Plant materials and stress conditions

In 2013, we obtained the M1 generation from EMS processed ‘S15’, and then acquired the M2 generation after self- crossing. After conducting waterlogging screening on M2 generation, we obtained a waterlogging resistant mutant strain, and self-crossed it to get M3 seeds. The seeds of M3 and wild-type (WT) peppers were germinated and planted in seedling tray. At the 5-leaf-1-heart phase, the robust seedlings with consistent growth rate were planted in 9 cm × 9 cm nursery pots, 1 seedling per pot. The pots were filled with soil until 1 cm to the edge, and the soil contained 60% farmland soil, 20% cow dung compost, and 20% river mud. When seedlings grew to the 6-leaf-1-heart period, they were subjected to waterlogging stress using dual-pot method. The nursery pots were put into a 15 cm × 40 cm larger pot, each larger pot included 6 pots (3 mutants, 3 WT). The water level at 2 cm above nursery pot surface was considered waterlogging. The water was supplemented every other day to maintain the flooding level, and the waterlogging treatment was repeated for three times. Ten days after the treatment, leaves and roots were washed with clean water, wiped, and quickly frozen with liquid nitrogen. The samples were stored in -80 °C freezer for future use.

Agronomic characterization

The height and root length of randomly selected pepper plants were measured with a ruler. The dry weight and fresh weight of over-ground part, underground part and the entire plant were recorded. Then the plants were killed at 105 ℃ for 30 min, and dried at 75 ℃ until constant weight.

Measurements of enzyme activity and plant inclusions

Proline content was measured by the acid ninhydrin method. The fresh leaves were washed and dried with paper towel. Samples of leaves (0.5 g) were cut into pieces, mixed with 5 mL 3% sulfosalicylic acid solution in a large tube, and boiled for 10 min under shaking. The extract was filtered with a funnel into a clean tube after cooling down, 2 mL filtered extract was mixed with 2 mL acetic acid and 2 mL acid ninhydrin, and boiled for 30 min after sealed with plastic wrap. After cooling down, 4 mL toluene was added into the tube and fully oscillated. The upper red solution was collected and its absorption at 520 nm was measured using toluene as reference. Proline content [x (μg mL^-1)] in the 2 mL tested samples was obtained from the standard curve and the proline concentration in fresh leaves was calculated based on the following formula: Proline content (μg g^-1) = (x × 5/2)/fresh leaf weight (g).

Anthrone method was used to measure soluble sugar content. They were measured with anthrone colorimetry. Samples of leaves (0.1 g) were placed in a ground glass weighing bottle, mixed with 20 mL distilled water, and extracted twice in boiling water for 30 min. The extract was filtered into a 50 mL volumetric flask, and the weighing bottle and residues were washed repeatedly before being filled to constant volume. Sample extract (0.5 mL) was mixed thoroughly with 1.5 mL distilled water, 0.5 mL anthrone ethyl acetate solution and 5 mL concentrated sulfuric acid, before being immediately placed in boiling water bath for 1 min. The heated sample extract was cooled naturally to room temperature to determine the absorbance at 630 nm. The final soluble sugar contents were calculated from the standard curve: soluble sugar (μg g^-1 FW) = [(corresponding sucrose content from standard curve (μg) × total extract volume (mL)]/[(measurement volume (mL) × fresh weight of the sample (g)].

The content of malondialdehyde (MDA) was determined by thiobarbituric acid (TBA method) by commercial kits (Nanjing Jiancheng Bioengineering Institute, Nanjing China). Samples of leaves (0.1 g) were thoroughly ground with a cold mortar and pestle in an ice bath. The grinding medium was 4 mL saline, plus homogenizing glass beads. The homogenate was centrifuged for 10 min at 2500 rpm and 25 °C. The supernatant referred was crude enzyme extract and used to determination. The absorbance of the reaction mixture was determined by using a spectrophotometer (UV-1780, Shimadzu, Kyoto, Japan).

The colorimetric assay was used to measure the contents of peroxidase (POD), catalase (CAT), superoxide dismutase (SOD), glutathione reductase (GS) and hydroxyl free radicals (OH) (the kit was purchased from Nanjing Jiancheng Bioengineering Institute, Nanjing Shi, China) (^{Yang et al., 2016}). A sample of leaves (0.1 g) without midrib were thoroughly ground with a cold mortar and pestle in an ice bath. The grinding medium was 4 mL saline, plus homogenizing glass beads. The homogenate was centrifuged for 10 min at 2500 rpm and 4 °C. The supernatant referred was crude enzyme extract and used to determination. The absorbance of the reaction mixture was determined by using a UV-1780 spectrophotometry (Shimadzu, Japan).

