RESEARCH ARTICLE

Allelic diversity between and within three wild annual Cicerspecies

Zvi Peleg • Alon Shabtay • Shahal Abbo

Received: 23 March 2014 / Accepted: 2 June 2014 / Published online: 26 June 2014

� Springer Science+Business Media Dordrecht 2014

Abstract Most wild Cicer species have narrow eco-

geographic amplitude. Likewise, domesticated chick-

pea suffers from severe adaptive limitations due to its

unique evolutionary history. The wild progenitor may

offer only limited adaptive allelic variation for

improving the chickpea crop. Therefore, there is a

need to explore allelic diversity between and within

annual Cicer sp. that span diverse natural habitats.

Here we characterized the allelic diversity between

and within wild populations of C. pinnatifidum, C.

judaicum and C. cuneatum spanning most of their

documented native range in Turkey, Israel and Ethi-

opia. Eco-geographical analysis resulted in clear

separation between the collection sites of C. cuneatum

in east Africa and the other two east Mediterranean

species. Analysis of molecular variance shows that

only 18 % of the allelic variation accounts for

differences between the three species, while 34 %

was contributed from difference between populations.

Interestingly, most (48 %) of the allelic variation was

detected among accessions within populations. PCoA

analysis confirmed the independent taxonomic and

indeed the genetic integrity of the two east Mediter-

ranean sister species C. pinnatifidum and C. judaicum.

Conservation of large rich populations seems a more

effective strategy than the preservation of small thin

populations of annual Cicer sp. Given the relatively

narrow geographic range of most annual Cicer sp.,

accessing germplasm lines from ecologically distinct

habitats emerges as the most promising strategy for the

identification of useful adaptive allelic variation.

Keywords Chickpea � Cicer cuneatum � Cicer

judaicum � Cicer pinnatifidum � Eco-geographic

adaptation � Genetic diversity � Microsatellites

Introduction

Chickpea (Cicer arietinum L.) is an important grain

legume crop across the Mediterranean basin, East

Africa, the Indian sub-continent and in certain New

World regions. In rotation with cereals chickpea has

an indispensable role in breaking disease cycles and

fixing atmospheric nitrogen (e.g. Singh 1997; Kumar

and Abbo 2001). In recent years chickpea production

has increased, placing it now as the second in

importance grain legume in global terms (http://

faostat.fao.org/site/567/default.aspx#ancor). Tradi-

tionally, chickpea was of relatively lesser significant in

the economy of highly industrialized nations, and as a

Electronic supplementary material The online version ofthis article (doi:10.1007/s10722-014-0141-2) contains supple-mentary material, which is available to authorized users.

Z. Peleg (&) � A. Shabtay � S. Abbo

The Levi Eshkol School of Agriculture, The Robert H.

Smith Faculty of Agriculture, Food and Environment,

The Hebrew University of Jerusalem, P.O. Box 12,

7610001 Rehovot, Israel

e-mail: zvi.peleg@mail.huji.ac.il

123

Genet Resour Crop Evol (2015) 62:177–188

DOI 10.1007/s10722-014-0141-2

consequence our understanding of the biological and

the ecological determinants of its yield potential was

limited as compared with better studied grain crops

like maize (Zea mays L.), rice (Oryza sativa L.), wheat

(Triticum aestivum L.), and soybean (Glycine max (L.)

Merr.) (e.g. Kumar and Abbo 2001).

Massive efforts conducted in ICRISAT and else-

where in recent years have brought chickpea genetics

and genomics to the forefront thereby providing new

opportunities for identification of the genetic systems

that control grain yield (e.g. Lichtenzveig et al. 2005;

Hiremath et al. 2012; Nayak et al. 2010; Varshney

et al. 2012, 2013). However, while sequence and

genomic data are no longer likely to limit crop

physiology studies or molecular breeding efforts, it

becomes clear that phenotyping of diverse domesti-

cated and wild germplasm are likely to be the weakest

link. While domesticated chickpea germplasm collec-

tions are rich and diverse (Pundir et al. 1988), and have

been analysed by large scale field experiments (e.g.

Berger et al. 2006), wild Cicer germplasm collections

are still quite small relative to the number of acces-

sions from the wild progenitors of the temperate

cereals (wheat and barley) deposited in genebanks

(Berger et al. 2003). Efforts to increase the number of

Cicer accessions are currently being done by various

groups and this is likely to create an impact in the near

future.

