A molecular marker and detection method for identifying goose egg-laying performance

Abstract

The present invention discloses a molecular marker and a detection method for identifying goose egg-laying performance, and relates to the technical field of molecular biology. The molecular marker provided by the present invention has a nucleotide sequence as shown in SEQ ID NO.3. The present invention also provides primers for amplifying the molecular marker, and the nucleotide sequence is shown in SEQ ID NO.1 and SEQ ID NO.2. The geese genomic DNA is amplified by the molecular marker primers. When the sequence shown in SEQ ID NO.3 can be amplified, it indicates that the goose has high egg-laying performance; when the sequence cannot be amplified, it indicates that the goose does not have high egg-laying performance. The molecular marker and molecular marker primer provided by the present invention can efficiently and accurately identify geese with high egg-laying performance, have significant application value in goose breeding, and can be particularly used for the identification and screening of geese with high egg-laying performance, providing a reliable reference for goose breeding.

Description

Technical Field

[0001] The invention relates to the technical field of molecular biology, and in particular to a molecular marker and a detection method for identifying goose egg-laying performance. Background Art

[0002] Like most economic traits, the breeding method for goose egg production is mainly conventional breeding, that is, breeding measures based on phenotypic selection. At present, individual cage breeding of geese has not yet been fully popular. The selection of geese egg production is mainly based on the entire family of captives as the selection unit, and the decision to keep or remove individuals is only based on the size of the family's average egg production. This has led to slow progress in improving the egg production of geese using conventional breeding.

[0003] In recent years, with the change of feeding methods and the development of artificial insemination technology, the egg production and pedigree records of individual geese have been realized. These developments allow breeders to estimate breeding values ​​by regressing the phenotypic values ​​of individuals, siblings, parents and offspring on breeding values, and conduct conventional breeding based on this. However, since egg production traits are also affected by random environmental factors such as nutrition, environment, and disease, these factors are obstacles to further improving goose egg production based on phenotypic breeding.

[0004] Since the 21st century, whole genome sequencing technology has enhanced people's understanding of various economic traits of livestock and poultry, and whole genome selection technology has been applied and effective in the selection of poultry egg production. Breeders usually integrate the significant sites of functional genes of important economic traits based on whole genome resequencing of different poultry, and develop poultry commercial breeding chips for genomic selection breeding. Generally speaking, genomic selection requires calculating the effect of markers in a reference population through known phenotypes and genotypes of candidate marker sites; then, the genomic breeding value of the candidate population with known phenotypes and genotypes is estimated based on the estimated effects. Therefore, it is necessary to develop a molecular marker for identifying and screening goose egg-laying performance, and use molecular biology to achieve efficient and accurate identification of high-egg-producing geese, providing a reliable reference for goose breeding. Summary of the invention

[0005] The purpose of the present invention is to provide a molecular marker and a detection method for identifying goose egg-laying performance. The molecular marker provided by the present invention has a nucleotide sequence as shown in SEQ ID NO.3. The present invention also provides primers for amplifying the molecular marker, and the nucleotide sequence is shown in SEQ ID NO.1 and SEQ ID NO.2. The geese genomic DNA is amplified by the molecular marker primers, and whether the goose has high egg-laying performance can be identified according to the sequence of the amplified product. The molecular marker and molecular marker primer provided by the present invention can efficiently and accurately identify geese with high egg-laying performance, have significant application value in goose breeding, and can be particularly used for the identification and screening of geese with high egg-laying performance, providing a reliable reference for goose breeding.

[0006] In order to achieve the above object, the present invention provides a molecular marker for identifying the egg-laying performance of geese, the nucleotide sequence of the molecular marker is shown in SEQ ID NO.3; the molecular marker is located on chromosome 3 of the goose, wherein the reference genome of the goose is PRJNA813978.

[0007] The present invention also provides a primer for amplifying the above molecular marker, and the nucleotide sequence of the primer is shown as SEQ ID NO.1 and SEQ ID NO.2.

[0008] The molecular marker for identifying the egg-laying performance of geese provided by the present invention can be used in goose breeding, and can be particularly used for the identification and screening of geese with high egg-laying performance.

