SSR analysis of introgression of drought tolerance from the genome of Hordeum spontaneum into cultivated barley (Hordeum vulgare ssp vulgare)

Abstract

Wild barley (Hordeum vulgare ssp. spontaneum) and landraces are important sources of resistance to biotic and abiotic stresses since they possess wide genetic diversity that may be missing in current elite varieties. In this study, we evaluated a set of 57 barley introgression lines divided in groups depending on the expected levels of introgression (50, 25, and 12.5 %) from one Hordeum spontaneum accessions (Hsp 41-1) and on those (50 and 25 %) from a second (Hsp 41-5); in both cases the 25 % level was represented by two groups depending on the other parent. The two H. spontaneum accessions have been used as the best sources of drought tolerance in the ICARDA barley-breeding program. Graphical genotyping and genetic diversity analysis were used to examine the relative contribution of H. spontaneum and the extent of genetic differences among the 57 lines using 74 microsatellite markers that cover 941 cM of the barley genome. The average proportion of the genome containing H. spontaneum alleles in each group was of 44.5 %, group 1; 24.6 %, group 2; 21.6 %, group 3; 45.4 %, group 4; 19 %, group 5; 15.5 %, group 6 and 11.4 %, group 7. Introgression lines in group 1 and 4, with the highest observed introgression with Hsp 41-1 and Hsp 41-5, showed higher grain yield and better agronomic performance under field conditions in Breda and Khanaser, i.e., the two most stressed environments in which the groups were phenotyped, indicating the usefulness of using H. spontaneum as a source of chromosomal linkage blocks important for improved drought tolerance. However, more extensive genome coverage will be needed to identify the specific chromosomal regions associated with superior performance under extreme drought.

Full text

SSR analysis of introgression of drought tolerance
from the genome of Hordeum spontaneum into cultivated
barley (Hordeum vulgare ssp vulgare)
B. Lakew •R. J. Henry •J. Eglinton •M. Baum •
S. Ceccarelli •S. Grando
Received: 5 November 2011 / Accepted: 11 September 2012 / Published online: 19 September 2012
ÓSpringer Science+Business Media B.V. 2012
Abstract Wild barley (Hordeum vulgare ssp. spon-
taneum) and landraces are important sources of
resistance to biotic and abiotic stresses since they
possess wide genetic diversity that may be missing in
current elite varieties. In this study, we evaluated a set
of 57 barley introgression lines divided in groups
depending on the expected levels of introgression (50,
25, and 12.5 %) from one Hordeum spontaneum
accessions (Hsp 41-1) and on those (50 and 25 %)
from a second (Hsp 41-5); in both cases the 25 % level
was represented by two groups depending on the other
parent. The two H. spontaneum accessions have been
used as the best sources of drought tolerance in the
ICARDA barley-breeding program. Graphical geno-
typing and genetic diversity analysis were used to
examine the relative contribution of H. spontaneum
and the extent of genetic differences among the 57
lines using 74 microsatellite markers that cover
941 cM of the barley genome. The average proportion
of the genome containing H. spontaneum alleles in
each group was of 44.5 %, group 1; 24.6 %, group 2;
21.6 %, group 3; 45.4 %, group 4; 19 %, group 5;
15.5 %, group 6 and 11.4 %, group 7. Introgression
lines in group 1 and 4, with the highest observed
introgression with Hsp 41-1 and Hsp 41-5, showed
higher grain yield and better agronomic performance
under field conditions in Breda and Khanaser, i.e., the
two most stressed environments in which the groups
Electronic supplementary material The online version of
this article (doi:10.1007/s10681-012-0795-9) contains
supplementary material, which is available to authorized users.
B. Lakew
Holetta Agricultural Research Centre, Ethiopian Institute
of Agricultural Research, P.O. Box 2003, Addis Ababa,
Ethiopia
R. J. Henry
Queensland Alliance for Agriculture and Food Innovation,
University of Queensland, Brisbane, QLD 4072, Australia
J. Eglinton
School of Agriculture, Food and Wine, Faculty of
Sciences, University of Adelaide, Waite Campus, PMB1,
Glen Osmond, SA 5064, Australia
M. Baum S. Ceccarelli (&)S. Grando
Biodiversity and Integrated Gene Management Program,
ICARDA, P.O. Box 5466, Aleppo, Syria
e-mail: s.ceccarelli@cgiar.org
Present Address:
S. Ceccarelli
40 Impasse Suzanne Bernard, 34070 Montpellier, France
Present Address:
S. Grando
Consortium of International Agricultural Research
Centers, Agropolis International, Avenue Agropolis,
34394 Montpellier, France
123
Euphytica (2013) 191:231–243
DOI 10.1007/s10681-012-0795-9

