Method for regulating the flowering period of gossypium hirsutum based on ghcml1, ghpcmp-e88 and ghclasrp genes and related molecular markers

Abstract

The application discloses a method for regulating the flowering period of Gossypium hirsutum based on GhCML1, GhPCMP-E88 and GhCLASRP genes and related molecular markers, and belongs to the technical field of genetic engineering.The application discloses a method for regulating the flowering time of Gossypium hirsutum, which significantly shortens the flowering time by inhibiting the expression of GhCML1, GhPCMP-E88 or GhCLASRP genes.Based on GWAS analysis, a CAPS marker is developed for screening of early-maturing varieties.The application provides new genetic resources and molecular markers for the breeding of early-maturing varieties of Gossypium hirsutum, and has important agricultural application value.

Description

Technical Field

[0001] This invention relates to the field of genetic engineering technology, and in particular to a method for regulating the flowering period of upland cotton based on the GhCML1, GhPCMP-E88 and GhCLASRP genes, as well as related molecular markers. Background Technology

[0002] Cotton (Gossypium spp.) is an important crop for producing natural fibers, edible oils, and plant proteins, with upland cotton being the most widely cultivated variety. Current climatic conditions are unfavorable for cotton seedling growth, but early-maturing cotton can effectively adapt to these conditions due to its shorter whole growth period (WGP). Therefore, cultivating early-maturing varieties is crucial for cotton production. Early maturity in cotton is a complex quantitative trait, primarily involving flowering time (FT) and WGP. FT is closely related to WGP and is a key characteristic influencing early maturity. FT also marks the transition of cotton from vegetative to reproductive growth, influenced by both external environment and endogenous genes. Linkage and association analyses are two popular QTL mapping techniques used to determine the genetic basis of complex quantitative traits in cotton. However, the accuracy of linkage analysis needs improvement due to the narrow genetic base of populations. Association analysis, on the other hand, does not require the construction of specialized segregating populations and can directly utilize the extensive genetic variation in natural populations, making it much more accurate than linkage analysis. Since the genome of the upland cotton standard line TM-1 was published, numerous association analyses have been performed using natural populations. Based on linkage disequilibrium, association analysis was used to map SSRs associated with FT. Furthermore, many single nucleotide polymorphism (SNP) markers closely associated with FT have been identified using genome-wide association studies (GWAS). Although association analysis has revealed several genomic regions associated with FT, further exploration of more genomic regions is needed to breed early-maturing varieties. Therefore, further exploration of potential genes associated with FT expression is of great significance for expanding the resource pool of early-maturing genes and breeding early-maturing cotton varieties. Summary of the Invention

[0003] The purpose of this invention is to provide a method and related molecular markers for regulating the flowering period of upland cotton based on the GhCML1, GhPCMP-E88, and GhCLASRP genes, in order to solve the problems existing in the prior art. This invention identifies that the GhCML1, GhPCMP-E88, and GhCLASRP genes are significantly correlated with flowering time.

[0004] To achieve the above objectives, the present invention provides the following solution:

[0005] This invention provides a method for regulating the flowering time of upland cotton, including the step of inhibiting the expression of GhCML1, GhPCMP-E88 or GhCLASRP genes.

[0006] Furthermore, the method of inhibiting the expression of GhCML1, GhPCMP-E88, or GhCLASRP genes includes virus-induced gene silencing.

[0007] The present invention also provides a breeding method for upland cotton, including the steps of detecting the expression levels of GhCML1, GhPCMP-E88 or GhCLASRP genes in varieties and selecting varieties with low expression levels for breeding.

[0008] This invention provides a gene combination for regulating the flowering time of upland cotton, comprising at least one of the genes GhCML1, GhPCMP-E88, and GhCLASRP.

[0009] Furthermore, the gene combination is used to screen or breed early-flowering upland cotton varieties.

[0010] This invention provides a molecular marker for detecting the flowering time of upland cotton, the molecular marker being developed based on SNP sites or haplotypes of the GhFRO7, GhCML1, GhPCMP-E88 or GhCLASRP genes.

[0011] Furthermore, the molecular marker is a CAPS marker, developed based on the D10_61214168 or D11_24001762 SNP site.

[0012] Furthermore, the CAPS marker is genotyped using the restriction endonuclease BstBI.

[0013] This invention provides a breeding method for upland cotton, comprising the following steps:

[0014] The expression levels or haplotypes of GhCML1, GhPCMP-E88, or GhCLASRP genes in the varieties were detected; varieties with low expression levels or carrying the D10_Hap3 or D11_Hap3 haplotypes were selected for breeding; the haplotypes were identified by the CAPS markers.

