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Whole genome association analysis algorithm based on parent genotypes and progeny phenotypes

A whole-genome, association analysis technology, applied in the field of bioinformatics, can solve the problems of large experiments and sequencing costs, consumption, etc., and achieve the effect of reducing manpower, material resources and time costs

Active Publication Date: 2021-12-14
INST OF AQUATIC LIFE ACAD SINICA
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  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

Generally, the larger the sample size, the higher the accuracy of the associated gene information obtained. In general, the number of experimental samples ranges from hundreds to tens of thousands, which requires a very large cost of experiments and sequencing

Method used

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  • Whole genome association analysis algorithm based on parent genotypes and progeny phenotypes
  • Whole genome association analysis algorithm based on parent genotypes and progeny phenotypes
  • Whole genome association analysis algorithm based on parent genotypes and progeny phenotypes

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Embodiment Construction

[0039]Next, the association analysis method based on parental genotype and offspring phenotype described in the present invention is described with grass carp sample data.

[0040] S1) Whole-genome resequencing was performed on the parent grass carp (15 females and 15 males) used for breeding in our laboratory in 2014. The sequencing platform was Illumina Xten with a sequencing depth of 20×.

[0041] S2) Obtain the offspring body weight data of the parents described in S1), and collect 1729 tail phenotype data (example: Table 1) of 190 parent pairs (some parent pairs did not collect valid offspring phenotype data):

[0042] Table 1: Body weight data of 1729 offspring (example)

[0043] sample number female parent male parent weight(g) A1681 F14 M12 109.16 B0039 F5 x9 119.01 A1693 F14 2 99.95 A2479 F8 M9 134.84 … … … … A1664 F14 M9 87.39

[0044] S3) Using BWA software to compare the whole genome resequencing data o...

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Abstract

The invention discloses a whole genome association analysis algorithm based on parent genotypes and progeny phenotypes, the algorithm comprises the following steps: acquiring parent genotypes, progeny phenotypes and progeny phenotype parent information of a group to be analyzed, and establishing a combined genotype matrix of progeny according to genotypes of parent pairs, obtaining possible genotype combination information of different progenies of each SNP site and corresponding progeny group grouping phenotype data, constructing a statistical model of a progeny combination genotype and a corresponding progeny phenotype for correlation analysis, and obtaining a correlation P value of the phenotype and each SNP site; then, distinguishing correlation types of the SNP sites, calculating whether conforming to additive or complete dominant effects or not, and screening candidate sites; obtaining the average distance of the strong correlation markers according to LD attenuation of the whole genome SNP markers for screening of a final marker set.

Description

technical field [0001] The invention belongs to the technical field of bioinformatics, specifically a genome-wide association analysis algorithm based on parental genotypes and offspring phenotypes. Background technique [0002] Gene sequences often contain sequence variations of different magnitudes (for example, human genes contain millions of sequence variations), that is, single nucleotide polymorphisms (SNPs). Traits have direct or indirect effects. Genome-Wide Association Studies (GWAS) refers to the use of SNPs in the genome as molecular genetic markers to detect the genetic markers of a large number of individuals in the genome-wide range, obtain genotypes, and then compare them with observable traits ( Phenotype) to conduct correlation analysis, screen out SNPs related to traits, and mine genetic variations that affect traits. [0003] The existing GWAS method analyzes the corresponding relationship between the genotype and phenotype of the same individual. In ord...

Claims

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Application Information

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IPC IPC(8): G16B20/30G16B20/20G16B20/50G16B30/20
CPCG16B20/30G16B20/20G16B20/50G16B30/20
Inventor 夏晓勤石米娟张婉婷程莹寅
Owner INST OF AQUATIC LIFE ACAD SINICA
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