Chicken salmonella enteritidis infection related biomarker and application thereof

Abstract

The invention discloses a chicken salmonella enteritidis infection related biomarker and application thereof, and belongs to the technical field of poultry genetic breeding and propagation. The invention finds that the content of RUNX2 transcription factors in cecum T cells infected by salmonella enteritidis is obviously different, the expression quantity of RUNX2 in a susceptible group is far higher than that of RUNX2 in a resistance group, which indicates that the RUNX2 is a susceptible gene infected by salmonella enteritidis, and if a chicken shows typical enteritis symptoms such as diarrhea, inappetence and the like and the expression level of RUNX2 is detected to be obviously increased, the RUNX2 is a susceptible gene infected by salmonella enteritidis. This may be a marker of a chicken susceptible to Salmonella enteritidis; if the chicken does not show corresponding symptoms and the expression level of the RUNX2 is not greatly increased, the chicken is indicated to have resistance to the salmonella enteritidis, the resistance of the chicken to the infected salmonella enteritidis can be identified on the molecular level through a single-cell transcriptomics technology, and a technical support is provided for breeding poultry varieties resistant to salmonella enteritidis infection.

Description

Technical Field

[0001] The invention relates to the technical field of poultry genetic breeding and reproduction, and in particular to a biomarker related to chicken Salmonella enteritidis infection and an application thereof. Background Art

[0002] Salmonella enterica serovar Enteritidis (S. Enteritidis) is a common zoonotic Gram-negative foodborne pathogen that is non-host-specific but invasive, and mainly parasitizes in the intestines of animals and humans. Salmonella enterica serovar Enteritidis infection can colonize in the intestine and invade intestinal epithelial cells, which may cause damage to the intestinal wall, manifested as diarrhea, loss of appetite, weight loss and other symptoms, and even cause serious complications such as sepsis, thereby interfering with the chicken's immune system, reducing its resistance to other pathogens and increasing the risk of infection with other pathogens. Infection with Salmonella enterica serovar Enteritidis increases the mortality rate of chickens and reduces growth rate; affects egg production performance and even causes a decline in the quality of chicken products. Moreover, Salmonella enterica serovar Enteritidis is an important foodborne pathogen. Humans may be infected with Salmonella by eating infected poultry or eggs, causing food poisoning, which is extremely harmful to animal husbandry and human health. Traditional methods of preventing and controlling Enteritidis Salmonella, such as injecting antibiotics and vaccines, cannot fundamentally solve the problem of infection in livestock and poultry. However, Enteritidis Salmonella infection is genetically regulated. Analyzing the regulatory mechanism of Enteritidis infection in chickens and then improving the genetic resistance of chickens to Enteritidis infection is an effective way to prevent and control Enteritidis Salmonella infection.

[0003] The genetic background of the host has a profound impact on the resistance to S. enteritidis. After undergoing high-intensity selection for production performance and vitality, chicken breeds and strains still retain differences in immune response and disease resistance to S. enteritidis, providing the possibility of genetically improving poultry disease resistance. Identifying chickens that are resistant to S. enteritidis will help reduce the contamination of Salmonella in poultry products (such as chicken and eggs), reduce the spread of S. enteritidis in the population, ensure food safety for consumers, and ensure the healthy operation and sustainable development of the breeding industry.

[0004] Changes in the characteristics of individual transcription factors can reflect the response of the animal body to Salmonella enteritidis infection. Linking transcription factors with biological phenotypes can provide clues for the discovery of new biomarkers. The cecum is the primary invasion site of Salmonella enteritidis. Changes in the characteristics of cecal tissue can, to a certain extent, reflect whether an animal is infected with Salmonella enteritidis. Among them, transcription factors can be used as potential biomarkers reflecting Salmonella enteritidis infection. Therefore, understanding the relationship between animal transcription factors and Salmonella enteritidis infection is of great significance to the genetic breeding and reproduction of chickens. However, no biomarkers related to the resistance of chickens to Salmonella enteritidis infection have been reported so far. Summary of the invention

[0005] In view of the above-mentioned prior art, the purpose of the present invention is to provide a biomarker related to chicken Salmonella enteritidis infection and its application. The biomarker of the present invention can identify the infection resistance of chickens to Salmonella enteritidis, has high sensitivity and strong specificity, and is expected to become a new means of identifying the infection resistance of Salmonella enteritidis.

