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Article

Uncovering Key Transcription Factors Driving Chilling Stress Tolerance in Rice Germination

by
Vívian Ebeling Viana
1,*,
Camila Pegoraro
2,
Viviane Kopp da Luz
2,
Antonio Costa de Oliveira
2 and
Luciano Carlos da Maia
2
1
Department of Crop Protection, Federal University of Pelotas, Pelotas 96160-000, Brazil
2
Department of Plant Breeding, Federal University of Pelotas, Pelotas 96160-000, Brazil
*
Author to whom correspondence should be addressed.
DNA 2024, 4(4), 582-598; https://doi.org/10.3390/dna4040038
Submission received: 19 September 2024 / Revised: 15 November 2024 / Accepted: 12 December 2024 / Published: 16 December 2024
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Abstract

:
Background: Rice, one of the main foods in Brazil and the world, is sensitive to chilling (0–15 °C), especially in the germination and reproductive stages. Chilling causes delayed germination and affects coleoptile elongation at the S3 stage (needlepoint), causing poor plant establishment, stunted growth, and non-vigorous plants, also impacting weed management. Elucidating the mechanisms responsible for resilience under cold conditions helps the development of tolerant cultivars. Transcription factors (TFs) act in stress response signaling, making them indispensable in the tolerance mechanism. Objective: Thus, this study aimed to identify and characterize the expression profile of transcription factors in the response to chilling stress in rice at the germination stage. Methods: To determine the transcriptional profile of 2408 genes belonging to 56 TF families, RNAseq was performed on the shoot tissue of seedlings of Oro (chilling-tolerant) and Tio Taka (chilling-sensitive) genotypes grown under control conditions (25 °C) and chilling stress (13 °C) until the S3 stage. Results: Of the total genes analyzed, 22% showed significant differential expression in the analyzed cultivars. There were 117 genes that showed significant differential expression in the tolerant cultivar, 60 of which were downregulated and 57 upregulated. In the sensitive cultivar, 248 genes had a significant differential expression, of which 98 genes were downregulated and 150 genes were upregulated. A total of 170 genes encoding TFs were commonly and significantly differentially expressed in the tolerant and sensitive genotypes. Conclusions: Here, we revealed potential new targets involved in the regulation of chilling stress in rice at the S3 stage.

1. Introduction

Rice (Oryza sativa L.) is part of the lives of millions of farmers and, as a nutritious crop, it is the food base for more than a billion people [1]. The rice plant is susceptible to extreme temperatures and, therefore, to cold or heat stress. Cold stress is caused by low temperatures and is classified as chilling (0–15 °C) and freezing (<0 °C). Chilling stress affects rice cultivation in different countries, including Japan, China, Korea, India, Australia, and Brazil, causing losses in yield and grain quality [2,3,4].
In general, cultivars of the japonica subspecies are more tolerant and predominant in temperate regions. In contrast, cultivars of the indica subspecies are more sensitive and grow in tropical and subtropical regions [5]. In Rio Grande do Sul, a southern state of Brazil and the main rice-producing state in the country (responsible for 70% of the rice production), the cultivation of cultivars of the indica subspecies predominates in a flooded cultivation system [6]. In this region, the climate is subtropical, and chilling stress can occur in the germination and reproductive stages [6,7]. Specifically, in the Rio Grande do Sul, chilling stress mainly affects rice germination during the S3 stage (seedling 3, commonly known as needlepoint). Chilling causes delayed germination, especially affecting coleoptile elongation at the S3 stage, leading to poor plant establishment, stunted growth, and non-vigorous plants. The needlepoint is also important for weed management in rice crop, since early seeding helps the application of nonselective herbicides. Early weed control and early irrigation are strategies used to reduce weed impact in flooded rice areas [8]. In the reproductive stage, chilling stress causes delayed flowering, spikelet sterility, and reduced grain filling [9,10].
Cold tolerance is a complex trait, involving the participation of many genes. The identification of these genes makes it possible to elucidate the mechanisms responsible for resilience under cold conditions and helps in the development of tolerant cultivars. To achieve this, it is necessary to understand the different stages of signal perception and transduction in response to cold, including the activation of transcription factors (TFs) and the expression of cold-responsive (COR) genes. TFs regulate gene expression by binding to sequences present in target gene promoters. The involvement of different families of TFs, including NAC, WRKY, AP2/EREBP, bHLH, ERF, bZIP, MYB, C2H2, and GRAS, in cold tolerance in rice has been reported [11,12].
The identification of TFs induced by chilling may help in the understanding and manipulation of genes involved in tolerance to this stress. Therefore, the objective of this study was to identify and characterize the expression profile of transcription factors in the response to chilling stress in rice at the germination stage, since it is the main rice stage affected by chilling stress in Rio Grande do Sul state.

2. Materials and Methods

2.1. Plant Material and Growth Conditions

To search for the differentially expressed genes (DEGs) for TFs, we studied two contrasting genotypes related to their performance under chilling stress. The genotypes Oro (japonica rice) and Tio Taka (indica rice) were used as tolerant and sensitive to chilling stress, respectively, since they were previously characterized in response to chilling stress at the germination phase under field conditions [13]. At chilling stress, the Oro genotype performed better than Tio Taka in terms of their germination index, shoot, and radicle length [11,13].