were phenotyped, indicating the usefulness of using
H. spontaneum as a source of chromosomal linkage
blocks important for improved drought tolerance.
However, more extensive genome coverage will be
needed to identify the specific chromosomal regions
associated with superior performance under extreme
drought.
Keywords Barley Wild barley 
Drought resistance Graphical genotyping
Introduction
Barley (Hordeum vulgare L.) is considered to be the
most drought tolerant of the small grain cereals grown
in Mediterranean climates and is a major crop
in Mediterranean countries (Forster et al. 2004).
Significant variation to abiotic stresses exists in
primitive landraces and related wild species gene
pools (Ceccarelli et al. 1995; Forster et al. 2000). Wild
barley (H. vulgare ssp. spontaneum, (C. Koch) Thell,
hereafter abbreviated as Hsp) and landraces from the
Mediterranean environment have already proven to be
a useful source of genes for modern crop improvement
(Ellis et al. 2000; Lakew et al. 2011). A number of
morphological, agronomic and physiological traits
have been identified from wild barley, which can
improve the performance of barley under drought
stress conditions (Nevo 1992; Grando et al. 2001; Ellis
et al. 1997,2000; Ivandic et al. 2000; Teulat et al.
1997,1998; Shakhatreh et al. 2010). Wild barley has
also been used as a source of major resistance genes for
diseases such as powdery mildew, rust, and scald
(Ceccarelli and Grando 1987; Eglinton et al. 1999).
This richness of genetic diversity in wild barley and its
occurrence in a wide range of habitats including many
extremely unfavorable conditions such as biotic and
abiotic stresses in the region suggests that the wild
barley from the near east Fertile Crescent can be
exploited for the improvement of cultivated barley
(Jana and Pietrzak 1988; Shakhatreh et al. 2010).
Thus, the exploitation and utilization of the favorable
alleles of wild barley that were lost in cultivated barley
during domestication might be useful in the develop-
ment of drought tolerant varieties for low rainfall
environments.
Development of molecular markers permits the dis-
section of various qualitative and complex quantitative
traits and definition of their locations through genome
analysis. Genetic loci known to be involved in the
control of specific traits in cultivated barley can now be
targeted and investigated in the wild barley gene pool in
the search for novel and rare alleles(Forster et al. 2000).
In this regard, molecular markers offer a promising tool
to understand the complexity of the genetic control of
drought tolerance as well as the possible introgressions
of important genomic regions through marker-assisted
selection. To this end, the application of graphical
genotypes (GGT) analysis is a useful tool to estimate
the proportion of the donor parental genome in a genetic
background of elite cultivars.
Since its introduction (Young and Tanksley 1989),
graphical genotyping has been used for developing
highly informative genotyping sets (e.g., Macaulay
et al. 2001), and for tracing the inheritance of specific
genomic regions introgressed in various forms of
adapted lines and identifying specific regions of the
genome associated with desirable traits (e.g.,
McCouch et al. 1997; Hayano-Saito et al. 1998; Matus
et al. 2003; Van Berloo et al. 2001,2007; Semagn et al.
2007). In this study, a set of 57 barley genotypes
carrying various levels of chromosome segments of
Hsp were analyzed to investigate the extent and
positions of the introgressions from Hsp and to
identify introgression lines that could be useful for
future barley improvement under drought conditions.
Materials and methods
Plant material
The ICARDA barley breeding program has evaluated
several wild barley accessions and identified two
accessions, Hsp 41-1 and 41-5, as having superior
adaptation to drought stress. These accessions have
been used as parents in the ICARDA breeding
program, and they were phenotyped and genotyped
by Varshney et al. (2012); they do differ for a number
of traits with Hsp 41-1 being earlier, taller, with a
longer spike while yield is similar under severe
drought. They clustered in different groups resulting
from using DArT, SNP, and SSR markers.
The progenies from crosses with the two Hsp went
through several cycles of crossing and selection during
the breeding program specifically targeted at dry areas,
generating lines with improved adaptation to drought
232 Euphytica (2013) 191:231–243
123

