Next Article in Journal
Estimating Switchgrass Biomass Yield and Lignocellulose Composition from UAV-Based Indices
Previous Article in Journal
Productivity of Modern Raspberry Varieties and Prospects for Their Selection
 
 
Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
Journals
Crops
Volume 5
Issue 1
10.3390/crops5010002
crops-logo
Submit to this Journal Review for this Journal Propose a Special Issue
► Article Menu

Article Menu

share Share announcement Help format_quote Cite question_answer Discuss in SciProfiles
first_page
settings
Order Article Reprints
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Article

Impact of Mutations in Soybean Oleate and Linoleate Desaturase Genes on Seed Germinability of Heat-Stressed Plants

by
Johnson O. Toyinbo
1,
Gautam Saripalli
1,
Hrishikesh P. Ingole
1,
Zachary T. Jones
1,
Salman Naveed
1,
Enoch Noh
2,
Sruthi Narayanan
2 and
Sachin Rustgi
1,2,*
1
Department of Plant and Environmental Sciences, Clemson University Pee Dee Research & Education Center, Florence, SC 29506, USA
2
Department of Plant and Environmental Sciences, Clemson University, Clemson, SC 29634, USA
*
Author to whom correspondence should be addressed.
Crops 2025, 5(1), 2; https://doi.org/10.3390/crops5010002
Submission received: 24 September 2024 / Revised: 12 November 2024 / Accepted: 2 January 2025 / Published: 9 January 2025
Browse Figures
Versions Notes

Abstract

:
Soybean is the primary oilseed crop in the United States, with significant industrial value. Understanding the molecular mechanisms of heat stress tolerance in soybean plants is critical for developing stress-resistant cultivars. Current knowledge about the role of fatty acid desaturases (FADs) in modulating membrane fluidity under abiotic stress prompted this investigation into the impact of mutations in the FAD genes on seed germination from heat-stressed plants. In soybean plants, exposure to heat stress during anthesis is known to significantly reduce seed germination. In silico expression analysis indicated high expression levels of the soybean FAD2 and FAD3 genes in the leaves. Therefore, a detailed expression analysis of these genes was conducted using qRT-PCR from leaf tissue. Generally, downregulation of these genes was observed in the mutants; however, two genes, FAD3A and FAD2-3, showed a more than 2-fold increase in expression in six out of ten mutants under heat stress. This upregulation was particularly pronounced (7-fold) in the mutant S17CR-170. Correlation analysis revealed a positive correlation (up to 0.48) between the expression level of FAD3A, FAD3B, FAD3C, and FAD2-3 and the decline in germination from heat-stressed plants. This suggests these FAD genes may act as negative regulators of germination under heat stress conditions.

