Characterization of sunflower inbred lines (Helianthus annuus L.) for high oleic
acid content using SSR markers
Nancy G. Grandón1, Ma. Valeria Moreno1, Ma. Carolina Scorcione1, Jorge O. Gieco1, Daniel
Alvarez2, Norma Paniego3, Ruth Heinz3.
1
Laboratorio de Biotecnología, INTA-EEA Manfredi. Ruta Nac. Nº 9. Km 636. (5988) Manfredi,
Córdoba, Argentina. E-mail: nggrandon@manfredi.inta.gov.ar. 2Grupo Mejoramiento de Girasol, INTAEEA Manfredi. Ruta Nac. Nº 9. Km. 636. (5988) Manfredi, Córdoba, Argentina. 3Instituto de
Biotecnologia, CNIA-INTA Castelar. Los Reseros y Las Cabañas s/n. (1686) Hurlingham, Buenos Aires,
Argentina.
ABSTRACT
 Sunflower seed oil contains a high proportion (about 90%) of unsaturated fatty acids: oleic
(C18:1) and linoleic (C18:2) acids. They have been described as healthier, essential to human metabolism
and potent hypocholesterolemic factors. High oleic acids levels can extend oxidative stability and life
oil´s utility. Therefore, the increasing current market demand has been oriented for quality differentiated
foods and focused sunflower breeding programs towards the development of improved cultivars with
increased oleic acid content. The identification of QTL associated with this trait is a powerful molecular
tool to facilitate sunflower breeding programs progress. The aim of this work was to generate a mapping
population for the high oleic acid content from two contrasting inbred lines, identify polymorphic SSR
markers between the two parental lines and characterize the population for oleic acid content.
 An F2 mapping population comprising 115 F2 individuals was developed from a cross between
R285 (high oleic acid) and R023 (low oleic acid) inbred lines. Three hundred eighty six SSR markers
which have been previously mapped in sunflower were used (275 HA and 111 ORS series). Genotyping
was done by capillary electrophoresis and allele identification was performed using GeneMapper v. 4.0
software (Applied Biosystem). The mapping population of 115 F2 individuals was developed from a cross
between R285 and R023 parental inbred lines. The experimental field design used was a randomized
complete block assay with three replicates and the fatty acid composition was determined by gas
chromatography.
 Eighty two polymorphic SSR markers (21.24%) between both parental inbred lines were
identified. This first step allowed the selection of those polymorphic markers that were used to genotype
the F2 mapping population. The phenotypic analysis revealed fatty acid content variation segregating
within the mapping population (p<0.05). Three categories according to oleic acid content (low: 12.96 –
37.74%, intermediate: 41.35 – 58.7%, high: 63.88 – 87.91%) were identified.
 The generation of an F2 mapping population derived from contrasting inbred lines for oleic acid
content, its phenotypic characterization and the identification of 82 polymorphic SSR markers between
these parental lines, represent strategic tools to perform future QTL analysis and to generate molecular
markers useful for marker assisted breeding.
 The results of this work will allow the advance in the genetic behavior dissection of high oleic
acid trait, enabling the detection of QTL and linked markers, useful as a molecular tool for the sunflower
breeding programs of INTA.
Key words: oleic acid – QTL – SSR markers – sunflower.
INTRODUCTION
Cultivated sunflower (Helianthus annuus L.) seed oil contains near 90% of unsaturated fatty acids:
oleic (C18:1) and linoleic (C18:2) acids. They have been described as healthier, essential to human
metabolism and potent hypocholesterolemic factors (Kris-Etherton and Yu, 1997). Moreover, high oleic
acids levels can extend oxidative stability and oil life utility. The increasing current market demand has
been oriented for quality differentiated foods and focused sunflower breeding programs towards the
development of improved cultivars with increased oleic acid content.
