Comparative transcriptome analysis of sweet corn seedlings under low-temperature stress

CJ-00226; No of Pages 11 TH E C ROP J O U R NA L XX ( 2 0 17 ) XXX–X XX

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Comparative transcriptome analysis of sweet corn seedlings under low-temperature stress☆ Jihua Mao, Yongtao Yu, Jing Yang, Gaoke Li, Chunyan Li, Xitao Qi, Tianxiang Wen, Jianguang Hu⁎ Guangdong Provincial Key Laboratory of Crops Genetics and Improvement, Crop Research Institute, Guangdong Academy of Agricultural Sciences, Guangzhou 510640, China

AR TIC LE I N FO

ABS TR ACT

Article history:

Stress induced by low temperature, which represents a widespread environmental factor,

Received 3 January 2017

strongly affects maize growth and yield. However, the physiological characteristics and

Received in revised form 17 March

molecular regulatory mechanisms of maize seedlings in response to cold remain poorly

2017

understood. In this study, using RNA-seq, we investigated the transcriptome profiles of two

Accepted 28 March 2017

sweet corn inbred lines, “Richao” (RC) and C5, under cold stress. A total of 357 and 455

Available online xxxx

differentially expressed genes (DEGs) were identified in the RC and C5 lines, respectively, 94 DEGs were detected as common DEGs related to cold response in both genotypes, and a

Keywords:

total of 589 DEGs were detected as cold tolerance-associated genes. By combining protein

Maize (Zea mays L.)

function clustering analysis and significantly enriched Gene Ontology (GO) terms analysis,

Low temperature stress

we suggest that transcription factors may play a dominating role in the cold stress response

RNA-seq

and tolerance of sweet corn. Furthermore, 74 differentially expressed transcription factors

Cold-responsive gene

were identified, of those many genes involved in the metabolism and regulation of hormones. These results expand our understanding of the complex mechanisms involved in chilling tolerance in maize, and provide a set of candidate genes for further genetic analyses. © 2017 Crop Science Society of China and Institute of Crop Science, CAAS. Production and hosting by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).

1. Introduction Maize (Zea mays L.) is a thermophilic crop that is highly sensitive to cold stress [1]. The optimum temperature for maize growth ranges from 21 to 27 °C; suboptimal temperatures (10–20 °C) decrease the capacity for biomass production and lead to growth retardation, whereas temperatures below 10 °C may cause irreversible damage and result in plant death [2,3]. In recent years, maize cultivation has been extended into regions where

the high temperature is below the optimum required for this crop. In China, maize is sown from February to May, when the soil temperature is above 8 °C. Early sowing can improve yield as the result of a longer growing season [4], however, it potentially exposes seedlings to low-temperature stress in the early spring. The development of cold-tolerant varieties is crucial for future maize cropping in temperate regions. The primary injury induced by cold stress in plants is usually shown in leaves, where a large range of physiological

☆ Peer review under responsibility of Crop Science Society of China and Institute of Crop Science, CAAS. ⁎ Corresponding author. E-mail address: [email protected] (J. Hu). Peer review under responsibility of Crop Science Society of China and Institute of Crop Science, CAAS.

http://dx.doi.org/10.1016/j.cj.2017.03.005 2214-5141 © 2017 Crop Science Society of China and Institute of Crop Science, CAAS. Production and hosting by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).

Please cite this article as: J. Mao, et al., Comparative transcriptome analysis of sweet corn seedlings under low-temperature stress, The Crop Journal (2017), http://dx.doi.org/10.1016/j.cj.2017.03.005

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and biochemical responses are affected. Cold-induced effects on photosynthesis can inhibit CO2 assimilation, and induce the overproduction of potentially dangerous reactive oxygen species (ROS), leading to the destruction of cellular structures and to perturbed metabolism [5–7]. Root development is also affected by low temperature, in turn reducing nutrient and water uptake [8,9]. Maize germplasm varies greatly in cold tolerance. Cold-tolerant genotypes usually show slight photoinhibition, reduced degradation of photosynthetic pigments, and increased activity and/or content of several protective antioxidants [2,4,10,11]. The exchange of photosynthetic metabolites between mesophyll and bundle sheath cells is more efficient in cold-tolerant maize genotypes [12]. Numerous quantitative trait loci (QTL) have been identified for cold tolerance in maize [13]. Major QTL associated with photosynthesis (determined by chlorophyll fluorescence) explained 19.0%–37.4% of phenotypic variance, and QTL located in the same regions were also found to control seedling dry weight or leaf pigment composition under cold conditions [13–16]. However, the numbers and positions of QTL were inconsistent, owing to the influence of genetic background and the low resolution of QTL mapping, limiting the precise identification of the causative genes and their application in molecular-assisted selection of crops [17]. High-throughput analyses of gene expression based on cDNA-AFLP, suppression subtractive hybridization, and microarrays have been used to explain the molecular mechanisms of the cold response of maize seedlings. Several genes involved in photosynthesis, sugar metabolism, signal transduction, circadian regulation, and cell wall function have been identified as candidate genes associated with cold response and cold acclimation [18–20]. However, those studies did not clearly reveal the genetic basis of differences in cold tolerance among diverse maize genotypes. RNA-seq technology is another powerful approach used to identify large numbers of genes associated with specific traits and to discover novel stress response pathways. This technology has been used to study nitrogen-limitation, water-deficit, and heat-stress responses in maize [21–24]. In the present study, two sweet corn inbred lines, RC and C5, with contrasting cold tolerance were exposed to low-temperature stress. Dynamic changes in morphology and physiology between the two lines were then compared and the expression profiles of genes were analyzed by RNA-seq. Cold stress-inducible genes were classified as common and specifically regulated genes as characterized by their expression patterns, and their functional significance was evaluated.

