Commentary: Comparative Transcriptome Analysis of Raphanus sativus Tissues

A Commentary on Sequencing, de novo assembly and comparative analysis of Raphanus sativus transcriptome Obtaining sequence information for a plant species of interest greatly facilitates functional genomic research. However, many plant species have not been sequenced due to the complexities of their genomes and the high cost of sequencing. Therefore, the transcriptomes of several plants were sequenced using next-generation sequencing technology. RNA-seq technology is an important high-throughput tool for both gene mapping and the transcriptome analysis of non-model organisms lacking genome information Additionally, RNA-seq data can help connect the genome to gene function (Adams, 2008) and have tremendously expanded the volume of transcriptome information available for non-model plants. The uniformly processed and matched nature of the transcriptome data also facilitates their integration with upstream factor-binding and chromatin-modification signals (Gerstein et al., 2014). The transcriptome sequencing analyses of single tissues from Raphanus sativus were recently reported because it is an important Brassicaceae plant with both economic value and medicinal properties (Wang et al., 2013; Zhang et al., 2013). These studies have advanced functional genomic investigations of R. sativus. However, routine analysis and annotation methods have impeded our understanding of the functional genomics and medicinal potential of R. sativus. The traditional analysis of transcriptome data focuses on evaluating the expression changes of single genes. The accumulating volume of transcriptome data requires the development of new methods and tools for data integration. The network theory and similar methods have been widely used to analyze high-throughput data in the field of systems biology (Ashburner, 2000; Lee et al., 2010; Kleessen et al., 2013). Cytoscape is an open source software used for visualizing molecular interaction networks and biological pathways. The software can also integrate these networks with annotation and gene expression data (Shannon et al., 2003; Ma et al., 2014). Using R. sativus as a model, Wu et al. (2015) combined the leaf sequencing data with the root sequencing data and obtained the better transcriptome assembly of R. sativus. For example, the authors obtained 68,086 unigenes with an average length of 576 bp by Trinity program, which represents a rich genome resource of R. sativus. Moreover, a total of 31,875 potential simple sequence repeats (SSRs) were identified in this article. SSRs are repeating DNA sequences of 2–6 bp and widely used in molecular marker identification, high-throughput genome mapping, and the analysis of species diversity. Thus, the identification of multiple SSRs in