Method and application of identifying fish genome structural variation based on graph pan-genome

Abstract

The present invention discloses a method and application for identifying fish genome structural variation based on a graph pan-genome. The method comprises the following steps: 1) comparing the genomic data of individual fish of different germplasms with a reference genome to determine the variation information between each individual's genome sequence and the reference genome; 2) constructing a graph pan-genome using this variation information; and 3) comparing the genomic data of the individual fish to be identified with the graph pan-genome to generate a genomic structural variation dataset for the individual fish to be identified. This method can comprehensively and accurately identify fish genome structural variation and identify unique structural variation, providing a scientific basis for fish genetic improvement, breeding, and resource conservation, and is suitable for widespread application.

Description

Technical Field

[0001] The present invention belongs to the technical field of pan-genome identification of structural variation, and specifically relates to a method and application of identifying fish genome structural variation based on a pan-genome graph. Background Art

[0002] With the development of genomics, especially the rise of pan-genomics, an increasing number of species are being mapped to reveal their genetic diversity and structural variation. In genomic research, structural variation (such as insertions, deletions, inversions, and translocations) is a key factor influencing species phenotypic diversity and adaptive change. Fish, as a major group of vertebrates, possess rich genetic diversity and complex genetic architecture. Important traits (such as growth rate, disease resistance, and reproductive capacity) are often closely associated with genomic structural variation. However, existing technologies primarily identify structural variation through linear genome sequence alignment. This approach has limitations when dealing with complex genomic regions (such as repetitive sequences and highly variable regions), making it difficult to fully and accurately capture structural variation information. Identifying structural variation in fish genomes not only helps understand adaptive mechanisms but also provides a scientific basis for fish breeding and resource conservation. Traditional methods rely primarily on alignments to a single linear reference genome, which is difficult to fully capture structural variation information. Therefore, graph-based pan-genome approaches have emerged. These methods can store and display the complete genetic information and sequence and structural variation of a species, becoming a new hotspot in fish genetics research.

[0003] Graph-pangenomes represent individual genomes and their variations as a graph structure based on de novo genome assembly. This graph structure comprehensively displays a species' genetic information and structural variation, including single nucleotide polymorphisms (SNPs), insertion / deletion mutations (InDels), copy number variations (CNVs), and presence / absence variations (PAVs). Compared to traditional linear genomes, graph-pangenomes more accurately reflect a species' genetic diversity and structural variation, providing a powerful tool for analyzing important traits. Summary of the Invention

[0004] An object of the present invention is to solve at least the above problems and / or disadvantages and to provide at least the advantages which will be described hereinafter.

[0005] To address the challenges of existing technologies, the present invention provides a method for identifying structural variation in fish genomes based on a graph-based pan-genome. This method allows for rapid identification of structural variation in fish genomes using a constructed pan-genome containing structural variation information for all germplasm germplasms. This method is simple, requires minimal memory, and is not limited by the number of genomes.

[0006] To this end, the technical solution provided by the present invention is:

[0007] In the first aspect, a method for identifying fish genome structural variation based on a pan-genome graph comprises the following steps:

[0008] 1) Compare the genomic data of individual fish from different germplasms with the reference genome to determine the variation between each individual genome sequence and the reference genome; that is, compare the genomic data of individual fish from each germplasm with the reference genome one by one;

[0009] 2) constructing a graphical pan-genome using the variation information;

[0010] 3) Comparing the genome data of the individual fish to be identified with the graphical pan-genome to generate a dataset of genomic structural variations of the individual fish to be identified.

[0011] Preferably, in the method for identifying fish genome structural variation based on graph pan-genome, in step 1), representative fish germplasms are selected for de novo genome assembly to obtain individual fish genome data of different germplasms.

[0012] Preferably, in the method for identifying fish genome structural variation based on graph pan-genome, in step 1), the genome assembly data is compared with the reference genome using minimap2 software to obtain variation information in vcf format, and then the graph pan-genome is constructed.

[0013] Preferably, in the method for identifying fish genome structural variation based on the graph pan-genome, in step 3), the sample of the individual fish to be identified is subjected to 10× high-depth resequencing, and each gene sequencing sample is aligned to the graph pan-genome using vg giraffe software to obtain a result file in GAM format;

[0014] Then, use "vg stats" to count the alignment results; use "vg gamsort" to sort the alignment results on the constructed pan-genome, and use "vg call" to detect structural variations in samples from different germplasms to generate a variant file in vcf format for each sample;

[0015] Use bgzip to compress the variant files in vcf format and use tabix to create an index; use bcftoolsmerge software to merge the variant files of each sample, and finally generate a total variant data file in vcf format containing all samples.

[0016] Preferably, the method for identifying fish genome structural variations based on a graph pan-genome also includes: using plink to convert the total variation data file in vcf format into map and ped formats, combining the phenotypic information of different germplasm samples, and using gcta64 to perform PAV-GWAS to identify structural variations related to economic traits of fish.

[0017] Preferably, in the method for identifying fish genome structural variation based on a graph-pan-genome, the T2T assembled and sequenced mirror carp "Longke No. 11" is used as the reference genome. More preferably, the fish individuals of different germplasms include carp "Longke No. 12", German mirror carp, Yuxuan Yellow River carp No. 2, Furui carp No. 2, Jian carp No. 2, Yuanjiang carp, red carp, Songpu mirror carp, and Heilongjiang carp.

[0018] Preferably, in the method for identifying fish genome structural variation based on graph pan-genome, the genes in the graph pan-genome are divided into core gene families, variable gene families and unique gene families according to the number of germplasms covered.

[0019] Preferably, in the method for identifying fish genome structural variation based on map pan-genome, the fish individual to be identified belongs to one of the fish individuals of different germplasm in step 1).

[0020] Preferably, the method for identifying fish genome structural variation based on pan-genome analysis comprises the following steps:

[0021] Step 1: Select representative fish germplasms for de novo genome assembly using PacBio HiFi sequencing, de novo assembly using Hifiasm software, Hi-C sequencing and mapping to the chromosome level, and analysis of its integrity using BUSCO;

[0022] Step 2: Integrate the chromosomal genomes from Step 1, using the T2T genome as the backbone of the pan-genome. Combined with previously published or sequenced third-generation genomes, the genome assembly data was aligned with the reference genome using minimap2 software to obtain variant information in vcf format. This was then used with vg software to construct the pan-genome. Genes in the pan-genome were divided into core gene families, variable gene families, and unique gene families based on the number of germplasms covered.

[0023] Step 3: Perform 10× high-depth resequencing on samples of different germplasms for the pan-genome obtained in step 2; use vg giraffe software to align the clean reads of each sample to the pan-genome, and obtain a result file in GAM format;

[0024] Step 4: Then use "vg stats" to count the alignment results; use "vggamsort" to sort the alignment results on the constructed pan-genome, and use "vg call" to detect SVs in samples of different germplasms to generate a variant file in vcf format for each sample;

[0025] Step 5: Use bgzip to compress the variant file in vcf format and use tabix to create an index. Use bcftools merge to merge the variant files of each sample, and finally generate a total variant file in vcf format containing all samples;

[0026] Step 6: Use plink to convert the vcf file into map and ped formats. After quality control, combine the phenotypic information of samples from different germplasms, and use gcta64 to perform PAV-GWAS to identify structural variations associated with important economic traits of fish.

[0027] Secondly, the genes related to the high-quality traits of carp are:

[0028] Chr1:11972915, the variant type is deletion, the nucleotide sequence before deletion (wild type) is shown in SEQ ID NO:1, and the nucleotide sequence after deletion (mutant type) is shown in SEQ ID NO:2;

[0029] Chr1:21527167, the variant type is deletion, the nucleotide sequence before deletion (wild type) is shown in SEQ ID NO:3, and the nucleotide sequence after deletion (mutant type) is shown in SEQ ID NO:4;

[0030] Chr1:23399634, the mutation type is insertion, the nucleotide sequence before insertion (wild type) is shown in SEQ ID NO:5, and the nucleotide sequence after insertion (mutant type) is shown in SEQ ID NO:6;

[0031] Chr7:2062567, the variant type is deletion, the nucleotide sequence before deletion (wild type) is shown in SEQ ID NO:7, and the nucleotide sequence after deletion (mutant type) is shown in SEQ ID NO:8;

[0032] Chr31:9671978, the variant type is insertion, the nucleotide sequence before insertion (wild type) is shown in SEQ ID NO:9, and the nucleotide sequence after insertion (mutant type) is shown in SEQ ID NO:10;

[0033] Chr40:9140647, the variant type is insertion, the nucleotide sequence before insertion (wild type) is shown in SEQ ID NO:11, and the nucleotide sequence after insertion (mutant type) is shown in SEQ ID NO:12;

[0034] Chr48:8724756, the variant type is deletion, the nucleotide sequence before deletion (wild type) is shown in SEQ ID NO:13, and the nucleotide sequence after deletion (mutant type) is shown in SEQ ID NO:14;

[0035] Chr50:4154584, the variant type is insertion, the nucleotide sequence before insertion (wild type) is shown in SEQ ID NO:15, and the nucleotide sequence after insertion (mutant type) is shown in SEQ ID NO:16;

[0036] Chr20:2258997, the variant type is deletion, the nucleotide sequence before deletion (wild type) is shown in SEQ ID NO:17, and the nucleotide sequence after deletion (mutant type) is shown in SEQ ID NO:18;

[0037] Chr25:3825897, the variant type of which is insertion, the nucleotide sequence before insertion (wild type) is shown in SEQ ID NO:19, and the nucleotide sequence after insertion (mutant type) is shown in SEQ ID NO:20; and / or,

[0038] Chr44:16600200, the variant type is deletion, the nucleotide sequence before deletion (wild type) is shown in SEQ ID NO:21, and the nucleotide sequence after deletion (mutant type) is shown in SEQ ID NO:22;

[0039] Among them, Chr1:11972915, Chr1:21527167, Chr1:23399634, Chr7:2062567, Chr31:9671978, Chr40:9140647, Chr48:8724756 and Chr50:4154584 were related to the intramuscular fat content of carp, and Chr20:2258997, Chr25:3825897 and Chr44:16600200 were related to the linoleic acid content of carp muscle.

[0040] In a third aspect, the gene is used in breeding carp with high-quality traits.

[0041] The present invention has at least the following beneficial effects:

[0042] (1) The present invention comprehensively reflects genetic variation by identifying fish genome structural variation based on a map pan-genome. By constructing a map pan-genome, it is possible to comprehensively capture genetic variation information among individual fish, including multiple types of structural variation.

[0043] (2) The present invention can improve the accuracy of structural variation identification and use graphical structures to represent genomic information, which can more accurately identify the location, size and type of structural variation.

[0044] (3) The present invention can eliminate mapping bias. The pan-genome technology can eliminate mapping bias in traditional linear genome sequence alignment and improve the efficiency of identifying structural variations.

[0045] (4) The present invention helps reveal the characteristics of complex sites. By deeply analyzing the characteristics of complex sites in the map-pan-genome, it can reveal structural variation sites closely related to fish genomes. The present invention's method for identifying structural variation in fish genomes based on the map-pan-genome has the advantages of being comprehensive, accurate, and efficient, providing a new technical means for fish genetic improvement, breeding, and resource conservation.

[0046] Other advantages, objectives and features of the present invention will be reflected in part from the following description and will be understood by those skilled in the art through study and practice of the present invention. BRIEF DESCRIPTION OF THE DRAWINGS

[0047] Figure 1 The carp pan-genome map constructed for the embodiment of the present invention includes: A: display of 10 carp germplasm resources; B: gene family saturation analysis; C: core, variable, and unique gene family analysis; D: petal map displaying the core genes and variable genes of 10 carp species; E: gene family frequency analysis of 10 carp germplasms; F: statistical analysis of the core, unique, and variable gene families of each carp germplasm.

[0048] Figure 2 These are the PAV detection and annotation result diagrams of the mirror carp "Longke No. 11" (KB) and the common carp "Longke No. 12" (YZ) in the embodiments of the present invention, wherein A: GO enrichment analysis of PAV-associated genes of the mirror carp "Longke No. 11" (KB); B: KEGG pathway enrichment analysis of PAV-associated genes of the mirror carp "Longke No. 11" (KB); C: GO enrichment analysis of PAV-associated genes of the common carp "Longke No. 12" (YZ); D: KEGG pathway enrichment analysis of PAV-associated genes of the common carp "Longke No. 12" (YZ).

[0049] Figure 3It is a structural variation diagram related to carp high-quality traits identified based on PAV-GWAS in an embodiment of the present invention, wherein A: Manhattan plot and QQ plot in PAV-GWAS analysis of carp intramuscular fat content; B: Manhattan plot and QQ plot in PAV-GWAS analysis of carp muscle linoleic acid content.

[0050] Figure 4 This is an analysis chart of intramuscular fat content in carp carrying different PAV genotypes related to intramuscular fat content in an embodiment of the present invention.

[0051] Figure 5 This is a graph analyzing the linoleic acid content in carp carrying different genotypes of PAVs related to linoleic acid content in an embodiment of the present invention. DETAILED DESCRIPTION

[0052] The present invention will be described in further detail below in conjunction with the accompanying drawings so that those skilled in the art can implement the invention with reference to the description.

[0053] It should be noted that the experimental methods described in the following embodiments are conventional methods unless otherwise specified, and the reagents and materials can be obtained from commercial channels unless otherwise specified.

[0054] The present invention aims to provide a method for identifying structural variation in fish genomes based on graph-pan-genomics. This method utilizes graph-pan-genomics technology to construct a graph structure containing the genomic information of multiple fish individuals. Next-generation resequencing data is then mapped to the graph-pan-genomics, and structural variation associated with fish genomes is identified using PAV-GWAS. This method can comprehensively and accurately identify structural variation in fish genomes and identify unique structural variation, providing a scientific basis for fish genetic improvement, breeding, and resource conservation, and is suitable for widespread application.

[0055] The present invention provides a method for identifying fish genome structural variation based on a pan-genome graph, comprising the following steps:

[0056] (1) Genomic data collection and preprocessing: Collect genome sequencing data of multiple fish individuals and perform quality control and preprocessing, including removing low-quality sequences and correcting sequencing errors, to ensure that the data quality meets the requirements of subsequent analysis.

[0057] (2) De novo genome assembly: Assemble the genomes of multiple fish individuals with high quality to obtain the sequence information of individual genomes.

[0058] (3) Obtaining variation information: Use alignment software (such as minimap2, MUMmer, etc.) to align the individual genome with the reference genome to obtain variation information (vcf file).

[0059] (4) Graph pan-genome construction: Using specialized graph pan-genome construction software (e.g., vg, pggb, etc.), the genomic variation information of multiple fish individuals and the reference genome sequence are integrated into a graph structure to construct a graph pan-genome. This graph pan-genome can comprehensively display the genetic variation between individuals, including multiple types of structural variation such as single nucleotide polymorphisms (SNPs), insertion / deletion mutations (InDels), copy number variations (CNVs), and presence / absence variations (PAVs).

[0060] (5) Structural variation identification: Based on the graph pan-genome, structural variation is identified using specialized variation analysis software (such as SyRI, SVMU, Assemblylytics, etc.). These software can efficiently identify a variety of variation types, including large-scale structural variation (SV), copy number variation (CNV), and presence / absence variation (PAV). By comparing the graph structural differences between different individuals, structural variation sites related to the fish genome are identified.

[0061] (6) Analysis of important traits: Based on the mined structural variation information, combined with the biological characteristics and phenotypic data of fish, the identified structural variations are analyzed for important traits. By comparing and analyzing the functions and characteristics of core / non-core genes, the generation mechanism of common and unique phenotypes of fish is explored. At the same time, through statistical methods (such as genome-wide association analysis GWAS) and machine learning algorithms, structural variation sites on the genome that are significantly associated with important traits are screened out, providing key information for subsequent breeding and resource protection. At the same time, this method is applied to fish breeding practice to improve breeding efficiency by screening individuals with excellent traits.

