Method for regulating and controlling florescence of upland cotton based on GhCML1, GhPCMP-E88 and GhCLASRP genes and related molecular marker

Abstract

The invention discloses a method for regulating and controlling the florescence of upland cotton based on GhCML1, GhPCMP-E88 and GhCLASRP genes and a related molecular marker, and belongs to the technical field of gene engineering. The invention discloses a method for regulating and controlling the flowering time of upland cotton, which obviously 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 early-maturing varieties. The invention provides new gene resources and molecular markers for breeding early-maturing varieties of upland cotton, and has important agricultural application value.

Description

Technical Field

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

[0002] Cotton (Gossypium spp.) is an important crop for producing natural fiber, edible oil, and plant protein. Upland cotton is the most widely cultivated cotton variety. Current climatic conditions are unfavorable for the growth of cotton seedlings, but early-maturing cotton varieties can effectively adapt to these conditions due to their 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 and WGP are closely related and are key traits influencing early maturity. FT also marks the transition from vegetative to reproductive growth in cotton and is influenced by both the external environment and endogenous genes. Linkage and association analyses are two popular QTL mapping techniques for determining the genetic basis of complex quantitative traits in cotton. However, due to the narrow genetic base of populations, the accuracy of linkage analyses needs to be improved. Association analyses do not require the construction of specialized segregating populations and can directly leverage the extensive genetic variation in natural populations, making them much more accurate than linkage analyses. Since the genome of the standard upland cotton line TM-1 was released, numerous association analyses have been conducted using natural populations. Based on linkage disequilibrium, association analysis has mapped SSRs associated with FT. Furthermore, many single nucleotide polymorphism (SNP) markers closely associated with FT have been identified through genome-wide association studies (GWAS). Although association analysis has revealed several genomic regions associated with FT, further exploration of additional genomic regions is needed to develop early-maturing varieties. Therefore, further exploration of potential genes associated with FT expression is crucial for expanding the early-maturing gene library and breeding early-maturing cotton varieties. Summary of the Invention

[0003] The present invention aims to provide a method for regulating the flowering time of upland cotton based on the GhCML1, GhPCMP-E88, and GhCLASRP genes and related molecular markers to address the problems of the above-mentioned prior art. The present invention identifies that the GhCML1, GhPCMP-E88, and GhCLASRP genes are significantly associated with flowering time.

[0004] To achieve the above object, the present invention provides the following solutions:

[0005] The present invention provides a method for regulating the flowering time of upland cotton, comprising 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 gene includes virus-induced gene silencing.

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

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

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

[0010] The present invention provides a molecular marker for detecting the flowering time of upland cotton. The molecular marker is developed based on a SNP site or haplotype of a GhFRO7, GhCML1, GhPCMP-E88 or GhCLASRP gene.

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

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

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

[0014] Detecting the expression level or haplotype of GhCML1, GhPCMP-E88 or GhCLASRP gene in the variety; selecting varieties with low expression level or carrying D10_Hap3, D11_Hap3 haplotype for breeding; the haplotype is identified by the CAPS marker.

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

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

[0017] The present invention analyzed 418 upland cotton lines through GWAS and identified that the GhCML1, GhPCMP-E88, and GhCLASRP genes are significantly associated with flowering time. qRT-PCR and VIGS experiments confirmed that silencing these genes can significantly advance flowering time. The CAPS marker developed based on SNPs can efficiently screen early-flowering varieties. Haplotype analysis showed that D10_Hap3 and D11_Hap3 have the highest frequencies in modern varieties, indicating that they are subject to artificial selection. The present invention provides a new theoretical basis for the genetic improvement of early-maturing traits related to upland cotton, provides important genetic resources for molecular breeding of early-maturing cotton varieties, and provides a foundation for subsequent genomic research and molecular marker-assisted selection. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] Figure 1 Identification of flowering time haplotypes on chromosomes A02, D10, and D11; (a) Manhattan plots 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 Identification of flowering time haplotypes on chromosomes A02, D10, and D11; (a) is the flowering time of A02_Hap1, A02_Hap2, and A02_Hap3; (b) is the flowering time of D10_Hap1, D10_Hap2, and D10_Hap3; (c) is the flowering time of D11_Hap1, D11_Hap2, and D11_Hap3; (d) is the frequency distribution of A02_Hap in Max-50 and Min-50; (e) is the frequency distribution of D10_Hap in Max-50 and Min-50; (f) is the frequency distribution of D11_Hap in Max-50 and Min-50; different letters indicate significant differences at the 5% level according to Duncan's test;

[0020] Figure 3 Screening of candidate genes related to flowering time by qRT-PCR; (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. Different letters indicate significant differences at the 5% level according to the Duncan test.

