From Landraces To Improved Cultivars: Assessment of Genetic Diversity and Population Structure of Mediterranean Wheat Using SNP Markers
From Landraces To Improved Cultivars: Assessment of Genetic Diversity and Population Structure of Mediterranean Wheat Using SNP Markers
Sustainable Field Crops Programme, Institute for Food and Agricultural Research and Technology (IRTA),
Lleida, Spain
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a1111111111 * josemiguel.soriano@irta.cat
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Abstract
Assessment of genetic diversity and population structure in crops is essential for breeding
and germplasm conservation. A collection of 354 bread wheat genotypes, including Mediter-
OPEN ACCESS ranean landraces and modern cultivars representative of the ones most widely grown in the
Citation: Rufo R, Alvaro F, Royo C, Soriano JM Mediterranean Basin, were characterized with 11196 single nucleotide polymorphism
(2019) From landraces to improved cultivars: (SNP) markers. Total genetic diversity (HT) and polymorphic information content (PIC) were
Assessment of genetic diversity and population
0.36 and 0.30 respectively for both landraces and modern cultivars. Linkage disequilibrium
structure of Mediterranean wheat using SNP
markers. PLoS ONE 14(7): e0219867. https://doi. for the modern cultivars was higher than for the landraces (0.18 and 0.12, respectively).
org/10.1371/journal.pone.0219867 Analysis of the genetic structure showed a clear geographical pattern for the landraces,
Editor: David D. Fang, USDA-ARS Southern which were clustered into three subpopulations (SPs) representing the western, northern
Regional Research Center, UNITED STATES and eastern Mediterranean, whereas the modern cultivars were structured according to the
Received: March 18, 2019 breeding programmes that developed them: CIMMYT/ICARDA, France/Italy, and Balkan/
eastern European countries. The modern cultivars showed higher genetic differentiation
Accepted: July 2, 2019
(GST) and lower gene flow (0.1673 and 2.49, respectively) than the landraces (0.1198 and
Published: July 15, 2019
3.67, respectively), indicating a better distinction between subpopulations. The maximum
Copyright: © 2019 Rufo et al. This is an open gene flow was observed between landraces from the northern Mediterranean SPs and the
access article distributed under the terms of the
modern cultivars released mainly by French and Italian breeding programmes.
Creative Commons Attribution License, which
permits unrestricted use, distribution, and
reproduction in any medium, provided the original
author and source are credited.
Program (Generalitat de Catalunya). The funders stability under a broad range of environmental conditions. In the Mediterranean Basin, the cli-
had no role in study design, data collection and matic regions vary greatly, including both favourable lands and drylands that are subject to fre-
analysis, decision to publish, or preparation of the
quent drought episodes and high temperature stress, particularly during grain filling [2].
manuscript.
Wheat is estimated to have originated around 10000 years BP in the Fertile Crescent. From
Competing interests: The authors have declared there it spread to the west of the Mediterranean Basin and reached the Iberian Peninsula
that no competing interests exist.
around 7000 years BP [3]. During this migration, domestication and selection by humans
resulted in the development of landraces that were very well adapted to local environments
[4]. From the middle of the 20th century, the cultivation of local landraces was progressively
abandoned, as a consequence of the Green Revolution, and they were replaced by the im-
proved and more productive semi-dwarf cultivars. Mediterranean landraces are an important
group of genetic resources because of their documented resilience to abiotic stresses, their
resistance to pests and diseases, and their genetic diversity [4, 5].
Knowledge of genetic diversity provides valuable information for understanding the rela-
tionships between cultivars and facilitates their characterization and classification, determina-
tion of population structure, etc., thus enriching breeding strategies for crop improvement, for
example helping breeders to develop new cultivars reducing pre-breeding activities. In the last
few decades, several markers have been used for genetic studies [6]. However, the high-density
genome coverage provided at low cost in recent years by new high-throughput genotyping
technologies such as single nucleotide polymorphism (SNP) arrays or genotyping-by-sequenc-
ing (GBS) have made them the procedures of choice for wheat genetic analysis [7–11].
The aim of this study was to explore the existence of genetic and/or geographic structures
and genetic diversity in collections of wheat landraces from the Mediterranean Basin and
modern cultivars representative of the ones most widely cultivated in the region.
Molecular characterization
DNA isolation was performed from lyophilized leaf samples at Trait Genetics GmbH (Gate-
rsleben, Germany). Accessions were genotyped with 13177 SNPs from the Illumina Infinium
15K Wheat SNP Chip at Trait Genetics GmbH (Gatersleben, Germany). Markers were ordered
according to the SNP map developed by Wang et al. [13].
