Fast-growing and high-temperature-resistant breeding chip for procambarus clarkii as well as application and individual breeding method thereof

Abstract

The invention discloses a genetic typing chip for synergistically breeding fast-growing and high-temperature-resistant characters of procambarus clarkii and an application method of the genetic typing chip. Aiming at the technical bottlenecks that the traditional procambarus clarkia breeding period is long, the character selection efficiency is low and multi-character collaborative breeding is difficult to realize, a 50K cGPS liquid-phase breeding chip, namely 'Hailongcore No.1', is constructed by taking procambarus clarkia populations of different geographical populations as genetic variation sources; single nucleotide polymorphism molecular markers obviously associated with fast-growing and high-temperature-resistant characters of the procambarus clarkii are screened through whole genome association analysis, and a breeding model is constructed according to the single nucleotide polymorphism molecular markers and is applied to improvement of economic characters of the procambarus clarkii. According to the method, rapid typing of procambarus clarkii individuals can be achieved, the problems that traditional selective breeding is long in period, poor in accuracy, low in efficiency and free of theoretical basis are solved, an efficient molecular tool is provided for improved variety breeding of procambarus clarkii, the breeding efficiency of stress-resistant high-yield new varieties is remarkably improved, and the method has important industrial application value.

Description

Technical Field

[0001] The invention belongs to the technical field of molecular breeding of aquatic animals, and particularly relates to a gene typing chip for coordinated breeding of fast-growing and high-temperature-resistant traits of Procambarus clarkii and an application method thereof. Background Art

[0002] Procambarus clarkii, native to northern Mexico and the southern United States, has rapidly spread globally due to its adaptability and rapid reproduction, becoming a key aquaculture species. Currently, China, the world's largest producer and consumer of Procambarus clarkii, has a 31.89 million mu (approximately 1.6 hectares) aquaculture area and an annual output of 3.256 million tons, accounting for approximately 9.26% of freshwater aquaculture output and ranking fourth among freshwater aquaculture species. Its total economic output is 497.4 billion yuan.

[0003] However, the long-standing practice of a pruning model and self-breeding seedling production strategy for Procambarus clarkii aquaculture, coupled with inadequate protection and identification of wild germplasm resources and low breeding efficiency, has led to a severe decline in Procambarus clarkii's germplasm resources, creating an industry bottleneck. Furthermore, global warming is expected to lead to rising temperatures, threatening aquaculture industries such as Procambarus clarkii. The optimal aquaculture temperature for Procambarus clarkii is 21-28°C. Above 30°C, crayfish begin burrowing to avoid the impact, and mortality rates increase when water temperatures exceed 33°C. June to August is the period when crayfish prices rebound, but the early onset of high temperatures forces crayfish to burrow prematurely, preventing farmers from harvesting large numbers for market and significantly reducing aquaculture profitability. Similarly, this negative impact of this harvesting model is that heat-tolerant individuals are captured, allowing those with less tolerance to hide and reproduce. This leads to a rapid decrease in crayfish genetic diversity and environmental adaptability, significantly increasing aquaculture risks.

[0004] Therefore, economic traits related to rapid growth and heat tolerance in Procambarus clarkii need to be cultivated to break the bottleneck. Due to differences in tolerance levels between individuals within a population and genetic variation between populations of the same species, traditional selective breeding techniques are currently inefficient in this regard. Genomic selection is a more promising method than traditional selective breeding to develop effective multi-genetic traits. Currently, genome-wide association studies (GWAS) have been widely used to identify markers or genes related to economic traits in aquatic species, such as rapid growth and disease tolerance in fish. However, GWAS analyses on rapid growth and heat tolerance in aquatic crustaceans are still insufficient. As a wide-temperature invasive species with a wide range of latitudes and strong environmental adaptability, crayfish is a very worthy research object for the study of heat tolerance differences among populations. Conducting a comprehensive and in-depth evaluation of Procambarus clarkii germplasm resources, developing modern biobreeding technologies, and cultivating improved varieties are important measures to promote the sustainable development of the Procambarus clarkii aquaculture industry.

