SNP chip for detecting genotype of lettuce and application thereof

Abstract

The application discloses a SNP chip for detecting a lettuce genotype and application thereof. The application provides a chip for detecting a lettuce genotype, which comprises: reagents for specifically detecting 1210 SNP sites; the 1210 SNP sites are 588 SNP sites in Table 1 and 622 SNP sites in Table 2; and position information of the 1210 SNP sites is determined by alignment based on a lettuce genome reference sequence, wherein the lettuce genome reference sequence is Lsat_Salinas_v11 version. The SNP chip of the application provides a powerful, efficient and economic technical platform for lettuce genetic breeding research, can accelerate the breeding process of the lettuce, deepen genetic analysis and promote innovation of germplasm resources.

Description

Technical Field

[0001] This invention relates to the field of biotechnology, and more specifically to an SNP chip for detecting lettuce genotypes and its applications. Background Technology

[0002] Lettuce is an important leafy vegetable worldwide, possessing extremely high economic value and nutritional and health benefits. With increasingly diversified market demands, higher requirements are being placed on the breeding of new lettuce varieties, such as high yield, high quality, disease resistance, stress tolerance, and wide adaptability. Traditional breeding methods mainly rely on phenotypic selection, which has limitations such as long cycles, low efficiency, and susceptibility to environmental influences.

[0003] Marker-assisted selection (MAS) and genome-wide selection (GS) are key technologies for overcoming the bottlenecks of traditional breeding, with their core being rapid, accurate, and high-throughput genotyping of germplasm resources. Among numerous molecular markers, single nucleotide polymorphisms (SNPs) have become the preferred next-generation molecular markers due to their wide distribution, abundance, high stability, and ease of automated detection in the genome.

[0004] Currently, solid-phase matrix-based SNP chip technology is very mature and widely used in major crops (such as rice, corn, and wheat). However, the development of genotyping tools is relatively lagging behind in lettuce, an important vegetable crop. Existing technologies mainly suffer from the following problems:

[0005] 1. The contradiction between throughput and cost: Traditional molecular marker technologies (such as SSR and RFLP) have low throughput and slow efficiency, which cannot meet the detection needs of large-scale breeding populations. While some high-throughput sequencing technologies can obtain a large number of SNPs, they are expensive and complex to analyze, making them difficult to apply on a large scale in routine breeding procedures.

[0006] 2. Lack of specialized, high-efficiency genotyping tools: There is a lack of cost-effective, medium-throughput SNP genotyping chips specifically designed for lettuce. While solid-phase chips offer high throughput, their customization and manufacturing costs are high, and they lack flexibility, making them unsuitable for the needs of small and medium-sized breeding units or specific research projects.

[0007] 3. Insufficient marker density and representativeness: Existing lettuce SNP marker sets often suffer from problems such as limited number, uneven genome coverage, or low efficiency in detecting polymorphisms in different ecological types of lettuce (e.g., head, loose leaf, Roman, and stem lettuce), which limits their effectiveness in genome-wide association studies (GWAS) and fine gene mapping.

[0008] In conclusion, developing a lettuce-specific SNP chip with independent intellectual property rights, superior performance, and controllable cost is of great strategic significance and practical application value for enhancing the core competitiveness of lettuce breeding in my country and ensuring the sustainable development of the vegetable industry. Summary of the Invention

[0009] To address the aforementioned technological gaps and deficiencies, the present invention aims to provide a Lettuce 1K liquid phase SNP chip.

[0010] In a first aspect, the present invention claims protection for a chip for detecting the genotype of lettuce.

[0011] The chip for detecting lettuce genotypes claimed in this invention includes: a reagent for specifically detecting 1210 SNP sites; the 1210 SNP sites are the 588 SNP sites in Table 1 and the 622 SNP sites in Table 2; The location information of the 1210 SNP sites was determined by alignment with the lettuce genome reference sequence, which is version Lsat_Salinas_v11 (Genome assembly Lsat_Salinas_v11, URL: https: / / www.ncbi.nlm.nih.gov / datasets / genome / GCF_002870075.4 / ).

[0012] The location information of each target region mentioned below was also determined by comparison with the lettuce genome reference sequence (Lsat_Salinas_v11 version).

[0013] Furthermore, the reagent may be (or contain) a single-stranded nucleotide probe.

