97
Population genetic structure and genetic 
diversity study in Lallemantia royleana 
(Benth.) Benth.: identification of 
potential gene pools in Iran
Abstract
Lallemantia royleana (Benth.) Benth. (Family Lamiaceae), is one of the most 
popular medicinal plants in Iran. It is an herbaceous pant that is commonly 
known as “Lady mantle”. The vernacular name of Lallemantia royleana’s seed 
is Balangu or Balangu Shirazi that is used as a source of medicine. Medicinal 
plants are very important from economic point of view in Iran and several large 
industries are focused on medicinal plants cultivation, extraction and export. 
Therefore, providing data on the biology of these plants is important for the 
country. Lallemantia royleana grows in different parts of Iran and forms several 
local populations. Genetic, morphological and biochemical divergence of 
geographical populations are well known in plant species. We have no report on 
population genetic structure, genetic fragmentation, local adaptation and gen 
flow of Lallemantia royleana populations in the country. Therefore, the present 
population genetics investigation was programmed to produce data on above said 
questions. Randomly collected plants of 7 geographical regions were studied by 
ISSR molecular markers. This information can be used in hybridization and gene 
conservation of this medicinal plant in Iran. 
Iz vleček
Lallemantia royleana (Benth.) Benth. (družina Lamiaceae) je ena najbolj 
priljubljenih zdravilnih rastlin v Iranu. To je zelnata rastlina, njena semena 
z domačim imenom Balangu ali Balangu Shirazi so uporabna v zdravilstvu. 
Zdravilne rastline so v Iranu tudi gospodarsko pomembne in številna velika 
industrijska podjetja se ukvarjajo z gojenjem zdravilnih rastlin, predelavo in 
njihovim izvozom. Zato so raziskave biologije the rastlin pomembne. Lallemantia 
royleana uspeva v različnih predelih v Iranu in ima številne lokalne populacije. 
Genetska, morfološka in biokemična raznolikost geografskih populacij je dobro 
znana. Ne obstajajo pa podatki o genetski strukturi, genetski fragmentiranosti, 
lokalnih prilagoditvah in genetskem toku med populacijami v Iranu. Zato 
v članku z raziskavo populacijske genetike poskušamo odgovoriti na zgornja 
vprašanja. Naključno vzorčene rastline iz sedmih geografskih območij smo preučili 
z ISSR molekularnimi markerji. To bo uporabno za križanje (hibridizacijo) in 
varstvo genetske raznolikosti te zdravilne vrste v Iranu. 
Key words: Gene flow, genetic 
fragmentation, ISSR, population 
assignment, Lallemantia.
Ključne besede: genski tok, genska 
fragmentacija, ISSR, dodelitev 
populaciji, Lallemantia.
Received: 23. 4. 2018
Revision received: 4. 9. 2018
Accepted: 4. 9. 2018
1 Faculty of Life Sciences & Biotechnology, Shahid Beheshti University, Tehran, Iran.
2 Department of Boilogy, Faculty of Science, Arak University, Arak, Iran. Email: seyedmehdi_talebi@yahoo.com
* Corresponding author. E‑mail: f_koohdar@yahoo.com
Fahimed Koohdar1 ,
*, Masoud Sheidai1 