Data analysis
Polymorphic information content (PIC) values were calculated following the formula
described by Botstein et al. [14] using the Cervus software v3.0.7 [15] (available at http://www.
fieldgenetics.com). Genetic diversity was estimated as total diversity (HT) [16] using POP-
GENE v1.32 [17]. The coefficient of genetic differentiation, i.e. the proportion of total variation
that is distributed between populations (GST), was calculated as GST = DST/HT, where DST is
the genetic diversity between populations. DST was calculated as DST = HT—HS, where HS is
the mean genetic diversity within populations. Gene flow was estimated as Nm = 0.5(1- GST)/
GST according to McDonald and McDermott [18].
Linkage disequilibrium (LD) was estimated as the square of marker correlations (r2) for
markers with known map positions using TASSEL 5.0 [19] at a significance level of P<0.001
with a sliding window of 50 cM. The intra-chromosomal r2 values were plotted against the
genetic distance and a LOESS curve was fitted to determine the distance at which the curve
intercepts the line of a critical value of r2 in order to estimate how fast the LD decay occurs for
each chromosome. The critical value of r2 was determined as the mean r2 for each genome.
The genetic structure of the collection was estimated using the Bayesian clustering algo-
rithm implemented in the STRUCTURE software v2.3.4 [20] using an admixture model with
burn-in and Monte Carlo Markov chain for 10000 and 100000 cycles, respectively. A continu-
ous series of K were tested from 1 to 10 in seven independent runs. The Evanno method [21]
was used to calculate the most likely number of subpopulations with STRUCTURE HAR-
VESTER software [22]. Principal coordinates analysis (PCoA) based on genetic distance was
performed using GenAlEx 6.5 [23].
Diversity analysis between accessions was determined by simple matching coefficient [24]
implemented in DARwin software v.6 [25]. The un-rooted tree was calculated using the neigh-
bour-joining clustering method [26]. The tree is divided in:
• Clusters: Main divisions of the tree
• Branches: Division within clusters
• Groups: Genotypes from the same subpopulation within a branch
Results
SNP polymorphism and diversity
A total of 11196 polymorphic markers were located in the map developed by Wang et al. [13].
In order to reduce the risk of errors in further analyses, markers and accessions were analysed
for the presence of duplicated patterns and missing values. For the landrace collection, 8 mark-
ers with more than 25% of missing values as well as 730 markers with minor allele frequency
(MAF) lower than 5% were excluded from the analysis, leaving a total of 10458 SNPs (Table 1).
For the modern collection, 3 markers with more than 25% of missing values and 487 markers
with an MAF lower than 5% were excluded, leaving 10706 polymorphic markers. The total
number of polymorphic markers was 11074, of which 10090 (91%) were polymorphic in both
collections, 368 only in landraces and 616 only in modern cultivars.
The D genome had the lowest number of markers, whereas the B genome showed the best
coverage (Table 1). Genetic diversity (HT) and PIC were estimated for each chromosome. For
the landraces, HT ranged from 0.39 (1A, 4B) to 0.25 (4D) (mean 0.36) and PIC ranged from
0.33 (1A) to 0.21 (4D) (mean 0.30). For the modern collection, HT ranged from 0.40 (2D, 6D)
to 0.29 (7D) (mean 0.36) and PIC ranged from 0.33 (1D, 2D) to 0.25 (7D) (mean 0.30)
(Table 1). A summary statistics is reported in S2 File.
Table 1. Number of SNP markers (N), gene diversity (HT), polymorphic information content (PIC) and linkage disequilibrium (LD) (r2, % of markers in LD at
P<0.001, and LD decay in cM ) for all of the chromosomes and genomes in both types of germplasm.
