Differential expression profiles and pathways of genes in drought resistant tree species Prunus mahaleb roots and leaves in response to drought stress

Scientia Horticulturae 226 (2017) 75–84

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Differential expression profiles and pathways of genes in drought resistant tree species Prunus mahaleb roots and leaves in response to drought stress Ying Feng, Chenglin Liang, Binbin Li, Tian Wan, Tao Liu, Yuliang Cai

MARK

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College of Horticulture, Northwest Horticultural Plants Genetic and Breeding Key Laboratory of Ministry of Agriculture, Northwest Agriculture & Forestry University, 3 Taicheng Lu, Yangling, 712100, Shaanxi, PR China

A R T I C L E I N F O

A B S T R A C T

Keywords: Candidate genes Drought Differentially expressed genes Prunus mahaleb RNA-seq Transcriptome

Prunus mahaleb exhibits tolerance to drought as woody plant genotype, shows great potential for cherry rootstock breeding, while the molecular mechanism for its respond to water deficiency is still not fully understood. The physiological and RNA-seq approaches were used to investigate the transcriptome mechanisms that allow P. mahaleb to survive in arid environments. 1, 573 differentially expressed genes (DEGs) involved in drought response were selected from well-watered and drought-stressed P. mahaleb leaves (517) and roots (1, 056). Carbohydrates metabolism, hormone signal transduction and secondary metabolites were intensive pathways involved. Glycogen biosynthesis and glycosyl hydrolases genes were reduced to rebuild energy homeostasis, NCED homology genes were induced for stomatal regulation and water conservation. The expression of linolenic acid and amino acids synthesis related genes was generally increased to enhance drought tolerance. CBF/NF-Ys, MYB, WRKY and U-box as TFs may regulate key functional genes to adapt the stress. It is indicated differences pertaining to the molecular mechanisms occurring in tree roots vs. shoots in response to drought stress. A core set of 32 candidate genes were identified that could function as targets for detailed functional studies of drought responses at molecular level in prunus family. Furthermore, these genes may be used to potentially breed trees with drought tolerance.

1. Introduction Drought is a major abiotic stress for plant survival and severely impacts on the yield and quality in agricultural production systems (Chaves et al., 2003; Sivritepei et al., 2008; Küçükyumuk et al., 2015). Given the increasing threatens of water deficiency globally, it is of great importance for breeders to understand the molecular responses of plants to drought stress and develop novel molecular approaches to enhance the drought tolerance of plants. The natural germplasm resources with excellent drought resistance are ideal materials to reveal the mechanism on plant responses and survival under water deficient conditions. Prunus are the most economically beneficial population for producing fruits, such as peach, cherry, plum and apricot. Most of them are sensitive to water deficits, while prunus mahaleb is one of the drought resistant species shows great potential for cherry rootstock breeding (Hrotkó, 2016). P. mahaleb is native to Europe and Western-Asia (Rehder, 1927; Hrotkó, 2016). It grows in thickets and open woodland on dry slopes, especially in central and southern Europe typically in

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thickets on dry karst areas (Faust and Surányi, 2010). It was reported that this species can survive in extremely drought conditions, the drought resistance of this species is due to its deep root systems allowing more water uptake, thus maintaining a stable hydraulic conductivity (k) in stem throughout the drought season (Nardini et al., 2015). Various strategies of avoidance and tolerance are taken in plants to adapt to drought stress. The integrated responses involve changes at whole plant level, such as shoot-root carbon allocation, plant growth rate, leaf and root morphology, leaf abscission, stomatal conductance and photosynthesis (Sivritepe et al., 2008; Chaves et al., 2009; Pucholt et al., 2015). Besides that, molecular changes induced by drought stress were also examined by remodelling of the transcriptome, including upregulation of stress signalling, energy metabolism, secondary metabolites production, transcription factors and defence processes (Singh et al., 2013; Dietze et al., 2014). Apparently, the responses of woody plants coping with extreme drought are involved the morphological, physiological, biochemical and molecular processes. Jiménez et al. (2013) stated that drought resistance of prunus plants is closely related

Corresponding author. E-mail addresses: [email protected], [email protected] (Y. Feng), [email protected] (C. Liang), [email protected] (B. Li), [email protected] (T. Wan), [email protected] (T. Liu), [email protected] (Y. Cai). URL: http://[email protected] (Y. Cai). http://dx.doi.org/10.1016/j.scienta.2017.07.057 Received 14 April 2017; Received in revised form 28 July 2017; Accepted 28 July 2017 0304-4238/ © 2017 Elsevier B.V. All rights reserved.

