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Article

Comparative Analysis of the Expression of Genes Involved in Fatty Acid Synthesis Across Camelina Varieties

by
Elisa Gómez
1,
Gregorio Hueros
2,
David Mostaza-Colado
1,*,
Aníbal Capuano
3,
Mercedes Uscola
4,5 and
Pedro V. Mauri
1
1
Agro-Environmental Research Area, Madrid Institute for Rural, Agricultural, and Food Research and Development (IMIDRA), El Encín, A-2 Highway, Km. 38.200, Alcalá de Henares, 28805 Madrid, Spain
2
Department of Biomedicine and Biotechnology, Genetics Area, Cellular Biology and Genetics Building, University of Alcalá (UAH), Alcalá de Henares, 28805 Madrid, Spain
3
Camelina Company España S.L., Camino de la Carrera 11, Fuente el Saz de Jarama, 28140 Madrid, Spain
4
Department of Biology and Geology, Physics and Inorganic Chemistry, Rey Juan Carlos University, C/Tulipán s/n, Móstoles, 28933 Madrid, Spain
5
Institute for Research on Global Change (IICG-URJC), Rey Juan Carlos University, C/Tulipán s/n, Móstoles, 28933 Madrid, Spain
*
Author to whom correspondence should be addressed.
Agriculture 2025, 15(12), 1305; https://doi.org/10.3390/agriculture15121305
Submission received: 23 April 2025 / Revised: 6 June 2025 / Accepted: 9 June 2025 / Published: 17 June 2025
(This article belongs to the Special Issue Crop Yield Improvement in Genetic and Biology Breeding)
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Abstract

:
Camelina sativa (L.) Crantz, a native European oilseed crop of the Brassicaceae family, is notable for its short life cycle, making it well-suited for crop rotation and diversification. Its seeds contain a high content of oil (36–47%) that is rich in polyunsaturated fatty acids (PUFAs) such as alpha-linolenic acid (ALA, C18:3, Ω-3) and linoleic acid (LA, C18:2, Ω-6). This oil has diverse industrial applications, including low-emission biofuels, animal feed, pharmaceuticals, biolubricants, bioplastics, and cosmetics. We analyzed the expression of seven key enzymes involved in fatty acid biosynthesis across nine C. sativa accessions at three stages of silique development using highly efficient qRT-PCR assays designed for the target genes and a normalizing control. Our detailed expression analysis revealed significant variation across varieties, with only the gene FAB2c exhibiting genotype-independent expression, indicating a constitutive and essential role in monounsaturated fatty acid (MUFA) biosynthesis. Other genes showed significant interactions between the variety and developmental stage, highlighting the combined influences of genetic background and silique maturation on gene regulation. V18 emerges as particularly promising, exhibiting elevated expression of genes linked to PUFA and VLCFA biosynthesis—traits of significance for food, biofuel, and industrial applications. These findings, together with the developed qRT-PCR assays, provide valuable tools for selecting Camelina varieties with optimized genetic profiles, highlighting the potential of harnessing natural transcriptional diversity for crop improvement.

1. Introduction

Camelina sativa (L.) Crantz, also known as false flax, is a relict oil crop from the Brassicaceae family. It is native to Europe and southwest Asia and was introduced to America and Canada as a flax contaminant. The genetic diversity of this crop originates from Ukraine and Russia [1,2]. The cultivation of camelina dates back to the late Neolithic and early Bronze Age, with its oil used for lamps, body care, and food in the Roman Empire. It was used as a fuel until 1940, when it was replaced by more productive crops [3,4,5]. Currently, camelina is grown on over 10,000 hectares annually in Europe, with a significant portion in organic farming [5]. However, camelina can tolerate drought and biotic stresses and adapts well to poor soils. In the context of climate change, camelina crops can reduce fossil fuel use and greenhouse gas emissions, promoting sustainable agriculture that preserves ecosystems and biodiversity [6]. In addition, the straw can be used as mulch to prevent weed growth or pelletized for biomass production [7,8].
Camelina is an herbaceous annual plant with two biotypes: winter and spring [4,6]. This bushy plant grows as a rosette of leaves and later develops a stem with numerous leaves and branches. The inflorescence comprises pale yellow flowers approximately 5–7 mm in diameter [9]. The small, pear-shaped silique, measuring from 0.8 to 2 cm, has a 2–3 mm long tip and contains about 15 oval-shaped yellow seeds that turn dark brown upon maturation. C. sativa has an estimated genome size of ~782 Mb. Although it is currently a diploid species (2n = 40), it derived from the hybridization of three ancestral Camelina species and originated from allotetraploid and diploid subgenomes [1,4,10]. The hybridization of subgenomes occurred rapidly and recently, similar to oilseed rape, cotton, or wheat, during the expansion of agriculture 5–10,000 years ago, so that C. sativa retains some features of its hexaploid origin, such as the presence of three copies for most genes.
Camelina oil, traditionally used in folk medicine for treating wounds and burns [11], has recently gained interest for its oil composition, making it suitable for food, feed, and biofuel applications. It contains essential fatty acids (FAs), such as Ω-3 α-linolenic acid (ALA, C18:3, 25–35%) and Ω-6 linoleic acid (LA, C18:2, 17–24%), which are linked to reduced risks of coronary and inflammatory diseases [6,7]. The oil also includes oleic acid (18:1, 13–20%), eicosenoic acid (C20:1, 12–19%), and minor fatty acids like palmitic (C16:0, 5–7%), stearic (C18:0 0–3%), and erucic (C22:1 2.6–3.3%; [3]) acids. The level of erucic acid in the oil is much lower than that in other oilseeds, such as rapeseed oil (50%), except when compared to canola seed, which has been genetically selected for a low euric acid content [12]. Camelina oil contains a high percentage of unsaturated fatty acids (UFAs) (83–89%) and significant antioxidants like α-tocopherol (0.26–0.39 mg/kg), γ-tocopherol (0.26–0.39 mg/kg), and vitamin E (202–234 mg/kg), which enhance its stability against oxidative degeneration and increase its shelf life [4,13,14]. Additionally, its phytosterol composition, including β-sitosterol (9.72–48.11%), offers potential cancer prevention and anti-inflammatory benefits [7,15].
However, the FA composition of camelina oil is still amenable to substantial improvement since the crop has not undergone extensive breeding due to its abandonment in the last century. As a result, there is presently a very limited number of suitable cultivars.
Gene expression related to FA synthesis has been extensively studied in several plant species, including rapeseed, rice, olive, peanut, flax, and Arabidopsis thaliana, a phylogenetically close model species to Camelina sativa [16,17,18]. These studies encompass individual gene expression analyses and global studies using advanced techniques such as RNA-Seq [19,20]. However, few studies have explored the expression of these genes as a tool to identify varieties with potential for genetic improvement. The actual seed FA composition largely depends on the expression of genes encoding FA-modifying enzymes. Of particular interest for our study are desaturases, which introduce double bonds at specific positions along the hydrocarbon chain, forming MUFAs and PUFAs, and elongases, which add two carbon atoms to the hydrocarbon chain, extending the length of the fatty acid [12].
The present study focuses on several genes involved in the fatty acid composition (Figure 1): FAB1, FAB2 (FAB2a and FAB2c), ADS2, FAD2, FAD3, and FAE1 [17,21]. Fatty acid biosynthesis 1 (FAB1) is encoded in the chloroplasts and initiates the elongation of the carbon chain from palmitic acid (C16:0-ACP) to stearic acid (C18:0-ACP) [17,22,23]. These FAs can be subsequently modified by soluble enzymes such as palmitoyl-ACP desaturase (FAB2) and stearoyl-ACP desaturase (ADS2), which catalyze the formation of double bonds between the C9 and C10 carbon atoms in palmitic and stearic acid, respectively. Thus, they result in the production of the monounsaturated fatty acids (MUFAs) palmitoleic acid (C16:1 Δ9-ACP) and oleic acid (C18:1 Δ9-ACP).
MUFAs can be further unsaturated, producing PUFAs. Fatty acid desaturase 2 (FAD2) catalyzes the desaturation of oleic acid bound to phosphatidylcholine (PC), producing linoleic acid (LA) (C18:2 Δ9,12 or Ω-6). Fatty acid desaturase 3 (FAD3), in turn, converts linoleic acid into α-linolenic acid (ALA or Ω-3) (C18:3 Δ9,12,15) by the desaturation of linoleic acid bound to PC in the endoplasmic reticulum [17,22,24,25]. Finally, we analyzed the expression of fatty elongase 1 (FAE1), which is involved in the elongation of the carbon chain from oleic acid to VLCFAs. Mutations in FAE1 may increase the oleic acid content in seed triacylglycerols (TAGs) [17,26,27].
In this work, we analyzed the expression levels of seven genes coding for key enzymes involved in fatty acid biosynthesis throughout seed development in nine C. sativa varieties. Seven of these were chosen based on prior research that has provided valuable data, albeit not yet completed, on their fatty acid profiles [6,7]. cDNA was obtained from immature siliques at three developmental stages and three replicates (a, b, and c), grown at Finca El Encín (Alcalá de Henares, Madrid, Spain) of the Instituto Madrileño de Investigación y Desarrollo Rural, Agrario y Alimentario (IMIDRA). By analyzing gene expression through qRT-PCR, we identified differential gene expression patterns that point to accessions potentially best suited for the various agronomical or industrial applications of camelina oils. In addition, we developed precise and efficient qRT-PCR tests that can be used as molecular tools for future breeding programs. We hypothesize that the gene expression profiles of key fatty acid biosynthesis enzymes vary significantly among Camelina sativa varieties and developmental stages. This differential expression analysis will provide valuable molecular insights to support the selection of varieties with desirable traits for agronomic and industrial applications.

