Extensive post-transcriptional buffering of gene expression in the response to severe oxidative stress in baker's yeast.
William R BlevinsTeresa TavellaSimone G MoroBernat Blasco-MorenoAdrià Closa-MosqueraJuana DíezLucas B CareyM Mar AlbàPublished in: Scientific reports (2019)
Cells responds to diverse stimuli by changing the levels of specific effector proteins. These changes are usually examined using high throughput RNA sequencing data (RNA-Seq); transcriptional regulation is generally assumed to directly influence protein abundances. However, the correlation between RNA-Seq and proteomics data is in general quite limited owing to differences in protein stability and translational regulation. Here we perform RNA-Seq, ribosome profiling and proteomics analyses in baker's yeast cells grown in rich media and oxidative stress conditions to examine gene expression regulation at various levels. With the exception of a small set of genes involved in the maintenance of the redox state, which are regulated at the transcriptional level, modulation of protein expression is largely driven by changes in the relative ribosome density across conditions. The majority of shifts in mRNA abundance are compensated by changes in the opposite direction in the number of translating ribosomes and are predicted to result in no net change at the protein level. We also identify a subset of mRNAs which is likely to undergo specific translational repression during stress and which includes cell cycle control genes. The study suggests that post-transcriptional buffering of gene expression may be more common than previously anticipated.
Keyphrases
- rna seq
- gene expression
- single cell
- induced apoptosis
- high throughput
- oxidative stress
- cell cycle
- dna methylation
- cell cycle arrest
- endoplasmic reticulum stress
- protein protein
- transcription factor
- electronic health record
- mass spectrometry
- binding protein
- cell proliferation
- signaling pathway
- amino acid
- dna damage
- ischemia reperfusion injury
- big data
- small molecule
- label free
- cell death
- dendritic cells
- wastewater treatment
- artificial intelligence
- cell wall
- deep learning