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Diversification of seed carotenoid content and profile in wild
barley (Hordeum chilense Roem. et Schultz.) and Hordeum
vulgare L.–H. chilense synteny as revealed by DArTSeq
markers
C. M. Avila .M. G. Mattera .C. Rodrı
´guez-Sua
´rez .C. Palomino .
M. C. Ramı
´rez .A. Martin .A. Kilian .D. Hornero-Me
´ndez .S. G. Atienza
Received: 27 September 2018 / Accepted: 6 February 2019
ÓSpringer Nature B.V. 2019
Abstract The high carotenoid content and distinc-
tive carotenoid profile of tritordeum are conferred by
its wild progenitor, Hordeum chilense. Genetic studies
on this wild barley could exploit the knowledge gained
in Hordeum vulgare L. if the synteny between H.
vulgare and H. chilense is established. DArTSeq
markers were aligned to barley genome and used to
inspect H. chilense-barley synteny. All chromosome
pairs showed a good degree of collinearity with the
exception of 7Hv–7Hch, where a reciprocal
translocation in 7Hch was identified. Carotenoid
analyses revealed a high diversity for total carotenoids,
free and esterified lutein in a collection of H. chilense.
Population structure analyses revealed the existence of
two subgroups contrasting for total carotenoids, free
lutein and esterified lutein in seeds. Lutein esters were
produced with palmitic and linoleic acids as happens in
tritordeum. However, tritordeum prefer palmitic acid
for the synthesis of lutein esters but this preference is
not maintained in H. chilense. This indicates the
existence of diversity in the enzymes involved in the
esterification which could be useful in tritordeum
breeding. Furthermore, several accessions produced
lutein monoesters but they lacked diesters which
suggests that esterification is controlled by more than
one enzyme in H. chilense. A total of 91 marker-trait
associations were identified for carotenoid content and
profile. These associations constitute a good starting
point for future genetic analyses for the identification
of candidate genes from H. vulgare genome.
Keywords Carotenoid esters Lutein esters
Hordeum chilense Tritordeum Wild relatives
Introduction
The progressive narrowing of the genetic diversity in
crops (Tanksley and McCouch 1997; Warburton et al.
2006) is a serious threat to agriculture. Modern
Electronic supplementary material The online version of
this article (https://doi.org/10.1007/s10681-019-2369-6) con-
tains supplementary material, which is available to authorized
users.
C. M. Avila
A
´rea Mejora y Biotecnologı
´a, IFAPA-Centro Alameda del
Obispo, Apdo. 3092, 14080 Co
´rdoba, Spain
M. G. Mattera C. Rodrı
´guez-Sua
´rez
C. Palomino M. C. Ramı
´rez A. Martin
S. G. Atienza (&)
Institute for Sustainable Agriculture, CSIC, Avda.
Mene
´ndez Pidal s/n, 14080 Co
´rdoba, Spain
e-mail: sgatienza@ias.csic.es
A. Kilian
Diversity Arrays Technology, University of Canberra,
Bruce, ACT 2617, Australia
M. G. Mattera D. Hornero-Me
´ndez
Departament of Food Phytochemistry, Instituto de la
Grasa (CSIC), Campus Universidad Pablo de Olavide,
Edificio 46. Ctra. de Utrera, Km 1, 41013 Seville, Spain
123
Euphytica (2019) 215:45
https://doi.org/10.1007/s10681-019-2369-6(0123456789().,-volV)(0123456789().,-volV)
varieties present a combination of favourable alleles
adapted to intensive cropping systems but their
potential to evolve in a changing environment has
decreased as the result of reduced genetic diversity
(Charmet 2011). Breeders are reluctant to go back to
wild relatives for new variation (Rasheed et al. 2017)
but wild species constitute an important source of
diversity for breeding (McCouch et al. 2013). Wild
relatives can be crossed with wheat to increase the
diversity available for breeding (King et al. 2017;
Martı
´n et al. 2018; Rodrı
´guez-Sua
´rez et al. 2011). The
utilization of more distantly related species is also
possible, such as the development of translocation
lines of Agropyron cristatum L. Gaertn. (Ochoa et al.
2015)orHordeum chilense Roem. et Schultz. into
common wheat (Mattera et al. 2015a; Mattera and
Cabrera 2017; Rey et al. 2015; Said et al. 2012).
Intergeneric hybridization has allowed the develop-
ment of new crops such as triticale and tritordeum
[9Tritordeum martini A. Pujadas (Pujadas 2016)],
the latter being the amphiploid derived from the hybrid
between H. chilense and durum wheat (Martin and
Sa
´nchez-Monge 1982). This new crop is being com-
mercialized at present by Agrasys S.L. (Vivagram
Ò
)
due to the golden color of its flour and other functional
properties (www.tritordeum.com). The differential
properties of tritordeum are conferred by H. chilense
(Martin et al. 1996). This is particularly important for
the high carotenoid content of tritordeum seeds
(Atienza et al. 2007b) since it confers the golden
colour which is one of the main commercial attributes
of tritordeum derived products.
