De novo RNA-Seq analysis of the oleauginous microalgae Ankistrodesmus sp. UCP0001: Gene identification and metabolic pathways reconstruction for the biosynthesis of fatty acids and triacylglycerols

Abstract

Microalgae have great potential as feedstock to produce next-generation biofuels. The scarceness of genomic level information, however, prevents the rational de novo microalgae strain design. In this research, we describe the next-generation sequencing, de novo assembly, and functional annotation of the transcriptome of Ankistrodesmus sp. UCP0001. In total 48,867,830 high-quality sequence reads were de novo assembled into 38,414 unigenes (mean length = 508 bp, N50 = 1038 bp). Seventy-two percent of unigenes presented mapping information. Based on the KEGG pathway assignment, the fatty acids and the triacylglycerol biosynthesis pathways were reconstructed. Our results demonstrate that the synergy among high-throughput sequencing technologies and appropriate bioinformatics tools provides a fast, low-cost, and effective approach to generate invaluable functional genomic information in non-model microalgae species (e.g., Ankistrodesmus sp.). With the de novo assembled and annotated transcriptome we have successfully identified genes encoding enzymes and reconstructed metabolic pathways for the biosynthesis of fatty acids and triacylglycerols in this microalgae species. This genetic information could be used for the de novo microalgae strain design with desirable characteristics to produce biodiesel and capabilities for the biosynthesis of others valuable bioactive compounds of interest to the pharmacological, food, and cosmetic industries.