, Seyed Mehdi Talebi2 DOI: 10.2478/hacq‑2018‑0009 18/1 • 2019, 97–104

18/1 • 2019, 97–104
98
Fahimeh Koohdar, Masoud Sheidai & Seyed Mehdi Talebi
Population genetic structure and genetic diversity study in Lallemantia royleana 
(Benth.) Benth.: identification of potential gene pools in Iran
1. Introduction 
Geographically widely distributed plant species encoun‑ ter various ecological conditions and variable altitudes. 
These taxa are subjected to different selection pressures 
and sometimes due to geographical barriers suffer from 
population fragmentation. In these situations, plants re‑ veal morphological and genetic divergence in their local 
populations (see for example, Azizi et al. 2014, Sheidai 
et al. 2012, 2013, 2014, Minaeifar et al. 2015). Some 
medicinal species even reveal difference in their phyto‑ chemical compositions
Habitat fragmentation reduced the number of plant in‑ dividuals in local populations, which in turn brings about 
inbreeding and reduced level of genetic diversity due to 
the act of genetic drift (Freeland et al. 2011). Due to me‑ dicinal and economic importance of medicinal plants, 
it is frequently used by local people. Therefore they be‑ come threatened by both habitat fragmentation (reduced 
genetic variability) and eradication by local inhabitants. 
Therefore we reveal a genetic investigation in geographi‑ cal populations of medicinally important plant species 
Lallemantia royleana (Benth.) Benth. in Iran. The data 
obtained is important for conservation and germ plasm 
evaluation of this medicinal plant in the country. 
Population genetics analyses provide valuable informa‑ tion about the levels of genetic variation, the partitioning 
of genetic variability within/between populations, gene 
flow, inbreeding, self‑pollination versus outcrossing, ef ‑ fective population size and population bottleneck. The 
information obtained can help in developing effective 
management strategies for endangered and/or invasive 
species (Chen 2000, Ellis & Burke 2007). 
Lallemantia royleana (Benth.) is an annual herb of the 
genus Lallemantia L. (Family Lamiaceae) and is com‑ monly known as “Lady mantle”. The vernacular name of 
Lallemantia royleana’s seed is Balangu or Balangu Shirazi 
(Naghibi et al. 2005). This species grows in Western Si‑ beria, Central Asia, Xinjiang, Pakistan, Kashmir, Iran, 
Syria, Kazakhstan, Kyrgyzstan, Russia, Tajikistan, Turk‑ menistan, Uzbekistan, SW Asia, and Europe (Cao Shu 
1994). Balangu is agood source of fiber, oil and protein 
and has medicinal, nutritional and human health prop‑ erties (Naghibi et al. 2005). This natural herb is used for 
the treatment of arthritis, joint pain, rheumatism, osteo‑ arthritis and abscesses inflammations. This seed absorb 
water quickly when soaked in water and produce a sticky, 
turbid and tasteless liquid. The Balangu seeds are used in 
a wide range of products made in traditional or indus‑ trial such as a beverage (namely Tokhme Sharbati) and 
bread in Iran and Turkey (Mazhe et al. 2012).
Different molecular markers have been used in popula‑ tion genetic studies. We used ISSR (Inter‑simple sequence 
repeats) since these markers are reproducible, cheap, easy 
to work and are known to be efficient in population ge‑ netic diversity studies (Sheidai et al. 2012, 2013, 2014, 
Minaeifar et al. 2015).
2. Material and methods 
2.1. Plant material 
Seventy‑four plant specimens of Lallemantia royleana 
were randomly collected from 7 geographical populations 
during 2014–2015 in Iran (Table 1, Figure1).
Figure 1: Distribution map of Lallemantia royleana populations.
Slika 1: Karta razširjenosti populacij vrste Lallemantia royleana.
2.2. DNA extraction and ISSR assay
Fresh leaves were collected randomly in each of the stud‑ ied populations and dried in silica gel powder. Genomic 
DNA was extracted using CTAB with activated char‑ coal protocol (Murry and Tompson, 1980). The quality 
of extracted DNA was examined by running on 0.8% 
agarose gel. Ten ISSR primers; (AGC)5GT, (CA)7GT, 
(AGC)5GG, UBC810, (CA)7AT, (GA)9C, UBC807, 
UBC811, (GA)9A and (GT)7CA commercialized by 
UBC (the University of British Columbia) were used.
PCR reactions were performed in a 25μl volume con ‑ taining 10 mM T ris‑HCl buffer at pH 8; 50 mM KCl; 1.5 
mM MgCl2; 0.2 mM of each dNTP (Bioron, Germany), 
0.2 μM of a single primer; 20 ng genomic DNA and 3 U 
of Taq DNA polymerase (Bioron, Germany).

