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. 2016 Dec 19;23(1):197–205. doi: 10.1007/s12298-016-0397-4

Genetic variation of a global germplasm collection of chickpea (Cicer arietinum L.) including Italian accessions at risk of genetic erosion

C De Giovanni 1,✉,#, S Pavan 1,✉,#, F Taranto 1, V Di Rienzo 1, M M Miazzi 1, A R Marcotrigiano 1, G Mangini 1, C Montemurro 1, L Ricciardi 1, C Lotti 2
PMCID: PMC5313401  PMID: 28250595

Abstract

Chickpea (Cicer arietinum L.) is one of the most important legumes worldwide. We addressed this study to the genetic characterization of a germplasm collection from main chickpea growing countries. Several Italian traditional landraces at risk of genetic erosion were included in the analysis. Twenty-two simple sequence repeat (SSR) markers, widely used to explore genetic variation in plants, were selected and yielded 218 different alleles. Structure analysis and hierarchical clustering indicated that a model with three distinct subpopulations best fits the data. The composition of two subpopulations, named K1 and K2, broadly reflects the commercial classification of chickpea in the two types desi and kabuli, respectively. The third subpopulation (K3) is composed by both desi and kabuli genotypes. Italian accessions group both in K2 and K3. Interestingly, this study highlights genetic distance between desi genotypes cultivated in Asia and Ethiopia, which respectively represent the chickpea primary and the secondary centres of diversity. Moreover, European desi are closer to the Ethiopian gene pool. Overall, this study will be of importance for chickpea conservation genetics and breeding, which is limited by the poor characterization of germplasm collection.

Keywords: Chickpea, Genetic diversity, SSR, Population structure

Introduction

Chickpea (Cicer arietinum L.) is a self-pollinated legume species (2n = 2x = 16). It is the third most cultivated legume in the world (FAOSTAT 2013) and is typically grown in the cold season of semi-arid regions. Vavilov (1926) supported the idea of Southwest Asia being the primary centre of origin, with Ethiopia as the secondary centre (Van Der Maesen 1987).

Two commercial types of chickpea, differing for seed morphological traits, are grown globally: desi and kabuli. Desi seeds, angular and dark-coloured, are mainly produced in the Asia and Ethiopia, and represent about 75% of world chickpea production. Kabuli seeds are owl-shaped, beige coloured and are generally grown in the Mediterranean region and Mexico (Kassie et al. 2009).

In Italy, about 8000 ha are cultivated with chickpea (Italian National Institute of Statistics 2014, www.istat.it/it/files/2014/11/C13.pdf) and in all the Mediterranean countries chickpea is often used in traditional recipes like hummus, panelle, farinata and falafel. Several landraces, that usually owe their name from the cultivation area, are still cultivated in marginal territories and appreciated for their quality. However, modern cultivars, selected for improved agronomic and commercial traits, are gradually replacing this gene pool, which is thus seriously exposed to the risks of genetic erosion (Negri 2003; Patanè 2006).

The description of genetic diversity is of great importance for the efficient safeguard of plant germplasm and its utilization for breeding purposes. Several molecular tools, based on DNA polymorphisms, are available to assess plant genetic diversity (Weising et al. 2005; Nybom et al. 2014). Simple Sequence Repeat (SSR) markers are widely used due to their high reproducibility, multi-allelic nature and co-dominant inheritance (Tautz 1989). Several SSR markers were developed and used in chickpea (Hüttel et al. 1999; Udupa and Baum 2001; Lichtenzveig et al. 2005; Sethy et al. 2006; Choudhary et al. 2006; Saxena et al. 2014; Parida et al. 2015; Khajuria et al. 2015). Most of them have a known genomic localization, following linkage analysis (Winter et al. 2000; Nayak et al. 2010; Jamalabadi et al. 2013; Khajuria et al. 2015).

The present study was addressed to the genetic characterization of a germplasm collection including accessions from main chickpea growing countries. A large set of Italian landraces was included in the analysis, resulting in useful information on a threatened gene pool that was still awaiting genetic characterization.

Materials and methods

Plant materials

The chickpea germplasm collection used in this study was made up of 103 accessions (Table 1). Sixty-nine accessions were selected from the USDA genebank collection to represent main chickpea growing countries, including those located in the diversity centres of Asia and Ethiopia. Genotypes were assigned to the commercial types desi and kabuli according to the information available at the Genesys global database on plant genetic resources (www.genesys-pgr.org). Thirty-four Italian genotypes were provided from the Institute of Biosciences and Bio-Resources (IBBR-CNR) of Bari (Italy), including 32 landraces and 2 commercial cultivars, Sultano and Califfo. Italian accessions have a clear kabuli phenotype, except for the accessions 110694, 110229 and DEL-01, which have a black seed resembling desi chickpeas.

Table 1.

