A phasing and imputation method for pedigreed populations that results in a single-stage genomic evaluation

Title
A phasing and imputation method for pedigreed populations that results in a single-stage genomic evaluation
Publication Date
2012
Author(s)
Hickey, John
Kinghorn, Brian
Tier, Bruce
Van Der Werf, Julius H
( author )
OrcID: https://orcid.org/0000-0003-2512-1696
Email: jvanderw@une.edu.au
UNE Id une-id:jvanderw
Cleveland, Matthew A
Type of document
Journal Article
Language
en
Entity Type
Publication
Publisher
BioMed Central Ltd
Place of publication
United Kingdom
DOI
10.1186/1297-9686-44-9
UNE publication id
une:12734
Abstract
Background: Efficient, robust, and accurate genotype imputation algorithms make large-scale application of genomic selection cost effective. An algorithm that imputes alleles or allele probabilities for all animals in the pedigree and for all genotyped single nucleotide polymorphisms (SNP) provides a framework to combine all pedigree, genomic, and phenotypic information into a single-stage genomic evaluation. Methods: An algorithm was developed for imputation of genotypes in pedigreed populations that allows imputation for completely ungenotyped animals and for low-density genotyped animals, accommodates a wide variety of pedigree structures for genotyped animals, imputes unmapped SNP, and works for large datasets. The method involves simple phasing rules, long-range phasing and haplotype library imputation and segregation analysis. Results: Imputation accuracy was high and computational cost was feasible for datasets with pedigrees of up to 25 000 animals. The resulting single-stage genomic evaluation increased the accuracy of estimated genomic breeding values compared to a scenario in which phenotypes on relatives that were not genotyped were ignored. Conclusions: The developed imputation algorithm and software and the resulting single-stage genomic evaluation method provide powerful new ways to exploit imputation and to obtain more accurate genetic evaluations.
Link
Citation
Genetics Selection Evolution, v.44, p. 1-11
ISSN
1297-9686
0999-193X
Start page
1
End page
11

Files:

NameSizeformatDescriptionLink