Introduction

Potato (Solanum tuberosum L.) is a thermophilic crop of perennial nightshade and is considered as a vegetable and staple crop in many countries because of its high nutrition contents [1]. During potato cultivation in the field, various abiotic stresses would exert detrimental impact on its growth status, such as drought stress, salt stress and extreme temperatures [2]. Among these abiotic factors, temperature is the most indisciplinable factor affecting potato growth and development [3]. For potato, the optimal temperature for the growth of aerial portion is approximately 20–25 °C and the best temperature for tuber formation is around 15–20 °C [4]. Due to global warming prediction, heat stress has become a severe agricultural problem in many areas, with significantly influencing the potato growth and tuberization process and subsequently impacting on the tuber yield and quality [5,6,7]. Therefore, it is of great significance for potato breeding to illuminate the mechanism of heat stress on potato, reveal the response mechanism of potato to heat stress and explore heat resistant genes.

To delve into the associated response mechanisms to heat stress and characterize the significantly differentially expressed genes in various biological pathways, the next generation sequencing (NGS) technology has been widely used in many plant species [8]. NGS technology, also called massive parallel deep-sequencing technology, can be performed in three platforms: Roche (454) GS FLX sequencer, Solexa/Illumina genome analyzer and Applied Biosystems SOLiD sequencer [9]. These platforms have their own advantages and disadvantages, and have been extensively applied in the biotic and abiotic stress response mechanisms due to their rapid sequencing and lower cost characteristics [6]. For instance, Qi et al. [10] investigated the molecular mechanisms response to water logging stress, and also profiled the expression levels of differentially expressed genes in cucumber plants via this method. In Ammopiptanthus mongolicus, the candidate genes and developed SSR markers involved in drought tolerance were identified by this method [11]. And a wide range of heat-associated biological pathways have been mapped in KEGG database and numerous genes have been identified to be related to heat stress in a lot of plant species, such as Arabidopsis, switchgrass, spinach and so on [6, 12, 13].

At present, many researches have demonstrated that the expression of many heat response genes could change significantly in a very short time under heat stress, especially Hsfs and Hsps which are sensitive to high temperature [14]. For example, most OsHsfs members were observed to be up-regulated expressed after 10 min of heat stress in rice [15]. In our previous study, we found that the transcript levels of most StHsf members began to show dramatic changes at 2 or 6 h, indicating that Hsfs are sensitive to heat stress in potato [2]. Similarly, in potato, most Hsp20 members were extremely increased after being treated for 3 h and 24 h underheat stress, and few members were up-regulated after a 24 h heat stress [14]. However, gene expression is a dynamic process with the extension of heat treatment time. The expression levels of plentiful heat response genes were dramatically increased in the first several hours after heat stress, but decreased when heat lasted for more than several hours [2], suggesting that different kinds of heat response genes perform functions during different periods of heat stress. In many countries, the effects of high temperature on potato cultivation tend to last for 3 days or longer, not only several minutes or several hours.

Therefore, in order to excavate the heat response genes under continuous heat stress, the transcriptome sequencing between non-stressed and 3 days of heat-stressed potato leaves (cv. Russet Burbank) was performed. The differentially expressed genes (DEGs) were identified and aligned to GO database and KEGG database, which provided important information to gain insight into the potential regulatory biological pathways in respond to heat stress. Some candidate genes that likely played vital roles in the relative long-term heat stress were identified based on the differential gene expression profiles. These results will be useful for further understanding the molecular mechanisms of potato plant tolerance to heat stress and provide the theoretical and practical basis for breeding heat-tolerance varieties.

Methods and materials

Plant materials and growth conditions

This research used Russet Burbank (S. tuberosum) as the potato material and was conducted in the Fredericton Research and Development Centre, Agriculture and Agri-Food Canada. The 1-month-old tissue culture seedlings were moved in clay pots and grown in an illumination and aeration chamber with 70% of humidity under 14 h light/10 h dark regime at 20 ℃ day/18 ℃ night. Two weeks later, half of the plantlets were moved to another chamber with the same condition except the temperature (35 ℃ day/28 ℃ night) for 3 days; while the rest plants were remained in the original chamber as control. The second fully expanded leaves of the plantlets from two different temperature treatments were harvested and blended separately. All collected samples were immediately immersed in liquid nitrogen and stored at − 80 ℃ prior to RNA extraction.