[0062] In order to enable those skilled in the art to better understand the technical solutions of the present invention, the following embodiments are provided for illustration:

[0063] Example 1: A method for identifying structural variation of high-quality traits of carp based on a pan-genome

[0064] 1. Construction of carp resource groups

[0065] A total of 7 carp resource groups were collected nationwide, including the mirror carp "Longke No. 11", carp "Longke No. 12", German mirror carp, Yuxuan Yellow River carp No. 2, Furui carp No. 2, Jianli No. 2, and Yuanjiang carp, as well as the purse red carp, Songpu mirror carp, and Heilongjiang carp for which third-generation sequencing data were already available, for a total of 10 carp germplasm pan-genome construction maps.

[0066] 2. Genome sequencing

[0067] The above 7 carp germplasms, including mirror carp "Longke No. 11", carp "Longke No. 12", German mirror carp, Yuxuan Yellow River carp No. 2, Furui carp No. 2, Jianli No. 2, and Yuanjiang carp, were subjected to second-generation small fragment, HiFi, Hi-C, transcriptome and full-length transcriptome library construction, and the ultra-long ONT library construction and sequencing of the mirror carp "Longke No. 11" (KB) assembled and sequenced by T2T was also performed.

[0068] 3. De novo genome assembly

[0069] The genomes of mirror carp "Longke 11," carp "Longke 12," German mirror carp, Yuxuan Yellow River carp 2, Furui carp 2, Jian carp 2, and Yuanjiang carp were constructed and assembled with high quality, obtaining sequence information for various plasmome genomes. Ultimately, the genome contig N50 length of the seven carp accessions was 28.34 Mb, with an average genome size of 1.57 Gb.

[0070] 4. Genome annotation

[0071] The construction and sequencing of eukaryotic transcriptome libraries of 6 different tissues of 7 carp germplasms assisted in genome assembly and annotation. Hi-C technology assisted in genome assembly. Genome annotation mainly includes three aspects: repetitive sequence annotation, gene annotation (including gene structure prediction and gene function prediction), and non-coding RNA (ncRNA) annotation. Through genome annotation of 7 carp genomes, the results showed that the average repetitive sequence accounted for 41.46% of the 7 carp genomes, and an average of 45,217 coding genes were predicted, of which 99.5% of the genes could be predicted to have functions. Based on the HiC data obtained by sequencing, the assembled contigs / scaffolds sequences were mounted to the near-chromosome level, and then manually corrected according to the chromosome interaction strength, and finally the chromosome-level genome was obtained. The average genome size is 1.57Gb, and the average mounting rate is 96.83%.

[0072] 5. Construction of pan-genome

[0073] The first step in building a graph pan-genome is to select a suitable reference genome. In the present embodiment, the mirror carp "Longke No. 11" (KB) assembled and sequenced with T2T is used as a reference genome. Utilize minimap2 comparison software to compare the genome sequencing data of 9 individuals with the reference genome respectively, it is intended to determine the difference between the individual genome sequence and the reference genome, and obtain variation information (vcf files) such as single nucleotide polymorphisms, insertions and deletions. After completing the comparison, it is necessary to analyze the variation information in detail. This includes identifying key information such as the position, type, frequency of the variation, and annotating it to reveal the impact of variation on gene structure and function. After obtaining the variation information, you can start using a special graph pan-genome construction tool vg to build a graph pan-genome. This step integrates the reference genome sequence and variation information into a complex graph structure, in which each node represents a position in the genome, and the edge represents the connection relationship between different positions. The genes in the pan-genome are divided into core gene families, variable gene families, and unique gene families according to the number of covered germplasms.

[0074] 6. Identification of structural variations

[0075] Samples from different accessions were resequenced at 10× high depth. The quality-controlled sequencing sequences (clean reads) of each sample were aligned to the pan-genome using vg giraffe software, generating a GAM-formatted structural variation result file. The alignment results were then statistically analyzed using "vg stats." On the constructed pan-genome, the alignment results were sorted using "vggamsort," and SV detection was performed on samples from different accessions using "vg call," generating a VCF-formatted variation file for each sample. The VCF-formatted variation files were compressed using bgzip and indexed using tabix. The variation files for each sample were merged using bcftools merge, ultimately generating a VCF-formatted total variation file containing all samples.

[0076] 7. PAV-GWAS analysis of carp quality traits

[0077] The vcf file was converted to map and ped formats using plink. After quality control, the phenotypic information of high-quality traits (including intramuscular fat content and linoleic acid content) of different carp germplasms was combined. A mixed linear model (MLM) was used in the GCTA software to conduct a PAV-GWAS of carp high-quality traits. Population structure was used as a fixed effect, and the individual kinship matrix as a random effect. The P value threshold was corrected using the Bonferroni correction method to determine the significance threshold. When the P value of a SNP exceeded the threshold, it was considered a PAV significantly associated with carp high-quality traits, thus identifying structural variants associated with carp high-quality traits. Manhattan plots and QQ plots were created using the R language CMplot package to visualize the results of the genome-wide association analysis.

[0078] 8. Results Analysis

[0079] The Carp Pan-Genome was constructed using the genomes of 7 carp germplasms (Mirror Carp "Longke 11", Carp "Longke 12", German Mirror Carp, Yuxuan Yellow River Carp 2, Furui Carp 2, Jian Carp 2, Yuanjiang Carp) and 3 existing carp reference genomes (Hebao Red Carp, Heilongjiang Carp, Songpu Mirror Carp), a total of 10 carp germplasms. Figure 1 (A) Gene family saturation analysis Figure 1 As shown in Figure B, as the number of genomes increases, the number of core gene families decreases, while the number of pan-gene families increases. Figure 1 As shown in Figure C, there are 17,745 core gene families (accounting for 43.44% of all gene families), 21,714 variable gene families (accounting for 53.15% of all gene families), and 1,393 unique gene families (accounting for 3.41% of all gene families). Figure 1 As shown in Figure 1D, there are 20 unique gene families in the mirror carp "Longke No. 11" (KB) and 34 unique gene families in the carp "Longke No. 12 (YZ). The frequency analysis of different gene families in 10 carp germplasms is shown in Figure 1E. Among them, the gene family that only appears in one carp germplasm is the unique gene, the gene family that appears in 10 carp germplasms is the core gene, and the gene family that appears in 2 to 9 carp germplasms is the variable gene. The statistics of core, unique and variable gene families of each carp germplasm are shown in Figure 1E. Figure 1 As shown in F, among them, the number of variable genes in red common carp and Songpu mirror carp is relatively large among the 10 carp germplasms, and the number of gene families identified in red common carp is the largest, which is 31,656 gene families.

[0080] PAV detection and annotation of mirror carp “Longke 11” (KB) and carp “Longke 12” (YZ): The PAV detection and annotation results of mirror carp “Longke 11” (KB) are shown in the figure. Figure 2As shown in Figure AB: KB-specific PAV-associated genes are enriched in biological processes such as platelet-derived growth factor receptor signaling pathway, threonine metabolism process, and feeding behavior; KB-specific PAV-associated genes are enriched in pathways such as dorsal-ventral axis formation, Apelin signaling pathway, cell apoptosis, phenylalanine metabolism, PPAR signaling pathway, and autophagy.

[0081] The PAV detection and annotation results of carp “Longke No. 12” (YZ) are as follows Figure 2 As shown in the figure CD: YZ-specific PAV-associated genes are enriched in biological processes such as glutamine-tRNA aminoacylation, protein deubiquitination, lipoprotein metabolism, TOR signaling, and MyD88-dependent toll-like receptor signaling pathways; YZ-specific PAV-associated genes are enriched in metabolic pathways such as steroid biosynthesis and inositol phosphate metabolism; and biological system pathways such as the intestinal immune network produced by IgA.

[0082] The quality traits (referring to fish meat quality) indicators (including intramuscular fat content and linoleic acid content) of 266 fish of Yuxuan Yellow River Carp No. 2, Jian Carp No. 2, Mirror Carp "Longke No. 11", Carp "Longke No. 12" and Songpu Mirror Carp were tested. Combined with the PAVs identified by pan-genome sequencing, PAV-GWAS was conducted to identify PAVs associated with carp quality traits. The results showed that with the Bonferroni corrected P value (0.05 / 162727) as the significance threshold, a total of 8 PAVs were identified that were significantly associated with carp intramuscular fat content ( Figure 3 Among them, DEL Chr1:11972915 and DEL Chr1:21527167 on chromosome 1, DELChr7:2062567 on chromosome 7, and DEL Chr48:8724756 on chromosome 48 are deletion mutations, and carp carrying the deletion mutation genotype (MM) have higher intramuscular fat content and better quality fish meat ( Figure 4 ). INS Chr1:23399634 on chromosome 1, INS Chr31:9671978 on chromosome 31, INS Chr40:9140647 on chromosome 40, and INSChr50:4154584 on chromosome 50 are insertion mutations. Among them, INS Chr1:23399634 on chromosome 1 and INSChr50:4154584 on chromosome 50, which carry the insertion mutation genotype (MM), have higher intramuscular fat content and better quality fish meat ( Figure 4 ). Eight PAVs significantly associated with intramuscular fat content in carp were located in the intronic and intergenic regions of genes (Table 1). At the same time, using the Bonferroni-corrected P value (0.05 / 162727) as the significance threshold, a total of three PAVs significantly associated with linoleic acid content in carp muscle were identified ( Figure 3 Among them, DEL Chr20:2258997 located on chromosome 20 and DEL Chr44:16600200 located on chromosome 44 are deletion mutations. For DEL Chr20:2258997, carp carrying the deletion mutation genotype (MM) have higher linoleic acid content and better fish quality; while for DEL Chr44:16600200, carp carrying the wild type (WW, i.e. not deleted) have higher linoleic acid content and better fish quality. INS Chr25:3825897 located on chromosome 25 is an insertion mutation. Carp carrying the wild type (WW, i.e. not inserted) have higher linoleic acid content and better fish quality. (Table 2 and Figure 5 Three PAVs significantly correlated with linoleic acid content in carp were located in intronic and intergenic regions (Table 2).

[0083] Table 1 PAVs associated with intramuscular fat content in carp identified by PAV-GWAS

[0084]

[0085] Table 2 PAVs associated with linoleic acid content in carp identified by PAV-GWAS

[0086]

[0087] The PAV sequences related to the intramuscular fat content of carp are shown in SEQ ID NOs: 1-16, wherein the genome sequence of DEL Chr1: 11972915 is shown below, and the mutation type is deletion.

[0088] (SEQ ID NO: 1)

[0089] GACAAAACATATTTAATGCTATTTCATAAGTAATGCAGTAAACCAGTGGTGACTTCATACACCCACTAAAATTCAAATTGGGACCAAG

[0090] GGGTTAAACGTAATTGCAAAATTGACTTAATTCTCTATAATAATATATCTCCAGATGCTGCT

[0091] (SEQ ID NO:2)AATGAAATTAAGACAAAACATATTTAA

[0092] (SEQ ID NO: 1 represents the sequence before deletion, and SEQ ID NO: 2 represents the sequence after deletion).

[0093] The genomic sequence of DEL Chr1:21527167 is shown below, and the mutation type is deletion.

[0094] (SEQ ID NO:3)

[0095] TAAGATCACTGGAAACCCCTGGATGTGCAATCAAACCTGCTGGACACTGAACAAAAGTTACACATAAAAACCTTGTTAAAAACAAACT

[0096] ATAAACTCCTCATACCTACCAAGAAATCAGTACAATACTGCAATTCAGTATTACAGCTACTTGCAGGCCCATATCTAAAAACAAACAA

[0097] GGCAATAAGCCTCTATTTAACAGGCAAAAAGGCATTTTTAAAACAGGGACCAACCTGAAAACTCACTGGCATACAGCCAGCACACGAC

[0098] AGACTGGAGCAGGGCCGTGCACAGACATTTTGAGGAGCAGTGGCCCAAACCAAAAAAAAGGGGGCAAAAGGAGGGTGGGTGCTTAATA

[0099] CAAATTATCCAGTTGTCACAAATTTTCAATTAAAAGAGAAGATCGCACACTCTGTAATAACTGACTTTATTGAAGATGTTGGCCAACA

[0100] AACTCCGTTTAGTCTGTTTTTAGGAAGGCTACAACTTTGGTGTTAATATATATATATATATATATATATATATATTGTTTCAGAAATG

[0101] CAAAAAATTAAATATTAAAATTTAAACTTCATTTGGTTGGTTTTATGTTGTTAAAAGTTAACTTTAAGAAAAGAAATATGACTGTCTG

[0102] TAAAAGGTATTAGTTTTTAAATTTTATTTCACATGGGTTTGAATCAGATTCGGTCAGATGGTCATTTTACATTCAGATGGTGCATCTT

[0103] ACCCACTGACTCGACTCGGGTCAACTTACCCCAAACCCGGGGCAAACTGAGCCATGGGAACTTTATAAGAAGCCATATTTTTAGAACC

[0104] CTTTGTCTTAGATACATTCTGATCATTGAAAATGATAGGAATACTTTCATTTGGATAGGATAGATAATTTCATTGTACTTATGCGTTT

[0105] TTTTCGACTCATTACCGACAAAAACAAACAAACTAATTACTAATTCTACGGATCAACCACTGACTAATGTGGATCGTAATGCATCTAC

[0106] CTGGTAATGCAACGACCCGCGGGGACTGTGGTCTCCACTCTCCAGAGAGCGGAACACAGATTGTGAGTGTTGCTGCGGAGCGAGCGGG

[0107] AAACATGGAGCGAAATCAGCGGAGCGGCAACCGACAGCTTTGAGGTGCGGTGATGGGGGATTGGTGAGAGGGGCACTTCAGCCGATGA

[0108] GGACAAAGAGGCAGTGGCCCCAGCCACCGGGCCACCCCCCTGTGCACGACCCTGGGCAGGAGGATAAACCATCTGCTAGTTCTCATTC

[0109] AAAGCGCCACATGTCACAAAGGGGTAGTATCAAGAATGATGCATGCCAAGCAACCCAACACTTCCCCCTTTTATATGGACAACACAAG

[0110] CACTAATTGACTCATGAAACTTACCCAACTATATATATATATATATATATATATATATATAT

[0111] (SEQ ID NO:4)

[0112] CTTCAAGAAATCAGTACAATACTGCAATTCAGTATTACAGCTACTTGCAGGCCCATATCTAAAAACAAACAAGGCAATAAGCCTCTAT

[0113] TTAACAGGCAAAAAGGCATTTTTAAAACAGGGACCAACCTGAAAACTCACTGGCATACAGCCAGCACACGACAGACTGGAGCAGGGCC

[0114] GTGCACAAACATTTTGAGGAGCAGTGGCCCAAACCAAAAAAAAGGGGGCAAAAGGAGGGTGGGTGCTTAATACAAATTATCCAGTTGT

[0115] CACAAATTTTCAATTAAAAGAGAAGATCGCACACTCTGTAATAACTGACTTTATTGAAGATGTTGGCCAACAAACTCCGTTTAGTCTG

[0116] TTTTTAGGAAGGCTACAACTTTGGTGTTAATATATATATATATATATATATTGTTTCAGAAATGCAAAAAATTAAATATTAAAATTTA

[0117] AACTTCATTTGGTTGGTTTTATGTTGTTAAAAGTTAACTTTAAGAAAAGAAATATGACTGTCTGTAAAAGGTATTAGTTTTTAAATTT

[0118] TATTTCACATGGGTTTGAATCAGATTCGGTCAGATGGTCATTTTACATTCCGATGGTGCATCTTACCCACTGACTCGACTCGGGTCAA

[0119] CTTATCCCAAACCCGGGGCAAACTGAGCCATGGGAACTTTATAAGAAGCCATATTTTTAGAACCCTTTGTCTTAGATACATTCTGATC

[0120] ATTGAAAATGATAGGAATACTTTCATTTGGATAGGATAGG

[0121] (SEQ ID NO: 3 represents the sequence before deletion, and SEQ ID NO: 4 represents the sequence after deletion).