Although the genus Cicer as a whole spans a vast

geographic range, from the Canary Islands in the west

to the Himalaya foothills in the east and from

Uzbekistan in the north to Ethiopia in the south, most

of the annual and perennial Cicer taxa have a rather

limited geographic distribution attesting to their strict

ecological affinities and indeed narrow adaptive range

(e.g. Abbo et al. 2003; Berger et al. 2003; van der

Maesen 1972). More specifically, the relatively nar-

row range of the wild progenitor of domesticated

chickpea, C. reticulatum Ladiz., suggests that the

prospects for improving the adaptive range of domes-

ticated chickpea by direct crossing and recruiting

environmental adaptation alleles from this species into

modern high yielding cultivars are quite limited. As a

consequence, an alternative strategy involving more

remote taxa and employing comparative genetic

approaches was proposed (e.g. Ben-David and Abbo

2005; Abbo and Mallikarjuna 2008). Regrettably

however, recent attempts to apply the latter approach

faced difficulties and progress was limited due to

crossability barriers between closely related wild taxa

(e.g. Abbo et al. 2011).

As part of our interest in chickpea and its wild

relatives we have assembled a working collection of

several wild annual Cicer species (e.g. Ben-David and

Abbo 2005; Ben-David et al. 2010, 2006; Abbo et al.

2011). When taken together, the latitudinal range of

the three species involved in our long-term studies

spans almost the entire range of the genus as a whole,

these are C. pinnatifidum Jaub. et Spach native to

Turkey, C. judaicum Boiss. native to Israel and Jordan,

and C. cuneatum Hochst. ex A, Rich. native to Eritrea

and Ethiopia. In some of the cases collections were

made while sampling more than one individual from

certain habitats thereby providing an opportunity to

explore between- and within-populations diversity in

both genetic and phenotypic terms (Ben-David and

Abbo 2005; Frenkel et al. 2008). Measures of genetic

diversity between and within populations are impor-

tant parameters in devising germplasm collection and

conservation strategies, but thus far such information

for wild Cicer species is rather scarce.

The availability of such geographically diverse

wild Cicer material enables to address questions

concerning between-species phenotypic and genetic

comparisons including the structure of genetic diver-

sity within the genus as a function of eco-geographic

variables. Accordingly, our objectives in this study

were as follows: (1) to estimate the overall genetic

variation in the collection by using a limited set of

microsatellite DNA markers; (2) to evaluate the

microsatellite allelic diversity between and within

annual Cicer taxa spanning a wide latitudinal gradient;

(3) to reassess the independent taxonomic status of the

closely related species C. judaicum and C. pinnatifidum;

(4) to try and associate between the microsatellite

variability, phenological variation and response to

the ascochyta pathogen Didymella rabiei in Israeli

C. judaicum.

Materials and methods

Population sampling

One hundred and twenty two accessions of wild Cicer

from tree species: C. pinnatifidum (33 accessions), C.

judaicum (61 accessions), and C. cuneatum (28

accessions) were employed in this study. The

178 Genet Resour Crop Evol (2015) 62:177–188

123

accessions are maintained in Rehovot, Israel, as pure

lines and were propagated inside insect-proof screen

houses to minimize the scope for cross-pollination.

Full description of these accessions is given in Fig. 1

and Table S1.

Sample preparation and genotyping

Fresh leaf tissue (*200 mg) from 2 months old

greenhouse-grown plants was used for DNA extrac-

tion by CTaB method. A NanoDrop� ND1000 Spec-

trophotometer (NanoDrop Technologies, Inc.,

Wilmington, DE, USA) was used to measure the

DNA concentration. Thirty-two microsatellites (SSR)

primers (Lichtenzveig et al. 2005; Winter et al. 2000)

were tested for polymorphism using 3-5 accessions

from each species and the reference line cv. Hadas.

Eight SSR markers showed polymorphism within and/

or between species and were used for the analysis (see

Table S2). Polymerase chain reaction (PCR) protocols

and primers used in this study were as previously

described by (Lichtenzveig et al. 2005) while adjust-

ing the annealing temperature for each species to

improve amplification efficiency (Table S2). Lengths

of the amplified segments were detected with an

automated laser fluorescence (A.L.F.) sequencer and

analysed using the computer program Fragment

Analyzer Ver. 1.02 (Amersham Pharmacia Biotech)

by comparing with internal size standards. The

chickpea cultivar Hadas was used as a reference in

each run to ensure size accuracy and to minimize run-

to-run and gel-to-gel variations. The list of SSR

markers and their chromosomal location is given in

Table S2.