RNA extraction and library preparation

Total RNA was extracted from 0.5 g potato leaf samples using the RNeasy Maxi kit (Qiagen, Germany). The quality and concentration of the total RNA samples were examined using the 2100 Bioanalyzer (Agilent Technologies) and NanoDrop 1000 Spectrophotometer (Thermo Scientific). After that, the total RNA samples were divided into two parts. One part of the total RNA samples was used for cDNA library construction; the other part was retained for the validation of transcriptome sequencing results.

The messenger RNA (mRNA) was isolated from total RNA sample of each treatment using oligo (dT) attached beads. The purified mRNA was subsequently trimmed into shorter fragments (~ 20 nt) by specific buffer and reverse-transcribed to synthesize cDNA. After end-repair, 3′ end adenylation and ligation of the Illumina sequencing adapters, the cDNA fragments were purified and amplified by PCR to build the final libraries.

Transcriptome sequencing and analysis of differential expression genes (DEGs)

The tested cDNA libraries were ready for RNA sequencing on a HiSeq-2000 platform at the Canadian Centre for Computational Genomics. Millions of short sequencing fragments (reads) were obtained. The raw reads were pre-processed by trimming from the sequencing adapters using Trimmomatic [16] and removing the low quality reads whose length less than 32 bp. The filtered reads were aligned to a potato reference genome (S. tuberosum assembly 4.03) using STAR [17].

Different exploratory data analyses were conducted in gene expression levels to detect the potential outliers by exploring the homogeneity of biological replicates and appreciating the global effects of the different experimental variables. The differential gene expression analysis was performed using DESeq [18] and edgeR [19] of R Bioconductor packages.

Validation of the RNA-seq results using droplet digital PCR

RNAs were extracted from non-stressed and 3 days of heat-stressed leaves as described above. The specific primers were designed by Primer-Blast in NCBI website (https://www.ncbi.nlm.nih.gov/tools/primer-blast/). Droplet digital PCR (ddPCR) was performed on QX200 Droplet Digital PCR System (Bio-Rad) which consists of the QX200 Droplet Generator and the QX200 Droplet Reader. The PCR samples were mixed by 2 μL DNA sample (2–4 ng), 0.5 μL of 10 μM primer mixture, 11.5 μL EvaGreensupermix and 9 μL ddH2O. Then 20 μL PCR samples were transferred into the individual sample walls of the 8-channel droplet generator cartridge (DG8, Bio-Rad) and 70 μL of droplet generation oil was added to the oil walls of DG8 cartridge. After the creation of monodispersed droplets in the QX200 Droplet Generator, 40 μL droplets were used for PCR using the following cycling program: 95 °C for 5 min, then 40 cycles of 95 °C for 30 s, 55 °C for 30 s, 72 °C for 45 s, 4 °C for 5 min, 90 °C for 5 min and 10 °C for keeping the PCR products. The numbers of PCR-positive and PCR-negative droplets were counted by the associated QuantaSoft™ software of the QX200 Droplet Reader. The expression of each gene was normalized and calibrated against the reference gene EF1α, which has a relative stable expression level under different conditions.

Functional annotation and analyses of gene ontology (GO) and KEGG pathway enrichment

GO was used to describe the function attributes of genes or gene products in organisms. GO enrichment analysis illustrates the significantly enriched GO items in DEGs compared with the genome background, and provides a method to elucidate which biological functions are significantly associated with the DEGs [6]. The sequences of all the detected genes were blasted to the Gene Ontology database using Blast2GO to extract their GO annotation information [20]. Then topGO function in bioconductor software was applied to perform GO enrichment analysis of the differentially expression genes with the p value ≤ 0.05 [21].

To further understand the biological function of DEGs and to detect the main pathways in which the DEGs involved, the gene sequences were mapped to the KEGG database by BLASTX with an E-value cutoff of < 10E−5 (https://www.genome.jp/kegg/). According to the KEGG annotation information of the differentially expressed genes, the pathway enrichment analysis of these genes was conducted using hypergeometric inspection [22]. After multiple testing corrections, the pathways with p value ≤ 0.05 were selected as the significant enriched pathways.

