Abstract

   Sub-optimal temperatures can adversely affect tomato (Solanum
   lycopersicum) growth, and K^+ plays an important role in the cold
   tolerance of plants. However, gene expression and K^+ uptake in tomato
   in response to sub-optimal temperatures are still not very clear. To
   address these questions, one cold-tolerant tomato cultivar, Dongnong
   722 (T722), and one cold-sensitive cultivar, Dongnong 708 (S708), were
   exposed to sub-optimal (15/10 °C) and normal temperatures (25/18 °C),
   and the differences in growth, K^+ uptake characteristics and global
   gene expressions were investigated. The results showed that compared to
   S708, T722 exhibited lower reduction in plant growth rate, the whole
   plant K^+ amount and K^+ net uptake rate, and T722 also had higher
   peroxidase activity and lower K^+ efflux rate under sub-optimal
   temperature conditions. RNA-seq analysis showed that a total of 1476
   and 2188 differentially expressed genes (DEGs) responding to
   sub-optimal temperature were identified in S708 and T722 roots,
   respectively. Functional classification revealed that most DEGs were
   involved in “plant hormone signal transduction”, “phenylpropanoid
   biosynthesis”, “sulfur metabolism” and “cytochrome P450”. The genes
   that were significantly up-regulated only in T722 were involved in the
   “phenylpropanoid biosynthesis” and “plant hormone signal transduction”
   pathways. Moreover, we also found that sub-optimal temperature
   inhibited the expression of gene coding for K^+ transporter SIHAK5 in
   both cultivars, but decreased the expression of gene coding for K^+
   channel AKT1 only in S708. Overall, our results revealed the cold
   response genes in tomato roots, and provided a foundation for further
   investigation of mechanism involved in K^+ uptake in tomato under
   sub-optimal temperatures.

   Keywords: sub-optimal temperature, tomato, transcriptome, potassium,
   uptake

1. Introduction

   Tomato (Solanum lycopersicum), which originated in sub-tropical areas
   [[38]1], is sensitive to chilling temperature [[39]2,[40]3]. However,
   its production areas usually experience sub-optimal temperatures (which
   range between two thresholds, a minimum (8–12 °C) and an optimum (25–27
   °C)) [[41]4,[42]5,[43]6]. Sub-optimal temperatures affect the
   vegetative and fruit growth of tomato plants, which ultimately leads to
   decline in the yield [[44]1]. Hence, to improve tomato production and
   breeding under these conditions, it is necessary to understand the
   mechanisms underlying tomato responses to sub-optimal temperatures.

   Plants can respond and tolerate to cold stress by changing several
   biochemical processes and traits features [[45]7]. These changes
   include alterations in the composition, structure, and function of the
   plasma membrane; synthesis of cryoprotectant molecules, including
   soluble sugars and low-molecular-weight nitrogenous compounds, such as
   proline; and increases in the scavenging activity of reactive oxygen
   species (ROS) [[46]8,[47]9]. Peroxidase (POD) is one of the most
   important antioxidative enzymes, and can alleviate oxidative damage by
   scavenging ROS under stress conditions [[48]10,[49]11]. Cold
   temperatures also induce cascades of alterations in metabolic pathways,
   including the phenylpropanoid pathway, and in the activities of
   antioxidant enzymes [[50]12]. As one of the most important inorganic
   osmotica in plants, potassium (K) plays key role in establishing the
   osmotic adjustment ability [[51]13,[52]14]. The available evidence
   suggest that K improves plant survival rate under cold stress by
   reducing ROS accumulation and increasing antioxidant levels
   [[53]15,[54]16]. A significant negative correlation has been found
   between the leaf K concentration and frost damage, and an adequate K
   supply can effectively increase the frost resistance of plants, whereas
   K deficiency can increase the susceptibility of plants to low
   temperatures [[55]17,[56]18,[57]19]. The K requirement of greenhouse
   tomato plants is very high for vegetative growth and fruit production
   [[58]20], but little is known regarding the K^+ uptake characteristics
   of two tomato cultivars differing in cold resistance under sub-optimal
   temperature conditions.

   In plant roots, K^+ uptake from the outer environment is mainly
   mediated by K^+ channels and transporters [[59]21,[60]22,[61]23]. All
   abiotic stress results in disturbance to K^+ homeostasis and provokes a
   feedback control on K^+ channels and transporters expression and
   post-translational regulation of their activity, optimizing K^+
   absorption and usage [[62]24,[63]25,[64]26]. However, few studies have
   focused on the expression of genes related to K^+ uptake and
   translocation during exposure to sub-optimal temperature stress.
   Although some studies have reported that low temperature decreases the
   uptake [[65]27] and influx [[66]26] of K^+, it is still unclear whether
   sub-optimal temperatures affect K^+ uptake and translocation by
   affecting the expression of genes coding for K^+ channels and
   transporters.

   RNA sequencing (RNA-seq) is a critical method for profiling global gene
   expression in response to biotic and abiotic stress [[67]28,[68]29]. In
   tomato, transcriptome profiling has been used for comparative analysis
   of expression of defense related genes between two tomato cultivars
   with different resistances to salt, cold and disease stress
   [[69]30,[70]31,[71]32]. However, to the best of our knowledge, a
   transcriptome analysis of tomato under sub-optimal temperature
   conditions that focuses on the root system has not been reported yet.

   In this study, we profiled differences in plant growth, K^+ uptake, and
   gene expression changes by making comparison between one cold-sensitive
   and one cold-tolerant tomato cultivar exposed to sub-optimal
   temperature conditions. We hypothesized that (1) under sub-optimal
   temperature conditions, the plant growth rate (PGR) and the POD
   activity of roots in cold-tolerant cultivar would be higher than that
   in the cold-sensitive cultivar; and (2) the cold-tolerant cultivar
   would exhibit enhanced cold tolerance by regulating not only the
   expression of genes related to cold tolerance in roots, but also K^+
   uptake. As mentioned earlier, K^+ uptake from outside is mainly
   mediated by K^+ channels and transporters; thus, we also hypothesized
   that (3) sub-optimal temperatures could inhibit the expression of genes
   coding for K^+ channels and transporters in roots, and that the
   inhibitory effect on cold-sensitive tomato would be stronger than that
   on cold-tolerant tomato.

2. Results

2.1. Plant Dry Weight and Root Morphology

   After 5 and 10 days after treatment (DAT), the increase in plant height
   (IPH), plant growth rate (PGR), root surface area and total root length
   of the two tomato cultivars under sub-optimal temperature were
   measured. Temperature significantly affected IPH, PGR, root surface
   area and total root length ([72]Table 1). Compared with the normal
   temperature treatment (CK), sub-optimal temperature (T) significantly
   decreased the IPH, PGR, root surface area and total root length in S708
   at 5 DAT, and decreased these parameters in both tomato cultivars at 10
   DAT. Under sub-optimal temperature conditions, the magnitude of
   decreases of IPH and PGR in S708 was larger than that in T722 at 5 and
   10 DAT ([73]Figure 1). There was a significant two-way interaction
   between temperature and cultivar for IPH and PGR at 10 DAT ([74]Table
   1).

