Next Article in Journal
ViT-SmartAgri: Vision Transformer and Smartphone-Based Plant Disease Detection for Smart Agriculture
Previous Article in Journal
Effect of Swathing or Direct Combining on Yield, Seed Losses and Costs of Camelina
 
 
Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
Journals
Agronomy
Volume 14
Issue 2
10.3390/agronomy14020326
agronomy-logo
Submit to this Journal Review for this Journal Propose a Special Issue
► Article Menu

Article Menu

share Share announcement Help format_quote Cite question_answer Discuss in SciProfiles thumb_up
...
Endorse textsms
...
Comment
first_page
settings
Order Article Reprints
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Article

Cross-Species Transferability of SSR Markers for Analyzing Genetic Diversity of Different Vicia species Collections

by
María Isabel López-Román
1,
Lucía De la Rosa
2,
Teresa Marcos-Prado
2 and
Elena Ramírez-Parra
1,*
1
Centro de Biotecnología y Genómica de Plantas, Instituto Nacional de Investigación y Tecnología Agraria y Alimentaria, Consejo Superior de Investigaciones Científicas—(CBGP, UPM-INIA/CSIC), Universidad Politécnica de Madrid, Campus de Montegancedo, Pozuelo de Alarcón, 28223 Madrid, Spain
2
Centro de Recursos Fitogenéticos, Instituto Nacional de Investigación y Tecnología Agraria y Alimentaria, Consejo Superior de Investigaciones Científicas—(CRF-INIA/CSIC), Alcalá de Henares, 28805 Madrid, Spain
*
Author to whom correspondence should be addressed.
Agronomy 2024, 14(2), 326; https://doi.org/10.3390/agronomy14020326
Submission received: 12 January 2024 / Revised: 29 January 2024 / Accepted: 31 January 2024 / Published: 2 February 2024
(This article belongs to the Special Issue Genetic Diversity and Breeding Strategies for Improving Yield in Legumes)
Browse Figures
Versions Notes

Abstract

:
Legumes play an essential role in sustainable agriculture due to their ability to fix nitrogen and high protein content. Vicia is a relevant genus of the Fabaceae family that includes important crop species, such as V. faba and V. sativa, but also other species considered minor crops. They are mainly used as animal feed and usually cope resiliently with extreme conditions; therefore, they could play an essential role in sustainable agriculture under the present scenario of climate change and growing population. However, the scarcity of commercial cultivars limits their use. The Spanish National Plant Genetic Resources Center has collections of several species of the genus Vicia, including international landraces, which could be an essential source of biodiversity for breeding programs. These seed resources are underutilized due to the limited availability of characterization data, including the lack of molecular markers for these species. In this study, we analyzed the cross-transferability of SSR (simple sequence repeat) molecular markers from V. sativa and V. ervilia to distinct species of the genus Vicia. We also used heterologous validated markers for the genotypic characterization and genetic diversity analysis of almost 500 accessions of three undercharacterized Vicia collections: V. articulata (one-flower vetch), V. ervilia (bitter vetch), and V. narbonensis (narbon bean or French vetch). Subsequently, these molecular data were integrated with passport and agromorphological data to select representative varieties from these Vicia collections and establish core collections, with minimum loss of genetic diversity versus the Spanish total collections. The characterization of these legume collections is an essential step from an economic and ecological point of view to obtain selected Vicia varieties to be used in sustainable agriculture.

1. Introduction

Legumes are the main source of vegetable protein for humans and livestock. Furthermore, their ability to perform symbiotic nitrogen fixation makes them beneficial for sustainable agricultural systems [1]. Within legumes, the botanical tribe Viceae, from the family Fabaceae (subfamily Papilionoideae), includes some important genera of agricultural relevance such as Pisum, Lens, Lathyrus, and Vicia [2].
Regarding the genus Vicia, its center of origin and diversification has been placed in the Mediterranean and Irano-Turanian regions [3]. However, Vicia species are nowadays distributed throughout temperate regions of the northern hemisphere in Europe, Asia, and North America and in nontropical regions in South America [4]. The genus includes over 34 cultivated species of great economic and environmental relevance, such as V. faba L., and V. sativa L., which are mainly grown as feedstuff (grain and forage), green manure, or cover crops, but also other minority species that have also had agronomic use, such as V. articulata Hormen, V. narbonensis L., or V. ervilia (L.) Willd., used as seeds for animal feed, or V. benghalensis L., V. pannonica Crantz, and V. villosa Roth, used as forage, among others [5]. Nowadays, these species could be recovered, apart from the direct use, by its ecological interest. Despite the relevance of the genus Vicia, there is a scarcity of commercial cultivars and certified seeds for crop sowing.
Genebanks play a crucial role in preserving the natural genetic diversity of these species, which may prove essential to obtain the traits required to combat diseases or emerging pests or to adapt to new and changing climatic conditions [6,7,8], but in many cases, the use of genetic resources can be limited by the absence of their genetic diversity characterization and the lack of evaluation of traits of agronomic interest [9]. The characterization, both genotypic and phenotypic, of these resources is essential to rationalize and promote the use of these collections, including those of the genus Vicia, allowing the selection of local varieties or landraces to be used directly by farmers or incorporated into breeding programs [10,11].
The total number of globally available accessions of the genus Vicia is difficult to calculate. However, we can estimate the status of most of them through GENESYS, the world’s largest platform for crop diversity conserved in worldwide genebanks that includes information about plant genetic resources (PGR) for food and agriculture (https://www.genesys-pgr.org/). We focused our studies on one-flower vetch (V. articulata), bitter vetch (V. ervilia), and narbon bean or French vetch (V. narbonensis) species of agronomic relevance, with many accessions available in the germplasm collections but with a lack of genetic diversity characterization. Reviewing the status of these collections worldwide, the GENESYS international platform reports a total number of 358 accessions of V. articulata, mainly traditional cultivars (landraces), with Spain being the main country of origin, according to passport data. The most important collections are conserved in the genebanks of Spain and Australia. V. ervilia has 2275 accessions available, mainly landraces, from Turkey, Spain, and Greece. The most important collections are those of the Russian, Australian, Lebanese, and Spanish genebanks. Finally, V. narbonensis has 1371 accessions, mainly of wild and natural biological status, with Turkey, Syria, Lebanon, Portugal, Israel, and Spain being the principal countries of origin. The most important collections are in Australian and Lebanese genebanks [12]. The Spanish genebank (Spanish National Plant Genetic Resources Center; CRF, INIA-CSIC) conserves one of the largest Vicia collections in the world and includes landraces, wild populations, and commercial cultivars both from Spanish and international origin. Previously, a high degree of variability has been observed for the agromorphological descriptors of the different accessions of these three collections (V. articulata, V. ervilia, and V. narbonensis). To understand the genetic basis of such high morphological diversity, a genomic characterization would be desirable.
Novel biotechnological tools and molecular markers have allowed a fast and low-cost genotyping of collections, complementing the classical approaches based on the evaluation of PGR by using agromorphological descriptors and allowing an effective development of core collections [13]. However, the lack of knowledge about their genomes and the absence of molecular markers has limited the utilization of some germplasm resources. Except for V. faba (faba bean), which is the only species of the genus with a reference genome [14], and V. sativa with different transcriptome studies [15,16], few genomic tools have been developed to explore the genetic diversity of Vicia genus germplasm collections. In the case of the faba bean, its genetic diversity has been analyzed using different molecular tools, including random amplification of polymorphic DNA (RAPD), amplified fragment length polymorphism (AFLP) derived markers, inter simple sequence repeats (ISSRs), or simple sequence repeats (SSRs) [17,18,19,20]. DNA markers have also been extensively used in assessing genetic diversity of V. sativa, including sequence-specific amplified polymorphism (SSAP), AFLPs, start codon targeted (SCoT), ISSRs, single nucleotide polymorphisms (SNPs), and SSRs [21,22].
SSR markers have become powerful tools for analyzing genetic variation, genetic mapping, and molecular breeding. Moreover, SSRs have been shown to be highly polymorphic, robust, and cross-transferable to several species of the genus Vicia. In the absence of specific markers, cross-amplification of Vicia sativa subsp. sativa microsatellites across 22 other Vicia species has been performed [23]. Recently, we analyzed the potential cross-transferability potentiality of several V. sativa SSR markers across 16 different species of the genus Vicia [15]. We will use these markers and those described from V. ervilia [24], whose transferability has not been tested, for the genotyping of V. articulata, V. ervilia, and V. narbonensis collections.
In this study, we aimed to (1) explore the cross-transferability of heterologous SSR molecular markers from V. sativa and V. ervilia to other species of the genus Vicia, (2) genotype the accessions of the Spanish collections of these species, and (3) analyze the genetic diversity in accessions of one-flower vetch, narbon vetch, and bitter vetch collections. Subsequently (4), these genotypic data were integrated with passport and agromorphological characterization data to select representative varieties from the V. articulate and V. ervilia collections.