[0006] To achieve the above object, the present invention adopts the following technical solution:

[0007] In a first aspect, the present invention provides the use of RUNX2 as a target in the preparation of a product for identifying the resistance of livestock and poultry to Salmonella enteritidis infection.

[0008] In the above application, the amino acid sequence of RUNX2 is shown in SEQ ID No. 1; specifically as follows:

[0009] MASNSLFSSVTPCQQNFFWDPSTSRRFSPPSSSLQPGKMSEVSPVVVAQQQQQQQQQQQEAAVPRLRPHDNRTMVEIIADHPAELVRTDSPNFLCSVLPSHWRCNKTLPVAFKVVAL GEVPDGTVVTVMAGNDENYSAELRNASAVMKNQVARFNDLRFVGRSGRGKSFTLTITVLTNPPQVATYHRAIKVTVDGPREPRRHRQKLDDSKPSLFPERLSDLGRIPHPSMRVGVPT QSPRPSLNSAPSPFNPQGQSQITDPRQAQSSPPWSYDQSYPSYLSQMTSPSIHSTTPLSSTRGTGLPAITDVPRRLSGASELGPFSDPRQFTSISSLTESRFSNPRMHYPATFTYTPP VTSGMSLGMSATTHYHTYLPPPYPGSSQNQSGPFQTSSTPYLYYGTSSGSYQFPMVPGGDRSPSRMLPPCTTTSNGSTLLNPNLPNQSDGVEADGSHSSSPTVLNSSGRMDESVWRPY.

[0010] In the above application, preferably, the livestock and poultry are chickens.

[0011] The second aspect of the present invention provides the use of RUNX2 gene as a target gene in the following (1) or (2):

[0012] (1) Preparation of products for identifying resistance of livestock and poultry to Salmonella enteritidis infection;

[0013] (2) Cultivate livestock and poultry breeds that are resistant to Salmonella enteritidis infection.

[0014] In the above application, the nucleotide sequence of the RUNX2 gene is shown in SEQ ID No. 2; specifically as follows:

[0015]

[0016] The present invention found that RUNX2 is differentially expressed in chickens susceptible and resistant to Salmonella Enteritidis, and the expression level in susceptible chickens is significantly higher than that in resistant chickens. Therefore, the infection resistance of chickens to Salmonella Enteritidis can be identified by detecting the expression level of the RUNX2 gene, and disease-resistant varieties resistant to Salmonella Enteritidis infection can be selected.

[0017] The third aspect of the present invention provides the use of a reagent for detecting RUNX2 in the preparation of a product for identifying the resistance of livestock and poultry to Salmonella enteritidis infection.

[0018] Preferably, the reagent is a reagent for detecting the content of RUNX2 in cecal T cells, for example: an ELISA kit, a Western blot kit, an immunohistochemistry reagent (IHC), etc. for detecting the content of RUNX2.

[0019] A fourth aspect of the present invention provides a kit for detecting the RUNX2 gene for use in the following (1) or (2):

[0020] (1) Preparation of products for identifying resistance of livestock and poultry to Salmonella enteritidis infection;

[0021] (2) Cultivate livestock and poultry breeds that are resistant to Salmonella enteritidis infection.

[0022] Preferably, the kit for detecting the RUNX2 gene is a fluorescent quantitative PCR kit.

[0023] A fifth aspect of the present invention provides a method for identifying resistance of chickens to Salmonella enteritidis infection, comprising the following steps:

[0024] The expression level of the RUNX2 gene in the tested chickens was detected. Chickens with low RUNX2 gene expression levels had higher resistance to Salmonella enteritidis infection than chickens with high RUNX2 gene expression levels.

[0025] Beneficial effects of the present invention:

[0026] The present invention is the first to study and find that: the content of RUNX2 transcription factor in cecal T cells after Salmonella enteritidis infection is significantly different, and the expression level of RUNX2 in the susceptible group is much higher than that in the resistant group, indicating that it is a susceptible gene after Salmonella enteritidis infection. If the chicken shows typical enteritis symptoms such as diarrhea and loss of appetite, and a significant increase in the expression level of RUNX2 is detected, this may be a sign of chickens susceptible to Salmonella enteritidis infection; if the chicken does not show the corresponding symptoms and the RUNX2 expression level is not significantly increased, it indicates that the chicken is resistant to Salmonella enteritidis. The single-cell transcriptomics technology can be used to identify the resistance of chickens to Salmonella enteritidis infection at the molecular level, providing technical support for the breeding of poultry varieties resistant to Salmonella enteritidis infection. BRIEF DESCRIPTION OF THE DRAWINGS

[0027] Figure 1 : Second cell quality control results.

