ABSTRACT
Primary microRNAs (miRNAs) are the precursors of miRNAs that modulate the expression of most mRNAs in humans. They fold up into a hairpin structure that is cleaved at its base by an enzyme complex known as the Microprocessor (Drosha/DGCR8). While many of the molecular details are known, a complete understanding of what features distinguish primary miRNA from hairpin structures in other transcripts is still lacking. We develop a massively parallel functional assay termed Dro-seq (Drosha sequencing) that enables testing of hundreds of known primary miRNA substrates and thousands of single-nucleotide variants. We find an additional feature of primary miRNAs, called Shannon entropy, describing the structural ensemble important for processing. In a deep mutagenesis experiment, we observe particular apical loop U bases, likely recognized by DGCR8, are important for efficient processing. These findings build on existing knowledge about primary miRNA maturation by the Microprocessor and further explore the substrate RNA sequence-structure relationship.
Subject(s)
MicroRNAs , Multiprotein Complexes , Nucleic Acid Conformation , RNA Processing, Post-Transcriptional , RNA-Binding Proteins , Ribonuclease III , Animals , Humans , MicroRNAs/chemistry , MicroRNAs/genetics , MicroRNAs/metabolism , Multiprotein Complexes/chemistry , Multiprotein Complexes/metabolism , RNA-Binding Proteins/chemistry , RNA-Binding Proteins/metabolism , Ribonuclease III/chemistry , Ribonuclease III/metabolism , Sf9 Cells , SpodopteraABSTRACT
High-throughput methodologies have enabled routine generation of RNA target sets and sequence motifs for RNA-binding proteins (RBPs). Nevertheless, quantitative approaches are needed to capture the landscape of RNA-RBP interactions responsible for cellular regulation. We have used the RNA-MaP platform to directly measure equilibrium binding for thousands of designed RNAs and to construct a predictive model for RNA recognition by the human Pumilio proteins PUM1 and PUM2. Despite prior findings of linear sequence motifs, our measurements revealed widespread residue flipping and instances of positional coupling. Application of our thermodynamic model to published in vivo crosslinking data reveals quantitative agreement between predicted affinities and in vivo occupancies. Our analyses suggest a thermodynamically driven, continuous Pumilio-binding landscape that is negligibly affected by RNA structure or kinetic factors, such as displacement by ribosomes. This work provides a quantitative foundation for dissecting the cellular behavior of RBPs and cellular features that impact their occupancies.