Table 1.

   F-value from two-way ANOVA analysis of effects of cultivar and
   temperature treatment on IPH, PGR, root surface area, total root
   length, MDA content and POD activity.
   DAT Variables IPH PGR Root Surface Area Total Root Length MDA Content
   POD Activity
   5 Cultivar (C) 23.74 ** 26.60 ** 2.81 ns 77.94 *** 13.64 * 107.19 ***
   Temperature (T) 113.77 *** 53.86 *** 40.71 *** 72.83 *** 62.28 **
   740.64 ***
   C × T 3.40 ns 12.75 * 4.88 ns 13.48 ** 23.23 ** 70.22 ***
   10 Cultivar (C) 30.77 ** 11.34 * 30.09 ** 4.30 ns 4.25 ns 52.14 ***
   Temperature (T) 296.34 *** 181.36 *** 93.44 *** 114.79 *** 34.88 **
   390.29 ***
   C × T 16.13 ** 16.93 ** 1.91 ns 3.79 ns 3.81 ns 42.14 ***
   [75]Open in a new tab

   ns not significant. * p ≤ 0.05, ** p ≤ 0.01, *** p ≤ 0.001.

Figure 1.

   [76]Figure 1
   [77]Open in a new tab

   Phenotypic response of the two tomato cultivars to sub-optimal
   temperature. (a) Increase in plant height (IPH), (b) plant growth rate
   (PGR), (c) root surface area, and (d) total root length of S708 and
   T722 cultivars grown at normal temperature (CK, 25/18 °C) and
   sub-optimal temperature (T, 15/10 °C) at 5 and 10 DAT. Data are the
   means with standard deviation shown by vertical bars (n = 3
   representing 3 biological replicates). The different small letters
   above the bars represent significant differences attested by the
   Tukey’s HSD test (p < 0.05).

2.2. MDA Content and POD Activity

   Temperature significantly affected malondialdehyde (MDA) content and
   POD activity at 5 and 10 DAT ([78]Table 1). Both cultivars exhibited an
   increase in MDA content after treated with sub-optimal temperature (T)
   at 10 DAT ([79]Figure 2), and the magnitude of increase in MDA content
   in S708 was larger than that in T722 at 5 and 10 DAT. Sub-optimal
   temperature significantly increased the POD activity in both cultivars
   at both sampling dates, and the magnitude of increase in POD activity
   in T722 was larger than that in S708. There was a significant two-way
   interaction between temperature and cultivar for POD activity at 5 and
   10 DAT ([80]Table 1).

Figure 2.

   [81]Figure 2
   [82]Open in a new tab

   Physiological responses of the two tomato cultivars to sub-optimal
   temperature. (a) MDA content and (b) POD activity of S708 and T722
   cultivars grown at normal temperature (CK, 25/18 °C) and sub-optimal
   temperature (T, 15/10 °C) at 5 and 10 DAT. Data are the means with
   standard deviation shown by vertical bars (n = 3 representing 3
   biological replicates). The different small letters above the bars
   represent significant differences attested by the Tukey’s HSD test (p <
   0.05).

2.3. K^+ Content in Different Organs and K^+ Uptake by Whole Plants

   Sub-optimal temperature treatment (T) significantly increased the roots
   K^+ content in both tomato cultivars at 5 DAT, although the roots K^+
   content did not differ between the normal (CK) and sub-optimal
   temperature treatments in both cultivars at 10 DAT ([83]Table 2).
   Temperature significantly affected K^+ content in stem. The stem K^+
   contents obtained for S708 at 5 and 10 DAT at sub-optimal temperature
   were 8.73% and 13.45% lower, respectively, than those obtained with the
   normal temperature treatment, whereas the rates obtained for T722 were
   5.99% and 5.03% lower, respectively, than those obtained with the
   normal temperature treatment. Sub-optimal temperature significantly
   reduced the leaves’ K^+ content in S708 at 10 DAT, although the leaf
   K^+ content did not differ between the normal and sub-optimal
   temperature treatments in both cultivars at 5 DAT. For each cultivar,
   the whole plant K^+ amount was significantly lower under sub-optimal
   temperature treatment than under normal temperature treatment at both
   sampling dates. The whole plant K^+ amounts obtained for S708 at 5 and
   10 DAT with sub-optimal temperature were 45.01% and 36.98% lower,
   respectively, than those obtained with the normal temperature
   treatment, whereas the rates obtained for T722 at 5 and 10 DAT with
   sub-optimal temperature were 17.26% and 19.09% lower, respectively,
   than those obtained with the normal temperature treatment. Moreover, at
   the same sampling date, the whole plant K^+ amount obtained for T722
   was higher than that obtained for S708 under normal and sub-optimal
   temperature conditions ([84]Table 2).

Table 2.

   K^+ content in roots, stems and leaves and K^+ amount in whole plants
   of the S708 and the T722 cultivar under normal (CK, 25/18 °C) and
   sub-optimal temperature (T, 15/10°C) conditions at 5 and 10 DAT. Data
   are the means with standard deviation (n = 3 representing 3 biological
   replicates). Different letters on the same column indicate significant
   differences attested by the Tukey’s HSD test (p < 0.05). F-value from
   two-way ANOVA analysis of effects of cultivar and temperature treatment
   on K^+ content in roots, stems and leaves and K^+ amount in whole
   plants.
   DAT Treatments K^+ Content (mg g^−1) K^+ Amount (mg Plant^−1)
   Root Stem Leaf
   5 S708 CK 23.76 ± 0.60 b 46.69 ± 0.55 b 25.11 ± 1.55 ab 15.45 ± 0.50 c
   S708 T 28.17 ± 1.31 a 42.62 ± 1.30 c 22.68 ± 0.52 b 8.48 ± 0.70 d
   T722 CK 23.69 ± 1.60 b 52.38 ± 0.96 a 26.55 ± 1.73 a 26.01 ± 1.01 a
   T722 T 27.40 ± 0.98 a 49.24 ± 0.92 b 26.18 ± 1.15 ab 21.52 ± 0.87 b
   Analysis of variance
   Cultivar (C) ns *** * ***
   Temperature (T) ** *** ns ***
   C × T ns ns ns ns
   10 S708 CK 26.70 ± 2.14 50.76 ± 2.38 a 27.46 ± 0.78 a 27.85 ± 0.98 c
   S708 T 29.07 ± 1.44 43.96 ± 1.51 b 22.90 ± 1.11b 17.55 ± 0.54 d
   T722 CK 24.68 ± 1.18 51.61 ± 0.74 a 27.66 ± 0.78 a 41.44 ± 0.39 a
   T722 T 26.17 ± 0.79 49.62 ± 0.74 a 26.48 ± 1.22 a 33.53 ± 1.23 b
   Analysis of variance
   Cultivar (C) ns * * ***
   Temperature (T) ns ** ** ***
   C × T ns ns * ns
   [85]Open in a new tab

   ns not significant. * p ≤ 0.05, ** p ≤ 0.01, *** p ≤ 0.001.

