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      Utility of EST-SNP Markers for Improving Management and Use of Olive Genetic Resources: A Case Study at the Worldwide Olive Germplasm Bank of Córdoba

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          Abstract

          Olive, the emblematic Mediterranean fruit crop, owns a great varietal diversity, which is maintained in ex situ field collections, such as the World Olive Germplasm Bank of Córdoba (WOGBC), Spain. Accurate identification of WOGBC, one of the world’s largest collections, is essential for efficient management and use of olive germplasm. The present study is the first report of the use of a core set of 96 EST-SNP markers for the fingerprinting of 1273 accessions from 29 countries, including both field and new acquired accessions. The EST-SNP fingerprinting made possible the accurate identification of 668 different genotypes, including 148 detected among the new acquired accessions. Despite the overall high genetic diversity found at WOGBC, the EST-SNPs also revealed the presence of remarkable redundant germplasm mostly represented by synonymy cases within and between countries. This finding, together with the presence of homonymy cases, may reflect a continuous interchange of olive cultivars, as well as a common and general approach for their naming. The structure analysis revealed a certain geographic clustering of the analysed germplasm. The EST-SNP panel under study provides a powerful and accurate genotyping tool, allowing for the foundation of a common strategy for efficient safeguarding and management of olive genetic resources.

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          Inference of Population Structure Using Multilocus Genotype Data

          We describe a model-based clustering method for using multilocus genotype data to infer population structure and assign individuals to populations. We assume a model in which there are K populations (where K may be unknown), each of which is characterized by a set of allele frequencies at each locus. Individuals in the sample are assigned (probabilistically) to populations, or jointly to two or more populations if their genotypes indicate that they are admixed. Our model does not assume a particular mutation process, and it can be applied to most of the commonly used genetic markers, provided that they are not closely linked. Applications of our method include demonstrating the presence of population structure, assigning individuals to populations, studying hybrid zones, and identifying migrants and admixed individuals. We show that the method can produce highly accurate assignments using modest numbers of loci—e.g., seven microsatellite loci in an example using genotype data from an endangered bird species. The software used for this article is available from http://www.stats.ox.ac.uk/~pritch/home.html.
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            Detecting the number of clusters of individuals using the software structure: a simulation study

            The identification of genetically homogeneous groups of individuals is a long standing issue in population genetics. A recent Bayesian algorithm implemented in the software STRUCTURE allows the identification of such groups. However, the ability of this algorithm to detect the true number of clusters (K) in a sample of individuals when patterns of dispersal among populations are not homogeneous has not been tested. The goal of this study is to carry out such tests, using various dispersal scenarios from data generated with an individual-based model. We found that in most cases the estimated 'log probability of data' does not provide a correct estimation of the number of clusters, K. However, using an ad hoc statistic DeltaK based on the rate of change in the log probability of data between successive K values, we found that STRUCTURE accurately detects the uppermost hierarchical level of structure for the scenarios we tested. As might be expected, the results are sensitive to the type of genetic marker used (AFLP vs. microsatellite), the number of loci scored, the number of populations sampled, and the number of individuals typed in each sample.
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              STRUCTURE HARVESTER: a website and program for visualizing STRUCTURE output and implementing the Evanno method

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                Journal
                PLANCD
                Plants
                Plants
                MDPI AG
                2223-7747
                April 2022
                March 29 2022
                : 11
                : 7
                : 921
                Article
                10.3390/plants11070921
                35406901
                02e1ac7d-479b-43b7-8deb-71455825477a
                © 2022

                https://creativecommons.org/licenses/by/4.0/

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