Sunflower seed oil composition and especially oleic acid content, is highly influenced by
environmental factors as the temperature and the amount of moisture in the soil (Lájara et al., 1990;
Baldini et al., 2002; Rondanini et al., 2003). In addition, high oleic acid genes show unstable expression
for oleic acid content in different genetic backgrounds and therefore phenotypic selection for the high
oleic acid trait could be difficult across different environments and seasons (Demurin and Škorić, 1996).
DNA markers are not influenced by the environment and therefore selection based on markers linked to
the high oleic acid trait will allow further advance in breeding for this character. Identifying molecular
markers linked to the high oleic acid trait (HOA) that can be further used in marker-assisted selection
(MAS) would greatly contribute in developing stable mid and high oleic acid breeding lines (Van der
Merwe, 2010).
Molecular markers are powerful tools to study genetic variation and relate them to phenotypic
variation (Varshney et al., 2005). SSRs (Simple Sequence Repeats) show high reproducibility and
genomic covering, co-dominance, neutrality and they are highly polymorphic (Spooner et al., 2005).
Therefore, they have been extensively used to study genetic variability in different organisms. In plants
SSRs are being used to assess genetic variability in germplasm collections for making appropriate choice
of parents to generate breeding populations, mapping and tagging of genes or QTL (Quantitative Trait
Loci) identification for agronomic and disease resistance traits, genome mapping, MAS of promising lines
and marker assisted backcrossing (MAB) during breeding programs, gender identification, studying the
population structure and taxonomic, as well as in the analysis of phylogenetic relationships (Kalia et al.,
2011).
Regarding HOA breeding, Fick (1984) found that the high oleic character was determined by a codominant gen called Ol, whereas Urie (1985) described this gen as dominant. A second modificator gen
(Ml) of Ol was detected as necessary for the character expression (Miller et al., 1987). Later, three
complementary genes Ol1, Ol2, Ol3 were described (Fernández-Martínez et al., 1989). The identification of
QTL associated with this trait is a powerful molecular tool to facilitate sunflower breeding programs
progress. SSR mapping to study high oleic character in cultivated sunflower was used in some recent
works (Ebrahimi et. al., 2008; Haddadi et. al., 2010). Furthermore, AFLP (Amplified Fragment Length
Polymorphism) and RFLP (Restriction Fragment Length Polymorphism) mapping in this species were
used. Different QTL for oleic acid (OA) and stearic acid (SA) content were detected (Pérez- Vich et. al.,
2002).
The sunflower Active Germplasm Bank of INTA Manfredi (AGB-IM) preserves circa 1200
accessions of different geographic origins, including East Germany, Argentina, Armenia, Australia,
Bolivia, Brazil, Bulgaria, Canada, Chile, China, Spain, United States, France, Greece, Hungary, Israel,
Italy, Morocco, Moldova, Poland, Romania, Russia, Syria, Turkey, Uruguay and ex-Yugoslavia. The
collection encompasses diverse accession categories including open-pollinized populations, composites,
cultivars, inbred lines, etc.
In the last six years, efforts to exploit germplasm bank genetic resources with genomics-driven plant
breeding methods such as linkage and association mapping are being made to characterize the bank and to
detect the genetic bases underlying agronomical trait. In this work, initial studies and recent advances in
high oleic acid breeding, including the fatty acid phenotype and the molecular characterization of the
parental lines of a mapping population underlying fatty acid composition traits, are presented. The aim of
this work was to identify polymorphic SSR markers between two cultivated sunflower inbred lines with
contrasting high oleic acid content, to generate an F2 mapping population derived from these lines and to
assess its phenotypic characterization, enabling the future detection of QTL and linked markers useful for
the sunflower breeding programs.
MATERIALS AND METHODS
An F2 mapping population was developed from a cross between R285 (high oleic acid) and R023
(low oleic acid) inbred lines. Table 1 shows the fatty acid profile of the parental lines. Field trails were
conducted in randomized complete block design with three replicates. The fatty acid composition of F4
seeds was determined by gas chromatography (AOCS, 1998). Statistical analysis (ANOVA) was made
with Infostat software (Di Rienzo et al., 2010).
