Differential transcriptomic changes in low-potassium sensitive and low-potassium tolerant tea plant (Camellia sinensis) genotypes under potassium deprivation

Differential transcriptomic changes in low-potassium sensitive and low-potassium tolerant tea plant (Camellia sinensis) genotypes under potassium deprivation

Scientia Horticulturae 256 (2019) 108570 Contents lists available at ScienceDirect Scientia Horticulturae journal homepage: www.elsevier.com/locate/...

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Scientia Horticulturae 256 (2019) 108570

Contents lists available at ScienceDirect

Scientia Horticulturae journal homepage: www.elsevier.com/locate/scihorti

Differential transcriptomic changes in low-potassium sensitive and lowpotassium tolerant tea plant (Camellia sinensis) genotypes under potassium deprivation

T

Yeyun Lia,1, Wenzhi Wanga,b,1, Kang Weib, Li Ruanb,c, , Liyuan Wangb, , Hao Chengb, Fen Zhangb, Liyun Wub, Peixian Baib ⁎



a

State Key Laboratory of Tea Plant Biology and Utilization, College of Tea and Food Technology, Anhui Agricultural University, Hefei, 230036, China National Center for Tea Improvement, Tea Research Institute, Chinese Academy of Agricultural Sciences, Key Laboratory of Tea Plant Biology and Resources Utilization, Ministry of Agriculture, Hangzhou, 310008, China c State Key Laboratory of Soil and Sustainable Agriculture, Institute of Soil Science, Chinese Academy of Sciences, Nanjing, 210008, China b

ARTICLE INFO

ABSTRACT

Keywords: Camellia sinensis K starvation Root morphology Differentially expressed gene

Potassium (K) deficiency is a common abiotic stress that can inhibit plant growth and thus reduce crop productivity. K shortages in tea farms are very severe in current tea production systems. Therefore, developing lowK tolerant tea plants is an effective approach to mitigating K deficiencies in agricultural production systems. Up to now, the mechanisms underlying the transcriptional changes of tea plants under K+ deprivation have not been studied. In this study, to elucidate the underlying mechanism of tea plant genotype tolerance to K deprivation, we investigated K deprivation-induced changes in root morphology and global transcription in two tea plant genotypes, “1511″ and “1601″, which are tolerant and sensitive to low-K conditions, respectively. The results showed that the root systems were more developed in “1511″ than “1601″. The K starvation treatment increased the proportion of roots with a 0.5–2 mm diameter in “1511″ and the proportion of those with a 0–0.5 mm diameter in “1601″. There were 487 and 294 up-regulated genes in “1511″ and “1601″ (> 2-fold change), respectively. The expression levels of the most differentially expressed genes in “1511″ were higher than those in “1601″. Under K+ starvation, we detected differentially expressed genes were only up-regulated in “1511″ associated with ethylene-related, ammonium transporter, nitrate transporter, catalase-related and phosphatidylinositol-related pathways. These up-regulated genes might play crucial roles in root architecture and K+ uptake and utilization, which would help enhance the low-K tolerance of “1511″. Our study provides new insights into the molecular mechanisms underlying tolerance of K+ starvation and builds a foundation for selecting low-K tolerance tea plant genotypes.

1. Introduction Tea plants are generally grown in tropical and subtropical regions where the soils are generally highly leached and acidic, which results in low soil fertility (Li et al., 2016; Ruan et al., 2014; Salehi and Hajiboland, 2008). More than 50% of typical tea plantations are deficient in K. Moreover, due to inappropriate tea plantation management practices, such as improper leaf picking and unbalanced fertilization measures, the K shortages on tea farms are often further exacerbated. The percentage of tea plantations with a K deficiency has increased from 59% in the 1990s to 74% in the 2010s in China, and K shortages

have become a great threat to the tea industry (Ruan et al., 2013). K deficiency in tea farms can lead to a significant reduction in plant photosynthetic efficiency, leaf generation rate, and tea quality components such as theanine, polyphenols, catechins, and β-phenylethanol, thus causing a great loss of tea productivity and quality (Ruan et al., 2013; Venkatesan et al., 2005). Moreover, K deficiency can reduce the resistance of tea plants to cold, drought, and insect pests stresses (Rahman et al., 2014) ; thus, it significantly affects the growth, development and stress resistance of tea plants and exhibits a great impact on tea quality (Rahman et al., 2014; Ruan et al., 2013). The root system is the primary method by which K+ enters the plant

Corresponding authors at: National Center for Tea Improvement, Tea Research Institute, Chinese Academy of Agricultural Sciences, Key Laboratory of Tea Plant Biology and Resources Utilization, Ministry of Agriculture, Hangzhou, 310008, China. E-mail addresses: [email protected] (L. Ruan), [email protected] (L. Wang). 1 These authors contributed equally to this work. ⁎

https://doi.org/10.1016/j.scienta.2019.108570 Received 16 February 2019; Received in revised form 6 June 2019; Accepted 8 June 2019 Available online 18 June 2019 0304-4238/ © 2019 Elsevier B.V. All rights reserved.

