Comparative transcriptome analysis of the cold resistance of the sterile rice line 33S

Hongjun Xie; Mingdong Zhu; Yaying Yu; Xiaoshan Zeng; Guohua Tang; Yonghong Duan; Jianlong Wang; Yinghong Yu

doi:10.1371/journal.pone.0261822

. 2022 Jan 14;17(1):e0261822. doi: 10.1371/journal.pone.0261822

Comparative transcriptome analysis of the cold resistance of the sterile rice line 33S

Hongjun Xie ^1,^#, Mingdong Zhu ^1,^#, Yaying Yu ¹, Xiaoshan Zeng ¹, Guohua Tang ¹, Yonghong Duan ¹, Jianlong Wang ^2,^*, Yinghong Yu ^3,^*

Editor: Jian Zhang⁴

PMCID: PMC8759683 PMID: 35030196

Abstract

Rice (Oryza sativa L.) is one of the most important species for food production worldwide. Low temperature is a major abiotic factor that affects rice germination and reproduction. Here, the underlying regulatory mechanism in seedlings of a TGMS variety (33S) and a cold-sensitive variety (Nipponbare) was investigated by comparative transcriptome. There were 795 differentially expressed genes (DEGs) identified only in cold-treated 33S, suggesting that 33S had a unique cold-resistance system. Functional and enrichment analysis of these DEGs revealed that, in 33S, several metabolic pathways, such as photosynthesis, amino acid metabolism, secondary metabolite biosynthesis, were significantly repressed. Moreover, pathways related to growth and development, including starch and sucrose metabolism, and DNA biosynthesis and damage response/repair, were significantly enhanced. The expression of genes related to nutrient reserve activity were significantly up-regulated in 33S. Finally, three NAC and several ERF transcription factors were predicted to be important in this transcriptional reprogramming. This present work provides valuable information for future investigations of low-temperature response mechanisms and genetic improvement of cold-tolerant rice seedlings.

Introduction

Rice (Oryza sativa L.) is one of the most important staple crop species, feeding more than half of the global population. Increasing rice yield is a priority to ensure global food security. Low temperature is one of the major environmental stresses that negatively impacts plant growth and yield potential. Due to its tropical and subtropical origin, rice is sensitive to low temperature [1]. The optimal temperature is 25–35°C for rice at the germination stage. Temperatures below 15°C would lead to a number of developmental damage in rice, including reduced germination rate, delayed seedling emergence and initial seedling growth, and high seedling mortality [2]. In the reproductive phase, low temperature can cause sterility by interrupting meiosis and mitosis, thus resulting in the failed formation of mature microspores [3]. The current high-yield production of superhybrid rice cultivars are frequently affected by cold stress in tropical or subtropical areas. Thus, improving rice cold stress tolerance could help maintain rice production in regions where it is currently grown and expand production into northern areas with lower annual temperatures [4].

Hybrid rice cultivars have a yield advantage that 10–20% greater than that of conventional inbred cultivars [5]. In the past few decades, numerous hybrid rice cultivars have been developed in more than 40 countries and have played a critical role in the global food supply [6]. Currently, F1 Hybrid rice is mainly produced using two systems: the cytoplasmic male sterility-based three-line system and the thermo/photoperiod-sensitive genic male sterile-based two-line system. The first is the traditional three-line system, which requires a cytoplasmic male-sterile (CMS) line, a restorer line, and a maintainer line to produce hybrid seeds and to maintain the CMS line [7, 8]. The other is a two-line breeding system, which uses a thermo-/photoperiod-sensitive genic male-sterile (T/PGMS) line as both a sterility line and a maintainer line under specific environmental conditions [9]. Compared with the three-line system, the two-line hybrid rice system has increased the yield potential of rice by 10% [10]. In addition, the two-line system is more cost-effective, produces higher quality grain, is more flexible in terms of germplasm, and is simpler to operate [11]. Previously, we developed a cold-resistant thermosensitive genic male-sterile (TGMS) line, 33S, with a critical temperature of <23°C [12]. This line has been widely used in rice breeding in China. With the use of 33S as the sterile line, 38 new hybrid rice varieties have been approved, and the total increased production area is more than one million hectares. We found that 33S seedlings had strong low-temperature tolerance. In the present study, the expression profile of the thermosensitive genie male-sterile variety S33 was analyzed by transcriptome sequencing to understand the molecular mechanism of low-temperature adaptation in T/PGMS rice lines.

Materials and methods

Plant materials and stress treatment

The japonica rice (O. sativa L.) variety Nipponbare (a cold-sensitive material) and the indica TGMS variety 33S (a cold-resistant material) were used for transcriptomic analysis. Rice seeds were germinated at 30°C under a photoperiod of 12 h of light/12 h of darkness. For the low-temperature treatment, fifty one-week-old seedlings were subjected to 15°C for seven days under a photoperiod of 12 h of light/12 h of darkness. After the treatment, leaf tissues randomly collected from ten seedlings were immediately frozen in liquid nitrogen and then stored at -80°C until RNA extraction. The remaining seedlings were moved to normal conditions and allowed to grow for another week.

RNA extraction and library construction

Total RNA was extracted from three independent biological replicates using the ethanol precipitation protocol and CTAB-pBIOZOL reagent according to the manufacturer’s instructions. Total RNA was qualified and quantified using a NanoDrop instrument (Thermo, USA) and an Agilent 2100 Bioanalyzer (Thermo Fisher Scientific, MA, USA). A total amount of 3 μg of RNA per sample was used as input material for the RNA sample preparations. Sequencing libraries were generated using a NEBNext^® Ultra^™ RNA Library Prep Kit for Illumina^® (NEB, USA) following the manufacturer’s recommendations. The library preparations were sequenced on an Illumina HiSeq 2500 platform in accordance with a 100 bp paired-end pattern (PE-100). Clean data were obtained by removing reads containing adapter, reads containing ploy-N and low quality reads from raw data, and all transcriptome analyses were based on the clean data.

RNA sequencing (RNA-seq) data analysis

Reference genome and gene model annotation files were downloaded from Rice Genome Annotation Project (GCF_000005425.2_Build_4.0_genomic) [13]. The index of the reference genome was built using Bowtie v2.0.6 [14], and paired-end clean reads were aligned to the reference genome using TopHat v2.0.9 [15]. To quantify the gene expression levels, HTSeq v0.6.1 was used to count the read numbers mapped to each gene [16]. Afterward, the reads per kilobase of exon model per million mapped reads (RPKM) of each gene was calculated based on the length of the gene and read count mapped to that gene. Differentially expressed genes (DEGs) were identified using the DESeq R package (version 1.10.1) between different samples with parameters: adjusted p value< 0.05 and |log2FC|> = 1 [17]. The resulting P-values were adjusted using the Benjamini and Hochberg’s approach for controlling the false discovery rate.

Availability of data and materials

The raw reads produced in this study were deposited in the NCBI SRA with the submission number SUB10060963 under bio Project PRJNA749812.

Functional annotation of DEGs

For Gene Ontology (GO) enrichment analysis, the Blast2GO software (version 2.3.5) was used to identify the DEGs according to biological process, molecular function and cellular component ontologies with a threshold E value ≤ 10⁻⁵ [18]. KOBAS software was used for the pathway enrichment and annotation analysis of the DEGs by comparison to the Kyoto Encyclopedia of Genes and Genomes (KEGG) database [19].

RT-qPCR validation

The RNA-seq data were validated via RT-qPCR analyses using an Applied Biosystems StepOnePlus^™ Real-Time System with SYBR^® Select Master Mix (2X) (ABI, USA). The reaction protocol was as follows: 95°C for 3 min; 40 cycles at 95°C for 15 s, 55°C for 15 s, and 72°C for 20 s; and then 72°C for 5 min. All the specific primers used were presented in S1 Table. Three technical replicates were included per sample. The rice actin 1 gene (gene locus: Os03g0718100) was used as an internal standard [20]. The relative expression value of the different genes were calculated using the 2^−ΔΔCt method.

Results and discussion

33S is more cold tolerant than Nipponbare

33S is an indica TGMS line that was selected for a 15-year hybrid from Peiai 64S, Yue 4B and Ganwanxian 30. Seedlings of the low-temperature-tolerant rice variety 33S and the low-temperature-sensitive variety Nipponbare were sampled after 7 days of low-temperature treatment at 15°C (Fig 1). After treatment, 12.4±0.08% of the Nipponbare seedlings died, while no visible growth effects were observed of the 33S seedlings after low temperature treatment. Additionally, the length of the shoots of Nipponbare was obviously reduced, while the length of the shoots and roots of 33S showed no differences (Fig 1).

Fig 1 — A. Seedling of 33S and Nipponbare. B. Shoot length of 33S and Nipponbare seedlings after cold treatment. C. Root length of 33S and Nipponbare seedlings after cold treatment. Different letters above the box indicate a significant difference at P < 0.05. Error bar was statistic by standard deviation.

Identification of DEGs and functional classification

In order to elucidate the cold response mechanism, seedlings of the low-temperature-tolerant rice variety 33S and the low-temperature-sensitive variety Nipponbare were sampled after 7 days of low-temperature treatment at 15°C. The samples were subjected to total RNA extraction and RNA-seq analysis using the Illumina HiSeq 2500 platform.

The genes and RPKM values of six samples were calculated. Differential expression analysis under two conditions was performed using the DESeq R package v1.10.1 using a threshold of P < 0.05 and |log2(fold change)| > = 1. A total of 938 DEGs were detected in 33S after cold treatment, including 347 upregulated genes and 591 downregulated genes (S2 and S3 Tables) (Fig 2). In Nipponbare, a total of 762 DEGs were detected after cold treatment, of which 398 were upregulated (S4 Table) and 364 were downregulated (Fig 2, S5 Table). Compared with the Nipponbare variety, more genes were down-regulated in 33S variety after seven days low temperature treatment. In contrast, more up-regulated genes were identified in Nipponbare variety. Venn diagram was constructed to analyze the common DEGs between 33S and Nipponbare. The result showed that only 143 common DEGs were detected between the two varieties (Fig 2C, S6 Table).

Fig 2 — A. Significantly up- or down-regulated genes in 33S-Cold vs. 33S-CK. B. Significantly up- or down-regulated genes in N-Cold vs. N-CK. C. Venn diagram indicating the number of DEGs common to 33S and Nipponbare. N indicates the variety of Nipponbare, CK indicates the control seedling not treated by cold temperature. DEGs were screened using a threshold of P <0.05 and |log2FoldChange| > = 1.

To further characterize genes affected by low temperature stress, all DEGs were subjected to Gene Ontology (GO) enrichment analysis. According to their functions, the DEGs were classified into three classes, including biological process, cellular component and molecular function (S7 and S8 Tables). The top 30 enrichment terms for 33S and Nipponbare were listed in Fig 3A and 3B, respectively. Possibly due to the difference in low temperature tolerance, the top 30 GO enrichment terms were dramatically different in 33S and Nipponbare varieties, even though few terms were enriched in cellular component for both varieties (Fig 3A and 3B). For 33S variety, within the top 30 most enrichment terms, there were ten, five, and fifteen enriched terms belonging to the biological process, cellular component, and molecular function categories, respectively. However, for Nipponbare variety, the number were nineteen, three, and eight. In the biological process category, a high percentage of DEGs were associated with oxidation-reduction process and single-organism metabolic process for 33S variety. In contrast, a high percentage of DEGs were enriched in metabolic process, cellular nitrogen compound biosynthesis, primary metabolic process, cellular metabolic process, heterocycle biosynthetic process, aromatic compound biosynthetic process, organic cyclic compound biosynthesis, regulation of transcription, regulation of RNA metabolic process, and regulation of RNA biosynthetic process. A relatively small number of DEGs were classified into terms of cellular component category for both varieties. In the molecular function category, a high percentage of DEGs were classified into oxidoreductase activity and cation binding terms. However, a relatively small number DGEs were fall into the molecular function category in Nipponbare variety. Taken together, all these results suggested that these two rice varieties responses differently under low temperature condition.

