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Transcriptional Responses of Chilean Quinoa (Chenopodium quinoa Willd.) Under Water Deficit Conditions Uncovers ABA-Independent Expression Patterns

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HIGHLIGHTSR49 genotype displayed best performance on selected physiological parameters and highest tolerance to drought. R49 drought over-represented transcripts has exhibited 19% of genes (306 contigs) that presented no homology to published databases. Expression pattern for canonical responses to drought such as ABA biosynthesis and other genes induced in response to drought were assessed by qPCR. Global freshwater shortage is one of the biggest challenges of our time, often associated to misuse, increased consumption demands and the effects of climate change, paralleled with the desertification of vast areas. Chenopodium quinoa (Willd.) represents a very promising species, due to both nutritional content and cultivation under water constraint. We characterized drought tolerance of three Chilean genotypes and selected Genotype R49 (Salares ecotype) based upon Relative Water Content (RWC), Electrolyte Leakage (EL) and maximum efficiency of photosystem II (Fv/Fm) after drought treatment, when compared to another two genotypes. Exploratory RNA-Seq of R49 was generated by Illumina paired-ends method comparing drought and control irrigation conditions. We obtained 104.8 million reads, with 54 million reads for control condition and 51 million reads for drought condition. Reads were assembled in 150,952 contigs, were 31,523 contigs have a reading frame of at least 300 nucleotides (100 aminoacids). BLAST2GO annotation showed a 15% of genes without homology to NCBI proteins, but increased to 19% (306 contigs) when focused into drought-induced genes. Expression pattern for canonical drought responses such as ABA biosynthesis and other genes induced were assessed by qPCR, suggesting novelty of R49 drought responses.
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ORIGINAL RESEARCH
published: 08 March 2017
doi: 10.3389/fpls.2017.00216
Frontiers in Plant Science | www.frontiersin.org 1March 2017 | Volume 8 | Article 216
Edited by:
Jose I. Hormaza,
IHSM La Mayora - CSIC, Spain
Reviewed by:
Aureliano Bombarely,
Virginia Tech, USA
Didier Bazile,
Agricultural Research Centre for
International Development, France
*Correspondence:
Andres Zurita-Silva
andres.zurita@inia.cl
Herman Silva
hesilva@uchile.cl
Present Address:
Andrea Morales,
Escuela de Tecnología Médica,
Facultad de Salud, Sede La Serena,
Universidad Santo Tomas,
Santiago, Chile
Specialty section:
This article was submitted to
Crop Science and Horticulture,
a section of the journal
Frontiers in Plant Science
Received: 29 September 2016
Accepted: 06 February 2017
Published: 08 March 2017
Citation:
Morales A, Zurita-Silva A,
Maldonado J and Silva H (2017)
Transcriptional Responses of Chilean
Quinoa (Chenopodium quinoa Willd.)
Under Water Deficit Conditions
Uncovers ABA-Independent
Expression Patterns.
Front. Plant Sci. 8:216.
doi: 10.3389/fpls.2017.00216
Transcriptional Responses of Chilean
Quinoa (Chenopodium quinoa Willd.)
Under Water Deficit Conditions
Uncovers ABA-Independent
Expression Patterns
Andrea Morales 1 †, Andres Zurita-Silva 2*, Jonathan Maldonado 3and Herman Silva 3*
1Centro de Estudios Avanzados en Zonas Áridas, Universidad de La Serena, La Serena, Chile, 2Instituto de Investigaciones
Agropecuarias, Centro de Investigación Intihuasi, La Serena, Chile, 3Laboratorio de Genómica Funcional & Bioinformática,
Departamento de Producción Agrícola, Facultad de Ciencias Agronómicas, Universidad de Chile, Santiago, Chile
HIGHLIGHTS
R49 genotype displayed best performance on selected physiological parameters and
highest tolerance to drought.
R49 drought over-represented transcripts has exhibited 19% of genes (306 contigs)
that presented no homology to published databases.
Expression pattern for canonical responses to drought such as ABA biosynthesis and
other genes induced in response to drought were assessed by qPCR.
Global freshwater shortage is one of the biggest challenges of our time, often associated
to misuse, increased consumption demands and the effects of climate change, paralleled
with the desertification of vast areas. Chenopodium quinoa (Willd.) represents a very
promising species, due to both nutritional content and cultivation under water constraint.
We characterized drought tolerance of three Chilean genotypes and selected Genotype
R49 (Salares ecotype) based upon Relative Water Content (RWC), Electrolyte Leakage
(EL) and maximum efficiency of photosystem II (Fv/Fm) after drought treatment, when
compared to another two genotypes. Exploratory RNA-Seq of R49 was generated by
Illumina paired-ends method comparing drought and control irrigation conditions. We
obtained 104.8 million reads, with 54 million reads for control condition and 51 million
reads for drought condition. Reads were assembled in 150,952 contigs, were 31,523
contigs have a reading frame of at least 300 nucleotides (100 aminoacids). BLAST2GO
annotation showed a 15% of genes without homology to NCBI proteins, but increased
to 19% (306 contigs) when focused into drought-induced genes. Expression pattern for
canonical drought responses such as ABA biosynthesis and other genes induced were
assessed by qPCR, suggesting novelty of R49 drought responses.
Keywords: drought tolerance, Andean grain, Salares and coastal/lowlands genotypes, RNA-Seq , qPCR
Abbreviations: RWC, Relative Water Content; EL, Electrolyte Leakage; qPCR, Quantitative Real-Time PCR; ABA, Abscisic
acid; BP, Biological process; FC, Fold-change; GO, Gene ontology.
Morales et al. Drought Transcriptional Responses in Chilean Quinoa
INTRODUCTION
Plants are sessile organisms that need to respond to a wide
array of abiotic and biotic stresses. This condition confers
strong selective pressures on their local adaptation to different
environments. The selective pressure at the abiotic level
implies stress responses, that includes numerous and complex
environmental conditions, such as light intensity, temperature,
salinity and drought. Therefore, understanding abiotic stress
responses at the physiological and genomic level is a relevant
issue to provide an essential foundation for future breeding and
genetic engineering efforts. Indeed, roughly 75% of the world’s
freshwater supplies are utilized in agriculture, and the increasing
climatic variability and the demographic pressures have led to
ecosystem degradation and have exacerbated the vulnerability
to drought and other abiotic stress factors (Food Agriculture
Organization of the United Nations, 2011). Consequently,
increasing crop productivity under conditions of limiting water
availability is of major importance (Avramova et al., 2015).
Research on drought responses in Arabidopsis, maize, tomato
and rice among others plants, have determined that a large
number of genes as well as signal transduction pathways are
involved in drought responses (Shinozaki et al., 2003; Shinozaki
and Yamaguchi-Shinozaki, 2007). The identification of genes
regulated by drought conditions has a high significance, because
it provides a comprehensive understanding of the transcriptional
responses and the identification of stress responsive promoters
and cis-elements.
