A methodological approach to identify agro-biodiversity hotspots for priority <i>in situ</i> conservation of plant genetic resources

<div><p>Agro-biodiversity is seriously threatened worldwide and strategies to preserve it are dramatically required. We propose here a methodological approach aimed to identify areas with a high level of agro-biodiversity in which to set or enhance <i>in situ</i> conservation of plant genetic resources. These areas are identified using three criteria: Presence of Landrace diversity, Presence of wild species and Agro-ecosystem ecological diversity. A Restrictive and an Additive prioritization strategy has been applied on the entire Italian territory and has resulted in establishing nationwide 53 and 197 agro-biodiversity hotspots respectively. At present the strategies can easily be applied at a European level and can be helpful to develop conservation strategies everywhere.</p></div

A methodological approach to identify agro-biodiversity hotspots for priority <i>in situ</i> conservation of plant genetic resources - Fig 2

<p>Landrace density index (a) and Shannon index (b) relative to landraces recorded in Italy.</p

Threshold values for each index used to apply the RS and the AS prioritization strategies.

<p>Threshold values for each index used to apply the RS and the AS prioritization strategies.</p

Percentages of the most frequently recorded species cultivated as landraces in the MAPAs identified through the RS (black columns) and the AS (white columns) prioritization strategies.

<p>Percentages of the most frequently recorded species cultivated as landraces in the MAPAs identified through the RS (black columns) and the AS (white columns) prioritization strategies.</p

Quadrants progressively taken into consideration and finally identified as MAPAs by applying the two strategies.

<p>Quadrants with landrace diversity (LRD) (b, f, g): blue. Quadrants with wild species under threat (PWS) (c, h): purple. Quadrants with agro-ecosystem ecological diversity (AED) (d, i): green. Finally identified MAPAs quadrants (e, l): red.</p

Principal coordinate analysis (PCoA) of nuSSRs diversity among 345 Andean and Mesoamerican accessions of common bean from America and Europe.

<p>The samples are color coded according to their gene pool and the continent of origin as identified by Bayesian STRUCTURE analysis.</p

Evidence for Introduction Bottleneck and Extensive Inter-Gene Pool (Mesoamerica x Andes) Hybridization in the European Common Bean (<i>Phaseolus vulgaris</i> L.) Germplasm

<div><p>Common bean diversity within and between Mesoamerican and Andean gene pools was compared in 89 landraces from America and 256 landraces from Europe, to elucidate the effects of bottleneck of introduction and selection for adaptation during the expansion of common bean (<i>Phaseolus vulgaris</i> L.) in Europe. Thirteen highly polymorphic nuclear microsatellite markers (nuSSRs) were used to complement chloroplast microsatellite (cpSSRs) and nuclear markers (phaseolin and <i>Pv-shatterproof1</i>) data from previous studies. To verify the extent of the introduction bottleneck, inter-gene pool hybrids were distinguished from “pure” accessions. Hybrids were identified on the basis of recombination of gene pool specific cpSSR, phaseolin and <i>Pv-shatterproof1</i> markers with a Bayesian assignments based on nuSSRs, and with STRUCTURE admixture analysis. More hybrids were detected than previously, and their frequency was almost four times larger in Europe (40.2%) than in America (12.3%). The genetic bottleneck following the introduction into Europe was not evidenced in the analysis including all the accessions, but it was significant when estimated only with “pure” accessions, and five times larger for Mesoamerican than for Andean germplasm. The extensive inter-gene pool hybridization generated a large amount of genotypic diversity that mitigated the effects of the bottleneck that occurred when common bean was introduced in Europe. The implication for evolution and the advantages for common bean breeding are discussed.</p> </div

Distribution and type of the American accessions of <i>P. coccineus</i> used in the present study.

<p>Distribution and type of the American accessions of <i>P. coccineus</i> used in the present study.</p

European <em>Phaseolus coccineus</em> L. landraces: Population Structure and Adaptation, as Revealed by cpSSRs and Phenotypic Analyses

<div><p>Relatively few studies have extensively analysed the genetic diversity of the runner bean through molecular markers. Here, we used six chloroplast microsatellites (cpSSRs) to investigate the cytoplasmic diversity of 331 European domesticated accessions of the scarlet runner bean (<i>Phaseolus coccineus</i> L.), including the botanical varieties <i>albiflorus</i>, <i>bicolor</i> and <i>coccineus</i>, and a sample of 49 domesticated and wild accessions from Mesoamerica. We further explored the pattern of diversity of the European landraces using 12 phenotypic traits on 262 individuals. For 158 European accessions, we studied the relationships between cpSSR polymorphisms and phenotypic traits. Additionally, to gain insights into the role of gene flow and migration, for a subset of 115 accessions, we compared and contrasted the results obtained by cpSSRs and phenotypic traits with those obtained in a previous study with 12 nuclear microsatellites (nuSSRs). Our results suggest that both demographic and selective factors have roles in the shaping of the population genetic structure of the European runner bean. In particular, we infer the existence of a moderate-to-strong cytoplasmic bottleneck that followed the expansion of the crop into Europe, and we deduce multiple domestication events for this species. We also observe an adaptive population differentiation in the phenology across a latitudinal gradient, which suggests that selection led to the diversification of the runner bean in Europe. The botanical varieties <i>albiflorus</i>, <i>bicolor</i> and <i>coccineus</i>, which are based solely on flower colour, cannot be distinguished based on these cpSSRs and nuSSRs, nor according to the 12 quantitative traits.</p> </div

Cytoplasmic and nuclear genetic structure.

<p>Comparison between the different clusterings of the accessions as inferred by BAPS at K2 (A) and at K5 and K6 (B) for cpSSR and nuSSR data. Only accessions shared between Spataro <i>et al</i>. <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0057337#pone.0057337-Spataro1" target="_blank">[20]</a> and the present study (158) are included; (C) TFPGA tree based on cpSSR and nuSSR Kullback–Leibler divergence matrices, as obtained with BAPS analysis.</p