Abstract
The biochemical defense of plants can change during their life-cycle and impact herbivore feeding and plant fitness. The annual species Aethionema arabicum is part of the sister clade to all other Brassicaceae. Hence, it holds a phylogenetically important position for studying crucifer trait evolution. Glucosinolates (GS) are essentially Brassicales-specific metabolites involved in plant defense. Using two Ae. arabicum accessions (TUR and CYP) we identify substantial differences in glucosinolate profiles and quantities between lines, tissues and developmental stages. We find tissue specific side-chain modifications in aliphatic GS: methylthioalkyl in leaves, methylsulfinylalkyl in fruits, and methylsulfonylalkyl in seeds. We also find large differences in absolute glucosinolate content between the two accessions (up to 10-fold in fruits) that suggest a regulatory factor is involved that is not part of the quintessential glucosinolate biosynthetic pathway. Consistent with this hypothesis, we identified a single major multi-trait quantitative trait locus controlling total GS concentration across tissues in a recombinant inbred line population derived from TUR and CYP. With fine-mapping, we narrowed the interval to a 58 kb region containing 15 genes, but lacking any known GS biosynthetic genes. The interval contains homologs of both the sulfate transporter SULTR2;1 and FLOWERING LOCUS C. Both loci have diverse functions controlling plant physiological and developmental processes and thus are potential candidates regulating glucosinolate variation across the life-cycle of Aethionema. Future work will investigate changes in gene expression of the candidates genes, the effects of GS variation on insect herbivores and the trade-offs between defense and reproduction.
Introduction
Plant fitness depends on a plants ability to reach the next generation. Thus, plants must be able to defend themselves from herbivores and pathogens throughout their life-cycle; first during vegetative growth, then at the time of flowering and finally during the production of fruits and seeds. Pest pressure and effects on survival and fitness can differ greatly across the growth of the plant (). Therefore, defensive compound quality and quantity can shift and be modified during various developmental stages (). Also, there can be negative allocation and/or constitutive costs between plant defense and plant fitness (). Glucosinolates (GS, i.e., mustard oils) and their associated myrosinase enzymes form a two-component chemical plant defense in the Brassicales, defending against herbivores and pathogens. GS are nitrogen and sulfur-rich plant metabolites that hydrolyse, upon contact with the myrosinase enzyme, to form the herbivore-deterrent compounds nitriles and isothiocyanates (; ). GS are spatially separated from myrosinase; hence the toxic compounds are only formed after an herbivore attack when the cell is ruptured (). The GS biosynthesis additionally has links to fundamental biochemical and developmental processes such as auxin biosynthesis. The Brassicaceae specific IAOX auxin pathway shares intermediate compounds with the indolic GS pathway (). Moreover GS can also be perceived by specialist herbivores as oviposition stimuli (). Although all Brassicales contain GS, the highest diversity (of 120 different) GS compounds is found within the economically important family Brassicaceae (; ). This diversity is thought to be due to a combination of gene and genome duplications within Brassicaceae and due to the selective pressure from co-adapting Brassicaceae Pierideae herbivores ().
Arabidopsis thaliana is used as an important system to understand the molecular pathways underlying GS biosynthesis and flowering time. GS quality and quantity change throughout the development of A. thaliana (; ) and are influenced by the presence of nutrients, such as sulfur, that are incorporated into GS (; ). The availability of these compounds can lead to local adaptation of GS pathway genes (). GS are derived from amino acids and can accordingly be divided into three main groups: indolic, aromatic, and aliphatic. The molecular mechanisms of the GS biosynthesis pathway have been reviewed and described extensively elsewhere (e.g., ; ; ). The diversity of aliphatic GS is, among others, due to different chain lengths and side chain modifications. BCAT3 and GS-ELONG genes regulate chain length (; ; ) and AOP1-3 and FMO-GS-OX1-5 modify the side chains (; ).
Arabidopsis thaliana is also an important model species for understanding the molecular mechanisms regulating flowering time ( and the references therein). The switch from the vegetative to reproductive phase is one of the most important transitions in the life-cycle of a plant, moderated by abiotic and biotic cues. A plant needs to defend its vegetative and its new valuable generative tissues against potentially different herbivore attackers. Hence, shifts between plant development and plant defense traits can be critical to plant fitness. found a link between the GS pathway and flowering time. They incorporated the aliphatic side-chain modifiers, GS-AOP genes, in an AOP-0 background and found that they changed the flowering time of A. thaliana. Whether shifts in GS profiles and life-history transitions are seen in other Brassicaceae could establish that this is a general principle of crucifer evolution.
The annual species Aethionema arabicum belongs to the sister lineage to the rest of the Brassicaceae family and hence is at an important position for genomic and genetic comparisons of trait evolution (; Figure 1A). For example, Ae. arabicum is being used to study several aspects of life-history evolution including the molecular mechanisms of fruit and seed heteromorphism (). Ae. arabicum grows on steep stony slopes mainly in Iran and Turkey, although populations have also been found in Cyprus and Bulgaria (). Populations of Ae. arabicum go through their entire life-cycle between April and June, just before the summer heat strikes (). However, the flowering time varies throughout the species distribution. The completion of the Ae. arabicum genome has also made it possible to study and show the synteny of GS genes between A. thaliana and Ae. arabicum (; ). However, the diversity of GS profiles in Ae. arabicum are not yet described.