Quinoa (Chenopodium quinoa Willd.) is an Andean native
crop that belongs to the Amaranthaceae family. It is an
allotetraploid plant (2n=4× = 36) with a genome size estimated
of 967 Mbp (Mujica and Jacobsen, 2006; Stevens et al., 2006)
and sequenced very recently with a total assembly size of
1.39 gigabases (Gb) (Jarvis et al., 2017), which shows disomic
inheritance for most qualitative traits (Simmons, 1971; Risi and
Galwey, 1984; Ward, 2000; Maughan et al., 2004). Quinoa was
domesticated and has been cultivated in the Andes for the
last 7,000 years before present (BP). It’s diversity is comprised
by five major ecotypes related to different sub-center origins
that include: Highlands (Peru and Bolivia), Inter-Andean valleys
(Bolivia, Colombia, Ecuador and Peru), Salares (Bolivia, Chile
and Argentina), Yungas (Bolivia) and Lowlands (Chile) (Risi and
Galwey, 1989a,b; Bertero et al., 2004; Zurita-Silva et al., 2014;
Bazile et al., 2015). Among nutritional characteristics it is know
that quinoa’s seeds have an exceptional balance between oil (4–
9%), protein (averaging 16%, with high nutritional relevance
due to optimal balance of essential amino acid content) and
carbohydrates (64%) (Bhargava et al., 2006; Vega-Gálvez et al.,
2010). Moreover, its high starch content (51–61%) enabling flour
production (Mastebroek et al., 2000; Repo-Carrasco et al., 2003;
Stikic et al., 2012) but with the advantages of gluten absence,
which has allowed the development of foods for consumers
with celiac disease (i.e., people allergic to gluten) (Jacobsen,
2003). Additionally, quinoa is a good source of vitamins, oil
with high linoleate and linolenate content (55–66% of the lipid
fraction), natural antioxidants such as α- and γ-tocopherol, and
a wide range of minerals (Repo-Carrasco et al., 2003; Vega-
Gálvez et al., 2010; Fuentes and Bhargava, 2011; Stikic et al.,
2012; Ruiz et al., 2014). Interestingly, quinoa consumption
may lead to comparatively lower weight gain, and improved
lipid profile and potential antioxidant effects, physiological
outcomes that have been linked to bioactive compounds, such
as saponins, quinoa proteins, polyphenolic compounds and 20-
hydroxyecdysone by yet unknown mechanisms (Simnadis et al.,
2015). Considering the attributes and potential to contribute
to food security worldwide, the draft genome sequence of an
inbred line has been recently published, comprising a free-access
Quinoa Genome DataBase (QGDB), which will provide insights
into the mechanisms underlying agronomically important traits
of quinoa (Yasui et al., 2016).
Quinoa is an interesting abiotic stress tolerant crop that should
be adopted as a model because has a good tolerance to high
salinity, boron, light intensity and drought (Orsini et al., 2011;
Ruiz-Carrasco et al., 2011; Zurita-Silva et al., 2014; Razzaghi
et al., 2015; Ruiz et al., 2016). In particular quinoa has a good
tolerance to water shortage that is due to its intrinsic lower
water requirement, the capability to regain its original level of
photosynthesis after a drought period, and both slow growth and
smaller leaf area during acclimation (Galwey, 1989; Jensen et al.,
2000; Jacobsen et al., 2003, 2009; Sun et al., 2014). There are
others factors than can be considered for this tolerance i.e., high
instantaneous photosynthetic efficiency in drought conditions
(Winkel et al., 2002; Bosque Sanchez et al., 2003); leaf shedding
(Jensen et al., 2000); its higher root branching and foraging
capacity of root system (Alvarez-Flores et al., 2014), and the
presence of leaf vesicles containing calcium oxalate, which could
reduce transpiration (Jensen et al., 2000; Siener et al., 2006).
It’s noteworthy that this tolerance to water deficit has allowed
reaching harvests with only 75 mm of rainfall (Martínez et al.,
2009). In this work we characterized three Chilean genotypes
(Martínez et al., 2015), one corresponding to Salares and two
from Lowlands native ecotypes, which frequently experience
water deficit during growth season, in terms of drought tolerance.
Later, for the most tolerant genotype, a RNA-seq analysis of the
transcriptome was performed to explore candidate transcripts
under contrasting water conditions i.e., deficit and normal
irrigation. A deep bioinformatics analysis is presented that
assessed a putative signal transduction pathway involved in
quinoa responses to drought. To validate the assembly of the
contigs, primer pairs were designed to amplify the sequences
of 15 selected transcripts, related to drought response and ABA
biosynthesis and to study the expression level of target genes
through Real Time -quantitative PCR (RT-qPCR).
MATERIALS AND METHODS
Plant Material
Three Chilean genotypes of Chenopodium quinoa Willd. were
used in this study: R49, from Colchane, Tarapacá Region, 3,850 m
altitude (Salares ecotype); PRJ, from Cahuil, O’Higgins Region,
39 m altitude and BO78 from Collipulli, Araucanía Region, 243 m
altitude (the last two coastal/lowland ecotypes; Table 1). The
seeds were kindly provided by the National Seed Bank of Chile
managed by Instituto de Investigaciones Agropecuarias INIA
Intihuasi (Vicuña, Chile).
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Morales et al. Drought Transcriptional Responses in Chilean Quinoa
TABLE 1 | Chilean genotypes studied: ecotype and geographical origin.
Genotype Ecotype Provenance Latitude/
Longitude
Altitude
(m.a.s.l.)
Rainfall
(a.a. mm)
R49 Salares Colchane
county
1925; 68353,850 187
PRJ Coastal /
lowlands
Cahuil 3429; 720039 641
BO78 Coastal /
lowlands
Collipulli 3757; 7226243 1,324
m.a.s.l., meters above sea level; a.a., annual average millimeters.
Plant Growth and Stress Conditions
Experiment consisted of 12 pots each containing two plants
for each genotype that were grown in 1L pots with a soil-sand
mixture (1:1) with irrigation every 2 days and temperatures that
fluctuated between 12 and 32C during 4 weeks at greenhouse
conditions. To select the genotypes tolerant to drought, at the
fourth week since germination half of the plants from each
genotype were maintained as control in the same irrigation
regimen, and the other half were deprived of water, and
distributed in six blocks that were set up according to a
randomized block design. The experiments were performed in La
Serena, Coquimbo Region, Chile (2954; 7115) during summer
(January).
To determinate the most drought tolerant genotype, we
analyzed the following physiological parameters: (1) Relative
Water Content (RWC) as described previously by Barrs and
Weatherley (1962), (2) Electrolyte Leakage (EL) as described
by Pinhero et al. (1997), and Fv/Fmdetermination (Woo
et al., 2008). The experiment was done using 1-month-old
plants under a water shortage condition (dry season). The
starting of the experiment was ceasing the plants irrigation and
the measurement of the physiological parameters previously
mentioned. For Fv/Fmdetermination, three different leaves by
treatment were measured from dark-adapted plants during 30
min, and then were subjected to an initial saturating pulse of 900
µmol photons m2s1, followed by a 40′′ delay in darkness and
subsequently 10’ of actinic illumination with saturating flashes at
20′′ intervals, using a foliar chamber 6400-40 coupled to LI-6400
fluorometer (LICOR), and were calculated following reported
methods (Woo et al., 2008).
For the transcriptome approach, a second experiment was
performed using the most drought tolerant genotype. The
growth conditions were similar to the previous experiment
and plant tissues were collected at the following stages: (a)
Stage 1 (D1), where relative water content (RWC) was near
80% (similar to control) and soil potential was significant
different between control and drought (0.6 MPa and 1.3
MPa, respectively); (b) Stage 2 (D2), where leaf RWC was
near 50–60% and the soil potential was 1.3 MPa; and (c)
Stage 3 (D3), where leaf RWC was near 30% and soil potential
was 2.7 MPa. For the control samples, the same stages were
used (C1, C2, C3), in which the analyzed parameters were
similar to stage 1 control (80% RWC and 0.6 MPa soil
potential) (Table S1). The collected tissues (whole plants) were
frozen in liquid nitrogen and then placed at 80C until
further use.
