BACKGROUND: Comprehensive annotation and quantification of transcriptomes are 
outstanding problems in functional genomics. While high throughput mRNA 
sequencing (RNA-Seq) has emerged as a powerful tool for addressing these 
problems, its success is dependent upon the availability and quality of 
reference genome sequences, thus limiting the organisms to which it can be 
applied.
RESULTS: Here, we describe Rnnotator, an automated software pipeline that 
generates transcript models by de novo assembly of RNA-Seq data without the need 
for a reference genome. We have applied the Rnnotator assembly pipeline to two 
yeast transcriptomes and compared the results to the reference gene catalogs of 
these organisms. The contigs produced by Rnnotator are highly accurate (95%) and 
reconstruct full-length genes for the majority of the existing gene models 
(54.3%). Furthermore, our analyses revealed many novel transcribed regions that 
are absent from well annotated genomes, suggesting Rnnotator serves as a 
complementary approach to analysis based on a reference genome for comprehensive 
transcriptomics.
CONCLUSIONS: These results demonstrate that the Rnnotator pipeline is able to 
reconstruct full-length transcripts in the absence of a complete reference 
genome.