FIGURE 1
The focus of this study is twofold. First, we describe the GS content of different tissues at different developmental stages for Ae. arabicum. We used two different Ae. arabicum accessions (TUR and CYP) differing in their life histories. We found that GS content in the leaves depends on the plants developmental stage. Moreover, we found that GS side-chain modifications are tissue specific and that the two Ae. arabicum accessions had a 10-fold difference of GS concentration in the fruits and a twofold difference in the leaves. Second, we identified the genomic locations controlling the GS profiles in Ae. arabicum by multi-trait and multi-environment quantitative trait locus (QTL) analyses using RIL populations developed from TUR and CYP. In total, we found five QTLs including one major QTL. Two QTL intervals contain homologs of BCAT3 and MYB28, involved in the regulation of long-chained GS formation (
Materials and Methods
Plant Material
Glucosinolates profiles and quantities of Ae. arabicum during development were measured in seeds, leaves, flowers, and fruits of two Ae. arabicum lines CYP and TUR. Seeds from the CYP individual originate from the pillow lavas of Kato-Moni in Cyprus (lat 35.057310 and lon 33.091832). The TUR individual is from the living plant collection of the Botanical Garden in Jena, Germany. However, population structure analyses have shown that this line originates from Turkey (Mohammadin et al., unpublished data). CYP and TUR have different life histories and growth characteristics. CYP has a more erect habit than TUR (Figure 1B) and CYP flowers very fast with only four leaves before flowering, while the TUR accession flowers from nine leaves onward. The CYP and TUR genotypes were used as parents to establish an F8 recombinant inbred line (RIL) population. For the QTL analyses we measured GS content in seeds (110 RILs), infructescences and leaves (99 RILs), all from the same mapping population.
For the GS through development as well as QTL experiments, seeds were germinated by placing them on a wet filter paper (demi-water) in a Petri dish sealed with Parafilm. However, the germination procedure differed between the two experiments. To measure GS content through development CYP and TUR seeds were imbibed at 18°C. Seeds showing a radicle after imbibition were sown directly in 12 cm pots, with five in each pot. Seeds for the QTL experiments were stratified at ∼4°C after which they were incubated at 18°C to allow germination. Seedlings for the QTL experiments were individually sown in 10 cm pots. Both experiments were conducted in the climate controlled greenhouse, at Wageningen UR with long day conditions (16 h light: 8 h dark) at 20°C.
To measure GSs during development, parental plants (CYP and TUR) were sampled weekly from the start of the experiment up to 8 weeks. Ae. arabicum does not have a rosette; hence cauline leaves of various ages were sampled and pooled to obtain the GS content throughout the plant. Seedlings (cotyledons and roots), leaves, flowers, immature fruits, and mature fruits where sampled separately and in triplicate (three different plants of the same line). Sampling was always done at 11:00 AM, taking diurnal GS variation into account (
For the QTL experiment, leaves were collected when the plants had six fully developed leaves. All plants then showed reproductive buds or were fully flowering. Per line, leaves from two individuals were pooled. Reproductive tissues (combining infructenscence, flowers, and fruits; this is later referred to as ‘fruits’) were collected from the main stem of every RIL and parents 1 month after the start of the experiment. All freshly collected samples were immediately stored in liquid nitrogen and stored at -80°C. To assess the GS QTL(s) in seeds, we used dry ripened seeds harvested in 2014 from 110 RILs.
Frozen samples were freeze-dried at -40°C for 24 h. For GS extraction, samples were ground with 3 mm glass beads to obtain 2–10 mg of material. For the GS measurements through development: if there was <5 mg of material, samples were pooled from the same tissue of one parent before GS extraction. To analyze the QTL for seed GS ∼10 mg of seeds from all RILS were used for GS extraction.
GS Extraction and Measurements
Leaves were freeze-dried until constant weight and ground to a fine powder. Between 2 and 10 mg of freeze dried leaves or 10 mg of seeds were extracted with 1 mL of 80% methanol (v:v) containing 0.05 mM intact 4-hydroxybenzylglucosinolate as internal standard (analysis of Ae. arabicum samples without addition of internal standard had shown that the samples do not contain 4-hydroxybenzylglucosinolate). After centrifugation, extracts were loaded onto DEAE Sephadex A 25 columns. Columns were washed with 1 ml 80% (v:v) methanol, 1 ml water, and 1 ml 0.02 M MES buffer (pH 5.2), before 50 μl of sulfatase solution (arylsulfatase from Sigma-Aldrich) was added. After incubation at room temperature overnight, desulfated glucosinolates were eluted with 0.5 mL water. The eluted desulfoglucosinolates were separated using high performance liquid chromatography (Agilent 1100 HPLC system, Agilent Technologies) on a reversed phase C-18 column (Nucleodur Sphinx RP, 250 mm × 4.6 mm, 5 μm, Machrey-Nagel, Düren, Germany) with a water (A)-acetonitrile (B) gradient (0–8 min, 10–50% B; 8–8.1 min, 50–100% B; 8.1–10 min 100% B and 10.1–13.5 min 10% B; flow 1.0 mL min-1). Detection was performed with a photodiode array detector and peaks were integrated at 229 nm. We used the following response factors: aliphatic glucosinolates 2.0, indole glucosinolates 0.5 (
Statistical Analyses
Statistical analyses of the development through time was not possible, because of limited sample sizes for all tissues at every time point (n = 3 or less due to pooling). Despite the lack of sample size, we found interesting patterns of GS change through time.
The linkage map used here contains 11 linkage groups and is based on 746 SNP from genotype by sequencing analysis of 167 RILs with the Ae. arabicum v2.5 used a reference genome (Nguyen et al., in preparation).
Genome-wide QTL analyses were done in Genstat (
Results
Glucosinolates during Plant Development in Aethionema arabicum
To investigate if GS contents change through Ae. arabicum plant development (temporal) and to assess the GS composition in different tissues (spatial) we measured the GS compounds of Ae. arabicum for the two parental lines CYP and TUR from seed to a fully generative stage.