H. chilense is a native South American diploid wild
barley that is distributed from 29°to 43°Latitude
South in Chile and Argentina. This species shows a
great diversity for agro-morphological and endosperm
storage proteins (Atienza et al. 2000,2002; Vaz Patto
et al. 2001). H. chilense is responsible for both the high
carotenoid content of the seeds of tritordeum (Atienza
et al. 2007b; Rodrı
´guez-Sua
´rez et al. 2014) and for the
distinctive esterification profile of carotenoids (Mat-
tera et al. 2015b; Mellado-Ortega and Hornero-
Me
´ndez 2015). Carotenoid esters increase carotenoid
retention during the storage of grain (Mellado-Ortega
et al. 2015) and flour (Mellado-Ortega and Hornero-
Mendez 2017) so that it is an important trait for
tritordeum breeding. Collectively, our results show
that tritordeums have a larger amount of carotenoids
than durum wheat, a high proportion of carotenoids
esterified with fatty acids and a preference towards
palmitic acid for the synthesis of lutein esters (Mattera
et al. 2015b,2017; Mellado-Ortega and Hornero-
Mendez 2012). However, carotenoid content and
profile remain unexplored in H. chilense despite
previous studies for other traits suggesting that a high
degree of diversity may exist for these traits.
Candidate gene approaches have permitted the
identification and mapping of the main genes produc-
ing the high lutein content in tritordeum (Atienza et al.
2007a; Rodrı
´guez-Sua
´rez and Atienza 2012; Rodrı
´-
guez-Sua
´rez et al. 2014). These advances have been
possible due to the carotenoid pathway being well
known (Cuttriss et al. 2011; Hirschberg 2001). How-
ever, the candidate gene approach is not viable when
the pathways underlying the traits of interest are not
fully understood. In this context, synteny-based can-
didate gene identification would be an interesting
option for H. chilense provided that macro-collinearity
relationships between H. chilense and H. vulgare L.
are established. This approach has been proven to be
useful for identifying collinear regions between
orphan crops or wild relatives and model species as
a first step towards the identification of candidate
genes responsible for traits of interest (Muchero et al.
2009; Webb et al. 2016). The existence of synteny
among species belonging in the Triticeae (Devos
2005) and the recent release of the barley reference
genome assembly and gene predictions (Mascher et al.
2017)(http://pgsb.helmholtz-muenchen.de/plant/
barley/download/index.jsp) provide new opportuni-
ties for genetic studies in H. chilense.
Several collecting missions covering the complete
distribution area of H. chilense (Gime
´nez et al. 1997;
Tobes et al. 1995) allowed the diversity available for
tritordeum breeding to be increased (Martin et al.
1998). Diversity studies in H. chilense have described
the existence of different ecotypes but they do not
agree on the number of groups (Castillo et al. 2010;
Vaz Patto et al. 2001). Indeed, while AFLP and
morphological data suggested the existence of three
ecotypes in H. chilense (Vaz Patto et al. 2001), later
studies using microsatellite markers concluded that H.
chilense diversity was structured in two different
groups (Castillo et al. 2010). Genotyping the diversity
panel in H. chilense with molecular markers covering
the complete genome of the species would allow one
to distinguish between both alternatives. Besides, this
information would be very useful for exploiting
123
45 Page 2 of 16 Euphytica (2019) 215:45
natural variation in this species for carotenoid content
and profile. The goals of the current study were to
investigate: (1) the synteny relationships between H.
chilense and barley using whole-genome coverage
DArTSeq markers; (2) the genetic structure of a
natural collection of H. chilense accessions represen-
tative of its distribution area; (3) the carotenoid
content and profile of this collection; and (4) the
identification of marker-trait associations for carote-
noid content and profile.
Materials and methods
Plant material and field testing
The plant material included a diversity panel and a
mapping population. The diversity panel consisted of
93 accessions of H. chilense from its complete
distribution area. The provenance of these accessions
has been previously reported (Vaz Patto et al. 2001).
The mapping population is a recombinant inbred (RI)
comprising 92 individuals (Rodrı
´guez-Sua
´rez et al.
2012).
Plants were sown in pots with a mixture 1:4.5 (v:v)
(sand:premium pflanzerde substrate). Osmocote Exact
Mini (1.2 g/L) (Everris International B.V.) was added.
Plants were maintained in growth chamber (light
period: 22 °C during 11 h ?16 °C during 1 h; dark
period: 10 °C during 11 h ?16 °C during 1 h) until
samples were taken for DNA isolation. For the field
trials, the diversity panel was initially sown as
described above and then transplanted into outdoors
facilities, following a completely randomized block
design with two replications. Plants were maintained
under anti-bird net structure. Grain samples were
harvested at maturity. Since H. chilense is a wild
barley, its spikes disarticulate at maturity. For this
reason, grains were harvested by hand daily for each
accession as they reached maturity.
DNA isolation and genotyping
Genomic DNA was isolated from bulked leaf tissue of
seedlings following the CTAB protocol with slight
modifications (Murray and Thompson 1980) using
TissueLyser II mill (Qiagen), two stainless-steel balls
(5 mm diameter) for sample disruption and 2 mL
Eppendorf tubes. Genotyping by sequencing analysis
of the diversity panel and the mapping populations
was performed at diversity arrays technology pty ltd
(Canberra, Australia).
Establishment of macro-synteny relationships
between H. chilense and H. vulgare
To inspect macro-synteny relationships between H.
chilense and barley, we compared the relative position
of DArTSeq markers in the genetic map of H. chilense,
with the location of the corresponding sequence in the
barley genome after alignment analyses.
