Abstract Background Cold is a significant limiting factor in productivity, particularly in northwestern and eastern China. Calcium-Dependent Protein Kinases (CDPKs), a primary calcium signaling sensor in plants, play an important role in their response to cold. Snow lotus (Sasussured involucrata Kar L) is a plant that thrives in harsh climates and grows in northwest China. However, there were no reports on the transcriptome of OE-SikCDPK1 transgenic tobacco in response to cold. Results When exposed to cold stress, OE-SikCDPK1 plants displayed a cold-tolerant phenotype compared to non-transgenic tobacco. Under cold conditions, relative water content reduced, relative conductivity increased, malondialdehyde levels rose, and cold-responsive gene expression increased. The OE-SikCDPK1 gene and non-transgenic tobacco were employed for research purposes. The transcriptome of leaves was sequenced using the HISAT2 sequencing platform, and the data were used to examine gene function annotation and differentially expressed genes (DEGs). 53,022 DEGs in tobacco leaves under cold treatment were obtained. The GO enrichment results revealed that it was enriched for biological-process, defense response and other processes under cold stress. The KEGG pathway enrichment analysis revealed that the metabolic pathways of significant enrichment of DEGs under cold stress mainly involved MAPK signaling pathway transduction. The transcription factor identification results showed that the transcription factors with the largest number of differential expressions under cold treatment were mainly from WRKY, AP2, MYB, bHLH, NAC and other transcription factor families. Conclusion The cold tolerance mechanism of snow lotus SikCDPK1 was comprehensively analyzed at the transcriptional level for the first time using RNA-seq technology. This study demonstrates that SikCDPK1 can respond to cold by participating in the MAPK signaling pathway and regulating the expression levels of transcription factors, including WRKY, AP2, MYB, bHLH, and NAC. These results offer valuable insights for further exploration of the cold tolerance mechanism associated with SikCDPK1. Keywords: Cold, SikCDPK1, Transcriptome sequencing, RNA-seq Introduction Plants face numerous environmental challenges, including drought, salinity, and temperature extremes, both cold and heat [[26]1–[27]4]. Cold stress is a significant global environmental factor that limits plant growth, development, yield, and geographical distribution, making it one of the most prevalent abiotic stresses. The initial response of plants to cold stress involves rapid increases in cytosolic [Ca^2+] levels [[28]5]. Subsequently, various signaling cascades enable plants to regulate the transcription of specific genes, thereby modulating their metabolism and physiology to adapt to cold conditions [[29]6, [30]7]. However, the molecular mechanisms by which key genes regulate calcium signaling in response to cold stress in snow lotus remain unknown. Plant response to cold stress encompasses regulation at multiple levels, including metabolic changes such as sugar and amino acid accumulation, as well as the C-repeat binding factor (CBF)/dehydration responsive element binding factor (DREB) response pathways [[31]8]. Given that cold conditions can lead to cellular dehydration, it is not surprising that various signaling pathways aimed at preventing cellular dehydration overlap following exposure to this environmental stressor. For instance, stress-induced responses are coordinated by members of the transcription factor (TF) family, including WRKY, MYB, APETALA 2/ethylene response element binding protein (AP2/EREBP), NAC, and the basic leucine zipper (bZIP) family [[32]9]. The production of osmoprotectants, such as cottonseed, alginose, fructose, proline, and glycine betaine, is common among a wide range of plant species under cold stress and serves to stabilize proteins and cellular structure [[33]10]. Plant transcriptome sequencing technologies can provide more comprehensive and rapid access to the expression information of all mRNA sequences in plant tissues. In recent years, the rapid development of sequencing technologies, especially the new generation of high-throughput sequencing technologies, has enabled them to better understand signaling and cold resistance-related genes in various plants in cold environments, and to help identify and analyze transcriptomes [[34]11]. In some non-model plants or plants without reference genome sequences, transcriptome sequencing allows rapid and efficient access to functional gene information [[35]12]. Since 2000, when Shinozaki et al. reported altered expression levels of a range of genes in cold environments, genetic information has been investigated in many plants [[36]13]. To resist adversity, plants adapt to