A molecular marker related to chicken wing traits and application thereof

Abstract

This invention discloses a molecular marker associated with chicken wing weight and its application, belonging to the field of marker-assisted breeding technology. The nucleotide sequence of the molecular marker is shown in SEQ ID NO.1, and a C / T mutation exists at base 101 of the sequence shown in SEQ ID NO.1. The genotypes of the molecular marker are CC, CT, and TT. Chickens with the CC genotype have significantly greater wing weight than those with the CT and TT genotypes. This invention, through genome-wide association analysis of the wing weight phenotype in yellow-feathered broiler chickens, identifies single nucleotide polymorphisms significantly associated with wing weight, screening for a significant association between the Chr Z:61242528 locus and chicken wing weight, providing new molecular markers and technical support for early screening, improvement, and breeding of superior chicken wing weight traits.

Description

Technical Field

[0001] This invention relates to the field of molecular marker-assisted breeding technology, and in particular to a molecular marker associated with the wing weight trait in chickens and its application. Background Technology

[0002] Chicken is one of the most important sources of animal protein worldwide. With global population growth and rising living standards, market demand for chicken, especially high-value cuts, continues to climb. Chicken wings, as a key part of broiler slaughtering and processing, directly determine the meat yield per unit and overall economic benefits. The development of poultry farming is of great significance to animal husbandry and agriculture. Wing weight is an important indicator reflecting carcass composition and meat production performance, and a key parameter for measuring chicken growth performance and dressing percentage. Therefore, increasing wing weight is an important breeding goal for optimizing broiler product structure and enhancing added value. Traditional broiler breeding mainly relies on phenotypic selection, that is, measuring phenotypic data such as carcass weight and wing weight of individuals or their relatives, combined with quantitative genetic methods (such as Best Linear Unbiased Prediction, BLUP) for genetic evaluation and selection. This method has achieved significant results in the past few decades, but it has limitations such as long cycle time and limited efficiency in selecting traits with low heritability.

[0003] To overcome the bottlenecks of traditional breeding, marker-assisted selection (MAS) technology has emerged. MAS analyzes DNA molecular markers (such as SNPs) closely linked to target traits, enabling accurate prediction of an individual's genetic potential early in life. This allows for direct selection of superior genotypes, significantly shortening generation intervals and accelerating genetic progress. With the development of genome sequencing technology, related techniques are increasingly widely and effectively applied in the study of quantitative traits in plants and animals. Methods such as genome-wide association studies (GWAS) can significantly improve breeding efficiency.

[0004] Currently, researchers both domestically and internationally have begun using techniques such as genome-wide association studies (GWAS) and RNA-seq to attempt to identify candidate genes and molecular markers related to chicken wing development. Preliminary studies have located genomic regions on chicken chromosome 4 associated with wing weight and suggested that genes such as PPARGC1A and LDB2, which are related to muscle development and energy metabolism, may be involved in regulation. However, the genetic markers discovered in these studies have limited resolution, and functional SNP loci that can be precisely located for efficient molecular breeding have not yet been identified.

[0005] Genome-wide association studies (GWAS) can provide insights into the genetic mechanisms of wing-weight traits during breeding and pinpoint key genes or regulatory regions, thus providing a scientific basis for marker-assisted selection (MAS) and genomic selection (GS), accelerating the breeding process of high-yielding and high-quality chicken breeds. Therefore, identifying marker genes and functional SNPs with clear causal relationships to wing-weight traits in chickens is not only urgently needed but also opens up new directions for poultry genetic breeding research. Summary of the Invention

[0006] The purpose of this invention is to provide a molecular marker associated with chicken wing weight and its application, thereby addressing the problems existing in the prior art. This invention uses genome-wide association analysis of chicken genomic DNA to screen for candidate genes and SNP loci significantly associated with chicken wing weight, providing theoretical support for the future breeding of high-quality chicken breeds.

[0007] To achieve the above objectives, the present invention provides the following solution: This invention provides a molecular marker associated with the heavy trait of chicken wings. The nucleotide sequence of the molecular marker is shown in SEQ ID NO.1. A C / T mutation exists at the 101st base of the sequence shown in SEQ ID NO.1. This mutation site is located at the 61242528th base of chromosome Z in the chicken GRCg6a_release95 genome. The molecular markers were identified as CC, CT, and TT genotypes; chickens with the CC genotype had significantly greater wing weights than those with the CT and TT genotypes.