The genetic map was constructed using Joinmap 4.0
(Van Ooijen 2006) and MSTmap (Wu et al. 2008).
Only DArTSeq markers consistently segregating in
the parental lines of the mapping population and with a
call rate of above 90% were used for mapping along
with markers previously mapped (Rodrı
´guez-Sua
´rez
and Atienza 2012; Rodrı
´guez-Sua
´rez et al. 2012).
JoinMap 4.0 mapping software (Van Ooijen 2006) was
used for segregation and linkage analysis. Mendelian
segregation was tested by Chi square goodness-of-fit
to a 1:1 ratio. Markers significantly deviating from
mendelian segregation were excluded. An LOD
threshold of above 9.0 was used to separate the
markers into seven distinct chromosomes. Marker
order within each chromosome was determined with
MSTmap (Linux version) (Wu et al. 2008) with the
following parameters: population type (RIL8); dis-
tance function kosambi; no_map_distance 35.0;
no_map_size 2.0; missing_threshold 10.0; estima-
tion_before_clustering no; detect_bad_data yes;
objective_function COUNT.
H. chilense-derived DArTSeq markers successfully
mapped in the H. chilense map were aligned to barley
genome. A BlastN search (Altschul et al. 1990) was
performed using BLAST ?(Camacho et al. 2009).
DArTSeq sequences were used as a query against the
barley coding sequences (nucleotides) of annotated
high and low confidence genes obtained from (http://
webblast.ipk-gatersleben.de/barley_ibsc/downloads/)
(Mascher et al. 2017).
Relationships between H. chilense and barley were
inspected using CIRCOS (Krzywinski et al. 2009).
Only the best hit to the barley genome was used to
inspect the relationships between H. chilense and
barley homoeologues chromosomes. In addition to
this, Spearman rank correlations were calculated
between the relative order of markers in each
123
Euphytica (2019) 215:45 Page 3 of 16 45
chromosome of the H. chilense map and the corre-
sponding order of the best matches in the barley
genome using Statitistix v 10.0.
Genetic structure of the diversity panel
A model-based clustering, employing a Bayesian
algorithm, was applied to infer the genetic structure
in the diversity panel of H. chilense accessions using
Structure software version 2.3.4 (Pritchard et al.
2000). A set of 474 DArTSeq markers distributed
throughout the seven chromosomes was used. The
program was run assuming a population admixture
model. The number of assumed groups (K) was set to
vary between 1 and 4, and for each value of K twenty
independently MCMC (Markov Chain Monte Carlo)
of 500,000 iterations were run, of which the first
50,000 were discarded as burn-in. The likelihood of
the data for a given number of assumed groups (K) is
provided by the software, and the value of K with the
highest likelihood can be interpreted as an estimation
of the underlying number of groups. A genotype was
considered to belong to a group when its membership
coefficient was C0.5. The membership probabilities
of each genotype to each group inferred were obtained
and used as covariate for the preliminary identification
of marker-trait associations, as described below. In
addition to this, a principal component analysis
(PCoA) was obtained based on genotype data from
the DArTSeq markers using Tassel 5.2.40 (Bradbury
et al. 2007) as an alternative method to inspect the
existence of structure in H. chilense. Markers used for
Genome Wide Association Scan (GWAS) analysis
(described below) were used for PCoA.
Extraction of carotenoids
Carotenoid pigments were extracted from H. chilense
grains (only the diversity panel) using the methods
described by (Mellado-Ortega and Hornero-Me
´ndez
2015). Briefly, the plant material (0.15 g; ca. 50 seeds)
was ground with a ball mill (MM400 Retsch) by
placing the seeds in a 2 mL safe-lock Eppendorf
Ò
tube
together with two stainless-steel balls (5 mm diame-
ter) during 1 min at 25 Hz rate. Carotenoids were
subsequently extracted with 1 mL of acetone (con-
taining 0.1% BHT), centrifuged at 13,500 g for 5 min
at 48C, and the supernatant was directly used for the
chromatographic analysis. Only a one-step solvent
treatment was necessary for the complete extraction of
pigments. All operations were carried out under
dimmed light to prevent isomerization and pho-
todegradation of carotenoids. Analyses were per-
formed in duplicate.
Pigment identification
The identification of carotenoid pigments and their
esters in H. chilense grains has already been presented
by Mellado-Ortega and Hornero-Me
´ndez (2015).
Briefly, the procedure consisted of: (1) separation of
pigment by thin-layer chromatography (TLC) and
cochromatography with purified pigments; (2) obser-
vation of the pigment color on TLC plates under white,
UV254 nm, and UV360 nm wavelength; (3) obtain-
ment of UV–vis spectra in different solvents and
comparison with the values reported in the literature;
(4) and chemical derivatization microscale test for the
examination of 5,6-epoxide, hydroxyl, and carbonyl
groups (Britton 1995; Davies and Ko
¨st 1988; Eugster
1995; Foppen 1971). Carbonyl and hydroxyl groups
were also investigated by Fourier transform infrared
spectroscopy. Zeaxanthin and lutein standards were
obtained in the laboratory by means of TLC from a de-
esterified carotenoid extract from red pepper (Cap-
sicum annuum L.) and mint (Mentha arvensis L.)
respectively (Mı
´nguez-Mosquera et al. 1992;Mı
´n-
guez-Mosquera and Hornero-Me
´ndez 1993). Carote-
noid esters were identified by liquid chromatography-
mass spectrometry (LC–MS (APCI ?)) as described
by (Mellado-Ortega and Hornero-Me
´ndez 2015).
