Meat duck whole genome molecular probe combination, 50K gene chip and application thereof

Abstract

The invention belongs to the technical field of gene detection and gene molecular breeding, and particularly relates to a meat duck whole genome molecular probe combination based on molecular phenotype screening, a 50K gene chip and application thereof. The molecular probe combination and the gene chip of the marker site combination for meat duck whole genome breeding simultaneously cover 7 representative meat duck varieties and 71 economic characters, have richer polymorphism and higher pertinence in meat duck groups, and are lower in cost and higher in speed compared with high-throughput sequencing detection; the breeding chip is designed according to the growth, feed efficiency, slaughtering, breeding, egg quality and various molecular phenotypes of the meat ducks, and compared with a high-throughput sequencing technology, the breeding chip is higher in seed selection accuracy, has higher breeding value, can be widely applied to breeding genotype detection of the meat ducks, and can be used for detecting the breeding genotypes of the meat ducks. And the method has creative significance in the aspect of meat duck genome selective breeding.

Description

TECHNICAL FIELD

[0001] The present application belongs to the technical field of gene detection and gene molecular breeding, and particularly relates to a meat duck whole genome molecular probe combination based on molecular phenotype screening, a 50K gene chip and application thereof. BACKGROUND

[0002] As one of the most dynamic and distinctive industries in China's animal husbandry, the meat duck industry has exceeded 5 billion in the national output in 2024. At present, white-feathered meat ducks account for 83.3% of the meat duck breeds. Meat ducks not only provide a large amount of meat, down products and a variety of foodstuffs, but also play an important role in enriching the people's diet culture. The contribution rate of meat duck breeding to the development of the meat duck industry has exceeded 40%. The current breeding technology of meat ducks mainly relies on traditional individual phenotype direct selection, family selection and BLUP selection, and there is still a lot of room for improvement in selection efficiency. Whole genome selection technology is a breeding technology that predicts phenotypes by using genetic markers covering the entire genome. Compared with traditional breeding methods, this technology can realize early selection, shorten the generation interval and improve the accuracy of breeding value estimation.

[0003] Genotype detection is the premise of genomic selection breeding. The current method for genotype determination of whole genome selection of meat ducks is second-generation resequencing technology. Although this technology can detect markers at the whole genome level, the sequencing cost is still high, the determination period is long, and the post-mark data analysis is complicated, making it difficult to be widely applied in breeding. Gene chip technology is a high-efficiency and low-cost genomic breeding technology with the advantages of short cycle, low cost and high analysis efficiency, which has been widely used in livestock and poultry genomic selection breeding. However, although there are liquid chips for ducks in the field, these chips cannot meet the requirements of whole genome selection breeding. The site design is only derived from a small number of trait-associated sites, and lacks practical effect test for whole genome selection application. Therefore, it is urgent to develop a general breeding chip for meat duck growth, feed efficiency, slaughter, reproduction, meat quality and other economic traits to meet the application requirements of meat duck genomic selection technology in all-round breeding of multiple traits, and to accelerate the application and promotion of meat duck genomic selection technology. SUMMARY

[0004] In order to overcome the shortcomings of the prior art, the present application provides a meat duck whole genome breeding chip and its application method. The chip contains a series of core sites significantly related to 71 traits such as growth, feed efficiency, slaughter, reproduction, egg quality and meat quality, and contains background sites to ensure the accuracy of the designed chip detection, which can be widely used in whole genome selection breeding, marker-assisted breeding, trait-related genotype identification, kinship identification, population genetic diversity analysis and whole genome association analysis of multiple economic traits of meat ducks.

[0005] The application discloses a molecular probe combination of marker locus combination for whole genome selection of meat duck, wherein the marker locus combination is composed of 53618 molecular markers, i.e., 53130 SNPs and 488 INDELs, the position information of the 53130 SNPs is shown in Table 1, the position information of the 488 INDELs is shown in Table 2, and the reference genome of the physical position is a meat duck reference genome IASCAAS_PekinDuck_T2T.

[0006] Table 1: 53130 SNPs position information

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[0112] Table 2: 488 INDELs position information

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[0116] The application also discloses an application of the meat duck whole genome molecular probe combination in preparation of a meat duck genome gene chip.

[0117] The application further discloses a 50K gene chip for meat duck whole genome selection, wherein the chip is loaded with the meat duck whole genome molecular probe combination.

[0118] Preferably, the 50K gene chip for meat duck whole genome selection is a liquid phase chip.