[0014] Furthermore, the chip includes 588 single-stranded nucleotide probes for detecting the 588 SNP sites in Table 1 and 1244 single-stranded nucleotide probes for detecting the 622 SNP sites in Table 2.

[0015] For each of the 588 SNP sites in Table 1, a target region (a 110bp sequence) is selected within a 110bp range upstream and downstream of the location of the SNP site on the lettuce genome reference sequence (Lsat_Salinas_v11 version). The target region covers the SNP site. A probe is designed for the target region, and the nucleotide sequence of the probe is the same as or reverse complementary to the nucleotide sequence of the target region.

[0016] For each of the 622 SNP sites in Table 2, two target regions are selected within a 110bp range upstream and downstream of the location of the SNP site on the lettuce genome reference sequence (Lsat_Salinas_v11 version). Each target region is a 110bp sequence and covers the SNP site. A probe is designed for each target region, and the nucleotide sequence of the probe is the same as or reverse complementary to the nucleotide sequence of the target region.

[0017] More specifically, the start and end positions of the target regions corresponding to each of the 588 single-stranded nucleotide probes used to detect the 588 SNP sites described in Table 1 are shown in Table 1. The 588 single-stranded nucleotide probes include the probe shown in SEQ ID NO:1.

[0018] More specifically, the start and end positions of the target regions corresponding to each of the 1244 single-stranded nucleotide probes used to detect the 622 SNP sites described in Table 2 are shown in Table 2. The 1244 single-stranded nucleotide probes include the two probes shown in SEQ ID NO:2 and SEQ ID NO:3.

[0019] Furthermore, in the chip, the single-stranded nucleotide probe is modified with biotin.

[0020] Accordingly, the chip also includes magnetic beads modified with streptavidin.

[0021] In some embodiments of the present invention, the chip is a liquid-phase probe hybridization chip.

[0022] Secondly, the present invention claims protection for the use of the chip described in the first aspect above in any of the following: (A1) Construction of a genetic map of lettuce; (A2) Construction of lettuce fingerprint profile; (A3) Analysis of lettuce population structure; (A4) Identification of lettuce varieties; (A5) Kinship test of lettuce; (A6) Locating genes for lettuce traits.

[0023] Thirdly, the present invention claims protection for the application of the chip described in the first aspect above in lettuce breeding.

[0024] Furthermore, the breeding can be molecular marker-assisted breeding.

[0025] The beneficial effects of this invention are: 1. Achieving a balance between high throughput and low cost: By adopting liquid-phase capture technology, only specific probes need to be synthesized, and targeted enrichment and high-throughput sequencing can be performed in solution, avoiding the high manufacturing cost of solid-phase chips and significantly reducing the detection cost of a single sample.

[0026] 2. Improved flexibility and efficiency of testing: This technology allows for flexible adjustment of sample size according to different project needs, enabling "on-demand testing", which is particularly suitable for material screening of different generations in the breeding process, greatly improving breeding efficiency.

[0027] 3. Ensure the optimality and universality of the markers: The selected 1,000+ SNP loci are evenly distributed throughout the genome, exhibiting high polymorphism, high reproducibility, and good representativeness. They can effectively distinguish different lettuce germplasm and are suitable for constructing high-density genetic maps, conducting population structure analysis, and constructing fingerprint maps of core germplasm resources.

[0028] The successful development of the lettuce 1K liquid phase SNP chip of this invention will provide a powerful, efficient, and economical technical platform for lettuce genetic breeding research. Its application will: (1) accelerate the breeding process: achieve rapid and accurate selection of target traits (such as disease resistance, commercial quality, bolting time, etc.) and shorten the breeding cycle. (2) deepen genetic analysis: provide a powerful tool for discovering key genes that control important agronomic traits and promote lettuce functional genomics research. (3) promote germplasm resource innovation: achieve accurate evaluation and efficient utilization of lettuce germplasm resources and lay the foundation for the discovery and introduction of new genes. Attached Figure Description

[0029] Figure 1 The distribution map of chromosomes marked by 1210 SNPs.

[0030] Figure 2 This is a clustering diagram of samples (PC1_PC2) drawn based on the PCA results.

[0031] Figure 3 This is a clustering diagram of samples (PC1_PC3) drawn based on the PCA results.

[0032] Figure 4 The sample clustering diagram (PC2_PC3) is drawn based on the PCA results.