2.4. K^+ Net Uptake Rate and K^+ Transportation Ratio

   Sub-optimal temperature significantly decreased the K^+ net uptake rate
   and K^+ transportation ratio in both tomato cultivars during 5–10 days
   ([86]Figure 3). Compared with normal temperature treatment, the
   magnitude of decreases in K^+ net uptake rate and K^+ transportation
   ratio under sub-optimal temperature in S708 was larger than that in
   T722. There was a significant two-way interaction between temperature
   and cultivar for K^+ net uptake rate ([87]Figure 3).

Figure 3.

   [88]Figure 3
   [89]Open in a new tab

   K^+ net uptake rate and K^+ transportation ratio of S708 and T722
   cultivars under normal (CK, 25/18 °C) and sub-optimal temperature (T,
   15/10 °C) conditions. (a) K^+ net uptake rate during days 5–10 of
   growth. (b) The percentage of net increased K^+ in shoots to net
   increased total K^+ in the entire plant during the days 5–10 of growth.
   Data are the means with standard deviation shown by vertical bars (n =
   3 representing 3 biological replicates). The different small letters
   above the bars represent significant differences attested by the
   Tukey’s HSD test (p < 0.05). F-values from two-way ANOVA analysis of
   effects of cultivar and temperature treatment on K^+ net uptake rate
   and K^+ transportation ratio. *p ≤ 0.05, **p ≤ 0.01, ***p ≤ 0.001.

2.5. K^+ Flux Rate

   At 5 hours after treatment, the mean flux of K^+ towards the external
   medium in T722 was negative under normal temperature (CK) and
   sub-optimal temperature (T), indicating the occurrence of K^+ influx in
   the roots ([90]Figure 4a). In contrast, the mean flux of K^+ obtained
   in S708 was positive under normal temperature and sub-optimal
   temperature conditions, indicating the occurrence of K^+ efflux in the
   roots. At 5 DAT, K^+ influx occurred in both cultivars under normal
   temperature condition; however, the K^+ efflux of both cultivars
   increased markedly under sub-optimal temperature conditions, and a more
   pronounced increase was observed in S708 ([91]Figure 4a). At 5 hours
   after treatment, the net flux of K^+ in both cultivars exhibited a
   stable and constant flux during the 10 min measurement period under
   normal and sub-optimal temperature conditions ([92]Figure 4b). At 5
   DAT, the trend of net flux of K^+ in S708 was similar to that in T722
   under normal and sub-optimal temperature conditions. The K^+ efflux
   increased from 227 to 308 pmol cm^−2 s^−1 in the S708 cultivar, and
   from 65.57 to 92.62 pmol cm^−2 s^−1 in T722 during the 10 min
   measurement period under sub-optimal temperature condition ([93]Figure
   4b).

Figure 4.

   [94]Figure 4
   [95]Open in a new tab

   Net flux of K^+ in root tips of S708 and T722 cultivars under normal
   (CK, 25/18 °C) and sub-optimal temperature (T, 15/10 °C) conditions.
   After being treated with normal and sub-optimal temperatures for 5
   hours and 5 days, a continuous flux recording of 10 min was conducted.
   (a) Mean fluxes of K^+ and (b) net flux of K^+ in both cultivars within
   the measuring periods. The data were collected every 6 s during the 10
   min measuring period. The positive values in the figures represent K^+
   efflux and negative values represent K^+ influx.

2.6. Summary of RNA-Seq Data

   To investigate the alterations in root gene expression regulated by
   sub-optimal temperatures, an RNA-Seq analysis of roots taken from S708
   and T722 plants at 5 DAT was conducted using Illumina sequencing
   technology. More than 40 million (M) single-end reads were generated
   for each library, and the total number of clean reads ranged from 40 to
   60 M, with a mapping rate over 95% ([96]Table S1).

2.6.1. DEGs in Response to Sub-Optimal Temperature

   The significant DEGs were identified by the criteria of at least a
   2-fold change, and the p-value of the false discovery (FDR) correction
   had to be less than 0.05 between the treated and control groups of S708
   and T722 cultivars. The FPKM and FDR values and the fold-changes for
   each gene of the S708 and T722 cultivar are shown in [97]Supplementary
   Tables S2 and S3, respectively. The results showed that the number of
   up-regulated or down-regulated DEGs was much higher in T722 than in
   S708 ([98]Figure 5). Moreover, 731 and 901 genes were up-regulated in
   S708 and T722, respectively, and 362 genes were common in both tomato
   cultivars ([99]Figure 5a); 745 and 1287 genes were down-regulated in
   S708 and T722, respectively, and 446 genes were common in both tomato
   cultivars ([100]Figure 5b).

Figure 5.

   [101]Figure 5
   [102]Open in a new tab

   Venn diagrams showing differentially up-regulated (a) or down-regulated
   (b) genes in S708 CK vs. S708 T and T722 CK vs. T722 T. S708 CK and
   T722 CK: S708 and T722 tomato seedlings grown under normal temperature
   condition (CK, 25/18 °C), S708 T and T722 T: S708 and T722 tomato
   seedlings grown under sub-optimal temperature conditions (T, 15/10 °C).
   The numbers above the circles indicate the total number of up- or
   down-regulated genes at sub-optimal temperature in each cultivar.

2.6.2. GO and KEGG Enrichment Analysis of DEGs

   To unravel the significantly altered biological processes upon cold
   stress, the DEGs of the two tomato cultivars were subjected to the GO
   term enrichment analysis [[103]33]. Some stress-related GO biological
   process terms, such as ‘oxidation-reduction process’, ‘hydrogen
   peroxide metabolic process’ and ‘hydrogen peroxide catabolic process’
   were significantly enriched (p < 0.001) in both tomato cultivars
   ([104]Table S4). More GO terms were significantly enriched (p < 0.001)
   in T722. Among these, two were involved in stress responses, including
   ‘response to stimulus’ and ‘phenylpropanoid metabolic process’ and four
   were involved in hormone responses, including ‘hormone metabolic
   process’, ‘hormone biosynthetic process’, ‘cytokinin biosynthetic
   process’ and ‘cytokinin biosynthetic process’ ([105]Table S4).

   To study the biological pathways associated with the DEGs, a KEGG
   pathway analysis of all the DEGs was performed. We summarized the top
   10 enriched KEGG pathways, and the up- and down-regulated DEGs in the
   KEGG pathway are shown in [106]Table S5. In the main text, we describe
   four significantly enriched KEGG pathways. The DEGs in the S708 CK-S708
   T and T722 CK-T722 T groups were significantly enriched in four
   metabolic pathways with p-values < 0.05: “plant hormone signal
   transduction” (24 DEGs/38 DEGs), “phenylpropanoid biosynthesis” (28
   DEGs/42 DEGs), “sulfur metabolism” (8 DEGs/10 DEGs) and “cytochrome
   P450” (13 DEGs/16 DEGs) ([107]Table 3).

