Identification, characterization, and expression profiling of genes encoding tubby-like proteins in rice exposed to realistic environmental contamination of anilofos and bentazone

Graphical abstract

Highlights

• •Seven rice tubby-like proteins genes were found to be responsive to herbicide stress.
• •These genes exhibited nuclear localization and contained conserved domains and stress-related motifs.
• •Expression and promoter analyses indicated roles in hormone signaling and stress response.

Abstract

Tubby-like proteins, which are encoded by large multigene families in plants, play important roles in abiotic stress tolerance; however, it is still unclear how they work in rice during herbicides stress. In order to address this gap, we looked into the traits and roles of genes encoding tubby-like proteins in rice plants (Oryza sativa; hereafter referred to as OsTLP genes) exposed to two herbicides, anilofos and bentazone. Transcriptome analysis revealed 7 genes encoding tubby-like proteins. Quantitative reverse-transcription PCR confirmed that the expression of 6 and 4 TLP genes was enhanced under anilofos- and bentazone-induced stress, respectively. Seven genes were found to be unevenly distributed over five of the twelve chromosomes, with segmental duplication playing a role in the growth of gene families, according to chromosomal mapping. According to a collinearity research, rice and other plant species have the following orthologous gene pairs: 17 with sorghum (Sorghum bicolor), 0 with Arabidopsis (Arabidopsis thaliana), 11 with maize (Zea mays), and 7 with soybean (Glycine max). These genes were divided into three clades by phylogenetic analysis. According to structural study, TLP genes have a variety of conserved domains, motif compositions, cis-acting elements, and designs that allow them to respond to both biotic and abiotic stress. Analysis of protein–protein interaction networks further showed that tubby-like proteins may contribute to anilofos and bentazone metabolism. According to in silico predictions of subcellular localization, all seven TLP genes’ encoded proteins are found in the nucleus. Docking analyses identified important amino acid residues implicated in pesticide binding between tubby-like proteins and the two herbicides (anilofos and bentazone). These results shed light on the TLP gene superfamily and provide useful resources for functional research on these genes’ functions in herbicides metabolism.

1. Introduction

Pesticides are widely used in agriculture to control pests such as insects, rodents, fungi, bacteria, and weeds in order to enhance agricultural productivity¹. Pesticides are used by many of the 1.8 billion people who work in agriculture worldwide to safeguard food supply and commercial crops². However, overuse of pesticides has contaminated the ecosystem extensively. In particular, residues of bentazone (BNTZ) and anilofos, two herbicides, are frequently detected in soil and water within cultivated land[3], [4]. Herbicide residues can have a detrimental effect on plant health by lowering dry biomass, sugar content, and total chlorophyll⁵. Furthermore, humans face health risks due to the buildup of toxic compounds in plant tissues, which can lead to major problems like immune system failure, food poisoning, and cognitive decline⁶. Prolonged pesticide residue exposure has also been linked to neurological diseases; imbalance of the cardiovascular, endocrine, respiratory, and renal systems; skeletal problems; dysregulation of the reproductive system; and even cancer².

Reducing the harmful effects of herbicide residues on both plants and human health is largely dependent on plant detoxification. Plants sequester and break down pesticide chemicals via enzymes[7], [8]. Following absorption, a three-phase metabolic mechanism converts pesticides into less toxic metabolites: I) transformation, II) conjugation, and III) compartmentation. Enzymes like haloacid dehalogenase and cytochrome P450 mediate the dehalogenation, hydrolysis, and oxidation of pesticides during phase I. In phase II, enzymes such as glycosyltransferases and acetyltransferases help conjugate pesticides and the products of degradation generated in phase I to glucosides and acetyl-CoA via enzymatic catalysis. In phase III, pesticides and their metabolites are either removed from the cell or integrated into plant macromolecules by ABC transporters and multidrug and hazardous compound extrusion transporters[8], [9]. Together, these enzymes improve detoxification and pesticide metabolism, lowering the buildup of toxic substances in plants. Previous research has demonstrated how rice plants produce BNTZ metabolites via metabolic enzymes such as sulfotransferase, cytochrome P450, and acetyltransferase¹⁰. Therefore, controlling several metabolic enzymes at once could greatly improve the plant’s capacity for detoxification and the metabolism of pesticides; yet, there is currently little research on this strategy.

Anilofos is a organophosphorus herbicide that is frequently used in fields of soybean, maize, cotton, wheat, rice, and rapeseed to control annual grasses and broad-leaf weeds because of its high crop tolerance and potency[11], [12], [13]. Due to its low biodegradability, anilofos has a half-life of 37–77 days and remains in soil and aquatic systems for a very long time[1], [11]. Residues found in water, soil, and agricultural products (Ranged from 0.04 to 0.09 mg/kg) frequently surpass the upper bounds established by regulatory agencies¹¹. Its accumulation could exert toxicity on earthworms (Pheretima) and Nile tilapia (Oreochromis niloticus) [11], [14] and induce mutagenicity in onion (Allium cepa) and reproductive toxicity in mice (Mus musculus) [15], [16], [17]. Moreover, human peripheral lymphocytes are both cytotoxically and genotoxically affected by anilofos and is classified as a moderately hazardous pesticide (Class II) by the World Health Organization¹⁸.

