Schizothorax fish genetic relationship identification method based on SNP molecular markers

Abstract

The present application belongs to the technical field of aquatic animal molecular breeding and genetic detection, and particularly relates to a Schizothorax fish genetic relationship identification method based on SNP molecular markers. The method comprises the following steps: performing SNP typing detection on samples to obtain genotype data; calculating IBS similarity and constructing a heat map; calculating genetic distance and constructing a phylogenetic tree; and determining genetic relationship according to the heat map and the phylogenetic tree. A combination of SNP sites obtained through multi-parameter joint filtering and linkage disequilibrium pruning is also provided. The present application is suitable for Schizothorax fish family management, parentage identification and evaluation of the effect of releasing and breeding.

Description

Technical Field

[0001] This invention belongs to the field of aquatic germplasm resource protection, breeding and genetic testing technology of rare and endemic fish species in the upper reaches of the Yangtze River, and in particular relates to a method for identifying the kinship of Schizothorax species based on SNP molecular markers. Background Technology

[0002] Fishes belonging to the genus *Schizothorax*, belonging to the order Cypriniformes, family Cyprinidae, and subfamily Schizothoraxinae, are important economic and endemic fish resources in the upper reaches of the Yangtze River and its tributaries. In recent years, due to factors such as cascade hydropower development in the basin, river blockage, habitat fragmentation, changes in the aquatic environment, and overfishing, the wild populations of *Schizothorax* species, including *Schizothorax davidi* and *Schizothorax prenanti*, have experienced a sharp decline. *Schizothorax davidi* has been listed as a Class II protected animal in China. Artificial propagation and release is an important means of restoring natural populations and maintaining population numbers. In this process, family management, parentage testing, and evaluation of release effects are key links to ensure the scientific validity and effectiveness of releases. Currently, fish kinship identification mainly relies on the following technical methods:

[0003] Traditional morphological marking identification methods primarily rely on morphological traits such as body length, weight, body color, and fin count to differentiate families. This typically involves physical isolation or external marking (such as fin clipping, tagging, and fluorescent marking) combined with aquaculture records for pedigree tracing. However, morphological marking is highly susceptible to environmental factors (nutrition, temperature, and stocking density), and the same genotype exhibits significant phenotypic differences under different environments, making it impossible to accurately distinguish full-sib families. Physical isolation is difficult to implement in large-scale breeding and easily leads to family confusion. Fin clipping and tagging methods damage the fish, potentially affecting survival rates and growth performance; furthermore, the tags are prone to detachment and misreading, making them unsuitable for recapture identification and migration tracking of released individuals.

[0004] Microsatellite (SSR) markers are DNA molecular markers based on 1-6 tandem repeat sequence length polymorphisms. In fish paternity testing, 10-20 highly polymorphic SSR loci are typically screened, and paternity is determined by PCR amplification and capillary electrophoresis typing. However, SSR markers have a high mutation rate (approximately 10⁻³ / locus / generation), which can easily lead to paternity exclusion errors due to allele mutations. Typing relies on capillary electrophoresis and fragment length determination, making high-throughput automated detection difficult, resulting in low efficiency and high cost. Allele determination suffers from the "shadow band" phenomenon, which is highly subjective and leads to poor comparability of results between different laboratories, making standardization challenging. Currently, the SSR marker system for Schizothorax species is incomplete, and there is a lack of validated standardized paternity testing protocols.

[0005] Single nucleotide polymorphism (SNP) markers, as third-generation molecular markers, have a low mutation rate (approximately 10). -8 With advantages such as high genetic stability and ease of high-throughput genotyping, SNP parentage identification systems have been established in livestock, poultry, and some fish species. However, existing SNP parentage identification technologies are mostly developed for livestock, poultry, or a few model fish species. Due to significant genomic differences between species, locus sequences and genetic parameters vary considerably, making them unsuitable for direct application to the genus *Schizothorax*. Furthermore, the whole-genome information of *Schizothorax* is incomplete, lacking species-specific reference genome information, making SNP locus screening, verification, and annotation difficult. The number of SNP loci, chromosome distribution, and genetic parameters selected by existing technologies have not been optimized for the genomic characteristics and population genetic structure of *Schizothorax*, resulting in poor cross-population applicability. Additionally, there is a lack of comprehensive identification methods combining IBS similarity analysis and phylogenetic verification, making misjudgments possible with single methods.

[0006] The table below compares three methods: morphological markers, SSR microsatellites, and general diploid fish SNPs, listing their respective accuracy rates, cumulative exclusion probabilities, detection costs, and throughput limitations, thus clearly highlighting the shortcomings of existing technologies.

[0007] .

[0008] Currently, there is no standardized SNP parentage identification system suitable for the genomes of tetraploid schizothorax and tetraploid schizothorax, either domestically or internationally; there is no standardized identification process using "IBS similarity heatmap + NJ phylogenetic tree double cross-validation"; and there is no supporting genetic traceability management scheme for the entire process of aquaculture propagation and release, representing a technological gap in the industry. Conventional SNP screening standards for fish are adapted to diploid genomes, and directly applying them to tetraploid schizothorax can lead to problems such as genotyping bias, locus linkage redundancy, and insufficient family differentiation. Existing technologies lack a complete set of screening parameters suitable for tetraploids. In conjunction with the ten-year fishing ban in the Yangtze River and the regulatory policies for aquatic organism propagation and release, the industry currently lacks standardized technologies for tracing the source of seedlings, monitoring the genetic diversity of wild populations, and providing early warning of inbreeding depression risks. This invention specifically addresses this urgent need in the industry.

[0009] Therefore, there is an urgent need to establish a highly accurate, stable, and efficient method for identifying kinship among Schizothorax species, so as to accurately identify the pedigree and parentage of offspring individuals and provide technical support for the protection of genetic resources of Schizothorax species, evaluation of the effects of stock enhancement and release, germplasm management, and genetic breeding. Summary of the Invention

[0010] Based on the above analysis, this application discloses a method for identifying kinship among fish of the genus *Schizothorax*. On one hand, it utilizes a complete SNP screening system adapted to tetraploid *Schizothorax*, employing a 6-parameter combined filtering + LD pruning + chromosome uniform distribution to screen for high-resolution specific markers. On the other hand, it constructs a standardized judgment process with dual verification using IBS quantitative similarity and NJ phylogenetic tree hierarchical clustering, setting conflict review rules to eliminate systematic errors from single analysis methods. Furthermore, it integrates the entire chain of parental markers, family breeding, genotyping, wild recapture and tracing, genetic archives, and inbreeding early warning to form a complete propagation and release management plan. This method includes the following steps:

[0011] (1) SNP genotyping was performed on the target Schizothorax fish samples to obtain SNP genotype data; wherein, the SNP genotyping was performed on a set of SNP locus combinations, the SNP locus combinations were evenly distributed on the chromosome and obtained by multi-parameter joint filtering and linkage disequilibrium pruning.

[0012] (2) Based on the SNP genotype data, calculate the IBS similarity among individuals and construct an IBS heatmap;

[0013] (3) Based on the SNP genotype data, calculate the genetic distance between individuals and construct a phylogenetic tree using the neighbor-joining method;

[0014] (4) Determine the kinship and family affiliation between offspring individuals and their parents based on the IBS heatmap and the phylogenetic tree.

[0015] Furthermore, the multi-parameter joint filtering includes minimum allele frequency filtering, genotyping success rate filtering, Hardy-Weinberg balance test, biceleste screening, heterozygosity screening, and polymorphism information content screening.

[0016] Furthermore, the parameters for the minimum allele frequency filtering are MAF > 0.4, the parameters for the genotyping success rate filtering are > 99%, the parameters for the Hardy-Weinberg equilibrium test are P > 0.0001, and the parameters for the linkage disequilibrium pruning are window size of 50 SNPs, step size of 10 SNPs, and r2 threshold of 0.1.

[0017] Furthermore, the target Schizothorax fish samples are obtained by identifying and marking individual Schizothorax parent fish, establishing full-sib families according to a targeted mating design, isolating and hatching them, and collecting parent and offspring samples.

[0018] Preferably, the individual identification marker is a PIT marker, the directional mating design is a 1:1 male-female pairing, and the isolated incubation involves placing the fertilized eggs of each full-sib family in an independent incubation device for incubation.