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body. The root morphology and its physiological and molecular responses play a decisive role in plant adaptations to low-K environments (Szczerba et al., 2009). In the soil-plant system, when the soil K concentration is lower than the critical value, the root system significantly reshapes its architecture to increase its contact area with the soil, thereby increasing plant K absorption (Ljung, 2013).Organic acid secretions significantly increase the mobility and effectiveness of soil K, thereby facilitating K easier absorption by plants (Wang et al., 2011). K deficiency induces root respiration and leads to an increased root-toshoot ratio to enhance K+ absorption (Singh and Blanke, 2000). Many functional genes, such as those encoding K transporters, ion channels, transcription factors, protein kinases, antioxidant enzymes, and some components of calcium signaling and hormonal signaling pathways, collectively regulate K+ signal perception and transduction, root growth, and K+ uptake and translocation. Transcriptional changes in these genes may affect plant tolerance to low-K stress (Wang and Wu, 2013; Zeng et al., 2015). Through the study of low-K tolerant genotypes, the cultivation and application of low-K tolerant rice, wheat, sweet potato and cotton have been promoted (Li et al., 2014; Ma et al., 2012; Ruan et al., 2015; Wang et al., 2015; Wang and Chen, 2012). Some progress has been made in K distribution and absorption, K deficiency and nutritional diagnosis, soil K management, and the efficient use of K in tea plants (Rapala-Kozik et al., 2008; Ruan et al., 2013; Venkatesan et al., 2005; Yang et al., 2013). However, our understanding of K+ deprivation-induced root system alterations and transcriptional changes in low-K tolerant and low-K sensitive tea plants is limited. Therefore, this study was conducted using two tea plant genotypes with the same genetic background (“1511″ and “1601″), which were obtained from the F1 tea population of a crossbreeding program. However, these genotypes had different low-K tolerances (i.e., “1511″ was low-K tolerant, and “1601″ was low-K sensitive). In this study, we investigated differential root morphological and transcriptional changes under K+-sufficient conditions and K+-starvation conditions (CK and SK), to provide insights into the possible molecular mechanisms underlying the in response to K deprivation. Our study will contribute to breeding new cultivars of low-K tolerance, solving soil potassium deficiency and improving production.

genotypes were grown under normal conditions for four weeks. Then, tea plant roots were collected for RNA extraction after 5 d of the control and SK treatment. 2.2. RNA extraction Total RNA was extracted from the “1511″ and “1601″ root samples of the control (CK) and subjected to K+-starvation (SK) treatment. Every sample contained three biological replicates, and each biological replicate contained 20 strains of consistently growing tea plants. Total RNA was extracted from the roots using the BIOZOL Total RNA Extraction Reagent (Biozol, Eching, Germany) pBIOZOL according to the manufacturer's protocol. RNA integrity was confirmed with an Agilent 2100 Bioanalyzer. 2.3. cDNA Library Preparation and Illumina Sequencing A total of 3 μg of RNA per sample was used as input material for the RNA sample preparations. Briefly, mRNA was isolated from total RNA through an oligo method (dT). Fragmentation was carried out using divalent cations in NEBNext First Strand Synthesis Reaction Buffer under elevated temperature. First-strand cDNA was synthesized using a random hexamer primer and M-MuLV reverse transcriptase, and second-strand cDNA synthesis was subsequently performed using DNA polymerase I and RNase H. The ends of the reverse-transcribed products were repaired, poly(A) was added and ligated to the sequencing adapter, and PCR amplification was performed to construct a cDNA library. The cDNA library from the tea roots was sequenced from both the 5′ and 3′ ends, using the Illumina HiSeq 2500 (Illumina, San Diego,CA, USA). The fluorescent images were processed for sequence base-calling and the quality values were calculated using the Illumina data processing pipeline. 2.4. De novo assembly of the transcriptome Before assembly, the raw reads were cleaned by removing the adaptor sequences, empty reads, reads containing unknown sequences “N” with a rate more than 10%, and low-quality reads containing more than 50% bases with a quality score ≤ 5. The de novo assembly of clean reads was performed using the Trinity program (Grabherr et al., 2011). Briefly, clean reads were first split into small pieces to produce contigs using de Bruijn graphs. The resulting contigs were then further joined into scaffolds using the paired-end reads. Gap filling was subsequently carried out to obtain complete scaffolds using the paired-end information to retrieve the read pairs with one read well-aligned to the contigs and another read located in the gap region. Subsequently, the TGICL program (Pertea et al., 2003) was used to assemble Camellia sinensis root unigenes to form a single set of non-redundant unigenes.

2. Materials and methods 2.1. Plant materials and SK treatment Two tea plant genotypes “1511″ and “1601″ were from the hybrid F1 population of Longjing 43 and Baihaozao, thereby they had similar genetic backgrounds. One-year-old cutting seedlings of “1511″ and “1601″ showed extremely different growth under low-K treatment. They had different sensitivities to low-K, which constituted comparative material with similar genetic backgrounds but extreme differences in low-K tolerance and root development. Thus, they were used to study the low-K tolerance mechanism under K deficient treatment in this experiment. The normal nutrient solution (pH 5) contained 1.0 mM NH4NO3, 0.035 mM CaH4O4P2, 0.3 mM K2SO4, 0.07 mM KH2PO4, 0.67 mM MgSO4, 0.495 mM CaCl2, 0.035 mM Al2 (SO4)3•18 H2O, 7.0 × 10−3 mM H3BO4, 1.0 × 10−3 mM MnSO4•H2O, 6.7 × 10−4 mM ZnSO4•7H2O, 1.3 × 10−4 mM CuSO4•5H2O, 4.7 × 10−5 mM (NH4)6Mo7O24•4H2O and 4.2 × 10−3 mM EDTA-FeNa. The nutrient solution was continuously ventilated by pumps and replaced weekly. The plants were hydroponically grown in a greenhouse at 30 °C/22 °C (day/night) with daily natural sunlight. First, tea plants were grown in normal nutrition solution for four weeks. Second, half of the above tea plants were transferred to a nutrient solution without K2SO4 (i.e., K starvation treatment) (SK), while the other half was transferred to a nutrient solution with K2SO4 as a control (i.e., control treatment) (CK). In the physiological experiments, the two tea plant genotypes were grown in normal and SK for eight weeks and collected to measure the growth parameters. In the molecular experiments, the two tea plant