Fig 3 — A. GO enrichment analysis of the DEGs in 33S rice seedlings after seven days of low-temperature treatment. B. GO enrichment analysis of the DEGs in Nipponbare rice seedlings after seven days of low-temperature treatment. The DEGs were classified into three main GO categories (biological processes, molecular functions and cellular components). C. KEGG pathway enrichment analysis of DEGs in 33S rice seedlings after seven days of low-temperature treatment. D. KEGG pathway enrichment analysis of DEGs in Nipponbare rice seedlings after seven days of low-temperature treatment. The P-value to determine the enrichment significance was calculated through hypergeometric distribution.

The low-temperature-responsive DEGs were further mapped to terms in the KEGG database. In 33S, 349 DEGs were significantly enriched in 67 metabolic pathways or signal transduction pathways, while in Nipponbare, 226 DEGs were enriched in 61 metabolic pathways or signal transduction pathways (S9 and S10 Tables). Seven pathways out of the top 20 significantly enriched pathways were significantly enriched in the 33S and Nipponbare varieties, including starch and sucrose metabolism, phenylpropanoid biosynthesis, metabolic pathways, carotenoid biosynthesis, carbon metabolism, carbon fixation in photosynthetic organisms, and biosynthesis of secondary metabolites (Fig 3C and 3D). In addition, the DEGs were also significantly enriched in pathways such as plant hormone signal transduction, phenylpropanoid biosynthesis, protein processing in the endoplasmic reticulum (ER), and photosynthesis pathways in both varieties. Metabolic pathways were mostly affected, followed by biosynthesis of secondary metabolites, during low-temperature treatment in both varieties. The KEGG enrichment analysis provided valuable information for investigating the pathways and gene functions involved in the cold stress response.

Validation of transcriptome data by RT-qPCR analyses

To validate the results of the RNA-seq data, RNA samples extracted for RNA-seq were also subjected to qRT-PCR analysis. A total of eight DEGs were randomly selected for quantitative qRT-PCR analysis, including four down-regulated genes (Os01g0124000, Os01g0971800, Os05g0382600, and Os06g0474800) and four up-regulated genes (Os03g0161900, Os03g0293000, Os02g0685200, and Os10g0509700). As anticipated, the expression profiles of these genes according to the qRT-PCR results were essentially consistent with those generated from RNA-seq, suggesting that the DEGs resulting from RNA-seq were credible for further analysis (Fig 4).

Fig 4 — Data are mean ± SD of three biological replicates. Asterisks indicate significant difference compared to control samples (*P < 0.05; **P < 0.01). The *actin 1* gene was used as an internal standard gene was used as an internal reference.

Low-temperature-responsive genes involved in hormone signal transduction

Cytokinin plays important roles not only in various plant growth and development processes but also in abiotic and biotic stress responses [21, 22]. Two-component A-type response regulators (ARRs) are part of the cytokinin signaling cascade, and 15 ARRs were identified in the rice genome [23]. In this study, four ARR genes (Os02g0557800, Os11g0143300, Os12g0139400, and Os04g0673300, encoding ARR3, ARR6, ARR9, and ARR10, respectively) responded to low-temperature treatment in the 33S variety. Three ARR genes (Os02g0557800, Os12g0139400, and Os04g0673300, encoding ARR3, ARR9, and ARR10, respectively) were responsive to low-temperature treatment in the Nipponbare variety (Table 1). ARR9 expression was previously reported to be regulated by the circadian clock in Arabidopsis [24]. In rice, ARR9 expression was shown to be downregulated under cold stress in three cold-tolerant genotypes [25]. Furthermore, rice ARR9 and ARR10 genes were strongly positively correlated with the zinc finger transcription factor (TF) Drought and Salt Tolerance (DST) [26]. The loss of DST function increases stomatal closure and reduces stomatal density, consequently resulting in enhanced drought and salt tolerance in rice. Our results suggested that the ARR-mediated cytokinin signaling cascade might be differentially involved in the low-temperature response of the two varieties.

Table 1. List of DEGs enriched in plant hormone signal transduction.

Variety	Loci	Pathway	log2FoldChange
33S	Os04g0673300	Two-component response regulator ARR6	1.7729
	Os11g0143300	Two-component response regulator ARR9	2.1111
	Os12g0139400	Two-component response regulator ARR10	2.0053
	Os02g0557800	Two-component response regulator ARR3	1.8845
	Os05g0186100	Histidine-containing phosphotransfer protein 4	3.0962
	Os03g0610900	Serine/threonine-protein kinase SAPK10	−1.9516
	Os12g0586100	Serine/threonine-protein kinase SAPK9	−2.0314
	Os06g0527800	Abscisic acid receptor PYL8	5.8919
Nipponbare	Os01g0221100	Probable indole-3-acetic acid-amido synthetase GH3.3	−1.9541
	Os01g0583100	Probable protein phosphatase 2C 6	1.3689
	Os11g0143300	Two-component response regulator ARR9	2.2694
	Os12g0139400	Two-component response regulator ARR10	2.0143
	Os02g0557800	Two-component response regulator ARR3	1.5918
	Os05g0186100	Histidine-containing phosphotransfer protein 4	2.5623
	Os05g0457200	Probable protein phosphatase 2C 49	3.0365

Open in a new tab

The C-repeat-binding factor (CBF)-dependent cold signaling pathway plays an important regulatory role in the low-temperature-responsive signaling pathway [27]. OST1 (OPEN STOMATA 1) acts upstream of CBFs to positively regulate freezing tolerance in Arabidopsis and increases the freezing resistance of plants by phosphorylating and stabilizing the key transcription factor ICE1, which acts upstream of the CBF genes [28]. In addition, OST1 can indirectly regulate the stability of CBF proteins and enhance the freezing resistance of plants by phosphorylating the new polypeptide chain-coupled protein complex β subunit BTF3 [29]. There are three OST1 homologs in the rice genome (Os03g0610900, Os12g0586100 and Os03g0764800). A previous study demonstrated that the expression of Os03g0610900 in rice was influenced by the methylation level of its promoter region, and low-temperature treatment could decrease the methylation level [30]. We found that two of the homologous genes (Os03g0610900 and Os12g0586100) responded to low-temperature treatment only in the 33S variety (Table 1). Additionally, no Ser/Thr protein kinase-encoding genes were identified in Nipponbare, which might partly explain the difference in the low-temperature tolerance between these two varieties. The different response patterns of Os03g0610900 and Os12g0586100 to low temperature need further investigation. The OST1 signaling pathway has not been clearly elucidated in rice, a monocotyledonous species, and the functions of some of the homologous genes in this pathway have not yet been identified. Therefore, it is necessary to determine the physiological and biochemical functions of these genes in rice in further studies.

PYL8 was previously reported to play an important role for ABA signaling and drought stress responses, and overexpression of PLY8 in Arabidopsis could increase the ABA sensitivity and drought tolerance [31]. According to our results, the expression of the PYL8 gene was dramatically induced in response to low-temperature treatment in 33S, which indicated that PYL8 might regulate plant cold tolerance through ABA signaling pathway (Table 1). However, the expression of this gene was not induced in the low temperature-sensitive Nipponbare variety.

Low-temperature-responsive genes involved in protein processing in the ER

Biotic and abiotic stress could result in protein misfolding and the accumulation of unfolded proteins. The ER responds to unfolded proteins, which can cause deleterious effects, in its lumen (ER stress) by activating intracellular signal transduction pathways; this process is collectively termed the unfolded protein response (UPR) [32]. The ubiquitin-mediated protein degradation pathway, which has been demonstrated as a key regulatory mechanism in response to biotic stress, is responsible for the major portion of specific cellular misfolded protein degradation [33]. In this study, five DEGs were enriched in protein processing in the ER pathway after 7 days of low-temperature treatment in 33S. Of the five DEGs, three (Os01g0369200, Os02g0639800, and Os04g0667800) were predicted to participate in the ubiquitin-mediated protein degradation pathway (Table 2). Another two DEGs (Os01g0135900 and Os07g0517100) were annotated as heat-shock proteins (HSPs), which also play an important role in abiotic stress. As molecular chaperones, HSPs are responsible for protein folding, assembly, translocation and degradation of damaged proteins and play critical roles in protecting plants against stress by stabilizing proteins and membranes [34]. In contrast, eight DEGs were enriched in protein processing in the ER pathway in Nipponbare, which suggested that the cold-sensitive variety Nipponbare experienced more severe ER stress after low-temperature treatment (Table 2). In addition, the enriched terms/pathways of DEGs between these two varieties were totally different, indicating that they responded differently to low-temperature treatment.

Table 2. List of DEGs enriched in protein processing in endoplasmic reticulum pathway.

Variety	Loci	Description	log2FoldChange
33S	Os01g0369200	Cullin-1	2.2995
	Os02g0639800	E3 ubiquitin-protein ligase RMA3	−1.8144
	Os01g0135900	17.9 kDa heat shock protein 2	−1.7106
	Os04g0667800	Ubiquitin-conjugating enzyme E2	−1.8764
	Os07g0517100	18.8 kDa class V heat shock protein	−2.7372
Nipponbare	Os06g0219500	26.2 kDa heat shock protein	1.8964
	Os01g0895600	Calreticulin-3	−1.1534
	Os02g0758000	24.1 kDa heat shock protein	3.5681
	Os01g0840100	Heat shock cognate 70 kDa protein	2.6097
	Os03g0832200	Calreticulin	−2.2437
	Os01g0184100	18.0 kDa class II heat shock protein	3.3999
	Os03g0799900	SEC12-like protein 1	−1.7853
	Os11g0703900	Heat shock cognate 70 kDa protein 2	−1.1669

Open in a new tab

Low temperature-responsive transcription factors

Transcription factors play a critical role in biotic and abiotic responses in plants. In this present paper, a total of 40 and 42 TFs were identified in the DEGs from 33S and Nipponbare varieties after 7 days of low temperature treatment, respectively (Table 3). The expression of TF families showed strong responses to low temperature treatment included AP2/ERF-ERF, B3, bHLH, bZIP, C2C2-CO-like, C2H2, C3H, B-box zinc finger protein, GARP-G2-like, GRAS, HB-BELL, HB-HD-ZIP, HMG, HSF, LOB, MADS-MIKC, MYB, MYB-related, NAC, SBP, NF-YC, zf-HD. Most of these TF families had been reported to play an important role in abiotic stress including cold stress [35–37] and some of these TFs had bene utilized to improve plant abiotic stress tolerance by genetic transformation technology [38–40].

Table 3. Transcription factors response to low temperature treatment in 33S and Nipponbare.

TF family	Number of genes identified
TF family	33S	Nipponbare
AP2/ERF	2	5
B3	1	1
bHLH	3	0
bZIP	3	2
C2C2-CO-like	2	4
C2C2-Dof	0	1
C2H2	5	0
C3H	0	1
B-box zinc finger protein	1	2
GARP-G2-like	2	1
GNAT	2	1
GRAS	1	2
HB-BELL	1	0
HB-HD-ZIP	2	3
HMG	1	1
HSF	3	5
LOB	1	0
MADS-MIKC	1	3
MYB	1	3
MYB-related	3	4
NAC	4	1
SBP	0	1
NF-YC	1	0
zf-HD	1	1

Open in a new tab

However, the numbers and members of differently expressed TFs showed a dramatic difference between 33S and Nipponbare variety. For example, five C2H2 (Os01g0871200, Os02g0709000, Os03g0239300, Os06g0166200, and Os09g0431900) family members were identified in 33S, however, no gene belonged to this family was detected in Nipponbare (Table 3, S11 and S12 Tables). In addition, four NAC (Os01g0393100, Os02g0214500, Os04g0460900, and Os11g0512000) family members responded to low temperature treatment, but just one NAC (Os03g0815100) gene was identified in Nipponbare (Table 3, S11 and S12 Tables). These differences were possibly due to the different response mechanism to low temperature stress.

bHLH (basic Helix-Loop-Helix) proteins are the second largest transcription factor families in plants and plays an important role in both plant development and abiotic stress responses [41]. bHLH genes had been demonstrated to be involved in cold response in a number of plants and overexpression of bHLH genes could enhance the cold tolerance in plants like apple, rice, and pummelo [42–45]. In particularly, OsbHLH1 gene from rice was demonstrated to be involved in cold stress response [44]. Genetic transformation of rice further demonstrated that overexpression of OsbHLH1 in rice could increase the cold tolerance during the germination and seedling stages [46]. In addition, most recently report showed that OsbHLH002 protein from rice was involved in cold response downstream of the phosphatase protein OsPP2C27 [47]. In our study, the expression of three bHLH genes (Os01g0566800, Os01g0577300, and Os01g0952800) were repressed by low temperature, which indicated that these genes might negatively correlated with the low temperature tolerance.

