A key gene for differentiation of duck meat and egg traits and a method for mining the key gene based on whole genome sequencing

Abstract

The present invention relates to a key gene for the differentiation of duck meat and egg traits and a method for mining the key gene based on whole genome sequencing. The key gene is the duck SIK1 gene, and its nucleotide sequence is shown in SEQ ID NO: 1. The present invention uses a method for analyzing the key genes in the domestication process of duck meat traits and egg traits using whole genome resequencing, and discovered the key gene SIK1 that affects the differentiation and domestication process of laying ducks and meat ducks. The gene SIK1 plays a role in regulating sugar metabolism and cell proliferation. The present invention used whole genome resequencing technology to assemble the genome of Jinding duck for the first time, and compared it with the genomes of other duck species such as Beijing duck, mining another key gene SIK1 gene for the differentiation of duck meat and egg traits, which is helpful for the molecular breeding of ducks and provides a new idea for the future exploration of key genes for the differentiation of meat / laying duck traits.

Description

Technical Field

[0001] The present invention belongs to the field of agricultural and animal husbandry technology, and more specifically relates to a whole-genome resequencing method for analyzing the domestication process of duck meat traits and egg-laying traits. The method obtains the duck SIK1 gene, a key gene that affects the differentiation and domestication process of laying ducks and meat ducks. Background Art

[0002] Ducks, a general term for waterfowl belonging to the Anatidae family and subfamily Anatidae, are one of the most widespread waterfowl species in the world and possess significant economic value. Scientific research in duck breeding and improvement contributes to improving the quality and efficiency of duck products. Based on their economic value, ducks are generally divided into three types: meat-producing, egg-laying, and dual-purpose. The Peking duck represents the meat-producing type, the Jinding duck represents the egg-laying type, and the Gaoyou duck represents the dual-purpose type. These three types of ducks differ significantly in body shape, growth rate, and egg production. Despite numerous reports, the differentiation of egg-laying and meat-producing traits in ducks and the genes controlling these traits remain unclear.

[0003] Because duck breeding characteristics are strongly dependent on the environment, traditional breeding methods struggle to directly select the correct genotype from phenotype, significantly limiting duck breeding and trait improvement. Combining molecular breeding with traditional breeding methods to efficiently and rapidly develop high-yield, high-quality varieties is a new trend in poultry breeding, offering new ideas and approaches. However, molecular breeding presupposes a clear understanding of the molecular genetics underlying the target traits and the functional genes.

[0004] In recent years, with the continuous development of sequencing technology, many poultry breeds, such as ducks, chickens, and geese, have completed reference genome sequencing. This allows for the exploration of the relationship between genetic variation and phenotypic polymorphism at the genome-wide level, greatly accelerating livestock breeding and providing a solid theoretical foundation for molecular breeding. This study sequenced the whole genome of the Jinding duck and compared it with the genomes of other duck breeds, such as the Peking duck, to identify key genes that differentiate between egg-laying and meat-producing traits, which will facilitate molecular breeding of ducks. Summary of the Invention

[0005] The purpose of the present invention is to use the whole genome resequencing method to analyze the key genes in the domestication process of duck meat traits and egg traits. The whole genome resequencing method of the present invention discovered the SIK1 gene, a key gene affecting the differentiation and domestication process of laying ducks and meat ducks.

[0006] The purpose of the present invention is achieved through the following technical solutions:

[0007] The present invention provides a key gene for differentiation of duck meat and egg traits, which is a duck SIK1 gene, and the nucleotide sequence of the gene is shown in SEQ ID NO: 1.

[0008]

[0009] The application of the key gene, the duck SIK1 gene is used in the molecular breeding of duck meat traits and egg traits; during the domestication process of egg-laying ducks and meat ducks, egg-laying ability and fat deposition have differentiated, and the duck SIK1 gene plays a role in regulating sugar metabolism and cell proliferation in meat ducks.

[0010] A key gene is used in the preparation of a duck growth promoter. The duck SIK1 gene plays a role in regulating sugar metabolism and cell proliferation, and therefore can be used in the preparation of a duck growth promoter. It can also be used in the preparation of a reagent for detecting duck growth rate.

[0011] A kit for detecting the growth rate of a duck comprises a reagent for detecting the duck SIK1 gene.

[0012] The reagent includes a primer for detecting the duck SIK1 gene; the primer is a Real-Time PCR primer, and its sequence is:

[0013] Upstream primer: 5'-CTGTACGTCCTTGTCTGTGGTT-3' (SEQ ID NO: 2),

[0014] Downstream primer: 5'-CGGATTAGCGTTTCACAGTCTTC-3' (SEQ ID NO: 3).

[0015] A siRNA targeting the key gene, wherein the siRNA is 3-si-SIK1, the sense strand of which is 5'-GCUUCAGCAUCACCAGCUATT-3' (SEQ ID NO: 4), and the antisense strand of which is 5'-UAGCUGGUGAUGCUGAAGCTT-3' (SEQ ID NO: 5).