1. Introduction

Soybean (Glycine max L., 2n = 40) is an important legume crop that serves as a rich source of dietary oil and protein for human and animal consumption. It is also used as a raw material for various medical and industrial purposes [1]. Soybean is the leading oilseed crop in the U.S., accounting for about 90% of the total oilseed production [2]. Consequently, continuous efforts are being undertaken to develop soybean cultivars that are tolerant/resistant to adverse environmental conditions.
Heat and drought are two major abiotic stresses that significantly impact the soybean yield. The exponential increase in fossil fuel use since industrialization, along with other anthropogenic activities, has led to a notable rise in global temperatures, particularly during the summer crop growing season. This rise in temperature has caused erratic rainfall patterns during the growing season, posing a significant threat to global food security.
The U.S. led global soybean production until 2018, with its decline attributed partly to a global warming-induced decline in productivity and primarily to increased soybean acreage in Brazil [3,4]. To mitigate heat-stress-triggered losses, the producers in the mid-Southern U.S. adopted an Early Soybean Production System (ESPS). Under this management strategy, early-maturing soybean varieties are planted in zones typically suitable for late-maturing varieties with the aim being to skip heat stress during anthesis by flowering early. This strategy, however effective, presents a unique challenge as plants sown under ESPS undergo seed maturation under heat stress [5].
Heat stress can occur at any developmental stage during soybean growth; however, it is most damaging during anthesis and seed development [6]. For instance, according to Lobel and Asner [7], an increase in temperature by 1 °C results in up to a 17% decline in soybean yield. Similarly, according to Schauberger et al. [8], soybean yield under rainfed conditions declines by up to 6% if the temperature rises above 30 °C during the growing season. Heat stress occurring at the time of anthesis or seed development causes a reduction in pollen viability, seed weight, and seed size. It also results in a loss of seed viability and vigor, leading to poor germination. Additionally, it causes seed coat wrinkling and discoloration, leading to poor physical appeal and reduced economic value [9,10,11,12].
Heat stress in crop plants generally results in several complex biochemical and physiological alterations that limit productivity [13]. Specifically, heat stress reduces assimilate production and translocation, increases carbohydrate starvation, and causes high respiration, especially under high nighttime temperatures [14]. Therefore, attempts are being made to understand the molecular mechanisms of heat stress tolerance in crop plants.
In soybean, molecular mechanisms of heat stress tolerance have been studied, and a few genes involved in the process have been identified. Similarly, several differentially expressed genes under heat stress have been identified in different tissues, including the leaf, pod, sepal, anther, and stigma [15], in seedlings [16], and at various developmental stages, such as leaves at the reproductive stage [17]. These early studies suggested that the molecular mechanisms of heat stress tolerance are complex and differ at various developmental stages, engaging different physiological and metabolic pathways. The physiological pathways impacted by heat stress in soybean include major pathways such as photosynthesis, stomatal conductance, and transpiration. While stomatal conductance and transpiration are reported to increase due to heat stress, photosynthesis is generally inhibited [17,18]. In another study, four different regimes of day and night temperatures were examined for their impacts on the physicochemical, agronomic, and genetic factors of two Chinese soybean genotypes. Physicochemical parameters included physiological traits like photosynthesis rate, stomatal conductance, and transpiration rate, as well as biochemical traits like superoxide dismutase (SOD), catalase (CAT), and peroxidase (POD) content. Agronomic traits included seeds and pods per plant and genetic factors included expression changes for the GmDNJ1, GmDREB1, GmHSF-34, GmPYL21, GmPIF4b, GmPIP1;6, GmGBP1, GmHsp90A2, GmTIP2;6, and GmEF8 genes. The overall results revealed that a temperature regime of 35 °C during the day and 27 °C at night was the most suitable for growing Chinese soybean genotypes, due to the significant increase in agronomic trait values and gene expression changes observed under this temperature regimen [19]. This finding highlighted genotypic differences in how different soybean genotypes respond to heat stress.
Lipidomic, proteomic, and metabolomic studies were carried out to further understand the molecular mechanisms of heat tolerance [11,20,21]. For instance, a detailed study of leaf metabolites revealed the importance of sugar and nitrogen metabolism under heat and drought stress in soybean [22]. Similarly, temperature- and genotype-specific differences were observed in the seed metabolome, and a diverse set of antioxidant metabolites like tocopherols, flavonoids, phenylpropanoids, and ascorbate precursors were found to be enriched in the seeds of a heat-tolerant soybean cultivar [11]. In another study, changes in the content and composition of lipids derived from the leaves of two soybean cultivars differing in heat stress tolerance after exposure to heat stress were observed [20]. Additionally, another study proposed a connection between the lipid unsaturation index, the expression levels of soybean oleate and linoleate desaturase genes, and heat stress tolerance [3]. Similarly, other biochemical pathways, such as the antioxidant defense mechanism (which increases the activity of enzymes like superoxide dismutase), phytohormone signaling (salicylic acid and abscisic acid), and carbohydrate metabolism, also function synergistically to minimize damage caused by heat stress [18,23,24]. Overall, the studies above clearly reveal that the metabolites and the pathways involved are responsible for heat stress tolerance in soybean plants.
The complex molecular mechanisms of heat stress tolerance in soybean plants are genetically regulated, with the differential expression of downstream genes linked to the aforementioned physiological and metabolic pathways playing an important role. These downstream genes include various classes of genes encoding for transcription factors, enzymes involved in biosynthetic pathways, and growth hormone metabolism (reviewed in detail by Jianing et al. [18]). Therefore, efforts have been made to characterize these genes. For instance, an earlier report identified a regulatory network of transcription factors encoding heat shock factors, ethylene-responsive element binding factors (EREB), and WRKY TFs, which showed differential expression under heat stress in soybean roots [25]. Similarly, in another study, high expression of the DREB1 gene family (another class of TFs), dehydrins, and LEA genes under heat stress was also reported [26].
Fatty acid desaturases (FADs) are enzymes that introduce double bonds into lipid fatty acyl chains. Soybean has genes for both extraplastidic and plastidic FADs. The gene for extraplastidic oleate Δ12-desaturase, FAD2, exists as a family of eight members: FAD2-1A, FAD2-1B, FAD2-2A, FAD2-2B, FAD2-2C, FAD2-2D, FAD2-2E, and FAD2-3 [27,28,29]. These genes are responsible for converting 18:1 extraplastidic lipids into 18:2 lipids. Similarly, the linoleate Δ-15 desaturase genes, FAD3, exist as a family of three members: FAD3A, FAD3B, and FAD3C [30,31]. These linoleate desaturase genes are responsible for converting 18:2 extraplastidic lipids into 18:3 lipids. Recently, the role of FAD3 in modulating membrane fluidity in response to drought and salinity stress in soybean plants was demonstrated [1]. Similarly, the ectopic expression of the soybean FAD3A gene in rice improved germination in cold-stressed plants [32]. However, the roles of FAD2 and FAD3 in heat stress tolerance remain relatively unexplored, with only a few studies (including our own study; [20]) providing some evidence of these genes’ involvement during heat stress, either in soybean [33] or in other crops like maize [34] and tobacco [35]. In our own earlier research, we showed a decline in the expression levels of FAD2 and FAD3 in soybean leaves upon exposure to heat stress [20]. In another recent study, FAD2-1, was shown to interact with GmCDPKSK5 (a type of calcium-dependent protein kinase) and assist in seed development in soybean under heat stress conditions [33]. Similarly, in maize, differential expression of FAD genes was observed in different tissues under heat stress [34]. In tobacco, the silencing of FAD7 was shown to enhance the photosynthetic efficiency and membrane stability under heat stress [35].
In this study, we aimed to understand the role of the FAD genes in imparting heat stress tolerance in soybean plants by using mutants for these genes. Soybean plants were subjected to heat stress during flowering, and the expression of FAD2 and FAD3 genes was analyzed in leaves of 10 different soybean null mutants and the wild type. These mutant lines were generated by Pham et al. [36] to develop high-oleate and low-linoleate soybean genotypes. The high-oleate soybean mutants were created by pyramiding mutations in the FAD2-1A and FAD2-1B genes. However, these lines still produce linolenic acid within a range of 4–6%, which is undesirable due to the oxidative instability it imparts to the soybean oil. To address this, mutants were developed in the FAD3 genes, and one or more of these mutations were stacked with the high-oleic acid mutations. This approach resulted in 10 mutant lines with double, triple, and quadruple FAD mutations, which were used in this study to investigate the impact of heat stress on germination. Additionally, RT-PCR-based FAD gene expression analysis was performed on leaf tissue collected from heat-stressed and control plants to study the impact of heat stress on FAD gene expression.

2. Materials and Methods

2.1. Plant Material

The genetic materials used in the present study are single, double, triple, and quadruple soybean FAD2 and FAD3 mutants and their respective wild types (Table 1). Seeds of these mutants were obtained from the University of Missouri, Columbia, Missouri, USA, and the wild-type M92-220 from the University of Minnesota, St. Paul, Minnesota, United States of America.

