Mapping specificity landscapes of RNA-protein interactions by high throughput sequencing

Jankowsky, Eckhard; Harris, Michael E.

doi:10.1016/j.ymeth.2017.03.002

Cited by 11 publications

(22 citation statements)

References 31 publications

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“…The approach is conceptually related to the RNAcompete (Ray et al, ; Ray et al, ) and the RNA bind‐n‐seq methods (Dominguez et al, ; Lambert et al, ), although these techniques do not assess the kinetics of RNA protein interactions. For HiTS‐Kin, RNAs with 7 to 8 randomized nucleotides can currently be used, limited by the sequencing depth (Guenther et al, ; Jankowsky & Harris, ). Bound or processed RNAs are separated from the unbound, or unprocessed RNA species.…”

Section: Approaches To Measure the Kinetics Of Rna–protein Interactionsmentioning

confidence: 99%

“…The RNA pool is measured over several time points, which provides the kinetic parameters for all substrate variants. Depending on the reaction setup, obtained kinetic parameters reflect binding kinetics or other reaction steps (Jankowsky & Harris, ).…”

Section: Approaches To Measure the Kinetics Of Rna–protein Interactionsmentioning

confidence: 99%

“…Because HiTS‐Kin interrogates the entire sequence space of an RNA pool, sophisticated kinetic specificity models can be developed (Jankowsky & Harris, ; Jankowsky & Harris, ; Niland, Anderson, Jankowsky, & Harris, ). Most current specificity models for RNA–protein interactions are based on equilibrium binding and Position Weight Matrices (PWMs), which assume independent contributions of each nucleotide position to the free binding energy (Guenther et al, ; Zhao & Stormo, ).…”

Section: Approaches To Measure the Kinetics Of Rna–protein Interactionsmentioning

confidence: 99%

“…HiTS‐Kin has been applied to several RNA interacting proteins, including C5 from E.coli and RNase H (Kielpinski, Hagedorn, Lindow, & Vinther, ; Lin et al, ). Detailed methodological aspects of the HiTS‐Kin technique have been recently described (Jankowsky & Harris, ). HiTS‐Kin and the corresponding equilibrium technique HiTS‐Eq (High Throughput Equilibrium Binding) can be combined to characterize kinetic landscapes spanning several reaction steps for all sequence variants of a given RNA pool (Jain, Lin, Morgan, Harris, & Tolbert, ; Lin et al, ).…”

Section: Approaches To Measure the Kinetics Of Rna–protein Interactionsmentioning

confidence: 99%

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Approaches for measuring the dynamics of RNA–protein interactions

Licatalosi

Jankowsky

2019

WIREs RNA

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RNA-protein interactions are pivotal for the regulation of gene expression from bacteria to human. RNA-protein interactions are dynamic; they change over biologically relevant timescales. Understanding the regulation of gene expression at the RNA level therefore requires knowledge of the dynamics of RNA-protein interactions. Here, we discuss the main experimental approaches to measure dynamic aspects of RNA-protein interactions. We cover techniques that assess dynamics of cellular RNA-protein interactions that accompany biological processes over timescales of hours or longer and techniques measuring the kinetic dynamics of RNA-protein interactions in vitro.

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Section: Approaches To Measure the Kinetics Of Rna–protein Interactionsmentioning

confidence: 99%

Section: Approaches To Measure the Kinetics Of Rna–protein Interactionsmentioning

confidence: 99%

Section: Approaches To Measure the Kinetics Of Rna–protein Interactionsmentioning

confidence: 99%

Section: Approaches To Measure the Kinetics Of Rna–protein Interactionsmentioning

confidence: 99%

See 2 more Smart Citations

Approaches for measuring the dynamics of RNA–protein interactions

Licatalosi

Jankowsky

2019

WIREs RNA

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“…The above limitations and the importance of regulation by RBPs have sparked a growing interest in developing direct, quantitative genomic-scale approaches for measuring RBP/RNA interactions and affinities. Methods such as MITOMI, HiTS-EQ, HiTS-RAP, RNA Bind-N-Seq and RNA-MaP can provide equilibrium binding constants or apparent affinities Jain et al, 2017;Jankowsky and Harris, 2017;Lambert et al, 2014;Martin et al, 2012;Tome et al, 2014). Of these, RNA-MaP and HiTS-RAP, two related techniques that utilize a v8.0 4 modified sequencing platform and an array of ~10 5 unique immobilized RNA species, eliminate an intermediate capture step that can alter binding occupancies, thereby allowing highly accurate thermodynamic and kinetic binding measurements via fluorescence readout Tome et al, 2014)& vide infra).…”

Section: Introductionmentioning

confidence: 99%

A quantitative and predictive model for RNA binding by human Pumilio proteins

Jarmoskaite

Denny

Vaidyanathan

et al. 2018

Preprint

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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. v8.0 3 Results Library designStarting with the PUM2 consensus motif, which has been determined by pull-down, crosslinking and in vitro selection experiments ( Figures 1A, S1A), we designed an oligonucleotide v8.0 5 library to systematically address the factors that determine binding specificity ( Figure S1B). To control for structural and context effects, each sequence variant was embedded in two to four scaffolds ( Figure 1B). We systematically varied the sequence of the PUM2 binding site and the flanking sequence ( Figure S1B). We also included insertions to test the potential for noncontiguous binding sites and variants of sequence motifs of related PUF proteins to provide additional sequence variation for testing PUM2 binding models ( Figure S1B). Massively parallel measurements of PUM2 binding affinitiesUsing RNA-MaP, we determined PUM2 protein binding affinities for >20,000 distinct RNAs and we report on >5000 herein; sequences designed to address distinct questions will be reported separately. The DNA library was sequenced on an Illumina MiSeq flow cell, followed by in situ transcription in a custom-built imaging and fluidics setup ( Figure 1C; ). The RNA transcripts were immobilized by stalling the RNA polymerase at the end of the DNA template, and RNA-protein association was measured by equilibrating the RNA with increasing concentrations of fluorescently labeled protein and imaging binding to each cluster (comprising ~1000 copies of an RNA variant) (Buenrostro et al., 2014)( Figure 1C). The resulting binding curves were used to obtain the dissociation constant (KD) and the corresponding ∆G value (= RTlnKD) of the protein for each RNA variant.

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