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2.2. Physiological measurements

to its genetic background. Thus, besides the physiological and morphological explanation, it is necessary to explore the unique molecular and biochemical mechanisms associated with drought tolerance in some extreme plants. P. mahaleb grows well in water-limited areas with native drought resistance and plays an important role in economic and ecological environment. However, few studies have been reported to reveal the molecular mechanisms of drought tolerance in this species. RNA-seq has been used successfully to identify abiotic stress related genes, implicating several biosynthetic pathways that assist in the overall tolerance to drought stress. The molecular responses of plants to drought has been well documented in model plant Arabidopsis (Sakuraba et al., 2015), rice (Oono et al., 2014), Morus L. (Wang et al., 2014), B. juncea (Bhardwaj et al., 2015), and barley (Hübner et al., 2015) using high-throughput transcriptomics. For Prunus plants, Wang et al. (2015) characterized the transcriptome of P. mongolica under drought stress, and shed new lights on the molecular mechanisms underlying the response to drought in this species. Generally, root system initially experiences and signals drought in plants, thus, playing a key role in coping with water stress. This is consistent with the finding that there are genes specifically expressed in certain root types under drought stress (Ghosh and Xu, 2014). MdNRT2.4 and MpNPR1-2 were found specifically expressed in Malus roots under drought (Bassett et al., 2014). Since drought responses may varied in different plant organs or tissues (Zhou et al., 2007), the analysis in both mature leaves and root tips is critical for plants to adapt to water deficits. The objectives of this research were to identify stress-induced patterns of gene expression and select candidate genes related to drought resistance under severe drought in P. mahaleb. Transcriptome highthroughput sequencing was performed in root and leaf tissues of P. mahaleb plant under well-watered and water-deficient conditions. respectively to profile the gene expression, together with physiological process and biochemical functions, to provide a comprehensive analysis of drought acclimation in this species. The acquired genes, pathway analysis and other information may provide new insights into the molecular mechanisms underlying P. mahaleb response to water stress.

RWC was calculated using the following equation, RWC(%) = [(FW − DW)/(TW − DW)] × 100. Superoxide dismutase (SOD) activity was determined using NBT-illumination method (Giannoplitis and Ries 1977); peroxidase (POD) activity was determined using guaiacol colorimetric method, and catalase (CAT) activity using hydrogen peroxide method (Zou, 2000). Alondialdehyde (MDA) content was determined by barbituric acid colorimetric method (Zhao et al., 1994a,b). Proline (Pro) content was determined using ninhydrin colouring and spectrophotometry method (Zhang et al., 1990). The leaf samples for physiological measurements were harvested at 4 stages according to pot soil moisture content: 75%–80% (well-watered), 55%–60% (mild drought), 40%–45% (moderate drought) and 30%–35% (severe drought)of field capacity. 2.3. Preparation of total RNA and cDNA for transcriptome sequencing Total RNA was isolated from plant root tips and leaves by using TRIzol® reagent according to the manufacture’s protocol. 0.1 g root tips or leaf tissues were well ground into fine powders and added 1 ml TRIzol® reagent. The extracted liquid was added into 0.2 ml of chloroform and centrifuged at 1200rcf for 15 min at 4 °C, and the cleared supernatant was transferred into a new tube and added into 0.5 ml isopropanol. Then, tubes were incubated at room temperature for 10 min and centrifuged at 1200rcf for 10 min at 4 °C. 1 ml of 75% ethanol was added into the tube to wash the RNA deposit and then dried and suspended in RNase-free water. The RNA quality was controlled using Nanodrop, Qubit 2.0 and Aglient 2100. After that, the RNA was used for cDNA library constructionusing Takara PrimeScript RT reagent Kit. 2.4. Sequencing and de novo assembly of the prunus mahaleb transcriptome Qubit2.0 and Agilent 2100 were used to test the concentration of the library and insertion fragment size (Insert Size), respectively. The Q – effective concentration of library accurate quantitative PCR method was used to ensure the quality of library. 12 cDNA libraries were sequenced by SBS (Sequencing By Synthesis) sequencing technology with an Illumina HiSeq™ 2500 sequencer. Read length is PE125. De novo assembly of the transcriptome was performed by Trinity software. To ensure a uniform transcriptome reference across samples, all clean reads were pooled together for assembly, then clean reads of each sample was individually aligned to the assembled transcriptome reference to get mapped reads for subsequent analysis.