2.2. Plant Growth and Heat Stress Treatment

Seeds of each genotype were planted in two-gallon pots containing Fafard®3B Mix/Metro-Mix®830 (SUNGRO Horticulture, Agawam, MA, USA). The pots were fertilized with Osmocote (18:6:12, N:P2O5:K2O) at 25 g per pot and supplemented with a systemic insecticide, Marathon (a.i., Imidacloprid; OHP, Inc., Mainland, PA, USA), at 4.5 g per pot to prevent insect pest invasion. The pots were arranged in randomized complete block design with replicates. Before the heat stress treatment, all plants were grown at 30 °C during the day and 20 °C at night, with a 12 h photoperiod. At anthesis, half of the plants were exposed to 38 °C during the day and 28 °C at night for two weeks, while the remaining plants were kept at 30 °C during the day and 20 °C at night. After the heat stress, all plants were returned to the optimal growing conditions.

2.3. Gene Expression Analysis (In Silico and qRT-PCR)

In silico expression analysis was carried out using the publicly available soybean expression data for leaves, fruits, flowers, roots, and nodules (RNA-sequencing atlas of soybean genotype A81-356022 at https://legacy.soybase.org/soyseq/, accessed on 10 September 2023). After retrieval, the expression data were analyzed and plotted using MS Excel.
For qRT-PCR analysis, leaf samples were collected for RNA extraction from three biological replicates on the 7th day from the start of the heat stress treatment. Total RNA extraction was performed using MagMax Plant RNA isolation kit (Applied Biosystems, Thermo Fischer Scientific, California, USA) according to the manufacturer’s instructions. After DNase treatment, RNA was used for first-strand cDNA synthesis with the RevertAid RT Reverse Transcription Kit (Thermo Fisher Scientific, Waltham, MA, USA). Gene-specific primers used for the expression analysis are listed in Supplementary Table S1. Expression of FAD genes was normalized to Actin 6 [20], and differential expression analysis was performed using the delta delta Ct method [37]. A heatmap showing differential expression of selected soybean FAD genes in leaf samples collected from plants exposed to heat stress or kept under optimal growth conditions was created using the online tool Clustvis [38].

2.4. Seed Germination Measurement

Seed germination data were recorded on six seeds from each replicate of the mutant and wild type plants, which were either exposed to heat stress during early flowering or kept under optimal growing conditions. Seeds were sown in a Fafard Sungro #3B potting mix in flat trays at 28 ± 2 °C daytime and 18 ± 2 °C nighttime temperatures under a 16 h photoperiod and germination was recorded ten days after sowing by counting the seedlings. The mean germination percentage of seeds obtained from heat-stressed plants was subtracted from the germination percentage of seeds from plants grown under optimal conditions to estimate decline in germination due to heat stress.

2.5. Statistical Analysis

The analysis of variance (ANOVA) and mean separation for seed germination was carried out using SAS v.9.4 [39]. Normalized percentage of germination decline was calculated with respect to maximum percentage of decline considered as 100%. Therefore, the percentage of decline for S17-PR170 was considered as 100% and the percentage of decline of the remaining genotypes was calculated accordingly. A correlation plot showing the relationship between gene expression (studied using qRT-PCR) and the percentage of decline in seed germination was generated using the R software package “Corrplot” [40].

3. Results and Discussion

3.1. Impact of FAD Genes on the Germination of Seeds Derived from Heat-Stressed Plants

This goal was achieved by studying the effect of mutations in the soybean FAD genes on the germination of seeds derived from plants exposed to heat stress during flowering, as well as those grown under optimal conditions.
An analysis of variance (ANOVA) of germination percentages revealed significant differences (p < 0.001) among genotypes, treatments, and the interaction between genotype and treatment (Table 2). Mean separation analysis showed that seeds obtained from plants grown under optimal conditions had a significantly higher germination percentage than those from heat-stressed plants. Seeds from all heat-exposed genotypes displayed reduced or no germination under heat stress, except for S15-17812, S16-17495, S17PR-345, S17PR-501, and S17PR-662 (Table 3). This analysis suggested that soybean plants exposed to heat stress, regardless of genotype, exhibit reduced germination; however, the severity of this effect varied among different genotypes.
While there are no reports on the impact of high-oleic-acid FAD mutants on seed germinability after heat exposure, Bachleda et al. [41] reported a negative effect of high-oleic-acid mutations in the soybean FAD2-1A and FAD2-1B genes on germination under cold stress. Similarly, another study demonstrated that ectopic expression of the FAD3A gene improved germination in cold-stressed rice plants [32]. These findings suggest that mutations in the FAD2 and FAD3 genes have opposing effects on germination under different stress conditions, with a negative impact on cold-stressed plants and a positive impact on the germination of seeds from heat-stressed plants, as observed in this study.
The differential expression of FAD genes under optimal growth and heat stress conditions has been previously demonstrated in soybean [20] and other crop plants, such as Brassica [42] and maize [34]. In our earlier work, we studied the expression of FAD genes in two soybean cultivars with contrasting levels of heat stress tolerance under control and heat stress conditions [20]. This study showed correspondence between the reduced accumulation of polyunsaturated lipids and the expression levels of FAD3A and FAD3B in the heat-tolerant soybean genotypes DS25-1 under heat stress conditions. Therefore, the present study validates our previous findings by further establishing a connection between FAD gene expression and heat stress tolerance.
Further analysis of the germination changes (Table 3) in the wild-type genotypes, Williams 82 and M92-220, revealed no significant difference in seeds derived from plants grown under optimal conditions. However, for the seeds derived from heat-stressed plants, both cultivars showed a decline in germination compared to those grown under optimal conditions. Notably, the normalized percentage decline was more pronounced in Williams 82 (35.06%) compared to M92-220 (19.58%), suggesting that M92-220 may be more tolerant to heat stress. These results are consistent with an earlier study that identified Williams 82 as heat-sensitive due to its decreased germination percentage under heat stress [43].
Interestingly, among the 10 mutants studied, five exhibited a negative germination decline percentage, indicating an increase in germination of seeds from heat-exposed plants, which may suggest heat tolerance. It would be valuable to examine these lines for other heat-tolerance-associated traits, such as yield, seed dimensions and shape, and above- and below-ground biomass. This would help to establish a better connection among heat stress tolerance, lipidome remodeling, and FAD gene expression. The remaining genotypes showed a positive decline, indicating susceptibility, and this decline was more pronounced compared to the two wild types (Table 3).
Interestingly, the differences observed in the performance of the various mutant lines could be attributed to differences in their genetic backgrounds, as evidenced by the variations in FAD gene expression levels across the mutant lines, regardless of their mutation stacking levels (see Section 3.3). This study would have benefited if all mutant lines had been near-isogenic to each other.

