CN117925861A - Structure variation marker based on ERBB4 gene and applied to Wenchang chicken breeding and detection method thereof - Google Patents

Structure variation marker based on ERBB4 gene and applied to Wenchang chicken breeding and detection method thereof Download PDF

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CN117925861A
CN117925861A CN202410330002.0A CN202410330002A CN117925861A CN 117925861 A CN117925861 A CN 117925861A CN 202410330002 A CN202410330002 A CN 202410330002A CN 117925861 A CN117925861 A CN 117925861A
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赵鹏举
彭宸
王争光
余东游
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Hainan Research Institute Of Zhejiang University
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Abstract

The invention discloses a structural variation marker based on an ERBB4 gene and applied to Wenchang chicken breeding and a detection method thereof, which relate to agricultural bioengineering, wherein the structural variation marker is positioned on the ERBB4 gene of chromosome chr7, the insertion site is 3538284, and the inserted structural variation sequence is SEQ ID No. 01; the invention obtains a structural variation marker sequence which is used as a molecular marker for Wenchang chicken breeding through detection and screening.

Description

Structure variation marker based on ERBB4 gene and applied to Wenchang chicken breeding and detection method thereof
Technical Field
The invention relates to the field of genetic engineering, in particular to a structural variation marker based on an ERBB4 gene and applied to Wenchang chicken breeding and a detection method thereof.
Background
Wenchang chicken is generally referred to as Hainan Wenchang chicken, which is a broiler variety originally produced from Hainan province in China, and has the characteristic of outstanding appearance to meat quality compared with other chicken varieties. A method is needed to be capable of screening by detecting variation and being applied to Wenchang chicken breeding as a molecular marker.
ERBB4 is a member of the Tyr protein kinase family and the epidermal growth factor receptor subfamily, and the encoded type I membrane proteins bind to and are activated by neuregulin and other factors, inducing a variety of cellular responses, including mitosis and differentiation. Regulate development of the heart, central nervous system, gene transcription, cell proliferation, differentiation, migration, and apoptosis in animals. Meanwhile ERBB4 was found to be one of the positively selected genes in the chicken genome, playing an important role in the regulation of embryonic and skeletal development.
The invention obtains a structural variation marker sequence which is used as a molecular marker for Wenchang chicken breeding through detection and screening, and can provide powerful reference for directional breeding of body weight in actual breeding work.
Disclosure of Invention
In order to solve the defects in the prior art, the invention aims to provide a structural variation marker based on an ERBB4 gene and applied to Wenchang chicken breeding and a detection method thereof.
In order to achieve the above object, the present invention adopts the following technical scheme:
The structure variation marker is positioned on the ERBB4 gene of chromosome chr7, the insertion site is 3538284, and the inserted structure variation sequence is SEQ ID No. 01.
The structural variation marker based on the ERBB4 gene and applied to Wenchang chicken breeding, wherein the weight of an individual inserted with the structural variation marker sequence is higher than that of an individual without the structural variation marker sequence.
The detection method based on ERBB4 gene and applied to the structural variation marker of Wenchang chicken breeding,
The method comprises the following steps:
step one, SV identification of second generation sequencing:
obtaining individual Illumina double-end sequencing data, calculating by combining multiple detection software with multiple SV detection algorithms, combining SVs obtained by each sample by using SURVIVOR software, filtering the combined SVs, and refining break points of the SVs according to the highest frequency positions of the SVs;
Step two, SV identification based on assembly:
using Pggb software to construct a universal genome variation map to detect structural variations based on assembly, the assembled genome comprising: newly assembled genome WChap and published assembled genomes; next, the SV of all autosomes and Z chromosomes on WChap were identified using the vg kit; the generated vcf file contains all 31 SVs that assemble the genome;
ERBB4 is located at Chr7:3090622-3581723 in the newly assembled genome WChap;
The position in the reference genome bGalGalGal1. Mat. Broiler. GRCg7b (GCF_ 016699485.2) is NC_052539.1 3133650-3625134;
The position in the reference genome bGalGalGal1.pat. Whiteleghornlayer.GRCg7w (GCF_ 016700215.2) is NC_052580.1 3074777-3566088;
Step three, constructing a flood genome map;
Using WChap1 as the backbone of the pangenome map, incorporating previously identified second-generation sequencing-based and assembly-based SVs into the pangenome variation map using the construction module of the vg kit without deleting any alternative alleles; then indexing the generated pan genome map; SV is depicted in the figure as a bubble, the path representing the corresponding allele; the path comprises a start node and a stop node of the reference sequence, and a path traversing the nodes;
Step four, SV genotyping based on the graph:
Genotyping 354 samples with high depth sequencing (> 10×) using the pan genome map; comparing CLEAN READS of each sample with the genome of the map to obtain a result file in a GAM format, and excluding comparison with comparison quality <5 or comparison with base quality < 5; then using "vg pack" to build an index; on the constructed flood genome map, "vg call" was used to generate SV genotyping results for 354 samples;