[0016] 3-si-SIK1 has a high interference efficiency and can be used in cell transfection experiments. It can also be used in molecular breeding for duck meat and egg traits.

[0017] A method for analyzing key genes in the domestication process of duck meat and egg traits using whole genome resequencing, comprising the following steps:

[0018] S1. We constructed laying duck chromosomes using nanopore sequencing and Hi-C techniques. We constructed a Hi-C library and analyzed the Hi-C assembly data. We annotated the genome and repetitive sequences, predicted the genome's gene structure, noncoding RNAs, and pseudogenes, and annotated gene functions.

[0019] S2. Resequence several local duck breeds; by comparing the genomes of laying and broiler ducks, identify candidate differential regions (CDRs) on autosomes, search for regions with extreme differences in allele frequency (FST) and maximum differences in genetic diversity (πlog ratio), perform principal component analysis on the genetic data to analyze population structure, detect homozygous single nucleotide polymorphisms (SNPs) and indels, and identify sites of difference between the sequenced samples and the reference genome;

[0020] S3. When predicting gene mutation regions with potential high / moderate functional effects, it was found that the high mutation region may contain SIK1, a key gene that affects the differentiation and domestication process of egg-laying ducks and meat ducks.

[0021] Prior to step S1, the present invention also performs sample collection, library preparation, and sequencing steps. Specifically, the method includes downloading the genomes of wild ducks and broiler ducks to identify potential target genomic regions; resequencing a certain number of wild ducks and performing third- and second-generation genome sequencing analysis on a certain number of laying ducks, followed by genome reassembly; rapidly freezing blood and tissue samples from all of the wild ducks and laying ducks to -20°C, followed by total DNA extraction; and slaughtering the ducks under identical processing conditions, measuring their weight and appearance, among other traits. The laying ducks used in this method are Jinding ducks, and the broiler ducks are Peking ducks.

[0022] (1) Compared with the existing technology, the advantages of the present invention are: the present invention is the first to use whole genome resequencing technology to assemble the genome of Jinding duck, and compare it with the genomes of other duck species such as Beijing duck, thereby discovering another key gene SIK1 gene for the differentiation of duck meat and egg traits, which is helpful for the molecular breeding of ducks and provides new ideas for exploring key genes for the differentiation of meat / eating duck traits in the future.

[0023] (2) The present invention uses Nanopore and Hi-C sequencing technologies to obtain high-quality genome assembly, and found more than 25 million domestication-related SNPs, insertions and deletions, and structural variations in wild ducks, meat ducks, and laying ducks. The SIK1 and IGF2 genes were screened out as key genes for the differentiation of laying ducks and meat ducks. The experiment found that high-glucose culture led to increased SIK1 mRNA and protein expression levels in duck embryo fibroblasts. High-glucose culture and silencing SIK1 can both induce cell proliferation, while overexpression of SIK1 can inhibit cell proliferation. Duck SIK1 may have the function of regulating sugar metabolism and cell proliferation.

[0024] (3) The technical solution of the invention is complete and comprehensive, the data is detailed, and the experimental results are reliable. BRIEF DESCRIPTION OF THE DRAWINGS

[0025] Figure 1 This is the qPCR result of SIK1 gene interference and overexpression in duck embryo fibroblasts, Figure 1a is the SIK1 mRNA expression level after SIK1 gene interference, showing that 3-si-SIK1 expression level is low and has a high interference efficiency; Figure 1 b SIK1 mRNA expression level after overexpression of SIK1 gene.

[0026] Figure 2 The genome information of Jinding duck is Figure 2 a is the genome assembly and annotation map of Jinding duck, Figure 2 b is the heat map of Hi-C assembled chromosomes, Figure 2 c is the collinearity between Beijing duck and Jinding duck.

[0027] Figure 3 is the resequencing data of different duck breeds; among them, Figure 3 a is the duck phylogeny and population structure analysis, Figure 3 b is the population structure of wild ducks and domestic ducks, Figure 3 c is some pictures of Chinese duck breeds.

[0028] Figure 4 It is a selective sweep gene map.

[0029] Figure 5 This is the KEGG pathway map of IGF2.

[0030] Figure 6 This is the KEGG pathway map of SIK1.

[0031] Figure 7 It is the expression of SIK1 gene in different parts of Jinding duck.

[0032] Figure 8 These are the CCK8 test results of the effects of high-glucose culture and SiRNA-SIK1 and pcDNA3.1-SIK1 on the proliferation of duck embryo fibroblasts. Note: **P<001NC vs NC(25mM Glucose); Δp<0.05SiRNA-NC vs SiRNA-NC(25mM Glucose) / SiRNA-SIK1; ΔΔp<0.01SiRNA-NC vs SiRNA-SIK1(25mM Glucose); #p<0.05pcDNA3.1 vs pcDNA3.1(25mM Glucose) / pcDNA3.1-SIK1(25mM Glucose); ##p<0.01pcDNA3.1 vs pcDNA3.1-SIK1.