[0005] High-quality genotyping methods are crucial for genomic selection and GWAS. Compared with whole-genome resequencing and simplified genome sequencing, gene chip genotyping technology offers high accuracy, good reproducibility, and low cost. Liquid-phase gene chips, in particular, not only possess these advantages but are also more flexible, simpler, and less expensive than conventional solid-state microarrays. Gene chip technology has begun to be gradually applied to trait improvement in aquatic species. Atlantic salmon was the first aquatic species to be introduced with gene chips. Researchers used a 6.5K SNPs chip to improve precocious puberty in Atlantic salmon. Subsequently, aquatic crustacean gene chips were successfully developed in the shrimp Litopenaeus vannamei and were used to genetically improve acute hepatopancreatic necrosis. Currently, a high-quality genome of the crayfish Procambarus clarkii has been assembled, laying a solid foundation for the development of liquid-phase gene chips for Procambarus clarkii. Summary of the Invention

[0006] The present invention aims to provide a gene chip for rapid growth and high-temperature resistant breeding of Procambarus clarkii, addressing the lack of rapid individual typing in the breeding of aquatic crustacean varieties. Combined with a genome-wide association analysis method, the present invention provides a molecular-assisted breeding method for the cultivation of high-temperature resistant, high-yield, and high-quality Procambarus clarkii, breaking the technical limitations of traditional selective breeding, providing a new example reference for the breeding of aquatic crustaceans, helping to achieve innovation in aquatic crustacean breeding technology, and promoting the rapid development of the aquatic crustacean seed industry.

[0007] A fast-growing and high-temperature-resistant breeding chip for Procambarus clarkii is provided. The detection product is a gene chip. The gene chip can detect SNPs sites related to the fast-growing and high-temperature-resistant properties of Procambarus clarkii.

[0008] As a preferred embodiment, the SNPs sites include some SNPs sites related to the body length, weight, abdominal segment length, abdominal segment width, abdominal segment height and abdomen length of the fast-growing crayfish, totaling 448.

[0009] As a preferred embodiment, the SNPs sites include some SNP sites related to the temperature tolerance of Procambarus clarkii, a total of 39.

[0010] A fast-growing and high-temperature-resistant breeding chip for Procambarus clarkii and SNPs sites related to the fast growth of Procambarus clarkii are used in the selection of fast-growing improved varieties of Procambarus clarkii and in products for detecting fast-growing traits.

[0011] A fast-growing and high-temperature-resistant breeding chip for Procambarus clarkii and SNPs sites related to high-temperature resistance of Procambarus clarkii, and the application of SNPs sites related to high-temperature resistance of Procambarus clarkii in the breeding of high-temperature-resistant varieties of Procambarus clarkii and high-temperature resistance trait detection products.

[0012] A method for breeding fast-growing and high-temperature-resistant individuals of Procambarus clarkii comprises the following steps:

[0013] (1) Extract genomic DNA from individuals in the reference population and breeding population, record individual phenotypes, and obtain SNP typing data using the above-mentioned gene chip;

[0014] (2) Using the genotypic and phenotypic data of the reference population, a genomic best linear unbiased prediction (GBLUP) breeding model was constructed to estimate the breeding values (GEBV) of the selected population.

[0015] (3) The rapid growth and high temperature resistance potential of the selected individuals were determined based on the GEBV values, and parents with the top 30% GEBV values were selected for group breeding.

[0016] The technical principle of the present invention is as follows: First, the whole genome resequencing data of 180 Procambarus clarkii from six different regions, namely Haikou, Hainan, Wuhu, Anhui, Jianhu, Jiangsu, Gehu, Jiangsu, Weishanhu, Shandong, and Panjin, Liaoning, were collected to screen for 51,011 high-quality, highly polymorphic SNPs. Specific probes were then designed to construct a 50K cGPS liquid-phase breeding chip, "Hailongxin No. 1." The average coverage of the marker sites on the chromosomes on this chip was 99.3%, with an average spacing of 36.7 Kb. Subsequently, 600 Procambarus clarkii reference populations were individually typed using Hailongxin No. 1, and individual traits were recorded. GWAS analysis revealed a total of 448 SNPs associated with Procambarus clarkii growth (body length, weight, abdominal segment length, abdominal segment width, abdominal segment height, and abdominal length), and 39 SNPs associated with Procambarus clarkii's temperature tolerance.