[0033] Figure 5 This is a sample clustering diagram (pca.3D) drawn based on the PCA results.

[0034] Figure 6 This is a line graph showing the cross-validation error rate.

[0035] Figure 7 Genetic diagram of the sample when K=7.

[0036] Figure 8 This is a phylogenetic tree.

[0037] Figure 9 Heatmap of kinship relationships. Detailed Implementation

[0038] The present invention will now be described in further detail with reference to specific embodiments. The given embodiments are merely illustrative of the invention and not intended to limit its scope. The embodiments provided below can serve as a guide for further improvements by those skilled in the art and do not constitute a limitation on the invention in any way.

[0039] Unless otherwise specified, the experimental methods used in the following examples are conventional methods, performed according to the techniques or conditions described in the literature in this field or according to the product instructions. Unless otherwise specified, the materials and reagents used in the following examples are commercially available.

[0040] Example 1: Design and fabrication of a lettuce 1K liquid-phase SNP chip I. Screening of SNP sites This invention performed whole-genome resequencing on 1238 original lettuce samples, yielding 30TB of data with an average sequencing depth of 10×. First, the original sequence data was aligned to the lettuce reference genome using the minimap2 tool. Then, SNP calling was performed using the GATK4 tool, and the SNP data underwent rigorous filtering, retaining SNPs with a MAF (minimum allele frequency) less than or equal to 0.05 and a deletion rate less than or equal to 0.01. Deletion genotype inference was performed using Beagle. After these steps, 15,734,280 SNP genotypes without deletions were retained. To remove redundant information, LD trimming was performed using the PLINK tool with parameters set to "500 50 0.8", yielding 2,878,014 high-quality SNPs as background markers. In addition, to ensure the uniform distribution of these SNPs in the genome, the clumping command in MRBIGR software was used to further process the SNP sites with the parameter set to "-win 3000 -r2 0.01" to ensure that the linkage between the selected SNP sites does not exceed a certain threshold, thereby obtaining 34,510 SNP data that are more representative and uniformly distributed.

[0041] Based on the obtained genotype data, a genome-wide association study (GWAS) was conducted, combining it with 21 lettuce phenotypic indicators. SNPs with a significant association p-value less than 1e-5 were initially included in the foreground marker set. To improve the specificity and accuracy of the markers, the screening process was further optimized: by extracting flanking sequences of SNPs and comparing them with the lettuce reference genome, non-unique matching sequencing reads were filtered to identify highly specific marker sites. Simultaneously, redundant markers that overlapped between different phenotypic traits, as well as sites that overlapped with background markers, were removed, ultimately retaining 13,895 sites as the core foreground markers for the microarray. To further enrich the functional associations of foreground markers, this study systematically integrated published genetic resources: 28 articles reported genes / quantitative trait loci (QTLs) related to important lettuce traits were reviewed. These traits covered key agronomic characteristics such as downy mildew resistance, postharvest browning, water use efficiency, biomass accumulation, leaf size, head formation, leaf angle, leaf lobes, leaf margins, leaf color, stem color, seed color, bolting and flowering time, and seed dormancy and germination, involving a total of 252 functional genes or QTL intervals. The study first anchored these functional genes or QTL loci to their original reported lettuce reference genome (v11 version), then extracted 100bp flanking sequences from each SNP locus (total length 201bp) to construct a FASTA file, and rigorously compared it with the reference genome. Finally, 264 eligible foreground marker loci were selected from the 252 reported intervals. After integrating this subset of loci with the 13,895 core foreground markers obtained previously, the total number of foreground markers on the chip reached 14,159, providing more comprehensive functional marker support for subsequent chip applications and genetic analysis of lettuce traits.

[0042] Based on the above background and prospects, a total of 48,669 SNP loci were identified. Based on a uniform chromosome distribution, 1210 SNPs were ultimately evaluated and screened. The distribution of these 1210 SNP loci on the lettuce chromosome is shown below. Figure 1 As shown.

[0043] For each SNP site, one or two target regions were selected within a 110 bp range upstream and downstream of the SNP site on the lettuce genome reference sequence (Lsat_Salinas_v11 version). These target regions encompassed the SNP site. A probe was designed for each target region, with the nucleotide sequence of the probe identical to that of the target region (or alternatively, it could be designed to be inversely complementary). A total of 588 SNP sites with single-target regions were designed, and their SNP site and corresponding target region information are shown in Table 1; a total of 622 SNP sites with dual-target regions were designed, and their SNP site and corresponding target region information are shown in Table 2.