[0008] This invention also provides the application of the above-mentioned molecular markers as targets in any of the following: (1) Identify the key characteristics of chicken wings; (2) Select chicken breeds with high wing weight; (3) Assist in the breeding of new high-winged heavy chicken varieties.

[0009] This invention also provides the use of the above-mentioned molecularly marked products in any of the following: (1) Identify the key characteristics of chicken wings; (2) Select chicken breeds with high wing weight; (3) Assist in the breeding of new high-winged heavy chicken varieties.

[0010] Optionally, the product includes primers, probes, and gene chips.

[0011] The present invention also provides a method for identifying the heavy characteristics of chicken wings, comprising the following steps: Genomic DNA was extracted from the chickens to be tested, and whole-genome resequencing technology was used to obtain the genotypes of the molecular markers mentioned above, and the wing weight trait of the chickens to be tested was determined. Chickens with the CC genotype had significantly greater wing weight than those with the CT and TT genotypes.

[0012] Optionally, the chicken is a yellow-feathered broiler.

[0013] This invention also provides a method for assisting in the breeding of new high-winged, heavy chicken breeds, comprising the following steps: Genomic DNA was extracted from the chickens to be tested, and whole-genome resequencing technology was used to obtain the genotypes of the molecular markers mentioned above. Chickens with the CC genotype were retained.

[0014] Optionally, the chicken is a yellow-feathered broiler.

[0015] The present invention discloses the following technical effects: This invention utilizes genome-wide association analysis (GWAS) to identify single nucleotide polymorphisms (SNPs) significantly associated with wing weight in yellow-feathered broiler chickens, detecting a total of 860 SNPs. Among these, the Chr Z:61242528 locus showed a significant association with wing weight. The CC genotype population at this locus exhibited greater wing weight than the CT and TT populations. The phenotypic differences between the CC and CT / TT genotypes were significant (P<0.05), while the phenotypic differences between the CT and TT genotypes were not significant (P>0.05). This invention provides novel molecular markers and technical support for early screening, improvement, and breeding of superior chicken wing weight traits.

[0016] This invention also performed gene annotation at the Chr Z:61242528 locus, identified key genes and signaling pathways affecting wing weight traits in poultry, revealed the underlying genetic mechanisms, filled the gap in genome-wide association studies of wing weight traits in yellow-feathered broilers, and provided theoretical support for the breeding of high-quality new chicken breeds. Attached Figure Description

[0017] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0018] Figure 1 This is a 1% agarose gel electrophoresis image of the original genomic DNA of a portion of individuals; where 456-472 represent sample numbers and M represents standard DNA molecules; Figure 2 The Manhattan plot shows the results of the whole gene association analysis for wing weight; the chromosome numbers from left to right are Chr 1, Chr 2, Chr 3, ..., Chr 38, Chr W, Chr Z. Figure 3 The result is a QQ image with heavy wings. Detailed Implementation

[0019] Various exemplary embodiments of the present invention will now be described in detail. This detailed description should not be considered as a limitation of the present invention, but rather as a more detailed description of certain aspects, features, and embodiments of the present invention.

[0020] It should be understood that the terminology used in this invention is merely for describing particular embodiments and is not intended to limit the invention. Furthermore, with respect to numerical ranges in this invention, it should be understood that each intermediate value between the upper and lower limits of the range is also specifically disclosed. Any stated value or intermediate value within a stated range, as well as each smaller range between any other stated value or intermediate value within said range, is also included in this invention. The upper and lower limits of these smaller ranges may be independently included or excluded from the range.

[0021] Unless otherwise stated, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art. While only preferred methods and materials have been described herein, any methods and materials similar or equivalent to those described herein may be used in the implementation or testing of this invention. All references to this specification are incorporated by way of citation to disclose and describe methods and / or materials associated with those references. In the event of any conflict with any incorporated reference, the content of this specification shall prevail.

[0022] Various modifications and variations can be made to the specific embodiments described in this specification without departing from the scope or spirit of the invention, as will be apparent to those skilled in the art. Other embodiments derived from this specification will also be apparent to those skilled in the art. This specification and embodiments are merely exemplary.

[0023] The terms “include,” “including,” “have,” “contain,” etc., used in this article are all open-ended terms, meaning that they include but are not limited to.