List of the 103 Cicer arietinum accessions genotyped in this study

Accession number Origin Seed type Biological status Structure
PI 115448 India Desi Traditional cultivar/landrace K1
PI 359054 India Desi Traditional cultivar/landrace K1
PI 450561 India Desi Traditional cultivar/landrace Adm
PI 214043 India Desi Traditional cultivar/landrace K1
PI 358927 India Desi Traditional cultivar/landrace K1
PI 214312 India Desi Traditional cultivar/landrace K1
PI 315806 India Desi Traditional cultivar/landrace K1
PI 297264 India Desi Traditional cultivar/landrace K1
PI 359014 India Desi Traditional cultivar/landrace K1
PI 212890 India Desi Traditional cultivar/landrace K1
PI 359018 India Desi Traditional cultivar/landrace K1
PI 216026 India Desi Traditional cultivar/landrace K1
PI 512301 India Desi Advanced/improved cultivar K1
PI 358914 India Desi Traditional cultivar/landrace K1
PI 315798 India Desi Traditional cultivar/landrace K3
PI 251514 Iran Desi Traditional cultivar/landrace K3
W6 16882 Iran Kabuli Traditional cultivar/landrace K3
PI 250143 Pakistan Desi Traditional cultivar/landrace K3
PI 359002 Myanmar Desi Traditional cultivar/landrace K1
PI 220649 Afghanistan Desi Traditional cultivar/landrace K1
PI 426565 Pakistan Desi Traditional cultivar/landrace Adm
PI 513144 Pakistan Desi Traditional cultivar/landrace K1
PI 140293 Iran Desi Traditional cultivar/landrace K1
PI 222774 Iran Desi Traditional cultivar/landrace K1
PI 358934 Iran Desi Traditional cultivar/landrace K1
PI 583753 Bangladesh Desi Advanced/improved cultivar K1
110219 Italy Kabuli Traditional cultivar/landrace K3
110398 Italy Kabuli Traditional cultivar/landrace K3
110213 Italy Kabuli Traditional cultivar/landrace K2
110227 Italy Kabuli Traditional cultivar/landrace K3
SANT-01 Italy Kabuli Traditional cultivar/landrace K3
110490 Italy Kabuli Traditional cultivar/landrace K3
110493 Italy Kabuli Traditional cultivar/landrace Adm
110410 Italy Kabuli Traditional cultivar/landrace K3
110467 Italy Kabuli Traditional cultivar/landrace K3
110412 Italy Kabuli Traditional cultivar/landrace K3
110222 Italy Kabuli Traditional cultivar/landrace K3
110226 Italy Kabuli Traditional cultivar/landrace K3
110229 Italy Desi Traditional cultivar/landrace K3
MAT-02 Italy Kabuli Traditional cultivar/landrace K3
MAT-03 Italy Kabuli Traditional cultivar/landrace K3
DEL-01 Italy Desi Traditional cultivar/landrace K3
110216 Italy Kabuli Traditional cultivar/landrace Adm
110694 Italy Desi Traditional cultivar/landrace K3
110696 Italy Kabuli Traditional cultivar/landrace K3
110400 Italy Kabuli Traditional cultivar/landrace K3
110402 Italy Kabuli Traditional cultivar/landrace K3
110228 Italy Kabuli Traditional cultivar/landrace K3
110231 Italy Kabuli Traditional cultivar/landrace K3
110407 Italy Kabuli Traditional cultivar/landrace K2
110408 Italy Kabuli Traditional cultivar/landrace K2
110397 Italy Kabuli Traditional cultivar/landrace K2
110215 Italy Kabuli Traditional cultivar/landrace K2
110693 Italy Kabuli Traditional cultivar/landrace K2
106900 Italy Kabuli Traditional cultivar/landrace K2
106872 Italy Kabuli Traditional cultivar/landrace K2
106867 Italy Kabuli Traditional cultivar/landrace K2
106941 Italy Kabuli Traditional cultivar/landrace K3
Califfo Italy Kabuli Advanced/improved cultivar K3
Sultano Italy Kabuli Advanced/improved cultivar K3
PI 502999 Mexico Kabuli Advanced/improved cultivar K2
W6 17597 Mexico Kabuli Breeding/research material Adm
PI 507020 Mexico n.a Traditional cultivar/landrace K2
PI 339154 Turkey Kabuli Traditional cultivar/landrace K2
PI 339181 Turkey Kabuli Traditional cultivar/landrace K2
PI 509299 Turkey Kabuli Traditional cultivar/landrace K2
PI 509207 Turkey Kabuli Traditional cultivar/landrace K2
PI 509147 Turkey Kabuli Traditional cultivar/landrace K1
PI 509163 Turkey Kabuli Traditional cultivar/landrace K1
PI 509236 Turkey Kabuli Traditional cultivar/landrace K2
PI 642853 Australia Kabuli Advanced/improved cultivar K3
PI 518255 Australia Desi Traditional cultivar/landrace K1
W6 2973 n.a Kabuli Traditional cultivar/landrace K1
PI 543921 USA Desi Advanced/improved cultivar K1
W6 10046 Bulgaria Desi Traditional cultivar/landrace K3
PI 193487 Ethiopia Desi Traditional cultivar/landrace K3
PI 193481 Ethiopia Desi Traditional cultivar/landrace K3
PI 196840 Ethiopia Desi Traditional cultivar/landrace K3
PI 193479 Ethiopia Desi Traditional cultivar/landrace K2
PI 193480 Ethiopia Desi Traditional cultivar/landrace K2
PI 257586 Ethiopia Desi Traditional cultivar/landrace K3
W6 10451 Russia Desi Traditional cultivar/landrace K3
PI 343014 Russia Kabuli Advanced/improved cultivar K3
PI 343019 Russia Desi Advanced/improved cultivar K3
PI 343016 Russia Kabuli Advanced/improved cultivar K3
PI 503025 USA Kabuli Traditional cultivar/landrace Adm
PI 503001 USA Kabuli Advanced/improved cultivar K2
PI 533683 Spain Desi Advanced/improved cultivar K3
PI 533676 Spain Desi Advanced/improved cultivar K3
PI 543010 Spain Desi Advanced/improved cultivar K3
PI 533681 Spain Kabuli Advanced/improved cultivar K2
PI 533673 Spain Kabuli Advanced/improved cultivar K2
PI 572411 Spain Desi Traditional cultivar/landrace K3
PI 509196 Turkey Kabuli Traditional cultivar/landrace K1
W6 11071 Hungary Kabuli Advanced/improved cultivar K3
PI 508096 USA Desi Advanced/improved cultivar K3
PI 512300 USA Kabuli Advanced/improved cultivar K3
PI 503006 Chile Kabuli Traditional cultivar/landrace K2
W6 2938 n.a. Kabuli Traditional cultivar/landrace K2
PI 292006 Jordan Kabuli Traditional cultivar/landrace Adm
PI 513151 Pakistan Kabuli Traditional cultivar/landrace K2
PI 357651 Serbia-Montenegro Kabuli Advanced/improved cultivar K3
PI 357648 Serbia-Montenegro Kabuli Advanced/improved cultivar K2
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For each genotype, geographical origin, seed type, biological status and subpopulation (K) resulting from STRUCTURE analysis are reported. Adm indicates genotypes of admixed ancestry

