A molecular marker associated with growth and development traits in yellow-feathered broiler chickens and its application

Abstract

This invention discloses a molecular marker associated with the growth and development traits of yellow-feathered broiler chickens and its application, belonging to the field of molecular breeding technology. The SNP molecular markers correspond to the sequence information of chromosome 4 in the Gallus_gallus-6.0 version of the chicken reference genome published in NCBI, specifically at 75971034 bp (genotypes GG, GC, CC) and 75971177 bp (genotypes GG, GA, AA). The 75971034 bp genotype is a favorable genotype with the GG genotype at the locus, carrying significantly higher mid-metabolic weight, 87-day weight, and 113-day weight compared to individuals carrying the CC genotype. The 75971177 bp genotype is also a favorable genotype with the GG genotype at the locus, carrying significantly higher mid-metabolic weight compared to individuals carrying the AA genotype. Using these molecular markers for molecular-assisted selection allows for early screening of mid-metabolic weight, 87-day weight, and 113-day weight, effectively reducing production costs, promoting genetic improvement, and demonstrating high economic benefits and application value.

Description

Technical Field

[0001] This invention belongs to the field of molecular breeding technology, specifically relating to a molecular marker related to the growth and development traits of yellow-feathered broilers and its selection and application method. Background Technology

[0002] With rapid economic growth and rising income levels, chicken meat, prized for its high protein content and balanced amino acid profile, has become increasingly popular among consumers, leading to growing demand. my country's broiler market is gradually recovering, with per capita poultry consumption reaching a significant level. Therefore, accelerating chicken growth and development is the optimal way to increase chicken production and meet domestic demand. Identifying variations in chicken growth and development traits helps producers design optimal breeding programs, improving chicken yield and feed conversion ratio by enhancing population genetic performance.

[0003] In biological inheritance, RNA plays a crucial "bridging" role, and the collective term for all RNA after transcription is the transcriptome. Single-analysis may have limitations in biological research. Studying important economic traits in livestock and poultry from multiple perspectives, including genome-wide association studies (GWAS) and transcriptomics, allows for more detailed observation of cellular dynamics, clearer identification of characteristics in specific cells or states, and a comprehensive and accurate elucidation of the genetic regulatory mechanisms of these traits. By studying genetic markers in growth through GWAS analysis, combining cis-eQTL results from liver transcriptome data, and identifying relevant SNPs through GWAS and cis-eQTL co-localization analysis, the reliability and universality of the analysis results are significantly improved. This provides reliable molecular markers for SNP-based genome-wide selection (GS), thereby assisting in the breeding of yellow-feathered broilers, improving production efficiency and profitability, providing a reference for breeding work, and accelerating the improvement process of domestically bred breeds. Summary of the Invention

[0004] The purpose of this invention is to identify genetic variations in 87-day body weight, 113-day body weight, and mid-cycle metabolic body weight, providing a basis for early selection of growth and development traits, saving production costs and accelerating genetic progress. By providing a molecular marker related to growth and development traits and its selection and application method, this invention promotes precision breeding of chicken body weight.

[0005] To solve the above-mentioned technical problems, the basic concept of the technical solution of this invention is as follows: Based on the needs of breeding and production practices, a group of Wenchang chickens of the same market age (113 days old) is selected. During the rearing process, free access to feed and water is provided, and the diet is based on the feeding standards for yellow-feathered broilers (NY / T33). (2004). Body weight at 87 days of age (BW87) and at market age (BW113) was measured, and mid-cycle metabolic weight (MWT) was calculated using the formula: MWT = [(BW113 - BW87) / 2]. 0.75 Genome-wide association analysis was performed using whole-genome resequencing data to screen and identify genetic variations that significantly affect growth and development traits. This provides technical support for early selection of body weight at different ages and for breeding faster-growing broiler strains.

[0006] Improving body weight in broiler production faces numerous challenges, primarily due to the influence of various genetic and environmental factors. Large-scale assays are an effective strategy to enhance the accuracy of phenotypic data and uncover potential genetic variations. Furthermore, deep whole-genome resequencing can efficiently reveal genetic variations associated with body weight at different ages. Association analysis combining phenotypic and whole-genome sequencing data can help identify reliable molecular markers, thus supporting precision breeding for broiler weight.