hypochlorite and then germinated for three days in darkness at 25 °C. The seedlings were transferred to pots filled with a 3:1 mixture of turf and vermiculite soil and grown in a growth chamber (photoperiod, 12/12 h day/night; light irradiance, 250 μmol quanta m− 2 s− 1; temperature, 28/25 °C; relative humidity, 60%/80%). A set of 150 typical and healthy plantlets with three fully expanded leaves were selected from each line. Seedlings from both genotypes were evaluated at T1 (15/12 °C, day/night) and T2 (8/5 °C, day/night) low temperatures, as well as at CK (28/25 °C, day/night) for five days. After treatment, all plantlets were returned to normal growth conditions.

2.2. Phenotypic evaluation index of cold tolerance in sweet corn seedlings Four traits associated with cold tolerance were recorded as follows. (1) Number of surviving plants, determined for each genotype as the number of plants still alive (having produced new leaves) at the end of the experiment. (2) Accumulation of biomass (g plant−1): five typical seedlings were selected and fresh weight (FW) of the whole plant was measured using an electronic analytical balance (ED124S, Sartorius, Germany). The difference between the average weight before and after treatment represented an increase in the amount of biomass. (3) Chlorophyll fluorescence: measurements were performed after plants were subjected to low temperature (T1 and T2) for 0 (before treatment), 1, 3, or 5 days (i.e., 4 h after the beginning of the light phase of the photoperiod). The plants were dark-adapted for 30 min at 24 °C before measurements were made. The middle part of the second fully expanded leaf from the bottom was then fixed in a leaf clip (Junion-PAM, Walz, Germany). Maximum quantum efficiency of PSII primary photochemistry (Fv/Fm), PSII operating quantum efficiency (ΦPSII), and non-photochemical quenching (NPQ) were measured as described by Fracheboud [10]. Experiments were repeated five times using five plants per line for each experimental variant. (4) Physiological traits: fully expanded leaves collected from eight seedlings were pooled into a sample at each time point for the determination of malondialdehyde (MDA) content and superoxide dismutase (SOD) activity. For MDA assays, 0.5 g fresh leaf was homogenized in 10 mL 0.1% trichloroacetic acid (TCA) and centrifuged at 5000 × g for 20 min at 4 °C. For SOD assays, 0.5 g leaf was ground using a mortar and pestle with 0.5 g inert sand and 10 mL chilled 50 mmol L−1 phosphate buffer (pH 7.8). The samples were centrifuged at 5000 × g for 10 min. The supernatants were removed and used to determine MDA concentrations and SOD activity respectively, according to the protocol described by Esim and Atici [25].

2. Materials and methods 2.3. Sample preparation and RNA sequencing 2.1. Plant materials and experimental design Two sh2 sweet corn inbred lines, RC and C5, were used. These lines were supplied by the Crop Research Institute, Guangdong Academy of Agricultural Sciences, Guangzhou, China. They are important parental lines, widely used in breeding, that show different levels of cold-stress tolerance in the field. Kernels were surface-sterilized in 5% (w/v) sodium

8/5 °C and 28/25 °C were chosen as the treatment and control temperatures, respectively. The roots and leaves were sampled from both cold-stressed and control plants at 8 h and 24 h after stress. Root samples consisted of root tips approximately 5–10 mm long, and leaf samples consisted of the third fully expanded leaf from the top. Leaves and roots were harvested from five seedlings per time point. Samples of each

Please cite this article as: J. Mao, et al., Comparative transcriptome analysis of sweet corn seedlings under low-temperature stress, The Crop Journal (2017), http://dx.doi.org/10.1016/j.cj.2017.03.005

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tissue and time point were frozen immediately in liquid nitrogen and stored at − 80 °C for RNA isolation. Total RNA was extracted using a Plant RNA Extraction Kit (Tiangen Biotech (Beijing) Co., Ltd., China). RNA quality was checked by separation of samples on 1% agarose gel electrophoresis and qualified with a Nano Drop 2000 (Thermo Scientific, USA). Equal amounts of total RNA from each tissue and time point were pooled. Finally, 20 μg of total RNA from the RC and C5 lines (both for cold treatments and for control) were used for Illumina sequencing (Beijing Berry Genomics Co. Ltd., China). cDNA library construction and high-throughput sequencing were performed following the manufacturer's instructions (Illumina HiSeq 2500, USA). Four individual paired-end (PE) cDNA libraries were generated and then sequenced on the Illumina HiSeq 2500 Genome Analyzer.