Genomic DNA extraction

The first true leaf of a single plant for each accession was collected for DNA extraction, placed in liquid nitrogen and stored at −80 °C until use. Genomic DNA was extracted using the DNeasy 96 Plant Mini Kit (Qiagen, Germany) following the manufacturer’s instructions. DNA concentration and quality were measured by means of a Nano-Drop 1000 Spectrophotometer (Thermo Scientific, Waltham, MA) and 1% agarose gel.

Microsatellite assay

A set of 157 SSR primer pairs was tested in a preliminary assay on 3% agarose gel, using a panel of eight chickpea accessions chosen from the collection. This allowed the pre-selection of polymorphic SSR loci. PCR was carried out in a final volume of 12.5 µl containing 1× Buffer, 0.2 mM of each dNTPs, 0.25 µM of primer pairs, 20 ng of genomic DNA and 0.5 units of DreamTaq DNA polymerase (Thermo Scientific, Waltham, MA). PCR reactions were performed in a C1000 thermal cycler (Bio-Rad, Hercules, CA) with the following conditions: initial denaturation of 5 min at 94 °C; 10 touch-down PCR cycles of 30 s at 94 °C, 45 s at the appropriate annealing temperature and 60 s at 72 °C; 25 PCR cycles of 30 s at 94 °C, 45 s at 50/48 °C and 60 s at 72 °C; final elongation of 5 min at 72 °C. Twenty-two polymorphic primer pairs were tested on the whole germplasm collection using capillary electrophoresis. In detail, forward primers were tagged by adding a 5′ tail with the universal primer M13. The reaction mixture contained 20 ng of genomic DNA, 1x PCR buffer, 0.032 µM forward primer, 0.16 µM reverse primer, 0.08 µM of a primer complementary to the M13 tail and labelled with Fam, Vic, Pet, or Ned fluorescent dyes (Thermo Scientific, Waltham, MA), 0.2 mM dNTPs, 2.5 mM MgCl2, and 0.5 U of DreamTaq DNA polymerase (Thermo Scientific, Waltham, MA) in a final volume of 12.5 µl. PCR products were separated by the ABI PRISM 3130 Avant Genetic Analyzer (Thermo Scientific, Waltham, MA) capillary electrophoresis system, using a mix containing 2 µL PCR reaction, 12 µL Hi-Di Formamide (Thermo Scientific, Waltham, MA) and 0.5 µL GeneScan 600 LIZ Size Standard (Thermo Scientific, Waltham, MA). The allele size was assigned using GeneMapper 5.0 (Applied Biosystem).

