Morphological and genetic diversity among and within common bean (Phaseolus vulgaris L.) landraces from the Campania region (Southern Italy)

Scientia Horticulturae 180 (2014) 72–78

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Morphological and genetic diversity among and within common bean (Phaseolus vulgaris L.) landraces from the Campania region (Southern Italy) Daria Scarano a , Fernando Rubio b , Juan José Ruiz b , Rosa Rao a , Giandomenico Corrado a,∗ a b

Dipartimento di Agraria, Università di Napoli Federico II, Portici, NA, Italy Department of Applied Biology, Miguel Hernandez University of Orihuela, Orihuela, Spain

a r t i c l e

i n f o

Article history: Received 3 May 2014 Received in revised form 3 October 2014 Accepted 9 October 2014 Keywords: SSR Diversity Phenotypic variation Genetic resources

a b s t r a c t The common bean (Phaseolus vulgaris L.) is arguably the most important food legume and a fundamental source of proteins especially for rural societies. In several countries, this species is characterized by a number of locally adapted landraces and many of them are at risk of extinction. In Italy, common bean cultivation has always been a typical element of rural economies especially in the Southern regions. We carried out an investigation of the morphological and genetic diversity in 25 common bean populations cultivated in the Campania region (Southern Italy). We analyzed 26 qualitative and 11 quantitative traits following the IPGRI descriptors. Furthermore, 10 SSRs were employed to examine genetic polymorphism, differentiation and population structure. Molecular and morphological data distinguished all the landraces under investigation. A considerable phenotypic diversity among landraces was observed for many characters, including some related to agronomical performance. At molecular level, all the SSRs were polymorphic, with an average of 8.5 alleles per locus. Moreover, the vast majority of the landraces (92%) displayed intra-varietal differences. Our work indicated the presence of a wide-ranging variation among and within cultivated common bean landraces. Moreover, it provided evidence that the implementation of measures for their on-farm conservation, management and promotion should be useful also to preserve genetic variability. © 2014 Elsevier B.V. All rights reserved.

1. Introduction Common bean (Phaseolus vulgaris L.) is a world-wide cultivated legume of agricultural interest in many countries (Lioi and Piergiovanni, 2013). In Italy, it represents the main grain legume for direct human consumption. Common bean was introduced into Italy from the New World in the 16th century (Bitocchi et al., 2012; Piergiovanni and Lioi, 2010). The first documentation dates to 1532 and refers to a donation of seeds from the Spanish Emperor Charles V to the Pope Clemente VII (Lioi and Piergiovanni, 2013). Since its introduction into Europe, this species has experienced an adaptive radiation being, for instance, cultivated for the production of dry seeds, shell seeds and green pods (Angioi et al., 2010; Lioi and Piergiovanni, 2013). Bean diversification can be ascribed to different factors such as the need for adaptation to the soil type and climatic conditions of new

∗ Corresponding author. Tel.: +39 0812539446. E-mail addresses: [email protected], [email protected] (G. Corrado). http://dx.doi.org/10.1016/j.scienta.2014.10.013 0304-4238/© 2014 Elsevier B.V. All rights reserved.

environments, the geographical isolation of several growing areas, the cultivation technique (e.g. the frequent consociation with local maize varieties) as well as aesthetical and organoleptic preferences of specific areas. In Mediterranean countries, common bean cultivation is present nearly in all the traditional agricultural settings (Lioi and Piergiovanni, 2013; Negri and Tosti, 2002). The strong link between rural agriculture and common bean has given rise to landraces that are frequently associated to restricted areas (Negri and Tosti, 2002; Piergiovanni and Lioi, 2010). During the last decades, in Italy as well as in other developed European countries, the cultivated area of P. vulgaris has declined because of economic (e.g. low competitiveness, decreasing price on the international market), social (e.g. larger availability of animal proteins, its strong identification with a rural diet) and technical reasons (e.g. diffusion of fertilizers, mono-culture and mechanical harvesting). This reduction has been particularly evident for elite cultivars that replaced traditional varieties after WWII, while in several Italian cropping areas, farmers still maintain in cultivation common bean landraces (Lioi et al., 2005; Marotti et al., 2007; Negri and Tosti, 2002; Piergiovanni and Lioi, 2010).