[0017] Beneficial Effects: This invention has developed the first 50K cGPS liquid-phase breeding chip for Procambarus clarkii, "Hailongxin No. 1," which boasts high locus polymorphism and uniform genomic distribution, with an average locus detection rate exceeding 99.0%, and is capable of genotyping individual Procambarus clarkii. Through efficient chip genotyping technology, combined with GWAS analysis, a breeding model was constructed using SNPs significantly associated with heat tolerance and growth. This model was applied to the population selection of superior Procambarus clarkii varieties, achieving selection accuracy close to theoretical values. This approach improves the accuracy of breeding fast-growing, heat-resistant varieties of Procambarus clarkii and shortens the traditional breeding cycle, providing a new genomic breeding method for the selection of superior varieties of Procambarus clarkii for economic traits. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] Figure 1 Schematic diagram of the distribution of the marker sites of the Hailongxin No. 1 chip on the chromosomes of Procambarus clarkii in one embodiment of the present invention.

[0019] Figure 2 Schematic diagram of the genotype detection rate of the Hailongxin No. 1 chip marker sites in a sample in one embodiment of the present invention.

[0020] Figure 3 Schematic diagram of the genotype consistency rate of the Hailongxin No. 1 chip marker site in repeated samples in one embodiment of the present invention.

[0021] Figure 4 Schematic diagram of the group typing effect of the Hailongxin No. 1 chip in one embodiment of the present invention.

[0022] Figure 5 A schematic diagram showing a comparison of growth traits among three populations in one embodiment of the present invention.

[0023] Figure 6 A schematic diagram showing a comparison of the UTT and maximum heat-resistant temperature of three groups in one embodiment of the present invention.

[0024] Figure 7 A schematic diagram of a comparative heat-resistance mortality curve for three groups in one embodiment of the present invention. DETAILED DESCRIPTION

[0025] The following is a detailed description of an embodiment of the present invention in conjunction with the accompanying drawings: This embodiment is implemented on the premise of the technical solution of the present invention, and a detailed implementation method and specific operation process are given, but the protection scope of the present invention is not limited to the following embodiment.

[0026] A fast-growing and high-temperature-resistant breeding chip for Procambarus clarkii and its application method are developed, and the specific operating steps are as follows:

[0027] 1. Development of gene chips

[0028] 1) Thirty Procambarus clarkii were collected from six different geographical latitudes: Haikou, Hainan, Wuhu, Anhui, Jianhu, Jiangsu, Gehu, Jiangsu, Weishanhu, Shandong, and Panjin, Liaoning.

[0029] 2) gDNA was obtained from the abdominal muscles of 180 Procambarus clarkii (30 mg), and a 300-500 bp DNA small fragment library was constructed. After circularization and replication, DNA nanoballs (DNBs) were formed.

[0030] 3) After Qubit quality control, paired-end sequencing was performed using the MGIDL-T7 sequencing chip using combined probe-anchored polymerase chain reaction (cPAS) technology to obtain raw sequencing data (Raw Reads).

[0031] 4) Sequencing reads were quality filtered and aligned using the Procambarus clarkii genome (NCBI accession number: GCF_020424385.1) as a reference.

[0032] 5) Putative SNPs were identified according to the following thresholds: minor allele frequency (MAF) ≥ 0.05, genotyping rate ≥ 0.1, and Hardy-Weinberg equilibrium (HWE) significance ≥ 0.01.

[0033] 6) Based on the principle that variant sites are evenly distributed on chromosomes, 51,011 high-quality SNPs were finally screened. The average number of SNPs on 94 chromosomes was 543, and the average distance between loci was 37.26 kb ( Figure 1 ), and then synthesize the corresponding probes to construct the "Hailongxin No. 1" SNP array.

[0034] 2. Gene chip typing test and quality assessment

[0035] 1) 22 samples were randomly sampled and replicated twice, generating a total of 24 sample data. These samples were typed using the "Hailongxin 1" SNP array for demo testing.

[0036] 2) Genotyping of 123 samples from three breeding populations was performed and quality control (QC) was performed again. Low-quality SNPs with significant allele frequency (MAF < 0.05), missing values (> 0.1), and high weak-weakness (HWE) (< 0.01) were removed using PLINK software and R version 3.0. A total of 33,576 SNPs were retained for population genotyping.

