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      Chloroplast Microsatellite Diversity in Phaseolus vulgaris

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          Abstract

          Evolutionary studies that are aimed at defining the processes behind the present level and organization of crop genetic diversity represent the fundamental bases for biodiversity conservation and use. A Mesoamerican origin of the common bean Phaseolus vulgaris was recently suggested through analysis of nucleotide polymorphism at the nuclear level. Here, we have used chloroplast microsatellites to investigate the origin of the common bean, on the basis of the specific characteristics of these markers (no recombination, haploid genome, uniparental inheritance), to validate these recent findings. Indeed, comparisons of the results obtained through analysis of nuclear and cytoplasmic DNA should allow the resolution of some of the contrasting information available on the evolutionary processes. The main outcomes of the present study are: (i) confirmation at the chloroplast level of the results obtained through nuclear data, further supporting the Mesoamerican origin of P. vulgaris, with central Mexico representing the cradle of its diversity; (ii) identification of a putative ancestral plastidial genome, which is characteristic of a group of accessions distributed from central Mexico to Peru, but which have not been highlighted beforehand through analyses at the nuclear level. Finally, the present study suggests that when a single species is analyzed, there is the need to take into account the complexity of the relationships between P. vulgaris and its closely related and partially intercrossable species P. coccineus and P. dumosus. Thus, the present study stresses the importance for the investigation of the speciation processes of these taxa through comparisons of both plastidial and nuclear variability. This knowledge will be fundamental not only from an evolutionary point of view, but also to put P. coccineus and P. dumosus germplasm to better use as a source of useful diversity for P. vulgaris breeding.

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            Estimation of average heterozygosity and genetic distance from a small number of individuals.

            M Nei (1978)
            The magnitudes of the systematic biases involved in sample heterozygosity and sample genetic distances are evaluated, and formulae for obtaining unbiased estimates of average heterozygosity and genetic distance are developed. It is also shown that the number of individuals to be used for estimating average heterozygosity can be very small if a large number of loci are studied and the average heterozygosity is low. The number of individuals to be used for estimating genetic distance can also be very small if the genetic distance is large and the average heterozygosity of the two species compared is low.
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              Enhanced Bayesian modelling in BAPS software for learning genetic structures of populations

              Background During the most recent decade many Bayesian statistical models and software for answering questions related to the genetic structure underlying population samples have appeared in the scientific literature. Most of these methods utilize molecular markers for the inferences, while some are also capable of handling DNA sequence data. In a number of earlier works, we have introduced an array of statistical methods for population genetic inference that are implemented in the software BAPS. However, the complexity of biological problems related to genetic structure analysis keeps increasing such that in many cases the current methods may provide either inappropriate or insufficient solutions. Results We discuss the necessity of enhancing the statistical approaches to face the challenges posed by the ever-increasing amounts of molecular data generated by scientists over a wide range of research areas and introduce an array of new statistical tools implemented in the most recent version of BAPS. With these methods it is possible, e.g., to fit genetic mixture models using user-specified numbers of clusters and to estimate levels of admixture under a genetic linkage model. Also, alleles representing a different ancestry compared to the average observed genomic positions can be tracked for the sampled individuals, and a priori specified hypotheses about genetic population structure can be directly compared using Bayes' theorem. In general, we have improved further the computational characteristics of the algorithms behind the methods implemented in BAPS facilitating the analyses of large and complex datasets. In particular, analysis of a single dataset can now be spread over multiple computers using a script interface to the software. Conclusion The Bayesian modelling methods introduced in this article represent an array of enhanced tools for learning the genetic structure of populations. Their implementations in the BAPS software are designed to meet the increasing need for analyzing large-scale population genetics data. The software is freely downloadable for Windows, Linux and Mac OS X systems at .
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                Author and article information

                Journal
                Front Plant Sci
                Front Plant Sci
                Front. Plant Sci.
                Frontiers in Plant Science
                Frontiers Media S.A.
                1664-462X
                27 November 2012
                22 January 2013
                2012
                : 3
                : 312
                Affiliations
                [1] 1Dipartimento di Scienze Agrarie, Alimentari ed Ambientali, Università Politecnica delle Marche Ancona, Italy
                [2] 2Dipartimento di Agraria, Università degli Studi di Sassari Sassari, Italy
                [3] 3Centro per la Conservazione e la Valorizzazione della Biodiversità Vegetale, Università degli Studi di Sassari Surigheddu, Alghero, Italy
                [4] 4Cereal Research Centre, Consiglio per la Ricerca e Sperimentazione in Agricoltura Foggia, Italy
                Author notes

                Edited by: Scott Jackson, University of Georgia, USA

                Reviewed by: Steven B. Cannon, United States Department of Agriculture, USA; Jeremy Coate, Cornell University, USA

                *Correspondence: L. Nanni, Dipartimento di Scienze Agrarie, Alimentari ed Ambientali, Università Politecnica delle Marche, Via Brecce Bianche, 60131 Ancona, Italy. e-mail: l.nanni@ 123456univpm.it

                This article was submitted to Frontiers in Plant Genetics and Genomics, a specialty of Frontiers in Plant Science.

                Article
                10.3389/fpls.2012.00312
                3551191
                23346091
                459cdbac-f027-4eee-ac6c-a8beac058755
                Copyright © 2013 Desiderio, Bitocchi, Bellucci, Rau, Rodriguez, Attene, Papa and Nanni.

                This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in other forums, provided the original authors and source are credited and subject to any copyright notices concerning any third-party graphics etc.

                History
                : 30 October 2012
                : 27 December 2012
                Page count
                Figures: 5, Tables: 9, Equations: 0, References: 66, Pages: 15, Words: 10914
                Categories
                Plant Science
                Original Research

                Plant science & Botany
                phaseolus,crop evolution,cpssr,recombination,population structure,speciation,introgression

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