Genetic analysis

PowerMarker software (Liu and Muse 2005) was used

to calculate allelic frequencies, allele numbers, and

diversity indices (He) for each marker. PowerMarker

was also used to calculate polymorphism information

content (PIC) values according to Anderson et al.

(1993). For marker i, the PIC was calculated as:

PICi ¼ 1�Xn

j¼1

p2ij

where pij is the frequency of the jth allele for marker

i and summed across n alleles. This value provides an

estimate for the discriminatory power of a given

microsatellite locus by taking into account not only the

number of alleles per locus, but also its relative

frequency in the population genetics studied.

Fig. 1 A Geographic distribution of the three wild Cicer

species. B Principle component analysis (based on correlation

matrix) of eco-geographical parameters characterizing the wild

Cicer habitats. Lt, latitude; Ln, longitude; Alt, altitude above sea

level; Tmin coldest period, minimum temperature in January;

Tmax warmest period, maximum temperature in August. Biplot

vectors are trait factor loadings for principal component (PC)1

and PC2

Genet Resour Crop Evol (2015) 62:177–188 179

123

Individual pairwise genetic distances (Peakall and

Smouse 2006) were calculated for all markers. A

principal coordinate analysis (PCoA) was performed

on markers data set with GENEALEX 6.0 (Genetic

Analysis in Excel) software (Peakall and Smouse

2006). Analysis of molecular variance (AMOVA) was

employed to estimate the variance between popula-

tions and among accessions within populations with

1,000 bootstrap replicates.

The correlation between pairwise genetic distances

and geographic (measured in kilometres) distances

among populations was investigated by the Mantel test

(Mantel 1967) of matrix correspondence. All Mantel

tests were performed using the GENEALEX 6.0

software.

The STRUCTURE program was used to analyse

and cluster the studied genotypes. This program

implements a model-based clustering method assign-

ing individuals to clusters and identifying migrants

and individuals resulting from admixture (Pritchard

et al. 2000). The number of clusters (K) was set from 1

to 12. Each K was replicated 10 times for 10,000

iterations after a burn-in period of 100,000. An

admixture model was employed in which the fraction

of ancestry from each cluster is estimated for each

individual without prior information on the population

of origin.

Results

Eco-geographic characterization of the wild

chickpea sampling sites

Principle component analysis of the eco-geographical

variables, alongside a general distribution map, for the

collection sites of the three wild Cicer species is

presented in Fig. 1. The PCA extracted two major

principle components (Eigenvalue [ 1) that collec-

tively accounted for 80.9 % of the eco-geographical

variance. Principle component 1 (PC1, X-axis)

explained 58.2 % of the dataset variance, and was

loaded positively with minimum temperature (Tmin)

in the coldest period and annual precipitation, and

negatively with maximal temperature (Tmax) in the

warmest period and latitude (Lt). PC2 (Y-axis)

explained 22.7 % of the variance and was loaded

positively with longitude (Ln) and negatively with

altitude above sea level (Alt). The PCA resulted in

clear separation between the collection sites of

C. cuneatum in east Africa (depicted in red) and the

other two east Mediterranean species along PC1. The

separation between C. judaicum (green) and C.

pinnatifidum (blue) is apparent along PC2, presumably

influenced by the latitudinal differences (Fig. 1).

In C. pinnatifidum, the PCA exposed two major

components explaining 78.9 % of the total variance in

the dataset. PC1 explained 45.8 % and was loaded

positively with Tmax, Lt, Ln, and annual precipitation.

PC2 explained 33.1 % and was loaded positively with

Tmin and negatively with Alt (Fig. S1a). In C.

judaicum, the PCA exposed two major components

explaining 89.9 % of the variation in the data set. PC1

accounted for 56.8 % of the variation and was

positively loaded with Ln, Alt and Tmax and nega-

tively with Ln and Tmin. PC2 explained 34 % of the

variation and was positively loaded with the annual

precipitation and longitude (Fig. S1b). The PCA

created a clear separation between the northern

(Kerem Maharal, Nahal Milek, Mei-Ami, Nahal

Narbeta) and the southern (Kiryat Sefer, Nahal Anava,

Nahal Meara, Menora) populations in Israel. In

C. cuneatum, the PCA accounted for 94.8 % of the

variation in the data set. PC1 explained 72.8 % of the

variation and was loaded positively with annual

precipitation, Alt and Ln and negatively with Tmax

and Lt. PC2 accounted for 22 % of the variation and

was loaded positively with Tmin (Fig. S1c). The

effectiveness of the PCA is apparent from the distinct

position of the eastern most population near Harar

relative to the other highlands sites of Ethiopia and

Eritrea.

