Molecular breeding method for anti-egg-laying performance decline of laying hens based on eQTL of YIPF1 gene and application

Abstract

This invention belongs to the field of molecular breeding technology and provides a method based on... YIPF1 Molecular breeding methods and applications for inhibiting egg production decline in laying hens using the eQTL gene. This invention combines molecular markers with... YIPF1 Gene expression levels have a regulatory role; the combined molecular markers are located at Chr8:24801464 and Chr8:24802450 loci in the chicken genome, respectively. This invention breaks through the traditional single-trait research paradigm, integrating multidimensional omics and phenotypic data to identify genes from a systems biology perspective. YIPF1 The gene and its regulatory site combination, Chr8:24801464 and Chr8:24802450, serve as key targets in the process of tissue functional decline in laying hens. This gene possesses cross-tissue, dynamically correlated early warning characteristics, providing a reliable tool for early assessment and precise breeding of anti-aging traits in laying hens, and has significant application value for achieving the goal of an ultra-long laying cycle.

Description

Technical Field

[0001] This invention belongs to the field of molecular breeding technology, specifically involving... YIPF1 Molecular breeding methods and applications for improving the resistance to egg production decline in laying hens using the eQTL gene. Background Technology

[0002] Modern egg-laying hen breeding faces a key challenge: how to strike a balance between high egg production and an extended laying period. Extending the laying cycle has become a focus of breeding research. However, achieving this goal requires not only genetic improvement but also systematic support in areas such as nutrition management, feeding systems, and disease control, while ensuring the continuous stability of egg-laying hen survival rates and production efficiency.

[0003] A key challenge of extending the laying cycle is the gradual degeneration of the structure and function of multiple organs and tissues in laying hens with increasing age. Problems such as imbalanced liver lipid metabolism, declining reproductive system function, weakened intestinal barrier, and decreased immunity become increasingly prominent. This systemic aging not only threatens animal welfare but also directly manifests as a decline in later egg production, poorer eggshell quality, and increased mortality, severely restricting further improvements in farming efficiency.

[0004] Currently, the industry's assessment of tissue deterioration mainly relies on late-stage phenotypic observation or post-slaughter pathological analysis, lacking molecular indicators that can provide early warning and objectively reflect the internal functional state. This lagging and indirect assessment method greatly limits the efficiency of genetic selection for the complex trait of "ultra-long-cycle healthy egg production" in breeding.

[0005] Molecular marker-assisted breeding offers a potential solution to the above-mentioned dilemmas, but existing research is mostly limited to single trait-related loci and lacks a dynamic molecular marker system that can systematically reflect the overall functional decline process of the organism, making it difficult to support a precision breeding strategy aimed at "adapting to an ultra-long laying period".

[0006] Therefore, there is an urgent need to provide a molecular marker and breeding method that can reflect the aging process and tissue function decline of laying hens in an early and systematic way, in order to solve the problems of the existing assessment methods being lagging behind, lacking objective molecular indicators, and being unable to efficiently carry out precise genetic improvement of long-lived and healthy laying hens. Summary of the Invention

[0007] The purpose of this invention is to provide a method based on YIPF1 This invention relates to a molecular breeding method and application of the eQTL gene in laying hens to combat declining egg production performance. The invention identifies a key gene that reflects the decline in tissue function in laying hens and is closely related to egg production rate. YIPF1 The study identified two genomic loci that are significantly associated with the expression level of this gene, providing a reliable tool for early assessment and precise breeding of anti-aging traits in laying hens, and has important application value for achieving the goal of an ultra-long laying cycle.

[0008] This invention provides the application of reagents for identifying combined molecular markers in the identification of laying hens resistant to egg production decline and / or in the breeding of laying hens resistant to egg production decline, wherein the combined molecular markers... YIPF1 Gene expression levels have a regulatory effect; The combined molecular markers are located at the Chr8:24801464 and Chr8:24802450 sites in the chicken genome, respectively.

[0009] As a preferred embodiment, the genotype at the Chr8:24801464 locus is AA, AB, or BB; The genotypes at the Chr8:24802450 locus are AA, AB, and BB.

[0010] As a preferred embodiment, the chicken genome references the chicken Gallus_gallus-7.0 version sequence information.

[0011] As a preferred embodiment, the YIPF1 The gene's NCBI accession number is 424653.

[0012] The present invention also provides a product for identifying laying hens resistant to declining egg production performance, the product comprising reagents for detecting genotypes at the Chr8:24801464 and Chr8:24802450 loci.