3.2. In Silico Gene Expression Analysis

This analysis utilized the available expression data for FAD2, FAD3, FAD6, FAD7, and FAD8 genes from SoyBase (https://legacy.soybase.org/soyseq/, accessed on 10 September 2023). The in silico expression data indicated significantly higher expression level for the FAD2 and FAD3 genes in leaves compared to other tissues (Figure 1), as well as compared to FAD6, FAD7, and FAD8 genes. This prompted us to conduct qRT-PCR analysis for FAD2 and FAD3 genes using leaf tissue.
Additionally, our earlier study demonstrated differential expression of these genes in leaves under heat stress in both heat-sensitive and heat-tolerant soybean genotypes, and predicted association with reduced accumulation of polyunsaturated lipids under heat stress [20] Figure 1).

3.3. qRT-PCR Analysis of FAD2 and FAD3 Expression Level Changes Under Heat Stress

In most cases, the results showed either downregulation (<−2 fold) or no significant change in expression under heat stress compared to the control (Figure 2 and Figure S1). FAD-3A showed upregulation in 8 of the 12 genotypes (10 mutants and 2 wild types), but not S15-17812, S17PR-662, S16-17495, and S17PR-501. FAD-3B showed downregulation in 9 of the 12 studied genotypes, but not M92-220, S17CR-172, and S17CR-170. Similarly, FAD-3C showed downregulation in 9 out of the 12 genotypes, except S17CR-172, S17PR-662, and S17CR-170. On the other hand, FAD-2-1A showed downregulation in all genotypes except for S15-17812. Similarly, FAD-2-1B showed downregulation in all genotypes except for S17CR-172 and S17PR-501. Meanwhile, somewhat mixed results were observed for FAD-2-2C, which showed upregulation in S16-17495, and FAD-2-3, which showed upregulation in seven mutants and downregulation in five mutant lines (Figure 2 and Figure S1).
The reduced expression of FAD3 genes in the leaves of heat-stressed plants directly or indirectly impacts photosynthesis by affecting membrane stability and fluidity, which in turn influences assimilate accumulation in cotyledons. This is expected to affect the accumulation of reserves, as well as the enzymes and energy resources needed during germination.
While the downregulation of genes is expected due to heat stress, there are instances where the upregulation of these genes has been observed. Of the seven genes studied, two—FAD3A and FAD2-3—showed higher expression (>2-fold) in 6 out of 12 lines. The expression of FAD3A was particularly pronounced (7-fold higher) in the mutant S17CR-170 under heat stress, despite the fact that it carries a point mutation in this gene. Similarly, other mutants such as S17-CR172, S17-PR499, and S17CR-170 also exhibited high expression levels for either the soybean FAD-3A or FAD-2-3 genes, or both. All these genotypes have substitutions in the target genes, not deletions or gene truncations [36].
Additionally, FAD genes belong to a large gene family consisting of 75 members, as revealed by a genome-wide analysis of these genes in three soybean genomes [45]. Therefore, compensatory expression leading to a cumulative increase in gene expression is a plausible explanation for the observed spike. Another possible explanation is that substitutions rendering enzymes dysfunctional or with reduced functionality often result in overproduction of the transcript to compensate for the loss of function.
Furthermore, the germination analysis of seeds derived from heat-stressed plants showed a significant decline in germination (p < 0.01), which was positively correlated (up to 0.48) with changes in the expression pattern of four genes (FAD3-A, FAD3-B, FAD3-C, and FAD2-3) (Figure 3). This suggests that the FAD genes act as negative regulators of seed germination in the heat-exposed plants, where the high expression of these genes contributes to reduced germination through an unknown mechanism. An interesting observation is the high expression of the FAD2-2C gene in the mutant line S16-17495, correlates with increased germination under heat stress. This may indicate a mechanism where the overproduction of 18:2 fatty acids facilitates the cycling of polyunsaturated fatty acids during membrane remodeling under heat stress. However, the exact mechanism behind the high germination of selected FAD mutants under heat stress remains unclear. Similar high performance (e.g., high yield) under heat stress has been observed in other oilseed crops, such as peanuts [46]. As previously mentioned, heat stress is a complex trait controlled by a network of genes, including transcription factors, heat shock proteins, regulatory proteins, and non-coding RNAs [47]. Future detailed studies involving the aforementioned gene will provide better insights into the molecular mechanism of heat tolerance in soybean and clarify whether selected FAD genes are actually regulated by other transcription factors or non-coding RNAs. Additionally, other mutants, such as S15-17182, S17-PR345, S17PR-501, and S17PR-662, also showed high germination rates after exposure to heat stress, with one to three FAD genes (FAD3-A in S17-PR345; FAD2-3 in S17PR-662; FAD2-3 and FAD2-1A in S15-17182; and FAD2-1B and FAD2-3 in S17PR-501; and FAD-3A, FAD-3B, and FAD2-3 in S17CR-170) exhibiting high expression in these lines under heat stress.

4. Conclusions

The present study aimed to understand the role of FAD genes in heat stress tolerance in soybean plants, focusing on the germinability of seeds from heat-exposed plants. This investigation used 10 different FAD mutant lines (Table 1) alongside their respective wild types. These mutant lines, which include double, triple, and quadruple FAD mutations, provide valuable material for assessing the impact of FAD genes on heat stress tolerance in soybean plants. Initial screening of these lines was conducted to evaluate the variability in germination percentage of seeds derived from plants grown under optimal conditions and those exposed to heat stress during flowering. To further support these findings, RT-PCR-based gene expression analysis of the FAD genes was performed on leaf tissue collected from heat-stressed and control plants, allowing examination of the impact of heat stress on FAD gene expression. The results revealed a negative correlation between the expression patterns of specific FAD3 (FAD3-A, FAD3-B, and FAD3-C) and FAD2 (FAD2-3) genes under heat stress and the seed germinability of heat-exposed plants. These observations suggest that FAD3 genes may influence lipid unsaturation level, membrane stability, and, consequently, the stability of the photosynthetic machinery, the accumulation of reserves, and germination.