[0044] Table 1. Information on 588 SNP sites and their single target regions

[0045] Table 2. Information on 622 SNP sites and their dual target regions

[0046] In Tables 1 and 2, in the "SNP site" column, the character before the colon (:) is the chromosome number, and the Arabic numeral after the colon (:) is the physical location of the SNP site on the chromosome in the lettuce genome (determined based on alignment with the lettuce genome reference sequence Lsat_Salinas_v11). In the three characters following from right to left, the base before the ">" is the reference base (i.e., the base of the SNP site in Lsat_Salinas_v11), and the base after the ">" is the mutant base (i.e., the base of the SNP site in other materials).

[0047] In Table 1, for example, in “chr2:21735212T>C”, “Chr2” represents chromosome 2, and “21735212” indicates that the specific location of this SNP site on chromosome 2 in the Lsat_Salinas_v11 version of the lettuce genome reference sequence is position 21735212. “T>C” indicates that the nucleotide value of this SNP site is T in the lettuce genome reference sequence, while the nucleotide value is C in some other materials. In the “Target Region” column, the character before “-” is the start position of the target region, and the character after “-” is the end position of the target region. The target region is the location where probes are designed for the SNP sites in the first column. For example, the start and end positions of the target region for the SNP site “chr2:21735212T>C” correspond to positions 21735195 and 21735304 of chromosome 2 in the Lsat_Salinas_v11 version of the lettuce genome reference sequence, respectively. The nucleotide sequence of the target region is (5'-3'): TTGATTTCATAATTATCTGTCCTATAAAAGTCTCGAATTTTGGATTTATGGCAAACAGCTGTTTAAAAAAAATGGAACTTTGCAGAAACTTCACAGAAACGTTTCTTGGA (SEQ ID No. 1). The nucleotide sequence of the single-stranded DNA probe targeting this region is (5'-3'): TTGATTTCATAATTATCTGTCCTATAAAAGTCTCGAATTTTGGATTTATGGCAAACAGCTGTTTAAAAAAAATGGAACTTTGCAGAAACTTCACAGAAACGTTTCTTGGA (SEQ ID No. 1).

[0048] In Table 2, for example, in “chr7:93922665C>A”, “Chr7” represents chromosome 7, and “93922665” indicates that the specific location of this SNP site on chromosome 7 in the Lsat_Salinas_v11 version of the lettuce reference gene is position 93922665 on chromosome 7. “C>A” indicates that the nucleotide at this SNP site is C in the lettuce genome reference sequence, while the nucleotide in some other materials is A. In the “Target Region” column, the character before “-” is the start position of the target region, and the character after “-” is the end position of the target region. The target region is the location where probes are designed for the SNP sites in the first column. For example, the start and end positions of target region 1 for the SNP site “chr7:93922665C>A” correspond to positions 93922583 and 93922692 on chromosome 7 of the lettuce reference genome Lsat_Salinas_v11, respectively. The nucleotide sequence of target region 1 is (5'-3'): ACTTCCATAGAGTCAAACTGTAACTGCTTTTCATAGTCTCCAACTGACTCAGCTTCCAAGTTATTCAGTATCTGGGACCCACCATGTAAACTACTTTGTTTATCTTGAAA (SEQ ID No. 2). The nucleotide sequence of the single-stranded DNA probe targeting this target region 1 is (5'-3'): ACTTCCATAGAGTCAAACTGTAACTGCTTTTCATAGTCTCCAACTGACTCAGCTTCCAAGTTATTCAGTATCTGGGACCCACCATGTAAACTACTTTGTTTATCTTGAAA (SEQ ID No. 2). No. 2); the start and end positions of target region 2 of this SNP site correspond to positions 93922628 and 93922737 of chromosome 7 in the Lsat_Salinas_v11 version of the lettuce reference genome, respectively. The nucleotide sequence of target region 2 is (5'-3'): GACTCAGCTTCCAAGTTATTCAGTATCTGGGACCCACCATGTAAACTACTTTGTTTATCTTGAAAGGAATTTGTATCACCACTTGAAGCATCTGTTGTATGTGGCGCTTG (SEQ ID No. 3). The nucleotide sequence of the single-stranded DNA probe targeting target region 2 is (5'-3'): GACTCAGCTTCCAAGTTATTCAGTATCTGGGACCCACCATGTAAACTACTTTGTTTATCTTGAAAGGAATTTGTATCACCACTTGAAGCATCTGTTGTATGTGGCGCTTG (SEQ ID No. 3).