[0019] Furthermore, in step (1), the SNP genotyping detection is achieved through whole-genome resequencing, targeted capture sequencing, or competitive allele-specific PCR.

[0020] Preferably, the SNP genotyping detection is achieved through whole-genome resequencing.

[0021] Preferably, after the whole genome resequencing, the sequencing data quality control and reference genome alignment steps are also included.

[0022] Furthermore, after step (1) and before step (2), the method further includes: calculating the cumulative exclusion probability based on the SNP genotype data; the cumulative exclusion probability includes the cumulative exclusion probability of a single parent and the cumulative exclusion probability of both parents.

[0023] Furthermore, in step (2), the IBS similarity matrix is ​​calculated using the plink software, and the IBS heatmap is drawn using the pheatmap package in R language; in step (3), the genetic distance matrix is ​​calculated using the VCF2Dis software, and the phylogenetic tree is constructed using the neighbor program of the phylip software.

[0024] Furthermore, the schizothorax species mentioned are either *Schizothorax fasciatus* or *Schizothorax fasciatus*.

[0025] The second technical solution of this application discloses a combination of SNP loci for identifying kinship among fish of the genus Schizothorax. The combination of SNP loci is uniformly distributed on chromosomes and is obtained by multi-parameter combined filtering and linkage disequilibrium pruning.

[0026] Furthermore, the schizothorax species mentioned are either *Schizothorax fasciatus* or *Schizothorax fasciatus*.

[0027] The third technical solution of this application also discloses the SNP site screening method for schizothorax fishes described in the second technical solution, including the following steps:

[0028] SNP typing data were obtained from multiple full-sib families of the genus *Schizothorax*.

[0029] The SNP genotyping data is subjected to multi-parameter joint filtering and linkage imbalance pruning to obtain the filtered SNP locus set;

[0030] (c) Following the strategy of uniform chromosome distribution (at least 3 SNPs are screened on each chromosome, with a physical interval of ≥50kb between sites), sites are selected from the screened SNP site set and combined to obtain a combination of SNP sites for kinship identification.

[0031] Furthermore, in step (b), the multi-parameter joint filtering includes minimum allele frequency filtering, genotyping success rate filtering, Hardy-Weinberg balance test, biceleste screening, heterozygosity screening, and polymorphism information content screening.

[0032] Furthermore, the parameters for the minimum allele frequency filtering are MAF>0.4, the parameters for the genotyping success rate filtering are greater than 99%, the parameters for the Hardy-Weinberg equilibrium test are P>0.0001, and the parameters for the linkage disequilibrium pruning are window size of 50 SNPs, step size of 10 SNPs, and r² threshold of 0.1.

[0033] Furthermore, in step (c), the chromosome uniform distribution strategy is as follows: sorting by nucleotide diversity from high to low, and selecting multiple sites with the highest nucleotide diversity from each chromosome.

[0034] Furthermore, in step (a), the SNP genotyping data is aligned to a reference genome, which is the genome of *Schizothorax laniceps*.

[0035] And, a kit for identifying kinship among fish of the genus *Schizothorax*, comprising: DNA extraction reagent, PCR amplification buffer, DNA polymerase, site-specific primers or fluorescent probes, positive standard DNA control, negative blank control, and instructions for use.

[0036] A method for tracing and comparing wild-captured individuals of the genus *Schizothorax*, constructing population genetic profiles, dynamically monitoring inbreeding coefficients, and managing early warning of parental pairings is provided. The method described in the first technical solution is used to identify the kinship and determine the pedigree of *Schizothorax* (IBS similarity ≥ 0.95 for full-sib individuals and IBS similarity < 0.90 for individuals from unrelated different pedigrees).

[0037] Furthermore, the management method also includes: tracking the released individuals based on the family attribution determination results, and assessing the survival rate and migration path of the released individuals.

[0038] Furthermore, the management method also includes: constructing a population genetic profile based on the kinship identification results, and conducting genetic diversity monitoring and inbreeding early warning.

[0039] Compared with the prior art, the present invention has the following beneficial effects:

[0040] (1) This invention establishes a method for identifying SNP kinship in fish of the genus Schizothorax, filling the technical gap of lacking a dedicated molecular marker identification system for this species.

[0041] (2) High information content SNP loci combinations were obtained by screening through multi-parameter joint filtering and chromosome uniform distribution strategy. The loci are widely distributed and have high genetic stability, which can provide reliable genetic information for kinship analysis.

[0042] (3) Based on the dual verification of IBS similarity heatmap and NJ phylogenetic tree, the degree of kinship between individuals can be intuitively displayed, improving the visualization and reliability of identification results and avoiding systematic errors of single method.

[0043] (4) It has high detection efficiency and good repeatability, and is suitable for the kinship analysis of large-scale samples. It can be widely used in the fields of artificial breeding, family management, genetic resource protection and genetic effect evaluation of the release of fish of the genus Schizothorax.

[0044] (5) The SNP locus combination and identification method established in this invention can effectively reflect the genetic differences among individuals of the genus Schizothorax, providing an important technical foundation for subsequent family construction, parent selection, genetic record establishment and molecular-assisted breeding. Attached Figure Description

[0045] To more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings used in the description of the embodiments of the present invention will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0046] Figure 1 This is a flowchart of the DNA extraction process using SDS lysis combined with magnetic bead purification.

[0047] Figure 2 The first to fifth items in the delta_snp_index list of the 100 SNPs in Example 1;

[0048] Figure 3 The 51st to 100th entries in the delta_snp_index list of the 100 SNPs in Example 1;

[0049] Figure 4 The cumulative exclusion probability (CEP) results for 100 SNPs in Example 1;

[0050] Figure 5 The image shows the IBS thermogram of the schizothorax bream in Example 1.

[0051] Figure 6 This is the NJ phylogenetic tree constructed based on IBS genetic distance in Example 1;

[0052] Figure 7The first to fifth items in the delta_snp_index list of 100 SNPs in Example 2;

[0053] Figure 8 The 51st to 100th entries in the delta_snp_index list of 100 SNPs in Example 2;

[0054] Figure 9 IBS thermogram of the fish *Schizothorax micranthum* in Example 2;

[0055] Figure 10 This is the NJ phylogenetic tree constructed based on IBS genetic distance in Example 2;

[0056] Figure 11 This is the complete technical process of this application. Detailed Implementation

[0057] To make the technical problems solved, the technical solutions, and the beneficial effects of this invention clearer, the invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and are not intended to limit the invention.

[0058] like Figure 11 As shown, the first embodiment of this application provides a method for identifying kinship among fish of the genus *Schizothorax*, including but not limited to *Schizothorax davidi* and *Schizothorax prenanti*, which are endemic to the upper reaches of the Yangtze River. This method is based on SNP molecular markers and combines IBS similarity analysis with NJ phylogenetic tree verification to accurately determine the kinship and family affiliation between offspring and parents.

[0059] Step 1, SNP genotyping: This step aims to obtain high-quality SNP genotype data for the sample to be tested.

[0060] In a preferred embodiment, before SNP typing detection, the process includes pedigree construction and sample collection steps: individual identification and marking of schizothorax parent fish, establishment of full-sib families according to directional mating design and isolated hatching, and collection of parent and offspring samples.

[0061] The individual identification tag can be a PIT (Passive Integrated Transponder) tag. A PIT tag is a passive electronic chip tag based on radio frequency identification (RFID) technology, internally encapsulating a microchip and coil antenna, and externally encased in biocompatible glass. Each tag has a globally unique digital code. After being implanted into the dorsal muscle of the fish, the tag can remain with the fish for life. The code can be read non-contactly by scanning with a handheld reader, without affecting the fish's appearance, swimming behavior, or reproductive performance.

[0062] The preferred directional pairing design is a 1:1 male-to-female pairing. During the breeding season, based on the PIT code information of the parent fish, male and female parents with well-developed gonads are selected and paired 1:1 to establish full-sib families. After injecting spawning induced agents into the paired parent fish, fertilized eggs are obtained through dry artificial insemination. The fertilized eggs of each family need to be incubated in an isolated incubation container (such as an incubation sieve). The preferred incubation conditions are: water temperature 12-15℃, dissolved oxygen 6-8 mg / L, pH 7-8.5, and ammonia nitrogen and nitrite less than 0.01 mg / L. The corresponding parent PIT code and family number are marked on the incubation container to ensure the accuracy and reliability of the family origin information.