[0021] Figure 4Development of CAPS markers using D10_61214168 and D11_24001762; (a) is a schematic diagram of restriction enzyme digestion of PCR products of the D10_61214168 allele; (b) is a schematic diagram of restriction enzyme digestion of PCR products of the D11_24001762 allele; (c) is the detection of the D10_61214168 allele using the restriction enzyme BstBI; (d) is the detection of the D11_24001762 allele using the restriction enzyme BstBI; Ref: reference allele; Alt: alternative allele; M: marker;

[0022] Figure 5 This is a VIGS-mediated functional analysis of candidate genes related to flowering time in upland cotton; wherein, (a) is the budding time phenotype of TRV:00, TRV:GhFRO7, TRV:GhCML1, TRV:GhPCMP-E88 and TRV:GhCLASRP plants; (b) is the flowering time phenotype of TRV:00, TRV:GhFRO7, TRV:GhCML1, TRV:GhPCMP-E88 and TRV:GhCLASRP plants; (c) is the flowering time phenotype of TRV:00, TRV:GhFRO7, TRV:GhCML1, TRV:GhPCMP-E88 and TRV:GhCLASRP plants. 7. Phenotypes of plant height, first fruiting branch node, and initial node height of TRV:GhCML1, TRV:GhPCMP-E88, and TRV:GhCLASRP plants; (d) Bud appearance time, flowering time, plant height, first fruiting branch node, and initial node height of TRV:00, TRV:GhFRO7, TRV:GhCML1, TRV:GhPCMP-E88, and TRV:GhCLASRP plants; Data are mean ± SD (n ≥ 9); different letters indicate significant differences at the 5% level according to Duncan's test;

[0023] Figure 6 are the relative expression levels of key flowering-related genes in TRV:00 and silenced plants; (a) is the relative expression level of key flowering-related genes in TRV:00 and TRV:GhFRO7; (b) is the relative expression level of key flowering-related genes in TRV:00 and TRV:GhCML1; (c) is the relative expression level of key flowering-related genes in TRV:00 and TRV:GhPCMP-E88; (d) is the relative expression level of key flowering-related genes in TRV:00 and TRV:GhCLASRP; different letters indicate significant differences at the 5% level according to the Duncan test. DETAILED DESCRIPTION

[0024] Various exemplary embodiments of the present invention will now be described in detail. This detailed description should not be considered as limiting 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 the genes GhCML1, GhPCMP-E88, GhCLASRP, and GhFRO7 are shown in SEQ ID NOs. 27-30, respectively. The nucleotide at position 1794 in SEQ ID NO. 30 represents the nucleotide polymorphism of the CAPS marker D10_61214168 of the present invention, which has a C / T polymorphism and a G / A polymorphism in its reverse complement sequence. Both polymorphism relationships are used in the present invention to describe the CAPS marker, and those skilled in the art can readily ascertain that both descriptions are identical. 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 the present invention is located at the 712th nucleotide of the GhCML1 gene shown in SEQ ID NO.27, the polymorphism is G / T, and the polymorphism of its reverse complementary sequence is C / A; the CAPS marker primer of D11_24001762-F is shown in SEQ ID NO.313; the CAPS marker primer of 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 variety resources reported in the study of 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-environment phenotyping analysis at four experimental sites: E1 (Dunhuang, Gansu, China in 2020), E2 (Aral, Xinjiang, China in 2020), E3 (Korla, Xinjiang, China in 2020) and E4 (Shihezi, Xinjiang, China in 2020). In 2021, 201 upland cotton lines were added to the original 418 core upland cotton lines, of which 134 were from Li et al. (LiL, ZhangC, HuangJ, et al. (2021) Genomic analyses reveal the genetic basis of early maturity and identification of loci and candidate genes in upland cotton (gossypiumhirsutuml.). Plant Biotechnol J), and 67 were from Table 1. A total of 619 accessions of germplasm were constructed and planted 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 3 biological replicates in each environment. There were approximately 40 plants in a single copy of each material. In addition, 619 upland cotton lines were divided into five categories based on geographic origin: Northern Specific Early-maturing Region (18, NSEMR), Northwest Inland Region (165, NIR), Yellow River Region (217, YRR), Yangtze River Region (114, YZRR), and Non-regional Region (114, FR). They were also divided into early varieties, mid-season varieties, and modern varieties based on their breeding period.