2.2. RNA-Seq and Data Processing

The seeds of the Oro and Tio Taka genotypes were germinated in a growth chamber under control conditions (25 °C) and chilling stress (13 °C) until reaching the S3 stage (needlepoint, when the prophyll of the coleoptile emerges). For each treatment and each genotype, three biological replicates with 50 seeds each were used in a randomized block design [13]. When the plants reached the S3 stage, the shoots of both treatments and genotypes were collected individually, fixed in nitrogen, and stored at −80 °C until RNA extraction.
For total RNA isolation, the Plant RNA Reagent Purelink (Invitrogen) was used, according to the manufacturer’s recommendations. RNA quality and quantity were measured using a NanoDrop ND-1000 equipment (GE Healthcare, Wilmington, DE, USA) and the integrity was measured using agarose gel electrophoresis [13]. The libraries were prepared using the TruSeq RNA Sample Preparation V 2 kit (Illumina, San Diego, CA, USA), following the manufacturer’s instructions. The quality of libraries was evaluated through Agilent 2100 BioAnalyser (Agilent Technologies, Santa Clara, CA, USA) using the kit Agilent DNA 1000 (Agilent, Santa Clara, CA, USA). Library sequencing was performed as paired-end 2100 bp on the platform HiSEqn 2500 (Illumina, San Diego, CA, USA) [13].
For the analysis and visualization of read quality, the software FastQC v0.12.1 was used, and low-quality bases and library adaptors were removed from each library using Trimmomatic ver. 0.32. Reads were mapped against the reference genome of Oryza sativa L. japonica cv. Nipponbare (IRGSP build 1.0-RAP-DB). In the first phase, TopHat ver. 2.0.11 and Bowtie ver. 0.12.7 software packages were used for the mapping of reads on the pseudomolecules of the rice genome (available at http://rapdb.dna.affrc.go.jp/index.html, accessed on 1 February 2016). Later, the Cufflinks ver. 2.1.1 software was used in the transcript assembly and Cuffdiff ver. 2.1.1 was used to estimate the differential expression of each locus. For both packages, default parameters were used, as indicated in other reports [13,14,15].
For differential gene expression, a multidimensional scaling (MDS) graph was obtained in R ver. 3.1.0 (R Development Core Team, Vienna, Austria) and the package classic edgeR ver. 3.2.4, according to the parameters indicated by Anders et al. [16]. Only transcripts with FPKM (Fragments Per Kilobase Of Exon Per Million Fragments Mapped) values ≥1, Log2FC –1 or +1 were considered using cummRbund software [14].
The expression data of each genotype were normalized using the baseline control condition, resulting in the following two sets of data: genes differentially expressed in Oro and genes differentially expressed in Tio Taka. They were considered differentially expressed genes if the significance value equaled p ≤ 0.05.

2.3. Searching for TFs

We searched for the analyzed TFs using rice Oryza sativa L. japonica in the Plant Transcription Factor Database v5.0 (https://planttfdb.gao-lab.org/, accessed on 4 September 2024) [17]. We used all the available TFs for searching their corresponding gene in The Rice Annotation Project Database (RAP-DB) (https://rapdb.dna.affrc.go.jp/index.html, accessed on 5 September 2024) using the ID conversion tool to convert the MSU ID to RAP ID. The RAP ID was used to search for DEGs in our transcript datasets. The gene ID, as well as the gene symbol of the genes used here, were retrieved from RAP-DB (https://rapdb.dna.affrc.go.jp/index.html, accessed on 8 September 2024).
From the two RNAseq datasets, it was possible to obtain the following four sets of TF-encoding genes: (1) DEGs in the tolerant cultivar (Supplementary Table S1); (2) DEGs in the sensitive cultivar (Supplementary Table S2); (3) DEGs in both cultivars (Supplementary Table S3); and (4) DEGs in both cultivars that were not significant (Supplementary Table S4).
Volcano plots were designed using the Galaxy software ver. 24.1.4 (https://usegalaxy.org/, accessed on 8 September 2024) [18], following the tutorial of Hiltemann et al. [19]. Heatmaps were designed using The Multiple Experiment Viewer (TM4 MeV) ver. 4.9.0 [20]. For network analysis, upregulated genes were submitted to the Search Tool for the Retrieval of Interacting Genes (STRING) database version 12.0 [21], using Oryza sativa japonica as the input organism, with a minimum required interaction score of 0.400 and network edges representing evidence of an interaction. Clustering was performed using k-means.

3. Results

By comparing samples of the same rice cultivar in different conditions (control and chilling) we constructed two comparison groups: tolerant (Oro cultivar) and sensitive (Tio Taka cultivar). Thus, it was possible to obtain four sets of TF-encoding genes: (1) significant DEGs in the tolerant cultivar; (2) significant DEGs in the sensitive cultivar; (3) significant DEGs in both cultivars; and (4) non-significant DEGs in both cultivars.
To uncover the key transcription factors potentially involved in chilling tolerance, we searched all TF families available in the Plant Transcription Factor Database platform known to be present in the rice (Oryza sativa L. japonica) genome. A total of 2408 genes coding for TFs from 56 families were identified (Table 1). The tolerant cultivar presented a fewer number of TF-encoding DEGs with significant expression than the sensitive cultivar. Of the total genes analyzed, 22% showed significant differential expression in the studied cultivars.
The volcano plot shows all genes expressed in the tolerant and sensitive cultivars, considering genes with significant and non-significant differential expression (Figure 1). The total number of TF-encoding DEGs was 675 in both cultivars, of which 140 were not significant for any of the cultivars; another 115 genes were non-significant only in the tolerant cultivar (Figure 1A) and another 114 genes were non-significant only in the sensitive cultivar (Figure 1B).