2.5. Transcriptome analysis The identified differentially expressed genes (DEGs) were subjected to GO (Gene Ontology) and KEGG (Kyoto Encyclopedia of Genes and Genomes) pathway enrichment analyses using the GOseq R package and KOBAS 2.0, respectively. DEGs between the control and treatment group were identified using logarithmic ratios of RPKM (reads per kb per million reads) values with parameters of |log2Ratio| > 1 and false discovery rate (FDR) ≤ 0.001. If log2 (ratio) > 0, then the gene is considered up-regulated; otherwise, it is considered down-regulated. Finally, significant DEGs in both tea cultivars were considered differentially regulated genes. 2.6. qRT-PCR analysis The RNA samples for the transcriptome analysis were also used for real-time PCR assays to ensure the reliability and repeatability of the 2

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Fig. 1. Difference in the sensitivity to K+ starvation between the two tea plant genotypes (low-K tolerant “1511″ and low-K sensitive “1601″). (A) Phenotypic differences of tea plants during K+-sufficient (CK) and K+-starvation (SK) treatments for eight weeks; (B) leaf, stem, and root K+ contents; and (C) K biological utilization index (the two tea plant genotypes under CK and SK conditions for eight weeks). Data are the means ± SE (n = 3); and different letters in each column denote significant differences at the p < 0.05 level.

results. A total of 800 ng of RNA was used as a template for first-strand cDNA synthesis, which was performed using the Fast Quant RT kit (TIANGEN, China) in a reaction volume of 20 μL according to the manufacturer's instructions. Quantitative RT-PCR was performed using an ABi7500 real-time PCR machine with SYBR Green reagents (Takara, Japan). The expression patterns were analyzed in 20 μL reactions. qRTPCR was performed with three biological replicates and three technical replicates. The relative quantitative 2−ΔΔCt method was applied to analyze the quantitative changes in the selected genes in the two treatments. (Revel et al., 2002)

treatment. The growth trends of “1511″ and “1601″ were basically equivalent (Fig. S1A). The leaf, root and stem K+ contents between “1511″ and “1601″ had no significant differences before the treatment. (Fig. S1B). There was no difference in the K biological utilization index between “1511″ and “1601″ before the treatment (Fig. S1C). Considerable phenotypic differences were noted between “1511″ and “1601″ under K+ starvation for eight weeks. “1511″ showed greater shoot and root growth than “1601″ after 8 weeks under the SK treatment. (Fig. 1A). The leaf and root K+ contents were higher in “1511″ than “1601″ under both K+-sufficient conditions and K+-starvation conditions (CK and SK), while the stem K+ contents were lower in “1511″ than “1601″ under both CK and SK (Fig. 1B). For “1511″ and “1601″, the K+ contents in different tissues was ordered as follows under both CK and SK: leaf > root > stem (Fig. 1B). Under K starvation, the K biological utilization index of “1511″ was noticeably higher than that of “1601″, and the difference between the two was not significant when K was sufficient. Therefore, genotypic variation in the K biological utilization index between “1511″ and “1601″ was observed only in the SK treatment (Fig. 1C). Significant and differential reductions in root development were noted in “1511″ and “1601″ due to K deprivation (Fig. 2). The total root length, total root surface area, root volume and root tips in “1601″ were 77.43%, 63.72%, 51.69% and 78.07% of those in “1511″ under regular K+ supply conditions, respectively, and the total root length, total root surface area, root volume and root tips in “1601″ were only 46.35%, 35.66%, 27.17% and 62.95% of those in “1511″ under SK, respectively (Fig. 2A-D). These data suggest that the development of the root system in the low-K sensitive genotype “1601″ was more severely inhibited than that in the low-K tolerant genotype “1511″, especially under SK. Further root architecture analysis revealed that under both CK and SK, the total lengths of two types of fine roots (0 < D ≤ 0.5 mm and 0.5 < D ≤ 2 mm) were significantly reduced in “1601″ compared to those in “1511″ (Fig. 2E and G). In “1511″, the proportion of the length of thin roots (0 < D ≤ 0.5 mm) accounted for 53.38% and 51.58% of the whole root systems under CK and SK, respectively. However, a higher proportion of the length of thin roots was found in “1601″,

2.7. Root parameter, biomass and K+ concentration measurements An EPSON scanner was used to scan whole roots. WinRHIZO, an image analysis system specifically designed for washed root measurement, was employed to analyze the root parameters. The leaves, shoots and roots of the test plants were excised and separately dried at 80 °C for 48 h, and then weighed. The plant K+ concentrations were measured using a flame photometer (Model 425, Sherwood Scientific Ltd, Cambridge, UK) after the plant samples were digested with a mixture of H2O2 and H2SO4. To measure the plant biomass and K+ concentrations, three replicates were performed. The formula for K content (Wu et al., 2011) and K biological utilization are shown below (Siddiqi et al., 1981): Root K content = Root K concentration ∙ root dry weight; Stem K content = Stem K concentration ∙ stem dry weight; Leaf K content = Leaf K concentration ∙ leaf dry weight; K biological utilization = dry weight of shoot / K concentration of shoot. 3. Results 3.1. Morphological and physiological changes in the two tea plant genotypes under SK The phenotypes of “1511″ and “1601″ were observed before the 3

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accounting for 62.9% and 67.43% of the whole root system under CK and SK, respectively. For “1511″, thick roots with 0.5–2 mm diameters (0.5 < D ≤ 2 mm) accounted for 45.1% and 47.15% of the whole root systems under CK and SK, respectively. For “1601″, thick root lengths accounted for 36.91% and 32.44% of the total root length under CK and SK, respectively (Fig. 2F and H). Under SK, the proportion of roots with diameters less than 0.5 mm over all the roots in “1601″ was significantly higher than that in “1511″ (p < 0.05), and the proportion of roots with diameters ranging from 0.5 to 2 mm in “1601″ was lower than that in “1511″ (p < 0.05) (Fig. 2F, H). In summary, more roots with a higher proportion of thick roots developed in the low-K tolerant tea strain than the low-K sensitive tea strain, especially in the SK treatment.