2. Materials and methods 2.1. The growing conditions, experimental design and sampling The experiments were conducted at Northwest A & F University, Yangling, China (34∘20′N, 108∘24′E). Two-year old P. mahaleb seedlings were grown in glasshouse with day/night temperature of 28/18 °C. Sixty pots containing potting humus were divided into two equal groups, and one group was use for drought treatment and for the other one for well-water control. Seedlings were grown one year in field in 2014, and then transplanted into 4.5L pots and placed in glasshouse on 14th February 2015. They were irrigated every 3 days to field capacity as needed and fertilized weekly with Hoagland’s solution. All plants were irrigated as the same manner before treated, the soil moisture in pots was maintained about 75% of field capacity. The water-stress treatment was imposed by stopping irrigation, while the control treatment was continued watering. Plant drought stress was monitored based on leaf relative water content (RWC). On day 15, the first time of leaf wilting appearance, and the leaf RWC of water-stressed plants was 65% (vs 89% in control). All plants were sampled, including leaves under water-stressed and control treatments (LS1, LS2, LS3, LCK1, LCK2 and LCK3 respectively) and root tip under water-stressed and control treatments (RS1, RS2, RS3, RCK1, RCK2 and RCK3). Mature and healthy leaves (4–6th leaves from the apical meristem) were sampled from each plant and immediately frozen in liquid nitrogen. Root tip tissues were harvested at the same time after quickly washing off and sucking moisture, and then frozen in liquid nitrogen. The frozen tissues were stored at −70 °C for further analysis.

2.5. The identification of differential expressed genes and pathway analysis In order to define the set of expressed genes, raw read counts were normalized to RPKM (Reads per Kilobase per Million), above or equal to 1 were filtered out. Differential expressed genes (DEGs) were selected by performing the negative binomial test implemented in the DESeq package. In present study, the DEGs were filtered by their fold changes (> 2) and FDR (Benjamini-Hochberg method adjusted p-values < 0.01) as screening standards. To identify the Differential Expression Genes (DEGs), they were annotated by comparing to previously annotated genes in public databases, NCBI non-redundant (NR) database, Swiss-Protdatabase, Gene Ontology, euKaryotic Orthologous Groups/Clusters of Orthologous Groups (KOG/COG). Pathway analysis was implemented using Kyoto Encyclopedia of Genes and Genomes (KEGG) database. Then, HMMER Software and Pfam Information database were used for unigene sequences prediction of amino acids comments. GO terms and KEGG pathways fulfillig the criterion of a Bonferroni-corrected pvalue ≤ 0.05 were defined as significantly enriched in DEGs. BLAST Evalue ≤10−5 and HMMER E-value ≤10−10 were set as select 76

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database were used. 487 leaf DEGs and 836 root DEGs were annotated by these database, and the annotation percentage were 94.2% and 79.2%, respectively. In GO database, all DEGs were distributed into “cell part”, “catalytic activity” and “metabolic process” with total of 50 annotation categories. In this study, the distributed DEGs GO annotation categories were similar overall in leaf and root drought responses (Supplemental Fig. S1). Most of DEGs in roots and leaves were distributed into 7 categories including metabolic process (290 root DEGs/114 leaf DEGs), catalytic activity (258/104), cellular process (231/160), binding (224/ 134), single-organism process (194/135), cell part (136/96) and cell (134/96). The number of DEGs in roots was more than those in leaves on all GO categories, except 6 categories including “extracellular region” (11/15), “organelle part” (25/34), “reproductive process” (10/ 13), “reproduction” (11/13), “membrane-enclosed lumen” (0/2) and “rhythmic process” (0/1). The DEGs’ predicted proteins in leaves and roots of P. mahaleb in response to drought were classified by KOG database (Supplemental Fig. S2). Most of proteins were assigned to 10 categories of “Signal transduction mechanism” (90 root DEGs/34 leaf DEGs), “General function prediction” (68/37), “Posttranslational medication and protein turnover” (37/20), “Lipid transport and metabolism” (26/17), “Transcription” (25/13), “Energy production and conversion” (23/11), “Carbohydrate transport and metabolism” (20/16), “Inorganic ion transport and metabolism” (19/11) and “Amino acid transport and metabolism” (17/12). As to the DEGs predicted proteins classified by COG database, most of them were distributed into four categories of “Transcription” (87/38), “General function prediction only” (116/68), “Signal transduction mechanisms” (99/38) and “Replication, recombination and repair” (78/35).