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Currently, modern nutritional recommendations inspired by the traditional dietary patterns of Greece, Spain, Portugal and Southern Italy have increased the value of legumes as healthy source of proteins. Moreover, consumers are more attracted by agricultural and food products that are distinguished from others by certain characteristics, qualities or reputations that derive from their geographical origin. For all these reasons, traditional common bean varieties are receiving a growing attention from both consumers and policy makers (Piergiovanni and Lioi, 2010). The primary policy goal for conservation and exploitation of agricultural biodiversity should focus on the assessment of the existing diversity not only between but also within landraces (Esquinas-Alcazar, 2005). This effort is essential to prospect strategies for the implementation of adequate on-farm conservation schemes and it is as a prerequisite for the possible development of breeding programs (Esquinas-Alcazar, 2005; Huang et al., 2010). The evaluation of morphological traits is a traditional, important method for the description and the determination of relationship among common bean landraces (Skroch and Nienhuis, 1995). In addition, molecular analysis provides additional information that is independent of environmental effects and in P. vulgaris, it has proved to be a valuable tool for association mapping and the study of genetic diversity, population structure and phylogenetic relationships (Beebe et al., 1995; Bitocchi et al., 2012; Blair et al., 2009; Metais et al., 2000; Shi et al., 2011). Moreover, DNA analyses of plant genetic resources are valuable to identify duplicate accessions in core collections and possible cases of homonymy and synonymy in cultivated landraces (Corrado et al., 2014; Rao et al., 2009). In Italy, the common bean cultivation has always been a typical element of rural economies especially in the Southern regions (Piergiovanni and Lioi, 2010). In those areas, common bean is probably the horticultural crop with the highest number of landraces (Perrino et al., 1984). The germplasm of different Italian regions has been characterized (Lioi et al., 2012; Mercati et al., 2013; Piergiovanni and Lioi, 2010; Raggi et al., 2013), but despite the long history of cultivation, the number of accessions (Hammer et al., 1989) and the presence of some well-known landraces that excel for product quality (e.g. “di Controne”, “Dente di Morto”), the germplasm of the Campania region (Southern Italy) has been poorly investigated. The aim of this study was to collect, characterize and evaluate the diversity of traditional common beans that are cultivated in the Campania region (Southern Italy) using morphological and molecular data.

2. Materials and methods 2.1. Plant material and its description The study took place at the Genetics’ Experimental Station of the Faculty of Agricultural Science, University of Naples Federico II (Portici, Italy), during the 2012–2013 period. The investigation was performed on 25 common bean landraces (P. vulgaris L.) from different geographic areas of the Campania region (Table 1). Collected seeds were not multiplied before trials. The morphological characterization was done according to the IPGRI recommendations, including the number of replications (IPGRI, 1982). Briefly, we recorded a number of highly hereditable characters selected as being easily seen and expressed in all environments (IPGRI, 1982). In total, we analyzed 26 qualitative and 11 quantitative traits. Traits under investigation, along with their IPGRI code, are reported in Supplementary Tables 2 and 3.

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Table 1 List of the landraces investigated, their code and site of collection/growing area. AV: Avellino; BN: Benevento; NA: Naples; SA: Salerno. Code

Name

Site of collection/growing area

Province

BM C DM EU F MI MP OC OS P1 P2 P3 P4 P5 R RG RL RO SI TBC TC TV V ZI ZO

Bianco di Controne Dente di Morto Dente di Morto a Formella Mustacciello Mustacciello Occhio nero Occhio nero Sel Pirolo 1 Sel Pirolo 2 Sel Pirolo 3 Sel Pirolo 4 Sel Pirolo 5 della Regina della Regina (di Gorga) della Regina Cannellino Romano Screziato impalato Tondino bianco Tondo Tondino Cannellino Viscardi Zampognaro d’Ischia Zolfariello

Montefalcone Controne Marigliano Acerra Visciano Ischia Pimonte Oliveto Citra alta valle del Sele Acerra Acerra Acerra Acerra Acerra Casalbuono Stio San Lupo Agro-acerrano-nolano Castellabate Caposele Caposele Villaricca Agro-acerrano-nolano Ischia Visciano

