In order to detect the linkage disequilibrium existing between alleles
at a marker locus and alleles of a linked quantitative trait locus (Q
TL), a least squares interval mapping approach using multiple regressi
on on marker data has been developed. It allows inclusion in the model
of the parameters describing the experimental and environmental situa
tion, so that the QTL x environment effects can be tested. The method
can also be applied using any general statistical package to data for
which the usual normal distribution assumption does not hold, and wher
e the use of weighted approaches is therefore required. A method to co
pe with the frequent problem in biological experiments of missing data
was also used. The analysis was performed on data concerning two comp
onents of maize pollen competitive ability, obtained from an experimen
t over 2 years. The method, in comparison with the traditional single
marker approach, has been shown to be more powerful in detecting QTLs
and more precise in determining their map position. The analysis has i
dentified QTLs expressed across years, putative QTLs with major effect
s and QTLs accounting for genotype x environment interaction.