PDF(Pubmed)
Abstract：
BACKGROUND: Recent 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 in Saccharomyces cerevisiae.
RESULTS: Our 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.
CONCLUSIONS: Our 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.
RESULTS: Our 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.
CONCLUSIONS: Our 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.
摘要：
背景：最近的研究发现了在注释基因之外的数千个非规范开放阅读框（nORFs）的普遍转录和翻译。nORF对细胞表型的贡献很难使用常规方法推断，因为nORF往往很短，最近的从头起源，卑微的表达。在这里，我们开发了一个专门的共表达分析框架，用于研究低表达的转录调控，进化,nORFs在酿酒酵母中的潜在细胞作用。
结果：我们的结果表明，nORFs倾向于优先与参与细胞运输或稳态的基因共表达，但很少与参与RNA加工的基因共表达。机械上,我们发现位于保守基因下游的年轻denovonORF倾向于通过转录通读来利用它们的邻居\'启动子，导致高共表达和高表达水平。转录搭载还影响位于基因上游的年轻从头nORF的共表达谱，但程度较小，对表达水平没有可检测的影响。转录搭载影响，但不能确定，附近基因出现的从头nORF的转录谱。大约40%的nORFs不与任何基因强烈共表达,但仍然受到转录调节,并且倾向于形成全新的转录模块。我们提供Web浏览器界面（https://carvunislab。csb.皮特.edu/shiny/coexpression/)以高效查询，可视化，并下载我们的coexpression推论。
结论：我们的结果表明nORF转录受到高度调控。我们的共表达数据集是前所未有的资源，用于揭示nORF如何集成到蜂窝网络中，有助于细胞表型，和进化。
结果：我们的结果表明，nORFs倾向于优先与参与细胞运输或稳态的基因共表达，但很少与参与RNA加工的基因共表达。机械上,我们发现位于保守基因下游的年轻denovonORF倾向于通过转录通读来利用它们的邻居\'启动子，导致高共表达和高表达水平。转录搭载还影响位于基因上游的年轻从头nORF的共表达谱，但程度较小，对表达水平没有可检测的影响。转录搭载影响，但不能确定，附近基因出现的从头nORF的转录谱。大约40%的nORFs不与任何基因强烈共表达,但仍然受到转录调节,并且倾向于形成全新的转录模块。我们提供Web浏览器界面（https://carvunislab。csb.皮特.edu/shiny/coexpression/)以高效查询，可视化，并下载我们的coexpression推论。
结论：我们的结果表明nORF转录受到高度调控。我们的共表达数据集是前所未有的资源，用于揭示nORF如何集成到蜂窝网络中，有助于细胞表型，和进化。
