Efficient high-accuracy whole-genome selection method capable of performing parallel operation

Abstract

The invention relates to the technical field of animal and plant breeding and human disease prediction, and provides an efficient high-accuracy whole-genome selection method capable of performing parallel operation. The method comprises the following steps: firstly, reading an original genotype file and a phenotype file, constructing a new genotype file and a new phenotype file, and calculating agenetic relationship matrix of all individuals; then, extracting all individuals in the new phenotypic file as a reference group, and extracting all individuals without phenotypic data in the originalgenotypic file as a prediction group; carrying out whole genome association analysis by utilizing the reference group data, and extracting result characteristics of the whole genome association analysis; constructing a model library with specific characters, sequentially optimizing an optimal fixed effect and an optimal random effect by adopting a cross validation strategy, and selecting an optimal prediction model from the model library; and finally, calculating genome estimated breeding values of the prediction group by utilizing the optimal prediction model. The method can quickly, accurately and stably predict individual genome breeding values, and thus the accuracy and efficiency of whole genome selection are improved.

Description

technical field [0001] The invention relates to the technical fields of animal and plant breeding and human disease prediction, in particular to an efficient, parallel-computable and highly accurate genome-wide selection method. Background technique [0002] With the development of high-density single nucleotide polymorphism (SNP) genotyping technology covering the whole genome, genome-wide selection (prediction), as a powerful tool for statistical analysis of genome, is widely used in the identification of complex traits in plant and animal breeding. Genetic value (species value) prediction and assessment, and in human genetics research. [0003] The existing genome-wide selection methods are divided into two categories: one is the direct method represented by the genome-wide best linear unbiased prediction GBLUP (Genomicbest linearunbiasedprediction), which only needs to construct the genome-wide relationship matrix between individuals, and obtain the variance components. ...

AI Technical Summary

Problems solved by technology

Among them, the direct method has high calculation efficiency, but due to its simple assumptions on the genetic construction of traits, the accuracy of the estimated breeding value is poor; the indirect method has relatively complex assumptions on the genetic construction of traits, which is more in line with the genetic mechanism of traits, and has better prediction Accuracy, but because its assumption introduces many unknown parameters, the parameter solving process is extremely complicated and the calculation efficiency is poor, which limits the application of the indirect method in actual prediction

Images