[0007] Specifically, the technical solution of the present invention is as follows: A molecular marker associated with the growth and development traits of yellow-feathered broiler chickens, wherein the SNP molecular marker is chr4:75971034, containing a nucleotide sequence with a G / C polymorphism at position 75,971,034 bp on chicken chromosome 4; and chr4:75971177, containing a nucleotide sequence with a G / A polymorphism at position 75,971,177 bp on chicken chromosome 4; Specifically, the SNP molecular marker sequence is GTCCTACAT. G GTGCTCAGTC (SEQ ID NO.4) corresponds to the chicken reference genome Gallus_gallus published in NCBI. Version 6.0 sequence information: Chromosome 4, 75,971,034 bp, nucleotide sequence with G / C polymorphism, genotypes GG, GC, CC; GG genotypes have significantly higher 87-day, 113-day, and mid-metabolous weights than GC and CC genotypes, and / or the SNP molecular marker sequence is TCAAAACAC. A CTGTGCAAGA (SEQ ID NO.5) corresponds to the chicken reference genome Gallus_gallus published in NCBI. Sequence information for version 6.0: Chromatography 4 at 75,971,177 bp shows a polymorphism of G / A nucleotide sequence, with genotypes of GG, GA, and AA. The metastatic weight of the GG genotype is significantly higher than that of the GA and AA genotypes.

[0008] The physical locations of the above molecular markers are referenced from the chicken reference genome Gallus_gallus-6.0 (in NCBI, the genome name is: Genome assembly GRCg6a; accession number is: GCF_000002315.6, and the URL is https: / / www.ncbi.nlm.nih.gov / gdv / browser / genome / ?id=GCF_0000023156).

[0009] In this invention, the three genotypes of the molecular marker chr4:75971034 showed significant differences in weight at 87 days, 113 days, and mid-metabolic weight. Specifically, individuals carrying the GG genotype had the highest weight; those carrying the GC genotype had a moderate weight; and those carrying the CC genotype had the lowest weight. Similarly, the three genotypes of the molecular marker chr4:75971177 also showed significant differences in mid-metabolic weight. Specifically, individuals carrying the GG genotype had the highest weight; those carrying the GA genotype had a moderate weight; and those carrying the AA genotype had the lowest weight.

[0010] The present invention also provides primers for amplifying the above-mentioned molecular markers.

[0011] In this invention, the specific primer sequences for amplifying molecular markers are shown in SEQ ID NO.1-3: Primer 1: ACCTGCCCATTCCACAGGTA (SEQ ID NO.1); Primer 2: CCGACTGTGACCAAAGGAGC (SEQ ID NO.2); Primer 3: TTTGGTTCCTCGCTGACTGG (SEQ ID NO.3); Primer 2: CCGACTGTGACCAAAGGAGC (SEQ ID NO.2).

[0012] The present invention also provides a reagent or kit containing the above-mentioned primers.

[0013] The molecular markers, primers, reagents, or kits provided by this invention can be used in any of the following applications: (1) Application in early prediction of growth and development traits in yellow-feathered broilers; (2) Application in chicken genetic resource weight improvement or molecular marker-assisted breeding; This invention also provides a molecular marker-assisted breeding method for high-quality chickens, comprising: (1) Extract genomic DNA from the chickens to be tested; (2) Using DNA as a template, perform PCR amplification using the primers described above; (3) Analyze the PCR amplification products to determine the genetic potential of chickens for breeding and propagation.

[0014] In this invention, step (3) includes: performing allele detection on the amplification products, and determining the following based on the genotyping results: The genotype of the polymorphic site contained in molecular marker chr4:75971034 is GG, indicating that the chickens being tested have a high body weight level; the genotype of the polymorphic site contained in molecular marker chr4:75971177 is GG, indicating that the chickens being tested have a high body weight level.