RNA Extraction, library preparation and sequencing

Total RNA was extracted from tissues using TRI Reagent (Sigma Life Science, St. Louis, Missouri, USA), according to manufacturer’s instructions. RNA quality was checked by RNase-free agarose gel electrophoresis to avoid possible degradation and contamination, and then verified using Agilent 2100 Bio-analyzer (Agilent Technologies, Santa Clara, California, USA). Next, Poly (A) mRNA was isolated using oligo-dT beads (Qiagen, Hilden, Germany), and then broken into short fragments by adding fragmentation buffer. First-strand cDNA was synthesized using random hexamer-primed reverse transcription, followed by the synthesis of the second-strand cDNA using RNase H and DNA polymerase I. The cDNA fragments were purified using a QIA quick PCR extraction kit, and then washed with EB buffer for end reparation poly (A) addition and ligated to sequencing adapters. Following agarose gel electrophoresis and extraction of cDNA from gels, the cDNA fragments were purified and enriched by PCR to construct the final cDNA library, which was then sequenced on the sequencing platform (HiSeq X Ten, Illumina, San Diego, California, USA) using the paired-end technology. Three biological replicates were performed for each line, thus six libraries were generated and sequenced.

Transcriptome analysis

Raw reads were filtered to remove low quality sequences (there were more than 50% bases with quality lower than 20 in one sequence), reads with more than 5% N bases (bases unknown) and reads containing adaptor sequences through the Perl program. Then the clean reads were mapped to the tomato reference genome using TopHat2 (http://ccb.jhu.edu/software/tophat), with the following parameters: -min-intron-length 20 -max-intron-length 10 000 -read-mismatches 1. The differentially expressed genes (DEGs) were identified using the R package edgeR (R Foundation for Statistical Computing, Vienna, Austria). The expression level of each gene was calculated and normalized to FPKM (fragments per kilobase of transcript per million fragments mapped). The false discovery rate (FDR) was used to determine the threshold of the P-value in multiple tests. In our study, the FDR < 0.05 and fold change > 2 were used as significance cut-offs of the gene expression differences. The DEGs were used for Gene Ontology (GO) and KEGG (Kyoto Encyclopedia of Genes and Genomes) enrichment analyses according to ^{Tan et al. (2018)}; GO terms with corrected P-value < 0.05 and KEGG pathways with P-value < 0.05 were considered significantly enriched by differential expressed genes.

Quantitative real-time PCR

The total root RNA was extracted using TaKaRa MiniBEST Plant RNA Extraction Kit (Takara Bio, Kusatsu, Shiga, Japan), followed by reverse transcription to obtain a total of 200 ng cDNA. qRT-PCR based on SYBR method was used to validate the DEGs (FastStart Essential DNA Green Master, Roche, Basel, Switzerland), CpAction was used as the internal reference gene (^{Liu et al., 2017}). The qPCR primers (Table 1) were synthesized by Shanghai Biotech (Shanghai, China). PCR reaction system was 20 μL: Master mix 10 μL, forward and reverse primers 0.5 μL each, 10 times diluted cDNA 5.0 μL, H₂O 4 μL. The qPCR cycle was: 95 ℃ for 10 min, 95 ℃ 15 s, 60 ℃ 30 s, 72 ℃ 15 s for 45 cycles.

Data analysis

SPSS17.0 (IBM, Armonk, New York, USA) was used to conduct one-way ANOVA. LSD and Duncan’s method were used for pairwise comparisons. P < 0.05 was considered significant.

Phenotypic evaluation of experimental materials

Under waterlogging stress, root length, plant height, fresh and dry weights of entire plant were all affected. Moreover, there were significant differences between mutant and WT after waterlogging treatment. The root length, plant height, fresh weight and dry weight of the mutants were 78.30%, 17.68%, 83.84% and 105.19% higher than WT, respectively (Table 2).

Table 1 Information of primer sequences. 

Table 2 Agronomic traits of pepper under waterlogging stress. 

Each value is the mean ± standard deviation (SD, n = 6). The effects are significant at p < 0.05 with a one-way ANOVA.

