https://orcid.org/0009-0009-8710-2299
Figures
Abstract
Inositol tetrakisphosphates kinase (ITPK) plays a vital role in regulating cellular responses to abiotic stress, plant hormone signaling and various other aspects of plant growth and development. Additionally, it is also involved in phosphorous, inositol phosphate metabolism and synthesize phytic acid which is the main phosphorous storage form in seeds. While essential for plant physiology, high phytic acid levels reduce the bioavailability of minerals such as Fe and Zn, which impact nutritional quality negatively. Despite its importance, the ITPK gene family remains largely unexplored in bread wheat. In this study, we conducted a comprehensive genome-wide analysis, including phylogenetic analysis and expression profiling, of the ITPK gene family in wheat. We systematically examined gene structure, chromosomal distribution, motif and domain conservation, promoter analysis, synteny analysis, protein modeling and protein-protein interaction of ITPKs. A total of 15 ITPK genes have been identified in wheat (T. aestivum). The TaITPK genes were distributed on chromosome number 1, 4, 5 and 7 in all the three genomes A, B and D. Comparative phylogenetic analysis resolved four major groups, with wheat ITPK sequences represented in Groups I, III, and IV, whereas Group II contained no wheat sequence. The conserved domain and motif analysis showed the presence of Ins134_P3_kin domain at N-terminus and CPase_L_D2 in C-terminus of protein. String based protein interaction analysis suggested ITPK genes interact with Inositol polyphosphate multi kinase (IPK1) and Inositol-pentakisphosphate 2 kinase (IPK2) which were also involve in synthesis of phyti acid. Furthermore, in-silico expression analysis of ITPK genes revealed their preferential tissue-specific and growth stage expression, especially after anthesis of wheat. Preliminary qRT-PCR profiling of selected TaITPK genes revealed treatment-dependent relative expression patterns under FeSO4 and ZnSO4 supplementation. The current study has identified 15 ITPK genes present in hexaploid wheat genome. Their evolutionary, structural, and expression analyses provide a foundation for further functional characterization of this gene family in wheat.
Citation: Umar F, Maqbool R, Khan MA, Sadia B (2026) Genome wide identification and analysis of inositol tetrakisphosphate kinase (ITPK) gene family in Triticum aestivum L. PLoS One 21(9): e0359528. https://doi.org/10.1371/journal.pone.0359528
Editor: Aimin Zhang, Institute of Genetics and Developmental Biology Chinese Academy of Sciences, CHINA
Received: April 21, 2026; Accepted: September 15, 2026; Published: September 29, 2026
Copyright: © 2026 Umar et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Data Availability: All data are in the manuscript and/or supporting information files.
Funding: The author(s) received no specific funding for this work.
Competing interests: no authors have competing interests.
1. Introduction
Phytic acid (PA; myo-inositol hexakisphosphate, IP6) is abundantly present plant compound that constitutes about 1–5% of the dry weight of edible legumes, cereals, oilseeds, and nuts which are the major components of human and animal diets [1]. The phytate content in these foods varies greatly, depending on several factors such as crop species, soil type, growing conditions, fertilizer application, harvesting time, post-harvest processing, and analytical methods used for quantification [2]. Generally, foods cultivated with modern high-phosphate fertilizers tend to accumulate higher levels of phytic acid compared to those grown using organic or compost-based systems [3]. Due to its highly phosphorylated inositol ring, PA readily forms insoluble complexes with multivalent cations [4,5].
In plants PA is synthesized through two pathways: lipid-dependent and lipid-independent [6]. In cereal and legume seeds, the lipid-independent pathway follows which begin with the conversion of glucose-6-phosphate to inositol-3-phosphate by myo-inositol-3-phosphate synthase (MIPS) [7]. Successive phosphorylation by various kinases then produces inositol pentakisphosphate (IP5), which is finally converted into phytic acid (IP6) [8]. The phosphorylation cascade leading from inositol triphosphate (IP4) to inositol hexakisphosphate (IP₆) represents one of the most conserved biochemical pathways in eukaryotes [9]. Among extensive research into inositol phosphate metabolic enzymes in plants, the Inositol teris/tetrakisphosphate kinase (ITPK) also known as Inositol-1,3,4-triskisphosphate 5/6-kinase (ITP5/6 K) gene family receives special attention because it is abundantly present in plants and catalyzes the penultimate step of Phytic acid synthesis [10]. It plays a crucial intermediary role by catalyzing the conversion of inositol trisphosphate (IP3) to inositol pentaphosphate (IP5) via sequential phosphorylation [11]. Through this role, ITPKs not only contribute to phytic acid biosynthesis, but also participate in energy metabolism, phosphate signaling, and abiotic stress responses. Since late 1980s, numerous studies have also demonstrated its beneficial roles, highlighting its antioxidant, anti-carcinogenic, and antidiabetic properties [12,13].
However, Phytic acid has been known as an anti-nutrient agent since long [14–16]. In plants, phytic acid primarily occurs as salts of mono- and divalent cations such as K ⁺ , Mg² ⁺ , and Ca² ⁺ , and it accumulates in seeds during the maturation phase [17–19]. Monogastric animals, including humans and poultry, cannot effectively metabolize phytic acid because their digestive systems lack adequate phytase enzyme activity required to hydrolyze phytate and release its bound nutrients [20]. This property is of great concern in cereal-based diets, particularly in developing countries where wheat constitutes a primary food source. Chronic deficiency of Fe and Zn leads to hidden hunger, a form of malnutrition affecting billions of people worldwide [21]. Therefore, a major goal of modern wheat improvement programs is to reduce phytate content while maintaining adequate phosphorus storage for seed viability.
Since ITPKs catalyze the rate-limiting steps in the conversion of lower inositol phosphates to phytic acid, understanding their gene structure, expression regulation, and evolutionary conservation is an essential step toward developing low-phytate, micronutrient-rich wheat varieties. However, the understanding of ITPKs for its functional role and genetic diversity in wheat not studied extensively, especially given the complex polyploid nature of the wheat genome. In recent years, significant interest has been directed towards the ITPK family of enzymes in different crops due to their role in the sequential phosphorylation steps involved in phytate synthesis in cereal crops like maize and rice but limited in wheat. In wheat, the expression pattern of the selected genes involved in the final step of biosynthetic pathway of phytic acid at different growth stages has been studied which suggest their role in phytic acid accumulation. However, their response to iron and zinc availability is not well understood. Recent advances in bioinformatics tools have made it possible to conduct comprehensive genome-wide studies, enabling the identification of gene families across complex polyploid genomes.
The present study was undertaken to perform a genome-wide identification analysis of the ITPK gene family in Triticum aestivum L. First, TaITPK gene members were identified and their chromosomal distribution was determined. Subsequently, their phylogenetic relationships, syntenic associations, and protein structural features were analyzed to understand their evolutionary origin and diversification. To further explore their potential regulatory mechanisms, promoter regions were examined for cis-regulatory elements. Finally, expression profiling under different iron and zinc conditions was carried out to assess the possible functional roles of TaITPK genes in wheat. This will provide a strong basis for understanding ITPKs family members in wheat.