Supplementary Materials

The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/crops5010002/s1, Figure S1: Bar diagrams showing the differential gene expression fold changes for (a) FAD2-1A; (b) FAD2-2; (c) FAD2-3; (d) FAD2-1B; (e) FAD3A; (f) FAD3B; and (g) FAD3C. These diagrams represent 12 different soybean genotypes under optimum and heat stress conditions. The error bars indicate the standard error of the mean (SEM) in the fold changes. The blue bars in each figure represent the expression delta Ct values under optimum conditions, while the orange bars indicate the expression delta Ct values under heat stress conditions; Table S1: List of gene-specific primers for qRT-PCR analysis.

Author Contributions

J.O.T. performed the experiment and collected the data jointly with H.P.I., Z.T.J., S.N. (Salman Naveed) and E.N.; G.S. and J.O.T. analyzed the data; J.O.T. wrote the first draft of the manuscript jointly with G.S.; S.R. conceived the experiment and edited and finalized the manuscript jointly with S.N. (Sruthi Narayanan). All authors have read and agreed to the published version of the manuscript.

Funding

This work is supported by the SC Soybean Board (2013753) to S.R.; the USDA NIFA grant (2015061) to S.N. (Sruthi Narayanan) and S.R.; the USDA National Institute of Food and Agriculture, Hatch/Multi-State project S009 to S.R.

Data Availability Statement

All the data related to manuscript are presented in the main text.

Acknowledgments

The authors would like to acknowledge the financial support from the SC Soybean Board (2013753) to S.R.; the USDA NIFA grant (2015061) to S.N. (Sruthi Narayanan) and S.R.; the USDA National Institute of Food and Agriculture, Hatch/Multi-State project S009 to S.R.

Conflicts of Interest

The authors declare no conflicts of interest, financial or otherwise.