Landraces Modern cultivars
2
N HT PIC LD (r ) LD (%) LD decay N HT PIC LD (r2) LD (%) LD decay
1A 595 0.39 0.33 0.16 45 2 604 0.37 0.28 0.18 44 1
1B 812 0.36 0.30 0.11 35 2 834 0.33 0.28 0.17 45 2
1D 293 0.36 0.30 0.34 49 1 295 0.39 0.33 0.41 60 3
2A 576 0.38 0.30 0.13 30 1 590 0.36 0.30 0.16 42 3
2B 925 0.36 0.30 0.10 28 1 999 0.36 0.29 0.18 48 2
2D 376 0.37 0.30 0.30 59 2 388 0.40 0.33 0.40 68 2
3A 522 0.37 0.30 0.09 28 1 522 0.35 0.31 0.17 46 1
3B 770 0.35 0.30 0.10 31 1 781 0.34 0.30 0.14 45 2
3D 134 0.35 0.28 0.13 23 1 137 0.36 0.29 0.14 23 1
4A 435 0.35 0.30 0.10 26 1 433 0.35 0.29 0.16 43 1
4B 375 0.39 0.31 0.14 38 3 382 0.36 0.32 0.17 51 2
4D 39 0.25 0.21 0.09 23 2 51 0.39 0.30 0.12 32 2
5A 628 0.36 0.31 0.12 29 1 655 0.36 0.31 0.18 46 3
5B 860 0.38 0.31 0.11 31 2 867 0.37 0.31 0.18 53 2
5D 93 0.33 0.27 0.12 29 10 143 0.38 0.30 0.12 29 10
6A 648 0.36 0.30 0.14 34 7 674 0.36 0.31 0.18 52 9
6B 774 0.36 0.31 0.13 33 2 787 0.32 0.30 0.26 63 4
6D 135 0.35 0.28 0.18 45 1 146 0.40 0.32 0.15 38 4
7A 703 0.37 0.31 0.09 29 2 665 0.35 0.31 0.11 37 4
7B 652 0.37 0.30 0.11 34 2 637 0.36 0.31 0.17 56 2
7D 113 0.32 0.26 0.07 16 4 116 0.29 0.25 0.08 21 6
Genome A 4107 0.37 0.31 0.12 31 - 4143 0.36 0.30 0.16 43 -
Genome B 5168 0.37 0.31 0.11 31 - 5287 0.35 0.30 0.18 51 -
Genome D 1183 0.33 0.27 0.22 39 - 1276 0.37 0.30 0.20 44 -
Total 10458 0.36 0.30 0.14 32 - 10706 0.36 0.30 0.18 46 -
https://doi.org/10.1371/journal.pone.0219867.t001
Linkage disequilibrium
LD was determined (r2) for single chromosomes. In the landraces, LD ranged from 0.07 in
chromosome 7D to 0.34 in chromosome 1D, with a mean among chromosomes of 0.14. The
percentage of locus pairs showing a significant LD at P<0.001 ranged from 16% to 59% for
chromosomes 7D and 2D, respectively, with a mean of 33% (Table 1). In modern cultivars
the mean value of r2 was 0.18, with 45% of the locus pairs in LD. Chromosome 7D, as reported
for landraces, showed the lowest LD (0.08), with 21% of the locus pairs in LD at P<0.001
(Table 1). The maximum LD was found in chromosome 1D (0.41), showing 60% of the locus
pairs with a significant LD at P<0.001. However, as reported for the landraces, the chromo-
some with the most locus pairs with a significant LD was 2D (68%, r2 = 0.4).
The extent of LD was also investigated for the three genomes. The highest r2 was found in
the D genome for both landraces and modern cultivars (0.22 and 0.20, respectively). The D
genome had the most markers with significant LD at P<0.001 (39%) in the landraces, whereas
in the modern cultivars the B genome had the most, with 51% of the locus pairs showing a sig-
nificant LD at P<0.001 (Table 1). The decay of LD varied for each chromosome. For the A and
B genomes, LD decay ranged from 1 to 9 cM, whereas for the D genome it ranged from 1 to 10
cM (Table 1, S3 File).
Population structure
The first analysis of the population structure of the 354 accessions was carried out using 557
common SNPs markers between landraces and modern cultivars evenly distributed across the
genome. The markers were selected according to the distance of the LD decay for each chro-
mosome in order to avoid the use of markers with a significant LD. The Bayesian clustering
method using the Evanno test [21] to infer the most likely number of structured subpopula-
tions (ΔK) revealed the presence of two distinct subpopulations, one including landraces and
the other including modern cultivars (data not shown). On the basis of this result, a subse-
quent analysis of population structure was performed independently for the landraces and
modern cultivars.
The highest value of ΔK for the landraces was observed for K = 2 (2861), followed by K = 3
(1031) (Fig 1A). Population structure for both K = 2 and K = 3 showed a geographical pattern.