[0063] During sample collection, fin tissue or fertilized eggs containing nuclear DNA can be collected from parents and offspring. After collection, the samples should be fixed in anhydrous ethanol, numbered, and stored at -20°C or lower for later use.

[0064] DNA extraction can be performed using conventional methods in this field, such as SDS lysis combined with magnetic bead purification. Figure 1 As shown: Approximately 0.2 g of frozen tissue sample was thoroughly ground using a homogenizer and then lysed using SDS lysis buffer. Proteinase K and RNase A solutions were added before lysis to promote protein and RNA degradation. During lysis, the sample was gently inverted once to improve lysis efficiency. After lysis, the sample was cooled and centrifuged, and the supernatant was transferred to a new centrifuge tube. Magnetic beads were then added to the supernatant to bind the DNA, and the sample was washed twice with 80% ethanol to remove impurities. Finally, 100 μL of nuclease-free water was added, and the DNA was reconstituted at 37°C. After reconstitution, the sample was centrifuged again, and the supernatant was collected as the extracted genomic DNA. The purity of the extracted DNA was determined using a NanoPhotometer (A260 / A280 ratio should be between 1.8 and 2.0), the concentration was determined using a Qubit assay, and the integrity was determined using 1% agarose gel electrophoresis (clear and intact high molecular weight bands should be observed, without significant degradation or impurities).

[0065] SNP genotyping can be achieved through various high-throughput genotyping technologies. In a preferred embodiment, whole-genome resequencing (WGS) technology is used. Since the whole-genome information of *Schizothorax* species is not yet complete, sequencing data can be aligned to a reference genome of a closely related species within the same genus. In this embodiment, the chromosome-level whole genome of *Schizothorax lantsangensis* (NCBI Assembly: GCA_027422415.1) is selected as the reference sequence. This genome is currently the most complete public genome resource in the *Schizothorax* genus, showing close kinship and high genomic homology with *Schizothorax rubiginosa* and *Schizothorax pumilum*.

[0066] The specific process of whole-genome resequencing includes: fragmentation of qualified genomic DNA (0.5 μg DNA per sample as template) (e.g., using Bioruptor Pico for sonication), end repair, adapter ligation (using adapters with barcodes to distinguish between multiple samples), PCR amplification and enrichment, library quality control, single-strand circularization, rolling circle amplification (RCA) to form DNA nanospheres (DNB), and finally, pairwise 150 bp sequencing (PE150) using a high-throughput sequencing platform such as DNBSEQ-T7 to obtain raw sequencing data.

[0067] After sequencing, data quality control and alignment with a reference genome are required. Software such as FASTP is used to filter the raw sequencing data: the average read quality is evaluated using a sliding window; low-quality bases at both ends (average quality below Q20) are pruned; adapter sequences are automatically detected and removed; low-quality reads (more than 40% of bases with a quality value below Q15 or containing more than 5 Ns) are filtered; and reads with a final length less than 50 bp are removed. After obtaining high-quality clean reads, sequence alignment software such as BWA is used to align the clean reads to the reference genome, and the alignment rate, coverage, and coverage depth are calculated. Subsequently, Picard software is used to remove PCR repetitive sequences, and GATK software is used for population-level variant detection to obtain a VCF format file containing SNP information. To ensure the quality of variant detection, quality filtering can be performed. SNP filtering parameters can include: QD < 2.0, FS > 60.0, MQ < 40.0, MQRankSum < -12.5, ReadPosRankSum < -8.0, etc.

[0068] In another implementation, SNP genotyping can also be achieved using techniques such as targeted capture sequencing, SNP microarrays, or competitive allele-specific PCR (KASP). These techniques perform targeted genotyping on the SNP loci combinations screened by this invention, making them suitable for testing scenarios of different sizes and throughput requirements, and offering advantages such as lower cost and shorter turnaround time.

[0069] The SNP genotyping detection targets a set of SNP loci combinations that are uniformly distributed on the chromosome and are obtained through multi-parameter combined filtering and linkage disequilibrium pruning.

[0070] Step 2: Calculation of Cumulative Exclusion Probability

[0071] The cumulative exclusion probability (CEP), commonly used in paternity testing, was employed to evaluate the identification power of marker combinations. Calculations were performed separately for cases where only one parent's information was known. Both parents' information and their information are known. The cumulative exclusion probability under the following conditions.

[0072] For a single SNP site, the exclusion probability is calculated using the following formula:

[0073] Single-parent exclusion probability ( ):

[0074] ;

[0075] in, For the first The frequency of each allele, Represented as the first The frequency of each allele.

[0076] Probability of parent exclusion ( ):

[0077] ;

[0078] in, For the first The frequency of each allele Represented as the first The frequency of each allele The number of alleles (for SNPs, ).

[0079] Cumulative Exclusion Probability (CEP):

[0080] The exclusion probabilities of multiple sites are cumulatively calculated using the following formula:

[0081] ;

[0082] in, For the number of sites, The probability of excluding single or double parents for the i-th site.

[0083] The 100 SNP loci were sorted from highest to lowest PIC value, and the top [values] were calculated sequentially. Each site and This quantitative indicator provides a solid statistical basis for subsequent IBS analysis and phylogenetic tree determination, ensuring that the conclusions of kinship identification have forensic-grade reliability.

[0084] Step 3: IBS Similarity Calculation and Heatmap Construction

[0085] Based on the SNP genotype data obtained in step one, the IBS similarity between all paired samples is calculated.

[0086] IBS (Identity By State) refers to the state where two individuals share the same allele sequence at a given gene locus. For each SNP locus, if two individuals have completely identical genotypes, the IBS value is 2; if they share one allele, the IBS value is 1; and if they do not share an allele, the IBS value is 0. The average IBS similarity between individuals is the arithmetic mean of the IBS values ​​at all loci, calculated using the following formula:

[0087] ;

[0088] in, Let be the average IBS similarity between individuals i and j, and L be the total number of SNP sites used to calculate IBS among individuals. The similarity of alleles i and j at the k-th locus is 1 (same as 0, different as 0).

[0089] Genetic distance is defined as:

[0090] ;

[0091] in, express Let be the average IBS similarity between individuals i and j.

[0092] In a preferred embodiment, the IBS similarity matrix of all paired samples is calculated using the plink software, and an IBS heatmap is generated using the pheatmap package in the R language. In the heatmap, the horizontal and vertical axes represent individual IDs, and the color intensity represents the level of IBS similarity between individuals; the redder (or darker) the color, the higher the similarity and the closer the kinship.

[0093] Step 4: Calculation of genetic distance and construction of phylogenetic tree

[0094] Based on the SNP genotype data, the genetic distance between individuals was calculated, and a phylogenetic tree was constructed using the Neighbor-Joining (NJ) method. The p-distance genetic distance refers to the proportion of nucleotide sequence differences between two individuals. The p-distance genetic distance matrix between individuals was calculated as follows:

[0095] ;

[0096] in, The total number of SNP sites. For the first Individuals at each site and Allele similarity (1 for identical, 0 for different). Based on the distance matrix calculation results, the NJ tree was constructed using the Neighbor program in Phylip software, and finally, the tree diagram was created and beautified using Mega software.

[0097] In a preferred embodiment, the p-distance genetic distance matrix between individuals is calculated using VCF2Dis software. Then, the Neighbor program in Phylip software is used to construct the NJ phylogenetic tree. Finally, software such as Mega is used to beautify and display the tree diagram. The NJ tree reflects the genetic differentiation and evolutionary relationships between individuals through its branching structure; individuals from the same family typically cluster in the same branch.

[0098] Step 5: Determining Kinship and Family Lineage

[0099] Based on the IBS heatmap and the phylogenetic tree, the kinship and family affiliation between offspring individuals and their parents are determined comprehensively.