the changing external environment by adjusting their own physiological and biochemical pathways. Once a signal is received from an abiotic stimulus, defence mechanisms are activated. The signal is transmitted through the signal transduction system and then through signaling cascade and amplification of transcription factors (TFs) to downstream functional genes [[37]14]. Xinjiang Tianshan snow lotus is an excellent extreme climate tolerant plant, and the study of adversity genes associated with it is of great significance to improve plant resistance. In the early stage, our group overexpressed SikCDPK1 and found it is cold-tolerant [[38]15]. However, current studies on the mechanism of OE-SikCDPK1 tobacco response to cold mainly focus on physiological and biochemical aspects, while transcriptome analysis of OE-SikCDPK1 tobacco response to cold and molecular mechanisms of SikCDPK1 adaptation to cold abiotic stress have not been reported. Transcriptome analysis was performed on SikCDPK1 tobacco, and the genes related to SikCDPK1 regulating cold stress were discovered, and the molecular mechanism of SikCDPK1 resistance to stress was explored. In this study, we performed physiological of plants exposed to cold stress to characterize the adaptation of tobacco to stress. Meanwhile, through high-throughput transcriptome sequencing, we preliminarily obtained the gene expression signature and deciphered the potential mechanism of OE-SikCDPK1 tobacco in response to cold, which provided a theoretical basis for in-depth study of the involvement of SikCDPK1 in stress regulation. Our findings deepen our understanding of plant adaptation to stress and provide valuable information for plant chilling tolerance enhancement. Materials & methods Plant materials and different treatments Seeds of Nicotiana tabacum ‘NC89’ and pure ‘OE-SikCDPK1’ transgenic tobacco of T3 generation were used in current investigation. Germinant Nicotiana tabacum were transferred to pots containing vermiculite in the greenhouse at 28/20°C under 16-h light/8-h dark photoperiod (60% relative humidity). When the tobacco grew to six leaves and one heart, the following treatments were set up, respectively. Cold treatment: transgenic and non-transgenic plants, treated at -4 °C for 3 h. The fourth true leaf of tobacco was collected as a sample and quickly packed in a 5 ml sterile and enzyme-free centrifuge tube. These samples were frozen in liquid nitrogen immediately and stored at -80 °C and sent to Beijing Bemac Bioinformatics Co. Three biological repeats in each treatment were performed. The sampling protocol is shown in Table [39]1. Table 1. Sampling scheme of different genotypes of tobacco under different treatments Samples Treatment Normal -4℃ Non-transgeic 3 3 Trans-SikCDPK1 3 3 [40]Open in a new tab Physiological index measurement One gram of fresh leaves was taken and weighed on an electrical scale to determine fresh weight. After that, they were dipped in distilled water (H[2]O) for 24 h. Then leaves were removed from the water, excess water was wiped out and leaves were weighed again to determine turgid weight. Afterward, the leaves were sun-dried and packed in small paper bags and oven dried at 70 °C for 24 h to determine the dry weight. Relative water content (RWC) was determined with this formula: RWC = (FW-DW)/(TW-DW) × 100 [[41]16]. Half a gram of fresh leaf sample (chopped into small pieces) was dipped in distilled water for half an hour, and REC1 was measured by using an REC meter. REC2 was recorded by heating the samples in a water bath at 90 °C for 50 min. The final value of relative electricity conductivity (REC; %) was determined with this formula: REC%=(REC1 ÷ REC2) ×100 [[42]17]. Malondialdehyde (MDA) content was measured according to (Schmedes and Hølmer, 1989) with slight modifications. Powdered samples (0.2 g) were homogenized in 10 mL of 10% (w/v) trichloroacetic acid (TCA). Homogenate was centrifuged at 9660× g for 10 min. Then, 2 mL of the supernatant was mixed with 2 mL of 10% (w/v) TCA containing 0.6% (w/v) of thiobarbituric acid (TBA) and incubated at 100 °C for 20 min, and then quickly cooled on ice followed by centrifugation at 9660× g for 10 min. Absorbance at 532, 600, and 450 nm was measured using Jenway 7305 UV/Visible Spectrometer (Jenway, London, UK). The MDA content was calculated according to the formula MDA content (µM/gFW) = 6.45 (OD [532] − OD [600]) − 0.56 OD [450] [[43]18]. RNA extraction, library preparation, RNA-Seq, and sequence assembly RNA extraction was performed on 12 samples for RNA-Seq analysis. RNA was extracted using RNA kits, and RNA quality and concentration were determined by agarose gel electrophoresis and spectrophotometer, while RNA was accurately quantified using Agilent 2100 Bio analyzer RNA Nano chip. After the samples were tested and