Ordas et al. BMC Genomics 2010, 11:174 http://www.biomedcentral.com/1471-2164/11/174 Table 2 Phenotypic and genetic correlation coefficients among resistance and agronomic traits calculated in the population of RILs derived from EP39 × EP42. ATa S PH H Y STL RSTL SDR CDR AT 0.92* 0.01 0.32* -0.36* 0.10* 0.11* -0.11* -0.21* S 0.97+ -0.01 0.32* -0.42* 0.11* 0.13* -0.12* -0.20* PH 0.23+ 0.20 0.07 0.37* 0.48* -0.05 0.15* 0.05 H 0.85+ 0.74+ 0.53 -0.14* 0.07 0.05 0.01 -0.20* Y -0.68+ -0.68+ 0.27 -0.84 0.12* -0.07 0.17* 0.16 STL 0.32+ 0.43+ 0.51+ 0.61 -0.03 0.82* -0.25* -0.18 RSTL 0.19 0.38+ -0.28 0.29 0.70+ -0.35 -0.37* -0.24* SDR -0.44 -0.53+ 0.12 - -0.19 -0.08 -0.09 0.51* 0.94 0.58 0.68+ CDR -0.76 -0.41 0.56 - 0.22 The phenotypic correlation coefficients are shown above the diagonal while the genetic correlation coefficients are shown below the diagonal. The correlation coefficients were obtained after evaluation in two environments under artificial selection with corn borer eggs a AT = anthesis, S = silking, PH = plant height, H = grain humidity, Y = yield, STL = stalk tunnel length, RSTL = relative stalk tunnel length, SDR = shank damage rating, CDR = cob damage rating. * Phenotypic correlation was significant at the 0.01 probability level. + Genotypic correlation exceeded twice its standard error. 2.4 and 2.8 cm and both parents contributed with favourable alleles. The QTL at bin 8.05 was also related to relative stalk tunnel length. Concerning ear resistance traits, one QTL was detected for cob damage rate with a LOD score lower than 3 and a validation frequency lower than 30%.1",5,"not_at_top"> In the RILs, we also detected 6, 1, 1, and 4 QTLs for silking, plant height, kernel humidity, and yield, respec- tively (Figure 1; Table 3). For these traits, the percentage of genetic variance explained by the QTLs, calculated in the whole data set, varied from 10 to 45%. However, the percentages of genetic variance explained by the QTLs were much lower when they were calculated by cross validation. The QTL for silking at bin 8.05 is remarkable because it explains 29% of the phenotypic variance. This QTL was detected for silking in the 92% of the CV/G runs, indicating a great precision in the location. A QTL for yield at bin 8.05 was located near a QTL related to stalk tunnel length and relative stalk tunnel length. A QTL for plant height and grain humidity was found at bin 3.05 and explained 16% of the phenotypic variance, approximately, for each trait. For both traits, the QTL was detected with great precision (more than 95% of the CV/G runs). For silking, each parent contributed with favourable alleles to half of the QTLs, while for yield, the favourable alleles for most QTLs came from EP42. EP42 also provided the allele that increased the trait for the QTL related to plant height and kernel humidity. Discussion As expected from previous experiments [29,30] EP39 was resistant, while EP42 was susceptible to MCB stalk Page 3 of 10 tunnelling. The value of EP39 × EP42 for stalk tunnel length was close to the mid-parent value which suggests that additive effects were more important than domi- nant effects. This is in concordance with previous experiments in which the dominant effects were not sig- nificant, except for one single cross [14-16]. Contrarily to stalk tunnel length, the hybrid was more ear resistant than the most resistant line indicating that dominant effects would also play an important role, in agreement with results reported by Cartea et al. [18] and Velasco et al. [31]. Similarly, the EP39 × EP42 hybrid exhibited a considerable degree of heterosis for most agronomic traits. Although both parental lines did not differ for many traits, the significant genetic variation found among RILs for all traits, except for kernel damage, showed that this population is a valuable material to detect QTLs among European germplasm, especially for MCB resistance. The lack of significant RILs × environ- ment interaction for stalk tunnel length is in agreement with previous research [10,29,32]. Plant height was highly and significantly correlated to a resistance trait, such as stalk tunnel length. This result is in agreement with the result reported by Schon et al. [33], but not with results obtained by other authors [7,9,34]. This suggests that the genetic relationship between both traits depends on the germplasm being evaluated. The 3 QTLs for stalk tunnelling by MCB detected in this study did not overlap with the QTLs for stalk tun- nelling by MCB detected in the intermated B73 × Mo17 population [10]. Differences due to genetic heterogeneity or sampling limited number of progeny could explain the lack of coincidence between two particular QTL experiments. On the contrary, the QTLs for stalk tun- nelling detected in the present study were in the same or adjacent bins to QTLs for stalk tunnelling by ECB consistently detected in other experiments [7-9,33-35]. The coincidence of the three QTL locations in experi- ments carried out with genetically diverse maize popula- tions and with different corn borer species indicates the importance of those genomic regions for corn borer resistance across corn borer species and maize popula- tions. The resistance mechanisms of maize to ECB or MCB attack at early stages of plant development are probably based on toxins, for example DIMBOA, but, based on structural compounds, particularly cell wall composition, later on [36-39]. Cell wall characteristics may affect insect feeding due to different reasons: ele- vated levels of indigestible fiber may increase the bulk density of the diet to the point that insect are unable to ingest sufficient quantities of nutrients and water [40], and/or lignified cell walls may produce tougher tissues that are more resistant to the tearing action of mand- ibles [41]. QTLs for MCB stalk tunnelling detected in this experiment at bins 1.02, 3.05, and 8.04 were close