Biomarker for identifying high-protein-content upland cotton variety and application of biomarker

Abstract

The invention discloses a biomarker for identifying high-protein-content upland cotton varieties and application of the biomarker, and relates to the technical field of biology. The biomarker is a gene GhiD03G013600 or a gene GhiA12G026360, and the gene GhiD03G013600 is a gene GhiA12G026360. The nucleotide sequence of the GhiD03G013600 gene is as shown in SEQ ID NO. 1, and the nucleotide sequence of the GhiD03G013600 gene is as The nucleotide sequence of the GhiA12G026360 gene is as shown in SEQ ID NO. 3. Research finds that the GhiA12G026360 gene and the GhiD03G013600 gene have differential expression in a low-protein-content upland cotton variety and a high-protein-content upland cotton variety, which indicates that the two genes may participate in the accumulation process of the protein content of the upland cotton and can be applied to identification of a high-protein-content upland cotton variety.

Description

Technical Field

[0001] The present invention relates to the field of biotechnology, and in particular to a biomarker for identifying upland cotton varieties with high protein content and application thereof. Background Art

[0002] Cotton is an economic crop that combines fiber, oil, and protein. Cottonseed, as a by-product of cotton, has great application prospects. It can not only be used as an oil resource, but also as a potential plant protein resource. The protein contained in cotton kernels is equivalent to that of soybean protein, and its quality and nutritional value far exceed those of cereal protein. Cottonseed protein can not only be used as edible protein, but also as an economical and affordable plant protein for feeding. High-protein cottonseed can replace soybean protein to a certain extent to meet the feed shortage in the development of my country's animal husbandry industry and promote the development of my country's animal husbandry industry. At present, research on the protein content of upland cotton is relatively lagging, and there are few high-protein excellent varieties, which cannot meet the market demand well. How to better utilize the rich upland cotton germplasm resources and cultivate high-protein upland cotton varieties has become an urgent problem to be solved. Exploring genes related to the protein content of upland cotton is an important way to cultivate high-protein upland cotton varieties. Summary of the invention

[0003] The purpose of the present invention is to provide a biomarker for identifying high-protein content upland cotton varieties and its application to solve the problems existing in the above-mentioned prior art. The present invention has found that the Ghir_A12G026360 gene and the Ghir_D03G013600 gene are differentially expressed in low-protein content upland cotton varieties and high-protein content upland cotton varieties, indicating that these two genes may be involved in the accumulation process of upland cotton protein content and can be used to identify high-protein content upland cotton varieties.

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

[0005] The present invention provides a biomarker for identifying high-protein content upland cotton varieties, wherein the biomarker is the Ghir_D03G013600 gene or the Ghir_A12G026360 gene;

[0006] The nucleotide sequence of the Ghir_D03G013600 gene is shown in SEQ ID NO.1;

[0007] The nucleotide sequence of the Ghir_A12G026360 gene is shown in SEQ ID NO.3.

[0008] The present invention also provides a primer pair for detecting the above biomarker. When the biomarker is the Ghir_D03G013600 gene, the primer pair comprises an upstream primer having a nucleotide sequence as shown in SEQ ID NO.5 and a downstream primer having a nucleotide sequence as shown in SEQ ID NO.6;

[0009] When the biomarker is the Ghir_A12G026360 gene, the primer pair includes an upstream primer having a nucleotide sequence as shown in SEQ ID NO.7 and a downstream primer having a nucleotide sequence as shown in SEQ ID NO.8.

[0010] The present invention also provides the use of a reagent for detecting the expression amount of the above-mentioned biomarker in preparing a detection product for identifying upland cotton varieties with high protein content.

[0011] Furthermore, the detection product is a test kit.

[0012] Furthermore, the reagent is the above-mentioned primer pair.

[0013] The present invention also provides a detection product for identifying upland cotton varieties with high protein content, including a reagent for detecting the expression amount of the above-mentioned biomarker.

[0014] Furthermore, the detection product is a test kit.

[0015] Furthermore, the reagent is the above-mentioned primer pair.

[0016] The present invention also provides the use of the above-mentioned biomarkers, primer pairs or detection products in identifying high-protein content upland cotton varieties.

[0017] The present invention also provides a method for identifying high-protein-content upland cotton varieties, comprising the steps of detecting the expression level of the above-mentioned biomarker in the upland cotton sample to be tested, and identifying the high-protein-content upland cotton varieties according to the expression level detection results;

[0018] When the biomarker is the Ghir_D03G013600 gene, the lower the expression level of the Ghir_D03G013600 gene, the higher the protein content of the upland cotton sample to be tested;

[0019] When the biomarker is the Ghir_A12G026360 gene, the higher the expression level of the Ghir_A12G026360 gene in the early stage of ovule development, the higher the protein content of the upland cotton sample to be tested; the lower the expression level of the Ghir_A12G026360 gene in the middle and late stages of ovule development, the higher the protein content of the upland cotton sample to be tested.

