Next Article in Journal
Evaluation of Phenolic Compounds and Antioxidant Activity in Three Black Cherry Tomato Varieties Grown Under Greenhouse Conditions
Previous Article in Journal
SnRK2s: Kinases or Substrates?
Previous Article in Special Issue
Ecophysiological and Molecular Analysis of Contrasting Genotypes for Leaf Senescence in Sunflower (Helianthus annuus L.) Under Differential Doses of N in Soil
 
 
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Article

Characterization and Early Response of the DEAD Gene Family to Heat Stress in Tomato

1
Collaborative Innovation Center for Efficient and Green Production of Agriculture in Mountainous Areas of Zhejiang Province, College of Horticulture Science, Zhejiang A&F University, Hangzhou 311300, China
2
Key Laboratory of Quality and Safety Control for Subtropical Fruit and Vegetable, Ministry of Agriculture and Rural Affairs, Zhejiang A&F University, Hangzhou 311300, China
3
Institute of Agricultural Experiment Station of Changxing Substation, Zhejiang University, Hangzhou 310058, China
*
Author to whom correspondence should be addressed.
These authors contributed equally to this work.
Plants 2025, 14(8), 1172; https://doi.org/10.3390/plants14081172
Submission received: 7 March 2025 / Revised: 31 March 2025 / Accepted: 7 April 2025 / Published: 9 April 2025

Abstract

:
The DEAD-box RNA helicase family, acting as a critical regulator in RNA metabolism, plays a vital role in plant growth, development, and adaptation to various stresses. Although a number of DEAD proteins have been reported to participate in heat stress response in several species, the response of DEAD-box RNA helicases to heat stress has not been comprehensively analyzed in tomato. In this study, 42 SlDEAD genes were identified from the tomato genome. Evolutionary analysis of DEAD family genes across different plant species reveals that DEAD family genes can be segregated into five groups. A comprehensive analysis of their physicochemical properties, gene structure, chromosome location, and conserved motifs unveils diversity among the members of the SlDEAD family. An investigation into the subcellular localization of seven SlDEAD proteins indicates that SlDEAD7, SlDEAD14, and SlDEAD26 are located in the endoplasmic reticulum, and SlDEAD40 is located in the endoplasmic reticulum and nucleus, whereas SlDEAD17, SlDEAD25, and SlDEAD35 are located in the chloroplast. The expression of 37 out of 42 SlDEAD genes was responsive to heat stress induction. During the early stage of high-temperature treatment, they exhibited five distinct expression patterns. These findings contribute to a deeper comprehension of the evolution, expansion complexity, and function of SlDEAD genes and provide insights into the potential role of SlDEAD genes in tomato tolerance to heat stress.

1. Introduction

Tomato is a globally cultivated vegetable crop. It not only serves as a staple ingredient in diverse cuisines worldwide but also significantly contributes to farmers’ incomes and the stability of the global vegetable supply. Global warming leads to an increase in annual temperature. Severe high-temperature stress can induce irreversible damage to plant growth, which may pervade the entire life cycle of plants [1]. Although tomato is considered a thermophilic crop, high-temperature stress can markedly affect its productivity through multiple mechanisms. High temperatures lead to alterations in the fluidity of the thylakoid membrane of chloroplasts, thereby reducing the maximum photochemical efficiency (Fv/Fm). When the temperature exceeds 35 °C, the activity of the Rubisco enzyme is inhibited, leading to a decline in the net photosynthetic rate [2]. Moreover, when pollen mother cells experience high temperatures during the meiosis stage, the abnormal programmed cell death of tapetal cells occurs. This results in over 70% pollen abortion and a 35–60% reduction in fruit setting rates [3]. Additionally, high temperatures can trigger an outburst of reactive oxygen species, shorten leaf lifespan, and reduce root activity. As a consequence, the supply of carbon assimilated during the fruit expansion period is reduced [4]. Therefore, high-temperature stress significantly impairs the growth and productivity of tomatoes. Understanding the molecular mechanism underlying the impact of high-temperature stress on tomato cultivation is consequently of critical significance. This understanding is essential for developing effective mitigation strategies and breeding heat-tolerant tomato varieties, which ensures tomato productivity and, in turn, global food security and the agricultural economy.
At the molecular level, high temperatures have profound impacts on gene expression, particularly at transcriptional and post-transcriptional levels. Transcription factors play a central role in the transcription process. For instance, heat shock transcription factors (HSFs) are usually activated upon exposure to high temperatures [1]. They bind to specific DNA sequences called heat shock elements (HSEs) located in the promoter regions of heat-responsive genes. This binding event initiates the transcription of genes encoding heat shock proteins (HSPs) and other stress-related proteins [5]. HSPs act as molecular chaperones, helping to refold misfolded proteins and prevent protein aggregation, which is a common consequence of high-temperature-induced cellular stress. In addition to HSFs, other transcription factors, such as dehydration–responsive element–binding proteins (DREBs), are also involved in the heat stress response [6]. DREBs can bind to dehydration–responsive elements (DREs) in the promoter regions of target genes. Some of these target genes are associated with enhancing plant tolerance to heat stress by regulating various physiological and biochemical processes [7]. These transcription factors and their associated heat-responsive genes have been employed in genetic engineering and marker-assisted selection techniques, offering targeted strategies to enhance heat tolerance in tomatoes. For example, four tomato HSF genes were reported to be upregulated under high-temperature treatment, and their expression levels were closely linked to the thermophenotypes of eight tomato genotypes [8]. This finding indicates that the identified HSF genes can be utilized to assist in screening for potential thermotolerant cultivars.
At the post-transcriptional level, RNA-binding proteins emerge as pivotal regulators. RBPs possess the ability to specifically recognize and bind to target RNAs. Through this binding interaction, they orchestrate a series of crucial processes, including RNA processing and mRNA transport, stability, and translation [9,10]. Under heat stress conditions, the regulatory functions executed by RBPs play a vital role in modulating gene expression at the RNA level [11,12], ensuring the continuous and appropriate expression of heat-responsive genes. For example, mutations of the ESR1 (enhanced stress response 1) gene, which encodes an Arabidopsis K Homology (KH) Domain containing RBPs, confer increased heat tolerance [13]. This increased tolerance is achieved by altering the expression of several abiotic stimuli genes, such as defensin-like family genes.
RNA helicases (RHs), the highly conserved proteins in all kingdoms of life [14,15], constitute a large group of enzymes that primarily function in the unwinding of RNA molecules. They are widely recognized for their involvement in the remodeling of RNA and ribonucleoprotein complexes (RNPs), which is mainly dependent on their binding activity to RNAs in an ATP-dependent reaction [16]. The RH family genes have been progressively identified at the genomic level in model crops. Specifically, there are 115 RH family genes in rice [17], 113 in Arabidopsis [17], 136 in maize [18], 213 in soybean [18], and 161 in cotton [19].
Based on protein sequence homology and their oligomeric state, RHs are divided into six superfamilies: SF1 to SF6. Among them, members from SF3 to SF6 usually function in ring-shaped hexametric toroid structures [20]. In contrast, helicases from SF1 and SF2 are typically non-oligomeric proteins containing a core structure composed of two RecA-like domains [21]. In eukaryotes, the majority of RNA helicases belong to the SF2 superfamily, with only a small fraction being SF1 proteins. According to the conserved motif and structural or mechanistic features, RHs in the SF2 superfamily are further divided into several subfamilies [22,23,24]. Among these subfamilies, DEAD (Asp-Glu-Ala-Asp)-box-containing RHs are the largest group ever discovered [21].
Due to their activities in RNA remodeling, DEAD-box RHs play specific roles in almost all aspects of RNA processing and metabolism, including double-stranded RNA unwinding, pre-mRNA processing, and RNA export, translation, storage, and decay in eukaryotes [25,26,27]. In recent years, the mechanism by which DEAD-box RNA helicases regulate RNA transcription and post-transcription has been gradually elucidated, and growing evidence indicates that DEAD-box RHs are essential for organelle biogenesis, plant growth, development, and stress resistance [28,29,30,31,32,33,34,35,36], particularly in relation to temperature stresses. For example, Arabidopsis DEAD-box RH AtRH7/PRH75 was involved in the processing of 18S pre-rRNA and ribosome assembly, which resulted in auxin-related developmental defects and cold sensitivity in AtRH7/PRH75-knockout mutants [37]. The cold-induced DEAD-box RH AtRCF1 is required for the correct splicing of the pre-mRNA of cold-responsive genes like CIR1, SPFH, PRR5, and SK12, which contributed to the enhanced tolerance of Arabidopsis to low temperature and freezing stresses [25]. In rice, the mutation of the gene TCD33 that encodes a chloroplast-located DEAD-box RH induced an albino phenotype and severe defects in the chloroplast structure under low-temperature conditions [38]. Rice OsRH42 was reported to interact with U2 small nuclear RNA and was located in splicing spots in the nucleus [33], and its knockout caused defects in pre-mRNA splicing and plant growth under cold stress. Collectively, these studies imply that DEAD-box RHs play crucial roles in plant tolerance to extreme temperatures.
Although the function of DEAD-box RHs has been extensively explored in Arabidopsis and rice, only a few studies on DEAD-box RHs in tomato have been reported. A tomato mutant, designated as res (restored cell structure by salinity), was named in accordance with its phenotype, wherein the morphological alterations and cellular disorganization under normal conditions were restored under salt stress conditions [39]. A subsequent study on the res mutant disclosed that the res gene encodes a chloroplast-targeted DEAD-box RNA helicase 39 (SlDEAD39) [40,41]. SlDEAD39 modulated the maturation of chloroplast 23S rRNA by binding to the RNA molecules containing the hidden break-B site [41], which might contribute to its roles in tomato plant development and salt tolerance. In addition, SlDEAD23 and SlDEAD35 were reported to potentially be involved in abiotic stress, such as salt and cold, as well as the biotic stress of ToLCNDV infection [29]. Moreover, SlDEAD31 was proven to positively regulate tomato tolerance to salt and drought stresses, potentially via the upregulation of stress-related genes [42]. However, the response of tomato DEAD-box RHs to heat stress has not been deeply analyzed.
In this study, we conducted a comprehensive analysis of the characteristics and subcellular localization of 42 DEAD-box RHs in tomato and investigated their responses to heat stress. We found that 42 SlDEAD proteins exhibited diverse patterns in both their subcellular localization and expression in response to heat stress. These findings provide new clues for the future study of the functions of SlDEAD in tomato and to identify potential target genes for molecular breeding aimed at enhancing the heat tolerance of tomatoes.