stress. In the present study, we used the set of 57
introgression lines carrying various expected levels of
introgression from Hsp accessions 41-1 and 41-5
described by Lakew et al. (2011). As shown in Table 1
the seven groups had from an expected maximum of
50 % Hsp genome (group 1 with Hsp 41-1, and group
4 with Hsp 41-5), to an expected minimum of 12.5 %
Hsp genome (groups 6 with Hsp 41-1 and group 7 with
Hsp 41-5). Two groups of Hsp 41-1 (2 and 3) had both
25 % expected Hsp genome but they were kept
separate because the non spontaneum parent belonged
to two different type of germplasm, predominantly
adapted to a Mediterranean type of environment
(group 2) and predominantly non-adapted (group 3).
Similarly, two groups of Hsp 41-5 (5 and 7) had both
25 % expected Hsp genome, but were kept separate as
group 5 was a single and group 7 a double introgres-
sion of Hsp 41-5.
Genotyping
DNA was extracted from leaf tissues of 2–3 week-old
plants using a Cetyl-trimethylammonium bromide
(CTAB) protocol as described by Saghai-Maroof
et al. (1984). Seventy-four polymorphic simple
sequence repeat (SSR) markers were selected from
the public sequences of Ramsay et al. (2000) and
Karakousis et al. (2003) based on their uniform
distribution across the genome, quality of their PCR
product and polymorphism level, and used to genotype
the 57 introgression lines (Supplemental Table S1).
Fifty SSR markers were labeled (forward primer at the
5-prime end with 6-FAM, NED, HEX or VIX ABI
dyes) and the remaining 24 markers were unlabelled.
Polymerase chain reaction (PCR) was performed in a
total reaction volume of 10 lL that consisted of 1 lL
of the 50 ng/lL genomic DNA (template DNA), 1 lL
of 109PCR buffer containing 15 mM Mg
??
,1 lLof
a 2 mM dNTPs mixture, 0.5 units of Taq DNA
polymerase (Roche) and 0.5 lL of a 2.5 lM solution
of the forward and reverse primers. DNA amplifica-
tions were performed in a thermocycler (Applied
Biosystems GeneAmp PCR system 9600/9700/2700
as previously reported for each marker (Liu et al.
1996; Ramsay et al. 2000). PCR products for labeled
primers were analyzed with an ABI-Prism 377 DNA
Sequencer (Applied Biosystems) whereas amplified
products of unlabelled primers were separated on 5 %
denaturing polyacrylamide gels and visualized by
silver-staining as described by Bassam et al. (1991).
Allele data collection and size determination from the
ABI prism 377 was performed using the computer
software GeneScan 3.1 and Genotyper 2.1 (PerkinEl-
mer Biotechnologies, Foster City, CA, USA) The
scored allele data of the microsatellite markers were
recoded for the GGT analysis as follows: B and D for
lines with donor allele from Hsp 41-1 and 41-5 and U’
for lines with elite alleles (alleles present in the
introgression from elite varieties other than the donor
allele).
Data analysis
GGT and genome introgression analysis
To assess the proportion of wild barley chromosomal
segments derived from Hsp lines 41-1 and 41-5 and
conserved in the barley breeding lines, we calculated
the expected percentages based on the pedigree of
each line, while the observed percentages were
estimated from the molecular data obtained from the
GGT analysis. Chi-square test was used to test the
difference between the observed and the expected
percentage of Hsp 41-1 and 41-5 genome.
The GGT software (van Berloo 2007) was used to
determine the extent of genome conserved from the
donor parent in each introgression line and to construct
GGT. The graphical genotype shows the chromosomal
segment conserved or introgressed from Hsp into the
elite lines. The GGT analysis considers the distances
between markers in such a way that if two flanked loci
have alleles coming from the same parent, the interval
between them is considered as the length of the
segment, while if the chromosomal segment is flanked
by one marker of donor type and one marker of
recipient type, then half of the interval between them is
considered to have the length of one parent and the
other half from the other one (Young and Tanksley
1989). The program constructs a graphical represen-
tation of the data and visualizes, either by linkage
group or by individual genome examined.
Relationships with grain yield
The 57 lines were field tested during 2003–2004 (04),
2004–2005 (05), and 2005–2006 (06) at two locations
in Syria, Tel Hadya (TH: 36°010N, 36°560E, elevation
284 m asl) and Breda (BR: 35°560N, 37°100E,
Euphytica (2013) 191:231–243 233
123