Allelic variation of microsatellite markers

in the three wild chickpea species

Cicer pinnatifidum—Total of 88 amplified fragments

were detected among the 33 C. pinnatifidum acces-

sions over the 12 tested microsatellite loci (Table 1).

The number of detected alleles per locus varied

between 3 and 11, with an average of 7.1 alleles per

locus. The genetic diversity ranged between 0.88

(XH3F8) to 0.41 (XH1D24a) with average diversity of

0.71. The PIC value was highest for XH3F8 (0.87) and

lowest for XH1D24a (0.38). When analysed according to

the source populations, the highest PIC value 0.41 was

detected among Kahramanmarash–Adiyaman road

population, and the lowest 0.15 in Burc (Table 2).

180 Genet Resour Crop Evol (2015) 62:177–188

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Cicer judaicum—Total of 46 amplified fragments

were detected among the 27 C. judaicum accessions

over 10 microsatellite loci (Table 1). The number of

alleles ranged from two to nine with an average of 4.6

alleles per locus. The mean observed heterozygosity

was highest for XH5A4a (0.11). The PIC values ranged

between 0.81 in XH1B13b and 0.26 in XH1D24a, with an

average of 0.56. When analysed according to the

source population, the highest genetic diversity

(Table 2) was detected in Nahal Anava (0.43) and

the lowest in Nahal Milek (0.1). Heterozygosity was

detected only in the Kerem Maharal population (0.04).

Cicer cuneatum—Total of 50 amplified fragments

were detected in 28 accessions of C. cuneatum over 10

microsatellite loci (Table 1). Frequency of the major

allele ranged between 0.84 for XH1D24a to 0.25 for

XH1B13b, with an average of 0.5. The genetic diversity

ranged between 0.84 (XH3F8) and 0.28 (XH1D24a) with

average of 0.61. The PIC values ranged between 0.82

(XH3F8) and 0.26 (XH1D24a). When analysed based on

the source populations, heterozygosity was detected in

two populations, Mendefera and in the Mendefera-

Barantu road, both with value of 0.06. The PIC value

ranged between 0.3 in the Mendefera population and

0.21 in the Bilbala population (Table 2).