[0015] This invention provides the application of genes GhCML1, GhPCMP-E88, or GhCLASRP in regulating the flowering time of upland cotton.

[0016] The present invention discloses the following technical effects:

[0017] This invention, through GWAS analysis of 418 upland cotton lines, identified the GhCML1, GhPCMP-E88, and GhCLASRP genes as significantly associated with flowering time. qRT-PCR and VIGS experiments confirmed that silencing these genes significantly advanced flowering time. CAPS markers developed based on SNPs can efficiently screen for early-flowering varieties. Haplotype analysis showed that D10_Hap3 and D11_Hap3 had the highest frequencies in modern varieties, indicating that they have been artificially selected. This invention provides a new theoretical basis for the genetic improvement of early-maturing traits in upland cotton, offers important genetic resources for molecular breeding of early-maturing cotton varieties, and lays the foundation for subsequent genomic research and marker-assisted selection. Attached Figure Description

[0018] Figure 1 The identification of flowering time haplotypes on chromosomes A02, D10, and D11; (a) Manhattan diagrams of chromosomes A02, D10, and D11 and LDBLOCK near significant SNPs; (b) major haplotypes and gene structures of A02_Hap, D10_Hap, and D11_Hap.

[0019] Figure 2 The identification of flowering time haplotypes on chromosomes A02, D10, and D11 was performed. (a) shows the flowering times of A02_Hap1, A02_Hap2, and A02_Hap3; (b) shows the flowering times of D10_Hap1, D10_Hap2, and D10_Hap3; (c) shows the flowering times of D11_Hap1, D11_Hap2, and D11_Hap3; (d) shows the frequency distribution of A02_Hap in Max-50 and Min-50; (e) shows the frequency distribution of D10_Hap in Max-50 and Min-50; and (f) shows the frequency distribution of D11_Hap in Max-50 and Min-50. According to the Duncan test, the different letters indicated significant differences at the 5% level.

[0020] Figure 3 To screen candidate genes related to flowering time by qRT-PCR; where (a) is the relative expression level of GhATJ49; (b) is the relative expression level of GhPCMP-E87; (c) is the relative expression level of GhHEXBP; (d) is the relative expression level of GhDTX51; (e) is the relative expression level of GhFRO7; (f) is the relative expression level of GhCML1; (g) is the relative expression level of GhPCMP-E88; and (h) is the relative expression level of GhCLASRP; according to Duncan's test, different letters represent significant differences at the 5% level;

[0021] Figure 4To develop CAPS markers using D10_61214168 and D11_24001762; where (a) is a schematic diagram of restriction endonuclease digestion of the PCR product of the D10_61214168 allele; (b) is a schematic diagram of restriction endonuclease digestion of the PCR product of the D11_24001762 allele; (c) shows the detection of the D10_61214168 allele using restriction endonuclease BstBI; (d) shows the detection of the D11_24001762 allele using restriction endonuclease BstBI; Ref: reference allele; Alt: substitute allele; M: mark;

[0022] Figure 5 Functional analysis of candidate genes related to flowering time in upland cotton mediated by VIGS; (a) shows the budding time phenotype of TRV:00, TRV:GhFRO7, TRV:GhCML1, TRV:GhPCMP-E88, and TRV:GhCLASRP plants; (b) shows the flowering time phenotype of TRV:00, TRV:GhFRO7, TRV:GhCML1, TRV:GhPCMP-E88, and TRV:GhCLASRP plants; (c) shows the flowering time phenotype of TRV:00, TRV:GhFRO7, TRV:GhCML1, TRV:GhPCMP-E88, and TRV:GhCLASRP plants. 7. Phenotypic values ​​of plant height, first fruiting branch node position, and first node position of TRV:GhCML1, TRV:GhPCMP-E88, and TRV:GhCLASRP plants; (d) shows the budding time, flowering time, plant height, first fruiting branch node position, and first node position of TRV:00, TRV:GhFRO7, TRV:GhCML1, TRV:GhPCMP-E88, and TRV:GhCLASRP plants; data are mean ± standard error (n≥9); according to Duncan's test, different letters represent significant differences at the 5% level;

[0023] Figure 6 The relative expression levels of key flowering-related genes in TRV:00 and silent plants are shown in (a) and (b) respectively. (c) represents the relative expression levels of key flowering-related genes in TRV:00 and TRV:GhFRO7. (d) represents the relative expression levels of key flowering-related genes in TRV:00 and TRV:GhCML1. (c) represents the relative expression levels of key flowering-related genes in TRV:00 and TRV:GhPCMP-E88. (d) represents the relative expression levels of key flowering-related genes in TRV:00 and TRV:GhCLASRP. According to the Duncan test, different letters represent significant differences at the 5% level. Detailed Implementation

[0024] Various exemplary embodiments of the present invention will now be described in detail. This detailed description should not be considered as a limitation of the present invention, but rather as a more detailed description of certain aspects, features, and embodiments of the present invention.

