Transcriptome Analysis of Yellow Horn (Xanthoceras sorbifolia Bunge): A Potential Oil-Rich Seed Tree for Biodiesel in China

BACKGROUND: Yellow horn (Xanthoceras sorbifolia Bunge) is an oil-rich seed shrub that grows well in cold, barren environments and has great potential for biodiesel production in China. However, the limited genetic data means that little information about the key genes involved in oil biosynthesis is available, which limits further improvement of this species. In this study, we describe sequencing and de novo transcriptome assembly to produce the first comprehensive and integrated genomic resource for yellow horn and identify the pathways and key genes related to oil accumulation. In addition, potential molecular markers were identified and compiled. METHODOLOGY/PRINCIPAL FINDINGS: Total RNA was isolated from 30 plants from two regions, including buds, leaves, flowers and seeds. Equal quantities of RNA from these tissues were pooled to construct a cDNA library for 454 pyrosequencing. A total of 1,147,624 high-quality reads with total and average lengths of 530.6 Mb and 462 bp, respectively, were generated. These reads were assembled into 51,867 unigenes, corresponding to a total of 36.1 Mb with a mean length, N50 and median of 696, 928 and 570 bp, respectively. Of the unigenes, 17,541 (33.82%) were unmatched in any public protein databases. We identified 281 unigenes that may be involved in de novo fatty acid (FA) and triacylglycerol (TAG) biosynthesis and metabolism. Furthermore, 6,707 SSRs, 16,925 SNPs and 6,201 InDels with high-confidence were also identified in this study. CONCLUSIONS: This transcriptome represents a new functional genomics resource and a foundation for further studies on the metabolic engineering of yellow horn to increase oil content and modify oil composition. The potential molecular markers identified in this study provide a basis for polymorphism analysis of Xanthoceras, and even Sapindaceae; they will also accelerate the process of breeding new varieties with better agronomic characteristics.