CN114171122A - Breeding method of pinctada martensii improved variety with growth characters based on whole genome selection - Google Patents
Breeding method of pinctada martensii improved variety with growth characters based on whole genome selection Download PDFInfo
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Abstract
The invention discloses a method for breeding improved Pinctada martensii growth traits based on whole genome selection, which comprises the steps of selecting a reference population by measuring phenotype; obtaining SNP locus information in the whole genome range by using a sequencing technology; estimating the effect value of SNP by using three methods of rrBLUP, BayesA and BayesB, and analyzing the accuracy; and then estimating the GEBV of each individual in the reference population. The method can select the pinctada martensii at an early stage, shorten the culture period, reduce the investment, increase the accuracy of character selection and reduce the factors of environmental influence. The GEBV obtained by the method can be used as a standard for breeding improved varieties of growth traits, an effective molecular breeding method is provided for breeding excellent varieties of pinctada martensii with excellent growth traits, the culture yield and the quality of the pinctada martensii are improved, and the green and healthy development of the pinctada martensii culture industry is promoted.
Description
Technical Field
The invention belongs to the technical field of aquatic product genetic breeding, and particularly relates to a method for breeding improved Pinctada martensii growth traits based on whole genome selection.
Background
Pinctada fucata martensii is a main shellfish for cultivating seawater nucleated pearls in China. In the stage of continuous descending of the yield of seawater pearls in China, the cultivation of excellent varieties is one of effective ways for solving the industrial problems. The combination of the traditional breeding method and the genotyping technology can improve the accuracy and precision of character selection, and more importantly, greatly shortens the breeding time, thus becoming the mainstream direction of current breeding. The cultivation of new species suitable for local sea area cultivation improves the growth and pearl-breeding characters of cultivation groups, which is the primary task for solving the industrial dilemma. At present, various research units utilize the traditional breeding technology to cultivate new cultured species of Pinctada martensii of Haiyou No. 1, Nanke No. 1, Nanzhen No. 1 and Haiyang No. 1.
Despite major advances in traditional breeding of Pinctada martensii, most are based on selection for phenotypic traits. The phenotypic character is determined by the gene and the environment, and the environment interference often influences the selection effect and reduces the accuracy of selection. By referring to crop and livestock breeding technology, the development of molecular marker assisted breeding technology is of great significance for improving the accuracy of target characters and accelerating the breeding process. The growth traits of the pinctada martensii belong to quantitative traits and are controlled by multiple genes, so that more markers or marker information of a whole genome is required for analysis. At present, for growth character marker assisted breeding, methods such as QTL positioning and association analysis, candidate gene association analysis and the like are mostly adopted to discover economic character related genes and molecular markers. Whole genome selective breeding is a method for estimating the breeding value of an individual by combining phenotypic information with genomic marker information, because the method uses markers covering the whole genome, and generally, the higher the marker density, the more accurate the breeding value estimation. The advantages of genome selection are that the estimation accuracy is higher, the early selection can be carried out, the selection time is shortened, and the breeding cost is saved.
At present, aiming at the selection of the growth traits of pinctada martensii, a growth trait QTL map is preliminarily constructed, and a batch of genes and SNP sites related to the growth traits are excavated, but a method for selecting by utilizing the marker information of a genome range is not reported.
Disclosure of Invention
The invention aims to provide a method for efficiently and accurately breeding improved Pinctada martensii seeds with growth characteristics.
The technical scheme adopted by the invention is as follows:
the invention provides a method for breeding improved Pinctada martensii growth traits based on whole genome selection, which is characterized by comprising the following steps:
s1: and (3) performing Pinctada martensii phenotype determination and establishing a reference population: selecting a reference population by determining phenotype;
s2: re-sequencing the whole genome of a reference population, collecting and analyzing genotypes: performing resequencing on pinctada martensii individuals by using a genome resequencing technology to obtain SNP locus information in a whole genome range;
s3: optimal genome selection method evaluation: estimating the effect value of SNP by using three methods of rrBLUP, BayesA and BayesB according to the phenotypic value of the reference population and the SNP locus information, and analyzing the accuracy of the 3 methods according to the correlation and regression coefficient of the breeding value and the phenotypic value;
s4: estimated breeding value GEBV: the highest accuracy genome selection method identified in S3 is used to estimate the GEBV of each individual in the breeding population or other populations.
In some embodiments of the invention, the phenotype of step S1 includes shell length, shell width, shell height, total weight, and shell weight.