For K = 2 the landraces were separated following an east-west pattern within the Mediterra-
nean Basin, whereas for K = 3 landraces mainly from the Balkan Peninsula were separated
either from eastern Mediterranean ones or from French and Italian ones included in the west-
ern Mediterranean. The subpopulations (SPs) were classified as western (SP1), northern (SP2)
and eastern Mediterranean (SP3) (Fig 1B) according to the geographical region of the coun-
tries most represented in the SP. The inferred population structure for K = 3 showed that 45%
of the accessions (77 out of 170) showed a strong membership coefficient (q-value) to one of
the SPs (q>0.7), whereas using a moderate q-value (>0.5) the number of accessions within an
SP increased to 144 (85%), leaving 26 as admixed (S1 File). The western Mediterranean SP
(SP1) included 43 accessions, of which 28 corresponded to western countries (Spain, Portugal,
France, Morocco, Algeria and Tunisia), with 23 of them having a mean q-value greater than
0.8 (Table 2). SP1 also included 10 landraces (23%) from eastern countries and 6 (14%) from
northern countries. The northern Mediterranean SP (SP2) included 59 accessions, with 68%,
24% and 8% corresponding to northern (Albania, Bosnia and Herzegovina, Croatia, France,
Greece, Italy, Macedonia, Romania and Serbia), western and eastern Mediterranean countries,
respectively (Table 2 and Fig 1B and 1C). Finally, the eastern Mediterranean SP (SP3) included
42 accessions, of which 86% corresponded to eastern countries (Cyprus, Egypt, Jordan, Iraq,
Lebanon, Libya, Syria and Turkey) and 12% and 2% to western and northern countries,
respectively (Table 2). As shown in Table 2 and Fig 1, the northern Mediterranean SP included
accessions from Balkan countries, but also French, Italian and Spanish landraces. On the other
hand, three accessions from Israel belonged to the western Mediterranean SP, but their q-val-
ues (average q = 0.605) were lower than those of the accessions from western Mediterranean
countries. Also, 40% of the accessions from Tunisia belonged to SP2. Accessions from Portugal
and Spain were distributed in SP1 and SP2. As shown in Table 2, the inconsistencies observed
for these countries could be related to the low q-values for the most represented SP. The three
Portuguese accessions included in SP2 had a mean q-value of 0.592, and the Spanish and
Greek accessions showed q-values slightly higher than 0.5 for the two SPs (Table 2), denoting a
high level of admixture in all of them.
Following the Evanno test, as previously reported for landraces, the most likely number of
structured SPs (ΔK) for modern cultivars was K = 2 (728) (Fig 2A). The first cluster grouped
mainly cultivars developed by French and Italian breeding programmes, and the second one
grouped mainly cultivars from North Africa, the Middle East and Spain, with evident CIM-
MYT and ICARDA genetic background (S1 File). A set of cultivars mainly from Serbia
remained admixed. If the second highest value for the structured subpopulations was chosen
(K = 3) (105), a third SP clustered all Serbian accessions, plus 2 from Macedonia and 1 from
Hungary (Fig 2B and 2C, S1 File). According to the classification into three structured
Fig 1. Genetic structure of Mediterranean landraces. (A) Estimation of the number of subpopulations (SPs) according to the Evanno test. (B) Inferred
structure of the landrace collection based on 170 genotypes. Each individual is represented by a coloured bar with length proportional to the estimated
membership to each of the three SPs. (C) Geographic distribution of the wheat subpopulations within the Mediterranean Basin. Circles indicate the
proportion of each SP in the country. Red, SP1 (western Mediterranean); green, SP2 (northern Mediterranean); blue, SP3 (eastern Mediterranean); grey,
admixture. Map source: https://commons.wikimedia.org/wiki/File:Middle_East_location_map.svg.
https://doi.org/10.1371/journal.pone.0219867.g001
subpopulations, 79% of the accessions (145 out of 184) showed a q >0.7. The first SP (SP4)
included 73 cultivars from France, 10 from Italy and 1 from Serbia. The second SP (SP5)
included cultivars from eastern Europe, mainly Serbia (21 out of 24). The third SP (SP6)
included 33 cultivars from Spain, 15 cultivars from North African countries, 12 from the Mid-
dle East and Central Asia (Afghanistan), and finally 4 from northern Mediterranean countries
(France and Italy). Finally, 12 cultivars remained as admixed.
The relationships between landraces and modern cultivars were also analysed by PCoA as a
complementary way to visualize their clusters. In agreement with the results shown by
STRUCTURE, the first two coordinates of the PCoA clearly separated the landraces from the
modern cultivars, and within each group accessions were clustered matching the results of
STRUCTURE (Fig 3). Landraces from the Balkan Peninsula ‘TRI 1667’ and ‘TRI 1671’ (Alba-
nia), ‘Moriborska’ (Bosnia and Herzegovina), ‘41-II/4-B’ and ‘Legan Bezosja’ (Serbia), and
‘Solonetu Nou’ (Romania) were positioned on the positive side of the PCoA1 close to the
Table 2. Mean membership coefficients across the landraces from each country included in each SP. Only structured genotypes (q>0.5) are shown in the table. q-val-
ues >0.7 are indicated in bold.