2. Materials and methods
2.1. Identification, classification and phylogenetic tree construction of ITPK gene family
The protein sequence of Arabidopsis Thaliana (AT5G16760, AT4G33770, AT4G08170, AT2G43980) and Oryza sativa (LOC4347597) ITPK gene family were used as query retrieved from TAIR and NCBI. The query proteins were BLASTP to search against Triticum aestivum in Ensembl Plant https://plants.ensembl.org/index.html to find out wheat homeologs with cut off E-value < 1e−5. The candidate proteins were further screened out using NCBI CD search https://www.ncbi.nlm.nih.gov/Structure/bwrpsb/bwrpsb.cgi. Moreover, molecular weight, theoretical iso electrical point Pi, GRAVY, No. of amino acids were calculated using Expasy ProtParam https://web.expasy.org/protparam/. The chromosome ID and gene location were retrieved from Ensembl Plant https://plants.ensembl.org/index.html. The subcellular localization of each protein was predicted using CELLO: Subcellular Localization Predictive system database http://cello.life.nctu.edu.tw/
Furthermore, protein sequences of Arabidopsis thaliana, Zea mays, Hordeum vulgare and Oryza sativa were selected along with Triticum aestivum as these species represented well-characterized dicot and monocot plants and facilitate evaluation of the evolutionary relationships, conservation, and divergence of the ITPK gene family. These protein sequences were aligned in MUSCLE https://www.ebi.ac.uk/jdispatcher/msa/muscle?stype=protein with default parameters using MEGA 11 and IQ-TREE was used to construct an maximum likelihood (ML) phylogenetic tree with 1000 bootstrap repeats for ultra-fast bootstrapping [22]. The phylogenetic tree was visualized using iTOL v7 (https://itol.embl.de (accessed on 7 August 2025)) [23].
2.2. Gene structure, conserved motif and domain analysis
To analyze the conserved motifs present in the wheat ITPK gene family, the MEME Suite web server https://meme-suite.org/meme/ was used providing the full-length protein sequences, with the maximum number of motifs set to ten [24]. The exon–intron organization of ITPK genes was examined using GSDS 2.0 https://gsds.gao-lab.org/Gsds_help.php which provided a graphical representation of gene structure. Domain analysis was performed using the NCBI Conserved Domain Database (CD-Search) tool to identify and confirm functional protein domains. Finally, an integrated visualization combining gene structure, conserved motifs, and domain architecture was generated using the Gene Structure View (Advanced) function in TBtools-II [25].
2.3. Comparative synteny analysis of ITPK genes
To further investigate the conservation and evolutionary relationships of ITPK genes, a synteny analysis was performed between Triticum aestivum and other plant genomes (Oryza sativa, Zea mays, Hordeum vulgare, and Arabidopsis thaliana). The genomic sequence (FASTA) and genomic annotation (GFF3) files were retrieved from the Ensembl Plants database. Homologous gene pairs were identified using protein sequence with an E-value threshold of 1e − 10, and the resulting alignment file, along with the GFF annotation, was used as input for MCScanX. The syntenic relationships among ITPK genes were visualized in TBtools-II [26]. Conserved syntenic blocks containing ITPK genes were identified to trace evolutionary conservation.
2.4. Gene location on chromosomes and gene divergence analysis
The chromosomal distribution map of wheat ITPK genes was generated using the Gene Location Visualize (Advanced) function in TBtools-II. The chromosome lengths, physical positions, and length of each gene were retrieved from the Ensembl Plants and used to map the locations of TaITPK genes across wheat chromosomes. Furthermore, to estimate sequence divergence among ITPK paralogous gene pairs, the coding sequences (cds) were aligned using MUSCLE algorithm in MEGA11. The evolutionary divergence among paralogous pairs was calculated by using Nei-Gojobori method (Jukes-Cator) model [27]. After that, selection pressure was estimated with non-synonymous (Ka) and synonymous (Ks) substitution rates via Pairwise dN/dS estimation tool in MEGA11. The dN/dS (Ka/Ks) ratio was calculated to infer the type of selection acting on duplicated genes [28].
2.5. Protein modeling and Protein-protein interaction
The three-dimensional (3D) structures of TaITPK proteins were predicted using the SWISS-MODEL online server (https://swissmodel.expasy.org/) [29,30]. The peptide sequences of each TaITPK protein were submitted to the server, and homology-based structural models were generated. The reliability and quality of the predicted models were evaluated based on Global Model Quality Estimation (GMQE) and Qualitative Model Energy Analysis (QMEAN) scores [31,32].
Moreover, For protein-protein interaction prediction, STRING database was used (https://string-db.org/) by uploading the peptide sequences of TaITPK genes [33,34]. The interaction network was constructed to identify potential interacting partners and associations among TaITPK proteins.
2.6. Cis-regulatory element (Promoter) analysis
For analyzing the cis-acting regulatory element of each TaITPK gene, the 1.5 kb upstream region of each gene was retrieved from the Ensembl Plants database (Triticum aestivum genome, IWGSC RefSeq v2.1). The extracted promoter sequences were analyzed using the PlantCARE database (https://bioinformatics.psb.ugent.be/webtools/plantcare/html/) to identify putative cis-regulatory motifs [35]. Visualization of cis-element distribution was carried out using TBtools-II using the “Simple Bio-sequence Viewer” module [36].
2.7. In silico expression analysis of TaITPK genes
For in silico expression analysis, RNA seq data for expression analysis of TaITPK genes in different tissues at different growth stages and under drought and heat stress in wheat was downloaded from Wheat Exp (https://dubcovskylab.ucdavis.edu/wheatexp) [37]. Heat map showing expression of each gene was constructed in TBtool.
2.8. Plant material and application of FeSO4 and ZnSO4
Two wheat (Triticum aestivum L.) genotypes, ‘Akbar-2019’ and ‘Fateh Jang-2016’, were cultivated at the experimental field of the Department of Plant Breeding and Genetics, University of Agriculture, Faisalabad, during the 2024–2025 wheat growing season. The experiment consisted of four treatments, i.e., Control (no micronutrient application), Soil application of FeSO4 (20 kg ha−1), Soil application of ZnSO4 (20 kg ha−1), and combined FeSO4 + ZnSO4 application (each at 20 kg ha−1) [38]. The soil collected from 0−15 cm surface from the selected field have range of 1.002–1.012 ppm Zn and 1.614–1.695 ppm Fe. For RNA extraction, spikes were sampled 14 days after anthesis (DAA). The collected samples were immediately frozen in liquid nitrogen and stored at −80°C until further molecular analysis.
