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. Issue 1 (December 2015)
- Record Type:
- Journal Article
- Title:
- 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. Issue 1 (December 2015)
- Main Title:
- 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
- Authors:
- Yao, Lina
Tan, Tin
Ng, Yi-Kai
Ban, Kenneth
Shen, Hui
Lin, Huixin
Lee, Yuan - Abstract:
- Abstract 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 microalgaDunaliella 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 fromde novo assembly were annotated based on the best hits in five model microalgae, namelyChlamydomonas reinhardtii, Coccomyxa subellipsoidea C-169, Ostreococcus lucimarinus, Volvox carteri, Chlorella variabilis NC64A and a high plant speciesArabidopsis 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 thisAbstract 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 microalgaDunaliella 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 fromde novo assembly were annotated based on the best hits in five model microalgae, namelyChlamydomonas reinhardtii, Coccomyxa subellipsoidea C-169, Ostreococcus lucimarinus, Volvox carteri, Chlorella variabilis NC64A and a high plant speciesArabidopsis 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 ofD. 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 ofD. tertiolecta genes with homologs of five other green algae and a model high plant species can facilitate the annotation ofD. 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. … (more)
- Is Part Of:
- Biotechnology for biofuels. Volume 8:Issue 1(2015)
- Journal:
- Biotechnology for biofuels
- Issue:
- Volume 8:Issue 1(2015)
- Issue Display:
- Volume 8, Issue 1 (2015)
- Year:
- 2015
- Volume:
- 8
- Issue:
- 1
- Issue Sort Value:
- 2015-0008-0001-0000
- Page Start:
- 1
- Page End:
- 16
- Publication Date:
- 2015-12
- Subjects:
- Dunaliella tertiolecta -- Next-generation sequencing -- RNA-Seq -- Random insertional mutant -- Lipid metabolism
Biotechnology -- Periodicals
Biomass energy -- Periodicals
Energy-Generating Resources -- Periodicals
662.88 - Journal URLs:
- http://rave.ohiolink.edu/ejournals/issn/17546834/ ↗
http://www.biotechnologyforbiofuels.com/ ↗
http://link.springer.com/ ↗ - DOI:
- 10.1186/s13068-015-0382-0 ↗
- Languages:
- English
- ISSNs:
- 1754-6834
- Deposit Type:
- Legaldeposit
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- Available online (eLD content is only available in our Reading Rooms) ↗
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- British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
- 9815.xml