[0013] As a preferred embodiment, the reagents include one or more of the following: reagents for nucleic acid extraction and amplification, reagents for detecting nucleic acid amplification products, reagents for constructing sequencing libraries, or reagents for sequencing.

[0014] As a preferred embodiment, the reagent comprises primers for detecting Chr8:24801464 and Chr8:24802450 sites.

[0015] This invention also provides a method for screening laying hens resistant to declining egg production, comprising the following steps: Genomic DNA was extracted from the laying hens to be tested, and genotypes were identified at two genetic variation sites, Chr8:24801464 and Chr8:24802450. Laying hens carrying the AA genotype at Chr8:24801464 and the AB genotype at Chr8:24802450 were considered to be laying hens resistant to declining egg production performance.

[0016] As a preferred embodiment, the identification method includes identification using the Axiom™ Genome-Wide Chicken Genotyping Array genotyping chip.

[0017] This invention also provides a marker-assisted breeding method for laying hens resistant to declining egg production performance, comprising the following steps: Using the screening method described above, genotypes were identified for the two genetic variation loci, Chr8:24801464 and Chr8:24802450. Laying hens carrying both the AA genotype at the Chr8:24801464 locus and the AB genotype at the Chr8:24802450 locus were selected for breeding, resulting in laying hens resistant to declining egg production performance.

[0018] Beneficial effects: This invention provides the application of reagents for identifying combined molecular markers in the identification of laying hens resistant to egg production decline and / or in the breeding of laying hens resistant to egg production decline. The combined molecular markers described in this invention... YIPF1 Gene expression plays a regulatory role; the combined molecular markers are located at Chr8:24801464 and Chr8:24802450 loci in the chicken genome, respectively. This invention breaks through the traditional single-trait research paradigm, integrating multidimensional omics and phenotypic data to identify genes from a systems biology perspective. YIPF1 The gene and its regulatory site combination (Chr8:24801464, Chr8:24802450) serve as key targets in the process of tissue function decline in laying hens. YIPF1 Genes possess cross-tissue, dynamic association early warning characteristics, which can provide a reliable tool for the early assessment and precise breeding of anti-aging traits in laying hens, and have important application value for achieving the goal of ultra-long laying cycles.

[0019] The present invention YIPF1 Compared with existing technologies, gene technology also has the following advantages: 1. Multi-tissue expression characteristics: The aforementioned YIPF1 The gene is expressed in multiple tissues of laying hens, and can comprehensively and consistently reflect the process of tissue functional decline.

[0020] 2. Production phenotypic correlation: The aforementioned YIPF1 The gene was significantly associated with important production phenotypes such as egg production rate (ELR).

[0021] 3. High application value of molecular markers: By integrating the above... YIPF1 Gene expression information and its regulatory sites were analyzed, and a combination of gene biomarkers covering both the expression and DNA levels was constructed, suitable for in vivo, early-stage, and large-scale screening.

[0022] This invention achieves the following technical effects by using marker-assisted selection in combination with molecular markers Chr8:24801464 and Chr8:24802450: 1. Effectively delays the progression of key gene ( YIPF1 The expression level of ) decreases with aging. The laying hens bred in this invention, carrying the dominant genotype combination (AA type at Chr8:24801464 locus and AB type at Chr8:24802450 locus), compared with unverified individuals, exhibit superior performance. YIPF1 The decline in gene expression during aging was significantly suppressed.

[0023] 2. Significantly enhances the anti-aging ability of egg production traits. because YIPF1 Gene expression stability is positively correlated with egg production performance. Therefore, the egg production capacity of the laying hen population bred through this invention shows a significantly slower decline with increasing age.

[0024] 3. Extend the economic cycle of high-quality egg production. The application of this invention enables laying hen flocks to continuously produce high-quality eggs for a longer period of their life cycle, effectively extending the "maintenance age of high-quality eggs." This invention can be used for the early assessment of the degree of tissue function decline in laying hens and can serve as a basis for individual screening and molecular-assisted selection in the process of breeding for ultra-long laying cycles. It has significant application value and industrialization prospects in laying hen genetic breeding and healthy life assessment.

[0025] 4. Overcome the shortcomings of existing technologies This invention effectively overcomes the limitations of single-marker breeding, such as limited practicality and insufficient exploitation of genetic potential, by constructing and validating specific combinations of molecular markers. Assisted selection based on the molecular modules provided by this invention can more systematically and stably alleviate the decline in egg production performance in the later stages of laying, significantly improving the sustainability of egg production in laying hens. This approach not only has significant economic application value but also represents a major optimization and upgrade to existing molecular marker breeding technologies. Attached Figure Description

[0026] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the accompanying drawings used in the embodiments will be briefly described below.