2. Materials and Methods

2.1. Plant Material and Experimental Design

Nine varieties (V1, V3, V7, V11, V14, V15, V16, V17, and V18) of Camelina sativa were grown under field conditions at El Encín (IMIDRA) during the 2023 season. The information regarding the selected varieties is subject to intellectual property protection and cannot be disclosed at this point. The field trial was conducted using a design (Figure 2) comprising four blocks, each containing one replicate of the nine Camelina varieties. This arrangement was implemented to control for spatial variability in the field, particularly with respect to soil heterogeneity and microclimatic differences. Although replications were not randomly assigned across the entire field (thus the design does not conform to a completely randomized design (CRD)), each block functioned as a spatial replicate, allowing for the control of field position effects.

2.2. Sample Collection

Three to five plants were selected from the 27 samples (9 varieties by 3 three replicates (a, b, and c)). Siliques were collected from all samples and, since the pollination date of each silique cannot be controlled, they were classified into three developmental stages based on the silique size: (1) early (S) for siliques less than 0.8 mm in length; (2) medium (M) for siliques between 0.8 and 1.3 mm in length; and (3) late (L) for siliques greater than 1.3 mm in length (Figure 3). Therefore, we simplified the methodology described in the Camelina Developmental Transcriptome Atlas to adapt it to our circumstances [28]. The siliques were immediately frozen in liquid nitrogen and stored at −80 °C until RNA extraction.

2.3. RNA Extraction and cDNA Synthesis

For RNA extraction, siliques were pooled according to their size (10 S, 4 M, or 2 L) for each sample. The frozen siliques were pulverized by vigorous shaking while preserving the freezing temperature in a TissueLyser machine (Qiagen, Barcelona, Spain), using 2 mL tubes containing 2 steel beads. The resulting powder was processed using the Promega Maxwell 16 LEV Plant RNA Kit (Promega, Madison, WI, USA). The RNA extraction procedure included a DNAse treatment to remove any genomic DNA contamination. The RNA was eluted in 50 µL of RNAse-free H2O; the concentration was measured in a Nanodrop spectrophotometer (Thermo Fisher Scientific, Wilmington, DE, USA) and adjusted to 200 ng/µL. RNA purity was assessed by measuring the absorbance at 230 nm, 260 nm, and 280 nm; RNA samples showed 260/280 ratios higher than 2 and 260/230 ratios higher than 2.2. RNA integrity was then evaluated by running 2 µg samples on denaturing 1.5% agarose gels. cDNA synthesis was performed using the PrimeScript™ Reagent Kit (Takara, Kusatsu, Japan) following the manufacturer’s recommendations in reactions containing 500 ng RNA in a final volume of 10 µL (Appendix A Table A1).

2.4. Candidate Gene Selection

Initially, we selected 13 candidate genes known to be involved in the fatty acid biosynthesis pathway (Figure 1), along with 2 housekeeping genes commonly used as internal reference controls. Given that C. sativa is an ancestral hexaploid species, we identified and analyzed the three homoeologous copies for each candidate gene to ensure comprehensive representation of gene function across subgenomes. We conducted an in silico expression analysis using the ePlant Camelina platform (Figure 4 and Appendix A Figure A1) (https://bar.utoronto.ca/eplant_camelina) (accessed on 29 November 2023), which provides gene expression data across various tissues and developmental stages [28]. Only genes that met the following criteria were retained for further analysis: (i) detectable expression in developing siliques, the target tissue of this study, and (ii) consistent expression across all three homoeologous copies, ensuring functional redundancy or complementarity in the hexaploid genome.
Based on these filtering criteria, 7 genes from the fatty acid biosynthesis pathway were selected for experimental validation by qRT-PCR. Additionally, ACT-7 was chosen as the normalizing gene due to its stable expression across developmental stages and tissues, as confirmed in previous Camelina studies. Gene sequences were retrieved from Ensembl Plants (https://plants.ensembl.org/Camelina_sativa) (accessed on 7 November 2023) for primer design and further analysis.