RNA Extraction
Total RNA was obtained from plant tissues using the Trizol
reagent (Invitrogen Corp., Carlsbad, CA, USA) following the
manufacturer’s protocol. We extracted the RNA individually
from three different plants for each stage (D1, D2, and D3; C1,
C2, and C3), and tissues were separated between root and shoot.
After quality analysis (Meisel et al., 2005) we composed two
different pools (drought and control) using the same quantity
from each plant tissue (root and shoot, 1.6 µg each) and sent
to Macrogen (http://www.macrogen.com) for Illumina 100 bp
paired-ends sequencing procedure.
Library Construction, Deep Sequencing
and De novo Transcriptome Assembly
Library construction and deep sequencing for each sample
were performed at Macrogen (Inc. Seoul, South Korea) using
Solexa HiSeq2000 platform with the previous construction of
a Truseq mRNA library for paired end application according
to Macrogen’s protocol with an insertion length of 550 bp.
The sequence reads were quality trimmed and assembled using
the CLC Genome Workbench version 4.8 (CLC Bio: CLC
genomics workbench [http://www.clcbio.com]). Trimming was
done following parameters: Q 20; no more than 2 ambiguities;
final read length 50 bp. Reads assembly was done from a
pooling of all the paired end short-read data (hybrid assembly)
using the following parameters: similarity =0.95; length fraction
=0.7; insertion/deletion cost =3; mismatch cost =3; automatic
bubble and word size; minimum contig length of 200 bp to avoid
singlets. Paired end range distance was 217 to 442 bp for the
control sample and 211 to 380 bp for the drought treatment
sample. To compare contigs assembly we used both CLC and
Oases 0.1.22 (Schulz et al., 2012) [http://www.ebi.ac.uk/~zerbino/
oases]. Contigs were scanned for full length coding sequence
(full length CDS) using the tool GETORF from EMBOSS version
6.3.1 (Rice et al., 2000), looking for open reading frame regions
between START and STOP codons and a minimum of 300
nucleotides. Considering that drought related proteins described
in other models have more than 100 aa, and incomplete genes
can’t be resolved without a deep genome exploration that is out of
the scope of this work, we chose this cutoff to avoid the presence
of incomplete genes. Results were filtered through Perl script to
obtain the longest predicted CDS by contig.
Exploratory Data Analysis
Contigs with predicted full length CDS obtained from the de novo
hybrid assembly were used as a reference set of transcripts for
RNA-seq analysis. Short-read sequence data from control and
drought samples were separately mapped against the reference
set of assembled transcripts using the CLC Genome Workbench
RNA-seq function using the following parameters: similarity =
0.95; length fraction =0.7; maximum mismatches =2; unspecific
match limit =10. Paired reads were counted as two, and paired
end distances were set as described previously for the assembly.
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Morales et al. Drought Transcriptional Responses in Chilean Quinoa
For exploratory expression analysis, we selected contigs with
at least 5 total reads mapped to each hybrid contig to increase
the results confidence (Tittarelli et al., 2009). The relative
“over/under-represented” gene levels were defined as the number
of reads mapped uniquely to the gene. The representation levels
were compared using a Z-Test (Kal et al., 1999) with the control
sample as reference. This test compares counts by considering
the proportions that make up the total sum of counts in each
sample, correcting the data for sample size. For visual inspection,
original over/under-represented values were transformed by
Log10 method and then normalized by the Quantile method that
was the best to fits the results (Bolstad et al., 2003).
Functional Annotation
Functional annotation was performed on assembled contigs with
predicted full length CDS by BLAST2GO software (Conesa
and Gotz, 2008). We used as input BLASTX results of our
contigs against NCBI RefSeqProt database (Pruitt et al., 2007;
Mestanza et al., 2015) and Arabidopsis TAIR10 database
(The Arabidopsis Information Resource, Genome Release 10
[http://www.arabidopsis.org]) with an e-value cut-off of 1e6.
Also, it was performed an INTERPROSCAN analysis (Hunter
et al., 2009) with BLAST2GO default parameters. We used
BLAST2GO program defaults in all mapping and annotation
steps and the False Discovery Rate (FDR) cut-off was set
to 0.05% probability level. The data from INTERPROSCAN
terms, enzyme classification codes (EC), and metabolic pathways
(KEGG, Kyoto Encyclopedia of Genes and Genomes) were
merged with GO terms for a wide functional range cover in
annotation (Conesa and Gotz, 2008).
Quantitative Real-Time PCR Analysis
For each sample, 10 µg total RNA was treated with DNAse
RNAse-free (Fermentas), 5 µg of which was reverse transcribed
in a 20 µL volume using Affinity Script Multiple Temperature
cDNA Synthesis Kit (Agilent) primed with oligo dT. The
resulting cDNA was diluted to 200 µL with distillate water. Gene-
specific primers were designed to span the selected genes using
Primer3 software (http://frodo.wi.mit.edu/primer3/). qPCR was
carried out on 1 µL diluted cDNA by triplicate using the
MaxPro3000P Stratagene Sequence Detection System, Brilliant
III Ultra Fast SYBR Green QPCR master mix (Agilent) and
primers at a final concentration between 250 and 450 nM. The
primers list is shown in (Table S2). qPCR analysis was performed
and data (±S.D.) represents three biological replicates following
previous reports (Ruiz-Carrasco et al., 2011; Mestanza et al.,
2015).
Statistical Analysis
A two-way analysis of variance (ANOVA), followed by
Tukey’s post-test, was performed to evaluate the drought
effects on relative water content, electrolyte leakage and Fv/Fm
determination to compare genotypes among each other, after
testing for normality and homogeneity of variances using the
Shapiro-Wilkes test and variation coefficient, respectively.
RESULTS
R49 Exhibits the Most Drought Tolerant
Phenotype
Based on the altitudinal and latitudinal distribution of
quinoa in Chile we analyzed three genotypes representing
the biogeographical areas where this staple crop is actually
grown. The genotype R49 is representative of the Chilean
highlands (Salares ecotype), where 200 mm/year of rainfall
are concentrated in only 1 month during the summer rainy
season at an altitude of 3,800 m. The PRJ genotype is grown in
central coastal Chile with a rainfall of 600 mm/year that is also
concentrated during the fall season, and the genotype BO78 is
from the southern Chile were the rainfall reaches 1,300 mm and
the rain period occur throughout the whole year, the last two
genotypes corresponding to coastal/lowland ecotype.