[0025] The nucleotide sequences of genes GhCML1, GhPCMP-E88, GhCLASRP, and GhFRO7 are shown in SEQ ID NO. 27-30, respectively. The nucleotide marked at position 1794 in SEQ ID NO. 30 is the nucleotide polymorphism site of the CAPS marker D10_61214168 of this invention, with a polymorphism of C / T and a polymorphism of G / A in its reverse complementary sequence. This invention uses two polymorphism relationships to describe the CAPS marker simultaneously; those skilled in the art can undoubtedly determine that the two descriptions have the same meaning. The CAPS marker primer for D10_61214168-F is shown in SEQ ID NO. 31; the CAPS marker primer for D10_61214168-R is shown in SEQ ID NO. 32. The nucleotide polymorphism site of the CAPS marker D11_24001762 of this invention is located at nucleotide 712 of the GhCML1 gene shown in SEQ ID NO.27, with a polymorphism of G / T and a polymorphism of C / A for its reverse complementary sequence; the CAPS marker primer for D11_24001762-F is shown in SEQ ID NO.313; and the CAPS marker primer for D11_24001762-R is shown in SEQ ID NO.34.

[0026] Example 1

[0027] 1. Materials and Methods

[0028] 1.1 Plant materials and field trials

[0029] In 2020, 418 core upland cotton line resources reported in the study by Ma et al. (Ma Z, He S, Wang X, et al. (2018) Resequencing a core collection of upland cotton identifies genomic variation and loci influencing fiber quality and yield. Nat Genet 50:803-813) were collected for multi-environmental phenotypic analysis at four experimental sites: E1 (Dunhuang, Gansu, China, 2020), E2 (Alar, Xinjiang, China, 2020), E3 (Korla, Xinjiang, China, 2020), and E4 (Shihezi, Xinjiang, China, 2020). In 2021, 201 new upland cotton varieties were added to the original 418 core varieties, including 134 from Li et al. (Li L, Zhang C, Huang J, et al. (2021) Genomic analyses reveal the genetic basis of early maturity and identification of loci and candidate genes in upland cotton (gossypium hirsutum l.). Plant Biotechnol J), and 67 from Table 1. This invention constructed a total extended population of 619 accessions and planted them in two environments: E5 (Korla, Xinjiang, China, 2021) and E6 (Shihezi, Xinjiang, China, 2021). All field experiments were conducted in a completely randomized block design with three biological replicates in each environment. Approximately 40 plant species were represented in a single copy of each material. In addition, the 619 upland cotton lines were divided into five categories according to their geographical origin: Northern Specific Early-maturing Region (18, NSEMR), Northwest Inland Region (165, NIR), Yellow River Region (217, YRR), Yangtze River Region (114, YZRR), and other regions (114, FR). They were also divided into early varieties, mid-term varieties, and modern varieties according to their breeding period.

[0030] Information on 167 varieties (Table 167)

[0031]

[0032]

[0033]

[0034] 1.2 Phenotypic Evaluation and Statistical Analysis

[0035] This invention investigated the free radical response (FT) of 418 upland cotton lines in six environments. IBM SPSS 27.0 software was used to perform analysis of variance and descriptive statistics on the phenotypic data. Minimum (Min), maximum (Max), mean, coefficient of variation (CV), standard deviation (SD), skewness, and kurtosis are the basic parameters of the descriptive statistics. The best linear unbiased estimate (BLUP) was calculated using the R package "lme4". Generalized heritability (h) was also assessed. 2 Calculate using the following formula:

[0036]

[0037] and Let represent the genetic variance, the variance of the interaction between genotype and environment, and the error variance, respectively; n represents the number of environments; and r represents the number of replicates.

[0038] 1.3 Mutation Identification and Filtering

[0039] This invention resequencing 67 varieties listed in Table 1, and collecting resequencing datasets from 134 varieties analyzed by Li et al. and 418 varieties analyzed by Ma et al. Paired-end sequencing reads were mapped to the upland cotton TM-1 reference genome (v2.1, ZJU assembly) using BWA software. Then, SAMtools retained reads with unique locations and mapping quality values ​​greater than 30 in the reference genome TM-1 and exported them as BAM format. Sorted BAM files and duplicate reads identified from library construction or sequencing were generated using Picard software. SNP and indel detection were then performed using bcftools and GATK, and high-quality variants (MAF > 0.05, deletion rate < 10%) were screened. Finally, ANNOVAR was used to annotate variant sites. SNP density maps were plotted using the R package "CMplot".

