Ponsuksili et al. BMC Genomics 2010, 11:572 http://www.biomedcentral.com/1471-2164/11/572 microarray probe-sets based on the current porcine sequence information [6]. We focus on eQTL of genes whose expression at slaughter is significantly correlated to technological meat quality traits addressed in com- mercial pig breeding schemes. Taking into account own observations on the reliability of eQTL mapping we highlight eQTL located on the same chromosome as the corresponding genes themselves [7]. Results Summary analysis of eQTL detection Expression data were obtained from M. longissimus dorsi samples of 74 F2 animals of a resource population using Affymetrix Porcine Genome Arrays containing in total 24,123 probe-sets of which 20,689 probe-sets were assigned to a known gene [6]. MAS5 analysis revealed consistent ‘present calls’ for 11,457 probe-sets. This pre- selected set was further analyzed with the more sophisti- cated hybrid algorithm PLIER [8,9] and the expression levels were subjected to linkage analysis. Out of 11,457 probe-sets 6,117 showed at least one eQTL at the 5% chromosome-wide significance threshold (average F-value 4.92, corresponding to LOD score = 2.0 and nominal significance of p ≤ 10-3) corresponding approxi- mately to the suggestive linkage threshold proposed by Lander & Kruglyak [10] (Table 1). In total, the 11,457 probe-sets revealed 9,180 eQTL at LOD score > 2 (Additional file 1), 1,058 eQTL at LOD score > 3, and 160 eQTL at LOD score > 4. Only 29 had eQTL with LOD score > 5. This yielded an average of 1.5 eQTL per transcript (ranging from 1 to 6 eQTLs). The eQTL were distributed over all autosomes with some regions har- boring particularly many eQTL with high significance (Figure 1). Out of the 9,180 eQTL 8,168 eQTL could be assigned to the porcine genome sequence (Ensembl Sscrofa9 database, released April 2009). In total 653 eQTL were mapped on the same chromosome as the corresponding gene itself. These eQTL are putative cis- eQTL. Integration of trait, expression, and mapping data to identify genes related to the meat quality In order to link the eQTL to the genetic background of a classical phenotypic trait of interest, it is necessary to Table 1 Global eQTL summary Page 2 of 14 establish a relationship between the variation of that classical phenotypic trait, the expression levels of various transcripts, and the mapping position of the eQTL and the corresponding transcripts. Therefore, we selected transcripts whose expression level showed significant correlation with individual meat quality traits and with the composite traits, PC2 and PC3 (Tables 2, 3, 4) (p ≤ 0.05, corresponding to correlation coefficients ranging between |0.24-0.50|) and we focussed on those tran- scripts with eQTL on their own chromosome as the structurally fixed linkage group (collateral transcript and eQTL position). Out of 653 eQTL that were mapped on the chromosome of their corresponding genes 262 tran- scripts showed correlation with at least one meat quality trait. These are displayed in Figure 2, 3, 4, 5 and 6. The linkage map showed accurate match of microsatellites marker order with the marker arrangement in the cur- rent porcine genome sequence assembly (Sscrofa9 assembly, April 2009). A total of 73 out 115 microsatel- lites marker were found to align on the porcine genome sequence assembly map position by BLAST analysis. Reflecting this alignment, the position of 262 transcripts in the porcine physical map was assigned to the corre- sponding eQTL position in the genetic linkage maps. Most of the eQTL of transcripts whose expression level correlated with meat quality traits were found on SSC1, 2, 3, 6, 9 and 14. Table 2 summarizes the number of eQTL related to various meat quality traits. Most of these meat quality parameters were correlated or dependent on each other. Such correlations were reported by many studies [11-13]. In a previous study we used principle components (PCs) to reduce the multi dimensional data sets into lower dimensions [13]. The principal component (PC2) is a meat quality vector and has high loadings for pH24ld, pH24st and meat color which are inversely correlated with drip loss. The princi- pal component (PC3) is also a meat quality vector with large positive contribution of conductivity (LF1ld, LF24ld, LF24sm) and negative contribution of pH1ld. In order to scale down the list of 262 putative cis-eQTL for meat quality, transcript levels of genes correlated with the two PCs with high loadings of meat quality traits were considered. The level of expression of 38 and 47 probe-sets, respectively, were correlated with the new Total # of probe-sets 11,457 11,457 11,457 11,457 Lod score threshold Nominal Total # of # of probe-sets with at least P eQTL one eQTL # of eQTL mapped # of eQTL with ipsi- chromosomal location* >2 >3 >4 >5 4.90E-03 4.59E-04 4.50E-05 3.52E-06 9180 1058 160 29 6117 990 159 29 8168 955 139 25 653 125 35 13 *, i.e. # of eQTL located on the same chromosome as the corresponding probe-set.