[0020] The present invention discloses the following technical effects:

[0021] Based on the determination of protein content of 491 upland cotton samples by near infrared spectroscopy, the present invention randomly selected 146 samples for Kjeldahl nitrogen determination, analyzed the phenotype and the interaction between genotype and environment; further obtained QTLs / SNPs related to protein content of upland cotton by GWAS analysis, and screened candidate genes in the confidence interval in combination with the transcriptome data of "TM-1". The present invention selected 2 QTLs as candidate intervals from the QTLs detected by multiple environments and two methods, found two significant SNP sites, and identified a total of 12 candidate genes in the 200Kb interval upstream and downstream of these two sites. The published RNA-seq expression profile data and annotation information were used to finally screen out 2 candidate genes, and qRT-PCR was used for verification, and it was found that Ghir_A12G026360 and Ghir_D03G013600 were differentially expressed in low protein content varieties and high protein content varieties, indicating that these two genes may be involved in the accumulation process of upland cotton protein content.

[0022] The present study discovered stable genetic loci related to the protein content of upland cotton, laying the foundation for further exploring the genetic mechanism of upland cotton protein. This is of great significance for effectively screening excellent materials to alleviate the shortage of protein raw materials in feed, breeding and other industries and to improve the comprehensive utilization rate of cotton seeds. BRIEF DESCRIPTION OF THE DRAWINGS

[0023] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0024] Figure 1 This is a time-space distribution map of 491 upland cotton varieties; dots represent different breeding periods; green: before 1949, red: 1950-1979, blue: 1980-1999, brown: 2000-present; according to the geographical origin of the materials: Northern Extra Early Maturity Cotton Region (NSER), Northwest Inland Cotton Region (NIR), Yellow River Basin Cotton Region (YRR), Yangtze River Basin Cotton Region (YZRR) and foreign materials (Foreign); the yellow cotton mark represents the planting area this time, from high to low in latitude, they are Liaocheng, Shandong, Huanggang, Hubei, Sanya, Hainan;

[0025] Figure 2is the distribution diagram of SNPs at different positions of each chromosome; where a is the distribution density of SNPs on different chromosomes; b is the distribution ratio of SNPs in different regions of the genome;

[0026] Figure 3 The figure is a population structure diagram of 491 upland cotton germplasm resources; a is a cluster analysis diagram based on the NJ method; b is a population structure diagram based on principal component analysis; c is a subgroup component analysis (K=2, 3), and the y-axis represents the probability statistics of an individual belonging to a certain subgroup;

[0027] Figure 4 is the candidate gene location map of chromosome A12; a is the local Manhattan map of E2 (Liaocheng in 2022); b is the local Manhattan map of BLUP1 environment; c is the LD heat map of 200Kb upstream and downstream of RsGhir_A12_105119146; d is the box plot of the phenotypes of different haplotype materials of rsGhir_A12_105119146; e is the phenotypes of rsGhir_A12_105119146 in four ecological regions (NIR: Northwest Inland Cotton Region; YZRR: Yangtze River Basin Cotton Region; YRR: Yellow River Basin Cotton Region; NSER: Northern Extra Early Cotton Region); f is the genetic diversity of rsGhir_A12_105119146 in four breeding periods; g is the tissue-specific expression heat map of the candidate gene; h is the qRT-PCR analysis of Ghir_A12G026360 in extreme varieties, and the asterisks in the figure indicate significant differences between the periods ( * P<0.05, ** P<0.01); "Xinluzhong4" is a low-protein material carrying the AA haplotype; "IsraelV" is a high-protein material carrying the CC haplotype;

[0028] Figure 5 is the candidate gene location map of chromosome D03; a is the local Manhattan map of BLUP2; b is the LD heat map of 200kb upstream and downstream of rsGhir_D03_44545099; c is the box plot of the phenotypes of different haplotype materials of rsGhir_D03_44545099; d is the genetic diversity distribution of rsGhir_D03_44545099 in four ecological regions (NIR: Northwest Inland Cotton Region; YZRR: Yangtze River Basin Cotton Region; YRR: Yellow River Basin Cotton Region; NSER: Northern Extra Early Cotton Region); e is the genetic diversity of the qPC-D03-3 interval in four breeding periods; f is the tissue-specific expression of the candidate gene; g is the qRT-PCR analysis of Ghir_D03G013600, and the asterisks in the figure indicate significant differences between the periods ( * P<0.05, **P<0.01); "CRI16" is a low-protein material carrying the GG haplotype; "IsraelV" is a high-protein material carrying the AA haplotype. DETAILED DESCRIPTION

[0029] 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 should be understood as a more detailed description of certain aspects, features, and embodiments of the present invention.

[0030] It should be understood that the terms described in the present invention are only for describing a particular embodiment and are not intended to limit the present invention. In addition, for the numerical range in the present invention, it should be understood that each intermediate value between the upper and lower limits of the scope is also specifically disclosed. The intermediate value in any stated value or stated range, and each smaller range between any other stated value or intermediate value in the described range is also included in the present invention. The upper and lower limits of these smaller ranges can be independently included or excluded in the scope.

[0031] Unless otherwise indicated, all technical and scientific terms used herein have the same meanings as those generally understood by those skilled in the art. Although the present invention describes only preferred methods and materials, any methods and materials similar or equivalent to those described herein may also be used in the implementation or testing of the present invention. All documents mentioned in this specification are incorporated by reference to disclose and describe the methods and / or materials associated with the documents. In the event of a conflict with any incorporated document, the content of this specification shall prevail.

