A molecular marker of an alpha-amylase gene SNP site related to body weight of ictalurus punctatus, a breeding method and application thereof

Abstract

The application provides a kind of molecular marker of alpha-amylase gene SNP site related to channel catfish weight, breeding method and application, belong to molecular marker breeding technical field.The correlation of the site identified by the present application chr1:37047670 with weight trait reaches extremely significant level (P=1.79×10-15), far more than the genome significance threshold, and the site is located in alpha-amylase ( α‑ amylase ) gene region, directly participates in energy metabolism and growth and development regulation, has clear biological significance, ensures the stability and effectiveness of the screened molecular marker in breeding application.The weight of CC genotype individual of the site is significantly better than that of TC and TT genotypes, and the effect remains consistent in different breeding generations.Using the marker, individuals with fast growth potential can be screened at the seedling stage, without waiting for the market period to measure production, effectively shortening the breeding cycle and improving the breeding efficiency.

Description

Technical Field

[0001] This invention relates to the field of molecular marker breeding technology, and in particular to a molecular marker, breeding method, and application of an α-amylase gene SNP site related to the body weight of the spotted catfish. Background Technology

[0002] Spotted catfish ( Ictalurus punctatus Due to its rapid growth, strong adaptability, and high feed conversion rate, it has become one of the dominant species in freshwater aquaculture in my country. Its body weight and length directly determine the breeding cycle, harvest yield, marketable size, and economic benefits. However, traditional phenotypic selection has limitations such as long generation intervals, significant environmental disturbances, and low selection accuracy, making it difficult to meet the needs of modern aquaculture for rapid improvement of growth traits.

[0003] Whole-genome resequencing technology, through high-throughput sequencing of different individuals of a species with a known reference genome, combined with sequence alignment, can accurately obtain individual genome sequences and genetic variation information. This allows for the discovery of genetic variations significantly associated with phenotypic traits at the population level, making it a key technology for analyzing the functional information of a species' genome. Building upon this, genome-wide association studies (GWAS) identify variations significantly associated with specific phenotypes by detecting millions of genetic variation sites in the genome. GWAS has been widely applied to the genetic analysis of complex human diseases and important agronomic traits in plants and animals. This research method, initially proposed by Risch and Merikans, marked a shift in complex trait research from a candidate gene strategy to a whole-genome perspective. In bony fish research, the FarmCPU model has been widely used due to its ability to effectively control false positives caused by population stratification and kinship.

[0004] Nevertheless, existing research on growth traits in channel catfish remains significantly insufficient. While some quantitative trait loci (QTLs) associated with growth have been reported, key functional variations, candidate genes, and regulatory pathways related to body weight remain unclear. More importantly, previous studies have lacked a systematic assessment of the genetic structure, subpopulation differentiation, and genetic diversity levels of breeding populations, limiting the interpretability of association analysis results and hindering the practical application of molecular markers in subsequent breeding.

[0005] Therefore, it is urgent to identify SNP molecular markers that are significantly associated with the weight trait of channel catfish and have stable genetic effects, and to establish simple and feasible detection methods and application systems to break through the bottleneck of traditional breeding and provide reliable molecular marker support for the breeding of fast-growing channel catfish. Summary of the Invention

[0006] The purpose of this invention is to provide a molecular marker, breeding method, and application for the α-amylase gene SNP site related to the body weight of the spotted catfish, providing valuable molecular markers, candidate genes, and population genetics references for genome selection breeding and genetic resource management of the spotted catfish.

[0007] To achieve the above-mentioned objectives, the present invention provides the following technical solution: This invention provides a molecular marker associated with the weight of the spotted catfish, wherein the molecular marker is an SNP site at position 37047670 on chromosome 1, and the SNP site is a T / C mutation.

[0008] Preferably, the genotype of the SNP site is TT, TC or CC.

[0009] Preferably, the gene associated with the SNP site is the α-amylase gene.

[0010] The present invention also provides an application of the above-mentioned molecular markers related to the body weight of the spotted catfish in the breeding of spotted catfish.

[0011] This invention also provides a molecular marker-assisted breeding method for the spotted catfish, comprising the following steps: (1) Extract genomic DNA from the spotted catfish individuals to be tested; (2) Detect the genotype of the above SNP sites; (3) Assess the individual's weight based on genotype information; (4) Select individuals with excellent growth traits based on the evaluation results of step (3) for breeding.

