Digital gene expression analysis based on integrated de novo transcriptome assembly of sweet potato [Ipomoea batatas (L.) Lam].

• Main Authors: Xiang Tao, Ying-Hong Gu, Hai-Yan Wang, Wen Zheng, Xiao Li, Chuan-Wu Zhao, Yi-Zheng Zhang
• Format: Article
• Language: English
• Published: Public Library of Science (PLoS) 2012-01-01
• Series: PLoS ONE
• Online Access: http://europepmc.org/articles/PMC3338685?pdf=render

BACKGROUND: Sweet potato (Ipomoea batatas L. [Lam.]) ranks among the top six most important food crops in the world. It is widely grown throughout the world with high and stable yield, strong adaptability, rich nutrient content, and multiple uses. However, little is known about the molecular biology of this important non-model organism due to lack of genomic resources. Hence, studies based on high-throughput sequencing technologies are needed to get a comprehensive and integrated genomic resource and better understanding of gene expression patterns in different tissues and at various developmental stages. METHODOLOGY/PRINCIPAL FINDINGS: Illumina paired-end (PE) RNA-Sequencing was performed, and generated 48.7 million of 75 bp PE reads. These reads were de novo assembled into 128,052 transcripts (≥ 100 bp), which correspond to 41.1 million base pairs, by using a combined assembly strategy. Transcripts were annotated by Blast2GO and 51,763 transcripts got BLASTX hits, in which 39,677 transcripts have GO terms and 14,117 have ECs that are associated with 147 KEGG pathways. Furthermore, transcriptome differences of seven tissues were analyzed by using Illumina digital gene expression (DGE) tag profiling and numerous differentially and specifically expressed transcripts were identified. Moreover, the expression characteristics of genes involved in viral genomes, starch metabolism and potential stress tolerance and insect resistance were also identified. CONCLUSIONS/SIGNIFICANCE: The combined de novo transcriptome assembly strategy can be applied to other organisms whose reference genomes are not available. The data provided here represent the most comprehensive and integrated genomic resources for cloning and identifying genes of interest in sweet potato. Characterization of sweet potato transcriptome provides an effective tool for better understanding the molecular mechanisms of cellular processes including development of leaves and storage roots, tissue-specific gene expression, potential biotic and abiotic stress response in sweet potato.