A survey of the complex transcriptome from the highly polyploid sugarcane genome using full-length isoform sequencing and de novo assembly from short read sequencing

Abstract

Background: Despite the economic importance of sugarcane in sugar and bioenergy production, there is not yet a reference genome available. Most of the sugarcane transcriptomic studies have been based on Saccharum officinarum gene indices (SoGI), expressed sequence tags (ESTs) and de novo assembled transcript contigs from short-reads; hence knowledge of the sugarcane transcriptome is limited in relation to transcript length and number of transcript isoforms. Results: The sugarcane transcriptome was sequenced using PacBio isoform sequencing (Iso-Seq) of a pooled RNA sample derived from leaf, internode and root tissues, of different developmental stages, from 22 varieties, to explore the potential for capturing full-length transcript isoforms. A total of 107,598 unique transcript isoforms were obtained, representing about 71% of the total number of predicted sugarcane genes. The majority of this dataset (92%) matched the plant protein database, while just over 2% was novel transcripts, and over 2% was putative long non-coding RNAs. About 56% and 23% of total sequences were annotated against the gene ontology and KEGG pathway databases, respectively. Comparison with de novo contigs from Illumina RNA-Sequencing (RNA-Seq) of the internode samples from the same experiment and public databases showed that the Iso-Seq method recovered more full-length transcript isoforms, had a higher N50 and average length of largest 1,000 proteins; whereas a greater representation of the gene content and RNA diversity was captured in RNA-Seq. Only 62% of PacBio transcript isoforms matched 67% of de novo contigs, while the non-matched proportions were attributed to the inclusion of leaf/root tissues and the normalization in PacBio, and the representation of more gene content and RNA classes in the de novo assembly, respectively. About 69% of PacBio transcript isoforms and 41% of de novo contigs aligned with the sorghum genome, indicating the high conservation of orthologs in the genic regions of the two genomes. Conclusions: The transcriptome dataset should contribute to improved sugarcane gene models and sugarcane protein predictions; and will serve as a reference database for analysis of transcript expression in sugarcane.