Bentazone (BNTZ), a selective benzothiadiazole herbicide, is also frequently used to eradicate perennial and broadleaf weeds from rice, maize, wheat, and soybean crops[10], [19]. This herbicide has become a serious environmental pollutant as a result of overuse. Rapid runoff is made possible by its highwater solubility (7112 mg/L), low mineralization rate, and poor soil adsorption capacity (Koc = 55.3). Groundwater BNTZ concentrations in Spain have reached 120 μg/L, significantly higher than the European Union’s legal limit of 0.1 μg/L[20], [21], [22]. In aquatic settings, residual BNTZ has the potential to bioaccumulate and harm aquatic life²³. With a reported half-life of 8–35 days, this soil pollutant is extremely resistant to hydrolysis and is only partially broken down by microbial activity. After the final usage, it may remain in aquifers for up to 20 years²⁰. For instance, the BNTZ accumulation concentrations in rice plant tissues treated with 0.2 mg/L BNTZ for six days were found to reach almost 1 mg/kg, significantly higher than China’s maximum residue limit of 0.1 mg/kg¹⁰. Human respiratory distress, nausea, vomiting, diarrhea, tremors, and even death are all brought on by BNTZ, while being categorized by the US Environmental Protection Agency as “Group E,” which means it is not carcinogenic to animals[24], [25].

Tubby-like proteins (TLPs) were initially discovered in obese Tubby mice and were thus named after them[26], [27]^. These proteins, which are encoded by TLP genes, are characterized by two distinct domains, the F-box situated near the N-terminal and the Tubby domain positioned at the C-terminal, which exhibit a coevolutionary relationship[28], [29]. The F-box domain is highly conserved and serves as a crucial point of interaction with other proteins, such as specific Skp1-like (SK) proteins, which function as SCF-type E3 ligases[27], [28]. The Tubby domain facilitates anchoring to the plasma membrane via phosphatidylinositol 4,5-bisphosphate (PI(4,5)P₂) [26], [28]. The TLP gene family has been identified across numerous plant species, and many of its members play pivotal roles in various organs under abiotic stress[26], [27], [29]. The expression of TLP genes in plants increases in response to a variety of stressors, including drought, salinity, and cold temperatures, in order to enhance plant resistance⁹. For example, OsTLP2 regulates OsWRKY13 expression by binding to PRE4 elements in the OsWRKY13 promoter region to regulate defense responses in rice³⁰. According to Wang et al., OsFBX148 interacts with OSK4/7/17 to form a SCF complex, which is involved in controlling ROS buildup and ABA signal transduction in plants and enhancing tolerance to abiotic stressors³¹. Based on the above-summarized findings, we postulate that TLP genes regulate detoxifying enzymes operating within a multiphase degradation process, hence contributing to metabolize and detoxify pesticide in rice plants. It’s yet unclear how these genes affect rice pesticide metabolism and detoxification.

In the present study, we examined the transcripts of BNTZ- and anilofos-responsive TLP genes throughout the rice genome to investigate their potential involvement in pesticide metabolism and detoxification. Additionally, we examined these genes' projected subcellular localization, chromosomal locations, structures, motif compositions, cis-acting elements, collinearity, and conserved domains. Using quantitative reverse transcription PCR (qRT-PCR), we confirmed that the expression of 4 and 6 TLP genes varied in response to BNTZ and anilofos exposure, respectively. We also evaluated the TLPs' binding affinities to the two herbicides that are expressed by each of the seven TLP genes. Overall, this study offers a practical screening method to detect TLP genes in rice plants that respond to BNTZ and anilofos exposure. This would enable changes in toxicological reactivity and BNTZ and anilofos resistance in both crops and habitats.

2. Materials & methods

2.1. Preparation of plant materials

Wild rice seeds (Oryza sativa, Nipponbare) were sterilized using 3% H₂O₂ and incubated at 30℃ in darkness for 72 h to induce germination. After germination, the seeds were grown for ten days in a 50% Hoagland nutritional solution. All subsequent treatments were conducted under the following controlled environmental conditions for 6 days: 75% relative humidity, 14 h of sunlight per day (200 μmol/m²/s light intensity, 30℃), and 10 h of darkness per night (25℃). The growth medium was refreshed every 2 days during the 6-day incubation period. For transcriptome library construction and RNA-seq analysis, Ten-day-old rice seedlings were exposed to 0.04 mg/L anilofos (Standard, 93%, BASF, Germany) or 1.8 mg/L BNTZ (Standard, 96%, Richen, China) for 6 days, with three biological replicates per concentration (The results of the preliminary experiments for concentration screening were showed in Figs. S1 and S2). During treatment, root and shoot samples were collected on the 2nd, 4th, and 6th day. All the root and shoot samples collected from these three time points were pooled separately by tissue type and then take the same mass for homogenization for extracting total RNA. For qRT-PCR analysis, different concentrations of anilofos (0, 0.02, 0.04, 0.06, 0.08, and 0.10 mg/L) and BNTZ (0, 0.45, 0.9, 1.35, 1.8, and 2.25 mg/L) were applied to the 10-day-old seedlings for 6 days, with three biological replicates per concentration. Shoot and root tissue samples were collected on the 2nd, 4th, and 6th day after treatment.

2.2. Transcriptome library construction and RNA-seq analysis

Total RNA was isolated using Trizol reagent (Thermo Fisher Scientific, USA) and treated with DNase I (Takara, Shiga, Japan). Subsequently, a total of 24 sequencing libraries were generated, representing three biological replicates for each of the following eight treatment groups: Shoot - anilofos/BNTZ (control without pesticide), Shoot + anilofos/BNTZ (with pesticide treatment), Root - anilofos/BNTZ (control without pesticide), and Root + anilofos/BNTZ (with pesticide treatment). The cDNA libraries (totaling 24 samples, including replicates) were then sequenced using the Illumina HiSeqTM250 platform (Illumina, San Diego, CA, USA). The raw sequencing data were processed and analyzed through the bioinformatic pipeline provided by BMKCloud (https://www.biocloud.net). Following this initial analysis, differential expression analysis was performed using the DESeq2 package (v1.30.1) in R. Genes with an adjusted p-value (False Discovery Rate, FDR) < 0.05 and an absolute log₂ fold change >1 were considered significantly differentially expressed. Clean readings were linked to the rice genome (MSU RGAP Release 7.0) (https://rice.plantbiology.msu.edu/index.shtml) after low-quality nucleotides were eliminated.

