scholarly journals Comparison of multiple-trait genetic evaluation accuracy using region marker relationships with traditional best linear unbiased prediction (BLUP)

2010 ◽  
Vol 9 (46) ◽  
pp. 7781-7787
Author(s):  
Mahboubeh ◽  
Rostami Angasi ◽  
Ardeshir ◽  
Nejati Javaremi ◽  
Hassan ◽  
...  
Keyword(s):  
Best Linear Unbiased Prediction ◽  
Genetic Evaluation ◽  
Multiple Trait ◽  
Linear Unbiased Prediction ◽  
Best Linear Unbiased ◽  
Evaluation Accuracy ◽  
Unbiased Prediction

An empirical check on best linear unbiased prediction genetic evaluation using pig field recording data

1997 ◽  
Vol 77 (2) ◽  
pp. 211-216 ◽  
Author(s):  
V. M. Quinton ◽  
C. Smith
Keyword(s):  
Large Body ◽  
Best Linear Unbiased Prediction ◽  
Genetic Evaluation ◽  
Linear Unbiased Prediction ◽  
Field Recording ◽  
Best Linear Unbiased ◽  
Simulation Results ◽  
Pig Performance ◽  
Computer Simulation Studies ◽  
Unbiased Prediction

The theory and use of best linear unbiased prediction in genetic evaluation are well developed. However, there has been little empirical checking of its efficacy in practice. The objective here was to use a large body of Canadian pig performance records to check on the predicted benefits of BLUP in genetic evaluation. Phenotype records were available on fat depth and on days to 100 kg on some 65 000 progeny born in 1994 and 1995 from parents evaluated before 1994. Rank correlations between parent and progeny in data were calculated within herd-year-season to avoid effects due to differences in these factors. Computer simulation studies were also run to check on the predicted results. The simulation results confirmed the expectations on the higher correlation of mid-parental EBV than of mid-parental phenotype with progeny genotype and a regression (of progeny phenotype on mid-parental EBV) of unity when all relevant pedigree and performance data were used. In the data analysis, the (rank) correlations with progeny phenotype were consistently higher (36 and 27%) for mid-parental BLUP genetic evaluation than for mid-parental phenotypes, confirming the superiority of the BLUP evaluations over phenotypes. However, the regression of progeny phenotype on mid-parent BLUP EBV was usually less than the predicted value of unity. Simulation results suggest that either the base population heritability was lower than that used in the evaluation or that the information used was incomplete. Key words: Best linear unbiased prediction, EBV, pigs, performance, selection

Genetic gains and levels of relatedness from best linear unbiased prediction selection of Eucalyptus urophylla for pulp production in southeastern China

2000 ◽  
Vol 30 (10) ◽  
pp. 1601-1607 ◽  
Author(s):  
Xianming Wei ◽  
Nuno MG Borralho
Keyword(s):  
Tree Height ◽  
Best Linear Unbiased Prediction ◽  
Eucalyptus Urophylla ◽  
Multiple Trait ◽  
Southeastern China ◽  
Linear Unbiased Prediction ◽  
Genetic Gains ◽  
Breeding Objectives ◽  
Best Linear Unbiased ◽  
Unbiased Prediction

Breeding values for diameter at breast height (DBH), tree height (HT), relative bark thickness (BKR), and pilodyn penetration (PP) in Eucalyptus urophylla St. Blake plantations were predicted with best linear unbiased prediction (BLUP) approach. These values along with their economic weights derived from a previous study were then used to estimate economic genetic gains for three breeding objectives (pulp, woodchips, and wood volume) in southeastern China. The results showed substantial gain can be expected from selecting top 5% trees, with a reduction of up to US$35 for producing a tonne of ovendry pulp. However, actual gains can be strongly influenced by how the breeding objectives have been defined and whether the key traits have been included in the selection criteria. This study also showed that problem in the increase of coancestry associated with selection on BLUP would not be serious, with average coancestry amongst the selected population was less than 1%. More importantly, an unrestricted multiple-trait BLUP selection did not result in the same increase in relatedness in the selected population than it does for the single trait situation.

