Blood mrna markers for selecting residual feed intake in ducks and uses thereof

Abstract

The application discloses a blood mRNA marker for selecting residual feed intake of ducks, which comprises HLX 、 ECM1 、 CSF3R and ASS1 , the sequence of the HLX gene is shown as SEQ ID NO. 1, the sequence of the ECM1 gene is shown as SEQ ID NO. 2, the sequence of the CSFSR gene is shown as SEQ ID NO. 3, and the sequence of the ASS1 gene is shown as SEQ ID NO. 4. The application compares and analyzes gene expression profiles of blood samples of high and low residual feed intake of ducks at 22 days and 42 days by using RNA-Seq technology and bioinformatics methods, screens core genes which are differentially expressed at two ages and are highly related to residual feed intake, and the discovery of the differentially expressed genes provides a theoretical basis for accelerating molecular breeding of feed utilization rate of meat ducks.

Description

Technical Field

[0001] This invention belongs to the field of poultry blood biochemical marker technology, specifically relating to a blood mRNA marker for selecting residual feed intake in ducks and its application. Background Technology

[0002] my country is a major duck farming country, with 4.218 billion commercial ducks slaughtered in 2023, accounting for about 70% of the world's total. Feed costs account for approximately 60%-70% of the total cost in duck production. Therefore, improving feed utilization is a necessary breeding goal for reducing duck farming costs and optimizing the industrialization of the duck industry.

[0003] Residual feed intake (RFI) is the difference between actual and predicted feed intake. It reflects the differences in feed utilization caused by variations in the genetic background of livestock and poultry, and can be used as an effective indicator of feed utilization. Generally, lower RFI results in better feed utilization than higher RFI. It has been found that using RFI for selection can reduce body fat content and increase muscle mass, thereby reducing feed intake and improving feed efficiency without affecting livestock and poultry growth. To date, RFI breeding work in meat ducks has progressed slowly. The main reasons include: meat ducks exhibiting different RFI traits require a long feeding period; the RFI calculation formula is complex; and mastering and accurately calculating individual feed intake requires significant manpower and resources. Therefore, identifying RFI-related biomarkers for early selection is a crucial foundation for solving these problems and accelerating the genetic improvement of feed utilization traits and the breeding of new meat duck breeds.

[0004] Studies have found that the remaining feed intake of livestock and poultry is influenced by their physiological state, including feed desire, digestion and absorption, and energy metabolism. As a major component of the internal environment, blood monitoring can quickly and accurately reflect the body's current physiological state. Furthermore, blood samples are typically obtained through simple venous blood collection, which is more non-invasive than methods such as tissue biopsies. Currently, numerous studies have identified blood biomarkers related to remaining feed intake in livestock, but few have been reported for blood biomarkers related to remaining feed intake in meat ducks. Given that mRNA levels can dynamically and accurately reflect cellular function and the body's physiological state in the early stages, and existing mRNA detection methods offer high convenience, sensitivity, and specificity, mRNA markers have been widely used for the early detection and diagnosis of certain pathological and physiological states. Currently, however, there are no clearly defined blood mRNA biomarkers related to remaining feed intake in ducks.

[0005] Search results revealed that CN113174441A provides a lncRNA related to duck residual feed intake and its application. The lncRNA is XR_001191699.1. RNA-Seq technology and bioinformatics methods were used to compare and analyze the gene expression profiles of liver tissues with high and low residual feed intake in ducks, identifying and screening key differentially expressed lncRNAs related to residual feed intake and lipid metabolism. CN114196763A provides a microRNA molecular marker related to duck residual feed intake and its application. The molecular marker is miRNA-1260-5p. miRNA-Seq technology and bioinformatics methods were used to compare and analyze the gene expression profiles of liver tissues with high and low residual feed intake in ducks, identifying and screening key differentially expressed miRNAs related to residual feed intake and lipid metabolism. CN117187413 discloses a hypothalamic marker related to duck residual feed intake and its application. The microRNA molecular marker is miRNA-182-5p, and the mRNA molecular marker is DDC. Molecular marker technology can be used to rapidly identify the RFI trait in small-sized meat ducks. Summary of the Invention

[0006] This invention addresses the technical problem by overcoming the shortcomings of existing technologies and provides a blood mRNA biomarker for selecting residual feed intake in ducks and its application. By collecting venous blood from ducks in the early or middle stages of growth, the residual feed intake of an individual can be rapidly and accurately identified using qPCR technology, providing an important means to accelerate the breeding process of residual feed intake in ducks.