[0040] 1.4 Genome-wide association analysis and haplotype / allele analysis

[0041] For 418 core upland cotton lines, GWAS was performed on FT characteristics using 1,574,032 high-quality SNPs. Marker-phenotypic association analysis was conducted using a mixed linear model (MLM) in GEMMA software and performed by vcf2gwas software. SNPs with significant associations were screened using a p-value < 10⁻⁵ threshold, and significant SNPs with non-synonymous mutations were further annotated. Haplotypes were identified by calculating LD blocks within 100 kb of important SNPs with non-synonymous mutations based on LDBlockShow. Here, to obtain more accurate haplotypes / alleles, the FT of each haplotype / allele was calculated using the average of 619 upland cotton lines in E5 and E6 environments. Considering that early maturity is an adaptation to NIR light and suitability for mechanized harvesting, the present invention considers lines with short FTs to have favorable haplotypes / alleles. Furthermore, this invention selected 100 cotton varieties from the earliest (Min-50) and latest (Max-50) FT populations and calculated the frequency distribution of haplotypes / alleles in both populations to further identify favorable haplotypes / alleles. Additionally, haplotype frequencies were calculated in the same manner for four ecoregions (NIR, NSEMR, YRR, and YZRR) and three breeding ages (early, middle, and modern). The phenotypic variation explanation (PVE) for each SNP marker was calculated using the following formula: PVE = (2β) 2 [×MAF×(1-MAF)] / [2β] 2 ×MAF×(1-MAF)+(se(β)) 2 [×2×N×MAF×(1-MAF)]. Where β and MAF are obtained from GEMMA software.

[0042] 1.5 RNA extraction and qRT-PCR

[0043] Seeds of four early-flowering upland cotton varieties (Ji91-28, Ganmian4, L-5F45, and Jiian8) and four late-flowering upland cotton varieties (C1835, Kyuan4, Emian20, and Jimian11*) were germinated in seedling cups containing a 1:1 (by volume) mixture of substrate and vermiculite. After germination, seedlings were transferred to an artificial climate chamber with a temperature of 25°C, a 16-hour to 8-hour light-dark cycle, and a humidity of approximately 60-80% for incubation. When the early-flowering plants reached the third true leaf stage, samples were taken and immediately stored at -80°C. The material was then pulverized in a mortar pre-cooled with liquid nitrogen, and RNA was extracted using the RNAprepPurePlantPlus kit (Tiangen Biotech, Beijing, China). UnionScript first-strand cDNA synthesis mix (containing dsDNase, GenesandBiotech, Beijing, China) was used for qPCR to synthesize cDNA. qRT-PCR amplification was performed using BrightCycle Universal SYBR Green qPCR Mix with UDG (ABclonal, China). For potential candidate genes, qRT-PCR-specific primers were developed using the Primer-BLAST website (https: / / www.ncbi.nlm.nih.gov / tools / primer-blast / ). (The primers for amplifying qGhATJ49 are shown in SEQ ID NO. 1-2, the primers for amplifying qGhFRO7 are shown in SEQ ID NO. 3-4, the primers for amplifying qGhHEXBP are shown in SEQ ID NO. 5-6, the primers for amplifying qGhDTX51 are shown in SEQ ID NO. 7-8, the primers for amplifying qGhCML1 are shown in SEQ ID NO. 9-10, the primers for amplifying qGhPCMPE87 are shown in SEQ ID NO. 11-12, the primers for amplifying qGhPCMPE88 are shown in SEQ ID NO. 13-14, the primers for amplifying qGhCLASRP are shown in SEQ ID NO. 15-16, and the primers for amplifying GhActin are shown in SEQ ID NO. 17-18).

[0044] The internal control gene used in the experiment was GhActin (GenBank accession number AY305733). Using 2 -ΔΔCTThe expression levels of GhActin and other candidate genes were determined. Similarly, qRT-PCR was used to confirm the expression levels of key flowering genes in TRV:00, TRV:GhFRO7, TRV:GhCML1, TRV:GhPCMP-E88, and TRV:GhCLASRP plants. These genes included GhFT, GhCAL, GhSOC1, GhAP1, GhCOL2, GhSVP, and GhLFY. At least three biological replicates were used in each experiment.