There were a total of nine different GS compounds detected in Ae. arabicum (Figure 2). Ae. arabicum seeds contain only three GS that are all aliphatic and derived from the amino acid methionine: 3MSOOP (3-methylsulfonylpropyl, C11H21NO11S3), 7MSOH (7-methylsulfinylheptyl, C15H29NO10 S3), and 8MSOO (8-methylsulfinyloctyl C16H31NO10S3) GS (Figure 2). 8MSOO was the only compound that occurred in all tissues (flowers, fruits, and leaves). In addition to 8MSOO Ae. arabicum leaves and fruits also contained the Met-derived 3MSOP (3-methylsulfinylpropyl, C11H21NO10S3), 3MTP (3-methylthiopropyl, C11H21NO9S3) GS and the indolic tryptophane-derived I3M (indolyl-3-methyl, C16H20N2O9S2), 4MOI3M (4-hydroxy-indolyl-3-methyl, C17H22N2O10S2), 4OHI3M (4-methoxy-indolyl-3-methyl, C17H21N2O10S2), and 1MOI3M (1-methoxy-indolyl-3-methyl, C17H22N2O10S2) GS (Figure 2). Thus, compounds differ both in chain-length elongation and in side-chain modifications with a different number of oxygen and sulfur atoms creating sulfinylalkyls, sulfonylalkyls, and thioalkyls for aliphatic GS and adding methoxy- groups to the indolic GS. The greatest variety of compounds was found in the early developing leaves and fruits of TUR (Figures 2B,C), although this variation decreased through time in the leaves.
FIGURE 2

Time course of glucosinolate (GS) composition of different tissues of Aethionema arabicum accessions CYP and TUR. Shown are the averages and standard deviations. Bars and points with standard deviations have a sample size of n = 3. Bars and points without standard deviations were from pooled tissue (hence n = 1). All y-axes have a different scale. Numbers in brackets are total GS content in umol/gram dry weight. (A) Seed and flower GS. (B) Fruit GS. I = immature fruit, M = Mature fruit. Numbers of the abbreviations along the x-axis are the weeks from the start of the experiment. (C) Leaf GS: for every line (CYP or TUR) the top graph are the aliphatic GS and the bottom the indolic GS. Highlighted are the number of weeks after which plants start budding (blue) or are in full bloom (pink). (D) Ratio of long versus short aliphatic glucosinolates (GS). The ratio is calculated as the sum of all C7 and C8 GS divided by all C3 GS. The x-axis shows the tissues (L = leaves, I = immature fruits, M = mature fruits, F = flower, Seeds = ripened seeds). Numbers following the abbreviations are the weeks after the start of the experiment. Vertical dotted lines divide the graph into the different tissues.
Differences between the ratio of different GS compounds can be a valuable method to examine differences between genotypes (
QTL Analyses
To understand the genetic regulation of GS in Ae. arabicum we investigated the GS profiles and identified the genomic locations underlying the GS phenotype in Ae. arabicum leaves, fruits and seeds from RILs and their parental lines TUR and CYP. In addition to single-trait QTL analyses we also applied multi-trait and multi-environment QTL analyses to assess the effects of the QTLs on the different compounds and on the different tissues.
The leaf and fruit samples of the RILs were taken after budding or even during flowering and contain only 3MSOP, 3MTP, 8MSOO, 4OHI3M, and I3M. The segregation spectrum of the RILs was similar for most GS whether they were isolated from leaves, fruits or seeds (Supplementary Figure S2). However, the GS concentrations depended on the particular compound and tissue, with indolic GS being lower than aliphatic GS (Supplementary Figure S2). While the distribution of the GS concentrations of RIL lines were more mostly intermediate between the parental values, in particular for seed GS concentrations differed for some compounds between RIL and parental lines (Supplementary Figure S2).
For the single-trait single-environment analysis, we found six different QTLs on four different linkage groups Q5.1 on LG5, Q6.1 and Q6.2 on LG6, Q8.1 and Q8.2 on LG8 and Q10.1 on LG10 (Table 1). Three of the QTLs (Q6.1, Q6.2, and Q8.2) also occur in the multi-trait and multi-environment QTL analyses (Table 2 and Supplementary Table S2). Q8.2 is a major QTL throughout all our analyses. The single-trait single-environment analysis shows a QTL for the indolic 4OHI3M. However, this peak is not present in the multi-environment QTL analysis (Supplementary Table S2).