Data analysis

The amplified fragments were used to get a binary matrix, in which amplicons were marked with 1 or 0 for presence and absence, respectively. A dendrogram of genetic similarity among the accessions was generated based on the Jaccard’s similarity coefficient and the Unweighted Pair Group Method using Arithmetic Averages (UPGMA) implemented in NTSYS-PC v. 2.0 (Rohlf 1998). Population structure was determined using the Bayesian model-based clustering approach implemented in STRUCTURE v. 2.3.4 (Pritchard et al. 2000), which assigns individuals to K subpopulations according to a membership coefficient (qi). For each K (from 1 to 10), ten runs were performed. A Markov chain Monte Carlo (MCMC) of 100000 burn-in phases followed by 100000 iterations was run to generate the membership coefficient (qi) matrix. The optimal K value was determined using the ad-hoc statistic ΔK (Evanno et al. 2005), which was estimated with the software Structure Harvester (Earl and vonHoldt 2012). Individual samples were assigned to each subpopulation when the value of the corresponding qi was ≥0.6. Genotypes with the highest qi < 0.6 were considered of admixed ancestry.

To evaluate the allelic and genetic diversity for each locus, number of observed alleles (No), expected (He) and observed heterozygosity (Ho), fixation index and Shannon’s information index (I) were calculated using POPGENE v1.32 (https://sites.ualberta.ca/~fyeh/popgene_download.html). The informativeness of each marker was also inferred by the calculation of the Resolving Power (Rp) and Discriminating Power (PD) parameters, as indicated by Prevost and Wilkinson (1999) and Kloosterman et al. (1993).

Results

SSR markers

One-hundred and fifty-seven SSR markers were selected among those reported from Khajuria et al. (2015) (69), Sethy et al. (2006) (17) and from Nayak et al. (2010) (88). Preliminary tests on agarose gel electrophoresis and a subset of eight accessions allowed the identification of 22 polymorphic SSR loci, which were further scored on capillary gel electrophoresis, enabling the discrimination of up to 2 bp length polymorphisms. Information and statistics on each marker are reported in Table 2. In total, 218 different alleles were detected in a germplasm collection of 103 accessions. Marker size ranged from 131 bp (for NCGPR-21) to 344 bp (for ICCM-242) (Table 2). The highest number of alleles (26) was scored for the marker CaGMS-13, whereas the lowest (2) was associated with the markers CaGMS-1235 and NCPGR-76. The average expected heterozygosity (He) was considerably higher (0.70) than observed heterozygosity (Ho) (0.26). Extreme values were 0.30 (CaGMS-561) and 0.94 (CaGMS-1 and CaGMS13) for He and 0.06 (CaGMS-1250 and NCPGR-53) and 0.93 (NCPGR-76) for Ho. In accordance with these data, inbreeding coefficients were positive for most of the markers. The Shannon’s Information Index (I) was on average 1.63 and ranged from 0.66 (CaGMS-1250 and CaGMS-561) to 2.96 (CaGMS13), thus reflecting the effectiveness of the SSR loci in revealing genetic variation. The number of distinguished cultivars (NDC) ranged from 0 (CaGMS-1235, NCPGR-53 and NCPGR-76) to 20 (ICCM-0068). The resolving power (Rp) ranged from 0.17 (NCPGR-76) to 3.6 (ICCM-69). The extreme values of Discrimination power (PD) were associated with NCPGR-76 (0.14) and CaGMS-1 (0.96). Correlation with NDC was highly significant (p < 0.001) for both the PD (r = 0.71) and for the Rp parameter (r = 0.57).

Table 2.

Allelic variation of 22 simple sequence repeat (SSR) loci in 103 chickpea genotypes