2.9. RNA isolation, cDNA synthesis and qRT-PCR analysis
RNA was isolated using TRIzolTM Reagent [39]. Extracted RNA integrity was determined using 1% agarose gel electrophoresis and quantification of RNA through Nano-drop-8000. For the synthesis of cDNA, First Strand cDNA kit Thermo-Scientific Revert Aid (K1622; 100rxns) was used and protocol was followed according to manufacturer guidance [40]. The primers information is given in S5 Table. Then, the Thermo-Scientific Maxima SYBR green Master mix was used. The Actin (housekeeping gene) was used as internal reference gene for comparison with transcript of target genes. The list of primers used mentioned in S5 Table (See Supporting Information). The reaction mixture contained 0.5µl of each forward and reverse primer, SYBR green 6µl, cDNA 1µl and water 2µl. Total 10µl reaction was prepared. Then expression was determined using Quant Studio 5 real time PCR machine and following profile was used: Initial denaturation at 95°C for 10 min, denaturation at 95°C for 15 seconds and annealing of primer at 60°C for 1 minute and 40 cycles.
The relative expression levels were calculated using the 2−△△𝐶𝑡 method, ΔCt = Ct_target − Ct_actin and ΔΔCt = ΔCt_treatment − ΔCt_control [41]. For each genotype × treatment combination, qRT-PCR measurements were performed in three technical repeats from one biological sample. The relative expression values are presented as mean ± standard error (SE) of the technical measurements. As independent biological replicates were not available, no inferential statistical analysis was performed, and the expression patterns were interpreted descriptively.
3. Results
3.1. Identification, classification and Phylogenetic analysis of ITPK gene family
The protein sequence of ITPK genes were identified through BLASTP in Triticum aestivum using query sequence of Arabidopsis Thaliana and Oryza sativa https://plants.ensembl.org/index.html. After removing redundant, the remaining genes were further screened for conserved domain analysis in NCBI-CD Search https://www.ncbi.nlm.nih.gov/Structure/bwrpsb/bwrpsb.cgi and incomplete domains were removed. Furthermore, through Motif finder, pseudogenes with lack of inositol 1,3,4 trisphosphates 5/6 kinase were also excluded. The full length transcripts of all identified genes were aligned through ClustalW https://www.genome.jp/tools-bin/clustalw to check any differences among them. Our analysis yielded 15 ITPK genes of Triticum aestivum. The gene IDs, chromosome IDs, gene locus, no. of amino acids, molecular weight, isoelectric point and subcellular localization are listed in S1 Table. (See Supplementary Information). The no. of amino acids varied from 214 to 503. The GRAVY ranges from −0.098 to 1.56. The TaITPKs were predicted to localized in mitochondria, chloroplast, cytoplasm, extra cellular and plasma membrane. Most of the genes were present in cytoplasm. The average molecular weight and isoelectric point of ITPK gene family was 41.06 kda and 5.60 respectively and showed large variation.
We constructed the Maximum Likelihood Phylogenetic tree of Triticum aestivum with Oryza sativa, Zea mays and Arabidopsis thaliana ITPK proteins. The identified wheat ITPK genes were named with reference to previously reported homologous ITPK genes in related cereal species and were further distinguished according to their chromosomal locations and corresponding A, B, and D subgenomes. The numerical gene designations are independent of the phylogenetic Groups I–IV. The phylogenetic analysis classified the ITPK into four distinct clades reflecting their evolutionary divergence. The multiple homeologous present in wheat within this clade indicated a significant level of gene expansion, might be the result of polyploidization and tandem duplication. The close clustering of the sequences showed evolutionary conserved origins. In case of Group I, ITPK6 sequences formed a distinct and relatively compact cluster. It’s separation from other clades identified early evolutionary divergence. Group 1 also included AtITPK4 in it which showed more similarity to OsITPK6. Total three ITPK6 genes are present in this clade. Group II did not contain any wheat sequence, whereas AtITPK1, ZmITPK1, and OsITPK5 were present in this group. No corresponding wheat sequence was recovered under the identification criteria used in the present study. The absence of a wheat member may reflect lineage-specific gene loss or sufficient sequence divergence to prevent its detection under the present identification criteria. However, these possibilities cannot be conclusively distinguished based on the present phylogenetic analysis alone.
The Group III included ITPK1 and ITPK4 gene groups indicating a shared evolutionary origin. Despite being classified as different subgroups, phylogenetic association of ITPK1 and ITPK4 showed that they may come from common ancestral gene. The TaITPK1 homoeologs clustered most closely with the barley HvITPK1 sequence in the present phylogenetic analysis. The ITPK4 group of T. aestivum showed similarity with H. vulgare, O. sativa and Z. mays but not with A. thaliana. This clade also doesn’t include AtITPK4 gene. Total six members of wheat included in Group III. The T. aestivum ITPK2 genes showed similarity with ITPK2 genes of H. vulgare, O. sativa and Z. mays. The OsITPK1 gene also showed similarity with ITPK2 genes of T. aestivum, Z. mays and H. vulgare. The other members in Group IV were ITPK3 genes in which T.aestivum ITPK3 group showed more similarity with O. sativa and H. vulgare. The total six genes of T. aestivum are present in Group IV. This classifications of groups can also be seen in Fig 1B depicting multiple sequence alignment of protein sequences of the members of each four groups.
Each color showed different group. The numbers adjacent to the branches represent bootstrap values ranges from 35 to 100%. B. Multiple sequence alignment of ITPK protein sequences of different species included in each four phylogenetic groups.
3.2. Gene structure, conserved motif & domain analysis of TaITPK gene family
To study the structural conservation and potential functional divergence among the ITPK gene family members, comprehensive motifs, domains and gene structure analysis were performed among ITPK gene family members of T. aestivum, A. thaliana, O. sativa, H. vulgare and Z. mays. The results strongly support the phylogenetic classification and provide evidence of evolutionary conservation of gene family and subgroups division.
A total 10 conserved motifs have been identified among which many motifs like motif 1, 2, 3, and 7 present throughout in all member of ITPK family (Fig 2A). These conserved regions might indicate their role in inositol phosphate kinase activity, including ATP-binding and substrate recognition sites. The ITPK2 and ITPK3 showed a highly conserved motif pattern arranged in same order and position showing highly conserved structural and functional redundancy. Likewise, ITPK1 and ITPK4 gene family member showed conserved pattern typically arranged in same order and depicting their evolutionary conservation [42]. Furthermore, members of ITPK6 group showed contrast with others with different arrangements and losses of motifs suggesting functional divergence or adaptation.
C. Gene structure of TaITPK gene family.
Functional domain analysis (Fig 2B) which revealed multiple conserved domains in ITPK gene family. Two super domain families present were Ins 134_P3_kin_N superfamily (inositol 1, 3, 4-trisphosphate 5/6-kinase proteins) an ATP grasp domain that plays a crucial intermediary role by catalyzing the conversion of inositol trisphosphate (IP3) to inositol pentaphosphate (IP5) via sequential phosphorylation [12] and CPase_L_D2 (Carbamoyl-phosphate synthase L chain) an ATP binding domain which catalyzes the ATP-dependent synthesis of carbamyl-phosphate from glutamine or ammonia and bicarbonate [43].