2. Results

2.1. Identification and Phylogenetic Analysis of SlDEAD Proteins

A total of 42 SlDEAD genes, namely, SlDEAD1 to SlDEAD42, as named in a previous study [43], were identified from the tomato genome. Their gene ID and the corresponding homologs in Arabidopsis are presented in Table 1. The amino acid sequence of 42 SlDEAD proteins varies in length, ranging from 394 to 1221 amino acids. The smallest SlDEAD protein is SlDEAD41, which has a molecular weight of 44.85 KDa. In contrast, the largest one is SlDEAD2, comprising 1221 amino acid residues with a molecular weight of 135.06 KDa (Table 1). The isoelectric points of SlDEAD proteins span from 5.21 to 9.96, and approximately one-third of them possess an isoelectric point of less than 7. The instability indexes range from 33.14 to 63.63. Only 12 of them have an instability index below 40, indicating that the majority of these proteins may be unstable.
Sequence alignment and phylogenetic analysis reveal that these SlDEAD proteins are clustered into four clades (Figure 1). Clade I contains only five SlDEAD proteins, including SlDEAD7, SlDEAD15, SlDEAD29, SlDEAD30, and SlDEAD31. Clade IV comprises 18 SlDEAD proteins—SlDEAD1, SlDEAD2, SlDEAD3, SlDEAD6, SlDEAD9, SlDEAD10, SlDEAD11, SlDEAD12, SlDEAD14, SlDEAD20, SlDEAD23, SlDEAD25, SlDEAD27, SlDEAD28, SlDEAD35, SlDEAD36, SlDEAD37, and SlDEAD42—making it the largest clade. The 42 SlDEAD proteins shared nine highly conserved motifs, namely, Q-motif, motif I, motif Ia, motif Ib, motif II, motif III, motif IV, motif V, and motif VI, which are arranged in a specific order (Figure 1, Supplementary Figure S1). Through a detailed examination of these motifs across the SlDEAD proteins (Supplementary Figure S1), it is evident that the majority of these motifs exhibit a high degree of conservation. Notably, with the exception of SlDEAD21 and SlDEAD39, where the first amino acid of the Q-motif is serine, the Q-motifs of the remaining 40 DEAD proteins commence with alanine. Single amino acid alteration also occurs in the first amino acid of motif Ia. In most of the 42 DEAD proteins, motif Ia has a sequence of SAT. However, the serine in this position is replaced by threonine in SlDEAD2, SlDEAD10, and SlDEAD39 and substituted by alanine in SlDEAD17. Moreover, in the remaining motifs, more than one amino acid substitution event can be observed.
To investigate the phylogenetic relationships of DEAD families in tomato and other species, we additionally identified 57 DEAD genes from Arabidopsis, 118 from soybean (Glycine max), 53 from rice (Oryza sativa), 56 from potato (Solanum tuberosum), and 54 from pepper (Capsicum annuum) (Figure 2). Phylogenetic tree analysis based on the sequence alignment of these DEAD proteins showed that the 380 DEAD proteins were divided into five groups, namely, groups I to V (Figure 2). Among them, group V contains 136 DEAD proteins and thus forms the largest group. The SlDEAD proteins from clade IV (Figure 1) were further segregated into groups IV and V. Specifically, three of them, SlDEAD23, SlDEAD25, and SlDEAD35, were assigned to group IV, and the remaining 15 SlDEAD proteins were categorized into group V. SlDEAD proteins in the other clades shown in Figure 1 were correspondingly classified into groups I, II, and III when aligned with DEAD proteins from other species (Figure 2).

2.2. Collinearity Analysis and Chromosome Localization of SlDEAD Family Genes

Genome-level duplication events contribute to the diversification of genes and gene families within the plant genome. Previous studies reveal that a recent large-scale duplication event in the Solanaceae family was shared by tomato and potato [44,45]. To explore the gene replication events of SlDEAD genes in tomato, an intra-species collinearity analysis of the DEAD gene family was performed (Figure 3A, Supplementary Table S2). The analysis identified six duplication events involving 11 genes. Specifically, SlDEAD4 and SlDEAD18, SlDEAD14 and SlDEAD20, SlDEAD19 and SlDEAD21, SlDEAD19 and SlDEAD40, SlDEAD23 and SlDEAD35, and SlDEAD21 and SlDEAD26 occur in segment duplication events. Two tandem replication clusters were identified from the SlDEAD gene family, including SlDEAD19 and SlDEAD20 in chromosome 6 and SlDEAD21 and SlDEAD22 in chromosome 7. The collinearity between tomato and three other species, Arabidopsis, potato, and pepper, was also conducted to investigate the gene duplication events in the evolutionary history of DEAD family genes (Figure 3B and Supplementary Table S2). As shown in Figure 3B, a total of 22, 3, 7, and 32 paired collinearity relationships were found between 42 SlDEAD genes in tomato and 57 AtDEAD genes in Arabidopsis, 56 StDEAD genes in potato, and 54 CaDEAD genes in pepper. The result indicates that the DEAD gene family in tomato is more closely related to that of Solanaceae plants than to that of Arabidopsis.
According to the annotation information in the tomato genome, we found that the 42 SlDEAD genes were unevenly distributed across the 12 chromosomes (Figure 4). No correlation between the length of the chromosome and the number of SlDEAD genes was detected. The maximum number of eight SlDEAD genes was discovered on chromosome 12, followed by five SlDEAD genes on each of chromosomes 1, 2, and 10. However, no SlDEAD genes were mapped to chromosome 11. Multiple SlDEAD gene clusters were located at the distal end of the tomato chromosomes. For example, SlDEAD30, SlDEAD31, SlDEAD32, and SlDEAD33 were clustered in the extreme end region of chromosome 10. A similar phenomenon was noted in potato and pepper. Clusters of StDEAD and CaDEAD genes were detected on diverse chromosomes within their genomes.

2.3. Gene Structure and Conserved Motif Analysis of Tomato SlDEAD Genes

Among the 42 SlDEAD genes, only SlDEAD6, SlDEAD9, and SlDEAD42 lack introns (Table 1). The remaining SlDEAD genes contain various numbers of introns. Specifically, SlDEAD14 contains as many as 26 introns, while the others have at least one intron each (Table 1). The sequences of SlDEAD18, SlDEAD28, and SlDEAD32 exceeded 10 kb in length, possibly due to the presence of relatively large introns. To explore the cis-regulatory elements responsible for their potential functions, the 2 kb DNA sequences upstream of the corresponding SlDEAD genes were analyzed (Figure 5). A large number of cis-acting elements, such as hormone response, light response, and stress-related elements, were identified in the promoter regions of SlDEAD genes. Among them, light response elements are the most prominent in all SlDEAD family genes, suggesting the expression of SlDEAD genes might be closely tied to light. Additionally, anoxic-induced elements and elements responsive to MeJA, ABA, and GA were detected in the majority of SlDEAD genes, suggesting a possible role of these SlDEAD proteins in hormone signaling and stress response.

2.4. Subcellular Localization of SlDEAD Proteins

Subcellular localization prediction suggests that 27 SlDEAD proteins might be located in the nucleus, while the others are distributed in the cytoplasm, mitochondria, and chloroplast (Table 1). Since subcellular localization can provide additional clues into their potential functions, seven SlDEADs, including SlDEAD7, SlDEAD14, SlDEAD17, SlDEAD25, SlDEAD26, SlDEAD35, and SlDEAD40, were selected for experimental verification in conjunction with organelle marker genes (Figure 6). The results show that SlDEAD7, SlDEAD14, and SlDEAD26 were localized in the endoplasmic reticulum (ER), while SlDEAD17, SlDEAD25, and SlDEAD35 were targeted at the chloroplast. Only the localization of SlDEAD17 and SlDEAD25 was consistent with the localization prediction. On the other hand, SlDEAD40 was found to be located in both the ER and the nucleus. The results indicate that SlDEADs may perform diverse functions with specific localization in various organelles.

