Multi-trait genomic prediction of methane emission in Danish Holstein

TY - ABST

T1 - Multi-trait genomic prediction of methane emission in Danish Holstein

AU - Manzanilla Pech, Coralia Ines V

AU - Løvendahl, Peter

AU - Lassen, Jan

PY - 2019/9/1

Y1 - 2019/9/1

N2 - Reducing methane (CH4) emissions in livestock production is a challenge for this century. In dairy cattle, selecting for lower methane emitting animals is one of the best approaches to reduce CH4 as genetic progress is cumulative and permanent. However, genetic selection requires a large amount of animals with records in order to get accurate estimated breeding values (EBV). Given that, CH4 records are scarce, the use of information on routinely recorded traits highly correlated with CH4 has been suggested to increase the accuracy of genomic EBV (GEBV) through multi-trait genomic prediction. Therefore, the objective of this study was to estimate and compare the accuracies of prediction of GEBV for CH4 including or not, energy corrected milk (ECM) and body weight (BW) information in a multi-trait analysis. A total of 14,013 weekly records on CH4 from 2,241 Danish Holstein multiparous cows with ~60,000 weekly records (from ~2700 cows) on ECM and BW were included in the analyses. The reference population contained 2,714 cows with phenotypes (in CH4, ECM or BW), 1,920 with genotypes with 50K markers. Four cross validation groups were created randomly grouping daughters per sire. Several scenarios were analyzed: the base scenario was single trait of CH4 not including additional information, and posteriorly including ECM, BW or both traits as information in 1) reference and validation populations or 2) only in reference population. Accuracies were obtained using single step GBLUP (SS-GBLUP). Fixed effects included herd-year*season-year, lactation week, and parity number as covariate. Random effects included additive genetic effect, permanent environmental effect and residual. The average accuracy of GEBV for CH4 in the base scenario was 0.28 (SE=0.03). Based on our results, we conclude that including information on ECM can increase significantly the accuracy of GEBV for CH4, whereas, BW information only improved the accuracy slightly.

AB - Reducing methane (CH4) emissions in livestock production is a challenge for this century. In dairy cattle, selecting for lower methane emitting animals is one of the best approaches to reduce CH4 as genetic progress is cumulative and permanent. However, genetic selection requires a large amount of animals with records in order to get accurate estimated breeding values (EBV). Given that, CH4 records are scarce, the use of information on routinely recorded traits highly correlated with CH4 has been suggested to increase the accuracy of genomic EBV (GEBV) through multi-trait genomic prediction. Therefore, the objective of this study was to estimate and compare the accuracies of prediction of GEBV for CH4 including or not, energy corrected milk (ECM) and body weight (BW) information in a multi-trait analysis. A total of 14,013 weekly records on CH4 from 2,241 Danish Holstein multiparous cows with ~60,000 weekly records (from ~2700 cows) on ECM and BW were included in the analyses. The reference population contained 2,714 cows with phenotypes (in CH4, ECM or BW), 1,920 with genotypes with 50K markers. Four cross validation groups were created randomly grouping daughters per sire. Several scenarios were analyzed: the base scenario was single trait of CH4 not including additional information, and posteriorly including ECM, BW or both traits as information in 1) reference and validation populations or 2) only in reference population. Accuracies were obtained using single step GBLUP (SS-GBLUP). Fixed effects included herd-year*season-year, lactation week, and parity number as covariate. Random effects included additive genetic effect, permanent environmental effect and residual. The average accuracy of GEBV for CH4 in the base scenario was 0.28 (SE=0.03). Based on our results, we conclude that including information on ECM can increase significantly the accuracy of GEBV for CH4, whereas, BW information only improved the accuracy slightly.

M3 - Conference abstract for conference

T2 - 70th Annual Meeting of the European Federation of Animal Science (EAAP)

Y2 - 26 August 2019 through 30 August 2019

ER -