qualified, library construction was performed, and the specific steps can be referred to Fig. [44]1. Fig. 1. Fig. 1 [45]Open in a new tab Transcriptome sequencing process RNA-Seq data analysis The library quality is de-evaluated by screening the downstream data, obtaining Clean Data, and performing sequence comparison with the specified reference genome to obtain Mapped Data. Differential expression analysis, functional annotation and functional enrichment of differentially expressed genes, gene expression related network analysis, etc. are performed based on the expression of genes in different treatment groups. RNA extraction Total RNA was isolated from the leaves of control and cold-stressed tobacco plants using the Pure polysaccharide polyphenol plant total RNA extraction kit (DP441; TianGen; China). RNA quantity and purity were determined spectrophotometrically while RNA integrity was evaluated after electrophoresis in a 1.5% (w/v) agarose gel. Cloning, real-time quantitative PCR (qRT-PCR) analysis of SikCDPK1 Total RNA was extracted from the frozen samples with three replicates using the RNA Prep Pure kit (TIANGEN Biotech) following the manufacture’s recommendations. The first-strand cDNA was synthesized from 2 mg total RNA based on a PrimeScript Reverse Transcriptase Kit (Takara). Based on the sequence of SikCDPK1 (GenBank [46]ALO51437), two pairs of primers were designed in Table [47]2. The primers for the target genes, SikCDPK1-F and SikCDPK1-R, were used in Table [48]2 for PCR amplification. The PCR program was as follows: pre-denaturation at 94 ℃ for 5 min; denaturation at 94 ℃ for 30 s; replication at 62 ℃ for 40 s; extension at 72 ℃ for 1 min and 30 s; 30 cycles. The positive product was named as SikCDPK1, sequenced by Beijing Huada Genetics. Table 2. The primers used in this study Primer name Primer sequence(5’→3’) Purpose SikCDPK1-F GGATCCATGGGGAATACTTGTGTTGGAC Gene clone SikCDPK1-R GTCGACCCGTCGATACCGGAAAAAAC Gene clone GAPDH-F GAPDH-R SikCDPK1-qF SikCDPK1-qR TAGCAAGGATGCTCCCATGTTCGT AAAGGAGCAAGGCAGTTGGTTGTC ATCCCAAACTGCCCTTGTCCTA GAAGATACCCCACCTACCCCTAAC Internal genes primers Internal genes primers Gene expression analysis Gene expression analysis [49]Open in a new tab qRT-PCR was performed using the Light Cycler FastStart DNA Master SYBR Green I Kit (Roche Diagnostics, Indianapolis, IN, USA) and 250 nM of forward and reverse primers in a Light Cycler 2.0 device (Roche Diagnostics) with SikCDPK1 and GAPDH as reference genes, respectively. qPCR conditions were as follows: initial denaturation at 95 °C for 10 min, followed by 40 cycles of 95 °C for 10 s, 62 °C for 5 s, and 72 °C for 12 s. The relative gene expression was evaluated with Light Cycler 4.1 software. There are three replicates for both samples and techniques. Statistical analysis The expression of snow lotus SikCDPK1 gene was calculated using the 2^−∆∆Ct method [[50]19], and the experimental data were subjected to LSD (least significance difference) multiple ANOVA using the SPSS 18.0 software, with the test of significance set at p < 0.05 (significant level) and p < 0.01 (highly significant level), and GraphPad Prism 9.1 was used for graphing. Results Phenotypic and physiological responses to cold stress To explore the cold resistance of SikCDPK1, non-transgenic tobacco was compared with OE-SikCDPK1 tobacco after cold stress, and it was found that the phenotypes of transgenic plants and non-transgenic plants were not much different before and under room temperature conditions. After cold, it was found that the non-transgenic tobacco leaves drooped severely and the leaf color deepened, and the transgenic tobacco also showed drooping, but their top leaves were still vigorous and the leaf color was lighter than that of the non-transgenic, and the wilting degree of transgenic tobacco was weaker than that of the non-transgenic (Fig. [51]2A). Fig. 2. [52]Fig. 2 [53]Open in a new tab Phenotypic and physiological responses of two cultivars (Non-transgeic and OE-SikCDPK1) under control and cold stress conditions. A, The phenotypes of wild type tobacco and transgenic lines after low temperature; B, The expression level of OE-SikCDPK1 in Tobacco. wild type Tobacco; OE1, OE2; C, RWC; D, REC; E, MDA. All data are presented as means ± SE from three independent experimental replicates(*p < 0.05, **p < 0.01)) The quantitative reverse transcription polymerase chain reaction (qRT-PCR) analysis was conducted to assess the expression levels of the SikCDPK1 gene in transgenic OE-SikCDPK1 tobacco plants under cold stress conditions. The results demonstrated a significant upregulation of SikCDPK1 expression in the OE-SikCDPK1 plants compared to the wild-type control under the same cold stress treatment. Specifically, the expression levels of SikCDPK1 increased markedly following exposure to cold