Native RNA sequencing in fission yeast reveals frequent alternative splicing isoforms.

The unicellular yeast (fission yeast) retains many of the splicing features observed in humans and is thus an excellent model to study the basic mechanisms of splicing. Nearly half the genes contain introns, but the impact of alternative splicing in gene regulation and proteome diversification remains largely unexplored. Here we leverage Oxford Nanopore Technologies native RNA sequencing (dRNA), as well as ribosome profiling data, to uncover the full range of polyadenylated transcripts and translated open reading frames.

Identification of Taxonomically Restricted Transcripts from Illumina RNA Sequencing Data.

In order to perform a well-balanced comparative transcriptomic analysis, the reference genome and annotations for all species included in the comparison must be of a similar quality and completeness. Frequently, comparative transcriptomic analyses include non-model organisms whose annotations are not as well curated; this inequality can lead to biases.To avoid potential biases stemming from incomplete annotations, a comparative transcriptomic analysis can incorporate de novo transcriptome assemblies for each species, which reduces this disparity.

Uncovering de novo gene birth in yeast using deep transcriptomics.

De novo gene origination has been recently established as an important mechanism for the formation of new genes. In organisms with a large genome, intergenic and intronic regions provide plenty of raw material for new transcriptional events to occur, but little is know about how de novo transcripts originate in more densely-packed genomes. Here, we identify 213 de novo originated transcripts in Saccharomyces cerevisiae using deep transcriptomics and genomic synteny information from multiple yeast species grown in two different conditions.

Extensive post-transcriptional buffering of gene expression in the response to severe oxidative stress in baker's yeast.

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.