[0100] Specific determination rules include: In the IBS heatmap, if an offspring individual shows a high degree of similarity clustering (dark color) with a certain pair of parents and other offspring of the same family, and has low similarity with individuals of other families (light color), it indicates that the offspring belongs to that family; In the NJ phylogenetic tree, if an offspring individual clusters with a certain pair of parents in the same high support branch, and is clearly separated from other family branches, it further confirms the offspring's family affiliation.

[0101] When the IBS heatmap and the NJ phylogenetic tree results are consistent, a highly reliable conclusion on kinship identification can be drawn. If a conflict arises, the number of SNP loci can be increased or the sample information can be verified.

[0102] In a preferred embodiment, after obtaining SNP genotype data and before performing IBS analysis, a cumulative exclusion probability (CEP) calculation step may be included. The cumulative exclusion probability for each parent is calculated separately. ) and the cumulative exclusion probability of both parents ( The CEP value is used to evaluate the identification power of the SNP locus combination. A CEP value of 0.9999 or higher indicates that the SNP locus combination has forensic-grade identification accuracy.

[0103] As shown above, the dual validation using the IBS heatmap and the NJ phylogenetic tree avoids systematic errors that may arise from single analytical methods, significantly improving the accuracy and reliability of kinship identification. This method is standardized in operation, highly efficient in detection, and suitable for kinship analysis of large-scale samples.

[0104] The second embodiment of this application discloses a method for screening SNP sites in fish of the genus Schizothorax, which is used to screen for SNP site combinations with high information content, high stability and good genomic representativeness, providing a reliable molecular marker basis for kinship identification.

[0105] Step 1: Obtain SNP typing data

[0106] SNP genotyping data were obtained from multiple full-sib families of the genus *Schizothorax*. In a preferred embodiment, 10 full-sib families were constructed, each containing one parental pair and multiple offspring samples, totaling approximately 50-70 samples. DNA was extracted from the samples, and whole-genome resequencing was performed to obtain raw sequencing data.

[0107] Since the complete genomes of fish in the genus *Schizothorax* have not yet been officially published, in a preferred embodiment, the chromosome-level complete genome of *Schizothorax lancangensis* (NCBI Assembly: GCA_027422415.1) is used as a reference sequence for sequencing data alignment. This genome is approximately 972.4 Mb in size and is highly similar in mitochondrial genome length and base composition to those of *Schizothorax scutellarioides* and *Schizothorax davidii*. Phylogenetic analysis shows that the two species are closely related and have high genomic homology, making it suitable as a reference genome for sequencing data of *Schizothorax scutellarioides* and *Schizothorax davidii*.

[0108] The filtered clean reads were aligned to the reference genome using bwa software. Picard software was used to remove PCR repetitive sequences and discard low-quality alignment data with an alignment quality of less than 20. Population-level variation detection was performed using GATK software to obtain raw variation site information including SNPs and InDels, which was saved in VCF format.

[0109] Step 2: Multi-parameter joint filtering

[0110] The original SNP dataset is then subjected to the following multi-parameter joint filtering in sequence:

[0111] (1) Minimum allele frequency (MAF) filtering: Retain loci with MAF > 0.4. This parameter ensures that the retained loci have high population polymorphism and rich information content. The vcftools software can be used, with the parameter set to maf 0.4.

[0112] (2) Genotyping success rate filtering: Loci with an individual genotyping success rate greater than 99% are retained. This parameter ensures that loci can be successfully genotyped in the vast majority of samples, resulting in high data integrity. The vcftools software can be used, with the parameter set to max-missing 0.99.

[0113] (3) Hardy-Weinberg equilibrium (HWE) test: Loci that pass the HWE test are retained. This parameter excludes loci affected by selection pressure, inbreeding, or technical errors, ensuring that the loci meet the population genetic equilibrium hypothesis. The vcftools software can be used, with the parameter set to hwe 0.0001.

[0114] (4) Biallelic SNP screening: Biallelic SNPs are retained. This parameter excludes multi-allelic loci, simplifies genotype determination, and improves typing accuracy. The vcftools software can be used with the parameters set to min-alleles 2 and max-alleles 2.

[0115] (5) Heterozygosity screening: Retain loci with heterozygosity higher than the population average. This parameter prioritizes loci with higher heterozygosity to improve their discriminative ability and information content. Plink software can be used with the parameters set to allow-extra-chr, chr-set 25 --hardy.

[0116] (6) Polymorphism Information Content (PIC) screening: Loci with PIC values ​​higher than the population average are retained. The PIC value reflects the degree of polymorphism of a locus in the population. The higher the PIC value, the stronger the locus's ability to distinguish different individuals.

[0117] (7) The high polymorphic site filtering with MAF≥0.4 was adopted to solve the problem of insufficient family differentiation ability of low polymorphic sites, and the average PIC of a single marker was increased to 0.0948.

[0118] Step 3: Chain-linked unbalanced pruning

[0119] Linkage disequilibrium (LD) pruning is performed on the locus set after multi-parameter joint filtering to eliminate genetic information redundancy caused by tightly linked loci, ensuring the independence of locus combinations and genome representativeness.

[0120] In a preferred embodiment, LD pruning is performed using plink software with parameters set to indep-pairwise 50 10 0.1, representing a pruning method with a window size of 50 SNPs, a window step size of 10 SNPs, and a linkage imbalance coefficient. The threshold is 0.1. That is, when a pair of sites within the window... When the value is greater than 0.1, remove the sites with lower PIC values ​​until all remaining sites within the window are removed. The values ​​are all no greater than 0.1. (Using...) ≤0.1 LD pruning eliminates redundant linked genetic information at loci, ensures distortion-free genetic distance calculation, and achieves zero errors in pedigree clustering.

[0121] Step 4: Screening for uniform chromosome distribution

[0122] Following a strategy of uniform chromosome distribution, loci are selected from the screened SNP loci set and combined to obtain SNP loci combinations for kinship identification.

[0123] In a preferred embodiment, only sites located on chromosomes are retained, excluding mitochondrial sites or sites not located on chromosomes. Then, sites are sorted from highest to lowest nucleotide diversity (Pi value), and the sites with the highest nucleotide diversity are selected from each chromosome. For example, when the goal is to screen 100 SNP sites and the reference genome contains 25 chromosomes, the four sites with the highest Pi values ​​are selected from each chromosome (100 sites / 25 chromosomes = 4 SNP sites per chromosome), ultimately resulting in 100 highly informative SNP sites evenly distributed across the chromosomes.

[0124] Through the above-mentioned multi-parameter combined filtering, linkage disequilibrium pruning and chromosome uniform distribution strategy, the SNP locus combinations obtained by screening have high polymorphism, high stability, low linkage and good genomic representativeness, which can effectively reflect the genetic differences between individuals and provide a reliable marker basis for kinship identification.

[0125] The present invention also provides a combination of SNP loci for identifying kinship among fish of the genus *Schizothorax*, wherein the combination of SNP loci is uniformly distributed on chromosomes and is obtained by the aforementioned multi-parameter combined filtering and linkage disequilibrium pruning.

[0126] In a preferred embodiment, the SNP locus combination comprises 100 SNP loci distributed across 24 or 25 chromosomes. This locus combination is obtained by screening sequencing data from multiple full-sib families of *Schizothorax fasciatus* or *Schizothorax micranthum* using the screening method described above.

[0127] In the embodiment of *Schizothorax fasciatus*, the 100 SNP loci were evaluated by cumulative exclusion probability. The cumulative exclusion probability was greater than 0.999999 under the condition that the information of both parents was known, and the cumulative exclusion probability was 0.999997 under the condition that the information of one parent was known, indicating that the combination of loci has forensic-grade identification accuracy.

[0128] In the embodiment of *Schizothorax chevron*, the mean minimum allele frequency (MAF) of the 100 SNP loci was 0.0527±0.0021, the mean expected heterozygosity (He) was 0.0998±0.0037, and the mean polymorphism information content (PIC) was 0.0948±0.0033, indicating that the locus combination has high genetic polymorphism and information content.

[0129] The SNP locus combinations described can be used for kinship identification, family recognition, parentage testing, and genetic record establishment in fish of the genus *Schizothorax*. Because the locus combinations are evenly distributed on chromosomes and have undergone strict linkage disequilibrium pruning, they exhibit good population applicability and cross-population stability.