[0032] It will be apparent to those skilled in the art that various modifications and variations may be made to the specific embodiments of the present invention description without departing from the scope or spirit of the present invention. Other embodiments derived from the present invention description will be apparent to those skilled in the art. The present invention description and examples are exemplary only.

[0033] The words “include,” “including,” “have,” “contain,” etc. used in this document are open-ended terms, meaning including but not limited to.

[0034] Example 1

[0035] 1. Materials and Methods

[0036] 1.1 Material sources and material processing

[0037] The present invention uses 491 natural populations of representative cotton germplasm resources as experimental materials (see Table 1), which are divided according to the ecological zones where the materials come from ( Figure 1), of which 151 were from the Northwest Inland Cotton Area, 27 were from the North Early-maturing Cotton Area, 188 were from the Yellow River Basin Cotton Area, 86 were from the Yangtze River Basin Cotton Area, 31 were from foreign materials, and the sources of 8 materials were not yet clear. A total of three field test sites were set up in this experiment from 2020 to 2023, as shown in Table 2. They are located at Linqing Experiment Station of Shandong Cotton Research Center, Liaocheng City, Shandong Province (LC; 36°48′N, 115°41′E), Experiment Station of Huanggang Academy of Agricultural Sciences, Huanggang City, Hubei Province (HG; 30°57′N, 114°92′E) and Sanya National Germplasm Sanya Wild Cotton Nursery, Sanya City, Hainan Province (SY; 18°36′N, 109°17′E). All three sites were designed in randomized blocks. Except for Hainan, which set up two biological replicates and harvested across years, the remaining two sites set up three biological replicates and harvested in the same year. Cotton was managed according to the local tillage and cultivation system. At maturity, 20 cotton bolls with smooth cotton boll opening and natural fullness were harvested from the middle of each variety. After air drying under natural conditions, the fibers and cotton seeds were separated using a roller gin. The separated cotton seeds were then delinted with concentrated sulfuric acid, washed and exposed to the sun for more than two days. Afterwards, healthy, full and uniform cotton seeds were selected as test materials for subsequent near-infrared spectroscopy analysis and Kjeldahl nitrogen determination to determine the protein content of upland cotton.

[0038] Table 1 491 upland cotton varieties

[0039]

[0040]

[0041] Table 2 Field design and layout of natural populations

[0042]

[0043] Note: Kjeldahl method (KM); near infrared spectroscopy (NIRS).

[0044] 1.2 Determination of protein content in upland cotton

[0045] Near-infrared spectroscopy analysis method: A FOSS near-infrared analyzer (NIRS DS2500F, Denmark) was used for detection. The near-infrared spectral data of cotton seeds were substituted into the constructed model using WINISIIII (FOSS Near-infrared Systems, Silver Springs, MD, USA) software to output the predicted value of cotton seed protein content. Finally, the average value of 9 scans was taken for subsequent analysis.

[0046] Kjeldahl nitrogen determination method: The method refers to the national standard GB / T5009.5-2016.

[0047] 1.3 Resequencing data comparison and SNP marker detection

[0048] FastQC (v0.11.9) was used to assess the quality of the resequencing data of 491 and 146 cotton germplasm resources, and fastp (v0.23.2) was used to remove the adapter sequences and low-quality reads in the sequencing samples. The resequencing data quality-controlled by BWA software (v0.7.17-r1188) were aligned with the reference genome "TM-1" of Huazhong Agricultural University version 1.1 (HAUv1.1). SAMtools (v0.1.19-44428cd) was used to convert the alignment results into Bam format, and the MarkDuplicates module of GATK (v4.2.6.1) was used to remove duplicate data.

[0049] GATK, bcftools (v0.1.19-44428cd) and VCFtools (v0.1.16) were used to jointly identify variant sites. The filtering conditions were as follows: (1) The variant sites that could be identified by GATK, bcftools and VCFtools were retained at the same time; (2) The quality value of each SNP site was guaranteed to be greater than 30; (3) The “Variant Filtration” module of GATK was used to filter the variant sites with “QD < 2.0, MQ < 35.0, FS > 70.0, SOR > 3.0, MQ Rank Sum < -12.5, Read Pos Rank Sum < -4.0”; (4) Finally, VCFtools was used to filter the SNP variant sites with minor allele frequency (MAF) > 5% and missing rate (missing rate) < 20%.

[0050] 1.3.1 Phylogenetic tree analysis

[0051] A python script was used to screen quadruple degenerate loci (4DSNPs) from 491 SNP datasets of upland cotton, and 7080 4D SNPs were finally obtained. The vcf file containing 4DSNPs was used to calculate the distance matrix of each sample, and then submitted to ATGC FastME2.0 (http: / / www.atgc-montpellier.fr / fastme / ), and the neighbor joining method was selected to construct the phylogenetic tree, and the "ggtree" in R (v4.3.2) was used for visualization.