2.5. Primer Design

The cDNA sequences of the 3 copies of each gene were aligned, and conserved regions were selected for primer design. The primer design tool included in the Vector NTI version 11.5 software (Invitrogene, Waltham, MA, USA) was used for primer design. The software parameters were adjusted to identify primer pairs with a Tm of 58–60 °C and an amplicon size lower than 100 bp. Whenever possible, the primers selected for each gene (Appendix A Table A2) spanned one intron site to minimize amplification from contaminating genomic DNA in the cDNA preparations.
Due to sequence divergence among gene copies, it was not possible to design a reliable primer pair for FAB2b that would ensure specific and uniform amplification across all three homoeologous genes. Only genes with detectable expression in siliques and viable primer design across their copies were included in the qRT-PCR analysis.

2.6. qRT-PCR Analysis

We used 10 µL reactions containing 5 µL 2 × SYBR® Premix Ex Taq (Takara), 0.2 µM each primer, and approximately 10 ng of cDNA for real-time PCR quantitation. Reactions were run in a LightCycler96 real-time PCR machine (Roche, Mannheim, Germany) with the following program:
  • Preincubation at 95 °C, 120″;
  • Amplification for 40× (95 °C, 5″, ramp 4.4 °C/s; 60 °C, 30″, ramp 1 °C/s; fluorescence acquisition);
  • Melting from 60 °C to 97 °C continuously (4.4 °C/s).
For the initial qRT-PCR test validation, we tested each primer pair for specificity and sensitivity by running 10 µL qRT-PCR reactions using as a template a serial dilution of cDNA (1, 1:5, 1:25, 1:125, and 1:625; H2O). Standard curves were performed to calculate the efficiency of the primers from the serial dilutions of cDNA.

2.7. Data Analysis

The assays were conducted for the nine varieties at three silique developmental stages with three biological and two technical replicates. The relative expression level of each gene of interest was determined using the ∆∆Ct relative quantification method, using ACT-7 as a reference gene [29], and gene expression data were analyzed by calculating the Log2 fold change (Log2FC) values for each gene across all varieties and developmental stages. The fold change (FC) represents the ratio of gene expression levels relative to a reference sample (Sa-V1), which was used as the baseline in all comparisons.

2.8. Statistical Analysis

As linear models did not fit normality or homoscedasticity assumptions, the effects of the independent variables, varieties, and silique classes on the expression of each gene were analyzed with a generalized linear mixed-effects model using the function “glmer” of the package lme4 [30], and the sample ID was included as a random factor. When appropriate, multiple comparisons of means were adjusted using the Sidak method to control the family-wise error rate using the function “emmeans” from the package agricolae [31]. The Log2 gene expression was used to create a heatmap. Samples were grouped through clustering based on the Euclidean distance and complete linkage using the function “pheatmap” from the package pheatmap [32]. All analysis were carried out with R version 4.2.2 (31 October 2022) [33].

3. Results

RNA was extracted from the siliques of nine Camelina sativa varieties (V1, V3, V7, V11, V13, V15, V16, V17, and V18) with three replicates (a, b, and c) at three different stages of silique development, which were collected according to their size (early, intermediate, and late) (S, M, L), to assess the expression of genes involved in the fatty acid pathway. RNA quality was evaluated using gel electrophoresis (Appendix A Figure A2) and Nanodrop measurements (Appendix A Table A2).

3.1. Selection of Candidate Genes Based on Their in Silico Expression Pattern

The expression of the initial thirteen selected genes and two housekeeping genes involved in the fatty acid synthesis pathway was studied in silico. As camelina has a recent hexaploid origin, it is expected to have three copies (homoeologous) of each gene. We searched the camelina genome to identify such homologous genes, and their IDs were used for in silico expression pattern analyses at ePlant Camelina (Appendix A Figure A1). Only the genes that showed expression in siliques for all three copies were selected for analysis by qRT-PCR (Appendix A Figure A2). Therefore, we excluded the ADS1, FAD6, FAD7, FAD8, and SLD1 genes from our study because they either did not show expression in siliques or did not show expression in siliques for all three copies of each gene.

3.2. Primer Design

Primer pairs were successfully designed from the conserved regions of the three copies of each gene, as described in the ‘Section 2’. However, we could not proceed with FAB2b, as the alignment did not allow the design of suitable sense and antisense primers from the region shared by the three gene copies.
The performance of each qRT-PCR test was evaluated using serial (1:5) dilutions of cDNA, from 10 ng/reaction to 0.016 ng/reaction, as described in the ‘Section 2’. These analyses produced the ΔCT vs. Log(concentration) curves shown in Figure 5.
All the primer sets that were finally accepted showed an efficiency close to two and an R2 value close to one. This study ultimately focused on seven fatty acid synthesis genes and one housekeeping gene, which was used as an internal normalizer in the relative quantitation method used (ΔΔCt) [34].

3.3. Expresssion Analyses

The qRT-PCR profiles of seven Camelina sativa fatty acid synthesis genes were analyzed at different developmental stages of siliques (small, medium, and large). For each gene, the relative expression level in each sample was calculated as a function of the expression value for sample S1a from V1, which therefore acquired the expression value of one. The results are presented in Figure 6; bars represent relative expression levels and are dimensionless, with error bars representing the standard errors of the means.

3.3.1. ADS2

Although both the variety (χ2 = 266; p < 0.001) and silique class (χ2 = 13.9; p < 0.001) had significant effects, the effect of the variety was conditional on the silique class (interaction of variety × silique; χ2 = 26.7; p = 0.045). The highest expression levels were found in late siliques of V18 (silique L-V18) having almost 11 times higher expression than the lowest value in silique M-V11. V11 showed the lower expression values across all silique classes. Interestingly, silique development was not always correlated with increasing expression of the gene. For instance, in V3 the expression of the gene seemed to correlate negatively with the developmental stage.

