Prediction of genomic breeding values of carcass traits using whole genome SNP data in Hanwoo (Korean cattle)

It is widely known that the environment influences phenotypic expression and that its effects must be accounted for in genetic evaluation programs. The most used method to account for environmental effects is to add herd and contemporary group to the model. Although generally informative, the herd effect treats different farms as independent units. However, if two farms are located physically close to each other, they potentially share correlated environmental factors. We introduce a method to model herd effects that uses the physical distances between farms based on the Global Positioning System (GPS) coordinates as a proxy for the correlation matrix of these effects that aims to account for similarities and differences between farms due to environmental factors. A population of Hanwoo Korean cattle was used to evaluate the impact of modelling herd effects as correlated, in comparison to assuming the farms as completely independent units, on the variance components and genomic prediction. The main result was an increase in the reliabilities of the predicted genomic breeding values compared to reliabilities obtained with traditional models (across four traits evaluated, reliabilities of prediction presented increases that ranged from 0.05 ± 0.01 to 0.33 ± 0.03), suggesting that these models may overestimate heritabilities. Although little to no significant gain was obtained in phenotypic prediction, the increased reliability of the predicted genomic breeding values is of practical relevance for genetic evaluation programs.

Download Full-text

Accuracy of genomic selection using stochastic search variable selection in Australian Holstein Friesian dairy cattle

Genetics Research ◽

10.1017/s0016672309990243 ◽

2009 ◽

Vol 91 (5) ◽

pp. 307-311 ◽

Cited By ~ 93

Author(s):

KLARA L. VERBYLA ◽

BEN J. HAYES ◽

PHILIP J. BOWMAN ◽

MICHAEL E. GODDARD

Keyword(s):

Variable Selection ◽

Genomic Selection ◽

Critical Issue ◽

Stochastic Search ◽

Selection Strategy ◽

Genomic Breeding ◽

Breeding Values ◽

Stochastic Search Variable Selection ◽

Snp Data ◽

Search Variable

SummaryGenomic selection describes a selection strategy based on genomic breeding values predicted from dense single nucleotide polymorphism (SNP) data. Multiple methods have been proposed but the critical issue is how to decide whether an SNP should be included in the predictive set to estimate breeding values. One major disadvantage of the traditional Bayes B approach is its high computational demands caused by the changing dimensionality of the models. The use of stochastic search variable selection (SSVS) retains the same assumptions about the distribution of SNP effects as Bayes B, while maintaining constant dimensionality. When Bayesian SSVS was used to predict genomic breeding values for real dairy data over a range of traits it produced accuracies higher or equivalent to other genomic selection methods with significantly decreased computational and time demands than Bayes B.

Download Full-text

Comparison of dimensionality reduction methods to predict genomic breeding values for carcass traits in pigs

Genetics and Molecular Research ◽

10.4238/2015.october.9.10 ◽

2015 ◽

Vol 14 (4) ◽

pp. 12217-12227 ◽

Cited By ~ 3

Author(s):

C.F. Azevedo ◽

M. Nascimento ◽

F.F. Silva ◽

M.D.V. Resende ◽

P.S. Lopes ◽

...

Keyword(s):

Dimensionality Reduction ◽

Carcass Traits ◽

Genomic Breeding ◽

Breeding Values ◽

Reduction Methods

Download Full-text

PSXIV-37 Accuracies of genomic breeding values for growth and carcass traits in Brangus beef cattle using K-means clustering for cross-validation.

Journal of Animal Science ◽

10.1093/jas/sky404.310 ◽

2018 ◽

Vol 96 (suppl_3) ◽

pp. 142-142

Author(s):

S Peters ◽

M Sinecen ◽

K Kizilkaya ◽

M Yildiz ◽

D Garrick ◽

...

Keyword(s):

Beef Cattle ◽

Cross Validation ◽

Carcass Traits ◽

Genomic Breeding ◽

Breeding Values

Download Full-text

Accuracy of predicting genomic breeding values for residual feed intake in Angus and Charolais beef cattle

Journal of Animal Science ◽

10.2527/jas.2012-5715 ◽

2013 ◽

Author(s):

L. Chen ◽

F. Schenkel ◽

M. Vinsky ◽

D. H. Crews ◽

C. Li

Keyword(s):

Beef Cattle ◽

Feed Intake ◽

Residual Feed Intake ◽

Genomic Breeding ◽

Breeding Values

Download Full-text

Association between polymorphisms of Myf5 and POU1F1 genes with growth and carcass traits in Hanwoo (Korean cattle)

Genes & Genomics ◽

10.1007/s13258-011-0006-4 ◽

2011 ◽

Vol 33 (4) ◽

pp. 425-430 ◽

Cited By ~ 10

Author(s):

Jiyeon Seong ◽

Jae Don Oh ◽

Il Cheong Cheong ◽

Kun Woo Lee ◽

Hak Kyo Lee ◽

...

Keyword(s):

Carcass Traits ◽

Korean Cattle

Download Full-text

Genotype imputation from various low-density SNP panels and its impact on accuracy of genomic breeding values in pigs

animal ◽

10.1017/s175173111800085x ◽

2018 ◽

Vol 12 (11) ◽

pp. 2235-2245 ◽

Cited By ~ 1

Author(s):

D.A. Grossi ◽

L.F. Brito ◽

M. Jafarikia ◽

F.S. Schenkel ◽

Z. Feng

Keyword(s):

Genotype Imputation ◽

Low Density ◽

Genomic Breeding ◽

Breeding Values ◽

Snp Panels

Download Full-text

Genomic Breeding Values for Claw Diseases/Disorders in Czech Holstein Cows

Acta Universitatis Agriculturae et Silviculturae Mendelianae Brunensis ◽

10.11118/actaun201967051245 ◽

2019 ◽

Vol 67 (5) ◽

pp. 1245-1251

Author(s):

Ludmila Zavadilová ◽

Eva Kašná ◽

Zuzana Krupová

Keyword(s):

Infectious Diseases ◽

Fixed Effects ◽

Genetic Correlations ◽

Genetic Effect ◽

Holstein Cows ◽

Additive Genetic Effect ◽

Genomic Information ◽

White Line ◽

Genomic Breeding ◽

Breeding Values

Genomic breeding values (GEBV) were predicted for claw diseases/disorders in Holstein cows. The data sets included 6,498, 6,641 and 16,208 cows for the three groups of analysed disorders. The analysed traits were infectious diseases (ID), including digital and interdigital dermatitis and interdigital phlegmon, and non-infectious diseases (NID), including ulcers, white line disease, horn fissures, and double sole and overall claw disease (OCD), comprising all recorded disorders. Claw diseases/disorders were defined as 0/1 occurrence per lactation. Linear animal models were employed for prediction of conventional breeding values (BV) and genomic breeding values (GEBV), including the random additive genetic effect of animal and the permanent environmental effect of cow and fixed effects of parity, herd, year and month of calving. Both high and intermediate weights (80% and 50%, respectively) of genomic information were employed for GEBV50 and GEBV80 prediction. The estimated heritability for ID was 3.47%, whereas that for NID 4.61% and for OCD was 2.29%. Approximate genetic correlations among claw diseases/disorders traits ranged from 19% (ID x NID) to 81% (NID x OCD). The correlations between predicted BV and GEBV50 (84–99%) were higher than those between BV and GEBV80 (70–98%). Reliability of breeding values was low for each claw disease/disorder (on average, 3.7 to 14.8%) and increased with the weight of genomic information employed.

Download Full-text