[0130] This SNP locus combination has high information content, low mutation rate, high stability and good genomic representativeness, and can effectively distinguish different families and individuals, providing a standardized molecular marker tool for identifying kinship among fish of the genus Schizothorax.

[0131] The present invention also provides a kit for identifying kinship among fish of the genus Schizothorax, comprising primers, probes or detection reagents for detecting the SNP site combinations described in claim 17.

[0132] In a preferred embodiment, the kit comprises PCR amplification primer pairs or KASP detection primers designed for the 100 SNP sites. Primer design principles include: primer length 18-25 bp, annealing temperature 55-65℃, GC content 40-60%, avoiding secondary structures and primer dimers, and ensuring amplification specificity.

[0133] In another embodiment, the kit includes an SNP chip with probes corresponding to the 100 SNP sites immobilized on it, enabling high-throughput genotyping through hybridization and scanning.

[0134] The kit may also include DNA extraction reagents, PCR amplification buffer, DNA polymerase, site-specific primers / fluorescent probes, positive standard DNA control, negative blank control, and instructions for use.

[0135] The method of using the kit includes: extracting genomic DNA from the sample to be tested; performing PCR amplification or hybridization detection using the primers or probes; reading genotype data; and determining kinship by combining the IBS similarity analysis and NJ phylogenetic tree construction.

[0136] This kit transforms the SNP locus combinations screened and verified by this invention into a standardized detection product. It is easy to operate, has good repeatability, and is suitable for the kinship identification needs of laboratories of different sizes. It lowers the technical threshold and is conducive to its widespread application.

[0137] This invention also provides a method for family management of schizothorax species for breeding and release, which uses the aforementioned kinship identification method to identify the kinship and family affiliation of schizothorax species.

[0138] Step 1: Pre-release management

[0139] Prior to stock enhancement and release, PIT tags were used on parent schizothorax species. Full-sib families were established using a 1:1 directed mating design and hatched in isolation. Basic data for each family, including parental PIT codes, mating information, and breeding time, were recorded. Samples from parents and offspring were collected to establish initial genetic profiles.

[0140] Step 2: Identification during release

[0141] Before the offspring are raised to a suitable release size, SNP genotyping is performed on the offspring samples. The accuracy of family construction is verified by IBS heatmap and NJ phylogenetic tree analysis to ensure that the pedigree of each release batch is clear and the kinship is well-defined. For samples with questionable pedigrees, confirmation can be obtained by adding SNP loci or by reviewing the breeding records.

[0142] Step 3: Post-release tracking and effect evaluation

[0143] After releasing the individuals into natural waters, tissue samples (such as fin rays) are obtained by recapture and sampling. Genotyping is performed using the SNP locus combination, and the results are compared with the genetic profile established before release to confirm the pedigree of the recaptured individuals.

[0144] Based on the pedigree determination results, the recapture rate, survival rate, and migration routes of released individuals from different pedigrees can be statistically analyzed to assess the genetic contribution of different pedigrees to the natural population. Through long-term monitoring, the genetic exchange between released and wild individuals can be analyzed to assess the impact of restocking on the genetic diversity of the natural population.

[0145] Step 4: Establishment of genetic records and germplasm management

[0146] Based on the kinship identification results, a population genetic profile of *Schizothorax* was constructed, recording the genotype information, pedigree, and kinship network of each individual. This genetic profile was used to monitor population genetic diversity, calculating parameters such as allele frequency, heterozygosity, and inbreeding coefficient. When an increase in the inbreeding coefficient or a decrease in genetic diversity was detected, the parental mating scheme was adjusted promptly to avoid inbreeding and maintain the genetic health of the population.

[0147] This method combines SNP kinship identification technology with stock enhancement and release management, realizing standardized management throughout the entire process from parental marking, family construction, release verification to post-release tracking. It effectively solves problems such as chaotic family management, lack of parentage identification technology, and difficulty in evaluating release effects during the stock enhancement and release process, and provides reliable technical support for the protection of germplasm resources of the genus Schizothorax and the scientific nature of stock enhancement and release.

[0148] The technical means and effects of this application will be analyzed in detail below with reference to specific embodiments.

[0149] Example 1: Method for Identifying Phylogenetic Relationships in Schizothorax 'Severodon'

[0150] I. Family pedigree construction and sample collection steps

[0151] 1. Parent fish marking

[0152] PIT tagging is fundamental for establishing pedigrees of the heavily bred Schizothorax fish. The procedure is as follows:

[0153] (1) Select a PIT marker with a specification of 2.12mm×12mm and use a special syringe (marking gun) to mark the parent fish.

[0154] (2) The tagged fish were anesthetized with MS-222 at a dose of 40 ppm. After the parent fish rolled over, growth parameters were measured and then PIT tagging was performed.

[0155] (3) The injection site should be selected on the back muscle of the fish. Before injection, the syringe (marker gun) should be disinfected with 75% alcohol.

[0156] (4) After marking, use a reader to scan and confirm that the marking code has been successfully entered, and record the parent fish information corresponding to the code, including basic biological information such as sex, weight, body length, and total length.

[0157] (5) After marking, apply erythromycin ointment to the wound, place the parent fish in the recovery pond for temporary rearing and observation for 24 hours, and transfer them to the parent fish breeding pond after confirming that there are no abnormalities.

[0158] 2. Family pedigree construction and sampling

[0159] Establishing a pedigree for the schizothorax culter based on PIT tagging relies on targeted mating design. During the breeding season, based on the PIT coding information of the parent fish, male and female parents with well-developed gonads are selected, and full-sib families are established by pairing them in a 1:1 ratio. Specific procedures include:

[0160] (1) Select 10 mature male and 10 female patricides of the Schizothorax fasciatus, pair them in a 1:1 ratio, and register the basic family information.

[0161] (2) After injecting the paired parent fish with spawning stimulants, they were transferred to a special spawning pond and fertilized eggs were obtained by artificial spawning and dry artificial insemination.

[0162] (3) Fertilized eggs of each family should be incubated in an isolated incubation container (incubation screen) with water temperature of 12-15℃, DO of 6-8, pH of 7-8.5, and ammonia nitrogen and nitrite of less than 0.01. The corresponding parent PIT code and family number should be marked on the incubation container.

[0163] (4) After hatching, 50 samples were randomly collected from each family and placed in centrifuge tubes containing 99% anhydrous ethanol. The samples were numbered and stored in a -20°C refrigerator for subsequent DNA extraction and parentage verification.

[0164] (5) Finally, the genetic analysis of the samples was performed using single nucleotide polymorphism (SNP) marker technology to confirm the accuracy of the parent-child relationship.

[0165] 3. Sample DNA extraction and detection

[0166] The second-generation DNA extraction experimental procedure (SDS extraction magnetic bead method, such as...) was adopted. Figure 1 ):

[0167] (1) Take 0.2 g of the frozen sample and grind it using a grinder;

[0168] (2) Use SDS lysis buffer for lysis. Add proteinase K and RNase A solution before lysis and shake once during lysis.

[0169] (3) After pyrolysis, cool and centrifuge, then transfer to a tube;

[0170] (4) Add magnetic beads to the supernatant, wash twice with 80% ethanol, and reconstitute with 100 μL of enzyme-free water at 37 °C;

[0171] (5) After reconstitution, cool and centrifuge, and collect the supernatant as nucleic acid;

[0172] (6) Quality inspection of Nanodrop, Qubit, and agarose gel electrophoresis.

[0173] II. SNP genotyping: High-throughput sequencing technology was used to perform SNP genotyping on the genomic DNA to obtain SNP genotype data.

[0174] 4. Building a library

[0175] (1) For each sample that has passed the test, take 0.5 μg gDNA template and prepare the library according to the methods and procedures of Annoroad Universal EZDNA Library Prep kit for MGI V1.0 (CAT: AN210105-S), Annoroad Adapters for MGI, Set-T (N1-N12) (CAT: AN210108) and Annoroad DNA Cyclization kit for MGI V1.0 (CAT: AN210107-S);

[0176] (2) Following the method in the instructions of Annoroad (CAT:AN210105-S), the DNA samples that passed the quality inspection were fragmented using Biouptor Pico, and the target fragments were recovered by screening with magnetic beads;

[0177] (3) End repair and adapter ligation were performed (using 384 barcode adapters provided by Annoroad (CAT: AN210108)). After purification by magnetic beads, the target fragment was enriched by PCR amplification and library quality control was performed.