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Population genetic structure and genetic diversity study in Lallemantia royleana 
(Benth.) Benth.: identification of potential gene pools in Iran
The amplifications
, 
reactions were performed in Tech‑ ne thermocycler (Germany) with the following program: 
5 min initial denaturation step 94 °C, followed by 40 cy‑ cles of 1 min at 94 °C; 1 min at 57 °C and 1 min at 72 °C. 
The reaction was completed by final extension step of 7 
min at 72 °C. The amplification products were observed 
by running on 1% agarose gel, followed by the ethidium 
bromide staining. The fragment size was estimated by us‑ ing a 100 bp molecular size ladder (Fermentas, Germany). 
2.3. Data analysis 
2.3.1.  Genetic diversity and population 
structure
ISSR bands obtained were coded as binary characters 
(presence = 1, absence = 0). The genetic diversity param‑ eters like, allele diversity (Weising et al. 2005), Nei’s gene 
diversity (H), Shannon information index (I), number of 
effective alleles, and percentage of polymorphism (Free‑ land et al. 2011), were determined for each population. 
Nei’s genetic distance was used for clustering (Weising 
et al. 2005, Freeland et al. 2011). Neighbor Joining (NJ), 
UPGMA (Unweighted Paired Group using average) clus‑ tering and Neighbor‑Net method of networking was used 
for grouping after 100 times bootstrapping/ permuta‑ tions (Freeland et al. 2011, Huson & Bryant 2006). The 
Mantel test was performed to check correlation between 
geographical and the genetic distances of the studied pop‑ ulations (Podani 2000). PAST ver. 2.17 (Hammer et al. 
2012) programs was used for these analyses. Pearson coef‑ ficient of correlation was determined between geographi‑ cal features (altitude, longitude and latitude) and genetic 
diversity parameters. 
AMOVA (Analysis of molecular variance) test (with 
1000 permutations) as implemented in GenAlex 6.4 
(Peakall & Smouse 2006), and Nei’s Gst analysis of Geno‑ Dive ver.2 (2013) (Meirmans & Van Tienderen, 2004), 
were used to reveal significant genetic difference among 
the studied populations (Sheidai et al. 2014). 
The population
 
genetic differentiation was studied by 
G’st_est = standardized measure of genetic differentia‑ tion (Hedrick 2005), and D_est = Jost measure of dif‑ ferentiation (Jost 2008). In order to overcome potential 
problems caused by the dominance of ISSR markers, a 
Bayesian program, Hickory (ver. 1.0) (Holsinger & Lewis 
2003), was used to estimate parameters related to genetic 
structure (theta B value) (Tero et al. 2003). 
Bayesian based model STRUCTURE analysis 
(Pritchard et al. 2000), and maximum likelihood‑ based 
method of K‑ Means clustering were used to study the 
genetic structure of populations (Sheidai et al. 2014). For 
STRUCTURE analysis, data were scored as dominant 
markers (Falush et al. 2007). The Evanno test (Evanno 
et al. 2005) and K‑ Means clustering were used to iden‑ Table 1: Geographical populations in Lallemantia species. 
Tabela 1: Geografske populacije vrst rodu Lallemantia. 
Geographical 
populations
Province Locality Number of 
individuals 
Longitude Latitude Altitude  
(m)
1
Razavi Khorasan Sabzevar 5 N 36.124394 E 57.392022 975
north Khorasan Esfarayen 5 N 37.043399 E 57.303396 1253
Razavi Khorasan Dargaz 5 N 37.264024 E 59.062901 477
2
Tehran Varamin 3 N 35.192931 E 51.385210 921
Tehran Ghiamdasht 3 N 35.312385 E 51.390316 1032
Tehran Sorkhe Hesar 2 N 35.412883 E 51.340322 1452
3 Semnan Mahdishahr 15 N 35.424278 E 53.211328 1667
4
Ilam Ilam 5 N 33.181355 E 46.370062 1110
Zanjan Zanjan 5 N 36.292310 E 48.230727 1882
5
Yazd Hosein abad 4 N 32.025460 E 54.140368 1136
Esfahan Esfahan 10 N 32.391909 E 51.400089 1579
6 South Khorasan 6 N 32.361815 E 58.575615 1583
7
Shiraz Shiraz 3 N 28.292160 E 53.337890 1050
Kerman Kerman 3 N 36.432337 E 12.003355 66