step five, the GWAS of the SV is screened to obtain a structural variation marker sequence which is used as a molecular marker and applied to Wenchang chicken breeding:
performing GWAS on the SV data set by using a linear mixed model, adjusting gender, relatives and group structures as auxiliary factors, calculating a relatives matrix by using SNP, and determining the group structures; determining a genome-wide significance threshold using the unified threshold; screening to obtain a structural variation marker sequence which is used as a molecular marker for Wenchang chicken breeding.
The detection method based on ERBB4 gene and applied to the structural variation marker of Wenchang chicken breeding,
The method for identifying the SV of the second generation sequencing specifically comprises the following steps: obtaining Illumina double-ended sequencing data of 354 individuals, obtaining Illumina double-ended sequencing data of the individuals, calculating by combining multiple SV detection algorithms through multiple detection software, and combining the SV obtained by each sample by using SURVIVOR software, wherein the parameters are as follows: 501 110 50; the combined SVs were then filtered using the following parameters: NA 50 100000 0-1; next, break points of SVs are refined according to their highest frequency locations;
the various SV detection algorithms are: read-pair (RP), split-Read (SR), READ DEPTH (RD) and Assemble (AS);
the various detection software is as follows: manta, delly, wham, smoove, dysgu and GRIDS.
The detection method of the structural variation marker based on the ERBB4 gene and applied to Wenchang chicken breeding comprises the following steps of identifying based on assembled SV:
In addition to the newly assembled genome WChap1, the published assembled genomes from 30 samples of NCBI were used to detect assembly-based structural variations by constructing a universal genome variation map; this step was done using Pggb software with parameters-p 95-s 10000-T20-poa-params 1,9,16,2,41,1; next, SV for all autosomes and Z chromosomes on WChap were identified using vg kit in deconstruct mode of default parameters; the vcf file generated contained SVs for all 31 assembled genomes.
The detection method of the structural variation marker based on the ERBB4 gene and applied to Wenchang chicken breeding comprises the following steps of:
Using WChap1 as the backbone of the pangenome map, incorporating previously identified second-generation sequencing-based and assembly-based SVs into the pangenome variation map using the construction module of the vg kit without deleting any alternative alleles; then, indexing the generated generic genome map in XG and GCSA formats by using 'vg index', and enabling 'L' parameters for the two formats; SV is depicted in the figure as a bubble, the path representing the corresponding allele; the paths include a start node and an end node of the reference sequence, and paths traversing the nodes.
The detection method of the structural variation marker based on the ERBB4 gene and applied to Wenchang chicken breeding comprises the following steps:
genotyping 354 samples with high depth sequencing (> 10×) using the pan genome map; comparing CLEAN READS of each sample with the genome of the map by using VG GIRAFFE to obtain a result file in a GAM format, and excluding comparison with comparison quality <5 or comparison with base quality < 5; then under default parameters, an index is built by using the 'vg pack'; on the constructed flood genome map, "vg call" was used to generate SV genotyping results for 354 samples, with parameters of-v-bias-mode-het-bias 2,4.
The method for detecting the structural variation marker based on the ERBB4 gene and applied to Wenchang chicken breeding comprises the following steps of selecting the GWAS of SV to obtain a structural variation marker sequence serving as a molecular marker and applied to Wenchang chicken breeding:
GWAS were performed on SV datasets using a linear hybrid model of GEMMA (v1.0.3) and adjusted for gender, relatives and population structure as cofactors. The affinity matrix was calculated using all SNPs in GEMMA and population structure was determined using the first 10 principal components. The genome-wide significance threshold was determined using a unified threshold of 0.05/n, where n represents the effective number of independent SVs and SNPs calculated using a genetic type I error calculator.
The application of the structural variation marker based on the ERBB4 gene and applied to Wenchang chicken breeding is applied to Wenchang chicken breeding as a molecular marker.
The invention has the advantages that:
The invention obtains a structural variation marker sequence which is used as a molecular marker for Wenchang chicken breeding through detection and screening;
the weight of the individuals inserted with the structure variation marker sequence of Wenchang chicken is higher than that of the individuals without the structure variation marker sequence.
Drawings
FIG. 1 shows the result of electrophoresis of the insertion verification of the structural variant marker sequence of the present invention.
Detailed Description
The invention is described in detail below with reference to the drawings and the specific embodiments.
The samples and their sources are shown in table 1:
TABLE 1
Total 354 individuals, with Wenchang chickens from 3 chicken farms.
Structural Variation (SV) detection procedure
1. SV identification for second generation sequencing