[0045] 1.6 VIGS Experiment in Cotton

[0046] To investigate the function of candidate genes in controlling FT, VIGS experiments were conducted using Zhongmian 113 as the recipient material to verify the function of four candidate genes. The corresponding silenced fragments (300-500 bp) of the four candidate genes were introduced into the TRV-based (pYL156) vector, named TRV:GhFRO7, TRV:GhCML1, TRV:GhPCMP-E88, and TRV:GhCLASRP. The vectors were then introduced into Agrobacterium strain GV3101 using a freeze-thaw method. The primers used to construct the pYL156 vector to silence the four candidate genes are shown in SEQ ID NO. 19-26. Specifically, the primers for GhFRO7 are SEQ ID NO. 19-10, GhCML1 are SEQ ID NO. 21-22, GhPCMP-E88 are SEQ ID NO. 23-24, and GhCLASRP are SEQ ID NO. 25-26.

[0047] Then, TRV:GhCLA1 (positive control), TRV:00 (negative control), TRV:GhFRO7, TRV:GhCML1, TRV:GhPCMP-E88, and TRV:GhCLASRP were mixed with the helper vector pYL192 at a 1:1 ratio and incubated at 28°C in the dark for 3 hours before being injected into the cotyledons of 7-day-old cotton plants. The virus-infected seedlings were cultured in the dark for 24 hours in an artificial climate incubator, and then transferred to long-day conditions (16 hours light / 8 hours dark). For the positive control (TRV:GhCLA1), after the appearance of albinism, gene-silenced plants with expression levels 50% lower than those in TRV:00 plants were selected by qRT-PCR; these selected plants were designated as TRV:GhFRO7, TRV:GhCML1, TRV:GhPCMP-E88, and TRV:GhCLASRP. Five early-maturing-related traits were studied in TRV:00, TRV:GhFRO7, TRV:GhCML1, TRV:GhPCMP-E88, and TRV:GhCLASRP: budding time (BT), FT, plant height (PH), first fruit node (FFBN), and first fruit node height (HFFBN). Phenotypic analysis was performed using at least nine plants for each VIGS construct.

[0048] 1.7 Selective Adaptation Signals

[0049] As indicators of genetic distance population differences, the fixation index (Fst) and nucleotide diversity (π) provide insights into the biology of evolutionary processes. To identify candidate genes with potential selective roles in evolution, π and Fst were calculated near important SNPs extending within a 100 kb range for the YZRR, YRR, NSEMR, and NIR groups using VCFtools. Similarly, π and Fst were calculated in the same manner for early, mid-, and modern varieties. Furthermore, a 10 kb sliding window and a 10 kb step size were used to determine Fst and π.

[0050] 1.8 Development of CAPS Markup

[0051] Based on two SNPs (D10_61214168 and D11_24001762) within the candidate genes, D10_Hap and D11_Hap were identified, and two specific CAPS markers were developed based on these haplotypes. The relevant primers are shown in Table 2. First, genomic DNA was obtained from 4-week-old cotton leaves using the Super Plant Genomic DNA Kit (Tiangen Biotech, Beijing, China). The concentration and purity of the collected DNA were determined by agarose gel electrophoresis and spectrophotometry. The extracted DNA was then used as a template for PCR amplification. Finally, the restriction endonuclease BstBI was used to digest the 879bp and 631bp PCR products, which were then separated by electrophoresis on a 1.5% (w / v) agarose gel.

[0052] 2 Results

[0053] 2.1418 upland cotton germplasms' FT phenotypic diversity

[0054] All germplasm samples were field-grown in six environments: E1, E2, E3, E4, E5, and E6. This invention observed a wide range of variation in free radical time (FT). In E1, FT ranged from 75.5 to 89.5 days; in E2, from 60 to 73 days; in E3, from 69 to 85 days; in E4, from 63 to 87.5 days; in E5, from 64 to 89.5 days; in E6, from 68.67 to 83.67 days; and for BLUP, from 71.94 to 80.42 days. The coefficient of variation for FT was highest in E4 (4.80%), while it was lowest for BLUP (1.88%) (Table 2). Pearson correlation analysis revealed a significant positive correlation between FT values ​​across different environments. The distribution of FT was approximately normal across all environments, a typical characteristic of quantitative traits regulated by multiple genes. Analysis of variance also showed that environment, genotype, and their interactions had a significant impact on FT (Table 2). Furthermore, the h-value of FT... 2 The percentage was even higher, at 81.39% (Table 3). These results indicate that while FT is primarily influenced by genetic factors, it is also affected by environmental factors.