In some embodiments of the present invention, the SNP sites are SNP sites with ultra-high density within the whole genome obtained using a genome re-sequencing method.
In some embodiments of the invention, the sequencing depth is at least 10 x.
In some preferred embodiments of the invention, the sequencing depth is greater than 10 x.
In some embodiments of the present invention, the specific steps of step S2 are: extracting sample genome DNA, and detecting the quality and concentration of the DNA sample. And randomly breaking the DNA sample qualified for detection, purifying, connecting a sequencing joint, preparing cluster, and sequencing to obtain sequencing original data. In order to ensure the quality of sequencing data, the quality of original data is controlled by analyzing the base composition and the quality distribution before information analysis, and then the raw data (raw data) is filtered by utilizing SOAPnukel software to obtain effective data (clean data). After quality control and data filtering are carried out on sequencing original data, BWA comparison is applied to compare clean data to a reference genome. The alignment results were counted, pre-processed (sorted, de-duplicated, ID added, etc.) using Samtools, Reseqtols and Picard-tools. Then, SNP information is detected by using unified Genotyper of GATK. And then filtering the sites with polymorphism between the detected genotype and the reference sequence based on all SNP information of the sample obtained after comparison to obtain a SNP data set with high reliability for calculating genome selection.
In a second aspect of the invention, there is provided a genomic estimated breeding value obtained by the method of the first aspect of the invention.
In a third aspect of the invention there is provided the use of a genomically estimated breeding value according to the second aspect of the invention in identifying or assisting in identifying a growth trait.
In a fourth aspect of the invention, the application of the genome estimated breeding value in the second aspect of the invention in breeding of excellent Pinctada martensii variety is provided.
In a fifth aspect of the invention, there is provided use of the genomically estimated breeding values of the second aspect of the invention in assisted breeding.
According to a sixth aspect of the invention, there is provided the use of the genomically estimated breeding values according to the second aspect of the invention in germplasm resource improvement of pinctada martensii.
In a seventh aspect of the present invention, there is provided a method for breeding improved pinctada martensii species, wherein the genome of the second aspect of the present invention is used to estimate the breeding value as a standard for selection.
The invention has the beneficial effects that:
the invention provides a method for quickly and accurately estimating the growth character genome of pinctada martensii and estimating the breeding value. The method utilizes the genome re-sequencing technology to identify the SNP sites in the genome range, the density of the SNP sites is high, the accuracy is high, and the accuracy of genome selection prediction can be greatly improved. The method can select the pinctada martensii at an early stage, shorten the culture period, reduce the investment, increase the accuracy of character selection and reduce the factors of environmental influence.
The genome estimated breeding value GEBV obtained by the method can be used as a standard for breeding improved varieties of growth traits, and an effective molecular breeding method is provided for breeding excellent varieties of Pinctada martensii with excellent growth traits; the method can accelerate the cultivation of excellent Pinctada martensii variety with growth character, improve the growth character of Pinctada martensii, improve the cultivation yield and quality of Pinctada martensii, and promote the green and healthy development of Pinctada martensii cultivation industry.
Drawings
FIG. 1 shows the distribution of SNPs on chromosomes.
Detailed Description
The concept and technical effects of the present invention will be clearly and completely described below in conjunction with the embodiments to fully understand the objects, features and effects of the present invention. It is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all embodiments, and those skilled in the art can obtain other embodiments without inventive effort based on the embodiments of the present invention, and all embodiments are within the protection scope of the present invention.
Example 1
1. Pinctada martensii phenotype determination and reference population establishment
The new variety of pinctada martensii 'Hai selection No. 1' and the golden yellow shell color breeding population are selected as research materials, and the growth traits including shell length, shell width, shell height, total weight and shell weight traits are measured (Table 1).
TABLE 1 statistical analysis of phenotypic traits
| Traits | Mean. + -. standard deviation (mm) |
| Length of shell | 65.71±6.95 |
| Width of shell | 24.36±1.87 |
| Height of shell | 67.32±6.2 |
| Total weight of | 44.52±8.91 |
| Shell weight | 20.12±3.85 |
2. Reference population whole genome re-sequencing, genotype collection and analysis processing
Genomic DNA extraction and library sequencing were performed on the reference population.