SSR LG Range No Ho He F I NDC Rp PD Reference
NCPGR-53 LG1 197–205 4 0.06 0.54 0.89 0.86 0 1.96 0.58 Sethy et al. (2006)
NCPGR-21 LG2 131–175 16 0.15 0.87 0.83 2.25 15 2.28 0.89 Sethy et al. (2006)
CaGMS-24 LG3 228–252 4 0.09 0.51 0.82 0.78 1 1.76 0.60 Khajuria et al. (2015)
CaGMS-1270 LG3 214–228 6 0.17 0.75 0.77 1.47 6 2.42 0.81 Khajuria et al. (2015)
CaGMS-13 LG3 258–327 26 0.11 0.94 0.89 2.96 15 2.33 0.94 Khajuria et al. 2015
ICCM-178 LG3 281–299 7 0.17 0.80 0.79 1.69 5 2.57 0.85 Nayak et al. (2010)
CaGMS-33 LG4 153–185 11 0.14 0.75 0.81 1.73 12 2.29 0.79 Khajuria et al. (2015)
ICCM-0068 LG4 196–268 18 0.28 0.90 0.68 2.47 20 2.73 0.94 Nayak et al. (2010)
CaGMS-1154 LG4 227–235 4 0.16 0.61 0.74 1.13 1 1.72 0.69 Khajuria et al. (2015)
ICCM-0069 LG4 243–284 14 0.80 0.90 0.11 2.39 4 3.60 0.90 Nayak et al. (2010)
CaGMS-18 LG5 212–185 4 0.13 0.63 0.79 1.08 2 2.06 0.69 Khajuria et al. (2015)
CaGMS-992 LG5 173–213 8 0.20 0.76 0.74 1.59 7 2.40 0.83 Khajuria et al. (2015)
ICCM-0076 LG5 265–312 17 0.31 0.89 0.65 2.43 16 2.65 0.91 Nayak et al. (2010)
ICCM-242 LG6 282–344 14 0.17 0.90 0.81 2.41 10 2.34 0.93 Nayak et al. 2010
NCPGR-50 LG6 189–234 17 0.16 0.88 0.81 2.34 14 2.33 0.90 Sethy et al. (2006)
CaGMS-561 LG6 140–156 6 0.20 0.30 0.33 0.66 6 1.05 0.37 Khajuria et al. (2015)
CaGMS-742 LG7 239–263 7 0.14 0.53 0.74 1.09 4 1.48 0.62 Khajuria et al. (2015)
CaGMS-1235 LG8 298–310 2 0.12 0.50 0.75 0.69 0 1.76 0.59 Khajuria et al. (2015)
CaGMS-1250 LG8 242–246 3 0.06 0.44 0.86 0.66 1 1.30 0.49 Khajuria et al. (2015)
CaGMS-1 LG8 237–331 24 0.26 0.94 0.72 2.93 19 2.80 0.96 Khajuria et al. (2015)
NCPGR-86 n.a. 210–216 4 0.85 0.52 −0.64 0.82 1 0.50 0.28 Sethy et al. (2006)
NCPGR-76 n.a. 244–248 2 0.93 0.50 −0.86 0.69 0 0.17 0.14 Sethy et al. (2006)
Mean – – 9.91 0.26 0.70 0.59 1.63 7.23 2.02 0.72 –
Min – – 2.00 0.06 0.30 −0.86 0.66 0 0.17 0.14 –
Max – – 26 0.93 0.94 0.89 2.96 20 3.60 0.96 –
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For each marker, linkage group (LG) localization, number of alleles (No), observed and expected heterozygosity (Ho and He), Wright’s fixation index (F), Shannon’s information index (I), number of distinguished cultivars (NDC), discrimination power (PD) and resolving power (Rp) are reported

Genetic structure

The software STRUCTURE was used to estimate the number of hypothetical subpopulations (K) present in our collection and the probability of each genotype to fall into one of the designated subpopulations. An admixture-based clustering model was used to infer the genetic structure of 103 chickpea accessions. Using the ΔK approach of Evanno et al. (2005), we found that a model with 3 subpopulations (K1; K2; K3) best fits the data with 93.2% of ancestry derived from one of the subpopulations and 6.8% of admixed ancestry (highest membership coefficient q < 0.6) (Fig. 1; Table 1). The subpopulations could be discriminated to a great extent on the basis of the seed commercial type and the geographical origin. In more detail, the subpopulation K1 is formed by 22 desi accessions, all from the Asian continent except for PI543921 (from U.S.) and PI518255 (from Australia), and four kabuli accessions (PI509196, PI509147, PI509163 and W62973); the subpopulation K2 includes 22 kabuli accessions from different geographical origin and two Ethiopian desi accessions (PI193479 and PI193480); the subpopulation K3 groups 27 kabuli and 18 desi accessions. The vast majority of desi K3 accessions originate from Ethiopia and European countries. Of the 34 Italian accessions genotyped in this study, 23 group in the K3 subpopulation, including the commercial cultivars Califfo and Sultano and the black-seeded genotypes 110694, 110229 and DEL-01, 9 group in the K2 subpopulation and 2 are of admixed ancestry.

Fig. 1.

Fig. 1

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Genetic structure of 103 chickpea accessions as revealed by the SSR markers used in this study. a Plot of mean likelihood and standard deviation (SD) for ten independent runs for a number of subpopulations (K) ranging from 1 to 10. b Evanno’s Delta K plot generated by structure analysis. K = 3 shows a peak indicating that three subpopulations sufficiently define genetic variation in the dataset of 103 accessions used in this study. c Bar-plot describing population structure. Each individual is represented by a thin horizontal line, which is partitioned into K coloured segments whose length is proportional to the estimated membership coefficient (q) in each subpopulation (K1, K2 and K3). Individuals with the highest q < 0.6 are not assigned to any of the populations and thus considered of admixed ancestry. (Colour figure online)

Genetic relationships among individuals

The UPGMA dendrogram based on the Jaccard’s similarity supports to a great extent the results obtained with structure analysis. In more detail, two main clusters included most accessions of the subpopulations K1 and K3 (Fig. 2). The rest of the dendrogram includes kabuli accessions from K1, K2 and K3, with the exception of the desi accessions PI358943, PI193479, PI193480 and PI115448.