C2H2 type zinc finger proteins participate in responses to different environmental stresses in plant, including cold and drought stress [48]. In banana fruit, MaC2H2-1, MaC2H2-2 and MaC2H2-3 were cold inducible in the peel during low temperature storage, and MaC2H2s were proposed to be involved in cold stress response via repressing the transcription of MaICE1 [49]. Overexpression of a soybean C2H2-type zinc finger gene GmZF1 could enhance the cold tolerance of transgenic Arabidopsis [50]. In this present study, the expression of five C2H2-type zinc finger TFs showed response to low temperature treatment, one of which was induced (Os02g0709000) and the other four were repressed (Os01g0871200, Os03g0239300, Os06g0166200, and Os09g0431900). However, the function of these genes in rice and their homologous in other plant species have been characterized.

The NAC (NAM, ATAF and CUC) proteins constitute a large transcription factor family with more than 150 members in rice and a number of them have been demonstrated to play crucial roles in plant abiotic stress response [51]. The SNAC2 gene from rice could be induced by abiotic stress, including drought, salinity, cold, and wounding. The transgenic experiment results showed that overexpression of SNAC2 could significantly enhance the severe cold stress tolerance (4–8 °C for 5 days) of the transgenic plants [52]. In this present paper, four NAC genes (Os01g0393100, Os02g0214500, Os04g0460900, and Os11g0512000) showed response to low temperature treatment in 33S. The expression of one of the four NAC genes (Os04g0460900) downregulated by cold treatment, while the other three genes Os01g0393100, Os02g0214500, and Os11g0512000) were induced by low temperature stress (Table 2). Os02g0214500 encodes the OsNAC20 protein and Os01g0393100 encodes the OsNAC26 protein. Previous report demonstrated that Os01g0393100 showed response to Combined abiotic stress, which indicated that Os01g0393100 might play an important role in rice abiotic stress regulation [53]. Most recently, OsNAC20 and OsNAC26 genes were demonstrated to be expressed specifically in rice endosperm and regulated starch and storage protein synthesis [54]. In this paper, we found that the direct target genes of OsNAC20 and OsNAC26, including Os02g0242600, Os02g0248800, Os02g0249000, Os02g0249600, Os02g0249800, Os02g0249900, Os02g0268100, Os05g0328333, Os05g0329100, Os05g0329400, Os05g0330600, Os05g0331550, Os05g0331800, and Os05g0332000, were dramatically induced by low temperature in 33S variety (S2 Table). These genes encoding the endosperm specific proteins and starch biosynthesis genes. The decreased photosynthesis pathway genes and increased storage protein coding genes indicated that the low temperature tolerance 33S rice variety showed a dormant-like state to response the low temperature.

33S recruits specific DEGs to enhance its tolerance to cold stress

As indicated in Fig 2, 795 DEGs were detected only in 33S and not in Nipponbare (Fig 1C; S6 Table). These 795 DEGs suggested that 33S had a special adaptation system for cold stress (Fig 5). First, in 33S, basic nutrient and energy metabolism process were highly altered: the expression of genes involved in “photosynthesis” (the expression of 24 DEGs was downregulated in cold-treated 33S) and “amino acid metabolism” (8 downregulated DEGs of 9 DEGs) was almost entirely repressed, while that of “starch and sucrose metabolism” (11 upregulated DEGs of 14 DEGs) and “major CHO metabolism” (7 upregulated DEGs of 8 DEGs) completely increased. To reduce consumption, the expression of genes involved in several metabolic pathways, such as “secondary metabolite biosynthesis” (9 downregulated DEGs of 11 DEGs) and “redox” (10 downregulated DEGs of 11 DEGs), and genes encoding miscellaneous enzymes, including kinases (31 downregulated DEGs of 40 DEGs), was also predominantly repressed. Moreover, several pathways related to maintaining genetic stability, growth and development, such as “transport (mainly protein and phosphate transporters, or ABCs)” (22 upregulated DEGs of 36 DEGs) and “DNA biosynthesis and damage response/repair” (10 upregulated DEGs of 12 DEGs), were increased significantly. Furthermore, the expression of genes related to nutrient reserve activity was mostly upregulated, including 13 upregulated prolamin PPROL genes, whose expression increased 54.7-fold, and 11 upregulated glutelin type A and B genes, whose expression increased at least 166.6-fold. Overall, 33S was able to reduce unnecessary energy consumption by silencing most bioactivities and increasing nutrient reserve activity to maintain growth under low temperature. This adaptation system seems similar to that of hibernation.

Fig 5 — A. Overview of metbolism. B. Response activities.

Conclusions

A comparative RNA-seq analysis was performed to identify low temperature-inducible DEGs in rice seedlings after 7 days of 15°C stress. In total, 938 and 762 DEGs were identified under low-temperature stress in 33S and Nipponbare, respectively. Due to differences in their tolerance to low temperature, these two varieties showed different transcriptional responses. A large number of TF-encoded genes were expressed in response to low-temperature treatment, which indicated that TFs play an important role in cold tolerance. The expression of genes involved in cytokinin and ABA signaling was dramatically induced in response to low-temperature treatment, which suggested that phytohormone played a critical role in the low-temperature response. Furthermore, the expression of most of the DEGs involved in protein processing in the ER pathway was repressed under low-temperature treatment. However, compared with the responses of genes under short-term cold treatment, some of the genes exhibited an opposite response pattern in this paper, indicating that these genes have different functions at different stages of cold treatment. The results of the present study provide a basis for an improved understanding of the molecular mechanism associated with the relatively long-term low-temperature stress response of rice seedlings.

Supporting information

S1 Table. Primers used for qRT-PCR in this study.

(DOC)

Click here for additional data file.^{(36.5KB, doc)}

S2 Table. List of genes upregulated in response to low-temperature treatment in 33S.

(XLS)

Click here for additional data file.^{(105.5KB, xls)}

S3 Table. List of genes downregulated in response to low-temperature treatment in 33S.

(XLS)

Click here for additional data file.^{(155KB, xls)}

S4 Table. List of genes upregulated in response to low-temperature treatment in Nipponbare.

(XLS)

Click here for additional data file.^{(114.5KB, xls)}

S5 Table. List of genes downregulated in response to low-temperature treatment in Nipponbare.

(XLS)

Click here for additional data file.^{(108KB, xls)}

S6 Table. List of 795 DEGs that respond to low temperature only in 33S.

(XLS)

Click here for additional data file.^{(1.8KB, xls)}

S7 Table. GO enrichment analysis of DEGs in 33S.

(XLS)

Click here for additional data file.^{(376.5KB, xls)}

S8 Table. GO enrichment analysis of DEGs in Nipponbare.

(XLS)

Click here for additional data file.^{(196.4KB, xls)}

S9 Table. KEGG pathway enrichment analysis of DEGs in 33S.

(XLS)

Click here for additional data file.^{(61KB, xls)}

S10 Table. KEGG pathway enrichment analysis of DEGs in Nipponbare.

(XLS)

Click here for additional data file.^{(19.6KB, xls)}

S11 Table. TF response to low-temperature treatment of 33S.

(XLS)

Click here for additional data file.^{(35KB, xls)}

S12 Table. TF response to low-temperature treatment of Nipponbare.

(XLS)

Click here for additional data file.^{(36KB, xls)}

Data Availability

All relevant data are within the paper and its Supporting information files.

Funding Statement

This work was funded by the National Key R&D Program of China (2018YFD0301001). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