2.4. Reads processing and identification of DEGs The raw reads were cleaned by removal of adapter sequences, low-quality reads, and reads with >10% of Q < 20 bases, and then aligned to the B73 reference sequence (AGPv3, downloaded from Maize GDB, http://ftp.maizesequence.org/ current/) using TopHat [26], with no more than two base mismatches. Transcriptome assembly was carried out using the paired end assembly method as implemented in Cufflinks [27], and reads mapped to genomic regions were used to estimate gene expression levels. The raw gene expression counts were normalized using the reads per kilo base per million reads (RPKM) method. The calculated gene expressions eliminate the influence of different gene lengths and sequencing discrepancies, and can be used for direct comparison among samples [28]. DEGs were analyzed by comparison of cold-treated samples with the control. The Cuffdiff tool in the Cufflinks software package was used to identify DEGs using default parameters based on the Chi-square test. Computed P-values of each contrast were corrected for multiplicity using the FDR approach of Benjamini and Yekutieli [29]. In this experiment, a P ≤ 0.05 and a | log2 RPKM ratio | ≥ 1 were set as the thresholds to determine the significance of gene-expression difference between samples. All the DEGs identified from two genotypes were considered as cold-responsive genes. Heatmaps based on hierarchical cluster analysis of RPKM-normalized expression of common cold-responsive genes were generated using PermutMatrix [30] with Pearson correlation as the distance metric. GO annotation was performed, followed by functional classification using WEGO software [31], and KEGG ontology and enrichment analysis was performed with KOBAS 2.0 (KEGG Orthology Based Annotation System, v2.0) [32].

2.5. Validation of candidate cold-responsive DEGs by quantitative real-time PCR (qRT-PCR) Four DEGs (GRMZM2G427618, GRMZM2G101405, GRMZM2G106303, GRMZM2G054900) from C5 and six DEGs (GRMZM2G079632, GRMZM2G144420, GRMZM2G475059, GRMZM2G149756, GRMZM5G838285, GRMZM2G004795) from RC were randomly chosen for qRT-PCR assays. Primers were designed using Primer 3 (https://www.ncbi.nlm.nih.gov/tools/ primer-blast/) (Table S1).

3

RC and C5 were sown under the 28/25 °C condition until seedlings grew to the three-leaf stage, and were then exposed to treatment at 8/5 °C. Leaves and roots were sampled and mixed from five plants with three biological replicates of the 0 (before cold treatment), 8 h and 24 h cold treatments. Plant management, sample collection, and total RNA isolation were performed as described above. After RNase-free DNase I (TaKaRa Biomedical Technology (Beijing) Co. Ltd., China) treatment, approximately 1 μg total RNA was used for reverse transcription using Superscript II reverse transcriptase (TaKaRa Biomedical Technology (Beijing) Co. Ltd., China). qRT-PCR was performed using CFX96 (Bio-Rad Laboratories Inc., USA) and SYBR Green I (Tiangen Biotech (Beijing) Co., Ltd., China). Each cDNA sample was subjected to real-time PCR analysis in triplicate. The relative expression levels of genes were calculated using the 2–ΔΔCt method andglyceraldehyde-3-phosphate dehydrogenase (GAPDH) from maize as the reference gene. The thermal cycling conditions were as follows: pre-denaturation at 94 °C for 30 s; 94 °C for 5 s, 56 °C for 30 s, and 72 °C for 30 s, for 45 cycles.

3. Results 3.1. Phenotypic evaluation of experimental materials To assess the response of sweet corn seedlings to mild and severe low-temperature stress, RC and C5 seedlings at the three fully expanded leaf stage were subjected to T1 (15/12 °C) and T2 (8/5 °C) stress for 5 days, respectively. Visual damage was observed on the leaves of both genotypes five days after T2 treatment. RC seedlings showed obvious symptoms of chlorosis, whereas distinct wilting, dehydration, and dry necrosis of leaf edges were observed on C5 leaves. Morphological differences were also observed between CK and T1-stressed seedlings in either genotype (Fig. 1-A). In addition, the development of maize seedlings was significantly suppressed under cold conditions compared with the controls. After five days, the fresh weight of RC increased by 123.4% and 53.4% under CK and T1, and decreased slightly, by 0.5%, under T2. In contrast to a 37.1% increase under CK, the fresh weight of C5 plants declined by 1.2% and 52.2% after five days of T1 and T2, respectively (Fig. 1-B). Finally, RC showed 100% survival under both T1 and T2, whereas 100% and 60% of C5 plants survived after T1 and T2 treatment.