2.5. Expression Pattern of SlDEAD Genes in Response to High-Temperature Stress

To determine whether these SlDEADs respond to heat stress, we analyzed their expression levels in tomato leaves during the early stage of high-temperature treatment. The expression levels of SlDEAD5, SlDEAD6, SlDEAD12, SlDEAD16, SlDEAD19, and SlDEAD21 genes in tomato leaves were too low to be precisely detected under both normal and high-temperature stress conditions by RT-qPCR. These genes were thus excluded from the analysis. The RT-qPCR results (Figure 7 and Figure 8) reveal that the expression of all the remaining 37 SlDEAD genes responded to high-temperature treatment to varying extents. Based on their expression patterns at 1, 3, 6, and 12 h post-treatment (hpt) at high temperatures, we classified the 37 SlDEAD genes into five groups. Group 1 contained seven SlDEAD genes (Figure 7A), including SlDEAD1, SlDEAD9, SlDEAD11, SlDEAD13, SlDEAD24, SlDEAD37, and SlDEAD41. Their expression exhibited a dynamic pattern, with a significant increase at 1 or 6 hpt and a return to baseline expression at 12 hpt. Both groups 2 and 3 consisted of eight SlDEAD genes (Figure 7B,C). These SlDEAD genes were continuously activated during the first 12 h. The difference in the expression pattern between groups 2 and 3 was whether the expression of the genes at 12 hpt was significantly decreased compared to 6 hpt. Twelve SlDEAD genes, including SlDEAD3, SlDEAD4, SlDEAD10, SlDEAD12, SlDEAD17, SlDEAD18, SlDEAD25, SlDEAD28, SlDEAD32, SlDEAD33, SlDEAD38, and SlDEAD39, were classified into group 4. Their expression was suppressed at 1 hpt but then increased at 3 and 6 hpt. The other two SlDEAD genes, SlDEAD30 and SlDEAD40, exhibited a continuous downregulation during the first 12 h. The results suggest that most of the SlDEAD family genes respond to heat stress, and the diverse expression patterns under heat stress may indicate their varied roles in the tomato’s response to heat stress.

3. Discussion

DEAD-box RNA helicases are a class of highly conserved enzymes that rely on their activities of ATPase to perform a broad range of functions in most RNA metabolic processes. Over the past few years, significant research efforts have been dedicated to understanding their functions and mechanisms. Notably, recent studies have reported that DEAD-box family proteins can modulate phase separation by regulating their own domains in an ATP-bound state, which, in turn, enables the selective recruitment or release of free proteins and nucleic acids within cells, as demonstrated in [46]. In this study, we identified 42 DEAD family genes from tomatoes and constructed evolutionary trees in comparison with 57 DEAD genes from Arabidopsis, 118 genes from soybean, 53 genes from rice, 56 genes from potato, and 54 genes from pepper. The presence of a large RNA helicase gene family across these species strongly suggests that RNA helicases are likely to play pivotal regulatory roles in multiple aspects of plant growth and development. From the results of phylogenetic and collinear analyses, it is evident that most DEAD genes within the same cluster share similar characteristics (Figure 1 and Figure 2). Specifically, 57 and 59 collinear pairs, respectively, were detected in the collinearity analysis between tomato and potato, as well as tomato and peppers. In contrast, a considerably lower number of collinear pairs was observed between tomato and Arabidopsis. The functional diversity of DEAD gene family members in tomato might be attributed to structural disparities among genes. For example, SlDEAD15 contains 18 introns, while SlDEDA6 and SlDEDA42 are intron-less. In the sequence comparison of SlDEAD, there were six pairs of segmental and tandem duplication events in tomatoes involving 11 related genes. Moreover, the number of cis-acting elements enriched in the promoter sequences of different genes exhibited substantial variation. Collectively, the tomato DEAD gene has maintained a certain level of conservation throughout the evolutionary history of plants, albeit accompanied by a degree of genetic variation, which likely contributes to the adaptive evolution and functional diversification of this gene family in the context of tomato plants.
The conserved motifs within the DEAD family genes play a crucial role in modulating gene function [28]. The DEAD family harbors nine conserved motifs that are arranged in a precise order. Among them, motifs II, I, Q, and VI are indispensable for ATP binding and hydrolysis. In contrast, motifs Ia, Ib, III, IV, and V exhibit lower specificity but may participate in RNA interaction and the remodeling of ribonucleic acid molecules [21]. Motif I is critical for ATPase and helicase activity. Mutations in either the first alanine, the conserved lysine, or the last threonine result in the loss of ATPase activity, primarily due to a reduction in the affinity and hydrolysis rate of motif I for ATP [47,48]. Based on the analysis of motifs in tomato SlDEADs, we found that the first amino acid in SlDEAD21 and SlDEAD39 is serine, whereas in other genes, it is alanine, with a high degree of conservation. This disparity might lead to alterations in helicase activity. Although motif Ia is not directly engaged in ATP binding and hydrolysis, it is essential for RNA binding in conjunction with motifs IV and V [49]. Among the tomato DEAD family proteins, the alanine within motif Ia is predominantly converted into cysteine (C), serine (S), and valine (V) (Supplementary Figure S1). As a pivotal motif, motif III is involved in the coupling of ATPase and helicase activities. The mutation of specific amino acids within this motif leads to a complete loss of helicase activity, while the effects on ATP binding, hydrolysis, and RNA binding are relatively minor [50]. It was reported that replacing serine and threonine of the Has1 motif III with alanine slightly reduced ATP binding, hydrolysis, and RNA binding but marginally diminished helicase activity [50]. The first amino acid of motif III in SlDEAD17 is alanine, whereas it is threonine in SlDEAD2, SlDEAD10, SlDEAD36, and SlDEAD39 (Supplementary Figure S1). Taken together, the conserved motifs in tomato SlDEADs deviate slightly from those of the known DEAD helicases. Whether these modifications directly impact binding to RNA needs further investigation.
In recent years, extensive investigations into DEAD-box RNA helicases have uncovered their multifunctional characteristics. Notably, these enzymes function as crucial mediators among diverse aspects of RNA metabolism and serve as central nodes connecting multiple cellular processes [28]. For instance, some DEAD-box proteins have been reported to participate in RNA processing and maturation and mRNA transport. The eukaryotic DEAD-box protein DDX17 binds to a specific subgroup of pre-miRNA containing the VCAUCH motif and promotes its maturation through the formation of a microprocessor complex [51]. The overexpression of OsRH42 within the nucleus facilitates the splicing of pre-mRNA at low temperatures, thereby regulating the expression of stress-resistant genes under low-temperature conditions [33]. Except for their involvement in RNA processing, eIF4A-I and its closely related counterpart eIF4A-III, which are regarded as the smallest helicases, utilize their helicase activity to resolve the secondary structures in the 5′UTRs of mRNA during cap-dependent translation initiation [52]. eIF4A-III (DDX48) can be recruited by CTIF1 to the 5′ termini of mRNA bound by the nuclear-cap-binding complex (CBC), thereby enhancing translation [53].
Due to their roles in modulating RNA metabolism, DEAD-box RNA helicases are widely involved in plant responses to diverse stresses. A number of RNA helicases have been identified as highly promising candidates that endow plants with multiple stress tolerances. For example, OsABP in rice [54], PDH45 in chili peppers [55], and SlDEAD30 and SlDEAD31 [42] in tomatoes have the capacity to enhance tolerance to a variety of abiotic stresses such as drought, cold, and salinity. In this study, diverse cis-regulatory elements were identified within the SlDEAD genes (Figure 5). These results indicate that these genes may have distinct expression patterns under different conditions, encompassing growth, development, and stress-response aspects. These results imply that the SlDEAD family genes play a crucial role in regulating the tolerance of tomatoes to various stresses.
The subcellular localization of proteins is closely associated with their function. Distinct subcellular localizations define the specific physiological processes in which the corresponding proteins are involved. Previous research reveals that nucleus-localized OsRH42 helps in the splicing of pre-mRNA at low temperatures, thereby regulating cold-responsive gene expression [33]. The chloroplast-targeted DEAD-box RNA helicase SlDEAD39 participates in the processing of chloroplast 23S rRNA and affects the structure of cells and chloroplasts. Its mutant shows a chlorosis phenotype at the cotyledon stage with a reduced photosynthetic capacity and a significant inhibition of tomato growth [41]. Tomato SlRBP1 binds to a large number of RNAs related to chloroplast functions, channels RNA onto the SleIF4A2 translation initiation complex, and promotes the translation of its target RNAs to regulate chloroplast function. SlRBP1 knockdown mutants (SlRBP1) exhibit phenotypes of the reduced accumulation of total chlorophyll and impaired chloroplast ultrastructure [56]. Based on the result of subcellular localization prediction (Table 1), the majority of SlDEAD proteins were predominantly located in the nucleus, followed by chloroplasts, mitochondria, and cytoplasm. As shown in the subcellular localization utilizing transient expression in tobacco leaves, most of the tested SlDEAD proteins exhibited a different localization from the result of prediction. For example, SlDEAD40, which was predicted to be localized in the nucleus, was actually found in the endoplasmic reticulum in addition to the nucleus (Figure 6). It is thus proposed that SlDEAD40 might be involved in RNA splicing in the nucleus and RNA translation in the ER. Similarly, chloroplast-targeted SlDEAD35 may participate in the regulation of chloroplast RNA and affect plant photosynthesis under stress. Therefore, the results of subcellular localization provide a more precise basis for elucidating the functions of SlDEAD proteins.
The analysis of cis-acting elements that regulate gene expression patterns through interaction with various transcriptional factors and other regulatory molecules may reveal the potential to determine their abilities to regulate plants’ adaptation to various environmental stresses and developmental signals [57]. In this study, diverse cis-regulatory elements were identified within the SlDEAD genes (Figure 5), which indicates that these genes may have distinct expression patterns under different conditions, encompassing growth, development, and stress-response aspects. Notably, among the cis-acting elements within the SlDEAD genes, the quantity of light-responsive elements was the highest, suggesting that SlDEAD family genes may respond to light stimuli. Moreover, a number of stress-response elements, such as wound-responsive elements, elements related to drought inducibility, and anaerobic induction, as well as those associated with defense and stress responsiveness, were highly enriched. Additionally, several hormone response elements, including those responsible for auxin responsiveness, abscisic acid responsiveness, gibberellin-responsive elements, elements involved in zein metabolism regulation, and salicylic acid responsiveness, were abundantly present. These results imply that the SlDEAD family genes play a crucial role in regulating the tolerance of tomatoes to various stresses. Further verification of their expression patterns under various conditions is required in future studies.
High-temperature stress is one of the major abiotic stresses exacerbated by climate change. Under high-temperature stress, the gene expression within cells is significantly disrupted, leading to disorder in the overall transcription and translation processes of crops [58]. Heat stress can also trigger the formation of stress granules [59]. The formation and assembly of stress granules (SGs) are reversible, affording the cell the capacity to sequester mRNA in the form of complexes within SGs under adverse conditions. When normal conditions are restored, the mRNA can be released from SGs and may either enter the degradation pathway or re-enter the translation cycle [60]. Given their primary roles in regulating post-transcriptional processing and the stability of RNAs [31,61], DEAD-box RNA helicases are possibly a crucial factor in modulating plant tolerance to high-temperature stress. For example, high-temperature stress can suppress the expression of the DEAD-box RNA helicases STRS1 and STRS2 in Arabidopsis [62]. In the mutants of STRS1 and STRS2, the transcriptional levels of the heat-responsive genes HSP101, HSF4, and HSF7 were remarkably elevated, thereby enhancing the mutants’ tolerance to high temperatures. eIF4E is a highly characteristic RNA helicase in translation initiation [63]. After 30 min of heat stress, eIF4E and polyA+ mRNA become concentrated in cytoplasmic granules [64]. DEAD-box RNA helicases also act as RNA chaperones, actively resolving misfolded RNA structures. In rice, an increase in temperature directly augments helicase activity, and the expression of TOGR1 (Thermo-Tolerant Growth Required1) helicase is closely related to diurnal temperature fluctuations [65]. The nucleus-localized TOGR1 was further found to interact with the small subunit (SSU) pre-rRNA processome, which facilitates the correct folding of pre-rRNA and thus maintains rRNA homeostasis at high temperatures [65].
The expression pattern of target genes under specific stress conditions can effectively assist in screening for relevant resistance genes. Building on this, genes that exhibit significant up- or downregulation in response to stress are likely to play crucial roles in the plants’ adaptive mechanisms. In this study, we investigated whether the expression of SlDEAD genes responds to high-temperature stress. Our investigation reveals that the expression levels of the majority of SlDEAD genes exhibited dynamic changes over time and presented diverse trends (Figure 7 and Figure 8). A subset of genes, exemplified by SlDEAD30 and SlDEAD40, was significantly downregulated under high-temperature induction. Their downregulation suggests they may have a negative impact on high-temperature tolerance. A similar phenomenon was also reported in DEAD genes in rice in response to various stresses, in which the expression level of OsRH53 in rice declined under abiotic stresses such as drought, salt, cold, UV, and ABA treatments [66]. The majority of SlDEAD family genes showed an increasing trend within the 12 h period of high-temperature treatment, although their response times were sequential. Additionally, some SlDEAD genes exhibited at least one expression peak, suggesting the expression of these SlDEAD genes was dynamically regulated in the early phase of heat stress. This may be in accordance with the function of DEAD family genes during continual changes in RNA metabolism and post-transcriptional modulation.
Temperature is one of the key physical parameters influencing life on the Earth. Over the past few decades, high-temperature stress has led to a 5.5% and 3.8% decline in global wheat and corn production, respectively [25]. For every 1 °C rise in the global average temperature, the global yields of wheat, rice, corn, and soybeans are expected to decrease by an average of 6.0%, 3.2%, 7.4%, and 3.1% [26]. Developing heat-tolerant varieties is thus one of the fundamental approaches for plants to cope with high-temperature stress. Through an extensive investigation of the early response of tomato DEAD-box RHs to heat stress, this study identifies a number of highly promising candidate genes for potential genetic engineering and marker-assisted breeding. Genetic engineering technologies such as CRISPR/Cas9 have revolutionized plant breeding by enabling the precise manipulation of target genes [67]. With the application of these advanced genetic tools, the identified candidate genes can be effectively integrated into the revolution, which will endow the genetically engineered tomatoes with enhanced heat tolerance.

