GPS coordinates for modelling correlated herd effects in genomic prediction models applied to Hanwoo beef cattle

TY - JOUR

T1 - GPS coordinates for modelling correlated herd effects in genomic prediction models applied to Hanwoo beef cattle

AU - Cuyabano, Beatriz Castro Dias

AU - Rovere, Gabriel

AU - Lim, Dajeong

AU - Kim, Tae Hun

AU - Lee, Hak Kyo

AU - Lee, Seung Hwan

AU - Gondro, Cedric

N1 - Funding Information: Funding: This work was supported by the Next-Generation BioGreen21 Program (Project No. PJ01322204), Rural Development Administration, Republic of Korea, and by the National Institute of Food and Agriculture (AFRI Projects No. 2019-67015-29323 and 2021-67015-33411). Publisher Copyright: © 2021 by the authors. Licensee MDPI, Basel, Switzerland.

PY - 2021/7

Y1 - 2021/7

N2 - 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.

AB - 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.

KW - Carcass traits

KW - Genetic evaluation

KW - Geographical location

KW - Variance components

UR - http://www.scopus.com/inward/record.url?scp=85109334366&partnerID=8YFLogxK

U2 - 10.3390/ani11072050

DO - 10.3390/ani11072050

M3 - Journal article

C2 - 34359178

AN - SCOPUS:85109334366

SN - 2076-2615

VL - 11

JO - Animals

JF - Animals

IS - 7

M1 - 2050

ER -