Table 1 Linkage group (LG), number of alleles detected,

major allele frequency, gene diversity (He) and polymorphism

information contents (PIC) of microsatellite markers in three

wild Cicer species from Turkey, Israel, Ethiopia and Eritrea

Marker LG A Major allele

frequency

He PIC

Cicer pinnatifidum

TA3 8 3 0.65 0.51 0.44

STMS21 1 4 0.45 0.63 0.55

H1B13b 7 10 0.25 0.85 0.83

H1D24a 7 6 0.76 0.41 0.38

H5A4a 6 7 0.27 0.80 0.77

H3F8 3 11 0.22 0.88 0.87

H1B13a 3 8 0.33 0.77 0.73

TR1 6 11 0.32 0.83 0.81

H1D24b 7 7 0.63 0.57 0.55

H1D24c 7 6 0.46 0.72 0.69

H5A4b 6 7 0.25 0.83 0.80

H5A8b 2 8 0.37 0.79 0.77

Average 7.1 0.42 0.71 0.68

Cicer judaicum

TA3 8 2 0.96 0.08 0.07

H1B13b 7 9 0.26 0.83 0.81

H1D24a 7 3 0.83 0.28 0.26

H5A4a 6 4 0.61 0.53 0.46

H3F8 3 5 0.37 0.73 0.68

H1B13a 3 4 0.55 0.57 0.49

TR1 6 4 0.55 0.60 0.53

H1D24b 7 5 0.47 0.68 0.63

H5A4b 6 3 0.65 0.51 0.45

H5A8b 2 7 0.42 0.75 0.72

Average 4.6 0.57 0.56 0.56

Cicer cuneatum

TA3 8 4 0.63 0.51 0.43

STMS21 1 4 0.59 0.51 0.41

H1B13b 7 7 0.25 0.83 0.81

H1D24a 7 3 0.84 0.28 0.26

H5A4a 6 3 0.52 0.57 0.47

H3F8 3 9 0.26 0.84 0.82

H1B13a 3 8 0.26 0.81 0.78

H1D24b 7 5 0.58 0.61 0.58

H1D24c 7 3 0.54 0.56 0.47

H5A4b 6 4 0.53 0.63 0.58

Average 5 0.50 0.61 0.56

Table 2 Mean umber of alleles detected per locus (A), allelic

diversity (He), heterozygosity per population (Ho), and poly-

morphism information contents (PIC) among the populations

of three wild Cicer species from Turkey, Israel, Ethiopia and

Eritrea

Population A He Ho PIC

Cicer pinnatifidum

Araban 1.7 – – 0.28

Besni 1.6 0.26 0.10 0.20

Burc 1.5 0.19 0.05 0.15

Kahramanmaras 3.0 0.46 0.08 0.41

Sof Mt. 2.3 0.37 0.01 0.32

Yolagzı 0.9 – – 0.28

Cicer judaicum

Nahal A’naba 2.3 0.43 – 0.36

West Carmel 1.6 0.21 – 0.17

Kerem Maharal 1.7 0.26 0.04 0.21

Mey A’mi 1.6 0.23 – 0.18

Nahal Mylek 1.2 0.10 – 0.08

Cicer cuneatum

Adi-Quala 2.4 0.30 0.06 0.27

Mendefera 1.6 – – 0.30

Barantu rd. 2.2 0.33 0.06 0.29

Bilbala 1.3 – 0.06 0.21

Full eco-geographical information can be found in

supplementary Table S1

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The pattern of allelic variation

between and within populations

Cicer pinnatifidum—According to our analysis of

microsatellite allelic diversity among the six C.

pinnatifidum populations 45 % of the variation was

detected between population and the remaining 55 %

within populations (Fig. 2A). The PCoA plot shows

two major components explaining 51.2 % of the

allelic diversity between accessions. PCo1 accounted

for 27.1 % of the allelic variance and PCo2 explained

24.1 %. The scatter plot shows a clear separation

between the sampled populations (Fig. 2B), and the

effectiveness of the PCoA is apparent from placing of

the eastern most population of Yolagzı distal to the rest

westerly and more adjacent populations (Fig. 2B).

Cicer judaicum—Most of the allelic variance

(69 %) was detected within populations (among

accessions) and the remaining 31 % between the

populations (Fig. 2C). The two major PCo axes

account for 50.4 % of the allelic variation, with

PCo1 contributing 31.2 % and PCo2 19.2 %. The

PCoA created a clear separation between the northern

and southern Israeli population, however no clear

distinction is apparent between accessions belonging

to the different populations of these two population

groups. That is, no separation was obtained between

the different northern populations, and likewise

between the different southern populations (Fig. 2D).

Additional 34 C. judaicum accessions, obtained

from three geographical regions using a three-levelled

sampling hierarchy (population, sub-population,

accession; see Frenkel et al. 2010; Ozkilinc et al.

2010) were analysed separately (Fig. 3). In each

region, three populations were identified at a minimum

distance of 1.5 km, while subpopulations were defined

as plant clusters with a distance of 50–100 meters.

Five individual plants were sampled at a minimum

Fig. 2 Analysis of

molecular variance

(AMOVA) of SSR markers

haplotypes of three wild

Cicer species. A principal

coordinate (PCo) plot of

pairwise individual genetic

distances. C. pinnatifidum

(A, B), C. judaicum (C,

D) and C. cuneatum (E, F)

182 Genet Resour Crop Evol (2015) 62:177–188

123

distance of 10 m within each sub-population (Frenkel

et al. 2008, 2010; Ozkilinc et al. 2010). The popula-

tions from central Israel (Nataf and Haela Valley)

clustered separately from the northern ones (Menashe

Hills). Interestingly, an almost perfect separation was

obtained between the three populations of the northern

sampling region, while a lesser degree of separation is

apparent for the southern populations and their sub-

populations (Fig. 3).

Cicer cuneatum—The AMOVA have shown that

31 % of the allelic variation resides between popula-

tions while 69 % of the variation was observed within

populations (Fig. 2E). The PCoA showed two major

components explaining 65 % of the allelic diversity

between accessions. Most of the variance was

explained by PCo1 (50.8 %), creating a separation

between accessions sampled in Eritrea and those

sampled in Ethiopia (Fig. 2F). However, similar to the

situation observed for C. judaicum, here also the

PCoA failed to separate the different populations in

the two countries from each other (Fig. 2F).