[0052] 1.3.2 Principal Component Analysis

[0053] The principal component analysis (PCA) of 7080 4D SNPs was performed using the software GCTA (v1.94.1), and the first two components (PCA1 and PCA2) were selected as eigenvectors and visualized using the “ggplot2” package in R language.

[0054] 1.3.3 Group structure analysis

[0055] Admixture (v1.3.0) software was used to divide the population structure of 7080 4D degenerate sites identified in 491 natural populations. The K value ranged from 2 to 10 and was repeated 10 times. The appropriate K value was selected as the number of subpopulations based on the principle of maximum likelihood value, and then visualized using "ggplot2".

[0056] 1.4 Data processing and statistical analysis

[0057] Phenotype frequency histograms were plotted using R “ggplot2”, descriptive statistics of 11 environments were calculated using the “pastecs” package, and the broad-sense heritability of protein content (H 2 ) and Best Linear Unbiased Prediction (BLUP), and the “corrplot” package was used to draw the correlation matrix heat map. The “agricolae” package was used to perform LSD multiple comparisons of different ecological zones and breeding periods (P < 0.05). Genetic diversity was calculated using VCFtools (v0.1.16) software and visualized using “ggplot2”.

[0058] 1.5 Genome-wide association analysis

[0059] A total of 2296753 and 2222327 high-quality SNPs were used, with BLUP values ​​from 11 environments (E1, E2, E3, E4, E5, E6, E7, E8, E9, E10, and E11) and two methods as phenotypic data. The mixed linear model (MLM) in GEMMA (v0.98.3) was used for genome-wide association analysis. According to the principle of Bonferroni correction, -log 10 (P)>6.36 (P=1 / n, n is the total number of SNPs in the present invention) is too strict, and some sites related to the content of related proteins may be filtered out, resulting in a small number of identified QTLs. Therefore, the present invention adopts -log 10(P)>5 was used as the threshold to screen significant sites. The Manhattan plot was then drawn using the “CMplot” package in R, and “ggplot2” was used to draw the haplotypes of the excellent sites (P<0.05).

[0060] 1.6 Candidate gene screening

[0061] According to the LD decay distance of 300Kb in upland cotton, the significant SNPs above the threshold are divided into QTLs. The QTL naming method is QTL+trait+chromosome+number of QTLs, where QTL is represented by lowercase "q"; traits are represented by capital abbreviations, such as cottonseed protein content (Protein Content) is represented by PC; if there are multiple QTLs on the same chromosome, Arabic numerals 1, 2, 3, etc. are added after the chromosome. After using Haploview (v4.2) to determine the LDblock interval where the significant site is located, the LD linkage map is drawn. All genes in the LD block interval are extracted according to the physical position, and the candidate genes are finally determined by combining the results of gene expression, gene domain, Arabidopsis homologous annotation, etc.

[0062] The present invention uses the original sequencing data of different tissues and different developmental stages of the upland cotton standard reference system "TM-1", the data comes from the SRA database of NCBI (https: / / www.ncbi.nlm.nih.gov / sra / , PRJNA490626), uses salmon software (v0.13.1) to quantitatively analyze the transcripts, generates a gene expression matrix, and uses the TPM method to normalize the data, and uses the "pheatmap" package in R to visualize the gene expression levels.

[0063] 1.7 qRT-PCR analysis

[0064] In order to verify the expression level of the candidate gene, the present invention planted cotton materials with different protein contents - "CRI16", "Israel V" and "Xinluzhong 4" in the farm garden of Zhejiang Agriculture and Forestry University (30°20′N, 119°34′E). The day of flowering was set as day 0, and ovule samples were taken at 0, 10, 20 and 30 days after flowering, and three replicates were taken. After being frozen with liquid nitrogen, they were stored in a -80°C refrigerator. Total RNA was extracted using an RNA kit (Novozyme RC411), and after reverse transcription to obtain cDNA, real-time fluorescence quantitative PCR was performed. The reaction system is shown in Table 3, the reaction procedure is shown in Table 4, and the primer sequence is shown in Table 5.

[0065] qRT-PCR calculation method: GhActin4 was used as the internal reference gene, and 2 -ΔΔCTThe gene expression levels among three replicates were calculated by the PCR method, and the gene expression levels were visualized by GraphPadPrism (v10.0.3).

[0066] Table 3 Real-time fluorescence quantitative PCR reaction system

[0067]

[0068]

[0069] Table 4 Real-time fluorescence quantitative PCR reaction program

[0070]

[0071] Table 5 qRT-PCR primers

[0072]

[0073] 2. Results and Analysis

[0074] 2.1SNP marker variation statistics

[0075] The present invention detected 2222327 high-quality SNPs in 146 populations, and identified a total of 2296753 high-quality SNPs in a natural population consisting of 491 upland cottons. The SNPs identified in the 491 populations were all unevenly distributed on the 26 chromosomes of upland cotton (Table 6). There were obvious differences in the number of SNPs on different chromosomes. There were 1433396 SNPs distributed on the A subgenome, which was about 1.66 times that of the D subgenome, which was consistent with the size ratio of the At subgroup and the Dt subgroup. Among them, the A08 chromosome had the largest number of SNP markers, with a total of 264411 SNPs, accounting for 11.51%; the D04 chromosome had the least number of SNP markers, which was 33533 SNPs, accounting for 1.46%. From the perspective of the whole genome, the SNP marker density distributed on chromosome A08 was the highest, with an average of 2160 SNPs detected per Mb; the SNP marker density distributed on chromosome A02 was the lowest, with an average of 521 SNPs detected per Mb.