[0030] Table 167 Variety Information

[0031]

[0032]

[0033]

[0034] 1.2 Phenotypic evaluation and statistical analysis

[0035] The present invention investigated the FT of 418 upland cotton lines in 6 environments. IBM SPSS 27.0 software was used to perform variance analysis and descriptive statistics on the phenotypic data. Minimum value (Min), maximum value (Max), mean, coefficient of variation (CV), standard deviation (SD), skewness and kurtosis were the basic parameters of descriptive statistics. The best linear unbiased estimate (BLUP) was calculated using the R package "lme4". Broad-sense heritability (h 2 ) is calculated using the following formula:

[0036]

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

[0038] 1.3 Variant Identification and Filtering

[0039] The present invention resequenced 67 varieties in Table 1 and collected resequencing data sets of 134 varieties analyzed by Li et al. and 418 varieties analyzed by Ma et al. The double-end sequencing reads were mapped to the upland cotton TM-1 reference genome (v2.1, ZJU assembly) using BWA software. Then, SAMtools retained the reads with unique positioning positions in the reference genome TM-1 and positioning quality values ​​greater than 30 and exported them to BAM format. The sorted BAM files and repeated reads identified from library construction or sequencing were generated by Picard software. Subsequently, bcftools and GATK were used for SNP and Indel detection, and high-quality variants (MAF>0.05, deletion rate<10%) were screened out. Finally, ANNOVAR was used to annotate the variant sites. The SNP density map was drawn using the R package "CMplot".

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

[0041] For 418 core upland cotton lines, a GWAS of FT traits was performed using 1,574,032 high-quality SNPs. Marker-phenotype association analysis was performed using a mixed linear model (MLM) of GEMMA software and completed by vcf2gwas software. SNPs with significant associations were screened with a significance threshold of P<10-5, and significant SNPs with non-synonymous mutations were further annotated. Haplotypes were identified by calculating the LD blocks within 100kb of important SNPs with non-synonymous mutations based on LDBlockShow. Here, in order to obtain more accurate haplotypes / alleles, the present invention calculated the FT of each haplotype / allele using the average value of 619 upland cotton lines in two environments, E5 and E6. Considering that early maturity is an adaptation to NIR light and is suitable for mechanized harvesting, the present invention believes that lines with short FT have favorable haplotypes / alleles. In addition, the present invention selected 100 cotton varieties with the earliest FT (Min-50) and the latest FT (Max-50), and calculated the frequency distribution of haplotypes / alleles in the two populations to further identify favorable haplotypes / alleles. In addition, the haplotype frequencies of four ecological regions (NIR, NSEMR, YRR and YZRR) and three breeding ages (early, middle and modern) were calculated in the same way. The phenotypic variation explained (PVE) of each SNP marker was calculated by the following formula: PVE = (2β 2 ×MAF×(1-MAF)] / [2β 2 ×MAF×(1-MAF)+(se(β)) 2 ×2×N×MAF×(1-MAF)]. Wherein, β and MAF were 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 Jiiumian8) 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, the seedlings were moved to a climatic chamber maintained at 25°C, with a 16-hour light to 8-hour dark cycle and approximately 60–80% humidity for incubation. When early-flowering plants reached the third true leaf stage, they were sampled and immediately stored at −80°C. The material was then pulverized in a mortar cooled with liquid nitrogen, and RNA was extracted using the RNAprep PurePlant Plus Kit (Tiangen Biotech, Beijing, China). UnionScript First-Strand cDNA Synthesis Mix for qPCR (containing dsDNase, Genesand Biotech, Beijing, China) was used to synthesize cDNA. qRT-PCR amplification was performed using BrightCycle Universal SYBR Green qPCR Mix with UDG (ABclonal, China). qRT-PCR specific primers were developed for potential candidate genes using the Primer-BLAST website (https: / / www.ncbi.nlm.nih.gov / tools / primer-blast / ). (The primers used to amplify qGhATJ49 are shown in SEQ ID NOs. 1-2, the primers used to amplify qGhFRO7 are shown in SEQ ID NOs. 3-4, the primers used to amplify qGhHEXBP are shown in SEQ ID NOs. 5-6, the primers used to amplify qGhDTX51 are shown in SEQ ID NOs. 7-8, the primers used to amplify qGhCML1 are shown in SEQ ID NOs. 9-10, the primers used to amplify qGhPCMPE87 are shown in SEQ ID NOs. 11-12, the primers used to amplify qGhPCMPE88 are shown in SEQ ID NOs. 13-14, the primers used to amplify qGhCLASRP are shown in SEQ ID NOs. 15-16, and the primers used to amplify GhActin are shown in SEQ ID NOs. 17-18).

