@conference {41973,
	title = {Prospects for genome wide selection in the New Zealand livestock industries},
	booktitle = {Proceedings of the New Zealand Society of Animal Production},
	volume = {67},
	year = {2007},
	month = {Jan},
	pages = {162-168},
	publisher = {New Zealand Society of Animal Production},
	organization = {New Zealand Society of Animal Production},
	address = {Wanaka},
	abstract = {A number of DNA marker applications aid genetic selection within subpopulations of New Zealand{\textquoteright}s livestock farming industries. Advances in genomic tools have opened the possibility of genotyping individuals for a large set of markers, enough to have a large proportion of the genome {\textquoteleft}tagged{\textquoteright} with at least one of these markers. This creates opportunities for genome wide selection (GWS) {\textendash} the selection of breeding animals based on very large numbers of marker genotypes. There are a number of requirements for GWS to work, including the existence of genotyping technology to provide genotypes at a sufficient density, tractable statistical methods for estimating marker  effects to use in prediction models and suitably phenotyped populations which when genotyped allow estimation of relationships between markers and traits. Additional phenotyped populations are required to validate their predictive ability and demonstrate economic benefits to breeders and to the commercial tier. A high density genotyping platform is available for cattle, but may need further developments. Plans are underway for a similar platform for sheep, but not for deer. The dairy industry is well placed to implement GWS, as there is a large bank of DNA samples of industry sires representing most of the genome variation present. Genotyping these animals will allow marker effects to be estimated and the reduced generation interval arising from selecting young sires should easily overcome any decrease in selection accuracy compared with progeny testing. Industry structures are likely to evolve to allow a return to entities undertaking GWS. GWS will be mostbeneficial for traits with low heritability, that cannot be measured on selected parents and/or that are expensive to measure. Genes of known effect may continue to be accounted for individually, particularly if they exhibit non-additive effects.},
	issn = {1176-5283},
	author = {Dodds KG and Amer PR and Spelman RJ and Archer JA and Auvray B}
}