Figure 1 shows the genotype responses for relative water
content, electrolytic leakage and maximum efficiency of
photosystem II (Fv/Fm) parameter. The analysis of the relative
water content (Figure 1A) showed a gradual decrease for
all genotypes from 8 days from the treatment onward thus
decreasing their RWC below 30%; the genotype R49 showed a
slight difference compared to the others genotypes after 21 days
of drought. We could observe a significant difference [F(1.63) =
129.01; p<0.0001] since 18 days post treatment compared to
PRJ. On the other hand, BO78 showed an intermediate behavior
between both genotypes but not significantly different. When
measuring electrolytic leakage (Figure 1B), a significant increase
[F(1.63) =34.37; p<0.0001] for the central and south genotypes
was observed at 18 days, increasing over 70% EL; nevertheless,
the Salares genotype did not display major differences through
the whole experiment similar to control of all genotypes. The
parameter of maximum efficiency of photosystem II (Fv/Fm;
Figure 1C) significantly decreased [F(1.63) =6.47; p<0.0001]
as response to drought treatment for genotypes PRJ and BO78
only from 18 days of drought treatment, in contrast to a stable
Fv/Fmratio in genotype R49 throughout the whole experiment,
showing that photosynthetic machinery in R49 leaves remained
functional despite prolonged water deficit condition.
RNA-Sequencing, Reference
Transcriptome Assembly and Gene Space
of Quinoa under Drought Conditions
Two different samples were sequenced to obtain the R49 quinoa
transcriptome. One of the samples corresponded to plants with
the drought stress treatment and the other one to control plants
as described in materials and methods. After library construction,
Illumina paired -end sequencing was performed. 54 million and
51 million reads were obtained from the control and drought
conditions respectively. Both reads from control and drought
conditions were used to build a reference transcriptome due to
the lack of an available quinoa genome at that stage.
The sequence assembly was performed with the CLC Genome
Workbench software (version 4.8). The 104.8 millions of reads
were assembled into 150,952 contigs, with an average length of
538 bp, their size distribution is showed in (Figure S1). Out of the
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Morales et al. Drought Transcriptional Responses in Chilean Quinoa
FIGURE 1 | Physiological performance of quinoa genotypes in days under drought conditions. (A) Percentage of Relative water content (RWC). (B)
Percentage of Electrolytic leakage (EL). (C) Maximum efficiency of photosystem II (Fv/Fm). X-axis represents days under drought. RWC was measured based in the
plant total weight that corresponded to water; EL represents the percentage of ions that were released compared to total amount present in the plant; Fv/Fm
represents the capacity for photon energy absorbed by photosystem II (PSII) to be utilized in photochemistry under dark- and light-adapted conditions. Values and
Bars represent averages and standard deviation (n=3); ** and different letters denote significant differences (p<0.01 and p<0.05 respectively).
assembled contigs, 31,523 with predicted full length CDS were
used for further analysis as our reference transcriptome. The size
distribution of this subset of sequences is showed in Figure 2A
and the list of sequences is available in Additional File 1. Reads of
both conditions (drought and control) were individually mapped
back to our reference transcriptome and results were used in an
RNA-seq assay to do a qualitative analysis (e.g., present/absent
of a gene) (Mortazavi et al., 2008). Gene data is available in
Additional File 2.
Functional Annotation of Reference
Transcriptome
To obtain a functional annotation, the sequences with predicted
full length CDS (n=31,523) were aligned by BLAST against
the NCBI NR database and Arabidopsis TAIR10 database using
a cut-off E-value of 106. The number of quinoa genes that
exhibited homology with the sequences described in the NCBI
NR database was 29,334 (93.1%); on the other hand, 2,189 genes
(6.9%) did not match the database. These results were different
to others results previously reported (Riggins et al., 2010; He
et al., 2012; Huang et al., 2012; Zhang et al., 2012; Raney et al.,
2014), where the genes without match represented more than
40%. In this case contigs with predicted full length CDS where
used but the cited published works included the whole set of
contigs. We also cannot rule out that unknown sequences may
be novel genes in quinoa, which might be possibly derived
from chimerical sequences (assembly’s errors), or could be non-
conserved regions of proteins. The similarity distribution showed
that 41% of the query sequences have a similarity higher than
80%, while 91% of the hits have a similarity higher than 50%,
(Figure 2B). The E-value distribution of the top hits in the NR
database showed that 59.4% of the mapped sequences have strong
homology (<1.0E63), whereas 28.6% of the homolog sequences
ranged between 1.0E7and 1.0E63 and only 7% was >1.0E3,
which included sequences with no hit (Figure 2C). Those quinoa
genes displayed a significant range of identity to sustain that
a putative gene function was correlated to a functional gene
homology. Indeed, with the very recent availability of a reference
quinoa genome (Yasui et al., 2016), out of 31,523 contigs with
predicted full CDS, 30,445 mapped to 90,438 genome predicted
genes (e<1e10; score >=500; coverage >=50%), meaning
that our built-in reference transcriptome covers a 40% of the
genome transcripts (data not shown).
Annotation and determination of gene ontology of transcripts
with predicted full length CDS was done by BLAST2GO
platform. BLASTX, Interproscan, KEGG and Classification
Codes enzymes (EC) were combined to perform a classification
with a bigger GO coverage. Additional File 3 contains all the
results associated to functional annotation. The results of the GO
annotation were used to compare GO categories that changed
in response to drought in the expression qualitative subset
(2,456 contigs). Figure 3 presents the results for the categories:
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Morales et al. Drought Transcriptional Responses in Chilean Quinoa
FIGURE 2 | Identity analysis of quinoa genes. (A) Contig size distribution
(bp). (B) Blast hit sequence similarity distribution. (C) Blast hit sequence
E-value distribution. Red line represents the accumulation rate from low value
to high whereas green line represents the accumulation ratio from high value to
low.
biological process and molecular function, level 3, and cellular
component, level 8. As expected, it was possible to identify a
higher number of genes over-represented by drought (85) in
the biological process category “response to stress” (Figure 3A)
and also 60 genes that were down-represented. In the category
“cellular response to stimulus” we found the induction of
18 genes and in the category “response to abiotic stimulus”
57 genes were over-represented and 12 down-represented by
drought treatment. Analysis of molecular functions that were
affected by drought (Figure 3B), showed a majority of genes
related to “organic cyclic compound binding and heterocyclic
compound binding,” where 214 of them were over-represented
and 105 were down-represented, whereas in “small molecule
binding” 123 genes and 64 genes respectively. On the other
hand, in the most general category “protein binding” 95 genes
were over-represented and 80 genes were down-represented.
Also “transferase activity” (with 143 and 113 respectively),
“transcription factor activity, sequence-specific DNA binding”
(18 and 16), and “hydrolase activity” (133 and 118 genes) in
response to drought treatment.
Regarding the “cellular compartment” (Figure 3C), level
8 of Gene Ontology was used to gain insights, and the
results showed that the number of genes related to “plastids”
and “mitochondrion” that modified their representation was
remarkable: 44 genes were over-represented and 21 genes were
down-represented for “plastids,” whereas 35 genes and 17 genes
were modified for “mitochondrion.” This was followed by the
category “nucleus” with 48 genes and 27 genes respectively. Also
we found 2 categories that were only present in drought subset:
“vacuole” with 19 genes and “cytosol” with 17 genes.
Gene Ontology (GO) Enrichment Analysis
With each selected gene set we performed a gene ontology
enrichment analysis with focus on biological processes terms and
found that only GO terms “fruit ripening” and “reproduction”
were enriched in drought over-represented genes. Furthermore,
“pollen pistil interaction,” “abscission” and “carbohydrate
metabolic process” were enriched in drought down-represented
genes (Table 2). Indeed, we used 4 X fold change as a cutoff taking
in consideration that enrichment analysis did not produce any
enriched biological process at 2 X of fold of change.