[0049] It should be noted that, given the reference genome and its version number, and the specific location information of the target region within it, obtaining the specific sequence information of each probe is very easy for those skilled in the art. Due to space limitations, the specific sequence information of each probe is not presented visually in this article.

[0050] II. Preparation and Application Method of the Lettuce 1K Liquid Phase SNP Chip of the Present Invention The experimental procedures for chip fabrication and normal chip use were all completed based on the GenoBaits technology system. The specific experimental procedures are as follows: 1. Extract genomic DNA from the sample to be tested and construct a sample library; (1) Sample DNA extraction DNA was extracted from the samples using the GenoPrep DNA Rapid Extraction Kit (magnetic bead method, Borui Biotechnology Co., Ltd.).

[0051] (2) Sample DNA quality inspection The DNA concentration of the test samples was determined using a Qubit Fluorometric Quantitation (Thermo Fisher) instrument, and the integrity of the DNA was detected by 1% agarose gel electrophoresis. Samples that passed the tests were stored at 4°C for future use.

[0052] (3) Sample DNA fragmentation Take 12 μL of qualified DNA and place it in a 0.2 μL PCR tube. Place the tube in an ultrasonic disruptor to randomly break the DNA into fragments of 200-400 bp.

[0053] (4) Sample end repair Add 4 μL of GenoBaits End Repair Buffer and 2.7 μL of GenoBaits End Repair Enzyme to the tube, add water to make up to 20 μL, and incubate at 37°C for 20 minutes in an ABI 9700 PCR instrument to complete the end repair and A addition process of the fragmented fragments.

[0054] (5) Sample sequencing adapter connection Remove the tube from the PCR instrument and add 2 μL of GenoBaits Ultra DNA ligase, 8 μL of GenoBaits Ultra DNA Ligase Buffer, and 2 μL of GenoBaits Adapter. Add water to a final volume of 40 μL, then place the tube on an ABI 9700 PCR instrument at 22°C for 30 minutes to complete the ligation of the sequencing adapter.

[0055] (6) Sample DNA purification 48 μL of Beckman AMPure XP Beads (Beckman) was added to the ligation product to purify it. After purification, the fragments were screened using magnetic beads, and ligation products with insert fragments of 200-300 bp were retained.

[0056] (7) Sample library amplification Add 5 μL of sequencing adapter with barcode sequence, 1 μL of P5 adapter, and 10 μL of LevoBaits PCR Master Mix to the PCR tube from the previous step, and bring the volume to 20 μL with pure water. Amplify using an ABI 9700 PCR instrument with the following program: 95℃ pre-denaturation for 5 min; 95℃ denaturation for 30 s, 60℃ annealing for 30 s, 72℃ extension for 30 s, 8 cycles; 72℃ extension for 5 min. Different barcodes are used to distinguish different samples.

[0057] (8) Sample library purification Add 24 μL of Beckmen AMPure XP Beads (Beackman) to the PCR amplification product from the previous step. After mixing well with a pipette, place the 0.2 μL PCR tube on a magnetic rack until the solution becomes clear. Discard the supernatant and wash the magnetic beads once with 75% ethanol. Elute the library DNA with Tris-HCl at pH 8.0 to obtain the sample library.

[0058] 2. Genotyping of target samples at 1K SNP loci using liquid-phase gene chips. (1) DNA hybridization Take 500 ng of the constructed sample genomic DNA sequencing library, add 5 μL of GenoBaits Block I and 2 μL of GenoBaits Block II, and place it on an Eppendorf Concentrator plus vacuum concentrator (Eppendorf) to evaporate to dryness at ≤70℃. Add 8.5 μL of GenoBaits 2×Hyb Buffer, 2.7 μL of GenoBaits Hyb Buffer Enhancer, and 2.8 μL of nuclease-free water to the dry powder tube, mix well with a pipette, and incubate at 95℃ for 10 minutes on an ABI 9700 PCR instrument. Then, remove the PCR tube and add 3 μL of the synthesized probe (biotin-modified, probe concentration 60 ng / μL), vortex to mix, and incubate at 65℃ for 2 hours on an ABI 9700 PCR instrument to complete the probe hybridization reaction.