[0015] The present invention has the following beneficial effects: The molecular marker-assisted breeding method for different age-related body weights of the present invention can effectively increase body weights at different ages by determining the genotype of the SNP loci in the chicken to be tested, thus helping to meet consumer demand for chicken meat. Compared with traditional assessment methods, molecular markers related to growth and development can accurately identify genetic loci at an early stage, avoiding later measurement and observation. This provides a scientific basis for the breeding of fast-growing yellow-feathered broilers, has significant application value, significantly improves the economic benefits of the broiler industry, and accelerates genetic progress in breeding. Attached Figure Description

[0016] Figure 1 This is a Manhattan plot of genome-wide association analysis (GWAS) on chromosome 4 of Wenchang chickens regarding body weight at 87 days of age (BW87) in a preferred embodiment of the present invention. The X-axis of the Manhattan plot represents chromosomes 1–28 and 30–32, and the Y-axis represents the significance level (-log10(P)). A total of 12,263,342 SNP variants were analyzed, and the suggested significance threshold is -log10(P). -5 The significance threshold was -log10(1 / 12,263,342) = 7.09. Loci exceeding this threshold were considered significantly associated with body weight at 87 days of age. The QQ plot on the right represents the goodness of fit between the observed and expected values.

[0017] Figure 2 This is a Manhattan plot of genome-wide association analysis (GWAS) on chromosome 4 of Wenchang chickens regarding body weight at 113 days of age (BW113) in a preferred embodiment of the present invention. The X-axis of the Manhattan plot represents chromosomes 1–28 and 30–32, and the Y-axis represents the significance level (-log10(P)). A total of 12,263,342 SNP variants were analyzed, and the suggested significance threshold is -log10(P). -5The significance threshold was -log10(1 / 12,263,342) = 7.09. Loci exceeding this threshold were considered significantly associated with body weight at 113 days of age. The QQ plot on the right represents the goodness of fit between the observed and expected values.

[0018] Figure 3 This is a Manhattan plot of genome-wide association analysis (GWAS) on chromosome 4 of Wenchang chicken regarding metastatic metabolic weight (MWT) in a preferred embodiment of the present invention. The X-axis of the Manhattan plot represents chromosomes 1–28 and 30–32, and the Y-axis represents the significance level (-log10(P)). A total of 12,263,342 SNP variants were analyzed, and the suggested significance threshold is -log10(P). -5 The significance threshold was -log10(1 / 12,263,342) = 7.09. Loci exceeding this threshold were considered significantly associated with mid-cycle metabolic weight gain. The QQ plot on the right represents the goodness of fit between the observed and expected values.

[0019] Figure 4 This invention relates to the location distribution of the molecular marker chr4:75971177 in cis-eQTL and its linkage to nearby sites. The molecular marker chr4:75971177 influences LAP3 gene expression in liver tissue, and its co-localization probability with metastatic body mass is 0.99. The X-axis represents the local region of chromosome 4 (75.85–76.00 Mb), and the Y-axis represents the significance level (-log10(P)). A significance threshold of -log10(P) is suggested. -5 =5, the color represents the linkage relationship with nearby sites.

[0020] Figure 5 This invention relates to the location distribution of the molecular marker chr4:75971034 in cis-eQTL and its linkage to nearby sites. The molecular marker chr4:75971034 affects LAP3 gene expression in liver tissue. The X-axis represents the local region of chromosome 4 (75.85~76.00 Mb), and the Y-axis represents the significance level (-log10(P)). A significance threshold of -log10(P) is suggested. -5 =5, the color represents the linkage relationship with nearby sites.

[0021] Figure 6 This is the first-generation sequencing result of the chr4:75971177 molecular marker of the present invention, in which the 01 genotype is the complementary strand (based on the sequencing strand of the downstream primer), the SNP molecular marker chr4:75971034 is GG, and the homozygous mutant genotype is AA.

[0022] Figure 7This is the first-generation sequencing result of the chr4:75971034 molecular marker of the present invention, in which 00 and 11 are complementary strands (based on the sequencing strand of the downstream primer), the SNP molecular marker chr4:75971034 is GG, and the homozygous mutant genotype is CC.

[0023] Figure 8 This is a box plot comparing the differences in mid-term metabolic weight among different genotypes of chr4:75971177 in this invention.

[0024] Figure 9 This is a box plot comparing the differences in body weight at 87 days of age among different genotypes of chr4:75971034 according to the present invention.

[0025] Figure 10 This is a box plot comparing the differences in body weight at 113 days of age among different genotypes of chr4:75971034 in this invention.