[0007] One objective of this invention is to provide a blood mRNA biomarker for selecting residual feed intake in ducks, the blood mRNA biomarker comprising... HLX , ECM1 , CSF3R and ASS1 The HLX The gene sequence is shown in SEQ ID NO.1. ECM1 The gene sequence is shown in SEQ ID NO.2. CSF3R The gene sequence is shown in SEQ ID NO.3. ASS1 The gene sequence is shown in SEQ ID NO.4.

[0008] This invention proposes a blood mRNA marker method for selecting residual feed intake in ducks, aiming to establish a rapid, simple, accurate method for early differentiation of residual feed intake in ducks. The gene marker is... HLX , ECM1 , CSF3R , ASS1These genes are differentially expressed in the blood of ducks with different residual feed intakes during the early growth stage (22 days) and the middle growth stage (42 days). Therefore, high and low RFI identification of ducks can be completed at 22 days or 42 days. This accelerates the breeding of ducks with high residual feed intake, reduces production costs, promotes environmental protection, and achieves precision farming, which is of great significance to the sustainable development of duck farming.

[0009] This invention also provides a method for screening duck RFI trait-related genes using the above-mentioned blood mRNA markers for selecting duck residual feed intake, the method comprising the following steps: Step 1: Collect blood samples from 22-day-old or 42-day-old ducks for RNA extraction; Step 2: Convert RNA into cDNA using the FastKing gDNA Dispelling RT SuperMix kit (TIANGEN, China); Step 3: Based on the mRNA sequence, amplification primers were designed using the National Center for Biotechnology Information (NCBI), and cDNA from different duck blood samples was used as a template for quantitative fluorescence detection. Step 4: Analyze the quantitative results and screen the gene expression levels corresponding to different RFI traits in ducks. HLX , ECM1 , CSF3R , ASS1 High expression of all genes indicates that the tested individuals are low-RFI ducks; like HLX , ECM1 , CSF3R , ASS1 Low gene expression indicates that the tested individuals are high-RFI ducks.

[0010] In the above method for screening duck RFI trait-related genes using blood mRNA markers, the sequences of the amplification primers are shown below: HLX-F: GCCAGTTCTTCGCGTCTCTA HLX-R: GTCGGTTTGGTGACGTACT ECM1-F: CCGGCCCTACAAAAGGCG ECM1-R: CCGGCCCTACAAAAGGCG CSF3R-F:CCCCAAACCCTACGAGAACC CSF3R-R:GAGTTTGGTCCGGGGTCTTT ASS1-F: ACATCGTGGAGAACCGCTTT ASS1-R:TTTGATTCTCCGCACCTCCC.

[0011] The present invention further provides the application of the blood mRNA markers described above, which are used for early selection of residual feed intake in ducks.

[0012] In the application of the aforementioned blood mRNA biomarkers, the blood mRNA biomarkers are used to predict or assist in predicting ducks with high feed utilization rates; or the blood mRNA biomarkers are used to breed ducks with different feed utilization rates.

[0013] This invention further includes the application of the aforementioned blood mRNA biomarkers in the preparation of reagents for detecting duck feed utilization.

[0014] Of the reagents described above, the expression level of the blood mRNA marker is detected by nucleic acid amplification counting. The primers used for nucleic acid amplification are: HLX-F: GCCAGTTCTTCGCGTCTCTA HLX-R: GTCGGTTTGGTGACGTACT ECM1-F: CCGGCCCTACAAAAGGCG ECM1-R: CCGGCCCTACAAAAGGCG CSF3R-F:CCCCAAACCCTACGAGAACC CSF3R-R:GAGTTTGGTCCGGGGTCTTT ASS1-F: ACATCGTGGAGAACCGCTTT ASS1-R:TTTGATTCTCCGCACCTCCC.

[0015] This invention utilizes RNA-Seq technology and bioinformatics methods to compare and analyze the gene expression profiles of blood samples from ducks at 22 and 42 days of age with high and low residual feed intake. Core genes that are differentially expressed at both ages and are highly correlated with residual feed intake are screened out. The discovery of these differentially expressed genes provides a theoretical basis for molecular breeding to accelerate feed utilization in broiler ducks. Attached Figure Description

[0016] Figure 1 This is a transcriptome analysis of blood transcriptomes from high- and low-RFI ducks during the 22-day period, as presented in this invention. Figure (A) shows the PCA analysis of the blood transcriptomes from high- and low-RFI ducks during the 22-day period; (B) shows the correlation heatmap of differentially expressed genes; (C) shows the volcano plot of all genes; and (D) shows the KEGG enrichment analysis of differentially expressed genes.