Table 1: Fatty acid composition of inbred parental lines
Parental
C16:0
C18:0
C18:1
C18:2
C18:3
C20:0
C20:1
22:0
C22:1
C24:0
O/L
IY
R285
3.14
4.17
87.2
3.1
0.1
0
0.30
0.9
0.09
0.50
27.79
80.70
6.02
4.21
62.8
0.1
0
0.15
0.7
0.11
0.26
0.40
130.65
R023
25.4
C16:0: palmitic acid %, C18:0: stearic acid %, C18:1: oleic acid %, C18:2, linoleic acid %, C18:3: linolenic acid %, C20:0:
arachidic acid %, C20:1: eicosanoic acid %, C22:0: behenic acid %, C22:1: erucic acid %, C24:0: lignoceric acid %, O/L: ratio
oleic/linoleic, IY: iodine index.
DNA extraction was made using NucleoSpin Plant II kit (Machery – Nagel, Germany) based in 0.03
g of liophylized material. Inbred lines genotyping was performed with 386 SSR markers. PCR mix
containing 15 ng/µl template DNA, 1X PCR buffer, 1.5 mM MgCl2, 0.2 mM dNTPs (Fermentas,
Canada), 0.25 µM of each primer, 0.5 U of Taq DNA polymerase (Life Technologies, Argentina) was
amplified using AB GeneAmp system 9700 termocycler (Applied Biosystems, USA). Amplification
conditions were a touchdown of 64ºC-52ºC (35 cycles) and final extension at 72ºC. Flourescent fragments
were resolved using electrophoresis through an ABI 3130xl DNA analyzer (Applied Biosystems, USA).
Fragment sizing was done using the ROX 500 internal-lane standard (Applied Biosystems; ROX, 6carboxy-x-rhodamine). GeneMapper 4.0 software (Applied Biosystems, USA) was used to score SSR
alleles.
RESULTS AND DISCUSSION
An F2 mapping population comprising 115 individuals was obtained from a cross between the
contrasting inbred lines R285 and R023 for oleic acid content.
Eighty two (21.24%) of 386 SSR markers analyzed (54 HA set, 28 ORS set) were polymorphic
between both inbred lines and will be used in genotyping of F2 mapping population (Table 2). Remaining
SSR markers were monomorphic (24.6%), null alleles (7.5%), others showed nonspecific amplification
products with complex profile or multiallelic (21.5%) and 25.13% could not be amplified.
Table 2: Polymorphic SSR between R285 and R023 parental lines
Marker
name
HA102
Genbank
accession
number
BV727861
LG
allele in
R285 (bp)
Allele in
R023 (bp)
Marker
name
unknown
160
154
HA3582
Genbank
accession
number
BV728254
LG
allele in
R285 (bp)
Allele in
R023 (bp)
16
122
131
HA140
G67517
5
145
158
HA3627
BV728237
5
190
200
HA196
G67518
unknown
176
179
HA3632
BV728239
unknown
206
247
HA293
G67519
14
121
113
HA3691
BV728256
unknown
396
385
HA360
G67406
16
236
223
HA3700
BV728302
5
172
176
HA432
G67407
4
170
165
HA3703
-
4
213
215
HA557
BV728012
unknown
126
128
HA3847
BV728286
10
140
147
HA729
BV727945
unknown
125
128
HA3878
BV728314
7
199
232
HA790
BV727948
unknown
145
152
HA3886
BV728315
14
186
183
HA806
G67410
unknown
186
192
HA4011
BV728360
13
214
216
HA911
BV727888
8
180
178
HA4057
BV728333
3
208
206
HA969
BV727890
unknown
110
122
HA4149
BV728355
17
188
199
HA1108
BV727970
10
185
144
HA4239
BV728202
15
112
109
HA1155
BV727896
12
96
90
ORS59
BV012516
unknown
185
167
HA1848
BV728005
7
242
260
ORS229
BV012471
2
172
166
HA1938
BV728039
unknown
229
226
ORS297
BV006634
17
226
222
HA2057
BV728112
unknown
117
121
ORS316
BV005917
13
179
182
HA2063
BV728113
9
180
171
ORS371
BV006649
1
251
257
HA2077
BV727907
14
112
116
ORS420
BV005977
unknown
136
132
HA2145
BV728363
unknown
188
223
ORS457
BV005997
11
228
226
HA2178
BV728124
unknown
156
154
ORS510
BV006030
9
248