3.3.2. FAB1

In general, the expression of FAB1 increased along silique development (χ2 = 6.37; p = 0.041). Across varieties (χ2 = 57.6; p < 0.001), the minimum values of FAB1 expression were found in V15 and V11, with the former being slightly higher. Maximum values were found in V17 and V18, but especially in V1. The difference between the lowest and highest values ranged six-fold. However, the differences across silique classes differed marginally among varieties (interaction of variety × silique; χ2 = 24.7; p = 0.076). In the varieties with the lowest (V15) and the highest (V1) FAB1 expression, differences across silique developmental stages were smaller, but silique development generated more differences in other varieties, especially in V17 and V18.

3.3.3. FAB2a

The effect of the silique developmental stage on gene expression was marginally different across varieties (interaction of variety × silique; χ2 = 23.8; p = 0.094). Minimum values of FAB2a expression were found in V15 independently of the developmental stage of siliques and in silique S of V11. Maximum values were found in the mature siliques of V18, which exhibited approximately a tenfold increase compared to V15 (χ2 = 53.6; p < 0.001). The remaining size classes of siliques across varieties had intermediate values, with siliques L having slightly higher values in V7, V16, and V17.

3.3.4. FAB2c

The expression of FAB2c was highest in silique L, intermediate in M, and lowest in S, and gene expression was almost four times less in this silique class than in the L class (χ2 = 98.5; p < 0.001). The effect of the silique development was consistent across varieties (no interaction of variety × silique; χ2 = 9.5; p = 0.89). Our results suggest that this gene is consistently activated in mid-late developmental stages, regardless of the variety examined. For this gene, the differences in the expression were minor with only 2.4-fold differences between the minimum and the maximum expression across varieties (χ2 = 57.6; p < 0.001). The expression of the FAB2c gene had minimum values in V11 and V16, while maximum values were found in V18 and V1.

3.3.5. FAD2

For FAD2, both the variety (χ2 = 115; p < 0.001) and silique development (χ2 = 27.3; p < 0.001) had significant effects. However, the expression of FAD2 depended on the developmental stage only in specific varieties (interaction of variety × silique; χ2 = 52.5; p < 0.001). Maximum values were found in the late developmental stage of V18, with values of expression about 17 times higher than the minimum value obtained, and to a minor extent, in V14 and V7.

3.3.6. FAD3

Similar to FAD2, the expression of FAD3 depended on the developmental stage of the siliques, but only in specific varieties (interaction of variety × silique; χ2 = 2669; p < 0.001), despite the individual significant effects of the silique class (χ2 = 260; p < 0.001) and variety (χ2 = 27.7; p < 0.001). The expression of this gene showed a variation of about 300-fold between the groups with minimum (L-V15) and maximum values (L-V18). Strikingly, the expression pattern of this gene along development seemed to depend strongly on the genotype, with varieties showing the highest expression level at the earliest (V1, V3, and V17) or later (V7, V16, and V18) developmental stages of the silique.

3.3.7. FAE1

The expression of FAE1 was also dependent on the developmental class, but only in specific varieties (interaction of variety × silique; χ2 = 35.5; p = 0.0034), despite the individual significant effects of the silique class (χ2 = 319; p < 0.001) and variety (χ2 = 38.8; p < 0.001). In most varieties, the highest values of FAE1 gene expression were found in mature siliques. Values in the L-class siliques were exceptionally high in V7, V11, V14, V16, and V17, with values between 200- and 300-fold of the minimum, but even higher in V18, with expression values up to 1500 times higher than the lowest values.
Since FAE1 was expressed only at the very late stages of silique development, we cannot rule out the possibility that the wide expression range detected among varieties reflected differences in the maturation rate of the siliques in the different varieties.

3.3.8. Global Analyses

Significant variations in gene expression values were observed for specific genes in certain varieties and developmental stages. This phenomenon was consistently observed for some genes and varieties. We found that the expression levels of ADS2 and FAB2a in late siliques were outstandingly high in V18. The FAD2, FAD3, and FAE1 genes in V14 and V18 showed the highest relative expression values in late siliques compared to the other genes.
Figure 7 summarizes the expression data for all the genes, varieties, and developmental stages. Expression values are presented as Log2FC. FC is the fold change value, the number of times the expression of a gene varies as compared to the expression of the sample used as a reference in all cases (Sa-V1). Varieties and developmental stages were grouped using hierarchical clustering. The effects presented above for each gene, regarding variations across varieties and developmental stages, can now be examined in the context of the data obtained for the other samples. For instance, the relatively constant and moderated expression of FAB2c contrasts with the maturation and genotype-dependent expression of FAE1.

4. Discussion

Camelina sativa stands out for its notable agronomic traits, such as low water and fertilizer requirements, high adaptability, and resistance to adverse conditions. Its efficient transformation system, similar to Arabidopsis, combined with the wide availability of transcriptomic and genomic data, have facilitated the development of transgenic lines capable of synthesizing high levels of novel oils or unsaturated fatty acids (UFAs). These features have consolidated C. sativa as a model plant for lipid metabolism research and genetic improvement to enhance fatty acid synthesis and accumulation in seeds, with promising industrial and agricultural applications [21].
Given its allohexaploid nature with three subgenomes, each gene has three allele pairs [21,28,35,36], making it very difficult to introduce genetic variability through the use of classical mutagenesis [10]. Research has focused on increasing the seed size and production and enhancing the accumulation of essential fatty acids, such as Ω-3 and Ω-6, including disrupting the three copies of the FAE1 gene [10,21,35,37]. The EU applies the precautionary principle regarding genetically modified (GM) crops, permitting research only under confined conditions. Therefore, identifying natural variation in gene expression profiles represents a valuable alternative, especially within the current European Union legislative framework, which restricts the commercial use of gene-editing technologies such as CRISPR/Cas9 under GMO regulations [5,10].
In this context, we have conducted a detailed analysis of the genes involved in fatty acid biosynthesis in Camelina sativa, focusing on key enzymes such as desaturases (ADS1, ADS2, FAB2a, FAB2b, FAB2c, FAD2, FAD3, FAD6, FAD7, FAD8, and SLD) and elongases (FAB1 and FAE1). These enzymes introduce double bonds and extend fatty acid chains, generating MUFAs from saturated fatty acids (SFAs) and polyunsaturated fatty acids (PUFAs) from MUFAs.
Gene expression was examined through an in silico analysis using the Camelina Developmental Transcriptome Atlas developed by Kagale et al. [28]. Given Camelina’s allohexaploid genome, we aimed to include all three gene copies in our analyses [18]. We focused on siliques throughout development, selecting candidate genes in which all the copies were expressed in this tissue for the subsequent qRT-PCR analysis. We selected seven of the thirteen genes initially examined: ADS2, FAB1, FAB2a, FAB2c, FAD2, FAD3, and FAE1. The ACT-7 Actin gene was selected as a normalizer.
Quantitative real-time PCR (qRT-PCR) is crucial for a gene expression analysis, enhancing our understanding of genetic network regulation [20]. The accuracy of a qRT-PCR analysis depends on transcript normalization using stably expressed reference genes, such as the Actin gene, which has also been used by other authors [19,20].
RNA was extracted from nine Camelina sativa varieties at three silique developmental stages, early (S), middle (M), and late (L), with three biological replicates (a, b, and c), which ensured reliability. Oily seeds are generally regarded as challenging samples for nucleic acid extraction, but we successfully produced large quantities of high-quality total RNA (Table A1, Figure A2) using a commercial RNA purification kit (Promega, Madison, WI, USA).
Although we used conserved primers to quantify the selected genes for all three homologous copies, we are aware that this approach may not fully capture the individual expression patterns of individual genes. The expression of these genes is often complex and dynamic, and using gene-specific primers for each homologous gene would likely provide more precise information on their regulation. We plan to pursue this approach in future research to enhance our understanding of the regulation of fatty acid biosynthesis at the gene level.
Next, we designed high-quality real-time PCR tests for all the studied genes. These tests showed high specificity, almost 100% efficiency, and a quantitative capacity (linearity) over three orders of magnitude (Figure 5). These tests constitute a valuable resource for future research programs.