Results

Construction of expression profile of DEGs in potato leaves under heat stress

Potato plantlets with similar growth status were treated with different temperatures (control check: 20 °C day/18 °C night; heat treatment: 35 °C day/28 °C night). As shown in Fig. 1, compared with the control group, part of the leaves of the potato plants in the treatment group were slightly darker in color and covered with a thin layer of wax. This structure helps to reflect sunlight and reduce radiation absorption.

Fig. 1
figure 1

Potato plants before and after different temperature treatments. a Potato plants before treatments and b potato plants after 3 days of different temperature treatments. CK contrast check (20 °C day/18 °C night), HS Heat stressed potato plants (35 °C day/28 °C night)

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The second fully expanded leaf (usually the fourth or the fifth leaf) from each plant after 3 days of different treatments was collected and used for RNA sequencing by Illumina Hiseq-2000 system. After trimming the Illumina adapters and removing the low quality reads, a total of 48,646,835 and 46,181,488 clean paired reads were obtained from 49,200,771 and 46,654,357 raw paired reads which produced from non-stressed (CK) and heat stressed (HS) cDNA library, respectively. Finally, 21,681 genes were identified by alignment of the filtered reads and a potato reference genome (S. tuberosum assembly 4.03). Among these detected genes, 1420 (7%) genes showed significantly differential expression levels between HS and CK cDNA samples (deseq p value ≤ 0.05 or edger p value ≤ 0.05, and |log2 (fold change)|> 1): 771 (4%) and 649 (3%) genes were found to be over-expressed and under-expressed respectively (Fig. 2). The transcriptome sequencing information of these 1420 DEGs were presented in ESM 1. The identification of these DEGs paves the way for further investigation on molecular mechanisms of heat tolerance in potato.

Fig. 2
figure 2

Numbers of DEGs between potato leaves under different temperature treatments. Totally, 21,681 genes were identified by alignment of the filtered reads and a potato reference genome (Solanum tuberosum assembly 4.03). Among these detected genes, 20,261 genes showed no significantly differential expression; 1420 genes showed significantly differential expression levels between HS and CK cDNA samples: 771 and 649 genes were found to be over-expressed and under-expressed respectively. CK 20 °C day/18 °C night, HS 35 °C day/28 °C night

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3.2. Validation of Illumina-generated expression profile by droplet digital PCR analysis

To verify the reliability of RNA sequencing results, the expression patterns of 12 randomly selected genes were detected using droplet digital PCR (ddPCR) analysis. The primer pairs of these genes were presented in Table 1. The ddPCR data showed that the expression trends of these 12 genes were basically consistent with the result of RNA sequencing detection (ESM 2), and the two results had a very high correlation under two different detection methods (Fig. 3). Therefore, the results obtained from transcriptome sequencing were credible and could be used for the further analyses.

Table 1 List of primer sequences of 12 selected genes and reference gene used for the ddPCR analysis
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Fig. 3
figure 3

Correlation analysis of the results obtained from RNA-seq and ddPCR. Twelve DEGs, randomly selected from the RNA-seq data, were used to detect their expression changes between CK and HS by the method of ddPCR. The value in the table above showed the expression changes of DEGs under two different methods, that is log2 (DEG expression amount under heat stress/its expression amount under normal condition)

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Functional category of DEGs by GO-term analysis

In this study, these 1420 identified DEGs were aligned to GO database and classified into different categories according to their functions. Finally, the DEGs could be grouped into 49 GO categories after cutting off the GO terms including less than 9 genes (Fig. 4, ESM 3). Of these GO annotations, 27 GO terms were associated with biological process (BP), 16 GO terms were assigned to molecular function (MF), and 6 were assigned to cellular component (CC). In the category of biological process, “response to stimulus”, “response to stress”, “response to chemical” and “response to abiotic stress” including 127 (8.94%), 70 (4.93%), 57 (4.01%) and 36 (2.54%) DEGs respectively, were the predominant GO terms. GO terms like “catalytic activity” and “oxidoreductase activity” were the leading terms in the category of molecular function, especially “catalytic activity”, which contained the most DEGs (21.83%) among these 49 GO terms. In cellular component category, “plastid” and “plastid part” were the most representative terms and contained 55 (3.87%) and 31 (2.18%) DEGs, respectively. These results suggested that high temperature treatment may lead to various stresses on plants except heat stress, such as chemical stress, light stress and oxidative stress. Synergistic effects of intricate stresses might activate the gene expression of numerous enzymes like oxidoreductase, hydrolase, transferase and peptidase, to resist the adverse environment. Furthermore, under heat stress, the genes involved in the synthesis of plastid components were probably activated and helped to alleviate the stress damage on cellular components in plant organisms.