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Population genetic structure and genetic diversity study in Lallemantia royleana 
(Benth.) Benth.: identification of potential gene pools in Iran
tify optimum k genetic groups (Sheidai et al. 2014). Two 
summary statistics, 1‑ pseudo ‑ F and 2‑ Bayesian Infor ‑ mation Criterion (BIC) provide the best fit for k (Meir‑ mans 2012). 
2.3. Gene flow 
Gene flow was determined by different approaches. 1‑ 
Calculating Nm an estimate of gene flow from Gst by 
PopGene ver. 1.32 (1997) as: Nm = 0.5(1 ‑ Gst)/Gst. This 
approach considers equal amount of gene flow among 
all populations. 2‑ Population assignment test based on 
maximum likelihood as performed in Genodive ver. in 
GenoDive ver. 2. (2013). 
We used the statistical model called latent factor mixed 
models (LFMM) to check if ISSR markers show correla‑ tion with environmental features (longitude, latitude, and 
altitude) of the studied populations. The analysis was done 
by LFMM program version: 1.2 (Frichot et al. 2013).
3. Results 
3.1. Genetic diversity 
Genetic diversity parameters determined in the studied 
populations are presented in T able 2. The highest value for 
gene diversity occurred in populations 1 and 7 (0.193 and 
0.188, respectively). The highest level of genetic polymor‑ phism (75.41) occurred in population 1, while the lowest 
value of the same occurred in population 6 (36.07). 
The Mantel test produced significant correlation be ‑ tween geographical distance and genetic distance of the 
studied populations (r = 0.23, P < 0.01). This indicated 
the occurrence of isolation by distance (IBD) among 
populations and that close‑bye located populations have 
greater chance of gene flow compared to those located far 
from each other. 
However, detailed analysis of geographical features re‑ vealed a more complex relationship between genetic vari‑ ability and geographical features. 
The latitude was positively correlated with the Nei gene 
diversity (r = 0.53, P = 0.20), and genetic polymorphism 
(r = 0.74, P < 0.05). The altitude showed significant neg ‑ ative correlation with gene diversity (r = ‑0.81, P < 0.05), 
and the genetic polymorphism (r = ‑0.74, P < 0.05). The 
longitude was negatively correlated with the gene diver‑ sity (r = ‑0.33, (P > 0.05), and positively correlated with 
as the genetic polymorphism (r = ‑0.08, P > 0.05). 
3.2. Population genetic structure
AMOVA (T able3) produced significant genetic difference 
(PhiPT = 0.29, P = 0.001) among the studied popula‑ tions. It also revealed that 29% of total genetic variability 
occurred among the studied populations while, 71% oc‑ curred within these populations.
Pairwise AMOVA produced significant difference 
among these populations. Hickory test also produced 
high Theta B value (0.30) supporting AMOVA. 
Gst (0.32, P = 0.001), Hedrick
,
 standardised fixation 
index (G’st = 0.38, P = 0.001) and Jost
,
 differentiation 
index (D‑est = 0.12, P = 0.001), revealed that the studied 
populations are genetically differentiated.
UPGMA and NJ clustering as well as Neighbor‑Net 
produced similar results, therefore, the UPGMA tree is 
presented and discussed (Figure 2). UPGMA tree pro‑ duced three major clusters. Most of the plants in each 
population were placed close to each other, but some were 
placed intermixed with the other populations. 
Table 2: Genetic diversity parameters in Lallemantia royleana populations. 
Tabela 2: Genetska raznolikost populacij vrste Lallemantia royleana. 
Pop N Na Ne I He UHe %P
Hs
Pop1 15 1.525 1.310 0.305 0.193 0.199 75.41
0.248
Pop2 8 0.836 1.163 0.168 0.106 0.113 37.70
0.161
Pop3 15 1.148 1.232 0.233 0.147 0.153 54.10
0.191
Pop4 10 0.934 1.228 0.204 0.135 0.142 40.98
0.164
Pop5 14 1.344 1.270 0.271 0.171 0.178 63.93
0.24
Pop6 6 0.869 1.181 0.172 0.111 0.122 36.07
0.165
Pop7 6 1.016 1.334 0.275 0.188 0.205 47.54
0.236
Na = No. of alleles, Ne = No. of effective alleles, I = Shanon Information Index, He = Nei
,
 gene diversity,  
UHe = Unbiased Nei
,
 gene diversity, %P = Percentage of polymorphism, Hs = Genetic diversity due to sub‑populations. 
(Populations 1–7 are according to Table 1).