[0119] The application also discloses a kit for meat duck genotyping, wherein the kit comprises the meat duck whole genome molecular probe combination or the meat duck whole genome 50K gene chip.

[0120] The application also discloses an application of the meat duck whole genome molecular probe combination or the meat duck whole genome gene chip or the kit for meat duck genotyping in meat duck genome selection.

[0121] The application also discloses an application of the meat duck whole genome molecular probe combination or the meat duck whole genome gene chip or the kit for meat duck genotyping in meat duck breed identification, breed tracing or kinship identification.

[0122] Application of the foregoing meat duck whole genome molecular probe combination or the foregoing meat duck whole genome gene chip or the foregoing kit for meat duck genotyping in meat duck whole genome association analysis or trait-related gene positioning.

[0123] Application of the foregoing meat duck whole genome molecular probe combination or the foregoing meat duck whole genome gene chip or the foregoing kit for meat duck genotyping in meat duck whole genome association analysis or trait-related gene positioning.

[0124] Application of the foregoing meat duck whole genome molecular probe combination or the foregoing meat duck whole genome gene chip or the foregoing kit for meat duck genotyping in meat duck whole genome association analysis or trait-related gene positioning.

[0125] Compared with the prior art, the application has the following beneficial effects:

[0126] The meat duck whole genome molecular probe combination and the whole genome chip are for whole genome sequencing of meat duck breeds, have relatively rich polymorphism in a meat duck population, are more targeted, and have lower detection cost and faster speed compared with high-throughput sequencing technology; relevant sites for meat duck growth, feed efficiency, slaughter, reproduction, egg quality and various types of molecular phenotypes are mined, a breeding chip is designed, the selection accuracy is higher compared with high-throughput sequencing technology, has relatively high breeding value, can be widely applied to breeding genotype detection of meat ducks, and has a pioneering significance for meat duck genomic selection breeding. BRIEF DESCRIPTION OF DRAWINGS

[0127] Figure 1 A flow chart for meat duck 50K gene chip site design;

[0128] Figure 2 A distribution diagram of different chromosomes of meat duck 50K gene chip marker sites;

[0129] Figure 3 A quantity distribution diagram of different chromosomes of meat duck 50K gene chip marker sites;

[0130] Figure 4 A whole genome association analysis result diagram of plasma cholinesterase;

[0131] Figure 5 A principal component analysis diagram of test data of two strains. DETAILED DESCRIPTION

[0132] The technical solutions of the present application are described in detail below in combination with examples. The following examples are only used to more clearly illustrate the present application and cannot be used to limit the protection scope of the present application. Unless otherwise specified, the technical terms or scientific terms used in the present application are the commonly understood meanings by the skilled in the art to which the present application belongs. In the following examples, the experimental methods are all conventional methods, which are carried out according to the techniques or conditions described in the literature in the art or according to the product instructions, unless otherwise specified. The materials, reagents and the like used in the following examples can be obtained from commercial channels, unless otherwise specified.

[0133] As shown in the preparation method of the meat duck 50K breeding liquid phase gene chip, the following steps are included: Figure 1

[0134] (1) In the 3795 meat duck breeding population, considering the growth, feed efficiency, carcass, meat quality, reproduction, egg quality of the duck, 71 traits, based on the mixed linear model, the whole genome association analysis (GWAS) of the genotype and the trait phenotype is carried out, the GWAS significant signal is de-redundant by the linkage disequilibrium (LD), and the functional markers affecting the growth, feed efficiency, slaughter traits, meat quality traits, reproduction traits, egg quality traits and the like are obtained.

[0135] (2) The phenotypes of 16 kinds of plasma biochemical indexes: glutamic-pyruvic transaminase, glutamic-oxaloacetic transaminase, cholinesterase, total protein, albumin, total bilirubin, direct bilirubin, alkaline phosphatase, lactic dehydrogenase, glucose, uric acid, total cholesterol, triglyceride, high-density lipoprotein cholesterol, low-density lipoprotein cholesterol and phosphorus are determined, the whole genome association analysis is used, the GWAS significant signal is de-redundant by the LD, and the functional markers affecting the plasma biochemical indexes are obtained.

[0136] (3) 1174 and 1018 kinds of metabolites are identified in the muscle and the plasma, the whole genome association analysis of the metabolites is used, the LD is de-redundant, and the functional markers affecting the muscle and the plasma metabolite abundance are obtained.

[0137] (4) The microbial amplicon sequence variant (ASV) molecular phenotype in the cecum content is identified, the whole genome association analysis of the microorganism is used, the LD is de-redundant, and the functional markers affecting the cecum microbial abundance are obtained.