4.1. Gene Expression Insights

Differential gene expression patterns emerged among varieties and developmental stages, suggesting that the observed differences likely reflect inherent genetic variability among the studied varieties. The experimental design, involving sampling within a short timeframe under uniform conditions, minimized environmental influences such as high temperatures related to the accumulation of α-linolenic acid (ALA, C18:3, Ω-3) and soil composition changes [38,39,40,41]. The results indicate a complex and genotype-specific regulatory landscape that is influenced significantly by the silique developmental stage, genetic background, and their interaction, underscoring the combined influences of these variables on gene regulation (Figure 7).
ADS2 (Δ9 acyl lipid desaturase 2): The ADS2 gene encodes an extraplastidial desaturase located on the endoplasmic reticulum and whose substrate is fatty acids that are part of complex lipids such as sphingolipids, glycerolipids, and phosphoglycerolipids, which are integral components of cellular membranes. It is associated with the cold stress response, as its expression can modulate membrane fluidity. The expression of ADS2 exhibited strong varietal and developmental dependencies, with the highest transcript accumulation detected in late-stage siliques of V18. This indicates a potential genotype-specific enhancement of fatty acid synthesis activity during seed maturation, consistent with the role of ADS2 in the desaturation processes crucial for modifying fatty acid composition [12]. Interestingly, the lack of a consistent increase in ADS2 expression with the silique size in some varieties, such as V3, suggests that the temporal regulation are both variety- and stage-dependent, reflecting possible differences in the timing of lipid biosynthesis activity [16,38].
FAB1 (3-oxoacyl ACP (acyl carrier protein) synthase II): FAB1 is involved in primary fatty acid synthesis, whereby two carbons are added (elongase) to palmitic acid (C16:0-ACP) to form stearic acid (18:0-ACP) in the chloroplast. FAB1 expression generally increased significantly along silique development (χ2 = 6.37; p = 0.041), aligning with its function in the elongation of saturated fatty acids (SFAs) [15,17,23]. The intervarietal differences were notable (χ2 = 57.6; p < 0.001); maximum values were found in V17 and V18, but especially in V1. A similar pattern of a silique maturation-related increase in gene expression has been reported in Brassica napus [42]. The marked differences between V1 and V15 underscore genetic diversity in the fatty acid elongation capacity, a factor that can be exploited in breeding for seed oil quality [2,36].
FAB2a (stearoyl-ACP Δ9 desaturase 7): FAB2a encodes a chloroplast-localized desaturase that introduces a double bond at the Δ9 position of saturated fatty acids, thereby converting stearic acid (C18:0-ACP) to oleic acid (C18:1 Δ9-ACP). It plays a crucial role in synthesizing MUFAs. Maximum expression was observed in late siliques (L), particularly in V18, while minimum levels were recorded in V15 (χ2 = 53.6; p < 0.001). This gene is a potential target to engineer varieties containing increased concentrations of MUFAs.
FAB2c (stearoyl ACP Δ9 desaturase 3): This enzyme shares its localization and function with FAB2a. In the case of FAB2c, the increased expression associated with silique development is more pronounced than in FAB2a. Unlike other genes, the interaction with the variety was not significant (χ2 = 9.5; p = 0.89), suggesting an essential and constitutive role in the synthesis of MUFAs.
The expression of FAB1, which is involved in saturated fatty acid elongation, and FAB2a and FAB2c, encoding ω-9 desaturases that convert stearic acid (C18:0) to oleic acid (C18:1), increased significantly with silique maturation (χ2 = 6.37 and 98.5, respectively; p < 0.05). These patterns align with observations in other Brassicaceae species such as Brassica napus [38], supporting the crucial roles of these enzymes in seed oil biosynthesis [39].
FAD2 (fatty acid desaturase 2) is involved in the conversion of MUFAs to PUFAs. FAD2 forms linoleic acid (LA, C18:2 Δ9,12 or Ω-6) by desaturation at the Δ12 (Ω-6) position of oleic acid (C18:1, Δ9). The results show significant interactions between the variety and silique development (χ2 = 52.5; p < 0.001). The minimum expression was observed in V7, V11, V15, and V16 at different developmental stages. FAD2 desaturases demonstrated strong varietal effects with developmental modulation that was variety-specific. This is particularly notable in V18, highlighting the potential of our approach in the discovery of valuable germplasms, in this case for the production of improved varieties with increased contents of valuable PUFAs. This step has been extensively studied by several authors [16,17,22].
FAD3 (fatty acid desaturase 3): FAD3 forms α-linolenic acid (ALA, C18:3 Δ9,12,15 or Ω-3) by desaturation at the Δ15 (Ω-3) position of linoleic acid (C18:2 Δ9,12, or Ω-6). As for FAD2, our results show a significant interaction between silique development and the variety (χ2 = 2669; p < 0.001). FAD3 expression was particularly high in V18 during the late stage, up to 10 times higher than in other treatments. This overexpression was clearly visualized in the heatmap, corroborating its pivotal role in PUFA synthesis during seed maturation. This behavior is very likely related to the accumulation of PUFAs at late developmental stages, as previously reported [16,17,22,25,39,40].
FAE1 (fatty acid elongase 1) is responsible for the elongation of very-long-chain fatty acids (VLCFAs) such as eicosenoic (C20:1, Δ11) and erucic (C22:1 Δ11) acids, and is essential for lipid reserve accumulation in mature seeds. Its expression is strongly influenced by both the variety and silique stage, with exceptional expression levels in late siliques of V18 reaching up to 440 times higher than other genes (χ2 = 35.5; p = 0.0034). Its expression is also elevated in late siliques of V16, V7 and V17, as is highlighted in the heatmap (Figure 7). This observation correlates with the pivotal role of FAE1 in determining the content of VLCFAs, which are key components influencing seed oil properties such as the melting point and oxidative stability [26,27,35]. The high fold changes observed suggest that varietal differences in FAE1 expression could underlie significant phenotypic diversity in seed oil profiles [10,36]. Alternatively, the differences observed in the expression of this gene might reflect differences in the maturation rate of the varieties. If FAE1 was expressed at the very late stages of silique development, the high expression level detected in V18, among others, might reflect that this variety has entered the final steps of silique development earlier than the others.