[0037] 3) Demo test results showed that 99.67% of SNP minor allele frequencies were > 0.1, the average genotyping success rate was 99.18%, and the genotype consistency rate of repeated samples was 98.08%-98.87% ( Figure 2 , Figure 3 ). Neighbor phylogenetic analysis showed that the test population was successfully divided into three populations, such as Figure 4 .

[0038] 3. Construction of reference population and trait testing

[0039] 1) 140 one-year-old adult shrimps were randomly selected from five different groups cultured under the same environment in Wuhu, Anhui, China (latitude and longitude), with a female-to-male ratio of 1:1, for a total of 600 shrimps.

[0040] 2) Growth trait collection. The population origin and sex of each shrimp were recorded. Growth parameters of each shrimp were measured using a vernier caliper and a balance, including total length, body length, abdominal length, abdominal segment length, abdominal segment width, abdominal segment height, body wet weight, and meat wet weight.

[0041] 3) Collection of heat-resistance traits. The Arrhenius breaktemperatures (ABT) index of heart rate was used to evaluate the differences in heat-resistance of Procambarus clarkii. After the reference group was caught from the pond, it was temporarily kept at 25°C for 1 day. After that, the individuals in the reference group were connected to the infrared heart rate detector and placed in the experimental glass tank. The temperature setting range was 26-36°C, and the temperature test was carried out at a rate of 0.5°C / 30min. After the heart rate stabilized, the heart rate waveform and parameters were continuously collected for 10 minutes using LabChart software, and the ABT value of each crayfish individual was calculated according to the Arrhenius equation to evaluate the individual heat-resistance differences.

[0042] 4. Whole-genome association analysis

[0043] 1) Association analysis of growth traits. This study focused on growth traits such as total length, body length, abdominal length, abdominal segment length, abdominal segment width, abdominal segment height, and body weight of Procambarus clarkii. A GWAS was performed using a mixed linear model (MLM) in the GAPIT package in the R language to analyze phenotypic and SNP data. Low-quality SNPs were removed prior to GWAS analysis. The equation used for the MLM model is as follows:

[0044] Y=Xβ+Zμ+e,

[0045] Where Y is the growth trait phenotype vector, X is the fixed effects matrix, β is the covariate and fixed effects vector including the first three principal components of the population and sex of Procambarus clarkii, Z is the matrix of random additive genetic effects, u is the vector representing the random effect coefficients, and e is the residual effect. A modified Bonferroni correction was used to define the significance threshold. The genome-wide significant association and suggestive association thresholds were 0.05 / N and 1 / N, respectively, where N is the number of SNPs used in the association analysis. The specific code is as follows:

[0046] #Load R package

[0047] library(GAPIT)

[0048] library(writexl)

[0049] #Read data file (assuming it is in CSV format)

[0050] data<-read.csv("your_data_file.csv",header=TRUE,na.strings=

[0051] "-1")

[0052] #Processing gender variables (female = 0, male = 1)

[0053] data$sex<-ifelse(data$sex=="male",1,0)

[0054] #Extract phenotypic data (individual ID and growth traits)

[0055] Y<-data[,c(1,4)]

[0056] colnames(Y)<-c("Taxa","Growth_Trait")

[0057] #Extract covariates (group and gender)

[0058] CV<-data[,c(2,3)]

[0059] colnames(CV)<-c("Population","Gender")

[0060] #Extract genotype data and transpose it into GAPIT format (SNP as rows, individuals as columns) geno_raw<-data[,5:ncol(data)]

[0061] #Build the genotype format required by GAPIT

[0062] geno_formatted<-data.frame(

[0063] SNP=colnames(geno_raw),

[0064] Chromosome=1,

[0065] Position=1:ncol(geno_raw),

[0066] t(geno_raw))

[0067] colnames(geno_formatted)[4:ncol(geno_formatted)]<-data[,1]

[0068] #Replace -1 with NA

[0069] geno_formatted[geno_formatted==-1]<-NA

[0070] #Run GWAS analysis

[0071] myGAPIT<-GAPIT(

[0072] Y=Y,# phenotypic data

[0073] G = geno_formatted, # genotype data

[0074] CV = CV, # covariate matrix (group, gender) PCA.total = 3, # automatically add the first three principal components model = "MLM", # mixed linear model

[0075] MAF.threshold=0.05,#MAF filter threshold

[0076] geno.missing rate = 0.1, # genotype missing rate filter HWE.threshold = 0.01, # HWE test filter