[0138] (5) The functional markers regulating the gene expression are obtained by the cis-eQTL positioning, conditional eQTL analysis and LD de-redundancy of the gene expression in the pectoral muscle, liver and pancreas.

[0139] ​(6) Download 371 duck re-sequencing data of 6 breeds from the NCBI SRA database, including 166 Shaoxing ducks, 122 wild ducks, 33 Liancheng white ducks, 25 Z-type Beijing ducks, 17 Cherry Valley ducks, and 8 Maple Leaf ducks, identify genotypes, and use for selection signal (Fst) analysis to screen functional markers selected.

[0140] (7) Select sites that meet the following conditions: site heterozygosity < 50% (relaxed to 65% when filling gaps), deletion rate < 10%, and minimum allele frequency ≥ 0.35 (relaxed to 65% when filling gaps), and select background sites according to the principle of uniform distribution.

[0141] (8) Screen qualified probes that meet the above functional sites and background sites through a probe design system to create a 50K gene chip for meat duck genomic breeding as described above.

[0142] Example 1: Preparation of a 50K breeding chip for meat ducks

[0143] I. Construction of breeding population and determination of trait phenotypes

[0144] The breeding population used in the present application is from a white meat duck resource population jointly established by the Beijing Institute of Animal Science and Veterinary Medicine of the Chinese Academy of Agricultural Sciences and Shandong Zhongxin Food Co., Ltd. A total of 3795 Zhongxin white meat ducks from three generations in 2020-2023 were selected, and 14-day entry weight, 42-day exit weight, weight gain, metabolic weight, feed intake, feed conversion rate (FCR), residual feed intake (RFI), breast muscle width, keel length, breast muscle thickness (determined by B-ultrasound), breast muscle volume, and a total of 11 growth and feed efficiency traits were determined. Among them, 1019 ducks were subjected to a 42-day slaughter test, and 38 slaughter traits such as carcass weight / rate, whole eviscerated weight / rate, foot palm weight / rate, chest skin weight / rate, neck skin weight / rate, breast muscle weight / rate, chest muscle weight / rate, leg weight / rate, wing root weight / rate, two-section wing weight / rate, whole wing weight / rate, head weight / rate, neck weight / rate, skeleton weight / rate, intestine weight / rate, liver weight / rate, heart weight / rate, duck gizzard weight / rate, abdominal fat weight / rate, and 6 meat quality traits such as breast muscle shear force, water loss rate, pH, meat color a, meat color b, and meat color L were determined. For 1814 female ducks, 7 reproductive traits such as 210-day egg production, 280-day egg production, 300-day egg production, 25-28 week early egg production, 29-47 week peak egg production, 48-60 week late egg production, and 25-60 week egg production rate were determined, as well as 9 egg quality traits such as egg weight, egg length, egg short diameter, egg shape index, egg shell strength, egg shell weight, egg yolk weight, egg yolk height, and Haugh unit.

[0145] II. Genotype determination

[0146] From the above breeding population of 3795 meat ducks, blood was collected, and whole genome DNA was extracted using the standard phenol-chloroform method, a DNA library was constructed, and after the library was evaluated, it was qualified, and using DNBSEQ-T7 sequencing platform, PE150 sequencing was performed. The sequencing sequences obtained by sequencing were removed using Fastp (v.0.23.2) software to remove sequencing adapters and low-quality bases, and Clean Reads were obtained. The mem algorithm in BWA (v.0.7.17-r1188) software was used to align Clean Reads to the reference genome IASCAAS_PekinDuck_T2T. The PCR repeat sequences in the aligned bam file were removed using the Picard (v.1.123) software. The HaplotypeCaller module of GATK (v.4.6.1.0) was used for extraction and identification of genomic variations. The identified variation types include SNP and Indel. The combined genotype data of 3795 meat ducks was quality controlled, and 10349420 genomic variation sites with a minimum gene frequency greater than 0.05, a variation detection rate greater than 0.9, and located in autosomes were retained for downstream meat duck chip design.

[0147] III. Molecular phenotype determination

[0148] From the above breeding population for slaughter trait determination, 507 meat ducks were selected according to the principle of covering the family, and molecular phenotype determination was performed at 42 days of age. The determined molecular phenotypes include: plasma biochemical indicators, muscle and plasma metabolite abundance, cecum microbial abundance, chest muscle, liver, pancreas tissue gene expression.