Illumina double-ended sequencing data were obtained for 354 individuals from which SV was detected using several algorithms: read-pair (RP), split-Read (SR), READ DEPTH (RD) and Assemble (AS). By using six detection software: manta, delly, wham, smoove, dysgu and GRIDS, and each software has at least two algorithms integrated, we combine multiple SV detection algorithms to maximize sensitivity. The SV obtained for each sample was combined using SURVIVOR software with the following parameters: 501 110 50. The combined SVs were then filtered using the following parameters: NA 50 100000 0-1. Next, their break points are refined according to the highest frequency locations of SVs.
2. SV identification based on assembly
In addition to the newly assembled genome WChap1, the published assembled genomes from 30 samples of NCBI were used to detect assembly-based structural variations by constructing a universal genome variation map. This was done using Pggb software with parameters-p 95-s 10000-T20-poa-params 1,9,16,2,41,1. Next, SV for all autosomes and Z chromosomes on WChap were identified using vg kit in deconstruct mode of default parameters. The vcf file generated contained SVs for all 31 assembled genomes.
3. Pan genome map construction
WChap1 as backbone of the flood genome map, previously identified second-generation sequencing-based and assembly-based SVs were incorporated into the flood genome variation map using the construction module of vg kit without deleting any alternative alleles. The generated generic genome map is then indexed in XG and GCSA formats using "vg index" and the "-L" parameters are enabled for both formats. SV is depicted in the figure as a bubble, with the path representing the corresponding allele. The paths include a start node and an end node of the reference sequence, and paths traversing the nodes.
4. Map-based SV genotyping
354 Samples with high depth sequencing (> 10×) were genotyped using the pan genome map. The CLEAN READS of each sample was aligned with the map genome using "VG GIRAFFE" to obtain a result file in GAM format, excluding alignments with either alignment quality <5 or base quality < 5. An index is then built using "vg pack" under default parameters. On the constructed flood genome map, "vg call" was used to generate SV genotyping results for 354 samples, with parameters of-v-bias-mode-het-bias 2,4.
5. GWAS of SV
GWAS were performed on SV datasets using a linear hybrid model of GEMMA (v1.0.3) and adjusted for gender, relatives and population structure as cofactors. The affinity matrix was calculated using all SNPs in GEMMA and population structure was determined using the first 10 principal components. The genome-wide significance threshold was determined using a unified threshold of 0.05/n, where n represents the effective number of independent SVs and SNPs calculated using a genetic type I error calculator.
6. Structural variant marker sequences
The structural variation marker sequence which is used as a molecular marker for Wenchang chicken breeding is obtained by screening, and as shown in table 2, the genotyping result shows that three genotypes are available: 0/0 (no insert), 0/1 (heterozygous insert), 1/1 (homozygous insert). Analysis results associated with the traits showed that the weight of the inserted individuals was significantly higher than that of the non-inserted individuals at the same week of age as shown in table 3.
TABLE 2
TABLE 3 Table 3
The gene frequencies of the structural mutation marker sequences in each chicken species and their week-old body weights (g) are shown in Table 4 below:
TABLE 4 Table 4
Structural variation marker sequence insertion experiment verification flow:
1. The length of the structural mutation marker sequence is 3888bp, so that a detection Primer is designed in the inserted sequence, and the target fragment is 913bp long and has specificity by using the Primer-BLAST function of NCBI (https:// www.ncbi.nlm.nih.gov/tools/Primer-BLAST/index. Cgilink_LOC= BlastHome).
Forward primer F is 5'-GTGCCATCTGCCTCCATTCT-3' SEQ ID No. 02;
the reverse primer R is 5'-TCTGGAACGCTTCCTGTCAC-3' SEQ ID No. 03;
2. The blood samples used were verified to be taken from Wenchang Longquan Wenchang chicken Co., ltd. Hainan, and the PCR reaction system was directly configured as shown in Table 5 using TIANGEN KG204-01 blood direct PCR kit:
TABLE 5
3. PCR reaction conditions: pre-denaturation at 95℃for 3 min, denaturation at 95℃for 15 sec, annealing at 54℃for 20 sec, extension at 72℃for 50 sec, denaturation to extension for 30 cycles, extension at 72℃for 5 min
4. Electrophoresis: ① Agarose gel of 1.0% was prepared: 1.00g agarose was dissolved in 100ml 1% TAE and 8. Mu. L SPARKRED fluorescent nucleic acid staining reagent was added. ② Mu.l of PCR amplification product was pipetted into the gel wells in sequence while 5. Mu. L DNA MAKER (D2000) was added as reference. ③ After electrophoresis at a constant voltage of 120V for 30 minutes, the sample was observed under an ultraviolet lamp and recorded by photographing.
5. The result of the electrophoresis is shown in FIG. 1,
A band at 913bp indicates insertion of a structurally mutated tag sequence, and no insertion of a non-structurally mutated tag sequence.
Gel wells from left to right, 17 week old body weight (g) is shown in table 6:
TABLE 6
From the above experiments, it can be seen that: at the same week of age, individuals with the inserted structural variation marker sequences had significantly higher body weight than individuals without the insertion.
The foregoing has shown and described the basic principles, principal features and advantages of the invention. It will be appreciated by persons skilled in the art that the above embodiments are not intended to limit the invention in any way, and that all technical solutions obtained by means of equivalent substitutions or equivalent transformations fall within the scope of the invention.

