Abstract
BackgroundFor 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.ResultsIn 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.ConclusionsHerein, 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 materialThe online version of this article (doi:10.1186/s13068-015-0382-0) contains supplementary material, which is available to authorized users.
Highlights
For many years, increasing demands for fossil fuels have met with limited supply
Mutant selection and physiological characterization Mutants of D. tertiolecta subjected to random insertional mutagenesis were generated by transformation using pGreenII0000 plasmid with a bleomycin selection cassette
As an attempt to use a rapid fatty acid detection protocol, we compared the quantification results obtained from the GC–MS analysis with those obtained from Nile red assays
Summary
For many years, increasing demands for fossil fuels have met with limited supply. As a potential substi‐ tute and renewable source of biofuel feedstock, microalgae have received significant attention. As an alternative and renewable source of lipid-rich biomass feedstock for biofuels, microalgae have been explored and received considerable attention in the recent years [2]. These microorganisms are able to use the solar energy to combine water with carbon dioxide which is the main component of greenhouse gas emissions to produce biomass [3], which convert sunlight into chemical energy in the form of reduced carbon molecules (carbohydrates, oils/ fats). Oils or triacylglycerols (TAGs) can be used directly or by a simple chemical conversion to fatty acid methyl esters as biodiesels [4]
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