[0012] The present invention also provides an application of the above-mentioned molecular marker-assisted breeding method in the breeding of spotted catfish.

[0013] The beneficial effects of this invention compared to the prior art are as follows: (1) The association between the chr1:37047670 locus identified in this invention and the body weight trait reached a highly significant level (P=1.79×10⁻⁶). -15 This far exceeds the genome-wide significance threshold, and the site is located at α-amylase ( α-amylase This gene region directly participates in energy metabolism and growth and development regulation, possessing clear biological significance and ensuring the stability and effectiveness of the screened molecular markers in breeding applications. Individuals with the CC genotype at this locus exhibit significantly higher body weight than those with the TC and TT genotypes, and this effect remains consistent across different breeding generations. Using this marker, individuals with rapid growth potential can be screened at the seedling stage, eliminating the need to wait for yield testing at market, effectively shortening the breeding cycle and improving the efficiency of superior breed selection.

[0014] (2) The molecular markers provided by this invention can be used for PCR amplification with specific primers combined with Sanger sequencing to determine genotypes. The operation process is standardized and does not rely on expensive gene chips or high-throughput sequencing platforms. The results of this method are intuitive and the genotyping is accurate, making it particularly suitable for routine and batch genotyping in breeding farms or seed stations. Attached Figure Description

[0015] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the embodiments 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.

[0016] Figure 1 This is a density distribution map of SNPs obtained from high-depth resequencing of spotted catfish in Example 1 of the present invention; Figure 2 This is a low-depth resequencing depth distribution map of the spotted catfish in Example 1 of the present invention; Figure 3 This is a distribution map of the filling accuracy of low-depth resequencing samples of spotted catfish in Example 1 of the present invention; Figure 4 This is a Manhattan plot of the GWAS analysis of the weight trait of the spotted catfish in Example 1 of this invention, where the strongest signal is located on chromosome 1; the horizontal axis represents all chromosomes, and the vertical axis represents the locus - lg( P value), the green line is -lg( P The threshold of value, gene locus P The smaller the value, the less likely it is to be -log10 ( P The larger the value, the stronger the association between the locus and phenotypic traits or diseases; Figure 5 This is a QQ plot of the GWAS analysis of the weight trait of the spotted catfish in Example 1 of this invention; observation P The midpoint of the value conforms to the expected distribution, while the tail is significantly upward skewed, indicating the presence of genuine genetic signals and the reliability of the model; the horizontal axis in the figure represents loci. P The expected value is represented by the value on the y-axis, where the y-axis represents the location. P value is the actual value; from Figure 5 As can be seen from this, if the actual value and the expected value are basically consistent in the early stage (lower left) and rise in the later stage (upper right), it indicates that it is reasonable to use this model to analyze this trait. Figure 6 This is a statistical chart of the body weight of individuals with different genotypes at the chr1: 37047670 locus in Example 2 of the present invention. Detailed Implementation

[0017] Various exemplary embodiments of the present invention will now be described in detail. This detailed description should not be considered as a limitation of the present invention, but rather as a more detailed description of certain aspects, features, and embodiments of the present invention.

[0018] It should be understood that the terminology used in this invention is merely for describing particular embodiments and is not intended to limit the invention. Furthermore, with respect to numerical ranges in this invention, it should be understood that each intermediate value between the upper and lower limits of the range is also specifically disclosed. Every smaller range between any stated value or intermediate value within a stated range, and any other stated value or intermediate value within said range, is also included in this invention. The upper and lower limits of these smaller ranges may be independently included or excluded from the range.

[0019] Unless otherwise stated, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art. While only preferred methods and materials have been described herein, any methods and materials similar or equivalent to those described herein may be used in the implementation or testing of this invention. All references to this specification are incorporated by way of citation to disclose and describe methods and / or materials associated with those references. In the event of any conflict with any incorporated reference, the content of this specification shall prevail.

[0020] Various modifications and variations can be made to the specific embodiments described in this specification without departing from the scope or spirit of the invention, as will be apparent to those skilled in the art. Other embodiments derived from this specification will also be apparent to those skilled in the art. This specification and embodiments are merely exemplary.