[0076] Table 6 Summary of SNP information on 26 chromosomes

[0077]

[0078]

[0079] ANNOVAR was used to annotate and classify these SNPs ( Figure 2), it was found that 1,939,461 SNPs were located in the intergenic region, accounting for 84.44% of the total; the number of SNPs located in the upstream region of the gene was 148,145, and the number of SNPs located in the downstream region of the gene was 95,158, accounting for 6.45% and 4.14% of the total, respectively; there were 20,277 SNPs located in the coding region of the gene, which contained 12,975 non-synonymous mutations, thus causing codon changes; in addition, there were 69,165 SNPs located in the intron region, accounting for 3.01% of the total.

[0080] 2. Analysis of the natural population structure of 2491 upland cotton samples

[0081] 7080 4D degenerate loci (4D SNPs) were obtained from high-quality SNP datasets of 491 natural populations. After removing materials with unknown ecological regions, population structure analysis was performed on 483 materials ( Figure 3 c). It was found that when K=2, these materials were mainly divided into two subgroups, and then the distribution of different ecological sources of varieties in the two subgroups was analyzed. Subgroup 1 (G1) has a total of 310 materials, accounting for 63.1% of the total number of materials, of which the number of materials from the Yellow River and Yangtze River cotton areas is the largest, with 167 materials from the Yellow River cotton area and 71 materials from the Yangtze River cotton area. Among the remaining materials, 43 materials come from the northwest inland cotton area, 8 materials come from the northern extra-early maturing cotton area, and 21 materials belong to foreign countries; Subgroup 2 (G2) contains a total of 173 materials, accounting for 35.2% of the total materials, of which 108 materials are from the northwest inland cotton area, the highest proportion; 19 materials belong to the northern extra-early maturing cotton area, 21 materials belong to the Yellow River cotton area, 15 materials belong to the Yangtze River cotton area, and 10 materials belong to foreign varieties. The neighbor-joining method was used for cluster analysis to construct a phylogenetic tree ( Figure 3 The results in a) are consistent with the population structure results obtained by Admixture software, and the materials of G1 and G2 subgroups are also clustered together on the evolutionary tree. In order to verify the accuracy of the grouping, PCA analysis was performed on the genotypes ( Figure 3 b), the results show that among the 491 materials, the materials from the Yangtze River Basin and the Yellow River Basin cotton areas are mainly clustered together, while the materials from the Northwest Inland Cotton Area and the Northern Extra Early Maturing Cotton Area are clustered together, and the materials from foreign countries are scattered among these cotton areas, which is consistent with the previous two clustering results. Overall, the 491 materials are mainly divided into two categories.

[0082] 2.3 Genome-wide association analysis

[0083] The present invention uses 2296753 high-quality SNPs obtained from 491 populations and 2222327 high-quality SNPs obtained from 146 populations to perform genome-wide association analysis with protein content of upland cotton determined by near-infrared spectroscopy and Kjeldahl nitrogen determination, respectively, with the threshold set to -log 10 (P)>5.

[0084] The results of association analysis based on near-infrared spectroscopy showed that a total of 803 significant loci were identified, of which the loci on the Dt subgenome (702) were significantly more than those on the At subgenome (101), and the phenotypic variation explanation rate of these loci was between 3.90% and 6.79%. The most loci were on chromosome D12, with 372, -log 10 (P) ranged from 5.01 to 8.90, followed by chromosome D04, -log 10 (P) ranges from 5.00 to 7.90; and the number of sites detected on chromosomes A10 and D08 is the least, only 1. According to the LD decay distance of Kb, a total of 93 QTLs were identified, of which 63 QTLs were located in the At subgenome and 30 QTLs were located in the Dt subgenome. The present invention regards QTLs identified in two or more environments as stable QTLs, and finally found 24 stable QTLs. It is worth noting that the site reported in the article of Liu et al. is located in the qPC-A12-6 interval of the present invention, so the present invention believes that candidate genes can be further mined in this QTL interval.

[0085] The results of association analysis based on Kjeldahl nitrogen determination showed that a total of 413 significant SNPs were identified, most of which were distributed in the Dt subgenome, and the PVE of these sites was between 12.56% and 22.4%. The D03 chromosome had the largest number of sites, with a total of 283, -log 10 The range of (P) was between 5.01 and 8.18. The 413 significant SNPs were divided into 40 QTLs according to the LD decay distance of 300Kb, of which 30 QTLs were distributed in the At subgenome and 10 were distributed in the Dt subgenome. A total of 8 stable QTLs were identified.