[0024] Unless otherwise specified, the experimental methods used in the following examples are conventional methods. Unless otherwise specified, the instruments and equipment used in the following examples are all conventional laboratory instruments and equipment; unless otherwise specified, the experimental materials used in the following examples were all purchased from conventional biochemical reagent stores.

[0025] Example 1 1. Laboratory animals The experimental chickens were the 17th generation G strain of purebred yellow-feathered broiler chickens from Guangdong Jiangfeng Industrial Co., Ltd. The chickens were cage-raised at 77 days old, following the farm's feeding procedures. The chicken house was well-ventilated, and the ambient temperature, humidity, and lighting were suitable. Routine immunizations and disease prevention were administered.

[0026] 2. Sample collection and processing When the chickens were raised for 77 days, 505 yellow-feathered broilers (170 roosters and 335 hens) were randomly selected from the caged and housed group for blood collection under their wings. 1 mL of blood was drawn with a syringe, injected into a blood collection tube containing heparin sodium, and mixed to prevent blood clotting. The individual wing number was marked on the blood collection tube and stored in a -80℃ refrigerator.

[0027] 3. Experimental Methods 3.1 Phenotypic Data Determination Twelve hours before slaughter, the experimental chickens were provided with drinking water. At slaughter, the yellow-feathered broilers were bled through the carotid artery and then scalded in water at a temperature of about 60°C for 3 minutes to remove feathers. After the carcass surface was dried with kitchen paper, the carcass appearance characteristics were measured. The wing weight of each individual was measured and recorded by separating one side of the wing.

[0028] 3.2 Extraction and Detection of Genomic DNA Genomic DNA was extracted using the CTAB method, following standard extraction procedures. The extracted genomic DNA was then tested for integrity, purity, and concentration. DNA that met the requirements was retained, while DNA that did not meet the requirements was discarded or re-extracted and re-tested.

[0029] 3.3 Whole-genome resequencing and sequencing data quality control and alignment analysis The experiment was conducted according to the standard protocol provided by the sequencing company. For qualified genomic DNA samples, appropriate fragment sizes were selected using gel electrophoresis, followed by PCR amplification and library construction. The constructed libraries underwent quality testing, and qualified libraries were then sequenced using the DNBSEQ-T7 sequencer, performed by BGI Genomics Co., Ltd. To ensure the quality of information analysis, base sequencing quality distribution analysis, base type distribution checks, insert fragment distribution statistics, depth distribution statistics, and filtering of the raw image data (Raw Reads) files obtained from high-throughput sequencing were performed during sequencing using the DNBSEQ-T7 system.

[0030] The final sequences obtained from sequencing are remapped onto a reference genome before further analysis. The percentage of clean reads that can be mapped onto the reference genome is called the alignment efficiency, or Mapped (%). The reference genome species is Gallus gallus, and the reference genome is GRCg6a_release95, sourced from the Ensemble database.

[0031] 4. Data processing and statistical analysis 4.1 Descriptive statistical analysis of wing weight traits The collected wing weight data were initially organized using Excel, and outliers were removed from the data of each trait according to the μ±3σ principle. Descriptive statistical analysis was then performed on the data using Excel. The results of the analysis include sample size, mean, standard deviation, and coefficient of variation.

[0032] 4.2 Genome-wide association analysis The samples were sent to Beijing Biomarker Biotechnology Co., Ltd. for genome-wide association analysis. In order to screen for genes or molecular markers associated with wing weight traits across the entire genome, this invention performed low-coverage sequencing (6×) on 505 quality-tested samples.

[0033] Genome-wide association analysis (GWA) was performed using the LMM model in GEMMA software, combining phenotypic and genotypic data. Considering fixed factors (SNP effects) and random effects (inter-individual kinship), the statistical model is as follows: This invention is based on the developed high-density molecular marker data and uses GEMMA for association analysis. The formula for the linear mixture model (LMM) of GEMMA software is as follows (1): y=Wα+xβ+μ+e (1) In the formula, y is the phenotypic vector; W is the indicator matrix of the fixed effects; α is the coefficient vector of the fixed effects; x is the genotype vector; β is the SNP effect; μ is the random effects vector; and e is the residual.

[0034] 4.3 Group Stratification Population stratification refers to the difference in allele frequencies due to different ancestors. It has been proven to be a confounding factor that may lead to many false positive results. Therefore, when conducting association analysis on the wing weight of Jiangfeng yellow-feathered broiler chickens, a Quantile-Quantile Plot was redrawn on the wing weight of Jiangfeng yellow-feathered broiler chickens to determine whether there was any bias in the association analysis and whether there was stratification in the sample population.