2. Materials and Methods

2.1. Plant Materials and Genomic DNA Extraction

Analyzed collections included 115 accessions from V. articulata (one-flower vetch), 296 accessions from V. ervilia (bitter vetch), and 33 accessions from V. narbonensis (narbon bean or French vetch). The accessions of the species from the Vicia genus analyzed in this work are described in Tables S1–S3 and are available at the CRF site (https://bancocrf.inia.es/en/; accessed on 5 December 2023). Vicia seeds of each accession were germinated and grown in a greenhouse (photoperiod: 16 h light/8 h dark, at 22 °C), and samples from 4-week-old young leaves were stored at −80 °C until genomic DNA extraction. Genomic DNA was extracted using the DNeasy® Plant Mini kit (Qiagen, Madrid, Spain) according to the manufacturer’s guidelines. The qualitative and quantitative controls of the extracted DNA were analyzed using NanoDrop ND1000 (Thermo Scientific, Madrid, Spain). For subsequent genetic analyses, and in accordance with previous literature, these species were considered diploid [25].

2.2. SSR Genotyping by PCR Multiplex Amplification and Data Analysis

The 14 selected pairs of V. sativa SSR-containing oligonucleotides [15] and 4 pairs of V. ervilia SSR-containing oligonucleotides [24] were experimentally validated. Forward primers were labeled by adding different fluorescent probes (6-FAM, HEX, NED, PET, LIZ) as specified (Table S4). The multiplex PCR reaction was performed in a 15 μL volume containing 10 ng of genomic DNA and the simultaneous addition of the 18 pairs of oligos using Multiplex PCR NZYTaq 2x Colorless Master Mix (NZYTech Genes & Enzymes, Lisbon, Portugal), according to the manufacturer’s specifications. The cycling PCR parameters were one cycle of 2 min at 95 °C; 10 cycles of 30 s at 95 °C, 30 s at 55 °C, 60 s at 72 °C; 25 cycles of 30 s at 95 °C, 30 s at 50 °C, 60 s at 72 °C; and a final extension of 5 min at 72 °C. The PCR fragments containing the SSR alleles were analyzed on an ABI 3130xl Genetic Analyzer (Applied Biosystem, Woburn, MA, USA), and the fragment size was determined using the Peak Scanner 2.0 program (Applied Biosystems) with an internal size standard (GeneScan1200-LIZ; Applied Biosystems), rounding to integer allele numbers.

2.3. Population Structure and Genetic Diversity Analysis

The GenAlEx6.5 software [26] was used to analyze the different parameters of genetic variation and allelic diversity, polymorphic index content (PIC), Fixation Index (F), heterozygosity observed (Ho), and heterozygosity expected (He) calculated from the fragment size data matrix. Structure V2.3.4 software [27] was applied to infer the estimated number of subpopulations (K) and to quantify the probability that each genotype belongs to each of the inferred subpopulations. Ten independent runs were performed using simulated K values ranging from 1 to 10 inferred genetic clusters, a burn-in period of 100,000 steps, and 100,000 Monte Carlo Markov chain replicates. Structure Harvester plugin [28] was employed to determine the optimal K value by using the ΔK method defined by Evanno [29]. Darwin 6.0.15 software [30] was used to perform the phylogenetic cluster analysis, calculated genetic dissimilarity (GD) parameters, and Nei’s unbiased genetic distance, and generate a dendrogram using the unweighted pair-group method with arithmetic mean (UPGMA). Estimation of population differentiation by AMOVA method was performed using molecular data and testing a differentiation hypothesis using GenAlEx6.5 software [26].

2.4. Field Characterization of Agromorphological Traits

The agromorphological characterization of the Vicia collections was carried out at “Finca La Canaleja”, Alcalá de Henares, Madrid (602 m asl; 40°30′54″ N/03°18′42″ W). The meteorological conditions of this area have an average temperature of 13.7 °C and an average annual rainfall of 420 mm. The main soil characteristics of this field are calcium alfisol, loam, moderately alkaline (pH 8.4), saturation of bases (100%), and organic carbon (0.6%). The agronomic characterizations of the accessions from the different collections were carried out during different years, partially or totally, as indicated in Supplemental Tables S1b, S2b and S3b. Due to the fact that there is no official agromorphological descriptor list for the studied species, these traits were selected according to the IBPGR (now Alliance Biodiversity & CIAT) descriptor lists and the International Union for the Protection of New Varieties of Plants (UPOV) guidelines for other Vicia species (Supplemental Tables S1c, S2c and S3c). Complete agromorphological data analysis at indicated years are already available at CRF repositories and at https://webx.inia.es/web_coleccionescrf/CaracterizacionCRF.asp (accessed on 5 December 2023).

2.5. Statistical Analyses

AMOVA method was used to estimate population differentiation directly from molecular data and test a differentiation hypothesis using GenAlEx6.5 software [26]. For quantitative agronomic data, correlations of multivariable analysis and principal component analysis (PCA) were analyzed using the Statgraphics Centurion v18.1 software.

3. Results

3.1. Cross-Species Transferability of SSR Markers to Species of the Genus Vicia

In the present study, we explored the utility of heterologous SSRs from closely related species of the same genus. Preliminary works in our lab supported the potential cross-transferability of several V. sativa SSR markers across different species of the genus Vicia [15]. We selected some of these molecular markers to evaluate their transferability to other species of the genus, including V. ervilia, V. articulata, and V. narbonensis. Similarly, V. ervilia SSR marker oligonucleotides [24] were experimentally tested in our lab to evaluate their transferability to V. sativa, V. articulata, and V. narbonensis.
Fourteen primer pairs from V. sativa [15] and the only four currently available from V. ervilia [24] were used over genomic DNA from V. ervilia, V. sativa, V. articulata, and V. narbonensis for PCR amplification of SSR-containing fragments (Supplementary Table S4). The resulting PCR products were analyzed on agarose electrophoresis gel, discarding nonspecific miss-priming and null alleles. Later, fluorochrome-labeled fragments were analyzed on a genetic analyzer for fragment size and polymorphism determination. Nonpolymorphic SSRs were not considered as successfully transferable. Cross-transferability rates among different Vicia species varied depending on the SSR donor species (Table 1). For SSRs from V. sativa (VsSSRs), the average rate of heterologous transferability varied from 93% for V. narbonensis to 50% for V. ervilia, while for V. ervilia SSRs (VeSSRs), the results were more resounding: transferability of 100% for V. sativa and V. narbonensis and 0% for V. articulata. Furthermore, we identified seven SSRs from V sativa (VsSSR310, VsSSR179, VsSSR140, VsSSR129, VsSSRP, VsSSRS, VsSSRN) that presented 100% cross-transferability among the different members of the genus Vicia and elevated levels of polymorphism in their alleles. Moreover, simultaneous multiplex PCR was performed using the 18 pairs of primers over the accessions of the three Vicia collections. The high level of polymorphism observed for most of the SSR alleles made it possible to establish a fragment size matrix to analyze the genetic diversity of the different accessions present in the three germplasm collections maintained in the Spanish genebank, including landraces, wild populations, and commercial cultivars both from Spanish and international origins. Almost 500 accessions were genotyped from V. articulata (115 accessions), V. ervilia (296 accessions), and V. narbonensis (33 accessions) collections, and different genetic diversity analyses were conducted (Supplementary Tables S1–S3).

3.2. Genetic Diversity and Cluster Analysis of the V. articulata Collection

The V. articulata Spanish collection, with a total of 115 accessions, mainly includes landraces of Iberian Peninsula origin (Supplementary Table S1a). This collection was characterized using the nine SSR markers successfully transferable from V. sativa to V. articulata. A total of 65 different alleles were identified in this analysis. Alleles per locus ranged between 4 and 10 (average 7.2). VsSSRN (10 alleles), VsSSR129, and VsSSRS (9 alleles per locus) were the most polymorphic markers (Table 2).
Most of the loci had intermediate or elevated genetic diversity and a high level of SSR polymorphism. Thus, polymorphic information content (PIC) values ranged from 0.07 to 0.77, with an average of 0.46. Shannon’s Information Index (I) values varied from 0.63 to 1.78, with an average of 1.04 per locus. Total averages of the observed (Ho) and expected heterozygosity (He) were 0.30 and 0.49, respectively. The negative F value of VsSSR179 supports an excess of heterozygosity for this locus.
Genotyping profiles indicated that almost all the 115 accessions tested with these nine SSR sets had unique and specific profiles, except for some observed duplicities. Thus, the four accessions Va19, Va14, Va30, and Va45 had identical SSR profiles. The same happened with the couples Va17-Va18, Va80-Va81, and Va38-Va43. The greatest genetic distance was found among Va114 and Va64 or Va2. These results reinforce the potential of using a combination of data from markers of different origins to improve the discriminative power of our SSR set. Analyses of population structure and clustering analysis with the Structure software suggested one unique population. To infer phylogenetic relationships, hierarchical trees were constructed using the UPGMA clustering method and DARWIN software using dissimilarity data. Unweighted neighbor-joining analysis yielded a dendrogram in which the accessions of V. articulata were divided into three major clusters (Figure 1). Curiously, the two unique commercial varieties were included in group III, with high genetic closeness between them. The small number of commercial cultivars and wild populations did not allow extensive statistical analyses of their genetic contribution. However, AMOVA testing showed that only 14% of the genetic variations were due to differences among groups of landraces, wild populations, and commercial cultivars, indicating that most of the genetic variation (53%) was attributed to within-population variation (Table 3; Supplementary Table S5).