RT-qPCR Analysis of
Differentially-Expressed Genes
To confirm both the assembly and the exploratory approach to
select target genes, expression analysis by qPCR amplification was
performed (target genes and their representation are included in
Additional File 1). We also performed Sanger sequencing of all
genes used in the qPCR analysis of this work finding a perfect
match between the assembly and the sequenced fragment in 90%
of the cases (see Additional Files 4,5). On the other hand, when
mapping the predicted contigs with full CDS against the Quinoa
genome (Yasui et al., 2016) we found that 90% had a structure
according to the genome (e<1e10; score >=500; coverage >
=50%). The gene selection was made based on two criteria. First,
genes that were induced under drought conditions in other plant
models were identified through literature mining. In addition,
we attempted to reconstruct a canonical pathway associated with
drought stress, the Abscisic Acid (ABA) pathway. The ABA
biosynthesis pathway was used as a reference, corresponding to
the described by Seo and Koshiba (2011). This pathway consists
of 5 genes, three of which are located in the plastids: ABA1,
Frontiers in Plant Science | www.frontiersin.org 6March 2017 | Volume 8 | Article 216
Morales et al. Drought Transcriptional Responses in Chilean Quinoa
FIGURE 3 | GO classification of genes with differential expression
under drought conditions. Functional categories (A) Biological process; (B)
Molecular function; (C) Cellular component. Red bars: over-represented
genes; Blue bars: down-represented genes.
ABA4 and NCED3 and two in the cytosol: ABA2 and ABA3.
In addition to ABA biosynthesis pathway genes, two important
genes involved in ABA transport were included, ABCG25
and ABCG40. Others genes involved in stress response were
selected based in the changes of representation reads detected
TABLE 2 | Enriched Biological Processes in drought over-represented
gene set or down-represented gene set.
Gene set GO code GO Term p-value
Drought over-represented genes GO:0009835 Fruit ripening 1.3E02
GO:0000003 Reproduction 1.9E02
Drought down-represented genes GO:0009875 Pollen-pistil
interaction
5.5E03
GO:0009838 Abscission 1.1E02
GO:0005975 Carbohydrate
metabolic
process
1.3E02
Enrichment was determined by Fisher’s exact test and the result reduced to most specific
terms.
by RNA-Seq in quinoa: CqHSP20 (putative chaperones hsp20-
protein superfamily), CqCAP160 (cold acclimation protein 160),
CqLEA (late embryogenesis abundant protein family protein),
CqAP2/ERF (integrase-type DNA-binding protein superfamily),
CqPP2C (protein phosphatase protein family 2c), CqHSP83
(chaperone protein, protein family HTPG), and CqP5CS (delta
1-pyrroline-5-carboxylate synthase 2). To address the RNA-Seq
changes, expression analysis by qPCR of selected 15 unigenes
were performed. The qPCR analysis showed a similar pattern to
the in silico analysis (Figure 4). We determined that CqNCED3a
and CqNCDE3b were the only genes involved in the ABA
biosynthesis pathway that were up-regulated by drought in
quinoa. For CqABA1 and CqABA3, we determined slight down-
regulation by drought (<2 Fold Change), whereas CqABA2,
and CqABA4 were down-regulated (>2 Fold Change). Similar
slight down-regulation were determined for CqABCG25 and
CqABCG40, involved in ABA transport (Figure 4A). In addition,
the genes CqHSP20,CqLEA,CqCAP160,CqAP2/ERF,CqPP2C,
CqHSP83, and CqP5CS were up-regulated at variable magnitudes
in response to drought conditions as Figure 4B shown, which
is in agreement with previous reports in different plant models
(Kaye et al., 1998; Wang et al., 2004; Ali-Benali et al., 2005;
Nakano et al., 2006; Swindell et al., 2007; Umezawa et al., 2009;
Sharma and Verslues, 2010; Merewitz et al., 2011; Candat et al.,
2014). Interestingly, CqHSP20 and CqLEA experienced a shift
over 140-fold expression level, whereas other group of genes
(CqCAP160,CqAP2/ERF,CqPP2C,CqHSP83, and CqP5CS) the
expression level change was between 24 and 2-fold respectively.
DISCUSSION
Quinoa or quinua (Chenopodium quinoa Willd.) is vastly
distributed throughout the Andean region covering a range of
12,000 km from Colombia to Chile, also defining five ecotypes:
inter- Andean valleys, Highlands, Yungas, Salares (salt flats),
and coastal/lowlands. Due to the geographical diversity of
our country, several genotypes can be found in the only two
ecotypes present: Salares, which is distributed in the Tarapacá
and Antofagasta regions (18–25S), with elevations over 3,000 m
high and precipitation fluctuating between 100 and 200 mm per
year falling during the southern hemisphere summer, whereas
Frontiers in Plant Science | www.frontiersin.org 7March 2017 | Volume 8 | Article 216
Morales et al. Drought Transcriptional Responses in Chilean Quinoa
FIGURE 4 | Gene expression levels measured by qPCR. (A) ABA transport and biosynthesis genes expression levels. (B) Genes that respond to drought. The
expression levels are relative to the normalizer gene (Pre-mRNA splicing PRP18-interacting factor) that was identified from the in silico expression analysis. Bars
represent the standard deviation of three replicates.
coastal/lowlands, the latter being the only temperate latitude
ecotype is distributed in central Chile and more southern
latitudes (43S) (O’Higgins to Lakes’ regions) and are rain-fed
with variable altitudes between sea level and 1,000 m height.
A remarkable difference is that compared to the extremely dry
conditions where the “Salares” quinoa is grown in northern
Chile, rainfall in the central and southern zones of Chile occurs
during the southern hemisphere winter (June–August), with
rainfall fluctuations between 500 and 2,000 mm per year. This
rainfall increases steadily across 34–40S (Martínez et al., 2015).
Among this diversity it is possible to distinguish two groups
through genetic distance, most probably due to the lack of seed
exchanges: “coastal/lowlands” and “Salares” (Fuentes et al., 2008;
Martínez et al., 2015). Therefore, it was necessary to perform
a selection among the Chilean genotypes that could exhibit
distinctive tolerance to drought. Three representative Chilean
genotypes were assessed to select the most drought tolerant: R49
(Salares), PRJ (coastal/lowlands), and BO78 (coastal/lowlands).
These genotypes represent three bio geographical areas or
growing zones (north, central and south) previously described
(Fuentes et al., 2008, 2012). After the analysis of relative
water content, electrolytic leakage and maximum efficiency of
photosystem II, we determined that the R49 genotype was the one
with the best performance on physiological parameters selected
and the highest tolerance to drought, considering that decline
in photosynthetic parameters occurred concurrently with the
appearance of physical symptoms of drought stress, including
water loss and membrane stability among others.
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Morales et al. Drought Transcriptional Responses in Chilean Quinoa
The quinoa R49 transcriptome was sequenced by the Illumina
pair-ends method, using total RNA extracted from quinoa plants
under stress and from total RNA extracted out of control plants.
We obtained 104.8 millions of reads, which were assembled into
150,952 contigs with an average size of 538 bp, where 18,124
contigs had a higher or equal length of 1,000 bp and 132,826
contigs were less than 1,000 bp in length. The high percentage
of contigs less than 1 Kb is expected on this type of approach (de
novo assembly) were there were no reference transcriptome to
date of experiments and also due to the polyploidy of this specie
(Crawford et al., 2010; Mizrachi et al., 2010; Zhang et al., 2012).