Claims (9)

1. The structural variation marker based on the ERBB4 gene and applied to Wenchang chicken breeding is characterized in that the structural variation marker is located on the ERBB4 gene on chromosome chr7, the insertion site is 3538284, and the inserted structural variation marker sequence is SEQ ID No. 01.
2. The structural variation marker based on ERBB4 gene and applied to Wenchang chicken breeding according to claim 1, wherein the weight of the individual inserted with the structural variation marker sequence is higher than that of the individual without the inserted structural variation marker sequence.
3. The method for detecting the structural variation marker based on the ERBB4 gene and applied to Wenchang chicken breeding according to claim 1, which is characterized by comprising the following steps:
step one, SV identification of second generation sequencing:
obtaining individual Illumina double-end sequencing data, calculating by combining multiple detection software with multiple SV detection algorithms, combining SVs obtained by each sample by using SURVIVOR software, filtering the combined SVs, and refining break points of the SVs according to the highest frequency positions of the SVs;
Step two, SV identification based on assembly:
using Pggb software to construct a universal genome variation map to detect structural variations based on assembly, the assembled genome comprising: newly assembled genome WChap and published assembled genomes; next, the SV of all autosomes and Z chromosomes on WChap were identified using the vg kit; the generated vcf file contains all 31 SVs that assemble the genome;
ERBB4 is located at Chr7:3090622-3581723 in the newly assembled genome WChap;
The position in the reference genome bGalGalGal1. Mat. Broiller. GRCg7bGCF_016699485.2 is NC_052539.1 3133650-3625134;
Nc_052580.1 3074777-3566088 at position bgagal 1.pat. whistelloronllayer, grcg7wgcf_ 016700215.2;
Step three, constructing a flood genome map:
Using WChap1 as the backbone of the pangenome map, incorporating previously identified second-generation sequencing-based and assembly-based SVs into the pangenome variation map using the construction module of the vg kit without deleting any alternative alleles; then indexing the generated pan genome map; SV is depicted in the figure as a bubble, the path representing the corresponding allele; the path comprises a start node and a stop node of the reference sequence, and a path traversing the nodes;
Step four, SV genotyping based on the graph:
Genotyping 354 samples with >10 x high depth sequencing using the pan genome map; comparing CLEAN READS of each sample with the genome of the map to obtain a result file in a GAM format, and excluding comparison with comparison quality <5 or comparison with base quality < 5; then using "vg pack" to build an index; on the constructed flood genome map, "vg call" was used to generate SV genotyping results for 354 samples;
step five, the GWAS of the SV is screened to obtain a structural variation marker sequence which is used as a molecular marker and applied to Wenchang chicken breeding:
performing GWAS on the SV data set by using a linear mixed model, adjusting gender, relatives and group structures as auxiliary factors, calculating a relatives matrix by using SNP, and determining the group structures; determining a genome-wide significance threshold using the unified threshold; screening to obtain a structural variation marker sequence which is used as a molecular marker for Wenchang chicken breeding.
4. The method for detecting structural mutation markers based on ERBB4 gene and applied to Wenchang chicken breeding according to claim 3, wherein the step one, the SV identification of the second generation sequencing: obtaining Illumina double-ended sequencing data of 354 individuals, obtaining Illumina double-ended sequencing data of the individuals, calculating by combining multiple SV detection algorithms through multiple detection software, and combining the SV obtained by each sample by using SURVIVOR software, wherein the parameters are as follows: 501 110 50; the combined SVs were then filtered using the following parameters: NA 50 100000 0-1; next, break points of SVs are refined according to their highest frequency locations;