[0027] Figure 1 PCA distribution plots for cecal transcriptome data at 50, 70, and 100 weeks; Figure 2 PCA distribution plots of isthmic transcriptome data at 50, 70, and 100 weeks; Figure 3 DESeq2 analysis of volcano plots for the cecum; Figure 4 Analyze the volcanic map of the canyon using DESeq2; Figure 5 Heatmap of differentially significant genes in the cecum; Figure 6 Heatmap of significantly different genes in the isthmus; Figure 7 KEGG enrichment bar chart for genes with significant differential expression in the cecum; Figure 8 KEGG enrichment bar chart of genes with significant differences in the isthmus; Figure 9 For cecum-based YIPF1 Line graph showing the mean change in egg production rate for gene expression level groups; Figure 10 for YIPF1 Line graph showing the relationship between gene expression levels in the duodenum and cumulative egg production; Figure 11 for YIPF1 Line graph showing the relationship between gene expression levels in the isthmus and cumulative egg production; Figure 12 for YIPF1 Line graph showing the relationship between gene expression levels in the liver and cumulative egg production; Figure 13 for YIPF1 The expression levels of the gene at different ages (50 weeks, 70 weeks and 100 weeks) in laying hens are shown in the graph. Figure 14 for YIPF1 A diagram illustrating the combined effects of gene molecular modules; Figure 15 A graph showing the effect of key site combinations on egg production; In the attached diagram of the instruction manual, "ELR" represents the egg production rate. Detailed Implementation

[0028] This invention provides the application of reagents for identifying combined molecular markers in the identification of laying hens resistant to egg production decline and / or in the breeding of laying hens resistant to egg production decline, wherein the combined molecular markers can regulate... YIPF1 Gene expression levels; as one implementation method, genes YIPF1 The Ensembl ID is ENSGALG00010027096; the NCBI ID is 424653. This invention relates to the gene... YIPF1 These are key genes that can reflect the decline of tissue function in laying hens and are closely related to egg production rate.

[0029] This invention has found that transcriptomic analysis of the duodenum, isthmus, and liver reveals gene... YIPF1 During the laying hen production process (from 50 weeks of age to 100 weeks of age), there was a clear trend of decreasing expression levels.

[0030] The molecular markers used in this invention are located at the Chr8:24801464 and Chr8:24802450 loci in the chicken genome. As one embodiment, the genotypes at the Chr8:24801464 locus are AA, AB, and BB; the genotypes at the Chr8:24802450 locus are AA, AB, and BB. As one embodiment, the chicken genome references the chicken Gallus_gallus-7.0 sequence information. This invention's embodiments have found that the Chr8:24801464 and Chr8:24802450 genetic variation loci mitigate... YIPF1 Gene expression declines in the later stages of egg production, thus mitigating the negative impact of declining egg production levels with increasing age. Using the Chr8:24801464 and Chr8:24802450 loci for marker-assisted selection can effectively improve the anti-aging ability of egg production levels in laying hens, thereby enhancing the overall production sustainability and economic benefits of the laying hen population.

[0031] The embodiments of the present invention demonstrate that the two genetic variation sites, Chr8:24801464 and Chr8:24802450, mitigate the effects of genetic variation. YIPF1 Gene expression decreases in the later stages of egg production, thereby mitigating the negative impact of declining egg production performance with increasing age.

[0032] This invention also provides a product for identifying laying hens resistant to declining egg production performance, the product comprising substances for detecting Chr8:24801464 and Chr8:24802450 loci. The substances of this invention comprise one or more of the following: reagents for nucleic acid extraction and amplification, reagents for detecting nucleic acid amplification products, reagents for constructing sequencing libraries, or reagents for sequencing. The substances of this invention also include primers for detecting Chr8:24801464 and Chr8:24802450 loci.

[0033] This invention also provides a method for screening laying hens resistant to declining egg production performance, comprising the following steps: extracting genomic DNA from the laying hens to be tested, and identifying the genotypes of two genetic variation sites, Chr8:24801464 and Chr8:24802450; laying hens carrying the AA genotype at the Chr8:24801464 site and the AB genotype at the Chr8:24802450 site are laying hens resistant to declining egg production performance.

[0034] This invention does not specifically limit the method for extracting genomic DNA from laying hens; any method commonly used in the art can be employed. The sample from the laying hen can be venous blood or a feather sample with feather follicles, for subsequent genomic DNA extraction. In a specific embodiment of this invention, the chicken sample is obtained by venous blood collection, treated with an anticoagulant, followed by lysis and protease digestion, and then the individual genomic DNA data is extracted using the phenol-chloroform method.