Extracting genome DNA: extracting genomic DNA by using a marine animal tissue genomic DNA extraction kit of TIANGEN, and specifically comprises the following steps:
(1) 0.05g of adductor muscle was placed in an autoclaved 1.5mL centrifuge tube containing 200. mu.L of GA buffer;
(2) shearing muscle tissue, adding 4 μ L ribonuclease A (100mg/mL) solution, shaking for 15 s, and standing at room temperature for 5 min;
(3) adding 20 μ L protease K (20mg/mL) solution, mixing, centrifuging briefly, standing at 56 deg.C for 3h, shaking the mixed sample for 2-3 times per hour, and mixing for 15 s each time;
(4) adding 200 μ L buffer solution, fully reversing, mixing, standing at 70 deg.C for 10min, and centrifuging briefly;
(5) adding 200 μ L of anhydrous ethanol, fully reversing, mixing, and centrifuging briefly;
(6) adding the solution and flocculent precipitate obtained in the previous step into an adsorption column (the adsorption column is placed into a collecting pipe), centrifuging at 12,000rpm/min for 30 s, pouring off waste liquid, and placing the adsorption column back into the collecting pipe;
(7) adding 500 μ L buffer solution into adsorption column, centrifuging at 12,000rpm/min for 30 s, pouring off waste liquid, and placing adsorption column into collection tube;
(8) adding 600 μ L of rinsing liquid into adsorption column, centrifuging at 12,000rpm/min for 30 s, pouring off waste liquid, and placing adsorption column into collecting tube;
(9) repeating the operation step (7);
(10) placing the adsorption column back into the collection tube, centrifuging at 12,000rpm/min for 2min, pouring off waste liquid, and standing the adsorption column at room temperature for 10 min;
(11) transferring the adsorption column into a clean centrifuge tube, suspending and dropwise adding 100 μ L of elution buffer solution to the middle part of the adsorption membrane, standing at room temperature for 5min, centrifuging at 12,000rpm/min for 2min, and collecting the solution into the centrifuge tube.
Library construction and sequencing:
and carrying out ultrahigh-density SNP locus identification on the pinctada martensii by using a genome re-sequencing method (the sequencing depth is more than 10 x). Randomly breaking a DNA sample qualified for detection by using an ultrasonic high-performance sample processing system Covaris, connecting a sequencing joint after purification, preparing cluster by bridge PCR, and sequencing by using an Illumina HiSeqTM 2000 platform to obtain sequencing original data.
In order to ensure the quality of sequencing data, the quality of original data is controlled by analyzing the base composition and the quality distribution before information analysis, and then the raw data (raw data) is filtered by utilizing SOAPnukel software to obtain effective data (clean data). After quality control and data filtering are carried out on sequencing original data, BWA comparison is applied to compare clean data to a reference genome. The sequencing depth distribution of the reference genomic bases and the coverage of each chromosomal region were statistically analyzed.
The alignment results were counted, pre-processed (sorted, de-duplicated, ID added, etc.) using Samtools, Reseqtols and Picard-tools. SNP information was then detected using the unified Genotyper of GATK (FIG. 1). Then, based on all SNP information of the sample obtained after the comparison, the sites with polymorphism between the detected genotype and the reference sequence are filtered, and a SNP data set with high reliability is obtained for subsequent genome selection analysis (Table 2).
TABLE 2 Pinctada martensii 2.57M SNP marker information Table
| Chromosome numbering | Number of SNP markers | Chromosome numbering | Number of SNP markers |
| Chromosome 1 | 312993 | Chromosome 9 | 172418 |
| Chromosome 2 | 314028 | |
155988 |
| Chromosome 3 | 247828 | Chromosome 11 | 117490 |
| Chromosome 4 | 205609 | Chromosome 12 | 117029 |
| Chromosome 5 | 202282 | |
92911 |
| Chromosome 6 | 179484 | Chromosome 14 | 137646 |
| Chromosome 7 | 187543 | Chromosome 15 | 1868 |
| |
126710 |
3. Optimal genome selection method evaluation
And (3) estimating the effect value of the SNP by using three methods, namely rrBLUP, BayesA and BayesB according to the SNP data set and the phenotypic value of the reference group. And (3) dividing the reference group into a training set and a verification set by using the phenotypic values obtained in the step (1) and the SNP data set obtained in the step (2) for 10 times of cross validation (the ratio of the training set to the verification set is about 6:4), calculating breeding values by using three methods respectively, and analyzing the accuracy of the 3 methods according to the correlation between the breeding values and the phenotypic values and regression coefficients, wherein the specific result is shown in a table 3.