[0028] Figure 2 : UMAP nonlinear dimensionality reduction clustering (all cells in cecal samples).

[0029] Figure 3 : UMAP nonlinear dimensionality reduction clustering (6 samples in group S and group R).

[0030] Figure 4 : The relative expression level of specific marker gene in each cell.

[0031] Figure 5 : Cell annotation results.

[0032] Figure 6 : Heat map of RAS activity in cellular regulons of group R.

[0033] Figure 7 : Heat map of RAS activity in regulons of each cell population in group R.

[0034] Figure 8 : Heat map of RAS activity in regulons at the cellular level in group S.

[0035] Fig. 9 : Heat map of RAS activity of regulons in each cell population in group S.

[0036] Fig.10 : R group Regulon specificity ranking diagram.

[0037] Fig.11 : S group Regulon specificity ranking diagram.

[0038] Fig.12 : Heat map of RAS-specific regulons of each cell population in group R.

[0039] Fig.13 : Heat map of RAS-specific regulons of each cell population in the S group.

[0040] Fig.14 : ROC curve of RUNX2 in T cells.

[0041] Fig.15 : Detection results of RUNX2 gene expression in chicken. DETAILED DESCRIPTION

[0042] It should be noted that the following detailed descriptions are illustrative and are intended to provide further explanation of the present application. Unless otherwise specified, all technical and scientific terms used herein have the same meanings as those commonly understood by those skilled in the art to which the present application belongs.

[0043] In order to enable those skilled in the art to more clearly understand the technical solution of the present application, the technical solution of the present application will be described in detail below in conjunction with specific embodiments.

[0044] The test materials used in the examples of the present invention are all conventional test materials in the art and can be purchased through commercial channels. Experimental methods without detailed conditions are carried out according to conventional test methods or the operating instructions recommended by the supplier.

[0045] Example 1: Screening and identification of biomarkers associated with Salmonella enteritidis infection

[0046] 1. Experimental methods:

[0047] (1) Determination of whether chickens are infected with Salmonella enteritidis and sample collection

[0048] A total of 77 one-day-old Wenshang Luhua chickens with similar body weight and negative for Salmonella Enteritidis were selected and gavaged with 0.3 mL of 3.03 × 10 8 cfu / mL of Enteritidis Salmonella (purchased from the Chinese Veterinary Microbial Culture Collection Center, CVCC3377) bacterial solution was used to determine the bacterial content in feces by coating. 7 days after infection, the 17 chickens with the highest bacterial content were selected as the susceptible group (S group) and the 17 chickens with the lowest bacterial content were selected as the resistant group (R group) by the two-tail method. The 3 chickens with the highest bacterial content and the 3 chickens with the lowest bacterial content were used as the screening set, and their cecal tissues were used to prepare single-cell suspensions for single-cell transcriptome sequencing. The remaining chickens in the S group and the R group were used as the validation set.

[0049] (2) Single-cell transcriptome sequencing

[0050] ① Preparation of single cell suspension

[0051] The tissue was cut into 2 mm long pieces and incubated on ice in 20 mM EDTA-PBS for 90 min, shaking once every 30 min. After the incubation, the tissue was shaken vigorously and the supernatant was collected into a new centrifuge tube as fraction 1. Fresh EDTA-PBS was added to the fresh tissue for incubation, and a fraction was collected every 30 min until the supernatant was almost completely occupied by crypts. The last fraction (full of crypts) was washed twice with PBS, centrifuged at 300 g for 3 min, and dissociated with TrypLE express at 37 °C for 1 min. The 40 μm FlowmiTM Tip Strainer was used to remove cell debris and cell clusters; cell suspension was prepared after resuspending for subsequent experiments; trypan blue staining and a hemocytometer were used to calculate the concentration and cell viability of the single cell suspension; the next step of the experiment could be carried out when the number of live cells reached 90%.