Fig. 2.

Fig. 2

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Unweighted pair group method with arithmetic mean (UPGMA) dendrogram based on Jaccard’s similarity. Main nodes separating accessions of the subpopulations K1 and K2 are indicated with circles

Discussion

The genetic basis of cultivated chickpea is narrow, as a consequence of several bottlenecks occurring during its evolutionary history (Abbo et al. 2003). This represents a major limition for chickpea breeding (Amin and Melkamu 2014). Therefore, the collection and study of chickpea germplasm is of utmost importance to prevent further genetic erosion and efficiently address breeding efforts. A main objective of this work was the genetic characterization of a global chickpea germplasm collection, including several Italian landraces threatened by the advent of modern cultivars and potentially useful as a source of genes for adaptation and qualitative traits. In total, 218 alleles were scored by the analysis of 103 accessions with 22 SSR primer combinations, corresponding to an average of 9.9 alleles per locus. This confirms the value of SSR markers as a tool to detect intraspecific polymorphism in chickpea (Hüttel et al. 1999; Singh et al. 2003; Upadhyaya et al. 2008; Hajibarat et al. 2015).

For most markers, observed heterozygosity (Ho) was considerably lower than expected heterozygosity (He), leading to high values of inbreeding coefficients. This was expected, as chickpea is a strictly self-pollinated crop. The highest number of discriminated cultivars (NDC) was associated with the marker ICCM-0068. Our work, showing a statistic correlation between NDC and either PD or Rp, supports the conclusion of previous studies reporting a linear relationship between the efficacy of a primer combination to distinguish accessions (NDC) and the two parameters Rp and PD (Prevost and Wilkinson 1999; Fernandez et al. 2002).

A common conclusion from previous studies on chickpea genetic diversity was the distinction of two cultivated gene pools, corresponding to the two main commercial types desi and kabuli (Upadhyaya et al. 2008). Accordingly, structure analysis performed in this work led to the identification of two subpopulations, K1 and K2, which were largely composed by desi and kabuli accessions, respectively. However, our study also supports the identification of a third gene pool (K3), including both desi and kabuli accessions (Fig. 1; Table 1). Moreover, we found that K1 includes four kabuli accessions and K3 includes two desi accessions. Genetic similarity between some desi and kabuli genotypes was reported by previous studies. For example, following the SSR analysis of a chickpea composite collection, Upadhyaya et al. (2008) generated a Neighbour-Joining tree in which a small cluster of desi was included in major branch containing kabuli accessions and vice versa. In addition, the recent work of Penmetsa et al. (2016), evaluating the genetic structure of a representative set of cultivated chickpea, also questioned the strict dichotomy of a desi and kabuli genetic subdivision within cultivated chickpea.

This work highlights genetic divergence between desi accessions from Asia and other geographical origin, including Ethiopia, which is considered a secondary evolutionary centre (Van Der Maesen 1987). Notably, the work of Penmetsa et al. (2016), published during the revision of this manuscript, clearly distinguishes between chickpea gene pools from Ethiopia and the Indian sub-continent. Although, the 103 accessions genotyped in this study might not be representative of the whole genetic variation in cultivated chickpea, another relevant finding is that European desi accessions seem to be closer to the Ethiopian gene pool than to the Asian one (Fig. 2), and might thus originate from the former. Geographical patterns cannot explain the distribution of kabuli germplasm in the two subpopulations K2 and K3. Italian landraces, which can be in most cases classified as kabuli, clustered both in K2 and K3. This might indicate the presence of a wide genetic basis in Italian chickpea germplasm. However, this conclusion needs to be confirmed by future studies on chickpea genetic diversity.

In conclusion, the results of this study provide insights on the genetic diversity of cultivated chickpea and is expected to be useful for conservation genetics and breeding. We are currently performing an extensive characterization of agronomic, nutritional and technological properties of Italian accessions characterized in this study at the DNA level, in order to detect the traits of interest for breeding programs.

Acknowledgements

This work was supported by the SaVeGraINPuglia Programme (Reg.CE n. 1698/2005 Programma di Sviluppo rurale per la Puglia 2007/2013. Misura 214—Azione 4 Sub azione a). The authors would like to acknowledge Dr. Venturino Bisignano for kindly providing some Apulian genotypes characterized in this study.

