Genetic Markers Analyses and Bioinformatic Approaches to Distinguish Between Olive Tree (Olea europaea L.) Cultivars

The genetic diversity of 22 olive tree cultivars ( Olea europaea L.) sampled from different Mediterranean countries was assessed using 5 SNP markers (FAD2.1; FAD2.3; CALC; SOD and ANTHO3) located in four different genes. The genotyping analysis of the 22 cultivars with 5 SNP loci revealed 11 alleles...

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Bibliographic Details
Published in:Interdisciplinary sciences : computational life sciences 2016-12, Vol.8 (4), p.366-373
Main Authors: Ben Ayed, Rayda, Ben Hassen, Hanen, Ennouri, Karim, Rebai, Ahmed
Format: Article
Language:English
Subjects:
Alleles
Bioinformatics
Biomedical and Life Sciences
Clustering
Computation
Computational Biology - methods
Computational Biology/Bioinformatics
Computational Science and Engineering
Computer Appl. in Life Sciences
Correlation coefficient
Correlation coefficients
Cultivars
Fruit trees
Genetic analysis
Genetic diversity
Genetic markers
Genetic Markers - genetics
Genetics
Genotype
Genotypes
Genotyping
Health Sciences
Life Sciences
Markers
Mathematical and Computational Physics
Mathematical models
Medicine
Oils & fats
Olea - classification
Olea - genetics
Olea europaea
Olive oil
Olives
Original Research Article
Phylogeny
Similarity
Single-nucleotide polymorphism
Statistics for Life Sciences
Theoretical
Theoretical and Computational Chemistry
Trees
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Description
Summary:The genetic diversity of 22 olive tree cultivars ( Olea europaea L.) sampled from different Mediterranean countries was assessed using 5 SNP markers (FAD2.1; FAD2.3; CALC; SOD and ANTHO3) located in four different genes. The genotyping analysis of the 22 cultivars with 5 SNP loci revealed 11 alleles (average 2.2 per allele). The dendrogram based on cultivar genotypes revealed three clusters consistent with the cultivars classification. Besides, the results obtained with the five SNPs were compared to those obtained with the SSR markers using bioinformatic analyses and by computing a cophenetic correlation coefficient, indicating the usefulness of the UPGMA method for clustering plant genotypes. Based on principal coordinate analysis using a similarity matrix, the first two coordinates, revealed 54.94 % of the total variance. This work provides a more comprehensive explanation of the diversity available in Tunisia olive cultivars, and an important contribution for olive breeding and olive oil authenticity.
ISSN:1913-2751
1867-1462
DOI:10.1007/s12539-016-0155-x