[0052] ② Library construction and sequencing

[0053] This library construction and sequencing used the 10x Genomics platform of Shanghai Ouyi Biomedical Technology Co., Ltd. using microfluidic technology to encapsulate beads and cells with Cell Barcodes in droplets, collect the droplets containing cells, and then lyse the cells in the droplets so that the mRNA in the cells is connected to the Cell Barcode on the beads to form SingleCellGEMs. Reverse transcription reaction was performed in the droplets to construct a cDNA library, and the sample source of the target sequence was distinguished by the sample index on the library sequence.

[0054] (3) Data preprocessing

[0055] After the machine is completed, the raw data (raw reads) generated in the high-throughput sequencing are fastq format sequences. The 10xGenomics official software Cell Ranger (version 7.0.1) is used to perform data quality statistics on the raw data and compare it to the reference genome (chicken: Gallus gallus_v5.0). The software quantifies the high-throughput single-cell transcriptome data by identifying the CellBarcode markers that distinguish cells in the sequence and the UMI markers of different mRNA molecules in each cell, and obtains quality control statistical information such as high-quality cell number, gene median, and sequencing saturation.

[0056] Based on the preliminary quality control of Cell Ranger, the Seurat (version 4.0.0) software package was used to further quality control the data. The number of most cell expressions, the number of UMIs, and the proportion of mitochondrial transcript expression are concentrated in a certain area. According to the distribution of indicators such as nUMI, nGene, and percent.mito, low-quality cells were filtered. The specific quality control scheme was: retaining cells with more than 200 genes, more than 1000 UMIs, log10GenesPerUMI greater than 0.7, mitochondrial UMI ratio less than 5%, and red blood cell gene ratio less than 5% as high-quality cells, and using DoubletFinder (version 2.0.3) software to remove double cells. After the quality control is completed, the NormalizeData function in the Seurat package is used to standardize the data.

[0057] (4) Transcription factor identification and screening of key differential transcription factors

[0058] The FindVariableGenes function in the Seurat package (mean.function = FastExpMean, dispersion.function = FastLogVMR) was used to screen the top 2000 highly variable genes (HVGs, highly variable genes). The expression profiles of highly variable genes were used for PCA (principal component) dimensionality reduction analysis, and the results were visualized in two-dimensional space by UMAP (non-linear dimensionality reduction). Cell type annotation was performed based on the HPCA reference data set and specific marker genes obtained by previous studies using the SingleR (version 1.4.1) package. The motifs database of RcisTarget and GRNboost (SCENIC version 1.2.4, RcisTarget version 1.10.0 and AUCell version1.12.0) were used to run with default parameters. The potential target genes of each transcription factor were determined based on co-expression; the real transcription factors and their corresponding target genes were determined based on motif analysis using the RcisTarget package; the activity of each regulator in each cell was scored using the AUCell package (version 1.8.0).

[0059] To evaluate the cell type specificity of each regulator, the scFunctions (https: / / github.com / FloWuenne / scFunctions / ) package was used to calculate the regulator specificity score (RSS) based on Jensen-Shannon divergence (JSD) and the correlation index (CSI) of all regulators. Comparing the correlation results between the susceptible group and the resistant group, the differential transcription factors in different cell types can be obtained.

[0060] 2. Experimental results:

[0061] (1) Cell profile

[0062] The results of the first cell quality control are shown in Table 1. After aligning the reads to the reference genome using Cell Ranger, quality control results such as the number of high-quality cells, number of genes, and genome alignment rate in the original data were obtained to evaluate the quality of each sample.

[0063] Table 1: Results of the first cell quality control

[0064]

[0065] The results showed that: Estimated Number of Cells (the number of cells obtained) ≥ 7000, Sequencing Saturation (sequencing saturation) ≥ 40%, Fraction Reads in Cells (the number of sequenced reads aligned to high-quality cells) ≥ 70%, which met the basic requirements.

[0066] The results of the second cell quality control are shown in Figure 1 , based on the preliminary quality control of Cell Ranger, the experimental data was further quality controlled, and the data of multiple cells, double cells or unbound cells were eliminated for downstream analysis. The quality control standard is: retaining genes greater than 200, UMIs greater than 1000, and log10GenesPerUMI greater than 0.7 as high-quality cells, and then using DoubletFinder software to remove double cells for downstream analysis. The violins of the number of genes (nGene), the number of UMIs (nUMI) and the ratio of the number of genes per unit UMI in the corresponding sample before and after quality control reflect the complexity of the data. The points in the violin plot are concentrated, indicating that the stability and quality of the cells in the sample meet the requirements and the experimental data are reliable.