[0077] file.output=FALSE)#Turn off default output

[0078] #Extract GWAS results

[0079] gwas_results<-myGAPIT$GWAS

[0080] #Calculate the number of effective SNPs

[0081] N<-nrow(gwas_results)

[0082] #Calculate significance threshold

[0083] bonferroni_significant<-0.05 / N

[0084] suggestive<-1 / N

[0085] #Add significant mark

[0086] gwas_results$Threshold<-ifelse(gwas_results$P.value<=

[0087] bonferroni_significant,"Genome-wide significant",

[0088] ifelse(gwas_results$P.value<=suggestive,"Suggestive","Not

[0089] significant")

[0090] #Save the results as Excel file

[0091] write_xlsx(gwas_results,"GWAS_Results.xlsx")

[0092] # Output filter information

[0093] cat(paste("Analysis includes",N,"SNPs\n",

[0094] "Genome-wide significance threshold:",bonferroni_significant,"\n",

[0095] "Suggestive association threshold:",suggestive))

[0096] 2) Association analysis of heat tolerance traits. In this experiment, higher ABT values indicate greater heat tolerance. A binary analysis of the heat tolerance traits of Procambarus clarkii was performed. Based on the distribution of ABT within the population, individuals with ABT < 30°C were defined as heat-intolerant individuals, and individuals with ABT > 32°C were defined as heat-tolerant individuals, represented by 0 and 1, respectively. In R, a mixed linear model (MLM) in the GAPIT software package was used to perform GWAS on phenotypic and SNP data. The equation used for the MLM model is the same as in 4-1, and the code is as follows:

[0097] #Load R package

[0098] library(GAPIT)

[0099] library(writexl)

[0100] #Read data file (assuming it is in CSV format)

[0101] data<-read.csv("your_data_file.csv",header=TRUE,na.strings="-1")

[0102] #Convert the ABT value into a binary trait (0 = not heat-resistant, 1 = heat-resistant), excluding the intermediate value data$heat-resistant trait <-ifelse(data$ABT<30,0,

[0103] ifelse(data$ABT>32,1,NA))

[0104] data<-na.omit(data)#Delete samples with ABT between 30-32

[0105] #Processing gender variables (female = 0, male = 1)

[0106] data$sex<-ifelse(data$sex=="male",1,0)

[0107] #Extract phenotypic data (individual ID and binary heat tolerance traits)

[0108] Y<-data[,c(1,4)]

[0109] colnames(Y)<-c("Taxa","Thermotolerance")#Column names must strictly match GAPIT requirements

[0110] #The following steps are the same as 4-1.

[0111] 3) According to the set threshold, a total of 487 SNPs sites significantly associated with growth and heat resistance traits were screened, including 448 SNPs related to the growth of Procambarus clarkii (body length, weight, abdominal segment length, abdominal segment width, abdominal segment height, and abdomen length), and 39 SNPs related to heat resistance of Procambarus clarkii. The results are shown in Table 1.

[0112] 5. Gene collection and separation of breeding populations

[0113] 1) Before the gonads of Procambarus clarkii mature, select high-quality and healthy broodstock and use sterilized dissecting scissors to cut off the third pair of walking legs of Procambarus clarkii as the source of genetic material.

[0114] 2) After taking the DNA sample, a special tag is fixed on one of the chelipeds of the crayfish to distinguish individuals.

[0115] 3) In order to prevent the breeding group from mating prematurely, after the genetic material is collected, the male and female crayfish are separated according to gender and temporarily raised in canvas ponds for daily management.

[0116] 4) Use Hailongxin No. 1 to genotype the breeding population.

[0117] 6. Breeding model construction and breeding value prediction

[0118] 1) Genotype data integration: The genotypes of the reference population and the breeding population were merged to form a joint matrix. Only the 487 significant SNPs screened by GWAS were retained, and the genotypes were coded and standardized.

[0119] 2) Phenotypic data standardization: Nine growth traits of the reference population were Box-Cox transformed to eliminate dimensional differences. The heat tolerance trait (ABT) was kept binary coded (0 / 1), and a population-sex interaction effect matrix was constructed.