[0122] The genome sequence of INS Chr1:23399634 is shown below, and the mutation type is insertion.

[0123] (SEQ ID NO:5)

[0124] ATGTTGATCAAAAACATACATTTACTCACAAACTGACCACTGACCGCAACTTTCAGACGCCATCGTTATTTTTTGACTTAACTGTCAC

[0125] AGAATGGAACGCACAGGATAGTGGGATATCAATGGCAGCGAAGGATACATCTATGCTGCCTTCAAAAATCGGCCAGATGAAGGCATCT

[0126] CCGGAGACAGGAACTGAAACTAACACTGAATTCAGGCGTGCCTTGATGCCTCCTACCTTGGAATGCATCCTCCGAAGGCAGCATTTT

[0127] TCAGTTTTTTGGATGCAGCCTGAGACTGGATGAAGGATAATTTGTACATTTCTGTACTAAATAAAGAGTATAAACTATATCTTAAGAT

[0128] AAGTTAACATTTGAACCACTTTGATTAAATTATTTTTTTAAATTTATTATTACTTTATATAATTTCCTTCCTGATGGATACAAGTTAT

[0129] TTCTGAGTTCAGCTTTCAATTGTGACCAGTGGATTGGAAATATAAACTTGATAGCTTGATACAAATTAAATTGATAGTCTAATAAATC

[0130] ATGCATTCGCTACTGTTGTCTGCTCTGCAATGCTCTTTACCTTATCTCCAGTGAAGGGATTCTGCACACAAAAAAGAAAAGTCATGCC

[0131] CTGCATGAACATGAACATGAACATGCACCGTGATTAAGCGAGTGCTTCATTAAGGTTCCTGATGGATCTCATATCTATAAGATGAATT

[0132] TCTTTGTGCGAGGTTACAAATGTATATGTTCCTTTTCTAAGTGTGTCTCTCAAAAATGCACTTAACACCAAGACGCAAGTATTTTAAA

[0133] GGGATCGGGTCTTATCGGGTCCAATTGGGGAAAGCACATTTATTTTAAATTATCTGACACCTGAGGCAACGAATACTAAACCCATGTC

[0134] TGAGGCACTTGTCAATGTTTTGGACCCAAACCCGCTCGGGTCTCAGGTCAGACTTCAGGTTTTCGGATCCAAGGGGACCCGTGAAGAC

[0135] CTCTAGTGTTCACGTGAGAGTAGACCTTGTATTGTGAACAAGCTTTGGATAATATAATTTTGTAAATAAAGTTTTTTTTTTTTTTTCA

[0136] TAAAACTGAGGTTAAACCACAGGAGTCACATGGATTAATTTCACAGTGTCTTTCTTATCTTTCTGGACCTTGAACTTGTCAGTTGCGT

[0137] TGCTGTCAATGGAGGGACAGAAAGCTCACGGATTTCACTAAAAATATCTTCATTTGTGTTCTGAAGATGAACGAAAGTGTTATGGGTT

[0138] TGAAATTATATGACGTTGAATAATTGATGACATACAGTAAGTTTAATTTTTGGGTGAACTAACCCTTTAATAACATTTTACGTGTATT

[0139] TACACACAGTTTTTGTTTTGTCTGTGGGACAGACTGTTCCAGCAGGCTAAACTGGATTCTGGAAAGAGCACGTCTTGAGTTTGAGATGA

[0140] AGCATCAGGAAGCTGAGGACAGGCTTGCTCGAGGTACCCACCAATTCATGGTACAGATTCTGCAAATGCTTAGACCAACAGTGCCAC

[0141] (SEQ ID NO:6)

[0142] ATGTTGATCAAAAACATACATTTACTCACAAACTGACCACTGACCGCAACTTTCAGAGACGCCATCGTTATTTTTTGACTTAACTGTCAC

[0143] AGAATGGAACGCACAGGATAGTGGGATATCAATGGCAGCGAAGGATACATCTATGCTGCCTTCAAAAATCGGCCAGATGAAGGCATCT

[0144] CCGGAGACAGGAACTGAAACTAACACTGAATTCAGGCGTGCCTTGATGCCTTCCTACCTTGGAATGCATCCTCCGAAGGCAGCATTTT

[0145] TCAGTTTTTTGGATGCAGCCTGAGACTGGATGAAGGATAATTTGTACATTTCTGTACTAAATAAAGAGTATAAACTATATCTTAAGAT

[0146] AAGTTAACATTTGAACCACTTTGATTAAATTATTTTTTTAAATTTATTATTACTTTATATAATTTCCTTCCTGATGGATACAAGTTAT

[0147] TTCTGAGTTCAGCTTTCAATTGTGACCAGTGGATTGGAAATATAAACTTGATAGCTTGATACAAATTAAATTGATAGTCTAATAAATC

[0148] ATGCATTCGCTACTGTTGTCTGCTCTGCAATGCTCTTTACCTTATCTCCAGTGAAGGGATTCTGCACACAAAAAAGAAAAGTCATGCC

[0149] CTGCATGAACATGAACATGAACATGCACCGTGATTAAGCGAGTGCTTCATTAAGGTTCCTGATGGATCTCATATCTATATGTAACCAG

[0150] GTGGAAAAGATGTTGTCAAACATAAAACTGTTTTCTTTACACCCTGGTTTTGAGTGTACTGCGCATAGATTGGTTTTCATGTCTTGCTC

[0151] CCTGTTGCCATAAAGTTACACTGGCCCTTTAAGAAACACGGCTGCATGAGTCTCGTGAAGTGCCGCGAGTGCTGCAGATGAACAGCGC

[0152] GAGTTATCATTGCAGGGTGAATGTTCCACGTGAAGTGGAGGATCGATGACATTAAAATCCATTAAATCACAGAATATAGAGAAATATG

[0153] CACATATAGTGAGTTATAAACTCGTTCTCTGTGGTATTGTGACTCGGATGGCTGTGTAACTTTGCATATCGACGGTGATTGCTGACGA

[0154] ACATGTCAGGGTGGGGAAGCTAACCGTTTTTCTCCGAAGCGTAAGTGTTGTTAATTTAATCTGTATCAATGTACCGCTGAAAAGTTCA

[0155] CTTGTGCATAATTTAATGCAAAAACAGTGTTATTAATGCATAGCTATTTTATTTAGAGGGGAGAAAAGTGCTCCATATAGACCCTTTG

[0156] TGTTTTCCGGGGCGAGTGTAAAGCATTCAAGTGAGTGTTCACTTTTATTGATTGGAAAATTGTTTAATAGTGTTTCACTGGAATGAGTG

[0157] TAGTGGTATTATTGTTCTAACGTCATATGTTTCAAATGTTAAGGAAAAGTTTTGTATTTTTTCCCTTTATCATCGCAGAGGGAAATC

[0158] AAGTCAGCATAGGCTGTTGTTAACATGTGCTAGAGTGGTGATGAGCTGTAAGTTTGAATCATCAAAATTCACTTTTGAAGTCCTATGAG

[0159] TACTGATTTACTAAAAATGCAACTTCTAATTTCCTTTGCATGTACTTTTCCTATAATTTGAGTAGCCTTATTTGGTTTGACAATTTTG

[0160] ATTTATTGATGGCTGTTACACCTGGTGTTTTTATTTGTTTTCCAGCATAAAAGGCTACTACCGTTGTCTATGTTAGCTGGTCATTGTGA

[0161] ATTGTGGAAAAAGGCAAACTCATTTCATTGTGAAGATCAAACTTTATTGTTCGCCGTGGCTGTATTTAAGTTTTAATTCTCTGTCCG

[0162] AATTCCCAAAAATTTGCATACTTAATGCTGTGCTGTTTCAAGTGCAGTCTGGAATAAAAGGCCCCATTTAAATTTTCATCCTGTGTCC

[0163] GGTGTTACCAATTCATATTCCGGGCCACATAGATGAATTTCTTTGTGCGAGGTTACAAATGTATATGTTCCTTTTCTAAGTGTGTCTC

[0164] TCAAAATGCACTTAACACCAAGACGCAAGTATTTTAAAGGGATCGGGTCTTATCGGGTCCAATTGGGAAAAGCACATTTATTTTAAA

[0165] TTATCTGACACCTGAGGCAACGAATACTAAACCCATGTCTGAGGCACTTGTCAATGTTTTGGACCCAAACCCGCTCGGGTCTCAGGTC

[0166] AGACTTCAGGTTTTCGGATCCAAGGGGACCCGTGAAGACCTCTAGTGTTCACGTGAGAGTAGACCTTGTATTGTGAACAAGCTTTGGA

[0167] TAATATAATTTTGTAAATAAAGTTTTTTTTTTTTTCATAAAACTGAGGTTAAACCACAGGAGTCACATGGATTAATTTCACAGTGT

[0168] CTTTCTTATCTTTCTGGACCTTGAACTTGTCAGTTGCGTTGCTGTCAATGGAGGGACAGAAAGCTCACGGATTTCACTAAAAATATCT

[0169] TCATTTGTGTTCTGAAGATGAACGAAAGTGTTATGGGTTTGAAATTATATGACGTTGAATAATTGATGACATACAGTAAGTTTAATTT

[0170] TTGGGTGAACTAACCCTTTAATAACATTTTACGTGTATTTACACACAGTTTTTGTTTTGTCTGTGGGACAGACTGTTCCAGCAGGCTA

[0171] AACTGGATCTGGAAAGAGCACGTCTTGAGTTTGAGATGAAGCATCAGGAAGCTGAGGACAGGCTTGCTCGAGGTACCCACCAATTCAT

[0172] GGTACAGATTCTGCAAATGCTTAGACCAACAGTGCCAC

[0173] (SEQ ID NO: 5 represents the sequence before insertion, and SEQ ID NO: 6 represents the sequence after insertion).

[0174] The genomic sequence of DEL Chr7:2062567 is shown below, and the mutation type is deletion.

[0175] (SEQ ID NO:7)

[0176] CTATGTTTTTGGGGAAAAAAAAGAAGTCCAAAAAAGTATATGGACACTTTTGTTATTCTAATAAATGTGTGAATGTGATTGCATCAGA

[0177] TAAAAACATAAAACCACAATGCGGTATCCTCTCTTCACTAACTTCACTTTTTTCAATATTTTTGCTCAGTGTCTTTTAATCAACTTTT

[0178] GTTTTGTTAATTTTTAGTGAATTTA

[0179] (SEQ ID NO:8)TGGACCTCTTTTTTTTTTCCCAAAAACACATTCTCTTAAGATG

[0180] (SEQ ID NO: 7 represents the sequence before deletion, and SEQ ID NO: 8 represents the sequence after deletion).

[0181] The genome sequence of INS Chr31:9671978 is shown below, and the mutation type is insertion.

[0182] (SEQ ID NO:9)T

[0183] (SEQ ID NO: 10)

[0184] TTCAATTCAATTCAATTCAAGTTTATTTGTATAGCGCTTTTTACGATACAAATCATTACAAAGCAACTTTACAGAAAATTAAGTTTCT

[0185] ACAATATTTAGTAGT

[0186] (SEQ ID NO: 9 represents the sequence before insertion, and SEQ ID NO: 10 represents the sequence after insertion).

[0187] The genome sequence of INS Chr40:9140647 is shown below, and the mutation type is insertion.

[0188] (SEQ ID NO: 11)T

[0189] (SEQ ID NO: 12)