Fig. 4
figure 4

Gene ontology classification analysis of DEGs between non-stressed potato leaves and heat-stressed potato leaves. GO functions were represented in X-axis; the number of DEGs annotated in each GO term was presented in left Y-axis; and the right Y-axis showed the percentage of DEGs which were annotated in each GO term

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Analysis of KEGG pathways enrichment of DEGs

In order to further investigate the biological functions of the differentially expressed genes, these DEGs were mapped to the KEGG database and were found to be involved in 110 metabolic pathways (ESM 4). The top 20 enriched biological pathways were shown in Fig. 5 according to enrichment significance. The pathways with p value ≤ 0.05 were considered as significant enriched pathways. They were mainly related to “Limonene and pinene degradation” (ko00903), “starch and sucrose metabolism” (ko00500), “plant hormone signal transduction” (ko04075), “Carotenoid biosynthesis” (ko00906), “Stilbenoid, diarylheptanoid and gingerol biosynthesis” (ko00945), “plant pathogen interaction” (ko04626) and so on.

Fig. 5
figure 5

Top 20 biological pathways enrichment of the DEGs in potato leaves after 3 days of heat treatment. The dot size represented the number of the differentially expressed genes involved in each pathway. The different dot color represented the p value of each pathway; the pathways with p value ≤ 0.05 were significant enriched pathways. Rich Factor represented the ratio between the number of DEGs and all genes which were annotated in each pathway. (Color figure online)

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Moreover, among these pathways, “Metabolic pathways”, “Biosynthesis of secondary metabolites”, “Plant-pathogen interaction”, “Plant hormone signal transduction” and “Starch and sucrose metabolism” contained more DEGs (203, 130, 93, 79, 32 DEGs respectively) than any other pathways (Fig. 5, ESM 4). These results indicated that the expression levels of genes involved in these biological pathways changed significantly to respond to the heat stress. Also, the transcriptomic data provided basis for the deep research aimed at investigating the regulation mechanism of specific pathways in potato leaves under heat stress.

Expression analysis of Hsfs and Hsps in potato leaves under heat stress

Previous studies have shown that Hsfs and Hsps are sensitive to heat stress, which means they could be expressed in large quantities within a few minutes. Based on the result of transcriptome sequencing, only two Hsf members were identified to be differentially expressed. They were HsfA2 (PGSC0003DMG400008223) and HsfA3 (PGSC0003DMG401002683), whose expression levels were dramatically down-regulated in potato leaves after 3 days of heat treatment (Table 2). Unlike Hsfs, the expression of many Hsps had significant changes, such as some Hsp90s, Hsp70s and sHsps members. These StHsps could be enriched in the metabolic pathway of “protein processing in the endoplasmic reticulum” (Fig. 6). As shown in Fig. 6, the expression amounts of most Hsps in the cytoplasm was markedly decreased after 3 days of heat treatment (marked with green box). However, the expression levels of some Hsp70s and sHsps members were up regulated significantly (marked with red box). Totally, 9 Hsps with up-regulated expression were screened out (Table 2). Among them, the expression of Hsp26-CP (PGSC0003DMG400003219) and Hsp70 (PGSC0003DMG400027611) were extremely up-regulated (more than 10-fold) under heat stress, especially sHsp-CP whose expression increased to about 433-fold compared with the control. These results indicated that sHsp-CP and Hsp70 might play an important role in protecting cells and tissues during the long-term thermal stress response of potato.