2.3. Quantitative RT‑PCR analysis of TLP genes in rice

Total RNA was isolated from the pooled samples using the procedure established by Wang et al¹³. First-strand cDNA was synthesized from the extracted RNA using the ToloScript ALL-in-one RT EasyMix kit for qPCR (Tolo Biotech Co., Ltd.). Quantitative PCR was then performed using this cDNA as template. The reaction was set up with the 2 × Q3 SYBR qPCR Master Mix (Universal) kit (Tolo Biotechnology, Shanghai, China) on a Light Cycler® 96 Real-Time fluorescence quantitative PCR equipment (Roche, Basel, Switzerland). Table S1 lists the primers for TLP genes and the reference gene (OsActin). The thermal cycling conditions were: initial denaturation at 95℃ for 5 min; followed by 40 cycles of 95℃ for 10 s and 60℃ for 30 s. Relative expression of TLP genes was calculated using the − 2^−ΔΔCt method¹³.

2.4. Chromosomal localization, Ka/Ks analysis, and synteny analysis

Ensembl Plants (https://plants.ensembl.org/index.html) provided the whole genome and GFF3 files for rice, maize, sorghum, soybean, and Arabidopsis. The Rice Data Center in China provided the proteins and nucleic acid sequences of TLP genes (https://www.ricedata.cn/gene/). Gene distribution across chromosomes was determined using TBtools-II 2.371 software³². Chromosome localization and visualization were conducted using the relevant functions (Gene Location Visualize from GTF/GFF files) and default parameters in TBtools-II³³. Collinearity analysis was performed among all five species examined (rice, maize, sorghum, soybean, and Arabidopsis) using the One Step MCscanX-Super Fast plugin, and the results were visualized using the Advanced Circos plugin³⁴. Both plugins are integrated features of the TBtools-II. Furthermore, the ratio of nonsynonymous (Ka) to synonymous (Ks) nucleotide substitutions (Ka/Ks) was calculated using TBtools-II³⁵.

2.5. Evolutionary analysis of TLP genes

Arabidopsis, soybean, sorghum, and maize TLP sequences were found using BLAST (https://blast.ncbi.nlm.nihgov/) with a sequence similarity criterion of ≥40%, The Rice Genome Annotation Project (https://rice.uga.edu/) provided the rice TLP sequences, which were then used as query sequences. Then, a phylogenetic tree was constructed using the TLP sequences for all the above-mentioned plant species. Sequence alignment was conducted using the ClustalW algorithm in MEGA12 (Mega Limited, Auckland, New Zealand), followed by phylogenetic analysis using the neighbor-joining method with 1000 bootstrap replications³⁶. The resulting phylogenetic tree was visualized using iTOL 7.3 (https://itol.embl.de/).

2.6. Structural analysis of TLP genes and prediction of conserved motifs

The National Center for Biotechnology Information Conserved Domain Database 3.21 (https://www.ncbi.nlm.nih.gov/Structure/bwrpsb/bwrpsb.cgi) was used to examine the conserved domains of TLP genes. The genes’ exon–intron structures were determined by comparing the coding sequences and the corresponding genomic sequences on the GSDS 2.0 website (https://gsds.gao-lab.org/Gsds_help.php). The corresponding protein sequences were subjected to motif analysis using the MEME 5.5.9 program (https://meme-suite.org/meme/)³⁷. Domain structures and motif distribution were visualized using TBtools-Ⅱ.

2.7. Prediction of cis-acting elements within TLP genes

Using TBtools-II, OsTLP genes in the whole genome and GFF3 files were processed to extract 2000-bp sequences upstream of the transcription start sites. These sequences were then analyzed for predicting cis-acting elements using PlantCARE (http://bioinformatics.psb.ugent.be/webtools/PlantCARE/html). The results were compiled and visualized using TBtools-II³⁸.

2.8. Analysis of protein–protein interaction networks and prediction of subcellular localization OsTLPs

OsTLP sequences were queried in the STRING database (http://stringdb.org/). Proteins with an interaction score ≥0.400 were selected, whereas those with low interaction scores or not associated with stress resistance were excluded. The selected rice proteins were then utilized for generating protein–protein interaction networks, which were visualized using Cytoscape 3.8 (https://cytoscape.org/)³⁹. The TLP sequences were submitted to Plant-mPLoc 2.0 (https://www.csbio.sjtu.edu.cn/bioinf/plant-multi/) to predict their position in the cell⁴⁰. The results were visualized using Adobe Illustrator 2025 (Adobe Systems Incorporated, San Jose, California).

2.9. Molecular docking analysis and calculation of root mean square deviation for ligands

Molecular docking analysis was performed to investigate the potential mechanism through which anilofos and BNTZ molecules bind to OsTLPs. The PubChem database (https://pubchem.ncbi.nlm.nih.gov/) provided the three-dimensional structures of anilofos and BNTZ, while the UniProt database (https://www.uniprot.org/) provided the three-dimensional structures of OsTLPs. File formats were standardized using OpenBabel 2.4.1 (Primary Biotech, ChangZhou, China) before being subjected to docking simulations in Autodock 4.2.6 (Scripps, La Jolla, California) ⁴¹. The outcomes were visualized using Pymol 3.1.6.1 (DeLano Scientific LLC, San Carlos, California) and Discovery Studio 2019 (BIOVIA, San Diego, California).

To test the reliability of molecular docking, we included the root mean square deviation (RMSD) values for comparing the conformation of each ligand after docking with the crystal structure of the original ligand. The protein–ligand complexes and original ligand structures after molecular docking were imported into Pymol 3.1.6.1. Based on the instructions for alignment, the ligands in the complexes were compared with the original ligand structures to obtain the corresponding RMSD values⁴². The average value was calculated to evaluate the quality of molecular docking.