Table 1 Validation of the transcriptome assembly of using CDS mapping and genome alignments. Query

Database

Total number

Mapped number

Rate (%)

Shuchazao genome CDS DEGs under potassium starvation

Unigenes CDS Shuchazao

33932 1078

33137 688

97.66 % 63.82 %

3.3. DEGs identification and GO analysis In the present study, the reads per kilobase of transcript per million mapped reads calculation method was employed to compare the DEGs between the control and the treated groups. Two tea plant genotypes were used to analyze the transcriptional changes induced by CK and SK. We performed a hierarchical cluster analysis to show the different expression levels of the DEGs in the two genotypes. Genes are displayed using different colors, and the relative expression levels are illustrated by a color gradient from low (green) to high (red). The relative expression levels of “1511″ exceeded those of “1601″. Venn diagrams were also prepared to further analyze these DEGs in the tested genotypes. Among the DEGs identified in “1511″, 487 genes were up-regulated, and 284 genes were down-regulated. Among the DEGs in “1601″, 294 genes were up-regulated, and 76 genes were down-regulated. The number of “1511″ up-regulated and down-regulated genes surpassed that of “1601″ by 193 and 208 genes, respectively. (Fig. 3A-C). The GO analysis divided the identified DEGs into three categories: molecular function, cellular components and biological processes. The top GO terms affected by SK were “cytoplasmic part”, “cation binding”, and

3.2. Two-way blast of differentially expressed genes (DEGs) and transcriptome unigenes for the tea plant genome A total of 1078 DEGs were found in the transcripts of tea plants treated with SK. To validate the transcriptome assembly quality and the DEGs, we first used the unigenes in this transcriptome analysis as a database. Tea plant genomes were queried with a mapping rate of 97.66% (cultivar Shuchazao of Camellia sinensis (accession no. GS2002008)) (Wei et al., 2018a, 2018b). Second, we mapped all DEGs to genome sequences of the cultivar Shuchazao, which showed alignments with an identity of 63.82%. The unigene coding sequence (CDS) represent the genes in this study, and DEGs denote the differentially expressed genes under the SK treatment. The Shuchazao CDSs were predicted by tea genome sequencing. These results revealed that the genes that we used for further analysis were accurately mapped to DNA sequences (Table 1).

Fig. 2. Differentially changed root-growth parameters of the two tea plant genotypes under K+-sufficient and K+-starvation conditions. (A, B, C, and D), respectively, represent total root length, total root surface area, root volume and root tips of all the roots with diameters larger than 0 mm (D > 0 mm); (E and G) total length of roots with diameters within the range of 0 to 0.5 mm (0 < D ≤ 0.5 mm) and 0.5–2 mm (0.5 < D ≤ 2 mm), respectively; and (F and H) percentage of the root lengths at (0 < D ≤ 0.5 mm) and (0.5 < D ≤ 2 mm) over the total root length. Data are the means ± SE (n = 3), and the lowercase letters represent significant differences at p < 0.05. 4

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“oxidation-reduction activity” in “1511″ and “catalytic activity”, “metabolic process”, and “single-organism metabolic process” in “1601″. Many genes involved in mediating the process of “abiotic stimulus”, “osmotic stress”, “symplast” and “oxygen-containing compound” were only up-regulated in “1511″. Moreover, the functional abundance of specific up-regulated genes in “1511″ was higher than that in “1601″ (Fig. 4). The GO classification analysis of the DEGs revealed that these genes were involved many life processes.

“flavonoid biosynthesis”, “peroxisome” and “photosynthesis”. However, these pathways were significantly unaffected in “1601″. Fifteen pathways involving amino acid metabolism were affected in “1511″, while ten amino acid metabolism pathways were affected in “1601″. Under SK stress, the metabolism pathways for multiple amino acids were affected in both “1511″ and “1601″ (Fig. 5). The low-K+ treatment promoted the metabolism of amino acids, suggesting that a correlation existed between nitrogen and K. Overall, the number of affected KEGG metabolic pathways and the number of correlated DEGs in each pathway in “1511″ were greater than those in “1601″ under SK stress.

3.4. KEGG pathway enrichment analyses The KEGG pathway enrichment analysis suggested that the top five affected KEGG metabolic pathways in “1511″ were “ribosome”, “photosynthesis”, “carbon fixation”, “oxidative phosphorylation”, and “glycolysis/gluconeogenesis” (Fig. 5A), and those in “1601″ were “cysteine and methionine”, “carbon fixation”, “ribosome”, “glycolysis and gluconeogenesis”, and “flavonoid biosynthesis” (Fig. 5B). “Ribosome”, “carbon fixation”, and “glycolysis/gluconeogenesis” were all affected in both the low-K tolerant and low-K sensitive genotypes “1511″ and “1601″ but to different extents, suggesting that these three pathways played a crucial role in the responses of tea plants to SK stress. Additionally, the distinct pathways that were significantly affected in “1511″ included “oxidative phosphorylation”, “citrate cycle (TCA cycle)”, “phenylpropanoid metabolism”, “nitrogen metabolism”,