[0026] Figure 11 This is a box plot comparing the differences in mid-term metabolic weight among different genotypes of chr4:75971034 in this invention.

[0027] Figure 12 This is a box plot comparing the differences in LAP3 gene expression levels in liver tissue among different genotypes of chr4:75971177 of this invention. Increased LAP3 gene expression levels are associated with decreased body weight during the mid-metabolism phase.

[0028] Figure 13 This is a box plot comparing the differences in LAP3 gene expression levels in liver tissue among different genotypes of chr4:75971034 according to the present invention. The SNP molecular marker chr4:75971034 is GG, and the homozygous mutant genotype is CC. When the mutation from GG to CC occurs, the expression level of LAP3 gene increases, and the body weight at 87 days of age, 113 days of age, and mid-metabolic weight decrease.

[0029] Figure 14 This is a box plot comparing the mid-term metabolic weight differences among different genotypes of the Beijing Oil Chicken population chr4:75971177.

[0030] Figure 15 This is a box plot comparing the mid-term metabolic weight differences among different genotypes of the Beijing Oil Chicken population chr4:75971034. Detailed Implementation

[0031] To make the objectives, technical solutions, and effects of this invention clearer, the technical solutions of this invention are described in detail below with reference to specific examples. It should be understood that the specific embodiments described herein are only for explaining this invention and are not intended to limit this invention. Unless otherwise specified, the experimental methods used in the following embodiments are conventional methods; the materials and reagents used, unless otherwise specified, are commercially available reagents and materials.

[0032] Detailed information on the molecular markers of this invention is shown in Table 1, and primer information is shown in Table 2.

[0033] Table 1. Detailed information on molecular markers

[0034] Table 2 Primer Information

[0035] The detection of the above molecular marker site genotypes can be performed using the genome of the chicken to be tested as a template. After PCR amplification using the primers (SEQ ID NO.1-3) in Table 2, allele detection and sequencing of the amplification primers can be performed using direct sequencing or other effective methods.

[0036] The PCR reaction system, in 25 μl increments, consisted of: 1 μl template DNA, 1 μl 10 pmol / μl upstream primer, 1 μl 10 pmol / μl downstream primer, 12.5 μl 2*Master mix, and 9.5 μl ddH2O. The PCR reaction conditions were: 95℃ for 10 min, 95℃ for 30 s, 60℃ for 30 s, and 72℃ for 50 s, for a total of 30 cycles; followed by a final induction at 72℃ for 5 min. Based on the sequencing results, the genotypes of the two SNP loci were determined.

[0037] Example 1. GWAS analysis to identify SNP loci associated with body weight at different ages. This invention used 432 Wenchang chickens as experimental animals, all from a Wenchang chicken breeding company in Hainan. During the rearing process, they were provided with free access to feed and water, and their diet was based on the feeding standards for yellow-feathered broiler chickens (NY / T33). (2004). The experimental determination period was from 87 to 113 days of age. Phenotypic quality control was performed, and the phenotypic descriptions are shown in Table 3.

[0038] Table 3. Descriptive statistics of growth and development traits of Wenchang chickens

[0039] DNA extraction Collect 0.5 mL of venous blood from the wings of all test chickens using blood collection tubes, and use standard phenol. Whole-genome DNA was extracted using the chloroform method. The concentration and purity of the DNA samples (OD values: OD260 / 280, OD260 / 230) were accurately determined using a Nanodrop 2000 / 2000C nucleic acid and protein analyzer. DNA samples that passed the initial test were then subjected to 0.7% agarose gel electrophoresis to assess their purity and integrity. The DNA samples were then sent to the company for whole-genome resequencing.

[0040] Using the GRCg6a reference genome, the sequencing depth of each library was at least 10X. Quality control was performed using PLINK (V1.9) software, removing samples with a deletion rate higher than 10%, eliminating variants with a deletion rate exceeding 10%, and retaining variants with a minor allele frequency greater than 0.05. Ultimately, 432 individuals and 12,263,342 SNPs on autosomes were retained for subsequent analysis.

[0041] GWAS analysis was performed on growth and development traits (BW87, BW113, MWT) using a mixed linear model (MLM) in GEMMA software, with days, sex, and generations as covariates.