Table 3.

   Significantly enriched KEGG pathway of differentially expressed genes
   (DEGs) in response to sub-optimal temperature (T, 15/10 °C).
   Pathway Number of Up-Regulated Genes Number of Down-Regulated Genes
   Pathway ID
   S708 CK-S708 T Plant hormone signal transduction 17 7 ko04075
   Phenylpropanoid biosynthesis 13 15 ko00940
   Sulfur metabolism 8 0 ko00920
   Cytochrome P450 8 5 ko00982
   T722 CK-T722 T Plant hormone signal transduction 21 17 ko04075
   Phenylpropanoid biosynthesis 24 18 ko00040
   Sulfur metabolism 8 2 ko00920
   Cytochrome P450 8 8 ko00982
   [108]Open in a new tab

   Among the DEGs, 11 genes in the significantly enriched KEGG pathway
   “plant hormone signal transduction” were significantly induced by
   sub-optimal temperature in T722 ([109]Table 4), and 12
   peroxidase-related genes in the significantly enriched KEGG pathway
   “phenylpropanoid biosynthesis” were significantly induced by
   sub-optimal temperature in T722 ([110]Table 5).

Table 4.

   List of selected genes induced by sub-optimal temperature (T, 15/10 °C)
   in the significantly enriched KEGG pathway “plant hormone signal
   transduction” only in T722. S708 and T722 tomato cultivars grown under
   normal (CK, 25/18 °C) and sub-optimal temperature conditions. Values
   are the log[2]ratio (T/CK) for genes more than 1 or less than −1 with
   FDR < 0.05 as the threshold to judge the significance of gene
   expression difference between the two groups.
   Gene ID S708 T722 Annotation
   log[2](T/CK) log[2](T/CK)
   Auxin
   Solyc09g065850.2 0.72 1.40 IAA3 protein, AUX/IAA (S. lycopersicum)
   Solyc04g081270.1 0.03 1.28 Indole-3-acetic acid-induced protein, ARG7
   SAUR (S. lycopersicum)
   Gibberellin
   Solyc09g074270.2 0.93 1.05 Gibberellin receptor, GID1 (S. lycopersicum)
   Abscisic acid
   Solyc10g050210.1 0.56 1.44 Abscisic acid insensitive, ABF (S.
   lycopersicum)
   Ethylene
   Solyc12g009560.1 0.87 1.18 EIN3-binding F-box protein, EBF1 (A.
   thaliana)
   Brassinosteroid
   Solyc04g078470.2 0.56 1.16 CycD3;2 protein (A. thaliana)
   Jasmonic acid
   Solyc08g008600.2 0.46 2.19 Transcription factor, MYC2 (S. lycopersicum)
   Salicylic acid
   Solyc01g106640.2 0.06 1.50 Pathogenesis-related protein, PR1 (S.
   lycopersicum)
   Solyc10g085960.1 0.64 1.22 Pathogenesis-related protein, PR1 (S.
   tuberosum)
   Solyc09g007020.1 −0.31 1.24 Pathogenesis-related protein, PR1 (S.
   lycopersicum)
   [111]Open in a new tab

Table 5.

   List of selected genes induced by sub-optimal temperature in the
   significantly enriched KEGG pathway “phenylpropanoid biosynthesis” only
   in T722. S708 and T722 tomato cultivars grown under normal (CK, 25/18
   °C) and sub-optimal temperature conditions. Values are the log[2]ratio
   (T/CK) for genes more than 1 or less than −1 with FDR < 0.05 as the
   threshold to judge the significance of gene expression difference
   between the two groups.
   Gene ID S708 T722 Annotation
   log[2](T/CK) log[2](T/CK)
   Solyc11g018800.1 0.86 1.17 Lignin-forming anionic peroxidase (S.
   lycopersicum)
   Solyc10g078890.1 0.07 1.30 Peroxidase (S. lycopersicum)
   Solyc05g050880.2 0.02 1.86 Cationic peroxidase (S. lycopersicum)
   Solyc12g096530.1 0.92 1.29 Peroxidase (A. thaliana)
   Solyc02g085930.2 0.99 1.36 Peroxidase (A. thaliana)
   Solyc02g077300.1 0.61 1.02 Peroxidase (A. thaliana)
   Solyc03g120800.2 0.61 1.55 Peroxidase (A. thaliana)
   Solyc10g076210.1 0.35 1.14 Peroxidase (S. lycopersicum)
   Solyc01g058520.2 0.57 1.16 Peroxidase (S. lycopersicum)
   Solyc01g101050.2 0.57 1.55 Peroxidase (S. lycopersicum)
   Solyc05g050870.2 −0.09 1.48 Cationic peroxidase (S. tuberosum)
   Solyc05g050890.1 0.38 1.92 Cationic peroxidase (S. lycopersicum)
   [112]Open in a new tab

2.6.3. Expression Analysis of Genes Related to K^+ Uptake and Translocation

   Solyc03g083320.2 encoding a homologue of Oryza sativa calcineurin
   B-like protein OsCBL7, Solyc09g042660.2 and Solyc03g006110.2 encoding
   two homologues of O. sativa CBL-interacting protein kinase OsCIPK18 and
   OsCIPK5 were induced by sub-optimal temperature only in T722
   ([113]Table 6). Solyc09g005220.1 encoding a homologue of Arabidopsis
   K^+ channel AKT1 was inhibited during exposure to sub-optimal
   temperature, and this inhibitory effect was stronger in S708 than in
   T722. Moreover, Solyc12g005670.1 encoding S. lycopersicum K^+
   transporter SIHAK5, Solyc06g051830.1 encoding a homologue of O. sativa
   K^+ transporter OsHAK26, and Solyc08g007060.2 encoding a homologue of
   Arabidopsis nitrate transporter AtNRT1.5 were repressed in both
   cultivars under sub-optimal temperature condition ([114]Table 6).

Table 6.