[0067] (2) Single-cell transcriptome data analysis

[0068] ①UMAP (nonlinear dimensionality reduction) analysis

[0069] The dimensionality reduction algorithms used are PCA (Principal Components Analysis) and UMAP (Uniform Manifold Approximation and Projection) algorithms. The PCA-based dimensionality reduction results are visualized by UMAP for clustering of single-cell groups. The clustering algorithm uses SNN to ultimately obtain the optimal cell clustering. Closer points represent cells with similar gene expression patterns, while farther points represent cells with greater differences in gene expression. The horizontal and vertical axes represent the first and second principal components of dimensionality reduction, respectively. Each point in the figure represents a cell, and cells in different groups are distinguished by different colors ( Figure 2 ); cells from different samples are distinguished by different colors ( Figure 3 All cells in the cecal samples can be divided into 18 clusters (Fig. Figure 2 ), and appeared in all 6 samples ( Figure 3 ).

[0070] ②Cell type annotation

[0071] The SingleR (version 1.4.1) package was used to identify specific marker genes obtained by previous studies based on the HPCA reference dataset ( Figure 4 ) for cell type annotation, the horizontal axis represents different cell types, the vertical axis represents genes, the size of the dot reflects the expression ratio of the gene in the cell population, and the color of the dot reflects the expression level of the gene in the cell population: from light blue (low expression) to dark red (high expression). A total of 8 cell types were obtained ( Figure 5 ), each cell type is distinguished by a different color, namely Epithelium, Endothelium, Glia, Fibroblast, B cells, T cells, Myeloid, and Mast cells.

[0072] ③Scenic analysis

[0073] The SCENIC software can be used to identify the co-expressed modules (regulons) between transcription factors (TFs) and potential target genes, as well as the regulon activity score (RAS) of each cell ( Figure 6-Figure 9 The specific relationship between the predicted regulon and each cell type is obtained by calculating the regulon specificity score (RSS). Figure 10-13 ). The rows represent different regulons, the columns represent cells in different cell populations, and the color changes from blue to red, indicating that the RAS activity score changes from low to high. The higher the RAS score, the stronger the activity / specificity of the regulon in the population.

[0074] Through score analysis, it was found that in the R group, FOXO1 and IRF4 were highly expressed in T cells and were specifically associated with this cell population, and SOX5 was highly expressed in Mast cells and was specifically associated with this cell population; in the S group, FLI1 was highly expressed in Endothelium and was specifically associated with this cell population, FOXA1 was highly expressed in Epithelium and was specifically associated with this cell population, and RUNX2, ETS1 and IRF4 were specifically highly expressed in T cells.

[0075] ④ Screening of differential transcription factors between susceptible and resistant groups

[0076] Comparison between the R group and the S group showed that RUNX2 was specifically highly expressed in T cells only in the S group, and this transcription factor may be related to S. Enteritidis infection.

[0077] ⑤Confirmation of biomarkers of resistance to Salmonella enteritidis infection in chickens

[0078] The candidate biomarkers associated with Salmonella enteritidis infection in chickens were confirmed using the validation set. The ROC curve of each indicator of the candidate cecal differential biomarkers screened in this study was drawn using IBM SPSS Statistics 25 software, and the sensitivity and specificity were calculated. The diagnostic efficacy of a single transcription factor was analyzed, and biomarkers associated with resistance to Salmonella enteritidis infection in chickens were confirmed. The ROC curve is shown in Figure 2. Fig.14 shown.

[0079] SPSS software was used to draw the ROC curves of differential transcription factors in the S group and the R group. The ROC curve is a curve that reflects the relationship between sensitivity and specificity. The horizontal axis X-axis is 1-specificity, also known as the false positive rate (false alarm rate). The closer the X-axis is to zero, the higher the accuracy; the vertical axis Y-axis is called sensitivity, also known as the true positive rate (sensitivity). The larger the Y-axis is, the better the accuracy. Sensitivity refers to the proportion of actual down-regulated metabolites that the screening method can correctly judge as down-regulated. Specificity refers to the proportion of actual regulated metabolites that the screening method can correctly judge as down-regulated.