Table 1 Percentage of Hsp 41-1 and 41-5 genome retained by the 57 introgression lines
Geno Pedigree Group % parental genome Significance test
Expected Observed*
Hsp 41-
1
Hsp 41-
5
Hsp 41-
1
Hsp 41-
5
v
2
stat Pvalue
1H.spont.41-1/Tadmor 1 50 0 52.6 0 0.14 ns
2H.spont.41-1/Tadmor 1 50 0 47.6 0 0.12 ns
3H.spont.41-1/Tadmor 1 50 0 36.6 0 3.59 ns
4H.spont.41-1/Tadmor 1 50 0 52 0 0.08 ns
5H.spont.41-1/Tadmor 1 50 0 37.5 0 3.13 ns
6 SLB05-96/H.spon.t 41-1 1 50 0 42.5 0 1.13 ns
7 SLB05-96/H.spont 41-1 1 50 0 42.6 0 1.1 ns
8H.spont.41-1/Arta//SLB39-01 2 25 0 26.4 0 0.08 ns
9 Hml//H.spont.41-1/Tadmor 2 25 0 34.9 0 3.92 \0.05
10 PI386540/ArabiAbiad//H.spont.41-1/Tadmor 2 25 0 28.5 0 0.49 ns
11 SLB05-96//H.spont.41-1/Tadmor 2 25 0 22.5 0 0.25 ns
12 SLB05-96//H.spont.41-1/Tadmor 2 25 0 29.4 0 0.77 ns
13 Tadmor//H.spont.41-1/SLB39-39 2 25 0 32.9 0 0.52 ns
14 Zanbaka//H.spont.41-1/SLB39-39 2 25 0 13.1 0 0.67 ns
15 Zanbaka//H.spont.41-1/SLB39-39 2 25 0 23.8 0 4.41 \0.05
16 Zanbaka//H.spont.41-1/SLB39-39 2 25 0 21.7 0 0.31 ns
17 Zanbaka//H.spont.41-1/SLB39-39 2 25 0 13.6 0 2.31 ns
18 Zanbaka//SLB45-40/H.spont.41-1 2 25 0 26.4 0 0 ns
19 Sara/3/H.spont.41-1//ER/Apm 2 25 0 24.4 0 2.5 ns
20 Sara/3/H.spont.41-1//ER/Apm 2 25 0 28.9 0 5.66 \0.05
21 Sara/3/H.spont.41-1//ER/Apm 2 25 0 25.4 0 0.06 ns
22 Sara/3/H.spont.41-1//ER/Apm 2 25 0 16.6 0 0.44 ns
23 H.spont.41-1/Tadmor/4/Gloria0S0/Copal0S0//Abn/3/
Shyri
3 25 0 21.4 0 5.2 \0.05
24 H.spont.41-1/Tadmor/4/Gloria0S0/Copal0S0//Abn/3/
Shyri
3 25 0 29.1 0 0.08 ns
25 H.spont.41-1/Tadmor/4/Gloria0S0/Copal0S0//Abn/3/
Shyri
3 25 0 14.5 0 0.01 ns
26 H.spont.41-1/Tadmor/4/Gloria0S0/Copal0S0//Abn/3/
Shyri
3 25 0 22.2 0 0.61 ns
27 H.spont.41-1/Tadmor/4/Gloria0S0/Copal0S0//Abn/3/
Shyri
3 25 0 17.4 0 0.01 ns
‘28 H.spont.41-1/Tadmor/4/Gloria0S0/Copal0S0//Abn/3/
Shyri
3 25 0 25 0 2.82 ns
29 SLB39-39/H.spont.41-5 4 0 50 0 64.3 4.09 \0.05
30 SLB39-39/H.spont.41-5 4 0 50 0 46 0.32 ns
31 SLB39-39/H.spont.41-5 4 0 50 0 45 0.5 ns
32 SLB05-96/H.spont 41-5 4 0 50 0 35 4.5 \0.05
33 SLB05-96/H.spont 41-5 4 0 50 0 36.6 3.59 ns
34 Arta//H.spont.41-5/Tadmor 5 0 25 0 16.5 2.89 ns
35 Arta//H.spont.41-5/Tadmor 5 0 25 0 16.6 2.82 ns
36 SLB12-59//SLB45-40/H.spont.41-5 5 0 25 0 13.2 5.57 \0.05
37 Zanbaka//H.spont.41-5/Tadmor 5 0 25 0 20.7 0.74 ns
234 Euphytica (2013) 191:231–243
123

elevation 300 m asl) with a long-term average rainfall
of 343 mm (30 seasons) and 275 mm (25 seasons),
respectively, and hence representing, in the case of
barley, a favorable and a stress environment, respec-
tively. In 2005, three more environments were added
to represent a higher level of drought stress by using a
late planting at Breda (BRL05) and by adding two
additional dry locations, namely Khanaser in Syria
(KH: 30°140N, 28°550E, elevation 200 m asl) and
Khanasri in Jordan (KHJ: 32°240N, 36°030E, elevation
800 m asl), known from previous experimental
work as two locations providing severe stress—with
long-term average rainfall of 221 and 150 mm,
respectively. Therefore, the lines were tested in a
Table 1 continued
Geno Pedigree Group % parental genome Significance test
Expected Observed*
Hsp 41-
1
Hsp 41-
5
Hsp 41-
1
Hsp 41-
5
v
2
stat Pvalue
38 Zanbaka//H.spont.41-5/Tadmor 5 0 25 0 19.8 1.08 ns
39 Zanbaka//H.spont.41-5/Tadmor 5 0 25 0 13.1 5.66 \0.05
40 Zanbaka//SLB45-40/H.spont.41-5 5 0 25 0 19.8 1.08 ns
41 ArabiAbiad/Arar//H.spont.41-5/Tadmor 5 0 25 0 25.6 0.01 ns
42 ArabiAbiad/Arar//H.spont.41-5/Tadmor 5 0 25 0 19 1.44 ns
43 ArabiAbiad/Arar//H.spont.41-5/Tadmor 5 0 25 0 20.5 0.81 ns
44 ArabiAbiad/Arar//H.spont.41-5/Tadmor 5 0 25 0 21.2 0.58 ns
45 H.spont.41-5/Tadmor//Hml-02/Lignee131 5 0 25 0 21.6 0.46 ns
46 Moroc9-75//H.spont.41-1/Tadmor/3/Moroc9-75/
ArabiAswad
6 12.5 0 17.6 0 2.08 ns
47 Moroc9-75//H.spont.41-1/Tadmor/3/Moroc9-75/
ArabiAswad
6 12.5 0 15.9 0 0.92 ns
48 Moroc9-75//H.spont.41-1/Tadmor/3/Moroc9-75/
ArabiAswad
6 12.5 0 14.8 0 0.42 ns
49 Moroc9-75//H.spont.41-1/Tadmor/3/Moroc9-75/
ArabiAswad
6 12.5 0 14.2 0 0.23 ns
50 Moroc9-75//H.spont.41-1/Tadmor/3/Moroc9-75/
ArabiAswad
6 12.5 0 13.3 0 0.05 ns
51 Moroc9-75//H.spont.41-1/Tadmor/3/Moroc9-75/
ArabiAswad
6 12.5 0 17.2 0 1.77 ns
52 Clipper/3/JLB37-74/H.spont.41-5//JLB37-74/
H.spont.41-5
7 0 25 0 7.6 12.1 \0.001
53 Clipper/3/JLB37-74/H.spont.41-5//JLB37-74/
H.spont.41-5
7 0 25 0 13.6 5.2 \0.05
54 Clipper/3/JLB37-74/H.spont.41-5//JLB37-74/
H.spont.41-5
7 0 25 0 10.6 8.29 \0.01
55 Clipper/3/JLB37-74/H.spont.41-5//JLB37-74/
H.spont.41-5
7 0 25 0 9.4 9.73 \0.01
56 Clipper/3/JLB37-74/H.spont.41-5//JLB37-74/
H.spont.41-5
7 0 25 0 14.3 4.58 \0.05
57 Clipper/3/JLB37-74/H.spont.41-5//JLB37-74/
H.spont.41-5
7 0 25 0 12.6 6.15 \0.05
Key for groupings: Group 1 first generation Hsp 41-1; Group 2 second generation Hsp 41-1; Group 3 Hsp 41-1/Tadmor crosses with
wide elite background; Group 4 first generation of Hsp 41-5; Group 5 second generation Hsp 41-5; Group 6 third generation of Hsp
41-1; Group 7 double introgression of Hsp 41-5
* Observed percentages were estimated from the GGT analysis using the molecular marker data obtained from this study
Euphytica (2013) 191:231–243 235
123