parameters. 2.6. QRT-PCR analysis qRT-PCR was performed on an ABI StepOnePlus real-time PCR system. Reactions were performed in 20 μl volumes containing EvaGreen 2X qPCR MasterMix (Applied Biological Materials Inc.) and a quantity of cDNA corresponding to 10 ng of total RNA. Primers used for the qRT-PCRs are listed in Supplemental Table S1. Total RNA was used as template for reverse transcriptase reactions, and cDNA synthesis was done using 5X All-In-One RT MasterMix (with AccuRT Genomic DNA Remonval kit, Applied Biological Materials Inc.). qPCR reaction was performed in a volume of 20 μl volumes containing 10 μl EvaGreen 2X qPCR MasterMix, 2 μl cDNA, 1 μl of each primer, and 6 μl RNase-free sterile water. PCR reactions were performed at 95 °C for 10 min, followed by 35 cycles of 95 °C for 3 s, 60 °C for 30 s. All 12 cDNA samples were analyzed in triplicate. ACTIN was used as reference gene to normalize the relative expression of selected genes. Relative expression levels (Fold Changes) of 15 candidate genes were calculated using 2−ΔΔCt method and translated to log2 Fold Changes to compare with RNA-seq results. 3. Results 3.1. The key physiological players under drought stress Drought related physiological index including RWC, MDA, Proline, SOD, CAT and POD content were shown in Fig. 1. P. mahaleb leaf RWC decreased progressively under drought stress, and appeared to be 65% under severe drought, which is a moisture content of temporary wilting. Compared to well-watered plants, ChlorophyII content of waterstressed plant decreased slightly under mild and moderate drought, and down to half under severe drought. Proline, as osmotic regulation substances, was accumulated in the process of drought stress. To contrast, MDA content increased under drought stress than well-water treatment, indicating that the leaf cells experiencing membrane lipid peroxidation damage. CAT and POD content increased in the process of mild and moderate drought stress, and tended to decrease under severe drought. SOD content showed opposite trend that its content was slightly lower under severe drought than well-watered control.

3.4. Pathway analysis of P. mahaleb in response to severe drought Top 20 potential pathways involved in drought responses in roots and leaves were screened as most intensive response activities (Fig. 3). From KEGG tree analysis, “Carotenoid biosynthesis”, “Plant hormone signal transduction”, “Starch and sucrose metabolism”, “alpha-linolenic acid metabolism”, “Phenylpropanoid biosynthesis” and “Zeatin biosynthesis” were the most active physiological activities in leaves, while “Starch and sucrose metabolism”, “Porphyrin and chlorophyII metabolism”, “Amino sugar and nucleotide sugar metabolism”, “Cysteine and methionine metabolism”, “Linolenic acid metabolism”, “alpha-linolenic acid metabolism” and “Zeatin biosynthesis” were the most active ones in root tips. “Metabolism”, “Plant-pathogen interaction” and “Plant hormone signal transduction” were the main pathways in both leaves and roots responding to drought in P. mahaleb. There were specific pathways in roots such as “Peroxisome”and “Endocytosis” which were not showed in leaves.

3.2. Sequencing and de novo assembly of P. mahaleb transcriptome To obtain an overview of the transcriptome of P. mahaleb roots and leaves in response to drought stress, 12 cDNA libraries were constructed using the Illumina sequencing technology. These cDNA libraries were from roots and leaves that had been exposed to water deficit on day 15 (LS1, LS2, LS3, LCK1, LCK2 and LCK3) and well-watered control (RS1, RS2, RS3, RCK1, RCK2 and RCK3). 69.67Gb Clean Data was obtained, and Q30 bases percentage was higher than 92.58% for all samples. The results of sequencing data are shown in Table 1.

3.5. QRT-PCR validation of DEGs from RNA-Seq To confirm the accuracy and reproducibility of the Illumina RNASeq results, 15 candidate DEGs were selected to be tested using qRTPCR. The RNA-Seq results and qRT-PCR values were displayed in Fig. 4. The expression patterns were generally in consistent with those observed in RNA-Seq results.

3.3. Drought responsive DEGs selection and functions annotation in P. mahaleb To understand the functions of the assembled unigenes, 91744 unigenes annotation information was obtained, and annotated rate is 53.3% of P. mahaleb (Table 2). DEGs between well-watered and drought groups were identified by DESeq, 1573 DEGs related to drought responses were selected from P. mahaleb roots and leaves. The transcriptome data showed that the number of down-regulated unigenes was more than up-regulated unigenes. Root drought response DEGs (1056) were more than leaf response DEGs (517) in the experiment (Fig. 2). All DEGs were searched against the NCBI non-redundant database (http://www.ncbi.nlm.nih.gov) to find protein similarity (evalue ≤10−5 cut-off). GO, COG, KOG, NR and Swiss-Prot annotation

4. Discussion Prunus mahaleb is characterized as drought tolerant woody plant genotypes (Hrotkó 2016; Nardini et al., 2015). While very few researches are conducted to study the genomic resources of P. mahaleb, and the molecular mechanisms underlying its drought tolerance. There also lacks of global changes of gene expression in both roots and shoots of drought-stressed cherry so far. From DEGs GO cluster analysis, KOG/ COG annotation and KEGG pathway analysis, it was indicated that 77

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Fig. 1. Drought related physiological measurements on p.mahaleb. Note: The pot soil moisture content was 75%–80%, 55%–60%, 40%–45% and 30%–35% of field capacity in well-watered control, mild drought, moderate drought and severe drought respectively.

4.1. Changes in the expression of sugar, starch and other carbohydrate metabolism genes

sugar, starch and other carbohydrate metabolism, plant hormones signal transduction, plant secondary metabolites and transcription factors were the key activities involved in drought responses in P. mahaleb. Meanwhile, the genes’ expression changes and their putative function were analyzed and discussed, aiming to provide new insights into the molecular mechanisms related to drought resistance of this species.