[0120] 3) Use the VanRaden method to calculate the genomic kinship matrix, construct a mixed model equation, build a model for each trait, and solve the breeding value using the BLUP method. The specific code is as follows:

[0121] #Load R package

[0122] library(rrBLUP)

[0123] library(data.table)

[0124] library(BMTME)

[0125] #Read reference population data (including phenotype)

[0126] ref_data<-fread("reference_population.csv",na.strings="-1")

[0127] # Breeding population data (no phenotype)

[0128] sel_data<-fread("selection_population.csv",na.strings="-1")

[0129] #Read the GWAS significant site list (assuming it has been saved as CSV)

[0130] sig_snps<-fread("significant_snps.csv")$SNP_ID

[0131] #Merge genotype data

[0132] all_geno<-rbind(ref_data[,c(1,13:ncol(ref_data)),with=FALSE],sel_data[,c(1,4:ncol(sel_data)),with=FALSE])

[0133] #Screen significant SNP sites

[0134] geno_filtered<-all_geno[,c("ID",sig_snps),with=FALSE]

[0135] #Build genome relationship matrix G

[0136] M<-as.matrix(geno_imputed)

[0137] Z<-scale(M,center=TRUE,scale=TRUE)

[0138] #VanRaden method to calculate G matrix

[0139] G<-tcrossprod(Z) / mean(diag(tcrossprod(Z)))

[0140] # Divide reference set and breeding set

[0141] ref_ids<-ref_data$ID

[0142] sel_ids<-sel_data$ID

[0143] G_ref<-G[rownames(G)%in%ref_ids,colnames(G)%in%ref_ids]

[0144] G_sel<-G[rownames(G)%in%sel_ids,colnames(G)%in%ref_ids]

[0145] #Build a breeding model and define the list of traits to be analyzed

[0146] traits<-c("ABT","TotalLength","BodyLength","BodyWeight",

[0147] "AbdominalSegLength","AbdominalSegWidth",

[0148] "AbdominalSegHeight","AbdomenLength","AbdomenRatio")

[0149] # Initialize result storage

[0150] gebv_results<-data.frame(ID=sel_ids)

[0151] #Loop through each trait

[0152] for(trait in traits){

[0153] #Extract reference population phenotypic data

[0154] if(trait=="ABT"){

[0155] # Binary trait processing

[0156] y<-ref_data[[trait]]

[0157] y<-factor(y,levels=c(0,1))

[0158] }else{#Continuous trait standardization

[0159] y<-scale(ref_data[[trait]])}

[0160] #Build fixed effect matrix (group + gender)

[0161] X<-model.matrix(~factor(Population)+factor(Sex),data=ref_data)

[0162] # Fit the model using rrBLUP

[0163] model<-kin.blup(

[0164] data=data.frame(y=y,X[,-1]),

[0165] geno="ID",

[0166] pheno="y",

[0167] K = G_ref)

[0168] #Predicting breeding population GEBV

[0169] gebv<-G_sel%*%solve(G_ref)%*%model$u

[0170] gebv_results[[paste0(trait,"_GEBV")]]<-gebv[match(sel_ids,names(gebv))]}

[0171] #Save breeding value prediction results

[0172] fwrite(gebv_results,"GEBV_Predictions.csv")

[0173] 7. Genomic Selection Breeding

[0174] 1) 30% of the best male and female individuals with the highest breeding values were selected from 200 breeding groups (Table 2), and they were placed in a pond. After gonadal enhancement, group mating was performed.

[0175] 2) Randomly select the same number of unselected male and female individuals from the breeding group as the breeding group for mating as the control group 1.

[0176] 3) The male and female individuals with the lowest breeding values of 30% were mated in groups as control group 2.

[0177] 8. Breeding effect evaluation

[0178] 1) Growth trait evaluation. In mid-March 2025, the growth traits of three groups raised in the same environment in Wuhu, Anhui were measured, and the measurement results are shown in Table 3. The growth advantage of the selected group was significantly higher than that of the unselected control group 1 and the eliminated control group 2. Compared with the unselected group, the average total length of the selected group increased by 11.84 mm, an increase of 26.68%; the average body length increased by 11.11 mm, an increase of 28.17%; the average abdominal length increased by 3.6 mm, an increase of 29.71%; the average abdominal segment length increased by 1.2 mm, an increase of 25.23%; the average abdominal segment width increased by 2.55 mm, an increase of 21.19%; the average abdominal segment height increased by 1.7 mm, an increase of 27.18%; the average body weight increased by 2.63 g, an increase of 107.41%. Figure 5 shown.