[0149] (1) Plasma biochemical indicators

[0150] EDTA anticoagulant tubes were used for wing vein blood collection of 507 42-day-old meat ducks, and blood was centrifuged at 3000 rpm for 10 minutes, and the supernatant was aspirated and stored at -80°C for plasma biochemical indicator determination and plasma metabolite determination. The plasma was detected for 16 biochemical indicators by using an automatic biochemical analyzer (model: Hitachi 7080), including alanine aminotransferase (ALT), aspartate aminotransferase (AST), cholinesterase (CHE), total protein (TP), albumin (ALB), total bilirubin (TBIL), direct bilirubin (DBIL), alkaline phosphatase (ALP), lactate dehydrogenase (LDH) glucose (GLU), uric acid (UA), total cholesterol (CHOL), triglyceride (TG), high-density lipoprotein cholesterol (HDLC), low-density lipoprotein cholesterol (LDLC), and phosphorus (P), and the biochemical indicator detection reagent was purchased from Maike Biological Co., Ltd.

[0151] (2) Muscle and plasma metabolite abundance

[0152] Muscle metabolite determination: 100 mg of breast muscle of 42-day-old ducks was collected and ground in liquid nitrogen, placed in an EP tube, 500 μL of 80% methanol was added, vortexed and shaken, ice bathed for 5 min, 15000 g, 4°C centrifuged for 20 min, a certain amount of supernatant was diluted with mass spectrometry grade water to 53% methanol, 15000 g, 4°C centrifuged for 20 min, the supernatant was collected, and the sample was detected by liquid chromatography-mass spectrometry (LC-MS). Plasma metabolite determination: 100 μL of sample was placed in an EP tube, 400 μL of 80% methanol aqueous solution was added, and the other steps were the same as muscle metabolite determination. The raw file (.raw) obtained by mass spectrometry detection was imported into CompoundDiscoverer 3.3 software for spectrum processing and database search, and the qualitative and quantitative results of metabolites were obtained. The quantitative results were converted by log2 for final statistical analysis.

[0153] (3) Gene expression in breast muscle, liver and pancreas tissue

[0154] The breast muscle, liver and pancreas tissue of 42-day-old ducks were collected and placed in a frozen tube in liquid nitrogen for standby. The Trizol method was used to extract RNA from the tissue sample, and after the RNA was detected, the mRNA was enriched from the total RNA using Oligo dT magnetic beads, the cDNA library was constructed, and after the library was detected, the double-end PE150 sequencing was performed on the Illumina platform, and the sequencing amount was greater than 6G. After sequencing, the adapter sequence was removed by Cutadapt (v2.8), and the low-quality bases were removed by Fastp (v.0.23.2) software. The quality-controlled reads were aligned to the duck reference genome IASCAAS_PekinDuck_T2T by STAR (v2.7.10b) software. The aligned file and gene annotation gtf file were processed by Stringtie (v2.2.1) software, and the expression of each gene (TPM) was quantified. The genes with expression TPM>0.1 in at least 20% of the samples and located in autosomes were retained, and finally 15406 breast muscle genes, 14228 liver genes and 12433 skin genes were obtained as molecular phenotypes for downstream chip site mining.

[0155] (4) Microbial abundance in cecum

[0156] The cecal contents of 42-day-old meat ducks were collected, placed in cryogenic tubes, and stored in liquid nitrogen for later use. The Qiagen microbial DNA extraction kit was used to extract the cecal content DNA. After the DNA sample was amplified and detected, the PCR product was mixed and purified, and then subjected to end repair, A tailing, sequencing adapter addition, and purification to complete the 16s amplicon library preparation. The amplification region was V3-V4, and after library detection, double-end PE150 sequencing was performed on the Illumina platform with a sequencing amount of 20M reads. After sequencing, the sequencing data was processed using Cutadapt v2.8 to remove the adapter sequence, and vsearch (v2.28.1) software was used to splice the reads of each sample to obtain Raw Tags data. Fastp software was used to filter and process the Raw Tags to obtain high-quality Tags data (Clean Tags). The Clean Tags were compared with the Silva database (https: / / www.arb-silva.de / ) using vsearch software to remove chimeric sequences and obtain the final effective data Effective Tags. According to the sequence similarity, vsearch was used to cluster the sequences at 100% similarity to generate amplicon variant sequences (ASVs), remove plasmids and non-bacteria through species annotation, and quantify the abundance. ASVs identified in at least 20% of the samples were retained, and finally 1751 ASVs were obtained as microbial molecular phenotypes for downstream chip site mining.