Species relationship among the studied taxa

Analysis of molecular variance (AMOVA) shows that

only 18 % of the allelic variation is accounted for by

differences between the three studied species

(Table 3). Additional 34 % of the allelic variation

was contributed from difference between populations

(nested within species), and 48 % of the allelic

variation was detected among accessions nested

within populations.

The probabilities of the K number of clusters

showed the best solution for K = 3 which was

considerably better than K = 2, while K C 4 gave

only a small probability improvement. Low level of

admixture was found between populations and like-

wise between species (Fig. 4). The PCoA (Fig. 5A)

confirmed the independent taxonomic and indeed the

genetic integrity of the two east Mediterranean sister

species C. pinnatifidum (blue) and C. judaicum

(green). The correlation (Rm) between geographic

distance and genetic distance of the two Mediterra-

nean species (Mantel test, Fig. 5B) was significant

(Rm = 0.61, P \ 0.001).

Discussion

The Earth biosphere errantly undergoes a rapid decline

in biodiversity (i.e. biological diversity; Ricketts et al.

2005). Preservation of both inter- and intra-specific

biodiversity is of growing concern, particularly in

relation to global climatic change and urbanization.

Thus, better understanding of the relationships

between genetic diversity in natural populations and

ecological factors is fundamental for planning effec-

tive conservation strategies. In the current study, we

used microsatellites markers as a tool for the

Fig. 3 Estimated population structure based on allele fre-

quency variation of microsatellite markers. Each individual is

represented by a vertical bar, which is partitioned into K-colored

components representing the ancestry fractions in K = 3

clusters. Individual accessions are ordered by species (labeled

above)

Fig. 4 A principal coordinate (PCo) plot of pairwise individual

genetic distances among C. judaicum populations in three

regions

Table 3 Summary of analysis of molecular variance (AM-

OVA) of microsatellite haplotypes of the three wild Cicer

species

Source of variance df SS % P

Between species 2 180 18 \0.001

Between populations 12 343 34 \0.001

Within populations 48 356 48 \0.001

Total 62 879 100

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characterization of allelic diversity between and

within wild populations of three annual Cicer species.

Ecogeography of wild Cicer

The different annual species in the genus Cicer are

characterized by relatively narrow geographic range

(van der Maesen 1972; Berger et al. 2003), which is

thought to reflect narrow eco-geographic adaptation

(Abbo et al. 2003; Berger et al. 2003). Likewise, most of

the less studied perennial Cicer taxa also span narrow

geographic range (van der Maesen 1972). This may

suggest that narrow eco-geographic adaptation is a more

general phenomenon and probably of a deep evolution-

ary origin in this genus. In this work we have analysed

only a single Cicer species from each of three regions,

Turkey, Israel and East Africa. In eastern Turkey

however, three additional wild annual Cicer species

are known namely, C. echinospermum, C. bijugum and

C. reticulatum. In this region, and in certain ecological

settings, individuals from more than one species can be

found in close proximity, e.g. C. pinnatifidum and C.

reticulatum, in calcareous habitats or C. echinospermum

and C. bijugum on basaltic soils. Therefore, it would be

of great interest to identify diagnostic combinations of

eco-geographical parameters capable of differentiating

between the unique niches of these sympatric but

genetically distinct and reproductively isolated annual

Cicer taxa (Ladizinsky and Adler 1976). Such differen-

tiation may improve our understanding of the environ-

mental determinants of chickpea distribution in the wild

and the agro-ecological adaptation of the cultigen under

domestication.

Given the relatively large distance between the

Turkish, Israeli and the east African sampling sites and

their different ecological and geobotanical features,

the clear PCA separation between the three respective

regions and the sampling sites of studied Cicer taxa is

not surprising (Fig. 1). Still, using a relatively small

number of eco-geographic parameters it was possible

to obtain a good separation between the different

sampled populations within each of the studied species

(Fig. S1). Moreover, even within the relatively small

range of C. judaicum in Israel, with ca. 120 km

between the northern- and the southern-most sites, a

clear separation was obtained between southern and

northern populations. A separation that was also

reflected in the pattern of allelic diversity and other

genetically controlled plant traits (below).

