A comparison of genomic selection methods for breeding value prediction
نویسندگان
چکیده
منابع مشابه
Genomic breeding value prediction: methods and procedures.
Animal breeding faces one of the most significant changes of the past decades - the implementation of genomic selection. Genomic selection uses dense marker maps to predict the breeding value of animals with reported accuracies that are up to 0.31 higher than those of pedigree indexes, without the need to phenotype the animals themselves, or close relatives thereof. The basic principle is that ...
متن کاملMultiple-trait genomic selection methods increase genetic value prediction accuracy.
Genetic correlations between quantitative traits measured in many breeding programs are pervasive. These correlations indicate that measurements of one trait carry information on other traits. Current single-trait (univariate) genomic selection does not take advantage of this information. Multivariate genomic selection on multiple traits could accomplish this but has been little explored and te...
متن کاملBreeding and Genetics: Genomic Selection Methods II
Computer mating programs have helped breeders minimize pedigree inbreeding and avoid recessive defects by mating animals with parents that have fewer common ancestors. With genomic selection, breed associations, AI organizations, and on-farm software providers could use new programs to minimize genomic inbreeding by comparing genotypes of potential mates. Relationships could be computed between...
متن کاملGenomic breeding value prediction and QTL mapping of QTLMAS2010 data using Bayesian Methods
BACKGROUND Bayesian methods allow prediction of genomic breeding values (GEBVs) using high-density single nucleotide polymorphisms (SNPs) covering the whole genome with effective shrinkage of SNP effects using appropriate priors. In this study we applied a modification of the well-known BayesA and BayesB methods to estimate the proportion of SNPs with zero effects (π) and a common variance for ...
متن کاملGenomic breeding value prediction and QTL mapping of QTLMAS2011 data using Bayesian and GBLUP methods
BACKGROUND The goal of this study was to apply Bayesian and GBLUP methods to predict genomic breeding values (GEBV), map QTL positions and explore the genetic architecture of the trait simulated for the 15th QTL-MAS workshop. METHODS Three methods with models considering dominance and epistasis inheritances were used to fit the data: (i) BayesB with a proportion π = 0.995 of SNPs assumed to h...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Science Bulletin
سال: 2015
ISSN: 2095-9273
DOI: 10.1007/s11434-015-0791-2