Comparative studies on QTL mapping by simple interval mapping and composite interval mapping models for selected growth and yield traits in rice (Oryza sativa L.)

QTL mapping was performed for five yield determining traits including grain yield in rice using a double haploid population of IR64 and Azucena cross. A comparison of QTLs detected by two different models simple interval mapping (SIM) using MAPMAKER/QTL and composite interval mapping (CIM) using QTL Cartographer was made, and common QTLs across the models were identified. The SIM detected 5 significant QTLs whereas CIM revealed 9 QTLs and only CIM could dissect flowering and maturity with QTLs, indicating its power and precision in QTL detection. Clustering of QTLs controlling correlated traits was common in both models. Apart from the QTLs detected by SIM, extra five QTLs were observed in CIM model with much higher LOD scores than SIM. The position of QTLs on different chromosomes was identical in both models except in case of new QTLs identified by CIM on chromosome 3 and 10. Congregation of multiple QTLs in the same marker interval concurred with the results of trait phenotypic association with each other indicated sharing of common regions of chromosomes by the correlated traits. These chromosomal regions may be focused for further saturation with additional markers to confirm the nature of QTL affecting the trait. The MAPMAKER/QTL and QTL Cartographer have different approaches in detecting the QTL and because of the more precision of the latter model, additional QTLs that had significant effect on traits were detected. However the common QTL detected by both the approaches, could be considered as stable QTL and be of use in Marker Assisted Selection.