Table 1
| Tissue | GSa | QTLb | Marker | Position (cM)c | Lower–Upperd | -Log10(p) | AEe | SEf | PVE (%)g |
|---|---|---|---|---|---|---|---|---|---|
| Leaf | 3MSOP | Q8.2 | S44_973817 | 151.0 | 131.92–167.72 | 4.57 | 0.55 | 0.12 | 16.41 |
| Leaf | 3MTP | Q8.2 | S44_827783 | 153.9 | 143.57–164.25 | 7.99 | 1.99 | 0.317 | 28.34∗ |
| Leaf | 8MSOO | Q6.2 | S40_550522 | 78.8 | 61.78–95.83 | 6.26 | 0.40 | 0.075 | 19.44 |
| Leaf | 8MSOO | Q8.2 | S44_609479 | 158.1 | 121.15–167.72 | 4.36 | 0.32 | 0.075 | 12.44 |
| Leaf | A/I | Q10.1 | S61_1993061 | 124.5 | 85.19–160.54 | 3.54 | 5.73 | 1.52 | 12.12 |
| Leaf | A/I | Q8.2 | S44_827783 | 153.9 | 123.08–167.72 | 4.28 | 6.06 | 1.43 | 13.55 |
| Leaf | All GS | Q8.2 | S44_609479 | 158.1 | 147.14–167.72 | 7.5 | 2.95 | 0.49 | 27.13∗ |
| Fruit | 3MSOP | Q8.2 | S44_973817 | 151.0 | 140.99–160.92 | 8.26 | 2.98 | 0.46 | 30.74∗ |
| Fruit | 3MTP | Q6.2 | S58_8426 | 72.8 | 30.92–114.76 | 4.48 | 1.78 | 0.41 | 12.43 |
| Fruit | 3MTP | Q8.2 | S44_827783 | 153.9 | 139.37–167.72 | 7.3 | 2.42 | 0.41 | 22.92 |
| Fruit | 8MSOO | Q8.2 | S44_827783 | 153.9 | 145.97–161.85 | 10.36 | 3.34 | 0.448 | 37.12∗ |
| Fruit | 4OHI3M | Q5.1 | S53_4972590 | 25.0 | 0–71.94 | 4.07 | 0.42 | 0.10 | 11.94 |
| Fruit | 4OHI3M | Q8.2 | S44_827783 | 153.9 | 141.47–166.35 | 7.62 | 0.61 | 0.10 | 25.78∗ |
| Fruit | All GS | Q6.2 | S58_8426 | 72.8 | 0–129.44 | 4.64 | 4.4 | 0.99 | 10.28 |
| Fruit | All GS | Q8.2 | S44_827783 | 153.9 | 145.39–162.43 | 11.68 | 8.12 | 0.99 | 34.99∗ |
| Seed | 3MSOOP | Q8.1 | S81_435439 | 7.9 | 0.73–58.6 | 7.89 | 3.74 | 0.871 | 10.53 |
| Seed | 3MSOOP | Q8.2 | S44_827783 | 153.9 | 143.48–164.34 | 9.34 | 5.96 | 0.87 | 26.81∗ |
| Seed | 7MSOH | Q6.1 | S5_745413 | 16.6 | 0.0–41.18 | 5.62 | 0.15 | 0.03 | 14.6 |
| Seed | 7MSOH | Q8.2 | S44_973817 | 151 | 139.57–162.35 | 8.81 | 0.2 | 0.03 | 24.99∗ |
| Seed | 8MSOO | Q8.2 | S44_973817 | 151 | 140.04–161.88 | 7.57 | 6.37 | 1.06 | 25.84∗ |
| Seed | All GS | Q8.2 | S44_973817 | 153.9 | 146–161.83 | 10.17 | 33.7 | 1.79 | 13.03 |
Significant QTLs from single trait analyses in Aethionema arabicum TURxCYP recombinant inbred lines.
aGlucosinolate compound; A/I, ratio Aliphatic/Indolic; bQTL; the first number corresponds to the linkage group; cposition along linkage group in centimorgan; dlower and upper bound op QTL from Genstat; eadditive effect. Negative effects are from CYP, positive from TUR, Negative or positive effect means that the CYP or TUR allele has a stronger effect. fStandard error of additive effect; gpercentage of explained variance. ∗Major QTL (PVE ≥ 25%, after
Table 2
| QTL | Marker | Tissue | LGa | Position (cM)b | -Log(p) | GSc | PVE %d |
|---|---|---|---|---|---|---|---|
| Q6.1 | S5_745413 | Leaf | 6 | 16.57 | 4.34 | 3MTP 8MSOO | 3.6 5.9 |
| Q6.2 | S40_63849 | Leaf | 6 | 74.62 | 5.66 | 3MTP 8MSOO I3M | 4.0 15.5 6.9 |
| Q8.2 | S44_827783 | Leaf | 8 | 153.91 | 9.25 | 3MSOP 3MTP 8MSOO I3M | 14.9 24.3 7.4 3.8 |
| Q6.2 | S40_63849 | Fruit | 6 | 74.62 | 5.05 | 3MSOP 3MTP 8MSOO 4OHI3M | 6.4 12.9 3.6 4.3 |
| Q8.2 | S44_827783 | Fruit | 8 | 153.91 | 17.26 | 3MSOP 3MTP 8MSOO 4OHI3M | 24.0 24.4 34.1∗ 26.8∗ |
| Q6.1 | S5_745413 | Seed | 6 | 16.57 | 9.28 | 7MSOH 8MSOO | 16.8 6.6 |
| Q2.1 | S13_476613 | Seed | 2 | 167.30 | 7.56 | 3MSOOP 7MSOH | 3.0 3.5 |
| Q8.1 | S93_383588 | Seed | 8 | 11.54 | 4.14 | 3MSOOP | 7.2 |
| Q8.2 | S44_827783 | Seed | 8 | 153.91 | 10.54 | 3MSOOP 7MSOH 8MSOO | 26.6∗ 25.7∗ 18.5 |
Significant QTLs from multi trait analyses in Aethionema arabicum TURxCYP recombinant inbred lines.