4. Materials and Methods

4.1. Plant Materials and Heat Stress Treatment

Tomato seeds of Ailsa Craig were sown in pots and cultivated within a plant growth chamber under a photoperiod of 16 h of light (22000Lx) at 28 °C and 8 h of darkness at 18 °C. When the seedlings reached the three-leaf stage, the seedlings were transferred to a 40 °C incubator with a relative humidity of 70% for a 12 h treatment. Tomato leaves were harvested from three individual seedlings at 0, 1, 3, 6, 9, and 12 h after treatment. The harvested leaves were rapidly frozen in liquid nitrogen and then stored at −80 °C.

4.2. Analysis of DEAD Family Gene Structures

The phylogenetic tree of DEAD family genes identified in different species, including Arabidopsis, rice, soybean, tomato, pepper, and potato, was constructed. The sequence of each DEAD gene was downloaded from the NCBI online website (https://www.ncbi.nlm.nih.gov/ accessed on 30 March 2025) and then subjected to phylogenetic analysis using the MEGA7 maximum likelihood method. Interspecific and intraspecific gene collinearity analysis was carried out based on the genomic files downloaded from the BRAD database (http://brassicadb.cn/#/, accessed on 30 March 2025) and visualized using Circos. Maps of the tomato DEAD gene structure and chromosome localization were visualized using TBtools software (https://bio.tools/tbtools, accessed on 30 March 2025). The cis-element analysis within the promoter region of each SlDEAD gene was analyzed using PlantCARE (http://bioinformatics.psb.ugent.be/webtools/plantcare/html/, accessed on 30 March 2025) and visualized using TBtools software.

4.3. Analysis of SlDEAD Protein Properties

The protein sequence of each DEAD member was downloaded from the NCBI website. Their physicochemical properties, including their relative molecular weight, isoelectric point, and stability were analyzed using the online software on the website Expasy (https://www.expasy.org/ accessed on 13 October 2023). The conserved domain of each SlDEAD was analyzed by CD-Search (https://www.ncbi.nlm.nih.gov/Structure/bwrpsb/bwrpsb.cgi, accessed on 13 October 2023) and visualized using TBtools software. Identification of the conserved motifs in DEAD-box proteins [21,68] was performed using the online MEME Suite (https://meme-suite.org/meme/, accessed on 13 October 2023) [69].

4.4. RT-qPCR Analysis

Total RNA was isolated from leaves using the Trizol reagent according to the manufacturer’s instructions (Vazyme Biotech, Beijing, China; cat. No. 7E0661A4) and reverse transcribed to cDNA using a 5 x All-in-one qRT SuperMix (Vazyme Biotech, Beijing, China; cat. No. 7E782C3). RT-qPCR was performed using Power SYBR Green PCR Master Mix (Vazyme Biotech, Beijing, China; cat. No. Q312-02-AA) on a quantitative PCR system (qTower3, Analytik, Jena, Germany). The Actin gene was used as the internal control for the calculation of relative expression. The data were analyzed with the 2−ΔΔCt method [70]. For each primer pair, three technical replicate RT-qPCR reactions were conducted. Detailed information on the primer sequences is presented in Supplementary Table S1.

4.5. Subcellular Localization Analysis

The full-length sequences of the SlDEAD7, SlDEAD14, SlDEAD17, SlDEAD25, SlDEAD26, SlDEAD35, and SlDEAD40 genes were amplified using the specific primers shown in Supplementary Table S1 and cloned into pEarlyGate103 vector via gateway technology for GFP-fused expression. Agrobacterium GV3101 carrying GFP-DEAD fusion expression vectors were cultured overnight and adjusted to an OD600 of 0.8 for tobacco (Nicotiana benthamiana) leaf injection. The infected tobacco leaves were collected after 48 h and then observed under a laser confocal microscope (FluoView™ FV3000, Olympus, Tokyo, Japan) at a 40× objective magnification. Vectors with HDEL-RFP and H2B-RFP fusion proteins were used as the markers of the endoplasmic reticulum and nucleus, respectively [71]. The fluorescence images of GFPs and RFPs were captured under excitation laser wavelengths of 488 nm and 561 nm, respectively. To localize chloroplasts, the autofluorescence of the chloroplasts in the tobacco leaves was detected in the red wavelength range (600–720 nm).

4.6. Statistical Analysis

Statistical analysis was performed using SPSS Statistics (Version 17.0; SPSS Inc., Chicago, IL, USA). All data presented herein are the averages and standard errors derived from three biological replicates. The significant differences (p-value < 0.05) among samples were determined based on Duncan multiple range tests [72].

5. Conclusions

In this study, 42 SlDEAD genes were identified from the tomato genome, and a comprehensive analysis was conducted on their genetic relationships, chromosomal locations, conserved motifs, gene structures, and cis-regulatory elements, as well as their expression patterns. Despite the variations in the chromosome distribution, gene structure, and cis-elements among them, the 42 SlDEAD proteins all possess highly conserved domains. Taking the response to high-temperature stress as a case in point, it was found that, excluding the genes with low expression levels, the remaining 37 genes could be categorized into five groups based on the variation trends at different time points after high-temperature stress. After observing the subcellular localization of seven representative SlDEAD proteins, at least four of the SlDEAD genes were found to be located in the endoplasmic reticulum, three were located in the chloroplast, and one was located in the nucleus. These findings extend our understanding of the functional divergence and evolution of the DEAD gene family in tomato and reveal some candidate DEAD genes for future research on plant tolerance to abiotic stress.

Supplementary Materials

The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/plants14081172/s1, Table S1: List of primer sequences used in the study. Table S2: List of gene duplication pairs of SlDEAD genes between tomato and other species. Figure S1: Sequence alignment of 42 SlDEAD proteins identified from tomato genome.

Author Contributions

Conceptualization and writing—review and editing, L.T.; writing—original draft, Y.Y.; data acquisition and curation, Y.Y. and C.Y.; plant materials and treatment, C.Y., B.X., H.Z. and C.Z. All authors have read and agreed to the published version of the manuscript.

