Ontology highlight
ABSTRACT:
PROVIDER: PRJNA1164121 | ENA |
REPOSITORIES: ENA
Similar Datasets
Project description:Although it is well established the seasonal effect of the photoperiod over the transcriptional expression patterns in plants, this effect has not been studied in microalgae. Here we fill the gap using the model microalgae Ostreococcus tauri.
2023-08-31 | GSE155535 | GEO
Project description:Limited systems-level understanding of CO2 concentrating mechanism (CCM) and metabolic adaption in response to different CO2-level in wild oleaginous algae has hindered the development of microalgal feedstock and the knowledge of its role in global warming and oceanic acidification. Nannochloropsis are a group of small unicellular microalgae widely distributed in oceans and fresh water, which implies that it plays a crucial role in biogeochemical cycles impinged on global climate change. In addition, Nannochloropsis has been used for flue gas fixation in many large-scale and pilot-scale outdoor cultivation facilities for photosynthetic production of fuels and chemicals. To untangle the intricate genome-wide networks underlying CCM and metabolic adjustment under different CO2 concentrations in Nannochloropsis, we applied high-throughput mRNA-sequencing and reconstructed the structure and dynamics of the genome-wide functional network underlying robust microalgal CCM and in Nannochloropsis oceanica, by tracking the genome-wide, single-base-resolution transcript change for the complete time-courses of different CO2 concentrations.
2019-07-16 | GSE55861 | GEO
Project description:Limited systems-level understanding of oil synthesis in wild oleaginous algae has hindered the development of microalgal feedstock. Nannochloropsis is a small unicellular microalgae widely distributed in oceans and fresh water. In many large-scale and pilot-scale outdoor cultivation facilities, Nannochloropsis strains have been found to be capable of robust growth when supplied with flue gases, naturally accumulating large quantities of oils in a stationary phase, and exhibiting resistance to environmental contaminants. The rich genomic resources, compact genomes, resistance to foreign DNA invasion, wide ecological adaptation, large collections of natural strains and the demonstrated ability to grow on a large scale suggested Nannochloropsis can serve as research models and platform strains for economical and scalable photosynthetic production of fuels and chemicals. To untangle the intricate genome-wide networks underlying the robust biomass accumulation and oil production in Nannochloropsis, we applied high-throughput mRNA-sequencing and reconstructed the structure and dynamics of the genome-wide functional network underlying robust microalgal triacylglycerol (TAG) production in Nannochloropsis oceanica, by tracking the genome-wide, single-base-resolutiontranscript change for the complete time-courses of nitrogen-depletion-induced TAG synthesis.
2014-05-14 | GSE42508 | GEO
Project description:Transcription generates local topological and mechanical constraints along the DNA fiber, driving for instance the generation of supercoiled chromosomal domains in bacteria. However, the global impact of transcription-based regulation of chromosome organization remains elusive. Notably, the scale of genes and operons in bacteria remains well below the resolution of chromosomal contact maps generated using Hi-C (~ 5 - 10 kb), preventing to resolve the impact of transcription on genomic organization at the fine-scale. Here, we combined sub-kb Hi-C contact maps and chromosome engineering to visualize individual transcriptional units (TUs) while turning off transcription across the rest of the genome. We show that each TU forms a discrete, transcription-induced 3D domain (TIDs). These local structures impose mechanical and topological constraints on their neighboring sequences at larger scales, bringing them closer together and restricting their dynamics. These results show that the primary building blocks of bacteria chromosome folding consists of transcriptional domains that together shape the global genome structure.
2023-12-01 | GSE213028 | GEO
Project description:Pilot RNA-seq dataset created by the Geuvadis consortium (www.geuvadis.org)
2010-04-14 | E-GEUV-4 | biostudies-arrayexpress
Project description:Missing values in proteomic data sets have real consequences on downstream data analysis and reproducibility. Although several imputation methods exist to handle missing values, no single imputation method is best suited for a diverse range of data sets, and no clear strategy exists for evaluating imputation methods for large-scale DIA-MS data sets, especially at different levels of protein quantification. To navigate through the different imputation strategies available in the literature, we have established a workflow to assess imputation methods on large-scale label-free DIA-MS data sets. We used three DIA-MS data sets with real missing values to evaluate eight different imputation methods with multiple parameters at different levels of protein quantification; dilution series data set, a small pilot data set, and a larger proteomic data set.
2021-05-07 | PXD022996 | Pride
Project description:Missing values in proteomic data sets have real consequences on downstream data analysis and reproducibility. Although several imputation methods exist to handle missing values, no single imputation method is best suited for a diverse range of data sets, and no clear strategy exists for evaluating imputation methods for large-scale DIA-MS data sets, especially at different levels of protein quantification. To navigate through the different imputation strategies available in the literature, we have established a workflow to assess imputation methods on large-scale label-free DIA-MS data sets. We used three DIA-MS data sets with real missing values to evaluate eight different imputation methods with multiple parameters at different levels of protein quantification; dilution series data set, a small pilot data set, and a larger proteomic data set.
2021-05-07 | PXD023012 | Pride
Project description:Sexual reproduction and recombination are essential for the survival of most eukaryotic populations. Until recently, the impact of these processes on the structure of bacterial populations has been largely overlooked. The advent of large-scale whole-genome sequencing and the concomitant development of molecular tools, such as microarray technology, facilitate the sensitive detection of recombination events in bacteria. These techniques are revealing that bacterial populations are comprised of isolates that show a surprisingly wide spectrum of genetic diversity at the DNA level. Our new awareness of this genetic diversity is increasing our understanding of population structures and of how these affect host?pathogen relationships. Set of arrays organized by shared biological context, such as organism, tumors types, processes, etc. Computed
2005-10-20 | E-GEOD-3479 | biostudies-arrayexpress
Project description:Missing values in proteomic data sets have real consequences on downstream data analysis and reproducibility. Although several imputation methods exist to handle missing values, no single imputation method is best suited for a diverse range of data sets, and no clear strategy exists for evaluating imputation methods for large-scale DIA-MS data sets, especially at different levels of protein quantification. To navigate through the different imputation strategies available in the literature, we have established a workflow to assess imputation methods on large-scale label-free DIA-MS data sets. We used three DIA-MS data sets with real missing values to evaluate eight different imputation methods with multiple parameters at different levels of protein quantification; dilution series data set, a small pilot data set, and a larger proteomic data set of clinical ovarian cancer patient samples.
2021-05-07 | PXD023040 | Pride