[0033] Figure 9Figure 2 is the expression level of SIK1 and IGF2 mRNA after SIK1 intervention and high glucose culture. Note: **P<0.01NC vs NC (25mM Glucose); ΔΔp<0.01SiRNA-NC vs SiRNA-NC (25mM Glucose); NSp>0.05SiRNA-NC vs SiRNA-SIK1 / SiRNA-SIK1 (25mM Glucose); ##p<0.01pcDNA3.1 vs pcDNA3.1 (25mM Glucose)

[0034] / pcDNA3.1-SIK1 / pcDNA3.1-SIK1 (25mM Glucose).

[0035] Figure 10 The data are from duck embryo fibroblasts cultured in high glucose and treated with SiRNA-SIK1 or pcDNA3.1-SIK1. Note: **P<0.01NC vs NC(25mM Glucose); Δp<0.05; ΔΔp<0.01SiRNA-NC vs SiRNA-NC(25mM Glucose) / SiRNA-SIK1 / SiRNA-SIK1(25mM Glucose); #p<0.05; ##p<0.01pcDNA3.1 vspcDNA3.1(25mM Glucose)

[0036] / pcDNA3.1-SIK1 / pcDNA3.1-SIK1 (25mM Glucose). DETAILED DESCRIPTION

[0037] The present invention is described in detail below with reference to the accompanying drawings and embodiments:

[0038] The present invention uses whole-genome resequencing to analyze the key genes in the domestication process of duck meat and egg traits. To achieve the above objectives, the present invention adopts the following technical solutions:

[0039] 1.1 Sample collection, library preparation, and sequencing

[0040] The genomes of wild ducks and meat ducks (Peking ducks) were downloaded from the NCBI website to identify potential target genomic regions. In addition, the inventors collected wild ducks (Anas platyrhynchos) from Zhejiang Province and took 20 individuals for resequencing. Jinding ducks, as the main representative of laying ducks, are from Fujian Province. A total of 20 individuals (10 males and 10 females) were taken for third-generation and second-generation genome sequencing analysis, and genome reassembly was performed. All blood and tissue samples were quickly frozen to -20°C, and then the traditional phenol-chloroform method was used to extract total DNA. The ducks were slaughtered under the same processing conditions, and traits such as weight and appearance were measured.

[0041] 1.2 Jinding duck genome assembly

[0042] 1.2.1 Nanopore sequencing

[0043] Jinding ducks were subjected to third-generation single-molecule sequencing using nanopore sequencing technology: high-quality DNA was extracted, and genomic DNA was randomly sheared after passing the test. Large DNA fragments were enriched and purified using magnetic beads, and then cleaved and recovered. Fragment repair: selected large DNA fragments were subjected to damage repair, end repair, and 3' end A addition, and the reaction products were purified. Ligation: the repaired fragment products were ligated and purified to obtain the final library. Quantification: The established DNA library was accurately quantified using Qubit. Library loading: a certain amount of DNA library was taken, mixed with the relevant reagents on the library, and loaded into a flow cell. Real-time single-molecule sequencing was performed on the Nanopore PromethION sequencer to obtain raw sequencing data.

[0044] 1.2.2 Hi-C library construction and data collection

[0045] The type of Hi-C was in situ Hi-C, which included cell cross-linking, endonuclease digestion, end-repair, circularization, DNA purification and capture, and sequencing. High-throughput sequencing was performed using the Illumina HiSeq 2000 platform with a read length of PE150.

[0046] Fine-grab HI-C assembly was performed. Clean data was corrected using Canu software and assembled based on the corrected data. Third-generation sequencing data underwent three rounds of correction using Racon software, and second-generation data underwent three rounds of correction using Pilon software.

[0047] Assembly result evaluation: The assembly results were evaluated based on the following three aspects: alignment rate of next-generation sequencing reads, core gene integrity, and BUSCO assessment.

[0048] Clean reads were counted, with each cell representing four lines. Reads 1 and 2 were counted as two reads at each end. The samtools flagstat command was used to calculate the percentage of clean reads that matched the reference genome. The samtools flagstat command mapped the two-end sequencing reads to the reference genome, with distances consistent with the length distribution of the sequenced fragments. Alignment (%) was performed using BWAMEM with no parameters. BWA software compared short reads obtained by second-generation high-throughput sequencing (Illumina HiSeq sequencing platform) to the reference genome, and the completeness of the assembled genome was assessed by calculating the alignment rate.

[0049] The CEGMA v2.5 (default parameters) database contains 458 conserved core genes of eukaryotic organisms. CEGMA v2.5 was used to assess the completeness of the final genome assembly.

[0050] The BUSCO v2 database contains 2586 conserved core genes. The completeness of the genome assembly was assessed using BUSCO v2.0 software. BUSCO parameters included: -evalue 1e-05 (BLAST search E-value cutoff) and -sp generic (generic model).