   List of genes related to K^+ uptake and translocation in the S708 and
   the T722 cultivar under sub-optimal temperature conditions (T, 15/10
   °C). S708 and T722 tomato cultivars grown under normal (CK, 25/18 °C)
   and sub-optimal temperature conditions. Values are the log[2]ratio
   (T/CK) for genes more than 1 or less than -1 with FDR < 0.05 as the
   threshold to judge the significance of gene expression difference
   between the two groups.
   Gene ID S708 T722 Annotation
   log[2](T/CK) log[2](T/CK)
   Solyc09g042660.2 0.99 1.03 CBL-interacting protein kinase 18 OsCIPK18
   (O. sativa)
   Solyc03g006110.2 −0.02 2.04 CBL-interacting protein kinase 5 OsCIPK05
   (O. sativa)
   Solyc03g083320.2 0.94 1.24 Calcineurin B-like protein 7 OsCBL7 (O.
   sativa)
   Solyc09g005220.1 −1.56 −0.40 Potassium channel AKT1 (A. thaliana)
   Solyc12g006850.1 −0.94 −0.36 Potassium channel LKT1 (S. lycopersicum)
   Solyc12g005670.1 −1.07 −1.07 Potassium transporter 5 SIHAK5 (S.
   lycopersicum)
   Solyc06g051830.1 −3.39 −1.45 Potassiumtransporter HAK26 (O. sativa)
   Solyc08g007060.2 −1.26 −1.55 Nitrate transporter 1.5 AtNRT1.5 (A.
   thaliana)
   [115]Open in a new tab

2.6.4. Expression Analysis of Aquaporin Genes and Cold Tolerance-Related
Genes

   Two genes encoding aquaporins were repressed in both cultivars under
   sub-optimal temperature conditions ([116]Table S6). Through the
   analysis of cold resistance-related gene expression during sub-optimal
   temperature stress, we found that two genes encoding proline
   dehydrogenase were repressed in T722; of these, one proline
   dehydrogenase gene was repressed in S708. Moreover, three genes
   encoding mitogen-activated protein kinase (MAPK) were induced only in
   T722 under sub-optimal temperature conditions ([117]Table S6).

2.7. Verification of RNA-Seq Data

   The RNA-seq data was verified through a quantitative real-time PCR
   analysis of sixteen genes, which were selected from the following four
   groups: (i) the genes related to K^+ uptake and translocation, (ii)
   down-regulated aquaporin genes in both cultivars, (iii) up-regulated
   genes involved in the “phenylpropanoid biosynthesis” pathway in both
   cultivars, and (iv) up-regulated genes involved in the “plant hormone
   signal transduction” pathway in both cultivars under sub-optimal
   temperature condition. qPCR results revealed that gene expression
   trends were significantly similar (r^2 = 0.78) to those from the
   RNA-seq data, indicating that our RNA-seq results were reliable
   ([118]Figure 6).

Figure 6.

   [119]Figure 6
   [120]Open in a new tab

   Correlation analysis of gene expression values obtained from RNA-seq
   and data obtained using real-time qPCR. All qPCR reactions were
   performed in three biological replicates. Values are the
   log[2]ratio(T/CK) for genes. The determined coefficient (r^2) is
   indicated in the figure.

3. Discussion

   Decreasing the greenhouse temperatures affects different aspects of
   tomato growth and development [[121]1]. The comparison performed in
   this study showed that the phenotype of S708, including the IPH, and
   PGR was more significantly affected than that of T722 by sub-optimal
   temperature treatment ([122]Figure 1). The results described above
   suggest that the T722 cultivar was more tolerant to sub-optimal
   temperature than the S708 cultivar. Moreover, the T722 cultivar had a
   more developed root system than the S708 cultivar under sub-optimal
   temperature condition ([123]Figure 1c,d), which indicated that the T722
   cultivar has a stronger nutrient uptake ability than the S708 cultivar
   [[124]34]. MDA content was used to evaluate the cell membrane damage
   [[125]35]. In our study, the MDA content was significantly higher in
   S708 than in T722 under sub-optimal temperature condition ([126]Figure
   2a). This result suggested that the T722 suffered less membrane damage
   than S708 under sub-optimal temperature stress.

   Low temperature may lead to osmotic stress because low temperature
   impairs water absorption and transport [[127]36]. K^+ plays a key role
   in the establishment of a plant’s ability to adjust to osmotic changes
   and in improving the cold tolerance of plants [[128]14]. However, K^+
   uptake characteristics of tomatoes in response to sub-optimal
   temperatures are still not very clear. Our results showed that the
   whole plant K^+ amount and the net K^+ uptake rate were significantly
   higher in T722 than in S708 under sub-optimal temperature condition
   ([129]Table 2 and [130]Figure 3a). Many studies have indicated that
   there was a significant positive correlation between the K^+ amount and
   plant resistance to abiotic stress [[131]17,[132]18,[133]19]. A
   sufficient K supply can reduce the formation of ROS in plant cells and
   alleviate the damage to plants exposed to chilling or freezing stress
   [[134]15]. Therefore, we deduced that the higher K^+ amount observed in
   T722 might contribute to the defense of the plants against sub-optimal
   temperature stress. Moreover, we found that sub-optimal temperature
   induced a reduction in the K^+ transportation ratio in both cultivars
   during the 5–10 days period ([135]Figure 3b). This reduction might have
   caused the K^+ content in roots to significantly increase and that in
   stems to significantly decrease in both cultivars at 5 DAT ([136]Table
   2).

   To investigate the differences in gene expression between the T722 and
   S708 cultivars in response to sub-optimal temperature, we performed a
   comparative transcriptome analysis. The overall number of DEGs in
   cold-tolerant cultivar was higher than that in cold-sensitive cultivar
   at 5 DAT ([137]Figure 5). This result is different from the previous
   study [[138]35], and this might be related to the characteristics of
   the cultivar used in experiment. Different cultivars showed different
   cold responses at the transcriptional level. The DEGs may reveal the
   difference in the response to cold stress between the S708 and T722
   cultivars. GO enrichment analysis is helpful for highlighting the main
   biological processes in response to stress environment [[139]37]. In
   our study, we found that the genes involved in ROS homeostasis and
   hormone metabolic were differentially expressed between S708 and T722
   under sub-optimal temperature condition. These results showed that
   hormone and ROS may plant key roles in regulating gene expression in
   response to sub-optimal temperature stress.

   The cultivar-specific DEGs in T722 were considered crucial to its
   higher cold tolerance. Among them, most DEGs were involved in the
   “plant hormone signal transduction” and “phenylpropanoid biosynthesis”
   pathways. Plant hormones are known to regulate plant growth and
   development and thus allow the adaptation of plants to abiotic stress
   [[140]38]. Our results showed that 11 genes in the significantly
   enriched KEGG pathway, “plant hormone signal transduction” were induced
   only in T722 at 5 DAT ([141]Table 4). Among these genes, two
   auxin-related genes, including Solyc09g065850.2, which encodes
   indole-3-acetic acid (IAA)-induced protein IAA3, were up-regulated only
   in T722. In Arabidopsis, mutation of this gene can affect
   auxin-dependent root growth and lateral root formation [[142]39].
   Moreover, Solyc04g078470.2, which encodes a homologue of Arabidopsis
   CYCD3, responds to cytokinins and is required for proper secondary root
   thickening [[143]40]. These results might be linked to the stronger
   root system in T722 than in S708 under sub-optimal temperature stress.
   Solyc08g008600.2, involved in the jasmonic acid (JA) signaling pathway
   and encodes a transcription factor MYC2, which positively regulates the
   formation of lateral roots [[144]41] and tolerance to oxidative stress
   in Arabidopsis [[145]42]. This gene was strongly induced by sub-optimal
   temperature only in T722, which suggested that its up-regulation might
   contribute to cold tolerance in tomato. This result is consistent with
   the findings obtained in previous studies [[146]15], which showed that
   JA might act as a positive regulator in response to cold stress in
   tomato. Three genes (Solyc01g106640.2, Solyc10g085960.1 and
   Solyc09g007020.1) involved in the salicylic acid (SA) signaling pathway
   that encode the pathogenesis-related (PR) protein PR1 were more
   strongly induced by sub-optimal temperature in T722 than in S708
   ([147]Table 4). PR proteins such as β-1,3-glucanase exhibit antifreeze
   activity and even prevent the formation of intracellular ice [[148]43].
   These results showed that the plant hormones IAA, SA and JA might play
   their role in regulating root growth and in resisting sub-optimal
   temperature in T722.

