De novo transcriptome sequencing of radish (Raphanus sativusL.) and analysis of major genes involved in glucosinolate metabolism

Abstract

Abstract Background Radish (Raphanus sativus L.), is an important root vegetable crop worldwide. Glucosinolates in the fleshy taproot significantly affect the flavor and nutritional quality of radish. However, little is known about the molecular mechanisms underlying glucosinolate metabolism in radish taproots. The limited availability of radish genomic information has greatly hindered functional genomic analysis and molecular breeding in radish. Results In this study, a high-throughput, large-scale RNA sequencing technology was employed to characterize the de novo transcriptome of radish roots at different stages of development. Approximately 66.11 million paired-end reads representing 73,084 unigenes with a N50 length of 1,095 bp, and a total length of 55.73 Mb were obtained. Comparison with the publicly available protein database indicates that a total of 67,305 (about 92.09% of the assembled unigenes) unigenes exhibit similarity (e –value ≤ 1.0e-5) to known proteins. The functional annotation and classification including Gene Ontology (GO), Clusters of Orthologous Group (COG) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis revealed that the main activated genes in radish taproots are predominately involved in basic physiological and metabolic processes, biosynthesis of secondary metabolite pathways, signal transduction mechanisms and other cellular components and molecular function related terms. The majority of the genes encoding enzymes involved in glucosinolate (GS) metabolism and regulation pathways were identified in the unigene dataset by targeted searches of their annotations. A number of candidate radish genes in the glucosinolate metabolism related pathways were also discovered, from which, eight genes were validated by T-A cloning and sequencing while four were validated by quantitative RT-PCR expression profiling. Conclusions The ensuing transcriptome dataset provides a comprehensive sequence resource for molecular genetics research in radish. It will serve as an important public information platform to further understanding of the molecular mechanisms involved in biosynthesis and metabolism of the related nutritional and flavor components during taproot formation in radish.