Developments in genetic evaluation: from test days to genomics

2005 ◽  
Vol 2005 ◽  
pp. 237-237
Author(s):  
T. H. E. Meuwissen
Keyword(s):  
Best Linear Unbiased Prediction ◽  
Genetic Evaluation ◽  
Genomic Information ◽  
Linear Unbiased Prediction ◽  
The Past ◽  
The Future ◽  
Best Linear Unbiased ◽  
Genetic Evaluations ◽  
Direct Use ◽  
Unbiased Prediction

Genetic evaluations have come a long way during the past decades, where the development and implementation of Best Linear Unbiased Prediction (BLUP) was undoubtedly the most notable achievement. The most important advances during the past 10 years were probably the direct use of test-day data in the BLUP model, ie. test-day models, the correction for heterogeneous within herd variances, multiple across country genetic evaluations (MACE), and the inclusion of more and more functional, and often difficult, traits in the evaluations. This paper will review the developments in test-day models, and the future of the genetic evaluations field, namely the inclusion of genomic information in the evaluations.

Genetic Evaluation by Best Linear Unbiased Prediction Using Marker and Trait Information in a Multibreed Population

Genetics ◽  
1998 ◽  
Vol 148 (1) ◽  
pp. 507-515
Author(s):  
T Wang ◽  
R L Fernando ◽  
M Grossman
Keyword(s):  
Quantitative Trait Locus ◽  
Marker Locus ◽  
Best Linear Unbiased Prediction ◽  
Genetic Evaluation ◽  
Linear Unbiased Prediction ◽  
Gametic Disequilibrium ◽  
The Matrix ◽  
Best Linear Unbiased ◽  
Trait Locus ◽  
Unbiased Prediction

Abstract Genetic evaluation by best linear unbiased prediction (BLUP) requires modeling genetic means, variances, and covariances. This paper presents theory to model means, variances, and covariances in a multibreed population, given marker and breed information, in the presence of gametic disequilibrium between the marker locus (ML) and linked quantitative trait locus (MQTL). Theory and algorithms are presented to construct the matrix of conditional covariances between relatives (Gv) for the MQTL effects in a multibreed population and to obtain the inverse of Gv efficiently. Theory presented here accounts for heterogeneity of variances among pure breeds and for segregation variances between pure breeds. A numerical example was used to illustrate how the theory and algorithms can be used for genetic evaluation by BLUP using marker and trait information in a multibreed population.

scholarly journals Correction: Weighted Genomic Best Linear Unbiased Prediction for Carcass Traits in Hanwoo Cattle. Genes 2019, 10, 1019

Genes ◽  
2020 ◽  
Vol 11 (9) ◽  
pp. 1013
Author(s):  
Bryan Irvine Lopez ◽  
Seung-Hwan Lee ◽  
Jong-Eun Park ◽  
Dong-Hyun Shin ◽  
Jae-Don Oh ◽  
...  
Keyword(s):  
Carcass Traits ◽  
Best Linear Unbiased Prediction ◽  
Linear Unbiased Prediction ◽  
Best Linear Unbiased ◽  
Hanwoo Cattle ◽  
Unbiased Prediction

The authors wish to make the following corrections to this paper [...]

A method for reducing inbreeding with Best Linear Unbiased Prediction

1993 ◽  
Vol 1993 ◽  
pp. 33-33
Author(s):  
B Grundy ◽  
WG Hill
Keyword(s):  
Best Linear Unbiased Prediction ◽  
Breeding Value ◽  
Best Linear Unbiased Predictor ◽  
Linear Unbiased Prediction ◽  
Genetic Merit ◽  
Selection Decisions ◽  
Best Linear Unbiased ◽  
Estimated Breeding Value ◽  
Commercial Environment ◽  
Unbiased Prediction

An optimum way of selecting animals is through a prediction of their genetic merit (estimated breeding value, EBV), which can be achieved using a best linear unbiased predictor (BLUP) (Henderson, 1975). Selection decisions in a commercial environment, however, are rarely made solely on genetic merit but also on additional factors, an important example of which is to limit the accumulation of inbreeding. Comparison of rates of inbreeding under BLUP for a range of hentabilities highlights a trend of increasing inbreeding with decreasing heritability. It is therefore proposed that selection using a heritability which is artificially raised would yield lower rates of inbreeding than would otherwise be the case.

Sign in / Sign up

Export Citation Format

Share Document