non-orthogonal set of nine environments (loca-
tion 9year combinations) eventually reduced to
seven because of the large experimental error in two
of them. Growing season rainfall varied from a
maximum of 381.3 mm TH04 to a minimum of 74.8
at BRL05 with KHJ and KH being also very dry (138
and 175 mm, respectively). The experimental design
was an alpha lattice with two replications and seven
incomplete blocks per replication; a plot consisted of
eight rows, spaced 0.2 m apart and the row length was
2.5 m, with 3.0 m
2
harvested from six central rows for
yield determination. Seeds were sown using a plot drill
with a seeding rate of 125 kg/ha. Plots were kept free
from weeds, diseases, and insect pests by a combina-
tion of chemical and hand weeding. The data were
analyzed as described in Lakew et al. (2011) and the
best linear unbiased predictors (BLUPs) were used for
correlation and GGE biplot analysis. The relationship
between the percentages (subjected to angular trans-
formation) of the genome contributed by Hsp and the
grain yield in the 7 year-location combinations in
which the 57 lines were tested (Lakew et al. 2011) was
analyzed with the Pearson’s simple correlation coef-
ficient and with the GGE biplot (Yan 2001) using both
the individual lines data as well as the average grain
yield of the seven groups.
Results and discussion
Proportion of Hsp 41-1 and 41-5 chromosomal
segments conserved in the 57 barley introgression
lines
The two wild barley accessions Hsp 41-1 and 41-5
have made a variable contribution to the 57 breeding
lines.
The average proportion of the genome conserved
from Hsp line 41-1 in the 34 lines was 15.8 % ranging
from 13.1 to 52.6 %, while it was 9.2 % in the 23 lines
from the other donor parent Hsp line 41-5 ranging
from 7.6 to 64.3 %. Out of the 57 introgression lines,
13 had less than 15 % observed introgression of Hsp,
the majority (30) had 15–30 % introgression segments
and the remaining 14 lines had more than 30 %
(Table 1). The actual values are significantly skewed
from the expected as indicated by the results of v
2
tests, showing that the selection pressure imposed by
breeders had an influence in a number of cases on
whether the observed proportion of the Hsp genome
was higher or lower than the expected. In summary,
the 74 SSR markers when analyzed by GGT, estimated
the proportion of parental genome in the four groups
derived from Hsp line 41-1, with respect to the total
genome length (i.e., 941 cM), as 44.5, 24.6, 21.6, and
15.5 % in groups 1, 2, 3, and 6, respectively, and in the
three groups derived from Hsp line 41-5 as 45.4, 19.0,
and 11.4 %, in groups 4, 5, and 7, respectively
(Table 1). The contribution of Hsp 41-1 in group six
was not significantly higher than the expected 12.5 %.
The contribution of the other wild barley (Hsp 41-5) in
group four ranged from 35 to 64.3 % as compared to
the expected 50 % whereas the lines in group five
mainly retained a percentage of the donor genome
(between 13.1 and 25.6 %) lower than the expected
25 %. In contrast, the actual percentage of Hsp 41-5
genome in-group seven was much lower (7.6–14.3 %)
than the expected (25.0 %). This could be attributed to
a significant selection pressure against the Hordeum
spontaneum genome and the presence on non-parental
(other) alleles. Matus et al. (2003), Pillen et al. (2003),
and Hori et al. (2005) reported average percentage of
exotic substitution segments in backcross generations
of 12.6, 12.7, and 12.9 %. In another AB-QTL study,
von Korff et al. (2004), using two BC
2
doubled haploid
populations, estimated the average percentage of
substitution segments at 13.9 and 10.8 %. The lines
objects of the present study are a random sample of
those derived from crosses with H. spontaneum in the
breeding program and they were selected for adapta-
tion to low rainfall environments. Since the wild
barley genome may have provided alleles more rustic
and adapted to dry environments, we may speculate
(or hypothesize) that wild barley genome would
confer a higher adaptation to dry environments.
GGT and genome introgression
The linkage blocks conserved from the parental
genome (Hsp lines 41-1 and 41-5) were illustrated
using GGT as a mean to visualize the marker data in
the form of GGT where the percentages of parental
genome for each chromosome are shown. Introgres-
sions of Hsp were detected in all the lines and for all
chromosomes. The number of polymorphic markers
per chromosome varied from 7 on chromosome 1 to 14
on chromosome 5 (Fig. 1) with an overall average of
236 Euphytica (2013) 191:231–243
123