4.2. Functional and Applied Implications

Our results highlight a complex regulation of genes involved in fatty acid synthesis, controlled by both silique development and genetic background, as previously noted [38]. The elevated expression of FAE1 and FAD3 in specific varieties suggests potential applications in breeding programs focused on oil quality improvement. Furthermore, the observed intervarietal variability offers a valuable opportunity to develop cultivars adapted to specific environmental conditions or with enhanced lipid profiles [10,16,41].
The food industry requires oils rich in healthy SFAs, MUFAs, and PUFAs such as oleic acid, linoleic acid (LA, Ω-6), and α-linolenic acid (ALA, Ω-3). Camelina oil has a highly beneficial 2:1 ratio of Ω-3 to Ω-6 fatty acids, making it an excellent choice for promoting health when consumed raw [11,15,42]. It is suitable for food and feed, including nutraceutical and pharmaceutical purposes. The present study identifies two varieties that are particularly worthy of further investigation. V18 exhibits high FAB2c, FAD2, and FAD3 expression, which are associated with PUFA synthesis, making it suitable for producing healthy edible oils, some of which are essential for mammals (LA and ALA). Similarly, V1 displays relatively high expression of FAB1 and FAB2c, suggesting an accumulation of SFAs such as palmitic acid and stearic acids and MUFAs such as oleic acid.
For the biofuel industry, oils with high saturated and long-chain fatty acid contents are prioritized for improved stability and calorific value due to improved oxidation stability and cetane values [43,44]. In this context, three varieties are noteworthy. V18 stands out due to its extremely high expression of FAE1, which is linked to very-long-chain fatty acid (VLCFA) synthesis and is crucial for stable biofuels. V7 and V14, in turn, show high FAE1 expression at later developmental stages, making them potentially valuable for producing energy-dense biofuels.
In the industrial sector, MUFAs are essential for producing lubricants and bioplastics. MUFAs, such as oleic acid (C18:1) and erucic acid (C22:1), are desirable due to their thermal and oxidative stability, as well as their lubricating and anti-corrosive properties [45]. Two of the varieties studied here deserve attention. V18 showed high FAD2 and FAE1 expression, making it suitable for MUFA production. V14 and V7 exhibited elevated expression of FAB2a and FAD2, involved in SFA and MUFA accumulation, which might make them suitable for industrial material production.
Varieties such as V18 and V14 could be optimal for biofuels and technical industries due to their potential capacity for synthesizing long-chain and saturated fatty acids. Conversely, V1 and V18 stand out for food applications due to their high expression of genes linked to healthy fatty acids.
Unfortunately, the fatty acid profile for the varieties used in this study could not be obtained. We have data from seven varieties, which have been previously published [6,8], but the material for these analyses was obtained in other harvesting seasons, preventing the possibility of establishing solid correlations. This difficulty best illustrates the potential benefit of using the approach presented in this manuscript. Once correlated with the fatty acid profiles, the analyses of the expression patterns of selected genes should provide a consistent and reproducible method to track the quality of germplasms under selection using limited amounts of material.

5. Conclusions

Our findings provide valuable tools for selecting Camelina varieties with tailored genetic profiles, underscoring the potential to exploit natural transcriptional diversity for cultivar selection and improvement in agricultural and industrial contexts.
The results reveal that gene expression in siliques is driven by both developmental stages and the genetic background, with significant interactions observed in the expression of ADS2, FAD2, FAD3, and FAE1. Late silique developmental stages generally corresponded to increased expression of biosynthetic genes, consistent with the timing of oil accumulation in developing seeds. The pronounced expression peaks observed in V18 across multiple genes indicate elevated gene expression in mature siliques; however further investigation is needed to clarify the underlying regulatory mechanism. The precise and efficient q-RT-PCR assays developed here provide valuable molecular resources for future studies. Considering Camelina’s limited breeding history [3,4,5], such molecular insights are essential to accelerate varietal development that meets agronomic and industrial demands.

Author Contributions

Conceptualization, E.G., G.H., D.M.-C. and P.V.M.; methodology, E.G. and G.H.; software, M.U.; validation, E.G., G.H. and M.U.; formal analysis, E.G. and M.U.; investigation, E.G.; resources, A.C. and P.V.M.; data curation, M.U. and E.G.; writing—original draft preparation, E.G.; writing—review and editing, E.G., G.H., M.U., A.C. and D.M.-C.; visualization, E.G., G.H., D.M.-C., M.U., A.C. and P.V.M.; supervision, G.H., D.M.-C. and P.V.M.; project administration, D.M.-C. and P.V.M.; funding acquisition, D.M.-C. and P.V.M. All authors have read and agreed to the published version of the manuscript.

Funding

FP22-CAMEPRO and FP24-CICERCAM project are funded by the Community of Madrid through IMIDRA.

Institutional Review Board Statement

Not applicable.

Data Availability Statement

The data presented in this study are available on request from the corresponding author due to intellectual property protection.

Conflicts of Interest

The authors declare no conflicts of interest.