3.1. Differentially Expressed Genes in Chilling-Tolerant Genotype

A total of 117 genes showed significant differential expression in the tolerant cultivar, 60 of which were downregulated and 57 upregulated (Table 1 and Figure 2A). Of the 56 families analyzed, the following 36 presented TF-encoding genes with significant differential expression: AP2 (two genes), ARF (one gene), ARR-B (one gene), B3 (two genes), bHLH (eight genes), bZIP (eleven genes), C2H2 (six genes), C3H (two genes), CO-like (four genes), DBB (two genes), Dof (three genes), E2F/DF (one gene), ERF (thirteen genes), GRAS (two genes), HD-ZIP (two genes), HSF (three genes), LBD (one gene), LSD (one gene), MIKC_MADS (two genes), MYB (fifteen genes), MYB_related (five genes), NAC (five genes), NF-YA (one gene), NF-YB (one gene), Nin-like (one gene), RAV (one gene), S1Fa-like (one gene), SBP (two genes), TALE (three genes), TCP (three genes), Trihelix (three genes), Whirly (one gene), WRKY (seven genes), and ZF-HD (one gene) (Figure 2).
The gene network of these upregulated DEGs shows three clusters that are highly interconnected. Cluster I comprises MYB (OsMYB2–Os03g0315400) and C2H2 (OsZFP15–Os03g0820400) transcription factors. Cluster II, the biggest cluster, represents MYB (OsMYB30–Os02g0624300), C2H2 (OsZFP15–Os03g0437200), ERF (OsERF68–Os01g0313300), WRKY (OsWRKY24–Os01g0826400 and OsWRKY53–Os05g0343400), MYB (OsMYB4/MYB55–Os04g0517100), and C3H (C3H33–Os05g0128200). Cluster III contains Trihelix (Os04g0543500) and NAC (OsNAC37–Os08g0157900) transcription factors (Figure 2B).
Among the 10 most upregulated genes in the tolerant cultivar are the families MYB (three genes), C2H2 (three genes), ERF (two genes), NAC (one gene), and WRKY (one gene) (Table 2). On the other hand, among the 10 most downregulated genes in the tolerant cultivar are the families MYB (three genes), MYB_related (one gene), bHLH (two genes), ZF-HD (one gene), MIKC_MADS (one gene), ERF (one gene), and WRKY (one gene) (Table 2). Some of the clustered upregulated genes are among these 10 most upregulated genes.

3.2. Differentially Expressed Genes in Chilling Sensitive Genotype

In the sensitive cultivar, 248 genes had a significant differential expression, of which 98 genes were downregulated and 150 genes were upregulated (Table 1 and Figure 3A). Of the 56 families analyzed, the following 44 presented genes coding for TFs with significant differential expression: AP2 (three genes), ARF (four genes), B3 (five genes), BES1 (one gene), bHLH (twenty-three genes), bZIP (seventeen genes), C2H2 (twelve genes), C3H (eight genes), CAMTA (four genes), CO-like (one gene), CPP (two genes), DBB (two genes), Dof (six genes), E2F/DP (two genes), EIL (one gene), ERF (eleven genes), FAR1 (six genes), G2-like (eight genes), GATA (five genes), GRAS (eight genes), GRF (two genes), HB-other (one gene), HD-ZIP (eleven genes), HRT-like (one gene), HSF (six genes), LSD (four genes), MIKC_MADS (six genes), M-type_MADS (one gene), MYB (eighteen genes), MYB_related (ten genes), NAC (twenty genes), NF-YA (two genes), NF-YB (one gene), NF-YC (two genes), SBP (three genes), SRS (one gene), STAT (one gene), TCP (two genes), Trihelix (two genes), VOZ (one gene), WOX (one gene),WRKY (thirteen genes), YABBY (three genes), and ZF-HD (seven genes) (Figure 3).
The upregulated DEGs were clustered into nine groups that are highly interconnected (Figure 3B). Cluster I, the biggest with 20 genes form different TF families, comprise C2H2 (OsIDD2–Os01g0195000, OsZFP179–Os01g0839100, OsJMJ705–Os01g0907400, OsIDD14–Os03g0237250, Os05g0106000, and OsDLN212–Os08g0504000), bHLH (OsbHLH037–Os01g0218100, OsbHLH024–Os01g0575200, OsbHLH034–Os02g0726700, and OsbHLH032–Os09g0475400), bZIP (bZIP20–Os02g0266800 and OsbZIP48–Os06g0601500), DBB (OsBBX4–Os02g0606200 and OsBBX11–Os04g0493000), G2-like (OsDLN85–Os03g0325500, OsPHR1–Os03g0329900, OsPHR2–Os07g0438800, and OsMYBc–Os09g0299200), FAR1 (Os06g0166100), and ERF (ERF7–Os06g0166400). Cluster II is formed by NAC (NAC45–Os11g0127600 and NAC77–Os12g0123800), CPP (OsCPP5–Os05g0509400 and Os02g0274600), and E2F/DP (OsE2Fa-3–Os04g0416100). Cluster III comprise TFs from the WRKY family (OsWRKY77–Os01g0584900, OsWRKY10–Os01g0186000, OsWRKY97–Os12g0116400, and OsWRKY46–Os11g0116900) that show gene co-occurrence. Two-member clusters include Cluster IV, with B3 (Os03g0620400) and CO-like (OsCO3–Os09g0240200), Cluster V with B3 (OsDLN186–Os07g0563300 and Os10g0323000), Cluster VI with NAC (OsNAC121–Os10g0571600 and NAC103–Os07g0683200), Cluster VII with C3H (OsC3H67–Os12g0515500) and AP2 (AP2/EREBP43–Os04g0649100), Cluster VIII, with genes reported as involved in floral organ identity, namely MIKC_MADS (OsMADS2–Os01g0883100) and YABBY (Os03g0215200), and Cluster IX, with genes related to ethylene signaling, namely EIL (OsEIL4–Os08g0508700) and ERF (ERF92–Os01g0752500).
Among the 10 most upregulated TF-encoding genes in the sensitive cultivar are the following families: NAC (six genes), MYB (one gene), MYB_related (one gene), WRKY (one gene), and B3 (one gene) (Table 2). On the other hand, the 10 most downregulated TF-encoding genes in the sensitive cultivar were from the following families: bHLH (three genes), ERF (two genes), WRKY (one gene), bZIP (one gene), MYB (one gene), GRAS (one gene), and MIKC_MADS (one gene).