[0055] Table 2. Statistical data on flowering time patterns in six environments.

[0056]

[0057] Table 3418 shows the flowering time phenotypes and broad-sense heritability under six environmental conditions. (ANOVA analysis)

[0058]

[0059] 2.2 Identification of SNP sites significantly associated with FT

[0060] This invention used principal component analysis, phylogenetic tree analysis, and population structure analysis to divide 418 upland cotton lines into three major subgroups. The linkage disequilibrium (LD) decay rate was approximately 0.46 kb. After extensive screening, a total of 1,574,302 high-quality SNPs were identified. There were 576,078 SNPs in the Dt subgenome and 997,954 SNPs in the At subgenome, with the At subgenome having approximately 1.73 times more SNPs than the Dt subgenome. SNP density was physically located on all 26 chromosomes. To identify novel genes controlling FT, this invention performed GWAS using MLM analysis of FT phenotypic data from a single environment and BLUP analysis of all environments via GEMMA. GWAS identified 457 important SNPs (-log10(p)>5). Four SNP sites were found in E1, 210 in E2, 13 in E3, 25 in E4, 146 in E5, 33 in E6, and 25 in BLUP. This indicates that MLM can be used to identify associated signals. The mean PVE of these SNPs was 5.71%, ranging from 4.39% to 9.23%. These significant SNPs were mainly distributed on chromosomes A02, A10, A11, A12, D03, D09, D10, and D11. Twenty-five important SNP sites were found within genes, 18 of which led to nonsynonymous mutations in eight genes (GhATJ49, GhHEXBP, GhPCMP-E87, GhFRO7, GhCML1, GhDTX51, GhPCMP-E88, and GhCLASRP). Of the 25 SNPs located within this gene, two were significantly associated with free radical skewing (FT) and were associated in multiple environments. Specifically, the D11_24011417_SNP was associated with FT in E1, E6, and BLUP, while the D11_24011426_SNP showed a significant association in both E6 and BLUP. These findings demonstrate the multigenetic basis of FT plasticity.

[0061] 2.3 Discover three favorable early-flowering haplotypes and two favorable early-flowering alleles.

[0062] To determine haplotypes favorable for flowering, this invention selected important SNPs (-log10(p)>5) with nonsynonymous mutations on chromosomes A02, D10, and D11 for LD linkage analysis, revealing the existence of haplotypes on chromosomes A02, D10, and D11. Figure 1(a). By GWAS, the two SNP alleles from chromosome A02 (A02_6711941 and A02_6711947) were G / A and C / A, respectively. Due to the tight linkage between the two SNP sites, three different haplotypes (GG-CC, GA-CA, and AA-AA) were identified and named A02_Hap1, A02_Hap2, and A02_Hap3. Figure 1 (b). Of the 133 lines, haplotype A02_Hap3 was considered the favorable haplotype because its average FT (76.87d) was significantly lower than that of A02_Hap1 (78.55d), which included 454 varieties, and significantly lower than that of A02_Hap2 (77.88d), which included 14 varieties. Figure 2 (a). By GWAS, FT was associated with three SNP loci (D10_61213074, D10_61213558, and D10_61213909) on chromosome D10; the three SNP alleles were A / G, T / C, and T / C, respectively. These three SNPs consist of three major haplotypes (AA-TT-TT, AG-TC-TC, and GG-CC-CC), and due to their close interlocking relationship, they were named D10_Hap1, D10_Hap2, and D10_Hap3, respectively. Figure 1 (b). D10_Hap1, D10_Hap2, and D10_Hap3 consist of 397, 5, and 192 varieties, respectively. The FT of haplotype D10_Hap3 (76.79) was significantly lower than that of haplotypes D10_Hap1 (78.95d) and D10_Hap2 (78.13d), and was therefore considered a favorable haplotype. Figure 2 (b) The other 11 SNP loci associated with FT (D11_24001762, D11_24003645, D11_24003668, D11_24004421, D11_24004651, D11_24009646, D11_24010285, D11_24010356, D11_24010672 and D11_24050721) are closely associated with FT and are located on chromosome D11.

