Digital Gene Expression Analysis Based on Integrated De Novo Transcriptome Assembly of Sweet Potato [Ipomoea batatas (L.) Lam.]

Abstract

BackgroundSweet 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 FindingsIllumina 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/SignificanceThe 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.

Isolation and characterization of cDNAs and genomic DNAs encoding ADP-glucose pyrophosphorylase large and small subunits from sweet potato

“…Analysis of annotated transcripts in the sweet potato transcriptome generated and characterized in our previous studies (Tao et al 2012) revealed the presence of AGPase gene family members, including two genes for SSs and four for LSs. Primers specific for the sequences encoding each large and small AGPase subunit were accordingly synthesized and used for full-length cDNA cloning and sequencing.…”

“…In previous studies, we carried out Illumina DGE tag profiling of different sweet potato tissues, including young leaves, mature leaves, stems, fibrous roots, and tuberous roots at two developmental stages (initial and harvestable) (Tao et al 2012). In the present study, we analyzed the expression patterns of six AGPase subunits that were previously uncovered by the DGE tag profiling (Table 2).…”

“…A sweet potato transcriptome database was established from the cultivar Xushu 18 in our previous study (Tao et al 2012). Of 51,763 annotated transcripts (≥100 bp), 6 were annotated as AGPase SSs and LSs with complete open-reading frames.…”

“…Illumina DGE tag profiling of different tissues from sweet potato, including young leaves, mature leaves, stems, fibrous roots, and tuberous roots at different developmental stages, was carried out in our previous studies (Tao et al 2012). Since the number of DGE tags mapping to LSs and SSs may reflect LS and SS expression levels in different tissues and developmental stages, we mapped DGE tags to AGPase LSs and SSs using Bowtie 2.0.…”

Comparative transcriptome to reveal the drought tolerance mechanism in hexaploid <i>Ipomoea trifida</i>

“…Therefore, studying of transcriptome will provide important insights into the critical transcription factors and regulatory enzymes, their expression patterns, and the regulation of transcribed regions in drought stress conditions. Compared with the former methods, RNA-seq technologies are much simpler and more cost-effective, and wildly used in many plant species (Zhang et al, 2014;Robertson et al, 2010) for discovering novel transcripts and comparing gene expression, for instance, Ipomoea batatas (Tao et al, 2012), Ipomoea nil (Wei et al, 2015), Brassica napus (Trick et al, 2009), Zea mays , and Picrorhiza kurrooa (Gahlan et al, 2012).…”