3.2. Physiological response of sweet corn seedlings to lowtemperature stress The physiological response of seedlings to low temperature was evaluated based on MDA content, SOD activity, and chlorophyll fluorescence parameters (Fv/Fm, ΦPSII, and NPQ) of leaves and the data are shown in Table 1. MDA content is considered to be a symptom of stress-induced membrane injury. MDA contents followed an increasing trend in both genotypes after one day of cold treatment. The MDA content in C5 rose from 0.016 (CK) to 0.023 (T1) and 0.034 (T2), and slightly increased from 0.013 (CK) to 0.016 (T1) and 0.023 (T2) in RC. MDA content was more markedly changed in C5 than in RC, indicating that C5 plants

Please cite this article as: J. Mao, et al., Comparative transcriptome analysis of sweet corn seedlings under low-temperature stress, The Crop Journal (2017), http://dx.doi.org/10.1016/j.cj.2017.03.005

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A

B

C5

RC

Change of fresh weight

RC

CK

T1

T2

CK

T1

C5

2% CK

T2

T1

T2

CK

T1

T2

Fig. 1 – Leaves and biomass changes of RC and C5 after cold stress. (A) Leaves from RC and C5 seedlings grown under 28/25 °C (CK), 15/12 °C (T1), and 8/5 °C (T2) conditions for five days. (B) Fresh weight changes of RC and C5 seedlings after 5 days under 28/25 °C (CK), 15/12 °C (T1), and 8 °C/5 °C (T2) conditions. Positive and negative numbers represent increase and decrease, respectively.

suffered more severe membrane damage under cold stress. SOD activity in RC plants was significantly decreased at the beginning and reduced by 22.8% and 50.2%, after five days under T1 and T2 treatments, respectively, whereas no significant change was found in C5·In addition, the photosynthetic systems of both genotypes were affected by low temperature stress, and the changes were more marked under T2 treatment. After one day of cold stress, maximum quantum efficiency of PSII primary photochemistry (Fv/Fm) and PSII operating quantum efficiency (ΦPSII) in RC decreased by 14.2% and 18.5%, respectively. For the cold-sensitive C5 line, the decreases in Fv/ Fm and ΦPSII were 24.0% and 39.6%, respectively. Under T1 treatment, the photosynthetic capacity of both genotypes changed modestly after three days. Non-photochemical quenching (NPQ), which might protect the photosynthesis apparatus from inactivation and damage caused by excess excitation, increased first and then decreased in both genotypes. Under different low-temperature treatments, the rise in NPQ tended to accompany the decrease in Fv/Fm and ΦPSII.

3.3. RNA-seq analysis and the identification of DEGs RNA-seq experiments yielded > 150 Mb raw data per sample. After low-quality reads were removed, 45–54 million clean

reads per sample were used for further analysis (Table 2). Finally, 66%–69% of the clean reads were uniquely mapped to the B73 reference genome, with 93% of unique reads mapping to protein-coding genes, 1.5%–4.0% distributed among introns, and 4.9%–12.9% located in intergenic regions. For 39,528 available gene models in the maize GDB database (APG3.0), about 57% of genes (22,822, 22,485, 22,675, and 22,533 genes in C5-CK, C5-T, RC-CK, and RC-T, respectively) were expressed (with RPKM ≥1). Among these, 1323 and 1451 genes were expressed specifically in RC and C5 plants, respectively; 749 and 891 genes were expressed specifically under T and CK conditions in RC; and 735 and 1072 genes were expressed specifically under T and CK conditions in C5. The number of overlapped gene (genes expressed in all libraries) was 20,423. Based on the principles of DEG identification, 357 genes were identified in RC, consisting of 187 up regulated and 135 down regulated DEGs (Table S2). A total of 455 DEGs were found in C5, consisting of 355 up regulated and 100 down regulated DEGs (Table S3). Fewer down regulated than up regulated DEGs were validated in both genotypes. The cold-sensitive line C5 was more affected by cold stress than the cold-tolerant line RC, indicating that the two genotypes showed different cold responses at the transcriptional level. GO assignments were used to classify the functions of DEGs

Table 1 – Effects of low-temperature on physiological indexes of sweet corn seedlings. Material

Day/night temperature (°C)

Treatment

MDA content (μmol g−1 FW)

SOD activity (U g− 1 FW)

Fv/Fm

RC

28/25 15/12

CK T1-1d T1-3d T1-5d T2-1d T2-3d T2-5d CK T1-1d T1-3d T1-5d T2-1d T2-3d T2-5d

0.013 0.016 0.015 0.014 0.023 0.021 0.028 0.016 0.023 0.021 0.024 0.034 0.039 –

210.87 132.97 100.36 162.74 169.24 116.64 105.09 120.64 118.92 142.69 111.99 131.64 120.65 –