Funding

This work was financially supported by the Natural Science Foundation of Zhejiang Province (Grant No. LQ23C150002), the National Natural Science Foundation of China (Grant No. 32302525), and the Zhejiang A&F University Starting Funds of Scientific Research and Development (Grant No. 203402000101 and 2021LFR061).

Data Availability Statement

The original contributions presented in this study are included in the article and Supplementary Materials.

Acknowledgments

We thank Weipeng Wang (Huazhong Agricultural University) for providing the subcellular localization of markers.

Conflicts of Interest

The authors declare no conflicts of interest.

References

  1. Ding, Y.; Yang, S. Surviving and thriving: How plants perceive and respond to temperature stress. Dev. Cell 2022, 57, 947–958. [Google Scholar] [CrossRef] [PubMed]
  2. Zhang, J.; Lee, K.P.; Liu, Y.; Kim, C. Temperature-driven changes in membrane fluidity differentially impact FILAMENTATION TEMPERATURE-SENSITIVE H2-mediated photosystem II repair. Plant Cell 2025, 37, koae323. [Google Scholar] [CrossRef] [PubMed]
  3. Xu, J. Long-term mild heat causes post-mitotic pollen abortion through a local effect on flowers. Front. Plant Sci. 2022, 13, 925754. [Google Scholar] [CrossRef]
  4. Katano, K.; Honda, K.; Suzuki, N. Integration between ROS regulatory systems and other signals in the regulation of various types of heat responses in plants. Int. J. Mol. Sci. 2018, 19, 3370. [Google Scholar] [CrossRef]
  5. Schroda, M.; Vallon, O.; Wollman, F.-A.; Beck, C.F. A chloroplast-targeted Heat Shock Protein 70 (HSP70) contributes to the photoprotection and repair of Photosystem II during and after Photoinhibition. Plant Cell 1999, 11, 1165–1187. [Google Scholar] [CrossRef]
  6. Sato, H.; Mizoi, J.; Tanaka, H.; Maruyama, K.; Qin, F.; Osakabe, Y.; Morimoto, K.; Ohori, T.; Kusakabe, K.; Nagata, M. Arabidopsis DPB3-1, a DREB2A interactor, specifically enhances heat stress-induced gene expression by forming a heat stress-specific transcriptional complex with NF-Y subunits. Plant Cell 2014, 26, 4954–4973. [Google Scholar] [CrossRef]
  7. Schramm, F.; Larkindale, J.; Kiehlmann, E.; Ganguli, A.; Englich, G.; Vierling, E.; Koskull-Döring, P.V. A cascade of transcription factor DREB2A and heat stress transcription factor HsfA3 regulates the heat stress response of Arabidopsis. Plant J. 2008, 53, 264–274. [Google Scholar] [CrossRef] [PubMed]
  8. Aldubai, A.A.; Alsadon, A.A.; Migdadi, H.H.; Alghamdi, S.S.; Al-Faifi, S.A.; Afzal, M. Response of tomato (Solanum lycopersicum L.) genotypes to heat stress using morphological and expression study. Plants 2022, 11, 615. [Google Scholar] [CrossRef]
  9. Marondedze, C. The increasing diversity and complexity of the RNA-binding protein repertoire in plants. Proc. R. Soc. B Biol. Sci. 2020, 287, 20201397. [Google Scholar] [CrossRef]
  10. Yan, Y.; Gan, J.; Tao, Y.; Okita, T.W.; Tian, L. RNA-Binding Proteins: The Key Modulator in Stress Granule Formation and Abiotic Stress Response. Front. Plant Sci. 2022, 13, 882596. [Google Scholar] [CrossRef]
  11. Muthusamy, M.; Kim, J.H.; Kim, J.A.; Lee, S.I. Plant RNA binding proteins as critical modulators in drought, high salinity, heat, and cold stress responses: An updated overview. Int. J. Mol. Sci. 2021, 22, 6731. [Google Scholar] [CrossRef] [PubMed]
  12. Zheng, M.; Song, Y.; Wang, L.; Yang, D.; Yan, J.; Sun, Y.; Hsu, Y.F. CaRH57, a RNA helicase, contributes pepper tolerance to heat stress. Plant Physiol. Biochem. 2023, 205, 108202. [Google Scholar] [CrossRef] [PubMed]
  13. Thatcher, L.F.; Kamphuis, L.G.; Hane, J.K.; Oñate-Sánchez, L.; Singh, K.B. The Arabidopsis KH-domain RNA-binding protein ESR1 functions in components of jasmonate signalling, unlinking growth restraint and resistance to stress. PLoS ONE 2015, 10, e0126978. [Google Scholar] [CrossRef] [PubMed]
  14. Mu, F.; Zheng, H.; Zhao, Q.; Zhu, M.; Dong, T.; Kai, L.; Li, Z. Genome-wide systematic survey and analysis of the RNA helicase gene family and their response to abiotic stress in sweetpotato. BMC Plant Biol. 2024, 24, 193. [Google Scholar] [CrossRef]
  15. You, L.; Shi, C.; Wang, D.; Fu, Z.Q. Helicases clear hurdles during plant defense protein translation. Trends Biochem. Sci. 2024, 49, 192–194. [Google Scholar] [CrossRef]
  16. Li, X.; Li, C.; Zhu, J.; Zhong, S.; Zhu, H.; Zhang, X. Functions and mechanisms of RNA helicases in plants. J. Exp. Bot. 2023, 74, 2295–2310. [Google Scholar] [CrossRef]
  17. Umate, P.; Tuteja, R.; Tuteja, N. Genome-wide analysis of helicase gene family from rice and Arabidopsis: A comparison with yeast and human. Plant Mol. Biol. 2010, 73, 449–465. [Google Scholar] [CrossRef] [PubMed]
  18. Xu, R.; Zhang, S.; Huang, J.; Zheng, C. Genome-wide comparative in silico analysis of the RNA helicase gene family in Zea mays and Glycine max: A comparison with Arabidopsis and Oryza sativa. PLoS ONE 2013, 8, e78982. [Google Scholar] [CrossRef]
  19. Chen, J.; Zhang, Y.; Liu, J.; Xia, M.; Wang, W.; Shen, F. Genome-wide analysis of the RNA helicase gene family in Gossypium raimondii. Int. J. Mol. Sci. 2014, 15, 4635–4656. [Google Scholar] [CrossRef]
  20. Linder, P.; Owttrim, G.W. Plant RNA helicases: Linking aberrant and silencing RNA. Trends Plant Sci. 2009, 14, 344–352. [Google Scholar] [CrossRef]
  21. Cordin, O.; Banroques, J.; Tanner, N.K.; Linder, P. The DEAD-box protein family of RNA helicases. Gene 2006, 367, 17–37. [Google Scholar] [CrossRef] [PubMed]
  22. Jankowsky, A.; Guenther, U.P.; Jankowsky, E. The RNA helicase database. Nucleic Acids Res. 2011, 39, D338–D341. [Google Scholar] [CrossRef]
  23. Tanner, N.K. The newly identified Q motif of DEAD box helicases is involved in adenine recognition. Cell Cycle 2003, 2, 18–19. [Google Scholar] [CrossRef] [PubMed]
  24. Rocak, S.; Linder, P. DEAD-box proteins: The driving forces behind RNA metabolism. Nat. Rev. Mol. Cell Biol. 2004, 5, 232–241. [Google Scholar] [CrossRef]
  25. Guan, Q.; Wu, J.; Zhang, Y.; Jiang, C.; Liu, R.; Chai, C.; Zhu, J. A DEAD box RNA helicase is critical for pre-mRNA splicing, cold-responsive gene regulation, and cold tolerance in Arabidopsis. Plant Cell 2013, 25, 342–356. [Google Scholar] [CrossRef]
  26. Lorsch, J.R. RNA chaperones exist and DEAD box proteins get a life. Cell 2002, 109, 797–800. [Google Scholar] [CrossRef]
  27. Wang, H.; Ye, T.; Guo, Z.; Yao, Y.; Tu, H.; Wang, P.; Zhang, Y.; Wang, Y.; Li, X.; Li, B.; et al. A double-stranded RNA binding protein enhances drought resistance via protein phase separation in rice. Nat. Commun. 2024, 15, 2514. [Google Scholar] [CrossRef] [PubMed]
  28. Sloan, K.E.; Bohnsack, M.T. Unravelling the Mechanisms of RNA Helicase Regulation. Trends Biochem. Sci. 2018, 43, 237–250. [Google Scholar] [CrossRef]
  29. Pandey, S.; Muthamilarasan, M.; Sharma, N.; Chaudhry, V.; Dulani, P.; Shweta, S.; Jha, S.; Mathur, S.; Prasad, M. Characterization of DEAD-box family of RNA helicases in tomato provides insights into their roles in biotic and abiotic stresses. Environ. Exp. Bot. 2019, 158, 107–116. [Google Scholar] [CrossRef]
  30. Hou, X.L.; Chen, W.Q.; Hou, Y.; Gong, H.Q.; Sun, J.; Wang, Z.; Zhao, H.; Cao, X.; Song, X.F.; Liu, C.M. DEAD-BOX RNA HELICASE 27 regulates microRNA biogenesis, zygote division, and stem cell homeostasis. Plant Cell 2021, 33, 66–84. [Google Scholar] [CrossRef]
  31. Iserman, C.; Desroches Altamirano, C.; Jegers, C.; Friedrich, U.; Zarin, T.; Fritsch, A.W.; Mittasch, M.; Domingues, A.; Hersemann, L.; Jahnel, M.; et al. Condensation of Ded1p promotes a translational switch from housekeeping to stress protein production. Cell 2020, 181, 818–831. [Google Scholar] [CrossRef] [PubMed]
  32. Li, D.; Liu, H.; Zhang, H.; Wang, X.; Song, F. OsBIRH1, a DEAD-box RNA helicase with functions in modulating defence responses against pathogen infection and oxidative stress. J. Exp. Bot. 2008, 59, 2133–2146. [Google Scholar] [CrossRef] [PubMed]
