Three typical
mapping methods, the analysis of variance (ANOVA), the interval mapping(IM) and the composite interval mapping (CIM), were employed to construct the QTL maps of corn borer resistance, plant height and ear height for an F2 data of the cross Ki3× CML139 from CIMMYT. Numbers, positions and effects of
detected QTLs by these
methods were compared. The results are as follows. (1) 25
significant QTLs were detected by ANOVA, 21 QTLs by IM, and 23 QTLs by CIM for the three traits under the same significant level. So ANOVA had the highest capability for the detection although it might bias the estimates for positions and effects. (2) The same 15 QTLs of all 30 were detected by the three methods, other 9 QTLs were found out by two of the three methods, another 6 QTLs by only one method. This indicated that the similarity among methods was dominant. (3) The differences among whether average additive effects (absolute values) or
dominant effects (practical values) of QTLs estimated by different methods were insignificant, and the variation among methods was smaller than that within methods in general. (4) A suggestion for mapping QTLs is that multiple methods should be considered, and it is preferential to declare the QTLs detected simultaneously by several methods, and then jointly estimate their effects.
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