3.3. Genetic Diversity and Cluster Analysis of the V. ervilia Collection

The four homologous SSRs from V. ervilia and the seven SSR heterologous markers from V. sativa that were transferable to bitter vetch were used for analyzing the genetic diversity of the Spanish V. ervilia collection, which contains 296 accessions (complete passport data available in Supplementary Table S2).
The selected SSR markers were highly polymorphic for the analyzed accessions (Table 4). We identified 109 different alleles with 4 to 28 alleles per locus (average 9.9), the highest polymorphic markers being VsSSR129 (28 alleles) and VsSSRP (11 alleles). An analysis of different parameters of genetic diversity was performed. PIC values varied from 0.17 to 0.94, with an average of 0.56, indicating that most of the loci had intermediate or high diversity. Shannon’s Informative Index (I) of the loci ranged from 0.14 to 2.97 per locus (average 1.30). The averages of the observed (Ho) and expected heterozygosity (He) were 0.16 and 0.59, respectively. The high values of genetic diversity parameters such as allele number, Ho, He, PIC, and I support the validity of these molecular markers for evaluating the genetic diversity in V. ervilia (Table 4). Furthermore, the combined use of data from the 11 markers of homologous and heterologous origins greatly increases the discrimination potential of our SSR set. In fact, all the 296 accessions tested with this 11 SSR set had specific and unique profiles. The population structures and clustering analysis of the genotyping data matrix were analyzed using the DARWIN and Structure software and the K-Evanno method. Although no clear population structure was observed by clustering analysis, the hierarchical dendrogram constructed with dissimilarity data and UPGMA clustering method allowed for the differentiation of three main tree clusters. Curiously, according to the dendrogram (Figure 2), most of the international (non-Spanish) accessions (79%) were contained in cluster III, indicating high genetic proximity among these accessions despite being from different countries and distant origins. Furthermore, the subpopulation of Spanish origin presents a dissimilarity value of 0.57 compared with 0.59 for the complete collection (non-Spanish varieties only 0.48), suggesting the high potential for genetic diversity contributed by the Spanish collection. Additional analyses indicated that most of the commercial cultivars (67%) were contained in cluster III, indicating high genetic proximity among these accessions. However, the small number of existing commercial cultivars did not allow for in-depth analyses of diversity with statistical relevance. Moreover, AMOVA testing showed that only 11% of the genetic variations were due to differences among groups of landraces, wild populations, and commercial cultivars, indicating that most of the genetic variation (65%) is attributed to individual variation (Table S6). Complete information about diversity and heterozygosity parameters in landraces, wild populations, and commercial accessions is summarized in Table 5.
We compared the genetic diversity results of heterologous markers (SSRs from V. sativa to genotype V. ervilia accessions) and homologous markers (SSRs from V. ervilia to V. ervilia). The average allele number and PIC for markers from V. sativa were 10.43 and 0.52, respectively, and from V. ervilia, 9.00 and 0.63, respectively. These very similar numbers supported the potential of using heterologous markers to analyze the genetic diversity of V. ervilia accessions when there is low availability of homologous markers from the same species.

3.4. Genetic Diversity and Cluster Analysis of the V. narbonensis Collection

A total of 33 narbon vetch accessions, including landraces, cultivars, and wild populations (Supplementary Table S3), were analyzed for the identification of polymorphic alleles with the 17 SSR primers successfully transferable to V. narbonensis: the 13 SSR primer pairs from V. sativa and 4 SSRs from V. ervilia. Overall, at least 90 different loci were identified with 2 to 10 alleles per locus (average 5.3), with the highest being polymorphic VsSSR129 (10 alleles) and VeSSR02 and VsSRR185 (8 alleles). Genetic diversity, calculated as PIC, ranged from 0.03 to 0.80 with an average of 0.55, indicating that most of the loci had intermediate or high diversity. These results indicated elevated levels of SSR polymorphism. The Shannon’s Informative Index (I) of the loci varied from 0.08 to 1.97, with a mean of 1.19 per locus. Total averages of the observed (Ho) and expected heterozygosity (He) were 0.30 and 0.59, respectively (Table 6). Negative values for the Fixation Index (F) were found for the loci VeSSR07, VsSSR140, and VsSSR115, representing excess heterozygosity (Table 6). The average allele number and PIC for the V. narbonensis collection were 5.23 and 0.55, respectively, for SSRs from V. sativa and 5.50 and 0.56, respectively, for SSRs from V. ervilia. These values indicate similar genetic diversity values regardless of the species of origin of the SSR. Moreover, the combined use of the data from all the markers greatly increased the discrimination capacity of our SSR set. In fact, all the accessions tested with this SSR set had unique and specific profiles. The data matrix obtained using the 17 SSRs over the 33 accessions was analyzed for population structures and clustering analysis with the Structure program. No clear, strong population structure was obtained using the K-Evanno method [29] and clustering analysis, suggesting one unique population. To infer phylogenetic relationships, dissimilarity data were used to construct a hierarchical tree using the UPGMA clustering method within the DARWIN v6.0.15 software (Figure 3). Unweighted neighbor-joining analysis resulted in a dendrogram with five main clusters.
The narbon vetch Spanish collection contains mainly landraces (n = 12; 36.4%) but also several commercial varieties (n = 8; 24.2%) and 13 wild populations (39.4%) from Spanish origin, relevant due to their genetic diversity potential. To analyze whether cultivars have less genetic diversity than landraces, we performed a genetic diversity analysis comparing the degree of dissimilarity among landraces, commercial cultivars, and wild populations (Table 7). Our analysis indicated no drastic differences in genetic dissimilarity among the landraces (mean diversity 0.54), cultivars (mean diversity 0.49), and wild populations (mean diversity 0.61) versus the whole collection (genetic diversity 0.55), without extreme differences among the groups. As expected, these results indicated that wild populations had higher genetic diversity than cultivars or landraces and that the selection process to obtain landraces and commercial varieties has been focused mainly on the selection of wild and local forms. However, cultivars had only slightly less diversity than landraces. Curiously, five commercial cultivars were contained in cluster I, indicating high genetic proximity between these accessions (Figure 3). The heterozygosity and polymorphism diversity parameters also showed higher values in wild populations and landraces than in cultivars (Table 7). These results corroborate the diversity of wild populations, but not in a drastic way, and unexpectedly, landraces were less diverse than cultivars. These small discrepancies may be due to the small number of accessions available, but they also indicate the low degree of improvement existing in the cultivated varieties.
Supporting these conclusions, the Nei-index between the comparative of these populations ranged from 0.868 to 0.956, indicating a high degree of similarity. The AMOVA test indicated that only 4% of the genetic variation was due to differences among populations of landraces, wild populations, and commercial cultivars, indicating that most of the genetic variation (96%) is attributed to within-population variation (Table S7).

3.5. Field Evaluation of Vicia Collections Phenotypic Traits

The agromorphological evaluation of the V. articulata, V. ervilia, and V. narbonensis collections was performed according to the characterization of different quantitative and qualitative traits, including measures related to shape, color, size, and weight of whole plant, leaf, flower, seed, pod, and phenological data, along several years. Detailed information on accessions, years, and measured descriptors and parameters are included in Supplementary Tables S1–S3, and a summary of quantitative analyses of a selection of the more relevant agronomic data is available in Table 8, Table 9 and Table 10. The analysis of these agronomic data in the evaluated species allowed us to find great diversity and a wide range of values in parameters as relevant as the number of main branches, plant height, first pod height, and number of pods per plant in V. articulata (Table 8); the number of racemes and pods per plant in V. ervilia (Table 9); and the number of branches and pods per plant, 100-seed weight, plant height or harvest index in V. narbonensis (Table 10). Together, these data give an idea of the high phenotypic diversity present in the three collections analyzed.
Multivariable analysis and principal component analysis (PCA) methods were applied to examine correlations between these quantitative traits in the different Vicia species (Table S8). Thus, in V. articulata, there was a high correlation between the different phenological parameters of flowering and maturity and between plant height and first pod height. In V. ervilia, there was a high degree of correlation between the parameters of raceme number and pod number, parameters related to leaf size as leaf length, leaflet length, and leaflet width, and between the phenological parameters of flowering and maturity. In V. narbonensis, statistically significant correlations were also found between leaflet length and leaflet width, between the phenological parameters of flowering and maturity, between harvest index and seed weight, and between the beginning of flowering and leaf size. Interestingly, a negative association was observed between the parameters of branch number with harvest index and seed weight and between phenological data and height of V. narbonensis plants.

3.6. Building Core Collections

One of the main limiting factors for rational maintenance and appropriate utilization of large collections is their considerable number of accessions, which makes the possibility of a deep advance in the knowledge of their features difficult. The selection of representative core collections (CCs) is a strategic and efficient way to preserve and utilize the genetic diversity of plant species, reducing the costs and challenges associated with the management of genetic resources in gene banks worldwide. This approach may be especially relevant for vetch collections with many accessions, such as V. articulata (n = 115) and V. ervilia (n = 296), described in this work.
The genetic dissimilarity analysis from the genotypic data from SSR marker cluster analysis and principal component analysis (PCA) from phenotypic analyses, together with a deep study of passport data of the V. articulata total collection, permitted the selection of 20 accessions (17.4% of complete collection) that would represent the Spanish one-flower vetch core collections (Table S9). By examining the dispersion and distribution in different branches of the phylogenetic clusters, it was confirmed that the chosen accessions included in the CC were representative of the complete collection (Figure 1 and Figure 2). In fact, this representative CC shows a dissimilarity value of 0.61 compared with 0.44 for the complete V. articulata collection. Furthermore, it is worth noting that the accessions of this representative core collection retain similar agronomic values (average, dispersion, and broad range) to the total one-flower vetch collection (Supplementary Table S10).
A similar approach to the V. ervilia total collection permitted the selection of 53 accessions that established the Spanish bitter vetch core collection (Table S11). Through an analysis of the dispersion and distribution of phylogenetic clusters, it was verified that the selected samples within the CC (18.1%; 53/296) were representative of the complete collection. In fact, this representative CC showed a genetic dissimilarity value of 0.68 compared with 0.59 for the complete V. ervilia collection. Additionally, again, in this case, it is noteworthy that the accessions of this CC maintain comparable agronomic values (including average values, distribution, and a wide range) to those of the complete bitter vetch collection (Supplementary Table S12).