[0042] GWAS analysis results are as follows Figure 1-3 As shown, body weight at different ages corresponds to the 0.44 Mb region on chromosome 4 (chr4:75,724,081). A significant association was found between 76, 168, and 558. Further site annotation was performed on all sites in the associated genome region, locating genes such as LAP3, MED28, NCAPG, and LCORL.

[0043] Example 2. Screening and Validation of Molecular Markers Based on Genome and Transcriptome Liver tissues from 114 individuals of the same generation and population of Wenchang chickens were collected for transcriptome sequencing. Reads containing adapters, reads containing poly-N (N≥10%), and low-quality reads (Q≤5) were removed using FASTP (0.21.0) with default parameters to obtain clean data for downstream analysis. An index of the GRCg6a reference genome was constructed using STAR-build software, and the clean data of each sample was aligned with the reference genome using STAR to obtain a SAM file for each sample. The SAM files were sorted and converted to BAM format using Samtools (v.1.9). Transcripts and genes for each sample were assembled and quantified using featureCounts. Transcript abundance and gene expression levels were estimated based on read count and number of transcripts per million (TPM).

[0044] We downloaded the liver from the public database ChickenGTEx. cis -eQTL results, using coloc for GWAS and cis -eQTL colocalization analysis revealed that chr4_75971177 was found in MWT and cis The co-location probability (PP.H4) of -eQTL is 0.99 ( Figure 4 Furthermore, it was found that chr4_75971034 plays a regulatory role in the liver. cis -eQTL affects the LAP3 gene ( Figure 5 ).

[0045] Allelic identification of the amplified products was performed using first-generation sequencing. chr4_75971177: where 01 genotyping is based on the complementary strand (sequencing the downstream primer strand). First-generation sequencing peak diagram ( Figure 6 ); chr4_75971034: where 00 and 11 are the complementary strands (based on the downstream primer sequencing strand) First-generation sequencing peak diagram ( Figure 7 ).

[0046] Genotypic differences were analyzed by combining molecular markers with body weight phenotypes at different ages. The SNP marker chr4_75971177 contained a polymorphic locus with the GG genotype, indicating a higher mid-metabolical weight; a GA genotype, indicating a moderate mid-metabolical weight; and an AA genotype, indicating a lower mid-metabolical weight. Figure 8 The SNP marker chr4_75971034 contains a polymorphic locus with the genotype GG, indicating a higher body weight (BW87, BW113, MWT); the genotype GA indicates a moderate body weight (BW87, BW113, MWT); and the genotype AA indicates a lower body weight (BW87, BW113, MWT). Figure 9-11 ).

[0047] Genotypic differences were analyzed by combining molecular markers with LAP3 gene expression levels. The genotype of the polymorphic site contained in the SNP marker chr4_75971177 was GG, indicating low LAP3 gene expression; the genotype was GA, indicating moderate LAP3 gene expression; and the genotype was AA, indicating high LAP3 gene expression. Figure 12 The genotype of the polymorphic site contained in the SNP marker chr4_75971034 is GG, indicating that the LAP3 gene has a low expression level; if the genotype is GC, it indicates that the LAP3 gene has a moderate expression level; if the genotype is CC, it indicates that the LAP3 gene has a high expression level. Figure 13 ).

[0048] Example 3. Population validation of molecular markers Three hundred and ninety-four Beijing Oil Chicken individuals were selected, and the testing phase was chosen between 80 and 100 days of age. Body weight (BW80) at 80 days of age and body weight (BW100) at 100 days of age were measured, and mid-cycle metabolic weight (MWT) was calculated. Venous blood was collected simultaneously, and genomic DNA was extracted for testing. Qualified DNA samples were subjected to 0.7% agarose gel electrophoresis to assess DNA purity and integrity. The DNA samples were then sent to the company for whole-genome resequencing.

