Development and application of SNP molecular marker related to lint percentage of upland cotton

Abstract

The present application relates to the field of genetic engineering, in particular to the development and application of SNP molecular markers related to lint content of Gossypium hirsutum Linn. The present application develops the sequences of SNP1 and SNP2 and provides the method for genetic breeding and variety screening. Compared with the prior art, the method provided by the present application directly detects seed DNA, is not limited by time, environment and other factors, saves the time and input of high-lint material screening, and reduces the breeding cost of high-yield cotton.

Description

Technical Field

[0001] This invention belongs to the field of genetic engineering, specifically involving the development and application of SNP molecular markers related to terrestrial cotton calyx. Background Technology

[0002] Cotton is the world's most important natural fiber crop, and ensuring cotton fiber production is crucial for the stable development of the textile industry. High and stable yields have always been important goals of cotton breeding. Upland cotton accounts for over 95% of the annual cotton fiber production. Lint percentage (LP) is a significant component of cotton yield and has been the most effective trait for improving cotton yield in my country since the 1950s. Therefore, further improving lint percentage is an effective way to gradually increase my country's cotton production.

[0003] Marker-assisted recombinant breeding is considered an important tool for future crop breeding, based on the development of a batch of useful and efficient molecular markers. SSRs and SNPs are currently the two most widely used molecular markers. Among them, SNPs (Single nucleoprotein polymorphisms) have the largest number, widest distribution, and best polymorphism in the genome, making them the ideal molecular markers for constructing high-density genetic maps. High-throughput sequencing technology is the main method for developing high-quality SNPs, and with the reduction in sequencing costs, SNPs are gradually becoming a new generation of widely used molecular markers. Shen et al. used upland cotton recombinant inbred lines as experimental materials and located 11 yield-related QTLs based on a genetic map containing 110 SSR markers with a total map distance of 810.07 cM. Subsequently, by densifying the map markers, they constructed a genetic map containing 156 SSR markers with a total map distance of 1024.4 cM and located 26 QTLs. Using upland cotton recombinant inbred lines as experimental material, N i ng et al. constructed a genetic map containing 279 SSR markers with a total map distance of 1576.25 cM, locating 61 yield-related QTLs. Zhang et al., using upland cotton recombinant inbred lines as experimental material, developed SLAF-SNP markers and constructed a high-density genetic map containing 5521 SNPs with a total map distance of 3259.37 cM, locating 18 single-boll weight QTL loci stable in multiple environments, and annotating 344 genes. Ma et al. performed resequencing and association analysis on 419 upland cotton accessions, indicating that Gh_D02G0025 may be a key gene affecting lint percentage.

[0004] While a large number of QTL loci related to lint percentage exist, useful and efficient molecular markers remain scarce, making it difficult to achieve efficient marker-assisted selection in breeding. The SNP molecular marker combination disclosed in this invention can significantly improve the selection effect for lint percentage and will play an important role in the breeding of high-lint percentage varieties. Summary of the Invention

[0005] This invention provides two molecular markers for the identification of upland cotton varieties, the base sequences of which are SEQ ID No.1 and SEQ ID No.2.

[0006] This invention also provides a method for identifying and screening upland cotton clothing, comprising the following steps:

[0007] (1) Selecting quadrats

[0008] (2) Extracting DNA

[0009] DNA was extracted from the parents and 200 F2 single plants using the CTAB method. DNA integrity was detected by agarose gel electrophoresis, and DNA concentration was determined using NanoDrop 2000.

[0010] (3) Simplified genome sequencing

[0011] SNPs were developed using the Genotyping by Sequencing (GBS) method published by ELSHI RE et al. DNA was digested with two enzymes, MseI and TaqαI (Thermo-scientific Fermentas); adapters were ligated; DNA fragments of 397–420 bp (Qiagen, Valencia, CA) were recovered by gel electrophoresis and amplified by PCR (Phusion High-Fide Litey, Finnzymes), followed by sequencing on the Illumina HiSeq™ platform.