[0021] The terms “include,” “including,” “have,” “contain,” etc., used in this article are all open-ended terms, meaning that they include but are not limited to.

[0022] Example This invention provides a method for screening molecular markers related to the body weight of the spotted catfish, the specific steps of which are as follows: (1) Experimental fish and phenotypic determination The channel catfish used in this invention were sourced from the Yangzhong base of the Channel Catfish Germplasm Resource Bank of the Jiangsu Provincial Freshwater Fisheries Research Institute. Thirty-three individuals were randomly selected from a reference population of channel catfish cultured in the same pond, and the weight of each fish was measured and recorded. Forty-two individuals (168 from generation G2, 113 from generation G3, and 121 from generation G4) from the core population of three consecutive generations of channel catfish (G2-G4) were selected from the germplasm resource bank for the experimental group. Additionally, 100 individuals were randomly selected from each generation of the backup population of three consecutive generations of channel catfish (G2-G4) for verification experiments. Caudal fin tissue from the experimental fish was collected for genomic DNA extraction and rapidly placed in liquid nitrogen, then transferred to a -80°C freezer for later storage. All experiments were conducted in accordance with the regulations of the Animal Ethics Committee and were approved by the Bioethics and Biosafety Review Committee of the Jiangsu Provincial Freshwater Fisheries Research Institute.

[0023] (2) Extraction of genomic DNA The fully automated nucleic acid extractor was used to extract DNA from the samples using the ONREW DNA extraction kit. The extracted DNA samples were quality controlled by the following methods: (1) Purity detection: the OD260 / 280 ratio (acceptable range 1.8~2.0) and OD260 / 230 ratio (>2.0 is acceptable) were measured using a NanoDrop micro spectrophotometer to assess the degree of contamination such as protein and polysaccharide; (2) Concentration detection: accurate quantification was performed using a Qubit fluorometer in conjunction with a dsDNA HS Assay Kit; (3) Integrity detection: the clarity and integrity of the DNA master band were detected by 1% agarose gel electrophoresis, and the DNA integrity was assessed using an Agilent 4200 TapeStation (DIN value ≥6.0 is acceptable).

[0024] (3) Sequencing library construction 1) Construction of high-depth resequencing libraries High-depth genome resequencing was performed on 303 individuals in the reference population. The high-depth genome resequencing library was constructed using the standard procedure based on the MGISEQ platform: (1) DNA fragmentation: High-quality genomic DNA was randomly fragmented into fragments with a main band of about 350 bp using a Covaris ultrasonic disruptor; (2) End repair: The 3′ and 5′ protruding ends of the fragmented DNA were repaired using T4 DNA polymerase and T4 polynucleotide kinase to form blunt ends; (3) 3′ A addition: A single adenine (A) base was added to the 3′ end of the repaired DNA fragment using the Klenow fragment (3′→5′ exo-) to prevent self-ligation between fragments; (4) Adapter ligation and circularization: Sequencing adapters with sticky thymine (T) ends were ligated to the A-added product. After purification, the ligation product was denatured at high temperature to convert the double-stranded DNA into single strands, and then rolled circle amplification (RCA) was performed using phi29 DNA polymerase to amplify the linear single-stranded library into DNA nanoballs (DNBs); (5) Fragment screening and purification: AMPure XP magnetic beads were used to purify the ligation and circularization products and screen for fragments of appropriate size; (6) Library quality control: Agilent Bioanalyzer 2100 was used to detect the size distribution of library fragments (main band approximately 350 bp), and Qubit was used for precise quantification (concentration ≥ 2 ng / μL) to ensure that the library quality meets the requirements for sequencing.

[0025] 2) Construction of low-depth resequencing libraries Low-depth resequencing was performed on 402 individuals from the core population of three consecutive breeding generations (G2-G4). The library construction process for low-depth sequencing was basically the same as that for high-depth sequencing, using the same MGISEQ platform standard procedure. Given that low-depth sequencing requires only a smaller amount of sequencing data, the number of PCR amplification cycles was appropriately reduced during library construction to decrease PCR repeatability and reduce library bias. After passing quality control using an Agilent Bioanalyzer 2100 and Qubit, the libraries were used for sequencing.