References

  1. Singh, A.K.; Raina, S.K.; Kumar, M.; Aher, L.; Ratnarparkhe, M.B.; Rane, J.; Kachroo, A. Modulation of GmFAD3 expression alters abiotic stress responses in soybean. Plant Mol. Biol. 2022, 110, 199–218. [Google Scholar] [CrossRef] [PubMed]
  2. Economic Research Service US Department of Agriculture. Oil Crops Sector at a Glance. 2021. Available online: https://www.ers.usda.gov/topics/crops/soybeans-oil-crops/oil-crops-sector-at-a-glance/ (accessed on 2 September 2023).
  3. Rustgi, S.; Kakati, J.P.; Jones, Z.T.; Zoong-Lwe, Z.S.; Narayanan, S. Heat tolerance as a function of membrane lipid remodeling in the major US oilseed crops (soybean and peanut). J. Plant Biochem. Biotechnol. 2021, 30, 652–667. [Google Scholar] [CrossRef]
  4. Available online: https://www.statista.com/statistics/263926/soybean-production-in-selected-countries-since-1980/ (accessed on 5 July 2024).
  5. Bellaloui, N.; Smith, J.R.; Ray, J.D.; Gillen, A.M. Effect of maturity on seed composition in the early soybean production system as measured on near-isogenic soybean lines. Crop Sci. 2009, 49, 608–620. [Google Scholar] [CrossRef]
  6. Poudel, S.; Bikash, A.; Jagman, D.K.; Reddy, R.; Salliana, R.; Raju, B. Quantifying the physiological, yield, and quality plasticity of Southern USA soybeans under heat stress. Plant Stress 2023, 9, 100195. [Google Scholar] [CrossRef]
  7. Lobell, D.B.; Asner, G.P. Climate and management contributions to recent trends in U.S. agricultural yields. Science 2003, 299, 1032. [Google Scholar] [CrossRef]
  8. Schauberger, B.; Archontoulis, S.; Arneth, A.; Balkovic, J.; Ciais, P.; Deryng, D.; Elliott, J.; Folberth, C.; Khabarov, N.; Muller, C.; et al. Consistent negative response of US crops to high temperatures in observations and crop models. Nat. Commun. 2017, 8, 13931. [Google Scholar] [CrossRef] [PubMed]
  9. Heatherly, L.G.; Spurlock, S.R. Yield and economics of traditional and early soybean production system (ESPS) seedings in the Midsouthern United States. Field Crops Res. 1999, 63, 35–452. [Google Scholar] [CrossRef]
  10. Smith, J.R.; Mengistu, A.; Nelson, R.L.; Paris, R.L. Identification of soybean accessions with high germinability in high-temperature environments. Crop Sci. 2008, 48, 2279–2288. [Google Scholar] [CrossRef]
  11. Chebrolu, K.K.; Fritschi, F.B.; Ye, S.; Krishnan, H.B.; Smith, J.R.; Gillman, J.D. Impact of heat stress during seed development on soybean seed metabolome. Metabolomics 2016, 12, 28. [Google Scholar] [CrossRef]
  12. Hamayun, M.; Hussain, A.; Iqbal, A.; Khan, S.A.; Gul, S.; Khan, H.; Rehman, K.U.; Bibi, H.; Lee, I. Penicillium glabrum acted as a heat stress relieving endophyte in soybean and sunflower. Polish J. Environ. Stud. 2021, 30, 3099–3110. [Google Scholar]
  13. Kosina, P.; Reynolds, M.P.; Dixon, J.; Joshi, A. Stakeholder perception of wheat production constraints, capacity building needs and research partnerships in the developing countries. Euphytica 2007, 157, 475–483. [Google Scholar] [CrossRef]
  14. Snider, J.L.; Oosterhuis, D.M. How does timing, duration, and severity of heat stress influence pollen-pistil interactions in angiosperms? Plant Signal Behav. 2011, 6, 930–933. [Google Scholar] [CrossRef] [PubMed]
  15. Sinha, R.; Shostak, B.; Induri, S.P.; Sen, S.; Zandalinas, S.I.; Joshi, T.; Fritschi, F.B.; Mittler, R. Differential transpiration between pods and leaves during stress combination in soybean. Plant Physiol. 2023, 192, 753–766. [Google Scholar] [CrossRef] [PubMed]
  16. Wang, L.; Liu, L.; Ma, Y.; Li, S.; Dong, S.; Zu, W. Transcriptome profiling analysis characterized the gene expression patterns responded to combined drought and heat stresses in soybean. Comput. Biol. Chem. 2018, 77, 413–429. [Google Scholar] [CrossRef] [PubMed]
  17. Xu, C.; Xia, Z.; Huang, Z.; Xia, C.; Huang, J.; Zha, M.; Wang, S.; Imran, M.; Casteel, S.; Jiang, Y.; et al. Understanding the physiological and transcriptional mechanism of reproductive stage soybean in response to heat stress. Crop Breed. Genet. Genom. 2020, 2, e200004. [Google Scholar]
  18. Jianing, G.; Yuhong, G.; Yijun, G.; Rasheed, A.; Qian, Z.; Zhiming, X.; Mahmood, A.; Shuheng, Z.; Zhuo, Z.; Zhuo, Z.; et al. Improvement of heat stress tolerance in soybean (Glycine max L.) by using conventional and molecular tools. Front. Plant Sci. 2022, 13, 993189. [Google Scholar] [CrossRef] [PubMed]
  19. Ding, C.; Alghabari, F.; Rauf, M.; Zhao, T.; Javed, M.; Alshamrani, R.; Ghazy, A.-H.; Al-Doss, A.; Khalid, T.; Yang, S.H.; et al. Optimization of soybean physiochemical, agronomic, and genetic responses under varying regimes of day and night temperatures. Front. Plant Sci. 2024, 14, 1332414. [Google Scholar] [CrossRef] [PubMed]
  20. Narayanan, S.; Zoong-Lwe, Z.S.; Gandhi, N.; Welti, R.; Fallen, B.; Smith, J.R.; Rustgi, S. Comparative lipidomic analysis reveals heat stress responses of two soybean genotypes differing in temperature sensitivity. Plants 2020, 9, 457. [Google Scholar] [CrossRef]
  21. Krishnan, H.B.; Kim, W.S.; Oehrle, N.W.; Smith, J.R.; Gillman, J.D. Effect of heat stress on seed protein composition and ultrastructure of protein storage vacuoles in the cotyledonary parenchyma cells of soybean genotypes that are either tolerant or sensitive to elevated temperatures. Int. J. Mol. Sci. 2020, 21, 4775. [Google Scholar] [CrossRef]
  22. Das, A.; Rushton, P.J.; Rohila, J.S. Metabolomic profiling of soybeans (Glycine max L.) reveals the importance of sugar and nitrogen metabolism under drought and heat stress. Plants 2017, 6, 21. [Google Scholar] [CrossRef]
  23. Vital, R.G.; Müller, C.; Freire FB, S.; Silva, F.B.; Batista, P.F.; Fuentes, D.; Rodrigues, A.A.; Moura, L.M.F.; Daloso, D.M.; Silva, A.A.; et al. Metabolic, physiological and anatomical responses of soybean plants under water deficit and high temperature condition. Sci. Rep. 2022, 12, 16467. [Google Scholar] [CrossRef] [PubMed]
  24. Zhao, J.; Lu, Z.; Wang, L.; Jin, B. Plant Responses to Heat Stress: Physiology, Transcription, Noncoding RNAs, and Epigenetics. Int. J. Mol. Sci. 2021, 22, 117. [Google Scholar] [CrossRef] [PubMed]
  25. Valdés-López, O.; Batek, J.; Gomez-Hernandez, N.; Nguyen, C.T.; Isidra-Arellano, M.C.; Zhang, N.; Joshi, T.; Xu, D.; Hixson, K.K.; Weitz, K.K.; et al. Soybean Roots Grown under Heat Stress Show Global Changes in Their Transcriptional and Proteomic Profiles. Front. Plant Sci. 2016, 7, 517. [Google Scholar] [CrossRef] [PubMed]
  26. Kidokoro, S.; Watanabe, K.; Ohori, T.; Moriwaki, T.; Maruyama, K.; Mizoi, J.; Htwe, N.M.P.S.; Fujita, Y.; Sekita, S.; Shinozaki, K.; et al. Soybean DREB 1/CBF-type transcription factors function in heat and drought as well as cold stress-responsive gene expression. Plant J. 2015, 81, 505–518. [Google Scholar] [CrossRef] [PubMed]
  27. Schlueter, J.A.; Vasylenko-Sanders, I.F.; Deshpande, S.; Yi, J.; Siegfried, M.; Roe, B.A.; Schlueter, S.D.; Scheffler, B.E.; Shoemaker, R.C. The FAD2 gene family of soybean: Insights into the structural and functional divergence of a paleopolyploid genome. Crop Sci. 2007, 47, S14–S26. [Google Scholar] [CrossRef]
  28. Román, A.; Andreu, V.; Hernández, M.L.; Lagunas, B.; Picorel, R.; Martínez-Rivas, J.M.; Alfonso, M. Contribution of the different omega-3 fatty acid desaturase genes to the cold response in soybean. J. Exp. Bot. 2012, 63, 4973–4982. [Google Scholar] [CrossRef] [PubMed]
  29. Dar, A.A.; Choudhury, A.R.; Kancharla, P.K.; Arumugam, N. The FAD2 gene in plants: Occurrence, regulation, and role. Front. Plant Sci. 2017, 8, 1789. [Google Scholar] [CrossRef] [PubMed]
  30. Andreu, V.; Lagunas, B.; Collados, R.; Picorel, R.; Alfonso, M. The GmFAD7 gene family from soybean: Identification of novel genes and tissue-specific conformations of the FAD7 enzyme involved in desaturase activity. J. Exp Bot. 2010, 61, 3371–3384. [Google Scholar] [CrossRef] [PubMed]
  31. Chi, X.Y.; Yang, Q.L.; Lu, Y.D.; Wang, J.Y.; Zhang, Q.F.; Pan, L.J.; Chen, M.; He, Y.; Yu, S. Genome-wide analysis of fatty acid desaturases in soybean (Glycine max). Plant Mol. Biol. Rep. 2011, 29, 769–783. [Google Scholar] [CrossRef]
  32. Wang, X.; Yu, C.; Liu, Y.; Yang, L.; Li, Y.; Yao, W.; Cai, Y.; Yan, X.; Li, S.; Cai, Y.; et al. GmFAD3A, A ω-3 fatty acid desaturase gene, enhances cold tolerance and seed germination rate under low temperature in rice. Int. J. Mol. Sci. 2019, 20, 3796. [Google Scholar] [CrossRef]
