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Hagler, L. D.

Publications and source records attributed to Hagler, L. D..

2 recordsLinked to original sources

Structural probing of RNA hairpins quantifies protein occupancy on RNA and links it to function in human cells

RNA structures that form inside living cells influence processes ranging from translation to RNA decay, many of which are controlled by RNA-binding proteins (RBPs). Because RBP specificity depends on both local RNA structure and sequence motifs, traditional pulldown-based methods often obscure the structural context of bound RNAs. Here, a quantitative framework based on dimethyl sulfate mutational profiling and sequencing (DMS-MaPseq) is introduced that jointly measures RNA structure and protein binding at single-nucleotide resolution in human cells, enabling estimation of effective RNA-protein affinities and fractional occupancy directly in cells. Application of this approach to a 1,600-member library of MS2 hairpin mutants reveals that RNA folding is the strongest determinant of MS2 coat protein (MCP) recognition, and that stable MS2 structures must form for MCP to bind its target sequence. MCP also shows strong preference for its consensus loop sequence while displaying minimal dependence on stem length beyond ten base pairs or on stem GC content. Incorporation of an inducible degron fused to MCP allows precise tuning of intracellular protein concentrations analogous to those of many endogenous RBPs and show that DMS reactivity changes can be used to infer binding specificities across a subsaturating regime. A quantitative occupancy framework further shows that inferred fraction-bound values accurately predict how efficiently MCP fused to a downregulatory-domain drives RNA degradation. Together, these results establish a generalizable approach for measuring RBP-RNA affinities with structural resolution in living cells, dissecting how sequence and structure contribute to RBP recognition, and quantitatively linking occupancy to functional output.

biochemistry↗

SEISMICgraph: a web-based tool for RNA structure data visualization

In recent years, RNA has been increasingly recognized for its essential roles in biology, functioning not only as a carrier of genetic information but also as a dynamic regulator of gene expression through its interactions with other RNAs, proteins, and itself. Advances in chemical probing techniques have significantly enhanced our ability to identify RNA secondary structures and understand their regulatory roles. These developments, alongside improvements in experimental design and data processing, have greatly increased the resolution and throughput of structural analyses. Here, we introduce SEISMICgraph, a web-based tool designed to support RNA structure research by offering data visualization and analysis capabilities for a variety of chemical probing modalities. SEISMICgraph enables simultaneous comparison of data across different sequences and experimental conditions through a user-friendly interface that requires no programming expertise. We demonstrate its utility by investigating known and putative riboswitches and exploring how RNA modifications influence their structure and binding. SEISMICgraphs ability to rapidly visualize adenine-dependent structural changes and assess the impact of pseudouridylation on these transitions provides novel insights and establishes a roadmap for numerous future applications. GRAPHICAL ABSTRACT O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=80 SRC="FIGDIR/small/615187v1_ufig1.gif" ALT="Figure 1"> View larger version (21K): org.highwire.dtl.DTLVardef@1fac718org.highwire.dtl.DTLVardef@1252f03org.highwire.dtl.DTLVardef@31968dorg.highwire.dtl.DTLVardef@1930c4f_HPS_FORMAT_FIGEXP M_FIG C_FIG

molecular biology↗