Taking in consideration that a high number of these contigs could
be fragments of genes, we decided to select those contigs that
has been predicted as full length CDS (n=31,523 contigs). To
determine the identity of those predicted full length CDS quinoa
contigs, BLAST, Interproscan, KEGG and EC tools were used.
The results indicated that 6.9% of the analyzed genes had no
identity with any other gene in the public databases used in this
study. This is a small number of unknown genes compared to
other similar reports but the difference may lay in the fact that
we used only a subset of contigs with predicted full length CDS
to ensure more confidence avoiding assembly problems related to
polyploidy. Among the contigs with known identity, we observed
a small percentage having a low homology; therefore we assumed
that the function of the genes was indeed the one predicted for
the orthologous gene.
We indeed found six processes that could be reduced to two
main biological processes: “fruit ripening” and “reproduction”
under a 4 X fold change criterion and FDR p<0.05, 2,456
differentially represented genes were identified, from which
1,579 were over-represented and 877 were down-represented
under drought conditions. By analyzing the genes identity,
we found 76 genes with unknown identity that were down-
represented under drought, equivalent to 9% of the total of
genes that were down represented, whereas 306 genes with
unknown identity were over-represented under this stress,
equivalent to 19% of the total of genes over-represented in
drought. When we searched for the number of drought-induced
genes in other models such Arabidopsis (Seki et al., 2002),
the number of genes with known identity was one fifth to
the ones induced in quinoa under the same stress (277 vs.
1,273 respectively). By taking a sample of the genes population,
it was expected that the percentage of genes without identity
would be conserved from what is observed in the entire
population, in our case around 6.9%. We finally determined
that among drought over-represented transcripts, genes with
unknown identity were 19%, well above the expected 6.9%. These
results allow us hypothesized that the drought response in quinoa
might present several unknown paths. Recently, Raney et al.
(2014) published the transcriptome sequencing of two quinoa
genotypes in response to drought. These authors obtained a
lower number of genes in comparison to those reported in
our work, i.e., 462 differentially expressed contigs identified
upon water stress treatments, 251 which presented sequences
that could be annotated with a functional gene ontology and
assigned to a GO category, despite the use of a combination of
methodological approaches, including 454 and ESTs sequencing,
and different genotypes analyzed (Raney et al., 2014). Indeed,
these authors identified a group of 27 differentially expressed
genes that can be classified as having regulatory functions,
including one whose inferred polypeptide product showed high
amino acid sequence homology to Naringenin, 2-oxogluturate
3-dioxygenase, which is intermediate in the biosynthesis of
flavonoids in plants (Raney et al., 2014). It is interesting that
the two GO terms enriched on the drought over-represented
genes, the processes of “fruit ripening” and “reproduction,” has
been associated to drought stress in grapevine, cereals and
other plants on studies related to climate change (Castellarin
et al., 2007; Barnabas et al., 2008; Chaves et al., 2010; Fleury
et al., 2010) where they have been related to an escape
strategy before the onset of severe drought stress. This strategy
involves several biological processes, most of them directed to
dehydration avoidance like minimized water loss (e.g., caused
by stomatal closure, trichomes, reduced leaf area, senescence
of older leaves, etc.) or maximized water uptake (e.g., by
increased root growth). These changes must be equilibrated
energetically and we found that, under drought condition quinoa
also displayed reduction in pollen-pistil interactions, possibly
related to CLE genes in response to environmental stimuli
such as heat stress (Wang et al., 2016), reduction in abscission
processes and reduction in carbohydrate metabolic processes
suggesting different ways of metabolic plasticity under the
drought condition.
The results obtained from our in silico analysis served
as reference to further identify target genes for in vivo
experiments, where the expression patterns of 15 genes were
assessed by qPCR, which were chosen for canonical responses
to drought such as ABA biosynthesis, since ABA regulation
seemed to be one of the mechanisms utilized by quinoa
when facing drought induced decrease of turgor of stomata
guard cells (Jacobsen et al., 2009), and another group of
genes directly induced in response to drought. We could
determine that CqABA1,CqABA2, and CqABA4 from the ABA
biosynthesis pathway were repressed over two times. One
hypothesis to explain why these two genes were repressed
might be that in quinoa a family of corresponding genes might
be present as tetraploid species, and the designed primers
did not differentiate between the members of the family. A
previous study concluded that ABA apparently plays a minor
role under drought conditions in quinoa, and the authors
suggested that quinoa might produce other antitranspirants
compounds than ABA in the xylem sap (Jacobsen et al.,
2009). Also, hormonal stress signals may exist and may
play an important role in quinoa, suggesting that both
cytokinin and ethylene reactions should be further dissected in
quinoa.
The relative abundance of studied target genes was highly
variable in response to stressful conditions. There were genes
that had very low expression levels, as ABA-pathway transcripts
described above. In the other hand, the highest up-regulation
(over 200-fold) was exhibited by CqHSP20, might indicates
that drought treatment affected the thermal regulation via
water shortage, since Hsp20 genes have been induced to a
larger extent in tomato plants under various abiotic stresses,
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Morales et al. Drought Transcriptional Responses in Chilean Quinoa
including heat, salt, and drought treatments (Yu et al., 2016),
which may suggest that plants were inducing ABA-independent
responses as well. Small HSPs (sHSPs) are involved in folding
and assembling protein, keeping protein stabilization, activating
protein, and degrading protein in many normal cellular processes
and under stress conditions. Indeed, most of the HSPs (HSP18.1,
HSP18.3, HSP20, HSP21.7, HSP25.3, HSP26.26, and HSP30)
were significantly up-regulated during the heat treatment in
spinach (Spinacia oleracea L.) leaves under heat stress (Yan
et al., 2016). In the case of CqLEA gene that was induced
140-fold in treated plants, consistent with the fact that the
ABA-responsive element was first described for a group 2 LEA
gene from rice, there are genes for this group of proteins
whose expression in response to stress is mediated by ABA.
Moreover, there are examples of dual regulation; that is, their
response to stress is mediated by more than one pathway,
one of which may be ABA dependent (Welling et al., 2004;
Battaglia et al., 2008). A different case was CqAP2/ERF, whose
up-regulation might be pointing to a pivotal role in coordination
of regulatory networks underlying abiotic stress tolerance
(Golldack et al., 2014). Furthermore, functional analysis of berry
transcriptomic responses to higher temperatures revealed the
induction of heat shock protein (HSP) chaperones coincident
with up-regulation of ERF subfamily transcription factors and
increased ABA levels, suggesting their participation in the
maintenance of the acclimation response (Carbonell-Bejerano
et al., 2013).