[0035] 4.4 Gene annotation of significant SNPs After obtaining significant SNPs from genome-wide association analysis, genes within 50kb upstream and downstream of these sites were retrieved for gene annotation based on a reference genome.

[0036] 5. Results and Analysis 5.1 Genomic DNA Detection Results All genomic DNA samples need to be quality assessed using agarose gel electrophoresis. Some genomic DNA test results are as follows: Figure 1 As shown, the electrophoresis wells must be clean and uncontaminated, the main band must be clear, and there must be no tailing. Additionally, DNA purity must be measured at 1.6. <OD 260 / OD 280 <2.0, 1.8 <OD 260 / OD 230 <2.1. Genomic DNA testing results must simultaneously meet the above requirements before library construction can proceed. Unqualified samples must be discarded or DNA extracted again. Of all samples tested in this invention, 505 met the requirements.

[0037] 5.2 Sequencing data quality control and alignment results with the reference genome The sequencing data quality control results are shown in Table 1. Base type distribution detection was mainly used to check for AT and CG segregation, which may originate from sequencing or library construction. Significant segregation can affect subsequent analysis. The average percentage of G and C bases in the sample (GC%) was 41.36%, the average percentage of bases with a quality value greater than or equal to 20 (Q20%) was 98.03%, and the average percentage of bases with a quality value greater than or equal to 30 (Q30%) was 94.55%. The alignment efficiency between the sample genomic DNA and the reference genomic DNA was above 97.04%, with an average of 99.19%, indicating that the library construction and sequencing of this sample were normal.

[0038] Table 1. Statistical Evaluation of Sample Sequencing Data Note: Clean_Reads: Number of filtered reads; Clean_Base: Number of filtered bases, calculated by multiplying the number of Clean_Reads by the sequence length.

[0039] 5.3 Statistical analysis of SNP detection results between sample and reference genome There are two main types of SNP mutations: transition (Ti, a variation between bases of the same type) and transversion (Tv, a variation between bases of different types). Generally, the probability of transition is higher than that of transversion, i.e., Ti / Tv is greater than 1. As shown in Table 2, a total of 1,996,687,423 SNPs were detected in this experiment, and the heterozygous ratio (Het-ratio) was 48.27%.

[0040] Table 2. Statistical analysis of SNP detection results between the genome and the reference genome. Note: Heterozygosity Number (number of heterozygotes), Homozygosity Number (number of homozygotes), Het-ratio (percentage of heterozygotes).

[0041] 5.4 Descriptive statistical analysis results of wing weight traits The descriptive statistical analysis results of wing weight are shown in Table 3. The results show that a total of 505 chickens were measured (170 roosters and 335 hens). The coefficient of variation for wing weight was 5.73% for roosters and 7.75% for hens. The difference in wing weight between male and female yellow-feathered broilers was highly significant (P<0.01).

[0042] Table 3. Descriptive statistical analysis of wing weight traits Note: Different letters on the shoulder label indicate extremely significant differences (P<0.01), while the same letters or no letters indicate no significant differences (P>0.05).

[0043] 5.5 Results of Genome-wide Association Analysis This invention employed three software programs—Fastlmm, Emmax, and Gemma—to conduct genome-wide association studies (GWAS) on 505 yellow-feathered broiler chickens. Significantly associated SNPs with wing weight were identified across the entire genome (international chicken reference gene GRCg6a_release95, genome source: Ensemble). The Manhattan plot of the wing weight GWAS is shown below. Figure 2 There were 860 SNPs that were significantly correlated with wing weight, located on chromosomes Chr 2 and Chr 5 and sex chromosomes Z and W, respectively.

[0044] 5.6 Group Stratification Assessment Results Significant SNPs were found in wing weight analysis using different software and models. The QQ plot of the wing weight trait is shown below. Figure 3As shown, the horizontal axis represents the expected value, and the vertical axis represents the observed value. The thin line in the graph represents the 45° line, which is the predicted threshold. The gray area represents the 95% confidence interval of the scatter plot. The greater the distance between the SNP and the solid line, the stronger the association. Figure 3 As can be seen, most of the loci in the lower left corner of the graph are on the diagonal, indicating that the model selection is reasonable. The loci in the upper right corner that extend beyond the diagonal and confidence interval represent high significance with the target trait. This indicates that there is no population stratification in the experimental population.