stress, indicating that this gene is responsive to low temperatures. The relative expression levels were calculated using the internal reference gene GAPDH for normalization, and the data revealed that SikCDPK1 expression was several times higher in the OE-SikCDPK1 plants compared to wild-type plants at various time points during the cold treatment. This upregulation suggests that SikCDPK1 plays an active role in the plant’s response to cold stress (Fig. [54]2B). The leaf water content of the plant decreases when the plant is subjected to cold stress [[55]20]. Samples were taken before and after cold stress, and the relative water content of leaves was measured. Plants treated with cold showed a decreasing trend in relative water content, while transgenic plants showed a greater difference. As shown in Fig. [56]1B, there was no significant difference in relative water content between transgenic plants and non-transgenic plants at room temperature, 83.72% and 87.64% for non-transgenic plants, and transgenic plants, respectively. After cold, the relative water content was 26.34% for the non-transgenic strain(p < 0.01) (Fig. [57]2C). The relative conductivity of non-transgenic and OE-SikCDPK1 tobacco leaves before cold were 17.89%, 26.14%, respectively, with no significant differences between them (p > 0.05). After letting them to -4℃, the relative conductivity increased in all of them, and after cold, the relative conductivity of non-transgenic tobacco and OE-SikCDPK1 tobacco leaves increased by 47.70%, 18.60%, respectively, indicating that cold damaged cell membranes in all of them, and the difference in the degree of relative conductivity between them was more significant (p < 0.01) (Fig. [58]2D). Before cold treatment, the malondialdehyde (MDA)content of non-transgenic and transgenic types was 0.083 µmol/g and 0.072 µmol/g, respectively. There was no significant difference between the four (p > 0.05). After cold treatment, the malondialdehyde contents of non-transgenic versus transgenic types were 0.287 µmol/g, and transgenic types were 0.119 µmol/g, with significant differences in MDA contents among all four groups (p < 0.01) (Fig. [59]2E), indicating that the MDA accumulation rate of non-transgenic plants was faster than that of transgenic under cold stress. It indicates that the cold tolerance of transgenic plants is stronger than that of non-transgenic plants. Sequencing data output statistics Before performing data analysis, it is important to determine the high quality of these data to ensure the accuracy of the subsequent analysis results. The sequencing results for 12 samples (W1, S1, TW1, TS1) were analyzed, producing 83.52 Gb Clean Data were obtained; then after strict quality assessment and data filtering, the percentage of bases with sequencing quality values greater than 30 (Q30, error rate < 0.1%) in the total sequences was 94.46% and above. The related sequencing data are shown in Table [60]3. Table 3. Statistics of sequencing data Samples Total Reads Mapped Reads Clean reads Clean bases GC Content %≥Q30 W1-1 43,983,806 41,428,086 (94.19%) 21,991,903 6,564,932,834 43.40% 95.54% W1-2 48,893,866 46,277,928 (94.65%) 24,446,933 7,295,693,662 43.23% 95.39% W1-3 48,328,158 46,020,623 (95.23%) 24,164,079 7,213,264,020 43.19% 95.38% S1-1 52,753,366 50,273,498 (95.30%) 26,376,683 7,868,936,914 43.35% 95.36% S1-2 55,431,852 52,720,381 (95.11%) 27,715,926 8,272,644,018 43.66% 95.40% S1-3 40,601,114 38,678,942 (95.27%) 20,300,557 6,060,296,328 43.29% 95.36% TW1-1 41,014,672 38,293,037 (93.36%) 20,507,336 6,133,670,168 42.07% 95.17% TW1-2 44,493,858 39,942,552 (89.77%) 22,246,929 6,656,137,510 42.90% 94.60% TW1-3 41,127,006 38,559,756 (93.76%) 20,563,503 6,144,341,338 44.50% 94.46% TS1-1 46,401,176 37,077,803 (79.91%) 23,200,588 6,942,708,078 44.80% 94.99% TS1-2 52,433,752 49,610,318 (94.62%) 26,216,876 7,845,858,186 43.47% 94.75% TS1-3 43,652,254 41,318,543 (94.65%) 21,826,127 6,531,410,510 44.08% 94.60% [61]Open in a new tab Functional annotation and enrichment analysis of differentially expressed genes The differentially combined eight databases (COG, GO, KEGG, KOG, NR, Pfam, Swiss-Prot and eggNOG) from different treatments were compared and the number of Unigenes obtained was annotated (Table [62]4), notably the NCBI protein sequence database (NR) had a high annotation rate. It provides a reference for subsequent gene function annotation and enrichment. Table 4. Statistical table of the number of functional genes of differentially expressed genes DEG Set Total COG GO KEGG KOG NR Pfam Swiss-Prot eggNOG W1_vs_S1 4631 1,521 3,611 3,201 2,214 4,625 3,718 3,203 3,876 S1_vs_TS1 13,106 5,007 10,950 9,389 7,133 13,090 10,888 9,748 11,372 S1_vs_TW1 15,339 5,373 12,490 10,949 8,343 15,323 12,264 10,864 13,057 W1_vs_TS1 17,042 6,099 14,009 12,175 8,978 