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Population genetic structure and genetic diversity study in Lallemantia royleana 
(Benth.) Benth.: identification of potential gene pools in Iran
Plants of populations 4 and 5 formed the first cluster, 
while plants of populations 1–3 and 6 comprised the sec‑ ond cluster. Plants of populations 7 were placed in the 
third cluster, which joined the other two clusters with 
some distance. 
The MDS plot (Figure 3), revealed genetic affinity be ‑ tween populations 1 and 2, and between populations 3, 
5 and 6. It separated populations 4 and 7 from the other 
studied populations due to their genetic difference. 
Figure 2: UPGMA dendrogram of Lallemantia royleana populations (populations 1–7 are according to Table 1).
Slika 2: Dendrogram UPGMA populacij vrste Lallemantia royleana (populacije 1–7 so enake kot v Tabeli 1).












































































Figure 3: MDS plot of the studied Lallemantia royleana populations (populations 1–7 are according to Table 1). 
Slika 3: Graf analize MDS preučevanih populacij vrste Lallemantia royleana (populacije 1–7 so enake kot v Tabeli 1).



































        
























 
























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Fahimeh Koohdar, Masoud Sheidai & Seyed Mehdi Talebi
Population genetic structure and genetic diversity study in Lallemantia royleana 
(Benth.) Benth.: identification of potential gene pools in Iran
Evanno test performed on STRUCTURE analysis 
and pseudo‑ F index of K‑ Means clustering produced 
optimum number of k = 2. These results indicated that 
we have 2 genetic groups in the studied populations. 
STRUCTURE plot (Figure 4) based on k = 2, identified 
these two genetic groups (gene pools). 
The assignment test revealed that some plants in 
populations 1 are closer to the population 3 and 7. The 
same holds true for plants of populations 3 and 5, and 7 
as well as 5 and 6. Therefore, population assignment test 
also revealed some degree of gene flow among populations 
of the second gene pool. 
LFMM analysis revealed that out of 75 ISSR loci, 16 are 
adaptive. Some of these ISSR loci had low Nm value (<1) 
and are private alleles, for example, ISSR loci 2, 4, 5, 37, 
48, and 49. The other loci had high Nm value (>1.0) and 
were more frequently shared by the studied populations. 
4. Discussion 
traditional medicine is widely practiced in Iran and there‑ fore, medicinal plants cultivation and conservation are very 
important in the country. Many companies are focused on 
medicinal plants cultivation, extraction and export. 
Lallemantia royleana is one of the most popular medici‑ nal plants in Iran and is extensively consumed by locals. 
Therefore, it is threatened in natural habitats. In order 
to conserve this valuable plant species, it is necessary to 
monitor the size of its natural populations and study their 
level of genetic variability as well as population genetic 
fragmentation. 
Population fragmentation in general reduces the rate 
of gene flow and increases the genetic differentiation of 
populations. In such case, the genetic drift becomes ac‑ tive and reduces the within‑ population genetic variabil‑ ity (Setsuko et al. 2007, Hou & Lou 2011). In the pres‑ ent study, AMOVA revealed that Lallemantia royleana 
populations are genetically differentiated but contain 
high level of interpopulation genetic variability (71% of 
their total genetic variation). This should be due to out ‑ crossing nature of this species. High genetic diversity is 
very important for the continuity of the plant species and 
their adaptation to fluctuating environmental conditions 
(Çalişkan 2012). Moreover, gene flow among popula‑ tions introduces new genes in to the local populations 
and increases their genetic variability (Hou & Lou 2011, 
Sheidai et al. 2014). In the present study, both STRUC‑ TURE plot and population assignment test revealed the 
occurrence of gene flow among the studied Lallemantia 
royleana populations for example population 4 is located 
in the western part of the country, while population 7 is 
located in southern part, with great distance from each 
other. The location of population 5 is somewhat in the 
central parts of the country and between the other popu‑ lations and may be in contact with all these populations. 
This may be the reason that plants of this population 
showed the presence of alleles from the populations 4 






