Determination of population structure of wheat core collection for association mapping

Abstract

The microsatellites, as one of the most robust markers for identification of wheat varieties, were used for assessment of genetic diversity and population structure to promote effective use of genetic resources. In this study, the set of 284 wheat varieties were genotyped using 30 microsatellite markers. The chosen SSR markers were located among almost all linkage groups and covered all three genomes. The genotypes used originate from 24 different breeding centers worldwide and are included in an extensive core collection of the Institute of Field and Vegetable Crops in Novi Sad, Serbia. The total number of detected alleles was 349 at all analyzed loci. The average number of detected allelic variant per locus was 11.5. The mean value of polymorphic information content was 0.68. According to the probability of data obtained by program Structure, the results have shown presence of 6 subpopulations within the studied set of genotypes. The population structure positively correlated to some extent with geographic origin. The available pedigree data were included for additional explanation of population structure. The results of this study should provide valuable information for future association studies using the diverse wheat breeding material.

Characterization of some bread wheat genotypes using molecular markers for drought tolerance

“…The results that used SSRs are potential markers that could be used as marker to assist in selection for drought stress tolerance by molecular plant breeding. Moreover, the results are in agreement with those reported by Dodig et al (2010), Brbaklic et al (2015), Faheem et al (2015), Ramya et al (2015), and Tomar et al (2016), who assigned SSR markers to drought tolerance in wheat genotypes using molecular markers. Hao et al (2006) suggested that the allele's number in each locus and the calculated PIC values of these alleles should be evaluated together as part of an objective assessment of genetic diversity in genotype collections.…”

Genetic analysis of spike length in wheat

“…3). Microsatellites that exibited a relation with yield in both models were: gwm357, gwm636, cfa2114, gwm631, gwm190, barc5, barc12, barc110, gwm680, wmc457, which is in partial accordance with ALSALEH et al, (2015); ZHANG et al, (2015); BRBAKLIĆ et al, (2015).…”

“…The dispersion of the points represents two subpopulations, which have also been determined in the previous graphic representation. According to the literature, the division into subpopulations should have been done on the basis of the cultivars found in genealogies or on the basis of their geographical origin (HAO et al, 2011;NEUMANN et al, 2011;CHEN et al, 2012;DODIG et al, 2012;NIELSEN et al, 2014;BRBAKLIĆ et al, 2015). However, in the conducted research, the geographical origin could not explain the grouping of genotypes within the same subpopulations, due to the narrow genetic variability of the examined material.…”

Population structure of Nepali spring wheat (Triticum aestivum L.) germplasm

“…The unexpected population structure (4 subpopulations not 3; admixture) results may be due to the numerous factors that influence the structure of a germplasm population such as age of the variety, activities of plant breeders [ 41 , 42 ], geographical origin [ 36 , 38 , 43 , 44 ], market class [ 37 , 45 ] and ploidy level [ 39 ]. Wheat has been growing in Nepal (mostly in the western hills) from ancient times [ 46 ].…”