3.5. Annotation of the SK-induced DEGs 3.5.1. DEGs related to K and other metabolite transporters In this study, certain DEGs that were annotated as nutrient transporters were found. Four DEGs that were annotated as K transporters (TRINITY_DN255768_c0_g1,TRINITY_DN248739_c1_g1,TRINITY_DN27 1757_c12_g1 and TRINITY_DN265808_c0_g2) were up-regulated in “1511″. One ammonium transporter (TRINITY_DN277344_c3_g1), and ten nitrate transporters (TRINITY_DN264308_c1_g3,TRINITY_DN 203794_c1_g1,TRINITY_DN70954_c0_g1,TRINITY_DN265029_c3_g1,TRINITY_DN242410_c2_g1,TRINITY_DN276028_c1_g1,TRINITY_DN265 572_c0_g2, TRINITY_DN248268_c2_g4,TRINITY_DN 348545_c0_g1 and

Fig. 3. Hierarchical cluster analysis and Venn diagrams of tea genes showing transcriptional changes in response to K+ starvation. (A) Hierarchical cluster analysis of genes showing transcriptional changes in the two genotypes (low-K tolerant “1511″ and low-K sensitive “1601″). Values are the log2fold-change (K+ starvation/ control) of gene expression, and the relative expression levels are shown by a color gradient from low (green) to high (red). (B) Up-regulated genes; and (C) downregulated genes (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.). 5

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Fig. 4. GO classification of the assembled transcripts. (A) Functional category distribution of differentially expressed genes in low-K tolerant “1511″; and (B) functional category distribution of differentially expressed genes in low-K sensitive “1601″.

Fig. 5. KEGG pathway enrichment analyses of the two tea plant genotypes under K starvation. (A) Up-regulated KEGG pathway enrichment in low-K tolerant “1511″; and (B) up-regulated KEGG pathway enrichment in low-K sensitive “1601″.

TRINITY_DN242252_c0_g1) were only up-regulated in “1511″. Additionally, nineteen and six DEGs related to calcium signal transporters were up-regulated in “1511″and “1601″, respectively. Moreover, in “1511″, four DEGs that were annotated as ABC (ATP binding cassette) transporters (TRINITY_DN255674_c3_g1, TRINITY_DN261265_c0_g3, TRINITY_DN213001_c0_g2 and TRINITY_DN276090_ c0_g1) were up-regulated, while two DEGs related to ABC transporters (TRINITY_DN259465_c1_g9 and TRINITY_DN259729_c1_g1) were up-regulated in “1601″. This study found that the DEGs that were annotated as metabolite transporters were up-regulated in the two tested genotypes under SK conditions. More transporter DEGs were up-regulated in the low-K tolerant “1511″, than in the low-K sensitive “1601″ (Table 2).

3.5.2. DEGs related to plant hormone signal transduction and oxidative stress Our results showed that many genes related to plant hormone signal transduction were up-regulated under SK stress. Four genes (TRINITY_DN264300_c0_g5, TRINITY_DN248739_c1_g1, TRINITY _DN271757_c12_g1 and TRINITY_DN253528_c0_g1) and three genes (TRINITY_DN264300_c0_g5, TRINITY_DN261853_c2_g3 and TRINITY_DN263781_c0_g1) related to ethylene-mediated and jasmonic acid-mediated (JA) pathways, respectively, were significantly upregulated in “1511″; however, only one jasmonic acid-mediated DEG (TRINITY_DN263781_c0_g1) was up-regulated, and no DEGs related to the ethylene-mediated pathway were up-regulated in “1601″. In either “1511″ or “1601″, one up-regulated gene (TRINITY_DN263781_c0_g1) 6

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regulated in “1511″, but down-regulated in “1601″ under K starvation (Table S1).

Table 2 Number of up- and down-regulated genes in the two tea plant genotypes in response to K+-starvation. “+” represents up-regulated genes, and “−” represents down-regulated genes. Groups

1511

1601

Category

Potassium transporter Ammonium transporter Nitrate transporter Calcium ion transporter ATP binding cassette transporter Ethylene-related Jasmonic acid-related Abscisic acid-related Auxin-related Salicylic acid-related Catalase-related Peroxidase-related Oxygen-related Flavonol process Permease-related Phosphatidylinositol-related

4 + 0− 1 + 0− 10 + 0− 19 + 4− 4 + 5− 4 + 0− 3 + 0− 1 + 0− 1 + 0− 1 + 0− 1 + 0− 9 + 0− 25 + 5− 2 + 0− 4 + 5− 3 + 0−

4 + 0− 0 + 0− 0 + 0− 6 + 4− 2 + 0− 0 + 0− 1 + 0− 1 + 0− 1 + 0− 1 + 0− 0 + 0− 4 + 0− 22 + 4− 1 + 0− 3 + 0− 0 + 0−

Transporter

3.7. Real-time fluorescence quantitative PCR (qRT-PCR) analysis

Oxidative stress

To confirm the reliability of the RNA-seq data, a qRT-PCR analysis using gene-specific primers was performed to quantify the transcript levels of twelve randomly chosen genes (Fig. 6A) (Table 3). Furthermore, the transcript data from the RNA-seq and qRT-PCR analyses were compared using fold-change measurements. To compare the foldchanges, scatter plots were generated using the log2 ratio between the RNA-seq and qRT-PCR values (Fig. 6B). Our results revealed that the gene expression trends were significantly similar (r2 = 0.89) to those from the RNA-seq data, confirming the reliability of the RNA-seq data used in this study.

