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Post-transcriptional regulatory mechanisms play a role in many biological contexts through the control of mRNA degradation, translation and localization. Here, we show that the RING finger protein RNF219 co-purifies with the CCR4-NOT complex, the major mRNA deadenylase in eukaryotes, which mediates translational repression in both a deadenylase activity-dependent and -independent manner. Strikingly, RNF219 both inhibits the deadenylase activity of CCR4-NOT and enhances its capacity to repress translation of a target mRNA. We propose that the interaction of RNF219 with the CCR4-NOT complex directs the translational repressive activity of CCR4-NOT to a deadenylation-independent mechanism.

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Cells transcribe and translate thousands of noncanonical open reading frames (nORFs) whose impacts on cellular phenotypes are unknown. Here, we investigated nORF transcription, evolution, and potential cellular roles using a coexpression approach. We measured coexpression between ~6,000 nORFs and ~6000 canonical ORFs (cORFs) in the Saccharomyces cerevisiae genome by massively integrating thousands of RNA sequencing samples and developing a dedicated computational framework that accounts for low expression levels. Our findings reveal that almost all cORFs are strongly coexpressed with at least one nORF. However, almost half of nORFs are not strongly coexpressed with any cORFs and form entirely new transcription modules. Many nORFs recently evolved de novo in genomic regions that were non-coding in the Saccharomyces ancestor. Coexpression profiles suggest that half of de novo nORFs are functionally associated with conserved genes involved in cellular transport or homeostasis. Furthermore, we discovered that de novo ORFs located downstream of conserved genes leverage their neighbors' transcripts resulting in high expression levels. Where a de novo nORF emerges could be just as important as its sequence for shaping how it can influence cellular phenotype. 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.

High-risk human papillomaviruses (HPV) are an important agent that cause head and neck squamous cell carcinomas (HNSCC). Besides viral induced cancers, tobacco use and heavy alcohol consumption are believed to cause DNA damage, promoting tumorigenesis. How gene expression and DNA methylation differ between HNSCC based on HPV status is yet unknown. We used publicly available gene expression and DNA methylation data from the Cancer Genome Atlas and compared HPV positive and HPV negative HNSCC. We used differential gene expression analysis, differential methylation analysis and a combination of these two analyses to identify 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 analysis. Additionally, pathway and ontology analysis identified the extracellular matrix and receptor interaction pathway to be the most altered between HPV negative and HPV positive HNSCC groups. Combining gene expression and DNA methylation can help elucidate genes involved in HPV positive HNSCC tumorigenesis such as SYCP2 and TAF7L.