BN SA NA NA NA NA NA SA SA NA NA NA NA NA SA SA BN NA SA SA SA NA NA NA NA

2.2. Analysis of morphological data Qualitative characters were transformed into dummy binary attributes as reported (Romesburg, 2004). Pairwise similarities between landraces were calculated by using the Jaccard similarity coefficient (Sneath and Sokal, 1973). Variability of the quantitative traits between and within landraces was evaluated calculating the coefficient of variation (i.e. the absolute value of the standard deviation of the mean/mean). This coefficient ranges from 0 to 1. For continuous variables, pairwise dissimilarity coefficients were computed using squared Euclidean distances after standardization of mean values (Sneath and Sokal, 1973). To calculate the standardized value Zij for the ith attribute and jth object, we subtracted the mean of the values of the ith attribute from the corresponding value Xij in the data matrix and divided the result by the standard deviation of the values of the ith attribute. On the basis of each resemblance matrix, landraces were clustered by the unweighted pair-group method with arithmetic averages (UPGMA) (Sneath and Sokal, 1973). A cophenetic value matrix (Sneath and Sokal, 1973) of the UPGMA clustering was also used to test for the goodness-of-fit of the clustering to the resemblance matrix on which it was based, by computing the product-moment correlation coefficient (r) with 1000 permutations (Rohlf and Fisher, 1968). These analyses were conducted using the NTSYSpc v. 2.1 package (Rohlf, 1998). 2.3. SSR analysis Total DNA was isolated from leaves using a previously reported procedure (Caramante et al., 2009). We analyzed three plants per landrace. Ten SSR loci were used for PCR amplification (Buso et al., 2006; Gaitan-Solis et al., 2002; Grisi et al., 2007; Hanai et al., 2010; Yu et al., 2000). SSR features, primer sequences and annealing temperature (Ta ) are reported in Supplementary Table 1. PCR was performed in a 25 ␮l volume containing 20 ng genomic DNA, 1.5 mM MgCl2 , 100 mM dNTPs, 0.2 mM fluorescently labeled forward primer and unlabeled reverse primer, and 0.5 U Taq DNA polymerase (Promega) in 1× PCR buffer. The amplification conditions were: one denaturing step at 94 ◦ C for 5 min, followed by 35 cycles of 94 ◦ C for 45 s, Ta ◦ C for 45 s and 72 ◦ C for 1 min 30 s. After

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the final cycle, a 5 min step at 72 ◦ C was added. Amplification products were separated by agarose gel-electrophoresis to verify the presence of amplified fragments. For allelic discrimination, the fluorescent fragments were resolved by capillary electrophoresis and detected in an ABI Prism 3130 Genetic Analyzer system (Applied Biosystems). Signal peak height and allele sizes were scored using the Gene Mapper 4.0 software (Applied Biosystems) on the basis of the GeneScan 500Liz molecular weight standard (Applied Biosystems).

closest match possible and then averaged across replicates, using the Greedy algorithm of the software CLUMMP (Jakobsson and Rosenberg, 2007). To validate the estimated population structure, we calculated pairwise Fst between populations using MicroSatellite Analyzer (Dieringer and Schlotterer, 2003). Null distribution for p-value estimation was obtained from 10,000 permutations. 3. Results 3.1. Morphological characterization

2.4. Molecular data analysis For each SSR locus, we calculated the number of different alleles, the Shannon’s information index (−1 × Sum (pi × ln(pi )), the observed heterozygosity (Ho ; number of heterozygotes/N), the polymorphic information content (PIC; 1 − Sum pi 2 , equivalent to the expected heterozygosity) and the fixation index, where N is number of individuals, pi the frequency of the ith allele for the population and (Sum pi 2 ) represent the sum of the squared population allele frequencies. The detected intra-landraces variability (DILV) per SSR represents the percentage of within-landraces polymorphic loci. Analysis of Molecular Variance (AMOVA) was carried out using a distance matrix and suppressing within individual analysis. Permutations (999) were used to test for significance. All these calculations were performed using the Genalex 6.5 software (Peakall and Smouse, 2012). Population structure was estimated using a model-based Bayesian procedure implemented in the software Structure v2.3 (Pritchard et al., 2000) with the aid of Structure Harvester (Earl and Vonholdt, 2012), using previously reported settings (Corrado et al., 2013). The most informative number of subpopulations was identified using the K method (Evanno et al., 2005). The estimated cluster membership coefficient matrices of the 20 runs were permuted so that all replicates have the