[0049] By combining phenotypes to perform a significant analysis of differences between genotypes, see Figure 14-15 The genotypes chr4_75971177 and chr4_75971034, containing beneficial genotypes, can be used to identify phenotypic differences in inosinic acid content among Beijing Oil Chicken populations. The genotype of the polymorphic site contained in the SNP marker chr4_75971177 is GG, indicating a higher mid-metabolical metabolic weight; if the genotype is GA, it indicates a moderate mid-metabolical metabolic weight; and if the genotype is AA, it indicates a lower mid-metabolical metabolic weight. Figure 14 The SNP marker chr4_75971034 contains a polymorphic site with the genotype GG, indicating a higher mid-metabolous weight; the genotype GA indicates a moderate mid-metabolous weight; and the genotype AA indicates a lower mid-metabolous weight. Figure 15 The above evidence indicates that the chr4_75971177 and chr4_75971034 sites are key mutations that broadly affect body weight at different ages. In breeding practice, auxiliary selection at these sites can be used to improve the growth rate of broilers.

[0050] The above description is only a specific embodiment of the present invention, but the protection scope of the present invention is not limited thereto. Any changes or substitutions that can be easily conceived by those skilled in the art within the technical scope disclosed in the present invention should be included within the protection scope of the present invention.

Claims

1. The application of an SNP molecular marker in breeding for growth and developmental traits in yellow-feathered broilers, characterized in that: The SNP molecular marker sequence is GTCCTACAT. G GTGCTCAGTC (SEQ ID NO.4) corresponds to the chicken reference genome Gallus_gallus published in NCBI. Version 6.0 sequence information: Chromosome 4, 75,971,034 bp, nucleotide sequence with G / C polymorphism, genotypes GG, GC, CC; GG genotypes have significantly higher 87-day, 113-day, and mid-metabolous weights than GC and CC genotypes, and / or the SNP molecular marker sequence is TCAAAACAC. A CTGTGCAAGA (SEQ ID NO.5) corresponds to the chicken reference genome Gallus_gallus published in NCBI. Sequence information for version 6.0: Chromatography 4 at 75,971,177 bp shows a polymorphism of G / A nucleotide sequence, with genotypes of GG, GA, and AA. The metastatic weight of the GG genotype is significantly higher than that of the GA and AA genotypes.

2. A specific primer pair for detecting the SNP molecular marker as described in claim 1, characterized in that, Primer pairs for amplifying molecular marker chr4: 75971034 are shown in SEQ ID NO. 1 and 2; primer pairs for amplifying molecular marker chr4: 75971177 are shown in SEQ ID NO. 3 and 2. Primer 1: ACCTGCCCATTCCACAGGTA (SEQ ID NO.1); Primer 2: CCGACTGTGACCAAAGGAGC (SEQ ID NO.2); Primer 3: TTTGGTTCCTCGCTGACTGG (SEQ ID NO.3); Primer 2: CCGACTGTGACCAAAGGAGC (SEQ ID NO.2).

3. A reagent or kit containing the specific primer pair as described in claim 2.

4. A method for detecting the growth and development phenotypes of chickens, characterized in that, Detection of the SNP molecular marker in claim 1 in the chicken sample to be tested.

5. The method according to claim 4, characterized in that, Includes the following steps: (1) Extract genomic DNA from the chickens to be tested; (2) Detect the genotype of the SNP molecular markers at positions 75,971,034 and / or 75,971,177 on chicken chromosome 4; (3) Perform PCR amplification using the specific primer pair described in claim 2 to obtain the amplification product; (4) The alleles of the obtained PCR amplification products were sequenced by direct sequencing. (5) Based on the sequencing results, determine the genotype of the SNP molecular markers as described in claim 1 in the chickens to be tested; perform allele detection on the amplification products, and determine the following based on the genotyping results: the genotype of the polymorphic site contained in molecular marker chr4:75971034 is GG, indicating that the weight level of the chickens to be tested is high; the genotype of the polymorphic site contained in molecular marker chr4:75971177 is GG, indicating that the weight level of the chickens to be tested is high.

6. Any of the following applications of the SNP molecular marker as described in claim 1 or the reagent or kit as described in claim 3: (1) Application in early prediction of growth and development traits in yellow-feathered broilers; (2) Application in chicken genetic resource weight improvement or molecular marker-assisted breeding.

7. The application as described in claim 6, characterized in that, Screening for dominant gene genotyping: The genotype of the polymorphic site contained in molecular marker chr4:75971034 is GG, indicating that the chickens being tested have a higher weight level; and / or, the genotype of the polymorphic site contained in molecular marker chr4:75971177 is GG, indicating that the chickens being tested have a higher weight level.

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