  33. Zhou, Y.; Wang, S.; Hu, H.; Shen, Y.; Zhu, Y.; Liu, X.; Wei, J.; Yu, X.; Liu, S.; Ma, H. GmCDPKSK5 interacting with GmFAD2-1B participates in regulation of seed development in soybean under high temperature and humidity stress. Plant Mol. Biol. Rep. 2022, 40, 402–417. [Google Scholar] [CrossRef]
  34. Zhao, X.; Wei, J.; He, L.; Zhang, Y.; Zhao, Y.; Xu, X.; Wei, Y.; Ge, S.; Ding, D.; Liu, M.; et al. Identification of fatty acid desaturases in maize and their differential responses to low and high temperature. Genes 2019, 10, 445. [Google Scholar] [CrossRef] [PubMed]
  35. Hiremath, S.S.; Sajeevan, R.S.; Nataraja, K.N.; Chaturvedi, A.K.; Pal, M. Silencing of fatty acid desaturase (FAD7) gene enhances membrane stability and photosynthetic efficiency under heat stress in tobacco (Nicotiana benthamiana). Ind. J. Exp. Biol. 2017, 55, 532–541. [Google Scholar]
  36. Pham, A.T.; Shannon, J.G.; Bilyeu, K.D. Combinations of mutant FAD2 and FAD3 genes to produce high oleic acid and low linolenic acid soybean oil. Theor. Appl. Genet. 2012, 125, 503–515. [Google Scholar] [CrossRef] [PubMed]
  37. Livak, K.J.; Schmittgen, T.D. Analysis of relative gene expression data using real-time quantitative PCR and the 2−ΔΔCT. Methods 2001, 25, 402–408. [Google Scholar] [CrossRef] [PubMed]
  38. Metsalu, T.; Vilo, J. ClustVis: A web tool for visualizing clustering of multivariate data using principal component analysis and heatmap. Nucleic Acids Res. 2015, 43, W566–W570. [Google Scholar] [CrossRef] [PubMed]
  39. SAS Institute. Statistical Analysis Software (SAS) User’s Guide Version 9.4; SAS Institute: Cary, NC, USA, 2016. [Google Scholar]
  40. Wei, T.; Simko, V. R Package ’Corrplot’: Visualization of a Correlation Matrix. Version 0.95, 2024. Available online: https://github.com/taiyun/corrplot (accessed on 5 July 2024).
  41. Bachleda, N.; Grey, T.; Li, Z. Effects of high oleic acid soybean on seed yield, protein and oil contents, and seed germination revealed by near-isogeneic lines. Plant Breed. 2017, 136, 539–547. [Google Scholar] [CrossRef]
  42. Shaheen, N.; Khan, U.M.; Farooq, A.; Zafar, U.B.; Khan, S.H.; Ahmad, S.; Azhar, M.T.; Atif, R.M.; Rana, I.A.; Seo, H. Comparative transcriptomic and evolutionary analysis of FAD-like genes of Brassica species revealed their role in fatty acid biosynthesis and stress tolerance. BMC Plant Biol. 2023, 23, 250. [Google Scholar] [CrossRef]
  43. Khan, A.Z.; Khan, H.; Khan, R.; Ghoneim, A.; Ebid, A. Seed Developmental Profile of Soybean as Influenced by Planting Date and Cultivar under Temperate Environment. Am. J. Plant Physiol. 2007, 2, 251–260. [Google Scholar] [CrossRef]
  44. Severin, A.J.; Woody, J.L.; Bolon, Y.T.; Joseph, B.; Diers, B.W.; Farmer, A.D.; Muehlbauer, G.J.; Nelson, R.T.; Grant, D.; Specht, J.E.; et al. RNA-Seq Atlas of Glycine max: A guide to the soybean transcriptome. BMC Plant Biol. 2010, 10, 160. [Google Scholar] [CrossRef]
  45. Zhang, B.; Xia, P.; Yu, H.; Li, W.; Chai, W.; Liang, Z. Based on the whole genome clarified the evolution and expression process of fatty acid desaturase genes in three soybeans. Int. J. Biol. Macromol. 2021, 182, 1966–1980. [Google Scholar] [CrossRef] [PubMed]
  46. Akbar, A.; Manohar, S.S.; Variath, M.T.; Kurapaty, S.; Pasupuleti, J. Efficient partitioning of assimilates in stress-tolerant groundnut genotypes under high-temperature stress. Agronomy 2017, 7, 30. [Google Scholar] [CrossRef]
  47. Huang, L.Z.; Zhou, M.; Ding, Y.F.; Zhu, C. Gene networks involved in plant heat stress response and tolerance. Int. J. Mol. Sci. 2022, 23, 11970. [Google Scholar] [CrossRef] [PubMed]
Crops 05 00002 g001
Figure 1. The expression profile of soybean FAD genes in the vegetative and reproductive tissues was analyzed based on in silico soybean expression data available on SoyBase (https://legacy.soybase.org/soyseq/, accessed on 10 September, 2023). The data for the in silico analysis were retrieved from SoyBase, which is based on RNA-seq experiments, as described in Ref. [44].
Figure 1. The expression profile of soybean FAD genes in the vegetative and reproductive tissues was analyzed based on in silico soybean expression data available on SoyBase (https://legacy.soybase.org/soyseq/, accessed on 10 September, 2023). The data for the in silico analysis were retrieved from SoyBase, which is based on RNA-seq experiments, as described in Ref. [44].
Crops 05 00002 g001
Crops 05 00002 g002
Figure 2. A heatmap showing the differential expression of selected soybean FAD genes in leaf samples collected from the wild-type (Williams 82) and its FAD mutants under heat stress conditions (38 °C during the day and 28 °C at night with a 12 h photoperiod), relative to optimal growth conditions (30 °C during the day and 20 °C at night, with a 12 h photoperiod), as determined by qRT-PCR.
Figure 2. A heatmap showing the differential expression of selected soybean FAD genes in leaf samples collected from the wild-type (Williams 82) and its FAD mutants under heat stress conditions (38 °C during the day and 28 °C at night with a 12 h photoperiod), relative to optimal growth conditions (30 °C during the day and 20 °C at night, with a 12 h photoperiod), as determined by qRT-PCR.
Crops 05 00002 g002
Crops 05 00002 g003
Figure 3. A correlation plot showing the relationship between gene expression, as studied using qRT-PCR, and germination decline. The size and color of the filled circles is proportional to the level of the Pearson correlation coefficient; the scale on the right indicates the level of correlation. A higher intensity of blue color indicates a highly positive correlation coefficient, while a higher intensity of red indicates a low correlation coefficient.
Figure 3. A correlation plot showing the relationship between gene expression, as studied using qRT-PCR, and germination decline. The size and color of the filled circles is proportional to the level of the Pearson correlation coefficient; the scale on the right indicates the level of correlation. A higher intensity of blue color indicates a highly positive correlation coefficient, while a higher intensity of red indicates a low correlation coefficient.
Crops 05 00002 g003
Table 1. Soybean genotypes used in this study.
Table 1. Soybean genotypes used in this study.
NameGenotype
Williams 82Wild type
M92-220Wild type
S15-17812FAD2-1A, FAD2-1B null
S17PR-345FAD2-1A, FAD2-1B null
S17CR-172FAD2-1A, FAD2-1B, FAD3A null
S17CR-180FAD2-1A, FAD2-1B, FAD3A null
S17PR-662FAD2-1A, FAD2-1B, FAD3B null
S16-17495FAD2-1A, FAD2-1B, FAD3B null
S17PR-501FAD2-1A, FAD2-1B, FAD3C null
S17PR-499FAD2-1A, FAD2-1B, FAD3A, FAD3B null
S17CR-170FAD2-1A, FAD2-1B, FAD3A, FAD3C null
S17CR-301FAD2-1A, FAD2-1B, FAD3A, FAD3C null
Table 2. Mean squares of germination percentage for seeds obtained from plants of 15 soybean genotypes grown under both heat stress and optimal conditions.
Table 2. Mean squares of germination percentage for seeds obtained from plants of 15 soybean genotypes grown under both heat stress and optimal conditions.
Source of VariationDegree of FreedomGermination %
Rep50.09 *
Genotype (G)110.41 ***
Treatment (T)11.79 ***
G × T110.41 ***
Error1040.04
R2 0.73
*, *** indicate a significant F-test at the 0.05 and 0.001 levels of probability, respectively.
Table 3. Seeds derived from soybean FAD mutants exhibit a decline in germination when exposed to heat stress (HT) compared to those grown under optimal conditions (OT).
Table 3. Seeds derived from soybean FAD mutants exhibit a decline in germination when exposed to heat stress (HT) compared to those grown under optimal conditions (OT).
GenotypeGermination (HT)Germination (OT)Germination DeclinePercent Germination Decline *Normalized Percent Germination Decline #
Williams 82 (PI518671)0.700.970.272735.06
M92-220 (WT)0.830.980.151519.48
S17CR-1700.220.980.7777100.00
S15-178120.400.23−0.18−18−23.38
S16-174950.780.58−0.20−20−25.97
S17CR-1720.680.950.272735.06
S17CR-1800.261.000.747496.10
S17CR-3010.280.950.676787.01
S17PR-3450.620.33−0.28−28−36.36
S17PR-4990.000.590.595976.62
S17PR-5010.550.22−0.33−33−42.86
S17PR-6620.520.47−0.05−5−6.49
* The negative values indicate a high germination percentage under heat stress. The genotype showing the maximum percentage of decline (S17CR-170) was considered 100%. # The normalized decline for the remaining genotypes was calculated with S17-PR130 as the reference.
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.