[0190] TGTAGTGTCGTGTCTGCTGCCATGGATCTGAGGGATCACACTCAGTCTTGGGGTTTTGTTTCCAGAAGATAGACTTTATTTCAGAGAG

[0191] AAACGAAGCCGAGATGTTCTCTGCGAGAAGATCTCCAGAATGTTATGTGGTATCTCCTTATATACCATATACAGGGCGTTCCCAATAT

[0192] TCCATAATTTTCCTTAGGCTTACAATTCGATCCCTAGAGAGAAGGGGCCCCCTATTTGGTCTGGTAAGGAGAAAGGCCCTTTTGTTGG

[0193] TCTCCCCAGATGTTTCTCATCTGGGTCTGGACATTCTGGTCACGTAGGCATCTTTCTTCATATACTACAACCATAGGATTATAATGGA

[0194] ATAATAACTATAGACATATATGGCTAAATTCACATTGATTATAGAAAATCTTATTAATAAAAATCTTCTACATTTCCCCCCTCTGAGA

[0195] CTTAGTAAGTCTCATATTTGATTATTTTTATTCAGAGTGCTACTCCATAATCCAGTCTTATTAGTTAACACTACCTAGTGACTAAATA

[0196] AGTCACACTGTATTATTACCAATGACTAGATTATGTAATTTCACTCTGGGGAGCAACAGGACCAAACATCTCCTTCCACAGTTGGCTA

[0197] GGAGGGAGTAAAAGATCCAGCCTCCCTAATGTTATAAGCGTGAGCGTGTAATTGGTTCAGCACTTGCCTGTGATTGTCACAATTGTGT

[0198] ATAAAAGACATAAAAAATACATACAAAACATAACCCATTGAATATCACAAGATTATAATAATTGATCTTCAGCCCAGATACTCTATGT

[0199] ATCGTAGAGGGCCACCCTGGGCAGAAGTTAGGCTAGTACTTACACCCAGGGTATGGTTCATCTTTAGACCTCTTCATCGTCCTCGTTA

[0200] GAGTCACTTGAACTATCATCAAAAGTTTGTTCATTTAAATTTAGTTTGTTTAGCCATCCTTCATAATATTCCTTTAGGCTCCTCTCTG

[0201] TGATAATTTGTTGATTATTTGGGACTTTTATCACTTCCATTTGCTTAGCCGTAGCGTTGACGATTAATGTTCTCAATATAGGTAATAC

[0202] ACAACAAAATAACAATCCTCCTACTAATATGGCAACTCCCAAAAAACATTCCCAGTTAAGCAAACCATGCTCCCCATGCTCTAAATTT

[0203] CAAATCAATCCAATCCCAAATTTGTTTGTCTCTTCCGGCATTTGCTGTAACTTCAGCTCTTAATTTTTTTAATTTTAGTCATAACTTC

[0204] ACTAAAAGCTCCCCCAGGGGCAGCATTATTTGGTATAAAAGTACAACATTGATCTCCGAACATTGTCTGCCAAAAGCCAGTTAAGAGC

[0205] CTGTCTGTTTTGCCATGTCATTCTACTTGTTGCGTGTACTTGGTCTCCTAACAAGGTTAACGCATCATCAGTATAGTTAATGAATCTT

[0206] TCTTGATTATAATAAATGTAATTAATCCACTCTGCATTTTTATTTGGTGTGATCCAAACAAATATTGACTCAATAACCTTTTTATTTC

[0207] ATCTCTTGCCTTGAATTCATTAGGAATTCCTCTCGGTTGCCCAATTGAGTCTAACTATACATTTGGGTCTGTCTCGTAACCTCTTTTA

[0208] ATTCTGTTGTCTTCCCTACTTGTGCTTGATTCTGTTCCCCATTGTGCCATGTTAACTTCTTGAAGTAATCGTACTCTTACACATATAC

[0209] CTTTCCATCCTACTGTTAAAGAAGGCAGTAATATCTCACCTCCTCAGATCCAAAAGAAATCTGCTATTATTAATGATTGGTCTTCATA

[0210] AATTTCTATTGAAGGTAATGCAATAGTTTGATTTTCACATTCTTCGGGCGTTATTTTACTTCCGTTAGTTGTTCTGAGTGCTAACAGT

[0211] TCTGGAGCTCTAGAAGGAATTCCTGATTTCCAAGAATTTTTCTTATCTATGTACCAAATAATAGCACATTTTCTTTTAAATTTGCCCA

[0212] CATCTTGTGTTCCTTTTGGTTTATGGAAACACTGATATTCCTGTTTATAATCTATGCTATACAATTTTGGAATCTCTACTTTCGTTTT

[0213] TCAATTTTTATATTTTGGCTAACATCTGAATACTGACACCAAGATCCCCAGAGTGGTCTAAAAAATAATCTGTTAATTTAGGATGGTA

[0214] TGGCTGTTACTTTGTTTAACGGAGATTTGGAGCACAGCAAGCAATTTTTCTTTCCTGTTTCTCTAGCAGTAAAGGCTGCCCATTTATA

[0215] CCATTCATTATTTTGGGCTGTATCCCATAATGCATCAATATGATTAATGTCTACATCACCTTGAACATCAAAATCAGTGTTTCTACGA

[0216] TTTTTGATTATCATTGGTTCTGTTGGGTTGATATCATTGTCACTTTTGTTCAAAGGTTGAAAAGTCAATTGAAGGGAAGTCAGATTGC

[0217] TTTCCATTGGTTGAGTTTGGGTTTGCATTATTAAATGCATTAGGCATAGGATGGTCTTCAGACATGTTGTCAAATTTGTTCTCTGTCC

[0218] TCTCCAGTTCGTCTGACAGGAGGAAAGGTGCTCCTTGTGGATATTTCTTTGTGCTCTCGTCAGTTTGCACTTCATCATTTGTCTCTGA

[0219] TCTTTCCTCGTTACTCTCTCCTGCATCGTCTGGTTGTCTGTTTTCTTTTCTTTCTGCCTTTCCCATGGTAACTCTAGTACAGTGGTTT

[0220] AGATGATACCAGGTTGTGCTTCCCTCCACTTGGACTGCTGTTGGAGTAGCTCTCACCACTTTGTAGGTTCCTTCTCTCCTGGGCTCAT

[0221] TCCACTTTCTCCGGAATACCCTCAGATATACTTGGTCACCTGGAACAACTGGACAGGCAGTCTCCAATTCCTCTCTGGGCTCTTTCCT

[0222] TTTCTCCTGTAAATAGATAACTTTATGCATAGCAGTTAATTTCTTCATATTATATCGAAGTTTCATTTATAATTGCTCTAGAGGCAGT

[0223] CCTTTGCAAGGACCTTTGCAATATGGCACATGCATGGGTCGACCCGTAAGCATTTCATGCGGTGTTAAGTGCATGTTCCTGTTAGTTT

[0224] GCATGCGATAGCTTATTAGTGCAAGAGGTAAAGCATTAATCCAATTAAATTTTAGTACTTTGACATATTTTGTTTACTTTGGCCTTGAT

[0225] AGTACTGTTTAATTTTTCTTATCACTTCTTTCTGTTTCATTTGTTTAATTTTCCTTATAATTTTCCTTATCACTTCCCCCCTTGCGCA

[0226] ATGGTCAAAACCATGCGCATCTGCAATAAGAATATTCAAAAGTAGGTGCAATAATGTTTCCTTCATGTGTACGCCAGATCTCTTGTTA

[0227] GTCCTTTTTTAGCTTCCCTTCTGTTACACATTTATTGTTCATAGGGGCCCGCTTGTTGTTTAATTCGAATTATATAATCCAATTGAGG

[0228] TTGAGGTTCAATATGTACTACAGGTGCTAATATGGCTACCTGACACCCTAAAGCTTTTTTATCTTCAACATCCAGTGTAATCTTTCCC

[0229] TTACTGACACTGTTTACCTGTATATGTAAACAAATACCTTCTCTCTTCTGCAAGCAGCACACTGTAGTAAACTGAATAAAGATCAGTT

[0230] ACGATAAAATATTTGGCATCAGTAGGGACATTCATCAGTAATGTGTCGGGTTTGGAACTTCAGCTGGCAAATTATTTCATTTATTAT

[0231] TTATAAGTCTTTTTCATCGTTCATCCTATATTTTTTGTTTCCCATTTTTTTTCTACATATTCTGCAATATGTCGGACAGAATTAGTTA

[0232] TTAAAAATATTAATTTTAACAAATTCACCATCTGGTATTTATAGCTGCTCCATTTACCTGTTATGATGTACTTGGAGACACAATTTGC

[0233] TGTCCTTTGGTTTCTTTCTGCCATTTTTGTTCTATTTTCTCATCTCTCTGTTAATCATTTATCATTGTGCATTGAAATTCTGATTTTA

[0234] GTAGCTGTGCTTCAGGAATCTGTGCTTCAATAAACTTTCCCCATTTATTGACTCACATCTTGTTCTATCTGTCCTATCCAATAGACAT

[0235] TTGATTTTGGCTCTGCAATTACCATTTGTGTTTCTTTTTCCTATTGCAGCAATATATATTCCTTCTGTAGAACACCTAATTTGTAGCCC

[0236] TAATTTGCATAATGCATCTTCTTCCTAACAAATTGATAGGAGTCTGATTTGATACCAGAATGGGCATTATTATACTTTGATCTTTTGTT

[0237] TGTAGACACACTAGAGCTGTTATTGGAATTAATTGCATTTTTCCCTGAGAATCCTATTGTCTTTGCAAATTTTTCCAGACAAGGGGAG

[0238] ATGTGAGACATATTTTAAATTTAAACAGGTATAAAAACACCTCTGTGTCTAAAATCATGGGTGTGTTTTTCCTTCTATATTTTAATTT

[0239] GCATAATAATCTCTTGATCAGCTTTAGTTATTAAAATTGGAAGCTGACTCTCCCCTGTAAGATTCTCTGGGCACCCCTAATAACCTGA

[0240] ATTGGGACCTCCCCAAGGGTTTACTGGGTGCTGTACTGGACCTTGGTTAGGCTGTCGCCAGCTCTCTCCCTTCCACACTGAGGGTACT

[0241] TTTAAGGTGGATAGGTGGGATATTCATTTTTATTATGTCCGGGCTGTTCCATCTGCCCAGCACACACCTGGAGGACCAGTATAAACCT

[0242] CTTCCTCTCTGGCCTCGCTGTATGGGTTTCTTTCTCTCTTCCATTGTCCTGGCTGTTGAGTATAAACATTAATTATGGGCACAGGAAT

[0243] CGGGCGTGCGTTTGGAGGGATTTCTGTAAGTGGGCTAAACAATGTTGCCATTAATGGGTCTCTTTTTGGATCCCCTTCAGTTTCTTGC

[0244] TTCCACCTTTTCAGCTGTTTCTGAACATATGTGGTTGGATTTTTCGTGTTTCCCAGCTCTTGTCTCTCAAGGATTTAGGATTCAGTCT

[0245] GATCGGGTACTCCACACACAGTGCCTGCCACACTGCTGGTCCGAATGCATCAAAAACAATCCCATCCATATTACGAGAGTTCACTGCT

[0246] CTGTTTAGAGTAGTTGTTTGAAGAATTTCATCCATCTTTGTCCCTCCTACAATTTTAGCCAGCAAAGCTTTATTGTCTCTCACAGCCA

[0247] AAAGTTTGTCCATAGTTCCTTTCTCAAACACCCTGATCCACTTTCCAGCCCCCTCATGAATATCTGGGAGGCGATTGTCCAGCCCCTC

[0248] GAGGTCCTGTGGAGCCCAGGGGACTTACTGTCCCTGCCCACCCTTGATTAAAATTGGGAGGTGTGCAGCCAGTGGTCTGAATGTCCCC

[0249] TTTTTCTCTGCCCTGTTCCCATTTTCTGTTATCAAATAACTCATCTGCTTTATGTATATCCTCATTACTATAGAACAACTTACTTTTT

[0250] CCTCTCTCTGACCTATTTACCTCCTGTATCTTTTTTCCTGATTCTTTGATTTTCTCTTCCATTTCTTCTTCCATAGCTTGTACTTGTG

[0251] CTTCTATTTCTATTTATTATCTTTACTCCTTATTTTTTCTAATCCTTCCTCAAACCTGGGTTTATCTTCCTGGTTTGCTTTCATTTTT

[0252] TCTAACGCTGTACGTGCCTGTCTGTAACAGTCTGTAAATAGCCTTTACTTTTCTTTCTGTCTTGCCTCTGTGTTTTCACAGCTGGTTT

[0253] CTCTCTACCATCCATCTCTATATGCCCCTCCATCTCCAGTTCTCCTGTTACTTCCACTGTTCCCTTGAGAATTGGGAACTCTACCTCT

[0254] GAGGGGCAAATAGGGAGGCTCAAAAAATACTTTTCCCTTCTTCTCTCTGTCTCTTTGTCTGCCTGTTTAGTATTTTCCTGGCCTTTTT

[0255] TAAACTTTTCAACATATTCTCTCCTTCCTTCTTAAACATGGCTATTACTTATTTTTCTCTTTTTCCCTCTTTGCTTCTCTTTTTCTC

[0256] TTTTTTTTACTGATGCTTTCAGTTTTGTAGTTTTTTATTTTACCAGAGTTTCCATCTGCTCACACAATGCTACATCGAATGTCCCTTC

[0257] CTTTTGCCATTTTGTCATATTTTTGTTCTCTTCTGCCATTTGTTTGAGATCTTGTTTTATTTGCTCTTTACACAGTGGATATTTTAATC

[0258] CTATTATTTCCTGCCATATCTGAGTGGCTGTCATATCTTTTCTTATAATATTACAATCCAATATATACTTTTTTAATTCTGTATATAT

[0259] ATTTCTTTGTTTAATTATCTATTTTCATATTTATATATTTATTCATCTATCAACTTATCTTATCTATTTTTAACCAGTTTTTCCATTT

[0260] TTTTTTTCTTTATTCCTTAGTCTTTATTCATGCCTCTTTTGTATTTAGTTATTAATTCTGTTTGATGCATGTACACTTTTTGTATAAAT

[0261] TGATAATCTCAACTCTATTTTACTATCACTCAGTATGTATTACATTTCTAAAGATAATTCTTTATTTATCTTTACTTCTCTTTATTGT

[0262] TTTGTCGGCACTTATATTATTTTTTAATATACTTATTTAACTTAATGCCTTGCTCTCACTTCTACTGCTCTGGTCTCACAAAATTTCT

[0263] CCTTCTCTTTCACACGGACATCCAAAATGCAAAAGCCTATAAAAATCTTGATTTAAATTTATTGATTCTATTTTCCTAAACAAATTCA

[0264] CTCCTTCAAACCATTTCATCCTTTGTCCCTTCATCCTATAGGGCTCAATCTCTCATACTTTTGTCCCTTAATTTAATAGGGCTCATC

[0265] ATTCAATCATCCCTCTCGAGTGCGGTAGTTGCATCCAATCCTGCACGGCCACACCTAAGTGACGGTCCAGGAACGGTGCACAGCTTTT

[0266] ACCCACTCAATACGGAATTTATTTGTTCAAACATTCTCATCACTCACACAGACATTCGTCCGGACACAGTTTCACACACACAACAACA

[0267] CATAACACTCTTCCCTAGAGTGACCTGTCAGTTCTACTCGCTCTTTCACTGATGCACTTCCTCAACACAGTAAAAAAGCAGTACCCTG

[0268] CAGGAATTTATGCCTTTCCGTGCTGCCCTCTGTATCTCCCTAACAACCTCTACAGAGCGTTATCCAAAGGACTTTAACGCGCGATTTT

[0269] ACATCTGTTTACCGTTTATTGCTGTCCTTCTCTAGACCAATCTTCAATAAACACAGACCCTTACATGCAATGCATTTATGCCTACACC

[0270] ATTTAGTCTTAATTTAGGTCACCTATCAAGGCCTTTCTAACATTATATTAAATATGTGCATGCAATTTTTCTTCTGGAAACAAAACCC

[0271] CCCATTTTCATTTACTTATTTAATTCTAAATTTGGAAGAGCAGATTTTAAGTGACCTTACCACTCAGAACTGACTGTTCAACAACACA

[0272] CACTAATTATATAAGCAAAAATGCTTACCTTATTTTATGGTGGCCACCACTGTGTGCGTGTTGCTCATCAGTCAGTTCAAAAGCGGTC

[0273] GTCCACTCTGCTGCTCCTTTCCAGCCCCACGTTGGGCGCCAAATGTAGTGTCGTGTCTGCTGCCATGGATCTGAGGGATCACACTCAG

[0274] TCTTGGGGTTTTGTTTCCAGAAGATAGACTTTATTTCAGAGAGAAACGAAGCCGAGATGTTCTCTGCGAGAAGATCTCCAGAATGTTA

[0275] TGTGGTATCTCCTTATATACCATATACAGGGCGTTCCCAATATTCCATAATTTTCCTTAGGCTTACAATTCGATCCCTAGAGAGAAGG

[0276] GGCCCCCTATTTGGTCTGGTAAGGAGAAAGGCCCTTTTGTTGGTCTCCCCAGATGTTTCTCATCTGGGTCTGGACATTCTGGTCACGT

[0277] AGGCATCTTCTTCATATACTACAACCATAGGATTATAATGGAATAATAACTATAGACATATATGGCTAAATTCACATTGATTATAGA

[0278] AAATCTTATTAATAAAAATCTTCTAC

[0279] (SEQ ID NO: 11 represents the sequence before insertion, and SEQ ID NO: 12 represents the sequence after insertion).

[0280] The genomic sequence of DEL Chr48:8724756 is shown below, and the mutation type is deletion.

[0281] (SEQ ID NO: 13)

[0282] ATGCTAAAAAAAATGATGAGAAGTATGTGGTTATGTCAGTGAATGGTGAGAGTCAAAATTTCTGAAACTCTTATTACAAAAAAAAACA

[0283] AAAAAAAAAAACATCCTTGAATGCCCAGAGAAGTTCTGTTGCTTAGGATCTTCCCTTTCATTGCTCAGGAGACTTAACAGAGCATAGG

[0284] GTTTGTGCTTCTGAAGCTTTAAAAAATGTAAAAGG

[0285] (SEQ ID NO: 14) CAGTAGTGT

[0286] (SEQ ID NO: 13 represents the sequence before deletion, and SEQ ID NO: 14 represents the sequence after deletion).

[0287] The genomic sequence of INS Chr50:4154584 is shown below, and the mutation type is insertion.