Biological process

4. Discussion

Plant hormone

In this study, transcriptional alterations in low-K tolerant and low-K sensitive tea plant genotypes “1511″ and “1601″ were investigated to better understand the mechanisms regulating plant responses to K starvation (SK) stress. Our data indicated that SK significantly affected the architecture of the tea roots and the expression of numerous genes. The discussion section will focus on the following question: which key genes play an important role in improving SK tolerance of low-K tolerant tea genotype?

was found to be related to the abscisic acid (ABA), auxin and salicylic acid (SA) pathways (Table 2). Reactive oxygen species (ROS) are vital signaling molecules that are specific to low-K+ stress conditions. Our results suggested that under SK conditions, one DEG annotated as a catalase-related gene (TRINITY_DN269998_c0_g1) was only up-regulated in “1511″. There were nine up-regulated peroxidase-related DEGs (TRINITY_DN255699_c0_g2, TRINITY_DN243589_c3_g5,TRINITY _DN242410_c2_g1,TRINITY_DN265819_c5_g1,TRINITY_DN269998_c0 _g1,TRINITY_DN247796_c0_g2,TRINITY_DN276028_c1_g1, TRINITY_DN247796_c0_g1, and TRINITY_DN243263_c0_g2) in “1511″, but only four (TRINITY_DN243589_c3_g2,TRINITY_DN255699_c0_g1,TRINITY_DN244456_ c0_g3 and TRINITY_DN259022_c2_g1) in “1601″. In addition, in “1511″, twenty-five oxygen-related DEGs were upregulated, while in “1601″, twenty-two were up-regulated. These genes might be important for further investigations of the mechanisms underlying the responses of the two tested tea plant genotypes to SK stress at the molecular level (Table 2).

4.1. Root development-related metabolic regulation and physiological responses Previous studies revealed that certain phytohormones (ethylene, auxin, and jasmonic acid) are involved in the signal transduction of the plant response to low-K+ stress (Schachtman, 2015). Ethylene is important for root system development (He et al., 2005). Ethylene and auxin are the major phytohormones that control root morphology, such as primary root growth, root hair elongation, and gravitropism (Cherel et al., 2014). When plants are subjected to low-K stress, both the production of ethylene and the transcription of ethylene relevant genes enhanced root hair elongation and primary root growth (Shin and Schachtman, 2004; Jung et al., 2009). In rice and Arabidopsis, jasmonic acid-induced genes are associated with regulating roots in response to K+ deficiency (Takehisa et al., 2013; Armengaud et al., 2004). A more recent study showed that the expression of a K+ transporter gene (OsCHX14) involved in K+ homeostasis in rice flowers is regulated by jasmonic acid signaling (Chen et al., 2016). Auxin-related genes play an important role in the development of plants, lateral roots, adventitious roots and root hairs (Ma et al., 2012; Ljung, 2013). Taken together, this phytohormone signaling may constitute a regulatory network and synergistically control root architecture and K+ transporter expression under low-K stress conditions. Simultaneously, ROS are also vital signaling molecules specific to low-K stress conditions, and they stimulate root hair elongation (Jung et al., 2009; Kim et al., 2010; Shin et al., 2005; Wei et al., 2018a, 2018b). Peroxidase played an important role in oxidative stress (Apel and Hirt, 2004). Previous studies had reported that peroxidase appeared to be another component of the low-K signal transduction pathway in Arabidopsis roots. Studies in Arabidopsis revealed that peroxidase-related gene was found to be up-regulated during K deprivation (Kim et al., 2010). Root adaptations to K deficiency (low K) take place at physiological (Aleman et al., 2011; Amtmann et al., 2005; Armengaud et al., 2004; Shin and Schachtman, 2004), metabolic (Amtmann et al., 2005), and morphological levels (Chen and Gabelman, 2000) and are important for absorbing nutrients from the soil to regulate plant root development (Gahoonia et al., 2006; Hafsi et al., 2011; Han-Bai et al., 2009; Jia et al., 2008; Liu et al., 2017; Yang et al., 2003).

3.5.3. DEGs related to other biological processes In our study, three DEGs annotated as phosphatidylinositol-related biological processes TRINITY_DN277645_c3_g2 were only up-regulated in “1511″. We found that four permease-related genes (TRINITY_DN277344_c3_g1,TRINITY_DN251968_c8_g1,TRINITY_DN23 6835_ c0_g2 and TRINITY_DN263488_c1_g7) were up-regulated in “1511″, while three (TRINITY_DN254122_c0_g1, TRINITY_DN235064_c0_g2 and TRINITY_DN272531_c1_g1) were up-regulated in “1601″. Two DEGs (TRINITY_DN256160_c0_g1 and TRINITY_DN348545_c0_g1) and one DEG (TRINITY_DN240701_c0_g2) associated with flavone processes were up-regulated in “1511″ and “1601″, respectively (Table 2). 3.6. Digging deep into the DEGs We used a false discovery rate (FDR) ≤ 0.001 and an absolute value of fold change > 2 as the threshold to identify DEGs. At the same time, we selected genes (FPKM > 10) for a hierarchical cluster analysis of differential gene expression patterns in the two tea plant genotypes. The relative gene expression levels of “1511″ exceeded those of “1601″ (Supplementary Figure S2). Two specific candidate genes (TRINITY_DN268949_c1_g2 and TRINITY_DN242598_c0_g1) were considered to be more important in improving K starvation tolerance of tea plants. They were the pectinesterase related gene (TRINITY_DN268949_c1_g2) and the peroxidase gene (TRINITY_DN242598_c0_g1) of Camellia sinensis. Their expression levels were relatively high. What's more, the specific candidate genes were up7

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Fig. 6. Verification of the transcript levels obtained from RNA-seq using the qRT-PCR approach. (A) Transcript levels of 12 differentially expressed genes in the two tested genotypes, “1511″ and “1601″, obtained using RNA-seq and qPCR analyses; Data are the means ± SE (n = 3). (B) Correlation analysis of the gene expression levels obtained from RNA-seq and qRT-PCR. Values are the log2ratio (K+ starvation/control) of gene expression. All qRT-PCR assays were performed with three biological replicates.

