Genomic selection as a tool to decrease greenhouse gas emission from domestic ruminants

JC McEwan, CS Pinares-Patino, SM Hickey, EA Young, KG Dodds, S MacLean, G Molano, E Sandoval, H Kjestrup, R Harland, S Rowe, NK Pickering

E-Mail john.mcewan@agresearch.co.nz

A trial measured CH4 emissions, at 5 minute intervals, from 1,225 New Zealand dual purpose sheep placed in respiration chambers for 2 days, with repeat measurements two weeks later for another 2 days. While in the chambers they were fed, based on live-weight, a pelleted lucerne ration at 2.1 times estimated maintenance requirements. Methane outputs were calculated for gCH4/day and gCH4/kg dry matter intake (DMI) for each of the 4 days. Single trait models were used to obtain estimates of heritability and repeatability. Heritability of gCH4/day was 0.29±0.05, and for gCH4/kgDMI 0.13±0.03.  Repeatability between measurements 14 days apart were 0.55±0.02 and 0.26±0.02, for the two traits.  The genetic and phenotypic correlations of CH4 outputs with various production traits (weaning weight, live-weight at 8 months of age, dag score, muscle depth and fleece-weight at 12 months of age) measured in the first year of life, were estimated using bivariate models.  There was no evidence of unfavorable genetic correlations for the gCH4/kgDMI trait.

These animals, their sires, plus a further 288 animals evaluated through respiration chambers have been genotyped with either the Illumina 50K ovine beadchip or the new Illumina 600K ovine beadchip. The data is currently being analysed using genome wide association analysis and GBLUP to identify regions of interest and estimate molecular breeding values (MBVs) and their accuracies. The MBVs will complement genomic breeding values currently available commercially for 22 production related traits in New Zealand dual purpose sheep.

The medium term objectives are: to decrease the cost of methane measurement via the use of repeated brief measurements, increase the number of animals measured and genotyped and increase the accuracy of prediction. If successful the technology will be extended to dairy cattle.