the multiple SV detection algorithms are: read-pair, split-Read, READ DEPTH and Assembly;
The plurality of detection software comprises: manta, delly, wham, smoove, dysgu and GRIDS.
5. The method for detecting structural variation markers based on ERBB4 gene and applied to Wenchang chicken breeding according to claim 3, wherein the method is characterized by comprising the following steps:
In addition to the newly assembled genome WChap1, the published assembled genomes from 30 samples of NCBI were used to detect assembly-based structural variations by constructing a universal genome variation map; this step was done using Pggb software with parameters-p 95-s 10000-T20-poa-params 1,9,16,2,41,1; next, SV for all autosomes and Z chromosomes on WChap were identified using vg kit in deconstruct mode of default parameters; the vcf file generated contained SVs for all 31 assembled genomes.
6. The method for detecting structural variation markers based on ERBB4 gene and applied to Wenchang chicken breeding according to claim 3, wherein the third step is to construct a flood genome map:
Using WChap1 as the backbone of the pangenome map, incorporating previously identified second-generation sequencing-based and assembly-based SVs into the pangenome variation map using the construction module of the vg kit without deleting any alternative alleles; then, indexing the generated generic genome map in XG and GCSA formats by using 'vg index', and enabling 'L' parameters for the two formats; SV is depicted in the figure as a bubble, the path representing the corresponding allele; the paths include a start node and an end node of the reference sequence, and paths traversing the nodes.
7. The method for detecting structural variation markers based on ERBB4 gene and applied to Wenchang chicken breeding according to claim 3, wherein the method is characterized by comprising the following steps:
Genotyping 354 samples with >10 x high depth sequencing using the pan genome map; comparing CLEAN READS of each sample with the genome of the map by using VG GIRAFFE to obtain a result file in a GAM format, and excluding comparison with comparison quality <5 or comparison with base quality < 5; then under default parameters, an index is built by using the 'vg pack'; on the constructed flood genome map, "vg call" was used to generate SV genotyping results for 354 samples, with parameters of-v-bias-mode-het-bias 2,4.
8. The method for detecting structural variation marker based on ERBB4 gene and applied to Wenchang chicken breeding according to claim 3, wherein step five, the GWAS of SV is screened to obtain a structural variation marker sequence which is used as a molecular marker and applied to Wenchang chicken breeding:
GWAS performed on SV dataset using linear hybrid model gemma96v1.0.3 and adjusting gender, relatives and population structure as cofactors; calculating a relationship matrix using all SNPs in GEMMA, and determining a population structure using the first 10 principal components; the genome-wide significance threshold was determined using a unified threshold of 0.05/n, where n represents the effective number of independent SVs and SNPs calculated using a genetic type I error calculator.
9. The application of the structural mutation marker based on the ERBB4 gene and applied to Wenchang chicken breeding according to claim 1, wherein the structural mutation marker is screened by detecting mutation and is applied to Wenchang chicken breeding as a molecular marker.
CN202410330002.0A 2024-03-22 2024-03-22 Structure variation marker based on ERBB4 gene and applied to Wenchang chicken breeding and detection method thereof Withdrawn CN117925861A (en)

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Cited By (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN118360415A (en) * 2024-06-17 2024-07-19 浙江大学海南研究院 Structure variation marker based on ERBB4 gene and applied to Wenchang chicken breeding and detection method thereof
CN118360415B (en) * 2024-06-17 2024-10-18 浙江大学海南研究院 Structure variation marker based on ERBB4 gene and applied to Wenchang chicken breeding and detection method thereof

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