2.10. Statistical analysis

All quantitative experiments were conducted in triplicates. One-way analysis of variance was used to evaluate significant differences at p < 0.05 in statistical analyses conducted in SPSS 19.0 (IBM, Armonk, NY, USA). Data were visualized and mapped using Origin 2024 (OriginLab, Northampton, Massachusetts) and Adobe Illustrator 2025.

3. Results

3.1. Identification of OsTLP genes under BNTZ and anilofos stress

Eight treatment groups (Shoot − BNTZ, Shoot + BNTZ, Shoot − anilofos, Shoot + anilofos, Root − BNTZ, Root + BNTZ, Root − anilofos, and Root + anilofos) were subjected to RNA-Seq in order to determine the possible molecular mechanism underlying TLP’s defense against pesticide-induced phytotoxicity in rice seedlings (Table S2, Table S3). 24 cDNA libraries, each of which had a clean data volume of 5.985 Gb, with a Q30 base percentage exceeding 97.18% of raw data. The GC content of each library from 45.28% to 51.73%. The 24 samples had an average of 42.86 million total reads in each sample (Tables S2 and S3). Among them, a total of seven OsTLP genes were identified (Table S4). Further pairwise tests revealed that 4 (Shoot ± anilofos), 2 (Shoot ± BNTZ), 4 (Root ± anilofos), and 2 (Root ± BNTZ) TLP-encoding genes (false discovery rate < 0.05, |Log2 fold change| > 1) in the shoots and roots of rice displayed increased to varying degrees in expression level (Fig. S3, Table S5 and S6). These results showed that the treatment of BNTZ or anilofos has altered gene expression to varying degrees, which is potentially linked to herbicides stress responses.

3.2. Expression profile of OsTLP genes in rice under BNTZ and anilofos stress

To further investigate the expression of OsTLP genes, qRT-PCR was performed on the subset that showed an upward trend based on transcriptomic data: 4 under BNTZ treatment and 6 under anilofos treatment (Table S5). The expression levels of these OsTLP genes increased significantly under pesticide stress and reached maximum values at 1.8 mg/L BNTZ and 0.04 mg/L anilofos (Fig. 1, Fig. 2). For example, compared with the control, under 1.8 mg/L BNTZ treatment, the expression of the three genes was reached the maximum value: OsTLP1 (3.73-fold in shoots), OsTLP3 (3.55-fold in roots), and OsTLP10 (4.13-fold in roots) (Fig. 1A, B, and D). Similarly, under 0.04 mg/L anilofos treatment, the expression of the three genes was also reached its peak compared to the control (Fig. 2A, D, and F): OsTLP1 (2.74-fold in roots, 2.02-fold in shoots), OsTLP8 (3.48-fold in roots), and OsTLP12 (2.43-fold in shoots). The qRT-PCR expression profiles demonstrate that these genes are important for rice’s response to abiotic stress.

Fig. 1.

Effects of BNTZ induced change in genes expression levels of 4 TLP genes in rice roots and shoots, Ten-day-old rice seedlings were exposed to 0–2.25 mg/L BNTZ for 6 d. Different colors in the figure correspond to different concentrations of the pesticides. The results are the mean values ± SD (n = 3). Different lowercase and uppercase letters indicate a significant difference between each treatment concentration of BNTZ in the roots and shoots, respectively (p < 0.05, ANOVA).

Fig. 2.

Effects of anilofos induced change in genes expression levels of 6 TLP genes in rice roots and shoots, Ten-day-old rice seedlings were exposed to 0–0.10 mg/L anilofos for 6 d. Different colors in the figure correspond to different concentrations of the pesticides. The results are the mean values ± SD (n = 3). Different lowercase and uppercase letters indicate a significant difference between each treatment concentration of anilofos in the roots and shoots, respectively (p < 0.05, ANOVA).

3.3. Distribution of TLP genes on rice chromosomes

Illustrative diagrams were created to elucidate the chromosomal distribution of specific TLP genes within the rice genome. Fig. 3 illustrates the uneven distribution of these genes across five chromosomes. Specifically, OsTLP1 and OsTLP3 are situated on chromosome 1, OsTLP8 and OsTLP10 on chromosome 5, OsTLP7 on chromosome 4, OsTLP12 on chromosome 8, and OsTLP14 on chromosome 12 (Fig. 3). Notably, no TLP genes were identified on the remaining chromosomes (Fig. 3). Such uneven distribution suggests functional disparities among these genes, independent of chromosome length and size.

Fig. 3.

Chromosome distribution of OsTLP genes. The connecting lines represent paralogs. A Scale on the left represents the length of the chromosome in Mb. The thin vertical bars on the right represent the chromosomes of rice, the chromosome number is shown on the left of each chromosome, and the internal color represents the gene density on the chromosome, the bluer the color, the lower the gene density at that position, and the redder the color, the higher the gene density at that position.

3.4. Analysis of gene synteny

To clarify the homology relationship among TLP genes, we compared rice with two monocotyledonous (sorghum and maize) and two dicotyledonous (Arabidopsis and soybean) model plants. Interspecific collinearity analysis revealed 17 pairs of orthologous genes between rice and sorghum, 11 pairs between rice and maize, 7 pairs between rice and soybean, but no orthologous gene pairs between rice and Arabidopsis (Fig. 4, Table S7). Rice shared a significantly higher number of orthologous genes with monocotyledons than with dicotyledons. This indicated that the TLP gene family has a higher degree of collinearity retention within monocotyledonous plants, reflecting it has been conserved throughout evolution in monocotyledonous plants, which are more closely related to rice. On the contrary, due to the greater phylogenetic distance between rice and dicotyledonous plants and the longer independent evolutionary history, there is a higher divergence in the structure of TLP genes, resulting in a significant weakening of collinearity⁴³. The Ka/Ks ratios of gene pairs varied as follows: within rice, 0.083–0.182 (mean = 0.118); between rice and maize, 0.063–0.160 (mean = 0.108); and between rice and sorghum, 0.066–0.144 (mean = 0.108); a single value of 0.050 was measured for the comparison between rice and soybean (Table S8). Thus, these genes appear to be under purifying selection. Collectively, these findings suggest a close evolutionary relationship among the TLP genes of rice, sorghum, and maize, likely due to their shared monocotyledonous Gramineae ancestry.