Appendix A

Agriculture 15 01305 g0a1aAgriculture 15 01305 g0a1bAgriculture 15 01305 g0a1c
Figure A1. All genes analyzed in silico. Only those with expression in siliques were selected for the next step.
Figure A1. All genes analyzed in silico. Only those with expression in siliques were selected for the next step.
Agriculture 15 01305 g0a1aAgriculture 15 01305 g0a1bAgriculture 15 01305 g0a1c
Agriculture 15 01305 g0a2
Figure A2. Formaldehyde 1.5% agarose gel showing the high quality of the silique RNA obtained. The image shows all the samples extracted from the different varieties (V1, V3, V7, V11, V14, V15, V16, V17, and V18), with three replicates (a, b, and c) and three developmental stages (S, M, and L).
Figure A2. Formaldehyde 1.5% agarose gel showing the high quality of the silique RNA obtained. The image shows all the samples extracted from the different varieties (V1, V3, V7, V11, V14, V15, V16, V17, and V18), with three replicates (a, b, and c) and three developmental stages (S, M, and L).
Agriculture 15 01305 g0a2
Table A1. Nanodrop measurements.
Table A1. Nanodrop measurements.
SampleTypeConc.UnitA260 (Abs)A280 (Abs)260/280260/230Date and Time
V1.1 SRNA14,597ng/µL36,49316,68221923821 June 2023 17:12:38
V1.1 MRNA5381ng/µL13,454638121120421 June 2023 17:14:19
V1.1 LRNA6289ng/µL15,723742421220321 June 2023 17:15:16
V1.2 SRNA15,293ng/µL38,23217,31222123521 June 2023 17:16:22
V1.2 MRNA8644ng/µL21,60910,05021520721 June 2023 17:17:10
V1.2 LRNA7560ng/µL18,900896821118121 June 2023 17:18:07
V1.3 SRNA12,185ng/µL30,46213,80922124021 June 2023 17:18:54
V1.3 MRNA9517ng/µL23,79311,15421320221 June 2023 17:19:50
V1.3 LRNA5643ng/µL14,108677420816721 June 2023 17:20:45
V3.1 SRNA10,763ng/µL26,90912,19822124021 June 2023 17:53:15
V3.1 MRNA5870ng/µL14,676720020415221 June 2023 17:54:18
V3.1 LRNA6160ng/µL15,400725721220721 June 2023 17:55:03
V3.2 SRNA13,064ng/µL32,66014,81622023921 June 2023 17:55:54
V3.2 MRNA6226ng/µL15,565726621421921 June 2023 17:56:35
V3.2 LRNA7887ng/µL19,717935921116821 June 2023 17:57:24
V3.3 SRNA11,845ng/µL29,61213,57221824121 June 2023 17:58:12
V3.3 MRNA8102ng/µL20,255933821720721 June 2023 17:58:59
V3.3 LRNA7916ng/µL19,789935121216921 June 2023 17:59:49
V7.1 SRNA9600ng/µL24,00010,84222124222 June 2023 10:44:45
V7.1 MRNA5672ng/µL14,180666321321222 June 2023 10:45:56
V7.1 LRNA7027ng/µL17,568814621622222 June 2023 10:46:44
V7.3 SRNA9094ng/µL22,73510,38821923314 June 2023 10:28:01
V7.3 MRNA8559ng/µL21,398980721823114 June 2023 10:29:39
V7.3 LRNA7142ng/µL17,854811722022514 June 2023 10:30:32
V7.2 SRNA16,599ng/µL41,49619,02321823922 June 2023 10:47:49
V7.2 MRNA8892ng/µL22,23110,07022122322 June 2023 10:51:20
V7.2 LRNA6608ng/µL16,521763121722622 June 2023 10:52:03
V11.1 SRNA7351ng/µL18,377843521822022 June 2023 10:53:02
V11.1 MRNA9940ng/µL24,85011,38121822422 June 2023 10:53:41
V11.1 LRNA8759ng/µL21,898993722022422 June 2023 10:54:43
V11.2 SRNA12,417ng/µL31,04114,11322022922 June 2023 12:39:48
V11.2 MRNA5851ng/µL14,628710320615222 June 2023 12:40:24
V11.2 LRNA1763ng/µL4407202721723022 June 2023 12:41:24
V11.3 SRNA11,175ng/µL27,93812,64922123622 June 2023 12:42:20
V11.3 MRNA10,191ng/µL25,47711,97521318322 June 2023 12:43:04
V11.3 LRNA5431ng/µL13,577645221018122 June 2023 12:44:05
V14.1 LRNA8625ng/µL21,562987721822822 June 2023 12:45:00
V14.1 MRNA6124ng/µL15,309744820614422 June 2023 12:45:50
V14.1 LRNA3936ng/µL9840469221017122 June 2023 12:46:47
V14.2 SRNA12,435ng/µL31,08713,63922824227 June 2023 11:35:07
V14.2 MRNA8832ng/µL22,08010,37321317627 June 2023 11:36:03
V14.2 LRNA8503ng/µL21,258978521720827 June 2023 11:36:46
V14.3 SRNA18,155ng/µL45,38620,41522223827 June 2023 11:37:37
V14.3 MRNA7950ng/µL19,876919321619127 June 2023 11:38:17
V14.3 LRNA3806ng/µL9515440921620827 June 2023 11:39:05
V15.1 SRNA12,523ng/µL31,30714,16322124127 June 2023 11:40:05
V15.1 MRNA10,604ng/µL26,50912,12521921027 June 2023 11:40:50
V15.1 LRNA4647ng/µL11,617531721921927 June 2023 11:41:33
V15.2 SRNA16,608ng/µL41,52018,74822123327 June 2023 11:42:20
V15.2 MRNA5489ng/µL13,721650221117327 June 2023 11:42:50
V15.2 LRNA9272ng/µL23,18110,98321117127 June 2023 11:43:08
V15.4 LRNA8823ng/µL22,05710,31721418627 June 2023 11:45:03
V16.1 LRNA9421ng/µL23,55210,65422123527 June 2023 11:46:02
V17.1 SRNA14,150ng/µL35,37516,18921923726 June 2023 12:04:04
V17.1 MRNA7243ng/µL18,108839121618626 June 2023 12:05:03
V17.1 LRNA9493ng/µL23,73210,91921722726 June 2023 12:05:47
V17.2 SRNA16,695ng/µL41,73718,92122123826 June 2023 12:06:37
V17.2 MRNA7610ng/µL19,024900021117726 June 2023 12:07:15
V17.2 LRNA6126ng/µL15,315711621519626 June 2023 12:08:03
V17.4 SRNA15,474ng/µL38,68417,59122022926 June 2023 12:09:01
V17.4 MRNA6459ng/µL16,147762121219226 June 2023 12:09:40
V17.4 LRNA4994ng/µL12,486583521420726 June 2023 12:11:21
V18.1 SRNA12,369ng/µL30,92314,15021923126 June 2023 12:12:13
V18.1 MRNA10,177ng/µL25,44211,65121823226 June 2023 12:12:58
V18.1 LRNA10,785ng/µL26,96212,29621923526 June 2023 12:13:41
V18.2 SRNA7607ng/µL19,017868521923526 June 2023 12:14:33
V18.2 MRNA7811ng/µL19,527903921622326 June 2023 12:15:09
V18.2 LRNA6201ng/µL15,502720221521626 June 2023 12:15:53
V18.4 SRNA10,742ng/µL26,85512,25821922526 June 2023 12:16:51
V18.4 MRNA5906ng/µL14,765692621319726 June 2023 12:17:36
V18.4 LRNA8568ng/µL21,421987021714826 June 2023 12:18:33
Table A2. Primers for amplifying genes related to the fatty acid pathway. The sequence is presented (5′→3′), and * marks the position of an intron in the corresponding genomic DNA. All primers were designed to span introns in the genomic DNA.
Table A2. Primers for amplifying genes related to the fatty acid pathway. The sequence is presented (5′→3′), and * marks the position of an intron in the corresponding genomic DNA. All primers were designed to span introns in the genomic DNA.
GeneSense OligoAntisense OligoAmplicon Size (bp)
ACT-7AGAAAATACAGTGTCTGGATCGGAGGATCGTACTCTCCCTTTGAAATCCACAT*C86
ADS2TAGCCATCTTCTATGGATCTATGACTCTGCAACCTATAAAAACCACTGCCTCTTCAAATC99
FAB1AATGTGGAGTTTTGATTGGCTCAGCTCTTCTTGTATGAGATTCTCAGAGCTTCAA87
FAB2aAAGACCATTCAGTACTTGATTGGATCCGTGAAGCCAAGGTAGGGATTATTCTCTG70
FAB2cGAAGGGAGGAGAGCACAGGATTATCTGCTTGAACCTATCATTAGCTCTTTCCTCT85
FAD2TAGTGAACGCGTTCCTCGTCTTGATCCCACTCGGATGAATCGTAGTGA82
FAD3CTCTTCCCACAGATTCCCTCACTATCACTTGGTTCTCTGTAGTATCTTCCCAACACATG84
FAE1CAGGGTTTAAGTGTAACAGTGCGGTTTATCTATCGATGCAATGTTCCCAAGG90