3.3. Common Genes Differentially Expressed in Chilling-Tolerant and -Sensitive Genotypes

In the chilling-tolerant and -sensitive genotypes, 170 TF-encoding genes were commonly and significantly DEGs (Table 1 and Figure 4). Among the genes with contrasting transcriptional profiles between genotypes, which were upregulated in the chilling-tolerant and downregulated in the chilling-sensitive genotypes, we identified genes from the family WRKY (OsWRKY21–Os01g0821600, OsWRKY62–Os09g0417800, and OsWRKY71–Os02g0181300), Trihelix (OsGTγ-1–Os02g0542400), TALE (Os02g0226600), LBD (OsLBD1-8–Os01g0825000), ERF (OsDREB1B–Os09g0522000, OsDREB1A–Os09g0522200, OsERF74–Os05g0497300, OsERF096–Os10g0562900, OsERF77–Os04g0610400, and OsERF3–Os01g0797600), E2F/DP (OsE2Fe-1–Os02g0739700), DBB (OsBBX6–Os02g0646200), C2H2 (OsADR3–Os03g0764100), and bHLH (OsbHLH052–Os03g0122100, OsbHLH6–Os04g0301500, and OsbHLH148–Os03g0741100) (Figure 4). On the other hand, the TF-encoding genes identified that were downregulated in the chilling-tolerant and upregulated in the chilling-sensitive genotypes were from the families MYB (OsMYB21–Os11g0684000), C3H (OsTZF7–Os05g0525900), and bHLH (OsbHLH111–Os04g0489600) (Figure 4).