Fig. 4.

Synteny analysis of OsTLP genes. Synteny analysis of OsTLP genes between rice and soybean (A), maize (B), sorghum (C), and Arabidopsis (D). The colored lines are the syntenic TLP gene pairs for dicotyledon and monocotyledon crop genomes. The central circle represents the syntenic analysis between rice and the four other plant species, with different colors representing each species.

3.5. Phylogenetic analysis of OsTLP genes

To assess the evolutionary relationships between TLP gene families across species, we compared rice with two monocotyledonous (maize and sorghum) and two dicotyledonous (soybean and Arabidopsis) model plants (sequence similarity exceeded 40%; Table S9), and constructed an interspecific phylogenetic tree. The analysis revealed three distinct clades (or branches): I, II, and III comprising the following genes: branch I, 5 genes from rice, 5 from sorghum, 4 from maize, 5 from Arabidopsis, and 8 from soybean; branch II, 2 genes from rice, 2 from maize, 2 from sorghum, 1 from Arabidopsis, and 2 from soybean; and branch III, 3 genes from Arabidopsis and 4 from soybean (Fig. 5). Genes with similar genetic distances within the same branch of the evolutionary tree exhibited homology and functional similarity and may be paralogous or orthologous genes derived from the same ancestor. Specifically, paralogous genes, such as OsTLP1 and OsTLP10, belonged to the same cluster on the tree branches within the same species (rice), (Fig. 5). However, orthologous genes, such as OsTLP8 and SbTLP3, were from different species (rice and sorghum) located close to each other in the branches of the evolutionary tree (Fig. 5). Conversely, genes like OsTLP3 and AtTLP2 were located in different branches, indicating evolutionary differences and distinct functions (Fig. 5). Furthermore, the TLP genes of rice were in the same cluster as those of sorghum and maize on the evolutionary tree, but were at a relatively distant genetic distance from those of soybean and Arabidopsis. This indicated that the TLP genes of rice, sorghum, and maize have closer homology, revealing they are evolutionarily conserved in monocotyledonous gramineous species¹³.

Fig. 5.

Neighbor-joining phylogeny tree of the TLP genes from rice (yellow hexagons), Arabidopsis, soybean, sorghum, and maize. Different subgroups were marked using different colors. Neighbor-joining (NJ) bootstrap percentages (1000 replications) are indicated on the nodes. (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.)

3.6. Structure of OsTLP genes and conserved motifs

Understanding the structure of genes is crucial for elucidating their functions and expression patterns. Structural analysis of the seven OsTLP genes using TBTools-II revealed the presence of typical Tubby domains across all genes, suggesting conservation and functional similarity within the TLP gene family (Fig. S4, Table S10). Specifically, OsTLP1 and OsTLP10 exhibited the F-box_SF and Tubby domains, whereas the other genes displayed F-box_AtTLP-like and Tubby domains (Fig. S4). This pattern is typical of TLPs, where a Tubby domain is located at the C-terminal end, with the majority of the N-terminal region comprising the F-box domain. Furthermore, the analysis of exon–intron structures indicated that all 7 TLP genes have a conserved structure composed of 4 coding sequences, untranslated regions (UTRs) of different lengths, and 3–5 introns (Fig. S4). Additionally, to better understand gene structure and evolutionary diversity, we examined 6 conserved motifs within the 7 TLP genes (Fig. S5). The presence of these six motifs in all 7 genes underscores their fundamental importance in the core functions and structures of the TLP gene family. Overall, the above results indicate that these genes have a high degree of structural conservation, and their structure is very likely to have been maintained under intense evolutionary pressure ⁴⁴.

3.7. Analysis of cis-acting elements within TLP genes

Cis-acting elements are essential for gene expression. Here, we analyzed the promoter regions of TLP genes spanning 2,000 base pairs upstream of the transcription start site using PlantCARE and TBtools to pinpoint cis-acting elements associated with plant stress resistance. A total of 27 distinct cis-acting elements were identified (Fig. 6, Table S11) and classified into three primary categories: 1) elements linked to plant hormones (e.g., those responsive to auxin, gibberellin, abscisic acid, and salicylic acid); 2) elements associated with environmental factors (e.g., those responsive to low temperatures and light as well as those related to anaerobic induction); and 3) elements related to MYB binding sites activated in response to drought and light as well as the MYBHv1 binding site, among others. The TLP gene family contains cis-elements of hormone- and stress-responsive, indicating it plays a significant role in regulating plant growth and development and resisting abiotic stress²⁶.

Fig. 6.

Analysis of cis-acting elements in the promoter regions of the TLPs family. Different cis-acting elements are displayed in different colors. The number of small rectangles of the same color represents the quantity of the corresponding gene containing this element.