0.765 0.745 0.709 0.711 0.656 0.660 0.388 0.772 0.741 0.733 0.725 0.587 0.604 –

8/5

C5

28/25 15/12

8/5

e d d de b c a e c d bd b a

a b c b b c c a a a a a a

a a b b c c d a a a a b b

ΦPSII 0.697 0.671 0.545 0.584 0.568 0.516 0.279 0.689 0.663 0.598 0.569 0.416 0.397 –

a a b b b c d a a b b c c

NPQ 0.175 0.173 0.443 0.192 0.317 0.661 0.300 0.080 0.067 0.465 0.434 0.257 0.675 –

c c b c bc a c cd d b bc c a

“–” The indexes could not be measured in wilted leaves under severe stress. Values followed by different letters in the same column are significantly different (LSD) at the 0.05 probability level.

Please cite this article as: J. Mao, et al., Comparative transcriptome analysis of sweet corn seedlings under low-temperature stress, The Crop Journal (2017), http://dx.doi.org/10.1016/j.cj.2017.03.005

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Table 2 – Data quality of RNA-seq and transcripts from two genotypes. Items Clean reads Mapped reads Unique mapped reads Distribution of reads

Expressed transcript

Exon Intron Intergenic

C5-CK

C5-T

RC-CK

RC-T

46,352,944 35,763,863 32,397,220 (100%) 93.4% 1.5% 5.0% 22,822

45,908,128 34,656,655 31,663,303 (100%) 93.0% 2.1% 4.9% 22,485

47,972,286 36,487,172 31,680,855 (100%) 93.2% 1.4% 5.5% 22,675

53,600,900 39,682,933 36,435,330(100%) 93.1% 2.0% 4.9% 22,533

C5-CK and C5-T indicate control and treated samples, respectively, in C5; RC-CK and RC-T represent control and treated samples, respectively, in RC.

responding to cold stress, and a total of 187 and 277 genes received GO function annotations in RC and C5, respectively. Three non-mutually exclusive GO categories, biological process (BP), cellular component (CC), and molecular function (MF), were well represented, as shown in Fig. 2. Of these, binding and catalytic activities were the most dominant categories in both RC and C5. But unlike in C5, no gene from RC was assigned to a “cellular component”, “structure formation”, or “nutrient reservoir” GO term.

3.4. Identification of common cold-responsive DEGs Genes with differential expression in at least one inbred line were defined as cold-responsive genes. Overlapping cold-responsive genes in both lines represent common cold-responsive genes and may represent shared common cold-responsive mechanisms in sweet corn [24]. Totals of 714 cold-responsive genes and 94 overlapped DEGs were identified (Table S4). Most common cold-responsive genes, consisting of 10 down regulated and 83 up regulated DEGs, showed similar expression patterns in both lines. Several distinct patterns of gene expression are shown on the heatmap (Fig. 3-A).

Cellular component Molecular function

To explore the putative cold-responsive mechanisms of sweet corn seedlings, Gene Ontology was used to classify the possible functions of the common cold-responsive genes (Fig. 3-B). The results showed that 39, 99, and 84 genes were assigned to cellular component, molecular function, and biological process, respectively. For cellular component, the three largest categories were cell (GO: 0005623), cell part (GO: 0044464), and organelle (GO: 0043226). For biological process, the three largest categories were metabolic process (GO: 0008152), biological regulation (GO: 0065007), and cellular process (GO: 0009987). In addition, two major categories, binding (GO: 0005488) and catalytic activity (GO: 0003824), of molecular function accounted for 40.5% and 32.1% of genes. Candidate cold-responsive genes encoding enzymes and protein kinases involved in calcium signal transduction were identified, including calmodulin/calcium dependent protein kinases (GRMZM2G330049, GRMZM2G178074, GRMZM2G096753, GRMZM2G378852, and GRMZM2G459824), calcium-transporting ATPase (GRMZM2G006977), and calmodulin-binding protein (GRMZM2G054900). These genes were up regulated by 5–20 fold under cold stress in both lines. In consistency with the reduction of photosynthetic

Biological process

Fig. 2 – GO term assignment to all DEGs in RNA-seq data. Differentially expressed genes were assigned to three groups: cellular components molecular function, and biological process. The X-axis displays the most abundant categories of each group, and the Y-axis displays the percentages and numbers of the total genes in each category. Please cite this article as: J. Mao, et al., Comparative transcriptome analysis of sweet corn seedlings under low-temperature stress, The Crop Journal (2017), http://dx.doi.org/10.1016/j.cj.2017.03.005

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A

B

Fig. 3 – Expression patterns and GO categories of common cold-responsive genes. (A) Expression analysis of 94 candidate common cold-responsive genes analyzed using PermutMatrix. The RPKMs of common cold-responsive DEGs were normalized by calculating Z-scores and then used for hierarchical cluster analysis. Red, black, and green indicate high, medium, and low levels of gene expression, respectively. (B) GO term categories of common cold-responsive genes.

efficiency induced by cold treatment, two chlorophyll A-B binding proteins were commonly down regulated. One of them, GRMZM2G104549, was significantly down regulated by 5- and 11-fold in RC and C5, respectively.

