Plant Physiology and Biochemistry 156 (2020) 314–322
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Analysis of the Prunellae Spica transcriptome under salt stress Zixiu Liu a, b, c, d, Yujiao Hua a, b, c, Shengnan Wang a, b, c, Xunhong Liu a, b, c, *, Lisi Zou a, b, c, Cuihua Chen a, b, c, Hui Zhao a, b, c, Ying Yan a, b, c a
College of Pharmacy, Nanjing University of Chinese Medicine, Nanjing, China Collaborative Innovation Center of Chinese Medicinal Resources Industrialization, Nanjing, China c National and Local Collaborative Engineering Center of Chinese Medicinal Resources Industrialization and Formulae Innovative Medicine, Nanjing, China d Department of Pharmacy, Air Force Hospital of Eastern Theater Command, Nanjing, China b
A R T I C L E I N F O
A B S T R A C T
Keywords: Prunellae spica Transcriptome RNA-Seq Salt stress
Prunella vulgaris L. is a moderately salt tolerant plant commonly found in China and Europe, whose spica (Prunellae Spica) has been used as a traditional medicine. The scant transcriptomic and genomic resources of Prunellae Spica have greatly hindered further exploration of the underlying salt tolerance mechanism of this species. To clarify the genetic basis of its salt tolerance, high-throughput sequencing of mRNAs was employed for de novo transcriptome assembly differential expression analysis of Prunellae Spica under salt stress. 118,664 unigenes were obtained by assembling pooled reads from all libraries with 68,119 sequences annotated. A total of 3857 unigenes were differentially expressed under low, medium and high salt stress, including 2456 upregulated and 1401 down-regulated DEGs, respectively. Gene ontology analysis revealed that salt stressrelated categories involving ‘catalytic activity’, ‘binding’, ‘metabolic process’ and ‘cellular process’ were high ly enriched. KEGG pathway annotation showed that the DEGs from different salt stress treatment groups were mainly enriched in the pathways of translation, signal transduction, carbohydrate metabolism, energy meta bolism, lipid metabolism and amino acid metabolism, accounting for over 60% of all DEGs. Finally, it showed that the results of quantitative real-time polymerase chain reaction (qRT-PCR) analysis for 10 unigenes that randomly selected were significantly consistent with RNA-seq data, which further assisted in the selection of salt stress-responsive candidate genes in Prunellae Spica. This study represents a significant step forward in under standing the salt tolerance mechanism of Prunellae Spica, and also provides a significant transcriptomic resource for future work.
1. Introduction Prunellae Spica (Xia Ku Cao) is an annual to perennial herb that originates from spica of Prunella vulgaris L, which has been widely used in traditional medicine and food industry in the northeastern regions of Asia, including China, Korea and Japan. As a well-known traditional Chinese medicine, Prunellae Spica has been employed to reduce liver inflammation, improve eyesight, treat mammary gland hyperplasia and reduce swelling (Li et al., 2015). Modern pharmacological and clinical studies have demonstrated that it has anti-inflammatory, antimicrobial, antioxidant, antiviral and immunomodulatory effects. Additionally, it has been used to alleviate hypertension, sore throat, fever, thyroiditis and wounds (Aloglu et al., 2016; Bai et al., 2016; Chiu et al., 2004; Han et al., 2009; Harikrishnan et al., 2010; Li et al., 2015; Meng et al., 2014; Raafat et al., 2016). In addition to its traditional medicinal uses, it has
also been used extensively as an additive for beverages and soups in southeastern China. As the wild abundance of Prunellae Spica has declined and the demand for it has risen, it has become imperative to artificially cultivate Prunellae Spica (Fercha et al., 2014). When Pru nellae Spica is cultivated in the field, its yield and quality are affected by several different types of abiotic stresses. Particularly, salt stress is one of the most significant environmental factors limiting the quality of Pru nellae Spica. However, planting Prunellae Spica in salinized land can effectively attenuate the imbalance between commercial supply and demand for this species (Chen et al., 2013). Salt stress significantly limits plant growth, development, produc tivity and quality worldwide. It is estimated that over 6% of the world’s total land area and nearly 20% of irrigated land are adversely affected by salt stress, thereby limiting the yield and geographical distribution of cultivated crops (Luo et al., 2017). High salt stress causes significant
* Corresponding author. College of Pharmacy, Nanjing University of Chinese Medicine, Xianlin Road, Nanjing, 210023, China. E-mail addresses: [email protected]
, [email protected]
(X. Liu). https://doi.org/10.1016/j.plaphy.2020.09.023 Received 23 March 2020; Accepted 17 September 2020 Available online 29 September 2020 0981-9428/© 2020 Elsevier Masson SAS. All rights reserved.