[0157] IV. Duck 50K Breeding Chip Site Design

[0158] (1) Important economic trait-related site design

[0159] Important economic traits include seven categories (growth, feed efficiency, carcass, meat quality, reproduction, egg quality) and 71 traits. Based on the mixed linear model, whole genome association analysis of genotype and trait phenotype was performed, and the covariates included batch, gender, season, and the first three principal components of the genotype. The association analysis was completed in the GCTA (v1.93.0) software under the --mlma parameter. Based on P<1x10 -5 Filtering the GWAS results, 1721 growth trait significant sites, 525 feed efficiency trait significant sites, 27014 slaughter trait significant sites, 1023 meat quality trait significant sites, 861 reproduction trait significant sites, and 1799 egg quality trait significant sites were obtained.

[0160] Because of the strong linkage disequilibrium (LD) between the significant loci in the same signal in the GWAS results, when designing the chip, considering a marker site can capture the genetic variance of the entire signal. Therefore, it is still necessary to further remove redundancy of the GWAS significant loci through LD. First, according to the significance of the P value from the GWAS results, the SNPs are sorted to obtain a SNP candidate list. The first top SNP after sorting is selected, and the LD degree r2 of the SNP within the upstream and downstream 500Kb range is calculated. The candidate list is deleted if the linkage degree of the current top SNP is too high (r 2 >0.2), and the top SNP is retained. If there is no SNP with high linkage degree of the current top SNP, it is considered that the top SNP is an isolated SNP caused by false positives, and the top SNP is not retained. In this way, the first top SNP is removed and the candidate list is reduced. Next, the process is repeated to complete the next SNP with a high P value in the new candidate list until all SNPs are detected. Through the above analysis, 158 independent markers of growth traits, 82 independent markers of feed efficiency, 3386 independent markers of slaughter traits, 135 independent markers of meat quality traits, 101 independent markers of reproduction traits, and 284 independent markers of egg quality traits are obtained.

[0161] (2) Design of molecular phenotype-related loci of plasma biochemical indicators

[0162] Using a mixed linear model, whole genome association analysis was performed on the resequencing genotypes and 16 kinds of plasma biochemical indicators one by one, considering the covariates of batch, gender, and the first three principal components of genotype. Based on the GCTA (v1.93.0) software, GWAS analysis was completed under the mlma parameter. Through P<1×10 -5 Filtering the GWAS results, 6206 significant loci related to 16 kinds of plasma biochemical indicators were obtained, and through LD r 2 >0.2 redundancy (method same as above), 2287 biochemical indicator QTLs were identified, and QTLs with only one marker were deleted, obtaining 737 candidate QTLs affecting 16 kinds of plasma biochemical indicators. The most significant P value was selected as the representative marker of each QTL, and finally 737 candidate markers were obtained.

[0163] (3) Design of molecular phenotype-related loci of plasma and muscle metabolites

[0164] 1174 and 1018 metabolites were identified in muscle and plasma, respectively. After log2 transformation of the metabolite abundance, rank-based inverse normal transformation was performed by GenABEL (R package). Association analysis between SNPs and each metabolite molecular phenotype was performed by using mixed linear model (--mlma) in GCTA software, with batch, sex, and the first three principal components of genotypes as covariates. The significance threshold of the association between genotypes and metabolite molecular phenotypes was P<5x10 -8 , and 23189 loci significantly affected 709 plasma metabolites. By LD r 2 >0.2 to remove redundant QTLs and QTLs with only one marker, 2308 independent candidate markers affected 317 muscle metabolites and 2144 independent candidate markers affected 494 plasma metabolites.

[0165] (4) Cecum microbial molecular phenotype-related loci design

[0166] Based on the identified 1751 microbial ASVs molecular phenotypes, the microbial abundance ratio data were obtained by correcting the total count of each sample sequencing; the data with an abundance of 0 were filled using geometric Bayesian multiplication, and the filled data were corrected using central logarithmic transformation. Whole-genome association analysis was performed between the resequencing genotypes and the 1751 microbial ASVs molecular phenotypes by using a mixed linear model, with batch, sex, and the first three principal components of genotypes as covariates. The significance threshold of the association between genotypes and metabolite molecular phenotypes was P<5x10 -8 , and 23189 loci significantly affected 709 plasma metabolites. By LD r 2 >0.2 to remove redundant QTLs and QTLs with only one marker, 2308 independent candidate markers affected 317 muscle metabolites and 2144 independent candidate markers affected 494 plasma metabolites.