3.5. Analysis of cold tolerance-associated functional genes Genes exhibiting a different response (induction or repression) in one line than in another were designated as cold tolerance-associated genes. A total of 228 and 361 such genes were found in RC and C5, respectively. Most of them encoded transcription factors (TF), including members of the WRKY superfamily, the R2R3-MYB family, AP2 family, and the bHLH gene family, and zinc finger transcription factors, as shown in Table 3. A total of 30 and 44 TFs were found in RC and C5 (Table S5), and accounted for 13.2% and 12.2% of cold tolerance-associated genes in each line, respectively. It should be noted that members of some gene families were expressed commonly in cold-tolerant and sensitive lines. For example, three genes encoding AP2 domain containing protein (AC198403, GRMZM2G149756, and GRMZM2G307152) were up regulated in RC under cold stress, whereas another six gene family members (GRMZM2G066158, GRMZM2G434203, AC233933, GRMZM2G132223, GRMZM2G384386, and GRMZM2G060517) were detected in C5. Other types of genes exhibited genotype specificity. The expression of genes encoding protein phosphatase 2C (GRMZM2G177386, GRMZM2G166297, GRMZM2G001243, GRMZM2G082487, GRMZM2G308615, GRMZM2G159811, GRMZM2G122228, and GRMZM2G150468) changed significantly in the cold-sensitive C5 line but not in the cold-tolerant RC line. Genes encoding remorin proteins (GRMZM2G099239 and GRMZM2G081949) and rare cold inducible/plasma membrane protein 3 gene (GRMZM2G015605) were detected only in RC.

KEGG pathway analysis of cold tolerance-associated genes was performed to provide hints at their roles in different biological pathways. A total of 92 and 126 genes could be annotated by the KEGG pathway in RC and C5 lines, respectively. Only six and 15 pathways, respectively, were mapped, owing to the limited database and gene numbers. In the cold-tolerant RC line (Table S6), genes involved in carotenoid biosynthesis (zma00906) and plant hormone signal transduction (zma04075) pathways were markedly up regulated. Down regulated genes were significantly overrepresented in the pathways glycosphingolipid biosynthesis-globo series (zma00603) and protein processing in endoplasmic reticulum (zma04141). More pathways were affected by low temperature in the cold-sensitive C5 line (Table S7) than in the cold-tolerant RC line. Up regulated genes were involved in carbohydrate metabolism (zma00052), amino acid metabolism (zma00330//arginine and proline metabolism; zma00380//tryptophan metabolism), biosynthesis of secondary metabolites (zma00904//diterpenoid biosynthesis, zma00950//isoquinoline alkaloid biosynthesis and zma00941//flavonoid biosynthesis), and a pathway with protective activities (zma00480//glutathione metabolism). However, only lipid metabolism (zma00073//cutin, suberine and wax biosynthesis) was significantly enriched in down regulated cold tolerance-associated genes.

3.6. Validation of DEGs by qRT-PCR To validate candidate cold-responsive DEGs, 10 DEGs with marked changes were selected and further analyzed by qRT-PCR (Fig. 4). Of these, the gene expression levels of GRMZM2G101405, GRMZM2G054900, GRMZM2G079632, GRMZM2G144420, GRMZM5G838285, and GRMZM2G004795

Please cite this article as: J. Mao, et al., Comparative transcriptome analysis of sweet corn seedlings under low-temperature stress, The Crop Journal (2017), http://dx.doi.org/10.1016/j.cj.2017.03.005

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Table 3 – Some differentially regulated TFs in RC and C5 lines. Material RC

C5

Gene locus

TF family

Ratio (T/CK) a

GRMZM2G149756 AC198403 GRMZM2G307152 GRMZM2G119823 AC193786 GRMZM2G101350 GRMZM2G093020 GRMZM2G147716 GRMZM2G084583 GRMZM2G079632 GRMZM2G064541 GRMZM5G871347 GRMZM2G144346 GRMZM2G082376 GRMZM2G132751 GRMZM2G123212 GRMZM2G123212 GRMZM2G098925 GRMZM2G114137 GRMZM2G146614 GRMZM2G066158 GRMZM2G434203 AC233933 GRMZM2G132223 GRMZM2G384386 GRMZM2G062541 GRMZM2G333582 GRMZM2G082343 GRMZM2G170079 GRMZM2G033230 GRMZM2G366130 GRMZM2G074908 GRMZM2G087955 GRMZM2G016370 GRMZM2G029850 GRMZM2G172264 GRMZM2G465835 GRMZM2G156977 GRMZM2G081930