Z. Liu et al.
Plant Physiology and Biochemistry 156 (2020) 314–322
mg g− 1 fresh mass (FM). The soluble protein content was determined using UV–Vis spectro photometer (DENOVIX DS-11, Wilmington, DE, USA). The Prunellae Spica was homogenized and extracted with 8 mL of PBS (phosphate buffer saline, 0.1 mM Na2HPO4 and NaH2PO4, pH 7.4). After centrifu gation, 1 μL of the supernatant was assayed. The proline content was quantified via the colorimetric method, according to a previous report (Chen et al., 2018). The kit was purchased from Jiancheng (Nanjing, China). The soluble sugars, MDA, SOD, POD and ascorbic acid were extrac ted from the whole Prunellae Spica and detected using their corre sponding kits (Jiancheng, Nanjing). Absorbance was read at 630 nm, with glucose used as the standard.
negative effects on plants, including oxidative stress, ion toxicity, nutritional disorders, water stress, alterations of metabolic processes and even genotoxicity (Yu et al., 2016). The perception of salt stress takes place through various sensors, which then initiate a cascade of transcriptional changes in order to produce, protective proteins and metabolites (Gengmao et al., 2015). Significant research has been con ducted around gene expression changes that occur in response to salt stress (Guo et al., 2015; Kurt-Kizildogan et al., 2017; Skorupa et al., 2016). Salt tolerance genes in plants are related to many pathways, such as signal transduction, secondary metabolism, reactive oxygen species and regulation of transcription (Chakraborty et al., 2016; Coban and Baydar, 2016; Huang et al., 2012; Shen et al., 2017). Although the chemical components of Prunellae Spica have been examined in detail, little is known about the molecular mechanism underlying its salt tolerance (Cheung and Zhang, 2008; Du et al., 2016; Wang et al., 2016b; Zhang et al., 2016). In recent years RNA-seq has increasingly been used to both assemble novel transcripts and quantify their expression. Non-model organisms are preferentially studied by de novo transcriptome assembly which is cheaper and easier than sequencing an entire genome. The tran scriptomes of these organisms can reveal novel proteins and they often contain isoforms that are implicated in unique biological phenomena (Hua et al., 2016). In this study, the transcriptome of Prunellae Spica under salt stress conditions was constructed and quantified. Illumina RNA-seq analysis was performed for Prunellae Spica treated with NaCl at different concentrations (0, 50, 150, 200 mM). A total of 172, 580, 236 high-quality paired-end reads were generated and assembled into 118,664 unigenes. These genes were then annotated by matching against common sequence databases, including Uniport, Eggnog, Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), Pfam, SignalP and TMhmm. In order to explore possible salt stress tolerance mechanisms, a subset significantly differentially expressed unigenes were selected for further analysis based on their putative gene functions, metabolic pathways and expression profiles in Prunellae Spica. These results shed new light on the transcriptomic dynamics of Prunellae Spica in response to salt stress. In addition, this information may be beneficial to efforts aimed at identifying suitable genes for biotechnological manipulation to improve the salt tolerance of Prunellae Spica.