[0009] The present invention also provides a method for detecting goose egg-laying performance, comprising the following steps:

[0010] S1: Extract genomic DNA from the goose to be tested;

[0011] S2: Using the goose genomic DNA extracted from S1 as a template, PCR amplification was performed using primers with nucleotide sequences as shown in SEQ ID NO.1 and SEQ ID NO.2;

[0012] S3: The product amplified in S2 is sequenced and identified. When the nucleotide sequence of the amplified product is as shown in SEQ ID NO.3, it indicates that the identified goose has high egg-laying performance; when the nucleotide sequence of the amplified product is different from SEQ ID NO.3, it indicates that the identified goose does not have high egg-laying performance.

[0013] Furthermore, in the above detection method, the PCR amplification in S2 is specifically as follows:

[0014] The PCR amplification reaction system was 25 μL: 1 μL of each 10 μM primer, 1 μL of DNA template, 12.5 μL of 2× Rapid Taq MasterMix, and 9.5 μL of ddH2O;

[0015] PCR amplification reaction program: 95°C for 3 min; 95°C for 15 sec, 60°C for 15 sec, 72°C for 27 sec, 35 cycles; 72°C for 5 min.

[0016] The detection method provided by the invention can be used in goose breeding, and in particular can be used for identification and screening of geese with high egg-laying performance.

[0017] The molecular marker and detection method for identifying goose egg-laying performance of the present invention fills the gap in molecular biological identification and screening of goose egg-laying performance, and has the following advantages:

[0018] The present invention uses the provided primers to perform PCR amplification on the geese's genome DNA to be tested, and can determine whether the goose to be tested has high egg-laying performance based on the amplification result. The result can be determined by the presence or absence of the amplification product or the specific sequence. This method can efficiently and accurately identify geese with high egg-laying performance, has significant application value in goose breeding, and can be particularly used for the identification and screening of geese with high egg-laying performance, providing a reliable reference for goose breeding. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] Figure 1 This is a schematic diagram of the results of using two different methods to take the intersection of screening candidate genes in the present invention.

[0020] Figure 2 For the different varieties of geese in the present invention, Indel chr3:54429172 Statistical results of the proportion of mutations at the sites.

[0021] Figure 3 The above are the statistical results of the expression of ESR1 gene in different genotypes in goose ovary matrix in the present invention. DETAILED DESCRIPTION

[0022] The technical solutions in the embodiments of the present invention are described clearly and completely below. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of them. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0023] Note: All the experimental methods and materials not specifically described in this embodiment are conventional experimental methods and materials commonly used in experiments.

[0024] Example

[0025] In the birthplaces of multiple local breeds, wild swan geese and geese of four high-yield breeds and nine low-yield breeds (a total of 91 individuals) were collected, as shown in Table 1 below. Blood or tissues of each goose were collected and placed in liquid nitrogen, and then transferred to a -80°C refrigerator for storage.

[0026] Table 1 Sources and basic information of blood or tissue samples collected in the present invention

[0027]

[0028]

[0029] Genomic DNA was extracted from blood or tissue of each species using the DNeasy blood and tissue kit. The quality of DNA was assessed using an Agilent 2200 TapeStation, Qubit 2.0 fluorometer, and agarose gel electrophoresis. According to the manufacturer's instructions, a double-end library with an insert size of 350 bp was constructed using the TruSeq library construction kit and sequenced on the Illumina NovaSeq 6000 platform. The raw reads obtained by sequencing were first tested using FastQC software. According to the quality of the raw data, the raw sequencing data was quality controlled using the NGS QC Toolkit to remove residual primer and adapter sequences, and each sequencing read with a base sequencing quality of less than 70% and above 20 was also removed. The quality-controlled data was then tested using FastQC software. Subsequently, the quality-controlled data was aligned to the Sichuan White Goose Reference Genome (version number: PRJNA813978) using the 'bwa-k 40-M-R' parameters of the BWA-MEM software. The obtained SAM file was converted into BAM format using SAMtools software, and unmapped and non-uniquely mapped reads were filtered. The acquisition of variation information was carried out according to the best practice workflow recommended by GATK (v4.1.7.0) software. The present invention obtained a total of 2,831,184,184,200bp of raw data, with an average sequencing depth of 21.69× for each sample and an average alignment rate of 98.92%. These data had 98.22% and 95.19% data coverage of 1× and 4× of the genome, respectively. Through data analysis, a total of 12,633,596 SNP sites were obtained, located in the variation on the exons, of which 853,494 were synonymous mutation types, 589,820 were non-synonymous mutation types, 7,963 were premature translation termination types, 3,660 were unknown types, and 797 were termination codon deletion types. In addition, 1,288,558 indels were obtained, including 543,034 insertions and 745,524 deletions.