4. Discussion

Plants have developed specific mechanisms to sense external signals and implement adaptive responses necessary to adapt to environmental stresses [50]. Some morphological changes in the chilling stress at germination were observed in previous studies from our research group [11]. We observed that the germination was affected in the chilling-sensitive genotype (Tio Taka), which required 25 days from the germination stage to the S3 stage, while the chilling tolerant genotype (Oro) required 18 days to reach the S3 stage. Also, we previously reported that the germination index under chilling stress was 18.5% for the chilling-sensitive genotype and 84.75% for the chilling-tolerant genotype, and the frequency of coleoptiles larger than 5mm was approximately 40% in the chilling-tolerant genotype and near zero for the chilling-sensitive genotype [13]. The relative performance (under chilling conditions, with respect to the control conditions) of the shoot length under chilling stress was 16.70 and 95.24%, respectively, for the chilling-sensitive and tolerant genotypes, while the relative performance of the radicle length was affected in both, with the chilling-sensitive genotype being more affected [13].
The perception of abiotic stresses occurs at the outer cell membrane, and secondary signaling molecules such as reactive oxygen species (ROS) are produced. These molecules stimulate the intracellular membrane, which regulates Ca2+ levels, and initiate a cascade of protein phosphorylation, which acts on the cytoprotection of proteins, and TFs, which regulate the expression of stress-responsive genes. Stress signaling transduction occurs in a phytohormone-dependent or -independent manner. The products of the stress-response genes are divided into regulatory proteins, such as kinases, phosphokinases, and TFs, as well as functional proteins, which reduce the damage caused by stress. TFs are proteins that bind to sequences present in the promoters of stress-response genes to regulate their expression [51,52]. Genes are involved in the perception of the chilling stress associated with physiological changes. Superoxide dismutase, catalase, ascorbate peroxidase, dehydroascorbate reductase, glutathione reductase, kinases, calcium-dependent protein kinases, respiratory burst oxidase homolog, and the cyclic nucleotide-gated channel were found to be differentially expressed in our dataset as previously reported [11].
Among the most well-characterized TFs involved in chilling stress, we found DEGs from DREB/ERF, MYB, and bHLH families (Figure 2, Figure 3 and Figure 4). These TF families can act together or independently in the regulation of cold-responsive (COR) genes to induce biochemical and physiological changes in cells and organs under chilling stress. One of the best-known mechanisms of cold adaptation is signaling mediated by C-repeat-binding factors/dehydration-responsive element-binding protein (CBF/DREB1). These TFs recognize and bind to the cis-elements C-repeat/dehydration responsive element (CRT/DRE) of the promoters of COR genes to activate them [53]. The inducer of CBF expression (ICE1), a MYC-like basic helix-loop-helix (bHLH) TF, binds and activates the expression of CBF/DREB1. In rice, OsICE1 and OsICE2 interact with OsMYBS3, a single DNA-binding repeat MYB TF, to coordinate cold tolerance [54].
Here, we found that OsDREB1A (Os09g0522200) and OsDREB1B (Os09g0522000) were upregulated in the chilling-tolerant cultivar and downregulated in the chilling-sensitive cultivar (Figure 4). Furthermore, OsDREB1G (Os02g0677300) is among the ten most upregulated genes in the tolerant cultivar (Table 2). It is already known that different DREB1s in rice confer greater cold tolerance, such as OsDREB1A, OsDREB1B, OsDREB1D, OsDREB1F, and OsDREB1G [27]. CBF/DREB belongs to the large APETALA2/ethylene-responsive factor (AP2/ERF) family, whose TFs have at least one AP2/ERF DNA-binding domain (60~70 conserved amino acids). Based on the number and similarity of AP2 domains and the presence of other domains, the AP2/ERF family is subdivided into the following five subfamilies: AP2 (two AP2 domains), ERF (one AP2 domain), DREB (one AP2 domain), RAV–related to ABI3/VP1—(AP2 domain and B3 domain), and Soloist (one AP2 domain that is structurally distinct from other AP2/ERF members) [51,55,56]. Since ERFs and DREBs have only one AP2 domain, both were kept in the ERF subfamily.
Of the most upregulated genes in the tolerant cultivar, four genes have already been characterized as being involved with chilling tolerance (Table 2). The OsMYB30 gene (Os02g0624300) was the most expressed, followed by OsMYB2 (Os03g0315400). It was reported that MYB30 overexpression increased cold sensitivity in rice seedlings at the V3/V4 stage subjected to chilling stress and maintained under this condition for 7 days [22]. Thus, MYB30 was characterized as a negative regulator of cold tolerance, since it inhibits the expression of BMY (β-amylase) genes that contributed to starch breakdown-producing sugars involved in cell membrane protection against plant chilling. Furthermore, MYB30 overexpression did not affect the expression of genes from the classical cold-response pathways [22]. OsmiR528 decreases the expression of the OsMYB30 TF by targeting an F-box domain-containing protein gene (Os06g06050), which is a positive regulator of OsMYB30 [57]. This result is interesting because MYB30 has an important role in the negative regulation of chilling tolerance at the V3/V4 stage, which does not appear to occur at the S3 stage. In fact, the genes responsible for cold tolerance in rice can vary according to the development stage [58], since the damage caused by this stress varies according to the time at which the cold occurs. However, it should be considered that the effect of the natural expression of a gene under the control of an endogenous promoter (wild type) may be different from the effect caused by the overexpression of this gene under the control of a constitutive promoter (transgenic). This happens because the regulation and accumulation of transcripts of this gene are different. Furthermore, different genotypes overexpressing the same gene may present distinct phenotypes, depending on the promoter used, the gene insertion site and the mutations caused at that site, the genotype used, and the epigenetic modifications induced by the process [59].
The OsMYB2 (Os03g0315400) gene, the second most highly expressed gene in the chilling-tolerant cultivar (Figure 2 and Table 2), was reported to enhance chilling tolerance in rice at the seedling stage (two weeks of growth) [23]. Three C2H2 family genes (OsZFP15–Os03g0820400, OsZFP182–Os03g0820300, and OsZFP36–Os03g0437200) were also upregulated (Figure 2 and Table 2), and are involved in response to abiotic stress; OsZFP182 was also reported to be upregulated in response to cold stress [24,26,58].
Interestingly, we identified six other genes that were the most upregulated in the chilling-tolerant cultivar that have not yet been characterized for involvement in chilling stress, namely two genes from the C2H2 family, OsZFP15 (Os03g0820400) and OsZFP36 (Os03g0437200), one gene from the WRKY family, OsWRKY69 (Os08g0386200), one gene from the NAC family, OsNAC14 (Os01g0675800), one gene from the MYB family, OsMYBR17 (Os01g0863300), and one gene from the ERF family (Os01g0313300) (Figure 2 and Table 2). These genes are potential targets for future studies on their involvement in the chilling stress response.
Among the 10 genes most negatively regulated by chilling in the tolerant cultivar, six genes from the MYB, bHLH, MICK_MADS, ERF, and MYB_related families were characterized by their involvement in response to other abiotic stresses (Table 2). The genes of the ZF-HD (ZH-D3–Os12g0208900), MYB (2R_MYB78–Os08g0437300), WRKY (WRKY57–Os12g0102300), and bHLH (BHLH083–Os05g0103000) families have not yet been characterized and may be potential negative regulators of chilling tolerance. Similarly, in the sensitive cultivar, two upregulated genes, a B3 family gene (Os03g0620400) and a MYB family gene (Os2R_MYB45–Os04g0508500), were also not previously characterized and are potential negative regulators of chilling tolerance (Table 2). The other eight genes upregulated in the sensitive cultivar are not involved in the cold response.
Here, we investigated all TF-encoding genes identified in the rice genome (Oryza sativa L. japonica) according to the Plant Transcription Factor Database and The Rice Annotation Project Database. By the use of contrasting genotypes (belonging to the indica and japonica subspecies) as the tolerance to chilling stress at the germination stage (S3), our transcriptomic analysis revealed the transcriptional profile of many different TF families. Some of the uncharacterized genes that were DEGs in our dataset can be used in functional genomics studies to test their involvement in chilling tolerance, as well as to perform screenings of different genotypes to understand the effect of the genetic background in the chilling tolerance (Figure 5). Our results, together with the state-of-the-art underlying molecular regulation of chilling, highlight the complexity of the response mechanism to this stress and show that we still have some gaps that should be unveiled to depict the regulatory mechanism behind chilling tolerance.