Analysis of carotenoids
Carotenoid analysis was carried out by HPLC accord-
ing to the method of Mellado-Ortega and Hornero-
Me
´ndez (2015). The HPLC system consisted of a
Waters 2695 Alliance chromatograph fitted with a
Waters 2998 photodiode array detector, and controlled
with Empower2 software (Waters Cromatografia,
S.A., Barcelona, Spain). A C18 reversed-phase ana-
lytical column (Mediterranea SEA18, 3 lm,
20 90.46 cm; Teknokroma, Barcelona, Spain) was
used. Pigment separation was achieved by a binary-
gradient elution using an initial composition of 75%
acetone and 25% deionized water, which was
increased linearly to 95% acetone in 10 min, then
raised to 100% in 2 min, and maintained constant for
123
45 Page 4 of 16 Euphytica (2019) 215:45
10 min. Initial conditions were reached in 5 min. An
injection volume of 10 lL and a flow rate of 1 mL/min
were used. Detection was performed at 450 nm, and
the online spectra were acquired in the 350–700 nm
wavelength range. Quantification was done by using
calibration curves (peak area at 450 nm versus the
pigment concentration; range of 0.5–45 lg/mL) pre-
pared with lutein, b-carotene and zeaxanthin standards
isolated and purified from natural sources (Mı
´nguez-
Mosquera and Hornero-Me
´ndez 1993). The concen-
trations of lutein esters and cis-isomers of lutein were
estimated by using the calibration curve for free lutein,
since the esterification of xanthophylls with fatty acids
does not modify the chromophore properties. Analy-
ses were made in duplicate and data were expressed as
lg/g dry weight. Statistical analyses of variance for
total carotenoid content and concentration of each
compound were conducted using Statistix version 10.0
(Analytical Software, Tallahassee, FL, USA). Differ-
ences between genotypes or geographical origin were
established using Tukeys honest significance (HSD)
test at P\0.05. Dunnettes multiple comparison test
was used to identify genotypes with linoleate: palmi-
tate ratio ([Lutein–linoleate ?Lutein–dilinoleate]/
[Lutein–palmitate ?Lutein–dipalmitate]) signifi-
cantly different to 1:1 (hypothetic control).
Identification of marker trait associations (MTA)
for carotenoid content and profile in H. chilense
using GWAS
Marker-trait associations were determined using
TASSEL 5.2.45 (Bradbury et al. 2007). Only SNP
markers successfully mapped were considered for
association tests. Markers with more than 10% miss-
ing data points and markers with a minimum allele
frequency of less than 5% in the diversity panel were
excluded prior to association analyses, which resulted
in a set of 12,638 markers. Association analyses were
performed using the MLM model including the
Q-matrix derived from the Structure analysis
described above and the kinship matrix calculated
with Tassel (MLM ?Q?K). Marker-trait associa-
tions were declared significant at the threshold deter-
mined by the Bonferroni correction.
Results
Macro-synteny relationships between H. chilense
and barley
Both the diversity panel and the mapping population
were genotyped with DArTseq
Ò
platform. An initial
set of 103,429 silico DArT markers and 35,205 SNPs
was generated. Out of these, 22,213 silico DArT and
6,443 SNPs segregated between the parental lines of
the mapping population (H1 and H7 H. chilense
accessions), and were consistently detected in three
replicates of each accession. The marker dataset was
filtered using a 7.5% cutoff of missing data in the
mapping population which resulted in further reducing
the dataset (18,035 silico DArT and 5,381 SNPs). A
total of 16,631 markers were successfully mapped in
the H. chilense map. DArTSeq markers were aligned
to the barley genome using Blastn as implemented in
BLAST ?. A total of 1,425 DArTSeq markers
produced a significant match with barley genes (see
Supplementary file 1) and were used to inspect
synteny relationships.
Macro-synteny relationships between H. chilense
and barley are shown in Fig. 1. To investigate the
Fig. 1 Macro-synteny relationships between H. chilense and
barley. The relative position of DArTSeq markers in the H.
chilense map was compared with the location of the barley
sequence with the best match after alignment analysis in the H.
vulgare genome. Relationships between H. chilense and H.
vulgare were displayed with CIRCOS software
123
Euphytica (2019) 215:45 Page 5 of 16 45
degree of collinearity between both species, Spear-
man’s-rank correlations were calculated between the
relative order of markers in the H. chilense map and
the relative position of the barley sequences in the
barley genome. In general, a good degree of collinear-
ity was found between both species with values of
above 0.8 for all chromosome pairs with the exception
of 7Hch–7Hv, in which no correlation was found
(Table 1). Thus, this chromosome was inspected in
detail. Figure 2shows three differentiated blocks
within chromosome 7Hch. The central block shows
good collinearity with 7Hv. However, the distal parts
of 7HchS (black segment) and 7HchL (pink segments)
show correspondence with 7HvL and 7HvS respec-
tively (Fig. 2). This suggests the existence of a
reciprocal translocation between 7HchS and 7HchL
in H. chilense. To further test this hypothesis, we
generated a hypothetical original chromosome 7Hch
by reverting the hypothetical translocation and re-
calculated Spearman-rank correlations with the posi-
tion of homoeologue genes in barley. This resulted in a
correlation of 0.86 between 7Hch and 7Hv (Table 1),
which suggests that there is a good degree of
collinearity within the three blocks described above
and barley.