Table 2 Expression changes of Hsfs and Hsps among the DEGs
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Fig. 6
figure 6

Expression changes of Hsps in potato leaves with 3 days of heat treatment. The gene in the red box had significantly up-regulated expression; gene in the green box had significantly down-regulated expression; gene in the gray box was unsignificantly expressed. Heat stress condition: 35 °C day/28 °C night; normal condition: 20 °C day/18 °C night. (Color figure online)

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Discussion

The differentially expressed genes in response to heat stress in potato leaves have diverse functions

Heat stress becomes a major concern for crop growth, development and productivity due to global warming effect [23]. During the summer, potato plants often suffer from heat damage lasting for 3 days or longer. In order to reflect the actual situation during the potato planting period, the gene expression profiles were constructed in potato leaves under 3 days of heat treatment. Through transcriptome sequencing, the expression patterns of potato genes in response to heat stress at high temperature were analyzed, and heat-resistance related genes were identified. This study provides a basis for the study of the molecular mechanism of potato heat resistance.

Russet Burbank, which was used as the plant material in this research, is a very important and prevalent potato cultivar in the world, and occupied 70% of the processed potato market in North America [24]. After 3 days of high temperature treatment, several leaves of heat-stressed plants covered with a thin layer of wax, which helps to reflect sunlight and reduce radiation absorption (Fig. 1). According to RNAseq data, a total of 1420 DEGs were identified, including 771 up-regulated genes and 649 down-regulated genes (Fig. 2, ESM 1). The method of droplet digital PCR (ddPCR) was used to validate the credibility of the results obtained from Illumina platform. The detection results under two different methods had the similar trend, and the correlation coefficient between the RNA-seq data and ddPCR test results was 0.9352 (Fig. 3), suggesting that the RNA-seq results were reliable for further research.

These identified DEGs were subjected to GO enrichment analysis. Totally, 21% DEGs were found to be involved in “catalytic activity” (GO: 0003824), suggesting that heat stress triggered the expression changes of many genes encoded the enzymes which participate in different regulatory pathways in response to adverse environment (Fig. 4). For example, under heat stress, the synthesis of starch might be hindered because of down-regulated starch synthase gene (SS). In contrast, the gene encoded β-amylase was expressed significantly up-regulated, which promotes the hydrolysis of starch. This result was in accordance with the trends of starch content and reducing sugar content in tubers (ESM 5). In addition, many DEGs were activated to respond to different stimulus (GO: 0050896), stresses (GO: 0006950), chemical (GO: 0042221) and oxidative stress (GO: 0006979) to help the plants survive in the adverse environment caused by heat. Heat stress always causes other stresses, such as drought stress and oxidative stress [25, 26]. The interaction of these multifarious stresses has a worse effect on plants growth and development [23]. Similar results have been found in other plant species, such as switchgrass and spinach [6, 13]. Besides, many genes were clustered into the terms of “plastid” (GO: 0009536) and “plastid part” (GO: 0044435), indicating that these genes, such as a potato chloroplast sHsp (PGSC0003DMG400003219), would participate in repairing the cellular components, especially plastid components, to alleviate the destruction of membranaceous structures of cell and organelle caused by high temperature. In Arabidopsis, it has been demonstrated that AtHsp21 (a kind of chloroplast sHsp) could interact with the plastid nucleoid protein pTAC5 to maintain the function of plastid-encoded RNA polymerase, PEP [27]. However, the exact role of this sHsp in potato remains unknown.

The analysis of enriched pathways for differentially expressed genes in this study specifically showed the most potential biochemical pathways in which these DEGs involved under heat stress (Fig. 5). The major pathways included limonene and pinene degradation (map00903); starch and sucrose metabolism (map00500); plant hormone signal transduction (map04075); plant–pathogen interaction (map04626); metabolic pathway (map01100); biosynthesis of secondary metabolites (map01110) and so on. Under heat stress, most of the DEGs participated in the metabolic pathway which consists of a connected series of biochemical reactions catalyzed by abundant enzymes in a cell. Also, various signal transduction molecules were produced to generate a series of innate defensive reactions in response to heat stress [23, 28]. For example, as a stress hormone, ABA has been demonstrated to play an important role in the regulation of heat stress. In Arabidopsis, ABA signaling pathway and ABA-mediated heat responses were connected by HsfA6b [29]. In addition, many DEGs were observed to take part in the plant–pathogen interaction pathway and biosynthesis of secondary metabolites. Sustained high levels of heat stress may lead to plant susceptibility to pathogens [30, 31]. To defend against plant pathogens, many secondary metabolites, such as flavonoid, were induced to inhibit fungal growth [32, 33]. Therefore, many DEGs were also observed to be clustered in the plant–pathogen interaction pathway and biosynthesis of secondary metabolites under heat stress.