AP2 AP2 AP2 bHLH bHLH bHLH bZIP MADS MYB NAC NAC WRKY Zinc finger Zinc finger Zinc finger Zinc finger Zinc finger Zinc finger Zinc finger Zinc finger AP2 AP2 AP2 AP2 AP2 bHLH bHLH bHLH bZIP bZIP HD-ZIP MYB MYB MYB MYB NAC NAC NAC NAC

13.34 12.64 15.04 −11.31 −9.40 6.01 8.47 7.27 −10.29 5.64 5.71 6.23 −11.87 −11.25 −11.24 −10.99 −10.99 −8.74 −6.36 6.78 5.90 6.82 8.16 8.24 8.52 5.79 9.50 9.92 −8.70 9.84 20.08 6.60 7.05 23.61 26.93 6.96 7.47 7.72 10.06

a

Positive and negative numbers represent increase and decrease, respectively.

quickly increased within 8 h after cold treatment and then declined. In contrast, steady up regulation of genes GRMZM2G427618, GRMZM2G106303, GRMZM2G475059, and GRMZM2G149756 was observed over 24 h. All the genes showed higher expression under cold conditions, indicating that the cold-responsive DEGs identified by RNA-seq were reliable.

4. Discussion 4.1. Prerequisites for the identification of candidate coldresponsive genes in sweet corn In this study, we observed different responses to low temperature in RC and C5 sweet corn inbred lines. We also studied the physiological response patterns of two sweet corn genotypes when they were subjected to low temperatures for

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1, 3, and 5 days, to identify the time points at which gene expression was significantly changed. 15/12 °C (T1) and 8/5 °C (T2) were used to simulate mild and severe cold stress conditions, respectively. The temperatures were justified as seeing in previous studies [12,18–20]. Mild cold stress did not impair membrane and photosynthetic activities, although growth retardation was observed in both lines. Slight but significant decreases in Fv/Fm and ΦPSII were signs of chronic photoinhibition under the T1 condition, and enhanced NPQ prevented or reduced the potential damage (Table 1). Severe cold stress caused distinct membrane injury, reduced photosynthesis, and ultimately plant death. Despite rapid and positive responses in NPQ, Fv/Fm, and ΦPSII suddenly decreased after three days under T2 treatment, indicating that the photosynthetic systems were irreversibly damaged. The T2 treatment was chosen to explore candidate genes and cold acclimatization. Plant cold response can be divided into i) the alarm phase, characterized by extensive changes at the physiological and biochemical levels, and ii) the acclimation phase, corresponding to a metabolic shift leading to increased tolerance [33]. Because the two lines indeed showed markedly different physiological responses to cold stress after one day, 8 h and 24 h after stress were chosen as sampled time point for RNA-seq. DEGs identified in present study would include genes associated with cold stress alarm and acclimation phase.

4.2. Abundance of DEGs in response to cold stress in tolerant and sensitive lines RNA-seq technology was used to compare the transcriptomes of seedlings treated with low temperature to those grown under control conditions. Maize is rich in genetic and phenotypic diversity. A RNA-seq study of 21 maize inbred lines, from Stiff Stalk Synthetic and Non-Stiff Stalk Synthetic, showed that between 74.57% and 87.81% of reads could be mapped to the maize reference sequence [34]. Sweet corn belong to a special group which is not considered as a “reference” for maize genetics. Until now, most genomic or gene sequence researches focused on common maize, and there was little available information about sweet corn. Our research shown the sequence differences between sweet corn and common maize were more than those among common maize inbred lines. Recently, two maize inbred lines and their hybrid were used in a RNA-seq study, and 64%–79% of total paired reads aligned to the B73 reference genome [22]. Considered that, our result was acceptable and could be used for further research. In total, 357 and 455 genes were identified as being cold-responsive in RC and C5, respectively. Of these, 94 were identified as common cold-responsive genes in both genotypes. Previous studies have identified many cold-responsive genes of maize, 440 and 155 transcripts affected in the cold alarm and cold acclimation phases were detected [19]. In another study, only 18 cold-responsive genes were identified [18]. These discrepancies reflect the cold responses of specific genotypes, and the results were difficult to compare. Recently, a comparative analysis of gene expression changes in response to cold stress in two inbred maize lines was reported

Please cite this article as: J. Mao, et al., Comparative transcriptome analysis of sweet corn seedlings under low-temperature stress, The Crop Journal (2017), http://dx.doi.org/10.1016/j.cj.2017.03.005

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Fig. 4 – The dynamic expression patterns of 10 cold-responsive DEGs by qRT-PCR. The expression patterns of GRMZM2G079632, GRMZM2G144420, GRMZM2G475059, GRMZM2G149756, GRMZM5G838285, and GRMZM2G004795 in RC, and GRMZM2G427618, GRMZM2G101405, GRMZM2G106303, and GRMZM2G054900 in C5. The X-axis represents hours after stress, while the Y-axis represents cold-induced gene expression changes. Maize GAPDH was chose as reference gene and the gene expression level at 0 h (before cold treatment) was defined as 1.