[0167] (5) Breast muscle, liver, and pancreas transcription molecular phenotype-related loci design

[0168] In the breast muscle, liver, and pancreas, the expression amount TPM of 15406, 14228, and 12433 genes expressed on autosomes in at least 20% of samples was used as the molecular phenotype. After quantile correction and inverse normal transformation of TPM, the first 20 confounders were reserved as covariates for eQTL positioning according to the relationship between the corrected molecular phenotypes by using the Peer software R package. Covariates also included sex and batch, as well as the first three principal components of genotypes. Whether there was a significant association between genotypes and gene expression was calculated by using the following model:

[0169] g = a + yx + bS + e

[0170] where g is the gene expression, s is the random effect, i.e. SNP genotype result, x is the fixed effect, y and b are the correlation matrix, a is the constant (intercept), and e is the residual. Cis-eQTL analysis considers SNPs within 1 Mb upstream and downstream of each gene, and beta distribution permutation test is performed on SNP sampling using TensorQTL permutation method. The significance Pm value of each gene is obtained by permutation test, and the gene with FDR corrected Pm value less than 0.05 is used as the sampling significance Pm value of each gene. The beta distribution parameters of SNPs and gene association analysis in TensorQTL nominal mode are calculated according to the P value, and then the cis-eQTL significant threshold P of each gene is obtained. According to the threshold, the cis-eQTL results of TensorQTL nominal mode are screened. In muscle tissue, 7078496 mutations were identified to significantly affect the expression of 11832 cis genes, in liver tissue, 6629799 mutations were identified to significantly affect the expression of 10648 cis genes, and in pancreas tissue, 4888015 mutations were identified to significantly affect the expression of 7821 cis genes.

[0171] To screen the causal mutations that regulate the expression of each gene from cis-eQTLs, fine mapping of cis-eQTLs was performed for each gene. First, prior information obtained by Deterministic Approximation of Posterior (DAP) was used, which considers the distance from the transcription start site (TSS) and linkage disequilibrium (LD) information (r 2>0.25), the distance between the variant and the TSS of the target gene is calculated by TORUS software to estimate the prior information. Any variant with posterior inclusion probability (PIP) >0.8 is calculated by DAP as a fine mapping result (causative mutation). Through the above analysis, 9650, 8162 and 5184 fine mapping predicted causative mutations are identified in muscle, liver and pancreas tissues, respectively. In addition, the present application carries out conditional eQTL analysis on the results of cis-QTLs, extracts the most significant cis-QTLs of each gene P value as the first round of independent mutations, places them in the covariate, and re-performs eQTL positioning to detect whether the second round contains eQTL signals. The most significant eQTL signal is placed in the covariate as the second round of independent mutations, and eQTL positioning is re-performed until no additional independent signal is detected. The above process is completed by the cis_independent mode of the TensorQTL software. Thus, 22013, 14356 and 8399 independent mutations are obtained in the pectoral muscle, liver and pancreas, respectively. The present application takes the union set of the causative mutations and independent mutations obtained by the two strategies to obtain 66177 key regulatory sites of gene expression, and the LD r 2 >0.2 de-duplication (method same as above), 29426 candidate regulatory markers of gene expression are obtained.

[0172] (6) Selection signal site design

[0173] The resequencing data of 371 ducks of 6 breeds from the NCBI SRA database (https: / / www.ncbi.nlm.nih.gov / sra / ) is downloaded, including 166 Shaoxing ducks, 122 wild ducks, 33 Liancheng white ducks, 25 Z-type Beijing ducks, 17 Cherry Valley ducks and 8 Maple Leaf ducks. Through the steps of removing low-quality reads, aligning genomes, and identifying variants (methods same as above genotype determination), genotype information is obtained, which is combined with the genotype data of 3795 Zhongxin Baiyuhu Meat Ducks to retain 10349420 genomic variant sites with a minimum gene frequency greater than 0.05, a variant detection rate greater than 0.9, and located on autosomes for selection signal (Fst) analysis.

[0174] Screening of Zhongxin Baiyuhu Meat Duck specific markers, the present application carries out two breed comparison between Zhongxin Baiyuhu Meat Duck and other 6 breeds, through single site selection signal Fst analysis, the top 0.001% of the pre-Fst value is considered to be a selected site. Selection signal analysis is completed by vcftools (v0.1.13) software, through Fst analysis, a total of 7662 Zhongxin Baiyuhu Meat Duck positively selected sites are obtained, and LD r 2 >0.2 de-duplication (method same as above), 3568 selected markers are obtained.

[0175] According to the above functional site design principles, 40835 functional markers are obtained.