[0017] Figure 2This is a WGCNA analysis diagram of the 22-day blood transcriptome in this invention. In the figure, (A) is a network topology analysis diagram under different soft threshold powers, (B) is a module clustering dendrogram, (C) is a module-feature correlation diagram, and (D) is a module-module correlation diagram.

[0018] Figure 3 This is a gene relationship analysis diagram within the RFI-related modules of this invention. In the figure, (A) is a gene expression trend diagram of different samples in four modules significantly related to RFI, and (B), (C), (D), and (E) are PPI interaction diagrams between genes in the brown, black, blue, and pink modules, respectively.

[0019] Figure 4 This is a transcriptome analysis of blood transcriptomes from high- and low-RFI ducks at 42 days, as presented in this invention. Figure (A) shows the PCA analysis of the blood transcriptomes from high- and low-RFI ducks at 42 days; (B) shows the correlation heatmap of differentially expressed genes; (C) shows the volcano plot of all genes; and (D) shows the Veen plot of common differentially expressed genes in the blood transcriptomes at 22 and 42 days.

[0020] Figure 5 This is a validation analysis diagram of mRNA biomarkers in the blood of high- and low-RFI ducks in this invention. In the figure, (A) is a graph showing the expression trend of mRNA biomarkers in the blood transcriptome at 22 and 42 days, and (B) is a graph showing the expression trend of mRNA biomarkers in the blood at 22 and 42 days verified by RNA-seq. Detailed Implementation

[0021] The technical solution of the present invention will be further described in detail below with reference to the embodiments: This embodiment is implemented under the premise of the technical solution of the present invention, and provides detailed implementation methods and specific operation processes, but the protection scope of the present invention is not limited to the following embodiments. Example 1

[0022] I. Laboratory Animals Meat-type ducks were provided and raised by Jiangsu Yike Food Co., Ltd. The experimental procedures were as follows: hatching eggs were collected and incubated. After hatching, the ducks were numbered, sexed, vaccinated, and their birth weight was measured. Healthy, uniformly weighted 1-day-old meat ducks were selected and raised together until 22 days of age. At 22 days of age, blood samples were collected from all ducks (the collected blood was immediately added to TRIzon), and they were weighed. 800 ducks of similar weight were randomly selected and housed individually in cages. All ducks were fed the same feed. Each cage was equipped with a separate feed trough and waterer to ensure that each duck could only access feed from its own trough. The feed troughs were checked twice daily, morning and evening, and supplemental feeding was provided to ducks that ate quickly. Feed consumption was recorded. A weekly cycle was performed, with remaining feed weighed and replaced with fresh feed. The experiment ended at 42 days of age.

[0023] II. RFI Measurement and Blood Collection During the experiment, the body weight of broiler ducks at 22 days of age (BW22) and 42 days of age (BW42), feed intake (FI), average daily weight gain (BWG), average daily feed intake (ADFI), daily weight gain (ADG), feed conversion ratio (FCR), and residual feed intake (RFI) were collected and recorded. The formula for calculating residual feed intake (RFI) is as follows: RFI = ADFI – (b0 + b1 × MBW) 0.75 +b2×ADG) Where ADFI is daily feed intake; MBW0.75 is average metabolic body weight; ADG is daily weight gain; b0 is the intercept; and b1 and b2 are regression coefficients. The RFI value of broiler ducks was calculated using the linear fitting function in SAS 9.4 software. The growth performance of broiler ducks with different RFIs was compared, and the results are shown in Table 1.

[0024] Based on the calculated RFI values, the experimental duck flock was ranked, and the ducks were divided into high-RFI and low-RFI groups according to their RFI levels. Combining the FCR values ​​collected during the experiment, eight ducks with extreme values ​​from each of the high-RFI and low-RFI groups were selected, and blood samples were collected from them at 42 days of age (the collected blood was immediately added to TRIzon). Blood samples from corresponding individuals were also selected from the blood samples collected at 22 days of age, resulting in a total of 32 samples. The samples were cryopreserved in liquid nitrogen and then transferred to a -80°C freezer for long-term storage for total RNA extraction.