Within and between population allelic diversity

Patterns of genetic variability between and within

natural plant populations and their driving forces are

of great interest in evolutionary biology, as well as in

ecological- and population- genetics studies (e.g.

Futuyma 1998). Genetic variation within and between

plant populations is generated and maintained by

evolutionary forces such as mating system, meiotic

paring patterns, genetic drift (e.g. founder effect), gene

flow (e.g. pollen/seed dispersal), mutation and natural

selection (e.g. Hedrick 2006).

Fig. 5 A A principal coordinate (PCo) plot of pairwise

individual genetic distances between C. judaicum populations

(green) and C. pinnatifidum (blue). B Pair-wise geographical

versus genetic distances between Israeli wild C. judaicum

populations and Turkish C. pinnatifidum populations. C Repre-

hensive photo of leaf morphology of the two species. (Color

figure online)

184 Genet Resour Crop Evol (2015) 62:177–188

123

Ben-David and Abbo (2005) documented pheno-

logical variation between and within C. judaicum

populations in Israel. These authors later demonstrated

that this variation reflects heritable ecotypic variation

that is presumably selected for by environmental

determinants (Ben-David et al. 2010). The present

study, however, is the first report of DNA allelic

variation between and within wild annual Cicer

populations. The microsatellite markers used in this

study were originally developed for domesticated

chickpea C. arietinum. Consequently, we had to

screen more than 80 microsatellites before identifying

six markers capable of exposing polymorphism in all

three wild species. Still, the PCoA based on the allelic

variation in the studied materials resulted in clear

separation between the three Cicer species. Indeed,

low level of admixture was apparent based on the

STRUCTURE analysis (Fig. 4). This pattern was

observed despite the fact that only 18 % of the overall

allelic variation in the data set was accounted for by

differences between the three studied species

(Table 3).

Considering the unique ecology and morphology of

C. cuneaum compared with all other wild annual Cicer

taxa its genetic distinctness in terms of microsatellite

allelic variation is of no surprise. However, the clear-

cut separation obtained between C. pinnatifidum and

C. judaicum is very important. Over the years, the

independent taxonomic status of C. judaicum was

questioned. For example, Zohary (1972) considered C.

judaicum as a variant of C. pinnatifidum and com-

mented that individuals showing intermediate mor-

phology can be observed. In addition, van der Maesen

(1972) reported that the two species were found in

close proximity in the Damascus basin in Syria,

thereby attesting to (at least partial) overlap in their

eco-geographic affinities.

Our work experience with these two Cicer species

is entirely different. These two species have distinct

foliar morphological features that enable easy classi-

fication of both living and herbarium material

(Fig. 5C). The number of leaflets is larger in C.

judaicum while leaflet dentation is more pronounced

in C. pinnatifidum (Fig. 5C). In addition, C. judaicum

flowers are smaller and have a dull pink coloration as

compared with the larger and purple C. pinnatifidum

flowers. Over the years we have followed hundreds of

C. judaicum populations in Israel, about two dozens of

C. judaicum populations in Jordan, and several dozens

of C. pinnatifidum populations in southeastern Turkey.

Never have we observed any intermediate types

growing in any of the visited populations, neither did

we see any such types among several dozens of Cicer

specimen deposited in the herbarium of the Hebrew

University of Jerusalem. Moreover, our field observa-

tions and allelic variation analyses are in full accord

with the hybridization experiments conducted by

Ladizinsky and Adler (1976) and Abbo et al. (2011).

Namely, in both studies several reproductive barriers

were observed between C. judaicum and C. pinnatifidum

including abnormal floral morphology in the F1

hybrids and high degree of sterility among F1BC1

progeny (therein). Hence, the reproductive barriers

that maintain the distinct genetic integrity of C.

judaicum and C. pinnatifidum as separate biological

species are in full accord and indeed reflected in the

distinct microsatellite allelic pattern documented in

these two Cicer species. Unfortunately, we are unable

to inspect the Cicer populations in the Damascus

basin, however, the strong reproductive barriers

between these two species suggest that even if they

grow in close proximity the likelihood of successful

hybridization and introgression are slim.

Domesticated chickpea is a predominately self-

fertilizing species (Abbo et al. 2009). We are unaware

of studies documenting the reproductive biology of

wild Cicer, however, the size of the flowers in some

species and the observations of insects visits in wild

populations would suggest that the pattern observed

for the cultigen may not apply to all wild taxa. In the

current study, despite the small number of analysed

loci, we were able to pick up and identify heterozy-

gosity in certain accessions at certain loci.