Footnotes

C. De Giovanni and S. Pavan have contributed equally to this work.

Contributor Information

C. De Giovanni, Email: claudio.degiovanni@uniba.it

S. Pavan, Email: stefano.pavan@uniba.it

References

  1. Abbo S, Berger J, Turner NC. Evolution of cultivated chickpea: four bottlenecks limit diversity and constrain adaptation. Funct Plant Biol. 2003;30:1081–1087. doi: 10.1071/FP03084. [DOI] [PubMed] [Google Scholar]
  2. Amin M, Melkamu F. Management of Ascochyta Blight (Ascochyta rabiei) in chickpea using a new fungicide. Res Plant Sci. 2014;2:27–32. [Google Scholar]
  3. Choudhary S, Sethy NK, Shokeen B, Bhatia S. Development of sequence tagged microsatellite site markers for chickpea (Cicer arietinum L.) Mol Ecol Notes. 2006;6:93–95. doi: 10.1111/j.1471-8286.2005.01150.x. [DOI] [Google Scholar]
  4. Earl DA, vonHoldt BM. STRUCTURE HARVESTER: a website and program for visualizing STRUCTURE output and implementing the Evanno method. Conserv Genet Resour. 2012;4:359–361. doi: 10.1007/s12686-011-9548-7. [DOI] [Google Scholar]
  5. 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. doi: 10.1111/j.1365-294X.2005.02553.x. [DOI] [PubMed] [Google Scholar]
  6. Faostat (2013) Agriculture data. http://faostat.fao.org/site/567/default.aspx# ancor. Accessed Nov 2013
  7. Fernández M, Figueiras A, Benito C. The use of ISSR and RAPD markers for detecting DNA polymorphism, genotype identification and genetic diversity among barley cultivars with known origin. TAG Theor Appl Genet. 2002;104(4):845–851. doi: 10.1007/s00122-001-0848-2. [DOI] [PubMed] [Google Scholar]
  8. Hajibarat Z, Saidi A, Hajibarat Z, Taleb R. Characterization of genetic diversity in chickpea using SSR markers, Start Codon Targeted Polymorphism (SCoT) and Conserved DNA-Derived Polymorphism (CDDP) Physiol Mol Biol Plant. 2015;21:365–373. doi: 10.1007/s12298-015-0306-2. [DOI] [PMC free article] [PubMed] [Google Scholar]
  9. Hüttel B, Winter P, Weising K, Choumane W, Weigand F, Kahl G. Sequence-tagged microsatellite site markers for chickpea (Cicer arietinum L.) Genome. 1999;42:210–217. doi: 10.1139/g98-122. [DOI] [PubMed] [Google Scholar]
  10. Javad JG, Saidi A, Karami A, Kharkesh M, Talebi R. Molecular Mapping and Characterization of Genes Governing Time to Flowering, Seed Weight, and Plant Height in an Intraspecific Genetic Linkage Map of Chickpea (Cicer arietinum). Biochem Genet. 2013;51(5–6):387–397. doi: 10.1007/s10528-013-9571-3. [DOI] [PubMed] [Google Scholar]
  11. Kassie M, Shiferaw B, Asfaw S, Abate T, Geoffrey M, Setotaw F, Eshete M, Assefa K (2009) Current situation and future outlooks of the chickpea sub-sector in Ethiopia. ICRISAT working paper. ICRISAT and EIAR. 39 pp. www.icrisat.org/tropicallegumesII
  12. Khajuria YP, Saxena MS, Gaur R, Chattopadhyay D, Jain M, Parida SK, Bhatia S. Development and integration of genome-wide polymorphic microsatellite markers onto a reference linkage map for constructing a high-density genetic map of chickpea. PLoS ONE. 2015 doi: 10.1371/journal.pone.0125583. [DOI] [PMC free article] [PubMed] [Google Scholar]
  13. Kloosterman AD, Budowle B, Daselaar P. PCR amplification and detection of the human D1S80 VNTR locus: amplification conditions, population genetics and application forensic analysis. Int J Leg Med. 1993;105:257–264. doi: 10.1007/BF01370382. [DOI] [PubMed] [Google Scholar]
  14. Lichtenzveig J, Scheuring C, Dodge J, Abbo S, Zhang HB. Construction of BAC and BIBAC libraries and their applications for generation of SSR markers for genome analysis of chickpea, Cicer arietinum L. Theor Appl Genet. 2005;110:492–510. doi: 10.1007/s00122-004-1857-8. [DOI] [PubMed] [Google Scholar]
  15. Nayak SN, Zhu H, Varghese N, Datta S, Choi HK, Horres R, Jüngling R, Singh J, Kishor PB, Sivaramakrishnan S, Hoisington DA, Kahl G, Winter P, Cook DR, Varshney RK. Integration of novel SSR and gene-based SNP marker loci in the chickpea genetic map and establishment of new anchor points with Medicago truncatula genome. Theor Appl Genet. 2010;120:1415–1441. doi: 10.1007/s00122-010-1265-1. [DOI] [PMC free article] [PubMed] [Google Scholar]
  16. Negri V. Landraces in central Italy: where and why they are conserved and perspectives for their on-farm conservation. Genet Resour Crop Evol. 2003;50:877–888. doi: 10.1023/A:1025933613279. [DOI] [Google Scholar]