[0051] 1.2.3HI-C assembly and analysis

[0052] The raw data of Hi-C sequencing is filtered to remove adapter sequences and low-quality reads to obtain high-quality Clean Data. The raw data is compared with the preliminarily assembled genome to obtain mapped data. Based on the statistics of mapped data, the comparison efficiency, insert length, effective Hi-C data volume and coverage are calculated as the basis for evaluating the quality of the sequencing library. Finally, the Draft Genome sequence is further assembled using the effective Hi-C data, including the classification, sequencing and post-sequencing direction of the Draft Genome sequence, and the genome sequence is finally obtained, and the assembly results are evaluated. At the same time, fine annotation of the genome is performed, including repetitive sequence annotation and transposon classification, coding gene prediction, non-coding RNA annotation and pseudogene annotation; gene function annotation, including NR library annotation, KEGG metabolic pathway annotation, COG annotation (geneontology), TrEMBL annotation and regulatory motif prediction.

[0053] 1.2.4 Genome annotation analysis

[0054] With reference to relevant literature, the software was used to analyze the repetitive sequence annotation, coding gene prediction, non-coding RNA prediction, pseudogene annotation, gene function annotation and other information in the Jinding duck genome, and the prediction results were evaluated.

[0055] 1.2.5 Repeat sequence annotation

[0056] Based on the principles of structure prediction and de novo prediction, the repetitive sequence database of the genome was established using LTR_FINDER and RepeatScout. The database was classified using PASTEClassifier and then compared with Repbase 21 The databases were merged to form the final repeat sequence database. Using RepeatMasker 22 The software predicts the repetitive sequences of the genome based on the constructed repetitive sequence database.

[0057] Repeat sequence software parameters: LTR_FINDER, RepeatScout, and PASTEClassifier used default parameters. RepeatMasker parameters were -norna-engine wublast.

[0058] 1.2.6 Prediction of coding genes

[0059] Three different strategies were used to predict the genome's gene structure: de novo prediction, orthologous species prediction, and single-gene prediction. Prediction results were integrated using EVM v1.1.1. Genscan, Augustus v2.4, GlimmerHMM v3.0.4, GeneID v1.4, and SNAP (version 2006-07-28) were used for de novo prediction; Gemoma v1.3.1 was used for orthologous species prediction; Hisat v2.0.4 and Stringtie v1.2.3 were used for reference transcript assembly; TransDecoder v2.0 and Genemarks-TV 5.1 were used for gene prediction; and PASAV v2.0.2 was used for Unigene sequence prediction based on unreferenced transcriptome data. Finally, prediction results from these three methods were integrated using EVM v1.1.1, and the results were refined using PASAV v2.0.2. The results are shown in the progress chart.

[0060] 1.2.7 Non-coding RNA Prediction

[0061] Non-coding RNAs (ncRNAs) are non-protein coding RNAs, including microRNAs, rRNAs, and tRNAs with various known functions. Different strategies are used to predict non-coding RNAs based on their structural characteristics.36 Database, Blastn alignment of the whole genome, identification of microRNA and rRNA.

[0062] 1.2.8 Pseudogene Annotation

[0063] Pseudogenes have sequences similar to functional genes but have lost their original function due to mutations such as insertions or deletions. Using the predicted protein sequence and BLAST alignment, we searched for homologous gene sequences (possible genes) across the genome. We then used GeneWise to search for premature stop codons and frameshift mutations in the gene sequence to identify pseudogenes. GenBlastA: -e1E-5 (Blast parameter: e-value), all other parameters were set to default. GeneWise software parameters were set to default.

[0064] 1.2.9 Gene function annotation

[0065] The predicted gene sequences were compared with the functional databases NR, KOG, GO, KEGG, and TrEMB using BLAST v2.2.31 (-EVALue 1E-5). KEGG pathway analysis, KOG functional analysis, and GO functional analysis were used to annotate gene functions.

[0066] 1.3 Whole-genome resequencing

[0067] The quality and quantity of DNA samples from Fujian local varieties were determined by agarose gel electrophoresis. Paired-end libraries were generated for each qualified sample using standard procedures. The average insert length was 500 bp and the average read length was 150 bp. All libraries were cloned in Sequencing on the platform achieved an average raw read coverage of 10× for each sample. This sequencing depth ensures accurate mutation screening and genotyping, meeting the requirements for population genetic analysis. Uploaded resequencing data were downloaded from NCBI, and a total of 119 DNA samples from 13 varieties were screened.

[0068] 1.3.1 SNP / indel

[0069] To identify key genes that differentiate between laying ducks, meat ducks, and wild ducks, we aligned paired-end reads from different samples to the reference genome, detected homozygous single-nucleotide polymorphisms (SNPs) and indels, and identified sites of difference between the sequenced samples and the reference genome. Raw paired-end 150bp sequencing reads were aligned to the reference genome using Burrows-Wheeler alignment (BWAAlN) (default parameters). Identified SNPs / indels were further classified using SnpEff software based on gene annotations in the reference genome.

[0070] 1.3.2 Selective Scan Detection

[0071] We searched for highly differentiated regions among mallard, laying, and meat ducks on a genome-wide scale. We calculated the fitness index (FST) and p-values ​​of the likelihood ratio test using vcfflibs (https: / / github.com / vcflflib / vcflflib#vcflflib).

