Date of Award
Doctor of Philosophy (PhD)
Cryptic unstable transcripts (CUTs) are a largely unexplored class of nuclear exosome degraded, non-coding RNAs in budding yeast. It is highly debated whether CUT transcription has a functional role in the cell or whether CUTs represent noise in the yeast transcriptome. I sought to ascertain the extent of conserved CUT expression across a variety of Saccharomyces yeast strains to further understand and characterize the nature of CUT expression. To this end I designed a Hidden Markov Model (HMM) to analyze strand-specific RNA sequencing data from nuclear exosome rrp6Δ mutants to identify and compare CUTs in four different yeast strains: S288c, Σ1278b, JAY291 (S.cerevisiae) and N17 (S.paradoxus). My RNA-seq based method has greatly expanded upon previous CUT annotations in S.cerevisiae, underscoring the extensive and pervasive nature of unstable transcription. Utilizing a four-way genomic alignment I identified a large population of CUTs with conserved syntenic expression across all four strains. Furthermore I observed that certain configurations of gene-CUT pairs, where CUT expression originates from a gene 5’ or 3’ nucleosome free region, correlate with distinct expression trends for the associated gene. Bidirectional gene-CUT pairs correlate with higher expression of genes, and antisense gene-CUT pairs correlate with reduced gene expression. Interestingly these effects on gene expression are most prevalent in the presence of conserved CUT expression. Additionally I have shown that CUTs lack a well-defined 3’ nucleosome free region that is commonly observed at protein-coding genes, and suggests that 3’ NFRs are not characteristic of Sen1-dependent terminated transcripts.
Vera, Jessica Marie, "A Computational and Evolutionary Approach to Understanding Cryptic Unstable Transcripts in Yeast" (2015). Molecular, Cellular, and Developmental Biology Graduate Theses & Dissertations. 41.