[0086] By comparing the QTL intervals identified by the two methods, five QTLs were finally detected by the two methods (Table 7), namely qPC-A06-12, qPC-A06-14, qPC-A08-22, qPC-A12-7 and qPC-D03-3. These five intervals contained a total of 343 significant SNPs, -log 10(P) ranged from 5.0 to 8.19. qPC-D03-3 was also detected in seven environments, with 279 SNPs in this interval, the most significant SNP being rsGhir_D03_44836627, -log 10 The (P) value is 8.19, which shows that qPC-D03-3 is also a highly confident interval. In summary, the present invention sets the two intervals qPC-A12-6 and qPC-D03-3 as candidate intervals of the present invention.

[0087] Table 7 Identification of protein content QTLs in upland cotton by multiple environments or two methods

[0088]

[0089] Note: a: physical location of the most significant SNP; b: P value of the most significant SNP under the MLM model; c: represents different determination methods, ALL represents the joint detection of two methods.

[0090] 2.4 QTL Summary and Comparison

[0091] Since amino acids are an important component of protein content, the present invention summarizes the published QTLs of cottonseed protein traits (including amino acid traits). Among the 128 QTLs identified in the present invention, 22 QTLs overlap with QTLs reported by previous researchers, of which 7 were detected by Kjeldahl nitrogen determination, including 7 SNPs, and 15 were detected by near infrared, including 19 SNPs (Table 8). The above results show that both methods have a certain degree of accuracy, among which more QTL intervals were identified under near infrared spectral scanning, which may be because near infrared uses a larger population, and thus can identify more sites overlapping with previous studies.

[0092] Table 8 The QTL intervals overlapped between the present invention and previous studies on protein content in upland cotton

[0093]

[0094]

[0095] 2.5 Screening of candidate genes related to protein content in upland cotton

[0096] 2.5.1 Analysis of candidate genes on chromosome A12

[0097] The present invention found that there is a QTL interval on chromosome A12 that was identified by the two environments E2 (LC_2022) and BLUP1, and was reported in previous studies. This shows that this is a highly confident interval, so the present invention focuses on the interval qPC-A12-6, which contains only one SNP, namely rsGhir_A12_105119146. The present invention then performed a haplotype analysis on this SNP site to explore the association between haplotype and phenotype. Through genotyping, the present invention found that there are mainly two haplotypes at this site, namely, a variety containing 56 copies of haplotype AA and a variety containing 429 copies of haplotype CC ( Figure 4 d), and then the haplotype of rsGhir_A12_105119146 was subjected to variance analysis. Except for E3 (HG_2021) and E5 (SY2020_2021) environments, the remaining 6 environments showed significant phenotypic differences between varieties containing AA haplotype and varieties containing CC haplotype (P<0.05), and the protein content of varieties containing CC haplotype was significantly higher than that of varieties containing AA haplotype; In order to further understand the genetic characteristics of rsGhir_A12_105119146 in geographical distribution ( Figure 4 e), 491 upland cotton materials were divided into four major ecological source areas: NIR, YZRR, YRR, and NSER. It is worth noting that the four major ecological regions are more likely to obtain the dominant haplotype (CC) (>75%). In addition, the genetic diversity of the rsGhir_A12_105119146 locus decreased with the increase of breeding period, and the genetic diversity of upland cotton varieties after 2000 was the lowest ( Figure 4 The above results all indicate that there may be candidate genes related to controlling protein content in upland cotton near the rsGhir_A12_105119146 locus.

[0098] Then, near the linkage interval 200Kb upstream and downstream of this significant site ( Figure 4 c), 10 candidate genes were found, and the public transcriptome expression showed that the expression level of Ghir_A12G026360 in ovules was significantly higher than that in fibers ( Figure 4gh, Table 9), through homology comparison and combined with GO annotation, the present invention believes that Ghir_A12G026360 may be a candidate gene related to seed protein content. The homologous gene of Ghir_A12G026360 in Arabidopsis is glutamate synthase (GLT1). Through GO annotation, it was found that this gene is mainly involved in the ammonia assimilation cycle, the biological process of glutamate synthesis, and there is only one in Arabidopsis. Studies have reported that the glt1-T mutant showed severe growth defects in Arabidopsis under photorespiratory conditions, and under non-photorespiratory growth conditions, glt1-T was unable to convert glutamine (Glutamine, Gln) to Glu, which would accumulate Gln in the leaves, ultimately affecting nitrogen assimilation. These results all indicate that GLT1 plays a non-redundant role in glutamate synthesis and the compensatory metabolism of nitrogen status in Arabidopsis. In order to further verify the expression level of the candidate gene in cotton, the qRT-PCR technology was used to detect the expression level of Ghir_A12G026360 in cotton varieties with different protein contents. Analysis showed that the expression level of Ghir_A12G026360 in the low-protein material containing the AA haplotype "Xinluzhong4" was lower than that in the high-protein material containing the CC haplotype "IsraelV" in the early stage of development. With the increase of the development period, the expression level of this gene gradually increased, and was significantly higher than that of the high-protein material in the middle and late stages of ovule development. Therefore, the present invention determines that this gene may be involved in the process of ovule protein synthesis.