Share and Cite

MDPI and ACS Style

Toyinbo, J.O.; Saripalli, G.; Ingole, H.P.; Jones, Z.T.; Naveed, S.; Noh, E.; Narayanan, S.; Rustgi, S. Impact of Mutations in Soybean Oleate and Linoleate Desaturase Genes on Seed Germinability of Heat-Stressed Plants. Crops 2025, 5, 2. https://doi.org/10.3390/crops5010002

AMA Style

Toyinbo JO, Saripalli G, Ingole HP, Jones ZT, Naveed S, Noh E, Narayanan S, Rustgi S. Impact of Mutations in Soybean Oleate and Linoleate Desaturase Genes on Seed Germinability of Heat-Stressed Plants. Crops. 2025; 5(1):2. https://doi.org/10.3390/crops5010002

Chicago/Turabian Style

Toyinbo, Johnson O., Gautam Saripalli, Hrishikesh P. Ingole, Zachary T. Jones, Salman Naveed, Enoch Noh, Sruthi Narayanan, and Sachin Rustgi. 2025. "Impact of Mutations in Soybean Oleate and Linoleate Desaturase Genes on Seed Germinability of Heat-Stressed Plants" Crops 5, no. 1: 2. https://doi.org/10.3390/crops5010002

APA Style

Toyinbo, J. O., Saripalli, G., Ingole, H. P., Jones, Z. T., Naveed, S., Noh, E., Narayanan, S., & Rustgi, S. (2025). Impact of Mutations in Soybean Oleate and Linoleate Desaturase Genes on Seed Germinability of Heat-Stressed Plants. Crops, 5(1), 2. https://doi.org/10.3390/crops5010002

Article Metrics

Back to TopTop