References

1.Andaya VC, Tai TH. Fine mapping of the qCTS12 locus, a major QTL for seedling cold tolerance in rice. Theor Appl Genet. 2006;113(3):467–475. doi: 10.1007/s00122-006-0311-5 [DOI] [PubMed] [Google Scholar]
2.Fujino K. A major gene for low temperature germinability in rice (Oryza sativa L.). Euphytica. 2004;136(1):63–48. [Google Scholar]
3.Shinada H, Iwata N, Sato T, Fujino K. Genetical and morphological characterization of cold tolerance at fertilization stage in rice. Breed Sci. 2013;63(2):197–204. doi: 10.1270/jsbbs.63.197 [DOI] [PMC free article] [PubMed] [Google Scholar]
4.Ma Y, Dai X, Xu Y, Luo W, Zheng X, Zeng D, et al. COLD1 Confers Chilling Tolerance in Rice. Cell. 2015;160(160):1209–1221. doi: 10.1016/j.cell.2015.01.046 [DOI] [PubMed] [Google Scholar]
5.Normile D. Agricultural research. Reinventing rice to feed the world. Science. 2008;321(5887):330–333. doi: 10.1126/science.321.5887.330 [DOI] [PubMed] [Google Scholar]
6.Su N, Hu ML, Wu DX, Wu FQ, Fei GL, Lan Y, et al. Disruption of a rice pentatricopeptide repeat protein causes a seedling-specific albino phenotype and its utilization to enhance seed purity in hybrid rice production. Plant Physiol. 2012;159(1):227–238. doi: 10.1104/pp.112.195081 [DOI] [PMC free article] [PubMed] [Google Scholar]
7.Chen L, Liu YG. Male sterility and fertility restoration in crops. Annu Rev Plant Biol. 2014;65(1):579–606. doi: 10.1146/annurev-arplant-050213-040119 [DOI] [PubMed] [Google Scholar]
8.Wang Z, Zou Y, Li X, Zhang Q, Chen L, Wu H, et al. Cytoplasmic male sterility of rice with boro II cytoplasm is caused by a cytotoxic peptide and is restored by two related ppr motif genes via distinct modes of mRNA silencing. Plant Cell. 2006;18(3):676–687. doi: 10.1105/tpc.105.038240 [DOI] [PMC free article] [PubMed] [Google Scholar]
9.Yuan L. Purification and production of foundation seed of rice PGMS and TGMS lines. Hybrid Rice. 1994;6(1):1–3. [Google Scholar]
10.Singh RB, Virmani SS. Recent progress in the technology and development of hybrid rice in Asia. Rome, Italy: Bulletin De La Commission Internationale Du Riz, FAO; 1994. [Google Scholar]
11.Yang Q, Liang C, Zhuang W, Li J, Deng H, Deng Q, et al. Characterization and identification of the candidate gene of rice thermo-sensitive genic male sterile gene tms5 by mapping. Planta. 2007;225(2):321–330. doi: 10.1007/s00425-006-0353-6 [DOI] [PubMed] [Google Scholar]
12.Xie H, Tang G, Yinghong YU, Shenggao WU. Characterization of TGMS line 33S in rice. Agric Sci Technol. 2015;16(4):719–721. [Google Scholar]
13.Kawahara Y, Bastide M, Hamilton JP, Kanamor H. Improvement of the Oryza sativa Nipponbare reference genome using next generation sequence and optical map data. Rice (New York, NY). 2013;6(1):4. doi: 10.1186/1939-8433-6-4 [DOI] [PMC free article] [PubMed] [Google Scholar]
14.Langmead B, Salzberg SL. Fast gapped-read alignment with Bowtie 2. Nature Methods. 2012;9(4):357–359. doi: 10.1038/nmeth.1923 [DOI] [PMC free article] [PubMed] [Google Scholar]
15.Trapnell C, Pachter L, Salzberg SL. TopHat: discovering splice junctions with RNA-Seq. Bioinformatics. 2009;25(9):1105–1111. doi: 10.1093/bioinformatics/btp120 [DOI] [PMC free article] [PubMed] [Google Scholar]
16.Simon A, Theodor PP, Wolfgang H. HTSeq-a Python framework to work with high-throughput sequencing data. Bioinformatics. 2015;(2):166–169. doi: 10.1093/bioinformatics/btu638 [DOI] [PMC free article] [PubMed] [Google Scholar]
17.Love MI, Huber W, Anders S. Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2. Genome Biology. 2014;15(12):550. doi: 10.1186/s13059-014-0550-8 [DOI] [PMC free article] [PubMed] [Google Scholar]
18.Ashburner M, Ball CA, Blake JA, Botstein D, Butler H, Cherry JM, et al. Gene Ontology: tool for the unification of biology. Nature Genetics. 2000; 25(1):25–29. doi: 10.1038/75556 [DOI] [PMC free article] [PubMed] [Google Scholar]
19.Mao X, Cai T, Olyarchuk JG, Wei L. Automated genome annotation and pathway identification using the KEGG Orthology (KO) as a controlled vocabulary. Bioinformatics. 2005;21(19):3787–3793. doi: 10.1093/bioinformatics/bti430 [DOI] [PubMed] [Google Scholar]
20.Liu Q, Zheng L, He F, Zhao FJ, Shen Z, Zheng L. Transcriptional and physiological analyses identify a regulatory role for hydrogen peroxide in the lignin biosynthesis of copper-stressed rice roots. Plant Soil. 2015;387(1–2):323–336. [Google Scholar]
21.Jaroslav P, Novák J, Koukalová V, Luklová M, Bretislav B, Martin C. Cytokinin at the crossroads of abiotic stress signalling pathways. Int J Mol Sci. 2018;19(8):2450. [DOI] [PMC free article] [PubMed] [Google Scholar]
22.Mok DW, Mok MC. CYTOKININ METABOLISM AND ACTION. Annu Rev Plant Physiol Plant Mol Biol. 2001;52:89–118. doi: 10.1146/annurev.arplant.52.1.89 [DOI] [PubMed] [Google Scholar]
23.Du L, Jiao F, Chu J, Jin G, Chen M, Wu P. The two-component signal system in rice (Oryza sativa L.): a genome-wide study of cytokinin signal perception and transduction. Genomics. 2007;89(6):697–707. doi: 10.1016/j.ygeno.2007.02.001 [DOI] [PubMed] [Google Scholar]
24.Ishida K, Yamashino T, Mizuno T. Expression of the cytokinin-induced type-A response regulator gene ARR9 is regulated by the circadian clock in Arabidopsis thaliana. Biosci Biotechnol Biochem. 2008;72(11):3025–3029. doi: 10.1271/bbb.80402 [DOI] [PubMed] [Google Scholar]
25.Xu J, Zhang M, Liu G, Yang X, Hou X. Comparative transcriptome profiling of chilling stress responsiveness in grafted watermelon seedlings. Plant Physiol Biochem. 2016;109:561–570. doi: 10.1016/j.plaphy.2016.11.002 [DOI] [PubMed] [Google Scholar]
26.Buti M, Baldoni E, Formentin E, Milc J, Francia E. A meta-analysis of comparative transcriptomic data reveals a set of key genes involved in the tolerance to abiotic stresses in rice. Int J Mol Sci. 2019;20(22):5662. doi: 10.3390/ijms20225662 [DOI] [PMC free article] [PubMed] [Google Scholar]
27.Jaglo-Ottosen R. K. Arabidopsis CBF1 Overexpression Induces COR Genes and Enhances Freezing Tolerance. Science. 1998;280(5360):104–106. doi: 10.1126/science.280.5360.104 [DOI] [PubMed] [Google Scholar]
28.Ding Y, Li H, Zhang X, Xie Q, Gong Z, Yang S. OST1 kinase modulates freezing tolerance by enhancing ICE1 stability in Arabidopsis. Dev Cell. 2015;32(3):278–289. doi: 10.1016/j.devcel.2014.12.023 [DOI] [PubMed] [Google Scholar]
29.Ding Y, Jia Y, Shi Y, Zhang X, Song C, Gong Z, et al. OST1-mediated BTF3L phosphorylation positively regulates CBFs during plant cold responses. EMBO J. 2018;37(8):e98228. doi: 10.15252/embj.201798228 [DOI] [PMC free article] [PubMed] [Google Scholar]
30.Guo H, Wu T, Li S, He Q, Deng H. The methylation patterns and transcriptional responses to chilling stress at the seedling stage in rice. Int J Mol Sci. 2019;20(20):5089. [DOI] [PMC free article] [PubMed] [Google Scholar]
31.Lim CW, Baek W, Han SW, Lee SC. Arabidopsis PYL8 plays an important role for ABA signaling and drought stress responses. Plant Pathol J. 2013;29(4):471–476. doi: 10.5423/PPJ.NT.07.2013.0071 [DOI] [PMC free article] [PubMed] [Google Scholar]
32.Walter P, Ron D. The unfolded protein response: from stress pathway to homeostatic regulation. Science. 2011;334(6059):1081–1086. doi: 10.1126/science.1209038 [DOI] [PubMed] [Google Scholar]
33.Ning Y, Xie Q, Wang GL. OsDIS1-mediated stress response pathway in rice. Plant Signal Behav. 2014;6(11):1684–1686. [DOI] [PMC free article] [PubMed] [Google Scholar]
34.Wang W, Vinocur B, Shoseyov O, Altman A. Role of plant heat-shock proteins and molecular chaperones in the abiotic stress response. Trends Plant Sci. 2004;9(5):244–252. doi: 10.1016/j.tplants.2004.03.006 [DOI] [PubMed] [Google Scholar]
35.Lindemose SR, O"Shea C, Jensen M, Skriver K. Structure, Function and Networks of Transcription Factors Involved in Abiotic Stress Responses. International Journal of Molecular Sciences. 2013;14(3): 5842–5878. doi: 10.3390/ijms14035842 [DOI] [PMC free article] [PubMed] [Google Scholar]
36.Kizis D, Lumbreras V, Pagès M. Role of AP2/EREBP transcription factors in gene regulation during abiotic stress. Febs Letters. 2001;498(2–3):187–189. doi: 10.1016/s0014-5793(01)02460-7 [DOI] [PubMed] [Google Scholar]
37.Mengiste. The BOTRYTIS SUSCEPTIBLE1 Gene Encodes an R2R3MYB Transcription Factor Protein That Is Required for Biotic and Abiotic Stress Responses in Arabidopsis. Plant Cell. 2003;15(11):2551–2265. doi: 10.1105/tpc.014167 [DOI] [PMC free article] [PubMed] [Google Scholar]
38.Hongyan W, Honglei W, Hongbo S, Xiaoli T. Recent Advances in Utilizing Transcription Factors to Improve Plant Abiotic Stress Tolerance by Transgenic Technology. Frontiers in Plant Science. 2016;7(248):67. [DOI] [PMC free article] [PubMed] [Google Scholar]
39.Jung C, Seo JS, Han SW, Koo YJ, Kim CH, Song SI, et al. Overexpression of AtMYB44 Enhances Stomatal Closure to Confer Abiotic Stress Tolerance in Transgenic Arabidopsis. Plant Physiology. 2008;146(2):623–635. doi: 10.1104/pp.107.110981 [DOI] [PMC free article] [PubMed] [Google Scholar]
40.Al Abdallat A. M., Ayad J. Y., Abu Elenein J. M., Al Ajlouni Z. & Harwood W. A. et al. Overexpression of the transcription factor HvSNAC1 improves drought tolerance in barley (Hordeum vulgare L.). Molecular Breeding. 2014;33(2):401–414. [Google Scholar]
41.Penfield S, Josse EM, Kannangara R, Gilday AD, Halliday KJ, Graham IA. Cold and light control seed germination through the bHLH transcription factor SPATULA. Current Biology. 2005;15(22):1998–2006. doi: 10.1016/j.cub.2005.11.010 [DOI] [PubMed] [Google Scholar]
42.Jingjing Geng, Tonglu Wei, Yue Wang, et al. Overexpression of PtrbHLH, a basic helix-loop-helix transcription factor from Poncirus trifoliata, confers enhanced cold tolerance in pummelo (Citrus grandis) by modulation of H2O2 level via regulating a CAT gene. Tree physiology. 2019;39(12):2045–2054. doi: 10.1093/treephys/tpz081 [DOI] [PubMed] [Google Scholar]
43.Yao P, Sun Z, Li C, Zhao X, Li M, Deng R, et al. Overexpression of Fagopyrum tataricum FtbHLH2 enhances tolerance to cold stress in transgenic Arabidopsis. Plant Physiology and Biochemistry. 2018;125:85–94. doi: 10.1016/j.plaphy.2018.01.028 [DOI] [PubMed] [Google Scholar]
44.Wang YJ, Zhang ZG, He XJ, Zhou HL, Wen YX, Dai JX, et al. A rice transcription factor OsbHLH1 is involved in cold stress response. Theoretical & Applied Genetics. 2003;107(8):1402–1409. [DOI] [PubMed] [Google Scholar]
45.Feng X-M, Zhao Q, Zhao L-L, Qiao Y, Xie X-B, Li H-F, et al. The cold-induced basic helix-loop-helix transcription factor gene MdCIbHLH1 encodes an ICE-like protein in apple. Bmc Plant Biology. 2012;12:22. doi: 10.1186/1471-2229-12-22 [DOI] [PMC free article] [PubMed] [Google Scholar]
46.Luo BX, Xiao ZY, Xiao GY. Transgenic Rice with Bar and Osb HLH1 Genes and Its Agronomic Trait Analyses. Journal of Agricultural Biotechnology. 2012;20(1):30–37. [Google Scholar]
47.Xia C, Gong Y, Chong K, Xu Y. Phosphatase OsPP2C27 directly dephosphorylates OsMAPK3 and OsbHLH002 to negatively regulate cold tolerance in rice. Plant, Cell & Environment.2021; 44(2):491–505. doi: 10.1111/pce.13938 [DOI] [PubMed] [Google Scholar]
48.Wei K, Pan S, Li Y. Functional Characterization of Maize C2H2 Zinc-Finger Gene Family. Plant Molecular Biology Reporter. 2016;34(4):761–776. [Google Scholar]
49.Yan-Chao Han, Chang-Chun Fu. Cold-inducible MaC2H2s are associated with cold stress response of banana fruit via regulating MaICE1. Plant Cell Reports. 2019;38(5):673–680. doi: 10.1007/s00299-019-02399-w [DOI] [PubMed] [Google Scholar]
50.Guo-Hong Yu, Lin-Lin Jiang, Xue-Feng Ma, et al. A soybean C2H2-type zinc finger gene GmZF1 enhanced cold tolerance in transgenic Arabidopsis. PloS one. 2014;9(10):e109399. doi: 10.1371/journal.pone.0109399 [DOI] [PMC free article] [PubMed] [Google Scholar]
51.Huang L, Hong Y, Zhang H, Li D, Song F. Rice NAC transcription factor ONAC095 plays opposite roles in drought and cold stress tolerance. Bmc Plant Biology. 2016;16(1):203. doi: 10.1186/s12870-016-0897-y [DOI] [PMC free article] [PubMed] [Google Scholar]
52.Hu H, You J, Fang Y, Zhu X, Qi Z, Xiong L. Characterization of transcription factor gene SNAC2 conferring cold and salt tolerance in rice. Plant Molecular Biology. 2010;72(4–5):567–568. [DOI] [PubMed] [Google Scholar]
53.Pandiyan M, Krishnan SR, Ramanujam P, Manikandan R. Global Transcriptome Analysis of Combined Abiotic Stress Signaling Genes Unravels Key Players in Oryza sativa L.: An In silico Approach. Frontiers in Plant Science. 2017;8:759. doi: 10.3389/fpls.2017.00759 [DOI] [PMC free article] [PubMed] [Google Scholar]
54.Wang J, Chen Z, Zhang Q, Meng S, Wei C. The NAC transcription factors OsNAC20 and OsNAC26 regulate starch and storage protein synthesis. Plant physiology. 2020; 184(4):1775–1791. doi: 10.1104/pp.20.00984 [DOI] [PMC free article] [PubMed] [Google Scholar]

PLoS One. doi: 10.1371/journal.pone.0261822.r001

Decision Letter 0

Jian Zhang

23 Jun 2021

PONE-D-21-12476

Comparative transcriptome analysis of the cold resistance of the sterile rice line 33S

PLOS ONE

Dear Dr. Zhu,

Thank you for submitting your manuscript to PLOS ONE. After careful consideration, we feel that it has merit but does not fully meet PLOS ONE’s publication criteria as it currently stands. Therefore, we invite you to submit a revised version of the manuscript that addresses the points raised during the review process.