17,019 13,955 12,321 14,660 W1_vs_TW1 13,660 4,803 11,222 9,779 7,309 13,641 10,885 9,771 11,665 TW1_vs_TS1 16,432 5,710 13,494 11,759 8,781 16,413 13,485 11,934 14,121 [63]Open in a new tab To further investigate the molecular mechanism of SikCDPK1, transcriptome analysis was performed using RNA-seq sequencing. Gene expression is time-and space-specific, and genes or transcripts with significantly different expression levels under two different conditions are called differentially expressed genes (DEGs). DEGs under cold stress In order to analyze the biological functions and metabolic pathways involved in SikCDPK1 when subjected to stress, five differentially expressed genes were analyzed from the Wayne plot, COG classification plot, GO annotation classification and enrichment plot, and KEGG annotation classification and enrichment plot of differentially expressed genes for the OE-SikCDPK1 lines and non-transgenic lines under room temperature conditions, after cold treatment, combinations were analyzed. To understand how gene expression patterns change in transgenic tobacco under cold stress, we analyzed FPKM (fragments per kilobase per exon per million mapped fragments) values in the transcriptome. In the S1 vs. TS1 comparison group, there were 14,154 DEGs (7157 up-regulated genes and 6997 down-regulated genes). In the TW1 vs. TS1 comparison group, there were 18,293 DEGs (8886 up-regulated genes and 9407 down-regulated genes). In the W1 vs. S1 comparison group, there were 5329 DEGs (2042 up-regulated genes and 3287 down-regulated genes). In the W1 vs. TW1 comparator group, there were 15,246 DEGs (7910 up-regulated and 7336 down-regulated genes). This suggests that these genes play a role in cold resistance in transgenic tobacco (Fig. [64]3A). Fig. 3. [65]Fig. 3 [66]Open in a new tab Comparison of the number of DEGs. A, Bar chart showing the number of up and down regulated genes in different comparisons; B, Venn diagram showing the common and specific DEGs in different conditions In order to identify the differential genes shared between the transgenic and non-transgenic lines under stress, each of the four combinations mentioned above was presented in a Venn diagram. Each ellipse represents the differential genes in a comparative combination (treatment vs. control), and the numbers in the overlapping areas of the ellipse indicate the number of shared differential genes among the corresponding multiple comparative combinations, while the non-overlapping areas indicate the differential genes specific to each comparative combination. A total of 53,022 common DEGs, under room temperature, there were 4746 shared differential genes in the transgenic and non-transgenic combinations; 227 shared differential genes in the transgenic and non-transgenic combinations after cold; 13,573 shared differential genes in the four conditions (Fig. [67]3B). The number of differential genes differed under different treatments, indicating that the affected genes in tobacco transgenic to SikCDPK1 varied with different treatments. GO functional enrichment and analysis In order to better explain the biological functions of DEGs, GO enrichment analysis was carried out for the sets at room temperature, after cold treatment, and all transcripts were classified into three major categories, Biological Process, Molecular Function and Cellular Component (Fig. [68]4A and B). In the classification of biological processes, cell process is the most dominant process; cellular component is dominated by cell and cell part; in the category of molecular function, binding is the most dominant moiety, followed by catalytic activity. The results showed that a total of 21 biological processes 18 cellular components and 15 molecular functions were significantly enriched in these combinations. Fig. 4. [69]Fig. 4 [70]Open in a new tab GO analysis of DEGs. A, Enriched GO terms DEGs in transgenic and non-transgenic; B, Enriched GO terms DEGs after cold stress, the Y and X axes correspond to GO terms and the number of DEGs. C, The 10 most enriched GO terms among the DEGs identified in room temperature; D, The 10 most enriched GO terms among the DEGs identified in cold stress. The Y axis corresponds to the GO annotation, and the X axis shows the enrichment ratio between the number of DEGs enriched in a particular pathway. The color of the dot represents the p value, and the size of the dot represents the number of DEGs mapped to the reference pathway The biological processes, cellular components, and molecular functions of the top 10 significantly enriched genes were analyzed in these two treatment combinations. Analyzed the transcriptomes of differentially expressed (DEGs) transgenic lines before and after cold to identify target down, protein phosphorylation (GO:0006468), defense response (GO:0006952), response to stimulus (GO:0050896), biological regulation (GO:0065007), carbohydrate metabolic process (GO:0005975), cellular metabolic process (GO:0044237), metabolic process (GO:0008152), lipid metabolic process (GO:0006629), methylation (GO:0032259),regulation of transcription, DNA-templated (GO:0006355), organic substance metabolic process (GO:0071704).Transcriptome studies suggest that SikCDPK1 plays a key role in transcriptional reprogramming of cell wall/membrane biogenesis, cell cycle regulation, cell division, energy production and conversion, hormone signaling, lysosomal protein turnover and signal transduction. The main ones were related to stress tolerance, protein phosphorylation, carbon metabolism, and lipid metabolism biological processes. In addition, DEGs were enriched in specific molecular functions, such as protein serine/threonine kinase activity, transcription factor activity, sequence-specific DNA binding, and protein kinase activity related. Thus, the above biological processes drive the molecular functions to act and thus improve plant stress tolerance. KEGG functional enrichment To identify transgenic versus non-transgenic active pathways, the obtained genes were mapped to the pathways in the KEGG database. The DEGs of KEGG pathways were biologically classified into five major categories, namely Cellular Processes, Environmental Information Processing, Genetic Information Processing, Metabolism Organic Systems (OSS). A secondary classification of transgenic and non-transgenic DEGs revealed that the highest number of differentially expressed genes for Environmental adaptation and the lowest number of genes for Membrane transport were found at room temperature, with only 25 genes (Fig. [71]5A). After cold, the highest number of differentially expressed genes was found for Carbohydrate metabolism and the lowest for Nucleotide metabolism (Fig. [72]5B). Fig. 5. [73]Fig. 5 [74]Open in a new tab KEGG analysis of DEGs. A, KEGG classification diagram of differential genes in transgenic and non-transgenic; B, KEGG classification diagram of differential genes after cold stress; C, KEGG enrichment analysis of DEGs under room temperature; D, KEGG enrichment analysis of DEGs under cold stress. The Y axis corresponds to the KEGG pathway, and the X axis shows the enrichment ratio between the number of DEGs enriched in a particular pathway. The color of the dot represents the p value, and the size of the dot represents the number of DEGs mapped to the reference pathway Pathway enrichment analysis of the differential set of transgenic and non-transgenic genes at room temperature revealed that these differential genes were mainly involved in MAPK signaling pathway-plant and plant hormone signal transduction (Fig. [75]5C). After cold treatment, these pathways were also predominantly involved (Fig. [76]5D). In brief, a large number of genes in different pathways are involved in the cold tolerance of SikCDPK1, and the cold tolerance mechanism of SikCDPK1 can be explored in depth from different angles. Transcription factor enrichment Among the differentially expressed genes screened under room temperature conditions, a total of 389 transcription factors were identified in 20 classes of transcription factor families (Fig. [77]6A). Among these 20 gene families, the gene family with the highest number of transcription factors was the WRKY gene family (54), followed by AP2/ERF-ERF, RLK-Pelle_DLSV, MYB, bHLH, and the NAC family was significantly enriched. Among the differentially expressed genes screened after cold treatment, 83 transcription factors were present in 20 gene families (Fig. [78]6B). In conclusion, the transcriptional regulation of transcription factors involved in the regulation of abiotic stress by SikCDPK1 was found to be a key part of the plant response to abiotic stress. Fig. 6. [79]Fig. 6 [80]Open in a new tab Distribution of the DEGs into different transcription factor families during cold stress. A, Under room temperature; B, Under cold stress DEGs involved in MAPK signaling pathway MAPK cascade activation is at the center of a number of signaling pathways, and is an important class of molecules that receives signals converted and transmitted by membrane receptors and carries them into the nucleus, where they play a key role in a number of signaling pathways related to cell proliferation. In unstimulated cells, MAPK is in a quiescent state. When cells are stimulated by growth factors or other factors, MAPK receives activation signals from MAPKK and MAPKKK is activated, exhibiting stepwise phosphorylation. Plant MAPK cascades play pivotal roles in signaling plant defense against pathogen attack. MAPK cascades have also emerged as battlegrounds of plant-pathogen interactions. Activation of MAPKs is one of the earliest signaling