  33. Lu, C.A.; Huang, C.K.; Huang, W.S.; Huang, T.S.; Liu, H.Y.; Chen, Y.F. DEAD-Box RNA helicase 42 plays a critical role in pre-mRNA splicing under cold stress. Plant Physiol. 2020, 182, 255–271. [Google Scholar] [CrossRef]
  34. Baek, W.; Lim, C.W.; Lee, S.C. A DEAD-box RNA helicase, RH8, is critical for regulation of ABA signalling and the drought stress response via inhibition of PP2CA activity. Plant Cell Environ. 2018, 41, 1593–1604. [Google Scholar] [CrossRef] [PubMed]
  35. Lee, S.C.; Lim, C.W.; Lan, W.Z.; He, K.; Luan, S. ABA signaling in guard cells entails a dynamic protein-protein interaction relay from the PYL-RCAR family receptors to ion channels. Mol. Plant 2013, 6, 528–538. [Google Scholar] [CrossRef]
  36. Lee, S.C.; Luan, S. ABA signal transduction at the crossroad of biotic and abiotic stress responses. Plant Cell Env. 2012, 35, 53–60. [Google Scholar] [CrossRef]
  37. Huang, C.K.; Shen, Y.L.; Huang, L.F.; Wu, S.J.; Yeh, C.H.; Lu, C.A. The DEAD-Box RNA helicase AtRH7/PRH75 participates in pre-rRNA processing, plant development and cold tolerance in Arabidopsis. Plant Cell Physiol. 2016, 57, 174–191. [Google Scholar] [CrossRef]
  38. Xiaomei, W.; Rongrong, K.; Ting, Z.; Yuanyuan, G.; Jianlong, X.; Zhongze, P.; Gangseob, L.; Dongzhi, L.; Yanjun, D. A DEAD-box RNA helicase TCD33 that confers chloroplast development in rice at seedling stage under cold stress. J. Plant Physiol. 2020, 248, 153138. [Google Scholar] [CrossRef]
  39. José, O.G.A.; Nieves, F.G.; Carmen, L.B.; Isabel, E.; Francisco, B.F.; Trinidad, A.; Juan, C.; Rafael, L.; Benito, P.; Vicente, M.; et al. The tomato res mutant which accumulates JA in roots in non-stressed conditions restores cell structure alterations under salinity. Physiol. Plant 2015, 155, 296–314. [Google Scholar] [CrossRef]
  40. Albaladejo, I.; Egea, I.; Morales, B.; Flores, F.B.; Capel, C.; Lozano, R.; Bolarin, M.C. Identification of key genes involved in the phenotypic alterations of res (restored cell structure by salinity) tomato mutant and its recovery induced by salt stress through transcriptomic analysis. BMC Plant Biol. 2018, 18, 213. [Google Scholar] [CrossRef]
  41. Capel, C.; Albaladejo, I.; Egea, I.; Massaretto, I.L.; Yuste-Lisbona, F.J.; Pineda, B.; Garcia-Sogo, B.; Angosto, T.; Flores, F.B.; Moreno, V.; et al. The res (restored cell structure by salinity) tomato mutant reveals the role of the DEAD-box RNA helicase SlDEAD39 in plant development and salt response. Plant Cell Environ. 2020, 43, 1722–1739. [Google Scholar] [CrossRef]
  42. Zhu, M.; Chen, G.; Dong, T.; Wang, L.; Zhang, J.; Zhao, Z.; Hu, Z. SlDEAD31, a Putative DEAD-Box RNA helicase gene, regulates salt and drought tolerance and stress-related genes in tomato. PLoS ONE 2015, 10, e0133849. [Google Scholar] [CrossRef] [PubMed]
  43. Xu, R.; Zhang, S.; Lu, L.; Cao, H.; Zheng, C. A genome-wide analysis of the RNA helicase gene family in Solanum lycopersicum. Gene 2013, 513, 128–140. [Google Scholar] [CrossRef]
  44. Cui, L.; Wall, P.K.; Leebens-Mack, J.H.; Lindsay, B.G.; Soltis, D.E.; Doyle, J.J.; Soltis, P.S.; Carlson, J.E.; Arumuganathan, K.; Barakat, A.; et al. Widespread genome duplications throughout the history of flowering plants. Genome Res. 2006, 16, 738–749. [Google Scholar] [CrossRef] [PubMed]
  45. Song, C.; Guo, J.; Sun, W.; Wang, Y. Whole genome duplication of intra- and inter-chromosomes in the tomato genome. J. Genet. Genom. 2012, 39, 361–368. [Google Scholar] [CrossRef]
  46. Hondele, M.; Sachdev, R.; Heinrich, S.; Wang, J.; Vallotton, P.; Fontoura, B.M.A.; Weis, K. DEAD-box ATPases are global regulators of phase-separated organelles. Nature 2019, 573, 144–148. [Google Scholar] [CrossRef]
  47. Caruthers, J.M.; McKay, D.B. Helicase structure and mechanism. Curr. Opin. Struct. Biol. 2002, 12, 123–133. [Google Scholar] [CrossRef]
  48. Cordin, O.; Tanner, N.K.; Monique, D.; Linder, P.; Banroques, J. The newly discovered Q motif of DEAD-box RNA helicases regulates RNA-binding and helicase activity. EMBO J. 2004, 23, 2478–2487. [Google Scholar] [CrossRef]
  49. Svitkin, Y.V.; Pause, A.; Haghighat, A.; Pyronnet, S.; Witherell, G.; Belsham, G.J.; Sonenberg, N. The requirement for eukaryotic initiation factor 4A (eIF4A) in translation is in direct proportion to the degree of mRNA 5′ secondary structure. RNA 2001, 7, 382–394. [Google Scholar] [CrossRef]
  50. Rocak, S.; Emery, B.; Tanner, N.K.; Linder, P. Characterization of the ATPase and unwinding activities of the yeast DEAD-box protein Has1p and the analysis of the roles of the conserved motifs. Nucleic Acids Res. 2005, 33, 999–1009. [Google Scholar] [CrossRef]
  51. Xing, Y.H.; Yao, R.W.; Zhang, Y.; Guo, C.J.; Chen, L.L. SLERT regulates DDX21 rings associated with Pol I transcription. Cell 2017, 169, 664–678. [Google Scholar] [CrossRef]
  52. Andreou, A.Z.; Klostermeier, D. The DEAD-box helicase eIF4A: Paradigm or the odd one out? RNA Biol. 2013, 10, 19–32. [Google Scholar] [CrossRef]
  53. Choe, J.; Ryu, I.; Park, O.H.; Park, J.; Cho, H.; Yoo, J.S.; Chi, S.W.; Kim, M.K.; Song, H.K.; Kim, Y.K. eIF4AIII enhances translation of nuclear cap-binding complex-bound mRNAs by promoting disruption of secondary structures in 5′UTR. Proc. Natl. Acad. Sci. USA 2014, 111, 4577–4586. [Google Scholar] [CrossRef] [PubMed]
  54. Macovei, A.; Tuteja, N. microRNAs targeting DEAD-box helicases are involved in salinity stress response in rice (Oryza sativa L.). BMC Plant Biol. 2012, 12, 183. [Google Scholar] [CrossRef]
  55. Shivakumara, T.N.; Sreevathsa, R.; Dash, P.K.; Sheshshayee, M.S.; Papolu, P.K.; Rao, U.; Tuteja, N.; Udayakumar, M. Overexpression of Pea DNA Helicase 45 (PDH45) imparts tolerance to multiple abiotic stresses in chili (Capsicum annuum L.). Sci. Rep. 2017, 7, 2760. [Google Scholar] [CrossRef]
  56. Ma, L.; Yang, Y.; Wang, Y.; Cheng, K.; Zhou, X.; Li, J.; Zhang, J.; Li, R.; Zhang, L.; Wang, K.; et al. SlRBP1 promotes translational efficiency via SleIF4A2 to maintain chloroplast function in tomato. Plant Cell 2022, 34, 2747–2764. [Google Scholar] [CrossRef]
  57. Wang, S.; Meng, Y.; Ding, F.; Yang, K.; Wang, C.; Zhang, H.; Jin, H. Comparative Analysis of TPR Gene Family in Cucurbitaceae and Expression Profiling under Abiotic Stress in Cucumis melo L. Horticulturae 2024, 10, 83. [Google Scholar] [CrossRef]
  58. Tong, J.J.; Ren, Z.T.; Linhua, S.; Zhou, S.X.; Yuan, W.; Hui, Y.F.; Ci, D.; Wang, W.; Fan, L.M.; Wu, Z.; et al. ALBA proteins confer thermotolerance through stabilizing HSF messenger RNAs in cytoplasmic granules. Nat. Plants 2022, 8, 778–791. [Google Scholar] [CrossRef]
  59. Samanta, N.; Ribeiro, S.; Becker, M.; Laborie, E.; Pollak, R.; Timr, S.; Sterpone, F.; Ebbinghaus, S. Sequestration of proteins in stress granules relies on the in-cell but not the in Vitro folding stability. J. Am. Chem. Soc. 2021, 143, 19909–19918. [Google Scholar] [CrossRef] [PubMed]
  60. Zhu, S.; Gu, J.; Yao, J.; Li, Y.; Zhang, Z.; Xia, W.; Wang, Z.; Gui, X.; Li, L.; Li, D.; et al. Liquid-liquid phase separation of RBGD2/4 is required for heat stress resistance in Arabidopsis. Dev. Cell 2022, 57, 583–597. [Google Scholar] [CrossRef] [PubMed]
  61. Vashisht, A.A.; Tuteja, N. Stress responsive DEAD-box helicases: A new pathway to engineer plant stress tolerance. J. Photochem. Photobiol. B Biol. 2006, 84, 150–160. [Google Scholar] [CrossRef] [PubMed]
  62. Kant, P.; Kant, S.; Gordon, M.; Shaked, R.; Barak, S. STRESS RESPONSE SUPPRESSOR1 and STRESS RESPONSE SUPPRESSOR2, two DEAD-box RNA helicases that attenuate Arabidopsis responses to multiple abiotic stresses. Plant Physiol. 2007, 145, 814–830. [Google Scholar] [CrossRef] [PubMed]
  63. Toribio, R.; Muñoz, A.; Castro-Sanz, A.B.; Merchante, C.; Castellano, M.M. A novel eIF4E-interacting protein that forms non-canonical translation initiation complexes. Nat. Plants 2019, 5, 1283–1296. [Google Scholar] [CrossRef]