[0044] The internal control gene used in the experiment was GhActin (GenBank accession number AY305733). -ΔΔCTMethods: 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 include GhFT, GhCAL, GhSOC1, GhAP1, GhCOL2, GhSVP, and GhLFY. At least three biological replicates were used for each experiment.

[0045] 1.6 VIGS experiments in cotton

[0046] To explore the function of candidate genes in controlling FT, VIGS experiments were performed using Zhongmian 113 as the recipient material to functionally verify the four candidate genes. The corresponding silencing fragments (300-500bp) of the four candidate genes were introduced into a TRV-based (pYL156) vector and designated TRV:GhFRO7, TRV:GhCML1, TRV:GhPCMP-E88, and TRV:GhCLASRP. The vectors were then introduced into Agrobacterium tumefaciens strain GV3101 using the freeze-thaw method. The primers used to construct the pYL156 vector to silence the four candidate genes are shown in SEQ ID NOs. 19-26. Among them, the primers for GhFRO7 are SEQ ID NOs. 19-10, the primers for GhCML1 are SEQ ID NOs. 21-22, the primers for GhPCMP--E88 are SEQ ID NOs. 23-24, and the primers for GhCLASRP are SEQ ID NOs. 25-26.

[0047] TRV:GhCLA1 (positive control), TRV:00 (negative control), TRV:GhFRO7, TRV:GhCML1, TRV:GhPCMP-E88, and TRV:GhCLASRP were then mixed with the helper vector pYL192 at a 1:1 ratio and injected into the cotyledons of 7-day-old cotton plants after incubation at 28°C in the dark for 3 hours. Virus-infected seedlings were incubated in the dark in an artificial climate incubator for 24 hours before being transferred to long-day (16 h light / 8 h dark) conditions. For the positive control (TRV:GhCLA1), after the appearance of albinism, gene-silenced plants with expression levels less than 50% of those in TRV:00 plants were selected by qRT-PCR; these selected plants were designated TRV:GhFRO7, TRV:GhCML1, TRV:GhPCMP-E88, and TRV:GhCLASRP. Five early maturity-related traits were investigated in TRV:00, TRV:GhFRO7, TRV:GhCML1, TRV:GhPCMP-E88, and TRV:GhCLASRP: bud break time (BT), FT, plant height (PH), first fruiting branch node (FFBN), and first fruiting branch node height (HFFBN). At least nine plants were used for each VIGS construct.

[0048] 1.7 Selective Adaptation Signals

[0049] As indicators of genetically distant 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, VCFtools was used to calculate π and Fst around significant SNPs extending over a 100 kb range for the YZRR, YRR, NSEMR, and NIR groups. π and Fst were calculated identically for early, mid-period, and modern varieties. Furthermore, a 10 kb sliding window and 10 kb step size were used to determine Fst and π.

[0050] 1.8 Development of CAPS Marker

[0051] Based on two SNPs (D10_61214168 and D11_24001762) within the candidate gene, 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 Biochemical Technology Co., Ltd., 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 879 bp and 631 bp PCR products, and they were separated by electrophoresis on a 1.5% (w / v) agarose gel.

[0052] 2 Results

[0053] 2. FT phenotypic diversity of 1418 upland cotton germplasms

[0054] All germplasms were grown in the field in the following six environments: E1, E2, E3, E4, E5 and E6. A wide range of variation in FT was observed in the present invention. In E1, the range of FT was 75.5-89.5d; in E2, the range of FT was 60-73d; in E3, the range of FT was 69-85d; in E4, the range of FT was 63-87.5d; in E5, the range of FT was 64-89.5d; in E6, the range of FT was 68.67--83.67d; for BLUP, the range of FT was 71.94-80.42d. In E4, the coefficient of variation of FT was the largest, at 4.80%, while for BLUP, the coefficient of variation of FT was the smallest, at 1.88% (Table 2). Pearson's correlation analysis found that FT was significantly positively correlated between different environments. The distribution of FT was roughly normal in all environments, which is a typical characteristic of quantitative traits regulated by multiple genes. The results of variance analysis also showed that environment, genotype and their interaction had a significant effect on FT (Table 2). In addition, the h of FT 2 The results showed that FT was mainly affected by genetic factors, but also by the environment.