SP1 SP2 SP3
Country q mean N q mean N q mean N
Albania 0.755 3
Algeria 0.862 6 0.762 3 0.601 4
Bosnia and Herzegovina 0.691 3
Bulgaria 0.657 3
Croatia 0.700 3
Cyprus 0.661 1 0.501 2
Egypt 0.992 1 0.680 1 0.706 4
France 0.502 1 0.707 8
Greece 0.565 2 0.540 2
Iraq 0.517 1 0.546 1 0.915 8
Israel 0.605 3
Italy 0.615 3 0.727 6 0.986 1
Jordan 0.614 1 0.704 2
Lebanon 0.676 1 0.818 2
Libya 0.726 2
Macedonia 0.889 4
Morocco 0.845 15
Portugal 0.822 1 0.592 3
Romania 0.774 4
Serbia 0.761 4
Spain 0.526 4 0.544 6
Syria 0.591 3 0.966 5
Tunisia 0.973 1 0.738 3 0.539 1
Turkey 0.552 1 0.910 11
https://doi.org/10.1371/journal.pone.0219867.t002
Fig 2. Genetic structure of the modern cultivars. (A) Estimation of the number of subpopulations (SPs) according to the Evanno test. (B) Inferred structure of the
collection based on 184 genotypes. Each individual is represented by a coloured bar with length proportional to the estimated membership to each of the three
subpopulations. (C) Proportion of cultivars from the different countries/regions within each SP. Yellow, SP4; blue, SP5; violet, SP6.
https://doi.org/10.1371/journal.pone.0219867.g002
Fig 3. Principal coordinates analyses based on genetic distance. A) Landraces: red, SP1; green, SP2; blue, SP3; dark grey, admixed; light grey, modern cultivars. B)
Modern cultivars: yellow, SP4; dark blue, SP5; violet, SP6; dark grey, admixed; light grey, landraces.
https://doi.org/10.1371/journal.pone.0219867.g003
Table 3. Genetic diversity and variation between the MED6WHEAT subpopulations (SPs).
N HT HS DST GST Nm
SP1 43 0.2873 - - - -
SP2 59 0.3690 - - - -
SP3 42 0.3132 - - - -
SP4 82 0.2995 - - - -
SP5 62 0.2651 - - - -
SP6 24 0.3476 - - - -
Total 312 0.3842 0.3136 0.0706 0.1838 2.22
Landraces 144 0.3672 0.3232 0.0440 0.1198 3.67
Modern 168 0.3652 0.3041 0.0611 0.1673 2.49
SP1-SP2 102 0.3594 0.3282 0.0312 0.0868 5.26
SP1-SP3 85 0.3363 0.3003 0.0360 0.1070 4.17
SP1-SP4 125 0.3452 0.2934 0.0518 0.1501 2.83
SP1-SP5 67 0.3307 0.2762 0.0545 0.1648 2.53
SP1-SP6 105 0.3690 0.3174 0.0516 0.1398 3.08
SP2-SP3 101 0.3737 0.3411 0.0326 0.0872 5.23
SP2-SP4 141 0.3521 0.3343 0.0178 0.0506 9.39
SP2-SP5 83 0.3628 0.3171 0.0457 0.1260 3.47
SP2-SP6 121 0.3844 0.3583 0.0261 0.0679 6.86
SP3-SP4 124 0.3549 0.3064 0.0485 0.1367 3.16
SP3-SP5 66 0.3445 0.2892 0.0553 0.1605 2.61
SP3-SP6 104 0.3304 0.2892 0.0412 0.1247 3.51
SP4-SP5 106 0.3176 0.2823 0.0353 0.1111 4.00
SP4-SP6 144 0.3658 0.3236 0.0422 0.1154 3.83
SP5-SP6 86 0.3594 0.3063 0.0531 0.1477 2.88
https://doi.org/10.1371/journal.pone.0219867.t003
origin of the axes, together with the modern Serbian cultivars. Additionally, two landraces
from Italy (‘TRI 16900’ and ‘TRI 16516’) and three from France (‘Mounton a Epi Rouge’, ‘TRI
14046’ and ‘TRI 17938’) were located within the modern cultivars from SP4 that grouped mod-
ern French and Italian cultivars.
The six SPs showed a total genetic diversity (HT) ranging from 0.2651 for modern cultivars
from the Balkans and eastern Europe (SP5) to 0.3690 for northern Mediterranean landraces
(SP2) (Table 3). The genetic diversity among SPs (DST) was low (0.0706), resulting in a genetic
differentiation (GST) among SPs of 0.1838. This means that only about 18% of the variability
observed was due to differences between SPs. The estimation of GST also allowed us to estimate
the gene flow (Nm) among SPs. The value of this estimate (2.22) indicates a high level of gene
exchange, which denotes a low genetic differentiation among the SPs. When analysed by type
of accessions, the landraces showed a GST = 0.1198 and an Nm = 3.67, whereas the modern cul-
tivars showed a GST = 0.1673 and an Nm = 2.49, indicating higher gene exchange between the
landrace SPs (Table 3). When comparisons were made between two SPs, gene flow ranged
from 2.53 between western Mediterranean landraces (SP1) and modern Balkan cultivars (SP5)
to 9.39 between northern Mediterranean landraces (SP2) and cultivars developed mainly by
French and Italian breeding programmes (SP4) (Table 3).