[0288] (SEQ ID NO:15)

[0289] TTTCCTATCAAAATGCTTGCTACAGTTGCTAAAAATGCAGAAAATCGTACCTGATCTGAATTTTTTATGACGGACAAAAGCTTCGGAG

[0290] GCAGTGTGTAAACGTGATTAACAATGTGAGGTCGTATTTATTTTTTAATGTGCAAAGATTTCGGACTTAGTGTGCAATGACCTTTACT

[0291] GTTTACTAATGTGAGTAACAATAATTACTATAATTTGATATTTACGTTTTTATTAGTCATAATACATATATCTTAACATGTAAAATAT

[0292] CTATATATCTAATATAATATTTATATTAGAAATATATGAAAATAGATTAAAATAATAAAGTTAGAATTTTTTTTTACTTAAAGGCACA

[0293] AATTTTCGTAATAAAATATCCAAAACATAATATCCGCATATCCACATAGAAGAGATTGACTCATAAAACCGTATATAGACAGCTTTAC

[0294] TGATTATAAGGGGAGTTTTTCGAGAGTGCTTAAACTCGCGCTAGACCAAAGTCAGTCATAATGTTCTTTGACAATGGAAATGTTCTTT

[0295] GCTTGCTTTCTCTGTATAATTTATTGCCGTTTAAATAACTGTGGAAGGTGCAGGTAATAATAAAACAAATTACCCCATACTTGAACAT

[0296] CCTCCTTCACAGCATCATCAAGCTTTGCTTTTGTTATTGTTTTGAAAATGCGACTTCTAGCAGCGAAAACTTACATATTGTGCCTTTA

[0297] ATTTTTAATTATTATAATTAATATAGAAACAAAAATTCCACACACTATGCCAGCTTGCAAAAAATATCTCCCTGACATTTTATTAA

[0298] AAGCAAAATTTGATCAGAAATTGTATGAAACTTTTAATTAATTAATTTTTTTTTCATTAAATTAAACTTAAAATTTGTTTTATTAT

[0299] TTCGTAATATGTATGTAGTATATATAGTCTGAAATATAGTTTTTAAAAAAGTAAAATTTTATATATATATATATATATATTATATATA

[0300] TTGTATGCTGCTTAAGAAAGGTAATTTTGCTTTTGGAATAGGGGACAGATATTATTAATATAATATAATAATAATATTATTATTAAGATTT

[0301] TATCTTCTTTCTGATCCCTTTTGCACATGGGAATTTAAATTATCTAAAGAAGAAAATGAAATGTTTTGTGTTTTACCATGGAGCAATA

[0302] AAATAAAAAATGAAATGAAAAAATTA

[0303] (SEQ ID NO:16)

[0304] GTTTGACGGATGAAAAAGCTTTGCTTTTGTTATTGTTTTGAAAATGCGACTTCTAGCAGCAAAAACTTACATATTGTGCCTTTAATTT

[0305] TTAATTATTAAAATTAATATAGAAACAAAAATTCCACACACTATGCCAGCTTGCAAAAAATATCTCCCTGACATTTTATTAAAAGC

[0306] AAAATATAATCAGAAATTGTATGAAACTTTTAATTATTTTTTTTTTAATTAAATTAAACTTAAATTTTGTTTTTTATTATTTTGTAAT

[0307] ATGTATGTAGTATATATATAGAAGCAGATTAGTCTCAAATATAATTCACGCAAAAAACACGATTCACACATGCGTAGACAATTTCACA

[0308] TGCATGAAACCTAATTCACGTACACACAAAAAAAATTCACGTGCGTGAAAAAAAAAATATATTCACACAAAGCAATTCACATGCGCAA

[0309] AATAAAATTATATATTCATAAAATACATTTCACAAATGCAAAACACAATTCGTAGATATACAACTGTGCACAAACCTTTGAATGTT

[0310] TAAAATGTACGAGTGTCTGAATGTACGAATCGTCATTTACTACGAATCCACTCGGATTTGTGTGTGTGTGTTTTTGAGACTTTCCTGG

[0311] CAGAGCTCTCTTCCCACGTGGGTCTGTCGTACTCTTTAGCCAATCAGATGCGAGCTTACCATTCAACCAATCATATCATAAGCAACCG

[0312] AGAGTGCATTCAAGGAGCACGATTCTGCGCACCTTTTGCGCAATGTTGATTAATTAGAACGGAAATTAAGCCTTTACATCAGTAATCC

[0313] CAAAGACAGTAAAAGAAATGGACACAGCGACCCAATTGGAACTCAATTGAGACAAGTGAAGCCAATTTTTAGCGATTTTTAGCACTTC

[0314] CGTTTCTGACGCGCAGACTCAAACAAAGGAAGCTTCTGCCATTATTGTGACTTCATCTGAACATGTGCAAAACTACTCTCCTTGAATG

[0315] CACTCTCAGTGGCTTATGATATGATTGGTTGAATGGTAAGCTCGCATCTGATTGGCTAAAGAGTACGACAGACCCACGTGGGAAGAGA

[0316] GCTCTGCCAGGAAAGTCTCAAAAACACACACACACAAATCCGAGTGGATTCGTAGTAAATGACGATTCGTACATTTTTAAACATTCAAA

[0317] GGTTTTTGTGCACAGTTGTATATCTACGAATTGTGTTTTGCATTTGTGAAATGTATTTTATGAATATATAATTTTATTTTGCGCATGT

[0318] GAATTGCTTTTGTGAATATATTTTTTTTTCACGCACGTGAATTTTTTTTGTGTGTACGTGAATTAGGTTTCATGCATGTGAAATTG

[0319] TCTACGCATGTGTGAATCGTGTTTTTTGCGTGAATTATATTTGAGACTAATCTGCTTCCATACATATATAGTATGAAATATAGTTTTA

[0320] AAAAAGTTAAATTATATATATATATATATATATATATATATATATATATATTTGA

[0321] (SEQ ID NO: 15 represents the sequence before insertion, and SEQ ID NO: 16 represents the sequence after insertion).

[0322] The PAV sequences related to the linoleic acid content of carp are shown in SEQ ID NOs: 17-22, wherein the genome sequence of DEL Chr20: 2258997 is shown below, and the mutation type is deletion.

[0323] (SEQ ID NO: 17)

[0324] ATTTTTTTAAATGCTTTTGAAGTATATAATAATATATAAAGCATTATTTTTATTTAATATTTTATAAATTACATATATATATATATAT

[0325] ATATATATATATATATATATATATATATATATATATATATATTTATTTATTTATTTATTTATTTTTACATTTTTGTGTATTTTTCCAT

[0326] CTTTTCCACTTTTTAGGAAAAAATGTGTTTGTTGTGAAAATGTACAAAAATTGTAATATTCCTTAAAATGGGCAACTACAATTTTTGT

[0327] GGAAACCATGATACATTTTTTTGTCAGATTTCTTGAATAAAAAGTTCAAAAGAACAGAATTTCTTTGAAATGGGAATCTTTTGTAACA

[0328] TTATAAATGCCTTTACTGTCACTTTTGATCAATTTAATGTATCCCTGATGTGTAAAAGTAATCATTTCTAATTATAAGTAAAAAACCG

[0329] TGCTGATTTCAAAGTTTTAAACAAAAGAGTACGTTATCTGGGAGTAATGTGACTAATTGAACCACTAACTGAACTACAGCGAGTAACT

[0330] GGACACGTTCTGATTGAACTCGGCAGCAGGTTACGTACGATCTTTCTGTTGGCCCTCCTCGTCCAGATAGATGTTGGTCTTCATGTTC

[0331] CATATGAACTGATGAGCGAGGAGCTGGGACTTCTGTGCGGCCCACAGGATGTACTCGCGCACGTAACCCATCTGTCAAAAACGCCAGC

[0332] ATAGATGTCAACAGCAGCCCAGGGCTGTGAGAGTCAGATCAAACCACTGCTGTGTTAAAAAAGGGAGTTCAGGAAAGGTCACAGTTCA

[0333] CTCTTCCTCACCTTGTCATACCGCAGCGACTGAACGATTTGAGGAATGTAAAATAAAATGGCGTCCTGTAAAAGAAACGCAAGTGAGA

[0334] AATCACAGAAACATTATAGACAAACCTTAATCTGTTCCTCACACAAGGAATAAAACGGGTTTAAACCATAATCACCCTTCAAAACATC

[0335] TCCTTTTGTGTTTCACAGAAGAAAGAAAGTCATATAGGTTTAAAACAACATTTTTTCCTCGATCAAAAGTGTCAAGGTCTAAATACAT

[0336] CAATGGAAACTGTAGCTTAAAGCATAAATGCTGTCAAATATCTGATATTGATTGACAGCAAGTTAATTGCTCAGCTGAAGTATGAAAC

[0337] AGGACATTTTTAAAACATGGTTTCTAGACCTGGAAAAGTCACAGGAATTATTTTTTTTTAATAAAAAGTCAAGTAATTTTTTAGTTAA

[0338] CATTTTTTTTATTATGGCAAACTCTAAAATATTTTATTAGTTAGAAATTGCATTTCTAGACCTGGAAAAGTCACAGGAATTAATATTA

[0339] AAAATATTTAAAATATATATTTAAAAGTCAAGGAAACGTTTATAATGATTTTTTTTTTTTTTTTTTATAAAAAGTCAAGTAATTTTGT

[0340] AGTTAACATTTTTTTTATTATTATGTCAAACTCTAAAATATTTTATTAGTTAGAAATTGCATTTCTAGACCTGGAAAAGTCATGGGAA

[0341] TTAATATTTAAAATGTTATTAAAACATTAAAAAGTCAAGAAAATGTTTATAATGAATATTGTTTCTAGTTATATCAAGCTGTAAAATA

[0342] TTTTATTGGGCAGAAATTGCTATTTAAAATGTATTTCTAGACCTGGAAAAATCCTGGGAATTAATATAAATTAATAATAAGTAA

[0343] ATGAAATTTTTTTTACAATCTAATTTTTTTCTAGTTATATCAAGCTCTAATATATTTCATTGTGTAGAAATTGCTCTTTGAATCATGT

[0344] GATTTGTAGACATGCAGAAGTCATGGGAATTAATAATAAGTCAAGGACTTTAAGGACTTACTTTTTTTCTAGTTCTGTCAAACTAAAA

[0345] TATTTTATAAAAAAAATAAATTGCTATTTTAAAATTGTGATTTCTAGACCTGAAAAAGCCATGGGAGTCAACATTAACATCGACATTTT

[0346] TATAATAAATCACTTTTTTTCTACTTAGCTCAAGCTC

[0347] (SEQ ID NO:18)

[0348] ATTTTTTTAAATGCTTTTGAAGTATATAATAATATATAAAGCATTATTTTTATTTAATATTTTATAAATTACATATATATATATATAT

[0349] TTTTCACATTTTTGTATATTTTTCCATCTTTTCCACTTTTTAGGCGAAAATCTGTTTGTTGTGAAAATGTAAAAAAAAGTCTTAATAT

[0350] TCCTTAAAATTGGCAAAATGCCTTTACTGTCACTTTTGATCAATTTAATGTATCCCTGATGTGTAAAAGTAATCATTTCTAATTATAA

[0351] GTAAAAAACCGTGCTGATTTCAAAGTTTTAAACAAAAGAGTACGTTATCTGGGAGTAATGTGACTAATTGAACCACTAACTGAACTAC

[0352] AGCGAGTAACTGGACACGTTCTGATTGAACTCGGCAGCAGGTTACGTACGATCTTTCTGTTGGCCCTCCTCGTCCAGATAGATGTTGG

[0353] TCTTCATGTTCCATATGAACTGATGAGCGAGGAGCTGGGACTTCTGTGCGGCCCACAGGATGTACTCGCGCACGTAACCCATCTGTCA

[0354] AAAACGCCAGCATAGATGTCAACAGCAGCCCAGGGCTGTGAGAGTCAGATCAAACCACTGCTGTGTTAAAAAAGGGAGTCAGGAAAG

[0355] GTCACAGTTCACTCTTCCTCACCTTGTCATACCGCAGCGACTGAACGATTTGAGGAATGTAAAATAAAATGGCGTCCTGTAAAAGAAA

[0356] CGCAAGTGAGAAATCACAGAAACATTATAGACAAACCTTAATCTGTTCCTCACACAAGGAATAAAACGGGTTTAAACCATAATCACCC

[0357] TTCAAAACATCTCCTTTTGTGTTTCACAGAAGAAAGAAAGTCATATAGGTTTAAAACAACATTTTTTCCTCGATCAAGGTGTCAAGG

[0358] TCTAAATACATCAATGGAAACTGTAGCTTAAAGCATAAATGCTGTCAAATATCTGATATTGATTGACAGCAAGTTAATTGCTCAGCTG

[0359] AAGTATGAAACAGGACATTTTTAAAACATGGTTTCTAGACCTGGAAAAGTCACAGGAATTATTTTTTTTTAATAAAAAGTCAAGTAAT

[0360] TTTTTAGTTAACATTTTTTTTATTGGCAAACTCTAAAATATTTTTAGTTAGAAATTGCATTTCTAGACCTGGAAAAGTCACAGG

[0361] AATTAATATTAAATATTTAAAATATTTAAAAGTCAAGGAAACGTTTATAATTTTTTTTTTTTTTTTTTTAAAAGTCA

[0362] AGTAATTTTGTAGTTAACATTTTTTATTTATGTCAAACTCTAAAATATTTTTAGTTAGAAATTGCATTTCTAGACCTGGAAA

[0363] AGTCATGGGAATTAATTAAAATGTTATTAAACATTAAAAGTCAAGAAAATGTTTATAATGAATATTGTTTCTAGTTATATCAA

[0364] GCTGTAAAATTTTATTGGGCAGAAATTGCTATTTAAAAAATGTATTTCTAGACCTGGAAAAATCCTGGGAATTAATAAAATTA

[0365] ATAAAAGTAATGAAATTTTTTCAACTAATTTTTTTCTAGTTATATCAAGCTCTAATATTTCATTTGTGTAGAAATTGCTCT

[0366] TTGAATCATGTGATTTGTAGACATGCAGAAGTCATGGGAATTAATAAGTCAAGGACTTAAGGACTTACTTTTTCTAGTTCTG

[0367] TCAAACTAAAATATTTTATAAAAAAAAATTGCTATTTTAAAATTGTGATTTCTAGACCTGAAAAAGCCATGGGAGTCAACATTAAC

[0368] ATCGACATTTTTATAATAATCACTTTTTTCTACTTAGCTCAAGCTC

[0369] (SEQ ID NO: 17 represents the pre - deletion sequence, and SEQ ID NO: 18 represents the post - deletion sequence).

[0370] The genomic sequence of INS Chr25:3825897 is shown below, and the mutation type is insertion.

