Comparative Characterization of the Leaf Tissue of Physalis Alkekengi and Physalis Peruviana Using RNA-Seq and Metabolite Profiling
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fpls-07-01883 December 17, 2016 Time: 17:38 # 1 ORIGINAL RESEARCH published: 20 December 2016 doi: 10.3389/fpls.2016.01883 Comparative Characterization of the Leaf Tissue of Physalis alkekengi and Physalis peruviana Using RNA-seq and Metabolite Profiling Atsushi Fukushima1*, Michimi Nakamura2, Hideyuki Suzuki3, Mami Yamazaki2, Eva Knoch1, Tetsuya Mori1, Naoyuki Umemoto1, Masaki Morita4, Go Hirai4,5, Mikiko Sodeoka4,5 and Kazuki Saito1,2* 1 RIKEN Center for Sustainable Resource Science, Yokohama, Japan, 2 Graduate School of Pharmaceutical Sciences, Chiba University, Chiba, Japan, 3 Department of Biotechnology Research, Kazusa DNA Research Institute, Chiba, Japan, 4 Synthetic Organic Chemistry Laboratory, RIKEN, Saitama, Japan, 5 RIKEN Center for Sustainable Resource Science, Saitama, Japan Edited by: Xiaowu Wang, Chinese Academy of Agricultural The genus Physalis in the Solanaceae family contains several species of benefit to Sciences, China humans. Examples include P. alkekengi (Chinese-lantern plant, hôzuki in Japanese) Reviewed by: Erli Pang, used for medicinal and for decorative purposes, and P. peruviana, also known as Beijing Normal University, China Cape gooseberry, which bears an edible, vitamin-rich fruit. Members of the Physalis Zhonghua Zhang, genus are a valuable resource for phytochemicals needed for the development of Chinese Academy of Agricultural Sciences, China medicines and functional foods. To fully utilize the potential of these phytochemicals we *Correspondence: need to understand their biosynthesis, and for this we need genomic data, especially Atsushi Fukushima comprehensive transcriptome datasets for gene discovery. We report the de novo [email protected] Kazuki Saito assembly of the transcriptome from leaves of P. alkekengi and P. peruviana using [email protected] Illumina RNA-seq technologies. We identified 75,221 unigenes in P. alkekengi and 54,513 in P. peruviana. All unigenes were annotated with gene ontology (GO), Enzyme Specialty section: This article was submitted to Commission (EC) numbers, and pathway information from the Kyoto Encyclopedia of Plant Genetics and Genomics, Genes and Genomes (KEGG). We classified unigenes encoding enzyme candidates a section of the journal putatively involved in the secondary metabolism and identified more than one unigenes Frontiers in Plant Science for each step in terpenoid backbone- and steroid biosynthesis in P. alkekengi and Received: 13 July 2016 Accepted: 29 November 2016 P. peruviana. To measure the variability of the withanolides including physalins and Published: 20 December 2016 provide insights into their chemical diversity in Physalis, we also analyzed the metabolite Citation: content in leaves of P. alkekengi and P. peruviana at five different developmental Fukushima A, Nakamura M, Suzuki H, Yamazaki M, Knoch E, stages by liquid chromatography-mass spectrometry. We discuss that comprehensive Mori T, Umemoto N, Morita M, transcriptome approaches within a family can yield a clue for gene discovery in Physalis Hirai G, Sodeoka M and Saito K and provide insights into their complex chemical diversity. The transcriptome information (2016) Comparative Characterization of the Leaf Tissue of Physalis we submit here will serve as an important public resource for further studies of the alkekengi and Physalis peruviana specialized metabolism of Physalis species. Using RNA-seq and Metabolite Profiling. Front. Plant Sci. 7:1883. Keywords: Physalis, de novo transcriptome assembly, deep sequencing, marker development, secondary doi: 10.3389/fpls.2016.01883 metabolism, physalin, withanolide Frontiers in Plant Science | www.frontiersin.org 1 December 2016 | Volume 7 | Article 1883 fpls-07-01883 December 17, 2016 Time: 17:38 # 2 Fukushima et al. Transcriptome in Two Physalis Species INTRODUCTION of the metabolism including the withanolide biosynthesis pathway in leaves (Figure 1). Here we present a de novo The specialized or secondary metabolism in plants is an assembly transcriptome from the leaves of P. alkekengi and important source for fine chemicals including drugs, dyes, P. peruviana. We employed Illumina RNA-seq techniques and vitamins, and other chemical materials. The genus Physalis, demonstrate that these resources can provide the means for a the largest genera in the Solanoideae subfamily, contains the better understanding of chemical diversity in Physalis species. most economically important genera, e.g., Solanum tuberosum We annotated the assembled unigenes in P. alkekengi and (potato), S. lycopersicum (tomato), and Capsicum annuum (red P. peruviana and classified unigenes encoding enzyme candidates pepper; Martinez, 1998). Some plants in approximately 