The diversity in exon–intron structures within a gene family provides valuable insights into the evolutionary history and functional roles of its member [44]. To examine the structural features of ITPK genes, exon-intron were analyzed and the results (Fig 2 C) revealed that the four group of ITPK genes showed variation among them but similarity within the same group except few of the genes. The homeologous genes in wheat showed highly conserved structure within each group and had nearly similar exon-intron arrangement which indicates their conserved function among sub genomes and originated from same ancestral gene prior to polyploidization [45]. Furthermore, in case of ITPK1 group, only one exon presents in all species including monocots and dicots but varying in length of the exon. The TaITPK1 showed similar length of exon of size 1kb with Zea mays but AtITPK1, OsITPK1, HvITPK1 have longer exon size >1kb. Interestingly, OsITPK5 showed similarity with AtITPK1 and HvITPK1 and motif pattern depicts the similar kind of interpretation. The OsITPK1 gene showed more number of exons and introns not similar to other species indicating moderate complexity. Moreover, TaITPK4 genes and ZmITPK1 showed similarity with ITPK1 group of wheat having single exon and size of 1kb. The HvITPK4 also have single exon structure but size vary compared to other species. The OsITPK4 gene also have only one exon similar to HvITPK4 with same size. The slight variation in exon length indicated species specific coding sequences or variation in untranslated region (UTR) that would impact mRNA stability or translation efficiency sequence adaptions [46].
3.3. Comparative synteny analysis of ITPK gene family across different species
To study the evolutionary relationship among ITPK gene family members, we constructed an interspecies synteny analysis of 5 species comparing Triticum aestivum with other three monocotyledons species, i.e., Hordeum vulgare, Oryza sativa, Zea mays and one dicotyledon, i.e., Arabidopsis thaliana (Fig 3). The strength of association of TaITPK genes from highest to lowest with other species was: Hordeum vulgare [10], Oryza sativa [4], Zea mays [3] and Arabidopsis thaliana (0). The wheat and barley showed highest chromosome level conservation supporting known evolutionary relationships among Triticeae cereal. Furthermore, the synteny analysis of Triticum aestivum with Oryza sativa and Zea mays revealed limited chromosome-level collinearity may be due to extensive genome rearrangement and structural divergence following their evolutionary separation.
Syntenic gene pairs are highlighted in red lines.
3.4. Gene localization, selection pressure and divergence analysis of TaITPK genes
Hexaploid wheat (Triticum aestivum L.) consists of three sub-genomes, i.e., A, B, and D allowing each wheat gene to have possibly three homologs, one from each set of homologous chromosomes. Genes of TaITPK family randomly and unevenly distributed. Out of total seven chromosomes groups in wheat, ITPK genes were present on chromosome 1, 4, 5 and 7 (Fig 4). The chromosome 1A, 1B, 1D carried one gene respectively. Likewise, chromosome 7A, 7B, 7D and 5A, 5B and 5D also contained one gene present each on them. The chromosome 4 contained abundance no. of genes, i.e., 6 in manner of 2 genes on each 4A, 4B and 4D respectively. None of the gene was present on chromosomes 2, 3 and 6. Thus, a total of 15 TaITPK genes were identified across the A, B, and D sub genomes.
Here, the identified genes have been shown in red and chromosome with grey bar numbered in red
Furthermore, to analyze the selection pressure of ITPK gene family in wheat, the ratio of nonsynonymous (Ka) to synonymous (Ks) substitution rates was calculated describing that how natural selection affect ITPK gene divergence in wheat. If the value of Ka/Ks = 1, it indicates neutral selection, where mutations are neither strongly advantageous nor disadvantageous. Ka/Ks ratio < 1 indicates purifying selection, and Ka/Ks ratio > 1 indicated positive selection [28,47]. The results revealed both positive and negative evolution in ITPK genes in Triticum aestivum (S2 Table) (See Supporting Information). The total 33 duplication events have been observed in Triticum aestivum during evolution. In addition to identifying the type of selection, the approximate divergence time between duplicated gene pairs was calculated using formula T = Ks / (2r) × 10−6, where T represents the divergence time in million years, Ks is the rate of synonymous substitutions per site, and r corresponds to the assumed rate of synonymous substitutions per site per year. The substitution rate of 6.5 × 10−9 substitutions per synonymous site per year was used as a standard reference in cereals [48]. This calculation provided insights into the evolutionary timeframe during which duplication events occurred.
3.5. Analysis of cis-regulating elements in the promoter of TaITPK family genes
The function of a gene is largely influenced by the type and abundance of cis-regulatory elements present in its promoter region [49]. To study the transcriptional regulation of TaITPK genes, the 1.5 kb upstream promoter regions were analyzed using PlantCARE. A wide range of cis acting elements were noted including motifs associated with hormone response, growth, development and stress response which depicted the diverse regulatory control of TaITPK gene family (Fig 5). The promoter region also contained TATA-box and CAAT-box which are essential elements for transcriptional machinery [50]. Moreover, an abundance of development and seed-specific elements were also observed indicating that TaITPK genes were also active during grain filling maturation stage that coincide to accumulation of phytic acid
The genomic sequence 1500 bp upstream of the start codon was selected as the promoter for analysis.
3.6. Protein modeling and protein-protein interaction
To gain insight into the structural information about inositol tris-phosphate 5/6 protein, tertiary structures of protein models were generated via Swiss model using protein sequences of 15 wheat ITPK genes (Fig 6) Each ITPK groups from 1–4,6 showed similarity within their homeologous copies present on A, B and D genome. The quality of models was evaluated through GMQE (Global Model Quality Estimate) and QMEANDisCo [32,51] where GMQE and QMEANDisCo global scores range from 0 to 1, with higher values indicating better expected model quality [52]. The results suggested strong conservation among homoeologs. As wheat has hexaploid genome, the presence of similar A, B, and D copies strongly supported the idea that these genes were retained after polyploidization and remained structurally conserved. This suggests that these homoeologs may still be functionally important and were not lost during genome evolution.
The interaction of wheat ITPK genes with other proteins was further studied (Fig 7). The Protein-Protein Interaction (PPI) network of ITPK protein was constructed on STRING database with highest confidence (0.900) interaction score. The results showed that all the TaITPK proteins showed interaction with inositol pentakisphosphate 2-kinase which phosphorylates Ins (1,3,4,5,6) P5 at position 2 to form Ins (1,2,3,4,5,6) P6. Moreover, the TaITPK proteins also showed protein interaction with inositol polyphosphate multikinase. The analysis showed < 1.0e-16 PPI value which indicated higher degree of statistical significance and more interaction of TaITPK proteins among themselves than what would be expected for a random set of proteins of the same size and degree distribution drawn from the genome. Such an enrichment indicated that the proteins were at least partially biologically connected, as a group [53].