[0035] This invention does not specifically limit the method for genotyping; any method commonly used in the art can be employed. In a specific embodiment of this invention, the genotype of an individual is detected using the Axiom™ Genome-Wide Chicken Genotyping Array genotyping chip. Finally, referring to the chicken genome Gallus_gallus-7.0 version sequence information, molecular biology techniques are used to identify the genotypes of the two genetic variation sites (Chr8:24801464 and Chr8:24802450).

[0036] This invention also provides a marker-assisted breeding method for laying hens resistant to declining egg production performance, comprising the following steps: using the screening method described above, genotyping is performed on two genetic variation loci, Chr8:24801464 and Chr8:24802450, and laying hens carrying both the Chr8:24801464 locus AA genotype and the Chr8:24802450 locus AB genotype are selected for breeding to obtain laying hens resistant to declining egg production performance.

[0037] In the breeding process of this invention, individuals carrying both the AA genotype at the Chr8:24801464 locus and the AB genotype at the Chr8:24802450 locus are identified as individuals with a superior genotype combination possessing high anti-aging potential. In breeding decision-making, individuals carrying both the AA genotype at the Chr8:24801464 locus and the AB genotype at the Chr8:24802450 locus are identified as individuals with a superior genotype combination possessing high anti-aging potential. These individuals are preferentially retained as the core breeding population, while individuals not carrying this superior combination are either culled or used as a control group for subsequent verification. Through the above-mentioned cyclical processing and screening of the core breeding population, the targeted genetic improvement of the anti-aging ability of the laying hen population is ultimately achieved, resulting in a laying hen population adapted to an ultra-long laying cycle.

[0038] To further illustrate the present invention, the following description, in conjunction with embodiments, explains the invention based on... YIPF1 The molecular breeding methods and applications of the eQTL gene for improving the resistance to egg production decline in laying hens are described in detail, but they should not be construed as limiting the scope of protection of this invention.

[0039] Unless otherwise specified, the present invention does not have special requirements for the raw materials used in the preparation, and commercially available products well known to those skilled in the art can be used.

[0040] Example 1: Loci Chr8:24801464, Chr8:24802450 and Gene YIPF1 Screening process I. Sample Collection To locate genetic information related to changes in egg production performance in late-laying hens, representative individuals were collected at 50, 70, and 100 weeks of age, with 6, 6, and 12 individuals collected at each time point, respectively. Tissue samples were collected from two key tissues: the cecum and the isthmus.

[0041] To identify locus information related to changes in egg production performance in late laying hens, blood samples were collected from 246 individuals at 100 weeks of age for genomic analysis. Simultaneously, cecal and isthmus tissues were collected from 246 individuals to obtain transcriptomic data.

[0042] II. Transcriptome Data Analysis and Multi-omics Joint Analysis 1. Quantitative analysis of gene expression Total RNA was extracted from each tissue, RNA-seq libraries were constructed, and high-throughput sequencing was performed. High-quality sequencing sequences were aligned to the chicken reference genome (Gallus_gallus-7.0) using STAR software, and gene expression was counted using featureCounts. The results were then uniformly converted to TPM values ​​as a standard indicator of gene expression levels.

[0043] 2. Transcriptome sequencing experimental process RNA from the total sample was isolated and purified using TRIzol (Thermo Fisher, 15596018) according to the manufacturer's instructions. The quantity and purity of the total RNA were then quality controlled using a NanoDrop ND-1000 (NanoDrop, Wilmington, DE, USA), and RNA integrity was tested using a Bioanalyzer 2100 (Agilent, CA, USA); concentration >50 ng / μL, RIN value >7.0, and total RNA >1 μg met the requirements for downstream experiments. PolyA-containing mRNA was specifically captured using oligo(dT) magnetic beads (Dynabeads Oligo (dT), cat.25-61005, Thermo Fisher, USA) through two rounds of purification. The captured mRNA was fragmented at high temperature using a magnesium fragmentation reagent (NEBNextR 12340ES97, Frag / Prime Buffer) (NEBNextR Magnesium RNAFragmentation Module, cat. E6150S, USA) at 94℃ for 5 min. The fragmented RNA was then used to synthesize cDNA using reverse transcriptase (Invitrogen SuperScript™ II Reverse Transcriptase, cat. 1896649, CA, USA). Then, E. coli DNA polymerase I (NEB, cat.m0209, USA) and RNase H (NEB, cat.m0297, USA) were used to synthesize double-stranded DNA and RNA, converting the complex double strands into DNA double strands. Simultaneously, dUTP Solution (Thermo Fisher, cat.R0133, CA, USA) was incorporated into the double strands to blunt ends, and an A base was added to each end to allow ligation with adapters containing T bases at the ends. Magnetic beads were used to screen and purify the fragments by size. After screening and purification, PCR amplification was performed, with the following cycle: 98℃ for 1 min pre-denaturation, 98℃ for 10 s denaturation, 60℃ for 30 s annealing, and 72℃ for 30 s extension, repeated 14 times, followed by a final extension at 72℃ for 5 min. In PCR amplification, the characteristic of high-fidelity DNA polymerase that only amplifies cDNA chains without U bases is utilized to achieve chain specificity, resulting in a library with a fragment size of 300bp±50bp (chain-specific library).Finally, paired-end sequencing was performed using an Illumina Novaseq™ 6000 (LC Bio Technology CO.,Ltd. Hangzhou, China) according to standard operating procedures in PE150 sequencing mode.

