Genetic Diversity of Durum Wheat (Triticum turgidum L. ssp. durum, Desf) Germplasm as Revealed by Morphological and SSR Markers

Abstract

Ethiopia is considered a center of origin and diversity for durum wheat and is endowed with many diverse landraces. This research aimed to estimate the extent and pattern of genetic diversity in Ethiopian durum wheat germplasm. Thus, 104 durum wheat genotypes representing thirteen populations, three regions, and four altitudinal classes were investigated for their genetic diversity, using 10 grain quality- and grain yield-related phenotypic traits and 14 simple sequence repeat (SSR) makers. The analysis of the phenotypic traits revealed a high mean Shannon diversity index (H' = 0.78) among the genotypes and indicated a high level of phenotypic variation. The principal component analysis (PCA) classified the genotypes into three groups. The SSR markers showed a high mean value of polymorphic information content (PIC = 0.50) and gene diversity (h = 0.56), and a moderate number of alleles per locus (Na = 4). Analysis of molecular variance (AMOVA) revealed a high level of variation within populations, regions, and altitudinal classes, accounting for 88%, 97%, and 97% of the total variation, respectively. Pairwise genetic differentiation and Nei's genetic distance analyses identified that the cultivars are distinct from the landrace populations. The distance-based (Discriminant Analysis of Principal Component (DAPC) and Minimum Spanning Network (MSN)) and model-based population stratification (STRUCTURE) methods of clustering grouped the genotypes into two clusters. Both the phenotypic data-based PCA and the molecular data-based DAPC and MSN analyses defined distinct groupings of cultivars and landraces. The phenotypic and molecular diversity analyses highlighted the high genetic variation in the Ethiopian durum wheat gene pool. The investigated SSRs showed significant associations with one or more target phenotypic traits. The markers identify landraces with high grain yield and quality traits. This study highlights the usefulness of Ethiopian landraces for cultivar development, contributing to food security in the region and beyond.

Keywords: SSR markers; durum wheat; genetic diversity; landraces; morphological traits.

Figure 1

Map of Ethiopia showing the sample collection sites of landraces. The colored boxes represent the regions found in Ethiopia and the blue dots show sample collection sites.

Figure 2

A biplot of principal component analysis (PCA) of 104 durum wheat landraces and cultivars with their contribution value based on 10 agronomic and quality traits. The genotypes are colored based on their contribution to the two principal components from green (0%) to red (100%). The length of the arrows is equivalent to the variance of the variables, whereas the angles between them (cosine) are equivalent to their correlations. DH is days to heading; DM is days to maturity; SPS is number of spikelet per spike; PLH is plant height; TKW is thousand-kernel weight; GY is grain yield; GC is gluten content and GPC is grain protein content. PC1 and PC2 are principal component one and two, respectively.

Figure 3

Pairwise Nie’s standard genetic distance (GD) (A) and genetic differentiation (F_ST) (B) among studied populations. Darker colors indicate that populations are genetically distant, whereas lighter colors indicate that populations are genetically close.

Figure 4

Minimum Spanning Network (MSN) constructed for the 104 Ethiopian durum wheat genotypes based on Bruvo’s distance estimated using 14 SSR markers. Each node represents a single genotype. The nodes are colored according to the populations. The thickness of the lines represents the degree of relatedness between genotypes.

Figure 5

Biplot of discriminant analysis of principal component (DAPC) for thirteen studied populations. Different shapes and colors represent the populations. The bar plot at the right bottom corner shows the eigenvalues of identified dimensions. Dim1 and Dim2 are dimension one and two, respectively. DA is discriminant analysis.

Figure 6

Population structure of 104 Ethiopian durum wheat genotypes. Biplots showing the optimal number of clusters (K) at two (top left) and Log likelihood versus the number of K (top right) based on Evanno et al.’s (2005) method, and a structure bar graph of the populations at K = 2, where the green and orange colors represent the two genetic groups (bottom).

Figure 7

Boxplots depicting the association between different allelic combinations of (a) Xgwm46, (b) Xwmc256, and (c) Xgwm493 SSR loci with variation in agronomic and quality traits that were previously shown to have significant associations. The small rhombus within each boxplot shows the mean value while the small red circles outside the boxes represent outliers of corresponding traits. The letters ‘a’, ‘ab’ and ‘b’ indicate statistically significant differences at 0.01 level. ‘a’ has a mean that is statistically different from ‘b’; and ‘ab’ has a mean that is not statistically different from either ‘a’ or ‘b’.