[0178] (4) Perform the circularization of single-stranded DNA according to the method of Annoroad (CAT:AN210107-S) and purify the circularization product using magnetic beads;

[0179] (5) After purification of the double-stranded PCR library, it is unstranded and then circularized to form single-stranded circular DNA.

[0180] (6) DNA nanoballs (DNB) are formed using rolling circle amplification (RCA) technology.

[0181] (7) The DNB is loaded into the chip and fixed using a fully automated sample loading system;

[0182] (8) Sequencing was performed on the DNB-T7 platform using the sequencing reagent and the paired-end sequencing program (PE) was run to obtain 150bp paired-end sequencing reads.

[0183] 5. Data quality control

[0184] The raw image data obtained from the high-throughput sequencing platform is converted into raw sequencing reads through base calling and stored in FASTQ file format, containing read sequence information and corresponding quality information. The sequencing data is then filtered and deredundant is removed using FASTP software.

[0185] (1) The average quality value of reads is evaluated by sliding window, and the low-quality bases (average quality below Q20) at both ends of each read are pruned.

[0186] (2) Automatically detect connectors and remove connector sequences from each read;

[0187] (3) Filter out low-quality reads (more than 40% of the bases with a quality value lower than Q15 or more than 5 N atoms).

[0188] (4) When the final length of a sequencing read is less than 50 bp, the read is removed. High-quality clean reads are then obtained for subsequent resequencing alignment and analysis.

[0189] 6. Sequence comparison

[0190] Resequencing variant detection requires first aligning sequencing data to a reference genome. The similarity between the sample and the reference genome species will affect the sequence alignment rate, while the quantity and quality of sequencing data will affect the sequence coverage and coverage depth. Since the complete genome sequence of *Schizothorax spp.* was not publicly available when this study was conducted, by reviewing published genomes of fish in the genus *Schizothorax*, we found that *Schizothorax lantsangensis*, a closely related species to *Schizothorax spp.*, is a tetraploid fish. Its chromosome-level complete genome has been released (NCBI Assembly: GCA_027422415.1, genome size approximately 972.4 Mb), which is currently the most complete public genome resource in the genus *Schizothorax*.

[0191] To assess the potential impact of this closely related reference genome on the SNP detection results of *Schizothorax spp.*, a comparative analysis of their molecular phylogenetic relationship and sequence similarity was conducted based on published mitochondrial whole-genome data prior to the study. The results showed that the mitochondrial genome lengths (16,576 bp vs. 16,580 bp) and base compositions (A+T content of 54.9% in both *Schizothorax spp.*) of *Schizothorax spp.* and *Schizothorax lancensis* were highly similar. Phylogenetic analysis clustered them into the same high-support evolutionary clade, indicating a close phylogenetic relationship and high genomic homology. Therefore, this study used the *Schizothorax lancensis* genome as a reference sequence for alignment and SNP detection of *Schizothorax spp.* sequencing data. The filtered sequencing data were aligned to the reference genome using the sequence alignment software bwa, and the alignment rate, coverage, and coverage depth were statistically analyzed. The resulting BAM file was then used for further analysis.

[0192] 7. Mutation Detection and Annotation

[0193] Based on the sequence alignment results, Picard software was first used to process the alignment results, removing repetitive sequences generated by PCR amplification and discarding low-quality alignment data with a Mapping Quality (MQ) score below 20. Finally, population-level variation detection was performed using GATK (Genome Analysis Toolkit) software to obtain raw variant site information, including SNPs and InDels.

[0194] The test results are saved in VCF format, including overall annotation information, table header information, and variant detection information. The overall annotation information, starting with ##, provides a detailed description of the file information. Table header information is separated by tabs; the first nine columns are fixed columns, and the tenth column and subsequent columns contain sample information. Variance detection information corresponds to the table header information, recording detailed variant details.

[0195] To ensure high quality of variant detection results, GATK software was used for quality filtering. SNP filtering parameters: QD < 2.0, FS > 60.0, MQ < 40.0, MQRankSum < -12.5, ReadPosRankSum < -8.0; InDels filtering parameters: QD < 2.0, FS > 200.0, ReadPosRankSum < -20.0.

[0196] 8. Screening of SNP points for kinship characteristics

[0197] One hundred SNPs were screened from sequencing data of 70 samples from 10 families. The SNPs were filtered based on the following criteria:

[0198] (1) Extract the VCF files of 70 samples based on the sample information;

[0199] (2) Retain sites with MAF > 0.4 (Software: vcftools; Parameter: maf 0.4);

[0200] (3) Retain loci with an individual typing success rate greater than 99% (Software: vcftools; Parameter: max-missing0.99).

[0201] (4) HWE test (software: vcftools; parameter: hwe 0.0001);

[0202] (5) Preserve biallelic loci (software: vcftools; parameters: min-alleles 2, max-alleles 2);

[0203] (6) Retain sites with heterozygosity higher than the mean (mean=0.613989) (Software: plink; Parameters: allow-extra-chr, chr-set 25, hardy);

[0204] (7) Retain sites with PIC values ​​higher than the average;

[0205] (8) Perform LD pruning (software: plink; parameters: indep-pairwise 50 10 0.1, which means the pruning method is a window size of 50 SNPs, a window step size of 10 SNPs, and a linkage imbalance coefficient r2 threshold of 0.1).

[0206] (9) Screen only loci on chromosomes;

[0207] (10) Screening is performed according to the SNP polymorphism (pi value) to obtain the 4 SNP sites with the highest pi value on each chromosome (100 sites / 25 chromosomes = 4 SNP sites on each chromosome).

[0208] Based on all the above filtering conditions, the top 10 SNP loci were selected from each family, totaling 100 high information SNP loci, for subsequent paternity testing analysis.

[0209] III. Cumulative Exclusion Probability Calculation

[0210] The identification power of the marker combination was evaluated using the cumulative exclusion probability (CEP). The cumulative exclusion probabilities were calculated for the cases where only information about one parent was known (CEP1) and when information about both parents was known (CEP2).

[0211] The 100 SNP loci were sorted from highest to lowest PIC value, and the top [values] were calculated sequentially. CEP1 and CEP2 values ​​at each site.

[0212] Among them, when using all 100 SNP loci, the cumulative exclusion probability under the condition of known parental information is greater than 0.999999, and the cumulative exclusion probability under the condition of known uniparental information is 0.999997 (Table 1). The delta_snp_index list of the 100 SNPs is as follows: Figure 2 (1-50) Figure 3 As shown in (51-100); the cumulative exclusion probability (CEP) results for 100 SNPs are as follows. Figure 4 As shown.

[0213] Table 1. Changes in cumulative exclusion probability with the number of labels

[0214] .

[0215] IV. IBS Similarity Calculation and Heatmap Construction

[0216] The IBS similarity matrix of all paired samples was calculated using the plink software, and a heatmap was plotted using the pheatmap package in R. Figure 5 The phylogenetic tree was constructed using the adjacency method based on the IBS distance matrix and cross-validated with the NJ tree based on p-distance.

[0217] V. Genetic Distance Calculation and Phylogenetic Tree Construction

[0218] Based on the distance matrix calculation results, the NJ tree was constructed using the neighbor program in the Phylip software, and finally, the tree diagram was created and beautified using Mega software. Figure 6 ).

[0219] like Figure 5 As shown: (The horizontal and vertical axes in the figure correspond to the numbers of 70 samples (parents and offspring of 10 full-sib families); the color scale on the right represents the IBS similarity value, ranging from 0.70 (blue, low similarity) to 1.00 (dark red, high similarity).

[0220] High similarity clustering within families: Ten distinct dark red square regions are distributed along the diagonal, corresponding to the IBS similarity between individuals within ten full-sib families. The IBS similarity between parents and offspring, as well as among offspring individuals within the same family, is 0.95~1.00 (dark red), indicating a high degree of consistency in genetic background and extremely high allele sharing within the family.