[0045] 5.7 Association analysis between significant loci and wing weight trait Association analysis of genotype and wing weight phenotypic traits was performed using SPSS software. The results showed that the SNP site ChrZ:61242528 (at the 101st base of the sequence shown in SEQ ID NO.1) had three genotypes (CC, CT, and TT) in the yellow-feathered broiler population. The wing weight of the CC genotype population was greater than that of the CT and TT populations. The phenotypic differences between the CC and CT / TT genotypes were significant (P<0.05), while the phenotypic differences between the CT and TT genotypes were not significant (P>0.05). (See Table 4)

[0046] Table 4. SNPs significantly associated with wing weight trait. Note: The correlation was significant at the 0.05 level; different letters on the superscript indicate significant differences.

[0047] SEQ ID NO.1: ATCCATGATTGTTCCACAAAAAAATCGTAAGTAGAACTCACTTTTTTTCAGAAGGTAGCCTTTTTTGACAATATTTTTAAAAAGCATCCTTAGTTTTG C GACGAATTGTATTGTAGATTTCTTTTTCCATCCAATGTGTCATTAAACACTTGCTCTTGGTGCTAGAAAAGGAAGAAAACAACATATTTTAAGTTCAGAAA.

[0048] 5.8 Gene annotation of SNPs that are significantly associated at the whole genome level Preliminary gene annotation of the significant site Chr Z:61242528 was performed using Ensembl, with the annotation range being 100 kb upstream and downstream. The annotation results are shown in Table 5.

[0049] Table 5. Annotation results of genome-wide association analysis of wing weight In summary, this invention provides the SNP locus Chr Z:61242528, which is significantly associated with chicken wing weight trait, and molecular markers can be developed based on this locus. Yellow-feathered broilers with the CC genotype at this locus have higher wing weights, while those with the CT and TT genotypes have lower wing weights. Chicken wing weight is an important indicator of carcass development; higher wing weight indicates better carcass development. Therefore, selecting the CC genotype for wing weight in chicken wing weight trait breeding can improve breeding efficiency and quickly select chicken breeds with superior wing weight traits.

[0050] The embodiments described above are merely preferred embodiments of the present invention and are not intended to limit the scope of the present invention. Various modifications and improvements made by those skilled in the art to the technical solutions of the present invention without departing from the spirit of the present invention should fall within the protection scope defined by the claims of the present invention.

Claims

1. A molecular marker associated with the weight trait of chicken wings, characterized in that, The nucleotide sequence of the molecular marker is shown in SEQ ID NO.

1. A C / T mutation exists at the 101st base of the sequence shown in SEQ ID NO.

1. This mutation site is located at the 61242528th base of chromosome Z in the chicken GRCg6a_release95 genome. The molecular markers were identified as CC, CT, and TT genotypes; chickens with the CC genotype had significantly greater wing weights than those with the CT and TT genotypes.

2. The use of the molecular marker of claim 1 as a target in any of the following: (1) Identify the key characteristics of chicken wings; (2) Select chicken breeds with high wing weight; (3) Assist in the breeding of new high-winged heavy chicken varieties.

3. Testing the use of the product with the molecular marker of claim 1 in any of the following: (1) Identify the key characteristics of chicken wings; (2) Select chicken breeds with high wing weight; (3) Assist in the breeding of new high-winged heavy chicken varieties.

4. The application according to claim 3, characterized in that, The products include primers, probes, and gene chips.

5. A method for identifying the weight characteristics of chicken wings, characterized in that, Includes the following steps: Genomic DNA was extracted from the chickens to be tested, and the genotype of the molecular markers described in claim 1 was obtained by whole-genome resequencing technology to determine the wing weight trait of the chickens to be tested. Chickens with the CC genotype had significantly greater wing weight than those with the CT and TT genotypes.

6. The method according to claim 5, characterized in that, The chicken in question is a yellow-feathered broiler chicken.

7. A method for assisting in the breeding of new high-winged, heavy chicken breeds, characterized in that, Includes the following steps: Genomic DNA was extracted from the chickens to be tested, and the genotypes of the molecular markers described in claim 1 were obtained using whole-genome resequencing technology, retaining the CC genotype of the chicken individuals.

8. The method according to claim 7, characterized in that, The chicken in question is a yellow-feathered broiler chicken.

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