Please submit your revised manuscript by Jul 26 2021 11:59PM. If you will need more time than this to complete your revisions, please reply to this message or contact the journal office at plosone@plos.org. When you're ready to submit your revision, log on to https://www.editorialmanager.com/pone/ and select the 'Submissions Needing Revision' folder to locate your manuscript file.

Please include the following items when submitting your revised manuscript:

A rebuttal letter that responds to each point raised by the academic editor and reviewer(s). You should upload this letter as a separate file labeled 'Response to Reviewers'.
A marked-up copy of your manuscript that highlights changes made to the original version. You should upload this as a separate file labeled 'Revised Manuscript with Track Changes'.
An unmarked version of your revised paper without tracked changes. You should upload this as a separate file labeled 'Manuscript'.

If you would like to make changes to your financial disclosure, please include your updated statement in your cover letter. Guidelines for resubmitting your figure files are available below the reviewer comments at the end of this letter.

If applicable, we recommend that you deposit your laboratory protocols in protocols.io to enhance the reproducibility of your results. Protocols.io assigns your protocol its own identifier (DOI) so that it can be cited independently in the future. For instructions see: http://journals.plos.org/plosone/s/submission-guidelines#loc-laboratory-protocols. Additionally, PLOS ONE offers an option for publishing peer-reviewed Lab Protocol articles, which describe protocols hosted on protocols.io. Read more information on sharing protocols at https://plos.org/protocols?utm_medium=editorial-email&utm_source=authorletters&utm_campaign=protocols.

We look forward to receiving your revised manuscript.

Kind regards,

Jian Zhang

Academic Editor

PLOS ONE

Journal Requirements:

When submitting your revision, we need you to address these additional requirements.

1. Please ensure that your manuscript meets PLOS ONE's style requirements, including those for file naming. The PLOS ONE style templates can be found at

https://journals.plos.org/plosone/s/file?id=wjVg/PLOSOne_formatting_sample_main_body.pdf and

https://journals.plos.org/plosone/s/file?id=ba62/PLOSOne_formatting_sample_title_authors_affiliations.pdf

2. We suggest you thoroughly copyedit your manuscript for language usage, spelling, and grammar. If you do not know anyone who can help you do this, you may wish to consider employing a professional scientific editing service.

Whilst you may use any professional scientific editing service of your choice, PLOS has partnered with both American Journal Experts (AJE) and Editage to provide discounted services to PLOS authors. Both organizations have experience helping authors meet PLOS guidelines and can provide language editing, translation, manuscript formatting, and figure formatting to ensure your manuscript meets our submission guidelines. To take advantage of our partnership with AJE, visit the AJE website (http://learn.aje.com/plos/) for a 15% discount off AJE services. To take advantage of our partnership with Editage, visit the Editage website (www.editage.com) and enter referral code PLOSEDIT for a 15% discount off Editage services. If the PLOS editorial team finds any language issues in text that either AJE or Editage has edited, the service provider will re-edit the text for free.

Upon resubmission, please provide the following:

The name of the colleague or the details of the professional service that edited your manuscript

A copy of your manuscript showing your changes by either highlighting them or using track changes (uploaded as a *supporting information* file)

A clean copy of the edited manuscript (uploaded as the new *manuscript* file)”

3. We note that Figure 1 in your submission contain copyrighted images. All PLOS content is published under the Creative Commons Attribution License (CC BY 4.0), which means that the manuscript, images, and Supporting Information files will be freely available online, and any third party is permitted to access, download, copy, distribute, and use these materials in any way, even commercially, with proper attribution. For more information, see our copyright guidelines: http://journals.plos.org/plosone/s/licenses-and-copyright.

We require you to either (1) present written permission from the copyright holder to publish these figures specifically under the CC BY 4.0 license, or (2) remove the figures from your submission:

1. You may seek permission from the original copyright holder of Figure 1 to publish the content specifically under the CC BY 4.0 license.

We recommend that you contact the original copyright holder with the Content Permission Form (http://journals.plos.org/plosone/s/file?id=7c09/content-permission-form.pdf) and the following text:

“I request permission for the open-access journal PLOS ONE to publish XXX under the Creative Commons Attribution License (CCAL) CC BY 4.0 (http://creativecommons.org/licenses/by/4.0/). Please be aware that this license allows unrestricted use and distribution, even commercially, by third parties. Please reply and provide explicit written permission to publish XXX under a CC BY license and complete the attached form.”

Please upload the completed Content Permission Form or other proof of granted permissions as an "Other" file with your submission.

In the figure caption of the copyrighted figure, please include the following text: “Reprinted from [ref] under a CC BY license, with permission from [name of publisher], original copyright [original copyright year].

2. If you are unable to obtain permission from the original copyright holder to publish these figures under the CC BY 4.0 license or if the copyright holder’s requirements are incompatible with the CC BY 4.0 license, please either i) remove the figure or ii) supply a replacement figure that complies with the CC BY 4.0 license. Please check copyright information on all replacement figures and update the figure caption with source information. If applicable, please specify in the figure caption text when a figure is similar but not identical to the original image and is therefore for illustrative purposes only.

Additional Editor Comments (if provided):

please carefully address all the questions raised by both reviewers. In particular, the authors should provide more interpretation of the biological significance behind the RNA seq data. e.g. function-known genes involved in low-temperature response, which has been suggested by reviewer 2. The writing needs a thorough revision, as numerous typos, errors could be found in the text, while some unrelated contents should be excluded to make the logic flow clear.

[Note: HTML markup is below. Please do not edit.]

Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

1. Is the manuscript technically sound, and do the data support the conclusions?

The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented.

Reviewer #1: Yes

Reviewer #2: Partly

**********

2. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #1: Yes

Reviewer #2: I Don't Know

**********

3. Have the authors made all data underlying the findings in their manuscript fully available?

The PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified.

Reviewer #1: No

Reviewer #2: Yes

**********

4. Is the manuscript presented in an intelligible fashion and written in standard English?

PLOS ONE does not copyedit accepted manuscripts, so the language in submitted articles must be clear, correct, and unambiguous. Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here.

Reviewer #1: No

Reviewer #2: No

**********

5. Review Comments to the Author

Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters)

Reviewer #1: The manuscript drafted by Xie et al. profiled transcriptome changes of cold-resistant rice variety 33S and cold-sensitive variety Nipponbare in response to 7-days’ cold stress at seedling stage. The comparative analyses identified DEGs and regulatory pathways distinguished between 33S and Nipponbare. The study proposed regulation mechanisms in response to cold stress of rice. However, the manuscript hasn’t met the standard for publication at this moment. A major revision is recommended.

Comments:

1. The abstract should be succinct. The very detailed information, such as the ones in parentheses, are suggested to be excluded from the abstract. Grammar issues found in Abstract.

2. I didn’t see any Tables attached in the manuscript. Table 1, 3, and 4 were mentioned in paper (Table 2 is missing) but not shown.

3. Materials and Methods section needs more detailed descriptions. Such as the ‘RNA sequencing (RNA-seq) data analysis’ section: reference genome version needs to be clarified; No QC step or reads trimming? Line 122 needs citation; Line 124, which method used for p-value correction? What’s key parameters used in Tophat and HTseq?

4. Line 92, the seedling for experiment is ‘fifty-one-week-old seedlings’? That does not make sense at all.

5. Figures, figure legends, and Tables are very messy.

1). No figure legend for Figure 1.

2) current Figure 1 legend is actually for Figure 2. For Figure 2 legend, please add a sentence to clarify ‘N’ and ‘CK’. Line 149-153 is a better legend for figure 2 rather than the one in Line 185-186.

3) Supplementary tables should be consistent with their order appear in paper. Line174-179.

4) Figure 3 C and D, what’s Q-vaule? No ‘red line’ in figure 3 as descripted in it's legend.

Figure 3A, what’s the asterisk indicated?

5) Line 300-301, it should be Figure 2 instead of Figure 1.

6) Figure 5 legend is missing.

6. Line 145, inappropriate statement: ‘no 33S seedlings were affected by low temperature’. Since a large number DEGs were identified, there must be affections in 33S. You could say something like ‘no 33s seedlings died after cold treatment’.

7. I didn’t understand the logic in Line 179-182.

8. Throughout the paper, please make sure gene names are in italic format but not for protein names.

9. The RNAseq data should be deposit in public database.

10. Line 170-172, what’s Q <0.05 mean? And also ‘Differences in gene

expression in the six samples were examined using a threshold…’ is not accurate. DEGs are determined by two conditions not individual sample. Line 172-173 is a better description. Combine line 171-173.

Reviewer #2: The authors tried to investigate the low-temperature response mechanisms by comparative transcriptomic analysis between a TGMS variety (33S) and a cold-sensitive variety (Nipponbare). This study is meaningful for our understanding of low-temperature response mechanisms in rice seedling, as well as genetic improvement of cold-tolerant rice in future. However, the manuscript has to be improved in both science and writing for publication in PLOS ONE.

Major comments:

(1) No tables found in this manuscript.

(2) The analysis is insufficient. The authors performed RNA-Seq analysis, to focus on the biological question, they should focus on the specifically biological processes or DEGs in low-temperature response of 33S in contrast with Nipponbare.

(3) To be more convincing, the authors should also analyze the function-known genes involved in low-temperature response, not just common GO and KEGG analysis.

(4) Some descriptions were unrelated to the topic, and the logic is a little bit confusing. For example, the ARR9 is reported to be involved in cold treatment, but it is responsive to low-temperature treatment in the Nipponbare variety, which is a cold-sensitive variety. This cannot explain why 33S is cold-tolerant.

(5) Several conclusions were over speculative from the RNA-seq data throughout the manuscript. For example, the line 250~252 is not supported by only expression of ARRs, which needs more evidences, such as enrichment of GO or KEGG or others. The authors should draw any conclusion throughout the manuscript, cautiously.

Minor comments:

(1) The English writing need to be polished by a native English speaker or language service to correct spelling and grammar errors. For example, ‘Ehe’ should be ‘The’ in line 40. The first word of cold stress in line 48 should be capitalized. The gene names should be italicized in line 135, line 227~229, line 240~247, line 254, line 287~289, line 320~ 337, etc.

(2) Figure legends and figures should be of good shape. Some figure legends were not detailed, such as the means of green and red dots in line 185 (Figure 2). There were no A, B, and C marked in Figure 1. In Figure 1A, the roots showed shorter than control, which is contradictory with the statistical result of Figure 1B. In Figure 1C, ‘33S-Cold vs 33S-Cold’ should be ‘33S-Cold vs 33S-CK’. The statistical test, such as student’s t-test, should be added in Figure 4. Letter numbers have brackets in Figure 5, which is not observed in other Figures.

(3) The section of ‘Illumina RNA-seq and assembly analyses’ is the most basic for RNA-seq analysis, and was uncorrelated to the topic. It should be deleted to make the manuscript more concise or move to “Materials and Methods” section.

**********

6. PLOS authors have the option to publish the peer review history of their article (what does this mean?). If published, this will include your full peer review and any attached files.