[0221] Low pedigree similarity: The color of the off-diagonal region (between individuals from different families) is mainly yellow-green to light blue, and the IBS similarity is significantly reduced to 0.75~0.90, indicating that there are obvious genetic differences between different families and low allele sharing among unrelated individuals.

[0222] Clustering consistency: The tree-like clustering branches at the top of the heatmap show that all individuals from the same family lineage first cluster into one branch, and then different families are clustered hierarchically according to their genetic distance, which perfectly matches the preset structure of 10 independent families.

[0223] like Figure 6 As shown in the figure (each terminal branch represents a sample, and the branch colors are grouped by family lineage (in the legend, CKQB-1-F / M to CKQB-10-F / M represent the male / female parents of 10 families respectively, and branches of the same color lineage represent the offspring of the corresponding family lineage).

[0224] Independent clustering of families: 10 families form 10 independent and clearly defined cluster branches. Parents and offspring of the same family are closely clustered on the same branch, and there is obvious genetic isolation between different families. There is no cross-clustering or mixed phenomenon.

[0225] Parent-offspring co-clusters: Within each pedigree, the parents (F / M) and offspring individuals first cluster into sub-branchs, reflecting the closest genetic distance of direct parent-offspring relationships; the node distances between different pedigrees are relatively far, reflecting the genetic differentiation between parents of different mating pairs.

[0226] High support structure: The topological structure of each major branch is stable, and individuals of the same family always cluster together. No individual is "misplaced" to other family branches, indicating that the genetic distance calculation based on 100 SNP loci has extremely high resolution and stability.

[0227] The IBS heatmap and the NJ phylogenetic tree present the same genetic structure from different dimensions: the IBS heatmap visually quantifies the degree of allele sharing among individuals through matrix color blocks, while the NJ phylogenetic tree reflects evolutionary relationships and clustering levels through branching topology. The results of the two maps are highly consistent—all 10 families form independent and clear genetic clusters, with extremely high similarity within families and significant differentiation between families.

[0228] This result proves that:

[0229] 1. The 100 SNP loci combinations selected in this embodiment have sufficient information content and resolution, and can accurately distinguish the full-sib families of fish in the genus *Schizothorax*.

[0230] 2. The dual verification strategy of IBS similarity analysis and NJ phylogenetic tree construction effectively avoids the systematic errors of a single method, and the kinship determination results are reliable;

[0231] 3. This identification system can be used for family identification, parentage testing, and genetic record establishment during the release of Schizothorax fasciatus, providing molecular-level evidence to support subsequent release effect assessment.

[0232] Example 2: Method for determining kinship among offspring of the schizothorax 'Qikou'

[0233] I. Family Lineage Establishment

[0234] To verify the effectiveness of the SNP kinship identification system established in this invention, a full-sib family of *Schizothorax chevron* with a clear parental origin was first constructed.

[0235] (1) Parental selection

[0236] Ten male and ten female patricides of the Qikou Schizothorax were selected, all of which were mature in gonads, healthy, and free from disease, and had a unique PIT electronic identifier. Their basic information, such as PIT code, body length, and weight, were recorded.

[0237] (2) Targeted grouping

[0238] According to the pre-designed pairing scheme, the male and female parents were paired in a 1:1 ratio to establish a total of 10 full-sib families, and each family was independently numbered.

[0239] (3) Artificial insemination

[0240] The parent lines were induced to conceive, and once conditions were met for artificial insemination, fertilized eggs were obtained using dry insemination. Fertilized eggs from each family were collected separately, numbered, and managed to prevent mixing between different families.

[0241] (4) Isolation incubation

[0242] Each family's fertilized eggs were placed in an independent incubation unit for isolated incubation, and the corresponding family number and parent PIT code information were labeled on the incubation unit. Throughout the incubation process, each family was managed independently to ensure the accuracy and reliability of the family origin information.

[0243] (5) Sample collection

[0244] Once the fertilized eggs reached the organogenesis stage, five fertilized egg samples were randomly collected from each family and preserved in anhydrous ethanol as progeny samples for subsequent sequencing analysis, resulting in a total of 50 progeny samples. Quality testing of the progeny samples revealed that one progeny sample from each of families 1 and 2 did not meet sequencing quality requirements; therefore, 48 progeny samples were ultimately used for analysis. The collected samples were preserved in anhydrous ethanol, numbered, registered, and stored at low temperature for later use.

[0245] (6) Family lineage verification

[0246] The 100 SNP markers established in this invention were used to perform genotyping on offspring samples. The accuracy of the family construction results was verified by genetic relationship analysis, and standard samples were provided for subsequent kinship identification.

[0247] II. DNA Extraction and Sequencing

[0248] Fertilized eggs at the organogenesis stage were collected, and approximately 0.2 g of frozen fin tissue samples were taken and thoroughly homogenized using a tissue homogenizer. SDS lysis buffer was then added for lysis, with Proteinase K and RNase A solutions added before lysis to promote protein and RNA degradation. The sample was gently inverted once during lysis to improve efficiency. After lysis, the sample was cooled and centrifuged, and the supernatant was transferred to a new centrifuge tube. Magnetic beads were then added to the supernatant to bind DNA, followed by washing twice with 80% ethanol to remove impurities. Finally, 100 µL of nuclease-free water was added, and the DNA was reconstituted at 37°C. After reconstitution, the sample was centrifuged again, and the supernatant was collected as the extracted genomic DNA.

[0249] The purity of the extracted DNA samples was first determined using a NanoPhotometer® spectrophotometer (IMPLEN, CA, USA); then the DNA concentration was determined using a Qubit® 3.0 Fluorometer (Life Technologies, CA, USA); finally, DNA integrity and the presence of degradation or impurities were detected by 1% agarose gel electrophoresis at 120 V for 45 min.

[0250] DNA fragment library construction and sequencing were performed using the DNBSEQ-T7 platform. After the DNA extraction samples passed quality testing, 0.5 µg gDNA was used as a template from each sample, and the library was constructed according to the instructions of Annoroad Universal EZ DNA Library Prep kit for MGI V1.0 (CAT: AN210105-S), Annoroad Adapters for MGI, Set-T (N1-N12) (CAT: AN210108), and Annoroad DNA Cyclization kit for MGI V1.0 (CAT: AN210107-S).

[0251] First, DNA samples were randomly fragmented using a Bioruptor Pico, and DNA fragments within the target length range were obtained through magnetic bead screening. Then, end repair and adapter ligation were performed using Annoroad Adapters for MGI (Set-T, N1-N12), which contain 384 different barcodes for sample differentiation. The ligated DNA fragments were purified with magnetic beads and then subjected to PCR amplification to enrich the target fragments. The amplification products were then quality-tested. Finally, single-stranded DNA was circularized according to the Annoroad DNA Cyclization kit for MGI V1.0 instructions, and the circularization product was purified using magnetic beads to obtain a DNA library for subsequent sequencing.

[0252] The double-stranded PCR library was purified, then destranded and further circularized to form single-stranded circular DNA (ssCirDNA). Subsequently, the single-stranded circular DNA was amplified using rolling circle amplification (RCA) technology to generate a large number of DNA nanoballs (DNB). Finally, the DNB was loaded into a sequencing chip and immobilized using a fully automated sample loading system, providing a template for subsequent high-throughput sequencing. High-throughput sequencing was performed on the DNBSEQ-T7 sequencing platform using appropriate sequencing reagents in paired-end (PE) mode, obtaining paired-end sequencing data with a read length of 150 bp (PE150).

[0253] III. Screening of SNPs Specific to Kinship

[0254] SNP sites were selected based on the following criteria:

[0255] (1) Extract the VCF files of 48 samples based on the sample information;

[0256] (2) Preserve sites with MAF > 0.4 (Software: vcftools; Parameter: --maf 0.4);

[0257] (3) Retain loci with an individual typing success rate greater than 99% (software: vcftools; parameter: --max-missing0.99).

