Gene expression database

Description

Gene expression drives a multitude of cellular processes, and is what makes a cell functional and alive. Occurring at two levels at the transcription and translation level, both processes must work in tandem to yield functional proteins from the gene sequence to help effect changes to cellular physiology as well as to respond to changing environmental and nutritional circumstances. Recent promulgation of sequence-based approaches has significantly facilitated and expedited gene expression analysis. For example, RNA-seq transcriptome analysis offers an unbiased view of the transcriptome of a cell at the mRNA level, which tells a story of how rapid and widespread particular environmental and nutritional trigger is in affecting cellular fitness and physiology. The analysis process is completed by recent introduction of another sequence-based gene expression profiling technique known as Ribo-seq, which takes a deliberate look at the mRNA transcripts that are actively undergoing translation. Although not as well developed as RNA-seq, Ribo-seq still offers a tantalizing close look at translation processes from the genome-wide perspective.

This database collects a series of RNA-seq transcriptome and Ribo-seq analysis dataset that I have obtained in my own research. Original fastq datasets were downloaded from ArrayExpress, and the contents of the fastq files were analysed by an in-house RNA-seq and Ribo-seq software. As a given gene expression dataset could be analyzed in myriad ways to yield interesting biological insights, it is hoped that this collection of gene expression datasets could be an enabling tool for biologists in different fields.

RNA-seq transcriptome

  1. Wenfa Ng, “Transcriptome of Escherichia coli K-12 (MG1655) at stationary phase in minimal medium”, figshare, Link to dataset
  2. Wenfa Ng, “Transcriptome dataset of Bacillus subtilis 168 cultivated in LB medium”, figshare, Link to dataset
  3. Wenfa Ng, “RNA-seq transcriptome of Pseudomonas aeruginosa PAO1 in Brain Heart Infusion broth”, figshare, Link to dataset
  4. Wenfa Ng, “RNA-seq transcriptome of Pseudomonas putida KT2440 fed with glucose as sole carbon source”, figshare, Link to dataset
  5. Wenfa Ng, “RNA-seq transcriptome of Staphylococcus aureus at stationary phase in Tryptic Soy Broth”, figshare, Link to dataset
  6. Wenfa Ng, “RNA-seq transcriptome of Staphylococcus aureus MRSA at mid-exponential phase”, figshare, Link to dataset
  7. Wenfa Ng, “RNA-seq transcriptome of Pseudomonas putida KT2440 subsisting on glycerol as sole carbon source”, figshare, Link to dataset
  8. Wenfa Ng, “RNA-seq transcriptome of Pseudomonas putida KT2440 subsisting on fructose as sole carbon source”, figshare, Link to dataset
  9. Wenfa Ng, “RNA-seq transcriptome of Pseudomonas putida KT2440 subsisting on succinate as sole carbon source”, figshare, Link to dataset
  10. Wenfa Ng, “RNA-seq transcriptome of Pseudomonas syringae DC3000 in liquid minimal medium”, figshare, Link to dataset