Cavanagh et al. Genetics Selection Evolution 2010, 42:36 http://www.gsejournal.org/content/42/1/36 Table 1 Summary statistics of traits used in this in this study Trait Body weight Carcass weight Dressing percentage Total fat Carcass fat Internal fat Percent fat in carcass Subcutaneous fat depth* Subcutaneous fat area Total lean Carcass lean Percent lean in carcass Eye muscle area* Total bone Carcass bone Percent bone in carcass Unit kg kg % kg kg kg % Pixel mm2 kg kg % mm2 kg kg % Biological importance Proportion final weight to carcass weight Indicator of total fatness Indicator of carcass fatness Indicator of fatness in the internal depots Proportion of fat in the carcass Indicator of fatness Indicator of fatness Indicator of total lean Indicator of muscularity Proportion of lean in carcass Indicator of muscularity Indicator of total bone Indicator of size/quantity of bone Proportion of bone in carcass n 162 165 161 165 165 165 165 161 165 152 165 165 165 152 165 165 AVG 51 28 55 14 8.7 3.8 31 5.9 980 22 16 59 4205 7.4 2.9 11 SD 9.0 4.4 3 5.6 2.4 1.6 4 2.3 480 5.61 2.34 3 502 4.4 0.34 2 max 31 16 71 4.6 3.5 1.1 22 1 36 12 10 48 1245 2.5 1.98 7 Page 3 of 14 min 77 40 46 33 18 8.8 45 13 2597 32 22 67 5333 12 4.2 16 *Industry relevant refers to a trait that is used in the industry as a standard measure and hence is incorporated as a means for comparing this study with other studies Carcass weight and final body weight were adjusted only for cohort effects (Additional file 1). Residuals from the fitted models were obtained, and these were treated as the adjusted traits for subsequent QTL mapping. Marker analysis QTL mapping procedure A genome scan using 189 polymorphic microsatellite markers covering all 26 sheep autosomes was conducted in 510 backcross animals. For the linkage analysis, geno- typic and phenotypic information from the CT scan of 165 animals was used. The procedure of DNA extrac- tion, genotyping, allele calling and map positions has been outlined previously [26]. QTL analyses were performed for all traits using two methods. Based on a type I error of 0.05, the design (n = 160 animals) had a predicted power of 0.88 to detect QTL with 0.5 SD effect [29]. Solutions were obtained using the QTL-MLE procedure for normally distributed traits in ‘R’ [26]. As described in previous papers [26,27], when using QTL-MLE, a QTL with LOD ≥ 3.0 was deemed highly significant, significant if LOD ≥ 2.0, and suggestive for QTL with 1.75 ≤ LOD < 2.0. The second method involved regression analysis for a half-sib design implemented using the web-based pro- gram QTL Express [30]. QTL with chromosome-wide significance (P < 0.05) were described as suggestive QTL, whereas QTL exceeding the P < 0.01 chromo- some-wide levels and P < 0.05 experiment-wide levels were labelled as significant and highly significant QTL, respectively. A two-QTL model was also fitted to the data using a full two-dimensional scan of each chromo- some in QTL Express [30]. Meta-assembly A meta-assembly of QTL identified in this study was conducted by collating all known QTL from public sources for matched traits based on individual QTL locations and meta-scores as described previously [27]. The positions and confidence intervals of ovine and bovine QTL and blocks of conserved synteny across both species were identified and aligned to the genomes of both species. The individual QTL locations and their scores, and meta-score profiles can be browsed at http://crcidp.vetsci.usyd.edu.au/cgi-bin/gbrowse/oaries_- genome/. In addition to the lactation traits, QTL profiles for growth, body weight and carcass composition can now be browsed on this website. Growth and body weight meta-scores from the first paper of this series [26] were also loaded into the website. The carcass com- position traits were summarised into four trait classes: bone (percentage bone, bone weight, bone yield), fat (fat yield, back fat, fat depth, marbling, fat thickness, subcutaneous fat thickness), muscle (longissimus muscle area, rib eye area, carcass yield, retail product yield, shear force, lean meat yield) and weight (hot and cold carcass weight, yearling, weaning and slaughter weight). Single and aggregated bars, heat maps and plots can be selected for sheep and cattle as well as meta-scores for both species. Hyperlinks to the original manuscript reference are given. Results Analysis of carcass data The summary statistics for each phenotype are shown in Table 1. For the second cohort, carcass weight and