[0059] (2) DNA capture Add 100 μL of GenoBaits DNA Probe Beads (magnetic beads coated with streptavidin) to the reaction system from the previous hybridization step, pipette up and down 10 times, and incubate at 65°C for 45 minutes on an ABI 9700 PCR instrument to allow the magnetic beads to bind to the probe. Wash the probe-bound magnetic beads with 100 μL of GenoBaits Wash Buffer I and 150 μL of GenoBaits Wash Buffer II at 65°C, then wash them at room temperature with 100 μL of GenoBaits Wash Buffer I, 150 μL of GenoBaits Wash Buffer II, and 150 μL of GenoBaits Wash Buffer III. Resuspend the washed magnetic beads in 20 μL of nuclease-free water.

[0060] Add 13 μL of resuspended DNA (with magnetic beads) to a new 0.2 mL PCR tube, then add 15 μL GenoBaits PCR Master Mix and 2 μL GenoBaits Primer Mix to prepare a post-PCR system. Perform library amplification using an ABI 9700 PCR instrument. The amplification program is as follows: 95℃ pre-denaturation for 5 min; 95℃ denaturation for 30 s, 60℃ annealing for 30 s, 72℃ extension for 30 s, 15 cycles; 72℃ extension for 5 min.

[0061] Add 45 μL of Beckmen AMPure XP Beads (Beckman) to the post-PCR product and mix thoroughly using a pipette. Then place a 0.2 mL PCR tube on a magnetic rack until the solution becomes clear. Discard the supernatant and wash the magnetic beads twice with 75% ethanol. Elute the library DNA with Tris-HCl at pH 8.0. This completes the probe hybridization capture process.

[0062] (3) Quality control of DNA hybridization capture library The concentration of library DNA was determined using Qubit Fluorometric Quantitation (Thermo Fisher), and then agarose gel electrophoresis was used to detect whether the fragment size of the library DNA was between 300-400 bp.

[0063] (4) DNA hybridization capture library sequencing The constructed DNA library was sequenced using the BGI DNBSEQ-T7 sequencer.

[0064] (5) Genotype data analysis After the sequencing data underwent quality control using Fastp (version 0.20.0, parameters: -n 10 -q 20 -u 40), the sequencing data was aligned to the reference genome using the default parameters of BWA (bio-bwa.sourceforge.net). The sequencing data was then used to perform SNP identification using GATK (software.broadinstitute.org / gatk) software, and the genotyping information captured by the probes was extracted to form the final genotyping results.

[0065] Example 2: Application of the Lettuce 1K Liquid Phase SNP Chip of the Present Invention Using the lettuce 1K liquid phase SNP chip prepared in Example 1, population analysis was performed on 84 lettuce materials (Table 3) that participated in the analysis. The analysis included principal component analysis (PCA), population structure analysis, phylogenetic tree construction, and kinship analysis.

[0066] Table 3. 84 lettuce samples

[0067] Note: " / " indicates that the information is unknown.

[0068] First, basic statistics on genetic diversity parameters were performed on all SNP markers, including: minor allele frequency (MAF), polymorphism information content (PIC), observed allele number (Ao), expected allele number (Ae), observed heterozygosity (Ho), and expected heterozygosity (He). The results are shown in Table 4.

[0069] Table 4

[0070] MAF: Minor allele frequency. MAF = Minor_allele / n, where Minor_allele is the number of second genotypes detected at a locus, and n is the total number of genotypes detected at a locus. The minor genotype frequency of each locus is calculated using the above formula, and the average value represents the minor allele frequency of the population.

[0071] PIC: Polymorphism Information Content. The calculation formula is as follows: Where Pi and Pj are the frequencies of the i-th and j-th alleles, respectively, and n is the number of alleles. The average value represents the polymorphism information content of the population.

[0072]

[0073] Ao: Number of alleles observed. Ao = ∑x / n, where ∑x is the sum of the number of alleles at all measured loci (including non-polymorphic loci), and n is the total number of measured loci.