Supplementary Materials

The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/dna4040038/s1, Table S1: Significantly differentially expressed genes encoding for transcription factors at Oro genotype (chilling tolerant) under chilling stress; Table S2: Significantly differentially expressed genes encoding for transcription factors at Tio Taka genotype (chilling sensisitve) under chilling stress, Table S3: Significantly differentially expressed genes encoding for transcription factors at Oro (chilling tolerant) and Tio Taka (chilling sensisitve) under chilling stress, Table S4: Non-significantly differentially expressed genes encoding for transcription factors at Oro (chilling tolerant) and Tio Taka (chilling sensisitve) under chilling stress.

Author Contributions

Conceptualization, V.E.V., L.C.d.M., V.K.d.L., A.C.d.O. and C.P.; methodology, V.E.V., L.C.d.M. and C.P.; software, V.E.V., L.C.d.M. and C.P.; validation, V.E.V., L.C.d.M. and C.P.; formal analysis, V.E.V., L.C.d.M. and C.P.; investigation, V.E.V., L.C.d.M., V.K.d.L., A.C.d.O. and C.P.; resources, V.E.V., L.C.d.M., V.K.d.L., A.C.d.O. and C.P.; data curation, V.E.V., L.C.d.M. and C.P.; writing—original draft preparation, V.E.V., L.C.d.M. and C.P.; writing—review and editing, V.E.V., L.C.d.M. and C.P.; visualization, V.E.V., L.C.d.M. and C.P.; supervision, L.C.d.M. and C.P.; project administration, V.E.V., L.C.d.M. and C.P.; funding acquisition, L.C.d.M., A.C.d.O. and C.P. All authors have read and agreed to the published version of the manuscript.

Funding

Funding was provided by Coordenação de Aperfeiçoamento de Pessoal de Nıvel Superior (CAPES), Fundação de Amparo à Pesquisa do Rio Grande do Sul (FAPERGS) and Conselho Nacional de Desenvolvimento Cientıfico e Tecnológico (CNPq).

Data Availability Statement

The authors confirm that the data supporting the findings of this study are available within the article and its Supplementary Materials.

Conflicts of Interest

The authors declare that there are no conflicts of interest regarding the publication of this manuscript.