10.6 polymorphic markers per chromosome. Alleles
from Hsp were detected on all the 74 marker loci in
one or more individuals. The distribution of introgres-
sions from the donor parent varied among the seven
barley chromosomes. The average length of donor
chromosome segments of Hsp was 20.3 cM (28 %),
44.6 cM (28 %), 45.4 cM (27 %), 23.4 cM (24 %),
45.3 cM (22 %), 28.8 cM (28 %), and 37.0 cM
(26 %) for chromosomes 1H, 2H, 3H, 4H 5H, 6H,
and 7H, respectively (Fig. 1). The overall average size
of introgressed DNA per chromosome was 35.0 cM
(Fig. 1). In another similar study, Matus et al. (2003)
reported that the average insert length of wild barley
segments in recombinant chromosome substitution
lines of barley was 38.6 and 35 cM in AB populations
(von Korff et al. 2004).
7
11
12
10
14
11
74
Chr 1
Chr 2
Chr 3
Chr 4
Chr 5
Chr 6
Chr 7
All chromosomes
Hsp 41-1 Hsp 41-5 Non Hsp
p
arent
Fig. 1 Pie charts for the seven barley chromosomes depicting
the proportion of genome introgression in barley lines from the
Hsp donor parent. The pie charts were plotted from the graphical
genotyping analysis outputs. The numbers in the center of the
pies correspond to the number of SSR markers used in the study
Euphytica (2013) 191:231–243 237
123

