Background: Body weight (BW) is an important trait for meat production in sheep. Although over the past few years, numerous quantitative trait loci (QTL) have been detected for production traits in cattle, few QTL studies have been reported for sheep, with even fewer on meat production traits. Our objective was to perform a genome-wide association study (GWAS) with the medium-density Illumina Ovine SNP50 BeadChip to identify genomic regions and corresponding haplotypes associated with BW in Australian Merino sheep. Methods: A total of 1781 Australian Merino sheep were genotyped using the medium-density Illumina Ovine SNP50 BeadChip. Among the 53 862 single nucleotide polymorphisms (SNPs) on this array, 48 640 were used to perform a GWAS using a linear mixed model approach. Genotypes were phased with 'hsphase'; to estimate SNP haplotype effects, linkage disequilibrium blocks were identified in the detected QTL region. Results: Thirty-nine SNPs were associated with BW at a Bonferroni-corrected genome-wide significance threshold of 1 %. One region on sheep ('Ovis aries') chromosome 6 (OAR6) between 36.15 and 38.56 Mb, included 13 significant SNPs that were associated with BW; the most significant SNP was OAR6_41936490.1 (P = 2.37x10−16) at 37.69 Mb with an allele substitution effect of 2.12 kg, which corresponds to 0.248 phenotypic standard deviations for BW. The region that surrounds this association signal on OAR6 contains three genes: 'leucine aminopeptidase 3' (LAP3), which is involved in the processing of the oxytocin precursor; 'NCAPG non-SMC condensin I complex, subunit G (NCAPG)', which is associated with foetal growth and carcass size in cattle; and 'ligand dependent nuclear receptor corepressor-like (LCORL)', which is associated with height in humans and cattle. Conclusions: The GWAS analysis detected 39 SNPs associated with BW in sheep and a major QTL region was identified on OAR6. In several other mammalian species, regions that are syntenic with this region have been found to be associated with body size traits, which may reflect that the underlying biological mechanisms share a common ancestry. These findings should facilitate the discovery of causative variants for BW and contribute to marker-assisted selection.

TREEPLAN is an advanced analytical tool providing accurate and precise predictions of genetic values to operational tree breeders. This project aimed to exploit TREEPLAN's analytical power for the benefit of all sections of the forest growing industry; in particular, the deployment sector and programs not traditionally associated with the Southern Tree Breeding Association. The outputs include: the routine inclusion of reproductive and fitness traits into the assessment framework; better prediction of stand performance through competition models; the undertaking of pilot studies using data from large industry programs; and the better modelling of the genetic structures of hybrid populations.