4. Discussion

SSRs are codominant, abundant, reproducible markers with great genome coverage. Several studies have shown the potential transferability of heterologous SSR markers within legume genera between distantly related legumes [31]: from M. truncatula Gaertn. to Vicia faba, L. Pisum sativum L. and Cicer arietinum L. [32]; from Glycine max L. to Arachis hypogaea L. and from, P. sativum L., Trifolium pratense L. and M. truncatula to Lens culinaris L. [33]. The use of heterologous markers is especially useful in species whose genome is not sequenced, and therefore, there are no markers that allow for the analysis of the genetic diversity of accession sets. In this work, we analyzed the potential of using V. ervilia and V. sativa markers for genotyping different species of the genus Vicia (V. narbonensis, V. ervilia, and V. articulata). In the case of V. sativa, previous studies had shown the ability of cross-species transferability potential of SSR markers [15,23] but not from V. ervilia. Transferability of the 18 SSR markers that were evaluated in this work highly varied depending on the donor and target species, with averages of 69% from V. sativa SSR or 67% % from V. ervilia SSR. These cross-transferability averages were high in concordance with previously published results on pulses and other legumes [34]. In fact, the transferability rates of about 20% were considered reasonable when distantly related legume species were tested [35,36,37]. The high cross-transferability of the SSRs used in this work may be due, on the one hand, to the high genetic proximity between different species analyzed that are closely related and, on the other hand, to the fact that the used SSRs come from coding regions of the genome. Most of the markers that we used in this work were located on transcribed regions that were less polymorphic but more conserved than noncoding regions [15]. EST-SSR markers based on expressed sequence tags have been shown to have a high degree of sequence conservation among homologous genes, significant specificity, and a higher level of transferability across related species compared with nontranscribed genomic SSRs. At this point, it should be noted that a publication on V. ervilia SSR markers [24] does not specify the genomic origin of these sequences; however, in our laboratory, we showed that primer pairs to amplify VeSSRs work perfectly in PCR using V. ervilia cDNA as a template, which supports their coding region origin.
We must also underline the high number of alleles per locus of the markers analyzed. The SSR polymorphisms highly varied depending on the SSR and target species, with allele number averages of 7.2, ranging from 4 to 10 alleles in V. articulata; averages of 9.9, ranging from 4 to 28 alleles in V. ervilia; and averages of 5.3, ranging from 3 to 10 alleles per locus in V. narbonensis. The microsatellite with the highest polymorphism was VsSSR138, with between 9 and 28 polymorphic alleles depending on the species, followed by SSR179 and SSRS (both with 5–9 polymorphic alleles). Considering that normally, EST-SSRs present a lower degree of polymorphism because they are in more conserved coding regions, our data reinforced the high potential of these sets of molecular markers.
Regarding the use of V. ervilia SSRs (VeSSR02, VeSSR05, VeSSR07, and VeSSR09) as homologous markers for the genotyping of V. ervilia accessions, our statistics on the number of alleles and genetic diversity were consistent with previous reports [24,38,39]. However, our data indicate higher polymorphism and heterozygosity for these SSRs. Most likely, this fact is due to the small number and less genetic diversity of the bitter vetch accessions analyzed in previous works. Here, we analyzed almost 300 bitter vetch accessions from different geographical locations, which explains the higher observed polymorphism values. Likewise, the excellent values of genetic diversity obtained with these SSR markers validate their use for genotyping evaluation in bitter vetch.
Additionally, we used these heterologous markers to analyze the genetic diversity of germplasm collections. For the genotyping of the different collections analyzed, we used multiplex PCR. This methodology allows the simultaneous use of multiple primer sets within a single PCR mixture that produces amplicons of varying sizes and fluorescent labels that are specific to different DNA sequences. Based on our results, we can conclude that the PCR multiplex tool is a fast, efficient, high-yielding, and cost-effective technique for genotyping many accessions with several SSRs simultaneously. Similar approaches have been previously investigated in common vetch, wheat, grapevine, and tomato [15,40,41,42].
Plant genetic resources, including locally adapted landraces, are crucial to preserve the genetic diversity and develop future productive crops adapted to changing climate conditions and new social and economic demands. Genotypic characterization of PGR collections worldwide allows the identification of redundant duplications within and between different genebanks and the traceability of accession identity. In this work, we analyzed the combined use of heterologous and homologous markers to characterize the genetic diversity of three collections, V. articulata, V. narbonensis, and V. ervilia, from the Spanish genebank (CRF-INIA/CSIC). These three species are native to Southwestern Europe, Northern Africa, and Middle and Western Asia, and they are mainly used as fodder and grain for feed. Its consumption in humans is quite residual and minor and is reduced to times of scarcity due to its low palatability and presence of antinutrients [43,44,45,46]. Together with these uses, these species are considered crop wild relatives of other cultivated species of the genus Vicia [47]. In this context, V narbonensis is included in the tertiary gene pool of V. faba as a potential donor for cold tolerance [48], frost tolerance [49], biotic stresses like black bean aphid resistance and chocolate spot disease resistance [49], broomrape resistance [50], or increasing pods per plant number [51]. V. articulata and V ervilia are closed species with a high potential for breeding as donors of resistance to ascochyta blight rust [52] and broomrape resistance [50].
Although V. ervilia, V. articulata, and V. narbonensis are marginal or minor crops and could be considered orphan crops, they may play an essential role as resilient crops against climate change. Orphan crops are usually well adapted to extreme climates and low-input agricultural conditions, playing a critical role in local areas where they are cultivated. These crops are typical of the Mediterranean Basin, just as these areas have experienced drastic temperature changes associated with severe drought under the effect of climate change over recent decades. Rainfed agriculture is facing great risks and climate uncertainties, and these vetch crops appear as promising crop species, especially for being species tolerant to aridity, with potential adaptation to local climatic conditions [53]. Therefore, despite being minor crops, the diversity of their genetic resources, including wild populations and local varieties or landraces, must be characterized to guarantee their conservation. We must also emphasize that the Vicia collections from the Spanish genebank constitute an important part of the total accessions registered in GENESYS, the international platform with information about plant genetic resources for food and agriculture conserved in genebanks worldwide. Particularly relevant, we highlight that the accessions of V. articulata genotyped in this work constitute more than 60% of the total registered in GENESYS and that the V. ervilia collection described here contains more than 24% of accessions of non-Spanish origin from seven countries of the Mediterranean Basin, the origin and diversification center of the genus Vicia.
Genetic diversity analysis indicated that almost all the analyzed accessions presented specific and differential SSR patterns, suggesting few duplications, except for V. articulata. In this case, only nine SSRs were transferable, which may explain the low discriminatory potential of the set used. However, the total analyzed varieties in the V. narbonensis and V. ervilia collections had unique and specific profiles, allowing the identification of duplicates and closely related varieties. As expected, wild populations do present high genetic diversity when compared with the rest of the accessions. However, our results did not show extremely significant differences between the genetic diversity of landraces and commercial cultivars in the three Vicia collections. These data suggest that the genetic variability of commercial cultivars has not been lost during the breeding process or that these cultivars could be merely selected landraces. The analysis by origin of provenance could only be performed for bitter vetch, which is the only collection with a statistically significant number to carry out these analyses and included accessions from Spain, Greece, Morocco, Iran, Turkey, Afghanistan, and Cyprus (see detail passport data in Supplemental Table S3), countries within the Mediterranean and Irano-Turanian regions, which is the center of origin and primary diversification of genus Vicia [2,3,54,55]. Focusing on the bitter vetch collection, the phylogenetic analysis of the dendrograms indicated three main clusters (Figure 2). Accessions of Spanish origin showed great dispersion along the dendrogram, indicating high genetic variation, and most of the non-Spanish were contained in the same subclade of cluster III, suggesting high genetic proximity among these accessions. These data and the AMOVA test indicated that most of the genetic variations were due to within-accession variation and that the high dissimilarity value of Spanish compared to non-Spanish accessions of the global collection reinforces the high potential for genetic diversity contributed by the Spanish collection.
One issue in genebanks is the high volume of samples in some collections, which makes it challenging to maintain, characterize, document, and subsequently use them. The establishment of core collections, with a minimum number of nonredundant individuals having the maximum variability of the entire germplasm collection, largely alleviates this problem [56]. Compared with analyzing a complete germplasm collection, core collection characterization and evaluation is simpler and quicker. SSR molecular markers were employed in the current study to clarify the genetic variety of the vetch collection. Despite making up only about 17% of the original V. articulata collection, the selected individuals displayed higher heterozygosity and polymorphic average values (He = 0.64 ± 0.07, PIC = 0.61 ± 0.20) than those of the original collection (He = 0.49 ± 0.08, PIC = 0.46 ± 0.22), indicating that the V. articulata core collection (CC) retained most of the genetic diversity of the entire large collections. Similarly, V. ervilia CC contained only 15% of the original collection but had higher heterozygosity and polymorphic values (He = 0.68 ± 0.06, PIC = 0.62 ± 0.26) than the original bitter vetch collection (He = 0.59 ± 0.07, PIC = 0.56 ± 0.24). Furthermore, we demonstrated that the developed CC maintained most of the agromorphological potential of the original collection, supporting the value of these representative collections.

