Association analysis is a relatively novel approach in
quantitative traits studies that allows high resolution mapping
and time efficient and direct application on breeding material.
Since the markers, which are close to the quantitative trait
loci stable across environments and genetic backgrounds,
may be valuable for marker assisted selection, we chose
microsatellite markers previously linked to traits of interest
in various mapping studies. A set of 36 microsatellite markers
positioned near important maize (
Zea mays
L.) agronomic
loci was used to evaluate genetic diversity and determine
population structure. To verify the associations between
the markers and traits, a panel of diverse maize inbred lines
was genotyped with microsatellites and phenotyped for
flowering time, yield and yield components. A relatively
high level of polymorphism detected in number of alleles per
locus (8.2), average polymorphic information content value
(0.64), and average gene diversity (0.684) lines showed the
analyzed panel of maize inbred contained significant genetic
diversity and was suitable for association mapping. The
population structure estimated by model-based clustering
method grouped maize inbred lines into three clusters. The
association analysis using the general linear and mixed linear
models determined significant correlations between several
agronomic traits and three microsatellites on chromosomes
3, 5, and 8, namely
umc1025, bnlg1237, and
bnlg162
consistent across the environments, explaining from 4.7%
to 18.2% of total phenotypic variations. The results suggest
that the chromosome regions containing quantitative trait
loci (QTLs) associated with multiple yield-related traits
consistently across environments are potentially important
targets for selection.