[0072] 1.3.3 Principal Component Analysis

[0073] All SNPs were analyzed using principal component analysis (PCA) using EIGENSOFT software (version 4.2). This software package was used to perform PCA on genetic data and analyze population structure.

[0074] 1.3.4 SIK1 gene sequence analysis

[0075] Based on the resequencing data, differential SNPs were identified across samples. Primers were designed using Primer Premier software, with annealing temperatures shown in Appendix 3. PCR products were sequenced using Sanger sequencing, and gap-affinity sequences were further corrected.

[0076] 1.4 SIK1 gene function verification

[0077] 1.4.1 Culture and transfection of duck embryo fibroblasts

[0078] Duck embryo cells (Shanghai Cell Bank, Chinese Academy of Sciences) were subcultured in a duck embryo-specific culture medium (IMMOCELL, Xiamen, China) at 37°C and 5% CO2 for subsequent RNA interference efficiency, overexpression efficiency analysis, and high glucose induction experiments.

[0079] To confirm the role of SIK1 under high glucose induction, siRNA-SIK1 and pcDNA3.1-SIK1 (duck SIK1 gene interference and overexpression vectors, see below) were constructed and transiently transfected into duck embryo fibroblasts, followed by high glucose induction culture. The steps are as follows:

[0080] Group settings: control group, siRNA-NC group, siRNA-SIK1 group, pcDNA3.1 group, pcDNA3.1-SIK1 group, three replicates per group;

[0081] Transfection reagent preparation:

[0082] siRNA-NC and siRNA-SIK1 groups: 125 μl serum-free medium + 5 μl RNA reagent + 4 μl LipoRNAi reagent mixed;

[0083] pcDNA3.1 and pcDNA3.1-SIK1 groups: 125 μl serum-free culture medium (Thermo Fisher Scientific, Waltham, USA, the same below) + 2.5 μl plasmid (1 ug / μl) + 4 μl Lipo8000 (Beyotime, Shanghai, China) reagent were mixed.

[0084] When the confluence of duck embryo fibroblasts reached about 60%, fresh culture medium was replaced; 125 μl of transfection reagent was added to each well of the experimental group, and 125 μl of serum-free culture medium was added to each well of the control group. After 8 hours of transfection, the supernatant was removed, and the cells were washed with PBS, and 2 mL of fresh culture medium was added to continue culture; 48 hours after transfection, normal (RPMI 1640 sugar-free culture medium (Procell, Wuhan, China) + 10% FBS + 5 mM D-glucose solution (Procell, Wuhan, China)) and high-glucose culture medium (RPMI 1640 sugar-free culture medium + 10% FBS + 25 mM D-glucose solution) were added and cultured, respectively. After 24 hours, the cells were collected and the SIK1 and IGF2 mRNA levels of duck embryo fibroblasts were detected by qPCR; protein levels were detected by Western Blot, and cell proliferation activity was detected by CCK8 colorimetry.

[0085] 1.4.2 siRNA synthesis and interference efficiency analysis

[0086] 1-si-SIK1, 2-si-SIK1, and 3-si-SIK1 siRNAs and a negative control siRNA (si-NC) were designed according to the duck SIK1 gene sequence (SEQ ID NO: XM_005026639.5) and synthesized by Huzhou Hippo Biotechnology Co., Ltd. The siRNA sequences are shown in Table 1.

[0087] Duck embryo fibroblasts in the logarithmic growth phase were taken and when the cells grew close to 50% to 60% confluence, siRNA transfection was performed according to the instructions of the Lipofectmine 3000 kit (Thermo Fisher Scientific, Waltham, USA, the same below). siRNA (si-NC, 1-si-SIK1, 2-si-SIK1 and 3-si-SIK1) and liposome Lipofectamine3000 were diluted with 2 ml of serum-free Opi-MEM medium, so that the final concentration of the four siRNAs was 100 nmol / L. Cells were collected 48 hours after transfection, and the SIK1 mRNA level was detected by qPCR to analyze the interference efficiency. 3-si-SIK1 had a higher interference efficiency ( Figure 1), used in cell transfection experiments, or as siRNA of SIK1 gene, involved in molecular breeding for duck meat and egg traits.

[0088] Table 1 Specific siRNA sequences

[0089]

[0090] 1.4.3 Analysis of pcDNA3.1-SIK1 overexpression vector efficiency

[0091] Duck embryo fibroblasts were cultured at 5×10 ^5 The cells were seeded into 6-well plates at a density of 100 cells / ml and incubated overnight at 37°C in a 5% CO2 incubator. When the confluence of duck embryo fibroblasts reached 70-80%, the cells were transfected with Lipofectamine TM 3000 cells were transfected with pcDNA3.1-SIK1 overexpression plasmid and pcDNA3.1 control plasmid respectively according to the instructions. Fresh complete culture medium was replaced after 8 hours. Cells were collected after 48 hours, and SIK1 mRNA levels were detected by qPCR to analyze the overexpression efficiency.