The percentage of variability explained is shown for every GS compound that had a significant (α ≤ 0.05) interaction with the QTL.
aLinkage group; bmarker position in centimorgans; csignificant glucosinolate compounds (α ≥ 0.05); dpercentage of variance explained. ∗Major QTL (PVE ≥ 25%, after
The multi-trait single environment analysis shows that 4OHI3M is only significantly affected by the fruit QTLs (Figure 3). The indolic I3M significantly contributes to Q8.2 in the leaves (Figure 3). The multi-trait QTL (Figure 3) shows that aliphatic GS in all tissues significantly contribute to Q8.2. There is a difference in contribution between 3MSOP in leaves and fruits: while 3MSOP has a significant contribution with both QTLs in fruits there is only the significant contribution with Q8.2 in leaves (Figure 3). 3MTP however has a significant contribution with all the QTLs in leaves. Hence, the occurrence of 3MTP or 3MSOP seems to be tissue specific. Moreover, compared to leaves and fruits, seeds have two unique loci: Q2.1 and Q8.1.
FIGURE 3

Additive effect of QTLs from a multi-trait QTL analysis for different glucosinolates (GS) from different tissues of Aethionema arabicum. Shown are the Linkage Groups (numbers above the x-axis) with lines in them for the QTL. The middle line is always the main locus; the other two are its closest markers. Positive effects are from the TUR allele, and negative values from the CYP allele. Points represent the tissues (different shapes) and GS compounds (different colors, see legend at bottom of figure) with their standard error (gray whiskers). QTL with a significant (P < 0.05) effect on the GS are denoted with an asterisk. Blue bars along the linkage groups represent the QTL position and candidate genes. All points belonging to the same QTL are off-set for visibility.
The multi-trait (Figure 3) and multi-environment (Supplementary Table S2) analyses both show a large effect from the TUR allele for Q6.2 and Q8.2 in leaves and seeds, and for Q6.2 in leaves and fruits. However, Q2.1 in seeds (for 7MSOH and 8MSOO) had a large effect from the CYP allele. Q8.2 had a large effect from the CYP allele for the indolic GS, which was also the case for leaf Q6.1 (Figure 3). The combination of the low GS levels for TUR compared to CYP and the large effect of the TUR allele on the QTLs suggests that these QTLs could be inhibitors of GS synthesis.
As leaves and fruits contain the same compounds, we used a multi-environment QTL analyses to assess the effect of the QTLs on the tissues for every compound separately. In addition to the already shown QTLs of the single trait single environment analysis and the multi-trait single environment analysis, the multi-environment single trait analysis identified three new QTLs: Q1.1, Q3.1, and Q8.3 (Supplementary Table S2). This comparison shows that the QTLs are significantly correlated mainly in fruits. An exception to this is 3MTP where both leaves and fruits are significantly correlated with the QTLs.
Using the homology and synteny between A. thaliana and Ae. arabicum of GS pathway genes (
Eight out of the 15 genes within the 58 kB interval had SNPs within the transcriptomes (mRNAs) of Mohammadin et al. (submitted; Supplementary Table S3). Although SULTR2;1 has SNPs in this transcriptome dataset, we only identified a single SNP in FLC according to our cut-off values (there was one SNP in FLC with GQ = 39, our cut-off was GQ ≥ 40). However, the QTL effect could instead be caused by upstream regulatory differences.
Discussion
Here, we present the correlation between the reproductive phase change and the composition of defense compounds in the annual Brassicaceae Ae. arabicum. Although the GS pathway has been extensively studied in A. thaliana, the information from a phylogenetically distant crucifer may elucidate alternative regulators of the glucosinolate pathway. We show that the major genomic location (Q8.2) associating with GS variation contains 15 genes, among which are the sulfur transporter SULTR2;1 and the FLOWERING TIME LOCUS C (FLC), genes that are not yet reported to be directly involved in the GS biosynthesis pathway. Interestingly, the faster flowering ecotype (CYP) also has the higher constitutive glucosinolate content, which is contrast to the prevailing model of defense and fitness allocation costs.
Glucosinolates type and quality changes throughout the development of two Ae. arabicum individuals. This is most clearly seen in CYP where between the onset of budding and full-bloom there is an increase in aliphatic GS (Figure 2 and Supplementary Figure S1). Moreover both in CYP and TUR the level of GS decreases after flowering (Figure 2 and Supplementary Figure S1). Combining the change in GS throughout Ae. arabicum’s development and the large difference of GS concentration found between CYP and TUR strongly suggests some regulatory factor(s) other than the known genes involved in the GS biosynthesis pathway. The multi-trait and multi-environment QTL analyses indeed show one major QTL (Q8.2) explaining up to 37% of the variation between the RILs (Table 1). Preliminary fine mapping this region indicated 15 genes, including the intriguing candidates the sulfate transporter SULTR2;1 and FLOWERING TIME LOCUS C (FLC, one of the MADS-box transcription factors that regulated flowering in Brassicaceae (
The importance of sulfur for GS and its locality under our major QTL might indicate an indirect relation between sulfur transport and GS formation. SULTR2;1 is involved in the root to shoot sulfate transport (
Plant defense and the transition from a vegetative to a generative life stage can have an effect on one another. For example, the biosynthesis of GS can reduce fitness in A.thaliana (
Aethionema arabicum ripened seeds, from CYP as well as from TUR, have lower GS diversity than Ae. arabicum fresh leaves. This differs from other crucifers, e.g., A. thaliana, Brassica oleracea and B. napus, where the GS diversity and concentration are the highest in the seeds and decrease in the following order in the inflorescence, siliques, leaves and roots (
The two parental ecotypes used here (CYP and TUR) had a 10-fold difference in GS concentrations in the fruits and twofold difference concentration in leaves, with the earlier-flowering CYP genotype always having the higher aliphatic GS concentration (Figure 2). These differences seem to reflect the extremes found in other Brassicaceae species. For example Italian horseradish (Armoracia rusticana) roots can differ up to twenty times in GS concentration depending on the accession (
The different tissues of Ae. arabicum all show a skewed ratio of long- versus short-chain GS and different side chain modifications. A similar pattern has been shown in A. thaliana, where ecotypes with higher amounts of C3 GS had lower C8 to C7 ratios (
Our Ae. arabicum lines show that a during the transition from vegetative tissue to generative tissue correlates with a transition in GS content. Also, we consistently find that the early flowering CYP genotype has a higher constitutive GS content than the later flowering TUR genotype. QTL analyses for GS content of three different tissues all point to one major QTL containing two potential candidates SULTR2;1 and FLC. Future gene expression analysis, transformation experiments, fine mapping and phenotyping of more accessions could help to understand whether and if so in which way these genes and traits are involved in the plants defense pathway. Although the focus of our research has mainly been a genetic one, future research should also focus on the effect of the GS biosynthesis pathway on herbivores and herbivory.