[0044] 3. Locating key genes through cross-time transcriptome analysis Principal component analysis (PCA) was performed on cecal and isthmus tissue samples at three time points (50, 70, and 100 weeks) using the prcomp function in R (v4.2.3). Before analysis, genes with zero variance or missing values ​​were removed, and the data were logarithmically transformed. Subsequently, the PCA results were visualized using the factoextra (v1.0.7) and ggfortify (v0.4.17) R packages, and 95% confidence ellipses were added to aid in determining the segregation of samples from different groups. By plotting the PCA distribution maps of cecal and isthmus tissue at the three time points, the impact of different ages on the differences in sample expression profiles was observed visually at an overall level. Then, using transcriptome data from the cecum and isthmus of laying hens, genes showing a continuous increase or decrease at 50, 70, and 100 weeks were first screened. Based on this, DESeq2 analysis was performed on the gene expression matrices at 50 and 100 weeks. Volcano plots and heatmaps were used to visualize the results.

[0045] KEGG enrichment analysis was performed on differentially expressed genes identified in the cecum and isthmus tissues using the KEGG database. The KEGG database (http: / / www.genome.jp / kegg / ) provides important insights into the intrinsic mechanisms of biological systems from systemic functional, genomic, and chemical perspectives. Finally, key genes were located using the average egg production levels at multiple time points from 41 to 95 weeks of gestation. YIPF1 .

[0046] 4. Multi-omics association analysis Using transcriptome and genome data from 246 individuals, gene-locus associations were identified through eQTL mapping analysis. First, the quality-controlled genotype data was converted into a numerical matrix of an additive genetic model (0 / 1 / 2) using PLINK software, and then arranged into a genotype matrix with single nucleotide polymorphisms (SNPs) as rows and individual samples as columns. Simultaneously, the FPKM expression matrix obtained from transcriptome sequencing was cleaned and standardized, gene nomenclature was unified, and transcriptome sample numbers were accurately mapped to their corresponding genome individual numbers. To ensure strict matching of multi-omics data, samples lacking corresponding expression information in the genotype data were removed, resulting in a matching matrix with a completely consistent sample number and arrangement order for subsequent analysis. The associations between genes and loci were then analyzed. YIPF1 The relevant sites were screened, and the sites that have a regulatory effect on them were finally obtained: Chr8:24801464 and Chr8:24802450.

[0047] III. Results Analysis PCA analysis showed significant differences in the transcriptomic data of the cecum and isthmus at 100 weeks compared to those at 50 and 70 weeks, indicating substantial changes in tissue function during this period. Figure 1 and Figure 2 Using DESeq2 differential analysis, 795 and 1983 genes showed a sustained increase and significant change in the cecum and isthmus, respectively, while 1342 and 1515 genes showed a sustained decrease and significant change. Figure 3 and Figure 4 The heatmap results show that these genes undergo the most significant changes at 70 and 100 weeks. Figure 5 and Figure 6 ).

[0048] KEGG enrichment results showed significant differences between the two tissues, with genes concentrated in processes such as ribosomes and oxidative phosphorylation. Figure 7 and Figure 8 Finally, based on the gene expression levels in the cecal tissue, the genes were divided into high (H) and low (L) groups, ultimately identifying genes associated with changes in egg production levels from 41 to 95 weeks. YIPF1 ( Figure 9 By combining trans-temporal transcriptome and eQTL mapping analysis of 246 individual transcriptomes and genomes, the specific information of key genes and regulatory sites was finally located (Table 1).