events after plant sensing of pathogen/microbe-associated molecular patterns (PAMPs/MAMPs) and pathogen effectors. MAPK cascades are involved in signaling multiple defense responses, including the biosynthesis/signaling of plant stress/defense hormones, reactive oxygen species (ROS) generation, stomatal closure, defense gene activation, phytoalexin biosynthesis, cell wall strengthening, and hypersensitive response (HR) cell death. When plants are exposed to cold, MAPK signaling is critically important for cold tolerance (Fig. [81]7A). Fig. 7. [82]Fig. 7 [83]Open in a new tab Expression pattern analysis of MAPK Signaling pathway related DEGs In this study, 200 DEGs involved in the MAPK signaling pathway were identified from transgenic and non-transgenic genes, and 39 DEGs involved in the MAPK signaling pathway were identified from transgenic and non-transgenic genes, of which 30 were significantly up-regulated in the MAPK signaling pathway. The main included abscisic acid receptor PYR/PYL, lagellin-induced complex of the receptor FLS2/BAK1, a negative player in plant immunity MPK4, the pathogenesis-related protein PR1, RAN1, an evolutionarily conserved small G-protein family, a type of nuclear-localized protein with DNA-binding activity in plants EIN3/EIL, Carbohydrate-binding modules of ChiB, ABA signal transduction include the type 2 C protein phosphatases PP2C, ABA activated SnRK2 kinases, et al. All up-regulated gene show in heatmap(Fig. [84]7B). A, KEGG pathway presenting DEG in MAPK Signaling pathway, red boxes indicate that DEGs were up-regulated under cold stress; B, Heatmap presenting DEGs expression patterns of up-regulated. Discussion SikCDPK1 plays a positive role in conferring cold stress tolerance Plants are sedentary organisms, so the only way for plants to survive in harsh environments is to adapt quickly and efficiently to changes in their surroundings. Cold stress can affect plant growth and development [[85]21]. Plant adaptation to cold stress is a complex process with a range of changes occurring at both the physiological and molecular levels [[86]22]. It was found that snow lotus are cold-tolerant medicinal plants, SikCDPK1 is resistant to adversity, and overexpression of SikCDPK1 significantly increased the cold tolerance of tobacco. Understanding how SikCDPK1 responds to cold stress will provide valuable information and genetic resources for improving cold stress tolerance in plants. The qRT-PCR results provide compelling evidence that the SikCDPK1 gene is integral to enhancing cold tolerance in tobacco plants. The significant increase in SikCDPK1 expression in OE-SikCDPK1 tobacco under cold stress conditions aligns with previous transcriptomic analyses, which identified SikCDPK1 as a key gene involved in cold stress response pathways. The activation of SikCDPK1 may facilitate downstream signaling cascades that regulate other cold-responsive genes, including those involved in osmoprotectant synthesis and stress signaling pathways. The observed upregulation of SikCDPK1 supports the hypothesis that it mediates cold stress responses through transcriptional regulation, contributing to the plant’s ability to cope with adverse environmental conditions. Combining the phenotype of OE-SikCDPK1 tobacco in this study (Fig. [87]2) with the physiological data identified in our previous study, we found that it was affected by cold mainly express in the leaves. In this study, we sequenced the transcriptome of OE-SikCDPK1 tobacco using RNA-seq. The aim was to explore cold signaling perception and cold signaling by SikCDPK1 in response to cold stress at the transcriptional level. Cold stress signal perception and transduction Cold stress can rapidly induce membrane rigidity at microdomains, which affects protein folding and alters the physical state of the membrane. Thus, plant cells can sense cold stress through membrane stiffening, changes in protein/nucleic acid conformation and/or changes in metabolite concentrations [[88]23]. It has been shown that plants subjected to cold stress find increased membrane permeability, leading to leakage of cellular electrolytes of salts and organic acids into the environmental medium, thereby increasing relative electrical conductivity (REC) [[89]24]. Furthermore, MDA is the end product of membrane peroxidation, which is an indicator of membrane damage [[90]25]. Therefore, the cell membrane of transgenic tobacco is first affected by cold stress, with a large amount of osmotic material flowing out of the cell membrane and metabolic imbalance in transgenic tobacco. In addition, the accumulation of malondialdehyde alters the membrane system of the cell membrane. Cold stress-induced second messenger traits can be decoded by different pathways, such as cytoplasmic Ca^2+ and ABA [[91]26]. In this study, high-throughput