If you choose “no”, your identity will remain anonymous but your review may still be made public.

Do you want your identity to be public for this peer review? For information about this choice, including consent withdrawal, please see our Privacy Policy.

Reviewer #1: No

Reviewer #2: No

[NOTE: If reviewer comments were submitted as an attachment file, they will be attached to this email and accessible via the submission site. Please log into your account, locate the manuscript record, and check for the action link "View Attachments". If this link does not appear, there are no attachment files.]

While revising your submission, please upload your figure files to the Preflight Analysis and Conversion Engine (PACE) digital diagnostic tool, https://pacev2.apexcovantage.com/. PACE helps ensure that figures meet PLOS requirements. To use PACE, you must first register as a user. Registration is free. Then, login and navigate to the UPLOAD tab, where you will find detailed instructions on how to use the tool. If you encounter any issues or have any questions when using PACE, please email PLOS at figures@plos.org. Please note that Supporting Information files do not need this step.

PLoS One. 2022 Jan 14;17(1):e0261822. doi: 10.1371/journal.pone.0261822.r002

Author response to Decision Letter 0

27 Sep 2021

1. Please ensure that your manuscript meets PLOS ONE's style requirements, including those for file naming. The PLOS ONE style templates can be found at

https://journals.plos.org/plosone/s/file?id=wjVg/PLOSOne_formatting_sample_main_body.pdf and

https://journals.plos.org/plosone/s/file?id=ba62/PLOSOne_formatting_sample_title_authors_affiliations.pdf

Reply ：We have modified the style of PLoS One's style requirements.

The name of the colleague or the details of the professional service that edited your manuscript A copy of your manuscript showing your changes by either highlighting them or using track changes (uploaded as a *supporting information* file) . A clean copy of the edited manuscript (uploaded as the new *manuscript* file)”

Reply ：We have completed the revision in AJE.

Reply ：Figure 1 without copyright protection. The pictures and data are obtained by the author in this paper experiment.

Comments:

1. The abstract should be succinct. The very detailed information, such as the ones in parentheses, are suggested to be excluded from the abstract. Grammar issues found in Abs

Reply: we have simplified and modified the syntax of the abstract.

2. I didn’t see any Tables attached in the manuscript. Table 1, 3, and 4 were mentioned in paper (Table 2 is missing) but not shown.

Reply: the form has been placed in the appropriate position in the article.

Reply: Thank you for your suggestions. We have enriched the contents of materials and methods, and added corresponding references.

4. Line 92, the seedling for experiment is ‘fifty-one-week-old seedlings’? That does not make sense at all.

Reply: Sorry, this is a clerical error. We have replaced fifth one week old seeds with fifth one week old seeds.

5. Figures, figure legends, and Tables are very messy.

1). No figure legend for Figure 1.

Reply: the annotation of Figure 1 has been added.

Reply: the description has been added as required and the drawing notes have been modified.

3) Supplementary tables should be consistent with their order appear in paper. Line174-179.

Reply: I'm sorry for our carelessness. Modified as required

4) Figure 3 C and D, what’s Q-vaule? No ‘red line’ in figure 3 as descripted in it's legend.

Figure 3A, what’s the asterisk indicated?

Reply: Q-value has been modified to p-value. The description of the red line has been deleted. The asterisk in Figure 3A has no meaning and has been removed.

5) Line 300-301, it should be Figure 2 instead of Figure 1.

Reply: sorry, it has been modified

6) Figure 5 legend is missing.

Reply: sorry, we have added a drawing note.

Reply: Thank you for your suggestion. We have modified this part according to your suggestion

7. I didn’t understand the logic in Line 179-182.

Reply: Thank you for your suggestion. We have recounted this part.

8. Throughout the paper, please make sure gene names are in italic format but not for protein names.

Reply: we have checked and modified the format in the full text as required.

9. The RNAseq data should be deposit in public database.

Reply: we have submitted data in the public database and provided data acquisition channels in the paper.

10. Line 170-172, what’s Q <0.05 mean? And also ‘Differences in gene

Reply: Thank you for your comments. Q < 0.05 has been revised to P < 0.05. We re described the contents of lines 170-172.

Major comments:

(1) No tables found in this manuscript.

Reply: we have put the picture in the right place according to the text.

Reply: Thank you for your suggestion. We added the analysis of differential genes in the manuscript.

(3) To be more convincing, the authors should also analyze the function-known genes involved in low-temperature response, not just common GO and KEGG analysis.

Reply: Thank you for your suggestion. We analyzed and discussed the known genes involved in hypothermia (such as) in the revised manuscript.

Reply: Thank you for your suggestion. However, the current research results show that the mechanism of plant low temperature tolerance is very complex, and many genes are involved. Although 33S material has stronger adaptability to low temperature than Nipponbare, there must be some common genes responding to low temperature stress at the same time.

Reply: Thank you for your comments. The result data provided in our paper is indeed insufficient. We have modified the description of the conclusion。

Minor comments:

Reply: We apologize for our carelessness. We have carefully checked and revised the full manuscript.

Reply: Thank you for your comments. We have modified the picture format and annotation according to your comments.

Reply: Thank you for your suggestion. We have removed this part.

Attachment

Submitted filename: Response to Reviewers.docx

Click here for additional data file.^{(266.8KB, docx)}

PLoS One. doi: 10.1371/journal.pone.0261822.r003

Decision Letter 1

Jian Zhang

1 Nov 2021

PONE-D-21-12476R1Comparative transcriptome analysis of the cold resistance of the sterile rice line 33SPLOS ONE

Dear Dr. Zhu,

Please submit your revised manuscript by Dec 16 2021 11:59PM. If you will need more time than this to complete your revisions, please reply to this message or contact the journal office at plosone@plos.org. When you're ready to submit your revision, log on to https://www.editorialmanager.com/pone/ and select the 'Submissions Needing Revision' folder to locate your manuscript file.

Please include the following items when submitting your revised manuscript:

A rebuttal letter that responds to each point raised by the academic editor and reviewer(s). You should upload this letter as a separate file labeled 'Response to Reviewers'.
A marked-up copy of your manuscript that highlights changes made to the original version. You should upload this as a separate file labeled 'Revised Manuscript with Track Changes'.
An unmarked version of your revised paper without tracked changes. You should upload this as a separate file labeled 'Manuscript'.

If applicable, we recommend that you deposit your laboratory protocols in protocols.io to enhance the reproducibility of your results. Protocols.io assigns your protocol its own identifier (DOI) so that it can be cited independently in the future. For instructions see: https://journals.plos.org/plosone/s/submission-guidelines#loc-laboratory-protocols. Additionally, PLOS ONE offers an option for publishing peer-reviewed Lab Protocol articles, which describe protocols hosted on protocols.io. Read more information on sharing protocols at https://plos.org/protocols?utm_medium=editorial-email&utm_source=authorletters&utm_campaign=protocols.

We look forward to receiving your revised manuscript.

Kind regards,

Jian Zhang

Academic Editor

PLOS ONE

Journal Requirements:

Please review your reference list to ensure that it is complete and correct. If you have cited papers that have been retracted, please include the rationale for doing so in the manuscript text, or remove these references and replace them with relevant current references. Any changes to the reference list should be mentioned in the rebuttal letter that accompanies your revised manuscript. If you need to cite a retracted article, indicate the article’s retracted status in the References list and also include a citation and full reference for the retraction notice.

Additional Editor Comments:

As you may find from attached, reviewer 2 had no more comments, while reviewer 1 is still not satisfied with some of the data interpretation and requested further revision. I believe this paper will be accepted upon careful revisions.

[Note: HTML markup is below. Please do not edit.]

Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

1. If the authors have adequately addressed your comments raised in a previous round of review and you feel that this manuscript is now acceptable for publication, you may indicate that here to bypass the “Comments to the Author” section, enter your conflict of interest statement in the “Confidential to Editor” section, and submit your "Accept" recommendation.

Reviewer #1: (No Response)

Reviewer #2: All comments have been addressed

**********

2. Is the manuscript technically sound, and do the data support the conclusions?

Reviewer #1: Partly

Reviewer #2: Yes

**********

3. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #1: No

Reviewer #2: N/A

**********

4. Have the authors made all data underlying the findings in their manuscript fully available?

Reviewer #1: Yes

Reviewer #2: Yes

**********

5. Is the manuscript presented in an intelligible fashion and written in standard English?

Reviewer #1: Yes

Reviewer #2: Yes

**********

6. Review Comments to the Author

Reviewer #1: The revised version manuscript entitled with ‘Comparative transcriptome analysis of the cold resistance of the sterile rice line 33S’ was improved and basically addressed most of my concerns. However, a couple of points need to be clarified before acceptation. Especially, please specify criterion used for GO and KEGG enrichment analyses as some key conclusions were drawn from them (Point 2.2 in below).

1. In the abstract section, it uncommon to describe pathway by ‘reduced’ or ‘increased’. It can be replaced by ‘repressed’ or ‘enhanced’.

2. Materials and Methods section:

1) please specify the reference genome version, such as v7 or something else, used for RNAseq analysis.

2). There’s no criterion described for GO and KEGG pathway enrichment analyses. The E value <= 10-5 is expect value during BLAST but not for determining statistical significance for enrichment. I checked Table S8, S9, and S10 as the results for functional enrichment analyses and it seems most terms with p-value >0.05 which indicated statistically unsignificant. Since some conclusions were based on the functional enrichment analyses, please make it clear.

3. Figure 1: the labels for ‘33S’ and ‘Nipponbare’ are wrong; no letters indicated significant difference between comparison, but mentioned in legend; The error bar in Figure1C looked inconsistent with Figure 1B, did you used standard error or standard deviation for error bar?

4. Above Figure 2, on page 7, it should be ‘In contrast, more up-regulated genes were identified in Nipponbare variety’ instead of ‘down-regulated’.

5. Figure 2 legend, ‘|log2FoldChange| >1’ is actually ‘|log2FoldChange| >=1’ to be consistant with Materials and Methods?

6. Figure 3C and D, does the ‘qvalue’ in figure actually mean ‘pvalue’? What’s the ‘rich factor’ indicated?

Reviewer #2: (No Response)

**********

7. PLOS authors have the option to publish the peer review history of their article (what does this mean?). If published, this will include your full peer review and any attached files.

If you choose “no”, your identity will remain anonymous but your review may still be made public.

Do you want your identity to be public for this peer review? For information about this choice, including consent withdrawal, please see our Privacy Policy.

Reviewer #1: No

Reviewer #2: No

PLoS One. 2022 Jan 14;17(1):e0261822. doi: 10.1371/journal.pone.0261822.r004

Author response to Decision Letter 1

6 Dec 2021

6. Review Comments to the Author

1. In the abstract section, it uncommon to describe pathway by ‘reduced’ or ‘increased’. It can be replaced by ‘repressed’ or ‘enhanced’.

Response: Thanks for your suggestion. They were changed (line 31 and line 33, page 2).

2. Materials and Methods section:

1) please specify the reference genome version, such as v7 or something else, used for RNAseq analysis.

Response: the genome we used was GCF_000005425.2_Build_4.0_genomic, and we added it in the M&M.

Response: Thanks for your suggestion, we had corrected these descriptions, only that p<0.05 were described as significant, and those p>0.05 were considered not to enriched. But we still thought the DEGs in such pathways were valuable to reveal the regulation mechanism of cold tolerance. Please see the line 157-164, page 7, the corrections were made.

Response: we both used the standard deviation (SD), and this description was added into figure legends. Actually, the error bar in Figure1C looked inconsistent with Figure 1B, perhaps the root length were affected by cold leading to bigger difference.

4. Above Figure 2, on page 7, it should be ‘In contrast, more up-regulated genes were identified in Nipponbare variety’ instead of ‘down-regulated’.

Response: Thanks, it has been changed.

5. Figure 2 legend, ‘|log2FoldChange| >1’ is actually ‘|log2FoldChange| >=1’ to be consistant with Materials and Methods?