In the present study, the transcription of certain DEGs involved in ethylene biosynthesis were only up-regulated in “1511″. In “1511″, the expression levels of the jasmonic acid-related and auxin-related genes were higher than that in “1601″. In addition, the DEGs related to catalase-mediated pathways were only up-regulated in the low-K tolerant

genotype “1511″. The highest number of DEGs was associated with peroxidase-related and oxygen-related genes in “1511″ compared with those in “1601″. The peroxidase gene (TRINITY_DN242598_c0_g1) of Camellia sinensis was up-regulated in “1511″, but down-regulated in “1601″ under K starvation. We speculated that regulation of the

Table 3 Primers used for qRT-PCR validation. Unigenes

Forward 5'–3'

Reverse 5'–3'

TRINITY_DN242598_c0_g1 TRINITY_DN268949_c1_g2 TRINITY_DN260035_c2_g1 TRINITY_DN275231_c3_g2 TRINITY_DN250503_c6_g1 TRINITY_DN240304_c2_g4 TRINITY_DN256676_c2_g2 TRINITY_DN241418_c1_g1 TRINITY_DN278845_c4_g4 TRINITY_DN269715_c2_g2 TRINITY_DN279940_c11_g2 TRINITY_DN256092_c3_g1 TRINITY_DN278167_c4_g4 TRINITY_DN271696_c2_g3 TRINITY_DN276904_c3_g2 TRINITY_DN277948_c1_g3 TRINITY_DN273987_c0_g2 TRINITY_DN254272_c1_g3 TRINITY_DN252221_c9_g1 TRINITY_DN279897_c7_g1 TRINITY_DN273749_c0_g1 TRINITY_DN253750_c2_g1 TRINITY_DN265366_c5_g1 TRINITY_DN266235_c0_g5 TRINITY_DN275407_c1_g1 TRINITY_DN279551_c2_g1 TRINITY_DN277655_c3_g2

CTTTGTTAAGGGTTGTGATG CGCCTACTTATAGCAACG GCCCAGAGTGCTTCTAAT TTGTGACAAATACAGGGAC TGAAGTATGCAGCCTCTAC GATGGGCGAAGACCGAGTA GCTCATGCCACCTTCTAT CTCAAGCACCTTCAGCAA ATGAATAGTTTATCGGTCTG TTTTACCGTCACTCACCA AGATTTCAGAGTCGGTATG CGAATCCCTAGAATCGTCT CGAATCCCTAGAATCGTCT GCCGAGAACAACAAAGGT TCGTCCATAGGTCAAATC AGTAGTATTGCTGCTGTCTT GGGTACATGCGAAGAAAT ACAGGTTGAGGGAGTGAA GCAGCACGGAGCACTGACA ACCACCAGGAATAGGAAA GCTTATCTTATGCCTTCTCA CAAAGTGGCAATTTATGTG TTTTAGTCGCCAAATTGC ACGGGGTCTCGAAAAACAAGT AAGGGCAGACAGTAAGCGTC CCAGTGATTTGGAGGAGA CGGAAATGCCCGACTTAT

GACGGTTCCAGGGCAGGCAGC TTAATCCCATCTCCGATC AAGGCAGTCCATCCATAT AATTGACTATGAGGTGGC CAGTGTTTCCATCCGTCT GCAACAAAGGCAATCAAAGAAT CCCACAACTTAACCCACT TTTCCAAGTACCTTCCCTA GTGCCACTGGTTTATCTC ATCCAGCATAACAGCACA ACTGTATTCGGCAGATTG GTCGTCGGACTGAACATAG GTCGTCGGACTGAACATAG AGGCTATCGAGATGGGTAT AATAGCAATGAGATTCCCCAA TTGTTGAAAGTATCCCTGA GCAATAATGAGCCAAACTA TTGCTGATGGTAGGGTTA ACGAGTTCGCCGACCAAA TGACTACAGGTCGAACCA CACAGCCTGTAGGTTCTTT TTGGAGAAGGGAGATGAC ACAAAGGCTAAGAGAAGAAAG AAGAGACCCGCGATCCCATA AGACGCGTCACAAGTTCCAT ACCCGGAGGTTATTTGTA TATCTTCCAAATCGTCTACAC

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Fig. 7. Hypothetical model of the low-K tolerance mechanism. Values are the log2 fold-change (K+ starvation/control) of gene expression. Genes are shown by different colors, and the relative expression levels are shown by a color gradient from low (green) to high (red). For the heatmap from left to right: “1511″ and “1601″ (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.).

peroxidase gene might mediate the low-K signal, which led to the improved K starvation tolerance of “1511″. We found that the morphological differences in the root system of the two tea plant genotypes after SK stress were very notable. All root diameters, the total root length, the total root surface area, and the root volume in the low-K tolerant genotype “1511″ were all greater than those in the low-K sensitive genotype “1601″. Under SK, the low-K tolerant tea genotype showed a higher root development and growth ability than the low-K sensitive tea genotype “1601″ by preferentially developing thick roots (0.5 < D ≤ 2 mm); whereas the low-K sensitive tea genotype had a higher proportion of thin roots (0 < D ≤ 0.5 mm). Therefore, we speculate that a possible reason for the strong resistance of “1511″ to low-K stress is that plant hormone signal transduction and ROS metabolic processes regulated by these genes promote root growth, thus improving low-K stress tolerance.

regulated due to K starvation (SK). However, we found that the upregulation of some genes involved in nitrate transport, which indicated that the function of nitrate-induced regulation of tea plant responses to SK might be different from that in other plants. In addition, the DEGs related to ammonium transporter pathways were only up-regulated in the low-K tolerant genotype “1511″. These findings suggest that nitrogen metabolites were likely participated in low-K stress signaling. Therefore, the relationship between K and N transport is worth further research. Calcium signal transport genes are essential for regulating K uptake in response to low-K stress (Held et al., 2011; Liu et al., 2013; Xu et al., 2006). Plant-specific serine/threonine protein kinases, or CIPK proteins, can exclusively interact with calcineurin B-like proteins and form a CBL-CIPK complex, which in turn constitutes a specific regulatory network of Ca2+ signaling in plant cells (Liu et al., 2006; Yu et al., 2014). In our study, nineteen and six calcium signal transport genes were up-regulated in “1511″ and “1601″, respectively. These findings suggest that the enhancement of more calcium-related genes in “1511″ might be correlated to the greater adaptation of “1511″ to low-K stress than “1601″.