[0030] In order to detect genomic regions with significant characteristics of selective sweep, VCFtools software was used to calculate the genetic differentiation index (FST) and nucleotide diversity difference (log2θπ(swan goose θπ / domestic goose θπ)) in a 40kb sliding window and move in steps of 20kb across the entire genome. Considering that the selected genomic regions have a low level of genetic variation, the top 5% regions with the highest allele frequency differentiation and the top 5% regions with the highest nucleotide diversity difference were selected as candidate selective sweep regions, and the genes located in or near these regions were selected as candidate genes. Compared with swan geese, the high-yielding goose breed had 1376 and 30 regions with FST values ​​in the TOP5% and were subject to positive and negative selection, respectively, and the low-yielding goose breed had 1418 and 17 regions, respectively. One of these regions was subject to opposite selection in high and low egg production, located in an incompletely assembled fragment, and no gene was annotated. Among them, 536 and 11 regions were subject to positive and negative selection in high and low egg production geese, respectively, and 219 genes were annotated. There were 881 and 6 regions that were positively or negatively selected only in low-yielding goose breeds, respectively, and 317 genes were annotated. There were 840 and 18 regions that were positively or negatively selected only in high-yielding goose breeds, respectively, and 416 genes were annotated.

[0031] Genome-wide association studies (GWAS) were performed using the mixed linear model (MLM) procedure implemented in the genome-wide efficient mixed-model association (GEMMA) software. GWAS analyses were performed using identified SNPs (MAF ≥ 0.05, missingness ≤ 0.1, sequencing depth ≥ 4) and indels (MAF ≥ 0.05, missingness ≤ 0.3, sequencing depth ≥ 4) in all wild and domestic goose populations examined. The MLM procedure adopted the statistical model 'Y = Xα + Sβ + Kμ + e', where Y represents phenotype, X represents genotype, S is the structure matrix, K is the relative kinship matrix, α and β represent fixed effects, Kμ is the random effect, and e is the normally distributed residual. The first two principal component analysis eigenvectors obtained from these SNPs or indels were used to construct the population structure-corrected S matrix, and the simple matching coefficient matrix was used to construct the K matrix. Manhattan plots and QQ plots of the GWAS results were visualized using the qqman package in R software. P<0.05 / N+1 and P<1 / N+1 were set as the thresholds for significant and potential association with the trait, respectively, and the variant information was annotated to the gene name. The estimated number of independent markers was used for Bonferroni correction based on linkage disequilibrium correction, reaching a 5% genome-wide significant level (P<5.15 e-9) were annotated to the relevant region of the BPIFC gene. The estimated number of independent markers was used to perform a Bonferroni correction based on linkage disequilibrium correction, reaching a 5% genome-wide significant level (<6.74 e-8 ) are shown in Table 2 below, annotated to BPIFC, RTCB, SYNE1 and ESR1 genes.

[0032] Table 2 Loci and their annotations that are significantly associated with differences in egg production among different breeds

[0033]

[0034]

[0035] Indel downstream of ESR1 gene chr3:54429172 The genotype of the locus was correlated with the egg-laying performance of geese. The schematic diagram of the results of using two different methods to take the intersection to screen candidate genes is shown in the figure. Figure 1 As shown in the figure, only the ESR1 gene was screened out by both methods. The most significant marker in the ESR1 gene is the site Indel located downstream of the gene. chr3:54429172 , this site (Indel chr3:54429172 ) is a deletion of 2bp after 54429172bp on chromosome 3. The proportion of mutations at this site in different breeds of geese was statistically analyzed, and the results are as follows Figure 2 As shown in the figure, it can be seen that this site has almost no mutation in high-laying goose breeds, while the mutation rate of this site is higher in low-laying goose breeds (2bp deletion occurs). At the same time, the expression level of ESR1 gene in goose ovary matrix of different genotypes was further studied, and the statistical results of its expression level are shown in Figure 3 As shown, it can be seen that the homozygous mutation of this site will significantly change the expression level of the ESR1 gene in the goose ovary matrix.