[0371] (SEQ ID NO: 19)

[0372] AGCCACGCAGCGGAGCATCTGCTTTAAGGTTTTGTTGAACCTTTCAACCAGCCCATCGGTCTGCAGGTGGTACACAGTGGTCCGAAGC

[0373] TGCTTGACCTTTAGGAGGTGGCAGAGGTCAGCCATCTTCCGGGACATGAAGAGGGTGCCCTGGTCGGTCAGTATCTCCCGGGGTATGC

[0374] CGACCCGGCTGCACAGCAGGAAGAGCTCCTGGGCGATGGCTTTGGACGTGGCTTTGCGCAGTGGAATGGCTTCGGGGTACCGGGTCGC

[0375] ATAATCCACGATGACTAGAATGTGTTTGTGTCCCCGGGCGGACTTTGGCAGCGGCCCTACGAGGTCCATTCCTATCCGCTCAAAGGGC

[0376] ACCTCAATGATGGGCAGCGGGATTAGCGGAGCTGGGGGAGGAGTTTGTGGCGACGTCCTTTGGCAGTCCGGACAGGCCTGACAAAACC

[0377] GCTTGATCTCCGCCTCCATGCCGGGCCAATGGAACCTGTCCCGGACTCATTGAGTGGTGTTTTGCGCCCCCAGGTGGCCCGCCATAGG

[0378] ATGGGAATGGGCGAGCTCGATGATAGTCTGTGTCTTTGTGCGTGGGACAGGCCGTTCTGAACCACGAAGTGTGGGGTTGGGTGTGGTG

[0379] GCGGTTGGACCTCTTTTCCCTCAACCACTCTCACCTGCTTCCAGCAGTGCTTCAGCCGGTCGTCCCCAAGCTGCTCCTTCATAAAACT

[0380] TCCCCCACCCCGTACCTGCTGGAACACATCATAGAAAAGGTTAGCACTTTGGGGGGGGGGGGGCTCACCATCTCGGGCGCTGTCCGAA

[0381] GCCAGGAGGACAGGGCGCCGTCGGGGACCCCGGCTGACGTTCTTTGTCTTCTGGCGGTTCCCGGCAGGGCTGGCAGGCCGGGTGACTT

[0382] GGGTGAGCAGTTGGTCCAAGCCTGGCCAGTCTCTCCCCAACAGGACGGGCATGGGCAGGTCCCTGGTAATGGAGAGGCGAGCTTTGGT

[0383] TCCCATCCGTGGGGGAAACAGGGAGGACTGGACCAGGCTTACCGCACTTCCAGAGTCCAACAGGGCTGTATACGGTCGGCCGTTAATG

[0384] GAAACCTCGGTCTGGGGTGCCCCTCGTGGTGGCTTCAAATGGACAGCACAGCCTGCCAGCCAGGCACGATTGGGAGAGGGTGGTGGCT

[0385] CCGTGGGCATCGGCTCATCCTGTATGCCGGTGCCACGGTGCGGTAGGGCGCACAAATACGGAAATACACGGAAATTTAGTGCCAAGTC

[0386] CAGTTCAGCGTCGTCTTTGATTATCATAAAAGCAAATCTCCTAAATGAAAAAATATGTTTCAATAAAGGAGACTCGCACCCGATTGCA

[0387] ATCTTTTTAATCGGTGAAACCAACTTTCCATAATGTGAAAGCACCTGCATCACAATATTATCACTAAGGAAAGGGGGGATATTCAATA

[0388] TTGTGACTCTCTTTGATGGTAACATGAGAGGCAAAACAGATGTAAGTATTTCATCAATGATTATACTTCGCGCAACCACCTCATTTGC

[0389] TCTTTCTGCCGTATTCAAAAAAAATCATGGTCGTGTTATTCATTCTGGATGCAGAGAGAATATTTTGATGGCCAACAACTTCTCCTAC

[0390] ACCCAGACAGCACACGGATACTATCTTGACTCTGTGACGCAATGTGAGGGAATCAAGCCCATTATCACCCTGAGCAAACAAAACACAC

[0391] ACAAGATAAATATTAAATCAAATAAACAAACTTAGACGTTAAAAAAAATTAAATAAAATTTACATTTACGCATTTAGCAGACGCTTTT

[0392] ATCCAAAGTAACTTACAGTGCATTCAGGCTAACATTTTTTGACCTAACATGTGTTCCCTGGGAATCAAACCCACTACATTTTGCGCTG

[0393] TTAACGCAATGCTCTACCATTGAGCCACAGGAACACACAAAATAAGGAAACACACAAAAAAGCAAATACACGCTCTCACACGCACTCC

[0394] ACAAACGCCCATGCATGCGCAAAGAGAGAGAGATTAGATCAGTTTATCATTATGGCAGTTATTGACTCAGGAATGGGAGTGAAGTGTT

[0395] CAGAAAAGTCAGGGGGGAAACGTCCTTTTCGCGATATACTTGTCCATCTATGTATAATTTGTCCACTGTAATGATTGCTCTTTTTCCT

[0396] TCATTTATTTTGTTTTCATATTGGTAAAAGTTGCTTTCAATGTTCAAGAATGTCCTTTGGGTATTGTTAATTTAGGGCCATAGTTTGT

[0397] GCCTTAAGTTGTCTGCCTTGCTTTTGAACCAGTTCTGTGTGTTTATAGTGTTCAAATTTTGCGATGATTGGTCGTGGTTGGTTGTTG

[0398] TTTTGAGATCTGATACGGTGAACACGGTGAAAGGTGGTGATCTCTTCAGTTTTGGCTGGTAATTTGAGTTGTTTAATCATAAAGTCTT

[0399] TGACTGATTTCGCGGGGTCATCTGGAGTTTGTTCATGGATGACTGTGAAAACTAAACTGTCCCTCGTGCTGCGCATTTGCAAGTCCAA

[0400] AATGTTTTCTTTCATGGTTTTGTTTTCTGCAACAACAGAAGTGAGTCAGTGAACTGAATCCTTTAAAAAGTTATTTTCTTTAGTGAGA

[0401] GTGTCTATATGTCCTTGGCTGAATTCTAAGCTGTGCCACAATTTCTGGAATTCCTTGTGTATAACTTCAAAATGATATTTGTGCATTT

[0402] TTCTAATTGATATGTAAATCTTTCTGTTACCATTCGTTCCATTGTTTTCTCTAGTTGTAAAGTTAGTGCTACGCCATAGTGTATACG

[0403] TCTATAGTGTTACGCCCATGGACTGTTTTGTGTTTGTTTTCCTCCCCCATGTGCTCCATGTCCTAGTTTTCTCCCGTGTTTCCTTGTG

[0404] TCCATATTTGGTTCTTCATCTTCCTGTTCCCATTGAGTTACATTTGTTTCAGCTGTGTCGTTGCCCACTGCAAAAAAAAAAAATTAAC

[0405] TGACCCCGCTATTGTTGGGTTAATAACTTAGTACTCAGAAGCTAGATTGTTAACGGTATTTATTGAATGAACTAGGGCTGTGCGATAT

[0406] GAAAAAAAAAAAAAAAACCTATCATGATTTCTTTGATCAATTTTGCGATTTTGACACACACAGATATGCTTTACAGTCATAAATGCAT

[0407] TCAGGATGAATTTGAAACATATTTCCAAAAGAAAACCAATTAGAGCTTTATCAAAAAGTTGTAACGTCTCTAGAACAGACACAAGTCA

[0408] AAATAATCACTATAGTAAAGGTGTAACAAAATTTCTAGACTTATGGCAAAAAATATAAATAAATAAATCCTCAGTCCAGGGACTTTTT

[0409] TGCCATACATTGTTTACAGAGCTCATTAATTGTAGCGGTGTCGCAGGTGTTGAAATAGATTTGTTATACATTATACAGGTTCACACGT

[0410] ACTCCGTCAGCAGTGCGTAAATAGTATGTGTATTCGGTGCAGAAGCAGCAGCGAGAGCGCATTATTGTAACGCGAAAGCACATTAAAT

[0411] TAATGCATGAGCGCGTATCTATCCGCCCGCACGCAGATTTCCTCTGCTCTGTCACAAAACCAGACGCGTGTGCTCCGATACATGCTGC

[0412] TCTCGCTCGGAGAGAGTGCGCGCACTTAAAACATGTCTCCTCTCACTTAAACTGCGTCCTGTGCACTCTCTCTATGCTCATGTGCTAG

[0413] ATATTATTTTAGCATGTTTTTATTTCTAGCCTTTTACCGCGTGCAGTGTGAACGCTCTGATCCGTTAACATGGGTTTGGAAAAAAGGC

[0414] GCATCACAGACAGTGTGTGTGAACCTGGAGTTCCCTTTCGAAAGCTTCAGTCGATGCTGCGCTGCTCAGCGCATTGGGAAACGTCTTG

[0415] TTCGTGACCAGCTGTGAATAATGTGTGTAACACGTCGATAGAATTGACCCGGCGGTAATATAGCCTGGGTTGATGACGTCATCTGCGC

[0416] GCGCCCGCAACACGGGGCTATAAATAGATAAGCCACAGGTGCATCAACAGGTCTTTTGTCTTCAGATCATTCTGTGCATGTGTGCGTC

[0417] AGGAAGATTCTTTTTGTCTACTACAGATCTTCGTACGATGACCCAACGAAACAGTAAGTGTTGTGTTCCTCCATGCTCTCGTCCTATG

[0418] TATGAGCTGGATACGCATGATTACTGTTTTGTTTGTTTGGGGGAAGAGCACGCGGTTCTGGCTTTAGAGACGGGCGAGTGCGAGCATT

[0419] GTGAACTGCTCTCAGTGAAGATGCTTCGTGCTCGTCTGAACTATTTTCAGACCGCACCCACCTTTTCGTCGGAGGGCTCTCGTGCGGG

[0420] TCTGCGTGACGAGCGAGCGACGGGCCCGTCCCTTTCGCTTACAGTGTCACCAGATCCACGCATCCTCTCTCGTGATCTCGAAGCGTGC

[0421] TCCGGTGCTTCTTCGATTCACGAGGAGGATGATATATCTCTTGAGTCTTCGGGCGATGACCAGGCCGCCTCTGAACGCTCCTCTCGCG

[0422] AGAGGAAATCGGTCGAGGAGCTGCTCGAGGTGGTTACTCGCGCGGTGGACAGGCTGAAGCTTGACTGGCCACGCGACCAAGAGACCCC

[0423] CAAACGTAGTAAGCTGGAGGATAGGTTTCTGTCGGGTGGTAGGAGAGAGAGACCGCAACATCAGTCATTCCCCTTTTTCGAGGACCTC

[0424] CATGATGAACTGTCGAAGTCATGGAGCAAACCATATACTTCCCGAATCTTTGTGCCCTCGACGTTGACTTATCGTGGATGCAAAGTCA

[0425] CGGGGGTATTCGGAGATGCCTCGGGTTGAAGCGTCGCTTGCGAGCTATCTCTCGCCTGAATCTGCATCCTCGGTGAAGAAACCTACTC

[0426] TCCCCACTAAACCTTGTAGAATTACATCATCGCTAGTGGGTAAAGCTTATCAAGCTGCAGGTCAGGCTGGTGCTGCGCTGCACACTAT

[0427] GGCAGTGTTACAGGCATACCAGGCTGACCTATTGAAGGACTTGAGTGTGGGCAGTACAATCGATGAGGAAGCATTCGCTGAGCTTCGT

[0428] CGGGCCACAGATTTGTCTCTCCGGGCGACCAAGCAGACGGCTTGTGCCATTGGCCGGTCGATGTCAGCTTTAGTCAGCACGGAGAGGC

[0429] ATCTGTGGCTTAATTTGACGGGCATTAAAGAGAAGGAACGTTTGTTTCTTTTAGACTCTCCTATCTCTCCATCTGGCCTGTTTGGCGA

[0430] TTCGGTTAATACGGTCGTCGACAGGTTTAGGGAAGTAAAGAAACATGAAGAAGCGTTCGTTCAGTTTCTCCCTCGCCGCACTCAAGGG

[0431] GAGGGGCCATCAGCCACCCAGCCTCGCCCCGGTCCTTCAAAAACCAGGGAGGTTAAAAAGCAGAGCGTGGCAGACCGTGCTTCCCCTC

[0432] GTAGGGATTGGGGACAGGTTCGCCGTGCTCAGCAACCTCCCAAGCCAGACCTCAGGACTTTTATTAATAAGAAGAAGAAGTCCTGACG

[0433] CCATGGCGCCCGTGCTGGTGGGGGTAGTACCTCACGGGGTGGTGCGCGCTCGAGAGCTTTTCGCCCCGCCCCGTTACCCTCACAAAAC

[0434] CCCTCCATCCCCGCCGCTTCTTGTGCCTCGGGGGGCGGGGGTTTCCAGCGAGATATTAGATGTTCCAGTGCCTCCTGCCATCATTCTG

[0435] GACACGGAACATCTAACATCCCCTCAAAAGGAAGTATTGAAATTGGTACCACTCTCAGAGAGTCTGGCAGCGTGGAAACTTCTGCCAG

[0436] GCATTTCTGCATGGATGTTGAGCACAGTACGGATAGGATACAGCATCCAATTTATTCGTCATCCTCCACGTTTCAACGGCGTGGTTTC

[0437] CACTTCCGTGAAACCGGAGCTGATGCAGGTACTGTCTCAAGAGCTACAAACTCTTCTGGGCAAAGAGGCCATAGAACATGTTCCTCTT

[0438] CCACAGAGAGAGTCGGGCTATTACAGCAGATACTTCCTAGTTCCCAAAAAGGGTGGGGGAGTGCGTCCAATCTTGAATCTTCGAGGCT

[0439] TAAACCGTACAATCAGAGCACTCAAGTTCAAGATGTTAACCGTCAAGACGGTCGTGTCGCAAATTCGGCATCGCGATTGGTTTATCAC

[0440] GATCGATCTGAAGGACGCATATTTTCATATAGAGATTTTGCCACAACACAGGAAATTCTTGAGGTTCGCTTTCGGGGGCGAAGCATAC

[0441] CAGTTTCGGGTTCTTCCTTTCGGCCTAGCCTTATCACCCCGCACGTACACAAAATGCATGGATGCAGCGCTGGCTCCATTACGACTCC

[0442] AGGGCATTCGCATTTTGAATTATATCAACGATTGGCTGATACTAGCGCAATCGCGAGAGATGGCGCTACAACACAGGGACATCGTGTT

[0443] AGCTCATCTAGTTTCTCTGGGGTTGAGACTCAACACCGAGAAGAGTGTTCTCTGTCCGGCCCAGAGAACGACTTATCTCGGGATCGTT

[0444] TGGGATTCGATCACGATGCGGGCACAACTGTCTCCCGCTCGGATCGAGACCATTCAGCAGACCATGAGCAAGGTCAGGCTAGGCCAGG

[0445] ATCGCACTGTTCGTCAGTATCAAAAGATGTTAGGTTTCATGGCTTCAGCATCCACGGTGATTCCTTTGGGGCTGTTACACATGAGACC

[0446] GTTTCAGTTGTGGCTAAAAGCCAGAGGATTTCATCCGAGAGCCAATCCTCAAAGGCAAATAAAAGTGACGTGCCGCGGGCTTCGTACA

[0447] CTATCTCTGTGGCTCAGACCCCGGTTCCTTGCCTTGGGTCCCACTCTAGGGGCACCGTGTCGTCGCAGACTGCTAACGACAGATGCCT

[0448] CCCTGTTGGGCTGGGGAGCAGTCTTGGATGGCCACCCAGCTCAAGGGGAATGGGGGGGTCATCAGCTCGATTGGCACATCAATTGCCT

[0449] CGAGCCGATGGCCGTATTTCTGGCTCTGAAATATTTCCTCCATCATTTGAGAGACTGTCATGTTCTAGTACGGGTGGACAGCACAGCA

[0450] ACAGTCTCGTATATAAATCACCAGGGGGGTCTGCGCTCACGCAATCTGAACAAGATAGCGAGGCAGATTTTTCTTTGGGCCCAGGACA

[0451] AGCTCCTGTCACTCAGGGCAGTTTACATTCCGGGGCGTTGGAATGTGGGAGCGGATTTACTGTCCAGACAGACACTTCCGACAGGGGA

[0452] ATGGAAACTCCACCCAGAGGTAGTGAAACAGATTTGGGAAAAATTTTACGAAGCAGAGGTGGACCTCTTCGCCTCCCATCAGACAGCG

[0453] CAATGTCCCCTCTACTTCTCTCTGAGTCACCCAGCCCCCCTGGGTCTGGATGCGATGGCGCACACATGGCCCAGAATGCGCCTGTATG

[0454] CGTTTCCTCCAGTTTCTCTGCTCCCGGGAGTCCTAGCCAGAGTTCGCCAACAAGGGTCTTGCCTCTTGCTGATAGCGCCACGTTGGCC

[0455] GAACAGGGTATGGTTTTCGGAGATAATATCCATCCTCGACGGCTCGCCATGGGCGATTCCGGAGAGGAGGGACCTTCTGTCTCAGGCA

[0456] GGGGGTACGATATTCCATCCCAGGCCCGACCTGTGGAATCTTCATGTTTGGCCCCTGAAGGGTACCAGCTGAGAACACAGGGTGTC

[0457] GCCGGGTGTTATTGATACCATCCTTAGTGCTAGGGCTTTCTCCACCAGACAGAGTTATGCCAGTAAATGGGGTGTCTTTGACAGGTGG

[0458] TGTGTGGTACACAATGTAGATCCAGTCAACTGCCATATTGCTTCAGTTCTGGACTTTATGCAAGAGAAATTGTCAACAGGCACATGCC

[0459] CTGCTACTCTTAAGGTTTATGTGGCCGCTCTTTCGGCTTGCCACGCCTTGATTGACGGGATGCCCACTCGGAGACACCCTCTGCTCTC

[0460] TCGCTTTCTTCGTGGGGCCAGACGACTGAGGCCTACAGTAAAAAACCAAGATGCCTTCTTGGGACTTAGCTATAGTTCTCGAGGGTCTG

[0461] GTTGAAACCCCCTTTGAAACTTTAGAGTCAGCGTCTGATAGACTTCTAACTCTAAAAATGTTTTTCTCTCATGGCAATAACTTCTTTTGA

[0462] AGAGAATTGGGGATATGCAGGCTCTGTCTATCTCACCATCATGCTTAGACTTTGCCCAGGGAGCGTGAAAGTGATTCTGCATCCTCA

[0463] TCCTGATTACCTGCCTAAGGTTCCGTTTTCGGCTGTACATCCGGTCATTCTAGAGGCCTTCTGTCCTCCGCATTCGCAACGCCGGAG

[0464] CAGGAGAAATCTTATAGACTGTGTCCAGTCCGTGCTCTTCAGACTTACGTCCACTGCACTAGCCAGTGGCGTAAGTCGGAGCAACTGT

[0465] TCGTCTGTTATGGTGGTGGTAACAGAGGAGCAGCTGCCACCAGGCAGACCATGTCTCACTGGGTCAGGGATGCTATTGCTTTGGCTTA

[0466] TGAGGCGCGCGGTCAAGCTTCGCCTATAGGTCTTAGAGCTCACTCCACAAGGGGGGTCGCCTCCTCTAGTGCTTTAGCAAGGGGTGTC

[0467] CCCTTACAACAGGTTTGTGATGCGGCAGGTTGGTCCTCTCTGCACACATTCATAAGATTTTATAGTTTGGATGTCCATGCTACTCCGG

[0468] GCTCTCATGTCCTTGAGTCAACATCACAAGCTAATGTCTGAGGCCTTCTTGTGGTTTGGTAGCACACCCGCACAACCTTAGGGGTCCA

[0469] GACATTTTCAAGCATGGCGGCGTGGGTATTCTCATTCCCAATGCGCTGAGCAGCGCAGCATCGACTGAAGCTTTCGAAAGGGAACGTT

[0470] CCCGGTTACTTAGCTGTAACCTTGTTCCCTGAGAAAGCGGAACGAGATGCTGCGCTGAATTGCCGTACTGAAATATGTCCCAGGACTG

[0471] CTCTTCAGACAAAATGTCCTGTTGATGCACCTGTGGCTTATCTATTTATAGCCCCGTGTTGCGGGCGCGCGCAGATGACGTCATCAAC

[0472] CGAGGCTATATTACCGCCGGGTCAATTCTATCGACGTGTTACACACATTATTCACAGCTGGTCACGAACAAGACGTTTCCCAATGCGC

[0473] TGAGCAGCGCAGCATCTCGTTCCGCTTTCTCAGGGAACAAGGTTACAGCTAAATAACCGGGAACGTTACGTAGGCATATTCCCAGTCT

[0474] GTTCTGTTCTCGCGCTAGGCGCGTTGCATTCTGATTAGATCGTATGGCATACTGCGGAAGGTCAGGGCCCCGGAAAATCGTGCTATAA

[0475] AGCGATTTAGAAATCGCGCACGCTCGATCGTGATTTTATGATGATTTCTATCGCACAGCCCTAGAATGAACTGGCAATGAACAGAAAA

[0476] TAACTCGGGCTTATTTAATTATATATATGAAAAGGTGTTATCATGTTATGACTTAGATATTTTTACATATATTAACAATATTATTATT

[0477] TATTTTAATAGTAATTGGCGGCCCACCTGCAATACCATCGCGACCCACTAGGGGGCAGTGGCCCACAGGTTGAAAACCACTGGTTTAG

[0478] ACTATTAAAGGGGTCATATGATGCGATTTCAAGTTTTCTTTCTCTTTGGAGTGTTACATGCTCTTGGTGCATAAAGAAGATCTGTAAA

[0479] GTTGTAAAGACTAAAGTCTCAAACCCAAAGAGATATTCTTTATAAAAGTTGAGACTCGTCCACGCCCTCCTAAAACGCCTCATTTAAA

[0480] CACGCA

[0481] (SEQ ID NO:20)