3.8. Analysis of a protein–protein interaction network regulated by OsTLP genes

To elucidate the regulatory pathways and functional modules associated with OsTLP genes as well as the underlying molecular mechanisms in specific biological processes, we established a TLP-related protein–protein interaction network utilizing data from the STRING database (Fig. 7, Table S12, and Table S13). Analysis unveiled a robust association among the seven TLPs and ARF1, ARF6, ARF25, and TPC1 (Fig. 7). ARFs are transcription factors that bind to the 5′-TGTCTC-3′ DNA motif within auxin-responsive promoter elements (AuxREs) and have been shown to regulate the transcription of auxin-responsive genes by directly interacting with their promoters⁴⁵. Therefore, the significant correlation observed between TLPs and ARFs suggests the involvement of TLPs in auxin-mediated transcriptional regulation. TPC1 is a calcium ion channel located on the vacuole membrane that participates in calcium signal transduction, responds to environmental and hormonal cues, and is involved in rapid auxin signaling as a response to stress⁴⁶. Therefore, it is speculated that, in rice, the calcium signal mediated by TPC1 drives the TLPs to participate in auxin-mediated transcriptional regulation, impacting plant growth and development as well as their ability to withstand abiotic stress. Notably, the presence of TLP4 and TLP6 within the interaction network underscores the collaborative nature of TLPs, indicating that TLPs do not operate in isolation but through interaction with other TLP members.

Fig. 7.

Protein interactions network diagram of OsTLP genes in rice. The minimum required interaction score was set to 0.400. The size of the nodes and the shade of their color represent the magnitude of the degree value.

3.9. Subcellular mapping of TLPs

Subcellular localization experiments are essential for investigating how the protein–protein interaction network is regulated by the TLPs. In this study, the subcellular locations of the seven TLPs examined were predicted using Plant-mPLoc. The results indicated that all TLPs are located in the cell nucleus (Fig. S6). Based on the analysis of the protein–protein interaction network, TLPs are hypothesized to be involved in the transcription of ARFs regulating auxin-responsive genes, with ARFs binding to the gene promoter within the cell nucleus⁴⁷. This hypothesis is supported by our predictions of subcellular localization.

3.10. Molecular docking analysis

Molecular docking analysis predicted the binding potential of 4 OsTLPs with BNTZ and 6 OsTLPs with anilofos (Fig. S7, Fig. 8). The predicted physicochemical properties and three-dimensional structures of OsTLPs are presented in Fig. S8, Table S14 and S15. Notably, the predicted binding affinity varied substantially among different OsTLP-herbicide complexes. For BNTZ, OsTLP7 showed the strongest affinity (−5.34 kcal/mol), while OsTLP3 had the weakest (−2.84 kcal/mol). Conversely, for anilofos, OsTLP10 exhibited the strongest binding (−3.08 kcal/mol), and OsTLP7 the weakest (−1.16 kcal/mol). This suggests differential ligand preference among OsTLP family members. Despite this variation, common interaction patterns emerged: hydrophobic interactions (e.g., Pi-alkyl and alkyl) were prevalent across most complexes for both herbicides, indicating their importance in the binding interface. A complete summary of interaction types, residue counts, and binding energies for each OsTLP-herbicide pair is provided in Supplementary Table S16.

Fig. 8.

The receptor–ligand interaction of pesticides with the TLPs active site. Molecular docking of anilofos with OsTLP1 (A); molecular docking of anilofos with OsTLP3 (B); molecular docking of anilofos with OsTLP7 (C); molecular docking of anilofos with OsTLP8 (D); molecular docking of anilofos with OsTLP10 (E); molecular docking of anilofos with OsTLP12 (F).

3.11. Ligand RMSD analysis

The accuracy of molecular docking analyses can be reliably assessed by quantitatively predicting the geometric deviation between the conformation and the original crystal structure of BNTZ and anilofos⁴⁸. In this study, RMSD calculations revealed the following values for the docking of the four TLPs examined with BNTZ ligands ranged from 2.31 to 2.66 Å (average of 2.48 Å) (Table S16). For the docking of TLPs with anilofos ligands, the RMSD values ranged from 1.5 to 2.66 Å (average of 1.98 Å) (Table S16). The average RMSD value for the docking with anilofos (1.98 Å) was lower than that for the docking with BNTZ (2.48 Å). Considering that generally an RMSD value ≤2 Å is considered an accurate and good docking result, the above averages indicate a more accurate result for TLP–anilofos docking than for TLP–BNTZ docking, reflecting a higher degree of stability in the predicted binding pose for the anilofos ligand compared to the BNTZ ligand.

4. Discussion

TLP genes have been found in numerous plant species, including Arabidopsis thaliana, Glycine max, Zea mays, Sorghum bicolor, and Oryza sativa, and have been demonstrated to be essential to a variety of biological functions. The identification of TLP genes in these species has been greatly aided by the quick developments in whole-genome analysis and sequencing technologies[49], [50], [51]. Numerous research have attempted to understand how TLP genes respond to abiotic stresses such as salt, drought, and cold temperatures[49], [50]. Nevertheless, the function of this gene family in rice exposed to pesticides has not been well studied. In this study, we used bioinformatics techniques to systematically investigate how TLP genes in rice (O. sativa; thus referred to as OsTLP genes) respond to pesticide treatment. Transcriptomic screening initially identified 4 and 6 OsTLP genes with upward expression trends under BNTZ and anilofos treatments, respectively (Fig. S3, Table S5). Subsequent qRT-PCR validation confirmed this upward trend and revealed variations in response magnitude among these family members (Fig. 1, Fig. 2). Together, these results demonstrate that a subset of OsTLP genes is transcriptionally activated by herbicides stress. Thus, these genes are likely involved in rice’s adaptive transcriptional response to pesticides exposure. We detailed the conserved domains, chromosomal locations, cis-acting elements, gene structure, motif compositions, transcriptional expression patterns, and subcellular localization in addition to carrying out phylogenetic and collinearity analyses of the seven OsTLP genes discovered. The related proteins were also subjected to molecular docking experiments and protein–protein interaction analysis. Previous studies have demonstrated that gene duplication is essential for genome evolution and the expansion of gene families, with both tandem and segmental duplications contributing to gene family diversification⁵². These duplication events enable plants to rapidly respond to environmental stresses¹³. The seven OsTLP genes were shown to be involved in segmental duplication events in this investigation, indicating that segmental duplication has significantly influenced the development of OsTLP genes and their capacity for stress adaptation. Moreover, selective pressure analysis of duplicated OsTLP gene pairs revealed Ka/Ks ratios consistently below 1, which is indicative of strong purifying selection. This suggests a significantly lower rate of nonsynonymous (Ka) substitutions compared to synonymous (Ks) substitutions, implying substantial evolutionary conservation of OsTLP sequences due to the preferential fixation of synonymous mutations. Furthermore, we discovered robust evolutionary connections between rice and maize TLP gene pairs (OsTLP8-Zm00001eb146720 and OsTLP8-Zm00001eb289070) as well as from rice and sorghum (OsTLP7-SORBI_3008G047400). These relationships were further confirmed through interspecies collinearity analysis for rice vs. maize and rice vs. sorghum (Fig. 4). According to our findings, there aren't many parallels between the TLP genes in rice and those in Arabidopsis and soybeans (Fig. 4). Furthermore, we found that rice shared no orthologous gene pairs with Arabidopsis, but shared 7, 11, and 17 pairs with soybean, maize, and sorghum, respectively. These conclusions were further corroborated by phylogenetic analysis of the aforementioned plant species, which revealed shared motifs, functional domains, and gene architectures among TLP genes belonging to the same evolutionary grouping, emphasizing their evolutionary connections.

