Abstract
The objective of this work was to assess the genetic diversity and population structure of wheat genotypes, to detect significant and stable genetic associations, as well as to evaluate the efficiency of statistical models to identify chromosome regions responsible for the expression of spike-related traits. Eight important spike characteristics were measured during five growing seasons in Serbia. A set of 30 microsatellite markers positioned near important agronomic loci was used to evaluate genetic diversity, resulting in a total of 349 alleles. The marker-trait associations were analyzed using the general linear and mixed linear models. The results obtained for number of allelic variants per locus (11.5), average polymorphic information content value (0.68), and average gene diversity (0.722) showed that the exceptional level of polymorphism in the genotypes is the main requirement for association studies. The population structure estimated by model-based clustering distributed the genotypes into six subpopulations according to log probability of data. Significant and stable associations were detected on chromosomes 1B, 2A, 2B, 2D, and 6D, which explained from 4.7 to 40.7% of total phenotypic variations. The general linear model identified a significantly larger number of marker-trait associations (192) than the mixed linear model (76). The mixed linear model identified nine markers associated to six traits.
Highlights
A set of 30 microsatellite markers positioned near important agronomic loci was used to evaluate genetic diversity, resulting in a total of 349 alleles
The results obtained for number of allelic variants per locus (11.5), average polymorphic information content value
The population structure estimated by model‐based clustering distributed the genotypes into six subpopulations according to log probability of data
Summary
A tendency in the breeding process is introducing. The advancement in the field of molecular biology by applying genetic marker technologies and new statistical approaches are powerful tools for indirect selection of valuable traits through marker‐assisted selection (Landjeva et al, 2007). The detection of specific and precisely tagged chromosome regions responsible for the expression of certain agronomic traits could be an excellent contribution for the selection and generation of new high‐yielding wheat varieties. The knowledge of population diversity and structure is of major importance for an efficient use of elite lines and varieties in a breeding process (Laido et al, 2013). Spike‐related traits are important yield components, which are less environmentally sensitive and exhibit higher heritability than yield per se (Cuthbert et al, 2008). The analyses of the genetic control of spike‐related characteristics and of individual effects of different genes and quantitative trait loci (QTL)
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