5. Conclusions

In this study, 18 SSR markers were used to evaluate their transferability as heterologous markers from V. sativa and V. ervilia to four species of genus Vicia. Transferability highly varied depending on the donor and target species. Selected heterologous SSRs allowed a detailed genetic analysis of three Spanish Vicia genebank collections with almost 500 accessions, indicating that these sets of SSR markers will serve as valuable tools for genetic diversity analysis on Vicia species whose genome is not sequenced.
This is the first report on large-scale genotyping and analysis of the genetic diversity of three vetch species collections (bitter, one-flower, and narbon vetches). This extensive molecular characterization is critical for the management and conservation of the three collections, guiding their rational use in breeding applications. Our results provide support for analyzing the genetic diversity of vetch germplasm resources and the development of new methods for collecting, preserving, and utilizing germplasm resources. In addition, the potential use of SSR markers, especially for those species lacking genomic information, and the genomic information provided by this study may facilitate marker-assisted selection for breeding programs of narbon, one-flower, and bitter vetches.

Supplementary Materials

The following supporting information can be downloaded at https://www.mdpi.com/article/10.3390/agronomy14020326/s1; Table S1: passport information (a), agromorphological data (b), and agromorphological descriptors based on Bioversity International recommendations and UPOV guidelines for species of Vicia genus (c) of V. articulata accessions; Table S2: passport information (a), agromorphological data (b), and agromorphological descriptors based on Bioversity International recommendations and UPOV guidelines for species of Vicia genus (c) of V. ervilia accessions; Table S3: passport information (a), agromorphological data (b), and agromorphological descriptors based on Bioversity International recommendations and UPOV guidelines for species of Vicia genus (c) of V. narbonensis accessions; Table S4: gene-specific primers used for multiplex PCR amplification; Table S5: analysis of molecular variance (AMOVA) using SSR data tested in landraces, wild populations, and commercial cultivars of one-flower vetch; Table S6: analysis of molecular variance (AMOVA) using SSR data evaluated in landraces, wild populations, and commercial cultivars of bitter vetch; Table S7: analysis of molecular variance (AMOVA) using SSR data evaluated in landraces, wild populations, and commercial cultivars of narbon vetch; Table S8: plots displaying correlations among agronomic parameters and PCA analyses of one-flower, bitter, and narbon vetches; Table S9: core set selected from total one-flower vetch collection; Table S10: measurements of agromorphological traits in accessions of the one-flower vetch core collections; Table S11: core set selected from total bitter vetch collection; Table S12: measurements of agromorphological traits in accessions of bitter vetch core collections.

Author Contributions

L.D.l.R. and E.R.-P.: conceptualization, funding acquisition, resources, and supervision; M.I.L.-R. and E.R.-P.: genotypic assays; T.M.-P. and L.D.l.R.: phenotypic assays. L.D.l.R., M.I.L.-R., T.M.-P. and E.R.-P.: data curation and investigation; E.R.-P.: formal analysis, data visualization, and project administration; L.D.l.R. and E.R.-P.: wrote and edited the paper. All authors contributed to the article and revised and approved the submitted version. All authors have read and agreed to the published version of the manuscript.

Funding

This research was supported by grants RTI2018-094037-R-I00 and PDI2021-122138OR-I00 from the Spanish Ministerio de Ciencia e Innovacion (MCIN/AEI/10.13039/501100011033/FEDER; UE) and by the “Severo Ochoa Program for Centres of Excellence in R&D” (Agencia Estatal de Investigación of Spain, grant CEX-2020-000999-S to the CBGP). CSIC partially supports open-access publication fees.

Data Availability Statement

Details regarding the data supporting reported results can be found in the Supplementary Materials and in the public CRF repository https://bancocrf.inia.es/es/accessions/ (accessed on 5 December 2023).

Acknowledgments

The authors kindly acknowledge the Spanish Plant Genetic Resources Center (CRF, INIA-CSIC), especially I. Martin and L. Guasch, for providing the accessions used in this analysis, and to D. Rubiales (IAS-CSIC) for kindly donating the Viartana and Algana cultivars of V. articulata.

Conflicts of Interest

The authors declare no conflicts of interest.