[0176] (7) Design of background sites

[0177] The chip background site selection principle needs to meet the site heterozygosity < 50% (relaxed to 65% when filling the gap), deletion rate < 10%, minimum allele frequency ≥ 0.35 (relaxed to 65% when filling the gap), and 20082 background sites are selected according to the principle of uniform distribution.

[0178] (8) Evaluation and experimental verification of sites

[0179] The functional site evaluation principle needs to meet the deletion rate < 20%, the minimum allele frequency > 0.1, and remove non-biallelic SNP sites, and 40055 functional markers are obtained after filtering. Based on the sequence information of the functional markers and the background sites, primers and probes are designed, the probes need to meet the GC content between 30% and 70%, and the number of homologous similar regions of the probe sequence on the genome is ≤ 5. In addition, the genotypes of an additional 200 ducks are detected by newly designed probes, and the sequencing depth of the chip design site needs to meet at least 20% of the average sequencing depth. Therefore, 53618 effective markers are obtained as the final meat duck 50K gene chip design site set. Five, preparation and detection of meat duck 50K gene chip

[0180] The meat duck 50K gene chip of the present application includes 34744 functional markers and 18874 background sites. From the variation type, the chip includes 53130 SNPs and 488 INDELs. The selected 50K sites are based on the liquid phase probe capture technology GenoBaits, and a 50K site panel is designed and synthesized, and 200 samples are tested, and after sequencing and data analysis, the sample site detection rate is between 99.4%-99.8%, and the average detection rate is 99.6%. The overall distribution of chip sites is shown in Figure 2 , and the number of chip sites distributed in each chromosome is shown in Figure 3 .

[0181] Example 2 Evaluation of the application effect of meat duck 50K gene chip in genomic selection

[0182] A slaughter test was conducted on 330 42-day-old Zhonghua white-feathered meat ducks, and 13 traits including 42-day weight, feed intake, fattening weight gain, feed conversion ratio (FCR), residual feed intake (RFI), carcass weight, foot weight, breast muscle weight, leg weight, wing weight, neck weight, intestine weight, and gizzard weight were measured. Blood samples were collected, and the genotypes were determined by 50K gene chip through GenoPrep blood DNA rapid extraction kit (magnetic bead method). The BLUP breeding value was calculated based on the animal model, and the model was as follows:

[0183] y = Xb + Za + e,

[0184]

[0185] y is the trait phenotype value; b is the fixed effect, including gender and batch; a is the individual molecular phenotype random effect, wherein A is the kinship matrix through pedigree information technology, is the additive genetic variance; X and Z are the design matrices of fixed effect and random effect, respectively; e is the residual. The variance components are estimated by AI-REML algorithm, and The breeding value can be calculated through the following mixed model equation.

[0186]

[0187] The GBLUP model is similar to the BLUP model, except that the A matrix is replaced by the G matrix. The G matrix is a kinship matrix constructed by genotype information, and is calculated by p i is the minimum allele frequency of the ith locus, and M is the genotype information (0, 1, 2). The variance components are re-estimated by AI-REML algorithm, and The genomic breeding value can be calculated through the following mixed model equation.

[0188]

[0189] The estimated breeding values of BLUP and GBLUP models can be calculated by ASReml software. The breeding reference population is 1319 reference groups of slaughtered reference groups of two generations from 2023 to 2024, and the prediction population is 330 breeding groups of the third batch of breeding groups of the 2024 generation, and the reliability of the model prediction is calculated by the Pearson correlation coefficient of the estimated breeding value and the actual phenotype value. The difference between the prediction accuracy of the BLUP and the 50K gene chip GBLUP of the pedigree is compared as the evaluation result of the chip genomic selection effect (Table 3). The results show that the prediction accuracy of the 50K gene chip GBLUP is improved to a certain extent (0.009-0.188) in different traits, and the average accuracy is improved by 0.06, indicating that the application effect of the 50K gene chip of the meat duck is good in the genomic selection of the meat duck.