Response: Thanks, it has been changed.

6. Figure 3C and D, does the ‘qvalue’ in figure actually mean ‘pvalue’? What’s the ‘rich factor’ indicated?

Response: yes, qvalue is a adjust pvalue. And the rich factor means the ratio of DEGs in total specific annotated pathway/term.

Reviewer #2: (No Response)

Attachment

Submitted filename: Minor Revision - Response to Reviewers.docx

Click here for additional data file.^{(14.8KB, docx)}

PLoS One. doi: 10.1371/journal.pone.0261822.r005

Decision Letter 2

Jian Zhang

13 Dec 2021

Comparative transcriptome analysis of the cold resistance of the sterile rice line 33S

PONE-D-21-12476R2

Dear Dr. Zhu,

We’re pleased to inform you that your manuscript has been judged scientifically suitable for publication and will be formally accepted for publication once it meets all outstanding technical requirements.

Within one week, you’ll receive an e-mail detailing the required amendments. When these have been addressed, you’ll receive a formal acceptance letter and your manuscript will be scheduled for publication.

An invoice for payment will follow shortly after the formal acceptance. To ensure an efficient process, please log into Editorial Manager at http://www.editorialmanager.com/pone/, click the 'Update My Information' link at the top of the page, and double check that your user information is up-to-date. If you have any billing related questions, please contact our Author Billing department directly at authorbilling@plos.org.

If your institution or institutions have a press office, please notify them about your upcoming paper to help maximize its impact. If they’ll be preparing press materials, please inform our press team as soon as possible -- no later than 48 hours after receiving the formal acceptance. Your manuscript will remain under strict press embargo until 2 pm Eastern Time on the date of publication. For more information, please contact onepress@plos.org.

Kind regards,

Jian Zhang

Academic Editor

PLOS ONE

Additional Editor Comments (optional):

Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

Reviewer #1: All comments have been addressed

**********

2. Is the manuscript technically sound, and do the data support the conclusions?

Reviewer #1: Yes

**********

3. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #1: Yes

**********

4. Have the authors made all data underlying the findings in their manuscript fully available?

Reviewer #1: Yes

**********

5. Is the manuscript presented in an intelligible fashion and written in standard English?

Reviewer #1: Yes

**********

6. Review Comments to the Author

Reviewer #1: (No Response)

**********

7. PLOS authors have the option to publish the peer review history of their article (what does this mean?). If published, this will include your full peer review and any attached files.

If you choose “no”, your identity will remain anonymous but your review may still be made public.

Do you want your identity to be public for this peer review? For information about this choice, including consent withdrawal, please see our Privacy Policy.

Reviewer #1: No

PLoS One. doi: 10.1371/journal.pone.0261822.r006

Acceptance letter

Jian Zhang

6 Jan 2022

PONE-D-21-12476R2

Comparative transcriptome analysis of the cold resistance of the sterile rice line 33S

Dear Dr. Wang:

I'm pleased to inform you that your manuscript has been deemed suitable for publication in PLOS ONE. Congratulations! Your manuscript is now with our production department.

If your institution or institutions have a press office, please let them know about your upcoming paper now to help maximize its impact. If they'll be preparing press materials, please inform our press team within the next 48 hours. Your manuscript will remain under strict press embargo until 2 pm Eastern Time on the date of publication. For more information please contact onepress@plos.org.

If we can help with anything else, please email us at plosone@plos.org.

Thank you for submitting your work to PLOS ONE and supporting open access.

Kind regards,

PLOS ONE Editorial Office Staff

on behalf of

Professor Jian Zhang

Academic Editor

PLOS ONE

Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

S1 Table. Primers used for qRT-PCR in this study.

(DOC)

Click here for additional data file.^{(36.5KB, doc)}

S2 Table. List of genes upregulated in response to low-temperature treatment in 33S.

(XLS)

Click here for additional data file.^{(105.5KB, xls)}

S3 Table. List of genes downregulated in response to low-temperature treatment in 33S.

(XLS)

Click here for additional data file.^{(155KB, xls)}

S4 Table. List of genes upregulated in response to low-temperature treatment in Nipponbare.

(XLS)

Click here for additional data file.^{(114.5KB, xls)}

S5 Table. List of genes downregulated in response to low-temperature treatment in Nipponbare.

(XLS)

Click here for additional data file.^{(108KB, xls)}

S6 Table. List of 795 DEGs that respond to low temperature only in 33S.

(XLS)

Click here for additional data file.^{(1.8KB, xls)}

S7 Table. GO enrichment analysis of DEGs in 33S.

(XLS)

Click here for additional data file.^{(376.5KB, xls)}

S8 Table. GO enrichment analysis of DEGs in Nipponbare.

(XLS)

Click here for additional data file.^{(196.4KB, xls)}

S9 Table. KEGG pathway enrichment analysis of DEGs in 33S.

(XLS)

Click here for additional data file.^{(61KB, xls)}

S10 Table. KEGG pathway enrichment analysis of DEGs in Nipponbare.

(XLS)

Click here for additional data file.^{(19.6KB, xls)}

S11 Table. TF response to low-temperature treatment of 33S.

(XLS)

Click here for additional data file.^{(35KB, xls)}

S12 Table. TF response to low-temperature treatment of Nipponbare.

(XLS)

Click here for additional data file.^{(36KB, xls)}

Attachment

Submitted filename: Response to Reviewers.docx

Click here for additional data file.^{(266.8KB, docx)}

Attachment

Submitted filename: Minor Revision - Response to Reviewers.docx

Click here for additional data file.^{(14.8KB, docx)}

Data Availability Statement

All relevant data are within the paper and its Supporting information files.

The raw reads produced in this study were deposited in the NCBI SRA with the submission number SUB10060963 under bio Project PRJNA749812.

[pone.0261822.ref001] 1.Andaya VC, Tai TH. Fine mapping of the qCTS12 locus, a major QTL for seedling cold tolerance in rice. Theor Appl Genet. 2006;113(3):467–475. doi: 10.1007/s00122-006-0311-5 [DOI] [PubMed] [Google Scholar]

[pone.0261822.ref002] 2.Fujino K. A major gene for low temperature germinability in rice (Oryza sativa L.). Euphytica. 2004;136(1):63–48. [Google Scholar]

[pone.0261822.ref003] 3.Shinada H, Iwata N, Sato T, Fujino K. Genetical and morphological characterization of cold tolerance at fertilization stage in rice. Breed Sci. 2013;63(2):197–204. doi: 10.1270/jsbbs.63.197 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0261822.ref004] 4.Ma Y, Dai X, Xu Y, Luo W, Zheng X, Zeng D, et al. COLD1 Confers Chilling Tolerance in Rice. Cell. 2015;160(160):1209–1221. doi: 10.1016/j.cell.2015.01.046 [DOI] [PubMed] [Google Scholar]

[pone.0261822.ref005] 5.Normile D. Agricultural research. Reinventing rice to feed the world. Science. 2008;321(5887):330–333. doi: 10.1126/science.321.5887.330 [DOI] [PubMed] [Google Scholar]

[pone.0261822.ref006] 6.Su N, Hu ML, Wu DX, Wu FQ, Fei GL, Lan Y, et al. Disruption of a rice pentatricopeptide repeat protein causes a seedling-specific albino phenotype and its utilization to enhance seed purity in hybrid rice production. Plant Physiol. 2012;159(1):227–238. doi: 10.1104/pp.112.195081 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0261822.ref007] 7.Chen L, Liu YG. Male sterility and fertility restoration in crops. Annu Rev Plant Biol. 2014;65(1):579–606. doi: 10.1146/annurev-arplant-050213-040119 [DOI] [PubMed] [Google Scholar]

[pone.0261822.ref008] 8.Wang Z, Zou Y, Li X, Zhang Q, Chen L, Wu H, et al. Cytoplasmic male sterility of rice with boro II cytoplasm is caused by a cytotoxic peptide and is restored by two related ppr motif genes via distinct modes of mRNA silencing. Plant Cell. 2006;18(3):676–687. doi: 10.1105/tpc.105.038240 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0261822.ref009] 9.Yuan L. Purification and production of foundation seed of rice PGMS and TGMS lines. Hybrid Rice. 1994;6(1):1–3. [Google Scholar]

[pone.0261822.ref010] 10.Singh RB, Virmani SS. Recent progress in the technology and development of hybrid rice in Asia. Rome, Italy: Bulletin De La Commission Internationale Du Riz, FAO; 1994. [Google Scholar]

[pone.0261822.ref011] 11.Yang Q, Liang C, Zhuang W, Li J, Deng H, Deng Q, et al. Characterization and identification of the candidate gene of rice thermo-sensitive genic male sterile gene tms5 by mapping. Planta. 2007;225(2):321–330. doi: 10.1007/s00425-006-0353-6 [DOI] [PubMed] [Google Scholar]

[pone.0261822.ref012] 12.Xie H, Tang G, Yinghong YU, Shenggao WU. Characterization of TGMS line 33S in rice. Agric Sci Technol. 2015;16(4):719–721. [Google Scholar]

[pone.0261822.ref013] 13.Kawahara Y, Bastide M, Hamilton JP, Kanamor H. Improvement of the Oryza sativa Nipponbare reference genome using next generation sequence and optical map data. Rice (New York, NY). 2013;6(1):4. doi: 10.1186/1939-8433-6-4 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0261822.ref014] 14.Langmead B, Salzberg SL. Fast gapped-read alignment with Bowtie 2. Nature Methods. 2012;9(4):357–359. doi: 10.1038/nmeth.1923 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0261822.ref015] 15.Trapnell C, Pachter L, Salzberg SL. TopHat: discovering splice junctions with RNA-Seq. Bioinformatics. 2009;25(9):1105–1111. doi: 10.1093/bioinformatics/btp120 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0261822.ref016] 16.Simon A, Theodor PP, Wolfgang H. HTSeq-a Python framework to work with high-throughput sequencing data. Bioinformatics. 2015;(2):166–169. doi: 10.1093/bioinformatics/btu638 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0261822.ref017] 17.Love MI, Huber W, Anders S. Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2. Genome Biology. 2014;15(12):550. doi: 10.1186/s13059-014-0550-8 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0261822.ref018] 18.Ashburner M, Ball CA, Blake JA, Botstein D, Butler H, Cherry JM, et al. Gene Ontology: tool for the unification of biology. Nature Genetics. 2000; 25(1):25–29. doi: 10.1038/75556 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0261822.ref019] 19.Mao X, Cai T, Olyarchuk JG, Wei L. Automated genome annotation and pathway identification using the KEGG Orthology (KO) as a controlled vocabulary. Bioinformatics. 2005;21(19):3787–3793. doi: 10.1093/bioinformatics/bti430 [DOI] [PubMed] [Google Scholar]

[pone.0261822.ref020] 20.Liu Q, Zheng L, He F, Zhao FJ, Shen Z, Zheng L. Transcriptional and physiological analyses identify a regulatory role for hydrogen peroxide in the lignin biosynthesis of copper-stressed rice roots. Plant Soil. 2015;387(1–2):323–336. [Google Scholar]

[pone.0261822.ref021] 21.Jaroslav P, Novák J, Koukalová V, Luklová M, Bretislav B, Martin C. Cytokinin at the crossroads of abiotic stress signalling pathways. Int J Mol Sci. 2018;19(8):2450. [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0261822.ref022] 22.Mok DW, Mok MC. CYTOKININ METABOLISM AND ACTION. Annu Rev Plant Physiol Plant Mol Biol. 2001;52:89–118. doi: 10.1146/annurev.arplant.52.1.89 [DOI] [PubMed] [Google Scholar]

[pone.0261822.ref023] 23.Du L, Jiao F, Chu J, Jin G, Chen M, Wu P. The two-component signal system in rice (Oryza sativa L.): a genome-wide study of cytokinin signal perception and transduction. Genomics. 2007;89(6):697–707. doi: 10.1016/j.ygeno.2007.02.001 [DOI] [PubMed] [Google Scholar]