90 putatively involved in secondary metabolism. Our approaches species have a long history of cultivation. P. alkekengi var. provide a basis for future researches on bio-engineering of franchetii (Chinese-lantern, hôzuki in Japanese) has been used as Physalis plants and they represent a shortcut to gene discovery a medicinal plant and for decorative purposes. P. peruviana, also in these species. known as Cape gooseberry, has an edible fruit that contains many vitamins and antioxidants (Ramadan and Morsel, 2003). Members of the genus Physalis produce bioactive metabolites MATERIALS AND METHODS such as steroidal lactones withanolides (Eich, 2008). P. peruviana can produce withanolides and, P. alkekengi physalins, a different Plant Materials, RNA Isolation, and cDNA subgroup of withanolides. The structures of physalins A Synthesis and B were first determined in 1969 (Matsuura and Kawai, Physalis alkekengi var. franchetii and P. peruviana (Ground 1969; Matsuura et al., 1969) and subsequently more than 30 Cherry or Golden Berry) plants were grown in the experimental physalins were isolated. Studies using spectroscopic methods gardens of the RIKEN Center for Sustainable Resource Science, isolated 3 new- and 7 known steroids including physalins and Wako, Saitama, Japan. They are not an endangered or protected demonstrated that physalin B exhibited the most significant species. The third fresh leaves were collected from healthy cytotoxic activities against HeLa human cervical cells (Kawai plants (Supplementary Image 1). RNA isolation and cDNA et al., 2002; Li et al., 2014). Physalin B or F inhibited NF-kappa synthesis for sequencing were carried out as previously reported B activation (Jacobo-Herrera et al., 2006; Wu et al., 2012) and (Fukushima et al., 2015; Han et al., 2015a,b). We used both right- and left-sided partial structures were proposed to play unreplicated data for one sample per species. a significant role in their mode of action (Ozawa et al., 2013). 4b-Hydroxywithanolide E derived from P. peruviana inhibited Illumina Sequencing the growth of a human non-small lung cancer cell line (Yen et al., For the generation of cDNA libraries we employed an Illumina 2010). HiSeq 2000 sequencer (Illumina Inc., San Diego, CA, USA). High-throughput DNA sequencing with a next-generation We sequenced 100-bp paired-end (PE) reads as described sequencer (NGS) is useful for genome assembly, the detection of (Fukushima et al., 2015; Han et al., 2015a,b). Our short-read data single nucleotide polymorphisms (SNPs) and genetic variations, in FASTQ file format were produced by Casava 1.8 (Illumina, Inc. and for transcriptome characterization (Wang et al., 2009; Garber San Diego, CA, USA). Short reads that did not pass Illumina’s et al., 2011). RNA sequencing (RNA-seq) on NGSs can be used for standard quality filter were eliminated. The process yielded clean both model and non-model plants (Gongora-Castillo and Buell, reads from the mRNA pool isolated from P. alkekengi and 2013; Fukushima and Kusano, 2014; Weber, 2015). Successful P. peruviana, respectively (Table 1). transcriptome studies on non-model plants, e.g., crop plants such as the eggplant (Ramesh et al., 2016), pepper (Gordo et al., 2012) and tobacco (Lei et al., 2014) and medicinal plants, e.g., Data Pre-processing and De novo Withania somnifera (Gupta et al., 2013; Senthil et al., 2015) and Transcriptome Assembly P. peruviana (Garzon-Martinez et al., 2012) from the Solanaceae We performed de novo transcriptome assembly using the Trinity family have been published. Resources for transcriptome data program (Grabherr et al., 2011). We then subjected the assembled from medicinal plants, e.g., the Medicinal Plant Genomics unigenes to read alignment and transcript abundance estimation Resource (MPGR1) and the Medicinal Plants Transcriptomics with Bowtie (Langmead et al., 2009) and RSEM (Li and Dewey, (Medplants2; Gongora-Castillo et al., 2012a,b; Yeo et al., 2013) 2011). To estimate transcript abundance we used the Fragments are available. To take full advantage of the potential of important Per Kilobase of exon per Million mapped fragments (FPKM) phytochemicals we need to elucidate their biosynthesis. For this method. We identified 75,221 unigenes in P. alkekengi and 54,513 we need genomic data, especially comprehensive transcriptome unigenes in P. peruviana. The length and G C C% distribution datasets for gene discovery. of all unigenes are shown in Figures 2A,B. The G C C% and Our main aim of this study is to describe the whole basic statistics were calculated with the custom Ruby/Bioruby transcriptome map of P. alkekengi and P. peruviana leaves script (Goto et al., 2010), “Biostrings” (Pages et al., 2009), and and to inventory the basic information about a wide range the R/Bioconductor package “ShortRead” (Morgan et al., 2009). For quality control we used the