Analysis of population structure
The underlying population structure was firstly studied
with the Bayesian approach implemented in the
structure software (Pritchard et al. 2000). Evidence
of two subpopulations was provided by this analysis
since the DK value occurred at K = 2. Accessions H1
and H7 were considered as being representatives of
each of these groups since they had a membership
coefficient of 1.0 to each group. Each genotype was
assigned to either groupH1 or groupH7 based on
membership probability [0.5 (Fig. 3). GroupH7
includes 50 accessions, while group H1 consists of
the remaining 43 accessions. Most of the latter were
assigned to each subpopulation with a membership
probability coefficient of above 0.9. However, acces-
sions H31, H46 and H221 showed an intermediate
behaviour (with membership estimates around 0.5)
and 9 accessions assigned to groupH7 had member-
ship probabilities of below 0.9 (Fig. 3).
PCoA analysis was carried out as an alternative way
of inspecting the existence of a population structure
(Fig. 3). The first two principal coordinates explained
50.12% of total variation, PC1 being more important
(44.67% of total variation) than PC2 (5.60% of total
variation). Accessions in the PCoA graph were
depicted in red or blue according to their assignment
to groupH7 or groupH1 in the structure analysis,
respectively. The three accessions with membership
coefficients of around 0.5 (H31, H46 and H221) were
clearly separated from the rest in the PCoA graph
(Fig. 3). Similarly, the accessions represented as
triangles in the PCoA graph belong to groupH7 but
with membership coefficients of below 0.9.
The passport data of the accessions collected during
several expeditions to Chile were used to compare the
relationship between geographical distribution and the
population structure analysis (Fig. 4). GroupH7 cov-
ered a larger distribution than groupH1. Accessions in
groupH1 were mostly located in the central part of the
distribution area while accessions grouped with H7
were mainly found above and below the distribution
area of groupH1.
Variation for carotenoid content and profile in H.
chilense
The carotenoid composition, including carotenoid
esters, was analysed in all the accessions of the
diversity panel. Figure 5shows the chromatograms
corresponding to seeds of H1, H7 and H290. Both H1
and H7 are considered as representatives of the two
biotypes found after structure analysis. Both acces-
sions showed a similar profile with free lutein as the
Table 1 Spearman’s Rank correlation coefficients between H. chilense and H. vulgare
Chr.pair 1Hch–1Hv 2Hch–2Hv 3Hch–3Hv 4Hch–4Hv 5Hch–5Hv 6Hch–6Hv 7Hch–7Hv 7HchR
a
–7Hv
r 0.821
*
0.943
*
0.932
*
0.933
*
0.942
*
0.892
*
0.260 0.860
*Significant correlation at p\0.05
a
7HchR refers to a hypothetical original chromosome 7Hch by reverting the reciprocal translocation shown in Fig. 2
123
45 Page 6 of 16 Euphytica (2019) 215:45
main carotenoid and the presence of lutein monoesters
and diesters. The basic statistical parameters of the
quantitative carotenoid traits are shown in Table 2.
Total carotenoid content ranged between 5.07 and
43.68 lg/g. Lutein diesters were not detected in five
accessions (H55, H211, H290, H293 and H310). In
addition, the accession H290 was also characterized
by the absence of lutein monoesters.
GroupH1 and groupH7 were compared for carote-
noid profile. GroupH7 was characterized by higher
contents of total carotenoids, free lutein and esterified
lutein (Fig. 6). However, these groups did not differ
for the relative contribution of free and esterified lutein
relative to the total amount of lutein (Fig. 6).
Previous studies in tritordeum have shown a
skewed production of lutein esters towards palmitate
which suggested that H. chilense preferentially formed
lutein esters containing palmitic acid. Thus, the ratio
linoleate:palmitate ([Lutein–linoleate ?Lutein–dili-
noleate]/[Lutein–palmitate ?Lutein–dipalmitate]) was
calculated to investigate whether this assumption was
correct or it was genotype-dependent. Accession H35
exhibited a balanced synthesis of lutein esters with either
palmitic or linoleic acids. Out of 92 accessions producing
lutein esters, 43 did not differ from H35, which indicates
a lack of preference for the fatty acid involved in
esterification. On the contrary, 46 lines showed a
preference towards palmitic acid and only three acces-
sions, H210, H217 and H218, favoured linoleic acid for
carotenoid esterification (Fig. 7).
Association analysis for carotenoid profile
Genome-wide association analysis was performed for
lutein profile (free lutein, lutein palmitate, lutein
linoleate, lutein dilinoleate, lutein dipalmitate and
lutein linoleate–palmitate). A total of 12,638 DArT-
Seq markers mapped in the H. chilense map were
retained for the GWAS analysis after removing SNPs
with a minor allele frequency lower than 0.05 and
SNPs with more than 10% of missing data. Marker-
trait associations were determined by MLM taking
into account the population structure matrix (Q matrix
obtained from the structure analysis) and the kinship
matrix (K matrix calculated with TASSEL). No
significant MTA associations were found for lutein
palmitate and lutein dilinoleate. Manhattan plots for
the remaining traits are shown in Fig. 8. A total of 91
significant MTA were detected (see Supplementary
file 2). Most MTA were detected for free lutein (79
MTA) while the number of significant MTA was much
lower for lutein monolinoleate (1 MTA), lutein
dipalmitate (8 MTA) and lutein linoleate–palmitate
(3 MTA).
