Abstract

Raphanus sativus is an important Brassicaceae plant and also an edible vegetable with great economic value. However, currently there is not enough transcriptome information of R. sativus tissues, which impedes further functional genomics research on R. sativus. In this study, RNA-seq technology was employed to characterize the transcriptome of leaf tissues. Approximately 70 million clean pair-end reads were obtained and used for de novo assembly by Trinity program, which generated 68,086 unigenes with an average length of 576 bp. All the unigenes were annotated against GO and KEGG databases. In the meanwhile, we merged leaf sequencing data with existing root sequencing data and obtained better de novo assembly of R. sativus using Oases program. Accordingly, potential simple sequence repeats (SSRs), transcription factors (TFs) and enzyme codes were identified in R. sativus. Additionally, we detected a total of 3563 significantly differentially expressed genes (DEGs, P = 0.05) and tissue-specific biological processes between leaf and root tissues. Furthermore, a TFs-based regulation network was constructed using Cytoscape software. Taken together, these results not only provide a comprehensive genomic resource of R. sativus but also shed light on functional genomic and proteomic research on R. sativus in the future.

Highlights

  • As an important Brassicaceae plant with great economic value, Raphanus sativus was widely cultivated throughout the world

  • We further mapped the clean reads to Brassica rapa genome and found that the clean reads were mainly distributed in the coding sequence region (Figure 1A), which indicated that transcriptome sequencing had good quality

  • All the clean reads were de novo assembled by Trinity programs (Grabherr et al, 2011), which generated a total of 68,086 unigenes with an average length of 576 bp and an N50 of 773 bp (Figure 1B)

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Summary

Introduction

As an important Brassicaceae plant with great economic value, Raphanus sativus was widely cultivated throughout the world. With the development of next-generation sequencing technology, genetic information of R. sativus was gradually revealed in the recent years (Wang et al, 2013a; Xu et al, 2013; Zhang et al, 2013). The transcriptome profiles of leaf tissue of R. sativus were analyzed by RNA-seq technology in our previous study. Only 22 million clean reads were used and the unigenes generated in this study only represents a small proportion of R. sativus transcriptome because the sequencing coverage was not deep enough (Zhang et al, 2013). There is an urgent need to analyze more transcriptome data of R. sativus tissues, which will facilitate their potential use as general reference for other related R. sativus studies

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