Ponsuksili et al. BMC Genomics 2010, 11:572 http://www.biomedcentral.com/1471-2164/11/572 Page 12 of 14 Figure 6 Position of eQTL of probe-sets that show trait-correlated expression and that are located on the same chromosome (SSC17 and 18) as the corresponding genes. Left: physical map with positions of microsatellite markers (red) and genes (black) represented by the probe-sets Mb according to the Sscrofa9 genome sequence; Right: sex-averaged linkage maps of SSC 1 to 4 with positions of microsatellite markers and eQTL of corresponding probe-sets in cM; Both maps are linked based on the microsatellite marker positions (red and bold). Meat quality traits, with which the expression levels of probe-sets are correlated, are presented in brackets. Trait abbreviations are given at table 2. Preparation of target products, hybridization and scan- ning using the GeneChip scanner 3000 were performed according to Affymetrix protocols using 5 μg of total RNA to prepare antisense biotinylated RNA. The quality of hybridization was assessed in all samples following the manufacturer’s recommendations. Data were ana- lysed with Affymetrix GCOS 1.1.1 software using global scaling to a target signal of 500. Data were then imported into Arrays Assist software (Stratagene Eur- ope, Amsterdam, The Netherlands) for subsequent ana- lysis. The data were processed with MAS5.0 to generate cell intensity files (using default settings with detection P-values of < 0.04 for ‘present’, ≥0.04 and ≤ 0.06 for ‘marginal’, < 0.06 for ‘absent’; only ‘present’ calls were used). Quantitative expression levels of the present tran- scripts were estimated using PLIER (Probe Logarithmic Intensity Error) for normalization. The microarray data related to all samples have been deposited in the Gene Expression Omnibus (GEO, [28]) public repository (GEO accession number: GSE10204). Correlation between phenotype and gene expression Phenotypic data, i.e. expression levels and meat quality data as well as PC traits, were adjusted for systematic effects by analysis of variance performed with the procedure ‘Mixed’ of the SAS software package (SAS System for Windows, Release 9.02) before analysing their correlation and performing eQTL analysis. Full- sib family and sex were used as fixed effects, carcass weight as a covariate and slaughter date as random effect. Based on observations from 74 animals Pearson correlation coefficients were calculated between the residuals of the log2 transformed expression intensities of all 11,453 probes and each individual meat quality trait as well as between the expression levels and both composite traits, PC2 and PC3. For each pair of tran- script level and phenotype, Pearson correlation together with the P-value was computed (significance threshold p ≤ 0.05). The correlation coefficients at p ≤ 0.05 ranged between |0.24-0.50|. The observed false discovery rates were 0.08-0.34 which is reasonable for a microarray study, in particular, considering the rela- tively relaxed p-value (p ≤ 0.05). eQTL analysis In order to map eQTL adjusted expression values of 11,457 probe-sets were regressed onto the additive and dominance coefficients in intervals of 1 cM using the F2 option of QTL express [29]. Chromosome-wide signifi- cance levels were estimated by permutation tests using