   Further results showed that 12 peroxidase related genes involved in the
   significantly enriched KEGG pathway “phenylpropanoid biosynthesis” were
   significantly induced only in T722 at 5 DAT ([149]Table 5). This result
   is consistent with the results of POD activity which significantly
   increased in T722 under sub-optimal temperature ([150]Figure 2b). ROS
   are produced by plants upon exposure to low-temperature stress
   [[151]44,[152]45], and peroxidase is one of the most important
   antioxidative enzymes, and can alleviate oxidative damage by scavenging
   ROS under stress conditions [[153]10,[154]11]. Moreover, we found that
   three genes encoding mitogen-activated protein kinase (MAPK)
   (Solyc12g005360.1, Solyc02g090980.1 and Solyc05g008020.2) were induced
   only in T722 during exposure to sub-optimal temperatures ([155]Table
   S6). MAPK can enhance Nicotiana tabacum total peroxidase (POD)
   activity, thereby inducing less accumulation of H[2]O[2] and
   alleviation of ROS-mediated injuries [[156]46], which might at least
   partly explain the large number of peroxidase related genes that were
   up-regulated in T722. K^+ efflux is an important physiological
   phenomenon, that is usually detected almost instantaneously after the
   application of a stress factor and lasts from a few minutes to several
   hours [[157]47]. Our results showed that the T722 cultivar had a lower
   K^+ efflux rate than S708 cultivar at 5 hours and 5 days after
   treatment ([158]Figure 4), which is consistent with the previous
   results reported by Chen et al. (2005) [[159]48], who indicated that
   the cold-tolerant tomato root system has a strong ability to maintain
   K^+. K^+ efflux is mainly induced by stresses and ROS. The present
   results suggested that the sub-optimal temperature treatment induced
   the expression of genes coding for MAPK and peroxidase in T722, and
   increased the POD activity, which might contribute to ROS scavenging
   and reduced loss of K^+.

   It worth noting that almost the same number of peroxidase-related genes
   involved in the “phenylpropanoid biosynthesis” pathway were repressed
   in T722 ([160]Table S5). Peroxidases are involved in lignification,
   cell elongation, stress defense and seed germination. The diverse
   peroxidase activities facilitate opposing reactions in plants, such as
   generation/scavenging of ROS and loosening/stiffening of the cell wall
   [[161]49]. Similar results were also found in cytochrome P450 pathway;
   there were lots of up- and down-regulated glutathione S transferases
   (GSTs) involved in cytochrome P450 pathway, and these genes play roles
   in detoxifying oxidative-stress metabolites [[162]50]. The expression
   of defense genes has negative effects on plant growth, which to some
   degree counterbalances their positive effects [[163]34]. So we deduced
   that the up- and down-regulated defense related genes in T722 might
   help to maintain energy balance. Moreover, our results showed that
   eight sulfur metabolism-related genes were up-regulated in both
   cultivars. Sulfur assimilation is a platform for the biosynthesis of
   sulfur-containing defense compounds (SDCs), which are crucial for the
   survival of plants under biotic and abiotic stress [[164]51].

   To clarify the change of K^+ content in response to sub-optimal
   temperatures, the expression of genes coding for K^+ uptake and
   translocation was analyzed ([165]Table 6). The results showed that
   Solyc12g005670.1, the K^+ transporter SIHAK5, and a homologue of the O.
   sativa K^+ transporter HAK26 (Solyc06g051830.1), was repressed in both
   cultivars at 5 DAT. Moreover, under sub-optimal temperature conditions,
   a homologue of the Arabidopsis K^+ channel AKT1 (Solyc09g005220.1) was
   repressed only in S708. Similarly, the expression of another gene
   coding for S. lycopersicum K^+ channel LKT1 (Solyc12g006850.1) was
   down-regulated 2.11-fold in S708 and 1.44-fold in T722 ([166]Table 6).
   The Shaker type K^+ channel LKT1 in tomato belongs to the Arabidopsis
   AKT1 subfamily, and HAK5 belongs to the KT/HAK/KUP transporter family,
   which plays an important role in K^+ uptake [[167]52,[168]53,[169]54].
   Then, we verified the expression of these genes by qRT-PCR, and they
   were consistent with the RNA-seq data, despite the differential
   expression folds ([170]Figure 6).

   The phosphorylation of K^+ channels and transporters is the most
   important mechanism for the regulation of their function [[171]22].
   Several studies have demonstrated that the CBL-CIPK complex can
   regulate not only the expression of AKT1, but also the expression of
   AtHAK5 [[172]55,[173]56,[174]57,[175]58]. Our results show that a
   homologue of the O. sativa calcineurin B-like protein CBL
   (Solyc03g083320.2) and two homologues of the O. sativa CBL-interacting
   protein kinase CIPK (Solyc09g042660.2 and Solyc03g006110.2) were
   induced only in T722 ([176]Table 6). Our findings suggest that
   sub-optimal temperatures might repress K^+ net uptake rate and K^+
   influx by inhibiting the expressions of gene coding for K^+ channel and
   transporter and the CBL-CIPK pathway may be more active in T722 during
   sub-optimal temperature stress. Moreover, we found that
   Solyc08g007060.2, which encodes a homologue of the Arabidopsis nitrate
   transporter NPF7.3/NRT1.5, was inhibited in both cultivars by the
   sub-optimal temperature treatment ([177]Table 6). The encoded protein,
   which can regulate K^+ translocation to the shoots in Arabidopsis
   [[178]59,[179]60], was repressed by sub-optimal temperature. That may
   explain the decreased K^+ transportation ratio in both cultivars during
   the 5–10 days after treatment ([180]Figure 3b). In addition, there are
   close couplings between aquaporins and K-channel transporters in water
   uptake of roots [[181]20] and osmoregulation [[182]61]. Our
   transcriptome and qPCR analysis showed that sub-optimal temperature
   inhibits not only genes related to K^+ uptake and translocation, but
   also aquaporins ([183]Table S6 and [184]Figure 6), which may be another
   reason for the increased K^+ accumulation in roots under sub-optimal
   temperature conditions. Extensive studies have shown the roles of K^+
   uptake and transport related genes in resistance to salt and low
   potassium stress [[185]22,[186]62,[187]63], and the roles of these
   genes in the regulation of cold resistance should be analyzed in
   further studies.