[0190] Table 3: Comparison of prediction accuracy of the 50K gene chip of the meat duck and the pedigree BLUP

[0191]

[0192] Example 3: Application of the 50K gene chip of the meat duck in whole genome association analysis

[0193] At 42 days, 568 Zhongxinbaihuameatducks were collected for blood samples, and the supernatant was obtained by low-speed centrifugation to obtain plasma. The cholinesterase content in the plasma was determined based on a blood biochemical analyzer. The whole genome DNA was extracted from the lower sediment by using a GenoPrep blood DNA rapid extraction kit (magnetic bead method), and was subjected to targeted capture sequencing by using the 50K gene chip of the meat duck. The sequencing results were typed according to the reference example 1. The marker sites with a minimum allele frequency > 0.05 (--maf) and a missing rate < 0.1 (--geno) were reserved by using the PLINK software, and the individuals with a typing missing rate > 0.1 (--mind) were filtered. The mixed linear model of the GCTA software was used for whole genome association analysis, and the model was as follows:

[0194] y = Wɑ + Xβ + u + e

[0195] Where y is the cholinesterase phenotype vector, ɑ is the covariance, W is the covariance design matrix (including gender, batch, and the first three principal components of the genotype), β is the marker effect vector, X is the marker genotype matrix, u is the random multi-effect vector, G is the genomic kinship matrix, and e is the random residual. The GWAS results are shown in Figure 4 As shown in the table, a significant signal is located on chromosome 9.

[0196] According to P < 5 x 10-8 filtered GWAS results, 67 signals significantly associated with plasma cholinesterase content were obtained, and the screened signal interval chr9:2762625-4191173 was annotated, which contained 26 genes, including the BCHE gene. The BCHE gene has been reported to be associated with plasma cholinesterase content in Beijing ducks Plasma cholinesterase of wild duck cross F2 population was significantly correlated (Xu et al., 2019), and the above results showed that the trait GWAS gene mapping analysis could be carried out using the meat duck 50K gene chip, and better correlation analysis results were obtained.

[0197] Example 4 Application of meat duck 50K gene chip in different meat duck strain identification

[0198] Two strains of Zhongxianbaihuang duck, L1 strain and L4 strain, each with 100 individuals, were collected, and blood samples were collected. Genomic DNA was extracted using GenoPrep blood DNA rapid extraction kit (magnetic bead method), and sequencing was performed by "Guixin No. 1" gene chip. The PLINK software was used to retain marker sites with minimum allele frequency > 0.05 (--maf), and the missing rate was < 0.1 (--geno). At the same time, individuals with a missing rate of > 0.1 (--mind) were filtered. Subsequently, the test data was subjected to principal component analysis (PCA) by the --pca parameter of PLINK software, and the results are shown in Figure 5 Overall, L1 strain and L4 strain can be clearly distinguished. The above results show that the meat duck 50K breeding gene chip can be better applied to the strain identification of different meat ducks.

Claims

1. A molecular probe array for marker-based breeding of meat ducks, characterized in that, The marker site combination consists of 53,618 molecular markers, namely 53,130 SNPs and 488 INDELs. The location information of the 53,130 SNPs is shown in Table 1, and the location information of the 488 INDELs is shown in Table 2. The reference genome for the physical location is the meat duck reference genome IASCAAS_PekinDuck_T2T.

2. The application of the whole genome molecular probe combination of meat ducks as described in claim 1 in the preparation of whole genome gene chips of meat ducks.

3. A 50K gene chip for whole-genome selection in meat ducks, characterized in that, The chip is loaded with the whole genome molecular probe combination of duck as described in claim 1.

4. The 50K gene chip for whole-genome selection of meat ducks according to claim 3, characterized in that, The chip is a liquid phase chip.

5. A kit for genotyping meat ducks, characterized in that, The kit contains the whole genome molecular probe combination of ducks as described in claim 1 or the whole genome 50K gene chip of ducks as described in claim 3.

6. The application of the whole genome molecular probe combination of meat ducks according to claim 1, the whole genome gene chip of meat ducks according to claim 3, or the kit for genotyping of meat ducks according to claim 5 in the selection of meat duck genomes.

7. The application of the whole genome molecular probe combination of meat ducks according to claim 1, the whole genome gene chip of meat ducks according to claim 3, or the kit for genotyping of meat ducks according to claim 5 in meat duck breed identification, breed tracing, or kinship identification.

8. The application of the whole genome molecular probe combination of meat ducks according to claim 1, the whole genome gene chip of meat ducks according to claim 3, or the kit for genotyping of meat ducks according to claim 5 in whole genome association analysis or trait-related gene localization of meat ducks.

9. The application of the whole genome molecular probe combination for meat ducks as described in claim 1, the whole genome gene chip for meat ducks as described in claim 3, or the kit for genotyping of meat ducks as described in claim 5 in the analysis of genetic diversity of meat ducks.

10. The application of the whole genome molecular probe combination of meat ducks according to claim 1, the whole genome gene chip of meat ducks according to claim 3, or the kit for genotyping of meat ducks according to claim 5 in the analysis of meat duck germplasm resources, germplasm resource improvement, germplasm resource protection, or pedigree reconstruction.

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