Photosynthesis and carbon fixation are easily affected by drought, especially under long-term water deficiency (Chaves et al., 2009). The ability of plants to survive in severe drought conditions is associated with the accumulation of carbohydrates (Picon et al., 1997; Piper, 2011; Bianco and Scalisi, 2016). Concomitantly, carbon metabolism is of great interests and could play important role in conferring tolerance against drought stress by providing energy, signaling, regulation of osmotic, and modulating several physiological processes in plants (Sami 78

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Table 1 Transcriptome Illumina sequencing data and de nove assembled results on P. Mahaleb. Samples

Read Number

GC content(%)

≥Q30(%)

Mapped reads(Ratio)

LCK1 LCK2 LCK3 LS1 LS2 LS3 RCK1 RCK2 RCK3 RS1 RS2 RS3

21202130 28663596 23068394 23358936 21440130 29720520 24176609 22850421 18916514 20220994 23096527 21973106

46.71 46.38 46.99 46.38 46.42 46.73 47.01 46.77 47.05 47.32 47.07 47.07

93.08 94.6 93.16 94.42 94.46 94.73 94.47 93.04 92.58 94.62 92.65 92.62

19,644,107 (92.65%) 26,405,501(92.12%) 21,331,011 (92.47%) 21,580,247 (92.39%) 19,847,439 (92.57%) 27,466,682 (92.42%) 21,258,082 (87.93%) 20,341,420 (89.02%) 16,557,384 (87.53%) 17,836,115 (88.21%) 20,472,996 (88.64%) 19,304,057 (87.85%)

Note: RCK and LCK are well-watered control samples, LS and RS are drought treatment samples.

Fig. 2. Drought related up and down regulated DEGs venn diagram on p.mahaleb.

et al., 2016; Rathinasabapathi 2000). Soluble sugars such as, glucose, sucrose, fructose and raffinose maintains the leaf water content and osmotic adjustment to enhance plant tolerance to drought (Koster and Leopold 1988; Rathinasabapathi 2000). Carbohydrate metabolism was active to rebuild a new homeostasis status dealing with drought in P. mahaleb. Genes related to glycogen biosynthesis, glycosyl hydrolases, starch catabolic, sugar transport process were identified as drought responsive DEGs in P. mahaleb (Supplemental Table S2). Genes involved in starch catabolic processes were up-regulated in leaves, while trehalose, sucrose and L-arabinose biosynthetic genes were down-regulated. A similar pattern was observed for these genes in roots. Genes annotated to “Glycosyl hydrolases” had complex responses, many of them increased in leaves, while others decreased in both leaves and roots. Non-structural carbohydrates are considered to be important for woody plants living through the severe drought for reversing xylem embolism damage (Nardini et al., 2015), especially soluble sugars related to the restoration (Savi et al., 2016). In this study, genes associated with sugar transport and catabolism were generally up regulated in the drought treatment, and most of DEGs related to carbohydrate transport and metabolism were selected from plant leaf tissues other than roots. Although the genes in roots had similar variation trend, they were not considered as DEGs since their false discovery rate were greater than 0.01. These results may indicate that, under long and severe drought stress, shoot parts plays a prior role in energy metabolism and enhancing the drought tolerance of P. mahaleb. In general, from transcriptome changes, carbohydrates flow redirection was from reserve substances to soluble sugar facing the conditions of drought stress.

of ABA receptor homology PYR/PYL/RCAR was significantly decreased. In Ethylene signaling pathway, EREBP-like factor and homology ERFs, as the major downstream regulatory factors of ET signaling pathway, were significantly decreased in both roots and leaves. In Cytokinin signaling pathway, homology Cytokinin dehydrogenase 5 decreased in roots while Cytokinin dehydrogenase 7 increased in leaves. The transcription of protein phosphate 2C (PP2C) is negatively regulated ABA signal transduction (Arshad and Mattsson, 2014), which was up-regulated in severe drought treatment in this study. This was in agreement with the drought experiments in Mongolian Almond Prunus mongolica Maxim (Wang et al., 2015) and tobacco (Vranova et al., 2000). However, it was also reported that drought had no effects on PP2C transcription and expression in Fagus sylvatica (Lorenzo et al., 2002) or down regulated in resurrection grass sporobolus stapfianus during severe drought stress (Neale et al., 2000). Generally, the ABA-mediated pathway is inhibited by IAA, CTK and ethylene in abiotic stress, while SAs, JAs and BRs display synergistical action with ABA (Acharya et al., 2009). In this study, CTKs dehydrogenase genes were repressed in plant roots under drought, but were tending to increase in leaves. All Ethylene responsive TFs were repressed in both leaves and roots of plants under drought treatment, and the DEGs fold change was greater in roots than leaves. SAs, BAs and JAs were generally down regulated in both water-stressed roots and leaves. These contradictory results might be related to the variability in plant response mechanism, type and intensity of drought stress imposed. Although these hormones have been identified in various plant abiotic stresses, their associations with drought resistance is still not fully understood and needed to be examined with respect to their roles in responses to drought.