[0049] Table 1 Genes YIPF1 eQTL mapping analysis results

[0050] Example 2: Genes YIPF1 Analysis of trends expressed in different production cycles I. Sample Collection To verify the invention proposed YIPF1 To investigate gene expression dynamics across different production cycles, representative individuals were collected at three time points: 50 weeks, 70 weeks, and 100 weeks of age, with sample sizes of 6, 6, and 12 individuals at each time point, respectively. Tissue samples were collected from three key tissues: duodenum, isthmus, and liver.

[0051] II. Gene Expression Detection and Analysis 1. Quantitative analysis of gene expression Total RNA was extracted from each tissue, RNA-seq libraries were constructed, and high-throughput sequencing was performed. High-quality sequencing sequences were aligned to the chicken reference genome (Gallus_gallus-7.0) using STAR software, and gene expression was counted using featureCounts. The results were then uniformly converted to TPM values ​​as a standard indicator of gene expression levels.

[0052] 2. Transcriptome data analysis The transcriptome data obtained above were further analyzed. The ggplot2 package (v4.0.1) in R was used to plot the expression trends of key genes in different tissues, visually demonstrating their expression patterns as the individual grows. Based on the target gene expression values, the population was divided into high-expression and low-expression groups. ggplot2 was then used to plot the phenotypic changes of the two groups at different production cycles, visually demonstrating the potential effect of gene expression levels on phenotype.

[0053] III. Results Analysis according to YIPF1 Gene expression levels divided the population into high-expression and low-expression groups. The results showed that the cumulative egg production of the high-expression group was significantly higher than that of the low-expression group. Figures 10-12 Meanwhile, through transcriptomic analysis of the duodenum, isthmus, and liver, genes... YIPF1 During the laying hen production process (from 50 weeks of age to 100 weeks of age), a significant trend of decreasing expression levels was observed. Figure 13 ).

[0054] Example 3: Effect validation based on genotyping at loci Chr8:24801464 and Chr8:24802450 I. Sample Collection 241 experimental individuals were selected, and blood samples were obtained by collecting blood from the wing veins. Egg production rate ELR phenotypic data during the production process were recorded.

[0055] II. Genotyping at Target Locus 1. Target locus genotyping Chicken samples were collected using a wing vein blood collection method. After anticoagulation with an anticoagulant, the samples were lysed, digested with a protease, and genomic DNA was extracted using the phenol-chloroform method. The extracted DNA was dissolved in sterile double-distilled water and stored for later use. The blood collection method and phenol-chloroform extraction technique described herein are standard procedures in the field.

[0056] Using extracted genomic DNA as a template, whole-genome SNP genotyping was performed on each experimental individual using the Axiom™ Genome-Wide Chicken Genotyping Array (catalog number: 902148) manufactured by Axiom Technologies, Inc. Genotype is the combination of two alleles at the same gene locus. Typically, a gene locus has only two alleles, therefore there are usually three genotypes: "homozygous type I," "homozygous type II," and "heterozygous type."

[0057] Genotyping of the two genetic variation sites (Chr8:24801464 and Chr8:24802450) was performed using molecular biology techniques. The chicken reference genome Gallus_gallus-7.0 version sequence information was publicly available on the NCBI website.

[0058] Calculate the average egg production rate for each group.

[0059] III. Results Analysis By analyzing the genotype combinations of the two molecular markers Chr8:24801464 and Chr8:24802450, individuals carrying the following genotype combinations were identified. YIPF1 The highest gene expression levels were observed in the AA type at Chr8:24801464 and the AB type at Chr8:24802450. Figure 14 ).

[0060] Table 2 further shows that individuals carrying the AA_AB genotype combination (i.e., AA type at Chr8:24801464 and AB type at Chr8:24802450) had an average egg production rate (ELR) of 0.843894, which was higher than that of individuals with other genotype combinations. This indicates that the Chr8:24801464 and Chr8:24802450 genetic variation loci mitigate the effects of these variations. YIPF1 The expression of genes decreases in the later stages of egg production, thereby mitigating the negative impact of declining egg production with increasing age. Based on these results, marker-assisted selection was performed using the Chr8:24801464 and Chr8:24802450 loci, which effectively improved the anti-aging ability of egg production in laying hens, thereby enhancing the overall production sustainability and economic benefits of the laying hen population.

[0061] Table 2. Mean egg production rate of individuals with different genotype combinations

[0062] Example 4: Validation of the effect of Chr8:24801464 and Chr8:24802450 genotyping on egg production performance in another population I. Sample Collection Ninety-four experimental individuals were selected, and blood samples were obtained by collecting blood from the wing veins. The cumulative number of eggs laid during their production process from week 22 to week 60 was recorded.