Twenty-six binary or multistate characters were examined in 25 common bean landraces. Six traits were not polymorphic, while the remaining showed a considerable level of variation (Supplementary Table 2). All the landraces could be distinguished by at least one character. Taking into account the polymorphic characters, fortyone different IPGRI morphological phenotypes (out of a total of 65) were present. Sixteen landraces possessed at least one unique phenotype (i.e. not present in the other landraces). Considering the number of IPGRI-phenotypic classes that were covered, a trait that displayed a remarkable variability was the dry pod colour. Large differences were also present for the dry seed colour and shape (Lioi and Piergiovanni, 2013) and the most frequent bean colour was white (Fig. 1). Polymorphic qualitative data were used to cluster landraces. The average (±s.d.) of Jaccard’s pair-wise similarity coefficients was 0.37 (±0.12) and ranged from a minimum of 0.11 to 0.81. Similarity coefficients were used to build a dendrogram using the UPGMA algorithm (Fig. 2A). The cophenetic correlation coefficient was good and significant (r = 0.79; p < 0.01). This analysis indicated that the nine landraces with large white kidney shape beans clustered together. Despite having a different seed colours, the two landraces originating in the Ischia Island (MI and ZI) clustered together.

Fig. 1. Dry beans of the 25 landraces under investigation. For landrace codes see Table 1. Scale bar: 1 cm.

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Fig. 2. Hierarchical cluster analysis of the 25 landraces based on qualitative (A) or quantitative (B) traits. (A) UPGMA cluster based on similarities calculated with the Jaccard coefficient. (B) UPGMA dendrogram based on Squared Eculidean Distances calculated on normalized quantitative data (Z-scores). For landrace codes see Table 1. See Supplementary Tables 2 and 3 for data.

The analysis of 11 quantitative traits is reported in Supplementary Table 3. The data indicated a widespread variability among landraces (the average coefficient of variation was 0.25; Table 2), including variables that are considered the main components of been productivity (pods per plant, seeds per pod and weight of 100 seeds) (Nienhuis and Singh, 1986). The traits “pods per plants” and “racemes per plants” had the higher coefficient of variation between landraces and, as average, also within each landrace. The landraces with the higher average coefficient of variation of the traits analyzed were TO and TBC. To group landraces, dissimilarities were calculated based on the squared Euclidean distances. These are insensitive to additive and proportional translation. A dendrogram was built using the UPGMA algorithm (Fig. 2B). The correlation between Euclidean dissimilarities and ultrametric distances was high and significant (r = 0.89; p < 0.01). Although the correlation between qualitative and standardized quantitative data was very low and not significant (r = 0.11; p > 0.05), landraces with white kidney shaped beans formed one cluster, with the exception of the P1 and P3.

Table 2 Variation in quantitative traits among the 25 landraces. For each trait, the table reports the coefficient of variation (CV) and the maximum (max), average (mean) and minimum (min) value of the 11 quantitative traits analyzed. Trait

CV

Max

Mean

Min

Leaflet lenght (cm) Racemes per plant Pods per plant Pod lenght Pod beak lenght (mm) Locules per pod Seeds per pod Seed lenght (mm) Seed height (mm) Seed widht (mm) Seed weight (g)