4. Materials and Methods

4.1. Plant Materials and Sub-Optimal Temperature Treatment

   The cold-tolerant tomato cultivar Dongnong 722 (T722) and the
   cold-sensitive tomato cultivar Dongnong 708 (S708) used in this study
   were provided by the Tomato Breeding Center of Northeast Agricultural
   University in Harbin China. Pre-germinated seeds were sown into small
   pots (10 × 10 cm, one plant per pot) containing a mixture of
   vermiculite and perlite (volume: volume = 2:1). To avoid the influence
   of fertilization, each pot was irrigated once in 3 days with 100 mL of
   half-strength Hoagland nutrient solution that contained 2.0 mM
   Ca(NO[3])[2], 2.0 mM KNO[3], 0.5 mM MgSO[4], 0.5 mM NH[4]H[2]PO[4], 0.5
   mM (NH[4])[2]HPO[4], 0.5 mM NaCl, 20.6 μM FeNaEDTA, 6.25 μM H[3]BO[3],
   0.5 μM MnSO[4], 0.195 μM CuSO[4], 0.5 μM ZnCl[2], and 0.25 μM NaMoO[4].
   The pH of the nutrient solution was adjusted to 6.0 with 0.1 mM KOH.
   The seedlings were grown in a chamber with day/night temperatures of
   25/18 °C, 65% relative humidity, and a 16 h photoperiod (irradiation
   intensity of 480 μmol m^−2 s^−1).

   Once the seedlings reached the four-leaf stage, uniform-sized plants
   were selected for sub-optimal temperature treatment and transferred to
   a chamber with day/night temperatures of 15/10 °C (T) (the other
   parameters were not changed compared with these of the CK treatment).
   Two temperature treatments were used in this experiment: S708 and T722
   tomato seedlings grown in the normal temperature 25/18 °C (CK) chamber
   were used as the control groups, and S708 and T722 plants grown in the
   sub-optimal temperature chamber comprised the experimental treatment
   groups.

   This study was performed at the Laboratory of Vegetables Physiological
   Economy (Harbin, China). The dry weight, K^+ content and amount, root
   morphology, MDA content and POD activity of the plants were measured at
   5 and 10 days after treatment (DAT). At five hours and five days after
   treatment, the net flux of K^+ was measured. There were 60 pots for
   each treatment with a randomized arrangement resulting in a total of
   120 pots (2 treatments × 2 cultivars × 3 replicates × 2 sampling times
   × 5 pots). The experiment was replicated three times. Since there were
   obvious differences in plant growth rate, root surface area and total
   root length of the two tomato cultivars to sub-optimal temperature at 5
   DAT, so we selected the 5 DAT point as the optimum one for RNAseq
   analysis. At five DAT, the roots of five tomato seedlings in each
   treatment per replicate were harvested and pooled as one sample, with
   three samples per treatment (n = 3). The samples were cleaned with
   autoclaved deionized water, instantly frozen in liquid nitrogen and
   subsequently stored at −80 °C for RNA-seq library preparation
   [[188]64].

4.2. Measurements of Plant Height, Dry Weight and Root Morphology

   Plants were harvested 1 day prior to sub-optimal temperature treatment
   and 5 and 10 DAT. The plant height was measured using a ruler, and the
   dry weight values of the leaves, stems, and roots of tomato seedlings
   were obtained after the samples were dried in an oven at 70 °C to a
   constant weight. The plant growth rate (PGR) and increase in plant
   height (IPH) were calculated as previously described by Beadle (1993)
   [[189]65], with some modification:
   PGR (g day^−1) = (W2 − W1)/(T2 − T1)
   IPH (cm day^−1) = (H2 − H1)/(T2 − T1)

   where W is the total dry weight, T is the time, H is the plant height,
   the subscripts 1 and 2 indicate the start and the end of the period for
   which the IPH and PGR were calculated.

4.3. Measurements of MDA Content and POD Activity

   Membrane lipid peroxidation in tomato seedling roots was determined by
   measuring the malondialdehyde (MDA) content using the method of Dhindsa
   et al. (1981) [[190]66]. Peroxidase (POD) activity was assayed
   according to the method of Khanna-Chopra and Chauhan (2015) [[191]67].

4.4. Measurements of K^+ Content, K^+ Amount, K^+ Net Uptake Rate and K^+
Transportation Ratio

   The dry samples were ground into powder, and digested with sulfuric
   acid ashed in a muffle furnace to measure the K^+ contents of tomato
   seedlings, which were measured by flame spectrometry using a
   PerkinElmer atomic absorption spectrometer (Analyst 800). The K^+
   amount (expressed in units of mg K^+ plant^−1 DW) was calculated
   according to the method of Chachar et al. (2015) [[192]68].

   The K^+ net uptake rate of the plant was calculated according to the
   following equation [[193]69]: K^+ net uptake rate = (C[2] − C[1]) /
   [(t[2] − t[1]) × (R[2] + R[1])/2], where C is the total K amount, R is
   the root dry weight and t is the time; the subscripts 1 and 2 indicate
   the start and the end of the period for which the uptake rate was
   calculated: t[2]−t[1] = 5 d, and (R[2]+R[1])/2 = the mean root dry
   weight.

   The K^+ transportation ratio was calculated according to the following
   equation [[194]70]: K^+ transportation ratio = 100 × (S[2] − S[1]) /
   (C[2] − C[1]), where S is the total K amount in the shoots, C is the
   total K^+ uptake in the whole plants, and the subscripts 1 and 2
   indicate the start and the end of the period for which the uptake rate
   was calculated.

4.5. Measurement of Net K^+ Flux

   The net flux of K^+ was measured at the YoungerUSA Xuyue (Beijing)
   BioFunction Institute using Non-invasive Micro-test Technology and
   iFluxes/imFluxes 1.0 Software (NMT100 Series). Tomato seedlings with
   four leaves were cultured in half-strength Hoagland nutrient solution.
   After being treated with normal and sub-optimal temperatures for 5
   hours and 5 days, the tomato seedling roots were rinsed with distilled
   water, transferred to the measuring solution, and allowed to
   equilibrate for 30 min. The K^+ measuring solution consisted of 0.1 mM
   KCl, 0.1 mM CaCl[2], 0.1 mM MgCl[2], 0.5 mM NaCl. 0.3 mM MES, and 0.2
   mM Na[2]SO[4] (pH 6.0, maintained using Tris or HCl). After primary
   scans along the roots, a site in the root that was 400 μm from the root
   tip was selected for measurement of net flux of K^+. The glass
   micropipettes were prepared as previously described [[195]71]. The data
   were collected every 6 s during the 10 min measurement period. Each
   point represents the mean of three individual plants. Positive values
   in the figures represent K^+ efflux and negative values represent K^+
   influx.

4.6. RNA Preparation

   In the presence of liquid nitrogen, 100 mg of fresh tomato roots was
   ground into paste, and the total RNA from tomato roots was extracted
   using the TRIzol-based method described by Pattemore (2014) [[196]72].
   The RNA was quantified using an Agilent 2100 Bioanalyzer (Agilent
   Technologies, Santa Clara, CA, USA), and the RNA integrity and quality
   were evaluated using a NanoDrop spectrophotometer (Thermo Scientific,
   Wilmington, DE, USA).