Here, A0A3B6J0F1, A0A3B6B6S8, A0A3B6CED3 represent Inositol-pentakisphosphate 2-kinase; A0A3B6SPU8, A0A3B6TP90 represent Inositol polyphosphate multikinase proteins.
3.7. Tissue specific in silico TaITPK expression analysis
The RNA sequence data of Chinese spring wheat cultivar in different plant tissues and at different growth stages were analyzed. The results (Fig 8) revealed that TaITPK4-1A, TaITPK4-1B and TaITPK4-1D showed highest expression as compared to other genes in stem, spike, root and grain and low to none expression was observed in leaf tissue. In case of TaITPK3-4A, TaITPK3-4B and TaITPK3-4D moderate expression was observed in grain_z85 stage while at growth and development stages, zero to low level of expression was observed. The expression of TaITPK2-4A, TaITPK2-4B and TaITPK2-4D was low except at leaf_z71 stage which showed moderate gene expression. In TaITPK6-5A, TaITPK6-5B and TaITPK6-5D, the expression observed was moderate at all stages except in grain filling stages. The expression of TaITPK1-7A, TaITPK1-7B and TaITPK1-7D showed least expression results. The results showed contradiction to Yang et al. [54] observations in which the expression of AtITPK4 genes was lowest in root, stem, leaves and silique tissues and highest in AtITPK3 gene. This indicated the species-specific expression pattern of genes. Stiles et al. [10] showed highest expression of ITPK3 gene and lowest in ITPK2 and more expression was observed in early seed development stage.
Here, Zadoks scale(Zs) stages represented as: (Seedling stage = (zS10); Three leaves = zS13; Three tillers = zS23; Spike at 1 cm = zS30; Two nodes = zS32; Meiosis = zS39; Anthesis = zS65; 2 DAA = zS71; 14 DAA = zS75; 30 DAA = zS85 10). The bar scale at left showed the levels of expression: red color for highest expression level and blue color showed lowest expression level.
3.8. Expression patterns of TaITPK genes in response to FeSO4 and ZnSO4
To study the response of Inositol tetrkisphosphate (ITPK) genes involved in biosynthetic pathway of phytic acid, the relative expression analysis of four ITPK genes (ITPK2-4A, ITPK3-4D, ITPK4-1A, and ITPK6-5A) (as shown in Fig 9) were selected on the basis of in silico expression profiling. As similar in silico expressions were observed among the A, B, and D subgenome homoeologs, one representative member from each homoeologous group was chosen for preliminary expression analysis. ITPK1 was not included due to its comparatively weak overall in silico expression. However, this does not exclude the possibility that ITPK1 may show higher expression at other developmental stages, in specific tissues, or under conditions not examined in the present study. Furthermore, the selected genes were analyzed in two wheat genotypes, Fateh-Jang and Akbar-19 under control and minerals treated conditions at grain filling stage. The results revealed treatment-dependent expression pattern among the selected ITPK genes in both wheat genotypes at the grain filling stage. TaITPK3-4D showed comparatively higher relative expression under FeSO4, ZnSO4, and combined FeSO4 + ZnSO4 treatments in both Fateh-Jang and Akbar-19. TaITPK2-4A showed relatively low expression under individual treatments but showed higher relative expression under the combined treatment, especially in Akbar-19 genotype. In contrast, TaITPK4-1A showed relatively higher expression under FeSO4, especially in Fateh-Jang, whereas TaITPK6-5A showed increased in relative expression under combined treatment in Fateh-Jang only. Similar lower expression pattern of ITPK6 gene was observed in Arabidopsis ITPK4 in silique development stage by Yang et al. [54].
Bars represent mean relative expression ± SE of three technical measurements from one biological sample per genotype × treatment combination.
4. Discussion
The genome wide analysis identified 15 Inositol tetrakisphosphate (ITPK) genes which were distributed across the A, B and D sub-genomes of hexaploid wheat (Triticum aestivum L.) The presence of several homoelogous copies within each clade showed extensive gene expansion which were the results of polyploidization and tandem duplication [55–57]. The conservation of exon-intron arrangements and motifs among homoeologs depicted functional conservation during evolution while, some small differences among the gene copies indicate that they might have developed slightly different roles, helping the plant adapt to different growth or stress conditions. All TaITPK proteins contained the inositol [1,3,4] P3 5/6-kinases (ITPKs) domain, which is a conserved domain responsible for adding phosphate groups to inositol phosphate molecules to convert inositol triphosphate (InsP3) to inositol pentaphosphate (InsP5) via sequential phosphorylation [58]. This reaction is a key step in the phytate (inositol hexakisphosphate, IP₆) biosynthesis pathway. The conservation of this domain confirms that all identified wheat ITPK genes have similar catalytic functions to those found in rice and Arabidopsis, which are also involved in phosphate metabolism.
Furthermore, the mapping of TaITPK genes on wheat chromosomes showed that they were unevenly distributed across different chromosomes, but their positions correspond well to those found in other cereal crops like barley, rice and maize. This showed that these genes have evolutionarily conserved across cereals. The phylogenetic tree grouped TaITPK genes into several clades with their homologs from rice, maize, and barley, indicating that the ITPK gene family existed before the divergence of these species [47] and then expanded in wheat through polyploidization. Comparative synteny mapping between wheat and other cereal species revealed strong collinearity with rice, maize, and barley, confirming a conserved evolutionary path among monocots. These conserved genomic regions highlighted the functional stability of ITPK genes, suggesting that their enzymatic role in the inositol phosphate pathway has remained under strong purifying selection pressure throughout cereal evolution. In contrast, limited collinearity was observed between Triticum aestivum and the dicot Arabidopsis thaliana, which is consistent with the deep evolutionary divergence between monocots and dicots. The absence of syntenic relationships with Arabidopsis highlighted that ITPK gene family expansion and diversification were shaped primarily within monocot-specific evolutionary pathways.
The cis-regulatory (promoter) analysis revealed the presence of a numerous cis-regulatory elements that were responsible for controlling TaITPK gene expression during different developmental stages and stress conditions. Importantly, several growth and development related cis-elements such as the GCN4_motif, O2-site, and CAAT-box were detected. The GCN4_motif is an endosperm-specific element that activates genes during seed development and storage compound formation [59]. It was mostly found in promoter region of TaITPK1 genes that indicated the transcriptionally activation of this gene group during grain development. The O2-site were linked with seed maturation and protein synthesis [60,61] and the CAAT-box was generally involved in meristem and tissue differentiation [62,63] which may contribute to expression regulation during early development stage and reproductive tissue formation. In addition to developmental elements, several hormonal and stress-responsive elements, including ABRE (abscisic acid response), TGACG-motif (MeJA response), and TCA-element (salicylic acid response), were also detected. These cis-elements indicated the potential roles of TaITPK genes in phosphate signaling and abiotic stress regulation, as hormonal crosstalk often influences inositol phosphate metabolism under environmental challenges [64].
