Spatial correlation statistics enable transcriptome-wide characterization of RNA structure binding

Transcriptome regulation by PARP13 in basal and antiviral states in human cells

The RNA-binding protein PARP13 is a primary factor in the innate antiviral response, which suppresses translation and drives decay of bound viral and host RNA. PARP13 interacts with many proteins encoded by interferon-stimulated genes (ISG) to activate antiviral pathways including co-translational addition of ISG15, or ISGylation. We performed enhanced crosslinking immunoprecipitation (eCLIP) and RNA-seq in human cells to investigate PARP13's role in transcriptome regulation for both basal and antiviral states. We find that the antiviral response shifts PARP13 target localization, but not its binding preferences, and that PARP13 supports the expression of ISGylation-related genes, including PARP13's cofactor, TRIM25. PARP13 associates with TRIM25 via RNA-protein interactions, and we elucidate a transcriptome-wide periodicity of PARP13 binding around TRIM25. Taken together, our study implicates PARP13 in creating and maintaining a cellular environment poised for an antiviral response through limiting PARP13 translation, regulating access to distinct mRNA pools, and elevating ISGylation machinery expression.

RNA structure profiling at single-cell resolution reveals new determinants of cell identity

RNA structure is critical for multiple steps in gene regulation. However, how the structures of transcripts differ both within and between individual cells is unknown. Here we develop a SHAPE-inspired method called single-cell structure probing of RNA transcripts that enables simultaneous determination of transcript secondary structure and abundance at single-cell resolution. We apply single-cell structure probing of RNA transcripts to human embryonic stem cells and differentiating neurons. Remarkably, RNA structure is more homogeneous in human embryonic stem cells compared with neurons, with the greatest homogeneity found in coding regions. More extensive heterogeneity is found within 3' untranslated regions and is determined by specific RNA-binding proteins. Overall RNA structure profiles better discriminate cell type identity and differentiation stage than gene expression profiles alone. We further discover a cell-type variable region of 18S ribosomal RNA that is associated with cell cycle and translation control. Our method opens the door to the systematic characterization of RNA structure-function relationships at single-cell resolution.