[0092] 1.4.4 Cell proliferation assay

[0093] To investigate the regulatory role of SIK1 in duck embryo fibroblast proliferation, SIK1 was overexpressed / interfered under normal and high-glucose culture conditions (specific transfection methods and grouping were the same as above). Six replicate wells were set up in each group, and the proliferation of duck embryo fibroblasts was detected using the CCK8 colorimetric assay. After the cell culture was completed, 10 μl of CCK8 reagent (Dojindo Chemical Research Institute, Japan) was added to each well, and the cells were incubated in an incubator for an additional 2-4 hours. The absorbance of each well was measured at 450 nm using a microplate reader (Molecular Devices, USA), and the values ​​were statistically analyzed and plotted using GraphPad Prism 8.0.

[0094] 1.4.5 Western Blot Analysis

[0095] Total protein was extracted using a total protein extraction kit (containing Protease Inhibitor Cocktail) (Thermo Pierce, USA), and then total protein was quantified using a BCA quantification kit (Biyuntian). Equal amounts of protein were separated by 10% sodium dodecyl sulfate-polyacrylamide gel electrophoresis (SDS-PAGE) (Bio-Rad) and electrotransferred to a PVDF membrane. After transfer, T-TBS (containing 5% BSA) was blocked at room temperature for 1 hour. SIK1 (Affinity, 1:500), IGF2 (Affinity, 1:500) and β-actin (Affinity, 1:10000) primary antibodies were incubated at 4°C overnight. Then, the cells were incubated with goat anti-mouse or goat anti-rabbit IgG (1:5000) at room temperature for 1 hour. Finally, enhanced chemiluminescence (ECL) kit ( Band visualization was performed using WestDura Extended Duration Substrate (Thermo Pierce). Immunoreactive bands were quantified using Image J software and normalized to β-actin signal.

[0096] 1.5 SIK1 tissue-specific expression

[0097] The heart, liver, spleen, lung, kidney, stomach, ovary, chest, skin and other tissues of Jinding duck were taken for qPCR detection of SIK1 gene. Duck embryo fibroblasts of each group were collected for qPCR detection of SIK1 gene and IGF2. Primers were designed by PrimerPremier software, and the annealing temperature is shown in Table 2. Total RNA of cells was extracted using a total RNA kit (Thermo Fisher, USA). RNA concentration was determined using a Nanodrop spectrophotometer (Thermo Fisher, USA). All samples were subjected to 3 physical replicates, using 2 -△△Ct Methods Data were processed. The reference gene was glyceraldehyde-3-phosphate dehydrogenase (GAPDH).

[0098] Table 2 Real-Time PCR primers and conditions

[0099]

[0100] 1.6 Statistical analysis

[0101] SPSS 19.0 software was used for statistical analysis. The results were expressed as mean ± standard deviation (SEM). The means between two groups were compared with the independent sample t test, and the means between multiple groups were compared with one-way ANOVA analysis. When P < 0.05 (*), the difference was considered significant, and when P < 0.01 (**), the difference was considered extremely significant.

[0102] This invention uses whole-genome resequencing technology for the first time to assemble the genome of Jinding duck, and compares it with the genomes of other duck species such as Beijing duck, to explore the key genes for the differentiation of duck meat and egg-laying traits, which will help the molecular breeding of ducks and provide new ideas for exploring the key genes for the differentiation of meat / eating duck traits in the future.

[0103] 2. Results

[0104] 2.1 Genome assembly and annotation

[0105] In Section 1.2 of this paper, we constructed the Jinding duck chromosome using nanopore and Hi-C technologies. Third-generation nanopore sequencing yielded 170.26 Gb of data. After quality control, the data volume was 155.14 Gb, with an average read length of 21.35 Kb. The genome sequence was 1.15 Gb, with a contig N50 of 13.17 Mb.

[0106] Hi-C analysis identified 31 chromosomes (29 autosomes and chromosomes Z and W) totaling 1.13 Gb, representing 98.06% of the total chromosome length. The sequence and orientation of the chromosomes were determined for a total of 1.11 Gb, accounting for 97.71% of the total chromosome length. A total of 141.72 Mb of repetitive sequences, 18,672 genes, 393 tRNAs, 97 rRNAs, 216 miRNAs, and 776 pseudogenes were predicted. 94.15% of the genes were annotated using the NR, GO, KOG, and KEGG databases.

[0107] Compared with previous studies (Peking duck genome: https: / / www.ncbi.nlm.nih.gov / genome / ?term= txi d8839 , Table 3). The present invention significantly improved assembly quality by combining multiple sequencing technologies, further enhancing the completeness of the Jinding duck genome and the precise assembly of highly complex regions. Conserved genomic elements in the genome are relatively intact, as measured by a BUSCO score of 95.28% (Table 4), compared to previous Pekin duck genome assemblies with BUSCO scores below 91%. The Jinding duck genome demonstrates significant improvements in continuity and completeness compared to the Pekin duck genome.