References

  1. Smýkal, P.; Coyne, C.J.; Ambrose, M.J.; Maxted, N.; Schaefer, H.; Blair, M.W.; Berger, J.; Greene, S.L.; Nelson, M.N.; Besharat, N.; et al. Legume Crops Phylogeny and Genetic Diversity for Science and Breeding. Crit. Rev. Plant Sci. 2015, 34, 43–104. [Google Scholar] [CrossRef]
  2. Maxted, N. An ecogeographical study of Vicia subgenus Vicia. In Systematic and Ecogeographic Studies on Crop Genepools; International Board for Plant Genetic Resources: Rome, Italy, 1995; Volume 8, p. 184. [Google Scholar]
  3. Maxted, N. A phenetic investigation of Vicia L. subgenus Vicia (Leguminosae, Vicieae). Bot. J. Linn. Soc. 1993, 111, 155–182. [Google Scholar] [CrossRef]
  4. Leht, M. Phylogenetics of Vicia (Fabaceae) based on morphological data. Feddes Repert. 2009, 120, 379–393. [Google Scholar] [CrossRef]
  5. Mateo-Box, J.M. Leguminosas de Grano; Ed. Salvat: Barcelona, Spain, 1961; p. 550. [Google Scholar]
  6. Pellegrini, P.A.; Balatti, G.E. Noah’s arks in the XXI century. A typology of seed banks. Biodivers. Conserv. 2016, 25, 2753–2769. [Google Scholar] [CrossRef]
  7. Dempewolf, H.; Baute, G.; Anderson, J.; Kilian, B.; Smith, C.; Guarino, L. Past and future use of wild relatives in crop breeding. Crop Sci. 2017, 57, 1070–1082. [Google Scholar] [CrossRef]
  8. Ramirez-Villegas, J.; Jarvis, A.; Fujisaka, S.; Hanson, J.; Leibing, C. Crop and Forage Genetic Resources: International Interdependence in the Face of Climate Change; Routledge: Abingdon, UK, 2013; pp. 78–98. [Google Scholar]
  9. Van Hintum, T.; Brink, M. Technological and policy challenges to utilisation of plant genetic resources. In Sustaining Global Food Security: The Nexus of Science and Policy; Zeigler, R.S., Ed.; CSIRO Publishing: Clayton South, Australia, 2019; pp. 36–48. [Google Scholar]
  10. Hodgkin, T.; Rao, R.; Cibrian-Jaramillo, A.; Gaiji, S. The use of ex situ conserved plant genetic resources. Plant Genet. Resour. Charact. Util. 2003, 1, 19–29. [Google Scholar] [CrossRef]
  11. Westengen, O.T.; Skarbø, K.; Mulesa, T.H.; Berg, T. Access to genes: Linkages between genebanks and farmers’ seed systems. Food Secur. 2018, 10, 9–25. [Google Scholar] [CrossRef]
  12. GENESYS. Online Platform of Plant Genetic Resources for Food and Agriculture (PGRFA) Conserved in Genebanks Worldwide. Available online: https://www.genesys-pgr.org (accessed on 5 December 2023).
  13. Pathirana, R.; Carimi, F. Management and Utilization of Plant Genetic Resources for a Sustainable Agriculture. Plants 2022, 11, 2038. [Google Scholar] [CrossRef]
  14. Khazaei, H.; O’Sullivan, D.M.; Stoddard, F.L.; Adhikari, K.N. Recent advances in faba bean genetic and genomic tools for crop improvement. Legum. Sci. 2021, 3, e75. [Google Scholar] [CrossRef] [PubMed]
  15. De la Rosa, L.; López-Román, M.I.; González, J.M.; Zambrana, E.; Marcos-Prado, T.; Ramírez-Parra, E. Common vetch, valuable germplasm for resilient agriculture: Genetic characterization and Spanish core collection development. Front. Plant Sci. 2021, 12, 617873. [Google Scholar] [CrossRef] [PubMed]
  16. Ramírez-Parra, E.; De la Rosa, L. Designing Novel Strategies for Improving Old Legumes: An Overview from Common Vetch. Plants 2023, 12, 1275. [Google Scholar] [CrossRef] [PubMed]
  17. Román, B.; Satovic, Z.; Pozarkova, D.; Macas, J.; Dolezel, J.; Cubero, J.; Torres, A. Development of a composite map in Vicia faba, breeding applications and future prospects. Theor. Appl. Genet. 2004, 108, 1079–1088. [Google Scholar] [CrossRef] [PubMed]
  18. Link, W.; Dixkens, C.; Singh, M.; Schwall, M.; Melchinger, A.E. Genetic diversity in European and Mediterranean faba bean germ plasm revealed by RAPD markers. Theor. Appl. Genet. 1995, 90, 27–32. [Google Scholar] [CrossRef] [PubMed]
  19. Zeid, M.; Schön, C.-C.; Link, W. Genetic diversity in recent elite faba bean lines using AFLP markers. Theor. Appl. Genet. 2003, 107, 1304–1314. [Google Scholar] [CrossRef] [PubMed]
  20. Wang, H.-F.; Zong, X.-X.; Guan, J.-P.; Yang, T.; Sun, X.-L.; Ma, Y.; Redden, R. Genetic diversity and relationship of global faba bean (Vicia faba L.) germplasm revealed by ISSR markers. Theor. Appl. Genet. 2012, 124, 789–797. [Google Scholar] [CrossRef] [PubMed]
  21. Edwards, D.; Batley, J. Plant genome sequencing: Applications for crop improvement. Plant Biotechnol. J. 2010, 8, 2–9. [Google Scholar] [CrossRef]
  22. Kumar, J.; Gupta, D.S.; Gupta, S.; Dubey, S.; Gupta, P.; Kumar, S. Quantitative trait loci from identification to exploitation for crop improvement. Plant Cell Rep. 2017, 36, 1187–1213. [Google Scholar] [CrossRef]
  23. Raveendar, S.; Lee, G.A.; Jeon, Y.A.; Lee, Y.J.; Lee, J.R.; Cho, G.T.; Cho, J.H.; Park, J.H.; Ma, K.H.; Chung, J.W. Cross-amplification of Vicia sativa subsp. sativa microsatellites across 22 other Vicia species. Molecules 2015, 20, 1543–1550. [Google Scholar] [CrossRef]
  24. El Fatehi, S.; Béna, G.; Filali-Maltouf, A.; Ater, M. Genetic diversity of moroccan bitter vetch Vicia ervilia (L.) Willd. landraces revealed by morphological and SSR markers. Aust. J. Crop Sci. 2016, 10, 717–725. [Google Scholar] [CrossRef]
  25. Osman, S.A.; Ali, H.B.; El-Ashry, Z.M.; El-Khodary, S.E. Karyotype variation and biochemical analysis of five Vicia species. Bull. Natl. Res. Cent. 2020, 44, 91. [Google Scholar] [CrossRef]
  26. Peakall, R.; Smouse, P.E. GenAlEx 6.5: Genetic analysis in Excel. Population genetic software for teaching and research-an update. Bioinformatics 2012, 28, 2537–2539. [Google Scholar] [CrossRef]
  27. Pritchard, J.K.; Stephens, M.; Donnelly, P. Inference of population structure using multilocus genotype data. Genetics 2000, 155, 945–959. [Google Scholar] [CrossRef] [PubMed]
  28. Earl, D.A.; vonHoldt, B.M. STRUCTURE HARVESTER: A website and program for visualizing STRUCTURE output and implementing the Evanno method. Conserv. Genet. Resour. 2012, 4, 359–361. [Google Scholar] [CrossRef]
  29. Evanno, G.; Regnaut, S.; Goudet, J. Detecting the number of clusters of individuals using the software STRUCTURE: A simulation study. Mol. Ecol. 2005, 14, 2611–2620. [Google Scholar] [CrossRef] [PubMed]
  30. Perrier, X.; Jacquemoud-Collet, J.P. DARwin Software. 2006. Available online: http://darwin.cirad.fr (accessed on 5 December 2023).
  31. Erayman, M.; İlhan, E.; Güzel, Y.; Eren, A.H. Transferability of SSR markers from distantly related legumes to Glycyrrhiza species. Turk. J. Agric. For. 2014, 38, 32–38. [Google Scholar] [CrossRef]
  32. Gutierrez, M.; Vaz Patto, M.; Huguet, T.; Cubero, J.; Moreno, M.; Torres, A. Cross-species amplification of Medicago truncatula microsatellites across three major pulse crops. Theor. Appl. Genet. 2005, 110, 1210–1217. [Google Scholar] [CrossRef] [PubMed]
  33. He, G.; Woullard, F.; Marong, I.; Guo, B. Transferability of soybean SSR markers in peanut (Arachis hypogaea L.). Peanut Sci. 2006, 33, 22–28. [Google Scholar] [CrossRef]
  34. Choudhary, S.; Sethy, N.K.; Shokeen, B.; Bhatia, S. Development of chickpea EST-SSR markers and analysis of allelic variation across related species. Theor. Appl. Genet. 2009, 118, 591–608. [Google Scholar] [CrossRef] [PubMed]
  35. Reddy, M.; Rathour, R.; Kumar, N.; Katoch, P.; Sharma, T. Cross-genera legume SSR markers for analysis of genetic diversity in Lens species. Plant Breed. 2010, 129, 514–518. [Google Scholar] [CrossRef]
  36. Gupta, M.; Verma, B.; Kumar, N.; Chahota, R.K.; Rathour, R.; Sharma, S.K.; Bhatia, S.; Sharma, T.R. Construction of intersubspecific molecular genetic map of lentil based on ISSR, RAPD and SSR markers. J. Genet. 2012, 91, 279–287. [Google Scholar] [CrossRef]
  37. Datta, J.; Lal, N. Application of molecular markers for genetic discrimination of Fusarium wilt pathogen races affecting chickpea and pigeonpea in major regions of India. Cell. Mol. Biol. 2012, 58, 55–65. [Google Scholar]
  38. El Fatehi, S.; Béna, G.; Sbabou, L.; Filali-Maltouf, A.; Ater, M. Preliminary Results For Use SSR Markers in Bitter Vetch “Vicia ervilia (L.) Willd”. Int. J. Res. 2013, 1, 2311–2476. [Google Scholar]
  39. Russi, L.; Acuti, G.; Trabalza-Marinucci, M.; Porta, R.; Rubini, A.; Damiani, F.; Cristiani, S.; Dal Bosco, A.; Martuscelli, G.; Bellucci, M. Genetic characterisation and agronomic and nutritional value of bitter vetch (Vicia ervilia), an under-utilised species suitable for low-input farming systems. Crop Pasture Sci. 2019, 70, 606–614. [Google Scholar] [CrossRef]
  40. Röder, M.S.; Wendehake, K.; Korzun, V.; Bredemeijer, G.; Laborie, D.; Bertrand, L.; Isaac, P.; Rendell, S.; Jackson, J.; Cooke, R.J.; et al. Construction and analysis of a microsatellite-based database of European wheat varieties. TAG Theor. Appl. Genet. Theor. Angew. Genet. 2002, 106, 67–73. [Google Scholar] [CrossRef] [PubMed]
  41. Bredemeijer, M.; Cooke, J.; Ganal, W.; Peeters, R.; Isaac, P.; Noordijk, Y.; Rendell, S.; Jackson, J.; Röder, S.; Wendehake, K.; et al. Construction and testing of a microsatellite database containing more than 500 tomato varieties. TAG Theor. Appl. Genet. Theor. Angew. Genet. 2002, 105, 1019–1026. [Google Scholar] [CrossRef] [PubMed]