technology was used to explore the response mechanism of plants to external environmental changes, which can understand the response mechanism of plants to cold stress and effectively screen and mine specific functional genes of plants in response to abiotic stress. In this study, treated DEGs were enriched in the MAPK signaling pathway. GO analysis showed that DEGs were enriched in the overall membrane components, response to oxidative stress and carbohydrate metabolism processes. Under stress conditions, plants can differentiate the normal expression of intracellular genes, change the transcription of protease genes related to plant resistance, increase plant resistance substances, and avoid the damage of cold to plant cells through signal sensing, transduction, and regulation, thus enhancing the resistance of plants to cold. In recent years, there have been some reports on transcriptomic studies of plant response to abiotic stresses, but studies on the genes and molecular regulatory mechanisms of transgenic plants in response to cold stress are still weak. Previous studies have shown that the MAPK cascade response has been reported to translate environmental stimuli into cellular responses and negatively regulate freezing tolerance through phosphorylation of ICE1, a basic helix-loop-helix transcription factor that regulates CBF gene expression [[92]27], which mediates cold-induced transcription and plays a key role in freezing tolerance and cold domestication through binding to C repeat/DRE elements, activation of the MAPK pathway is a key component of the response to cold rapid response, as MPK4, MPK6 and MPK37 are rapidly activated following cold treatment [[93]28]. Transcriptional regulation The cold response in plants is a complex process involving the regulation of a set of transcription factors (TFs) and various genes. Transcriptional regulation plays an important role in the resistance to cold stress. Transcription factors (TFs) can recognize functional elements on the promoters of downstream genes to activate or repress the expression of target genes, resulting in corresponding biochemical and physiological responses that enhance the ability of plants to adapt to cold environments [[94]14]. Cold induces the expression of ethylene response element binding factor/APETALA2 (ERF/AP2)-type transcription factor family genes, and DREB/CBF is a member of the AP2/ERF family [[95]29]. Inducers of CBF expression 1 (ICE1) encode MYC-type basic loop helix (bHLH) transcription factors that can bind to the MYC recognition element in the CBF3 promoter and induce CBF3 expression during cold domestication [[96]30]. ICE-CBF is a key regulatory pathway in response to cold stress. In the present study, the expression of genes encoding TFs such as AP2 and bHLH was significantly altered under cold stress, therefore it is hypothesized that the ICE-CBF pathway is present in OE-SikCDPK1 tobacco in response to cold stress. All DEGs encoding TFs in SikCDPK1-transformed tobacco play a crucial role in cold stress resistance, which may be the main reason for the high cold tolerance of the transgenes. Conclusions In this study, based on phenotypic, physiological experiments and transcriptomic sequencing, we elucidated the expression regulatory pathways of SikCDPK1 in response to abiotic stresses and revealed the mechanisms of adaptation under cold stress (Fig. [97]8). The qRT-PCR analysis reinforces the role of SikCDPK1 as a significant contributor to cold tolerance in transgenic tobacco plants. In this study, the cold tolerance mechanism of SikCDPK1 was comprehensively analyzed at the transcriptional level for the first time by RNA-seq technology. A large number of differentially expressed transcription factors belonging to the WRKY, AP2, MYB, bHLH, and NAC families were identified under cold stress. In addition, some key genes encoding MAPK signaling were up-regulated under cold stress, suggesting that MAPK signaling be beneficial for improving cold tolerance in plants. These results provide directions for further exploration of the cold tolerance mechanism of SikCDPK1. In the future, genetic material is needed to reveal more specific information. By understanding the regulatory mechanisms and expression patterns of SikCDPK1, this study provides a valuable foundation for future research aimed at enhancing cold stress tolerance in other plant species through genetic manipulation of similar pathways. This study contributes to a deeper understanding of the complex and efficient mechanisms by which plants respond to stress combinations, thereby increasing the understanding of improving plant tolerance. Fig. 8. [98]Fig. 8 [99]Open in a new tab Mechanistic changes in transgenic tobacco after exposure to cold stress. Note This figure was drawed by Figdraw Acknowledgements