References

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Figure 1. RNA-seq analysis showing the transcription factor-encoding genes in shoots in the S3 stage of two rice genotypes, Oro (tolerant) and Tio Taka (sensitive), subjected to chilling stress (13 °C) during germination. (A) Volcano plot illustrating the upregulated and downregulated genes reaching statistical significance (p < 0.05), illustrated in red and blue, respectively, and the non-significant genes, illustrated in gray, in the chilling tolerant genotype Oro subjected to chilling stress (13 °C) during germination. (B) Volcano plot illustrating the upregulated and downregulated genes reaching statistical significance (p < 0.05), illustrated in red and blue, respectively, and the non-significant genes, illustrated in gray, in the chilling sensitive genotype Tio Taka, subjected to chilling stress (13 °C) during germination.
Figure 1. RNA-seq analysis showing the transcription factor-encoding genes in shoots in the S3 stage of two rice genotypes, Oro (tolerant) and Tio Taka (sensitive), subjected to chilling stress (13 °C) during germination. (A) Volcano plot illustrating the upregulated and downregulated genes reaching statistical significance (p < 0.05), illustrated in red and blue, respectively, and the non-significant genes, illustrated in gray, in the chilling tolerant genotype Oro subjected to chilling stress (13 °C) during germination. (B) Volcano plot illustrating the upregulated and downregulated genes reaching statistical significance (p < 0.05), illustrated in red and blue, respectively, and the non-significant genes, illustrated in gray, in the chilling sensitive genotype Tio Taka, subjected to chilling stress (13 °C) during germination.
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Figure 2. Differentially expressed transcription factor-encoding genes in shoots in the S3 stage exclusive from rice genotype Oro (chilling-tolerant) subjected to chilling stress (13 °C) during germination. (A) Heat map values in Log2FC. Genes were grouped into families, and the control (optimal temperature) condition was used as a baseline. (B) Interaction network of upregulated genes, obtained using the STRING database, with a minimum required interaction score of 0.400 and network edges representing evidence of an interaction. Clustering was performed using k-means, only clustered genes are shown. Network nodes represent proteins, and each node represents all the proteins produced by a single, protein-coding gene locus. Edges represent protein–protein associations.
Figure 2. Differentially expressed transcription factor-encoding genes in shoots in the S3 stage exclusive from rice genotype Oro (chilling-tolerant) subjected to chilling stress (13 °C) during germination. (A) Heat map values in Log2FC. Genes were grouped into families, and the control (optimal temperature) condition was used as a baseline. (B) Interaction network of upregulated genes, obtained using the STRING database, with a minimum required interaction score of 0.400 and network edges representing evidence of an interaction. Clustering was performed using k-means, only clustered genes are shown. Network nodes represent proteins, and each node represents all the proteins produced by a single, protein-coding gene locus. Edges represent protein–protein associations.
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Figure 3. Differentially expressed transcription factor-encoding genes in shoots in the S3 stage exclusive from rice genotype Tio Taka (chilling-sensitive) subjected to chilling stress (13 °C) during germination. (A) Heat map values in Log2FC. Genes were grouped into families, and the control (optimal temperature) condition was used as a baseline. (B) Interaction network of upregulated genes, obtained using the STRING database, with a minimum required interaction score of 0.400 and network edges representing evidence of an interaction. Clustering was performed using k-means, and only clustered genes are shown. Network nodes represent proteins, and each node represents all the proteins produced by a single, protein-coding gene locus. Edges represent protein–protein associations.
Figure 3. Differentially expressed transcription factor-encoding genes in shoots in the S3 stage exclusive from rice genotype Tio Taka (chilling-sensitive) subjected to chilling stress (13 °C) during germination. (A) Heat map values in Log2FC. Genes were grouped into families, and the control (optimal temperature) condition was used as a baseline. (B) Interaction network of upregulated genes, obtained using the STRING database, with a minimum required interaction score of 0.400 and network edges representing evidence of an interaction. Clustering was performed using k-means, and only clustered genes are shown. Network nodes represent proteins, and each node represents all the proteins produced by a single, protein-coding gene locus. Edges represent protein–protein associations.
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Figure 4. Differential expression of the transcription factor-encoding genes in shoots in the S3 stage, found in common in both Oro (chilling-tolerant) and Tio Taka (chilling-sensitive) rice genotypes, subjected to chilling stress (13 °C) during germination. The control (optimal temperature) condition was used as a baseline.
Figure 4. Differential expression of the transcription factor-encoding genes in shoots in the S3 stage, found in common in both Oro (chilling-tolerant) and Tio Taka (chilling-sensitive) rice genotypes, subjected to chilling stress (13 °C) during germination. The control (optimal temperature) condition was used as a baseline.
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Figure 5. Summary scheme showing some potential new transcription factors involved in chilling tolerance, based on a global transcriptional profile analyzing differential expression of the transcription factor-encoding genes in shoots in the S3 stage in two rice genotypes, Oro (chilling-tolerant) and Tio Taka (chilling-sensitive), subjected to chilling stress (13 °C) during germination.
Figure 5. Summary scheme showing some potential new transcription factors involved in chilling tolerance, based on a global transcriptional profile analyzing differential expression of the transcription factor-encoding genes in shoots in the S3 stage in two rice genotypes, Oro (chilling-tolerant) and Tio Taka (chilling-sensitive), subjected to chilling stress (13 °C) during germination.
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Table 1. Overview of the total transcription factor (TF) families within rice (Oryza sativa L. japonica) genome according to the Plant Transcription Factor Database, as well as the number of genes found in each family and the significantly differentially expressed transcription factor-encoding genes (DEGs) exclusively in the Oro genotype (chilling tolerant), exclusively in the Tio Taka (chilling sensitive), and in both genotypes (Tio Taka + Oro), subjected to chilling stress (13 °C) during germination S3 stage (control condition was used as a baseline to find the differentially expressed genes).
Table 1. Overview of the total transcription factor (TF) families within rice (Oryza sativa L. japonica) genome according to the Plant Transcription Factor Database, as well as the number of genes found in each family and the significantly differentially expressed transcription factor-encoding genes (DEGs) exclusively in the Oro genotype (chilling tolerant), exclusively in the Tio Taka (chilling sensitive), and in both genotypes (Tio Taka + Oro), subjected to chilling stress (13 °C) during germination S3 stage (control condition was used as a baseline to find the differentially expressed genes).
Familyn of TF Genes Within the Oryza sativa L. japonica GenomeChilling-Sensitive Genotype (Tio Taka)Chilling-Tolerant Genotype (Oro)Both Cultivars% *
AP22232022.73
ARF4841112.50
ARR-B110109.09
B36552010.77
BBR-BPC70000.00
BES1610250.00
bHLH2112382426.07
bZIP14017111329.29
C2H21351261020.74
C3H7482824.32
CAMTA740171.43
CO-like2114338.10
CPP2020010.00
DBB1322461.54
Dof3763024.32
E2F/DP1021360.00
EIL111009.09
ERF16311131020.86
FAR11336015.26
G2-like6280622.58
GATA3250531.25
GeBP130000.00
GRAS6982318.84
GRF1920010.53
HB-other1710217.65
HB-PHD10000.00
HD-ZIP61112631.15
HRT-like1100100.00
HSF3863228.95
LBD3921212.82
LFY20000.00
LSD1221133.33
MIKC_MADS6162216.39
M-type_MADS351002.86
MYB13018151133.85
MYB_related106105720.75
NAC170205819.41
NF-X120000.00
NF-YA2521220.00
NF-YB1611118.75
NF-YC1920326.32
Nin-like1501220.00
RAV401150.00
S1Fa-like201050.00
SBP2932017.24
SRS610016.67
STAT1100100.00
TALE4503415.56
TCP2323439.13
Trihelix4023525.00
VOZ210050.00
Whirly2011100.00
WOX171005.88
WRKY1281371023.44
YABBY1530126.67
ZF-HD1571160.00
Total 2408 24811717022.22
* Values shown as percentages (%) refer to the amount of DEGs representative from each family, concerning the number of genes found within the genome in each family.
Table 2. List of the 10 transcription factor-encoding genes more upregulated and more downregulated exclusively in the Oro (chilling-tolerant) and exclusively in the Tio Taka (chilling-sensitive), subjected to chilling stress (13 °C) during germination.
Table 2. List of the 10 transcription factor-encoding genes more upregulated and more downregulated exclusively in the Oro (chilling-tolerant) and exclusively in the Tio Taka (chilling-sensitive), subjected to chilling stress (13 °C) during germination.
Upregulated Genes—Oro (Chilling-Tolerant)
IDFamilyGene NameLog2FCFunctionReference
Os02g0624300MYBOsMYB306.11718Confers cold stress sensibility[22]
Os03g0315400MYBOsMYB25.786032Confers cold stress tolerance[23]
Os03g0820400C2H2OsZFP155.316598Confers salinity and drought tolerance[24]
Os03g0820300C2H2OsZFP1824.623318Abscisic acid-induced antioxidant defense[25]
Confers salt stress tolerance[26]
Upregulated in cold stress[26]
Os02g0677300ERFOsDREB1G3.986341Confers cold stress tolerance[27]
Os03g0437200C2H2OsZFP363.736962Abscisic acid-induced antioxidant defense and oxidative stress tolerance[28]
Os08g0386200WRKYOsWRKY692.697006Uncharacterized-
Os01g0675800NACOsNAC142.608557Confers drought tolerance[29]
Os01g0863300MYBOsMYBR172.538865Uncharacterized-
Os01g0313300ERF-2.473578Uncharacterized-
Downregulated genes—Oro (chilling-tolerant)
Os12g0208900ZF-HDOsZHD3−2.20005Uncharacterized-
Os04g0594100MYBOsMYB58/63, OsRRS1−2.14425Confers drought tolerance[30]
Negatively regulates plant growth and development [31]
Os04g0350700bHLHOsAN1−1.99325Awn development, grain size, and grain number[32]
Os09g0532900MYBOs2R_MYOsB85−1.91861Phenylalanine and lignin biosynthesis [33]
Os08g0112700MIKC_MADSOsMADS26−1.80766Negatively regulates pathogen resistance and drought tolerance[34]
Os03g0182800ERFOsEBP-89−1.8059Ethylene-dependent seed maturation and shoot development of rice[35]
Os08g0437300MYBOs2R_MYOsB78−1.62563Uncharacterized-
Os12g0102300WRKYOsWRKY57−1.41296Uncharacterized-
Os05g0103000bHLHOsBHLH083−1.33475Uncharacterized-
Os08g0157600MYB_relatedOsCCA1−1.32875Confers tolerance to salinity, osmotic, and drought stresses[36]
Upregulated genes—Tio Taka (chilling-sensitive)
Os03g0620400B3-6.865871--
Os04g0477300NACOsBET15.745444Suppression improves boron toxicity tolerance in rice[37]
Os04g0508500MYBOs2R_MYB455.300596--
Os12g0123700NACOsNAC1315.104718Rice blast disease resistance[38]
Os01g0584900WRKYOsWRKY775.095596Involved in disease resistance [39]
Os02g0685200MYB_relatedOsMYB1R4.960256Response to abiotic stresses[40]
Os04g0619000NACOsNAC0834.957849Negatively regulates rice immunity against Magnaporthe oryzae[24]
Os03g0109000NACOsNAC0554.938849Regulates GA-mediated lignin biosynthesis in rice straw[41]
Os11g0127600NACOsONAC0454.891635Confers drought and salt tolerance[42]
Os11g0126900NACOsNAC104.841549Confers drought tolerance and grain yield [43]
Downregulated genes—Tio Taka (chilling-sensitive)
Os08g0474000ERFOsERF104−4.51795Susceptibility to Pyricularia oryzae[44]
Os08g0549600bZIPOsFD4, OsbZIP69−3.67118Promotes the rice floral transition[45]
Os05g0203800MIKC_MADSOsMADS58−3.59836Specifies floral organ identities and meristem fate[46]
Os10g0403800bHLHOsbHLH174−3.43713--
Os01g0821300WRKYOsWRKY108−2.9151Promotes phosphate accumulation[47]
Os07g0589200GRASOsGRAS-37−2.78553--
Os05g0586300bHLHOsbHLH051−2.67864--
Os11g0523700bHLHOsbHLH002−2.59665Positive regulation of chilling tolerance[48]
Os09g0457900ERFOsERF102−2.53898--
Os11g0558200MYBOsMYB4P−2.50756Increases phosphate acquisition in rice[49]
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MDPI and ACS Style