The in-silico expression analysis revealed that several TaITPK genes were highly expressed in spike and grain tissues, especially during the reproductive and grain-filling stages [53]. This expression pattern coincided with the grain developmental period during which phytic acid accumulation is known to occur, suggesting a possible role of selected TaITPK genes in phytic acid metabolism during seed development [65]. Furthermore, preliminary qRT-PCR profiling indicated treatment dependent differences in the relative expression patterns of selected TaITPK genes under Fe and Zn supplementation. Among the genes examined, TaITPK3-4D showed comparatively higher relative expression under both Fe and Zn treatments, whereas TaITPK6-5A displayed a distinct expression pattern under the combined Fe and Zn treatment. These observations suggest that individual TaITPK members may respond differently to mineral availability. However, because the qRT-PCR measurements were based on technical replicates without independent biological replication, these expression patterns should be interpreted descriptively and require confirmation in biologically replicated experiments before any functional or metabolic conclusions can be drawn.
Phytate (inositol hexakisphosphate, IP₆) is the primary phosphorus storage compound in cereal grains [66], but it also functions as a strong chelator of divalent metal ions such as iron (Fe²⁺) and zinc (Zn²⁺), thereby reducing their bioavailability in humans and animals which mainly contributed towards micronutrient deficiencies in consumers [15]. The combined presence of seed-specific cis-elements and high expression of TaITPK genes in grains suggested that these genes play a critical role in phytate accumulation and consequently influence nutritional quality. Targeted manipulation of TaITPK genes offers a practical molecular strategy to address this problem. The identification of endosperm-active TaITPK or seed specific gene homologs provides suitable targets for CRISPR/Cas9-mediated gene knockout or silencing, allowing the development of low-phytate wheat lines without affecting plant growth or yield. Previous studies in rice and maize also showed that editing or silencing of ITPK genes significantly reduced seed phytate levels and improved mineral bioavailability [67–69]. Understanding this division of function will help breeders/ biotechnologists to target specific TaITPK genes without disturbing essential phosphate signaling pathways in other tissues. Although ITPK genes are functionally associated with the phytic acid biosynthetic pathway, phytic acid content was not directly measured in the present study. Therefore, the observed TaITPK expression patterns cannot be interpreted as direct evidence of changes in phytic acid accumulation. The possible relationship between TaITPK expression and phytic acid accumulation remains a hypothesis based on previous studies and requires validation through direct, biologically replicated phytic acid measurements.
5. Conclusion
In this study, we conducted a comprehensive genome-wide analysis of the TaITPK gene family, examining conserved domains, gene structure, protein motifs, chromosomal locations, selection pressure analysis, protein-protein interaction and expression profiles in different tissues at different growth stages which play an important role in synthesis of phytic acid. This in-depth study provides a foundation for researchers to better understand these genes and identify promising candidate genes for developing low-phytate crops by using advanced biotechnological tools, such as genome editing. Consequently, it paves the way for enhancing the nutritional quality of common wheat (T. aestivum) and other staple food crops.
Supporting information
S1 Table. Characteristics of TaITPK proteins identified in Triticum aestivum.
https://doi.org/10.1371/journal.pone.0359528.s001
(DOCX)
S2 Table. Ka/Ks ratios and divergence time of paralogous ITPK gene pairs.
https://doi.org/10.1371/journal.pone.0359528.s002
(DOCX)
S4 Table. Gene Ids of ITPK proteins of O. sativa, H. vulgare and Z. mays.
https://doi.org/10.1371/journal.pone.0359528.s004
(DOCX)
S5 Table. List of primers used in qRT-PCR analysis.
https://doi.org/10.1371/journal.pone.0359528.s005
(DOCX)
S1 File. Cis-regulatory elements identified in the promoter regions of TaITPK genes.
https://doi.org/10.1371/journal.pone.0359528.s006
(XLSX)
S2 File. Relative expression calculations for selected TaITPK genes.
https://doi.org/10.1371/journal.pone.0359528.s007
(XLSX)
References
- 1. Żyła K, Duda A. Towards Improved Bioavailability of Cereal Inositol Phosphates, Myo-Inositol and Phenolic Acids. Molecules. 2025;30(3):652. pmid:39942756
- 2. Nissar J, Ahad T, Naik HR, Hussain SZ. A review phytic acid: as antinutrient or nutraceutical. J Pharmacogn Phytochem. 2017;6(6):1554–60.
- 3. Maqbool MA, Beshir A. Zinc biofortification of maize (Zea mays L.): Status and challenges. Plant Breeding. 2018;138(1):1–28.
- 4. Li Y, Cheng Y, Tang N. Unraveling the Intricate Interplay: Iron and Zinc’s Regulatory Mechanisms on Calcium Bioavailability During Intestinal Absorption. Food Reviews International. 2024;41(2):345–72.
- 5. Zhang YY, Stockmann R, Ng K, Ajlouni S. Opportunities for plant-derived enhancers for iron, zinc, and calcium bioavailability: A review. Compr Rev Food Sci Food Saf. 2021;20(1):652–85. pmid:33443794
- 6. Sahu A, Verma R, Gupta U, Kashyap S, Sanyal I. An Overview of Targeted Genome Editing Strategies for Reducing the Biosynthesis of Phytic Acid: an Anti-nutrient in Crop Plants. Mol Biotechnol. 2024;66(1):11–25. pmid:37061991
- 7. Qin D, Toyonaga D, Saneoka H. Characterization of myo-inositol-1-phosphate synthase (MIPS) gene expression and phytic acid accumulation in oat (Avena sativa) during seed development. CEREAL RESEARCH COMMUNICATIONS. 2021;50(3):379–84.
- 8. Chatree S, Thongmaen N, Tantivejkul K, Sitticharoon C, Vucenik I. Role of Inositols and Inositol Phosphates in Energy Metabolism. Molecules. 2020;25(21):5079. pmid:33139672
- 9. Laha D, Parvin N, Hofer A, Giehl RFH, Fernandez-Rebollo N, von Wirén N, et al. Arabidopsis ITPK1 and ITPK2 Have an Evolutionarily Conserved Phytic Acid Kinase Activity. ACS Chem Biol. 2019;14(10):2127–33. pmid:31525024
- 10. Stiles AR, Qian X, Shears SB, Grabau EA. Metabolic and signaling properties of an Itpk gene family in Glycine max. FEBS Lett. 2008;582(13):1853–8. pmid:18474240
- 11. Goyal S, Nagar S, Mallesh G, Kumari K, Kharor N. A review on role of phytic acid and phytase in food and feed. Chem Sci Rev Lett. 2022;11(44):510–8.