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Figure 1. A simplified overview of the fatty acid synthesis and desaturation pathways in developing seeds, with a focus on the enzymes relevant to this study.
Figure 1. A simplified overview of the fatty acid synthesis and desaturation pathways in developing seeds, with a focus on the enzymes relevant to this study.
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Figure 2. Field design of the different C. sativa varieties and their replicates grown at El Encín during the 2023 season. Each color represent one camelina variety with four replicates (a, b, c and d). Three of the four replicates of each variety were selected for this study.
Figure 2. Field design of the different C. sativa varieties and their replicates grown at El Encín during the 2023 season. Each color represent one camelina variety with four replicates (a, b, c and d). Three of the four replicates of each variety were selected for this study.
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Figure 3. Images of varieties in the field and the harvesting process.
Figure 3. Images of varieties in the field and the harvesting process.
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Figure 4. Example of genes analyzed in silico. Only those with expression in siliques were selected for the next step. The other studied genes are showed in Figure A1.
Figure 4. Example of genes analyzed in silico. Only those with expression in siliques were selected for the next step. The other studied genes are showed in Figure A1.
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Figure 5. Results of the validation tests of the primer pairs designed for qRT-PCR. Each color represents a primer pair specific to a tested gene.
Figure 5. Results of the validation tests of the primer pairs designed for qRT-PCR. Each color represents a primer pair specific to a tested gene.
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Figure 6. Expression of genes involved in fatty acid synthesis in the siliques at different developmental stages (early (S), medium (M), and late (L)) from nine varieties of Camelina sativa (L.) Crantz. The data are presented as means ± SEs. Lower-case letters indicate statistically significant differences among treatments (interaction variety × silique), while capital letters indicate statistically significant differences among varieties. Note that * means a, b, c, d and ** means a, b, c, d, e, for simplicity, in the expression of FAD3 and FAE1 genes.
Figure 6. Expression of genes involved in fatty acid synthesis in the siliques at different developmental stages (early (S), medium (M), and late (L)) from nine varieties of Camelina sativa (L.) Crantz. The data are presented as means ± SEs. Lower-case letters indicate statistically significant differences among treatments (interaction variety × silique), while capital letters indicate statistically significant differences among varieties. Note that * means a, b, c, d and ** means a, b, c, d, e, for simplicity, in the expression of FAD3 and FAE1 genes.
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Figure 7. Heatmap of the mean fold change (FC) in expression values for all samples, including 9 varieties (coded on a green gradient) by three developmental stages (coded on a brown gradient) for the 7 genes examined. The scale on the right shows the Log2FC value (coded on a black to red gradient). The data have been ordered according to hierarchical clustering, as described in the Section 2.
Figure 7. Heatmap of the mean fold change (FC) in expression values for all samples, including 9 varieties (coded on a green gradient) by three developmental stages (coded on a brown gradient) for the 7 genes examined. The scale on the right shows the Log2FC value (coded on a black to red gradient). The data have been ordered according to hierarchical clustering, as described in the Section 2.
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MDPI and ACS Style

Gómez, E.; Hueros, G.; Mostaza-Colado, D.; Capuano, A.; Uscola, M.; Mauri, P.V. Comparative Analysis of the Expression of Genes Involved in Fatty Acid Synthesis Across Camelina Varieties. Agriculture 2025, 15, 1305. https://doi.org/10.3390/agriculture15121305

AMA Style

Gómez E, Hueros G, Mostaza-Colado D, Capuano A, Uscola M, Mauri PV. Comparative Analysis of the Expression of Genes Involved in Fatty Acid Synthesis Across Camelina Varieties. Agriculture. 2025; 15(12):1305. https://doi.org/10.3390/agriculture15121305

Chicago/Turabian Style

Gómez, Elisa, Gregorio Hueros, David Mostaza-Colado, Aníbal Capuano, Mercedes Uscola, and Pedro V. Mauri. 2025. "Comparative Analysis of the Expression of Genes Involved in Fatty Acid Synthesis Across Camelina Varieties" Agriculture 15, no. 12: 1305. https://doi.org/10.3390/agriculture15121305

APA Style

Gómez, E., Hueros, G., Mostaza-Colado, D., Capuano, A., Uscola, M., & Mauri, P. V. (2025). Comparative Analysis of the Expression of Genes Involved in Fatty Acid Synthesis Across Camelina Varieties. Agriculture, 15(12), 1305. https://doi.org/10.3390/agriculture15121305

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