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Background  For many years, increasing demands for fossil fuels have met with limited supply. As a potential substitute and renewable source of biofuel feedstock, microalgae have received significant attention. However, few of the current algal species produce high lipid yields to be commercially viable. To discover more high yielding strains, next-generation sequencing technology is used to elucidate lipid synthetic pathways and energy metabolism involved in lipid yield. When subjected to manipulation by genetic and metabolic engineering, enhancement of such pathways may further enhance lipid yield.    Results  In this study, transcriptome profiling of a random insertional mutant with enhanced lipid production generated from a non-model marine microalga  Dunaliella tertiolecta  is presented. D9 mutant has a lipid yield that is 2- to 4-fold higher than that of wild type. Using novel Bag2D-workflow scripts developed and reported here, the non-redundant transcripts from  de novo  assembly were annotated based on the best hits in five model microalgae, namely  Chlamydomonas reinhardtii ,  Coccomyxa subellipsoidea  C-169,  Ostreococcus lucimarinus ,  Volvox carteri ,  Chlorella variabilis  NC64A and a high plant species  Arabidopsis thaliana . The assembled contigs (~181 Mb) includes 481,381 contigs, covering 10,185 genes. Pathway analysis showed that a pathway from inositol phosphate metabolism to fatty acid biosynthesis is the most significantly correlated with higher lipid yield in this mutant.    Conclusions  Herein, we described a pipeline to analyze RNA-Seq data without pre-existing transcriptomic information. The draft transcriptome of  D. tertiolecta  was constructed and annotated, which offered useful information for characterizing high lipid-producing mutants.  D. tertiolecta  mutant was generated with an enhanced photosynthetic efficiency and lipid production. RNA-Seq data of the mutant and wild type were compared, providing biological insights into the expression patterns of contigs associated with energy metabolism and carbon flow pathways. Comparison of  D. tertiolecta  genes with homologs of five other green algae and a model high plant species can facilitate the annotation of  D. tertiolecta  and lead to a more complete annotation of its sequence database, thus laying the groundwork for optimization of lipid production pathways based on genetic manipulation.    Electronic supplementary material  The online version of this article (doi:10.1186/s13068-015-0382-0) contains supplementary material, which is available to authorized users.

biotechnology for biofuels

RNA-Seq transcriptomic analysis with Bag2D software identifies key pathways enhancing lipid yield in a high lipid-producing mutant of the non-model green alga Dunaliella tertiolecta