TABLE 3 accuracy of rrBLUB, BayesA and BayesB predictions
Note: r _ TBV _ GEBV: the correlation coefficient between GEBV and the phenotypic value (TBV), representing its accuracy, its square is called reliability; b _ TBV _ GEBV: and the regression coefficient of TBV to GEBV represents unbiasedness, and if b TBV _ GEBV is 1, unbiasedness is indicated, otherwise, unbiasedness is indicated.
By comparison, the direct correlation coefficients of the breeding value and the phenotypic value obtained by the rrBLUP method are both greater than those obtained by the BayesA and BayesB methods, so that the rrBLUP method is finally selected to calculate the estimated genome breeding value GEBV.
The selection of the genome selection method to replace phenotype selection is to estimate the breeding value by utilizing SNP sites in the whole genome range, so that the accuracy of selection can be greatly improved.
The SNP identification method in the step 2 is selected, so that the density and the accuracy of SNP loci can be greatly improved, and the accuracy of genome selective breeding value estimation can be improved.
And (3) selecting the method with the highest prediction accuracy determined in the step (3) to estimate the breeding value of each individual in the breeding population, so that references can be provided for seed reservation and breeding scheme customization according to the breeding value of the individual.
The method with the highest prediction accuracy obtained in the step 3 is selected, the breeding value is estimated, the seed reservation is realized, the early seed selection can be realized, the breeding period is shortened, and the breeding cost is saved.
In conclusion, the invention provides a method for quickly and accurately estimating the growth trait genome estimated breeding value GEBV of Pinctada martensii. The genome estimated breeding value GEBV obtained by the method can be used as a standard for breeding improved varieties of growth traits, and an effective molecular breeding method is provided for breeding excellent varieties of Pinctada martensii with excellent growth traits; the method can accelerate the cultivation of excellent Pinctada martensii variety with growth character, improve the growth character of Pinctada martensii, and promote the green and healthy development of Pinctada martensii cultivation industry.
The present invention is not limited to the above embodiments, and various changes can be made without departing from the spirit of the present invention within the knowledge of those skilled in the art. Furthermore, the embodiments of the present invention and the features of the embodiments may be combined with each other without conflict.
Claims (10)
1. The method for breeding the improved Pinctada martensii variety with the growth character based on the whole genome selection is characterized by comprising the following steps of:
s1: and (3) performing Pinctada martensii phenotype determination and establishing a reference population: selecting a reference population by determining phenotype;
s2: re-sequencing the whole genome of a reference population, collecting and analyzing genotypes: performing resequencing on pinctada martensii individuals by using a genome resequencing technology to obtain SNP locus information in a whole genome range;
s3: optimal genome selection method evaluation: estimating the effect value of SNP by using three methods of rrBLUP, BayesA and BayesB according to the phenotypic value of the reference population and the SNP locus information, and analyzing the accuracy of the 3 methods according to the correlation and regression coefficient of the breeding value and the phenotypic value;
s4: estimated breeding value GEBV: the GEBV of each individual in the breeding population or other population is estimated using the most accurate genome selection method identified in S3.
2. The breeding method according to claim 1, wherein the phenotypes of step S1 include shell length, shell width, shell height, total weight and shell weight.
3. The method according to claim 1, wherein the SNP sites are SNP sites with an ultra-high density within the whole genome obtained by the genome re-sequencing method in step S2.
4. The method of claim 3, wherein the sequencing depth is at least 10 x.
5. A genomic estimated breeding value obtained by the method according to any one of claims 1 to 4.
6. Use of the method of any one of claims 1 to 4 or the genomically estimated breeding value of claim 5 in identifying or assisting in identifying a growth trait.
7. Use of the method according to any one of claims 1 to 4 or the genomically estimated breeding value according to claim 5 for breeding of a pinctada martensii elite variety.
8. Use of the method of any one of claims 1 to 4 or the genomically estimated breeding value of claim 5 in assisted breeding.
9. Use of the method of any one of claims 1 to 4 or the genomically estimated breeding value of claim 5 for germplasm improvement of pinctada martensii.
10. A method for breeding improved Veronica martensii seeds, wherein the genome-estimated breeding value of claim 5 is used as a standard for selection.
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| Title |
|---|
| 郝瑞娟: "基于全基因组关联分析解析马氏珠母贝生长和矿化性 状关键基因", 《中国博士学位论文全文数据库（电子期刊）农业科技辑》》, no. 2, 15 February 2021 (2021-02-15), pages 10 * |
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