  17. Nybom H, Weising K, Rotter B. DNA fingerprinting in botany: past, present, future. Investig Genet. 2014;5(1):1. doi: 10.1186/2041-2223-5-1. [DOI] [PMC free article] [PubMed] [Google Scholar]
  18. Parida SK, Verma M, Yadav SK, Ambawat S, Das S, Garg R, Jain M. Development of genome-wide informative simple sequence repeat markers for large scale genotyping application sin chickpea and development of web resource. Front in Plant Sci. 2015;6(645):1–12. doi: 10.3389/fpls.2015.00645. [DOI] [PMC free article] [PubMed] [Google Scholar]
  19. Patanè C. Variation and relationships among some nutritional traits in Sicilian genotypes of chickpea (Cicer arietinum L.) J Food Qual. 2006;29:282–293. doi: 10.1111/j.1745-4557.2006.00074.x. [DOI] [Google Scholar]
  20. Penmetsa VR, Carrasquilla-Garcia N, Bergmann EM, Vance L, Castro B, Kassa MT, Sarma BK, Datta S, Farmer AD, Baek JM, Coyne CJ, Varshney RK, von Wettberg EJB, Cook DR. Multiple post-domestication origins of Kabuli chickpea through allelic variation in a diversification-associated transcription factor. New Phytol. 2016;211:1440–1451. doi: 10.1111/nph.14010. [DOI] [PubMed] [Google Scholar]
  21. Prevost A, Wilkinson MJ. A new system of comparing PCR primers applied to ISSR fingerprinting of potato cultivars. Theor Appl Genet. 1999;98:107–112. doi: 10.1007/s001220051046. [DOI] [Google Scholar]
  22. Pritchard JK, Stephens M, Donnelly P. Inference of population structure using multilocus genotype data. Genetics. 2000;155:945–959. doi: 10.1093/genetics/155.2.945. [DOI] [PMC free article] [PubMed] [Google Scholar]
  23. Rohlf FJ. NTSYS-pc. Numerical taxonomy and multivariate analysis system, version 2.02. New York: Exeter Software; 1998. [Google Scholar]
  24. Saxena MS, Bajaj D, Kujur A, Das S, Badoni S, Kumar V, Singh M, Bansal KC, Tyagi AK, Parida SK. Natural allelic diversity, genetic structure and linkage disequilibrium pattern in wild chickpea. PLoS One. 2014 doi: 10.1371/journal.pone.0107484. [DOI] [PMC free article] [PubMed] [Google Scholar]
  25. Sethy NK, Shokeen B, Edwards KJ, Bhatia S. Development of microsatellite markers and analysis of intraspecific genetic variability in chickpea (Cicer arietinum L.) Theor Appl Genet. 2006;112:1416–1428. doi: 10.1007/s00122-006-0243-0. [DOI] [PubMed] [Google Scholar]
  26. Singh R, Prasad CD, Singhal V, Randhawa GJ. Assessment of genetic diversity in chickpea cultivars using RAPD, AFLP and STMS markers. J Gen Breed. 2003;57:165–174. [Google Scholar]
  27. Tautz D. Hypervariability of simple sequences as a general source of polymorphic DNA markers. Nucleic Acids Res. 1989;17:6463–6471. doi: 10.1093/nar/17.16.6463. [DOI] [PMC free article] [PubMed] [Google Scholar]
  28. Udupa SM, Baum M. High mutation rare and mutational bias at (TAA)n microsatellite loci in chickpea (Cicer arietinum L.) Mol Genet Genomics. 2001;266:343–344. doi: 10.1007/s004380100568. [DOI] [PubMed] [Google Scholar]
  29. Upadhyaya HD, Dwivedi SL, Baum M, Varshney RK, Udupa SM, Gowda Cholenahalli LL, Hoisington D, Singh S. Genetic structure, diversity, and allelic richness in composite collection and reference set in chickpea (Cicer arietinum L.) BMC Plant Biol. 2008;8:106. doi: 10.1186/1471-2229-8-106. [DOI] [PMC free article] [PubMed] [Google Scholar]
  30. Van Der Maesen LJG. Origin, history and taxonomy of chickpea. In: Saxena MJ, Singh KB, editors. The chickpea. Cambridge: CAB International; 1987. pp. 11–34. [Google Scholar]
  31. Vavilov NI. Studies on the origin of cultivated plants. Leningrad: Inst Appl Bot Plant Breed; 1926. [Google Scholar]
  32. Weising K, Nybom H, Pfenninger M, Wolff K, Kahl G. DNA fingerprinting in plants: principles, methods, and applications. 2. Boca Raton: CRC Press; 2005. [Google Scholar]
  33. Winter P, Benko-Iseppon AM, Hüttel B, Ratnaparkhe M, Tullu A, Sonnante G, Pfaff T, Tekeoglu M, Santra D, Sant VJ, Rajesh PN, Kahl GF, Muehlbauer J. A linkage map of the chickpea (Cicer arietinum L.) genome based on recombinant inbred lines from a C. arietinum×C. reticulatum cross: localization of resistance genes for fusarium wilt races 4 and 5. Theor Appl Genet. 2000;101(7):1155–1163. doi: 10.1007/s001220051592. [DOI] [Google Scholar]

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