Physiological response of pepper to waterlogging stress

In addition, under waterlogging stress, the antioxidant enzymes in mutants showed higher activities: SOD, POD, CAT and GR enzymes of mutants were 90.61%, 77.92%, 43.05% and 106.67% more active than WT, respectively (Table 3). Meanwhile, the contents of proline and soluble sugar in mutants were 25.53% and 42.08% higher than WT (Table 4). And the contents of MDA and ˙OH were reduced in mutants by 47.54% and 68.72% compared to WT (Table 4).

RNA-seq analysis

Transcriptome sequencing was performed by Hiseq X ten. After eliminating the joint and low-quality sequences, we obtained 211 991 416 clean and high-quality sequences with a total of 31.79 Gb data. Among these sequences, 1 666 942 723 of them were uniquely matched to the pepper genome. The percentage of Q30 bases were 89.67%-90.64%, and the average GC content was about 45%, indicating that the quality of transcriptome sequencing was relatively high, with good reproducibility between different replicates, which satisfied the criteria for further bioinformatic analysis (Table 5).

GO functional annotation enrichment analysis

Under waterlogging stress, 61 DEGs were detected between mutant and wild-type. Among them, 37 DEGs were down- regulated in mutant, and 24 DEGs were up-regulated (Figure 1). After conducting the GO functional annotation analysis on differentially expressed genes, we found that these genes were concentrated in three major categories, biological processes, molecular functions and cell components (Figure 2), which included 6, 5 and 5 functional classes, respectively. The percentages of differential genes in these three categories were 45%, 35%, and 20%, respectively, Mutant and wild type had the largest differentially genes in single organism processes, antioxidant activity and membrane of this three categories, respectively, which indicated that most DEGs were significantly related to some of these biological functions. Indicating that most of these genes were significantly associated with some biological functions.

Table 3 Activities of antioxidant enzymes of pepper under waterlogging. 

Each value is the mean ± standard deviation (SD, n = 6). The effects are significant at p < 0.05 with a one-way ANOVA.

SOD: Superoxide dismutase; POD: peroxidase; CAT: catalase; GR: glutathione reductase.

Table 4 Contents of osmotic substances and oxidation products of pepper under waterlogging. 

Each value is the mean ± standard deviation (SD, n = 6). The effects are significant at p < 0.05 with a one-way ANOVA.

PRO: Proline; MDA: malondialdehyde; ˙OH: hydroxyl free radical.

Table 5 RNAseq data statistics. 

GC: Ratio of the sum of guanine and cytosine; Q20: Ratio of bases with a mass value greater than or equal to 20; Q30: Ratio of bases with a mass value greater than or equal to 30.

The fold changes (Mutant (Mut)/Wild-type (WT), in logarithm scale) were represented by y-axis (-log10 of the qvalue). Each dot in the figure represents a single gene, and the green and red dots represent the significantly differential genes. Green dot indicates an up-regulated gene (Mut/WT), and red dot indicates a down-regulated gene (Mut/WT). Blue dots represent genes with nonsignificant difference.

Figure 1 Differential expression genes. 

Figure 2 Gene ontology annotation of differentially expressed genes. 

KEGG Pathway analysis of DEGs

The KEGG enrichment analysis on DEGs showed that, 12 out of the 61 genes were annotated to seven pathways, including the cofactors and vitamin metabolism, amino acid metabolism, lipid metabolism, etc. (Figure 3).

KEGG: Kyoto Encyclopedia of Genes and Genomes.

Figure 3 KEGG annotation of differentially expressed genes. 

Quantitative verification of the critical genes

The expression levels of eight genes related to protective enzymes and endogenous hormone metabolism were quantified, and found to be significantly different between mutant and WT (Figure 4). Among them, the expression levels of auxin-induced protein related gene Cap.ARATH (Capana04g001523) and ethylene response related gene Cap.RAP2 (Capana08g000001) were significantly higher in mutant. The peroxidase related genes Cap.POD (Capana12g002272, Capana02g003649, Capana03g002143 and Capana12g002274) were up-regulated in mutants to different extents, which was consistent with the changes in POD activity; but another peroxidase related gene (Capana01g001329) was significantly down-regulated in mutants compared to WT. The expression level of MYB family related gene Cap.MYB1R1 (Capana05g002019) was also significantly increased in mutant.

FPKM: Fragments per kilobase of transcript per million fragments mapped; WT: wild-type; Mut: mutant.

Figure 4 Relative gene expression and FPKM level.