[0482] CGACCTGCTGACTGTGCGCTGGGTGCCCTCTGGTACACCCTCCGGGGAAATGGCGGTGCTCGCTCCCCAGCCTCTCGTCGCATCGTCA

[0483] TCTCCGCTAGCTCAACGGCCTCGACGAGCTCTCCCACGGTGCGGTAGGGCGCACAAATACCGGTCCACGACGACACGTTCGGCCACTT

[0484] GGGCGGCACTGGGGCTCCCGGCACGTTCGGCTGCTTGGGCGCGGGCTGGCAACCGACTATTATACTCCCAGGCTCGGAACAATTGGGC

[0485] CGCGGCGATGGGAGACAAACCCACACGCCCCAGTATTTCCTTCAGTAGTTCATCATAGGATTCCTTTTGGCGGGCTGGCATGGAAAAG

[0486] TAGGCCTGTTGGGGTTCCCCGGTTAACAACGGTACCAGTATCCGTGCCCACTCTTCCCGGGGCCAGTCCTCTCAAGCGGCGATGGTTT

[0487] CAAACATTCCCAGATAATGCTCTATATCGTCGTGGACGGTCATCTTTGGCAGGAGCTGGGTGGCTTGCGTGCGGGGGTCCGGCAGCAG

[0488] GGCCCGCTGAGCGGCCGTGAAGCGGAGAGCGGCGACCTCACGCTCTGTTTCGCCCTGTCGAGTGGCCATGTGCTCGACGATCTGCTGC

[0489] TGTCGAATGCTTATTTCCGTCAGGTGCTTGAGAAGCTCTTCCATAGCTGGGGAGGGAGTCACCGCCTGACGAGAAAGCAGAGGGGGGA

[0490] AAAAAAACAACAACTTGGTGAACCAGGACAATCGTGTGAGTCGGTGATCCTTCAGTAATCTGCCCGCATTCTCCACCAGTGTCACGGG

[0491] CTGAAGAATCACACGACAGGGTTTAGTGCAAAAGTGAAGCCCCGGAGGGTGTATTTATTGACAGGTGCTTTGATTTGTGCTGAATCCT

[0492] GTGGTGTCCAGTGCTCGTCCCTCGGTGCCACGTGATCCTGTTTGCCGGCCGGCTGAGTGCAAGGTGACTTGGTGTCCGGTGCTCGGGT

[0493] GGCGGGCTGGTCGATCCACAGCTTTCTGGAGGGACAAGAGACACAACGTTAGTTTCAGTCATCTGAAGATCCTCTCCTCCTTGTGTCA

[0494] CCTTCAGGCGCAGCGTTTATAGTCCTCTCCTCATCCGCTTCAGCTGGGACCGATCAGCCCGCTGTGATTGCGTGCAGGTGAATCTCCC

[0495] TCGTTGCCAGGGCGACGCTAATAGGTGCCCAGGACACGGCTTACAATACTTAAGTAAAGTTCAAGTATATTTTGAATTTTTGTAAGTA

[0496] TAAGTCAAGTATACTTAATTGTCATTATAAATATATATCTTAGAAGTACATAAAGCCCATTTCTGAGAAGTACCATAAAAAGTAAACT

[0497] AAAAGTATACTTTCCTATTTTTTAGTTTAAAATAAGTATACTAATAGCACACTTGAATAAACTTCTTTTTCGTAAGGGTAGCTTCACT

[0498] CATTGATTCCGTTGAGGACGATCCAGCTTCCACAGGCCCCATGATAGATGTTCCTTCCCCAGCAGGTATATCCGCGGTCAGCACTGCA

[0499] TCGGCCAGACCGACCTCAGACGATTTTACAGTGAGCCTATCTTCCTCATTTGCAGCACTATCCTTATTACCTCCAGCTGCGTTACTCT

[0500] TGTCAGGGCATGAACGGATTAAGTGGCCTGATTTATTGCATCCGAAGCATTTCATTTTGTCAGTAAAACACTACATATTCAAAATCGTC

[0501] CACACGGAAATTTAGTGCCAAGTCCAGTTCAGCGTCGTCTTTGATTATCATAAAAGCAAATCTCCTAATGAAAAAATATGTTTCAAT

[0502] AAAGGAGACTCGCACCCGATTGCAATCTTTTTAATCGGTGAAACCAACTTTCCATAATGTGAAAGCACCTGCATCACAATATTATCAC

[0503] TAAGGAAAGGGGGGATATTCAATATTGTGACTCTCTTTGATGGTAACATGAGAGGCAAAACAGATGTAAGTATTTCATCAATGATTAT

[0504] ACTTCGCGCAACCACCTCATTTGCTCTTTCTGCCGTATTCAAAAAAATCATGGTCGTGTTATTCATTCTGGATGCAGAGAGAATATT

[0505] TTGATGGCCAACAACTTCTCCTACACCCAGACAGCACACGGATACTATCTTGACTCTGTGACGCAATGTGAGGGGAATCAAGCCCATTA

[0506] TCACCCTGAGCAAACAAAACACACACAAGATAAATATTAAATCAAATAAACAAACTTAGACGTTAAAAAAAATTAAATAAATTTACA

[0507] TTTACGCATTTAGCAGACGCTTTTATCCAAAGTAACTTACAGTGCATTCAGGCTAACATTTTTTGACCTAACATGTGTTCCCTGGGAA

[0508] TCAAACCCACTACATTTTGCGCTGTTAACGCAATGCTCTACCATTGAGCCACAGGAACACACAAAATAAGGAAACACACAAAAAAGCA

[0509] AATACACGCTCTCACACGCACTCCACAAACGCCCATGCATGCGCAAAGAGAGAGAGATTAGATCAGTTTATCATTATGGCAGTTATTG

[0510] ACTCAGGAATGGGAGTGAAGTGTTCAGAAAAGTCAGGGGGGAAACGTCCTTTTCGCGATATACTTGTCCATCTATGTATAATTTGTCC

[0511] ACTGTAATGATTGCTCTTTTTCCTTCATTTATTTTGTTTTCATATTGGTAAAAGTTGCTTTCAATGTTCAAGAATGTCCTTTGGGTAT

[0512] TGTTAATTTAGGGCCATAGTTTGTGCCTTTAAGTTGTCTGCCTTGCTTTTGAACCAGTTCTGTGGTTTATAGTGTTCAAATTTTGCG

[0513] ATGATTGGTCGTGGTTGGTTGTTGTTTTGAGATCTGATACGGTGAACACGGTGAAAGGTGGTGATCTCTTCAGTTTTGGCTGGTAATT

[0514] TGAGTTGTTTAATCATAAAGTCTTTGACTGATTTCGCGGGGTCATCTGGAGTTTGTTCATGGATGACTGTGAAAACTAAACTGTCCCT

[0515] CGTGCTGCGCATTTGCAAGTCCAAAATGTTTTCTTTCATGGTTTTGTTTTCTGCAACAACAGAAGTGAGTCAGTGAACTGAATCCTTT

[0516] AAAAAGTTATTTTCTTTAGTGAGAGTGTCTATATGTCCTTGGCTGAATTCTAAGCTGTGCCACAATTTCTGGAATTCCTTGTGTATAA

[0517] CTTCAAAATGATATTTGTGCATTTTTCTAAATGATATGTAAATCTTTCTGTTACCATTCGTTCCATTGTTTTCTCTAGTTGTAAAGTT

[0518] AGTGCTACGCCCATAGTGTATACGTCTATAGTGTTACGCCCATGGACTGTTTTGTGTTTGTTTTCCTCCCCCATGTGCTCCATGTCCT

[0519] AGTTTTCTCCCGTGTTTCCTTGTGTCCATATTTGGTTCTTCATCTTCCTGTTCCCATTGAGTTACATTTGTTTCAGCTGTGTCGTTGC

[0520] CCACTGCAAAAAAAAAAAATTAACTGACCCCGCTATTGTTGGGTTAATAACTTAGTACTCAGAAGCTAGATTGTTAACGGTATTTATT

[0521] GAATGAACTAGGGCTGTGCGATATGAAAAAAAAAAAAAAAACCTATCATGATTTCTTTGATCAATTTTGCGATTTTGACACACACAGA

[0522] TATGCTTTACAGTCATAAATGCATTCAGGATGAATTTGAAACATATTTCCAAAAGAAAACCAATTAGAGCTTTATCAAAAAGTTGTAA

[0523] CGTCTCTAGAACAGACACAGTCAAAATAATCACTATAGTAAAGGTGTAACAAAATTTCTAGACTTATGGCAAAAAATATAAATAAAT

[0524] AAATCCTCAGTCCAGGGACTTTTTTGCCATACATTGTTTACAGAGCTCATTAATTGTAGCGGTGTCGCAGGTGTTGAAATAGATTTGT

[0525] TATACATTATACAGGTTCACACGTACTCCGTCAGCAGTGCGTAAATAGTATGTGTATTCGGTGCAGAAGCAGCAGCGAGAGCGCATTA

[0526] TTGTAACGCGAAAGCACATTAAATTAATGCATGAGCGCGTATCTATCCGCCCGCACGCAGATTTCCTCTGCTCTGTCACAAAACCAGA

[0527] CGCGTGTGCTCCGATACATGCTGCTCTCGCTCGGAGAGAGTGCGCGCACTTAAAAACATGTCTCCTCTCACTTAAACTGCGTCCTGTGC

[0528] ACTCTCTCTATGCTCATGTGCTAGATATTATTTTAGCATGTTTTTATTTCTAGCCTTTTACCGCGTGCAGTGTGAACGCTCTGATCCG

[0529] TTAACATGGGTTTGGAAAAAAAGGCGCATCACAGACAGTGTGTGTGAACCTGGAGTTCCCTTTCGAAAGCTTCAGTCGATGCTGCGCTG

[0530] CTCAGCGCATTGGGAAACGTCTTGTTCGTGACCAGCTGTGAATAATGTGTGTAACACGTCGATAGAATTGACCCGGCGGTAATATAGC

[0531] CTGGGTTGATGACGTCATCTGCGCGCGCCCGCAACACGGGCTATAAATAGATAAGCCACAGGTGCATCAACAGGTCTTTTGTCTTCA

[0532] GATCATTCTGTGCATGTGTGCGTCAGGAAGATTCTTTTTGTCTACTACAGATCTTCGTACGATGACCCAACGAAACAGTAAGTGTTGT

[0533] GTTCCTCCATGCTCTCGTCCTATGTATGAGCTGGATACGCATGATTACTGTTTTGTTTGTTTGGGGGAAGAGCACGCGGTTCTGGCTT

[0534] TAGAGACGGGCGAGTGCGAGCATTGTGAACTGCTCTCAGTGAAGATGCTTCGTGCTCGTCTGAACTATTTTCAGACCGCACCCACCCTT

[0535] TTCGTCGGAGGGCTTCCGTGCGGGTCTGCGTGACGAGCGAGCGACGGGCCCGTCCCTTTCGCTTACAGTGTCACCAGATCCACGCATC

[0536] CTCTCTCGTGATCTCGAAGCGTGCTCCGGTGCTTCTTCGATTCACGAGGAGGATGATATATCTCTTGAGTCTTCGGGCGATGACCAGG

[0537] CCGCCTCTGAACGCTCCTCTCGGAGAGAAATCGGTCGAGGAGCTGCTCGAGGTGGTTACTCGCGCGGTGGACAGGCTGAAGCTTGA

[0538] CTGGCCACGCGACCAAGAGACCCCCAAACGTAGTAAGCTGGAGGATAGGTTTCTGTCGGGTGGTAGGAGAGAGACCGCAACATCAG

[0539] TCATTCCCCTTTTTCGAGGACCTCCATGATGAACTGTCGAAGTCATGGAGCAAACCATATACTTCCCGAATCTTTGTGCCCTCGACGAT

[0540] TGACTTATCGTGGATGCAAAGTCACGGGGGTATTCGGAGATGCCTCGGTTGAAGCGTCGCTTGCGAGCTATCTCTCGCCTGAATCTG

[0541] CATCCTCGGTGAAGAAACCTACTCTCCCCACTAAACCTTGTAGAATTACATCATCGCTAGTGGGTAAAGCTTATCAAGCTGCAGGTCA

[0542] GGCTGGTGCTGCGCTGCACACTATGGCAGTGTTACAGGCATACCAGGCTGACCTATTGAAGGACTTGAGTGTGGGCAGTACAATCGAT

[0543] GAGGAAGCATTCGCTGAGCTTCGTCGGGCCACAGATTTGTCTCTCCGGGCGACCAAGCAGACGGCTTGTGCCATTGGCCGGTCGATGT

[0544] CAGCTTTAGTCAGCACGGAGAGGCATCTGTGGCTTAATTTGACGGGCATTAAAGAGAAGGAACGTTTGTTTCTTTTAGACTCTCCTAT

[0545] CTCTCCATCTGGCCTGTTTGGCGATTCGGTTAATACGGTCGTCGACAGGTTTAGGGAAGTAAAGAAACATGAAGAAGCGTTCGTTCAG

[0546] TTTCTCCCTCGCCGCACTCAAGGGGAGGGGCCATCAGCCACCCAGCCTCGCCCCGGTCCTTCAAAAACCAGGGAGGTTAAAAAGCAGA

[0547] GCGTGGCAGACCGTGCTTCCCCTCGTAGGGATTGGGGACAGGTTCGCCGTGCTCAGCAACCTCCCAAGCCAGACCTCAGGACTTTTAT

[0548] TAATAAGAAGAAGAAGTCCTGACGCCATGGCGCCCGTGCTGGTGGGGGTAGTACCTCACGGGGTGGTGCGCGCTCGAGAGCTTTTCGC

[0549] CCCGCCCCGTTACCCTCACAAAACCCCTCCATCCCCGCCGCTTCTTGTGCCTCGGGGGGCGGGGGTTTCCAGCGAGATATTAGATGTT

[0550] CCAGTGCCTCCTGCCATCATTCTGGACACGGAACATCTAACATCCCCTCAAAAGGAAGTATTGAAATTGGTACCACTCTCAGAGAGTC

[0551] TGGCAGCGTGGAAACTTCTGCCAGGCATTTCTGCATGGATGTTGAGCACAGTACGGATAGGATACAGCATCCAATTTATTCGTCATCC

[0552] TCCACGTTTCAACGGCGTGGTTTCCACTTCCGTGAAACCGGAGCTGATGCAGGTACTGTCTCAAGAGCTACAAACTCTTCTGGGCAAA

[0553] GAGGCCATAGAACATGTTCCTCTTCCACAGAGAGAGTCGGGCTATTACAGCAGATACTTCCTAGTTCCCAAAAAGGGTGGGGGAGTGC

[0554] GTCCAATCTTGAATCTTCGAGGCTTAAACCGTACAATCAGAGCACTCAAGTTCAAGATGTTAACCGTCAAGACGGTCGTGTCGCAAAT

[0555] TCGGCATCGCGATTGGTTTATCACGATCGATCTGAAGGACGCATATTTTCATATAGAGATTTTGCCACAACACAGGAAATTCTTGAGG

[0556] TTCGCTTTCGGGGGCGAAGCATACCAGTTTCGGGTTCTTCCTTTCGGCCTAGCCTTATCACCCCGCACGTACACAAAATGCATGGATG

[0557] CAGCGCTGGCTCCATTACGACTCCAGGGCATTCGCATTTTGAATTATATCAACGATTGGCTGATACTAGCGCAATCGCGAGAGATGGC