Fig. 2 Structural rearrangements in chromosome 7Hch of H.
chilense compared to barley 7Hv. aLinks between 7HchS and
7HvL (depicted in black) and 7HchL and 7HvS (depicted in
pink) suggest the existence of a reciprocal translocation between
7HchS and 7HchL. bHypothetical original 7Hch chromosome
constructed by interchanging the position of 7HchS and 7HchL
segments. (Color figure online)
123
Euphytica (2019) 215:45 Page 7 of 16 45
Regarding free lutein, significant MTA were
detected in all chromosomes but 7Hch. The highest
number of MTAs were located on chromosomes 1Hch
and 6Hch.Out of 12 MTA for lutein esterification
traits, two markers on 3Hch (14439596 and 14448303)
H31
H46
H221
-
PC2 (5.60% of total variation)
PC1 (44.67% of total variation)
0
0.5
1
H221
H46
H31
A
B
GroupH7. Coefficient > 0.9
GroupH7. Coefficient < 0.9
GroupH1. Coefficient > 0.9
GroupH1. Coefficient < 0.9
Group H7 Group H1
Correspondence with
Structure analysis
40
Fig. 3 Analysis of population structure in H. chilense. aMembership of H. chilense accessions to groupH1 (blue) and groupH7 (red)
after Structure analysis. bPrincipal component analysis (PCoA). (Color figure online)
c
Fig. 4 Distribution of H. chilense accessions grouped in
groupH1 (left) and grouphH7 (right) after analysis of population
structure. Accessions were placed on map of Chile using
MapTool by Darrin Ward (https://www.darrinward.com/lat-
long/)
123
45 Page 8 of 16 Euphytica (2019) 215:45
Group H7
Group H1
123
Euphytica (2019) 215:45 Page 9 of 16 45
were significantly associated with the variations in
lutein linoleate and lutein linoleate–palmitate (Sup-
plementary file 2).
Discussion
Synteny between H. chilense and H. vulgare
Comparative studies have allowed the establishment
of the relationships between the genomes of related
species such as grasses (Devos 2005; Moore et al.
1995) or legumes (Choi et al. 2004). Our results
indicate that H. chilense shows a good degree of
macro-collinearity with barley with the exception of
chromosome 7Hch, in which a significant reorganiza-
tion was detected. This reorganization was previously
hypothesized since the gene Phytoene synthase 1
(Psy1) was located in the short arm of chromosome
7Hch (Atienza et al. 2007a; Mattera et al. 2015b),
while the homoeologues genes in wheat are located in
the long arm of 7A, 7B and 7D (Pozniak et al. 2007;
Rodrı
´guez-Sua
´rez et al. 2010). However, our previous
studies have been conducted using H. chilense-wheat
genetic stocks, including chromosome addition,
translocation or substitution lines (Atienza et al.
2007a; Mattera et al. 2015b). Consequently, we were
not able to prove that the reorganization of 7Hch was
already present in the H. chilense genome since it
might have occurred during the development of the
different genetic stocks. Our current results confirm
that the translocation in 7Hch is present in the Hch
genome and it is not the result of an interaction with
the wheat genome.
The good degree of macro-synteny between H.
chilense and barley will allow the exploitation of the
genome resources available in barley (Mascher et al.
2017; Mayer et al. 2011; The_International_Bar-
ley_Genome_Sequencing_Consortium 2012). Specif-
ically, it will enable the identification of candidate
genes for traits of interest in barley. Similar strategies
are being applied in other crops such as white lupin
with the aim of synteny-based gene cloning
(Ksia˛ _
zkiewicz et al. 2017) or faba bean for the
identification of candidate genes for stomatal traits
(Khazaei et al. 2014).
H. chilense population structure and carotenoid
profile diversity
H. chilense has a wide variation in morphological
traits (Bothmer et al. 1980; Vaz Patto et al. 2001). H.
H290
H7
H1
1
2
3
45
678
Retention time (min)
0 5 10 15 20 25
Absorbance (450 nm)
Fig. 5 HPLC chromatograms obtained for H. chilense acces-
sions H1, H7 and H290. Peak identities: 1, (all-E)-Zeaxanthin;
2, (all-E)-Lutein; 3, (9Z)-Lutein and (13Z)-Lutein; 4, Lutein
linoleate; 5, Lutein palmitate; 6, Lutein dilinoleate; 7, Lutein
linoleate–palmitate; 8, Lutein dipalmitate
Table 2 Basic statistics for carotenoid in the diversity col-
lection (ug g
-1
dry weight)
Trait Min Max SD Mean
all-trans-zeaxanthin 0.52 4.59 0.67 1.44
all-trans-b-carotene 0.00 0.63 0.07 0.05
Free lutein 1.83 36.73 6.18 8.68
Lutein linoleate 0.00 4.48 0.92 1.62
Lutein palmitate 0.00 5.83 1.33 2.10
Lutein monoesters 0.00 9.59 2.18 3.71
Lutein dilinoleate 0.00 2.87 0.45 0.41
Lutein linoleate–palmitate 0.00 4.71 1.00 1.05
Lutein dipalmitate 0.00 3.63 0.74 0.76
Lutein diesters 0.00 9.57 2.13 2.23
Esterified lutein 0.00 16.96 3.91 5.94
Total lutein 4.37 39.02 7.61 14.62
Total carotenoid 5.07 43.68 8.01 16.11
Lutein monoesters = Lutein linoleate ?Lutein palmitate;
Lutein diesters = Lutein dilinoleate ?Lutein linoleate–
palmitate ?lutein dipalmitate; Esterified lutein = Lutein
monoesters ?Lutein diesters; Total lutein = Free
lutein ?Esterified lutein; Total carotenoids = all-trans-
zeaxanthin ?all-trans-b-carotene ?total lutein
123
45 Page 10 of 16 Euphytica (2019) 215:45
chilense was considered as being a polymorphic taxon
with a wide diversity in morphological characters
(Bothmer et al. 1980). Later works studied the
existence of population structure in H. chilense using
morphological and AFLP markers (Vaz Patto et al.