Differentially abundant genes both over-represented and
down-represented in drought treatment were compared among
them using Blast2GO. The categories that shown over-
represented genes that are commonly associated to drought were
“response to stress” as expected with 85 genes and “response
to abiotic stimulus” with 57 genes. Among the biological
processes that were found in both subsets but over-represented
in drought we highlight: “biosynthetic process,” “single-organism
metabolic process,” “nitrogen compound metabolic process,
“establishment of localization,” “single-multicellular organism
process” and “single-organism developmental process.” Also
there were four processes only detectable in the over-represented
subset: “cellular response to stimulus” (18 genes), “single
organism signaling” (18 genes), “developmental process involved
in reproduction” (13 genes) and “single organism reproductive
process” (13 genes). In general, these results coincide with
reports for Thellungiella, wheat, poplar, rice, cassava, Arabidopsis
and chickpea (Wong et al., 2005; Mochida et al., 2006;
Street et al., 2006; Gorantla et al., 2007; Lokko et al., 2007;
Huang et al., 2008; Varshney et al., 2009). These results
indicated that in quinoa most responses to drought are
conserved, as for most species where this abiotic stress has
been studied. The difference in tolerance levels might rely
in the population of genes without identity. When looking
at categories of genes that were regulated with stress, we
highlighted the plasma membrane related genes, because these
variations can be linked to cell turgor maintenance (Razzaghi
et al., 2015) or membrane stability observed by measuring
electrolyte leakage. Indeed, we found an up-representation of
transporter activity genes such as ABC, ERD6-like, MATE,
SWEET-like among others, in parallel with down-representation
of cell wall modifying genes. These variations can be attributed
to the ability to withstand stress levels to which the plant
was submitted, remobilization of assimilates and might be
linked to ROS (reactive oxygen species) detoxification, since
they cause severe cellular damage by peroxidation and de-
esterification of membrane-lipids (Golldack et al., 2014; Raney
et al., 2014).
CONCLUSIONS
This work has determined that quinoa transcriptome from
a tolerant genotype R49 has exhibited a 15% of genes (382
contigs) that not presented homology to the published databases
from 2,456 identified differentially represented transcripts
under drought conditions. The over-represented genes were
higher (1,579) than down-represented genes (877) by drought
treatment, and 19% of over-represented genes (306 contigs) were
unknown. In Arabidopsis, approximately 40% of enzyme- and
transporter-encoding genes have credible functional annotations,
and this number is even lower in non-model plants. The slight
up-regulation of ABA genes in response to drought stress in
quinoa might indicate that ABA-independent mechanisms are
committed to coordinate responses to acclimate to hydric deficit.
Also functional characterization of unknown genes remains a
challenge, but various databases and homologs cross-kingdom
comparative genomics could be mined to provide clues (Niehaus
et al., 2015). Therefore, integrative efforts are still necessary to
unravel how this resilient species is able to withstand in adverse
environments where others species fail to succeed. Indeed, the
information represents a very useful tool for selecting drought
tolerant parentals or lines with active tolerance mechanisms
for breeding purposes, being useful to explore the differentially
expressed gene space and valuable for loci identification in
ongoing quinoa breeding efforts.
AUTHOR CONTRIBUTIONS
AM performed drought treatments, prepared RNA samples
and interpreted the results. JM performed assembling,
expression analysis and interpreted the results. AM, HS,
and AZ designed the experiment and provided guidance
of the study. AZ and HS provided assistance in the data
analysis, management data interpretation and wrote the
manuscript. All authors have read and approved the final
manuscript.
ACKNOWLEDGMENTS
HS was supported by Iniciativa Científica Milenio, MNPCB P06-
065-F and CONICYT, FONDECYT/Regular No. 1120261; AZ
was supported by Innova Chile (BioTecZA 06FC01IBC-71), FIC-
R Atacama BIP-30432772-0, CONICYT FONDECYT/Regular
No. 1140039 2014/INIA and Regional Research Center INIA-
Intihuasi; AM was supported by a CONICYT Fellowship D-
24110186, Universidad Andres Bello Fellowship DI-22-11//I
Frontiers in Plant Science | www.frontiersin.org 10 March 2017 | Volume 8 | Article 216
Morales et al. Drought Transcriptional Responses in Chilean Quinoa
and was a member of the Biotechnology Doctoral Program
at Universidad Andres Bello. Authors want to thank technical
assistance of Msc María Alejandra Montoya.
SUPPLEMENTARY MATERIAL
The Supplementary Material for this article can be found
online at: http://journal.frontiersin.org/article/10.3389/fpls.2017.
00216/full#supplementary-material
Figure S1 | Distribution of contigs size obtained from the genome
reference (hybrid assembly).
Table S1 | Soil water potential for quinoa plants ecotype R49.
Table S2 | qPCR primers list for selected genes in this study.
Additional File 1 | FASTA file with predicted full length CDS contigs used
for further analysis as our reference transcriptome.
Additional File 2 | Excel spreadsheet with differentially expressed genes
(DEG analysis) when compared reads from drought and control
conditions. Proportions fold of change of values minus infinite and plus infinite
was set to 1,000,000 and 1,000,000 respectively.
Additional File 3 | Excel spreadsheet with the annotation and gene
ontology of transcripts with predicted full length CDS.
Additional File 4 | Excel spreadsheet with the validation of qPCR
amplicons by BLAST alignment against quinoa transcriptome. Amplicons
were sequenced using Sanger technology.
Additional File 5 | Excel spreadsheet with the structure validation of
selected quinoa genes by BLAST alignment against the genome predicted
transcripts (Yasui et al., 2016).
AVAILABILITY OF DATA AND MATERIALS
The nucleotide sequences of raw reads from this study were
submitted to NCBI’s Sequence Read Archive through the
BioProject ID: PRJNA305752. Contigs with predicted full length
CDS are available in Additional File 3.
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Conflict of Interest Statement: The authors declare that the research was
conducted in the absence of any commercial or financial relationships that could
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Frontiers in Plant Science | www.frontiersin.org 13 March 2017 | Volume 8 | Article 216
... Quinoa is also known for its ability to grow in marginal environments and tolerate a range of adverse growth conditions, such as high salinity [14][15][16][17], heat [18] and drought [15,19,20]. Detailed studies of quinoa subjected to drought stress have been conducted, both in the field and in greenhouse experiments, providing insight into the key physiological adaptations of quinoa. ...
... Tolerance of quinoa to abiotic stresses such drought, salinity, low soil fertility and frost has been well documented, making it a target crop for addressing future food security in the context of a climate crisis [13,19,20,31,65]. Studies have recorded significant yield deficits, especially under low soil water availability and high vapor pressure deficit, high temperatures and nitrogen deficiency [15,[66][67][68][69][70]. ...
... Plant drought response mechanisms have been reported in quinoa and include reduced growth [23,69], stomatal closure associated with abscisic acid and hydraulic signaling [22,25,[82][83][84], peroxisome abundance as a cellular sensor [68], the accumulation of osmoprotectants, antioxidant defense and membrane stabilization [19,20,26,27], and elevated recovery capacities of PSII and PSI photochemical activities after re-watering [85]. Understanding how the physiological mechanisms employed by quinoa in response to drought as well as specific strategies implemented by different genotypes influence the final yield is crucial for both crop management and breeding. ...
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Quinoa (Chenopodium quinoa Willd.) is a genetically diverse crop that has gained popularity in recent years due to its high nutritional content and ability to tolerate abiotic stresses such as salinity and drought. Varieties from the coastal lowland ecotype are of particular interest due to their insensitivity to photoperiod and their potential to be cultivated in higher latitudes. We performed a field experiment in the southern Atacama Desert in Chile to investigate the responses to reduced irrigation of nine previously selected coastal lowland self-pollinated (CLS) lines and the commercial cultivar Regalona. We found that several lines exhibited a yield and seed size superior to Regalona, also under reduced irrigation. Plant productivity data were analyzed together with morphological and physiological traits measured at the visible inflorescence stage to estimate the contribution of these traits to differences between the CLS lines and Regalona under full and reduced irrigation. We applied proximal sensing methods and found that thermal imaging provided a promising means to estimate variation in plant water use relating to yield, whereas hyperspectral imaging separated lines in a different way, potentially related to photosynthesis as well as water use.