Statements
Author contributions
SM conducted the GS through development experiment, did all the analyses and wrote the paper. T-PN revised the manuscript and helped with the QTL analyses. MvW conducted the QTL experiments. MR performed the GS analyses and revised the manuscript. MS led the experiments and revised the paper and figures.
Funding
This work was supported by the grants from NWO Vernieuwings Impuls VIDI (Grant number: 864.10.001) and (849.13.004), the latter as part of the ERA-CAPS “SeedAdapt” consortium project (www.seedadapt.eu).
Acknowledgments
We thank A. M. Houtkooper with his help to fine-tune the figures and M. de Geus, P. Bulankova, and A. Waheed for providing the drawing of A. thaliana and the photographs of Figure 1.
Conflict of interest
The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
Supplementary material
The Supplementary Material for this article can be found online at: http://journal.frontiersin.org/article/10.3389/fpls.2017.00876/full#supplementary-material
TABLE S1Average glucosinolate values of Aethionema arabicum lines TUR and CYP leaves and their standard deviations. The numbers after the tissues are number of weeks after start of experiment.
TABLE S2Significant QTLs from multi environment analyses in Aethionema arabicum TURxCYP recombinant inbred lines.
TABLE S3Arabidopsis thaliana homologs of Aethionema arabicum genes in the interval of the major Q8.2 and the fine-mapping details.
References
1
AarabiF.KusajimaM.TohgeT.KonishiT.GigolashviliT.TakamuneM.et al (2016). Sulfur deficiency–induced repressor proteins optimize glucosinolate biosynthesis in plants.Sci. Adv.21–18. 10.1126/sciadv.1601087
2
AgnetaR.MöllersC.De MariaS.RivelliA. R. (2014). Evaluation of root yield traits and glucosinolate concentration of different Armoracia rusticana accessions in Basilicata region (southern Italy).Sci. Hortic. (Amsterdam).170249–255. 10.1016/j.scienta.2014.03.025
3
BeekweelderJ.van LeeuwenW.van DamN. M.BertossiM.GrandiV.MizziL.et al (2008). The impact of the absence of aliphatic glucosinolates on insect herbivory in Arabidopsis.PLoS ONE3:e2068. 10.1371/journal.pone.0002068
4
BibalaniG. H. (2012). Investigation on flowering phenology of Brassicaceae in the Shanjan region Shabestar district, NW Iran (usage for honeybees).Ann. Biol. Res.61958–1968.
5
BouchéF.WoodsD.AmasinoR. M. (2016). Winter memory throughout the plant kingdom: different paths to flowering.Plant Physiol.173127–135.
6
BromanK. W.WuH.SenChurchillG. A. (2003). R/qtl: QTL mapping in experimental crosses.Bioinformatics19889–890. 10.1093/bioinformatics/btg112
7
BrownP. D.TokuhisaJ. G.ReicheltM.GershenzonJ. (2003). Variation of glucosinolate accumulation among different organs and developmental stages of Arabidopsis thaliana.Phytochemistry62471–481. 10.1016/S0031-9422(02)00549-6
8
BurkeJ. M.TangS.KnappS. J.RiesebergL. H. (2002). Genetic analysis of sunflower domestication.Genetics1611257–1267.