Examples of lines with a high and a low proportion of
Hsp introgression are given in Fig. 2a, b. Line 29
(SLB39-39/H.spont.41-5) from group four of first gen-
eration of Hsp 41-5 cross (50 % expected wild barley
introgression) had a 64.3 % introgression of Hsp genome
41-5 spread over the seven chromosomes (Fig. 2a). In
contrast, line 52 (Clipper/3/JLB37-74/H.spont.41-5//
JLB37-74/H.spont.41-5) from group 7 (25 % expected
(a)
0
25
50
75
100
125
150
175
200
cM
Chr 1
Bmac0213 38.00
Bmag0211 71.00
Bmac0032 73.00
Bmag0105 73.00
Bmac0154 92.00
Bmag0382 97.00
HvHVA1 112.00
Chr 2
Bmac0134 12.00
Scssr00334 66.00
HVBKASI 67.00
Bmag0378 69.00
Ebmac0684 75.00
Bmag0125 89.00
Bmag0114 90.00
HVM54 128.00
Ebmac0415 130.00
Bmag0749 145.00
Scssr08447 173.00
Chr 3
Scssr 10559 18.00
HvLTPPB 19.00
Bmag0006 41.00
Bmac0209 50.00
Ebmac0871 52.00
Scssr 25691 65.00
GMS116 71.00
Scind05281 120.00
Bmag0013 131.00
HVM62 151.00
Scssr 25538 163.00
Bmac0029 182.00
Chr 4
HVM40 19.00
HvOLE 26.00
Scssr20569 42.00
Scssr18005 52.00
GMS089 54.00
HVM68 57.00
Scssr14079 81.00
Bmag0419 86.00
Ebmac0701 96.00
HVM67 115.00
Chr 5
Scssr 02306 10.00
Scssr 07106 24.00
Bmac0113 42.00
Scind02587 51.00
Bmac0096 57.00
Bmag0337 61.00
Scind16991 82.00
Scssr 05939 110.00
HvLOX 137.00
Scssr 10148 143.00
GMS027 156.00
Bmag0222 170.00
GMS001 200.00
Scssr 03907 204.00
Chr 6
Bmac0316 10.00
Scssr09398 10.00
Scind60002 48.00
HVM74 71.00
EBmac0874 71.00
Bmag0009 72.00
Bmac0018 73.00
Ebmac0639 75.00
Scssr05599 111.00
Chr 7
HVM4 27.00
Scssr 07970 66.00
Bmac0167 77.00
Ebmac0827 78.00
Bmag0217 83.00
Bmag0321 83.00
Scssr 15864 84.00
HVCMA 88.00
Bmag0120 102.00
Scssr 04056 151.00
Bmag0135 168.00
Legend B D U
(b)
0
25
50
75
100
125
150
175
200
cM
Chr 1
Bmac0213 38.00
Bmag0211 71.00
Bmac0032 73.00
Bmag0105 73.00
Bmac0154 92.00
Bmag0382 97.00
HvHVA1 112.00
Chr 2
Bmac0134 12.00
Scssr00334 66.00
HVBKASI 67.00
Bmag0378 69.00
Ebmac0684 75.00
Bmag0125 89.00
Bmag0114 90.00
HVM54 128.00
Ebmac0415 130.00
Bmag0749 145.00
Scssr08447 173.00
Chr 3
Scssr10559 18.00
HvLTPPB 19.00
Bmag0006 41.00
Bmac0209 50.00
Ebmac0871 52.00
Scssr25691 65.00
GMS116 71.00
Scind05281 120.00
Bmag0013 131.00
HVM62 151.00
Scssr25538 163.00
Bmac0029 182.00
Chr 4
HVM40 19.00
HvOLE 26.00
Scssr20569 42.00
Scssr18005 52.00
GMS089 54.00
HVM68 57.00
Scssr14079 81.00
Bmag0419 86.00
Ebmac0701 96.00
HVM67 115.00
Chr 5
Scssr02306 10.00
Scssr07106 24.00
Bmac0113 42.00
Scind02587 51.00
Bmac0096 57.00
Bmag0337 61.00
Scind16991 82.00
Scssr05939 110.00
HvLOX 137.00
Scssr10148 143.00
GMS027 156.00
Bmag0222 170.00
GMS001 200.00
Scssr03907 204.00
Chr 6
Bmac0316 10.00
Scssr09398 10.00
Scind60002 48.00
HVM74 71.00
EBmac0874 71.00
Bmag0009 72.00
Bmac0018 73.00
Ebmac0639 75.00
Scssr05599 111.00
Chr 7
HVM4 27.00
Scssr07970 66.00
Bmac0167 77.00
Ebmac0827 78.00
Bmag0217 83.00
Bmag0321 83.00
Scssr15864 84.00
HVCMA 88.00
Bmag0120 102.00
Scssr04056 151.00
Bmag0135 168.00
Legend BDU
Fig. 2 Graphical genotyping of two barley introgression lines
showing the largest (line 29 of group 4 with 64.3 % of Hsp
segments) and the lowest (line 52 of group 7 with 7.6 % of Hsp
segments) amount of introgression: (red bar)Hsp segments;
(gray bar) vulgare segments. (Color figure online)
238 Euphytica (2013) 191:231–243
123

wild barley introgression) had only 7.6 % introgression
of the Hsp 41-5 genome, with the introgressed segments
located in only three of the seven chromosomes (3H, 4H,
and6H)(Fig. 2b). GGT of all the 57 lines are shown in
Fig. 3, where the broken lines separate the seven groups
as described at the bottom of Table 1.
Figure 3reflects visually the information given in
Table 1adding a graphical representation on how the
1: Chr 1 2: Chr 2 3: Chr 3 4: Chr 4 5: Chr 5 6: Chr 6 7: Chr 7
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
Legend B D U
Fig. 3 Graphical genotypes of the 57 barley introgression lines
using 74 SSR markers. Vertical bars represent the seven barley
chromosomes with chromosome numbers given on the top of
each bar.Numbers on the left side of each bar refer to the 57
lines (refer to Table 1) for pedigree of each line). Legend
B=Hsp 41-1; D =Hsp 41-5 and U =other elite sources
Euphytica (2013) 191:231–243 239
123

