Integrative classification of human coding and non-coding genes based on RNA metabolism profiles
Transcriptomics Dataset
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General Information
| Accession | GSE84722 |
| Title | Integrative classification of human coding and non-coding genes based on RNA metabolism profiles |
| Description | The pervasive transcription of the human genome results in a heterogeneous mix of coding and long non-coding RNAs (lncRNAs). Only a small fraction of lncRNAs possess demonstrated regulatory functions, making it difficult to distinguish functional lncRNAs from non-functional transcriptional byproducts. This has resulted in numerous competing incoherent annotations of human lncRNA. To address these challenges, we quantitatively examined transcription, splicing, degradation, localization and translation for coding and non-coding human genes. Annotated lncRNAs had lower synthesis and higher degradation rates than mRNAs. We discovered mechanistic differences explaining the slower splicing of lncRNAs. We grouped genes into coherent classes by performing annotation-agnostic unsupervised classification of RNA metabolism profiles. These classes contained both mRNAs and lncRNAs to varying degrees; they exhibited distinct relationships between steps of RNA metabolism, evolutionary patterns, and sensitivity to cellular RNA regulatory pathways. Our classification provides a functionally coherent alternative to genomic context-driven annotations of lncRNAs. |
| Landing Page | https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE84722 |
| Repository | Gene Expression Omnibus |
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