4.2. DEGs encoding ion transporters related to K uptake In plants, K transporters and channels are critical in the long-distance distribution of K+ from the roots to the upper parts of plants (Chen et al., 2015; Cherel et al., 2014; Liu et al., 2006; Yang et al., 2015). K+ absorption and translocation in plants occur mainly via highand low-affinity K uptake systems, which are mediated by K-related transporters and channels, respectively (Pyo et al., 2010; Wang and Chen, 2012; Wang and Wu, 2013; Ward et al., 2009). In our study, we found that genes related to K transport were up-regulated in “1511″ and that the K transport expression levels were significantly higher in “1511″ than in “1601″ under SK stress. Previous studies found that nitrate transporters affect K recycling between the root and shoot (Xia et al., 2015). In our study, we found that SK induced the up-regulation of 10 nitrate transporter genes in “1511″ but none in “1601″, suggesting that the two tea plant genotypes have different responses to nitrogen metabolism regulation under SK. Studies in Arabidopsis (Armengaud et al., 2004) and rice (Ma et al., 2012) revealed that several nitrate transporter genes are down-

4.3. DEGs related to K use efficiency (KUE) Several biological pathways, the phosphatidylinositol signaling system might be relevant to potassium use efficiency (KUE) under lowK stress (Britto and Kronzucker, 2008; Diem et al., 2001; Rapala-Kozik et al., 2008). In the present study, we found that DEGs associated with phosphatidylinositol-related biological processes were only up-regulated in “1511″, TRINITY_DN277645_c3_g2 associated with phosphatidylinositol, which was found to be 96.57% similar to the Zea mays gene (LOC542290). Previous studies had reported that the regulation of phosphorylation plays a key role in K+ transport regulation and provides energy for transportation if needed (Ho and Tsay, 2010; Lee et al., 2007). Therefore, the phosphatidylinositol gene might indirectly regulate other metabolic processes and then improve KUE. Our study 9

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showed that the K biological utilization index of “1511″ was clearly higher than that of “1601″. We speculate that differences in K biological utilization index may have led to the different adaptation capacities to low-K stress in the two tea plant genotypes. The K biological utilization index of “1511″ was noticeably higher than that of “1601″, which was most likely a key factor underlying the tolerance to low-K stress in “1511″.

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4.4. Other DEGs potentially correlated with K uptake With the profound effect on cell wall modification, the pectinesterase related gene was found to play an important role in the K+ uptake (Wu et al., 2017). Pectinesterase-inhibited plants were specifically modified as they bound less K, which leaded to a change in the absorption of K (Pilling et al., 2004). Our study showed that one DEG associated with pectinesterase (TRINITY_DN268949_c1_g2) was only up-regulated in “1511″. We speculated that regulation of the pectinesterase gene might affect the K uptake, which was very valuable for the future research. 5. Conclusions The two tea plant genotypes “1511″ and “1601″ exhibited markedly distinct root morphological and transcriptional changes under K starvation (SK). Despite the complexity of the responses to K deprivation, a hypothetical model based on the available results could be suggested for the low-K tolerance mechanism in “1511″ (Fig. 7). The expression levels of genes responding to low-K stress were higher in “1511″ than “1601″. The genes that regulate different metabolic processes may have been correlated with the differences in root architecture, K+ uptake and utilization observed between “1511″ and “1601″. The low-K tolerance mechanism of hypothetical model can contribute to understanding of the unique mechanisms of adaption to changes in K availability in tea plant. However, further investigations are required to understand how these specific genes regulate K metabolism. Declaration of Conflicts of Interest The authors declare that they have no conflicts of interest. Acknowledgments The study was supported by the National Natural Science Foundation of China (41601329 and 41877006), the Open Foundation of State Key Laboratory of Soil and Sustainable Agriculture (Y20160011), the earmarked fund for China Agriculture Research System CARS-19, and the Major Science and Technology Special Project of Variety Breeding of Zhejiang Province (2016C02053-8). Appendix A. Supplementary data Supplementary material related to this article can be found, in the online version, at doi:https://doi.org/10.1016/j.scienta.2019.108570. References Aleman, F., Nieves-Cordones, M., Martinez, V., Rubio, F., 2011. Root K(+) acquisition in plants: the Arabidopsis thaliana model. Plant Cell Physiol. 52, 1603–1612. Amtmann, A., Hammond, J.P., Armengaud, P., White, P.J., 2005. Nutrient sensing and signalling in plants: potassium and phosphorus. Adv. Bot. Res. 43, 209–257. Apel, K., Hirt, H., 2004. Reactive oxygen species: metabolism, oxidative stress, and signal transduction. Annu. Rev. Plant Biol. 55, 373–399. Armengaud, P., Breitling, R., Amtmann, A., 2004. The potassium-dependent transcriptome of Arabidopsis reveals a prominent role of jasmonic acid in nutrient signaling. Plant Physiol. 136, 2556–2576. Britto, D.T., Kronzucker, H.J., 2008. Cellular mechanisms of potassium transport in plants. Physiol. Plant. 133, 637–650. Chen, G., Feng, H., Hu, Q., Qu, H., Chen, A., Yu, L., Xu, G., 2015. Improving rice tolerance

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