[0026] (4) High-throughput genome sequencing Paired-End (PE) sequencing was performed on the constructed high- and low-depth resequencing libraries using the BGISEQ-500 high-throughput sequencing platform. Based on DNA nanosphere (DNB) technology and combinatorial probe-anchor synthesis (cPAS) technology, four different fluorescent groups were used to specifically label A, T, C, and G. Fluorescence signals were acquired using a high-sensitivity sCMOS camera to complete the conversion and recording from DNA sequence to optical signal. Sequencing was performed using a paired-end 150 bp (PE150) read length mode.

[0027] (5) Raw data output and quality control 303 high-depth resequencing samples were sequenced using the BGISEQ-500 platform, generating a total of 3.69 Tb of raw data, averaging 12.18 Gb per sample, with an average sequencing depth of 14.13×. The raw data underwent rigorous quality control and filtering: adapter sequence removal: sequencing adapter and barcode sequences were identified and removed from reads; low-quality read filtering: reads containing too many unknown bases (N bases, e.g., N>10%) were removed; quality trimming: reads with end quality values ​​consistently below a set threshold were trimmed; length filtering: reads with excessively short truncated lengths (e.g., shorter than 36 bp) were directly discarded; average quality filtering: reads with an average quality value below a threshold were filtered. After these quality control procedures, a total of 3.63 Tb of clean data was obtained, averaging 11.98 Gb per sample.

[0028] 402 low-depth resequencing samples were sequenced using the BGISEQ-500 platform, generating a total of 0.78 Tb of raw data, with an average of 1.95 Gb per sample and a sequencing depth of approximately 2.26×. Specifically, the sequencing depth of the 402 samples was mainly concentrated in the 1.5×~4× range, including 1.5×~2× 44 tails, 2×~2.5× 331 tails, 2.5×~3× 8 tails, 3×~3.5× 16 tails, and 3.5×~4× 3 tails (e.g., 16 tails). Figure 1 (As shown). The sequencing depth of the vast majority of samples (82.3%) was concentrated between 2× and 2.5×, which significantly reduced sequencing costs while ensuring sufficient coverage. After the raw data underwent the same quality control filtering process as high-depth sequencing, a total of 0.77 Tb of clean data was obtained for subsequent analysis.

[0029] (6) SNP detection in high-depth resequencing samples The clean reads of each sample were aligned with the T2T (Telomere-to-Telomere) level reference genome (0.862 Gb) of the channel catfish using BWA-MEM (Burrows-Wheeler Aligner Maximal Exact Matches) alignment software. After alignment, SAMtools was used to sort and remove duplicates from the alignment results, generating BAM format files for subsequent variant detection. Statistical results showed that the average mapping rate (alignment rate) for all samples was 99.74%, indicating a high degree of consistency between the sequencing reads and the reference genome, and the data quality met the requirements for subsequent analysis.

[0030] Genomic genetic variation detection was performed using the HaplotypeCaller module of GATK (Genome Analysis Toolkit) to identify single nucleotide polymorphism (SNP) sites in the samples. After variation detection, the original SNP sites were strictly quality controlled using hard filtering criteria: MQRankSum < -12.5 (mapped quality rank sum test); FS > 60.0 (Fisher test for chain bias); ReadPosRankSum < -8.0 (reads position rank sum test); MQ < 40.0 (mean mapped quality). Additionally, low-quality sites were further filtered according to the criteria of Missing Rate < 0.1 and Minimum Allele Frequency (MAF) > 0.01.

[0031] The number of SNPs for each quality control was 15,585,264, 11,436,154, 10,144,151, and 8,463,005, respectively. Finally, a high-depth genome resequencing SNP genotyping reference panel was constructed using 8,463,005 high-quality SNPs. These 8,463,005 SNPs were evenly distributed across the 29 chromosomes of the channel catfish. The number of SNPs on each chromosome ranged from 158,372 (Chr29) to 426,579 (Chr2), with an average of 291,825 SNPs per chromosome. The SNP density ranged from 7.94 to 11.70 SNPs / kb, with an average of 9.86 SNPs / kb. The distribution density of core SNPs on the genome is shown in the figure below. Figure 2 As shown, this provides a high-density, high-quality reference skeleton for subsequent genotype filling of low-depth data.