  64. Weber, C.; Nover, L.; Fauth, M. Plant stress granules and mRNA processing bodies are distinct from heat stress granules. Plant J. 2008, 56, 517–530. [Google Scholar] [CrossRef]
  65. Wang, D.; Qin, B.; Li, X.; Tang, D.; Zhang, Y.e.; Cheng, Z.; Xue, Y. Nucleolar DEAD-Box RNA helicase TOGR1 regulates thermotolerant growth as a pre-rRNA chaperone in rice. PLoS Genet. 2016, 12, 23. [Google Scholar] [CrossRef]
  66. Nawaz, G.; Sai, T.Z.T.; Lee, K.; Kim, Y.O.; Kang, H.S. Rice DEAD-box RNA helicase OsRH53 has negative impact on Arabidopsis response to abiotic stresses. Plant Growth Regul. 2018, 85, 153–163. [Google Scholar] [CrossRef]
  67. Bortesi, L. and Fischer, R. The CRISPR/Cas9 system for plant genome editing and beyond. Biotechnol. Adv. 2015, 33, 41–52. [Google Scholar] [CrossRef]
  68. Tanner, N.K.; Cordin, O.; Banroques, J.; Doère, M.; Linder, P. The Q Motif: A newly identified motif in DEAD Box helicases may regulate ATP binding and hydrolysis. Mol. Cell 2003, 11, 127–138. [Google Scholar] [CrossRef]
  69. Si, Z.; Wang, L.; Ji, Z.; Zhao, M.; Zhang, K.; Qiao, Y. Comparative analysis of the MYB gene family in seven Ipomoea species. Front. Plant Sci. 2023, 14, 1155018. [Google Scholar] [CrossRef]
  70. Rao, X.; Huang, X.; Zhou, Z.; Lin, X. An improvement of the 2(-delta delta CT) method for quantitative real-time polymerase chain reaction data analysis. Biostat. Bioinforma Biomath. 2013, 3, 71–85. [Google Scholar]
  71. Guo, Y.; Bao, Z.; Deng, Y.; Li, Y.; Wang, P. Protein subcellular localization and functional studies in horticultural research: Problems, solutions, and new approaches. Hortic. Res. 2023, 10, uhac271. [Google Scholar] [CrossRef] [PubMed]
  72. Chen, S.-Y.; Chen, H.J. Single-stage analysis of variance under heteroscedasticity. Commun. Stat.-Simul. Comput. 2010, 27, 641–666. [Google Scholar] [CrossRef]
Figure 1. Phylogenetic tree and motif analysis of SlDEAD family. The evolutionary relationships among the SlDEAD proteins in tomato are presented on the left, and the classified groups are annotated on the right. The conserved motifs are depicted as colored boxes. The conserved amino acid sequence within each motif are gaccpohlQ in Q-motif, SxtGoGKt in motif I, PtreLk in motif Ia, TPmkl in motif Ib, DEAD in motif II, lisAT in motif III, llfhxq+cx in motif IV, Tdvu-bGld in motif V, and HR*GRsmR in motif VI. The symbols used in the animo acid sequence represent different combinations of amino acids, in which O is for S, T, M, or F; l is for I, L, V, or M; x is for any residue; a is for F, W, Y, M, L, or I; c is for D, E, H, K, or R; h is for A, F, G, I, L, M, P, V, W, Y, T, C, E, K, S, Q, or D; + is for H, K, R, V, I, L, C, Q, or A; u is for A, V, L, F, or S; v is for A, E, L, V, or I; d is for D, S, or N; b is for R or K; f is for F or Y; − is for A, V, S, G, or T; * is for V, I, S, T, or L; m is for A or G; + is for V, I, L, C, K, R, Q, A, or H; q is for T, S, N, R, Y, or K; k for A, C, R, T, or S; e is for M or E; t is for T, N, or S; and r is for R or V.
Figure 1. Phylogenetic tree and motif analysis of SlDEAD family. The evolutionary relationships among the SlDEAD proteins in tomato are presented on the left, and the classified groups are annotated on the right. The conserved motifs are depicted as colored boxes. The conserved amino acid sequence within each motif are gaccpohlQ in Q-motif, SxtGoGKt in motif I, PtreLk in motif Ia, TPmkl in motif Ib, DEAD in motif II, lisAT in motif III, llfhxq+cx in motif IV, Tdvu-bGld in motif V, and HR*GRsmR in motif VI. The symbols used in the animo acid sequence represent different combinations of amino acids, in which O is for S, T, M, or F; l is for I, L, V, or M; x is for any residue; a is for F, W, Y, M, L, or I; c is for D, E, H, K, or R; h is for A, F, G, I, L, M, P, V, W, Y, T, C, E, K, S, Q, or D; + is for H, K, R, V, I, L, C, Q, or A; u is for A, V, L, F, or S; v is for A, E, L, V, or I; d is for D, S, or N; b is for R or K; f is for F or Y; − is for A, V, S, G, or T; * is for V, I, S, T, or L; m is for A or G; + is for V, I, L, C, K, R, Q, A, or H; q is for T, S, N, R, Y, or K; k for A, C, R, T, or S; e is for M or E; t is for T, N, or S; and r is for R or V.
Plants 14 01172 g001
Figure 2. Phylogenetic tree of DEAD family genes derived from six species, including Arabidopsis thaliana, rice (Oryza sativa), soybean (Glycine max), and Solanaceae crops, like tomato (Solanum lycopersicum), pepper (Capsicum annuum), and potato (Solanum tuberosum). DEAD genes in tomato are indicated by *.
Figure 2. Phylogenetic tree of DEAD family genes derived from six species, including Arabidopsis thaliana, rice (Oryza sativa), soybean (Glycine max), and Solanaceae crops, like tomato (Solanum lycopersicum), pepper (Capsicum annuum), and potato (Solanum tuberosum). DEAD genes in tomato are indicated by *.
Plants 14 01172 g002
Figure 3. Collinearity analysis and chromosomal localization of SlDEAD genes in tomato. (A) Intra-species collinearity analysis of SlDEAD genes in tomato. The grey boxes represent the twelve chromosomes of tomato, and the numbers on the boxes represent the positions along the corresponding chromosomes. The gray lines denote the gene duplication pairs in the whole tomato genome, and the red lines highlight collinearity relationships of SlDEAD gene pairs. (B) Inter-species collinearity analysis of DEAD genes among tomato (Sl), Arabidopsis (At), S. tuberosum (St), and C. annuum (Ca). Grey lines represent the gene pair experiencing gene replication events between tomato and the other three species, and the red lines refer the gene pair experiencing gene replication events between the SlDEAD and DEAD genes from the other three species.
Figure 3. Collinearity analysis and chromosomal localization of SlDEAD genes in tomato. (A) Intra-species collinearity analysis of SlDEAD genes in tomato. The grey boxes represent the twelve chromosomes of tomato, and the numbers on the boxes represent the positions along the corresponding chromosomes. The gray lines denote the gene duplication pairs in the whole tomato genome, and the red lines highlight collinearity relationships of SlDEAD gene pairs. (B) Inter-species collinearity analysis of DEAD genes among tomato (Sl), Arabidopsis (At), S. tuberosum (St), and C. annuum (Ca). Grey lines represent the gene pair experiencing gene replication events between tomato and the other three species, and the red lines refer the gene pair experiencing gene replication events between the SlDEAD and DEAD genes from the other three species.
Plants 14 01172 g003
Figure 4. Distribution of the identified DEAD genes on twelve chromosomes of tomato (A), potato (B), and pepper (C). The chromosome number is denoted at the top of each chromosome, and gene names are presented on the right side of each chromosome. The scale on the left is calibrated in megabases (Mbs). Chr, chromosome.
Figure 4. Distribution of the identified DEAD genes on twelve chromosomes of tomato (A), potato (B), and pepper (C). The chromosome number is denoted at the top of each chromosome, and gene names are presented on the right side of each chromosome. The scale on the left is calibrated in megabases (Mbs). Chr, chromosome.
Plants 14 01172 g004
Figure 5. Cis-acting regulatory elements of the promoters of SlDEAD family genes. The analysis was conducted on the 2 kb upstream region of each genes using TBtools (v2.210) software. The distinct colors represent the quantity of each cis-acting element.
Figure 5. Cis-acting regulatory elements of the promoters of SlDEAD family genes. The analysis was conducted on the 2 kb upstream region of each genes using TBtools (v2.210) software. The distinct colors represent the quantity of each cis-acting element.
Plants 14 01172 g005