2.3. RNA extraction, cDNA library construction, illumina sequencing and bioinformatic analysis Total RNA was extracted from all four sample groups using the RNAprep Qubit RNA kit and analyzed via an Agilent Technologies 2100 Bioanalyzer (Santa Clara, CA, USA), according to the manufacture’s protocol. A total RNA sample (0.1–1 μg) with RNA integrity number (RIN) of ≥7 and 28/18 S ratio of ≥1.5 was utilized for downstream analysis. After RNA extraction, poly(A) mRNA was purified using Oligod (dT) beads and then fragmented. First-strand cDNA was synthesized using a reverse transcriptase with random primers, and second-strand cDNA was synthesized using DNA polymerase I. Afterwards, the resulting cDNA fragments were subjected to end repair, addition of a single ‘A’ base and ligation with adapters. Finally, suitable fragments were selected and amplified through PCR to create a library for sequencing. Before analyzing differential gene expression, the edgeR package was used to adjust the read counts of each sequence library to one scaling normalized factor. Differential expression analysis between control samples (0 mM) and salt stress treatments (50, 100, 150 mM) was performed using the DEGseq R package. Based on the edgeR func tion of bioconductor, we screened differentially expressed genes (DEGs) using the following thresholds: FDR ≤ 0.01 and |log2 FC| ≥ 1 (FDR is the false discovery rate, log2FC means log2 [fold change] up/down regulation). Then, the identified DEGs were subjected to GO and KEGG pathway functional analysis, in which P-values ≤ 0.05 were considered to be significantly enriched.
2. Materials and methods
2.4. De novo transcriptome assembly and functional annotation
2.1. Plant materials and salt stress application
Illumina HiSeq™ 2500 was used to sequence the libraries. The raw data were filtered and low-quality sequences were removed by ngsQCToolkit-2.3.32 to obtain clean reads. If the content of N in a read exceeded 5%, the whole paired-end read was removed. If the content of low-quality bases (quality < 20) surpassed 30%, the whole read pair was also removed. If one read had adaptor sequence, it was removed together with the downstream sequence. High-quality reads were then assembled with Trinity software to construct an unigene library. For functional annotation, all unigene transcript sequences were compared to currently available databases including Uniport, Eggnog, GO (http://wegolgenomics.org.cn/cgi-bin/wego/index.pl), Pfam, TMhmm, Clusters of Orthologous Groups (COGs) and KEGG (http://www.genome .jp/kegg/kegg2.html), using BLASTx analysis with a cut-off E-value of 10− 5.
Prunellae Spica seedlings were collected in 2015 from Chuzhou City, Anhui Province, China. The seedlings were sown in plastic pots filled with garden soil and grown in a greenhouse at 20 ± 2 ◦ C, 50 ± 5% relative humidity, and a 16/8 h light/dark cycle until mature leaves fully developed. For salt treatments, NaCl solution was gradually added to the soil until the salt concentration reached either 0 (C), 50 (S_1), 100 (S_2) or 150 (S_3) mM. The experiment was arranged as a factorial setup based on a completely randomized design with five replicates. The seedlings were exposed to salt stress by adding NaCl to the soil when they were about five months old on February 26th and harvested on June 14th. 2.2. Physiological experiment Physiological and biochemical parameters including photosynthetic pigments, protein content, proline (PRO), total soluble sugars, malon diadehyde (MDA), superoxide dismutases (SOD), peroxidases (POD), catalase (CAT) and ascorbic acid were measured in seedlings of control and salt stressed plants at the anthesis stage, as previously reported (Chen et al., 2018). Chlorophyll a, b and carotenoid concentrations of the four conditions were assayed using a spectrophotometric method after homogenization with ethanol. The absorbance of the supernatant was measured at the OD665, OD649 and OD470 nm and converted to
2.5. Verification by quantitative real-time polymerase chain reaction (qRT-PCR) To validate the accuracy of the differential expression tests, 10 salt stress responsive transcripts with significant differential expression were randomly selected for qRT-PCR verification. Total RNA was isolated from the same samples as before using Trizol reagent (Invitrogen, USA). Reverse transcription of total RNA was carried out by the FastQuant RT 315
Z. Liu et al.
Plant Physiology and Biochemistry 156 (2020) 314–322
kit. First-strand cDNA was synthesized from 1 μg of total RNA using a FastQuant RT kit, following the manufacturer’s instructions. qRT-PCR was performed on a QuantStudio™ 7 Flex real-time PCR system using Power SYBR Green PCR Master Mix (Applied Biosystems, USA), ac cording to the manufacturer’s instructions. The thermal program for qRT-PCR was 10 min at 95 ◦ C, followed by 40 cycles of 15 s at 95 ◦ C and 1 min at 60 ◦ C. The relative expression of each target gene was analyzed by the 2-ΔΔCt method (Livak and Schmittgen, 2001).
43, 829, 428, 48, 203, 144, 43, 062, 024, and 45, 614, 440 paired-end raw reads with Q30 percentages (percentage of sequences with