Computational protocol: Chloroplast Microsatellite Diversity in Phaseolus vulgaris

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Protocol publication

[…] The percentage of polymorphic loci, the average number of observed alleles per locus (Na), the effective number of alleles per locus (Ne; Kimura and Crow, ), the number of private alleles (Np), and the expected heterozygosity (He; Nei, ) estimates based on allele frequencies, were computed using the Arlequin software, version 3.5 (Excoffier and Lischer, ). The whole sample, and the following partitions of the accessions were considered for these analyses: P. coccineus; P. vulgaris; and within the common bean sample according to the gene pool, the Andean wild (AW), Mesoamerican wild (MW), and northern Peru and Ecuador (PhI) populations.The differences between the AW and MW populations for the genetic diversity estimates (Ne and He) were tested using Wilcoxon signed-ranks non-parametric test for two groups, arranged for paired observations (i.e., one pair of estimates for each locus; Wilcoxon, ; Sokal and Rohlf, ).An ad hoc statistic (ΔH) was used to compare the diversity between the two main gene pools (AW, MW); this estimate measures the loss of diversity of one population compared to another, and it was originally proposed by Vigouroux et al. (): ΔH = 1 − (HePOP1/HePOP2), where POP1 refers to the population that shows the lower level of genetic diversity (He) compared to the other population (POP2). [...] A Bayesian model-based approach that was implemented in the Bayesian analysis of population structure (BAPS) software, version 5.3 (Corander et al., ), was used to infer the hidden genetic population structure of the whole sample (109 P. vulgaris and 10 P. coccineus accessions), and thus to assign the genotypes into genetically structured groups/populations (K). A spatial genetic mixture analysis was conducted (Corander et al., ). This method uses a Markov chain Monte Carlo simulation approach to group samples into variable user-defined numbers (K) of clusters. The best partition of populations into K clusters is identified as the one with the highest marginal log-likelihood. We carried out 10 repetitions of the algorithm for each K ranging between 2 and 20.The genetic diversity statistics described above were also computed for the genetic groups highlighted by the BAPS analysis (hereafter referred to as clusters). The differences between the clusters identified according to the genetic diversity estimates (Ne, He) were tested using the Wilcoxon signed-ranks non-parametric test for two groups, arranged for paired observations (Wilcoxon, ; Sokal and Rohlf, ), and the Bonferroni correction for multiple comparisons. […]

Pipeline specifications

Software tools Arlequin, BAPS
Applications Phylogenetics, Population genetic analysis
Organisms Phaseolus vulgaris, Proteus vulgaris