2001), or microsatellite markers (Castillo et al. 2010)
with slightly different results (two or three groups).
Our current results show the existence of two clearly
differentiated groups represented by accessions H1
and H7 in agreement with previous findings (Castillo
et al. 2010). On the contrary, three ecotypes (I, II and
III) were described in another work (Vaz Patto et al.
2001). Groups I and III correspond to groupH1 and
groupH7, respectively. However, the accessions
included in group II did not constitute a separate
group in our analysis. On the contrary, these genotypes
were distributed between group H1 (five accessions)
and group H7 (9 accessions) (Supplementary file 3).
The existence of three groups in H. chilense has been
hypothesized using a set of fourteen repetitive probes
and FISH analyses (Rey et al. 2018). However, that
work does not provide enough evidence to confirm the
existence of groups since only three accessions were
studied. Indeed, the authors acknowledged that more
individuals from each group should be analyzed to
confirm the existence of different hybridization pat-
terns in each group.
Compared to tritordeum, H. chilense shows a
higher degree of diversity for carotenoid content and
profile which is essential for genetic studies. Indeed,
the accessions analyzed in this work showed a
coefficient of variation of 49.1% while it was 26.7%
in tritordeum (Atienza et al. 2007b). Diversity is also
higher than that found in common, durum or einkorn
wheat (Ziegler et al. 2015). Regarding the carotenoid
profile, five accessions did not produce lutein diesters
in contrast with all previous reports in tritordeum.
Furthermore, accession H290 was also characterized
by the absence of lutein monoesters. The existence of
accessions with the ability to produce monoesters but
9.81 B
21.52 A
0.00
8.00
16.00
24.00
group H1 group H7
µg/g
A
4.69 B
12.11 A
0.00
5.00
10.00
group H1 group H7
µg/g
B
3.78 B
7.80 A
0.00
3.00
6.00
9.00
group H1 group H7
µg/g
C
25.59 A 25.62 A
0.00
10.00
20.00
30.00
group H1 group H7
E
18.06 A
14.55 A
0.00
5.00
10.00
15.00
20.00
25.00
group H1 group H7
D
56.36 A 59.83 A
0.00
20.00
40.00
60.00
group H1 group H7
F
Fig. 6 Comparative analysis of H. chilense groups for
carotenoid profile: total carotenoid content (a), free lutein (b),
esterified lutein (lutein monopalmitate ?lutein monolinoleate)
(c); ratio lutein diesters (lutein dilinoleate ?lutein dipalmi-
tate ?lutein linoleate–palmitate)/total lutein (free
lutein ?esterified lutein) (d); ratio lutein monoester (lutein
linoleate ?lutein palmitate)/total lutein (e); ratio free lutein/to-
tal lutein (f). Graphs a, b and c are shown as lg/g dry weight.
Bars with the same letter are not significantly different at
P= 0.05, determined by Tukey’s HSD test
123
Euphytica (2019) 215:45 Page 11 of 16 45
no diesters suggests the implication of more than one
enzyme for lutein esterification in H. chilense. How-
ever, the limited number of accessions without lutein
esters is a handicap for the identification of the genetic
basis using GWAS, and the development of alternative
strategies could be considered in future works.
Previous results showed palmitic acid selectivity in
the synthesis of lutein esters in tritordeum (Mattera
et al. 2015b,2017; Mellado-Ortega and Hornero-
Mendez 2012) which suggested a preference towards
palmitic acid for lutein esterification in H. chilense.
The existence of substrate specificity is not related to
the availability of fatty acids in tritordeum (Mellado-
Ortega and Hornero-Me
´ndez 2018). Indeed, linoleic
acid content was 2 fold higher in the endosperm
compared to palmitic acid (Mellado-Ortega and
Hornero-Me
´ndez 2018), but tritordeum synthesized a
larger amount of lutein esters with palmitic ones,
although this preference towards palmitic acid for
lutein esterification is not observed in H. chilense.
Although most accessions favored the synthesis of
lutein esters with palmitic acid (46 accessions), forty-
three accessions showed a balanced contribution of
palmitic and linoleic acid to the production of esters
and three accessions favored the utilization of linoleic
acid. This suggests the existence of diversity in the
xanthophyll acyl transferases involved in the esterifi-
cation in H. chilense, which could be used to modify
the esterification profile in tritordeum.
Significant differences were detected between
groupH1 and groupH7 for the carotenoid profile.