9
BurowM.MüllerR.GershenzonJ.WittstockU. (2006). Altered glucosinolate hydrolysis in genetically engineered Arabidopsis thaliana and its influence on the larval development of Spodoptera littoralis.J. Chem. Ecol.322333–2349. 10.1007/s10886-006-9149-1
10
DengW.YingH.HelliwellC. A.TaylorJ. M.PeacockW. J.DennisE. S. (2011). FLOWERING LOCUS C (FLC) regulates development pathways throughout the life cycle of Arabidopsis.Proc. Natl. Acad. Sci.U.S.A. 1086680–6685. 10.1073/pnas.1103175108
11
EdgerP. P.Heidel-FischerH. M.BekaertM.RotaJ.GlöcknerG.PlattsA. E.et al (2015). The butterfly plant arms-race escalated by gene and genome duplications.Proc. Natl. Acad. Sci.U.S.A.1128362–8366. 10.1073/pnas.1503926112
12
FalkK. L.TokuhisaJ. G.GershenzonJ. (2007). The effect of sulfur nutrition on plant glucosinolate content: physiology and molecular mechanisms.Plant Biol.9573–581. 10.1055/s-2007-965431
13
FrerigmannH.GigolashviliT. (2014). MYB34, MYB51, and MYB122 distinctly regulate indolic glucosinolate biosynthesis in Arabidopsis thaliana.Mol. Plant7814–828. 10.1093/mp/ssu004
14
GigolashviliT.KoprivaS. (2014). Transporters in plant sulfur metabolism.Front. Plant Sci.5:442. 10.3389/fpls.2014.00442
15
HalkierB. A.GershenzonJ. (2006). Biology and biochemistry of glucosinolates.Annu. Rev. Plant Biol.57303–333. 10.1146/annurev.arplant.57.032905.105228
16
HaudryA.PlattsA. E.VelloE.HoenD. R.LeclercqM.WilliamsonR. J.et al (2013). An atlas of over 90,000 conserved noncoding sequences provides insight into crucifer regulatory regions.Nat. Genet.45891–898. 10.1038/ng.2684
17
HiraiM. Y.SugiyamaK.SawadaY.TohgeT.ObayashiT.SuzukiA.et al (2007). Omics-based identification of Arabidopsis Myb transcription factors regulating aliphatic glucosinolate biosynthesis.Proc. Natl. Acad. Sci. U.S.A.1046478–6483. 10.1073/pnas.0611629104
18
HofbergerJ. A.LyonsE.EdgerP. P.Chris PiresJ.Eric SchranzM. (2013). Whole genome and tandem duplicate retention facilitated glucosinolate pathway diversification in the mustard family.Genome Biol. Evol.52155–2173. 10.1093/gbe/evt162
19
HopkinsR. J.van DamN. M.van LoonJ. J. A. (2009). Role of glucosinolates in insect-plant relationships and multitrophic interactions.Annu. Rev. Entomol.5457–83. 10.1146/annurev.ento.54.110807.090623
20
HualaE.DickermanA. W.Garcia-HernandezM.WeemsD.ReiserL.LafondF.et al (2001). The Arabidopsis information resource (TAIR): a comprehensive database and web-based information retrieval, analysis, and visualization system for a model plant.Nucleic Acids Res.29102–105. 10.1093/nar/29.1.102
21
IetswaartR.WuZ.DeanC. (2012). Flowering time control: another window to the connection between antisense RNA and chromatin.Trends Genet.28445–453. 10.1016/j.tig.2012.06.002
22
JensenL. M.JepsenH. S. K.HalkierB. A.KliebensteinD. J.BurowM. (2015). Natural variation in cross-talk between glucosinolates and onset of flowering in Arabidopsis.Front. Plant Sci.6:697. 10.3389/fpls.2015.00697
23
KliebensteinD. J. (2004). Secondary metabolites and plant/environment interactions: a view through Arabidopsis thaliana tinged glasses.Plant Cell Environ.27675–684. 10.1111/j.1365-3040.2004.01180.x
24
KliebensteinD. J.GershenzonJ.Mitchell-OldsT. (2001a). Comparative quantitative trait loci mapping of aliphatic, indolic and benzylic glucosinolate production in Arabidopsis thaliana leaves and seeds.Genetics159359–370.
25
KliebensteinD. J.KroymannJ.BrownP.FiguthA.PedersenD.GershenzonJ.et al (2001b). Genetic control of natural variation in Arabidopsis glucosinolate accumulation.Plant Physiol.126811–825. 10.1104/pp.126.2.811
26
KliebensteinD. J.LambrixV. M.ReicheltM.GershenzonJ.Mitchell-OldsT. (2001c). Gene duplication in the diversification of secondary metabolism: tandem 2-oxoglutarate–dependent dioxygenases control glucosinolate biosynthesis in Arabidopsis.Plant Cell13681–693.
27
KnillT.SchusterJ.ReicheltM.GershenzonJ.BinderS. (2008). Arabidopsis branched-chain aminotransferase 3 functions in both amino acid and glucosinolate biosynthesis.Plant Physiol.1461028–1039. 10.1104/pp.107.111609
28
KorolevaO. A.DaviesA.DeekenR.ThorpeM. R.TomosA. D.HedrichR. (2000). Different myrosinase and ideoblast distribution in Arabidopsis and Brassica napus.Plant Physiol.1271750–1763.
29
KusznierewiczaB.IoriR.PiekarskaA.NamiesnikJ.BartoszekA. (2013). Convenient identification of desulfoglucosinolates on the basis of mass spectra obtained during liquid chromatography–diode array–electrospray ionization mass spectrometry analysis: method verification for sprouts of different Brassicaceae species extracts.J. Chromatogr. A1278108–115. 10.1016/j.chroma.2012.12.075
30
LenserT.GraeberK.CevikÖ. S.AdigüzelN.DönmezA. A.KettermannM.et al (2016). Aethionema arabicum as a model system for studying developmental control and plasticity of fruit and seed dimorphism.Plant Physiol.1721691–1707. 10.1104/pp.16.00838
31
LiJ.HansenB. G.OberJ. A.KliebensteinD. J.HalkierB. A. (2008). Subclade of flavin-monooxygenases involved in aliphatic glucosinolate biosynthesis.Plant Physiol.1481721–1733. 10.1104/pp.108.125757
32
LyonsE.FreelingM. (2008). How to usefully compare homologous plant genes and chromosomes as DNA sequences.Plant J.53661–673. 10.1111/j.1365-313X.2007.03326.x
33
MagrathR.BanoF.MorgnerM.ParkinI.SharpeA.ListerC.et al (1994). Genetics of aliphatic glucosinolates. I. Side chain elongation in Brassica napus and Arabidopsis thaliana.Heredity (Edinb).72290–299. 10.1038/hdy.1994.39
34
MalikM. S.RileyM. B.NorsworthyJ. K.BridgesW. (2010). Variation of glucosinolates in wild radish (Raphanus raphanistrum) accessions.J. Agric. Food Chem.5811626–11632. 10.1021/jf102809b
35
ManoY.NemotoK. (2012). The pathway of auxin biosynthesis in plants.J. Exp. Bot.632853–2872. 10.1093/jxb/ers091
36
ManzanedaA. J.PrasadK. V. S. K.Mitchell-OldsT. (2010). Variation and fitness costs for tolerance to different types of herbivore damage in Boechera stricta genotypes with contrasting glucosinolate structures.New Phytol.188464–477. 10.1111/j.1469-8137.2010.03385.x
37
MateosJ. L.MadrigalP.TsudaK.RawatV.RichterR.Romera-BranchatM.et al (2015). Combinatorial activities of SHORT VEGETATIVE PHASE and FLOWERING LOCUS C define distinct modes of flowering regulation in Arabidopsis.Genome Biol.16:31. 10.1186/s13059-015-0597-1
38
Olson-ManningC. F.StrockC. F.Mitchell-OldsT. (2015). Flux control in a defense pathway in Arabidopsis thaliana is robust to environmental perturbations and controls variation in adaptive traits.G352421–2427. 10.1534/g3.115.021816
39
PayneR. W.MurrayD. A.HardingS. A.BairdD. B.SoutarD. M. (2009). GenStat for Windows, 12th Edn. Hemel Hempstead: VSN International.