[pone.0261822.ref024] 24.Ishida K, Yamashino T, Mizuno T. Expression of the cytokinin-induced type-A response regulator gene ARR9 is regulated by the circadian clock in Arabidopsis thaliana. Biosci Biotechnol Biochem. 2008;72(11):3025–3029. doi: 10.1271/bbb.80402 [DOI] [PubMed] [Google Scholar]

[pone.0261822.ref025] 25.Xu J, Zhang M, Liu G, Yang X, Hou X. Comparative transcriptome profiling of chilling stress responsiveness in grafted watermelon seedlings. Plant Physiol Biochem. 2016;109:561–570. doi: 10.1016/j.plaphy.2016.11.002 [DOI] [PubMed] [Google Scholar]

[pone.0261822.ref026] 26.Buti M, Baldoni E, Formentin E, Milc J, Francia E. A meta-analysis of comparative transcriptomic data reveals a set of key genes involved in the tolerance to abiotic stresses in rice. Int J Mol Sci. 2019;20(22):5662. doi: 10.3390/ijms20225662 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0261822.ref027] 27.Jaglo-Ottosen R. K. Arabidopsis CBF1 Overexpression Induces COR Genes and Enhances Freezing Tolerance. Science. 1998;280(5360):104–106. doi: 10.1126/science.280.5360.104 [DOI] [PubMed] [Google Scholar]

[pone.0261822.ref028] 28.Ding Y, Li H, Zhang X, Xie Q, Gong Z, Yang S. OST1 kinase modulates freezing tolerance by enhancing ICE1 stability in Arabidopsis. Dev Cell. 2015;32(3):278–289. doi: 10.1016/j.devcel.2014.12.023 [DOI] [PubMed] [Google Scholar]

[pone.0261822.ref029] 29.Ding Y, Jia Y, Shi Y, Zhang X, Song C, Gong Z, et al. OST1-mediated BTF3L phosphorylation positively regulates CBFs during plant cold responses. EMBO J. 2018;37(8):e98228. doi: 10.15252/embj.201798228 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0261822.ref030] 30.Guo H, Wu T, Li S, He Q, Deng H. The methylation patterns and transcriptional responses to chilling stress at the seedling stage in rice. Int J Mol Sci. 2019;20(20):5089. [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0261822.ref031] 31.Lim CW, Baek W, Han SW, Lee SC. Arabidopsis PYL8 plays an important role for ABA signaling and drought stress responses. Plant Pathol J. 2013;29(4):471–476. doi: 10.5423/PPJ.NT.07.2013.0071 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0261822.ref032] 32.Walter P, Ron D. The unfolded protein response: from stress pathway to homeostatic regulation. Science. 2011;334(6059):1081–1086. doi: 10.1126/science.1209038 [DOI] [PubMed] [Google Scholar]

[pone.0261822.ref033] 33.Ning Y, Xie Q, Wang GL. OsDIS1-mediated stress response pathway in rice. Plant Signal Behav. 2014;6(11):1684–1686. [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0261822.ref034] 34.Wang W, Vinocur B, Shoseyov O, Altman A. Role of plant heat-shock proteins and molecular chaperones in the abiotic stress response. Trends Plant Sci. 2004;9(5):244–252. doi: 10.1016/j.tplants.2004.03.006 [DOI] [PubMed] [Google Scholar]

[pone.0261822.ref035] 35.Lindemose SR, O"Shea C, Jensen M, Skriver K. Structure, Function and Networks of Transcription Factors Involved in Abiotic Stress Responses. International Journal of Molecular Sciences. 2013;14(3): 5842–5878. doi: 10.3390/ijms14035842 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0261822.ref036] 36.Kizis D, Lumbreras V, Pagès M. Role of AP2/EREBP transcription factors in gene regulation during abiotic stress. Febs Letters. 2001;498(2–3):187–189. doi: 10.1016/s0014-5793(01)02460-7 [DOI] [PubMed] [Google Scholar]

[pone.0261822.ref037] 37.Mengiste. The BOTRYTIS SUSCEPTIBLE1 Gene Encodes an R2R3MYB Transcription Factor Protein That Is Required for Biotic and Abiotic Stress Responses in Arabidopsis. Plant Cell. 2003;15(11):2551–2265. doi: 10.1105/tpc.014167 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0261822.ref038] 38.Hongyan W, Honglei W, Hongbo S, Xiaoli T. Recent Advances in Utilizing Transcription Factors to Improve Plant Abiotic Stress Tolerance by Transgenic Technology. Frontiers in Plant Science. 2016;7(248):67. [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0261822.ref039] 39.Jung C, Seo JS, Han SW, Koo YJ, Kim CH, Song SI, et al. Overexpression of AtMYB44 Enhances Stomatal Closure to Confer Abiotic Stress Tolerance in Transgenic Arabidopsis. Plant Physiology. 2008;146(2):623–635. doi: 10.1104/pp.107.110981 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0261822.ref040] 40.Al Abdallat A. M., Ayad J. Y., Abu Elenein J. M., Al Ajlouni Z. & Harwood W. A. et al. Overexpression of the transcription factor HvSNAC1 improves drought tolerance in barley (Hordeum vulgare L.). Molecular Breeding. 2014;33(2):401–414. [Google Scholar]

[pone.0261822.ref041] 41.Penfield S, Josse EM, Kannangara R, Gilday AD, Halliday KJ, Graham IA. Cold and light control seed germination through the bHLH transcription factor SPATULA. Current Biology. 2005;15(22):1998–2006. doi: 10.1016/j.cub.2005.11.010 [DOI] [PubMed] [Google Scholar]

[pone.0261822.ref042] 42.Jingjing Geng, Tonglu Wei, Yue Wang, et al. Overexpression of PtrbHLH, a basic helix-loop-helix transcription factor from Poncirus trifoliata, confers enhanced cold tolerance in pummelo (Citrus grandis) by modulation of H2O2 level via regulating a CAT gene. Tree physiology. 2019;39(12):2045–2054. doi: 10.1093/treephys/tpz081 [DOI] [PubMed] [Google Scholar]

[pone.0261822.ref043] 43.Yao P, Sun Z, Li C, Zhao X, Li M, Deng R, et al. Overexpression of Fagopyrum tataricum FtbHLH2 enhances tolerance to cold stress in transgenic Arabidopsis. Plant Physiology and Biochemistry. 2018;125:85–94. doi: 10.1016/j.plaphy.2018.01.028 [DOI] [PubMed] [Google Scholar]

[pone.0261822.ref044] 44.Wang YJ, Zhang ZG, He XJ, Zhou HL, Wen YX, Dai JX, et al. A rice transcription factor OsbHLH1 is involved in cold stress response. Theoretical & Applied Genetics. 2003;107(8):1402–1409. [DOI] [PubMed] [Google Scholar]

[pone.0261822.ref045] 45.Feng X-M, Zhao Q, Zhao L-L, Qiao Y, Xie X-B, Li H-F, et al. The cold-induced basic helix-loop-helix transcription factor gene MdCIbHLH1 encodes an ICE-like protein in apple. Bmc Plant Biology. 2012;12:22. doi: 10.1186/1471-2229-12-22 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0261822.ref046] 46.Luo BX, Xiao ZY, Xiao GY. Transgenic Rice with Bar and Osb HLH1 Genes and Its Agronomic Trait Analyses. Journal of Agricultural Biotechnology. 2012;20(1):30–37. [Google Scholar]

[pone.0261822.ref047] 47.Xia C, Gong Y, Chong K, Xu Y. Phosphatase OsPP2C27 directly dephosphorylates OsMAPK3 and OsbHLH002 to negatively regulate cold tolerance in rice. Plant, Cell & Environment.2021; 44(2):491–505. doi: 10.1111/pce.13938 [DOI] [PubMed] [Google Scholar]

[pone.0261822.ref048] 48.Wei K, Pan S, Li Y. Functional Characterization of Maize C2H2 Zinc-Finger Gene Family. Plant Molecular Biology Reporter. 2016;34(4):761–776. [Google Scholar]

[pone.0261822.ref049] 49.Yan-Chao Han, Chang-Chun Fu. Cold-inducible MaC2H2s are associated with cold stress response of banana fruit via regulating MaICE1. Plant Cell Reports. 2019;38(5):673–680. doi: 10.1007/s00299-019-02399-w [DOI] [PubMed] [Google Scholar]

[pone.0261822.ref050] 50.Guo-Hong Yu, Lin-Lin Jiang, Xue-Feng Ma, et al. A soybean C2H2-type zinc finger gene GmZF1 enhanced cold tolerance in transgenic Arabidopsis. PloS one. 2014;9(10):e109399. doi: 10.1371/journal.pone.0109399 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0261822.ref051] 51.Huang L, Hong Y, Zhang H, Li D, Song F. Rice NAC transcription factor ONAC095 plays opposite roles in drought and cold stress tolerance. Bmc Plant Biology. 2016;16(1):203. doi: 10.1186/s12870-016-0897-y [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0261822.ref052] 52.Hu H, You J, Fang Y, Zhu X, Qi Z, Xiong L. Characterization of transcription factor gene SNAC2 conferring cold and salt tolerance in rice. Plant Molecular Biology. 2010;72(4–5):567–568. [DOI] [PubMed] [Google Scholar]

[pone.0261822.ref053] 53.Pandiyan M, Krishnan SR, Ramanujam P, Manikandan R. Global Transcriptome Analysis of Combined Abiotic Stress Signaling Genes Unravels Key Players in Oryza sativa L.: An In silico Approach. Frontiers in Plant Science. 2017;8:759. doi: 10.3389/fpls.2017.00759 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0261822.ref054] 54.Wang J, Chen Z, Zhang Q, Meng S, Wei C. The NAC transcription factors OsNAC20 and OsNAC26 regulate starch and storage protein synthesis. Plant physiology. 2020; 184(4):1775–1791. doi: 10.1104/pp.20.00984 [DOI] [PMC free article] [PubMed] [Google Scholar]

PERMALINK

Comparative transcriptome analysis of the cold resistance of the sterile rice line 33S

Hongjun Xie

Mingdong Zhu

Yaying Yu

Xiaoshan Zeng

Guohua Tang

Yonghong Duan

Jianlong Wang

Yinghong Yu

Roles

Abstract

Introduction

Materials and methods

Plant materials and stress treatment

RNA extraction and library construction

RNA sequencing (RNA-seq) data analysis

Availability of data and materials

Functional annotation of DEGs

RT-qPCR validation

Results and discussion

33S is more cold tolerant than Nipponbare

Fig 1. Phenotype of 33S and Nipponbare after exposed to cold treatment.

Identification of DEGs and functional classification

Fig 2. Number of DEGs after low temperature treatment in 33S and Nipponbare.

Fig 3. Functional analysis of cold responsive genes.

Validation of transcriptome data by RT-qPCR analyses

Fig 4. RT-qPCR verification of expression profiles obtained through RNA-seq.

Low-temperature-responsive genes involved in hormone signal transduction

Table 1. List of DEGs enriched in plant hormone signal transduction.

Low-temperature-responsive genes involved in protein processing in the ER

Table 2. List of DEGs enriched in protein processing in endoplasmic reticulum pathway.

Low temperature-responsive transcription factors

Table 3. Transcription factors response to low temperature treatment in 33S and Nipponbare.

33S recruits specific DEGs to enhance its tolerance to cold stress

Fig 5. Functional analysis and metabolism overview of specific DEGs in 33S in response to cold stress.

Conclusions

Supporting information

Data Availability

Funding Statement

References

Decision Letter 0

Jian Zhang

Roles

Author response to Decision Letter 0

Decision Letter 1

Jian Zhang

Roles

Author response to Decision Letter 1

Decision Letter 2

Jian Zhang

Roles

Acceptance letter

Jian Zhang

Roles

Associated Data

Supplementary Materials

Data Availability Statement

ACTIONS

PERMALINK

RESOURCES

Similar articles

Cited by other articles

Links to NCBI Databases