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. 2021 Nov 24;10(12):2562.
doi: 10.3390/plants10122562.

Diversity of Water Yam (Dioscorea alata L.) Accessions from Côte d'Ivoire Based on SNP Markers and Agronomic Traits

Lassana Bakayoko  1   2 , Désiré N'Da Pokou  2 , Abou Bakari Kouassi  1 , Paterne A Agre  3 , Amani Michel Kouakou  4 , Konan Evrard Brice Dibi  4 , Boni Nzue  4 , Jean M Mondo  3   5 , Patrick Adebola  6 , Oluyemi T Akintayo  7 , Asrat Asfaw  3 , Assanvo Simon Pierre N'Guetta  1
Affiliations

Diversity of Water Yam (Dioscorea alata L.) Accessions from Côte d'Ivoire Based on SNP Markers and Agronomic Traits

Lassana Bakayoko et al. Plants (Basel). .

Abstract

Dioscorea alata (L.), also referred to as water, winged, or greater yam, is one of the most economically important staple food crops in tropical and subtropical areas. In Côte d'Ivoire, it represents, along with other yam species, the largest food crop and significantly contributes to food security. However, studies focusing on better understanding the structure and extent of genetic diversity among D. alata accessions, using molecular and phenotypic traits, are limited. This study was, therefore, conducted to assess the pattern of genetic variability in a set of 188 D. alata accessions from the National Agronomic Research Centre (CNRA) genebank using 11,722 SNP markers (generated by the Diversity Arrays Technology) and nine agronomic traits. Phylogenetic analyses using hierarchical clustering, admixture, kinship, and Discriminant analysis of principal component (DAPC) all assigned the accessions into four main clusters. Genetic diversity assessment using molecular-based SNP markers showed a high proportion of polymorphic SNPs (87.81%). The analysis of molecular variance (AMOVA) showed low molecular variability within genetic groups. In addition, the agronomic traits evaluated for two years in field conditions showed a high heritability and high variability among D. alata accessions. This study provides insights into the genetic diversity among accessions in the CNRA genebank and opens an avenue for sustainable resource management and the identification of promising parental clones for water yam breeding programs in Côte d'Ivoire.

Keywords: DArT-seq; Dioscorea alata; agronomic trait; genetic diversity; molecular markers; population structure.

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Conflict of interest statement

The authors declare no conflict of interest. The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript, or in the decision to publish the results.

Figures

Figure 1
Figure 1
Genetic relationship among 188 accessions of D. alata based on 11,722 SNPs: (a) Hierarchical circular clustering dendrogram generated using the UPGMA method and Jaccard’s dissimilarity matrix. Different colors indicate different groups identified: Cluster 1 (red), Cluster 2 (blue), Cluster 3 (black), and Cluster 4 (green), (b) Kinship Heatmap; the color gradient shows the similarity among accessions.
Figure 2
Figure 2
Grouping pattern in 188 D. alata accessions at K = 4 based on the Bayesian clustering method. The color displays each cluster: Red (cluster 1), Green (cluster 2), Blue (cluster 3), Yellow (cluster 4). Each vertical bar corresponds to an accession, and the color proportion in each bar represents the probability of each accession being affiliated to the different clusters.
Figure 3
Figure 3
Principal component plot showing clustering of the 188 D. alata accessions into four clusters. Each color represents a cluster: cluster 1 (red), cluster 2 (gold), cluster 3 (green), cluster 4 (blue), and admixture (purple).
Figure 4
Figure 4
Discriminant analysis of principal components based on 11,722 SNPs and the allelic sequences of 188 D. alata genotyped accessions from in vivo CNRA yam genebank. The axes represent the first two linear discriminant functions (LD). The circles correspond to each cluster identified. The dots in each circle represent individuals, and the number in the circle center indicates different subpopulations identified by DAPC analysis.
Figure 5
Figure 5
Characterization of grouping patterns using the first two linear discriminant functions in DAPC analysis: (a) linear discriminant function 1; (b) linear discriminant function 2.
See this image and copyright information in PMC

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