by Sobkowiak et al. [35]. Owing to the same genetic origin of the materials, 2500 DEGs showed a response common to both lines and only 66 genes were differentially expressed [15]. In our study, two contrasting cold tolerance inbred lines were evaluated and a comparative analysis of DEGs provided numerous cold-responsive candidate genes. Some putative

cold-responsive genes with large changes in expression during cold stress were found. Previous studies have revealed some genes and metabolic pathways involved in environmental stress tolerance, such as calmodulin/calcium dependent protein kinases [36–38], chlorophyll A-B binding protein [19,39], and members of the WRKY superfamily [35]. Novel

Please cite this article as: J. Mao, et al., Comparative transcriptome analysis of sweet corn seedlings under low-temperature stress, The Crop Journal (2017), http://dx.doi.org/10.1016/j.cj.2017.03.005

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cold-responsive genes identified in the present study may help to provide a deeper understanding of cold tolerance mechanisms in maize. Our study had some limitations. Two samples, at 8 h and 24 h after stress, were pooled for RNA-seq analysis. This pooling might have led to errors in DEG analysis and hence failed to reflect accurately the gene expression patterns under stress. Second, our methods lacked biological replicates, possibly reducing the reliability of our results. For this reason, we used qRT-PCR analysis to reduce the effect of these limitations, resulting in preliminary verification of 10 selected genes.

4.3. Potential candidate genes involved in cold tolerance of sweet corn Plant hormones are thought to play important roles in either the regulation of plant growth and development or the response to stress. In this study, many genes involved in plant hormone signal transduction showed differential expression under cold stress in both genotypes. Abscisic acid (ABA) is one of the main plant hormones mediating plant responses to environmental stresses. 9-cisepoxycarotenoid dioxygenase (NCED3) is the key enzyme in ABA biosynthesis and PP2C is a negative regulator of the ABA response [40]. Two genes homologous to NCED3 were up regulated in sweet corn, implying that the ABA signaling pathway was induced under cold stress. However, up regulation of eight PP2C genes was observed only in the cold-sensitive C5 line. We speculate that the cold-tolerant sweet corn accumulated much more ABA than the sensitive line to reduce the accumulation of ROS induced by low temperatures and to protect the cellular functions. We also found that the expressions of genes, associated with metabolic pathways of growth stimulators, changed greatly. GAs comprised of group of growth hormones control diverse processes, including cell elongation and leaf senescence [41]. Among the GA-associated genes, GA2ox7 was significantly up regulated by cold stress and more homologous genes were detected in C5 than in RC. GA2ox7 belongs to the GA 2-oxidation family, mediating a well-characterized type of GA catabolism that is involved in the deactivation of GA [42]. The reduction of GA activity appears to be associated with leaf senescence during cold stress. Cytokinin-O-glucosyltransferase is responsible for the reversible inactivation of cytokinins [43]. Several genes encoding that were up regulated by cold stress in the present study. Additionally, cytokinin oxidase/dehydrogenase, another negative regulator of cytokinin [44], was up regulated in C5. One may thus expect decreased cytokinin levels in the seedlings. We also observed the expression of early auxin-responsive factors (OsSAUR58, OsSAUR53, and OsSAUR16) to be increased in C5, but the function of these genes is poorly understood. Together, these findings strongly suggest that diverse hormones modulate the growth of sweet corn seedlings by responding to cold, especially in cold-sensitive genotypes. Hormone-associated DEGs may play important roles in cold tolerance. Membranes represent a primary site of cold-induced injury and also act as a receptor of the low temperature stress signal. Remorins are a set of hydrophilic proteins attached to the

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plasma membrane that may be structural components of plant cytoskeletons and/or membrane skeletons [45]. Some of these proteins may have key functions during responses to biotic and abiotic stimuli and maybe involved in hormone-mediated responses and signal transduction [46]. Genes encoding remorin proteins (GRMZM2G099239 and GRMZM2G081949) and rare cold inducible/plasma membrane protein 3 (RCI) (GRMZM2G015605) were significantly up regulated in the cold-tolerant sweet corn seedlings. It has been proposed that Arabidopsis RCI2A may act as a membrane protein stabilizer [47]. Kim et al. [48] reported that overexpression of OsLti6b, which encodes a protein homologous to AtRCI2A, increased cold tolerance in transgenic plants by reducing seedling wilting rates and ion leakage of mature leaves. We propose that the cell membrane participates in the early response to cold stress and that membrane composition may explain the variation in cold tolerance in maize observed in this study. Supplementary data for this article can be found online at http://dx.doi.org/10.1016/j.cj.2017.03.005.

Acknowledgments This study was supported by the Sciences and Technology Project of Guangdong Province (Nos. 2014B070706012, 2015B020202006), the Foundation of the President of the Guangdong Academy of Agricultural Sciences (No. 201509), and the Science and Information Technology Bureau of Guangzhou (No. 2013J2200083).

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