[0179] 2) Evaluation of heat resistance traits. The upper thermal tolerance (UTT) index was selected, and the heat resistance traits of three groups cultured in the same environment in Wuhu, Anhui were measured. In short, the test group was caught from the pond and temporarily kept in an environment of 25°C for 1 day. Afterwards, the test group was placed in an experimental glass tank. The starting temperature was 26°C, and the temperature was increased at a rate of 1°C / 2h. When the temperature was higher than 35°C, the temperature stress was continued at 0.5°C / 4h until all the experimental shrimp died. The death time and temperature of each shrimp were accumulated, and the measurement results are shown in Table 4. The heat resistance advantage of the selected group was significantly higher than that of the unselected control group 1 and the eliminated control group 2. Compared with the unselected group, the average UTT value of the selected group was increased by 72.81%, the maximum heat resistance temperature was increased by 1.43°C, and the half-lethal survival time was delayed by 478min. Figure 6 、 Figure 7 .

[0180] The above examples show that the GBLUP breeding model constructed based on the typing of the Hailongxin No. 1 gene chip and the SNP molecular markers significantly associated with rapid growth and heat resistance obtained through GWAS analysis has a significant effect on improving the growth traits and heat resistance traits of the offspring of the Procambarus clarkii population, which proves that Hailongxin No. 1 has great promotion value in the cultivation of excellent varieties of Procambarus clarkii.

[0181] Table 1 SNPs significantly associated with growth and heat resistance screened by GWAS

[0182]

[0183]

[0184]

[0185]

[0186]

[0187]

[0188]

[0189] Table 2 shows the breeding values of the selected parents

[0190]

[0191]

[0192] Table 3 is the growth trait statistics table

[0193]

[0194]

[0195] Table 4 is a statistical table of heat resistance characteristics

[0196]

[0197] The basic principles, main features, and advantages of the present invention are shown and described above. Those skilled in the art should understand that the present invention is not limited to the above embodiments. The above embodiments and descriptions are merely illustrative of the principles of the present invention. Various changes and modifications may be made to the present invention without departing from the spirit and scope of the present invention. Such changes and modifications are intended to fall within the scope of the present invention. The scope of protection claimed in the present invention is defined by the appended claims and their equivalents.

Claims

1. A fast-growing and heat-resistant breeding chip for Procambarus clarkii, characterized in that: The detection product is a gene chip, and the gene chip can detect SNPs sites related to the fast growth and heat resistance of Procambarus clarkii.

2. The fast-growing and heat-resistant breeding chip for Procambarus clarkii according to claim 1, characterized in that: The SNPs sites include some SNP sites related to the body length, weight, abdominal segment length, abdominal segment width, abdominal segment height and abdomen length of the fast-growing crayfish, totaling 448.

3. The fast-growing and high-temperature-resistant breeding chip for Procambarus clarkii according to claim 1, characterized in that: The SNPs sites include some SNP sites related to the temperature tolerance of Procambarus clarkii, totaling 39.

4. A fast-growing and high-temperature-resistant breeding chip for Procambarus clarkii and SNPs sites related to the fast growth of Procambarus clarkii, and its application in the selection of fast-growing and improved varieties of Procambarus clarkii and in the detection of fast-growing traits.

5. A fast-growing and high-temperature-resistant breeding chip for Procambarus clarkii and SNPs sites related to high-temperature resistance of Procambarus clarkii, and the application of SNPs sites related to high-temperature resistance of Procambarus clarkii in the selection of high-temperature-resistant varieties of Procambarus clarkii and high-temperature resistance trait detection products.

6. A method for breeding fast-growing and high-temperature-resistant individuals of Procambarus clarkii, characterized in that: The steps are as follows: (1) Extract genomic DNA from individuals in the reference population and breeding population, record individual phenotypes, and obtain SNP typing data using the above-mentioned gene chip; (2) Using the genotypic and phenotypic data of the reference population, a genomic best linear unbiased prediction (GBLUP) breeding model was constructed to estimate the breeding value (GEBV) of the selected population; (3) The rapid growth and high temperature resistance potential of the selected individuals were determined based on the GEBV values, and parents with the top 30% GEBV values were selected for group breeding.

Images