- 12. Marathe A, Krishnan V, Vinutha T, Dahuja A, Jolly M, Sachdev A. Exploring the role of Inositol 1,3,4-trisphosphate 5/6 kinase-2 (GmITPK2) as a dehydration and salinity stress regulator in Glycine max (L.) Merr. through heterologous expression in E. coli. Plant Physiol Biochem. 2018;123:331–41. pmid:29289899
- 13. Kumar A, Dash GK, Sahoo SK, Lal MK, Sahoo U, Sah RP, et al. Phytic acid: a reservoir of phosphorus in seeds plays a dynamic role in plant and animal metabolism. Phytochem Rev. 2023;22(5):1281–304.
- 14. Samtiya M, Aluko RE, Dhewa T. Plant food anti-nutritional factors and their reduction strategies: an overview. Food Prod Process and Nutr. 2020;2(1).
- 15. Bloot APM, Kalschne DL, Amaral JAS, Baraldi IJ, Canan C. A Review of Phytic Acid Sources, Obtention, and Applications. Food Reviews International. 2021;39(1):73–92.
- 16. Singh J, Arora SK. Antinutritional factors in plant based foods. Int J Agric Sci. 2023;19(1):366–75.
- 17. Amat T, Assifaoui A, Schmitt C, Saurel R. Importance of binary and ternary complex formation on the functional and nutritional properties of legume proteins in presence of phytic acid and calcium. Crit Rev Food Sci Nutr. 2023;63(33): 12036–58.
- 18.
Manzoor A, Nabi A, Shiekh RA, Dar AH, Usmani Z, Altaf A, et al. Phytates. Handbook of Plant and Animal Toxins in Food. CRC Press. 2022. p. 27–36.
- 19. Silva VM, Putti FF, White PJ, Dos Reis AR. Phytic acid accumulation in plants: biosynthesis pathway regulation and role in human diet. Plant Physiol Biochem. 2021;164:132–46.
- 20. Kryukov VS, Glebova IV, Zinoviev SV. Reevaluation of Phytase Action Mechanism in Animal Nutrition. Biochemistry (Mosc). 2021;86(Suppl 1):S152–65. pmid:33827406
- 21. Lowe NM. The global challenge of hidden hunger: perspectives from the field. Proc Nutr Soc. 2021;80(3):283–9. pmid:33896431
- 22. Mao Y, Hou S, Shi J, Economo EP. TREEasy: An automated workflow to infer gene trees, species trees, and phylogenetic networks from multilocus data. Wiley Online Library. 2020.
- 23. Letunic I, Bork P. Interactive Tree of Life (iTOL) v6: recent updates to the phylogenetic tree display and annotation tool. Nucleic Acids Res. 2024;52(W1):W78–82. pmid:38613393
- 24. Bailey TL, Boden M, Buske FA, Frith M, Grant CE, Clementi L, et al. MEME SUITE: tools for motif discovery and searching. Nucleic Acids Res. 2009;37(Web Server issue):W202-8. pmid:19458158
- 25. Chen C, Wu Y, Li J, Wang X, Zeng Z, Xu J, et al. TBtools-II: A “one for all, all for one” bioinformatics platform for biological big-data mining. Mol Plant. 2023;16(11):1733–42. pmid:37740491
- 26. Li X, Liu S, Yu P. Genome-Wide Identification of ATL Gene Family in Wheat and Their Expression Analysis in Response to Salt Stress. Plants (Basel). 2025;14(9):1306. pmid:40364335
- 27. Ghosh S, Chakraborty S. Phylogenomics Analysis of SARS-CoV2 Genomes Reveals Distinct Selection Pressure on Different Viral Strains. Biomed Res Int. 2020;2020:5746461. pmid:33299872
- 28. Hurst LD. The Ka/Ks ratio: diagnosing the form of sequence evolution. Trends Genet. 2002;18(9):486. pmid:12175810
- 29. Biasini M, Bienert S, Waterhouse A, Arnold K, Studer G, Schmidt T, et al. SWISS-MODEL: modelling protein tertiary and quaternary structure using evolutionary information. Nucleic Acids Res. 2014;42(Web Server issue):W252-8. pmid:24782522
- 30. Bordoli L, Schwede T. Automated protein structure modeling with SWISS-MODEL Workspace and the Protein Model Portal. Methods Mol Biol. 2012;857:107–36. pmid:22323219
- 31. Altunkulah E, Ensari Y. Protein Structure Prediction: an In-Depth Comparison of Approaches and Tools. Eskişehir Tek Üniversitesi Bilim ve Teknol Dergisi-C Yaşam Bilim Ve Biyoteknoloji. 2024;13(1):31–51.
- 32. Benkert P, Biasini M, Schwede T. Toward the estimation of the absolute quality of individual protein structure models. Bioinformatics. 2011;27(3):343–50. pmid:21134891
- 33. Szklarczyk D, Kirsch R, Koutrouli M, Nastou K, Mehryary F, Hachilif R, et al. The STRING database in 2023: protein-protein association networks and functional enrichment analyses for any sequenced genome of interest. Nucleic Acids Res. 2023;51(D1):D638–46. pmid:36370105
- 34. Szklarczyk D, Gable AL, Nastou KC, Lyon D, Kirsch R, Pyysalo S, et al. The STRING database in 2021: customizable protein-protein networks, and functional characterization of user-uploaded gene/measurement sets. Nucleic Acids Res. 2021;49(D1):D605–12. pmid:33237311
- 35. Zheng K, Lu J, He X, Lan S, Zhai T, Cao S, et al. Genome-Wide Identification and Expression Analysis of GATA Family Genes in Dimocarpus longan Lour. Int J Mol Sci. 2024;25(2):731. pmid:38255805
- 36. Wang Z, Wu W, Liu T, Shi W, Ma K, He Z, et al. Identification and Characterization of the StCPAI Gene Family in Potato. Plants (Basel). 2025;14(16):2472. pmid:40872095
- 37. Pearce S, Vazquez-Gross H, Herin SY, Hane D, Wang Y, Gu YQ, et al. WheatExp: an RNA-seq expression database for polyploid wheat. BMC Plant Biol. 2015;15:299. pmid:26705106
- 38. Hafeez MB, Ramzan Y, Khan S, Ibrar D, Bashir S, Zahra N, et al. Application of Zinc and Iron-Based Fertilizers Improves the Growth Attributes, Productivity, and Grain Quality of Two Wheat (Triticum aestivum) Cultivars. Front Nutr. 2021;8:779595. pmid:34966772
- 39. Pattemore JA. RNA extraction from cereal vegetative tissue. Methods Mol Biol. 2014;1099:17–21. pmid:24243192
- 40.
Mkt CN. MMLV first strand cDNA synthesis kit. 2007 July.
- 41. Cao M, Zhang Y, Zou X, Yin H, Yin Y, Li Z. Genome-wide identification, classification, expression analysis, and screening of drought and heat resistance-related candidates of the Rboh gene family in wheat. Plants. 2024;13(23):3377.