[0074] Ae: Expected number of alleles. Ae = 1 / ∑Pi 2 Pi is the frequency of the i-th allele. The effective allele count at each locus is calculated, and the average value is taken to represent the effective allele count of the population.

[0075] Ho: Observed heterozygosity. Ho = b / n, where b is the number of heterozygous genotypes detected at a certain locus, and n is the total number of genotypes detected at a certain locus. The observed heterozygosity of each locus is calculated according to the above formula, and the average value is taken to represent the observed heterozygosity of the population.

[0076] He: Expected heterozygosity. He = 1 - ∑Pi 2 , where Pi is the frequency of the i-th allele, calculate the expected heterozygosity of each locus, and take the average value to represent the expected heterozygosity of the population.

[0077] Population analysis comprises four parts: principal component analysis (PCA), population structure analysis, phylogenetic tree construction, and phylogenetic relationship analysis. The results of PCA, population structure analysis, and phylogenetic tree construction can determine the genetic diversity of the material and whether there are significant differences in genetic background. Phylogenetic relationship analysis can reveal the genetic similarity of non-family populations or populations with unclear pedigrees.

[0078] 1. Principal Component Analysis (PCA) Principal Component Analysis (PCA) is a statistical method that uses orthogonal transformations to convert a set of potentially correlated variables into a set of linearly uncorrelated variables; these transformed variables are called principal components. PCA is applied in many disciplines. In genetics, it is mainly used for cluster analysis. Based on the degree of difference in individual genomic SNPs, it clusters individuals into different subgroups according to different trait characteristics, and is also used to cross-validate with other methods.

[0079] This invention uses GCTA (v1.92.4) software to perform PCA analysis based on filtered SNP markers (1210 SNP loci in Tables 1 and 2), obtaining the variance explained rate of each PC and the score matrix of the sample in each PC. Key information extracted from the SNP information is divided into PC1, PC2, and PC3 according to the effect size from largest to smallest. The results mainly show the scatter plots of the first three PCs pairwise. The two-dimensional and three-dimensional plots of the first three PCs are shown below. Figures 2 to 5As shown in the figure, the 84 lettuce samples exhibit a clear population segregation trend on PC1, roughly divided into three main genetic clusters. PC2 further distinguishes samples within some subgroups, with samples within each cluster relatively clustered and no obvious outliers observed. PC3 captures the main structures of the remaining genetic variation, and some samples that overlap on the PC1 / PC2 plane are further separated in the PC1 / PC3 projection, indicating that PC3 has a supplementary role in population subdivision.

[0080] 2. Group Structure Analysis Population genetic structure refers to the non-random distribution of genetic variation within a species or population. A population can be divided into several subgroups according to geographical distribution or other criteria. Individuals within the same subgroup are highly related, while subgroups are more distantly related. Population structure analysis helps in understanding evolutionary processes and can determine the subgroup to which an individual belongs through genotype-phenotype association studies. Population structure analysis provides information on an individual's ancestry and composition, making it an important tool for analyzing genetic relationships.

[0081] Based on the filtered SNP markers (1210 SNP sites in Tables 1 and 2), the population structure was inferred using Admixture software (v1.3). Clustering was performed, assuming the number of clusters (K value) for each sample to be between 1 and 15. The optimal number of clusters was determined based on the cross-validation error rate (CV error); the K value with the lowest CV error rate corresponded to the optimal number of clusters. A line graph of the CV error rate is shown below. Figure 6 As shown.

[0082] The optimal number of clusters determined in this analysis is K=7.

[0083] To simulate the population classification and ancestral composition of each sample under different numbers of subpopulations (K = 2-15), pophelper software (v2.2.7) was used to plot the genetic composition of each sample in each subpopulation as a bar chart. Within each K value, each color represents a cluster. Figure 7 The figure shows the genetic map of the samples when K=7. As can be seen from the figure, in the gradient analysis of K values ​​from 2 to 15, different types of lettuce materials exhibit diverse genetic composition patterns. As the K value gradually increases, the genetic mixing characteristics within different cultivation types gradually emerge and further differentiate into multiple subpopulations, showing a more complex genetic composition, reflecting the genetic diversity accumulated by cultivated lettuce during long-term domestication and genetic mobility.