4.2. Changes in the expression of plant hormone signals In this study, after severe drought treatment, a number of hormonerelated genes were significantly up- or down-regulated in P. mahaleb roots and shoots (Supplemental Table S3), involving the regulations on plant hormones pathways, such as ABA, Ethylene, Cytokinin, salicylic acid, Brassinosteroid and Jasmonic acid signaling pathways. These genes were identified as genes involved in the drought responses in P. mahaleb. In ABA signaling pathway, biosynthesis related homology NCED was increased in both leaves and roots, while the transcript abundance

4.3. Changes in the expression of secondary metabolites Plant metabolism balance would be reprogrammed under drought stress, and osmotic modifications and secondary metabolism changes occurs commonly. These metabolites generally enhance drought resistance of plants. According to GO analysis, “metabolic process” was the most DEGs distributed item in P. mahaleb faced severe drought stress. The key genes were listed in Supplemental Table S4. In this study, a number of flavonid, lipid biosynthesis and transport

Table 2 Differential expression genes annotation involved in severe drought response on P. mahaleb. DEG Set

All DEGs

Up-regulated

Down-regulated

Annotated DEGs

Annotation percentage

COG

GO

KEGG

KOG

Pfam

Swiss-Prot

nr

LS vs LCK RS vs RCK

517 1056

165 69

352 987

487 836

94.2% 79.2%

171 272

274 438

67 111

215 380

400 664

362 574

487 834

Note: RCK and LCK are well-watered control samples, LS and RS are drought treatment samples.

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Fig. 3. KEGG pathway enrichment analysis of leaves and roots drought response DEGs on p.mahaleb.

key role in regulating the cellular osmotic adjustment, mitigating cellular damaging risk caused by ROS and preventing cell membrane injury and stabilizing proteins and enzymes when plants experiencing dehydration (Bohnert and Jensen 1996; Ashraf and Foolad 2007; Singh et al., 2015). Proline biosynthetic related gene annotated as “oxidationreduction, P5CS” increased in leaves. Cysteine biosynthetic process related genes was up regulated in leaves, as well as arginine and amines. Gene ‘c91221-c0′ is annotated as “AMP-binding enzyme Cterminal domain”, and it is interesting to see this gene was up regulated in leaves but down regulated in roots, which may contribute to drought resistance of P. mahaleb. According to physiological measurements, proline content increased persistently with the gradually water deficiency, which was consistent with the transcriptome results. However, the role of plant secondary metabolites to enhance drought resistance is not fully understood, and it is still difficult to explain specific function of diverse responses in secondary metabolites in others’ and present study (Niinemets 2015).

related genes increased in P. mahaleb leaves. Genes involved in lipids metabolic process. Linolenic metabolism pathway showed prominently both in shoot and root. Gene ‘c42289-c0′, annotated as “Lipocalin-like domain, Lipocalin/cytosolic fatty-acid binding protein” increased in leaves, and its leaf transcript abundance was much greater than in roots. ‘c97008-c0′ annotated as “FAD binding domain” was increased in leaves but decreased in roots. Fat acids play significant roles in improving stress tolerance by participating in a variety of defense pathways, including defense effector-triggered and systemic immunity (Zhigacheva et al., 2013). Alpha-linolenic from membrane lipids can mediate remodeling membrane fluidity to maintain an environment suitable for the function of critical integral proteins during stress (Upchurch 2008; Scotticampos and Phamthi, 2016). Li et al. (2016) stated that alpha-linolenic acid might be associated with cold tolerance in camellia japonica. Under drought stress, the linolenic acid content is increased in drought-tolerant cowpea cultivar while decreased in drought-susceptible cultivar (Maria et al., 2009). decreased on linolenic acid content, and they were in terms with FAD genes expression. Genes involved in the biosynthesis of amino acids such as proline, arginine, cysteine and amines were generally increased in this experiment after severe drought. These amino acids were reported to play a

4.4. Drought responsive transcription factors Transcription factors always regulate genes in complex abiotic 80

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Fig. 4. The RNA-Seq results and qRT-PCR values.

determine their functions in order to improve our knowledge of drought tolerance in prunus plant.

