Abstract
With 3 figures and 5 tables AbstractIn this study, we extended in silico mapping for single trait to analyse data from multiple environments by calculating intraclass correlations and to mapping pleiotropic QTL for multiple traits by defining new statistic to measure the correlation between multiple traits and the marker. Data sets include phenotypes of eight agronomic traits obtained from six different ecologic environments and years, and genotypic information from 477 polymorphic markers on 14 ancestral lines in the pedigree of ‘Suinong14’. With in silico mapping, a total of 39 markers distributed on 14 linkage groups are detected as QTL responsible for eight agronomic traits and 10 QTL are identified as having pleiotropic effects. Tracing transmission of functional QTL in the pedigree indicated that certain QTL, such as Sat_036 on linkage group D1a, Satt182 on linkage group L, and Satt726 on linkage group B2 may be responsible for the contribution of exotic germplasm to the improved cultivars.
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