256
HA2191
BV728131
16
204
206
ORS607
BV006704
11
276
274
HA2193
BV727902
16
137
127
ORS613
BV006091
10
230
226
HA2237
BV728143
unknown
122
132
ORS662
BV006121
1
230
320
HA2272
BV728137
unknown
252
228
ORS687
BV006138
15
166
163
HA2348
BV728037
unknown
286
280
ORS727
BV006163
17
189
197
HA2448
BV728038
unknown
212
214
ORS799
BV006742
13
140
203
HA2499
BV728042
unknown
148
138
ORS807
BV006217
10
268
255
HA2500
BV728041
unknown
137
141
ORS844
BV006252
9
305
307
HA2547
BV728047
unknown
206
142
ORS878
BV006281
10
191
200
HA2605
BV728347
8
88
75
ORS887
BV006290
9
243
249
HA2714
BV728147
14
223
227
ORS894
BV006297
8
251
249
HA2946
BV728089
unknown
135
116
ORS899
BV006302
16
322
312
HA3070
BV728164
unknown
106
111
ORS959
BV006356
1
246
236
HA3272
BV728357
7
162
164
ORS1024
BV006408
5
227
231
HA3288
BV728101
unknown
193
218
ORS1065
BV006445
2
273
297
HA3298
BV728102
unknown
134
131
ORS1085
BV006463
12
277
281
HA3330
BV728245
13
148
146
ORS1146
BV006511
11
344
380
HA3348
BV728079
unknown
203
185
ORS1222
BV006579
3
440
442
HA3349
BV728219
unknown
259
265
ORS1247
BV006602
17
339
336
HA3373
BV728080
unknown
183
181
ORS1265
BV006617
9
228
226
LG: linkage group according to Poormohammad Kiani et al. 2007. bp: base pairs
Fifty three out of 82 polymorphic SSR markers, have known position and localize on 16 sunflower
linkage groups (LG) (Poormohammad Kiani et al., 2007) (Table 2). Twenty-five of them were also
mapped by Ebrahimi et al. (2008) and Haddadi et al. (2010), on 14 LG. These authors reported that most
important QTL for OA trait are located on LG 10 with several QTL controlling fatty acids content.
Among polymorphic SSR markers detected in the present study, seven SSR mapping on LG 10 were
identified.
The percentage of polymorphism (21.24%) was low comparing with previous works (Maringolo,
2007; Talia, 2008); however the polymorphic SSRs are considered informative for this study. Therefore,
the incorporation of more SSR markers will contribute increase the probability of QTL detection for OA
contains.
Mean oleic acid content for the parental inbred lines and for all F4 families was determined as
described in Materials and Methods. According to the OA content the F4 families analyzed in this work
were categorized in three groups, low (12.96-37.74%), intermediate (41.35-58.70%) and high content
(63.88-87.91%). Analyses of phenotypic variance (ANOVA) revealed variation for oleic acid content in
the mapping population (p<0.05).
The results of this work allowed the validation of 82 HA markers in cultivated sunflower inbred lines
for high oleic traits. These have been used for QTL mapping for resistance to Sclerotinia head rot
(Sclerotinia sclerotiorum (Lib.) De Bary) (Maringolo, 2007) and characterization of genomic regions
involved in disease resistance (Talia, 2008). Currently they are being used to map QTL associated with
tolerance to water stress. The identification of this polymorphic SSR marker set between these parental
lines, along with the generation of the mapping population and its phenotypic characterization for OA
content represent strategic tools to perform future QTL analysis and to generate molecular markers useful
for marker assisted breeding.
ACKNOWLEDGEMENTS
Several grants from CONICET and INTA are gratefully acknowledged.
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