[0080] Youden index, also known as the accuracy index, is an index used to judge the authenticity of a screening test when it is assumed that the harmfulness of false negatives (missed diagnosis rate) and false positives (misdiagnosis rate) are of equal significance. Youden index = sensitivity + specificity - 1. The larger the Youden index, the greater the authenticity and the better the diagnostic method.

[0081] The results showed that the AUC value of the differential transcription factor RUNX2 was 1.000, the sensitivity was 100.0%, and the specificity was 100.0% ( Fig.14 ). Therefore, the transcription factor RUNX2 can have good identification performance for the resistance of chickens to enteritidis infection.

[0082] Example 2: Application of transcription factor RUNX2 in identification of resistance of chickens infected with Salmonella enteritidis

[0083] 1. Experimental methods:

[0084] Twelve one-day-old Wenshang Luhua chickens that were negative for Salmonella Enteritidis and had similar body weight were gavaged with Salmonella Enteritidis according to the method of Example 1. 7 days after infection, the three chickens with the highest bacterial content were taken as the susceptible group (S group) and the three chickens with the lowest bacterial content were taken as the resistant group (R group) by the two-tail method.

[0085] RNA was extracted from the cecum of chickens; the extracted RNA was reverse transcribed into cDNA; the expression level of RUNX2 transcription factor was monitored by designing specific primers (F: CAGACCAGCAGCACTCCATA; R: TTGGGCAAGTTTGGGTTTAG); internal reference genes (such as β-actin or GAPDH) were used as standardization genes to correct the expression data, and the expression level of RUNX2 was detected by real-time quantitative PCR.

[0086] 2. Experimental results:

[0087] The results are as follows Fig.15 As shown in the figure, the results showed that the expression level of RUNX2 in the S group was significantly higher than that in the R group, indicating that RUNX2 is a susceptibility gene after infection with Salmonella enteritidis. Therefore, the resistance of chickens to Salmonella enteritidis infection can be identified based on the expression level of RUNX2. If chickens show typical enteritis symptoms such as diarrhea and loss of appetite, and a significant increase in RUNX2 expression level is detected, this may be a sign that the chickens are susceptible to Salmonella enteritidis infection; if the chickens do not show the corresponding symptoms and the RUNX2 expression level is not significantly increased, the chickens may be resistant to Salmonella enteritidis.

[0088] The above description is only the preferred embodiment of the present application and is not intended to limit the present application. For those skilled in the art, the present application may have various modifications and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application shall be included in the protection scope of the present application.

Claims

1. Application of RUNX2 as a target in the preparation of a product for identifying resistance of livestock and poultry to Salmonella enteritidis infection; the amino acid sequence of RUNX2 is shown in SEQ ID No.

1.

2. Use of RUNX2 gene as a target gene in the following (1) or (2): (1) Preparation of products for identifying resistance of livestock and poultry to Salmonella enteritidis infection; (2) Breeding livestock and poultry breeds that are resistant to Salmonella enteritidis infection; The nucleotide sequence of the RUNX2 gene is shown in SEQ ID No.

2.

3. Application of reagents for detecting RUNX2 in the preparation of products for identifying resistance of livestock and poultry to Salmonella enteritidis infection.

4. The use according to claim 3, characterized in that: The reagent is a reagent for detecting the content of RUNX2 in cecal T cells.

5. The use according to claim 3, characterized in that: The reagent is an ELISA kit, a Western blot kit or an immunohistochemical reagent for detecting the content of RUNX2.

6. Use of a kit for detecting RUNX2 gene in the following (1) or (2): (1) Preparation of products for identifying resistance of livestock and poultry to Salmonella enteritidis infection; (2) Cultivate livestock and poultry breeds that are resistant to Salmonella enteritidis infection.

7. The use according to claim 6, characterized in that: The kit for detecting the RUNX2 gene is a fluorescent quantitative PCR kit.

8. A method for identifying chicken resistance to Salmonella enteritidis infection, characterized in that: The following steps are involved: The expression level of the RUNX2 gene in the tested chickens was detected. Chickens with low RUNX2 gene expression levels had higher resistance to Salmonella enteritidis infection than chickens with high RUNX2 gene expression levels.

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