Ontology highlight
ABSTRACT:
PROVIDER: PRJNA1070539 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| SRR27783400_1.fastq.gz | Fastqsanger.gz | |||
| SRR27783400_2.fastq.gz | Fastqsanger.gz | |||
| SRR27783399_1.fastq.gz | Fastqsanger.gz | |||
| SRR27783399_2.fastq.gz | Fastqsanger.gz |
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Project description:Background: Microalgae can make a significant contribution towards meeting global renewable energy needs in both lipid-based liquid biofuel and hydrogen biofuel. The development of energy-related products and chemicals from algae could be accelerated with improvements in systems biology tools, and recent advances in sequencing technology provide a platform for enhanced transcriptomic analyses. However, these techniques are still heavily reliant upon available genomic sequence data. We have developed a de novo sequencing, annotation, and quantitation pipeline that can be applied to unsequenced organisms for effective quantitative gene expression profiling. Chlamydomonas moewusii is a unicellular green alga capable of evolving molecular hydrogen (H2) under both dark and light anaerobic conditions, and has high hydrogenase activity that can be rapidly induced. However, to date, there is no systematic investigation of transcriptomic profiling during induction of hydrogen photoproduction in this organism. Results: In this work, we measured rates of hydrogen production and extracted RNA from samples of C. moewusii following various lengths of dark anaerobic incubation. RNA-Seq was applied to investigate transcriptomic profiles during the dark anaerobic induction of hydrogen photoproduction. One hundred fifty six million reads generated from seven samples were then used for de novo assembly after data trimming. The BlastX results against NCBI database and Blast2GO results were used to interpret the functions of the assembled 39,136 contigs, which were then used as the reference transcripts for RNA-Seq analysis. Nearly 98% transcripts had Blast hits, although more than one-third were annotated as hypothetical proteins. The expression value of RNA-Seq results was imported into statistical software for data quality control, normalization, and subsequent statistical analyses such as One-way ANOVA and K-means Clustering. Our results indicated that more transcripts were differentially expressed during the period of early and higher hydrogen photoproduction, and fewer transcripts were differentially expressed when rates of hydrogen photoproduction decreased. Conclusions: Herein, we have described a workflow to analyze RNA-Seq data without reference genome sequence information, which can be applied to the rapid development of other unsequenced microorganisms (both prokaryotic and eukaryotic) with the potential for development as fuel production strains. This study provided the first transcriptomic RNA-Seq dataset, as well as biological insights into the metabolic changes that occur concomitant with induction of hydrogen photoevolution in C. moewusii, which can help further development of this organism as a hydrogen photoproduction strain. Examine time course gene differential expression post anaerobic induction for hydrogen production
2013-09-04 | E-GEOD-46225 | biostudies-arrayexpress
Project description:Microalgae are natural biocatalysts of Hydrogen. Their ability to convert solar energy to valuable compounds with minimal ecological footprint potentially puts them as significant contributors to clean energy transition. Currently, this process, although promising, is not scalable because it is limited to oxygen-free conditions and is short-lived due to electron loss to other processes, mainly carbon fixation. Here we show that a strain, defected in thylakoid proton gradient regulation, ∆pgr5, bypasses both challenges simultaneously, leading to a prolonged 12-day hydrogen production under ambient mixotrophic conditions in a one-liter set-up. We report that ∆pgr5 possess a repressed ability to fixate carbon and this limitation is counterbalanced by an enhanced chloroplast-mitochondrion energetic exchange. This unique physiology supported the simplistic, yet robust and scalable hydrogen production capability of ∆pgr5.
2022-11-09 | PXD028843 | Pride
Project description:Biodiesel production from microalgae
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Project description:Background: Microalgae can make a significant contribution towards meeting global renewable energy needs in both lipid-based liquid biofuel and hydrogen biofuel. The development of energy-related products and chemicals from algae could be accelerated with improvements in systems biology tools, and recent advances in sequencing technology provide a platform for enhanced transcriptomic analyses. However, these techniques are still heavily reliant upon available genomic sequence data. We have developed a de novo sequencing, annotation, and quantitation pipeline that can be applied to unsequenced organisms for effective quantitative gene expression profiling. Chlamydomonas moewusii is a unicellular green alga capable of evolving molecular hydrogen (H2) under both dark and light anaerobic conditions, and has high hydrogenase activity that can be rapidly induced. However, to date, there is no systematic investigation of transcriptomic profiling during induction of hydrogen photoproduction in this organism. Results: In this work, we measured rates of hydrogen production and extracted RNA from samples of C. moewusii following various lengths of dark anaerobic incubation. RNA-Seq was applied to investigate transcriptomic profiles during the dark anaerobic induction of hydrogen photoproduction. One hundred fifty six million reads generated from seven samples were then used for de novo assembly after data trimming. The BlastX results against NCBI database and Blast2GO results were used to interpret the functions of the assembled 39,136 contigs, which were then used as the reference transcripts for RNA-Seq analysis. Nearly 98% transcripts had Blast hits, although more than one-third were annotated as hypothetical proteins. The expression value of RNA-Seq results was imported into statistical software for data quality control, normalization, and subsequent statistical analyses such as One-way ANOVA and K-means Clustering. Our results indicated that more transcripts were differentially expressed during the period of early and higher hydrogen photoproduction, and fewer transcripts were differentially expressed when rates of hydrogen photoproduction decreased. Conclusions: Herein, we have described a workflow to analyze RNA-Seq data without reference genome sequence information, which can be applied to the rapid development of other unsequenced microorganisms (both prokaryotic and eukaryotic) with the potential for development as fuel production strains. This study provided the first transcriptomic RNA-Seq dataset, as well as biological insights into the metabolic changes that occur concomitant with induction of hydrogen photoevolution in C. moewusii, which can help further development of this organism as a hydrogen photoproduction strain.
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Project description:The budding yeast, Saccharomyces cerevisiae, has emerged as an archetype of eukaryotic cell biology. Here we show that S. cerevisiae is also a model for the evolution of cooperative behavior by revisiting flocculation, a self-adherence phenotype lacking in most laboratory strains. Expression of the gene FLO1 in the laboratory strain S288C restores flocculation, an altered physiological state, reminiscent of bacterial biofilms. Flocculation protects the FLO1-expressing cells from multiple stresses, including antimicrobials and ethanol. Furthermore, FLO1+ cells avoid exploitation by non-expressing flo1 cells by self/non-self recognition: FLO1+ cells preferentially stick to one another, regardless of genetic relatedness across the rest of the genome. Flocculation, therefore, is driven by one of a few known â??green beard genesâ??, which direct cooperation towards other carriers of the same gene. Moreover, FLO1 is highly variable among strains both in expression and in sequence, suggesting that flocculation in S. cerevisiae is a dynamic, rapidly-evolving social trait. This dataset contains raw transcriptome data of flocculating cells (that express FLO1 driven by the GAL1 promoter) and non-flocculating cells (that do not express FLO1). Experiment Overall Design: Cultures of flocculating and non-flocculating cells were grown for 24 hours in YPGal medium. Subsequently, RNA was isolated from these cultures, converted into cDNA and analyzed using commercially available Afymetrix S98 arrays. For each culture, two biological replicates were analyzed.
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