0.24 0.40 0.34 0.23 0.29 0.23 0.22 0.22 0.12 0.20 0.26

7.8 6.4 5.9 163.4 41.0 7.6 6.6 15.9 9.0 5.9 67.9

5.49 2.59 3.08 100.12 25.53 4.14 3.87 12.40 6.85 4.36 46.09

3.4 0.8 1.6 67.4 14.0 2.6 2.8 7.2 5.0 2.8 19.3

3.2. Molecular characterization An analysis of the genetic diversity was carried out using 10 SSRs selected from the literature. All these loci were polymorphic in our germplasm collection. Main genetic parameters of the population under investigation are presented in Table 3. We detected 85 alleles, whose length ranged from 100 to 314 bp. Large differences were present in the number of alleles per locus, which ranged from 2 (PVBR5) to 15 (PVBR163). We did not observe a significant difference (p > 0.05; Mann-Whitney test) between the number of alleles of transcribed vs untranscribed SSRs (Supplementary Table 1). As anticipated for a selfing species, the observed heterozygosity was very low (on average, 6%), except for the BM188 and PVBR163 loci. The latter is one of the three loci that have been described as associated to QTLs (the others being PVBR5 and PVBR14) (Wright and Kelly, 2011). The PVBR163 locus had the higher diversity, number of alleles and PIC. A significant correlation between the number of alleles per locus and its observed heterozygosity was not present (p > 0.05; Spearman’s Rho). For instance, two (PVat007 and PvM115) of the tree loci that were homozygous in all samples had a number of allele well above the average. Allele frequency spanned from a maximum value of 0.813 (PVBR5) to a minimum of 0.007 for two alleles of the BM143 locus. These two rare alleles are present only in one plant of the RG landrace. The locus with the lower minor allele frequency (MAF) was PVBR163. Considerable differences among SSRs were also present in the PIC, which ranged from 0.30 (PVBR5) to 0.89 (PVBR163). The former has the lowest number of diversity, number of alleles, and PIC. PIC significantly correlated with the number of alleles per SSR (p < 0.01; Spearman’s Rho). The Fixation index showed substantial positive values and limited differences among SSRs. All the employed SSRs were able to detect intra-landraces variability, although with a different efficiency (Table 3). The locus with the higher (resp. lower) number of alleles was PVBR163 (resp. PVBR5). On average, intra-landraces variability was detected at 3.12 loci but varied largely among landraces (s.e.: 0.48). Two landraces (MI and OS) did not display genetic variability at the tested loci. On

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Table 3 Main genetic indices of the common bean landraces obtained by SSR analysis. Na: number of different alleles; I: Shannon’s information index; MAF: major allele frequency; Ho : observed heterozygosity; PIC: polymorphic information content; F: fixation index; DILV: detected intra-landrace variability. Locus

Na

Size range (bp)

I

MAF

Ho

PIC

F

DILV (%)

PVBR5 PVBR14 PVBR20 PVBR25 BM188 GATS91 BM143 PVat007 PVBR163 PVM115 Average Standard error

2 3 3 11 5 8 11 13 15 14 8.5 1.6

171–179 164–180 163–181 136–172 163–184 226–258 116–184 100–224 192–314 112–188

0.48 0.61 0.59 1.80 1.56 1.75 1.78 2.14 2.41 2.03 1.52 0.22

0.81 0.78 0.78 0.40 0.31 0.31 0.36 0.31 0.17 0.37 0.46 0.07

0.00 0.04 0.04 0.00 0.26 0.03 0.01 0.00 0.25 0.00 0.06 0.03

0.30 0.35 0.35 0.77 0.78 0.79 0.77 0.84 0.89 0.80 0.67 0.07

1.00 0.89 0.89 1.00 0.67 0.97 0.98 1.00 0.72 1.00 0.91 0.04

8 16 16 24 48 44 28 40 80 40 34 6.6

Table 4 Analysis of molecular variance among and within landraces. Df: degree of freedom; SS: sum of squares calculated from a square genetic distance matrix; Est. Var.: estimated variance. Source

df

SS

Est. Var.

Among landraces Within landraces

24 125

365.68 135.83

2.36 1.09

% 68 32

Total

149

501.51

3.44

100

the contrary, the three plants of the TBC landrace had at least one different allelic profile at each of the 10 SSR loci. To hierarchical partition genetic variation among landraces, we used the AMOVA statistical procedure. The results indicated that a considerable fraction of genetic variation (32%) was present within landraces (Table 4). Furthermore, Fst analysis was used to ascertain the degree of genetic differentiation among landraces (Supplementary Table 4). Out of the 300 possible pairwise combinations, 13 were not significant (p > 0.05). Briefly, the non-significant Fst values were obtained for comparisons that involved landraces with the same seed type (e.g. kidney-shaped white beans). 3.3. Genetic structure analysis The identification of genetically similar groups of plants was performed using an admixture model-based clustering analysis implemented in the software Structure. The Evanno’s test indicated that the most informative number of subpopulations (K) is 3 (Fig. 3). The inferred population structure is presented in Fig. 4.