[0025] Table 1 Comparison of growth performance of meat ducks with different RFIs

[0026] III. Whole Blood Total RNA Extraction and Sequencing Total RNA was extracted according to the Trizol reagent extraction instructions, and RNA-specific agarose gel electrophoresis was used to detect the integrity of the RNA samples and the presence of DNA contamination. RNA integrity was determined using an Agilent 2100 bioanalyzer, purity was detected using a NanoPhotometer spectrophotometer, and a Qubit 2.0 fluorometer was used for precise measurement of RNA concentration. RNA samples with an OD260 / 280 value ≥1.8 and a RIN value ≥8.0 were considered acceptable and could be used for library construction and deep sequencing on the Illumina NovaSeq 6000 platform.

[0027] IV. Identification of Differentially Expressed Genes Differentially expressed genes (DEGs) were analyzed and screened using the limma data package in R 4.2.2 software. The screening criteria were: the absolute value of the fold change (FC) ≥ 2 and the corrected fold change.P ≤0.05. Use the "pheatmap" and "ggplot2" R packages to visualize DEGs, generating volcano plots and heatmaps.

[0028] V. Enrichment analysis of differentially expressed genes GO and KEGG pathway Perform GO or KEGG pathway analysis on DEGs. Map genes to each term in the GO database (http: / / www.geneontology.org / ), calculate the number of genes in each term, and obtain a statistical count of genes with a specific GO function. Apply hypergeometric tests to identify GO entries that are significantly enriched in genes compared to the background.

[0029] KEGG is a major public database for pathways. Pathway significant enrichment analysis uses KEGG pathways as units and applies hypergeometric tests to identify pathways that are significantly enriched in genes compared to the overall background. Significant pathway enrichment can identify the most important biochemical metabolic and signal transduction pathways involved by genes.

[0030] VI. Screening of key differentially expressed genes The integrated gene expression matrix was analyzed using the WGCNA software in R to assess the correlation between different modules and RFI in broiler ducks. Modules associated with RFI were selected as WGCNA gene groups for further analysis. The "VennDiagram" R package was used to obtain the intersection genes between the DEGs group and the RFI-related gene groups generated by WGCNA. These intersection genes were considered key DEGs associated with RFI generation. The STRING online tool was used to predict and visualize molecular interactions and PPI networks. Key genes were input into the STRING tool to obtain the PPI network. The obtained PPI network was imported into Cytoscape software, and the Degree algorithm was used to calculate the top 50 genes with the most nodes as key pivot genes for evaluation.

[0031] VII. Combined Transcriptome Analysis at Multiple Ages Key DEGs associated with RFI generation were screened from the blood transcriptome of 22-day-old ducks and subjected to Veen analysis with the blood transcriptome of 42-day-old ducks. Common genes were further screened, with the screening criteria being the top 10 in the PPI network and an FPKM value ≥50. The final selected DEGs were used as blood mRNA markers for the remaining feed intake of ducks in the early selection process (see Table 2).

[0032] Table 2. Expression of key DEGs in the blood of broiler ducks of different ages

[0033] 8. Primer sequences for differentially expressed mRNAs used for qRT-PCR validation To assess the reliability and reproducibility of the sequencing data, blood samples were collected from 16 ducks with high and low RFI levels at 22 days of age as candidate genes. HLX , ECM1 , CSF3R , ASS1 The specific steps for fluorescence quantitative verification are as follows: Based on the corresponding mRNA sequence, the amplification primers used in the National Center for Biotechnology Information (NCBI) experiment are shown in Table 3. β-actin was used as the internal reference gene for quantitative mRNA expression. The relative expression level of mRNA was calculated based on the Ct values ​​of the target gene and the internal reference gene obtained in the experiment.

[0034] Table 3 Primer sequences for differentially expressed mRNAs used for qRT-PCR validation

[0035] The reaction system is shown below:

[0036] The loop condition is as follows:

[0037] The PCR system was thoroughly mixed, centrifuged after reaction, and aliquoted into 96-well plates. qRT-PCR reactions and analyses were performed on an ABI 7500 (Thermo Fisher Scientific, USA). 2 −ΔΔCt The relative expression levels of genes among the samples in each group were calculated using a t-test, and the relative expression levels were statistically analyzed. P <0.05 indicates a significant difference.