Cluster analysis
To better detail the kinship among accessions, a neighbour-joining tree was built using the
common SNPs markers between the landraces and modern cultivars. The dendrogram showed
Fig 4. Un-rooted neighbour-joining dendrogram. Colours of branches correspond to the SPs obtained by STRUCTURE analysis. Landraces (LR): red, SP1; green, SP2;
blue, SP3. Modern cultivars (M): yellow, SP4; dark blue, SP5; violet, SP6.
https://doi.org/10.1371/journal.pone.0219867.g004
two main clusters with a robust separation between them (Fig 4). Within each of these clusters,
accessions were mainly grouped in agreement with the groups obtained previously by STRUC-
TURE and PCoA analysis (Fig 4).
The first cluster of modern cultivars (M_Q1) included cultivars from France and Italy
(SP4), in addition to three landraces: ‘Bahatane’ and ‘TRI17938’ from France and ‘TRI16516’
from Italy. The second cluster of modern cultivars (M_Q2) represented mainly the accessions
carrying CIMMYT and ICARDA genetic background (SP6), including cultivars developed in
Turkey, Spain, Egypt, Syria, Morocco, Algeria, France, Italy, Afghanistan, Sudan and Tunisia.
This cluster also included the French cultivar ‘Boticelli’ classified in SP4 but including 37% of
the genetic background from SP6. Finally, the third cluster of modern cultivars (M_Q3) con-
tained the group of all elite cultivars from the Balkan Peninsula and eastern Europe (SP5): Ser-
bia (23), Macedonia (2) and Hungary (1). This cluster also included the Syrian landrace
‘Salamuni-A’, classified as admixed by STRUCTURE.
The clustering of landraces suggested a more complex distribution among the SPs accord-
ing to the higher frequency of admixture revealed by STRUCTURE. The first cluster (LR_Q1)
showed three branches, the first one with landraces mainly from the western Mediterranean
(SP1), with Morocco as the best-represented country of the branch (45% of the accessions).
The second country represented in this branch was Algeria (14%), and the remaining acces-
sions from Cyprus, Egypt, Greece, Iraq, Portugal, Spain, Syria, Tunisia and Turkey were repre-
sented in a lower frequency (3%-6%). The second and third branches included mainly eastern
Mediterranean landraces, with 81% of the accessions coming from Egypt, Iraq, Jordan, Syria
and Turkey. The remaining accessions were from western (Algeria, 11% and Tunisia, 4%) and
northern (France, 4%) Mediterranean countries.
The second cluster (LR_Q2) was represented by landraces from the three SPs in two main
branches. The first branch included a division between genotypes from the eastern (SP3) and
western (SP1) Mediterranean SPs. The eastern group was represented mainly by Turkish land-
races (46%). An additional 27% was represented by landraces from Cyprus, Iraq, Jordan and
Lebanon, and finally the remaining cultivars were previously grouped by structure analysis in
the northern Mediterranean SP (SP2). The second group of the branch was composed mainly
of landraces from the eastern Mediterranean countries Cyprus (10%), Israel (50%), Jordan
(20%) and Syria (10%), although the Bayesian clustering determined that their structure was
more similar to that of landraces from the western Mediterranean SP. Only one landrace from
Morocco was included in this group. The second cluster included landraces from the western
and northern Mediterranean SPs. The first branch included most of the accessions from west-
ern Mediterranean countries (Morocco, Portugal, Spain and Tunisia) and one accession from
Libya. In this branch, 50% of the accessions showed high levels of admixture. The second
branch of the cluster was divided into two groups, the first including mostly landraces classi-
fied as western Mediterranean by STRUCTURE. The group included cultivars from Algeria,
Greece, Italy, Morocco and Turkey. The second group was mainly composed of northern
Mediterranean landraces (71%) from Albania, France, Italy, Macedonia and Serbia. Although
included by structure analysis in this SP, Portugal, Spain and Tunisia from the western Medi-
terranean and Lebanon from the eastern Mediterranean were also included in this group.
Finally, the remaining landraces were included in four branches (LR_Q3) of the main clus-
ters examined above, with 76% corresponding to northern Mediterranean countries (Albania,
Bulgaria, Bosnia and Herzegovina, France, Greece, Croatia, Italy, Romania and Serbia). Within
these branches, five modern cultivars were also included: the Spanish cultivars ‘Montcada’ and
‘Montserrat’, the Turkish cultivars ‘Ata 81’ and ‘Cumhuriyet 75’, and the Serbian cultivar ‘KG
100’.
