Ontology highlight
ABSTRACT:
PROVIDER: PRJNA436729 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| SRR6811430_1.fastq.gz | Fastqsanger.gz | |||
| SRR6811430_2.fastq.gz | Fastqsanger.gz | |||
| SRR6811440_1.fastq.gz | Fastqsanger.gz | |||
| SRR6811440_2.fastq.gz | Fastqsanger.gz | |||
| SRR6811450_1.fastq.gz | Fastqsanger.gz |
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Project description:Background: The investigation of extremophile plant species growing in their natural environment offers certain advantages, chiefly that plants adapted to severe habitats have a repertoire of stress tolerance genes that are regulated to maximize plant performance under physiologically challenging conditions. Accordingly, transcriptome sequencing offers a powerful approach to address questions concerning the influence of natural habitat on the physiology of an organism. We used RNA sequencing of Eutrema salsuginuem, an extremophile relative of Arabidopsis thaliana, to investigate the extent to which genetic variation and controlled versus natural environments contribute to differences between transcript profiles. Results: Using 10 million cDNA reads, we compared transcriptomes from two natural Eutrema accessions (originating from Yukon Territory, Canada and Shandong Province, China) grown under controlled conditions in cabinets and those from Yukon plants collected at a Yukon field site. We assessed the genetic heterogeneity between individuals using single-nucleotide polymorphisms (SNPs) and the expression patterns of 27,016 genes. Over 39,000 SNPs distinguish the Yukon from the Shandong accessions but only 4,475 SNPs differentiated transcriptomes of Yukon field plants from an inbred Yukon line. We found 2,898 genes that were differentially expressed between the three sample groups and multivariate statistical analyses showed that transcriptomes of individual plants from a Yukon field site were as reproducible as those from inbred plants grown under controlled conditions. Predicted functions based upon gene ontology classifications show that the transcriptomes of field plants were enriched by the differential expression of light- and stress-related genes, an observation consistent with the habitat where the plants were found. Conclusion: Our expectation that comparative RNA-Seq analysis of transcriptomes from plants originating in natural habitats would be confounded by uncontrolled genetic and environmental factors was not borne out. Moreover, the transcriptome data shows little genetic variation between laboratory Yukon Eutrema plants and those found at a field site. Transcriptomes were reproducible and biological associations meaningful whether plants were grown in cabinets or found in the field. Thus RNA-Seq is a valuable approach to study native plants in natural environments and this technology can be exploited to discover new gene targets for improved crop performance under adverse conditions. Funding Acknowledgement: This work was sponsored by an Ontario Research Fund-Research Excellence award 03-043 to EAW and RKC with support from by Viterra Inc. and Sigma-Aldrich.
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Project description:There is a great need for setting novel measurable attributes at the cell physiological level in a scalable biopharmaceutical production process to be able to predict the process outcomes and improve process understanding. In a biologic production process, changes in culture environment due to several factors such as shear and bubble induced damage from gas sparging and agitation are known to occur. There is a gap in the knowledge of cellular response due to varying bioreactor environment itself during the course of cell culture, from lag-phase to log-phase to stationary-phase in culture. With the emergence of micro-arrays as tools for exploring cell physiological changes, it opens the possibility for studying the effect of bioreactor culture environment itself on the cell substrate. Such information could be eventually used to designate gene transcripts as biomarkers for cell status in a controlled bioreactor system. A model 5L bench-scale bubble aerated and impeller agitated bioreactor system was used to study gene expression profiles of a hybridoma cell line during the time-course of batch culture. Gene expression profiles that were variable from early-to-late in batch culture, as well as invariant gene profiles were summarized using microarray findings. Typical cellular functions studied were oxidative stress response, DNA damage response, apoptosis, antioxidant activity, cellular metabolism, and protein folding. These findings were also verified with a more rigorous semi-quantitative RT-PCR technique. The results of this study suggest that under predefined bioreactor culture conditions, significant gene changes from lag to log to stationary phase could be identified, which could then be used to track the culture state.
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Project description:There is a great need for setting novel measurable attributes at the cell physiological level in a scalable biopharmaceutical production process to be able to predict the process outcomes and improve process understanding. In a biologic production process, changes in culture environment due to several factors such as shear and bubble induced damage from gas sparging and agitation are known to occur. There is a gap in the knowledge of cellular response due to varying bioreactor environment itself during the course of cell culture, from lag-phase to log-phase to stationary-phase in culture. With the emergence of micro-arrays as tools for exploring cell physiological changes, it opens the possibility for studying the effect of bioreactor culture environment itself on the cell substrate. Such information could be eventually used to designate gene transcripts as biomarkers for cell status in a controlled bioreactor system. A model 5L bench-scale bubble aerated and impeller agitated bioreactor system was used to study gene expression profiles of a hybridoma cell line during the time-course of batch culture. Gene expression profiles that were variable from early-to-late in batch culture, as well as invariant gene profiles were summarized using microarray findings. Typical cellular functions studied were oxidative stress response, DNA damage response, apoptosis, antioxidant activity, cellular metabolism, and protein folding. These findings were also verified with a more rigorous semi-quantitative RT-PCR technique. The results of this study suggest that under predefined bioreactor culture conditions, significant gene changes from lag to log to stationary phase could be identified, which could then be used to track the culture state. We ran consecutive 5L bioreactor runs, each with an independent vial thaw, to achieve multiple biological replicates per time-point. Bioreactors were sampled approximately every 12 hours for RNA extraction. For the 5L bioreactors, microarray samples were run for day 1 (n=2), day 2 (n=2), day 3 (n=3), and day 3.5 (n=3). Here 2 or 3 of the three biological replicates run for each time-point were included in the analysis, based on >70% genes found. We define early exponential as day 1, peak exponential as day 2 and day 3 and late stationary as day 3.5.
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