The evolutionary relationships between TLP genes from rice and those of Arabidopsis, sorghum, soybean, and maize were subsequently elucidated by constructing a phylogenetic tree (Fig. 5, Table S9). Three distinct clades (or groups) were identified based on 43 TLP genes from these five plant species, which were grouped as follows: 27 genes in group I, 9 genes in group II, and 7 genes in group III. According to earlier research on TLP genes in rice, Arabidopsis, sorghum, soybean, and maize, this gene family has a conserved structure, function, and evolutionary trajectory and is essential for both monocot and dicot plants' stress responses[26], [53]. Furthermore, TLPs often have crucial conserved domains and motifs, highlighting their importance in regulatory activities[54], [55]. In this investigation, all six motifs associated with the TLP domain were found to be conserved and were present in all seven OsTLP genes, revealing how highly conserved this domain is across the rice genome. Additionally, previous research has shown high levels of domain conservation in other plant species as well[54], [55], [56]. Interestingly, in this study, six motifs beyond the TLP domain region were shared by TLPs in the same cohort. It is assumed that these motifs are associated with signal transduction, transcriptional control, cell cycle transition, or other functional activities [54], [55], [56]. The conservation of these amino acid residues in the TLP domain indicates the crucial roles that TLP genes play in a variety of regulatory activities. The F-box and Tubby domains were found in some TLP genes (Fig. S4, Table S10), which have been shown to be essential for plant adaptation and function[57], [58]. TLP genes have a well-established function in reducing abiotic stress[54], [55], [56]. These genes are characterized by a conserved TLP domain with 256–341 amino acid residues and are tightly linked to the development, growth, and stress reactions of plants[54], [55], [56]. It is possible that the preserved TLP domain helps rice to metabolize and detoxify pesticide in light of the aforementioned findings.

Cis-acting elements are crucial for regulating gene expression in plants, which in turn affects how TLPs respond to environmental stimuli under stress⁵⁹. Among the cis-acting elements found in rice in the seven OsTLP genes examined in the present study, light-responsive elements (LREs) showed the highest level of sequence variation (Fig. 6). It was discovered that all seven OsTLP genes, which were found upstream of the widely distributed rice LREs, appeared several times. Due to their high frequency and extensive distribution, LREs may affect plant responses by serving as crucial points for light signals to orchestrate the homeostasis of phytohormones such as IAA, GA, ABA, MeJA, and SA[60], [61]. This would increase tolerance to a number of abiotic stimuli, including as exposure to pesticides, salt, drought, and cold temperatures[8], [62]. According to Li et al., ABA boosts resilience to abiotic stress in rice⁶³, whereas Lin et al. maintained that SA and MeJA are necessary for metabolism and detoxification of pesticide in plants⁶⁴. According to Kumar et al.’s report, SA increases the breakdown of glyphosate, isoproturon, and fomesafen, reducing their phytotoxic effects on plants⁶⁵. We have demonstrated that under mesotrione and fomesafen stress, the cis-acting element controlling acetyltransferase reacts to ABA and GA⁶⁶, which confirms that it promotes mesotrione and fomesafen degradation and metabolism in rice plants⁶⁷. These results suggest that OsTLP genes are likely involved in responses to a variety of biotic and abiotic stressors, including BNTZ and anilofos treatment.

By comparing the sequences and expression patterns of these genes in model plants, we should be able to get further insight into the role of TLP genes in rice. ARFs, transcription factors that bind to the DNA motif 5′-TGTCTC-3′ in AuxREs, control the transcription of auxin-responsive genes by interacting directly with their promoters⁴⁵. Moreover, TPC1, a calcium ion channel situated on the vacuole membrane, is crucial for calcium signal transduction in response to various environmental and hormonal stimuli, including in rapid auxin signaling⁴⁶. All seven OsTLP genes examined interacted with ARFs and TPC1. It is speculated that the calcium signaling via TPC1 drives the OsTLP gene family to participate in auxin-mediated transcriptional regulation. Specifically, when rice responds to environmental stress or hormone signals, TPC1 is activated on the vacuole membrane, mediating specific calcium signal transients within the cytoplasm. The second messenger signal is very likely to be transmitted through the nuclear membrane into the nucleus, activating the TLP function. The activated OsTLPs in the nucleus directly interact with ARFs, which are also located in the nucleus, to regulate the transcription of downstream auxin-responsive genes⁶⁸. This process in turn regulates rice growth and development as well as tolerance to abiotic stress. In plants, the subcellular location of particular proteins is essential for controlling a number of biological processes[69], [70]. Our findings indicate that TLPs are predominantly localized in the nucleus, indicating their significant role in stress tolerance and in the regulation of cell functions. For plants to adapt to a variety of abiotic challenges, such as drought, salinity, and pesticide exposure, the nucleus, which controls gene expression, is essential²⁷. Signal transmission, environmental sensing, gene expression regulation, and other crucial nuclear functions required for cellular activity are most likely mediated by the TLPs present in the nucleus.

