Literature DB >> 19700729

A relationship matrix including full pedigree and genomic information.

A Legarra1, I Aguilar, I Misztal.   

Abstract

Dense molecular markers are being used in genetic evaluation for parts of the population. This requires a two-step procedure where pseudo-data (for instance, daughter yield deviations) are computed from full records and pedigree data and later used for genomic evaluation. This results in bias and loss of information. One way to incorporate the genomic information into a full genetic evaluation is by modifying the numerator relationship matrix. A naive proposal is to substitute the relationships of genotyped animals with the genomic relationship matrix. However, this results in incoherencies because the genomic relationship matrix includes information on relationships among ancestors and descendants. In other words, using the pedigree-derived covariance between genotyped and ungenotyped individuals, with the pretense that genomic information does not exist, leads to inconsistencies. It is proposed to condition the genetic value of ungenotyped animals on the genetic value of genotyped animals via the selection index (e.g., pedigree information), and then use the genomic relationship matrix for the latter. This results in a joint distribution of genotyped and ungenotyped genetic values, with a pedigree-genomic relationship matrix H. In this matrix, genomic information is transmitted to the covariances among all ungenotyped individuals. The matrix is (semi)positive definite by construction, which is not the case for the naive approach. Numerical examples and alternative expressions are discussed. Matrix H is suitable for iteration on data algorithms that multiply a vector times a matrix, such as preconditioned conjugated gradients.

Mesh:

Year:  2009        PMID: 19700729     DOI: 10.3168/jds.2009-2061

Source DB:  PubMed          Journal:  J Dairy Sci        ISSN: 0022-0302            Impact factor:   4.034


  230 in total

1.  Modeling additive and non-additive effects in a hybrid population using genome-wide genotyping: prediction accuracy implications.

Authors:  J-M Bouvet; G Makouanzi; D Cros; Ph Vigneron
Journal:  Heredity (Edinb)       Date:  2015-09-02       Impact factor: 3.821

2.  Genome-wide association study for carcass quality traits and growth in purebred and crossbred pigs1.

Authors:  Matteo Bergamaschi; Christian Maltecca; Justin Fix; Clint Schwab; Francesco Tiezzi
Journal:  J Anim Sci       Date:  2020-01-01       Impact factor: 3.159

3.  Bayesian inference of genetic parameters based on conditional decompositions of multivariate normal distributions.

Authors:  Jon Hallander; Patrik Waldmann; Chunkao Wang; Mikko J Sillanpää
Journal:  Genetics       Date:  2010-03-29       Impact factor: 4.562

4.  Ancestral Relationships Using Metafounders: Finite Ancestral Populations and Across Population Relationships.

Authors:  Andres Legarra; Ole F Christensen; Zulma G Vitezica; Ignacio Aguilar; Ignacy Misztal
Journal:  Genetics       Date:  2015-04-14       Impact factor: 4.562

5.  A comparison of genomic selection models across time in interior spruce (Picea engelmannii × glauca) using unordered SNP imputation methods.

Authors:  B Ratcliffe; O G El-Dien; J Klápště; I Porth; C Chen; B Jaquish; Y A El-Kassaby
Journal:  Heredity (Edinb)       Date:  2015-07-01       Impact factor: 3.821

6.  Incorporating the single-step strategy into a random regression model to enhance genomic prediction of longitudinal traits.

Authors:  H Kang; L Zhou; R Mrode; Q Zhang; J-F Liu
Journal:  Heredity (Edinb)       Date:  2016-12-28       Impact factor: 3.821

7.  Genomic selection in American mink (Neovison vison) using a SSGBLUP model for size and quality traits graded on live mink.

Authors:  Trine M Villumsen; Guosheng Su; Bernt Guldbrandtsen; Torben Asp; Mogens S Lund
Journal:  J Anim Sci       Date:  2021-01-08       Impact factor: 3.159

8.  Genetic analysis of carcass and meat quality traits in Nelore cattle1.

Authors:  Daniel Gustavo M Gordo; Rafael Espigolan; Tiago Bresolin; Gerardo A Fernandes Júnior; Ana F B Magalhães; Camila U Braz; Willian Bruno Fernandes; Fernando Baldi; Lucia G Albuquerque
Journal:  J Anim Sci       Date:  2018-09-07       Impact factor: 3.159

9.  Effect of family relatedness on characteristics of estimated IBD probabilities in relation to precision of QTL estimates.

Authors:  Gertraude Freyer; Jules Hernández-Sánchez; Natascha Vukasinovic
Journal:  BMC Genet       Date:  2010-09-26       Impact factor: 2.797

10.  Genomic prediction when some animals are not genotyped.

Authors:  Ole F Christensen; Mogens S Lund
Journal:  Genet Sel Evol       Date:  2010-01-27       Impact factor: 4.297

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