[0108] Table 3 Genome information: Peking and Jinding ducks

[0109]

[0110] Table 4 BUSCO evaluation results

[0111]

[0112] After Hi-C assembly and manual adjustment, the 1.13Gb genome sequence was mapped to 31 chromosomes, accounting for 98.06%, and the number of sequences was 400, accounting for 77.67% ( Figure 2 a) The total length of chromosome sequences with determined sequence and orientation is 1.11 Gb, accounting for 97.71% of the total chromosome sequence length. After error correction, the contig N50 and scaffold values ​​are 10.90 Mb and 76.08 Mb, respectively. The genome assembled at the chromosome level by Hi-C was digested into 100 Kb bins. Hi-C read pairs were then inserted between any two bins to signal the strength of the interaction between the two bins. A heatmap was then plotted as follows: Figure 1 As shown in b. It can be seen that the chromosomes are clearly divided into 31 groups; there are strong interactions between adjacent sequences near the diagonal of the chromosome, while the interaction signal intensity between adjacent sequences in the non-diagonal position is weak, which is consistent with the principle of Hi-C assisted genome assembly and proves that the genome assembly is effective ( Figure 2 b). The perfect match between the marker sequences in the radiation hybridization map indicates the accuracy and completeness of the assembly. The three genomes are collinear, indicating that the assembly structure is consistent ( Figure 2 c).

[0113] In Section 1.3 of this study, 13 Chinese native duck breeds—four wild ducks and 36 ducks (including Peking ducks)—were resequenced at an average depth of ×10. Principal component analysis (PCA) divided the samples into four groups: wild ducks, Muscovy ducks, meat ducks, and laying ducks. Adjacent native duck breeds (JD / SM / PT / LC(R)) clustered more closely, suggesting a closer genetic relationship and possible similar domestication history. Figure 3 a / b). Figure 3 (b) A phylogenetic tree of 119 duck species based on Bayesian clustering, with K values ​​ranging from 2 to 5. Branch colors represent species (same as in (a). With a K value of 4, four subgroups exist: FF (Muscovy duck), MDZ (Wild duck), MEAT (meat duck), and EGG (egg-laying duck).

[0114] 2.2 Screening of candidate differential regions (CDRs)

[0115] By comparing the genomes of laying ducks and meat ducks, we detected candidate differential regions (CDRs) on autosomes and searched for regions with extreme differences in allele frequency (FST) and maximum differences in genetic diversity (πlog ratio). We identified two CDRs (SIK1 and IGF2) that reached a significant level of P < 0.005 ( Figure 4 ).

[0116] IGF2 is related to individual growth rate, lean meat percentage and back fat thickness. IGF2 (insulin-like growth factor 2) is located on chromosome 5, and there are significant differences between laying ducks and meat ducks. IGF is the most complex and diverse growth factor known to date. IGF2 can promote cell mitosis and differentiation, participate in postpartum genome reconstruction, and play an important role in X chromosome inactivation. These functions all indicate that IGF2 plays an important role in growth and development. IGF2 is closely related to production performance such as individual growth rate, lean meat percentage, back fat thickness, etc., and has been used as a candidate gene in some species ( Figure 5 ).

[0117] During the analysis, we found a CDR gene located on chromosome 1, the SIK1 gene (salt-induced kinase 1), which encodes a serine / threonine protein kinase, which differs significantly between egg-laying ducks and meat ducks. It contains a ubiquitin-associated (UBA) domain-encoded protein and is a member of the adenosine monophosphate-activated protein kinase (AMPK) subfamily of kinases in the conserved signal transduction pathway. The SIK gene has not been reported in poultry, but it plays an important role in human cancer research, mouse insulin regulation, and the regulation of HepG2 cell lipid deposition. In particular, SIK1 can phosphorylate CRTC2 (cAMP-regulated transcriptional coactivator), inactivate CRTC2, and inhibit the expression of the gluconeogenesis rate-limiting enzyme gene downstream of CRTC2-CREB ( Figure 6 Abnormal gluconeogenesis leads to elevated hepatic glucose output and fasting blood glucose, which is closely related to metabolic diseases. Therefore, we speculate that SIK1 mutation may be one of the key factors in the differentiation of laying ducks from meat ducks.

[0118] The present invention conducted a tissue-specific expression experiment of SIK1 in Section 1.5. The results of SIK1 gene expression in different tissues of Jinding duck showed that SIK1 gene was expressed in all parts of the body, with the highest expression level in the lung and the lowest in the liver. There was no significant difference in other tissues ( Figure 7 We hypothesize that this phenomenon is related to the function of SIK1. SIK1 is primarily involved in gluconeogenesis and influences the regulation of intracellular lipid deposition. Under normal circumstances, the lungs are highly active, consuming glycogen at an accelerated rate, necessitating increased glycogen supply through reactions such as increased gluconeogenesis. The liver, on the other hand, is primarily involved in detoxification reactions and, under normal circumstances, does not require the consumption of large amounts of sugar, resulting in slightly lower SIK1 gene expression levels.