[0558] GCTACAACACAGGGACATCGTGTTAGCTCATCTAGTTTCTCTGGGGTTGAGACTCAACACCGAGAAGAGTGTTCTCTGTCCGGCCCAG

[0559] AGAACGACTTATCTCGGGATCGTTTGGGATTCGATCACGATGCGGGCACAACTGTCTCCCGCTCGGATCGAGACCATTCAGCAGACCA

[0560] TGAGCAAGGTCAGGCTAGGCCAGGATCGCACTGTTCGTCAGTATCAAAAGATGTTAGGTTTCATGGCTTCAGCATCCACGGTGATTCC

[0561] TTTGGGGCTGTTACACATGAGACCGTTTCAGTTGTGGCTAAAAGCCAGAGGATTTCATCCGAGAGCCAATCCTCAAAGGCAAATAAAA

[0562] GTGACGTGCCGCGGGCTTCGTACACTATCTCTGTGGCTCAGACCCCGGTTCCTTGCCTTGGGTCCCACTCTAGGGGCACCGTGTCGTC

[0563] GCAGACTGCTAACGACAGATGCCTCCCTGTTGGGCTGGGGAGCAGTCTTGGATGGCCACCCAGCTCAAGGGGAATGGGGGGGTCATCA

[0564] GCTCGATTGGCACATCAATTGCCTCGAGCCGATGGCCGTATTTCTGGCTCTGAAATATTTCCTCCATCATTTGAGAGACTGTCATGTT

[0565] CTAGTACGGGTGGACAGCACAGCAACAGTCTCGTATATAAATCACCAGGGGGGTCTGCGCTCACGCAATCTGAACAAGATAGCGAGGC

[0566] AGATTTTTCTTTGGGCCCAGGACAAGCTCCTGTCACTCAGGGCAGTTTACATTCCGGGGCGTTGGAATGTGGGAGCGGATTTACTGTC

[0567] CAGACAGACACTTCCGACAGGGGAATGGAAACTCCACCCAGAGGTAGTGAAACAGATTTGGGAAAAATTTTACGAAGCAGAGGTGGAC

[0568] CTCTTCGCCTCCCATCAGACAGCGCAATGTCCCCTCTACTTCTCTCTGAGTCACCCAGCCCCCCTGGGTCTGGATGCGATGGCGCACA

[0569] CATGGCCCAGAATGCGCCTGTATGCGTTTCCTCCAGTTTCTCTGCTCCCGGGAGTCCTAGCCAGAGTTCGCCAACAAGGGTCTTGCCT

[0570] CTTGCTGATAGCGCCACGTTGGCCGAACAGGGTATGGTTTTCGGAGATAATATCCATCCTCGACGGCTCGCCATGGGCGATTCCGGAG

[0571] AGGAGGGACCTTCTGTCTCAGGCAGGGGGTACGATATTCCATCCCAGGCCCGACCTGTGGAATCTTCATGTTTGGCCCCTGAAGGGTA

[0572] CCAGCTGAGGAACACAGGGGTGTCGCCGGGTGTTATTGATACCATCCTTAGTGCTAGGGCTTTCTCCACCAGACAGAGTTATGCCAGT

[0573] AAATGGGGTGTCTTTGACAGGTGGTGTGTGGTACACAATGTAGATCCAGTCAACTGCCATATTGCTTCAGTTCTGGACTTTATGCAAG

[0574] AGAAATTGTCAACAGGCACATGCCCTGCTACTCTTAAGGTTTATGTGGCCGCTCTTTCGGCTTGCCACGCCTTGATTGACGGGATGCC

[0575] ACTCGGGAGACACCCTCTGCTCTCTCGCTTTCTTCGTGGGGCCAGACGACTGAGGCCTACAGTAAAAACCAAGATGCCTTCTTGGGAC

[0576] TTAGCTATAGTTCTCGAGGGTCTGGTTGAAACCCCCTTTGAAACTTTAGAGTCAGCGTCTGATAGACTTCTAACTCTAAAAATGTTTT

[0577] TTCTCATGGCAATAACTTCTTTGAAGAGAATTGGGGATATGCAGGCTCTGTCTATCTCACCATCATGCTTAGACTTTGCCCCAGGGAG

[0578] CGTGAAAGTGATTCTGCATCCTCATCCTGATTACCTGCCTAAGGTTCCGTTTTCGGCTGTACATCCGGTCATTCTAGAGGCCTTCTGT

[0579] CCTCCGCCATTCGCAACGCCGGAGCAGGAGAAATCTTATAGACTGTGTCCAGTCCGTGCTCTTCAGACTTACGTCCACTGCACTAGCC

[0580] AGTGGCGTAAGTCGGAGCAACTGTTCGTCTGTTATGGTGGTGGTAACAGAGGAGCAGCTGCCACCAGGCAGACCATGTCTCACTGGGT

[0581] CAGGGATGCTATTGCTTTGGCTTATGAGGCGCGCGGTCAAGCTTCGCCTATAGGTCTTAGAGCTCACTCCACAAGGGGGGTCGCCTCC

[0582] TCTAGTGCTTTAGCAAGGGGTGTCCCCTTACAACAGGTTTGTGATGCGGCAGGTTGGTCCTCTCTGCACACATTCATAAGATTTTATA

[0583] GTTTGGATGTCCATGCTACTCCGGGCTCTCATGTCCTTGAGTCAACATCACAAGCTAATGTCTGAGGCCTTCTTGTGGTTTGGTAGCA

[0584] CACCCGCACAACCTTAGGGGTCCAGACATTTTCAAGCATGGCGGCGTGGGTATTCTCATTCCCAATGCGCTGAGCAGCGCAGCATCGA

[0585] CTGAAGCTTTCGAAAGGGAACGTTCCCGGTTACTTAGCTGTAACCTTGTTCCCTGAGAAAGCGGAACGAGATGCTGCGCTGAATTGCC

[0586] GTACTGAAATATGTCCCAGGACTGCTCTTCAGACAAAATGTCCTGTTGATGCACCTGTGGCTTATCTATTTATAGCCCCGTGTTGCGG

[0587] GCGCGCGCAGATGACGTCATCAACCGAGGCTATATTACCGCCGGGTCAATTCTATCGACGTGTTACACACATTATTCACAGCTGGTCA

[0588] CGAACAAGACGTTTCCCAATGCGCTGAGCAGCGCAGCATCTCGTTCCGCTTTCTCAGGGAACAAGGTTACAGCTAAATAACCGGGAAC

[0589] GTTACGTAGGCATATTCCCAGTCTGTTCTGTTCTCGCGCTAGGCGCGTTGCATTCTGATTAGATCGTATGGCATACTGCGGAAGGTCA

[0590] GGGCCCCGGAAAATCGTGCTATAAAGCGATTTAGAAATCGCGCACGCTCGATCGTGATTTTATGATGATTTCTATCGCACAGCCCTAG

[0591] AATGAACTGGCAATGAACAGAAAATAACTCGGGCTTATTTAATTATATATATGAAAAGGTGTTATCATGTTATGACTTAGATATTTTT

[0592] ACATATATTAACAATATTATTATTTATTTTAATAGTAATTGGCGGCCCACCTGCAATACCATCGCGACCCACTAGGGGGCAGTGGCCC

[0593] ACAGGTTGAAAACCACTGGTTTAGACTATTAAAGGGGTCATATGATGCGATTTCAAGTTTTCTTTCTCTTTGGAGTGTTACATGCTCT

[0594] TGGTGCATAAAGAAGATCTGTAAAGTTGTAAAGACTAAAGTCTCAAACCCAAAGAGATATTCTTTATAAAAGTTGAGACTCGTCCACG

[0595] CCCTCCTAAAACGCCTCATTTAAACACGCA

[0596] (SEQ ID NO: 19 represents the sequence before insertion, and SEQ ID NO: 20 represents the sequence after insertion).

[0597] The genomic sequence of DEL Chr44:16600200 is shown below, and the mutation type is deletion.

[0598] (SEQ ID NO:21)

[0599] TGCCAAATTATGTCATTTGATTATTATTTTTTTTTTTAATTTCTGTTATCCTGGAAAAATGTATCACAAAAATACTAAGGAGCATTG

[0600] TTTTCATTATGACATTAATAAGAAGAAATGTTTCTTGAGCACCATTTCCGTAGGATTACTTGACAAGTAATATTAATTGAAAATGCCA

[0601] TTTCTAAACAAAAAGAGTCTCACACTAGGGTACATATCATTGTGTT

[0602] (SEQ ID NO:22)GCTAAACCACATATTTG

[0603] (SEQ ID NO: 21 represents the sequence before deletion, and SEQ ID NO: 22 represents the sequence after deletion)

[0604] The present invention discloses a method for identifying structural variation of fish genomes based on a graph pan-genome. The present invention constructs a graphical pan-genome map of 10 carp germplasms by performing third-generation sequencing on mirror carp "Longke No. 11", carp "Longke No. 12", German mirror carp, Yuxuan Yellow River Carp No. 2, Furui Carp No. 2, Jianli No. 2, and Yuanjiang carp, and performing pan-genome analysis on the genomes of purse red carp, Songpu mirror carp, and Heilongjiang carp with existing third-generation sequencing data. Subsequently, 266 carp from 5 germplasms, including carp "Longke No. 12", Songpu mirror carp, mirror carp "Longke No. 11", Yuxuan Yellow River Carp No. 2, and Jianli No. 2, were subjected to second-generation resequencing. The resequencing results were aligned to the graph pan-genome for identification of presence / absence variations (PAVs), and PAV-GWAS analysis was performed with quality trait phenotypes, thereby identifying multiple PAV molecular markers related to carp quality traits. The method provided by this invention, based on a map-pan-genome approach to identifying structural variation in fish genomes, can be used to detect structural variation in important economic traits in fish and select fish varieties with superior traits such as intensive high-yield, high-quality, and disease resistance. The map-pan-genome demonstrates greater sensitivity and accuracy in detecting structural variation (SV). Compared to traditional single linear reference genomes, the map-pan-genome can more effectively identify and characterize structural variation, and has broad application prospects in molecular marker-assisted breeding and genomic selection breeding of fish.

[0605] The number of modules and processing scales described herein are used to simplify the description of the present invention. Applications, modifications and variations of the present invention will be apparent to those skilled in the art.

[0606] Although the embodiments of the present invention have been disclosed above, they are not limited to the applications listed in the description and implementation methods. They can be fully applied to various fields suitable for the present invention. For those familiar with the art, additional modifications can be easily implemented. Therefore, without departing from the general concept defined by the claims and the scope of equivalents, the present invention is not limited to the specific details and illustrations shown and described herein.

Claims

1. Application of insertion mutation of APPL2 gene PAV sequence in breeding carp with high quality trait of carp intramuscular fat content, characterized in that: The nucleotide sequence of the insertion mutation of the PAV sequence of the APPL2 gene is shown in SEQ ID NO: 16, and the nucleotide sequence of the wild type of the APPL2 gene before the insertion of the PAV sequence is shown in SEQ ID NO: 15.

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