[0063] Chicken samples were collected using a wing vein blood collection method. After anticoagulation with an anticoagulant, the samples were lysed, digested with a protease, and genomic DNA was extracted using the phenol-chloroform method. The extracted DNA was dissolved in sterile double-distilled water and stored for later use. The blood collection method and phenol-chloroform extraction technique described herein are standard procedures in the field.

[0064] II. Genotyping at Target Locus 1. Target locus genotyping Using extracted genomic DNA as a template, whole-genome SNP genotyping was performed on each experimental individual using the Axiom™ Genome-Wide Chicken Genotyping Array (product catalog number: 902148) manufactured by Axiom Technologies, Inc., USA. This included the loci Chr8:24801464 and Chr8:24802450.

[0065] III. Results Analysis Analysis of genotype combinations of the two molecular markers Chr8:24801464 and Chr8:24802450 revealed that individuals carrying the following genotype combinations had the highest cumulative egg production from 22 to 60 weeks: AA type at Chr8:24801464 and AB type at Chr8:24802450. Figure 15 ).

[0066] Comparative Example 1: Comparison of prediction intensity between single-site and two-site combinations I. Sample Collection Blood samples were collected from the wing veins of 246 individuals, and the egg production rate (ELR) phenotypic data of this population during the production process were recorded.

[0067] Chicken samples were collected using a wing vein blood collection method. After anticoagulation with an anticoagulant, the samples were lysed, digested with a protease, and genomic DNA was extracted using the phenol-chloroform method. The extracted DNA was dissolved in sterile double-distilled water and stored for later use. The blood collection method and phenol-chloroform extraction technique described herein are standard procedures in the field.

[0068] II. Genotyping at Target Locus 1. Genotyping process Using extracted genomic DNA as a template, whole-genome SNP genotyping was performed on each experimental individual using the Axiom™ Genome-Wide Chicken Genotyping Array (product catalog number: 902148) manufactured by Axiom Technologies, Inc., USA. This included the loci Chr8:24801464 and Chr8:24802450.

[0069] 2. Calculate the mean egg production rate of different groups after genotyping. After completing whole-genome typing of 246 experimental individuals, genotypic data for the target loci Chr8:24801464 and Chr8:24802450 were accurately extracted and matched one-to-one with the recorded late-laying egg production rate (ELR) data. In terms of grouping strategy, individuals were independently grouped based on a single molecular marker, and the average egg production rate of different genotype populations at both the Chr8:24801464 and Chr8:24802450 loci was statistically analyzed.

[0070] III. Results Analysis While existing technologies enable breeding selection using molecular markers, they typically only analyze and apply single markers. This method has significant limitations: firstly, the breeding effect of a single molecular marker is limited and cannot fully reflect the genetic regulatory network of complex traits; secondly, relying solely on a single marker makes it difficult to fully realize its potential value in breeding, potentially leading to unstable breeding results or limited improvement.

[0071] This invention overcomes the aforementioned limitations, revealing for the first time the synergistic effect between the molecular markers Chr8:24801464 and Chr8:24802450. When laying hens simultaneously carry the AA type at the Chr8:24801464 locus and the AB type at the Chr8:24802450 locus, they exhibit higher levels of [unclear - possibly related to egg production] in the later stages of egg production. YIPF1 Gene expression levels were significantly higher, and the average egg production rate reached 84.39% (Example 3), which was significantly better than other genotype combinations. In contrast, if selection is based solely on a single marker (as shown in the results of independent analysis of each marker in Table 3), regardless of which dominant genotype is selected, the comprehensive breeding effect under the molecular module combination described in this invention cannot be achieved, especially in maintaining egg production performance and anti-aging performance.

[0072] Table 3. Mean egg production rate of individuals with different genotypes

[0073] Comparative Example 2: Comparison of prediction strength between single loci and two-locus combinations in another population I. Sample Collection Blood samples were collected from the wing veins of 316 individuals, and the cumulative egg production phenotypic data of the population during the production process (22-60 weeks) were recorded.

[0074] Chicken samples were collected using a wing vein blood collection method. After anticoagulation with an anticoagulant, the samples were lysed, digested with a protease, and genomic DNA was extracted using the phenol-chloroform method. The extracted DNA was dissolved in sterile double-distilled water and stored for later use. The blood collection method and phenol-chloroform extraction technique described herein are standard procedures in the field.

[0075] At the same time, genomic information and cumulative egg production data from 22 to 60 weeks were collected from 94 individuals.

[0076] II. Genotyping at Target Locus 1. Genotyping process Using extracted genomic DNA as a template, whole-genome SNP genotyping was performed on each experimental individual using the Axiom™ Genome-Wide Chicken Genotyping Array (product catalog number: 902148) manufactured by Axiom Technologies, Inc., USA. This included the loci Chr8:24801464 and Chr8:24802450.