[0032] (7) SNP detection in low-depth resequencing samples After quality control, the clean reads were aligned to the T2T level reference genome of the channel catfish using BWA-MEM alignment software. Following alignment, SAMtools was used to sort and mark duplicates, removing duplicate reads introduced by PCR amplification and generating a sorted and deduplicated BAM file. This BAM file served as the direct input for subsequent GLIMPSE2 genotyping. Initial SNP calling was performed based on the alignment results, yielding 25,535 original SNP loci.

[0033] (8) Construction of high-depth reference panel Using 8,463,005 high-quality SNPs obtained from high-depth resequencing as the data source for the reference panel, Beagle v5.4 software was used for genotyping and phasing. The Beagle v5.4 phasing and panel construction workflow was as follows: Genotyping: The SNP genotypic data in the reference panel were standardized in format and quality-checked to ensure consistent genotypic coding across samples; Haplotype Phasing: Beagle v5.4 used a Hidden Markov Model (HMM) to phase the diploid genotype data, correctly assigning alleles for each individual to the paternal and maternal chromosomes according to parental origin. This process iteratively optimized haplotype estimation using a sliding window algorithm, with the window size adjustable based on data characteristics; Reference Panel Construction: The phased high-density haplotype data was integrated into a binary format reference panel file for subsequent low-depth data filling.

[0034] (9) Genotype filling process Genotype filling was performed by chromosome blocks using GLIMPSE2 v2.0.0 software. GLIMPSE2 is a genotype filling and phasing tool designed for low-coverage whole-genome sequencing data. Its core algorithm uses a Gibbs sampler, iterating alternately between haplotype filling and phasing, and uses an improved Li-Stephens Hidden Markov Model (HMM) for inference. The algorithm mainly includes: Initialization: Identifying rare variants from the reference panel based on low-depth sequencing genotype likelihoods and selecting a set of relevant haplotypes; Haploid Imputation: Performing imputation on the two haplotypes of each target sample, calculating the haplotype likelihood based on the original genotype likelihood and the current estimate of the other haplotype; Diploid Assignment: Assigning a diplotype to each target sample at the end of the initialization step; Gibbs Iteration: Running a series of burn-in iterations and main Gibbs iterations to continuously optimize the genotype calls and phasing results for each target sample; Posterior Integration: Integrating phasing uncertainty by averaging the imputation posterior probabilities of all main iterations.

[0035] (10) Filling results and filling accuracy assessment After the imputation was completed, a high-quality, high-density whole-genome SNP dataset was obtained, with a total of 8,462,898 SNPs. The number of SNPs on the 29 chromosomes ranged from 157,730 (Chr29) to 424,172 (Chr2), with an average of 289,972 SNPs per chromosome. The SNP density ranged from 7.90 to 11.64 SNPs / kb, with an average SNP density of 9.80 SNPs / kb. Furthermore, the imputation accuracy for each sample was calculated, and the average imputation accuracy for all samples reached 96.67%. Figure 3 This indicates that the constructed reference panel and filling strategy have high reliability.

[0036] (11) Genome-wide association analysis of body weight traits Genome-wide SNP association analysis of weight trait in 402 spotted catfish was performed using the FarmCPU model. The model treated SNPs as fixed effects and phenotypic values ​​as dependent variables, automatically controlling for population structure and individual phylogenetic relationships during iterative fitting to reduce confounding bias. Bonferroni correction was used to set a genome-wide significance threshold: α = 0.05 / total SNP count. Manhattan plots and QQ plots were used to visualize the results. P The goodness of fit between the values ​​and the expected distribution of the null hypothesis assesses the reliability of the results. The Manhattan plot shows that the strongest association site for the weight trait is chr1:37047670 (…).P =1.79×10 -15 () Figure 4 ). QQ chart shows that observation P The values ​​in the middle range closely match the expected values, while the tails show a significant upward skewness, confirming that population stratification is effectively controlled and that genuine genetic signals are present. Figure 5 Candidate genes associated with molecular markers significantly associated with body weight traits are: α-amylase (α-Amylase).

[0037] Example 2 Example 2 of this invention conducted a molecular marker verification experiment related to the weight trait of the spotted catfish. The specific steps are as follows: The verification experiment used backup population samples from three consecutive breeding generations of spotted catfish, G2-G4. 100 fish were randomly selected from each generation, and their 18-month-old weight data were retrieved from the germplasm resource database. At the same time, tail fin samples of each fish were retrieved from the germplasm resource bank sample library for DNA extraction. The DNA extraction and quality control process was the same as in Example 1.