Figure 6. Subcellular localization of SlDEAD proteins. The SlDEAD proteins under investigation encompass SlDEAD7, SlDEAD14, SlDEAD17, SlDEAD25, SlDEAD26, SlDEAD35, and SlDEAD40. The endoplasmic reticulum is marked by HDEL-fused RFP, while the nucleus is labeled with RFP-fused H2B. The autofluorescence emanating from the chloroplast (Chlo) serves as an indicator for the presence and location of the chloroplast.
Figure 6. Subcellular localization of SlDEAD proteins. The SlDEAD proteins under investigation encompass SlDEAD7, SlDEAD14, SlDEAD17, SlDEAD25, SlDEAD26, SlDEAD35, and SlDEAD40. The endoplasmic reticulum is marked by HDEL-fused RFP, while the nucleus is labeled with RFP-fused H2B. The autofluorescence emanating from the chloroplast (Chlo) serves as an indicator for the presence and location of the chloroplast.
Plants 14 01172 g006
Figure 7. Expression profiles of SlDEAD family genes in tomato at 1, 3, 6, and 12 h post high-temperature stress treatment. (AC) depict the expression pattern (the first panel) and relative expression levels (rest of the panels) of SlDEAD family genes in groups 1, 2, and 3. The y-axis in the first panel represents the normalized expression values derived from RT-qPCR results. The relative expression of each SlDEAD gene was calculated based on RT-qPCR data obtained from three independent biological replicates. Letters above the bars indicate significant differences (p < 0.05) calculated by Duncan’s new multiple range test.
Figure 7. Expression profiles of SlDEAD family genes in tomato at 1, 3, 6, and 12 h post high-temperature stress treatment. (AC) depict the expression pattern (the first panel) and relative expression levels (rest of the panels) of SlDEAD family genes in groups 1, 2, and 3. The y-axis in the first panel represents the normalized expression values derived from RT-qPCR results. The relative expression of each SlDEAD gene was calculated based on RT-qPCR data obtained from three independent biological replicates. Letters above the bars indicate significant differences (p < 0.05) calculated by Duncan’s new multiple range test.
Plants 14 01172 g007
Figure 8. Expression profiles of SlDEAD family genes in tomato at 1, 3, 6, and 12 h post high-temperature stress treatment. (A,B) depict the expression pattern (the first panel) and relative expression levels (rest of the panels) of SlDEAD family genes in groups 4 and 5, respectively. The y-axis in the first panel represents the normalized expression values derived from RT-qPCR results. The relative expression of each SlDEAD gene was calculated based on RT-qPCR data obtained from three independent biological replicates. Letters above the bars indicate significant differences (p < 0.05) calculated by Duncan’s new multiple range test.
Figure 8. Expression profiles of SlDEAD family genes in tomato at 1, 3, 6, and 12 h post high-temperature stress treatment. (A,B) depict the expression pattern (the first panel) and relative expression levels (rest of the panels) of SlDEAD family genes in groups 4 and 5, respectively. The y-axis in the first panel represents the normalized expression values derived from RT-qPCR results. The relative expression of each SlDEAD gene was calculated based on RT-qPCR data obtained from three independent biological replicates. Letters above the bars indicate significant differences (p < 0.05) calculated by Duncan’s new multiple range test.
Plants 14 01172 g008
Table 1. Properties of tomato DEAD family members.
Table 1. Properties of tomato DEAD family members.
Gene NameGene IDGenomic PositionPredicted LocationAmino AcidMass (Da)Isoelectric PointCoefficient of InstabilityNumber of ExonsHomologous Gene
SlDEAD1solyc01g005960626,619–632,574cyto60465,709.628.1641.96AT2G42520.1
SlDEAD2solyc01g05776056,514,938–56,523,137nucl1221135,061.409.9663.6311AT3G06480.1
SlDEAD3solyc01g07933070,910,189–70,918,827nucl77484,440.066.0639.785AT2G47330.1
SlDEAD4solyc01g09435077,623,834–77,631,727nucl49856,905.288.7345.849AT4G00660.2
SlDEAD5solyc01g09574078,699,069–78,705,889chlo87096,191.099.1751.9710AT5G08610.1
SlDEAD6solyc02g06819032,785,826–32,787,814nucl66275,669.389.2740.071AT2G33730.1
SlDEAD7solyc02g07010034,512,603–34,519,106cyto58565,234.038.9539.0715AT4G34910.1
SlDEAD8solyc02g07888038,098,218–38,103,721nucl59466,304.599.0441.1711AT5G05450.1
SlDEAD9solyc02g08129039,890,841–39,892,976nucl65376,086.828.9344.511AT2G33730.1
SlDEAD10solyc02g08666043,885,348–43,891,471nucl70677,150.909.3352.18AT2G33730.1
SlDEAD11solyc03g05298019,500,306–19,506,839chlo61266,413.247.2839.886AT2G42520.1
SlDEAD12solyc03g11235056,827,775–56,836,207nucl65170,294.399.8546.2210AT5G63120.2
SlDEAD13solyc03g11437058,425,702–58,432,243nucl56664,392.818.9745.6812AT3G18600.1
SlDEAD14solyc03g11744060,661,466–60,664,137cyto59566,647.426.1145.0227AT5G51280.1
SlDEAD15solyc04g08158063,117,504–63,123,510nucl74484,016.418.3545.7519AT4G16630.1
SlDEAD16solyc04g08279063,926,584–63,931,290nucl49955,268.095.2636.218AT3G53110.1 (LOS4)
SlDEAD17solyc05g006130839,121–843,666chlo55962,335.586.546.647AT1G59990.1
SlDEAD18solyc05g04885058,709,311–58,724,460nucl53761,075.088.7638.2310AT4G00660.2
SlDEAD19solyc06g06280036,012,777–36,014,915nucl41346,827.745.5843.314AT1G54270.1
SlDEAD20solyc06g06828038,699,501–38,702,707cyto59566,829.386.0948.063AT5G51280.1
SlDEAD21solyc07g04075046,856,884–46,859,084nucl41346,659.805.2147.444AT1G54270.1
SlDEAD22solyc07g04227052,721,025–52,727,332nucl59767,629.279.5438.710AT2G40700.1
SlDEAD23solyc07g04476055,132,119–55,137,026chlo63067,146.299.4333.147AT3G22330.1
SlDEAD24solyc07g06452063,853,690–63,858,103nucl75485,281.238.9742.648AT5G54910.1
SlDEAD25solyc08g04205028924,652–28934,324chlo74681,518.476.2646.9410AT5G26742.2
SlDEAD26solyc08g06280049,300,134–49,301,991nucl41346,887.765.5448.394AT1G54270.1
SlDEAD27solyc08g07620057,382,754–57,390,648nucl55361,228.048.7533.9613AT1G31970.1 (STRS1)
SlDEAD28solyc09g01593011,382,872–11,400,498chlo55860,842.186.6246.0114AT3G58570.1
SlDEAD29solyc09g09074065,522,411–65,531,624nucl79990,445.849.0651.3115AT3G16840.1
SlDEAD30solyc10g005520426,164–431,795nucl48854,692.308.5338.216AT1G16280.1
SlDEAD31solyc10g0075501,854,816–1,862,972nucl43948,897.709.1644.8313AT5G60990.1
SlDEAD32solyc10g0090703,093,425–3,105,024cyto78587,843.939.936.0611AT1G77030.1
SlDEAD33solyc10g0175305,410,295–5,419,584chlo79155,720.008.6640.299AT4G00660.2
SlDEAD34solyc10g08579064,194,367–64,199,371nucl50856,255.085.2236.318AT3G53110.1 (LOS4)
SlDEAD35solyc12g006320843,041–848,893mito64369,762.979.5643.147AT3G22330.1
SlDEAD36solyc12g03513023,234,550–23,240,564nucl61266,663.879.747.168AT3G01540.2
SlDEAD37solyc12g04486045,651,195–45,658,063nucl47953,288.408.7548.4710AT1G55150.1
SlDEAD38solyc12g05634047,655,899–47,661,775chlo80592,434.548.8948.8210AT1G63250.1
SlDEAD39solyc12g05674048,175,584–48,181,629chlo63670,077.559.8849.599AT4G09730.1
SlDEAD40solyc12g09599063,417,531–63,419,666nucl41346,843.665.4647.674AT1G54270.1
SlDEAD41solyc12g09600063,425,877–63,428,469nucl39444,850.525.6446.254AT1G54270.1
SlDEAD42solyc12g09870064,461,108–64,464,551nucl1147130,890.60638.691AT1G20920.1
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

Yan, Y.; Yu, C.; Xie, B.; Zhou, H.; Zhang, C.; Tian, L. Characterization and Early Response of the DEAD Gene Family to Heat Stress in Tomato. Plants 2025, 14, 1172. https://doi.org/10.3390/plants14081172

AMA Style

Yan Y, Yu C, Xie B, Zhou H, Zhang C, Tian L. Characterization and Early Response of the DEAD Gene Family to Heat Stress in Tomato. Plants. 2025; 14(8):1172. https://doi.org/10.3390/plants14081172

Chicago/Turabian Style

Yan, Yanyan, Chao Yu, Bolun Xie, Hui Zhou, Caiyu Zhang, and Li Tian. 2025. "Characterization and Early Response of the DEAD Gene Family to Heat Stress in Tomato" Plants 14, no. 8: 1172. https://doi.org/10.3390/plants14081172

APA Style

Yan, Y., Yu, C., Xie, B., Zhou, H., Zhang, C., & Tian, L. (2025). Characterization and Early Response of the DEAD Gene Family to Heat Stress in Tomato. Plants, 14(8), 1172. https://doi.org/10.3390/plants14081172

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop