Search for: All records

Abstract BackgroundRecent studies uncovered pervasive transcription and translation of thousands of noncanonical open reading frames (nORFs) outside of annotated genes. The contribution of nORFs to cellular phenotypes is difficult to infer using conventional approaches because nORFs tend to be short, of recent de novo origins, and lowly expressed. Here we develop a dedicated coexpression analysis framework that accounts for low expression to investigate the transcriptional regulation, evolution, and potential cellular roles of nORFs inSaccharomyces cerevisiae. ResultsOur results reveal that nORFs tend to be preferentially coexpressed with genes involved in cellular transport or homeostasis but rarely with genes involved in RNA processing. Mechanistically, we discover that young de novo nORFs located downstream of conserved genes tend to leverage their neighbors’ promoters through transcription readthrough, resulting in high coexpression and high expression levels. Transcriptional piggybacking also influences the coexpression profiles of young de novo nORFs located upstream of genes, but to a lesser extent and without detectable impact on expression levels. Transcriptional piggybacking influences, but does not determine, the transcription profiles of de novo nORFs emerging nearby genes. About 40% of nORFs are not strongly coexpressed with any gene but are transcriptionally regulated nonetheless and tend to form entirely new transcription modules. We offer a web browser interface (https://carvunislab.csb.pitt.edu/shiny/coexpression/) to efficiently query, visualize, and download our coexpression inferences. ConclusionsOur results suggest that nORF transcription is highly regulated. Our coexpression dataset serves as an unprecedented resource for unraveling how nORFs integrate into cellular networks, contribute to cellular phenotypes, and evolve. 

High-risk human papillomaviruses (HPV) are important agents, responsible for a large percentage of the 745,000 cases of head and neck squamous cell carcinomas (HNSCC), which were identified worldwide in 2020. In addition to being virally induced, tobacco and heavy alcohol consumption are believed to cause DNA damage contributing to the high number of HNSCC cases. Gene expression and DNA methylation differ between HNSCC based on HPV status. We used publicly available gene expression and DNA methylation profiles from the Cancer Genome Atlas and compared HPV positive and HPV negative HNSCC groups. We used differential gene expression analysis, differential methylation analysis, and a combination of these two analyses to identify the differences. Differential expression analysis identified 1854 differentially expressed genes, including PCNA, TNFRSF14, TRAF1, TRAF2, BCL2, and BIRC3. SYCP2 was identified as one of the top deregulated genes in the differential methylation analysis and in the combined differential expression and methylation analyses. Additionally, pathway and ontology analyses identified the extracellular matrix and receptor interaction pathway as the most altered between HPV negative and HPV positive HNSCC groups. Combining gene expression and DNA methylation can help in elucidating the genes involved in HPV positive HNSCC tumorigenesis, such as SYCP2 and TAF7L.