stresses, which makes them prime candidate genes for improving tolerance to abiotic stresses like drought. It is known that several TF families including bZIP (mainly AREB/ABF), DREB (AP2/EREBP), MYB,WRKY and NAC, are key regulators involved in response to abiotic stresses including drought (Heim et al., 2003; Xu et al., 2007; Zhu et al., 2013; Lata and Prasad 2011; Kiranmai et al., 2016; Seeve et al., 2016). In this study, some of the above TF family members were involved in drought response of P. mahaleb (Supplemental Table S5). CBF/NF-Ys are related to drought resistance in plants (Li et al., 2008; Han et al., 2013), and they were up-regulated in both roots and leaves in droughtstressed P. mahaleb. PeNF-YB1 gene is a member of plant NF-YB gene family that plays a regulative role in drought resistance of wood plants populus (Yan et al., 2012). PmNF-Y gene expressions are enhanced in prunus mume during salt and H2O2 stress responses (Yang et al., 2016). NF-YB may act in modulating an ABA-associated signaling pathway and impact on the plant reactive oxygen species (ROS) metabolsim and osmolyte accumulation (Yang et al., 2016). Three bZIP genes involved in this treatment were up regulated in leaves. Three MYB genes were up-regulated. ‘c85700-c0′ transcript, annotated as “MYB39”, was up regulated in both leaves and roots while one was up regulated in leaves and the other one was up regulated in roots. MYB regulons participate in some important transcriptional pathways that are involved in drought stress responses via ABA-dependent signaling systems (Baldoni et al., 2015). ‘c98012-c0′ transcript annotated as “WRKY transcription factor 17” was down regulated after treatment. Some results suggested that TaWRKYs are involved in regulating the expression of some key ROS-related and stress responsive genes under drought. AP2-like and NAC-like transcripts were all repressed in roots and leaves. It was interesting to see two transcripts belong to Zinc finger and U-box exhibited opposite trend in leaves and roots. ‘c104121-c0′ transcript annotated as “U-box domain-containing protein 9” was down regulated in roots while up-regulated in leaves.‘c55290-c0’transcript annotated as “Zinc finger CCCH domain-containing protein 49” was up regulated in roots while down regulated in leaves.

4.6. A core set of candidate genes involved in severe drought response in P. mahaleb leaves and roots A core set of candidate genes involved in severe drought responses in roots and leaves of P. mahaleb were selected. Based on DEGs annotation and reported functions in plant stress responses combined with DEGs fold change and expression abundance, a core set of 32 candidate genes were targeted for detailed functional studies of drought responses at molecular level in cherry and related species. For the specifically responsive DEGs in leaves, most of them were homologous to genes related to Glycosyl hydrolase family, transporters, PP2C, fatty-acid binding proteins and chlorophyll a/b binding proteins, while others were not annotated to homologous species for putative function description. For the specifically responsive DEGs in roots, most of them were homologous to genes encoding transcription factors, e.g. Zinc finger, MYBs, HSFs and NF-YAs, while others are genes encoding PP2C, PCS1 and some unknown proteins (Table 3). Ultimately, the present work provides an overview of deductive pathway in plant responses under drought stress and better understanding on the mechanisms involved in drought tolerance in P.mahaleb (Fig. 5). 5. Conclusion Carbohydrates metabolism, signal transduction of plant hormones, plant secondary metabolites are intensive pathways to be focused in present study. Genes involved in glycogen biosynthesis and glycosyl hydrolases may mediate carbohydrates flow redirection from reserve substances to soluble sugar to enhance drought tolerance. NCED homology was up-regulated for stomatal regulation and water conservation. Genes encoding fatty-acid binding protein, lpha-linolenic acid and linolenic may function by remodeling membrane fluidity to prevent cell membrane injury. Genes involved in the biosynthesis of amino acids such as proline, arginine, cysteine and amines were generally increased to enhance drought tolerance. Furthermore, CBF/NFYs, MYB, WRKY and U-box domain as TFs regulated key functional genes to adapt to drought stress. A core set of candidate genes were selected for potentially breeding trees with drought tolerance. A comprehensive deductive pathway was summarized to understand its molecular responses coping with drought stress in P. mahaleb.

4.5. The up-regulated unknown transcripts in response to drought A number of up-regulated DEGs without specific annotated function showed significantly increase either in roots or leaves. These unknown genes may play an important role in drought resistance in p.mahaleb (Supplemental Table S6). These genes are intriguing for species-specific with limited information, which needs to further investigation to 81

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Table 3 A core set of candidate genes involved in severe drought response on P. mahaleb. Gene ID

Putative function

LCK

LS

FDR

log2 FC

c93355-c0 c86692-c0 c93726-c0 c80600-c0 c72555-c0 c87176-c0 c98345-c0 c101418-c0 c97835-c0 c55086-c0 c42289-c0 c97008-c0 c100740-c14 c42268-c0 c97575-c0 c88141-c0 c95581-c0 c104121-c0 c81329-c0 c55022-c0 c82026-c0

