Evidence map›Paper›PMID 31078383›Full record

ArticleMolecular cell2019

A Quantitative and Predictive Model for RNA Binding by Human Pumilio Proteins.

Inga Jarmoskaite, Sarah K Denny, Pavanapuresan P Vaidyanathan, Winston R Becker, Johan O L Andreasson, Curtis J Layton, Kalli Kappel, Varun Shivashankar, Raashi Sreenivasan, Rhiju Das and 2 more

Open access · bronzeAbstract read
In one paragraph

Article in Molecular cell, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 44 papers.

0numbers the graph read from it
0cells of the map it votes in
44citing papers in PubMed
3.8field-weighted citation impact, top 6% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

44 citing papers in PubMed, 96 citations in OpenAlex.

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  14. FRET-guided modeling of nucleic acids.Nucleic acids research · 2024
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

12 authors at 3 institutions in 1 country.

Inga JarmoskaiteDepartment of Biochemistry, Stanford University School of Medicine, Stanford, CA 94305, USA.
Sarah K DennyBiophysics Program, Stanford University School of Medicine, Stanford, CA 94305, USA; Scribe Therapeutics, Berkeley, CA, 94704, USA.
Pavanapuresan P VaidyanathanDepartment of Biochemistry, Stanford University School of Medicine, Stanford, CA 94305, USA.
Winston R BeckerBiophysics Program, Stanford University School of Medicine, Stanford, CA 94305, USA.
Johan O L AndreassonDepartment of Genetics, Stanford University School of Medicine, Stanford, CA 94305, USA.
Curtis J LaytonDepartment of Genetics, Stanford University School of Medicine, Stanford, CA 94305, USA.
Kalli KappelBiophysics Program, Stanford University School of Medicine, Stanford, CA 94305, USA.
Varun ShivashankarNovartis Institutes for BioMedical Research, Cambridge, MA 02139, USA.
Raashi SreenivasanDepartment of Biochemistry, Stanford University School of Medicine, Stanford, CA 94305, USA.
Rhiju DasDepartment of Biochemistry, Stanford University School of Medicine, Stanford, CA 94305, USA.
William J GreenleafDepartment of Genetics, Stanford University School of Medicine, Stanford, CA 94305, USA; Department of Applied Physics, Stanford University, Stanford, CA 94305, USA; Chan Zuckerberg Biohub, San Francisco, CA 94158, USA. Electronic address: wjg@stanford.edu.
Daniel HerschlagDepartment of Biochemistry, Stanford University School of Medicine, Stanford, CA 94305, USA; Department of Chemistry, Stanford University, Stanford, CA 94305, USA; Department of Chemical Engineering, Stanford University, Stanford, CA 94305, USA; ChEM-H Institute, Stanford University, Stanford, CA 94305, USA. Electronic address: herschla@stanford.edu.
Stanford University · USChan Zuckerberg Initiative (United States) · USNovartis (United States) · US

Funding

Time-resolved small angle X-ray scatteringP01GM066275 · NIGMS · STANFORD UNIVERSITY · PI HERSCHLAG, DANIEL · 2003 to 2017
$17.8M
Next-generation computational/chemical methods for complex RNA structuresR35GM122579 · NIGMS · STANFORD UNIVERSITY · PI Rhiju Das · 2017 to 2026
$7.2M
High-resolution modeling of protein-RNA interfacesR01GM121487 · NIGMS · FRED HUTCHINSON CANCER RESEARCH CENTER · PI BRADLEY, PHILIP · 2017 to 2020
$1.7M
Quantitative high-throughput nucleic acid assays on a sequencing chipR01GM111990 · NIGMS · STANFORD UNIVERSITY · PI GREENLEAF, WILLIAM JAMES · 2014 to 2018
$1.5M
NIGMS NIH HHS P01 GM066275NIGMS NIH HHS R01 GM111990NIGMS NIH HHS R01 GM121487NIGMS NIH HHS R35 GM122579
6 · The paper itself

Abstract

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.

Indexed as

Nucleic Acid ConformationAmino Acid SequenceHumansKineticsProtein BindingRibosomesRNA-Binding ProteinsRNA, MessengerPUM1 protein, humanPUM2 protein, humanRNA-Binding ProteinsRNA, MessengereCLIPhigh-throughput biophysicspost-transcriptional regulationPUF proteinsPumilioRNA binding proteinsthermodynamics

Identifiers

PMID31078383
PMCPMC6645366
OpenAlexW2949207210

What OpenQuestion holds

Textmetadata
LicenceTDM
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.