[0038] VIII. Results and Analysis As a newly developed feed efficiency indicator in recent years, RFI (Regenerative Feed Flow Index) calculations are corrected for individual metabolic weight. Therefore, compared to feed conversion ratio (FCR), it can avoid the inherent differences in feed utilization efficiency among animals of different body sizes and growth stages, making feed utilization evaluation more scientific. Analysis of the growth performance of broiler ducks with different RFIs revealed no significant difference in body weight at 22 and 42 days. However, within these 21 days, low-RFI broiler ducks consumed 15% less feed than high-RFI broiler ducks. Therefore, promoting the application of RFI in large-scale farms directly helps reduce feeding costs and improve economic efficiency.

[0039] Twenty-one-day blood transcriptome analysis of high- and low-RFI broiler ducks revealed significant differences in gene expression between the two populations. The low-RFI broiler ducks showed 288 highly expressed genes and 137 low-expressed genes. KEGG enrichment analysis indicated that these genes were significantly enriched in pathways related to arginine biosynthesis, arachidonic acid metabolism, drug metabolism, taurine metabolism, primary bile acid biosynthesis, and niacin and nicotinamide metabolism. Results are shown below. Figure 1 These pathways are mostly related to the synthesis and decomposition of substances. It is speculated that the differences in the rate of substance synthesis and decomposition among individuals may lead to different RFI in meat ducks. Since blood is the main route for transporting substances in the body, it is an important way to quickly and accurately identify RFI in meat ducks by identifying key genes related to RFI in the blood.

[0040] We used WGCNA analysis to identify gene sets highly associated with the RFI trait. Using a scale-free topological fit index of 0.8, a soft threshold of 10, a minimum number of genes in the module of 100, and a gene hierarchical clustering graph template merging height threshold of 0.25, we analyzed all selected genes (excluding genes with expression levels less than 50% of the samples). Figure 2 The results showed that a total of 13 different templates were obtained. The brown and black modules were negatively correlated with RFI, while the blue and pink modules were positively correlated with RFI. The intersection of genes and differentially expressed genes in these four modules was analyzed, and PPI interaction analysis was performed. The results are shown below. Figure 3 .

[0041] To avoid false positives, we screened key genes highly correlated with RFI and analyzed the 42-day blood transcriptomes of the same individuals. We again found significant differences in gene expression between low-RFI and high-RFI duck populations, with 200 highly expressed genes and 125 low-expressed genes in the low-RFI duck population. By performing Veen analysis on the genes related to RFI in the 22-day blood sample previously screened using WGCNA analysis and the differentially expressed genes in the 42-day blood sample, we found that 18 genes were simultaneously upregulated and 2 genes were simultaneously downregulated. The results are shown below. Figure 4 Combining PPI interaction and FPKM values, select... HLX , ECM1 , CSF3R , ASS1 Four genes are blood biomarkers highly associated with duck RFI. Figure 5 The qRT-PCR results indicate that the reliability of transcriptome sequencing, and HLX , ECM1 , CSF3R , ASS1 The reproducibility of four genes as blood mRNA markers of residual feed intake in early-selected ducks.

[0042] From the perspective of acquisition methods, collecting blood from broiler ducks is relatively simple and causes minimal damage to the ducks' bodies, making it easy for broiler duck farmers to accept and perform. From the perspective of testing methods, qPCR technology is relatively mature, low-cost, high-precision, and fast, allowing for preliminary identification of RFI levels in broiler ducks in a short time, making it highly feasible for market implementation. Early identification and screening of broiler duck RFI can not only reduce feeding costs and environmental treatment costs in the short term, but also improve the overall genetic level of the duck flock in the long term, enhancing market competitiveness and generating sustainable economic benefits.

[0043] The above description is merely a specific embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any transformations or substitutions that can be conceived by those skilled in the art within the technical scope disclosed in the present invention should be included within the scope of the present invention. Therefore, the scope of protection of the present invention should be determined by the scope of the claims.

Claims

1. An application for selecting blood mRNA markers of residual feed intake in ducks, characterized in that, The blood mRNA biomarkers include HLX , ECM1 , CSF3R and ASS1 The HLX The gene sequence is shown in SEQ ID NO.

1. ECM1 The gene sequence is shown in SEQ ID NO.

2. CSF3R The gene sequence is shown in SEQ ID NO.

3. ASS1 The gene sequence is shown in SEQ ID NO.4; the blood mRNA marker is used to select the remaining feed intake of 22-day-old or 42-day-old broiler ducks.

2. The application of the blood mRNA marker according to claim 1, characterized in that, The blood mRNA biomarkers are used to predict or assist in predicting high feed utilization rates in 22-day-old or 42-day-old broiler ducks.

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