[0012] (4) Develop SNP

[0013] Data from the sequencing process was filtered using LI and other data analysis methods, and high-quality sequences were aligned to the TM-1 reference genome using BWA (0.7.17) software. SNP markers were identified using GATK (4.0.11.0) software.

[0014] (5) Constructing a genetic map

[0015] Genetic maps were constructed using MSTMap software.

[0016] (6) Implement QTL positioning

[0017] QTL positioning was performed using the Composite Interval Mapping (CIM) method in WinQTLCart 2.5 software, with a window size of 5 cM, a step size of 1 cM, 10 background markers, and a LOD value of 2.5.

[0018] (7) Mining SNP markers related to calyx

[0019] Based on the confidence intervals of the QTL, SNPs at their central locations were extracted. According to the two base types of the SNPs, the tested population was divided into two classes of individuals (lines), and the difference in lint percentage between the two classes was calculated. SNPs with highly significant differences were selected as candidate markers for further validation.

[0020] (8) Verification and application of SNP markers.

[0021] The beneficial effects of this invention are as follows: Compared with the prior art, the method provided by this invention can directly detect seed DNA, without being limited by time, environment and other factors, saving time and investment in screening high-lint content materials, and reducing the cost of high-yield cotton breeding. Attached Figure Description

[0022] Figure 1 A high-density genetic map containing 16,088 SNPs and a total map distance of 4282.81 cM. Figure 2 Wi nQTLCart detection results image

[0023] Figure 3 Figure 1 shows the average lint percentage and the significance of differences among the groups. Specific Implementation

[0024] 1. Creation of research materials and field design

[0025] A hybrid combination was constructed using Jifeng 1271 as the female parent and Jifeng 173 as the male parent. Hybridization was completed in Shijiazhuang, Hebei Province in the summer of 2018. In the winter of the same year, F1 was planted in Sanya, Hainan Province, and self-pollinated to harvest F2. In the summer of 2019, these F2 plants were planted in Shijiazhuang, Hebei Province, with 15 rows and 405 individual plants, spaced 7m apart, 0.7m apart, and 0.2m apart. 200 individual plants were randomly selected and continuously self-pollinated to obtain F3 and F4 plants, which were then planted in Shijiazhuang, Hebei Province in 2020 and 2021, respectively, with 4m rows, 0.7m apart, and 0.2m apart, with two replicates. All plants were managed using conventional field practices.

[0026] 2. Extracting DNA

[0027] DNA was extracted from the parents and 200 F2 single plants using the CTAB method. DNA integrity was detected by agarose gel electrophoresis, and DNA concentration was determined using NanoDrop 2000.

[0028] 3. Simplified genome sequencing

[0029] SNPs were developed using the Genotyping by Sequencing (GBS) method published by ELSH IRE et al. DNA was digested with two enzymes, MseⅠ and TaqαⅠ (Thermochemical Fermentas); adapters were ligated; DNA fragments of 397–420 bp (Qiagen, Valencia, CA) were recovered by gel electrophoresis and amplified by PCR (Phusion High-Fidelity, Finnzymes), followed by sequencing on the Illumina HiSeq™ platform.

[0030] 4. Develop SNPs

[0031] Data from the sequencing process was filtered using LI and other data analysis methods, and high-quality sequences were aligned to the TM-1 reference genome using BWA (0.7.17) software. SNP markers were identified using GATK (4.0.11.0) software.

[0032] 5. Constructing a genetic map

[0033] Genetic maps were constructed using MSTMap software.

[0034] 6. Implement QTL positioning

[0035] QTL positioning was performed using the Composite Interval Mapping (CIM) method in WinQTLCart 2.5 software, with a window size of 5 cM, a step size of 1 cM, 10 background markers, and a LOD value of 2.5.

[0036] 7. Discover SNP markers related to genomic distribution.

[0037] Based on the confidence intervals of the QTL, SNPs at their central locations were extracted. According to the two base types of the SNPs, the tested population was divided into two classes of individuals (lines), and the difference in lint percentage between the two classes was calculated. SNPs with highly significant differences were selected as candidate markers for further validation.