  42. This, P.; Jung, A.; Boccacci, P.; Borrego, J.; Botta, R.; Costantini, L.; Crespan, M.; Dangl, G.S.; Eisenheld, C.; Ferreira-Monteiro, F.; et al. Development of a standard set of microsatellite reference alleles for identification of grape cultivars. TAG Theor. Appl. Genet. Theor. Angew. Genet. 2004, 109, 1448–1458. [Google Scholar] [CrossRef] [PubMed]
  43. GRIN. Germplasm Resource Information Network (GRIN) The GRIN-Global Database Platform. Available online: https://npgsweb.ars-grin.gov/gringlobal/taxon/taxonomysearchwep (accessed on 5 December 2023).
  44. Van de Wouw, M.; Enneking, D.; Robertson, L.; Maxted, N. Vetches (Vicia L.). In Plant Genetic Resources of Legumes in the Mediterranean; Maxted, N., Bennett, S.J., Eds.; Current Plant Science and Biotechnology in Agriculture; Springer: Dordrecht, The Netherlands, 2001; Volume 39. [Google Scholar] [CrossRef]
  45. Enneking, D.; Lahlou, A.; Noutfia, A.; Bounejmate, M. A note on Vicia ervilia cultivation, utilisation and toxicity in Morocco. Al Awamia 1995, 89, 141–148. [Google Scholar]
  46. Renzi, J.; Cantamutto, M. Vicias: Bases Agronómicas Para el Manejo en la Región Pampeana; Ediciones INTA, Ed.; Ediciones INTA: Buenos Aires, Argentina, 2013; ISBN 978-987-521-470-5. [Google Scholar]
  47. Vincent, H.; Wiersema, J.; Kell, S.; Fielder, H.; Dobbie, S.; Castañeda-Álvarez, N.P.; Maxted, N. A prioritized crop wild relative inventory to help underpin global food security. Biol. Conserv. 2013, 167, 265–275. [Google Scholar] [CrossRef]
  48. Raina, S.N.; Ogihara, Y. Chloroplast DNA diversity in Vicia faba and its close wild relatives: Implications for reassessment. Theor. Appl. Genet. 1994, 88, 261–266. [Google Scholar] [CrossRef] [PubMed]
  49. Birch, A.N.E.; Tithecott, M.T.; Bisby, F.A. Vicia johannis and wild relatives of the faba bean: A taxonomic study. Econ. Bot. 1985, 39, 177–190. [Google Scholar] [CrossRef]
  50. Sillero, J.C.; Moreno, M.T.; Rubiales, D. Sources of resistance to crenate broomrape among species of Vicia. Plant Dis. 2005, 89, 23–27. [Google Scholar] [CrossRef] [PubMed]
  51. Inci, N.E.; Toker, C. Screening and selection of faba beans (Vicia faba L.) for cold tolerance and comparison to wild relatives. Genet. Resour. Crop Evol. 2011, 58, 1169–1175. [Google Scholar] [CrossRef]
  52. Rubiales, D.; Fondevilla, S.; Chen, W.; Gentzbittel, L.; Higgins, T.J.V.; Sánchez, M.Á.C.; Rispail, N. Achievements and Challenges in Legume Breeding for Pest and Disease Resistance. Crit. Rev. Plant Sci. 2014, 34, 195–236. [Google Scholar] [CrossRef]
  53. Siddique, K.; Loss, S.; Enneking, D. Narbon bean (Vicia narbonensis L.): A promising grain legume for low rainfall areas of south-western Australia. Aust. J. Exp. Agric. 1996, 36, 53–62. [Google Scholar] [CrossRef]
  54. Zohary, D.; Hopf, M. Domestication of Plants in the Old World: The Origin and Spread of Cultivated Plants in West Asia, Europe and the Nile Valley, 3rd ed.; Oxford University Press: Oxford, UK, 2000. [Google Scholar]
  55. Maxted, N.; Bennett, S. Plant Genetic Resources of Legumes in the Mediterranean; Kluwer Academic Publishers: Dordrecht, The Netherlands, 2001; Volume 39. [Google Scholar]
  56. Gu, R.; Fan, S.; Wei, S.; Li, J.; Zheng, S.; Liu, G. Developments on Core Collections of Plant Genetic Resources: Do We Know Enough? Forests 2023, 14, 926. [Google Scholar] [CrossRef]
Agronomy 14 00326 g001
Figure 1. Structure and genetic diversity of one-flower vetch collection. (A) Summary of CRF collection containing 115 V. articulata accessions classified by geographical origin and biological status. (B) Bar plot showing the genetic diversity structure for the 115 genotypes based on SSR profiles using the program STRUCTURE and k = 3 simulation. Different colors represent individuals belonging to different clusters. (C) Dendrogram generated from nine SSR primers in the one-flower vetch genotypes using hierarchical clustering analysis based on genetic diversity of tested accessions. Note different geographical origins. Color codes: Spanish landraces (black), non-Spanish landraces (blue), commercial cultivars (red), and other wild populations (green) accessions. Asterisks indicate accessions selected during this work as core collection members.
Figure 1. Structure and genetic diversity of one-flower vetch collection. (A) Summary of CRF collection containing 115 V. articulata accessions classified by geographical origin and biological status. (B) Bar plot showing the genetic diversity structure for the 115 genotypes based on SSR profiles using the program STRUCTURE and k = 3 simulation. Different colors represent individuals belonging to different clusters. (C) Dendrogram generated from nine SSR primers in the one-flower vetch genotypes using hierarchical clustering analysis based on genetic diversity of tested accessions. Note different geographical origins. Color codes: Spanish landraces (black), non-Spanish landraces (blue), commercial cultivars (red), and other wild populations (green) accessions. Asterisks indicate accessions selected during this work as core collection members.
Agronomy 14 00326 g001
Agronomy 14 00326 g002
Figure 2. Structure and genetic diversity of bitter vetch collection. (A) Summary of CRF collection containing 296 V. ervilia accessions classified by geographical origin and biological status. (B) Bar plot showing the genetic diversity structure for the genotypes based on SSR profiles using the program STRUCTURE and k = 3 simulation. Different colors represent individuals belonging to different clusters. (C) Dendrogram generated from 11 SSR primers in the bitter vetch genotypes using hierarchical clustering analysis based on genetic diversity of tested accessions. Note different geographical origins. Color codes: Spanish landraces (black), non-Spanish landraces (blue), commercial cultivars (red), and other wild populations (green) accessions. Asterisks indicate accessions selected during this work as core collection members.
Figure 2. Structure and genetic diversity of bitter vetch collection. (A) Summary of CRF collection containing 296 V. ervilia accessions classified by geographical origin and biological status. (B) Bar plot showing the genetic diversity structure for the genotypes based on SSR profiles using the program STRUCTURE and k = 3 simulation. Different colors represent individuals belonging to different clusters. (C) Dendrogram generated from 11 SSR primers in the bitter vetch genotypes using hierarchical clustering analysis based on genetic diversity of tested accessions. Note different geographical origins. Color codes: Spanish landraces (black), non-Spanish landraces (blue), commercial cultivars (red), and other wild populations (green) accessions. Asterisks indicate accessions selected during this work as core collection members.
Agronomy 14 00326 g002
Agronomy 14 00326 g003
Figure 3. Structure and genetic diversity of narbon vetch collection. (A) Summary of CRF collection containing 33 V. narbonensis accessions classified by geographical origin and biological status. (B) Bar plot showing the genetic diversity structure for the genotypes based on SSR profiles using the program STRUCTURE and k = 5 simulation. Different colors represent individuals belonging to different clusters. (C) Dendrogram generated from 17 SSR primers in the narbon vetch genotypes using hierarchical clustering analysis based on genetic diversity of tested accessions. Note different biological statuses. Color codes: landraces (black), commercial cultivars (red), and other wild populations (blue) accessions.
Figure 3. Structure and genetic diversity of narbon vetch collection. (A) Summary of CRF collection containing 33 V. narbonensis accessions classified by geographical origin and biological status. (B) Bar plot showing the genetic diversity structure for the genotypes based on SSR profiles using the program STRUCTURE and k = 5 simulation. Different colors represent individuals belonging to different clusters. (C) Dendrogram generated from 17 SSR primers in the narbon vetch genotypes using hierarchical clustering analysis based on genetic diversity of tested accessions. Note different biological statuses. Color codes: landraces (black), commercial cultivars (red), and other wild populations (blue) accessions.
Agronomy 14 00326 g003
Table 1. Cross-transferability analysis within Vicia genus using heterologous SSR markers from donor species over the indicated target species DNA. Homologous amplifications are indicated as controls (bold/shadowed cells).
Table 1. Cross-transferability analysis within Vicia genus using heterologous SSR markers from donor species over the indicated target species DNA. Homologous amplifications are indicated as controls (bold/shadowed cells).
SSR Marker Donor
Species
VsSSR310VsSSR102VsSSR179VsSSR185VsSSR073VsSSR140VsSSR217VsSSR129VsSSR138VsSSR115VsSSROVsSSRPVsSSRSVsSSRNVeSSR02VeSSR05VeSSR07VeSSR09V. sativa
(VsSSRs)		V. ervilia
(VsSSRs)
Target Species V. sativa++++++++++++++++++100%
(14/14)		100%
(4/4)
V. ervilia+−+−+−−+−−−+++++++50%
(7/14)		100%
(4/4)
V. narbonensis++++++−+++++++++++93%
(13/14)		100%
(4/4)
V. articulata+++−++−+−−−+++−−−−64%
(9/14)		0%
(0/4)
Table 2. Diversity statistics from nine SSR tested in accessions of V. articulata (n = 115 total collection).
