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Application Research for Soybean Genomics Selection by Comparing Bayesian B and Other Methods(PDF)

《大豆科学》[ISSN:1000-9841/CN:23-1227/S]

Issue:
2018年03期
Page:
535-358
Research Field:
Publishing date:

Info

Title:
Application Research for Soybean Genomics Selection by Comparing Bayesian B and Other Methods
Author(s):
TANG You1;  ZHENG Ping2;  WANG Jia-bo3;  ZHANG Ji-cheng2
(1.Electrical and Information Engineering College,Jilin Agricultural Science and Technology University, Jilin 132101, China; 2.College of Electrical and Information,Northeast Agricultural University, Harbin 150030, China; 3.Institute of Animal Husbandry,Heilongjiang Academy of Agricultural Sciences, Harbin 150086, China)
Keywords:
Bayesian B;  Genomic selection;  Cross validation;  Selection and breeding
PACS:
-
DOI:
10.11861/j.issn.1000-9841.2018.03.0353
Abstract:
In order to improve the breeding efficiency, different heritability and effective loci were set up by the genotype data and corresponding real characters of two groups of soybean to simulate the accuracy of different characters,statistical methods were used to simulate different characters to predict precise values. Cross validation repeated hundreds of times to stabilize the prediction value, compare and analyze Bayesian B and several common methods of genomic selection. The results showd that the Bayesian B method was better and more stable, indicating that the Bayesian B method had obvious advantages in the selection of soybean whole genome, which could be used in soybean breeding. At the same time, the application of Bayesian B method was introduced to guide the soybean breeding.

References:

［1］孙恺，孙健，舒小丽，等. 高异黄酮大豆突变体的筛选及其特性初步研究［J］. 核农学报,2016,30(11):2088-2095.(Sun K，Sun J，Shu X L，et al. Screening and characterization of a high isoflavone soybean mutant［J］. Journal of Nuclear Agriculture, 2016, 30 (11):2088-2095.)

［2］薛永国，魏崃，唐晓飞，等. 黑龙江省育成大豆品种性状演变的分析［J］. 大豆科学,2015,34(3):361-366.(Xue Y G，W L，Tang X F，et al. Analysis of the character evolution of soybean cultivars bred in Heilongjiang province ［J］. Soybean Science, 2015,34(3): 361-366.)
［3］穰中文，周清明. 水稻Dirigent基因家族生物信息学分析［J］. 湖南农业大学学报(自然科学版),2013,39(2):111-120.(Guo Q，Zhou Q M. Bioinformatics analysis of rice DIRIGENT gene family ［J］. Journal of Hunan Agricultural University (Natural Science Edition), 2013,39(2): 111-120.)
［4］周永正. 一般混合线性模型固定效应、随机效应与另一随机向量的联合估计［J］. 数学的实践与认识,2011(19):58-64.(Zhou Y Z. Joint estimation of fixed effects, random effects and another random vector in general mixed linear models［J］. Practice and Cognition of Mathematics,2011(19): 58-64.)
［5］Habier D，Fernando R L，Garrick D J. Genomic BLUP decoded: A look into the black box of genomic prediction ［J］. Genetics, 2013,194:597-607.?
［6］Wang C L，Qin Z，Li J，et al. Comparative study of estimation methods for genomic breeding values［J］. Science Bulletin,2016,61(5):353-356.
［7］Meuwissen T H，Hayes B J，Goddard M E. Prediction of total genetic value using genome-wide dense marker maps［J］. Genetics, 2001, 157(4): 1819-1829.
［8］Li B，Yu L X，Xi J J，et al. A widely applicable method for plant genomic DNA extraction［J］. Agricultural Biotechnology,2012,12(1):143-186.
［9］王欣，杨泽峰，徐辰武.基于育种值预测的基因组选择方法的比较［J］. Science Bulletin,2015,60(10):925-935，983.(Wang X，Yang Z F，Xu C W. Comparison of genomic selection methods based on prediction of breeding value ［J］. Science Bulletin, 2015,60 (10): 925-935，983.)
［10］Tang Y，Liu X L，Wang J B，et al. GAPIT Version 2: An enhanced integrated tool for genomic association and prediction［J］. Plant Genome,2016,9(2):1-9.?
［11］Anna W，Jesus A，Petek S，et al. Garrick.Mixture models detect large effect QTL better than GBLUP and result in more accurate and persistent predictions［J］. Journal of Animal Science and Biotechnology,2016,7(4):468-473.
［12］Pan X P，Zhang G Z，Zhang J J，et al. Zoeppritz-based AVO inversion using an improved Markov chain Monte Carlo method［J］. Petroleum Science,2017,14(1):75-83.
［13］王艳，韩英鹏，李文滨. 大豆分子标记研究新进展［J］. 大豆科学,2015,34(1):148-154，162.(Wang Y, Han Y P, Li W B. New progress in the research of soybean molecular markers ［J］. Soybean Science, 2015,34(1):148-154，162.)

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Last Update: 2018-06-07