... Yield improvement and pest resistance had been the main focus of the breeding programs in crops in Chile like wheat (Cortázar et al., 1988;Zerené et al., 1997), legumes (Paredes, 1994;Tay et al., 2004;Mera and Galdames, 2007), rice (Cordero-Lara, 2020), and quinoa (Zurita-Silva et al., 2014). In recent years resistance to abiotic stresses (Acuña et al., 2012;Soto-Cerda et al., 2015;del Pozo et al., 2016;Morales et al., 2017) and fruit/seed quality have also been included (Barticevic et al., 2004). ...
... Strong research orientated is needed for characterize, evaluate and select germplasm tolerant to higher environmental temperature, drought and salty soils (Isayenkov, 2019). Efforts had been done on some selected germplasm of landraces, cultivars or commercial varieties of tomato (Martínez et al., 2014;Tapia et al., 2015;Martínez et al., 2020;Blanchard-Gros et al., 2021), native potatoes (Lizana et al., 2017;Ávila-Valdés et al., 2020), Chilean beans cultivar (Lizana et al., 2006;Martínez et al., 2007), wheat (Lizana and Calderini, 2013;del Pozo et al., 2016;Brunel-Saldias et al., 2020;Meier et al., 2022), forage legumes (Acuña et al., 2010;Inostroza et al., 2015;Acuña et al., 2016;Inostroza et al., 2019), quinoa (Ruiz-Carrasco et al., 2011;Morales et al., 2017), grapevine (Bavestrello-Riquelme et al., 2012). However, a pre-breeding orientated characterization and phenotyping well-coordinated initiatives are required characterize wider collections and for accelerating the development of new and improved cultivars better adapted to environmental constrains (Camargo and Lobos, 2016;Zhao et al., 2019). ...
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Chile is part of one of the centers of crop origin identified by Vavilov, e.g., for strawberries and potatoes. It is also a center of diversification of other crop species such as maize, beans and quinoa. It is one of the biodiversity hotspots of the world and several native species have potential for domestication. All of these types of species are considered Plant Genetic Resources for Food and Agriculture (PGRFA). However, the rich plant genetic diversity present in Chile is being lost, mostly due to human activity. Therefore, ex situ and in situ conservation of this diversity are of critical importance. In this review we show the achievements in PGRFA conservation activities in the last 15 yr and in plant breeding for the last 60 yr in this country. Several gene banks exist, administrated by different institutions, with over 48 000 accessions preserved, mostly cereals (65%) and grain legumes (23%). Significant advances were achieved between 2006 and 2020 in the conservation, regeneration, characterization and documentation of PGRFA, but work is still needed to complete a fully operable data base for all collections. Over 16 000 accessions of Chilean origin are also kept in gene banks abroad. Plant breeding programs of several agriculturally important crops have made an outstanding contribution to Chilean agriculture and food security, with more than 375 commercial cultivars developed. More effort needs to be made to strengthen ex situ conservation and the sustainable use of PGRFA under coordinated actions, guided by a national strategy on genetic resources, if significant contributions are to be made in response to climate change.
... Transcriptome-based analyses of quinoa have been made to identify target genes and markers for drought and stress tolerance (Raney et al., 2014;Morales et al., 2017;Schmöckel et al., 2017) and also recently to characterize genetic differences in seed quality concerning flavonoid and proanthocyanin levels (Wang et al., 2020;Liu et al., 2022). However, knowledge about the particular genetic factors that regulate seed protein content in quinoa is lacking. ...
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Quinoa ( Chenopodium quinoa Willd.) is a crop that has great potential for increased cultivation in diverse climate regions. The seed protein quality obtained from this crop is high concerning the requirements to meet human nutritional needs, but the seed protein content is relatively low if compared to crops such as grain legumes. Increased seed protein content is desirable for increasing the economic viability of this crop in order for it to be used as a protein crop. In this study, we characterized three genotypes of quinoa with different levels of seed protein content. By performing RNA sequencing of developing seeds, we determined the genotype differences in gene expression and identified genetic polymorphisms that could be associated with increased protein content. Storage nutrient analyses of seeds of three quinoa genotypes (Titicaca, Pasankalla, and Regalona) from different ecoregions grown under controlled climate conditions showed that Pasankalla had the highest protein content (20%) and the lowest starch content (46%). Our seed transcriptome analyses revealed highly differentially expressed transcripts (DETs) in Pasankalla as compared to the other genotypes. These DETs encoded functions in sugar transport, starch and protein synthesis, genes regulating embryo size, and seed transcription factors. We selected 60 genes that encode functions in the central carbon metabolism and transcription factors as potential targets for the development of high-precision markers. Genetic polymorphisms, such as single nucleotide polymorphisms (SNPs) and base insertions and deletions (InDels), were found in 19 of the 60 selected genes, which can be further evaluated for the development of genetic markers for high seed protein content in quinoa. Increased cultivation of quinoa can contribute to a more diversified agriculture and support the plant protein diet shift. The identification of quinoa genotypes with contrasting seed quality can help establish a model system that can be used for the identification of precise breeding targets to improve the seed quality of quinoa. The data presented in this study based on nutrient and transcriptome analyses contribute to an enhanced understanding of the genetic regulation of seed quality traits in quinoa and suggest high-precision candidate markers for such traits.
... The cultivation of quinoa outside of the Andean region has been heavily promoted by the United Nations Food and Agriculture Organization. Quinoa not only has extremely high nutritional value, but is also genetically diverse species with strong drought and salt tolerance that can be grown in marginal soils with pH values from 4.5 to 9.5 [35]. Exploring the biological basis of its excellent nutritional and agronomic characteristics has become a major focus of current crop research. ...
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... The expressions of 13 hsp70 genes under drought conditions were observed in quinoa plants with 6 being downregulated at the initiation and the recovery phases of the drought stress. The genes CqNCED3a and CqNCDE3b were found to be upregulated during drought stress in quinoa and were linked to ABA biosynthesis (Morales et al. 2017). ...
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Chenopodium quinoa Willd. (quinoa) is a pseudo-grain serving as a staple dietary food in South America due to its high nutritional values. However, the high genetic diversity of this crop determines its high potential of adaptability to contrasting environments, including nutrient-poor soil, drought, heavy metals, fluctuating temperatures, and UV-B light irradiance. Despite enormous studies on the influences of abiotic stresses and the ability to combat the stresses by the plant itself, the role of the plant-associated microbiome in stress tolerance of quinoa has not been elucidated. Therefore, this chapter aims to provide a deep insight into the (1) abiotic stresses which are challenging for the growth and yield of quinoa, (2) role of microbiota in assuaging the effects of stresses by comparing with other grain crops, and (3) formulation of methods to use this potential of the microbiome for better yield of high quality of quinoa.
... Bohm et al. (2018) demonstrated with their study that bladder in quinoa leaves functions as salt dumper which helps tolerate salt. Morales et al. (2017) used a Chilean "Salares" quinoa ecotype. RNA-seq analysis of R49 genotype compared drought and control irrigation conditions. ...
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