8th INTERNATIONAL WHEAT CONFERENCE

PoPuLATIoN STRuCTuRe IN A CoRe CoLLeCTIoN
of WheAT ANd ASSoCIATIoN STudy oN A gRAIN yIeLd
uNdeR dIffeReNT WATeR RegImeS
Dejan Dodig 1 , Miroslav Zorić 2 , Borislav Kobiljski 3 ,
Vesna Kandić 1
1 Maize Research Institute, ‘Zemun Polje’, Slobodana Bajica 1, 11185 Belgrade, Serbia
2 Faculty of Technology, University of Novi Sad, Bulevar Cara Lazara 1, 21000 Novi Sad,
Serbia
3 Research Institute of Field and Vegetable Crops, Maksima Gorkog 30, 21000 Novi Sad,
Serbia
E-mail Address of presenting author: dejanza@yahoo.com
Understanding of genetic diversity, population structure, and molecular relatedness is
important for breeding, germplasm improvement, and association studies. A set of 96
common wheat genotypes of worldwide origin, including cultivars and breeding lines,
were characterized with 46 genome-wide SSR loci for genetic diversity and population
structure. Genetic diversity among these genotypes was examined using a genetic distance-based
and a model-based clustering methods. The model-based analysis identified
an underlying population structure, consisting of four main distinct subpopulations for
the whole genotype set, corresponding well to four major distance-based groups. Among
all of the genotypes, 58.3% were assigned into the corresponding subgroups, while others
were assigned into a mixed subpopulation. Partial least squares (PLS) regression method,
with nine environmental explanatory variables for interpreting genotype × environment
interaction for grain yield, also suggested that our germplasm collection does not represent
a single unstructured Hardy-Weinberger population. Analysis of molecular variance
(AMOVA) showed that 87.6% of the total variation could be explained by the variance
within the subpopulation groups. The effect of population structure on association mapping
was tested on three-year data of grain yield under irrigated, rainfed and drought
stress conditions. A total of 21 marker-grain yield associations (P < 0.01) were identified
with nine different SSR markers. Most associations were detected only in one to three
environments (year-treatment combinations) with an average R 2 value around 13%. Nevertheless,
marker gwm484 was associated with six environments, including irrigated,
rainfed and drought stress treatments, with R 2 values ranging from 23 to 36%. Microsatellite
marker gwm484 (on chromosome 2D) may be useful for marker assisted selection to
enhance yield under both non-stress and drought stress conditions. The results improved
our characterization of the germplasm used and will assist the selection of new crosses
for drought stress conditions.
Key Words: Associating mapping, population structure, water-stress, wheat, yield
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