Discussion
Genetic diversity
Genetic diversity is essential for plant breeding because it provides new knowledge for improv-
ing cultivars. In wheat, the genetic diversity was narrowed down during the second half of the
resolution and marker density required for association studies. Moreover, LD is influenced by
population structure due to stratification and unequal distribution of alleles within groups of
genotypes, which can result in false associations [20].
In the current study, the mean r2 calculated for intra-chromosomal loci was 0.12 and 0.18
with 32% and 46% of the locus pairs in LD for landraces and modern cultivars, respectively. It
is well known that crops gradually lose their genetic variability through domestication and
breeding, resulting in more uniform cultivars, reducing the recombination rate and affecting
LD [40, 41]. The D genome showed the highest r2 for both landraces and modern cultivars.
Similar results were reported by Chao et al. [42] and Lopes et al. [28], who explained that
higher LD in the D genome was linked to recent introgressions and population bottlenecks in
the origin of hexaploid wheat.
The first attempt to dissect the genetic structure of the MED6WHEAT panel showed a clear
separation based on historical breeding periods, i.e. landraces vs modern cultivars. Thus, for
subsequent analysis of population structure, independent analyses were carried out for the two
groups of germplasm. According to a Bayesian-based analysis, without a priori assignment of
accessions to populations, the landraces showed a geographic structure according to the east-
ern and northern zones of the Mediterranean Basin, whereas accessions classified as western
Mediterranean showed a high level of admixture. This classification denoted a migration from
the centre of wheat domestication in the Fertile Crescent to the west of the Mediterranean
Basin, as reported by Moragues et al. [43] and Soriano et al. [6] in durum wheat. The higher
admixture found in western Mediterranean landraces may be due to the incorporation and fix-
ation of favourable alleles from eastern and northern genetic pools during the migration pro-
cess. By contrast, for modern cultivars the separation was mainly based on the pedigree of the
accessions: CIMMYT/ICARDA, cultivars obtained mainly by French breeding programmes,
and accessions from the Balkan Peninsula. These groups may have originated through the
sharing of germplasm from different breeding programmes with similar growing conditions,
particularly from the shuttle breeding carried out by international centres. For the landrace
collection, only 45% of the accessions showed a strong q-value (>0.7), suggesting high levels of
admixture among SPs, whereas for the modern cultivars 79% of the accessions showed a strong
q-value. Oliveira et al. [44] suggested that admixture is the result of the incorporation of alleles
from more than one gene pool because of the spread of wheat from different ancestral popula-
tions. Moragues et al. [43] proposed as a possible cause of admixture the exchange of germ-
plasm between different Mediterranean regions during the expansion of the Arabian Empire.
The low level of admixture between modern cultivars could be due to the development by
breeding programmes of cultivars with specific adaptation to the local environments and the
use of different genetic resources.
Based on the defined SPs, the results of PCoA and neighbour-joining were in agreement
with those reported by STRUCTURE, showing first a robust separation between the landraces
and modern cultivars, and within these main clusters a separation into three genetic SPs.
The origin of the axes in the PCoA showed a mixture between landraces and modern culti-
vars, as also reported by Oliveira et al. [45]. Landraces from the Balkan Peninsula co-localized
with modern cultivars from the same region, and two landraces from Italy and three from
France were located close to modern cultivars from those countries. A possible cause of this
mixture could be the presence of these landraces in the pedigree of the modern cultivars, as
reported for the French landrace ‘Mounton a Epi Rouge’, which according to Bonjean [46]
played an important role in the pedigrees of improved French cultivars between 1965 and 1975.
According to the admixture revealed by STRUCTURE analysis, the modern cultivars
showed well-defined clusters with differentiation among SPs in the neighbour-joining tree,
whereas for the landraces the branches included accessions from different SPs. Only four
genotypes from a given SP were misclassified within the clusters of modern cultivars. Within
M_Q1, formed mainly by French and Italian cultivars, two French and one Italian landraces
were also included. Cluster M_Q2, which grouped most cultivars carrying CIMMYT and
ICARDA genetic background, also included the French cultivar ‘Boticelli’, which, although
belonging to SP4, has an important genetic background (37%) from SP6. Cluster M_Q3
included a landrace from Syria, classified as admixed, with 30% of its genetic background from
the northern Europe SP. The presence of landraces within modern cultivars was reported in a
global durum wheat panel by Kabbaj et al. [10], who concluded that the simplest explanation
was that they were not true landraces, but old tall cultivars wrongly labelled during the collect-
ing mission by the gene banks. This seems a plausible explanation, considering that the first
breeding attempts made by pioneer breeders or entrepreneurial Mediterranean agriculturalists
consisted in identifying and isolating the best lines already existing within original wheat land-
races [47]. Alternatively, the grouping within elite cultivars was probably due to the fact that
they were used in breeding programmes to enlarge the genetic diversity, as reported for grain
legumes by Sharma et al. [48].