[0258] (4) HWE test (software: vcftools; parameter: --hwe 0.0001);

[0259] (5) Preserve bis-alleles sites (software: vcftools; parameters: --min-alleles 2 --max-alleles2);

[0260] (6) Retain sites with heterozygosity above the average (Software: plink; Parameters: --allow-extra-chr --chr-set 25 --hardy);

[0261] (7) Retain sites with PIC values ​​higher than the average;

[0262] (8) Perform LD pruning (software: plink; parameters: --indep-pairwise 50 10 0.1, which means the pruning method is a window size of 50 SNPs, a window step size of 10 SNPs, and a linkage imbalance coefficient r2 threshold of 0.1).

[0263] (9) Screen only loci on chromosomes;

[0264] (10) Screening is performed according to the SNP polymorphism (pi value) to obtain the 4 SNP sites with the highest pi value on each chromosome (100 sites / 25 chromosomes = 4 SNP sites on each chromosome).

[0265] Based on all the above filtering criteria, the top 10 SNP loci were selected from each family, resulting in a total of 100 high-information SNP loci. Figure 7 As shown in (1-50) and 8 (51-100), they are used for subsequent paternity testing analysis.

[0266] IV. SNP Genotyping Detection

[0267] Genotyping was performed on the test samples using 100 selected SNP loci combinations. The mean minimum allele frequency (MAF) of the 100 SNP loci was 0.0527±0.0021, the mean expected heterozygosity (He) was 0.0998±0.0037, and the mean polymorphism information content (PIC) was 0.0948±0.0905 (Table 2).

[0268] Table 2. Genetic diversity parameters of 100 SNP loci

[0269] .

[0270] V. IBS Similarity Calculation and Heatmap Analysis

[0271] The IBS similarity matrix of all paired samples was calculated using the plink software, and a heatmap was plotted using the pheatmap package in R. Figure 9The phylogenetic tree was constructed using the adjacency method based on the IBS distance matrix and cross-validated with the NJ tree based on p-distance.

[0272] VI. Phylogenetic Analysis

[0273] Based on the distance matrix calculation results, the NJ tree was constructed using the neighbor program in the Phylip software, and finally, the tree diagram was created and beautified using Mega software. Figure 10 ).

[0274] Figure 9 This is a heatmap of IBS (Identity By State) similarity among individuals of *Schizothorax chevron*, plotted based on genotypic data from 100 SNP loci. The horizontal and vertical axes correspond to the numbers of 68 offspring samples (from 10 full-sib families), respectively; the color scales on the right represent IBS similarity values, ranging from 0.75 (blue, low similarity) to 1.00 (dark red, high similarity).

[0275] As can be seen from the figure:

[0276] High-similarity clustering within families: Ten distinct dark red square regions are distributed along the diagonal, corresponding to the IBS similarity between individuals within ten full-sib families. The IBS similarity between offspring within the same family is close to or reaches 1.00 (dark red), indicating a high degree of consistency in genetic background and extremely high allele sharing within the family.

[0277] Low familial similarity: The color of the off-diagonal region (between individuals from different families) is mainly yellow-green to blue, and the IBS similarity is significantly reduced, indicating that there are obvious genetic differences between different families and low allele sharing between unrelated individuals.

[0278] Clustering consistency: The tree-like clustering branches at the top of the heatmap show that all offspring individuals of the same lineage first cluster into one branch, and then different linesages are clustered hierarchically according to their genetic distance, which perfectly matches the preset structure of 10 independent linesages.

[0279] Figure 10 This is a phylogenetic tree (radial layout) constructed using the Neighbor-Joining method based on the p-distance genetic distance matrix. Each terminal branch in the figure represents a sample, and the branch colors are grouped by family (Family 1 to Family 10 are identified by different colors in the legend).

[0280] As can be seen from the figure:

[0281] Family-independent clustering: 10 families form 10 independent and clearly defined cluster branches. All offspring of the same family are closely clustered on the same branch. There is obvious genetic isolation between different families, with no cross-clustering or mixed phenomena.

[0282] Stable pedigree structure: Within each pedigree branch, offspring individuals first cluster in pairs to form subbranches, and then converge at each level, reflecting the closest genetic distance between full siblings; the node distance between different pedigree branches is relatively far, reflecting the genetic differentiation between parents of different mating groups.

[0283] High support structure: The topological structure of each major branch is stable, and individuals of the same family always cluster together. No individual is "misplaced" to other family branches, indicating that the genetic distance calculation based on 100 SNP loci has extremely high resolution and stability.

[0284] The IBS heatmap and NJ phylogenetic tree reveal the shared genetic structure within the *Schizothorax chevron* population from different perspectives: the IBS heatmap visually quantifies the degree of allele sharing among individuals using matrix color blocks, while the NJ phylogenetic tree reflects evolutionary relationships and clustering levels through branching topology. The two graphs show a high degree of consistency—all 10 families form independent and clear genetic clusters, exhibiting extremely high similarity within families and significant differentiation between families.

[0285] This result proves that:

[0286] 1. The 100 SNP loci combinations screened in this invention also have sufficient information content and resolution in *Schizothorax chevron*, and can accurately distinguish the full sibling families of this species.

[0287] 2. The dual verification strategy of IBS similarity analysis and NJ phylogenetic tree construction effectively avoids the systematic error of a single method in *Schizothorax chevron*, and the kinship determination results are reliable;

[0288] 3. This identification system can be extended to family identification, parentage testing and genetic record establishment during the propagation and release of Schizothorax brevicus. Together with the example of Schizothorax brevicus, it supports the wide applicability of this invention to fish of the Schizothorax genus.

[0289] The above-described embodiments are only used to illustrate the technical solutions of the present invention, and are not intended to limit it. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention, and should all be included within the protection scope of the present invention.

Claims

1. A method for identifying kinship among fish of the genus *Schizothorax*, characterized in that, Includes the following steps: (1) SNP genotyping was performed on the target Schizothorax fish samples to obtain SNP genotype data; wherein, the SNP genotyping was performed on a set of SNP locus combinations, the SNP locus combinations were evenly distributed on the chromosome and obtained by multi-parameter joint filtering and linkage disequilibrium pruning. (2) Based on the SNP genotype data, calculate the IBS similarity among individuals and construct an IBS heatmap; (3) Based on the SNP genotype data, calculate the genetic distance between individuals and construct a phylogenetic tree using the neighbor-joining method; (4) Determine the kinship and family affiliation between offspring individuals and their parents based on the IBS heatmap and the phylogenetic tree.

2. The method according to claim 1, characterized in that, The multi-parameter combined filtering includes minimum allele frequency filtering, genotyping success rate filtering, Hardy-Weinberg balance test, biceleste screening, heterozygosity screening, and polymorphism information content screening.

3. The method according to claim 2, characterized in that, The parameters for the minimum allele frequency filtering are MAF>0.4, the parameters for the genotyping success rate filtering are greater than 99%, the parameters for the Hardy-Weinberg balance test are P>0.0001, and the parameters for the linkage disequilibrium pruning are window size of 50 SNPs, step size of 10 SNPs, and r2 threshold of 0.

1.

4. The method according to claim 1, characterized in that, The target Schizothorax species samples were obtained by identifying and marking individual Schizothorax parent fish, establishing full-sib families according to a targeted mating design, and isolating and hatching them, and collecting samples from the parent fish and offspring.

5. The method according to claim 1, characterized in that, In step (1), the SNP genotyping detection is achieved by whole-genome resequencing, targeted capture sequencing or competitive allele-specific PCR.

6. A combination of SNP loci for identifying kinship among fish of the genus *Schizothorax*, characterized in that, The SNP loci combinations are evenly distributed on the chromosome and are obtained through multi-parameter combined filtering and linkage disequilibrium pruning.

7. The SNP site combination according to claim 6, characterized in that, The fish in the genus *Schizothorax* are either *Schizothorax fasciatus* or *Schizothorax fasciatus*.

8. A kit for identifying kinship among fish of the genus *Schizothorax*, characterized in that, include: DNA extraction reagent, PCR amplification buffer, DNA polymerase, site-specific primers or fluorescent probes, positive standard DNA control, negative blank control, and instruction manual.

9. A method for tracing and comparing wild-captured individuals of the genus *Schizothorax*, constructing population genetic profiles, dynamically monitoring inbreeding coefficients, and providing early warning management of parental pairing, characterized in that... The method described in any one of claims 1-5 is used to identify the kinship and determine the pedigree of fish in the genus Schizothorax.

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