Indeed groupH7 doubled the production of total
carotenoids, free lutein and esterified lutein compared
to groupH1 (Fig. 6). However, the relative contribu-
tion of free and esterified lutein to the total pool of
lutein was not significantly different between both
groups. This means that the relative proportion of
lutein esters is not determined by the total amount of
lutein as happened in wheat-H. chilense chromosome
substitution lines (Mattera et al. 2015b).
As explained above, groupH1 and groupH7 corre-
spond to groups I and III that were determined by
using AFLP markers and morphological traits (Vaz
Patto et al. 2001). Thus, it is possible to compare
groupH7 and groupH1 for morphological traits.
GroupH7 is characterized by broader, shorter spikes,
a greater density of stomata in the abaxial leaf size and
a high level of avoidance of rust fungi (Vaz Patto et al.
2001). However, these morphological traits do not
seem to be directly related to the carotenoid content in
seeds. In contrast, other traits such as seed color,
anthesis date or maturity date which could be associ-
ated with variations in the carotenoid profile did not
show differences between either group.
The passport data of the accessions obtained from
the collection missions in Chile were also considered.
The two groups found in H. chilense differed in their
geographic location (Fig. 4). The majority of acces-
sions of groupH1 were collected at around 34°latitude
South while accessions from H7 were obtained at
around 30°latitude south. According to the new
Koppen classification (Peel et al. 2007) the area
around 30°corresponds to a temperate environment
with hot summers (temperature of the hottest month
above 22 °C) while those included in groupH1 were
collected from a temperate environment with warm
summers (temperature of the hottest month below
22 °C and 4 months in which the temperature is above
10 °C). Besides, these areas are also different in terms
Fig. 7 Relative production of lutein esters with linoleic or
palmitic acids in the diversity panel. The relative production of
lutein esters with linoleic or palmitic acids was investigated by
calculating the ratio (lutein monolinoleate ?lutein dilinoleate)/
(lutein monopalmitate ?lutein dipalmitate) * 100. All samples
were compared with a control, H35, which produced the same
quantity of lutein esters with each fatty acid. Forty-six
accessions favored the synthesis of lutein esters with palmitic
acid (they are shown below the lower horizontal line) while
three accessions (appearing above the upper horizontal line)
produced a higher proportion of lutein esters with linoleic acid.
The remaining forty-three produced similar amounts of lutein
esters with each fatty acid at P= 0.05, determined by two-sided
Dunnett’s multiple comparisons with H35 as control
123
45 Page 12 of 16 Euphytica (2019) 215:45
of productivity according to (van Leeuwen et al.
2013). Seed carotenoids are important antioxidants
that contribute to the antioxidant system and reduce
seed ageing (Howitt and Pogson 2006). Thus, seed
carotenoids contribute to successful germination
(Howitt and Pogson 2006). The diversification for
carotenoid content between groupH1 and groupH7
suggests differences in the antioxidant system in seeds
between these groups which might be important
during germination.
Marker-trait associations
Significant MTAs were identified in all chromosomes
but 7Hch for free lutein content. In H. chilense, genes
related to either carotenoid synthesis or carotenoid
degradation, have been mapped on all chromosomes
with the exception of 1Hch (Rodrı
´guez-Sua
´rez and
Atienza 2012,2014; Rodrı
´guez-Sua
´rez et al. 2012).
Significant MTAs have been detected on all of the
chromosomes of durum wheat by association and
linkage mapping [reviewed by (Ficco et al. 2014)].
Thus, it is not surprising that the same may happen in
H. chilense.
Two markers were associated with more than one
esterification-related trait but not with free lutein
content. Thus, they could be important for explaining
differences in carotenoid esterification. None of these
sequences showed a significant similarity with barley
genes, or with other grasses (data not shown). The
MTAs reported in this work have not been validated
and thus we consider these results to be preliminary
ones.
Conclusions
H. chilense shows a good degree of macrocollinearity
with barley in all chromosomes but 7Hch where a
reciprocal translocation was identified. Esterification
is controlled by more than one enzyme as deduced by
the ability of some accessions to produce monoesters
but no diesters. Besides, there is diversity in the
xanthophyll acyl transferases involved in esterifica-
tion. Indeed, some accessions favoured the synthesis
of lutein esters with palmitic acid, as happens in
tritordeum, but other accessions did not show this
preference. The existence of marked differences for
Fig. 8 Manhattan plots from MLM model for free lutein (a), lutein monolinoleate (b), lutein dipalmitate (c) and lutein linoleate–
palmitate. For each trait, the LOD threshold determined using the Bonferroni correction at P= 0.05 (LOD of 5.4)
123
Euphytica (2019) 215:45 Page 13 of 16 45
carotenoid content may imply differences in the
antioxidant system between the subgroups of H.chi-
lense. The marker trait associations constitute a good
starting point for the identification of candidate genes
from H. vulgare genome for further genetic studies.
Acknowledgements Research funded by Grant AGL2014-
53195R, from Ministerio de Economı
´a y Competitividad, Spain
(MINECO) including FEDER funding. M.G.M. was recipient of
FPI (BES-2012-055961). D.H.-M. is a member of CaRed
Network, funded by MINECO (BIO2015-71703-REDT).
S.G.A. and CMA are members of FiRCMe Network, funded
by MINECO (AGL2016-81855-REDT).
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