[0119] 2.3 Identification of SIK1 gene function

[0120] The function of SIK1 gene was verified in Section 1.4 of the present invention. CCK8 was detected in duck embryo fibroblasts after transfection with si-SIK1 and pcDNA3.1 SIK1 and high glucose culture. The results showed that:

[0121] Compared with the pure blank group (NC group), the OD450 value of the high glucose group increased, and the difference was statistically significant (P<0.01).

[0122] After silencing SIK1, the OD450 values ​​of the SiRNA-NC high glucose group, SiRNA-SIK1 OD450, and SiRNA-SIK1 high glucose group were significantly increased compared with those of the SiRNA-NC group (P<0.01).

[0123] After overexpression of SIK1, compared with the pcDNA3.1 group, the OD450 value of the pcDNA3.1 high-glucose group was upregulated, while the OD450 of the pcDNA3.1-SIK1 and pcDNA3.1-SIK1 high-glucose groups was significantly downregulated (P<0.01).

[0124] The results suggest that both high glucose culture and Si-SIK1 can induce cell proliferation, while pcDNA3.1-SIK1 can inhibit cell proliferation, and this inhibition cannot be relieved by high glucose culture. Figure 8 What I see.

[0125] 2.4 High glucose and SIK1 interference affect SIK1 and IGF2 expression

[0126] After transfection of si-SIK1 and pcDNA3.1 SIK1, duck embryo fibroblasts were cultured under high glucose conditions. The expression trends of SIK1 and IGF2 mRNA were similar, e.g. Figure 9 Compared with the blank group (NC group), the expression of SIK1 and IGF2 in the NC (25mM Glucose) group was significantly increased (P<0.01). Compared with the SiRNA-NC empty group, the expression levels of SIK1 and IGF2 in the SiRNA-NC (25mM Glucose) group were significantly increased (P<0.01). There was no significant change in SIK1 expression in the SiRNA-SIK1 group and the SiRNA-SIK1 (25mM Glucose) group (P>0.05). Compared with the pcDNA3.1 group, the expression of SIK1 and IGF2 in the pcDNA3.1 (25mM Glucose) group, the pcDNA3.1-SIK1 group, and the pcDNA3.1-SIK1 (25mM Glucose) group were all significantly increased (P<0.01). These results indicate that high glucose and overexpression of SIK1 can change the expression levels of SIK1 and IGF2 mRNA, but silencing SIK1 has no significant effect on the expression levels of SIK1 and IGF2 mRNA.

[0127] Western Blot results showed that ( Figure 10): Compared with the NC group, the expressions of SIK1 and IGF2 were upregulated in the NC (25mM Glucose) group (P<0.01); compared with the Si-NC group, the expressions of SIK1 and IGF2 were upregulated in the siRNA-NC (25mM Glucose) group (P<0.01); the expressions of SIK1 and IGF2 were downregulated in the siRNA-SIK1 group (P<0.01), and SIK1 expression was downregulated (P<0.01) while IGF2 expression was upregulated in the siRNA-SIK1 (25mM Glucose) group (P<0.05); compared with the pcDNA3.1 group, SIK1 and IGF2 were upregulated in pcDNA3.1 (25mM Glucose), pcDNA3.1-SIK1, and pcDNA3.1-SIK1 (25mM Glucose) (P<0.01 or P<0.05).

[0128] This study constructed a high-quality genome of the Jinding duck. The 1.13GB sequence was assembled onto 31 chromosomes (29 autosomes, Z and W chromosomes), and SNPs, indels, and structural variations were screened. These results are helpful for designing specific genomic selection programs. Over 25 million SNPs, indels, and structural variations associated with domestication were found in 13 wild / laying / meat ducks. These loci will provide a reference for studying the genetic differences between domestic / wild ducks and the differentiation of laying / meat ducks. When predicting gene mutation regions with potential high / moderate functional effects, we found that some mutation regions may contain key genes that affect the differentiation of laying and broiler ducks, such as the SIK1 and IGF2 genes, particularly the SIK1 gene. During the domestication process of laying and broiler ducks, egg production and fat deposition diverged. The role of duck SIK1 in regulating glucose metabolism and cell proliferation may play an important role in this process, and its mechanism of action in ducks requires further investigation.

[0129] The above description is only a preferred embodiment of the present invention. All equivalent changes and modifications made according to the scope of the patent application of the present invention should fall within the scope of the present invention.

Claims

1. Application of key genes for differentiation of duck meat and egg traits in molecular breeding for domestication of duck meat and egg traits, characterized by: The key gene is the duck SIK1 gene, and its nucleotide sequence is shown in SEQ ID NO:

1.

2. An siRNA targeting the key gene according to claim 1, characterized in that: The siRNA is 3-si-SIK1, the sense strand of which is 5'-GCUUCAGCAUCACCAGCUATT-3', and the antisense strand of which is 5'-UAGCUGGUGAUGCUGAAGCTT-3'.

3. The use of siRNA according to claim 2, wherein: The siRNA is used in molecular breeding for duck meat trait domestication.

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