[0055] Table 2 Statistics of flowering time phenotypes in six environments

[0056]

[0057] Table 3 Analysis of variance (ANOVA) and broad-sense heritability of flowering schedule phenotypes of 418 varieties under six environments

[0058]

[0059] 2.2 Identification of SNPs significantly associated with FT

[0060] The present invention uses principal component analysis, phylogenetic tree analysis and population structure analysis to divide 418 upland cotton varieties into three major subgroups. The linkage disequilibrium (LD) decay rate is about 0.46kb. After extensive screening, a total of 1,574,302 high-quality SNPs were found. There are 576,078 SNPs in the Dt subgenome and 997,954 SNPs in the At subgenome, of which the number of SNPs in the At subgenome is approximately 1.73 times that of the Dt subgenome. The SNP density is physically located on 26 chromosomes. In order to identify new genes that control FT, the present invention performs GWAS by using GEMMA's MLM to analyze the FT phenotypic data of a single environment and BLUP of all environments. A total of 457 important SNPs (-log10(p)>5) were identified by GWAS. Among them, 4 SNP sites were found in E1, 210 were found in E2, 13 were found in E3, 25 were found in E4, 146 were found in E5, 33 were found in E6, and 25 were found in BLUP. It was shown that MLM can be used to identify association signals. The average 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. It can be seen that 25 important SNP sites are located within genes, of which 18 lead to non-synonymous mutations in 8 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 FT and were associated across multiple environments. Specifically, the D11_24011417_SNP was associated with FT in E1, E6, and BLUP, while the D11_24011426_SNP showed significant associations in both E6 and BLUP. These findings demonstrate a polygenic basis for FT plasticity.

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

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

[0063] Due to the tight linkage association among the 11 SNP loci, three core haplotypes (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-GG) were identified and named D11_Hap1, D11_Hap2, and D11_Hap3, respectively. Figure 1b). D11_Hap1, D11_Hap2, and D11_Hap3 had 385, 4, and 149 variants, respectively. Similarly, the FT of the D11_Hap3 line (76.40 d) was shorter on average than that of the D11_Hap1 line (78.97 d) and the D11_Hap2 line (78.29 d); therefore, D11_Hap3 was called a favorable haplotype ( Figure 2 c). In addition, the haplotype frequency distribution of the Min-50 (83.07d) and Max-50 (70.88d) lines was calculated to confirm the effect of these haplotypes on FT. The present invention found that the Min-50 germplasm showed a more favorable haplotype frequency 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 of A02_Hap1, A02_Hap2, and A02_Hap3 were 0.55, 0.04, and 0.41, respectively. The results showed that A02_Hap3 was the superior haplotype because it was more frequently distributed in the Min-50 population ( Figure 2 The frequencies of D10_Hap1 and D10_Hap3 were 0.94 and 0.06 in the Max-50 population, and 0.41 and 0.59 in the Min-50 population, respectively. The results showed that D10_Hap3 was the superior haplotype because it was 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 showed that D11_Hap3 was the superior haplotype because it was more frequently distributed in the Min-50 population ( Figure 2 In order to identify favorable alleles that promote flowering, the present invention selected important SNPs (D09_6523710 and D09_50028094) located on chromosome D09 in the GhPCMP-E87 and GhHEXBP genes for analysis (Figure 3). Figure 1a). The D09_6523710 SNP is divided into three types: AA, AG, and GG. The 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. In addition, the present 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 in Min-50 were greater than those in Max-50. In conclusion, D09_6523710_GG and D09_50028094_AA are favorable alleles for early flowering.

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

[0065] The present 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 Jiiumian8) and four late-flowering varieties. The present 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 showed no regular differential expression in either early-flowering or late-flowering varieties ( Figure 3ad). The above results indicate that the four genes, GhFRO7, GhCML1, GhPCMP-E88 and GhCLASRP, may be related to the regulation of cotton FT and may be potential candidate genes. Based on the four FT candidate genes, the present invention developed two CAPS markers. These markers rely on changes in the restriction endonuclease BstBI recognition sites caused by the D10_61214168 (A / G) and D11_24001762 (A / C) alleles for genotyping. Specifically, PCR products of 879bp and 631bp were obtained by primer amplification of the cotton genomic DNA region containing the D10_61214168 and D11_24001762 sites, respectively. Theoretically, two fragments of 369bp and 510bp should be produced after cutting with the restriction endonuclease BstBI of the D10_61214168_AA genotype PCR amplification product. After BstBI digestion, the PCR amplification product of the D11_24001762_AA genotype should theoretically produce two fragments of 338 bp and 293 bp ( Figure 4 The experimental results showed that after digestion with BstBI, the PCR amplification product of the D10_61214168_AA genotype showed two independent bands in agarose gel electrophoresis ( 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 generated were of similar size ( Figure 4 d).