To understand the molecular role of OsTLP in pesticide metabolism and degradation, more information about the interactions between pesticides and their receptor ligands is needed. According to Qiao et al, the likelihood that a detoxifying enzyme will play a role in the pesticide’s detoxification process increases with the strength of the bond between the pesticide molecule and the target protein⁷¹. In this work, we discovered that some of the proteins produced by the OsTLP genes, particularly OsTLP7, have a notable ability to establish hydrogen bonds with BNTZ and anilofos (Fig. 8, Fig. S7). This discovery could be crucial to comprehending how members of the TLP gene family contribute to the metabolism of pesticides. Furthermore, the calculated RMSD values of ligands revealed a lower flexibility of the active binding residues of TLP–anilofos docking compared with TLP–BNTZ docking as well as a more stable main chain conformation (see lower average RMSD value in Table S16). This analysis indicated a higher stability of TLP–anilofos docking and enhanced rigidity of the bound residues. Owing to the presence of multiple hydrogen bond acceptors (S, O, and Cl atoms) in the structure of anilofos, its binding residues form strong hydrogen bonds with TLPs. In contrast, the binding residues of BNTZ are more flexible and show higher affinity with TLPs. Clarifying the functions of the TLP gene family in metabolism of pesticide in plants requires this discovery, which provides the structural basis for their differential interactions with pesticides.

To offer a thorough characterization of the TLP gene family in rice, this study used a variety of bioinformatics techniques, such as phylogenetic analysis, chromosomal mapping, subcellular localization, collinearity analysis, motif composition analysis, and cis-acting element prediction. Transcriptome analysis was used to identify seven OsTLP genes that are responsive to BNTZ and anilofos stress. qRT-PCR and molecular docking studies were then used to confirm the expression of these genes and investigate their binding affinities with BNTZ and anilofos. However, without functional validation, the regulatory or functional complexity of OsTLP genes in pesticide metabolism may not be fully reflected in these bioinformatics and expression study findings. Overexpression and mutation studies can be used to further explore the molecular mechanisms via which these OsTLP genes regulate the detoxification and metabolism of BNTZ and anilofos in rice.

5. Conclusion

This study thoroughly examined the TLP gene family in rice, identifying seven genes (OsTLP) that react to BNTZ- and anilofos-induced stress, whose encoded proteins are primarily localized in the nucleus. Additionally, OsTLP genes may be essential for the plant’s reaction to BNTZ and anilofos stress, according to qRT-PCR findings. OsTLP genes are spread across five chromosomes in the three clades, according to classification, chromosomal distribution, and collinearity analysis. Of these, 28 and 7 genes show collinearity with maize and sorghum, respectively, and with soybean and Arabidopsis. The nonsynonymous Ka/Ks ratios of all collinear pairs were less than 1, suggesting that strong purifying selection occurred during their evolution. Three different clades were established based on the structural and functional characteristics of these genes. It was demonstrated that the majority of OsTLP genes had unique domains or motifs that interact with various substrates to adapt to a range of environmental situations. Several cis-acting elements were found in the upstream promoter regions of these genes, indicating a link between the transcriptional and translational activation of OsTLP genes and the plant stress response to BNTZ and anilofos. According to molecular docking analysis and RMSD values, BNTZ and anilofos bind to OsTLPs through a variety of amino acid residues with a minimum binding energy of −5.34 and −3.08 kcal/mol, respectively. Overall, these findings provide new insights into the physiological and molecular mechanisms underlying the function of OsTLP genes and open up new avenues for research into their role in the regulation of pesticide metabolism (BNTZ and anilofos in particular) and detoxification in rice plants.

CRediT authorship contribution statement

Zhi Jiang He: Writing – original draft, Visualization, Software, Methodology, Investigation, Formal analysis, Data curation. Yang Yang Mo: Validation, Software, Data curation. Xiao Lu Wang: Validation, Methodology, Formal analysis, Data curation. Zhi Zhong Zhou: Visualization, Validation, Formal analysis, Data curation. Yan Hui Wang: Validation, Resources, Investigation. Li Qing Zeng: Visualization, Validation, Data curation. Ying Yu Zeng: Validation, Data curation. Xiao Liang Liu: Validation, Data curation. Xuesheng Li: Writing – review & editing, Resources, Project administration. Zhao Jie Chen: Writing – review & editing, Writing – original draft, Supervision, Resources, Project administration, Funding acquisition, Conceptualization.

Informed consent

Not applicable.

Ethics approval

Not applicable.

Funding

This project supported by the National Natural Science Foundation of China (No. 32402414).

Declaration of competing interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Appendix A. Supplementary data

The following are the Supplementary data to this article:

Data availability

Plant genome data used in this study is available through the Ensemble Plants Database (https://plants.ensembl.org/index.html), with Taxonomy IDs for rice (39947), Arabidopsis (3702), soybean (3847), maize (4577), and sorghum (4558). The raw RNA-Seq data in this manuscript are available for downloading from the BIG Sub (https://ngdc.cncb.ac.cn/gsub/) (BioProject ID: PRJCA053977). All data generated or analyzed during this study are included in this published article (and its Supplementary Information Files).