When landraces were analysed by hierarchical clustering, a higher level of admixed geno-
types was found on the basis of the STRUCTURE classification. Although the main groups
within the clusters were formed mostly by members of specific SPs, a discrepancy between the
classifying methods was observed among groups of the same cluster. As reported for clusters
LR_Q1 and LR_Q2, some of the landraces misclassified by STRUCTURE according to their
country of origin or with a high level of admixture were grouped by neighbour-joining into
clusters containing accessions from the same geographical region. In LR_Q3, five modern cul-
tivars were also grouped with landraces, probably due to the presence in their pedigree of
genetic background from landraces or closely related accessions. However, the closed pedigree
of most commercial cultivars did not allow us to clarify this.
These results highlight the importance of using different approaches to determine the
genetic structure of a germplasm collection. Although the different methods are coincident for
the genotypes with strong genetic membership to a given group, they are useful to complement
the information provided when accessions show large admixture or gene flow among different
geographical regions, as in the case of Mediterranean landraces.
Gene flow
Genetic differentiation and gene flow provide information about population differentiation.
Gene flow homogenizes populations by genetically decreasing variance among populations
and increasing variance within populations. In our study, the analysis of genetic differentiation
and gene flow indicated that the majority of the genetic variation was explained by differences
among cultivars within genetic SPs. Differentiation of modern cultivar SPs was higher than
that of landrace SPs, indicating a lower level of gene exchange among cultivars from different
origins. These results are in agreement with population structure and neighbour-joining clus-
tering, in which a higher level of admixture was found for landraces from different geographi-
cal regions. Accordingly, it has also been suggested that the low genetic differentiation among
SPs is due to seed exchange by farmers, mainly influenced by geographic distances [49, 50].
When two SPs were compared, in general gene flow between landrace SPs was also higher
than between modern cultivars. Within landraces, the highest gene flow was found between
the northern Mediterranean SP and the western and eastern Mediterranean SPs. The value
was lower for the exchange between the western and eastern Mediterranean SPs, supporting
the hypothesis of geographic distance. When the modern cultivars were analysed, gene flow
showed a higher value between SP4 (France and Italy accessions) and SP5 (Balkan accessions).
Cultivars with a CIMMYT/ICARDA origin (SP6) had lower values of gene exchange with the
other SPs, probably because of the delivery of improved inbred lines to be released by local
programmes through the nurseries that these international centres distribute globally. In the
case of modern cultivars, the SPs reflected similarities between the genetic pools managed by
the breeding programmes conducted in each specific country. The highest gene flow value was
reported between SPs from different periods, i.e. between landraces from the northern Medi-
terranean (SP2) and modern cultivars released by French and Italian breeding programmes
(SP4), suggesting the presence of the genetic background of landraces or old cultivars in the
improved modern varieties.
Concluding remarks
The current study aimed to explore the presence of genetic and geographic structures in a col-
lection of bread wheat landraces and modern cultivars representing the variability existing for
the species in the Mediterranean Basin. The results demonstrated the usefulness of the meth-
odologies employed for achieving this goal. The structure for landraces showed a geographical
pattern with different levels of admixture, mainly justified by physical distances between the
territories where they were collected, whereas the structure for modern cultivars reflected dif-
ferences and similarities between the genetic pools managed by the breeding programmes
operating in the region.
The results reported in the current study may be of special interest for driving the develop-
ment of new cultivars with desirable traits for the climatic conditions of the Mediterranean
Basin, and for identifying useful molecular markers through genome-wide association studies
to assist breeding programmes.
Supporting information
S1 File. List of accessions.
(DOCX)
S2 File. Summary statistics for HT, PIC and LD for each one of the chromosomes.
(XLSX)
S3 File. Linkage disequilibrium plots.
(TIF)
Acknowledgments
This study was funded by project AGL2015-65351-R of the Spanish Ministry of Economy and
Competitiveness. RR is a recipient of a PhD grant from the Spanish Ministry of Economy and
Competitiveness. JMS was hired by the INIA-CCAA programme funded by INIA and the
Generalitat de Catalunya. The authors acknowledge the contribution of the CERCA Program
(Generalitat de Catalunya). Thanks are given to Marta Lopes (previously at CIMMYT, Ankara,
Turkey), Miguel Sánchez (ICARDA, Rabat, Morocco) and Dejan Dodig (Maize Research Insti-
tute, Zemun Polje, Belgrade, Serbia) for providing part of the modern germplasm used in the
study, and the different gene banks for providing landrace populations.
Author Contributions
Conceptualization: Fanny Alvaro, Jose Miguel Soriano.
Data curation: Rubén Rufo, Jose Miguel Soriano.
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