[0038] Subsequently, using the extracted DNA as a template, PCR amplification was performed with chr1:37047670-F / R as primers to obtain the gene fragment containing the chr1:37047670 locus (as shown in SEQ ID NO.3). The primer sequences are as follows: chr1:37047670-F:5'-AAAATCGTCCCACCTAGACC-3' (SEQ ID NO.1); chr1:37047670-R: 5'-GTGACTTTACCGATGTTGTCC-3' (SEQ ID NO. 2).

[0039] The nucleotide sequence of the molecular marker is shown in SEQ ID NO.3. chr1:37047670 is located at position 151 of SEQ ID NO.3, and the mutation type is T / C.

[0040] SEQ ID NO.3: 5'-AAAATCGTCCCACCTAGACCTCGAGTAGGACCATGGGTTCAAGTCCTACCTTGGGGCCTGGGACCTCGACACTCACCTGTAATGAACACATTTGTGAAACTCATAGCCACACAGTGACAATC TACTAGTATTATGTAATAATAGGTCTAGTGCGAATAAATAATGTCTTAGATGTCGGCTAGGACCCATCTCGAGACGACACTCCTTTTATAGACTTAAAGGACAACATCGGTAAAGTCACAAA-3'; The reaction system used for PCR was as follows: 2 μL of 100 ng / μL template DNA, 1 μL each of 10 pmol / μL upstream and downstream primers, 20 μL of Taq Mix, and double-distilled water to a final volume of 40 μL.

[0041] The PCR reaction program was as follows: pre-denaturation at 94℃ for 4 min; denaturation at 94℃ for 30 s, annealing temperature decreasing by 1℃ every two cycles starting from 60℃ (60℃→51℃), extension at 72℃ for 30 s, for a total of 20 cycles; followed by denaturation at 94℃ for 30 s, annealing at 55℃ for 30 s, extension at 72℃ for 30 s, for a total of 15 cycles; and holding at 72℃ for 10 min.

[0042] Sanger sequencing was performed on the PCR amplification products. The genotype of each individual was obtained by reading the Sanger sequencing map, and the average weight data of individuals with three genotypes (TT, TC, and CC) were statistically analyzed. This successfully verified that chr1:37047670 is significantly associated with the body weight trait. The average weight data of individuals with different genotypes at the chr1:37047670 locus are shown below. Figure 6 As shown.

[0043] Figure 6 The results showed that there were significant differences in body weight among the three genotypes of channel catfish at the chr1:37047670 locus. Among them, the average body weight of channel catfish carrying the CC genotype was significantly higher than that of individuals carrying the TC and TT genotypes.

[0044] In summary, the SNP locus screened in this invention—chr1:37047670—is significantly associated with the weight trait of the spotted catfish. Its genotype can be determined using a pair of primers, which is simple and reliable. It has promising applications in molecular marker-assisted breeding and genome selection breeding of the spotted catfish.

[0045] The above description is only a preferred embodiment of the present invention. It should be noted that for those skilled in the art, several improvements and modifications can be made without departing from the principle of the present invention, and these improvements and modifications should also be considered within the scope of protection of the present invention.

Claims

1. A molecular marker associated with the body weight of the spotted catfish, characterized in that, The molecular marker is an SNP site at position 37047670 on chromosome 1, which is a T / C mutation.

2. The molecular marker according to claim 1, characterized in that, The genotype of the SNP locus is TT, TC, or CC.

3. The molecular marker according to claim 1, characterized in that, The gene associated with the SNP site is the α-amylase gene.

4. The application of the molecular marker related to body weight of the spotted catfish as described in claim 1 in the breeding of spotted catfish.

5. A molecular marker-assisted breeding method for channel catfish, characterized in that, Includes the following steps: (1) Extract genomic DNA from the spotted catfish individuals to be tested; (2) Detect the genotype of the SNP site described in claim 1; (3) Assess the individual's weight based on genotype information; (4) Select individuals with excellent growth traits based on the evaluation results of step (3) for breeding.

6. The application of the molecular marker-assisted breeding method of claim 5 in the breeding of spotted catfish.

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