Fig. 3. Estimation of the optimum number of clusters for the common bean genotypes according to the Evanno’s method. The graph displays the DeltaK [mean (lL” (K)l/SD(L(K))] for each K value.

The groups defined by the Structure’s analysis represent statistically different subpopulations, as indicated by the evaluation of genetic differentiation (Supplementary Table 5). One subpopulation (Fig. 4, blue) comprised landraces with large white beans, such as the Cannellino, Dente di Morto and also the MP. The latter has white-dark broadly stripped beans. For the other two subpopulations, a clear distinction according to the area of origin or seed traits was not evident. Nonetheless, 95% of the samples had a membership coefficient higher than 0.8 (Supplementary Table 6), indicating that the vast majority of the genotypes were strongly assigned to subpopulations. At K = 3, the three analyzed plants per landrace were attributed to the same subpopulation (Supplementary Table 6), suggesting that the genetic differences within landraces represent true landrace variability. The only exception was the TBC. For this landrace, the plants were assigned to three different subpopulations, implying possible mixture of seeds or very strong genetic admixture. 4. Discussion Different regions of Southern Italy are considered rich of traditional varieties of horticultural species, including common bean (Hammer et al., 1989; Perrino et al., 1984). In the Campania region, there are several common bean types frequently reported in grey literature and archival materials but a systematic evaluation has not yet been carried out. Common bean types are traditionally classified according to their origin, use and features of the seed but the local denomination does not always express true genetic distinction (Negri and Tosti, 2002). According to our morphological analysis, local names were in many instances correctly related to seed colour or shape, such as Dente di Morto (dead man’s tooth), Solfariello (sulphurous, yellowish), Formella (in Neapolitan language the “formella” is the button) and dell’occhio (eye-shaped). The evaluation of phenotypic variation in common bean is crucial in determining adaptation, agronomic potential and breeding value of landraces. Many of the characters analyzed here presented a considerable phenotypic diversity among the genotypes. All the traditional varieties could be distinguished by at least one character, suggesting a significant diversification of the crop in the Campania region. Considering the bean cultivars that are commonly available on the market, many landraces were easily distinguishable especially considering seed morphology. Landraces displayed a potentially interesting variation also in traits that are related to productivity such as pods per plants. Although a spectrum of bean phenotypes was present (Lioi and Piergiovanni, 2013), the most frequent seed colour was white. It is likely that its diffusion is because Italian consumers associate this colour with a thin tegument and higher digestibility. In addition, the qualitative and quantitative phenotypic measurements were consistent in indicating a cluster of landraces with white large seeds. Overall, the

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Fig. 4. Estimated population structure of the the common bean landraces for K = 3 (see also Fig. 3). Each genotype is represented by a vertical line, which is partitioned into colored segments that represent the estimated membership fractions in the three clusters. (For interpretation of the references to color in this figure legend, the reader is referred to the web version of this article.)