[0099] Table 910 homologous genes and annotations of predicted candidate genes

[0100]

[0101] 2.5.2 Analysis of candidate genes on chromosome D03

[0102] In addition, the present invention found that there were clustered sites on chromosome D03 and they were significantly higher than the threshold ( Figure 5 ). The present invention then noticed that the qPC-D03-3 interval was detected by both methods. After statistics, the present invention found that there were 279 significant SNPs in the qPC-D03-3 interval, of which 27 SNPs were detected in two or more environments. Therefore, candidate genes can be mined in this interval. The present invention noticed that one of the SNPs (rsGhir_D03_44545099) was detected in both E8 (2021_LC) and BLUP2 ( Figure 5 Through genotyping, the present invention found that there are two haplotypes at this locus, namely AA and GG, among which the protein content of varieties containing the GG haplotype is significantly lower than that of varieties containing the AA haplotype in eight environments ( Figure 5c); the present invention then analyzed the genetic characteristics of the geographical distribution of this site ( Figure 5 d), it was found that the frequency of dominant haplotype (AA) was lower in varieties from NSER, but higher in the remaining three ecological zones (>50%); at the same time, within this interval, with the increase of breeding period, genetic diversity also decreased, and the genetic diversity of cotton varieties before the 1970s was significantly higher than that of varieties before the 1990s ( Figure 5 e), while some cotton varieties from 2000 to the present have the lowest genetic diversity. Linkage disequilibrium analysis of SNP revealed that the SNP is located in a strong linkage interval of 97.4 Kb ( Figure 5 b), while there are only two genes in this interval (Table 10), and public transcriptome analysis shows ( Figure 5 In f), the expression of Ghir_D03G013600 in ovules was significantly higher than that in fibers, especially at 20 DPA. The homologous gene of Ghir_D03G013600 in Arabidopsis is AT5G59410, which encodes a Rab5 interacting protein (Rab5ip). Rab5 is a regulatory guanosine triphosphatase that is associated with sorting endosomes and participates in endosomal membrane fusion reactions. It is also known as the switch of vesicle transport, affecting the transport of intracellular proteins.

[0103] It has been reported that Rab5ip represents a novel Rab5 interacting protein, which may act as a receptor of Rab5-GDP on endocytic vesicles and participate in the activation of Rab5. Therefore, the present invention considers Ghir_D03G013600 as a candidate gene for controlling cottonseed protein content on D03. In order to further verify the expression of the candidate gene, the expression level of Ghir_D03G013600 in varieties with different protein contents was detected using qRT-PCR technology. The results showed that the expression of Ghir_D03G013600 in low-protein materials containing GG haplotype "CRI16" was higher than that of high-protein materials containing AA haplotype "IsraelV" at all stages of the development process, and reached a significant level at 10DPA and 20DPA of ovule development, so the present invention determines that the gene may be related to the synthesis of upland cotton protein.

[0104] Table 102 homologous genes and annotations of the predicted candidate genes

[0105]

[0106] In summary, on chromosome A12, the present invention focuses on the interval qPC-A12-6, and then locates a candidate gene Ghir_A12G026360 in this interval, encoding GLT1, also known as glutamine-α-ketoglutarate transaminase (GOGAT), which converts inorganic nitrogen into organic nitrogen by participating in the glutamine synthetase (GS) / GOGAT cycle, and is considered to be a key gene involved in nitrogen absorption and nitrogen reabsorption produced by amino acid metabolism. There is only one NADH-GOGAT (AtGLT1) in Arabidopsis, and since the GOGAT gene is long and difficult to clone, there are few studies on the functional verification of this gene. NADH-GOGAT in rice is encoded by two genes, OsNADH-GOGAT1 and OsNADH-GOGAT2. Studies have shown that knockout materials of OsNADH-GOGAT1 and OsNADH-GOGAT2 will lead to a decrease in rice yield. Some studies have also shown that the NADH-GOGAT gene is located in the QTL region that controls the protein content of rice grains, and the metabolism of glutamine and glutamate will affect the protein content and free fatty acid composition of plant grains. Subsequently, the present invention compared the homology of Ghir_A12G026360 with the NADH-GOGAT2 of rice and found that the homology was as high as 70%. It is speculated that the gene may perform a similar function to NADH-GOGAT2. The expression level of this gene in different protein contents at different developmental stages of cotton seeds was verified by qRT-PCR. Since GhActin4 is more stably expressed in all tissues of cotton, it is selected as the internal reference gene of the present invention. The results showed that in the early stage of ovule development, Ghir_A12G026360 was expressed at a higher level in high-protein varieties. At 20DPA of ovule development, the expression level in low-protein varieties increased and gradually exceeded that of high-protein varieties. It is speculated that cotton seeds with high protein content are more sensitive in the early stage of development and have strong adaptability to the environment, so they convert amino acids earlier and start protein synthesis, so there is a higher level of glutamate synthase in the early stage, while low-protein cotton seeds start glutamate conversion in the later stage, so there is a phenomenon of differential gene expression. This shows that this gene may have different functions in upland cotton with different protein contents, and the specific regulatory mechanism needs further exploration.