Table 2. Diversity statistics from nine SSR tested in accessions of V. articulata (n = 115 total collection).
LocusNaNeFIPICHoHeuHe
VsSSR073 71.5380.5030.8040.5490.1740.3500.351
VsSSR10273.3700.5551.3730.3370.3130.7030.706
VsSSR129 91.7940.9411.0760.6480.0260.4430.445
VsSSR14041.0730.2320.1870.6430.0520.0680.068
VsSSR17952.067−0.1620.8940.0670.6000.5160.519
VsSSR31072.3530.7731.2420.4350.1300.5750.578
VsSSRN101.3160.4210.6280.4310.1390.2400.241
VsSSRP73.2980.0141.3550.7680.6870.6970.700
VsSSRS94.8950.2681.7810.2350.5830.7960.799
Mean7.2222.4120.3941.0380.4570.3000.4880.49
SE0.6410.4100.1170.1570.2090.0860.0790.08
Na, allele number; Ne, effective allele number; Ho, observed heterozygosity; He, expected heterozygosity; uHe, unbiased He; PIC, polymorphic information content; I, Shannon’s Information Index; F, Fixation Index.
Table 3. Diversity statistics from SSRs tested in landraces (Ls), wild populations (WPs), and commercial cultivars (CCs) of one-flower vetch CRF collection.
Table 3. Diversity statistics from SSRs tested in landraces (Ls), wild populations (WPs), and commercial cultivars (CCs) of one-flower vetch CRF collection.
PopulationNNaNeHoHeuHeFPICHN. Private Alleles
Landraces1117.11 ± 0.662.40 ± 0.410.30 ± 0.090.49 ± 0.080.49 ± 0.080.37 ± 0.120.45 ± 0.231.03 ± 0.1643
Wild Relatives21.14 ± 0.241.40 ± 0.210.28 ± 0.150.18 ± 0.090.24 ± 0.120.60 ± 0.230.15 ± 0.2210.27 ± 0.140
Commercial Cultivars21.78 ± 0.281.66 ± 0240.22 ± 0.120.29 ± 0.100.39 ± 0.130.25 ± 0.250.24 ± 0.240.45 ± 0.151
Na, allele number; Ne, effective allele number; Ho, observed heterozygosity; He, expected heterozygosity; uHe, unbiased He; PIC, polymorphic information content; F, Fixation Index.
Table 4. Diversity statistics from 11 SSRs tested in accessions of V. ervillia (n = 296 total collection).
Table 4. Diversity statistics from 11 SSRs tested in accessions of V. ervillia (n = 296 total collection).
LocusNaNeFIPICHoHeuHe
VeSSR0282.5850.3921.1710.5560.0950.6130.614
VeSSR0583.1870.7911.3290.6320.3380.6860.687
VeSSR07102.5860.6031.3060.5870.1350.6130.614
VeSSR09104.8100.8501.7500.7620.2160.7920.793
VsSSR073 51.2210.8390.1420.1720.0270.1810.181
VsSSR129 2817.1140.8882.9740.9390.1520.9420.943
VsSSR179104.0550.6251.5790.7190.0840.7530.755
VsSSR31042.3140.8460.9630.5160.2130.5680.569
VsSSRN61.3040.5080.4700.2270.1420.2330.234
VsSSRP114.4340.7801.7700.7500.1620.7740.776
VsSSRS91.5570.7270.8630.3430.1420.3580.358
Mean9.9094.1060.7131.3020.5640.1550.5920.593
SE1.9331.3520.0480.2160.2370.0250.0730.073
Na, allele number; Ne, effective allele number; Ho, observed heterozygosity; He, expected heterozygosity; uHe, unbiased He; PIC, polymorphic information content; I, Shannon’s Information Index; F, Fixation Index.
Table 5. Diversity statistics from SSRs tested in landraces (Ls), wild population (WPs), and commercial cultivars (CCs) of bitter vetch CRF collection.
Table 5. Diversity statistics from SSRs tested in landraces (Ls), wild population (WPs), and commercial cultivars (CCs) of bitter vetch CRF collection.
GroupNNaNeHoFIPICHeuHePriv. A.
LR2859.91 ± 1.934.12 ± 1.370.16 ± 0.020.71 ± 0.051.36 ± 0.220.56 ± 0.230.59 ± 0.070.59 ± 0.0768
WP11.18 ± 0.121.18 ± 0.120.18 ± 0.121.00 ± 0.000.13 ± 0.080.15 ± 0.280.09 ± 0.060.18 ± 0.120
CC103.45 ± 0.392.41 ± 0.380.10 ± 0.030.73 ± 0.100.91 ± 0.140.45 ± 0.200.49 ± 0.070.52 ± 0.070
Na, allele number; Ne, effective allele number; Ho, observed heterozygosity; He, expected heterozygosity; uHe, unbiased He; PIC, polymorphic information content; I, Shannon’s Information Index; F, Fixation Index; Priv. A.: private alleles.
Table 6. Diversity statistics from 17 SSRs tested in accessions of V. narbonensis (n = 33; total collection).
Table 6. Diversity statistics from 17 SSRs tested in accessions of V. narbonensis (n = 33; total collection).
LocusNaNeFIPICHoHeuHe
VsSSR31043.3460.4771.2730.6440.3670.7010.713
VsSSR10253.4300.8721.3420.6550.0910.7080.719
VsSSR17973.1840.1161.4300.6460.6060.6860.697
VsSSR18585.1581.0001.8660.7860.0000.8060.836
VsSSR07364.0550.8341.5420.7140.1250.7530.765
VsSSR14031.575−0.1980.6750.3350.4380.3650.371
VsSSR129105.4610.6171.9650.7960.3130.8170.830
VsSSR13841.7610.6490.8010.3900.1520.4320.439
VsSSR11521.031−0.0150.0790.0290.0300.0300.030
VsSSRO42.1500.0370.9240.4620.5150.5350.543
VsSSRP74.7550.6551.6710.7580.2730.7900.802
VsSSRS53.0500.5941.2540.6150.2730.6720.683
VsSSRN31.6030.2750.6890.3440.2730.3760.382
VeSSR0283.6920.6681.6150.7000.2420.7290.740
VeSSR0553.7550.0501.4460.6910.6970.7340.745
VeSSR0731.598−0.2960.6110.3150.4850.3740.380
VeSSR0962.3730.6331.1050.5180.2120.5790.587
Mean5.2943.0570.4101.1930.5530.2990.5930.604
SE0.5270.3250.0950.1220.2110.0480.0520.053
Na, allele number; Ne, effective allele number; Ho, observed heterozygosity; He, expected heterozygosity; uHe, unbiased He; PIC, polymorphic information content; I, Shannon’s Information Index; F, Fixation Index.
Table 7. Diversity statistics from SSRs tested in landraces (Ls), wild populations (WPs), and commercial cultivars (CCs) of narbon vetch CRF collection.
Table 7. Diversity statistics from SSRs tested in landraces (Ls), wild populations (WPs), and commercial cultivars (CCs) of narbon vetch CRF collection.
GroupNNaNeFIPICHoHeuHePriv. A.
L174.29 ± 0.382.73 ± 0.240.38 ± 0.101.07 ± 0.100.52 ± 0.190.30 ± 0.050.57 ± 0.050.59 ± 0.0515
WP83.71 ± 0.352.87 ± 0.310.46 ± 0.091.05 ± 0.110.52 ± 0.210.28 ± 0.050.57 ± 0.050.61 ± 0.065
CC83.41 ± 0.322.52 ± 0.330.35 ± 0.140.94 ± 0.110.47 ± 0.200.31 ± 0.070.51 ± 0.050.55 ± 0.066
L = landrace; WP, wild population; CC, commercial cultivar; Na, allele number; Ne, effective allele number; Ho, observed heterozygosity; He, expected heterozygosity; uHe, unbiased He; PIC, polymorphic information content; I, Shannon’s Information Index; F, Fixation Index; Priv. A.: private alleles.
Table 8. Measurements of agromorphological traits in accessions of the one-flower vetch (V. articulata) collection.
Table 8. Measurements of agromorphological traits in accessions of the one-flower vetch (V. articulata) collection.
Quantitative Agromorphological Traits
AverageSDMaxMin
Flowering
  Days to first flowering (d)159.46.0175.0139.0
  Days to 50% flowering (d)169.610.2211.0143.0
  Days to final flowering (d)208.611.4228.0175.0
  Days to maturity (d)221.56.4232.0196.0
Plant
  Height (cm)70.119.7121.135.8
  First pod height (cm)24.58.555.612.2
  Number of main branches7.242.7515.602.90
Pod/Seed
  Number of pods per plant74.7436.99195.7021.10
  Number of seeds per pod2.680.273.402.00
  Seed length (mm)4.730.245.434.12
  Seed width (mm)4.620.215.144.05
  Seed thickness (mm)2.640.233.922.07
  100-seed weight (g)4.190.435.403.36
  Protein content (mg/g seed)26.282.4932.2021.81
Table 9. Measurements of agromorphological traits in accessions of the bitter vetch (V. ervilia) collection.
Table 9. Measurements of agromorphological traits in accessions of the bitter vetch (V. ervilia) collection.
Quantitative Agromorphological Traits
AverageSDMaxMin
Flowering
Days to 50% flowering (d)154.48.2189.0133.0
Days to maturity (d)188.98.7225.0152.0
Plant
Height (cm)42.56.764.923.2
First pod height (cm)24.75.741.37.2
Leaf
Leaf length (mm)99.712.4168.059.6
Length of basal leaflet (mm)14.62.020.110.0
Width of basal leaflet (mm)3.60.65.52.1
Flower
Number of flowers by peduncle2.70.54.21.6
Pod/seed
Racime number per plant25.423.3123.23.6
Pod number per plant41.532.5179.86.1
Seeds per pod2.90.43.91.1
100-seed weight (g)3.80.65.92.6
Table 10. Measurements of agromorphological traits in accessions of the narbon vetch (V. narbonensis) collection.
Table 10. Measurements of agromorphological traits in accessions of the narbon vetch (V. narbonensis) collection.
Quantitative Agromorphological Traits
AverageSDMaxMin
Flowering
Days to first flowering (d)127.67.6151.0116.0
Days to 50% flowering (d)134.411.3179.0121.0
Days to final flowering (d)183.48.5208.0156.0
Days to maturity (d)193.96.6216.0183.0
Plant
Height (cm)61.413.889.537.8
First pod height (cm)25.27.339.512.7
Branches per plant3.61.67.62.1
Leaf
Petiole length (mm)2.00.52.91.0
Leaflet area (mm2)863.0224.31668.5573.3
Leaflet length (mm)44.26.068.235.0
Leaflet width (mm)28.03.337.422.9
Pod/seed
Pod number per plant15.210.856.71.5
Ovules per pod6.00.99.04.5
Harvest Index29.217.152.30.7
100-seed weight (g)20.76.826.85.5
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.

Share and Cite

MDPI and ACS Style

López-Román, M.I.; De la Rosa, L.; Marcos-Prado, T.; Ramírez-Parra, E. Cross-Species Transferability of SSR Markers for Analyzing Genetic Diversity of Different Vicia species Collections. Agronomy 2024, 14, 326. https://doi.org/10.3390/agronomy14020326

AMA Style

López-Román MI, De la Rosa L, Marcos-Prado T, Ramírez-Parra E. Cross-Species Transferability of SSR Markers for Analyzing Genetic Diversity of Different Vicia species Collections. Agronomy. 2024; 14(2):326. https://doi.org/10.3390/agronomy14020326

Chicago/Turabian Style

López-Román, María Isabel, Lucía De la Rosa, Teresa Marcos-Prado, and Elena Ramírez-Parra. 2024. "Cross-Species Transferability of SSR Markers for Analyzing Genetic Diversity of Different Vicia species Collections" Agronomy 14, no. 2: 326. https://doi.org/10.3390/agronomy14020326

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop