Next Article in Journal
Soil Amendment Using Biochar and Application of K-Humate Enhance the Growth, Productivity, and Nutritional Value of Onion (Allium cepa L.) under Deficit Irrigation Conditions
Next Article in Special Issue
The Omics Hunt for Novel Molecular Markers of Resistance to Phytophthora infestans
Previous Article in Journal
Genetic Analysis of Early White Quality Protein Maize Inbreds and Derived Hybrids under Low-Nitrogen and Combined Drought and Heat Stress Environments
Previous Article in Special Issue
Proteomics and Interspecies Interaction Analysis Revealed Abscisic Acid Signalling to Be the Primary Driver for Oil Palm’s Response against Red Palm Weevil Infestation
 
 
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Article

Investigation and Computational Analysis of the Sulfotransferase (SOT) Gene Family in Potato (Solanum tuberosum): Insights into Sulfur Adjustment for Proper Development and Stimuli Responses

1
Department of Plant Breeding, Faculty of Crop Science, Sari Agricultural Sciences and Natural Resources University (SANRU), Sari 4818166996, Iran
2
Faculty of Agriculture, Shahrood University of Technology, Shahrood 3619995161, Iran
3
Department of Crop and Animal Production, Cilimli Vocational School, Duzce University, 81750 Duzce, Turkey
4
Department of Biochemistry, Faculty of Biological Sciences, Quaid-i-Azam University, Islamabad 45320, Pakistan
5
Finnish Museum of Natural History, University of Helsinki, P.O. Box 7, 00014 Helsinki, Finland
6
Faculty of Biological and Environmental Sciences, University of Helsinki, P.O. Box 65, 00065 Helsinki, Finland
*
Authors to whom correspondence should be addressed.
Submission received: 16 October 2021 / Revised: 22 November 2021 / Accepted: 24 November 2021 / Published: 26 November 2021

Abstract

:
Various kinds of primary metabolisms in plants are modulated through sulfate metabolism, and sulfotransferases (SOTs), which are engaged in sulfur metabolism, catalyze sulfonation reactions. In this study, a genome-wide approach was utilized for the recognition and characterization of SOT family genes in the significant nutritional crop potato (Solanum tuberosum L.). Twenty-nine putative StSOT genes were identified in the potato genome and were mapped onto the nine S. tuberosum chromosomes. The protein motifs structure revealed two highly conserved 5′-phosphosulfate-binding (5′ PSB) regions and a 3′-phosphate-binding (3′ PB) motif that are essential for sulfotransferase activities. The protein–protein interaction networks also revealed an interesting interaction between SOTs and other proteins, such as PRTase, APS-kinase, protein phosphatase, and APRs, involved in sulfur compound biosynthesis and the regulation of flavonoid and brassinosteroid metabolic processes. This suggests the importance of sulfotransferases for proper potato growth and development and stress responses. Notably, homology modeling of StSOT proteins and docking analysis of their ligand-binding sites revealed the presence of proline, glycine, serine, and lysine in their active sites. An expression essay of StSOT genes via potato RNA-Seq data suggested engagement of these gene family members in plants’ growth and extension and responses to various hormones and biotic or abiotic stimuli. Our predictions may be informative for the functional characterization of the SOT genes in potato and other nutritional crops.

1. Introduction

The chemical element sulfur (S) is a necessary factor for life found in the amino acid cysteine (Cys) and methionine (Met), certain vitamins (e.g., thiamin and biotin), co-enzymes (e.g., S-adenosyl methionine), iron–sulfur complexes, prosthetic substances, glutathione (GSH) antioxidants, and others natural secondary metabolites [1]. The adequate S in the soil helps plant growth and development, and it is helpful to get a high plant yield of high quality [2]. Moreover, the deficiency of S makes plants susceptible to various biotic and abiotic stresses [3]. An S content ≤ 0.25% in any plant tissue may be considered severe S deficiency; plants with such deficiency have overall chlorosis and yellowish color due to lack of chlorophyll in the early stage of development [4].
Sulfotransferases (SOTs) (EC 2.8.2.-) are sulfate-regulating proteins in various organisms. In plants, the conjugate reaction of sulfate play a vital role in plant growth and development and in response to various stresses [5]. Sulfate is activated by two subsequent steps for the formation of adenosine-5′-phosphosulfate (APS) and 3′-phosphoadenosine-5′-phosphosulfate (PAPS) before being involved in further biochemical reactions [6]. Sulfotransferases (SOTs) (EC 2.8.2.-) catalyze the transfer of a sulfate group from PAPS to a hydroxyl group of different substrates [7]. Sulfated substances in plants function as secondary metabolites, hormones in coping with stimulus situations, and use as important S storage substances during the life cycle [8]. Plant SOTs are directly engaged in the sulfation process of desulpho-glucosinolate compounds (ds-Gl), which are important secondary metabolites that provide resistance against multiple biotic/abiotic stimuli in brassicales plants [9]. All SOT proteins can be identified by a histidine residue in their PAPS-binding region and by a specific SOT domain (Pfam: PF00685) [10]. SOT family members are specified by four conserved regions (I to IV) in their protein sequences [11], in which the I and IV regions are highly conserved sections [8]. Three AtSOT16, AtSOT17, and AtSOT18 genes in the Arabidopsis thaliana (At) genome are responsible for transferring a sulfuryl group to various ds-Gl compounds [8,12]. Various substances, such as brassinosteroids, gibberellic acids, glucosinolates, flavonoids, coumarins, and phenolic acids, can be sulfated by SOT proteins in various plant species [13,14].
Multiple studies indicate that SOT genes can regulate plant stimuli responses, stress sensing and signaling mechanisms, and developmental processes. For example, in rice, Oryza sativa, expression of some SOT gene was observed in root, stigma, and ovary tissues in response to indole acetic acid and Benzyl aminopurine [15]; BrSOT16 in Brassica rapa indicated strong expression in all tissues except for stamen [16]; ds-Gl AtSOTs, such as AtSOT15, is responsible for circadian control [13]; and expression levels of 11 OsSOTs exhibited some up- and downregulation in response to dehydration, high or low temperatures, and hormone stresses in various tissues [15]. Northern blotting of AtSOT12 revealed that the deduced protein employs flavonoids, brassinosteroids, and salicylic acid compounds as substrates; may be expressed in leaves, flowers, and roots; and responds to abiotic stimuli (such as salt, sorbitol, and cold), hormones, and interactions with biotic pathogens [17,18]. Studies on homologous genes from B. napus revealed increased BNST3 and BNST4 transcripts during exposure to hormones, low oxygen, xenobiotics, and herbicides [14,19]. This provides evidence for the role of these genes in stress responses and detoxification. Some experimental evidence suggests that SOT may also act as a tyrosyl protein and may involve in phytosulphokines biosynthesis [8]. The glucosinolate and their degradation products provide a defense to plant against insects and fungi. Some evidence shows the role of sulphotransferases in the biosynthesis of glucosinolate. Hence, further exploration of SOT can provide important information for the control of pests [8].
The importance of S during the plant life cycle and associated biological and chemical processes is helpful to overcome S shortage for crop production and improvement. Potato is considered an important food crop after wheat, maize, and rice. Adequate S content in potato plants facilitates the uptake of multiple nutrients, carbohydrate formation, vitamin synthesis, chlorophyll production, seed development and stress, and pest resistance [3,20]. Defective S contents lead to upward curving of potato leaves, along with light-green-to-yellow color. Hence, this leads to poor plant growth, prolate form, and postponed maturity [21]. Previous studies have shown that sufficient S elevated the yield of potato tubers and quality and increased tolerance against various pathogens through the sulfur-induced resistance (SIR) mechanism [3], whereas insufficient S lead to a reduction of several important compounds. [22]. These important aspects necessitate the understanding of plant S biology and adjustment of S nutrition in agricultural programs. Therefore, the identification of important sulfotransferases in the S metabolism may elucidate the S-mediated proper growth and resistance mechanisms in potato. SOTs have been identified in Arabidopsis (22 members) [8], rice (35 members) [15], and B. rapa (56 members) [16]. However, the identification and characterization of SOT proteins in the potato (Solanum tuberosum) genome are currently limited. In the current study, various bioinformatics approaches have been utilized to distinguish important cluster SOTs and their expression patterns in multiple tissues and during different biotic or abiotic stimuli. Our predictions may assist functional evaluation of the SOT gene family members in potato and related crop species.

2. Results

2.1. Identification of StSOT Genes

The deduced amino acid sequence of sulfotransferase domain (PF00685) was searched against the Hidden Markov Model (HMM) program and Phytozome database. This led to the identification of 29 putative StSOT proteins; all contained the Sulfotransfer_1 domain and were named according to their chromosomal order (Table 1).
The identified StSOT proteins had diverse lengths, ranging from 101 aa (StSOT07 and StSOT08) to 359 aa (StSOT21). Molecular weights (MWs) ranged from 11.83 kDa (StSOT07) to 41.56 kDa (StSOT21). Most of the identified StSOT proteins (approximately 65.5%) were of acidic nature (theoretical pI ≤ 7.0), ranging from 4.95 (cytosolic StSOT28) to 6.83 (cytosolic StSOT13). The subcellular location of proteins indicated that most of StSOTs (approximately 76%) can be considered as cytoplasmic proteins with no putative transmembrane domains (TMDs). StSOT07, StSOT08, and StSOT28 were predicted to be located in the nucleus in addition to the cytoplasm (Table 1). The proteins StSOT01 and StSOT22 were also predicted to be localized in the nucleus and extracellular region. Two StSOT proteins, namely StSOT23 and StSOT29, could also be found in the mitochondria. Not all StSOT proteins contained any putative TMDs in both cytosolic N- and C-terminal regions that can suggest their specific function during the other cellular pathways apart from membrane transport. The StSOT proteins’ post-translational phosphorylation analysis illustrated a wide variety of phosphorylated serine (S) residues, along with some changed threonine (T) and tyrosine (Y) sites (Figure 1 and Supplementary Materials Table S1). The proteins StSOT02, StSOT05, StSOT07, StSOT08, and StSOT28 were predicted to contain a limited amount of phosphorylated regions (in one or two residues) in their amino acid sequences, while some StSOTs, such as StSOT01, StSOT04, StSOT06, StSOT12, StSOT14, StSOT22, and StSOT26, were predicted as the possible highly phosphorylated sulfotransferase proteins in potato.

2.2. Phylogenetic Relationships, Conserved Motifs/Residues, and Gene Structure of StSOTs

The sulfotransferase proteins from potato, Arabidopsis, tomato, and Sorghum were used to generate a phylogenetic tree to classify the SOT proteins into subfamilies (Figure 2). The phylogenetic tree clustered SOTs into the four main groups according to the tree topology and classification of the sulfotransferases in Arabidopsis. Four SOTs of tomato along StSOT09 were classified in group I and showed a high genetic distance. Six StSOTs and five SOTs of tomato were located in group II, and all sorghum SOT proteins were grouped with StSOT01, StSOT02, StSOT04, StSOT05, and StSOT25 from potato and AtSOT16, AtSOT17 and AtSOT18 from Arabidopsis and four tomato SOTs in group III. Interestingly, all sorghum SOT proteins were separated from dicot SOTs. Group IV was the largest group, and most SOTs of potato, Arabidopsis, and tomato were located in this group (Figure 2).
Eight conserved motifs were predicted in the StSOT protein sequences via the MEME program (Figure 3a and Supplementary Materials Table S2). The StSOT proteins belonging to the same phylogenetic group shared an approximately similar conserved motif composition. Five out of the eight predicted motifs, namely motif 1, motif 2, motif 3, motif 4, and motif 6, were identified as having a Sulfotransfer_1 domain (Supplementary Materials Table S2). Motif 1 and motif 6 possessed the critical N-terminal PSB loop and C-terminal PB region, respectively, which are critical for the sulfotransferase activity of SOT proteins (Supplementary Materials Figure S1). The sequences related to these two important motifs are significantly conserved; this high conservation can be found in both cytosolic and membrane sulfotransferases (Supplementary Materials Figure S1).
The N-terminal region 5′ PSB in motif 1 is related to the PSB-loop and helix 3 sections in the sulfotransferase protein structure that encompasses five successive residues engaged in an interaction with the PAPS compound 5′-phosphate region. In this study, the amino acid residues in this motif that are engaged in sulfotransferase catalytic activity include completely conserved Lys-103 and relatively conserved Thr-106 that can be substituted by the functionally similar residues Ser and Cys (Figure 3a and Supplementary Materials Figure S1). Our results revealed that genes within each subfamily have significant similarities in exon and intron numbers. For example, all StSOT genes had an intronless structure except for StSOT18, StSOT19, StSOT23, and StSOT24, which contained two exons and one intron and were classified into the phylogenetic group II (Figure 3b).

2.3. Genomic Distribution, Duplication Assay, and Synteny Relationships of StSOT Genes

All StSOT gene family members were successfully mapped onto 9 out of 12 chromosomes in the potato genome. The chromosomal map revealed an unequal distribution of the gene family members throughout the chromosomes (Figure 4). Chromosome 5 harbored the largest number of StSOTs (13 genes), while only one StSOT each was predicted to be localized on chromosomes 2, 4, 6, and 9. Nine segmentally duplicated gene pairs categorized into five groups (including duplication and triplication events) were recognized in the StSOT gene family. These groups are indicated with different colors in Figure 4, revealing paralogous pairs. The highest numbers of duplicated/triplicated genes were distributed on chromosome 5, with three duplications and three triplications clustered into the four gene groups (Table 2).
Intraspecies synteny results revealed that many of the duplicated blocks were collinear, such as StSOT07StSOT08 and StSOT26StSOT27. The Ka/Ks magnitudes related to the paralogous pairs ranged from 0.228 to 0.448. According to these ratios, the duplication events were estimated to have occurred between 0.461 to 5.769 million years ago (MYA). The Ka/Ks ratios < 1 in duplicated gene pairs from StSOT family in potato suggested that these genes have been impressed by purifying selection (Table 2). Synteny analysis has also been performed across the potato and some related plant genomes, which can determine the probable functions of the potato StSOT genes (Figure 5). According to the results, all StSOT genes showed synteny relationships with their orthologs in the tomato (approximately 35%) and Arabidopsis (approximately 32%) genomes. The maximum orthology percentage of the StSOT on the potato genome was revealed with tomato. These wide synteny relations at the gene level were considered as confirmation for their close evolutionary relationships. These findings demonstrated the vast rearrangement events of potato chromosomes during the genome evolution process.

2.4. Identification of Cis-Regulatory Elements in StSOT Promoters

In the present study, the StSOT promoter regions in the potato genome were investigated to identify the putative cis-regulatory elements. Several kinds of cis-elements for responses to various phytohormones and abiotic stimulus conditions were identified (Supplementary Materials Table S3). The promoter common cis-elements, such as the core element TATA-box, CAAT-box, and circadian control element, were identified in all StSOT genes. The ABRE (abscisic acid responsiveness), ERE (ethylene responsiveness), and MeJA (Methyl jasmonate responsiveness) factors were predicted as frequently encountered hormone-responding cis-elements in most StSOT promoters. The light-responsive G-Box and Box 4, wounding-stress-responsive WUN-motif, anaerobic inducible ARE, and stress-responsive MYB elements were identified as the other regulatory cis-elements frequently occurring in the StSOT promoter areas, suggesting important roles of this gene family in stress responses. The TC-rich repeats (regulating defensive reactions), LTR (low-temperature responsive), TCA-element (salicylic acid-responsive), TGA-element (auxin-responsive), and W-Box (WRKY transcription factors binding region, important for abiotic stimuli responses) were identified as abiotic and hormone-stress-responsive elements predicted in StSOT08, StSOT11, StSOT13, StSOT16, StSOT22, and StSOT26. Multiple regulatory cis-elements related to phytohormones and environmental stimuli were identified in most StSOT genes, suggesting the critical roles of these genes in potato growth and responses to stress conditions.

2.5. Predicted miRNAs for StSOT Genes

Six StSOT transcripts were predicted to be regulated by various miRNAs. For example, the transcripts StSOT06, StSOT17, StSOT20, and StSOT21 were targeted by stu-miR8029, stu-miR8043, stu-miR8040-3p, and stu-miR8051-3p, respectively (Table 3). Interestingly, four miRNAs, including stu-miR7993a-d, were predicted to target both StSOT11 and StSOT15 for inhibition of translation (Table 3 and Figure 6). Furthermore, the targeted regions of StSOTs by these miRNAs were predicted into the Sulfotransfer_1 domain region, indicating that the StSOT genes are regulated by the identified miRNAs. Remarkably, the identified miRNAs targeted the StSOT genes in group IV, illustrating important similarities in their cellular functions during potato growth, development, and degradation. Moreover, targeting of StSOT genes by various miRNA isoforms may indicate an important role of these genes during various cellular processes in addition to S assimilation activity.

2.6. Protein–Protein Interactions

The interactome data revealed that SOT proteins interact with proteins involved in transmembrane transport, heme binding, iron–sulfur cluster binding, and transition of phosphate groups (Figure 7 and Supplementary Materials Table S4). SOT16, SOT17, and SOT18, which regulate S compounds and secondary metabolite biosynthetic processes, were likely part of an interaction network with a glucosyltransferase protein that contains transmembrane transporter activity and may respond to stimuli through ion homeostasis. APS (pseudouridine synthase/archaeosine transglycosylase-like family protein), APR (Adenine phosphoribosyl reductase), APK (Adenylyl-sulfate kinase), and MET3-1 precorrin methyl transferase were identified as other transferases working with StSOTs in the biosynthesis of S compounds and secondary metabolites (Supplementary Materials Table S4), which can mediate potato growth and stimuli resistance. The interaction of StSOTs with adenylyl-sulfate kinases can control sulfate assimilation and regulation of S-containing amino acid metabolic processes that are essential for plant reproduction and viability. The APR proteins in the network with StSOTs can adjust iron–sulfur complexes and reduce sulfate for Cys biosynthesis and can be induced by sulfate starvation. The annotation of the SUR, CYP, and AKN proteins that interact with StSOTs revealed the involvement of these interactions in secondary metabolite biosynthetic processes and sulfate assimilation, which modulate plant growth and development and responses to diverse stimuli. The SIR protein was also predicted to be engaged in metal ion transition and secondary metabolite biosynthetic processes that can regulate potato cellular response to stress and sulfate starvation (Supplementary Materials Table S4).

2.7. Predicted 3D Modeling, Binding Sites, and Validation of StSOT Proteins

The 3D models of StSOT proteins were prepared through the Phyre2 program, under >90% confidence, according to the templates 5mek (as a cytosolic sulfotransferase) and 1q44 and 1fmj (as the P-loop containing PAPS sulfotransferases in Arabidopsis). The 3D structure of StSOTs exhibited the conserved typical frames consisting of β3-α8 (as the PSB loop in the proteins 5′ region) and β8-α6 (as the 3′PB motif) (Figure 8 and Supplementary Materials Figure S2). In the model validation, the Ramachandran plot analysis revealed that the qualities of the StSOT protein models varied from 80% to 95%, suggesting the good quality of the predicted 3D models and reliability (Table 4). For further verification, the ProSA server was utilized for evaluation of probable errors within the protein models, indicating the existence of negative z-values in a conformation zone for the predicted models, which can be experimentally distinguished through both X-ray and NMR spectroscopy (Table 4). A remarkable proportion of residues in each protein model was included in the lowest energy regions, indicating decreasing energies in various parts of these putative StSOT proteins.
The highest numbers of protein channels were predicted in StSOT05, StSOT06, StSOT11, StSOT12, StSOT13, StSOT16, StSOT17, StSOT19, StSOT20, and StSOT22, with channel numbers of 11 to 13 (Table 4). Interestingly, some StSOT proteins with considerable similarity in their channel regions, such as StSOT05–StSOT06 and StSOT10–StSOT21, were also included in the same phylogenetic group. Accordingly, this may suggest that the evolutionary divergence of StSOTs can modulate gene characteristics to function in various molecular pathways.
Various numbers of ligand and ligand-binding amino acid residues were identified in the StSOT protein structures (Supplementary Materials Table S5). Some metallic and non-metallic heterogeneous were predicted in the center of the binding region in all candidate protein models (Figure 8). Ser, Pro, Gly, Lys, Tyr, and Arg were predicted as the binding residues in almost all of the ligand-binding regions in the candidate StSOT proteins, which suggest the importance of these residues in positioning on the DNA molecule and in the performance of cellular functions. The Ca, Zn, and Mg ions were identified as the metallic heterogeneous in the StSOT functional domains. Although some binding residues were predicted to be outside of the specific domain, our docking assay indicated that most of these functional regions were included in the Sulfotransfer_1 domain. The binding residues and their metallic or non-metallic interacting heterogeneous revealed that some variations suggest the functional specificity of StSOT genes, in addition to their common functions under stimuli exposure and responding to variations in cell metabolism.

2.8. Digital Expression Analyses of StSOT Genes

The normalized FPKM magnitudes obtained from the RNA-Seq datasets were employed to survey the mRNA transcription patterns of the StSOT in various tissues (Figure 9a). All the StSOT family genes were expressed in at least one of the tested potato tissues, except for StSOT29, which may play a regulatory role in another cellular pathway. Some StSOTs, including StSOT04, StSOT11, StSOT12, StSOT13, StSOT15, StSOT17, and StSOT24, exhibited substantial expression levels in all the potato candidate tissues, suggesting the fundamental functions of these sulfotransferases during potato growth and expansion. The developmental functions of these genes may be modulated via the ABRE/ERE-hormones-related and light-responsive Box 4 cis-elements present in promoter regions of these genes (Supplementary Materials Table S3). Some of the StSOT genes also exhibited a tissue-specific expression pattern. For example, StSOT09 and StSOT25 had approximately similar mRNA transcript levels only in the stem and tuber tissues, respectively. The sulfotransferase gene StSOT27 was strongly expressed in the tuber pith and root tissues, while StSOT28 had notable FPKM values in the leaf and petiole samples. The other StSOTs also had various transcription levels in two, three, or more tissues in potato, suggesting the engagement of these sulfotransferases in a wide variety of cellular functions in these tissues across multiple developmental stages.
The expression patterns of the potato-SOT-family-related genes were also examined during exposure to various hormones or biotic or abiotic stresses (Figure 9b). Among the biotic-stimuli-induced StSOTs, induction responses were observed under BABA and phytophthora exposures, with notable transcription rates in 19 and 14 StSOT genes, respectively (Figure 9b). Eight out of 29 StSOTs, including StSOT10, StSOT06, StSOT15, and StSOT11, were also upregulated in response to BTH treatment. Amongst the biotic-stress-induced genes, six StSOTs, including StSOT05, StSOT06, StSOT12, StSOT21, and StSOT25, exhibited notable mRNA transcription rates in response to all stimuli, suggesting important roles in defense against pathogens. Thirteen, nine, and seven StSOTs were identified as highly expressed genes during exposure to abiotic stimuli NaCl, mannitol, and high temperature, respectively. Of these, StSOT02, StSOT05, and StSOT11 exhibited remarkable transcription rates in response to all abiotic stimuli (Figure 9b). In addition, approximately 59%, 55%, 34%, and 24% of the StSOTs were substantially upregulated in response to exposure with the BAP, ABA, GA3, and IAA hormones, respectively. Based on our expression assay, StSOT02 and StSOT29 can be considered as sulfotransferases responsive to multiple hormones, due to their considerable upregulation when exposed to all the candidate hormones. These transcription levels in different StSOTs may be associated with stress-coping cis-regulatory elements predicted in the promoter areas. Most of these upregulated StSOTs under these stimuli have involvement in biosynthetic processes of secondary metabolites. These predictions may clarify the critical roles of StSOT family-related genes in defensive responses of potato under various stimulus conditions and may identify potential genes for further functional assays to enhance the endurance of potato and related crops to various biotic or abiotic stresses. Although the expression results of RNA-Seq data were not validated by qualitative PCR, several studies showed a high correlation between the results of RNA-Seq and qPCR, for instance in papain-like cysteine proteases (PLCPs) genes in cotton [23] and rice [24], extensin gene family in tomato [25], GASA gene family in apple [26], AP2/ERF genes in wheat [27], and Aux/IAA genes in pepper [28]. Moreover, expression patterns of StSOTs were compared with their orthologues in Arabidopsis thalina, AtSOTs, using the eFP Browser database (http://bar.utoronto.ca/efp/cgi-bin/efpWeb.cgi, accessed on 19 November 2021), which showed almost consistent patterns of expression. However, a functional study is needed to describe a perfect conclusion.

3. Discussion

The amino acid sequence of the sulfotransferase domain searched against the HMM program and Phytozome database led to the identification of 29 putative StSOT proteins. This revealed extensive variations in physicochemical properties, suggesting an effective role of genomic duplication and integration events during the evolution of this gene family in potato. In the previous studies, 35 SOT genes in rice [15], 22 genes in Arabidopsis [8], and 56 genes in Brassica rapa [16] were identified. It seems that ploidy level and genome size correlate with the gene number in plants [27]. Most of the identified StSOT proteins (approximately 65.5%) were acidic, suggesting a probable correlation of these StSOTs with secretory-pathway-related proteins. The considerable diversity predicted in the StSOT gene features may refer to evolutionary changes in the potato genome. Post-translational phosphorylation analysis of StSOT proteins revealed a wide variety of phosphorylated serine residues, along with some changed threonine and tyrosine sites. Some StSOTs, such as StSOT01, StSOT04, StSOT06, StSOT12, StSOT14, StSOT22, and StSOT26, were predicted as putative highly phosphorylated sulfotransferase proteins in potato. Protein phosphorylation can mediate multiple biological processes, such as plant development and stimuli responses [29,30], suggesting the importance of these highly phosphorylated StSOTs during the potato life cycle. Post-translational phosphorylation changes were reported to illustrate the dynamic modulation of plant proteins [31].
According to the conserved motifs predicted in StSOT proteins, the N-terminal region 5′ PSB in motif 1 is related to the PSB-loop and helix 3 sections in the sulfotransferase protein structure. This encompasses five successive residues engaged in an interaction with the PAPS compound 5′-phosphate region [32]. In this study, the amino acid residues in this motif engaged in sulfotransferase catalytic activity include the completely conserved Lys-103 and relatively conserved Thr-106, which can be substituted by the functionally similar residues Ser and Cys (Figure 3 and Supplementary Materials Figure S1). The conserved 3′ PB motif in the C-terminal part of the StSOTs encompassed β-sheet 8 and α-helix 6, which contains Arg-199 and Ser-207 as the interacting sites with the PAPS 3′-phosphate group and modulates its binding selectively [33]. Our results indicated a remarkable structural similarity among these motifs and a fixed number of separating residues in all StSOT proteins, suggesting that SOT genes were probably derived from a common ancestral gene. The similarities in the gene structures may also refer to a significant resemblance in expression patterns and regulatory functions in the cell [34]. Moreover, a highly similar distribution of exonic regions may refer to the evolutionary variations that were significantly occurred in the potato genome. The findings suggest that the exon/intron pattern may provide insights into the evolutionary relationships amongst gene family members.
Many SOT genes in some plant species may be generated through gene-duplication events [15,16]. At least two whole-genome duplication events have also been reported in the potato genome [35,36], revealing a paleopolyploid origin for this important nutritional crop. Furthermore, the Ka and Ks rates amongst the duplicated pairs can be considered as an important index to assay the selection pressure and approximate time related to the occurrence of duplications [37]. The Ka/Ks ratios < 1 in duplicated gene pairs from the StSOT gene family in potato suggest that the genes have been impressed by purifying selection [38]. It was suggested that the genes with conserved functions, pseudogenization, or both may be generated via purifying selection [35]. Regarding the predicted motifs in StSOT proteins, genes within a duplicated gene group might be functionally conserved. This may be attributed to one or more periods of primeval polyploidy occurrence in multiple angiosperm plant lineages [36]. Therefore, these gene duplications in the potato genome may explain the evolutionary novelties observed.
The wide synteny predicted amongst potato–tomato and potato–Arabidopsis at the gene level may suggest close evolutionary relationships. The relationships revealed the chromosomal duplication and inversion rearrangement events that organized the SOT genes in these genomes [39,40]. Our results suggest that most of the StSOT genes share a common ancestor and function with their SOT counterparts from tomato and Arabidopsis. Despite these close evolutionary relationships between potato and its relatives, some SOT genes from Arabidopsis and tomato were not mapped on any co-linear blocks compared with potato genes. This may be due to rearrangements and fusions, which can occur extensively on the chromosomes in plants [41,42]. This, in turn, may lead to selective gene loss caused by environmental situations [43]. The information obtained from comparative synteny may further elucidate evolution among crops.
Various stimuli responses are controlled via transcriptional adjustment, which can be modulated by cis-elements present in the gene promoter areas [37,44]. According to our results, multiple regulatory cis-elements related to phytohormones and environmental stimuli were identified in most StSOT genes, indicating the critical role of these genes in potato growth and stress responses. The presence of the light-responsive elements (especially G-Box) suggests that light signals can modulate transcription of StSOT genes, and this ultimately regulates genes engaged in defense, such as flavonoid biosynthesis pathways [45,46]. Moreover, miRNAs have also been identified in most organisms and are engaged in various cellular processes, such as stress responses, RNA silencing, protein degradation, and post-transcriptional adjustment [47,48]. Due to the important roles of transcription factors and ion transferases in growth regulation and stress responses in plants, these genes may be important clades of miRNA targets [44,45]. Therefore, the putative miRNAs that targeted six StSOT transcripts may mediate post-transcriptional regulation of potato SOT genes. Furthermore, miRNAs interact with multiple genes and play an integral role in determining tuberization rates [49]. Remarkably, the identified miRNAs targeted the StSOT genes in group IV, suggesting important similarities in their cellular functions during potato growth, development, and degradation. Moreover, targeting of StSOT genes by various miRNA isoforms suggests an important role of these genes during various cellular processes in addition to their S assimilation activity [1].
Protein–protein interactions can significantly modulate various cellular functions, such as replication, transcriptional adjustment, growth and development, signaling processes, and coordination of multiple metabolic systems [50,51,52]. The role of StSOT proteins in biosynthetic processes of secondary metabolites indicates their critical functions during proper potato growth and tuberization and stress responses through signaling pathways [50,51]. Moreover, our findings suggest the involvement of some StSOTs in the hormone metabolic processes that are critical for guard cell ABA responses and plant resistance against various herbivores and pathogens. StSOT proteins likely collaborate with proteins from iron–sulfur complexes and amino acid metabolism, which can regulate plant responses to external stimuli [46,50]. Moreover, the collaboration of StSOTs with various development-related proteins can effectively module potato growth and tuberization. As shown in the StSOT genes interaction network, APS-kinase, protein phosphatases, ATP-sulfurylase, protein methyltransferase, and NIR can modulate the metabolic pathways of defensive amino acids in potato. The amino acid catabolic system can modulate seedling tolerance against pathogen infection through the overproduction of multiple toxic metabolites, such as serotonin [53]. The construction of these defensive compounds and various S-containing biologically active phytochemicals derived from amino acids, such as tryptophan, is associated with GSH [53]. GSH and tryptophan metabolism may be two essential systems for plant hypersensitive immune responses to various pathogens [53,54]. Furthermore, our interaction network showed that the biosynthesis of amino acid–derived compounds under various stimuli is also regulated through SOT-interacting genes, which are necessary for pathogen resistance. Hence, these interacting proteins play indispensable roles during the life cycle of potato cells and sulfotransferases possess a dynamic gene network for metabolism in plants species.
According to the 3D structure of StSOTs, the β-turn and random coil regions in protein structure may provide tolerance to unfavorable circumstances [27,50]. Generally, our predicted 3D models were in good agreement with the parameters related to typical SOT proteins and can be utilized for peptide ligands and as a docking assay. In protein structures, the channels and cavities modulate protein function and can determine their binding specificity [51,55]. The highest numbers of protein channels were predicted in StSOT05, StSOT06, StSOT11, StSOT12, StSOT13, StSOT16, StSOT17, StSOT19, StSOT20, and StSOT22, with 11 to 13 channels (Table 4). The sulfotransferase proteins with similar structures in the channel and cavity regions may also function similarly in cells and under various environmental conditions [27,42,50,51]. Interestingly, some StSOT proteins with considerable similarity in their channel regions (such as StSOT05–StSOT06 and StSOT10–StSOT21) were also included in the same phylogenetic clade. Accordingly, this may suggest that the evolutionary divergence of StSOTs can modulate gene characteristics to function in various molecular pathways. Although some binding residues were predicted outside of the specific domain, according to our docking assay, most of these functional regions were included in the Sulfotransfer_1 domain. The binding residues and their metallic or non-metallic interacting heterogeneous suggest that some variations may possess some functional specificity of StSOT genes in addition to their common functions in response to stimuli and variations in cell metabolism [34].
Several studies have elucidated the roles of flavonoid and brassinosteroid metabolites in developmental processes [56]. Flavonoids, usually considered as phytochemical secondary metabolites, and the steroid hormones brassinosteroids, can modulate various physiological processes in the plant. These include growth, enlargement, and immunity via modulation of division, elongation, and differentiation of various cells [57]. Based on promoter site analysis and expression profile of StSOT genes, it seems that StSOTs are involved in potato growth, development, and response to phytohormones, such as brassinosteroids. The induced mutations and disorders in genes encoding the main building blocks of brassinosteroids and flavonoids disturbed the signaling systems, leading to severe growth failure and impaired organ development, eventually resulting in reduced productivity and yield [57]. The expression levels of StSOT01, StSOT3, StSOT21, StSOT26, and StSOT28 in potato leaf tissue may also be due to multiple light-responsive G-Box and Box 4 cis-regulatory elements present in the promoter regions of these sulfotransferases, which can collaborate with flavonoid-producer genes and ultimately regulate the growth process and tuberization in potato [45]. The presence of various hormone-responsive elements in the multiple StSOTs may provide further evidence for the importance of these genes in optimal potato optimal growth, development, and tuberization [58]. Further functional investigations of SOT genes in potato may lead to enhanced production of some varieties with larger tubers and improved nutritional value.
The transcription levels in different StSOTs may be associated with their stress-responsive cis-regulatory elements predicted in the promoter regions [59]. Most of these upregulated StSOTs under these stimuli indicate involvement in secondary metabolite biosynthetic processes. Secondary metabolites are biologically active and genetically variable compounds found in various plant species that function as natural pesticides and can inhibit insect herbivores [50,51]. The strong defensive responses of StSOT02, StSOT05, and StSOT11 during abiotic stress conditions may be related to their regulatory functions in secondary metabolite biosynthetic pathways and salicylic acid signaling [50,51]. Furthermore, potato resistance mechanisms in response to multiple stimuli may be modulated through the interaction and coexpression relationships of sulfotransferases with other stress-responsive genes. These predictions may clarify the critical roles of StSOT family-related genes in defensive responses of potato to various stimuli and may identify candidate genes for further functional assays to improve the endurance of potato and related crops to various biotic or abiotic stresses.

4. Materials and Methods

4.1. Recognition of the StSOT Family Members

The HMM profile related to the SOT domain (PF00685) was first retrieved through the Pfam database [10], and an HMM search (HMMER3.0) was conducted to identify the putative SOT proteins in the potato genome, with an expected value of E-10. The protein HMM profile was also compared to the Phytozome v12.1 database [60] to identify SOT proteins in potato. The recognized non-redundant putative SOT proteins were manually checked for the SOT domain (PF00685) by employing Pfam. The corresponding cDNA and genomic sequences of the distinguished SOTs were obtained from Phytozome and genes were named StSOT01 to StSOT29, according to the gene order on the potato chromosomes. In the first, the identified genes were sorted based on their chromosome number, and then the naming for each gene on a chromosome was done randomly.
The physicochemical properties of StSOT proteins, including molecular weights, isoelectric points (pI), and amino acid compositions, were determined with the ProtParam program [61]. Putative transmembrane domains and post-translational phosphorylation changes were predicted in StSOTs, using the SCAMPI program [62] and NetPhos 3.1 server [63], respectively. The location of the StSOT proteins in the cell was also determined with the CELLO program [64].

4.2. StSOT Proteins Alignment, Phylogenetic Relationships, and Identification of Conserved Residues

Sequence alignment of StSOT proteins was performed by using the T-COFFEE multiple sequence alignment packages [65]. The phylogenetic relationships were assessed by constructing the maximum likelihood (ML) phylogenetic tree via MEGAX software, according to the protein sequences of SOTs from potato, tomato, Sorghum, and Arabidopsis, with 1000 bootstrap replicates [66]. The Multiple Em for Motif Elicitation (MEME) server was also employed to identify conserved protein motifs in StSOT members [67].

4.3. StSOT Genes Structure and Chromosomal Map

The exon and intron organizations of potato StSOT genes were predicted by using the Gene Structure Display Server [68]. The chromosomal localization of StSOT genes was also determined on the 12 chromosomes (Chr) of potato by using the S. tuberosum genome info from the Potato Genome Sequencing Consortium database (PGSC) [36]. MapChart software was employed to generate a graphical chromosomal map for StSOT genes in the potato genome [69].

4.4. Gene Duplication and Synonymous and Non-Synonymous Substitution Rates of StSOTs

The identified StSOT genes were evaluated for gene duplication events through the alignment of their cDNA sequences by the ClustalX v.21 program [70]. An identity matrix between the aligned CDSs was prepared, and the duplicated gene pairs were determined as the genes sharing ≥ 90% identity in their nucleotide sequences. The duplicated StSOT gene pairs were subjected to codon alignment, using the ClustalW codon alignment tool in MEGAX software. The synonymous (Ka) and non-synonymous (Ks) substitution values were estimated by utilizing the Ka/Ks Calculator tool [38]. The time of duplication and divergence (million years ago) were also estimated through a synonymous mutation rate of λ substitutions per synonymous site per year as T= [Ks/2λ (λ = 6.5 × 10−9)] × 10−6 [71]. The comparative synteny relationships of SOT genes among the orthologous pairs between potato and tomato and between potato and Arabidopsis at gene levels were visualized through Circos software [72]. A similar method that was introduced for the recognition of SOT genes in potato was also used to identify the orthologous genes of other species (tomato and Arabidopsis).

4.5. Promoter Analysis, miRNA-Targets, and Protein Interaction Assay

The conserved cis-elements existing in the promoter area of StSOT genes were predicted by subjecting the 1500 bp upstream region of the start codon ATG in each putative StSOTs into the PlantCARE server [73]. The targeting miRNAs for the StSOT transcripts were identified by searching the gene-coding sequences against the published miRNAs in the S. tuberosum genome in the psRNATarget database [74] and visualized via Cytoscape [75]. The key StSOTs in the sulfotransferase family and S compound and secondary metabolites biosynthetic processes were identified according to their gene ontology annotations, and their protein–protein interaction network was predicted via the STRING v11 program [76].

4.6. Protein 3D Modeling, Validation, and Docking Analysis of the Ligand Site

The three-dimensional structures of StSOT proteins were predicted through Protein Homology/Analogy Recognition Engine V 2.0 (Phyre2) server [77]. The predicted protein models validation was assessed through Ramachandran Plot Analysis [78] and the Vadar server [79]. Protein secondary structures related to StSOTs were also identified by utilizing Vadar program. The protein molecular voids and pocket/channel numbers were estimated via the BetaCavity Web server [80]. The ProSA server was employed for the calculation of errors and plots in protein structure and validation of the 3D models [81]. Docking analysis of the ligand-binding regions in the predicted protein models was also performed via the 3DLigandSite program [82].

4.7. Expression Profiling of StSOT Genes

RNA-Seq data published by the Potato Genome Sequencing Consortium [36] were employed for an expression assay of the StSOT genes in multiple tissues and during exposure to various biotic or abiotic stimuli. The biotic stimuli consisted of infection with Phytophthora infestans, DL-b-amino-n-butyric acid (BABA), and elicitors’ acibenzolar-S-methyl (BTH) in mixed samples after 24, 36, and 72 h of exposure. The in vitro grown whole plants (after 24 h) were also subjected to three main abiotic stresses, including heat (35 °C), salinity (150 mM NaCl), and drought (mannitol 260 µM). Furthermore, the treatments with four significant hormones, including 6-benzyl amino purine (BAP; 10 µM), abscisic acid (ABA; 50 µM), indole-3-acetic acid (IAA; 10 µM), and gibberellic acid (GA3; 50 µM), were also considered for hormone-stress-induced expression assay of StSOT genes. The expression levels of each StSOT gene in various tissues and multiple stimuli conditions were identified based on transcripts ID search in the potato genome sequencing consortium RNA-Seq dataset [36], and the transcript magnitudes were determined in fragments per kilobase of exon model per million mapped reads (FPKM) and evaluated by using Cufflinks [83]. Expression levels of StSOT genes in tissues were presented based on a percentage. The heatmap related to StSOT gene expression was then provided via the Heatmapper program [84].

5. Conclusions

Various primary metabolic processes in plants are dependent upon sulfate assimilation. The uptake of inorganic sulfate through sulfate transporters in the plasma membrane of plant cells is the first stage of plant S metabolism. Transportation of S into hydroxyl-containing substrates is the sulfation reaction catalyzed by sulfotransferase genes. SOT genes can regulate plant stimuli responses, stress signaling pathways, and developmental processes. The tuberization process in potato can be disturbed by stimuli that disrupt the transportation of photosynthetic products into the tubers, resulting in impaired production. Comprehensive characterization of the SOT gene family using whole-genome sequencing can provide valuable insights into the various developmental and resistance mechanisms and may also identify novel sulfotransferases and their interacting or co-expressed genes. We conclude that StSOTs are diverse proteins, based on their sequence structure and function, and are involved in various pathways related to growth, development, and response to stresses. In the present study, we demonstrated how this important crop effectively employs numerous strategies, such as secondary metabolite biosynthesis, S compound generation, transferase activity, and production of iron–sulfur complexes to modulate various developmental and stimuli resistance processes. Our systematic study of the SOT gene family may provide a better understanding of the function of these genes and insights into their regulatory roles during growth, expansion, and response to stimuli in economically important crop species.

Supplementary Materials

The following are available online at https://0-www-mdpi-com.brum.beds.ac.uk/article/10.3390/plants10122597/s1, Figure S1: Multiple sequence alignments of SOT family proteins in potato. The crucial 5′ PSB loop and 3′ PB regions required for sulfotransferase activity are indicated as black rectangles. Figure S2: Predicted 3D of StSOT proteins in potato by using Phyre2 server. Table S1: The identified StSOT gene family members with Sulfotransferase domain (PF00685) from the Solanum tuberosum genome. The proteins post-transcriptional phosphorylation changes have been investigated. Table S2: The conserved motifs predicted in StSOT protein sequences. Table S3: The important cis-regulatory elements predicted in the promoter region of StSOT genes in potato. Table S4: The interaction relationships between Sulfotransferases and the other genes during multiple cellular functions. Table S5: The docking analysis of the Ligand binding site present in StSOT family proteins. The binding residues and metallic and non-metallic heterogenes were detected in blue spacefill, green spacefill, and colorful wireframe, respectively, in the related Figure 8.

Author Contributions

Conceptualization, S.F. and E.F.; methodology, S.F., H.A., E.F. and P.H.; formal analysis, S.F., P.H. and A.; investigation, P.H., A. and P.P.; writing—original draft preparation, S.F., E.F. and H.A.; writing—review and editing, P.H., A. and P.P.; funding acquisition, P.P. All authors have read and agreed to the published version of the manuscript.

Funding

This research received no external funding. Open access funding provided by University of Helsinki.

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

Not applicable.

Conflicts of Interest

The authors declare no conflict of interest.

References

  1. Takahashi, H.; Buchner, P.; Yoshimoto, N.; Hawkesford, M.J.; Shiu, S.-H. Evolutionary relationships and functional diversity of plant sulfate transporters. Front. Plant Sci. 2012, 2, 119. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  2. d’Hooghe, P.; Dubousset, L.; Gallardo, K.; Kopriva, S.; Avice, J.-C.; Trouverie, J. Evidence for proteomic and metabolic adaptations associated with alterations of seed yield and quality in sulfur-limited Brassica napus L. Mol. Cell. Proteom. 2014, 13, 1165–1183. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  3. Klikocka, H.; Haneklaus, S.; Bloem, E.; Schnug, E. Influence of sulfur fertilization on infection of potato tubers with Rhizoctonia solani and Streptomyces scabies. J. Plant Nutr. 2005, 28, 819–833. [Google Scholar] [CrossRef]
  4. Gupta, U.C.; Sanderson, J.B. Effect of sulfur, calcium, and boron on tissue nutrient concentration and potato yield. J. Plant Nutr. 1993, 16, 1013–1023. [Google Scholar] [CrossRef]
  5. Varin, L.; Marsolais, F.; Richard, M.; Rouleau, M. Biochemistry and molecular biology of plant sulfotransferases. FASEB J. 1997, 11, 517–525. [Google Scholar] [CrossRef]
  6. Schmidt, A. Distribution of APS-sulfotransferase activity among higher plants. Plant Sci. Lett. 1975, 5, 407–415. [Google Scholar] [CrossRef]
  7. Glendening, T.M.; Poulton, J.E. Partial Purification and Characterization of a 3′-Phosphoadenosine 5′-Phosphosulfate: Desulfoglucosinolate Sulfotransferase from Cress (Lepidium sativum). Plant Physiol. 1990, 94, 811–818. [Google Scholar] [CrossRef] [Green Version]
  8. Klein, M.; Papenbrock, J. The multi-protein family of Arabidopsis sulphotransferases and their relatives in other plant species. J. Exp. Bot. 2004, 55, 1809–1820. [Google Scholar] [CrossRef]
  9. Rausch, T.; Wachter, A. Sulfur metabolism: A versatile platform for launching defence operations. Trends Plant Sci. 2005, 10, 503–509. [Google Scholar] [CrossRef]
  10. Finn, R.D.; Bateman, A.; Clements, J.; Coggill, P.; Eberhardt, R.Y.; Eddy, S.R.; Heger, A.; Hetherington, K.; Holm, L.; Mistry, J. Pfam: The protein families database. Nucleic Acids Res. 2014, 42, D222–D230. [Google Scholar] [CrossRef] [Green Version]
  11. Varin, L.; DeLuca, V.; Ibrahim, R.K.; Brisson, N. Molecular characterization of two plant flavonol sulfotransferases. Proc. Natl. Acad. Sci. USA 1992, 89, 1286–1290. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  12. Klein, M.; Reichelt, M.; Gershenzon, J.; Papenbrock, J. The three desulfoglucosinolate sulfotransferase proteins in Arabidopsis have different substrate specificities and are differentially expressed. FEBS J. 2006, 273, 122–136. [Google Scholar] [CrossRef] [PubMed]
  13. Komori, R.; Amano, Y.; Ogawa-Ohnishi, M.; Matsubayashi, Y. Identification of tyrosylprotein sulfotransferase in Arabidopsis. Proc. Natl. Acad. Sci. USA 2009, 106, 15067–15072. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  14. Marsolais, F.; Sebastià, C.H.; Rousseau, A.; Varin, L. Molecular and biochemical characterization of BNST4, an ethanol-inducible steroid sulfotransferase from Brassica napus, and regulation of BNST genes by chemical stress and during development. Plant Sci. 2004, 166, 1359–1370. [Google Scholar] [CrossRef]
  15. Chen, R.; Jiang, Y.; Dong, J.; Zhang, X.; Xiao, H.; Xu, Z.; Gao, X. Genome-wide analysis and environmental response profiling of SOT family genes in rice (Oryza sativa). Genes Genom. 2012, 34, 549–560. [Google Scholar] [CrossRef]
  16. Zang, Y.; Kim, H.U.; Kim, J.A.; Lim, M.; Jin, M.; Lee, S.C.; Kwon, S.; Lee, S.; Hong, J.K.; Park, T. Genome-wide identification of glucosinolate synthesis genes in Brassica rapa. FEBS J. 2009, 276, 3559–3574. [Google Scholar] [CrossRef]
  17. Baek, D.; Pathange, P.; CHUNG, J.; Jiang, J.; Gao, L.; Oikawa, A.; Hirai, M.Y.; Saito, K.; Pare, P.W.; Shi, H. A stress-inducible sulphotransferase sulphonates salicylic acid and confers pathogen resistance in Arabidopsis. Plant Cell Environ. 2010, 33, 1383–1392. [Google Scholar] [CrossRef]
  18. Lacomme, C.; Roby, D. Molecular cloning of a sulfotransferase in Arabidopsis thaliana and regulation during development and in response to infection with pathogenic bacteria. Plant Mol. Biol. 1996, 30, 995–1008. [Google Scholar] [CrossRef]
  19. Rouleau, M.; Marsolais, F.; Richard, M.; Nicolle, L.; Voigt, B.; Adam, G.; Varin, L. Inactivation of brassinosteroid biological activity by a salicylate-inducible steroid sulfotransferase from Brassica napus. J. Biol. Chem. 1999, 274, 20925–20930. [Google Scholar] [CrossRef] [Green Version]
  20. Bednarek, P. Sulfur-containing secondary metabolites from Arabidopsis thaliana and other Brassicaceae with function in plant immunity. ChemBioChem 2012, 13, 1846. [Google Scholar] [CrossRef]
  21. Barczak, B.; Nowak, K. Effect of sulphur fertilisation on the content of macroelements and their ionic ratios in potato tubers. J. Elem. 2015, 20, 37–47. [Google Scholar] [CrossRef]
  22. Hopkins, L.; Parmar, S.; Błaszczyk, A.; Hesse, H.; Hoefgen, R.; Hawkesford, M.J. O-acetylserine and the regulation of expression of genes encoding components for sulfate uptake and assimilation in potato. Plant Physiol. 2005, 138, 433–440. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  23. Zhang, S.; Xu, Z.; Sun, H.; Sun, L.; Shaban, M.; Yang, X.; Zhu, L. Genome-wide identification of papain-like cysteine proteases in Gossypium hirsutum and functional characterization in response to Verticillium dahliae. Front. Plant Sci. 2019, 10, 134. [Google Scholar] [CrossRef] [Green Version]
  24. Niño, M.C.; Kang, K.K.; Cho, Y.G. Genome-wide transcriptional response of papain-like cysteine protease-mediated resistance against Xanthomonas oryzae pv. oryzae in rice. Plant Cell Rep. 2020, 39, 457–472. [Google Scholar] [CrossRef]
  25. Ding, Q.; Yang, X.; Pi, Y.; Li, Z.; Xue, J.; Chen, H.; Li, Y.; Wu, H. Genome-wide identification and expression analysis of extensin genes in tomato. Genomics 2020, 112, 4348–4360. [Google Scholar] [CrossRef]
  26. Fan, S.; Zhang, D.; Zhang, L.; Gao, C.; Xin, M.; Tahir, M.M.; Li, Y.; Ma, J.; Han, M. Comprehensive analysis of GASA family members in the Malus domestica genome: Identification, characterization, and their expressions in response to apple flower induction. BMC Genom. 2017, 18, 827. [Google Scholar] [CrossRef] [PubMed]
  27. Faraji, S.; Filiz, E.; Kazemitabar, S.K.; Vannozzi, A.; Palumbo, F.; Barcaccia, G.; Heidari, P. The AP2/ERF Gene Family in Triticum durum: Genome-Wide Identification and Expression Analysis under Drought and Salinity Stresses. Genes 2020, 11, 1464. [Google Scholar] [CrossRef]
  28. Waseem, M.; Ahmad, F.; Habib, S.; Li, Z. Genome-wide identification of the auxin/indole-3-acetic acid (Aux/IAA) gene family in pepper, its characterisation, and comprehensive expression profiling under environmental and phytohormones stress. Sci. Rep. 2018, 8, 12008. [Google Scholar] [CrossRef]
  29. Heidari, P.; Ahmadizadeh, M.; Izanlo, F.; Nussbaumer, T. In silico study of the CESA and CSL gene family in Arabidopsis thaliana and Oryza sativa: Focus on post-translation modifications. Plant Gene 2019, 19, 100189. [Google Scholar] [CrossRef]
  30. Rezaee, S.; Ahmadizadeh, M.; Heidari, P. Genome-wide characterization, expression profiling, and post-transcriptional study of GASA gene family. Gene Rep. 2020, 20, 100795. [Google Scholar] [CrossRef]
  31. Faraji, S.; Hasanzadeh, S.; Heidari, P. Comparative in silico analysis of Phosphate transporter gene family, PHT, in Camelina sativa gemome. Gene Rep. 2021, 101351. [Google Scholar] [CrossRef]
  32. Hell, R.; Dahl, C.; Knaff, D.; Leustek, T. Sulfur Metabolism in Phototrophic Organisms; Springer: Berlin/Heidelberg, Germany, 2008. [Google Scholar]
  33. Klaassen, C.D.; Boles, J.W. The importance of 3′-phosphoadenosine 5′-phosphosulfate (PAPS) in the regulation of sulfation. FASEB J. 1997, 11, 404–418. [Google Scholar] [CrossRef]
  34. Kakuta, Y.; Pedersen, L.G.; Pedersen, L.C.; Negishi, M. Conserved structural motifs in the sulfotransferase family. Trends Biochem. Sci. 1998, 23, 129–130. [Google Scholar] [CrossRef]
  35. Visser, R.G.F.; Bachem, C.W.B.; de Boer, J.M.; Bryan, G.J.; Chakrabati, S.K.; Feingold, S.; Gromadka, R.; van Ham, R.C.H.J.; Huang, S.; Jacobs, J.M.E. Sequencing the potato genome: Outline and first results to come from the elucidation of the sequence of the world’s third most important food crop. Am. J. Potato Res. 2009, 86, 417–429. [Google Scholar] [CrossRef] [Green Version]
  36. Diambra, L.A. Genome sequence and analysis of the tuber crop potato. Nature 2011, 475, 7355. [Google Scholar]
  37. Sheshadri, S.A.; Nishanth, M.J.; Simon, B. Stress-mediated cis-element transcription factor interactions interconnecting primary and specialized metabolism in planta. Front. Plant Sci. 2016, 7, 1725. [Google Scholar] [CrossRef] [Green Version]
  38. Zhang, Z.; Li, J.; Zhao, X.-Q.; Wang, J.; Wong, G.K.-S.; Yu, J. KaKs_Calculator: Calculating Ka and Ks Through Model Selection and Model Averaging. Genom. Proteom. Bioinform. 2006, 4, 259–263. [Google Scholar] [CrossRef] [Green Version]
  39. Abdullah; Faraji, S.; Mehmood, F.; Malik, H.M.T.; Ahmed, I.; Heidari, P.; Poczai, P. The GASA Gene Family in Theobroma cacao: Genome Wide Identification and Expression Analyses. Agronomy 2021, 11, 1425. [Google Scholar] [CrossRef]
  40. Heidari, P.; Faraji, S.; Ahmadizadeh, M.; Ahmar, S.; Mora-Poblete, F. New insights into structure and function of TIFY genes in Zea mays and Solanum lycopersicum: A genome-wide comprehensive analysis. Front. Genet. 2021, 12, 534. [Google Scholar] [CrossRef] [PubMed]
  41. Fujii, S.; Kazama, T.; Yamada, M.; Toriyama, K. Discovery of global genomic re-organization based on comparison of two newly sequenced rice mitochondrial genomes with cytoplasmic male sterility-related genes. BMC Genom. 2010, 11, 209. [Google Scholar] [CrossRef] [Green Version]
  42. Musavizadeh, Z.; Najafi-Zarrini, H.; Kazemitabar, S.K.; Hashemi, S.H.; Faraji, S.; Barcaccia, G.; Heidari, P. Genome-Wide Analysis of Potassium Channel Genes in Rice: Expression of the OsAKT and OsKAT Genes under Salt Stress. Genes 2021, 12, 784. [Google Scholar] [CrossRef] [PubMed]
  43. Xuan, Y.H.; Piao, H.L.; Je, B.I.; Park, S.J.; Park, S.H.; Huang, J.; Zhang, J.B.; Peterson, T.; Han, C. Transposon Ac/Ds-induced chromosomal rearrangements at the rice OsRLG5 locus. Nucleic Acids Res. 2011, 39, e149. [Google Scholar] [CrossRef]
  44. Ahmadizadeh, M.; Chen, J.-T.; Hasanzadeh, S.; Ahmar, S.; Heidari, P. Insights into the genes involved in the ethylene biosynthesis pathway in Arabidopsis thaliana and Oryza sativa. J. Genet. Eng. Biotechnol. 2020, 18, 62. [Google Scholar] [CrossRef]
  45. Biłas, R.; Szafran, K.; Hnatuszko-Konka, K.; Kononowicz, A.K. Cis-regulatory elements used to control gene expression in plants. Plant Cell Tissue Organ Cult. 2016, 127, 269–287. [Google Scholar] [CrossRef] [Green Version]
  46. Faraji, S.; Ahmadizadeh, M.; Heidari, P. Genome-wide comparative analysis of Mg transporter gene family between Triticum turgidum and Camelina sativa. BioMetals 2021, 34, 639–660. [Google Scholar] [CrossRef]
  47. Cui, Q.; Yu, Z.; Purisima, E.O.; Wang, E. Principles of microRNA regulation of a human cellular signaling network. Mol. Syst. Biol. 2006, 2, 46. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  48. Heidari, P.; Mazloomi, F.; Nussbaumer, T.; Barcaccia, G. Insights into the SAM synthetase gene family and its roles in tomato seedlings under abiotic stresses and hormone treatments. Plants 2020, 9, 586. [Google Scholar] [CrossRef]
  49. Amrutha, R.N.; Sekhar, P.N.; Varshney, R.K.; Kishor, P.B.K. Genome-wide analysis and identification of genes related to potassium transporter families in rice (Oryza sativa L.). Plant Sci. 2007, 172, 708–721. [Google Scholar] [CrossRef] [Green Version]
  50. Braun, P.; Aubourg, S.; Van Leene, J.; De Jaeger, G.; Lurin, C. Plant protein interactomes. Annu. Rev. Plant Biol. 2013, 64, 161–187. [Google Scholar] [CrossRef]
  51. Fukao, Y. Protein-protein interactions in plants. Plant Cell Physiol. 2012, 53, 617–625. [Google Scholar] [CrossRef] [Green Version]
  52. Kazemi, E.; Zargooshi, J.; Kaboudi, M.; Heidari, P.; Kahrizi, D.; Mahaki, B.; Mohammadian, Y.; Khazaei, H.; Ahmed, K. A genome-wide association study to identify candidate genes for erectile dysfunction. Brief. Bioinform. 2021, 22, bbaa338. [Google Scholar] [CrossRef]
  53. Hiruma, K.; Fukunaga, S.; Bednarek, P.; Piślewska-Bednarek, M.; Watanabe, S.; Narusaka, Y.; Shirasu, K.; Takano, Y. Glutathione and tryptophan metabolism are required for Arabidopsis immunity during the hypersensitive response to hemibiotrophs. Proc. Natl. Acad. Sci. USA 2013, 110, 9589–9594. [Google Scholar] [CrossRef] [Green Version]
  54. Ishihara, A.; Hashimoto, Y.; Tanaka, C.; Dubouzet, J.G.; Nakao, T.; Matsuda, F.; Nishioka, T.; Miyagawa, H.; Wakasa, K. The tryptophan pathway is involved in the defense responses of rice against pathogenic infection via serotonin production. Plant J. 2008, 54, 481–495. [Google Scholar] [CrossRef]
  55. Heidari, P.; Abdullah; Faraji, S.; Poczai, P. Magnesium transporter Gene Family: Genome-Wide Identification and Characterization in Theobroma cacao, Corchorus capsularis and Gossypium hirsutum of Family Malvaceae. Agronomy 2021, 11, 1651. [Google Scholar] [CrossRef]
  56. Mazid, M.; Khan, T.A.; Mohammad, F. Role of secondary metabolites in defense mechanisms of plants. Biol. Med. 2011, 3, 232–249. [Google Scholar]
  57. Jain, M. Next-generation sequencing technologies for gene expression profiling in plants. Brief. Funct. Genom. 2012, 11, 63–70. [Google Scholar] [CrossRef] [Green Version]
  58. Ghelis, T. Signal processing by protein tyrosine phosphorylation in plants. Plant Signal. Behav. 2011, 6, 942–951. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  59. Ahmadizadeh, M.; Heidari, P. Bioinformatics study of transcription factors involved in cold stress. Biharean Biol. 2014, 8, 83–86. [Google Scholar]
  60. Goodstein, D.M.; Shu, S.; Howson, R.; Neupane, R.; Hayes, R.D.; Fazo, J.; Mitros, T.; Dirks, W.; Hellsten, U.; Putnam, N. Phytozome: A comparative platform for green plant genomics. Nucleic Acids Res. 2012, 40, D1178–D1186. [Google Scholar] [CrossRef] [PubMed]
  61. Gasteiger, E.; Hoogland, C.; Gattiker, A.; Duvaud, S.; Wilkins, M.R.; Appel, R.D.; Bairoch, A. Protein Identification and Analysis Tools on the ExPASy Server. In The Proteomics Protocols Handbook; Humana Press: Totowa, NJ, USA, 2005; pp. 571–607. [Google Scholar]
  62. Bernsel, A.; Viklund, H.; Falk, J.; Lindahl, E.; von Heijne, G.; Elofsson, A. Prediction of membrane-protein topology from first principles. Proc. Natl. Acad. Sci. USA 2008, 105, 7177–7181. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  63. Blom, N.; Sicheritz-Pontén, T.; Gupta, R.; Gammeltoft, S.; Brunak, S. Prediction of post-translational glycosylation and phosphorylation of proteins from the amino acid sequence. Proteomics 2004, 4, 1633–1649. [Google Scholar] [CrossRef] [PubMed]
  64. Yu, C.-S.; Cheng, C.-W.; Su, W.-C.; Chang, K.-C.; Huang, S.-W.; Hwang, J.-K.; Lu, C.-H. CELLO2GO: A web server for protein subCELlular LOcalization prediction with functional gene ontology annotation. PLoS ONE 2014, 9, e99368. [Google Scholar] [CrossRef] [Green Version]
  65. Notredame, C.; Higgins, D.G.; Heringa, J. T-Coffee: A novel method for fast and accurate multiple sequence alignment. J. Mol. Biol. 2000, 302, 205–217. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  66. Kumar, S.; Stecher, G.; Li, M.; Knyaz, C.; Tamura, K. MEGA X: Molecular Evolutionary Genetics Analysis across Computing Platforms. Mol. Biol. Evol. 2018, 35, 1547–1549. [Google Scholar] [CrossRef]
  67. Bailey, T.L.; Boden, M.; Buske, F.A.; Frith, M.; Grant, C.E.; Clementi, L.; Ren, J.; Li, W.W.; Noble, W.S. MEME Suite: Tools for motif discovery and searching. Nucleic Acids Res. 2009, 37, W202–W208. [Google Scholar] [CrossRef] [PubMed]
  68. Hu, B.; Jin, J.; Guo, A.-Y.; Zhang, H.; Luo, J.; Gao, G. GSDS 2.0: An upgraded gene feature visualization server. Bioinformatics 2015, 31, 1296–1297. [Google Scholar] [CrossRef] [Green Version]
  69. Voorrips, R.E. MapChart: Software for the Graphical Presentation of Linkage Maps and QTLs. J. Hered. 2002, 93, 77–78. [Google Scholar] [CrossRef] [Green Version]
  70. Larkin, M.A.; Blackshields, G.; Brown, N.P.; Chenna, R.; McGettigan, P.A.; McWilliam, H.; Valentin, F.; Wallace, I.M.; Wilm, A.; Lopez, R. Clustal W and Clustal X version 2.0. Bioinformatics 2007, 23, 2947–2948. [Google Scholar] [CrossRef] [Green Version]
  71. Yang, Z.; Gu, S.; Wang, X.; Li, W.; Tang, Z.; Xu, C. Molecular evolution of the CPP-like gene family in plants: Insights from comparative genomics of Arabidopsis and rice. J. Mol. Evol. 2008, 67, 266–277. [Google Scholar] [CrossRef]
  72. Krzywinski, M.; Schein, J.; Birol, I.; Connors, J.; Gascoyne, R.; Horsman, D.; Jones, S.J.; Marra, M.A. Circos: An information aesthetic for comparative genomics. Genome Res. 2009, 19, 1639–1645. [Google Scholar] [CrossRef] [Green Version]
  73. Lescot, M.; Déhais, P.; Thijs, G.; Marchal, K.; Moreau, Y.; Van De Peer, Y.; Rouzé, P.; Rombauts, S. PlantCARE, a database of plant cis-acting regulatory elements and a portal to tools for in silico analysis of promoter sequences. Nucleic Acids Res. 2002, 30, 325–327. [Google Scholar] [CrossRef]
  74. Dai, X.; Zhuang, Z.; Zhao, P.X. psRNATarget: A plant small RNA target analysis server (2017 release). Nucleic Acids Res. 2018, 46, W49–W54. [Google Scholar] [CrossRef] [Green Version]
  75. Franz, M.; Lopes, C.T.; Huck, G.; Dong, Y.; Sumer, O.; Bader, G.D. Cytoscape. js: A graph theory library for visualisation and analysis. Bioinformatics 2016, 32, 309–311. [Google Scholar]
  76. Szklarczyk, D.; Gable, A.L.; Lyon, D.; Junge, A.; Wyder, S.; Huerta-Cepas, J.; Simonovic, M.; Doncheva, N.T.; Morris, J.H.; Bork, P.; et al. STRING v11: Protein–protein association networks with increased coverage, supporting functional discovery in genome-wide experimental datasets. Nucleic Acids Res. 2019, 47, D607–D613. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  77. Kelley, L.A.; Mezulis, S.; Yates, C.M.; Wass, M.N.; Sternberg, M.J.E. The Phyre2 web portal for protein modeling, prediction and analysis. Nat. Protoc. 2015, 10, 845–858. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  78. Lovell, S.C.; Davis, I.W.; Arendall III, W.B.; De Bakker, P.I.W.; Word, J.M.; Prisant, M.G.; Richardson, J.S.; Richardson, D.C. Structure validation by Cα geometry: ϕ, ψ and Cβ deviation. Proteins Struct. Funct. Bioinform. 2003, 50, 437–450. [Google Scholar] [CrossRef]
  79. Willard, L.; Ranjan, A.; Zhang, H.; Monzavi, H.; Boyko, R.F.; Sykes, B.D.; Wishart, D.S. VADAR: A web server for quantitative evaluation of protein structure quality. Nucleic Acids Res. 2003, 31, 3316–3319. [Google Scholar] [CrossRef]
  80. Kim, J.-K.; Cho, Y.; Lee, M.; Laskowski, R.A.; Ryu, S.E.; Sugihara, K.; Kim, D.-S. BetaCavityWeb: A webserver for molecular voids and channels. Nucleic Acids Res. 2015, 43, W413–W418. [Google Scholar] [CrossRef] [Green Version]
  81. Wiederstein, M.; Sippl, M.J. ProSA-web: Interactive web service for the recognition of errors in three-dimensional structures of proteins. Nucleic Acids Res. 2007, 35, W407–W410. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  82. Wass, M.N.; Kelley, L.A.; Sternberg, M.J.E. 3DLigandSite: Predicting ligand-binding sites using similar structures. Nucleic Acids Res. 2010, 38, W469–W473. [Google Scholar] [CrossRef] [Green Version]
  83. Trapnell, C.; Williams, B.A.; Pertea, G.; Mortazavi, A.; Kwan, G.; Van Baren, M.J.; Salzberg, S.L.; Wold, B.J.; Pachter, L. Transcript assembly and quantification by RNA-Seq reveals unannotated transcripts and isoform switching during cell differentiation. Nat. Biotechnol. 2010, 28, 511–515. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  84. Babicki, S.; Arndt, D.; Marcu, A.; Liang, Y.; Grant, J.R.; Maciejewski, A.; Wishart, D.S. Heatmapper: Web-enabled heat mapping for all. Nucleic Acids Res. 2016, 44, W147–W153. [Google Scholar] [CrossRef] [PubMed]
Figure 1. Phosphorylation prediction with scores ≥ 0.95 in StSOT proteins based on serine, threonine, and tyrosine, using NetPhos 3.1 server.
Figure 1. Phosphorylation prediction with scores ≥ 0.95 in StSOT proteins based on serine, threonine, and tyrosine, using NetPhos 3.1 server.
Plants 10 02597 g001
Figure 2. Phylogenetic relationships of SOT proteins from potato, tomato, Arabidopsis, and sorghum. The four main clusters were detected based on the ML method in the phylogenetic tree. Abbreviations: St, potato; Solyc, tomato; Sobic, sorghum; At, Arabidopsis.
Figure 2. Phylogenetic relationships of SOT proteins from potato, tomato, Arabidopsis, and sorghum. The four main clusters were detected based on the ML method in the phylogenetic tree. Abbreviations: St, potato; Solyc, tomato; Sobic, sorghum; At, Arabidopsis.
Plants 10 02597 g002
Figure 3. Conserved motifs predicted in the StSOT protein sequences (a). Exon–intron structure predicted in the StSOT family genes (b). Two important functional 5′ PSB and 3′ PB regions were detected in the motif 1 and motif 6, respectively.
Figure 3. Conserved motifs predicted in the StSOT protein sequences (a). Exon–intron structure predicted in the StSOT family genes (b). Two important functional 5′ PSB and 3′ PB regions were detected in the motif 1 and motif 6, respectively.
Plants 10 02597 g003
Figure 4. Chromosomal map of StSOT family genes in the potato genome. Five series of duplicated/triplicated StSOTs are indicated in different colors. The scale is in mega bases.
Figure 4. Chromosomal map of StSOT family genes in the potato genome. Five series of duplicated/triplicated StSOTs are indicated in different colors. The scale is in mega bases.
Plants 10 02597 g004
Figure 5. Synteny relationships of StSOT genes with orthologs from (a) tomato and (b) Arabidopsis.
Figure 5. Synteny relationships of StSOT genes with orthologs from (a) tomato and (b) Arabidopsis.
Plants 10 02597 g005
Figure 6. Interaction network between micro-RNAs and StSOT genes.
Figure 6. Interaction network between micro-RNAs and StSOT genes.
Plants 10 02597 g006
Figure 7. Protein–protein interaction network of SOT proteins, using Arabidopsis interactome data through STRING server v11, and improved by using Cytoscape.
Figure 7. Protein–protein interaction network of SOT proteins, using Arabidopsis interactome data through STRING server v11, and improved by using Cytoscape.
Plants 10 02597 g007
Figure 8. Three-dimensional docking analysis of StSOT protein ligand-binding sites. The binding residues, metallic heterogeneous and non-metallic heterogeneous are shown in blue spacefill, green spacefill, and colorful wireframe, respectively.
Figure 8. Three-dimensional docking analysis of StSOT protein ligand-binding sites. The binding residues, metallic heterogeneous and non-metallic heterogeneous are shown in blue spacefill, green spacefill, and colorful wireframe, respectively.
Plants 10 02597 g008
Figure 9. Tissue-specific (a) and stimuli-induced gene expression analysis (b) of StSOT genes in the potato genome based on RNA-Seq data reported by the potato genome sequencing consortium.
Figure 9. Tissue-specific (a) and stimuli-induced gene expression analysis (b) of StSOT genes in the potato genome based on RNA-Seq data reported by the potato genome sequencing consortium.
Plants 10 02597 g009
Table 1. Identified StSOT gene family members and their characteristics in the potato genome.
Table 1. Identified StSOT gene family members and their characteristics in the potato genome.
Gene IDGene SymbolProtein Length (aa)MW (KDa)Isoelectric PointSubcellular Localization
PGSC0003DMG400000144StSOT0129634.386.54Nuclear, Cyt., Extra.
PGSC0003DMG400027779StSOT0234540.017.12Cyt.
PGSC0003DMG400003287StSOT0333738.805.73Cyt.
PGSC0003DMG400031776StSOT0434440.105.4Cyt.
PGSC0003DMG400024622StSOT0535040.156.54Cyt.
PGSC0003DMG400018798StSOT0632637.565.62Cyt.
PGSC0003DMG400026753StSOT0710111.835.74Nuclear, Cyt.
PGSC0003DMG400026752StSOT0810111.987.68Nuclear, Cyt.
PGSC0003DMG400039363StSOT0931336.156.27Cyt.
PGSC0003DMG400005584StSOT1033038.496.6Cyt.
PGSC0003DMG400028349StSOT1133539.056.8Cyt.
PGSC0003DMG400028301StSOT1233539.177.11Cyt.
PGSC0003DMG400025717StSOT1330835.906.83Cyt.
PGSC0003DMG400036271StSOT1432938.386.42Cyt.
PGSC0003DMG400046427StSOT1533038.587.13Cyt.
PGSC0003DMG400028302StSOT1633238.666.72Cyt.
PGSC0003DMG400028350StSOT1724028.316.31Cyt.
PGSC0003DMG400015051StSOT1826931.417.71Cyt.
PGSC0003DMG400028341StSOT1926831.247.72Cyt.
PGSC0003DMG403028340StSOT2020924.687.67Cyt.
PGSC0003DMG400002358StSOT2135941.567.03Cyt.
PGSC0003DMG400014962StSOT2222626.066.59Nuclear, Extra.
PGSC0003DMG400029882StSOT2311813.636.5Cyt., Mitochondrial
PGSC0003DMG400020968StSOT2431636.907.16Cyt.
PGSC0003DMG400039919StSOT2524428.495.51Cyt.
PGSC0003DMG400046295StSOT2632938.255.83Cyt.
PGSC0003DMG400046521StSOT2716119.205.76Cyt.
PGSC0003DMG400014947StSOT2810512.244.95Cyt., Nuclear
PGSC0003DMG400009660StSOT2910612.108.99Cyt., Mitochondrial, Nuclear
Cyt., cytoplasm; Extra., extracellular.
Table 2. Duplicated gene pairs in the StSOT gene family and Ka/Ks analysis. Multiple duplication/triplication events were identified in five categories (in different colors in the chromosomal map in Figure 4).
Table 2. Duplicated gene pairs in the StSOT gene family and Ka/Ks analysis. Multiple duplication/triplication events were identified in five categories (in different colors in the chromosomal map in Figure 4).
Duplicated Gene PairsDuplication TypeKaKsKa/KsDate (Million Years Ago) a
1StSOT07-StSOT08Segmental0.02130.0750.2845.769
2StSOT10-StSOT13Segmental0.0030.0060.4480.461
StSOT10-StSOT13-StSOT150.0100.0420.2443.230
3StSOT26-StSOT27Segmental0.0140.0570.2544.384
StSOT14-StSOT26-StSOT270.0100.0330.3172.538
4StSOT16-StSOT22Segmental0.0150.0630.2524.846
5StSOT19-StSOT20Segmental0.0160.0290.5442.230
StSOT18-StSOT19-StSOT200.0100.0450.2283.461
StSOT19- StSOT20-StSOT290.0060.0240.2751.846
a Duplication and divergence time (million years ago) were computed based on the T= [Ks/2λ (λ = 6.5 × 10−9)] × 10−6 formula.
Table 3. Predicted miRNA-targeted StSOT transcripts in the potato genome.
Table 3. Predicted miRNA-targeted StSOT transcripts in the potato genome.
miRNA AccessionTarget GenemiRNA Aligned FragmentInhibition Type
stu-miR8029StSOT06CGAGGUUUUGUUUCUUUUUACCGATranslation
stu-miR7993aStSOT11UCAAUUCAAUUGGUGUAUUUUAUATranslation
stu-miR7993b-3pStSOT11UCAAUUCAAUUGGUGUAUUUUAUATranslation
stu-miR7993cStSOT11UCAAUUCAAUUGGUGUAUUUUAUATranslation
stu-miR7993dStSOT11UCAAUUCAAUUGGUGUAUUUUAUATranslation
stu-miR7993dStSOT15UCAAUUCAAUUGGUGUAUUUUAUATranslation
stu-miR7993cStSOT15UCAAUUCAAUUGGUGUAUUUUAUATranslation
stu-miR7993aStSOT15UCAAUUCAAUUGGUGUAUUUUAUATranslation
stu-miR7993b-3pStSOT15UCAAUUCAAUUGGUGUAUUUUAUATranslation
stu-miR8040-3pStSOT20CUAGUAUUAAUGUUAAUAUUCCleavage
stu-miR8043StSOT17CCGGUUUCAGGUUAAUAUAGUCleavage
stu-miR8051-3pStSOT21UUAUCAUACCAUCUUCUUUAUCleavage
Table 4. Properties of secondary and tertiary structures of StSOT proteins, validation, and channel numbers.
Table 4. Properties of secondary and tertiary structures of StSOT proteins, validation, and channel numbers.
Protein Nameα-Helixes (%)β-Sheets (%)Coils (%)Turns (%)Channel NumberRamachandran Plot (%)z-Values
StSOT01132 (44%)50 (16%)114 (38%)76 (25%)793.50%−8.4
StSOT02161 (46%)41 (11%)143 (41%)92 (26%)993.90%−8.73
StSOT03141 (41%)50 (14%)146 (43%)84 (24%)890.10%−8.15
StSOT04148 (43%)46 (13%)150 (43%)88 (25%)793.90%−8.15
StSOT05142 (40%)39 (11%)169 (48%)68 (19%)1292.80%−8.61
StSOT06152 (46%)39 (11%)135 (41%)80 (24%)1294.10%−8.16
StSOT0747 (46%)0 (0%)54 (53%)32 (31%)590.90%−1.85
StSOT0850 (49%)3 (2%)48 (47%)20 (19%)492.90%−2.01
StSOT09148 (47%)44 (14%)121 (38%)76 (24%)1093.20%−8.71
StSOT10151 (45%)47 (14%)132 (40%)72 (21%)1094.20%−8.45
StSOT11140 (41%)40 (11%)155 (46%)84 (25%)1194.00%−8.52
StSOT12146 (43%)42 (12%)147 (43%)84 (25%)1292.50%−8.66
StSOT13120 (38%)36 (11%)152 (49%)96 (31%)1381.70%−7.64
StSOT14145 (44%)46 (13%)138 (41%)80 (24%)594.50%−8.6
StSOT15152 (46%)50 (15%)128 (38%)88 (26%)395.10%−7.93
StSOT16148 (44%)42 (12%)142 (42%)76 (22%)1291.50%−9.05
StSOT17115 (47%)20 (8%)105 (43%)64 (26%)1295.40%−6.17
StSOT18128 (47%)30 (11%)111 (41%)44 (16%)793.60%−7.99
StSOT19132 (49%)31 (11%)105 (39%)64 (23%)1195.90%−7.92
StSOT20103 (49%)12 (5%)94 (44%)44 (21%)1294.20%−6.67
StSOT21143 (39%)43 (11%)173 (48%)76 (21%)1091.30%−7.93
StSOT2294 (41%)29 (12%)103 (45%)72 (31%)1379.90%−5.5
StSOT2337 (31%)25 (21%)56 (47%)36 (30%)592.20%−4.01
StSOT24146 (46%)35 (11%)135 (42%)68 (21%)989.80%−8.12
StSOT25113 (46%)21 (8%)110 (45%)60 (24%)593.00%−5.86
StSOT26154 (46%)45 (13%)130 (39%)96 (29%)693.30%−8.77
StSOT2783 (51%)3 (1%)74 (46%)32 (20%)494.30%−4.56
StSOT2849 (46%)0 (0%)56 (53%)24 (22%)580.60%−3.48
StSOT2949 (46%)0 (0%)57 (53%)24 (22%)594.20%−2.78
Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Share and Cite

MDPI and ACS Style

Faraji, S.; Heidari, P.; Amouei, H.; Filiz, E.; Abdullah; Poczai, P. Investigation and Computational Analysis of the Sulfotransferase (SOT) Gene Family in Potato (Solanum tuberosum): Insights into Sulfur Adjustment for Proper Development and Stimuli Responses. Plants 2021, 10, 2597. https://0-doi-org.brum.beds.ac.uk/10.3390/plants10122597

AMA Style

Faraji S, Heidari P, Amouei H, Filiz E, Abdullah, Poczai P. Investigation and Computational Analysis of the Sulfotransferase (SOT) Gene Family in Potato (Solanum tuberosum): Insights into Sulfur Adjustment for Proper Development and Stimuli Responses. Plants. 2021; 10(12):2597. https://0-doi-org.brum.beds.ac.uk/10.3390/plants10122597

Chicago/Turabian Style

Faraji, Sahar, Parviz Heidari, Hoorieh Amouei, Ertugrul Filiz, Abdullah, and Peter Poczai. 2021. "Investigation and Computational Analysis of the Sulfotransferase (SOT) Gene Family in Potato (Solanum tuberosum): Insights into Sulfur Adjustment for Proper Development and Stimuli Responses" Plants 10, no. 12: 2597. https://0-doi-org.brum.beds.ac.uk/10.3390/plants10122597

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