[0107] In higher plants, seed storage proteins are synthesized on the rough endoplasmic reticulum, and amino acids directly absorbed from the embryo or obtained through transamination reactions are subsequently transported to the protein storage vacuole via a vesicle-mediated pathway. In cottonseed, the two main storage proteins are globulins and albumins. During the cottonseed maturation process, both globulins and albumins are synthesized and stored in separate protein vacuoles. Rab5 has been reported to be involved in the transport of endosomes to vacuoles in Arabidopsis; in rice, the new guanine nucleotide exchange factor Rab5-GEF2 discovered can also activate Rab5a and two other Rab5 isoforms, participate in vesicle transport regulation, and is very important for the intracellular transport of glutenin precursors from the Golgi apparatus to the storage vacuole. Rab5 mutants with guanine nucleotide binding defects can cause small vesicles to accumulate at the cell periphery, which may inhibit vesicle fusion. This shows that the activation of Rab5 is very important. The newly discovered Ghir_D03G013600 on chromosome D03 of the present invention encodes a Rab5 interacting protein (Rab5ip), which is a novel Rab5 interacting protein that may play a role in the early steps of endosomal fusion and activate Rab5, and participate in vesicle transport and protein synthesis. Currently, Rab5ip protein has only been reported in the water stress resistance of fresh cut flowers, and no further research has been carried out in plants. The expression level of Ghir_D03G013600 in cotton varieties with different protein contents at different developmental stages was verified by real-time fluorescence quantitative PCR technology. The expression level of this gene was gradually decreasing in both high-protein and low-protein materials, and the expression level was higher in low-protein varieties than in high-protein varieties. At 10DPA and 20DPA of ovule development, the expression reached a significant difference level, indicating that this gene may have an antagonistic relationship with Rab5, affecting vesicle fusion by inhibiting the activation of Rab5, and ultimately affecting the synthesis of cottonseed protein. This shows that this gene may play a negative regulatory role in the accumulation of cotton protein content, which is contrary to previous studies on water stress resistance, indicating that this gene may play a different function in cotton than in other crops. The potential role of Rab5ip in the protein synthesis and transport pathway of upland cotton needs further experimental verification.

[0108] The nucleotide sequence of the Ghir_D03G013600 gene is shown in SEQ ID NO.1, and the amino acid sequence of the Ghir_D03G013600 protein is shown in SEQ ID NO.2; the nucleotide sequence of the Ghir_A12G026360 gene is shown in SEQ ID NO.3, and the amino acid sequence of the Ghir_A12G026360 protein is shown in SEQ ID NO.4.

[0109] The embodiments described above are only descriptions of the preferred modes of the present invention, and are not intended to limit the scope of the present invention. Without departing from the design spirit of the present invention, various modifications and improvements made to the technical solutions of the present invention by ordinary technicians in this field should all fall within the protection scope determined by the claims of the present invention.

Claims

1. A biomarker for identifying high-protein upland cotton varieties, characterized in that: The biomarker is the Ghir_D03G013600 gene or the Ghir_A12G026360 gene; The nucleotide sequence of the Ghir_D03G013600 gene is shown in SEQ ID NO.1; The nucleotide sequence of the Ghir_A12G026360 gene is shown in SEQ ID NO.

3.

2. A primer pair for detecting the biomarker according to claim 1, characterized in that: When the biomarker is the Ghir_D03G013600 gene, the primer pair includes an upstream primer having a nucleotide sequence as shown in SEQ ID NO.5 and a downstream primer having a nucleotide sequence as shown in SEQ ID NO.6; When the biomarker is the Ghir_A12G026360 gene, the primer pair includes an upstream primer having a nucleotide sequence as shown in SEQ ID NO.7 and a downstream primer having a nucleotide sequence as shown in SEQ ID NO.

8.

3. Use of a reagent for detecting the expression amount of the biomarker according to claim 1 in preparing a detection product for identifying high-protein content upland cotton varieties.

4. The use according to claim 3, characterized in that: The detection product is a test kit.

5. The use according to claim 3, characterized in that: The reagent is the primer pair according to claim 2.

6. A detection product for identifying high-protein content upland cotton varieties, characterized in that: Comprising a reagent for detecting the expression amount of the biomarker according to claim 1.

7. The detection product according to claim 6, characterized in that: The detection product is a test kit.

8. The detection product according to claim 6, characterized in that: The reagent is the primer pair according to claim 2.

9. Use of the biomarker according to claim 1, the primer pair according to claim 2, or the detection product according to any one of claims 6 to 8 in identifying high-protein content upland cotton varieties.

10. A method for identifying high-protein cotton varieties, characterized in that: The method comprises the steps of detecting the expression level of the biomarker according to claim 1 in the upland cotton sample to be tested, and identifying the upland cotton variety with high protein content according to the expression level detection result; When the biomarker is the Ghir_D03G013600 gene, the lower the expression level of the Ghir_D03G013600 gene, the higher the protein content of the upland cotton sample to be tested; When the biomarker is the Ghir_A12G026360 gene, the higher the expression level of the Ghir_A12G026360 gene in the early stage of ovule development, the higher the protein content of the upland cotton sample to be tested; the lower the expression level of the Ghir_A12G026360 gene in the middle and late stages of ovule development, the higher the protein content of the upland cotton sample to be tested.

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