp are obtained, the corn to be tested is a candidate deep-sowing-resistant corn plant with long mesocotyl characteristics, other materials are eliminated, and purposeful hybrid combinations are made to select new excellent varieties or new lines of deep-sowing-resistant corn, which are then applied to the safe production of corn in arid areas, and have great application potential. <110> Gansu Agricultural University <120> A constitutive QTL for maize mesocotyl length and its molecular marker and application <160> 4 <210> 1 <211> twenty two <212> DNA <213> Corn (Zea mays L.) <400> 1 cgagcgctct agacacgatt tt 22 <210> 2 <211> twenty three <212> DNA <213>Maize (Zea mays L.) <400>2 gaactggagg agcgagcatg tat 23 <210>3 <211>22 <212>DNA <213>Maize (Zea mays L.) <400>3 Ggaactccgt caaaatccca tc 22 <210>4 <211>22 <212>DNA <213>Maize (Zea mays L.) <400>4 gaggacaacg ctgctattct cg 22

Claims

1. Application of SSR molecular marker primers for maize mesocotyl length cQMES4 in maize deep sowing tolerance breeding, characterized in that The SSR molecular marker primers include umc1869 and umc1775; umc1869 is shown in SEQ ID NO: 1 and SEQ ID NO: 2 in the sequence listing, and umc1775 is shown in SEQ ID NO: 3 and SEQ ID NO: 4 in the sequence listing; PCR amplification is performed using umc1869 and umc1775, and amplification products with lengths of 232 bp and 249 bp are obtained, indicating that the corn to be tested is a deep-sowing-resistant corn variety or line with a long mesocotyl characteristic.

2. SSR molecular marker primers for maize mesocotyl length cQMES4, characterized by The SSR molecular marker primers include umc1869 and umc1775; umc1869 is shown in the sequence list as SEQ ID NO: 1 and SEQ ID NO: 2, and umc1775 is shown in the sequence list as SEQ ID NO: 3 and SEQ ID NO:

4.

3. The SSR molecular marker cQMES4 for maize mesocotyl length is characterized by The SSR molecular marker product of cQMES4 is amplified by PCR using the primers as described in claim 2.

4. Application of the SSR molecular marker cQMES4 in maize to regulate mesocotyl length in deep sowing environment, characterized by The SSR molecular marker primers include umc1869 and umc1775; umc1869 is shown in the sequence list as SEQ ID NO: 1 and SEQ ID NO: 2, and umc1775 is shown in the sequence list as SEQ ID NO: 3 and SEQ ID NO:

4.

5. A method for assisting the selection of deep-sowing tolerant corn materials with long mesocotyl characteristics, characterized in that The method comprises the following steps: extracting genomic DNA of a corn material to be tested; performing PCR amplification using SSR molecular marker primers umc1869 and umc1775; when amplification products with lengths of 232 bp and 249 bp are obtained, the corn to be tested is deep-sowing-resistant corn with a long mesocotyl characteristic.

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