Functional and transcriptional profiling of non-coding RNAs in yeast reveal context-dependent phenotypes and in trans effects on the protein regulatory network.
Laura Natalia Balarezo-CisnerosSteven ParkerMarcin G FraczekSoukaina TimoumaPing WangRaymond T O'KeefeCatherine B MillarDaniela DelneriPublished in: PLoS genetics (2021)
Non-coding RNAs (ncRNAs), including the more recently identified Stable Unannotated Transcripts (SUTs) and Cryptic Unstable Transcripts (CUTs), are increasingly being shown to play pivotal roles in the transcriptional and post-transcriptional regulation of genes in eukaryotes. Here, we carried out a large-scale screening of ncRNAs in Saccharomyces cerevisiae, and provide evidence for SUT and CUT function. Phenotypic data on 372 ncRNA deletion strains in 23 different growth conditions were collected, identifying ncRNAs responsible for significant cellular fitness changes. Transcriptome profiles were assembled for 18 haploid ncRNA deletion mutants and 2 essential ncRNA heterozygous deletants. Guided by the resulting RNA-seq data we analysed the genome-wide dysregulation of protein coding genes and non-coding transcripts. Novel functional ncRNAs, SUT125, SUT126, SUT035 and SUT532 that act in trans by modulating transcription factors were identified. Furthermore, we described the impact of SUTs and CUTs in modulating coding gene expression in response to different environmental conditions, regulating important biological process such as respiration (SUT125, SUT126, SUT035, SUT432), steroid biosynthesis (CUT494, SUT053, SUT468) or rRNA processing (SUT075 and snR30). Overall, these data capture and integrate the regulatory and phenotypic network of ncRNAs and protein-coding genes, providing genome-wide evidence of the impact of ncRNAs on cellular homeostasis.
Keyphrases
- genome wide
- gene expression
- dna methylation
- rna seq
- transcription factor
- single cell
- saccharomyces cerevisiae
- electronic health record
- escherichia coli
- genome wide identification
- protein protein
- amino acid
- binding protein
- machine learning
- small molecule
- body composition
- heat shock
- oxidative stress
- deep learning
- bioinformatics analysis