[0036] According to the mutation site of the above marker, molecular marker primers F and R that can specifically identify the site information by PCR amplification were developed, and the specific sequences are shown below. The egg-laying performance of geese was identified by the primers (F and R), and PCR amplification was performed using goose genomic DNA as a template. When the nucleotide sequence of the amplified product is as shown in SEQ ID NO.3, it indicates that the identified goose has high egg-laying performance; when the nucleotide sequence of the amplified product is different from SEQ ID NO.3, it indicates that the identified goose does not have high egg-laying performance. At the same time, the fragment of the nucleotide sequence as shown in SEQ ID NO.3 can be used as a molecular marker. By identifying the presence or absence of the molecular marker, it can be used to identify whether the goose to be tested has high egg-laying performance. It has significant application value in goose breeding, and can be especially used for the identification and screening of geese with high egg-laying performance. In the sequence of the molecular marker (SEQ ID NO.3), the 2bp in bold and underlined is a mutation site. When the 2bp of the site in the gene is missing, it means that the goose tested does not have high egg-laying performance.

[0037] The specific primers are (5'→3'):

[0038] F(SEQ ID NO.1):AGGAAAAGAAAGATGACCCAA;

[0039] R(SEQ ID NO.2): TGAGATGAAAGGACAGCGT;

[0040] Molecular marker (SEQ ID NO.3):

[0041]

[0042]

[0043] Blood or tissues were collected from Sichuan white geese with individual egg-laying records for DNA extraction. The extracted DNA was used as a template, and PCR amplification was performed using the primers developed above according to the PCR amplification system shown in Table 3 and the PCR amplification program shown in Table 4. The genotype was then sequenced and the genotype was determined. The genotype was used to conduct an association analysis on the egg-laying situation of the Sichuan white goose population, and the site was identified in combination with PCR amplification. Goose breeds that did not undergo mutations were selected for breeding statistics, and it was found that the selected goose breeds could increase the egg production by 3.5 eggs at 365 days of age, and the egg-laying frequency at 365 days of age was significantly increased by 0.08, as shown in Table 5 below.

[0044] Table 3 PCR amplification reaction system

[0045]

[0046]

[0047] Table 4 PCR amplification reaction program

[0048]

[0049] Table 5 The effect of using this marker to select Sichuan white geese

[0050]

[0051] In summary, the molecular markers, molecular marker primers and detection methods provided by the present invention can efficiently and accurately identify whether the identified goose has high egg-laying performance, and have significant application value in goose breeding, especially for the identification and screening of high egg-laying performance geese, providing a reliable reference for goose breeding.

[0052] Although the content of the present invention has been described in detail through the above preferred embodiments, it should be appreciated that the above description should not be considered as a limitation of the present invention. After reading the above content, it will be apparent to those skilled in the art that various modifications and substitutions of the present invention will occur. Therefore, the protection scope of the present invention should be limited by the appended claims.

Claims

1. A method for detecting goose egg-laying performance, characterized in that: The following steps are included: S1: Extract genomic DNA from the goose to be tested; S2: Using the goose genomic DNA extracted from S1 as a template, PCR amplification was performed using primers with nucleotide sequences as shown in SEQ ID NO.1 and SEQ ID NO.2; S3: The product amplified in S2 is sequenced and identified. When the nucleotide sequence of the amplified product is as shown in SEQ ID NO.3, it indicates that the identified goose has the high egg-laying performance at 365 days of age; when the nucleotide sequence of the amplified product is different from SEQ ID NO.3, it indicates that the identified goose does not have the high egg-laying performance at 365 days of age.

2. The detection method according to claim 1, characterized in that: The PCR amplification in S2 is specifically described as follows: The PCR amplification reaction system was 25 µL: 1 µL of each 10 µM primer, 1 µL of DNA template, 12.5 µL of 2× Rapid Taq Master Mix, and 9.5 µL of ddH2O; PCR amplification reaction program: 95℃ 3min; 95℃ 15sec, 60℃ 15sec, 72℃ 27sec, 35 cycles; 72℃ 5min.

3. Application of the detection method as described in any one of claims 1-2 in the identification and screening of 365-day-old high-laying performance geese.

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