[0077] 2. Calculate the mean egg production rate of different groups after genotyping. After obtaining the whole-genome SNP genotyping results for each experimental individual, the genotype information of the target loci (Chr8:24801464 and Chr8:24802450) was precisely extracted and matched one-to-one with the phenotypic data such as cumulative egg production and egg production rate of individuals within a specific production cycle (22-60 weeks of age). Population grouping was performed based on the genotype matching results: according to the allelic polymorphism of a single locus (Chr8:24801464 or Chr8:24802450), the experimental individuals were divided into different single-genotype groups, and the cumulative egg production during the pre-laying period (22-60 weeks) was counted.

[0078] IV. Presentation of Analysis Results Based on a standardized evaluation benchmark of a completely consistent egg production statistical period (22-60 weeks), this study conducted a cross-sectional comparison of the predictive efficacy of different screening strategies. The results (Table 4) show that in a larger population (316 individuals), using only a single locus (Chr8:24801464 or Chr8:24802450) for dominant genotype screening, except for a few extremely small sample groups (such as the Chr8:24801464 locus AB type, with only 1 individual), the cumulative egg production in all other groups failed to reach the excellent egg production level (152 eggs) achieved by the combined screening of two loci in a population of 94 individuals. This cross-population comparison within the same time period confirms that combined screening of two loci can effectively overcome the performance bottleneck of single-locus prediction.

[0079] Table 4. Average cumulative egg production of individuals with different genotypes

[0080] Therefore, this invention effectively overcomes the limitations of single-marker breeding, such as limited practicality and insufficient exploitation of genetic potential, by constructing and validating specific molecular marker combinations. Assisted selection based on the molecular modules provided by this invention can more systematically and stably alleviate the decline in egg production performance in the later stages of laying, significantly improving the sustainability of egg production in laying hens. This approach not only has significant economic application value but also represents a major optimization and upgrade to existing molecular marker breeding technologies.

[0081] Although the above embodiments have provided a detailed description of the present invention, they are only some embodiments of the present invention, and not all embodiments. People can obtain other embodiments based on these embodiments without creative effort, and these embodiments all fall within the protection scope of the present invention.

Claims

1. The application of reagents combined with molecular markers in the identification of laying hens resistant to egg production decline and / or in the breeding of laying hens resistant to egg production decline, characterized in that, The combined molecular marker pair YIPF1 Gene expression levels have a regulatory effect; The combined molecular markers are located at the Chr8:24801464 and Chr8:24802450 sites in the chicken genome, respectively.

2. The application according to claim 1, characterized in that, The genotypes at the Chr8:24801464 locus are AA, AB, and BB. The genotypes at the Chr8:24802450 locus are AA, AB, and BB.

3. The application according to claim 1, characterized in that, The chicken genome references the chicken Gallus_gallus-7.0 version sequence information.

4. The application according to claim 1, characterized in that, The YIPF1 The gene's NCBI accession number is 424653.

5. A product for identifying laying hens resistant to declining egg production, characterized in that, The product includes reagents for detecting the genotypes at the Chr8:24801464 and Chr8:24802450 loci.

6. The product according to claim 5, characterized in that, The reagents include one or more of the following: reagents for nucleic acid extraction and amplification, reagents for detecting nucleic acid amplification products, reagents for constructing sequencing libraries, or reagents for sequencing.

7. The product according to claim 5 or 6, characterized in that, The reagents include primers for detecting Chr8:24801464 and Chr8:24802450 sites.

8. A method for screening laying hens resistant to declining egg production, characterized in that, Includes the following steps: Genomic DNA was extracted from the laying hens to be tested, and genotypes were identified at two genetic variation sites, Chr8:24801464 and Chr8:24802450. Laying hens carrying the AA genotype at Chr8:24801464 and the AB genotype at Chr8:24802450 were considered to be laying hens resistant to declining egg production performance.

9. The screening method according to claim 8, characterized in that, The identification method includes identification using the Axiom™ Genome-Wide Chicken Genotyping Array genotyping chip.

10. A marker-assisted breeding method for laying hens resistant to declining egg production performance, characterized in that, Includes the following steps: Using the screening method described in claim 8 or 9, genotypes of the two genetic variation loci Chr8:24801464 and Chr8:24802450 are identified, and laying hens carrying both the AA genotype at the Chr8:24801464 locus and the AB genotype at the Chr8:24802450 locus are selected for breeding to obtain laying hens resistant to declining egg production performance.

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