[0066] 2.5 Silencing candidate genes significantly increases flowering

[0067] In order to explore the biological functions of candidate genes related to FT, the present invention conducted VIGS experiments on four potential FT regulatory genes (GhFRO7, GhCML1, GhPCMP-E88 and GhCLASRP). The VIGS experiment was successful when plants treated with TRV:GhCLA1 showed an albinism phenotype 8 days after virus injection. In addition, compared with TRV:00 control plants, the expression levels of these four genes in most gene-silenced plants were much lower. To further understand the connection between gene expression and FT, the present invention examined five early maturity-related traits in TRV:00 and silenced plants: BT, FT, PH, FFBN and HFFBN. Compared with TRV:00 control plants, plants silenced for GhFRO7, GhCML1, GhPCMP-E88 or GhCLASRP all exhibited an earlier flowering phenotype ( Figure 5 In addition, the BT of these gene silenced plants occurred significantly earlier than that of the TRV:00 control plants ( Figure 5Compared with the control plants, the GhCML1 gene silenced plants showed lower pH and HFFBN values, and their FFBN values ​​were significantly lower than those of the 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, and GhCML1 plays an important role in regulating FT, PH, HFFBN and NFFBN of upland cotton.

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

[0070] In order to verify the role of the four candidate genes in regulating flowering, the present invention detected several key flowering genes in silenced plants of upland cotton, including GhFT, GhCAL, GhSOC1, GhAP1, GhCOL2, GhSVP and GhLFY. The present 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 In the silenced TRV:GhCML1 and TRV:GhPCMP-E88 plants, the relative expression levels of GhFT, GhCAL, GhSOC1, GhAP1, GhCOL2, and GhLFY were significantly higher than those in the control plants, while the relative expression level of GhLFY was significantly lower than that in the control plants ( Figure 6 (b, c). Compared to control plants, TRV:GhCLASSRP-silenced plants showed increased expression of GhFT, GhCAL, GhAP1, and GhLFY, while significantly decreased expression of GhSOC1, GhCOL2, and GhSVP. These results suggest that the four candidate genes, GhFRO7, GhCML1, GhPCMP-E88, and GhCLASSRP, participate in the regulation of FT by influencing the expression of key flowering-related genes.

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

Claims

1. A method for regulating the flowering time of upland cotton, characterized in that: The method comprises the step of inhibiting the expression of GhCML1, GhPCMP-E88 or GhCLASRP gene.

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

3. A breeding method for upland cotton, characterized in that: The method comprises the steps of detecting the expression level of GhCML1, GhPCMP-E88 or GhCLASRP gene in the variety and selecting the variety with low expression level for breeding.

4. A gene combination for regulating the flowering time of upland cotton, characterized in that: Contains at least one of the GhCML1, GhPCMP-E88 and GhCLASRP genes.

5. The gene combination according to claim 4, characterized in that The gene combination is used for screening or breeding early-flowering upland cotton varieties.

6. A molecular marker for detecting flowering time of upland cotton, characterized in that: The molecular markers are developed based on SNP sites or haplotypes of the GhFRO7, GhCML1, GhPCMP-E88 or GhCLASRP genes.

7. The molecular marker according to claim 6, characterized in that The molecular marker is a CAPS marker, which is developed based on the D10_61214168 or D11_24001762 SNP site.

8. The molecular marker according to claim 7, characterized in that The CAPS marker was genotyped using the restriction endonuclease BstBI.

9. A breeding method for upland cotton, characterized in that: The following steps are involved: Detecting the expression level or haplotype of the GhCML1, GhPCMP-E88 or GhCLASRP gene in the variety; selecting varieties with low expression levels or carrying the D10_Hap3, D11_Hap3 haplotype for breeding; the haplotype is identified by the CAPS marker described in claim 7.

10. Application of genes GhCML1, GhPCMP-E88 or GhCLASRP in regulating flowering time of upland cotton.

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