Uncultured bacterium strain:non-photosynthetic bateria with CK
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ABSTRACT:
PROVIDER: PRJNA261156 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| SRR1576531_1.fastq.gz | Fastqsanger.gz | |||
| SRR1576531_2.fastq.gz | Fastqsanger.gz | |||
| SRR1575547_1.fastq.gz | Fastqsanger.gz | |||
| SRR1575547_2.fastq.gz | Fastqsanger.gz | |||
| SRR1575627_1.fastq.gz | Fastqsanger.gz |
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Project description:uncultured bacterium strain:non-photosynthetic microbial community with MED Genome sequencing
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2005-11-10 | GSE3030 | GEO
Project description:Antisense RNAs (asRNAs) have diverse functions across three superkingdoms of life. However, their physiological roles for photosynthesis, the most efficient conversion system of solar energy and carbon dioxide into desirable biofuel, are elusive. To understand asRNA-mediated photosynthetic response, we systematically identified non-coding asRNAs and analyzed their differential regulation upon high light and/or low temperature. We found that large fractions of antisense regions are pervasively transcribed and differentially induced upon the change of light and/or temperature. Particularly, photosynthesis and ribosome related genes are mostly regulated by asRNA. Futhermore, we found that 93 long non-coding asRNAs spanning more than half of the cognate open reading frames (ORFs), unexpectedly. Intriguingly, many of them are associated with photosynthetic genes and they have positive role to the expression level of their cognate ORFs. Thus, our systematic transcriptome analysis of photosynthetic response indicates that asRNAs may finetune transcriptional response to enable efficient photosynthetic energy conversion.
2020-07-25 | GSE60109 | GEO
Project description:Maize and rice are the two most economically important grass crops and utilize distinct forms of photosynthesis to fix carbon: C4 and C3 respectively. Relative to C3 photosynthesis, C4 photosynthesis reduces photorespiration and affords higher water and nitrogen use efficiencies under hot arid conditions. To define key innovations in C4 photosynthesis, we profiled metabolites and gene expression along a developing leaf gradient. A novel statistical method was implemented to compare transcriptomes from these two species along a unified leaf developmental gradient and define candidate cis-regulatory elements and transcription factors driving photosynthetic gene expression. We also present comparative primary and secondary metabolic profiles along the gradients that provide new insight into nitrogen and carbon metabolism in C3 and C4 grasses. These resources, including community viewers to access and mine these datasets, will enable the elucidation and engineering of C4 photosynthetic networks to improve the photosynthetic capacity of C3 and C4 grasses.
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Project description:To address the question of how photosynthetic bacterium Rhodopseudomonas palustris differentially regulates gene expression of three nitrogenase isozymes (Mo, V, and Fe nitrogenases), we constructed Mo strain (Mo nitrogenase only strain), V strain (V nitrogenase only strain), and Fe strain (Fe nitrogenase only strain), and analyzed the whole genome transcriptome profiles of each mutant and wild-type cells grown under nitrogen-fixing conditions. RNA was isolated from various Rhodopseudomonas palustris strains that were grown to the mid-logarithmic phase of growth. Fluorescently labeled cDNA was prepared by direct incorporation of either Cy3-dCTP or Cy5-dCTP during a first-strand reverse transcription reaction. The hybridization mixtures containing the two labeled cDNA samples to be compared were applied to microarray slides that had been covered with Lifterslips (Erie Scientific Company, Portsmouth, NH). The slides were assembled with hybridization chambers (Corning, Corning, NY) and submerged in a 65ºC water bath. After 14-16 h of hybridization, the slides were washed and scanned with a ScanArray 4000XL scanner (PerkinElmer, Boston, MA). Images (Cy3 and Cy5) were captured as TIFF files and were analyzed with the image processing software ImaGene version 5.6 (BioDiscovery, Inc., El Segundo, CA). The software package lcDNA was used for data normalization and assessment of the statistical confidence intervals of gene expression. Duplicate calibration experiments and three comparative experiments using RNA from three separately grown cultures (three biological replicates) with duplicate slides for each (10 slides in total) were used to generate each data set.
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