40
PetersenB. L.ChenS.HansenC. H.OlsenC. E.HalkierB. A. (2002). Composition and content of glucosinolates in developing Arabidopsis thaliana.Planta214562–571. 10.1007/s004250100659
41
PiotrowskiM.SchemenewitzA.LopukhinaA.MüllerA.JanowitzT.WeilerE. W.et al (2004). Desulfoglucosinolate sulfotransferases from Arabidopsis thaliana catalyze the final step in the biosynthesis of the glucosinolate core structure.J. Biol. Chem.27950717–50725. 10.1074/jbc.M407681200
42
RedovnikovicI. R.GliveticT.DelongaK.Vorkapic-FuracJ. (2008). Glucosinolates and their potential role in plant.Period. Biol.110297–309.
43
RohrF.UlrichsC.MewisI. (2009). Variability of aliphatic glucosinolates in Arabidopsis thaliana (L.)-Impact on glucosinolate profile and insect resistance.J. Appl. Bot. Food Qual.82131–135.
44
SchranzE. M.ManzanedaA. J.WindsorA. J.ClaussM. J.Mitchell-OldsT. (2009). Ecological genomics of Boechera stricta: identification of a QTL controlling the allocation of methionine- vs. branched chain amino acid- derived glucosinolates and levels of insect herbivory.Heredity102465–474. 10.1038/hdy.2009.12
45
SchranzM. E.MohammadinS.EdgerP. P. (2012). Ancient whole genome duplications, novelty and diversification: the WGD Radiation Lag-Time Model.Curr. Opin. Plant Biol.15147–153. 10.1016/j.pbi.2012.03.011
46
SønderbyI. E.Geu-FloresF.HalkierB. A. (2010). Biosynthesis of glucosinolates - gene discovery and beyond.Trends Plant Sci.15283–290. 10.1016/j.tplants.2010.02.005
47
SoteloT.SoengasP.VelascoP.RodriguezV. M.CarteaM. E. (2014). Identification of metabolic QTLs and candidate genes for glucosinolate synthesis in Brassica oleracea leaves, seeds flower buds.PLoS ONE9:e91428. 10.1371/journal.pone.0091428
48
Van ZandtP. A. (2007). Plant defense, growth, and habitat: a comparative assessment of constitutive and induced resistance.Ecology881984–1993. 10.1890/06-1329.1
49
VelascoP.SoengasP.VilarM.CarteaM. E.del RioM. (2008). Comparison of glucosinolate profiles in leaf and seed tissues of different Brassica napus crops.J. Am. Soc. Hortic. Sci.133551–558.
50
Velchev. (2015). “Plants,” inRed Data Book of the PR BulgariaVol. 1ed.VelchevV. (Sofia: Publishing House Bulgarian Academy of Sciences).
51
WeiZ.JulkowskaM. M.LaloëJ. O.HartmanY.de BoerG. J.MichelmoreR. W.et al (2014). A mixed-model QTL analysis for salt tolerance in seedlings of crop-wild hybrids of lettuce.Mol. Breed.341389–1400. 10.1007/s11032-014-0123-2
52
WindsorA. J.ReicheltM.FiguthA.SvatošA.KroymannJ.KliebensteinD. J.et al (2005). Geographic and evolutionary diversification of glucosinolates among near relatives of Arabidopsis thaliana (Brassicaceae).Phytochemistry661321–1333. 10.1016/j.phytochem.2005.04.016
Summary
Keywords
glucosinolates, development, QTL, Brassicaceae, Aethionema, multi-trait analyses
Citation
Mohammadin S, Nguyen T-P, van Weij MS, Reichelt M and Schranz ME (2017) Flowering Locus C (FLC) Is a Potential Major Regulator of Glucosinolate Content across Developmental Stages of Aethionema arabicum (Brassicaceae). Front. Plant Sci. 8:876. doi: 10.3389/fpls.2017.00876
Received
17 February 2017
Accepted
10 May 2017
Published
26 May 2017
Volume
8 - 2017
Edited by
Marion S. Röder, Institute of Plant Genetics and Crop Plant Research (LG), Germany
Reviewed by
Meike Burow, University of Copenhagen, Denmark; Antonio J. Manzaneda, Universidad de Jaén, Spain
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© 2017 Mohammadin, Nguyen, van Weij, Reichelt and Schranz.
This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
*Correspondence: Michael E. Schranz, eric.schranz@wur.nl
This article was submitted to Plant Genetics and Genomics, a section of the journal Frontiers in Plant Science
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