Glycosyl hydrolase family 14, maltose biosynthetic and starch catabolic process Beta-amylase 3 Kua-ubiquitin conjugating enzyme hybrid localisation domain ABC transporter G family member 22, Probable anion transporter 6, carbohydrate transport and metabolism; Major Facilitator Superfamily Chlorophyll A-B binding protein, early light-induced protein 1 Microtubule-based process, cytoskeleton dynein light chain type1 Protein phosphatase 2C, secondary metabolites biosynthesis, transport and catabolism phospho protein phosphatase activity Cytokinin dehydrogenase 7, energy production and conversion, FAD and cytokinin binding Sugar transporter ERD6-like 16 Unknown, hypothetical protein [Prunus persica] Lipocalin/cytosolic fatty-acid binding protein family, cell wall/membrane/envelope biogenesis, Lipocalin-like domain NADPH–cytochrome P450 reductase 2 Unknown, Remorin, C-terminal region, uncharacterized protein LOC103339377 [Prunus mume] Unknown, uncharacterized protein LOC103340081 [Prunus mume] Glycosyl hydrolase family 14, beta-amylase 1, chloroplastic [Prunus mume] bZIP transcription factor, Basic region leucine zipper,Transcription factor HY5 AARF domain-containing protein kinase At1g79600, ABC1 family U-box domain-containing protein 9 Glycosyl hydrolases family 16, hydrolase activity, hydrolyzing O-glycosyl compounds Chlorophyll a-b binding protein 13, metal ion binding, chloroplastic (Precursor) Plant invertase/pectin methylesterase inhibitor Pectinesterase 6 (Precursor) hydrolase activity, acting on ester bonds

28.1 4.5 41.6 19.6 211.2 34.1 33.2 11.0 0.9 363.0 127.7 50.3 107.9 59.9 54.2 10.9 26.0 63.7 24.9 550.6 27.7

342.0 83.4 139.9 50.8 1340.1 261.0 115.5 25.7 24.4 1410.0 507.4 123.7 246.6 279.6 160.3 65.1 120.5 155.1 0.9 169.0 1.1

0.000 0.000 0.000 0.000 0.000 0.000 0.001 0.004 0.000 0.000 0.001 0.002 0.008 0.000 0.003 0.002 0.000 0.004 0.000 0.000 0.000

3.4 4.1 1.7 1.3 2.6 2.8 1.7 1.1 4.6 1.9 1.4 1.2 1.1 2.5 1.3 2.3 1.8 1.1 −4.9 −1.8 −4.7

Gene ID

Putative function

RCK

RS

FDR

log2 FC

c94316-c0 c78935-c0 c98437-c0 c96856-c0 c101066-c0 c87495-c0 c55086-c0 c96698-c0 c55290-c0 c78737-c0 c95058-c0 c85547-c0 c54255-c0 c85700-c0 c100632-c0 c106228-c0

Heat shock protein 9/12 FR47-like protein, N-acetyltransferase activity, acetyltransferase (GNAT) family, Probable protein phosphatase 2C, phosphoprotein phosphatase activity CCAAT-binding transcription factor (CBF-B/NF-YA) subunit B Protein phosphatase 2C HSF-type DNA-binding, Heat stress transcription factor C-1 equence-specific DNA binding Unknown, hypothetical protein PRUPE_ppa014020 mg [Prunus persica] Aspartic proteinase PCS1 (Precursor) Eukaryotic aspartyl protease Zinc finger CCCH domain-containing protein 49 Unknown, hypothetical protein PRUPE_ppa011611 mg [Prunus persica] MYB, myb-like protein × [Prunus mume] Unknown, Wound-induced protein, uncharacterized protein LOC103329513 [Prunus mume] Zinc finger CCCH domain-containing protein 20 Transcription factor MYB39, transcription repressor MYB6-like [Prunus mume] NADH(P)-binding, NmrA-like family, short chain dehydrogenase Ethylene-responsive transcription factor 13-like, AP2 domain

0.1 0.6 3.6 27.0 7.9 7.4 202.4 37.9 80.8 35.1 0.7 20.7 49.1 4.1 154.8 56.6

36.4 5.2 71.7 86.1 106.2 47.5 1113.3 140.5 331.1 113.6 19.5 137.6 189.2 21.3 8.5 0.5

0.002 0.006 0.006 0.003 0.000 0.000 0.000 0.001 0.000 0.004 0.000 0.000 0.000 0.003 0.000 0.000

7.0 2.9 4.2 1.5 3.6 2.5 2.4 1.8 2.0 1.6 4.9 2.5 1.8 2.2 −4.4 −7.2

Note: FDR(false discovery rate) < 0.01, RPKM (Reads per Kilobase per Million) of LCK,LS,RCK and RS was mean values of three duplicate samples.

Fig. 5. Overview of deductive drought stressin P.mahaleb.

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