[0038] 8. Validation and Application of SNP Markers: An F2 population of 405 individuals was constructed using Jifeng 1271 as the maternal parent and Jifeng 173 as the paternal parent. The peltate percentage (LP) of the population was investigated. 200 individuals were randomly selected, and genomic DNA was extracted using the CTAB method. After passing the tests, GBS simplified genome sequencing was performed. High-quality SNP molecular markers were developed using bioinformatics techniques and software, and a high-density genetic map containing 16088 SNPs with a total map distance of 4282.81 cM was constructed (see appendix). Figure 1 Using WinQTLCart software, a QTL qLP-A13 for a single LP was located on chromosome A13. This QTL was detectable in the F2, F3, and F4 generations. (See attached image) Figure 2 The contribution rate was 6.54%-13.78%, and the enhancing gene originated from Jifeng 1271.

[0039] 2. SNP molecular markers

[0040] Two high-quality SNP molecular markers (SNP1 and SNP2) were found in the qLP-A13 site. The bases of Jifeng 1271 are T and G, respectively, and the bases of Jifeng 173 are A and A, respectively. The 50 bp upstream and downstream base sequences are shown in Table 1.

[0041]

[0042] Table 1

[0043] 3. Application of SNP molecular marker combinations

[0044] Using SNP1 and SNP2 in Jifeng 1271 and Jifeng 173, the genomic DNA sequence of individual plants in the F2 population was detected to determine the base type of each plant at the target site and the genotype was determined according to the base type of the parents. The genotype with the same genotype as Jifeng 1271 was designated as B, the genotype with the same genotype as Jifeng 173 was designated as A, and the heterozygous genotype was designated as H. The F2, F3, and F4 populations were divided into groups A, B, and H using the three genotypes, and the average lint percentage and significance of the differences in each group were calculated.

[0045] The results showed that, as shown in the attached document Figure 3 As shown in Table 2, (1) group A has the lowest lint percentage, group B has the highest lint percentage, and group H has a lint percentage in the middle; (2) SNP1 or SNP2 alone can clearly distinguish the lint percentage of different genotype groups, with the difference reaching a highly significant level; (3) after the combination of SNP1 and SNP2, the difference in lint percentage between different genotype groups increases. This indicates that the combination of SNP1 and SNP2 can improve the efficiency of lint percentage identification. In breeding, this molecular marker combination can be used to detect seed genomic DNA, make early judgments on materials with high or low lint percentages, effectively save breeding time, reduce costs, and improve efficiency.

[0046]

[0047] Table 2.

Claims

1. A combination of SNP molecular markers for the identification of upland cotton clothing, wherein the combination of SNP molecular markers consists of SNP1 and SNP2; The nucleotide sequence of SNP1 is shown in SEQ ID No.

1. The polymorphism at position 51 is either T or A. When the polymorphism at position 51 is T, it has a higher pelvic phenotype. The nucleotide sequence of SNP2 is shown in SEQ ID No.

2. The polymorphism at position 51 is G or A. When the polymorphism at position 51 is G, it has a higher pelvic phenotype. The upland cotton is Jifeng 1271, Jifeng 173, or a offspring bred from either of these as parents.

2. The application of the SNP molecular marker combination of claim 1 in lint identification or auxiliary screening of upland cotton varieties Jifeng 1271 and Jifeng 173 or their offspring, wherein when the polymorphism at position 51 of SNP1 is T, it has a higher lint percentage trait; and when the polymorphism at position 51 of SNP2 is G, it has a higher lint percentage trait.

3. Use according to claim 2, characterized in that, The cotton genomic DNA to be tested is provided, and the genotype of the SNP molecular marker combination is detected. The lint percentage of cotton plants with the genotype TTGG is significantly higher than that of cotton plants with the genotype AAAA. The cotton is Jifeng 1271, Jifeng 173, or a offspring bred from both of them.

4. A method for breeding a high lint cotton variety, characterized in that, Genomic DNA was extracted from the cotton plant to be tested, and the genotype of the SNP molecular marker combination described in claim 1 was detected. Cotton plants with the genotype TTGG were selected for breeding. The cotton plant was Jifeng 1271, Jifeng 173, or a offspring bred from the two as parents.

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