plant and seed phenotypes provided an identity to each landrace, although this could be achieved by scoring several descriptors. The number of alleles and a locus-specific allelic richness revealed the presence of a diffuse genetic variation. An estimated outcrossing of 6% can be inferred considering the average observed heterozygosity. This value is similar to that reported by Free (1970) (8%). Cross-fertilization is expected to occur more frequently between accessions with overlapping flowering periods and therefore, our estimate may be affected by the fact that (genetically) similar accessions are more likely to inter-cross. Of the two loci that displayed the highest Observed Heterozigosity (PVBR163 and BM188), the former was associated to a QTL related to plant height (Wright and Kelly, 2011). Almost all landraces (23 out of 25) displayed genetic variability. It is expected that garden-forms of common bean (i.e.: very roughly, those cultivated in few hundreds plants) tend to reach rapidly homogeneity, because fewer than a dozen plants per year will be sufficient to produce seeds (Maxted et al., 2011). We analyzed landraces that are still cultivated for local markets, thus making more likely the presence of some genetic variability. The AMOVA showed that a significant part of the genetic variation is present within landraces, indicating that, despite autogamy, the analysis of genetic variability on a single plant per landrace may provide limited information. Furthermore, the DNA analysis implies that measures to support on-farm conservation of common bean would be effective to preserve genetic variability (Corrado et al., 2014; Negri and Tosti, 2002). The observed subpopulation structure indicated that our germplasm collection could be clearly subdivided in three subpopulations. The membership coefficient of the genotypes to specific sub-populations was very high and possible admixture was detected in a reduced number of landraces. It is likely that the high self-pollination rate of bean, along with the fact that the cultivation of traditional variety is usually restricted to specific agricultural settings, contribute significantly to these features. Moreover, local farmers do not usually select beans considering yield (Zeven, 1997), but their distinctive visible features, making more likely a maintenance breeding. Of the three subpopulations identified, one associated to the kidney-shaped white beans. Taking also into account the morphological analysis, it is possible to deduce that traditional varieties named Dente di Morto, Cannellino and other selections present in the same area share a recent common ancestor and should be considered a landrace group (Zeven, 1998), that is either one landrace derives from another one or the landraces derive from the same parent population. Pairwise analysis of Fst supported this hypothesis, since a lack of a statistically significant genetic differentiation was present only for some comparisons between landraces with similar bean shape and colour. On the other hand, the Regina (in English: Queen) types, despite their

common name, were clearly different. It is worth to add that according to the legendary origin of these landraces, the three Regina’s beans under investigation refer to different queens, indicating that not only folk taxonomy but also historical information is useful to facilitate the understanding of traditional varieties (Teshome et al., 1997). In conclusion, the combined use of molecular and morphological markers allowed a detailed description of the variability present in our collection. As some of the traits are linked to agronomic performance, our data allow an informed choice of the varieties to be further investigated for nutritional and breeding value. Despite a low estimated rate of outcrossing and admixture, common beans from Campania comprise an appreciable level of inter- and intralandrace diversity both at morphological and molecular level, a result that needs to be considered when planning conservation strategies or breeding programmes. These traditional varieties still have a market share and many are receiving increasing support from local institutions as vital component of food tourism in rural areas (e.g. food festivals). For that reason, the here presented characterization is also an essential step to (re-)establish quality brands associated with traditional common bean varieties. Acknowledgments This work was supported by the “Salvaguardia della biodiversità agroalimentare in Campania” (SALVE) project, Programma di Sviluppo Rurale per la Campania 2007–2013, misura 214 az. f2 (Regolamento CE no. 1698/2005 del Consiglio del 20 settembre 2005). Appendix A. Supplementary data Supplementary data associated with this article can be found, in the online version, at http://dx.doi.org/10.1016/j.scienta. 2014.10.013. References Angioi, S.A., Rau, D., Attene, G., Nanni, L., Bellucci, E., Logozzo, G., Negri, V., Zeuli, P.L.S., Papa, R., 2010. Beans in Europe: origin and structure of the European landraces of Phaseulus vulgaris L. Theor. Appl. Genet. 121, 829–843. Beebe, S.E., Ochoa, I., Skroch, P., Nienhuis, J., Tivang, J., 1995. Genetic diversity among common bean breeding lines developed for Central-America. Crop Sci. 35, 1178–1183. Bitocchi, E., Nanni, L., Bellucci, E., Rossi, M., Giardini, A., Zeuli, P.S., Logozzo, G., Stougaard, J., McClean, P., Attene, G., Papa, R., 2012. Mesoamerican origin of the common bean (Phaseulus vulgaris L.) is revealed by sequence data. Proc. Natl. Acad. Sci. U.S.A. 109, E788–E796. Blair, M.W., Diaz, L.M., Buendia, H.F., Duque, M.C., 2009. Genetic diversity, seed size associations and population structure of a core collection of common beans (Phaseulus vulgaris L.). Theor. Appl. Genet. 119, 955–972.

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