4.7. Illumina Sequencing

   Poly(A) mRNA was enriched using beads with Oligo (dT), and the
   mRNA-enriched beads were sheared into short fragments in fragmentation
   buffer. Using these short mRNA fragments as templates, cDNA was then
   synthesized. Suitable fragments were used for PCR amplification. Twelve
   tomato root cDNA libraries were constructed for paired-end
   transcriptome sequencing using the Illumina HiSeqTM 2000 system by
   Shanghai Majorbio Biopharm Technology Co., Ltd. (Shanghai, China). All
   raw data were deposited in NCBI Sequence Read Archive (SAR,
   [197]http://www.ncbi.nlm.nih.gov/Traces/sra) with accession number
   SRP156519.

4.7.1. Transcriptome Assembly and Annotation

   The raw reads generated by Illumina HiSeqTM2000 were cleaned by
   removing adapter sequences, low-quality reads (Q < 25), reads
   containing more than 10% ‘N’, and fragments less than 20 bp long using
   SeqPrep ([198]http://gihub.com/jstjohn/) and Sickle
   ([199]http://github.com/najoshi/).

4.7.2. Analysis of Differential Gene Expression

   The clean reads were mapped to the S. lycopersicum reference genome
   sequence
   ([200]http://plants.ensembl.org/Solanum_lycopersicum/Info/Index). Gene
   expression levels in terms of transcript abundances were quantified by
   RSEM ([201]http://deweylab.biostat.wisc.edu/rsem/) and fragments per
   kilobase per million mapped (FPKM) [[202]73]. The differentially
   expressed genes (DEGs) between the different treatments were analyzed
   using edgeR
   ([203]http://www.bioconductor.org/packages/2.12/bioc/html/edgeR.html).
   Genes that exhibited a 2-fold or greater change between the two
   treatments and a false discovery rate (FDR) of 5% or less were defined
   as differentially expressed. The enrichment of DEGs was analyzed using
   GOATOOLS ([204]https://github.com/tanghaibao/goatools) [[205]74], and
   the GO terms with an adjusted p-value < 0.05 were considered
   significantly enriched in the DEGs. KOBAS
   ([206]http://kobas.cbi.pku.edu.cn/home.do) was used for KEGG metabolic
   pathway analysis, and the metabolic pathways with a p-value < 0.05 were
   defined as being significantly enriched [[207]75].

4.8. Verification of RNA-Seq Results by Quantitative Real-Time PCR (qRT-PCR)

   Sixteen genes were selected for verification of the RNA-seq results by
   qRT-PCR. The gene-specific primer pairs for the SIHAK5 reference were
   described by Nieves-Cordones et al. (2008) [[208]76], and the other
   gene-specific primers were designed using Primer 5.0 software and
   synthesized by Sangon Biotech Company (Shanghai, China). These genes
   and their specific primers used in the real-time PCR analysis are
   listed in the [209]Supplementary Materials (Table S7). Real-time
   quantitative RT-PCR (qRT-PCR) analyses were performed with independent
   samples from the S708 and T722 cultivars grown at 25/18 °C and 15/10 °C
   with the same conditions as those used for RNA-Seq analysis. All
   real-time PCR reactions were performed using the real-time PCR system
   qTOWER (Analytik jena, Jena, Germany). The reaction mixture, consisted
   of a final volume of 20 μL, which contained 10 μL of 2×SYBR Premix
   (BioTeke Corporation, Beijing, China, 0.3 μL of each primer, 8.8 μL of
   sterile deionized water, and 0.6 μL of the diluted cDNA template. The
   thermal cycling program comprised an initial step at 95 °C for 30 s,
   followed by 40 cycles at 95 °C for 20 s, 58 °C for 30 s, and 72 °C for
   15 s. Each sample was analyzed with three biological replicates. The
   tomato Actin gene was used as a reference gene and the gene expression
   was calculated by the 2^−△△Ct method [[210]77].

4.9. Statistical Analysis

   Mean comparison among different treatments was performed based on the
   Tukey’s honestly significant difference (HSD) test at the 0.05
   probability level. IPH, PGR, root surface area, total root length, MDA
   content, POD activity, K^+ content in roots, stems and leaves, K^+
   amount in whole plants, K^+ net uptake rate and K^+ transportation
   ratio were measured, and these data were analyzed with two-way ANOVA
   with cultivar, temperature and their interaction as fixed factors.
   These statistical analyses were conducted with SAS 9.1 software (SAS
   Institute Inc., Cary, NC, USA).

5. Conclusions

   Overall, we found some different responses to sub-optimal temperature
   by two tomato cultivars. Compared to cold-sensitive tomato cultivar
   S708, cold-tolerant cultivar T722 exhibited lower reduction in plant
   growth rate, the whole plant K^+ amount and K^+ net uptake, and T722
   also had higher POD activity and lower K^+ efflux rate under
   sub-optimal temperature conditions. The RNA-seq analysis showed that
   the overall number of DEGs at 5 DAT in T722 were higher than that in
   S708. GO and KEGG enrichment analysis showed that genes involved in ROS
   homeostasis and hormone metabolic were differentially expressed between
   S708 and T722 under sub-optimal temperature conditions. Up-regulation
   of these genes in T722 during sub-optimal temperature stress might play
   important roles in regulating plant root growth and cold tolerance.
   Moreover, we also found that sub-optimal temperature inhibited the
   expression of gene coding for K^+ channel AKT1, which is associated
   with K^+ uptake only in S708, might be a reason for less K^+ amount
   than T722. The results revealed the cold response genes in tomato
   roots, and provided a foundation for further investigating the
   mechanism of K^+ uptake in tomato under sub-optimal temperatures.

Supplementary Materials

   The following are available online at
   [211]https://www.mdpi.com/2223-7747/9/1/65/s1, Table S1: Major
   characteristic of twelve libraries. Table S2: The DEGs in the S708
   cultivar. Table S3: The DEGs in the T722 cultivar. Table S4:
   Significantly enriched GO biological process terms of DEGs in both
   tomato cultivars under sub-optimal temperature stress. Table S5: KEGG
   pathway enrichment analysis of DEGs. Table S6: List of aquaporins and
   cold tolerance related genes in the S708 and T722 cultivar under
   sub-optimal temperature conditions. Table S7: Primers used in qPCR
   experiments.
   [212]Click here for additional data file.^ (569KB, zip)

Author Contributions

   Conceptualization, F.W.; Funding acquisition, F.W.; Methodology, C.L.,
   X.Z. and F.W.; Project administration, F.W.; Software, H.G., W.Y.,
   D.G., M.K.uR. and N.L.; Writing—original draft, H.G. All authors have
   read and agreed to the published version of the manuscript.

Funding

   This work was funded by the China Agricultural Research System
   (CARS-23-B10).

Conflicts of Interest

   The authors declare no conflict of interest.

References