- 42. Dávila López M, Martínez Guerra JJ, Samuelsson T. Analysis of gene order conservation in eukaryotes identifies transcriptionally and functionally linked genes. PLoS One. 2010;5(5):e10654. pmid:20498846
- 43. Wang J, Chitsaz F, Derbyshire MK, Gonzales NR, Gwadz M, Lu S, et al. The conserved domain database in 2023. Nucleic Acids Res. 2023;51(D1):D384–8. pmid:36477806
- 44. Betts MJ, Guigó R, Agarwal P, Russell RB. Exon structure conservation despite low sequence similarity: a relic of dramatic events in evolution?. EMBO J. 2001;20(19):5354–60. pmid:11574467
- 45. Aramrak A, Kidwell KK, Steber CM, Burke IC. Molecular and phylogenetic characterization of the homoeologous EPSP Synthase genes of allohexaploid wheat, Triticum aestivum (L.). BMC Genomics. 2015;16:844. pmid:26492960
- 46. Li Q, Makri A, Lu Y, Marchand L, Grabs R, Rousseau M, et al. Genome-wide search for exonic variants affecting translational efficiency. Nat Commun. 2013;4:2260. pmid:23900168
- 47. Xiong T, Zhang Z, Fan T, Ye F, Ye Z. Origin, evolution, and diversification of inositol 1,4,5-trisphosphate 3-kinases in plants and animals. BMC Genomics. 2024;25(1):1–19.
- 48. Rathour M, Shumayla, Alok A, Upadhyay SK. Investigation of Roles of TaTALE Genes during Development and Stress Response in Bread Wheat. Plants (Basel). 2022;11(5):587. pmid:35270056
- 49. Liu Z, Yang J, Yan Z, Huang L, Xing C, Zhao M, et al. Genome-wide identification of GmEDS1 gene family members in soybean and expression analysis in response to biotic and abiotic stresses. Front Plant Sci. 2025;16:1554399. pmid:40365565
- 50. Savinkova LK, Sharypova EB, Kolchanov NA. On the Role of TATA Boxes and TATA-Binding Protein in Arabidopsis thaliana. Plants (Basel). 2023;12(5):1000. pmid:36903861
- 51. Studer G, Rempfer C, Waterhouse AM, Gumienny R, Haas J, Schwede T. QMEANDisCo-distance constraints applied on model quality estimation. Bioinformatics. 2020;36(6):1765–71. pmid:31697312
- 52. Waterhouse A, Bertoni M, Bienert S, Studer G, Tauriello G, Gumienny R, et al. SWISS-MODEL: homology modelling of protein structures and complexes. Nucleic Acids Res. 2018;46(W1):W296–303. pmid:29788355
- 53. Rosati D, Palmieri M, Brunelli G, Morrione A, Iannelli F, Frullanti E, et al. Differential gene expression analysis pipelines and bioinformatic tools for the identification of specific biomarkers: A review. Comput Struct Biotechnol J. 2024;23:1154–68. pmid:38510977
- 54. Tang Y, Tan S, Xue H. Arabidopsis inositol 1, 3, 4-trisphosphate 5/6 kinase 2 is required for seed coat development. Acta Biochim Biophys Sin. 2013;45(7):549–60.
- 55. Cannon SB, Mitra A, Baumgarten A, Young ND, May G. The roles of segmental and tandem gene duplication in the evolution of large gene families in Arabidopsis thaliana. BMC Plant Biol. 2004;4:10. pmid:15171794
- 56. Hu G, Grover CE, Arick MA, Liu M, Peterson DG, Wendel JF. Homoeologous gene expression and co-expression network analyses and evolutionary inference in allopolyploids. Brief Bioinform. 2021;22(2):1819–35. pmid:32219306
- 57. Kuzmin E, Taylor JS, Boone C. Retention of duplicated genes in evolution. Trends Genet. 2022;38(1):59–72. pmid:34294428
- 58. Karmakar A, Bhattacharya S, Sengupta S, Ali N, Sarkar SN, Datta K, et al. RNAi-Mediated Silencing of ITPK Gene Reduces Phytic Acid Content, Alters Transcripts of Phytic Acid Biosynthetic Genes, and Modulates Mineral Distribution in Rice Seeds. Rice Science. 2020;27(4):315–28.
- 59. Qu LQ, Xing YP, Liu WX, Xu XP, Song YR. Expression pattern and activity of six glutelin gene promoters in transgenic rice. J Exp Bot. 2008;59(9):2417–24. pmid:18467323
- 60. Li C, Qiao Z, Qi W, Wang Q, Yuan Y, Yang X, et al. Genome-wide characterization of cis-acting DNA targets reveals the transcriptional regulatory framework of opaque2 in maize. Plant Cell. 2015;27(3):532–45. pmid:25691733
- 61. Chen Y, Zhang W, Zhao F, Liu G, Zhao D, Xu J, et al. Genome-Wide Identification, Phylogeny and Expression Analysis of the Magnesium Release Gene Family in Wheat (Triticum aestivum L.). Curr Issues Mol Biol. 2025;47(11):882. pmid:41296386
- 62. Laloum T, De Mita S, Gamas P, Baudin M, Niebel A. CCAAT-box binding transcription factors in plants: Y so many?. Trends Plant Sci. 2013;18(3):157–66. pmid:22939172
- 63. Bai X, Qiao P, Liu H, Shang Y, Guo J, Dai K. Genome-wide identification of the E-class gene family in wheat: evolution, expression, and interaction. Front Plant Sci. 2024;15:1419437. pmid:39290745
- 64. Su XB, Ko A-LA, Saiardi A. Regulations of myo-inositol homeostasis: Mechanisms, implications, and perspectives. Adv Biol Regul. 2023;87:100921. pmid:36272917
- 65. Bhati KK, Aggarwal S, Sharma S, Mantri S, Singh SP, Bhalla S, et al. Differential expression of structural genes for the late phase of phytic acid biosynthesis in developing seeds of wheat (Triticum aestivum L.). Plant Sci. 2014;224:74–85. pmid:24908508
- 66. Cheng Z, Montgomery MK. Physiological roles of phosphoinositides and inositol phosphates: implications for metabolic dysfunction-associated steatotic liver disease. Clin Sci. 2025;139(19):1095–144.
- 67. Sengupta S, Bhattacharya S, Karmakar A, Ghosh S, Sarkar SN, Gangopadhyay G, et al. RNAi-mediated down-regulation of ITPK-2 enhanced inorganic phosphorus and minerals in the transgenic rice. J Biosci. 2021;46:32. pmid:33859067
- 68. Sashidhar N, Harloff HJ, Potgieter L, Jung C. Gene editing of three BnITPK genes in tetraploid oilseed rape leads to significant reduction of phytic acid in seeds. Plant Biotechnol J. 2020;18(11):2241–50. pmid:32191373
- 69. Vlčko T, Ohnoutková L. Allelic Variants of CRISPR/Cas9 Induced Mutation in an Inositol Trisphosphate 5/6 Kinase Gene Manifest Different Phenotypes in Barley. Plants (Basel). 2020;9(2):195. pmid:32033421