      
Figure 4: STRUCTURE plot of the studied Lallemantia royleana 
populations (populations 1–7 are according to Table 1).
Figure 4: Graf analize STRUCTURE preučevanih populacij vrste 
 Lallemantia royleana (populacije 1–7 so enake kot v Tabeli 1).
The STRUCTURE plot obtained based on admixture 
model and Bayesian approach revealed that populations 
1, 2 and 3 are genetically more alike and comprise the 
first gene pool, populations 4, 5 and 6 are genetically 
more alike and comprise the second gene pool while 
population 7 formed the third gene pool. More than half 
of individuals from population 5 shares alels with 2 gene 
pools.
This plot also revealed low degree of genetic admixture 
between the 3 gene pools, for example some plants in 
populations 1 and 6 had shared alleles with members of 
the populations 4 and 7. 
3.3. Gene flow 
We used different indirect approaches to study the level 
of gene flow or ancestral shared alleles in Lallemantia 
royleana populations. These approaches are based on dif‑ ferent assumptions and mathematical models. The Nm 
approach assumes equal rate of gene flow among popu‑ lations that might not be true always. The NM analysis 
produced mean Nm = 1.00, that indicate a low degree 
of gene flow among populations. The ISSR loci varied in 
their Nm value from 0.20 to 19.30. 
This result is in agreement with STRUCTURE result 
presented before. Most of the 74 ISSR loci studied, had 
high Nm value (>1.00). These loci were exchanged more 
frequently among the studied populations, while the oth‑ er loci were private loci and were confined to one or more 
local populations. 
More detailed information was obtained by popula‑ tion assignment test (Table 4). In this approach, the as‑ signment of current plant to the inferred population is 
determined by maximum likelihood method (Meirmans 
& Van Tienderen 2004). 

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Population genetic structure and genetic diversity study in Lallemantia royleana 
(Benth.) Benth.: identification of potential gene pools in Iran
and 7 and also from the other studied populations. This 
can bring about enough genetic variability for this me‑ dicinal plant species within the country.
Population genetic studies, also provides insight about 
population adaptive differences that have been developed 
between plants from different regions (Waples 1998). 
Populations
,
 genetic differences with presumed poten‑ tial adaptive value can be used in conservation strategies 
(Sheidai et al. 2012, 2013, 2014). LFMM analysis identi‑ fied some of the ISSR loci with potential adaptive value. 
The Mantel test revealed a pattern of isolation‑by dis ‑ tance across the distribution range of the studied Lalle-
mantia royleana populations. It suggested that the disper‑ sal of these populations might be constrained by distance, 
and gene flow is most likely to occur between neighbor‑ ing populations. As a result, more closely situated popula‑ tions tend to be more genetically similar to one another 
(Slatkin 1993, Hutchison & Templeton 1999, Medrano 
& Herrera 2008). The STRUCTURE analysis identified 
three different gene pools for Lallemantia royleana in Iran. 
These gene pools have their own specific alleles and may 
be used in conservation and hybridization programs. 
Lallemantia royleana populations showed a general 
trend of negative association between altitude and gene 
diversity as well as the genetic polymorphism. The altitude 
is an important factor for population genetic differentia‑ tion (Ohsawa & Ide 2008, Di et al. 2014, Noormoham‑ madi et al. 2015). Populations not only are differentiated 
on mountains along vertical axes, but genetic changes can 
also occur along horizontal axes. For instance, ridges may 
provide geographical barriers to gene flow between popu‑ lations on their opposite sides, so genetic differentiation 
may occur across ridges (Taberlet et al. 1998).
However, some studies also reported no differentiation 
between populations at low and high altitudes (Ohsawa 
et al. 2007), due to the overlap of flowering phenology in 
populations at different altitudes, species’ extensive pol‑ len flow, and long‑ distance seed dispersal between differ‑ ent altitudes by animals, particularly birds. 
In conclusion, the present study indicates that genetic 
divergence, limited gene flow and local adaptation have 
played role in diversification of Lallemantia royleana 
populations in Iran. These findings may be of use in con ‑ servation this medicinal plant in the country. 
Acknowledgment 
We thank Dr. Farrokh Ghahremani‑Nejad for allowing us 
to use Herbarium of KharazmiUniversity, Tehran. 
Masoud Sheidai , https://orcid.org/0000-0003-3983-6852
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(Benth.) Benth.: identification of potential gene pools in Iran
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