[0084] 3. Phylogenetic tree construction A phylogenetic tree (also known as an evolutionary tree) is a branching diagram or tree that describes the evolutionary order among populations, used to represent the evolutionary relationships between them. The degree of kinship between populations can be inferred based on their similarities or differences in physical or genetic characteristics. We construct phylogenetic trees using the neighbor-joining method.

[0085] Based on the SNP markers obtained after screening (1210 SNP sites in Tables 1 and 2), the NJ tree was constructed using MEGA-X software (model: p-distance; bootstrap: 1000 times). The results are as follows: Figure 8 As shown in the figure, the 84 lettuce samples clustered into four distinct clades. The closer the clades, the closer the kinship; the farther apart the clades, the greater the genetic difference.

[0086] 4. Kinship Analysis Kinship is defined as the relative value of the genetic similarity between two specific materials to the genetic similarity between any two materials.

[0087] Based on the filtered SNP markers (1210 SNP loci in Tables 1 and 2), kinship analysis was performed using GCTA software (v1.92.4) to obtain pairwise kinship matrices. A heatmap plotted using the kinship matrices is shown below. Figure 9 As shown in the figure, red indicates that the two materials are more closely related, while other colors indicate a more distant relationship. Lettuce with known information (lettuce) and 19 (lettuce with unknown information), 30 and 35, and 16 (lettuce with unknown information) and 62 (lettuce with known information) are more closely related, while Test1_2 and 31 are more distantly related.

[0088] The present invention has been described in detail above. Those skilled in the art will recognize that the invention can be practiced in a wide range of ways with equivalent parameters, concentrations, and conditions without departing from its spirit and scope, and without requiring unnecessary experiments. While specific embodiments have been provided, it should be understood that further modifications can be made to the invention. In summary, according to the principles of the invention, this application is intended to include any changes, uses, or improvements to the invention, including changes made using conventional techniques known in the art that depart from the scope disclosed herein.

Claims

1. A chip for detecting lettuce genotypes, including: A reagent for the specific detection of 1210 SNP sites; the 1210 SNP sites are the 588 SNP sites in Table 1 and the 622 SNP sites in Table 2; The location information of the 1210 SNP sites was determined by comparison with the lettuce genome reference sequence, which is version Lsat_Salinas_v11.

2. The chip according to claim 1, characterized in that: The reagent is a single-stranded nucleotide probe.

3. The chip according to claim 2, characterized in that: The chip includes 588 single-stranded nucleotide probes for detecting the 588 SNP sites in Table 1 and 1244 single-stranded nucleotide probes for detecting the 622 SNP sites in Table 2. For each of the 588 SNP sites in Table 1, a target region is selected within a 110bp range upstream and downstream of the location of the SNP site on the lettuce genome reference sequence. The target region covers the SNP site. A probe is designed for the target region. The nucleotide sequence of the probe is the same as or reverse complementary to the nucleotide sequence of the target region. For each of the 622 SNP sites in Table 2, two target regions are selected within a 110bp range upstream and downstream of the location of the SNP site on the lettuce genome reference sequence. Each target region covers the SNP site. A probe is designed for each target region, and the nucleotide sequence of the probe is the same as or reverse complementary to the nucleotide sequence of the target region.

4. The chip according to claim 3, characterized in that: The start and end positions of the target regions corresponding to each of the 588 single-stranded nucleotide probes used to detect the 588 SNP sites described in Table 1 are shown in Table 1; and / or The start and end positions of the target regions corresponding to each of the 1244 single-stranded nucleotide probes used to detect the 622 SNP sites in Table 2 are shown in Table 2.

5. The chip according to any one of claims 1-4, characterized in that: The single-stranded nucleotide probe is modified with biotin.

6. The chip according to any one of claims 1-5, characterized in that: The chip also includes magnetic beads modified with streptavidin.

7. The chip according to any one of claims 1-6, characterized in that: The chip is a liquid-phase probe hybridization chip.

8. The use of the chip according to any one of claims 1-7 in any of the following: (A1) Construction of a genetic map of lettuce; (A2) Construction of lettuce fingerprint profile; (A3) Analysis of lettuce population structure; (A4) Identification of lettuce varieties; (A5) Kinship test of lettuce; (A6) Locating genes for lettuce traits.

9. The application of the chip according to any one of claims 1-7 in lettuce breeding.

10. The application according to claim 9, characterized in that: The breeding method described is molecular marker-assisted breeding.

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