Many authors consider microsatellite loci to be

environmentally neutral (e.g. Ellegren 2004). How-

ever, despite the relatively small number of studied

microsatellite loci, our PCoA was capable to differ-

entiate between Turkish C. pinnatifidum populations,

and likewise between Israeli C. judaicum populations

and between east African C. cuneatum populations.

Moreover, even on a relatively small geographic range

within Israel, the observed allelic variation enabled to

classify the accessions sampled from the different

sites. The observed north–south separation of the

Israeli C. judaicum population is of significance for

two reasons. First, it corroborates our observations and

interpretations despite the seemingly limited number

of analysed loci. Second and more important, it may

Genet Resour Crop Evol (2015) 62:177–188 185

123

suggest that these loci are not neutral but rather are

subject to a range of selection pressures. Specifically,

our results are in line with a previous work by (Frenkel

et al. 2008) that have shown that the northern Cicer

Israeli populations have a different pattern of response

to the ascochyta blight fungal pathogen Didymella

rabiei compared with the southern populations. More-

over, D. rabiei isolates sampled from the northern C.

judaicum populations have shown a distinct allelic

pattern compared with D. rabiei isolates samples from

southern Israeli Cicer populations, thereby reflecting

their geographic origin and indeed co-evolutionary

history with their wild C. judaicum host (Frenkel et al.

2010).

Ben-David and Abbo (2005) studied the vernaliza-

tion response of Israeli C. judaicum populations but

observed no clear geographic pattern, and relatively

low (ca. 10 %) phenotypic variance component within

populations. This is in contrast to the considerable

(above 50 %) within population microsatellite allelic

variation observed in the present study. One possible

explanation to this discrepancy is the fact that there is

hardly any adaptive advantage for a wide phenological

response within any single habitat. All individuals at a

certain location are by definition exposed to the same

day-length and to similar seasonal temperature pro-

files, and hence are expected to be relatively similar in

terms of their life history traits, as observed by Ben-

David and Abbo (2005). This of course is quite

different with respect to selection pressures associated

with incidental disease infection and the resulting

allelic variation in disease response loci (Frenkel et al.

2008, 2010) or with microsatellite markers that are not

necessarily linked to such phenology loci.

Implications for germplasm exploration

and conservation

An important issue concerning germplasm exploration

revolves around what could be framed as finding the

desired balance between number of sampling sites

(habitats) and the number of sampled individuals

within any such site. Considering data obtained in

previous studies on wild chickpea (Ben-David and

Abbo 2005; Ben-David et al. 2006, 2010), sampling a

large number of ecologically and geographically

diverse habitats with relatively small number of

individuals per sites seems as the preferred strategy.

However, the large within-population allelic diversity

documented in this study calls for a reconsideration of

this view. At present, we have no clue about the

adaptive value of the local within-population allelic

variation in wild annual chickpea, and this is an

important issue worth pursuing. It should be borne in

mind that the relatively narrow geographic range of

the different annual Cicer species is a challenge, and

requires that different unique habitats of each such

species be explored in order to obtain a true estimate

for the potential of wild Cicer populations as a source

for agro-eco-ecologic adaptive genetic variation. At

present stage we would cautiously suggest that similar

to the finding with wild emmer wheat (Peleg et al.

2005, 2008) conservation of large rich populations

might be more rewarding a strategy than preservation

of small thin populations of annual Cicer. Clearly,

further work is required before more firm conclusions

could be drawn in this context.

In conclusion, the patchy distribution of wild Cicer

species (e.g. Ben-David et al. 2006), the relatively

small number of seeds produced per plant in the wild,

and the relatively high allelic variation within popu-

lations is a unique but highly vulnerable situation in

terms of germplasm conservation. This is because any

land development or construction within the natural

range of these species may wipe out unique local

genetic combinations. When taken together with the

extensive civil construction projects and agricultural

development that currently take place in many Turkish

provinces this situation calls for urgent deployment of

strict knowledge based conservation strategies (Abbo

et al. 2008).

Acknowledgments The authors are grateful to Prof. Tzion

Fahima, University of Haifa, Israel for providing the

infrastructure required for the microsatellite analyses. We

acknowledge the assistance of Dr. Roi Ben-David, Dr. Omer

Frenkel, Dr. Judith Lichtenzveig and Dr. Ruth vanOss.

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