AUTHOR=Soro Monique , Pita Justin S. , Somé Koussao , Otron Daniel H. , Yéo Edwige , Mutuku J. Musembi , Néya James B. , Tiendrébéogo Fidèle , Koné Daouda TITLE=Genomic analysis and identification of potential duplicate accessions in Burkina Faso cassava germplasm based on single nucleotide polymorphism JOURNAL=Frontiers in Sustainable Food Systems VOLUME=7 YEAR=2023 URL=https://www.frontiersin.org/journals/sustainable-food-systems/articles/10.3389/fsufs.2023.1202015 DOI=10.3389/fsufs.2023.1202015 ISSN=2571-581X ABSTRACT=

Cassava adaptation to climate change and its resistance to diseases are essential prerequisites for achieving food security in sub-Saharan Africa. The accessions collected from farmers’ fields are very important because they can provide new sources of genetic variability that are essential to achieve this goal. In this study, a panel of 184 accessions collected in Burkina Faso was genotyped using 36 single nucleotide polymorphism (SNP) markers. The accessions and markers that presented with more than 6% missing data were removed from the dataset and the remaining 34 markers and 166 accessions were retained for genetic diversity and population structure assessment. The average values of expected heterozygosity (0.46), observed heterozygosity (0.58), and polymorphic information content (0.36) indicated high genetic diversity within accessions. A complex genetic structure of 166 accessions was observed through the formation of 17 clusters using discriminant analysis of principal components (DAPC) and two clusters using Bayesian analysis. Out of the 166 accessions, 79 were unique multilocus genotypes (MLGs) and 87 were potentially duplicates. From the 79 MLGs, DAPC suggested eight clusters while the Bayesian analysis suggested seven clusters. Clusters shaped by DAPC appeared to be more consistent with a higher probability of assignment of the accessions within the clusters. Principal Coordinate Analysis (PCoA) showed a lack of clustering according to geographical origin. Information related to breeding patterns and geographic origin did not allow for a clear differentiation between the clusters according to the analysis of molecular variance (AMOVA). The results of this study will be useful for cassava germplasm conservation and breeding programs.