Most potato Hsfs and Hsps cannot be expressed efficiently under long-term heat stress

In our previous research, 27 Hsfs were identified in potato and most of them were highly expressed under 2 h of heat stress [2]. However, only StHsfA2 and StHsfA3 were observed to be significantly down-regulated in potato leaves under 3 days of heat treatment; while the expression of other Hsfs members had no significant difference. As the downstream genes of Hsfs, only few Hsps were expressed significantly increased after heat treatment. These results indicated that the continuous high temperature has a very serious effect on the expression of Hsfs, thus affecting the expression of their downstream genes. Numerous studies have shown that the expression of most Hsfs and Hsps could be activated in a short time after heat shock. For example, in rice, 16 of the 23 OsHsfs genes were significantly up-regulated expressed after 10 min to 30 min of heat stress [15]. In pepper, most CaHsfs and CaHsp20s were found to be strongly expressed after short-term thermal stress (40 ℃ 2 h) [34, 35]. Potatoes and peppers, both of which belong to the nightshade family, are closely related. Therefore, the expression of most StHsfs and StHsps in potato might be activated under short-term heat stress, but gradually decreased under continuous heat treatment.

Although most Hsps are activated under short-term heat stress, some Hsps genes with significantly up-regulated expression, such as Hsp26-CP and Hsp70, could still be found in potato leaves after 3 days of heat treatment. Hsp70 is one of the most conserved and widely distributed heat shock proteins. Under non-stress condition, Hsfs remain inactive state by binding with Hsp70s. While under heat stress, Hsp70s preferentially bind to the denatured proteins, and the released Hsfs would form into an active trimer that is transferred to the nucleus to activate the expression of Hsps [36]. Hsp70s can help the denatured proteins fold correctly, degrade denatured proteins and move them out of the cell to prevent protein aggregation. Therefore, they play an important role in plant response to heat stress [37].

StHsp26-CP, which belongs to sHsp family, was significantly expressed after heat stress. Although the transcription level of the gene cannot directly reflect its protein level, it can still provide a basis for in-depth study of the function of Hsps [38]. Transcriptome sequencing results showed that the expression levels of most cytoplasm sHsps and mitochondria sHsps were significantly down-regulated; while some chloroplast sHsps were up-regulated expressed significantly, especially Hsp26-CP, whose expression was 433 times as that of the control group. Therefore, the high level expression of Hsp26-CP under continuous heat stress indicated that Hsp26-CP is likely to play an important role in the response of potato to long-term heat stress. It has been found that the chloroplast sHsp (AtHsp21) could maintain the function of plastid-encoded RNA polymerase (PEP) and protect chloroplast by binding to plastid transcriptionally active 5 (pTAC5) in Arabidopsis [27]. This result is consistent with the GO clustering analysis (Fig. 4), indicating that numerous heat stress response genes might be involved in the repair of plastid components. However, further studies need to be conducted to find out whether potato chloroplast sHsp performs a similar function as AtHsp21.

Conclusion

In conclusion, a total of 1420 DEGs induced by 3 days of high temperature (35 °C day/28 °C night) were identified in potato leaves. Among them, 771 genes were significantly up-regulated and 649 genes were significantly down-regulated. These DEGs could be clustered into 49 different GO types and enriched into multiple metabolic pathways, reflecting the diversity of their functions. The transcriptome profiling of potato leaves between two different treatments facilitated the identification of major DEGs and regulatory mechanisms for the heat tolerance of potato plant. After 3 days of heat stress, most StHsfs members and StHsps members were not efficiently expressed, and only a few Hsps members (such as Hsp26-CP and Hsp70) could be expressed at high level. These data provide a basis for the study of gene function and the mechanism of heat tolerance regulation.