[0063] Due to the tight linkage among the 11 SNP sites, three core haplotypes were identified (CC-GG-AA-CC-AA-CC-GG-CC-TT-AA, CC-GG-AA-CC-AA-CC-CC-GG-CC-GG-CC-TT-GG and AA-AA-GG-GG-GG-TT-AA-TT-GG-GG-TT-GG-GG-GG), which were named D11_Hap1, D11_Hap2, and D11_Hap3, respectively. Figure 1(b). D11_Hap1, D11_Hap2, and D11_Hap3 have 385, 4, and 149 variants, respectively. Similarly, the average free finite element time (FT) of the D11_Hap3 series (76.40d) is shorter than that of the D11_Hap1 series (78.97d) and the D11_Hap2 series (78.29d); therefore, D11_Hap3 is considered a favorable haplotype. Figure 2 (c). Furthermore, the haplotype frequency distributions of the Min-50 (83.07d) and Max-50 (70.88d) lines were calculated to confirm the impact of these haplotypes on the FT. This invention found that the Min-50 germplasm exhibited more favorable haplotype frequencies than the Max-50 germplasm. In the Max-50 population, the frequencies of A02_Hap1, A02_Hap2, and A02_Hap3 were 0.90, 0.02, and 0.08, respectively; in the Min-50 population, the frequencies were 0.55, 0.04, and 0.41, respectively. The results show that A02_Hap3 is a superior haplotype because it is more frequently distributed in the Min-50 population ( Figure 2 (d). In the Max-50 population, the frequencies of D10_Hap1 and D10_Hap3 were 0.94 and 0.06, respectively, while in the Min-50 population, the frequencies were 0.41 and 0.59, respectively. The results indicate that D10_Hap3 is a superior haplotype because it is more frequently distributed in the Min-50 population. Figure 2 (e). In the Max-50 population, the frequencies of D11_Hap1, D11_Hap2, and D11_Hap3 were 0.89, 0.02, and 0.09, respectively; in the Min-50 population, the frequencies of D11_Hap1 and D11_Hap3 were 0.36 and 0.64, respectively. The results indicate that D11_Hap3 is a superior haplotype because it is more frequently distributed in the Min-50 population. Figure 2 (f). To identify favorable alleles promoting flowering, this invention selected important SNPs (D09_6523710 and D09_50028094) with nonsynonymous mutations located on chromosome D09 in the GhPCMP-E87 and GhHEXBP genes, respectively, for analysis (Figure f). Figure 1(a) The D09_6523710 SNP is divided into three types: AA, AG, and GG. The free finite element time (FT) of D09_6523710_GG is significantly earlier than that of D09_6523710_AA. The D09_50028094 SNP also has three types: GG, GA, and AA. The FT of D09_50028094_AA is significantly earlier than that of D09_50028094_GG. Furthermore, this invention calculated the individual frequency distributions of the D09_6523710 and D09_50028094 alleles in the Max-50 and Min-50 populations, respectively. The results showed that the frequencies of D09_6523710_GG and D09_50028094_AA were greater in Min-50 than in Max-50. In summary, D09_6523710_GG and D09_50028094_AA are favorable alleles for early flowering.

[0064] 2.4 Identification of FT candidate genes and development of CAPS markers

[0065] This invention conducted qRT-PCR experiments on the apical meristems of buds and young leaves at the third true leaf stage of four early-flowering varieties (Ji91-28, Ganmian4, L-5F45, and Jimian8) and four late-flowering varieties. The invention found that the relative expression levels of four genes—GhFRO7, GhCML1, GhPCMP-E88, and GhCLASRP—were significantly higher in the late-flowering varieties than in the early-flowering varieties. Figure 3 On the other hand, the four genes GhATJ49, GhHEXBP, GhPCMP-E87, and GhDTX51 did not show regular differential expression in early-flowering or late-flowering varieties. Figure 3The above results indicate that the four genes GhFRO7, GhCML1, GhPCMP-E88, and GhCLASRP may be related to the regulation of cotton FT and are potential candidate genes. Based on the four FT candidate genes, this invention developed two CAPS markers. These markers rely on genotyping based on changes in the restriction endonuclease BstBI recognition sites induced by the D10_61214168 (A / G) and D11_24001762 (A / C) alleles. Specifically, primer amplification of cotton genomic DNA regions containing the D10_61214168 and D11_24001762 sites yielded PCR products of 879 bp and 631 bp, respectively. Theoretically, the restriction endonuclease BstBI should produce two fragments of 369 bp and 510 bp after PCR amplification of the D10_61214168_AA genotype. After BstBI digestion, the PCR amplification product of the D11_24001762_AA genotype should theoretically produce two fragments of 338bp and 293bp. Figure 4 (a, b). Experimental results showed that after digestion with BstBI, the PCR amplification products of the D10_61214168_AA genotype showed two independent bands in agarose gel electrophoresis (a, b). Figure 4 c), while the PCR amplification product of the D11_24001762_AA genotype showed only one band in agarose gel electrophoresis after enzyme digestion, because the two fragments produced were similar in size ( Figure 4 d).