Viana, V.E.; Pegoraro, C.; da Luz, V.K.; Costa de Oliveira, A.; da Maia, L.C. Uncovering Key Transcription Factors Driving Chilling Stress Tolerance in Rice Germination. DNA 2024, 4, 582-598. https://doi.org/10.3390/dna4040038

AMA Style

Viana VE, Pegoraro C, da Luz VK, Costa de Oliveira A, da Maia LC. Uncovering Key Transcription Factors Driving Chilling Stress Tolerance in Rice Germination. DNA. 2024; 4(4):582-598. https://doi.org/10.3390/dna4040038

Chicago/Turabian Style

Viana, Vívian Ebeling, Camila Pegoraro, Viviane Kopp da Luz, Antonio Costa de Oliveira, and Luciano Carlos da Maia. 2024. "Uncovering Key Transcription Factors Driving Chilling Stress Tolerance in Rice Germination" DNA 4, no. 4: 582-598. https://doi.org/10.3390/dna4040038

APA Style

Viana, V. E., Pegoraro, C., da Luz, V. K., Costa de Oliveira, A., & da Maia, L. C. (2024). Uncovering Key Transcription Factors Driving Chilling Stress Tolerance in Rice Germination. DNA, 4(4), 582-598. https://doi.org/10.3390/dna4040038

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