Hsp genome is distributed in each of the seven
chromosomes of the 57 lines. For a further detailed
representation see supplemental Fig. S1a–g. In group
1, with an observed introgression of 44.5 %, the Hsp
41-1 chromosome segments are distributed throughout
all the chromosomes with the only exception of
chromosome 3 in line 5. In the case of groups 2 and 3,
with an observed introgression of 24.6 and 21.6 %,
respectively, the Hsp 41-1 chromosome segments are
more sparsely distributed: ten of the 15 lines of group 2
had Hsp 41-1 chromosome segments in all seven
chromosomes while five lines (line 13 with chromo-
some 1, line 15 with chromosome 4, line 17 with
chromosomes 3 and 6, and line 18 with chromosome
4) had one or more chromosomes without any
introgressed segment. The last group with introgres-
sion from Hsp 41-1 (group 6 with six lines) had
slightly more (15.5 %) than the expected 12.5 % Hsp
41-1 genome and all the lines had one or more
chromosomes with no Hsp 41-1 chromosome seg-
ments or with very small segments like chromosome 1
and 2. In the case of the groups derived from Hsp 41-5,
all the lines of group 4 (average observed introgression
of 45.4 %) had at least some Hsp 41-5 segments on
each of the seven chromosomes. On the contrary, the
other two groups (groups 5 and 7 with an observed
introgression of 19.0 and 11.4 %, respectively) had, as
expected, much less Hsp segments: in group 5 six of
the 12 lines had one or more chromosomes with no
Hsp segments. Of particular interest are the lines of
group 7, the groups with the largest deviation between
observed (11.4 %) and expected (25.0 %), in which
there was a high level of uniformity in the length and
position of the introgressed segments (see for example
chromosomes 1, 3, 6, and 7) suggesting that the two
sister lines used in the cross were very similar and had
a small amount of Hsp 41-5.
Relationships with grain yield
The relationships between the overall percentage of
the genome contributed by Hsp and the grain yield in
the 7 year-location combinations was analyzed with the
Pearson’s’ simple correlation coefficient and with the
GGE biplot (Yan 2001) using both the individual grain
yields of the 57 lines (Fig. 4) as well as the groups means
(Fig. 5). Both biplots explain between 60 and 86 % of
Fig. 4 GGE biplot of the
percentage genome
introgression (HSP) from
Hordeum spontaneum and
grain yield in seven
environments in
7 year 9location
combinations of 57 barley
genotypes (data from
Table 4 of Lakew et al.
2011.(Locations TH =Tel
Hadya, BR =Breda,
KH =Khanasri. Years 04,
05 and 06 =2004, 2005,
and 2006)
240 Euphytica (2013) 191:231–243
123

the GGE (Genotype ?Genotype 9Environment
interaction) and therefore are a good fitting to the data.
In the GGE biplot in Fig. 4the vector representing
the percentage of the genome contributed by Hsp is
closely associated with the grain yield in Khanaser
2005 and Breda 2004 which, with 771 kg/ha and
1,243 kg/ha (Table 2 from Lakew et al. 2011) were
the two lowest yielding year-location combinations.
The majority of lines of group 1 (numbers 1–7) and
some lines of group 2 (particularly 13, 16, and 22) are
close to the vectors of the two lowest yielding
locations and in some cases to Breda 2005 (BR05)
which was the third lowest yielding location-year
combinations with 1,912 kg/ha. Many of the lines
have a grain yield lower that average in the highest
yielding location-year combinations (TH04, TH05,
and TH06) with 3,312, 4,532, and 3,452 kg/ha,
respectively.
This suggests that, in general, the higher the
percentage of Hsp genome in the introgression lines,
the higher is the grain yield in the most severe drought
stress conditions. However, this applies more to Hsp
41-1 than to Hsp 41-5: in fact, the lines with the highest
observed introgression from Hsp 41-5 (lines 29–33) are
not as closely associated with the lowest yielding
location-year combinations (except line 29 i.e., the only
one with a significantly higher proportion of Hsp).
An indication that, even with large differences
between individual lines, the percent of observed
introgression with Hsp is associated with grain yield
under drought, is shown by the six lines of group 7
(average introgression of 11.4 %) which yielded
poorly in the low yielding location-year combinations
and, as a group, was the highest yielding in the highest
yielding location-year combinations (TH04, TH05,
and TH06).
The association between percent of observed intro-
gression with Hsp, and particularly Hsp 41-1, and grain
yield under drought is confirmed by the GGE biplot in
Fig. 5, in which group 1 is closely associated to both the
vector for percent of observed introgression with Hsp
and the average grain yield in most stressed location-
year combination, and group 4 (45.4 % introgression
with Hsp 41-5) is associated to the vectors of three low
yielding location-year combinations.
However, a more extended coverage of the genome
of the 57 introgression lines will be necessary to
identify the chromosomal segments responsible for the
differences in grain yield under the most stressed
conditions.
Acknowledgments We acknowledge the financial support of
B. Lakew who received a fellowship from Molecular Plant
Breeding CRC, Australia to carry out his PhD work between
Southern Cross University and ICARDA, Syria.
Fig. 5 GGE biplot of the
percentage genome
introgression (HSP) from
Hordeum spontaneum (Hsp)
and grain yield in
7 year 9location
combinations of seven
groups of barley genotypes
with 44.5 % (1), 24.2 % (2),
22.6 % (3) and 15.5 % (6)
Hsp 41-1 genome, and
45.4 % (4), 19.0 % (5) and
11.4 (%) Hsp 41-1 genome.
(Locations TH =Tel
Hadya, BR =Breda,
KH =Khanasri. Years: 04,
05 and 06 =2004, 2005 and
2006)
Euphytica (2013) 191:231–243 241
123

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