[0066] 2.5 Silent candidate genes significantly advance flowering.

[0067] To explore the biological functions of candidate genes associated with premature fertilization (FT), this invention performed a VIGS experiment on four potential FT-regulating genes (GhFRO7, GhCML1, GhPCMP-E88, and GhCLASRP). The VIGS experiment was successful when plants treated with TRV:GhCLA1 showed an albino phenotype 8 days after viral injection. Furthermore, compared to TRV:00 control plants, the expression levels of these four genes were significantly lower in most gene-silenced plants. To further understand the relationship between gene expression and FT, this invention examined five early-maturing related traits in TRV:00 and silenced plants: BT, FT, PH, FFBN, and HFFBN. Compared to TRV:00 control plants, plants silenced with GhFRO7, GhCML1, GhPCMP-E88, or GhCLASRP all exhibited an earlier flowering phenotype. Figure 5 (b, d). Furthermore, BT occurred significantly earlier in these gene-silenced plants than in the TRV:00 control plants (b, d). Figure 5(a, d). Compared with control plants, plants with silenced GhCML1 genes exhibited lower pH and HFFBN values, and their FFBN values ​​were significantly lower than those of control plants at TRV: 00. Figure 5 (c, d).

[0068] In summary, GhFRO7, GhPCMP-E88, and GhCLASRP are important candidate genes regulating the late flowering phenotype of upland cotton, while GhCML1 plays an important role in regulating FT, PH, HFFBN, and NFFBN in upland cotton.

[0069] 2.6 Candidate genes affect the expression of key flowering genes

[0070] To verify the role of four candidate genes in regulating flowering, this invention examined several key flowering genes in silenced upland cotton plants, including GhFT, GhCAL, GhSOC1, GhAP1, GhCOL2, GhSVP, and GhLFY. This invention used cDNA from the third true leaf of TRV:GhFRO7, TRV:GhCML1, TRV:GhPCMP-E88, TRV:GhCLASRP, and TRV:00 plants as templates for qRT-PCR experiments. The relative expression levels of the seven key flowering genes in the silenced TRV:GhFRO7 plants were significantly higher than those in the control TRV:00 plants. Figure 6 (a). In silenced TRV:GhCML1 and TRV:GhPCMP-E88 plants, the relative expression levels of GhFT, GhCAL, GhSOC1, GhAP1, GhCOL2, and GhLFY were significantly higher than in control plants, while the relative expression level of GhLFY was significantly lower than in control plants. Figure 6 (b, c) Compared with the control plants, the expression of GhFT, GhCAL, GhAP1, and GhLFY was increased in the silent plant TRV:GhCLASSRP, while the expression of GhSOC1, GhCOL2, and GhSVP was significantly decreased. These results indicate that the four candidate genes GhFRO7, GhCML1, GhPCMP-E88, and GhCLASSRP participate in the regulation of FT by affecting the expression of key flowering-related genes.

[0071] The embodiments described above are merely preferred embodiments of the present invention and are not intended to limit the scope of the present invention. Various modifications and improvements made by those skilled in the art to the technical solutions of the present invention without departing from the spirit of the present invention should fall within the protection scope defined by the claims of the present invention.

Claims

1. A method for regulating the flowering time of upland cotton, characterized in that, The method includes the step of inhibiting the expression of the GhCML1, GhPCMP-E88, or GhCLASRP genes; the nucleotide sequences of the GhCML1, GhPCMP-E88, or GhCLASRP genes are shown in SEQ ID NO.27-29, respectively.

2. The method according to claim 1, characterized in that, The methods for inhibiting the expression of GhCML1, GhPCMP-E88, or GhCLASRP genes include virus-induced gene silencing.

3. A breeding method for upland cotton, characterized in that, The method includes the steps of detecting the expression levels of GhCML1, GhPCMP-E88, or GhCLASRP genes in varieties and selecting varieties with low expression levels for breeding; the nucleotide sequences of the GhCML1, GhPCMP-E88, or GhCLASRP genes are shown in SEQ ID NO.27-29, respectively.

4. The application of genes GhCML1, GhPCMP-E88, or GhCLASRP in regulating the flowering time of upland cotton, characterized in that, The method includes the step of inhibiting the expression of the GhCML1, GhPCMP-E88, or GhCLASRP genes; the nucleotide sequences of the GhCML1, GhPCMP-E88, or GhCLASRP genes are shown in SEQ ID NO.27-29, respectively.

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