Evidence map›Paper›PMID 37732177›Full record

ArticlemedRxiv : the preprint server for health sciences2023

Joint genotypic and phenotypic outcome modeling improves base editing variant effect quantification.

Jayoung Ryu, Sam Barkal, Tian Yu, Martin Jankowiak, Yunzhuo Zhou, Matthew Francoeur, Quang Vinh Phan, Zhijian Li, Manuel Tognon, Lara Brown and 6 more

Open access · greenAbstract readPreprint
PubMed Full text at PMC Publisher
In one paragraph

Article in medRxiv : the preprint server for health sciences, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
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

0 citing papers in PubMed, 4 citations in OpenAlex.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

16 authors at 5 institutions in 4 countries.

Jayoung RyuMolecular Pathology Unit, Center for Cancer Research, Massachusetts General Hospital, Boston, MA, USA.
Sam BarkalDivision of Genetics, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA.
Tian YuDivision of Genetics, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA.
Martin JankowiakBroad Institute of Harvard and MIT, Cambridge, MA, USA.
Yunzhuo ZhouSchool of Chemistry and Molecular Biosciences, The University of Queensland, Brisbane, Australia.
Matthew FrancoeurDivision of Genetics, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA.
Quang Vinh PhanDivision of Genetics, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA.
Zhijian LiMolecular Pathology Unit, Center for Cancer Research, Massachusetts General Hospital, Boston, MA, USA.
Manuel TognonMolecular Pathology Unit, Center for Cancer Research, Massachusetts General Hospital, Boston, MA, USA.
Lara BrownDivision of Genetics, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA.
Michael I LoveDepartment of Genetics, Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, NC.
Guillaume LettreMontreal Heart Institute, Montréal, QC H1T 1C8, Canada.
David B AscherSchool of Chemistry and Molecular Biosciences, The University of Queensland, Brisbane, Australia.
Christopher A CassaDivision of Genetics, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA.
Richard I SherwoodDivision of Genetics, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA.
Luca PinelloMolecular Pathology Unit, Center for Cancer Research, Massachusetts General Hospital, Boston, MA, USA.
Brigham and Women's Hospital · USBroad Institute · USBaker Heart and Diabetes Institute · AUMontreal Heart Institute · CAUniversity of North Carolina at Chapel Hill · US

Funding

Comprehensive characterization of variants underlying heart and blood diseases with CRISPR base editingUM1HG012010 · NHGRI · MASSACHUSETTS GENERAL HOSPITAL · PI Daniel Evan Bauer, Luca Pinello · 2021 to 2026
$10.4M
Integrated pathogenicity assessment of clinically actionable genetic variantsR01HG010372 · NHGRI · BRIGHAM AND WOMEN'S HOSPITAL · PI CASSA, CHRISTOPHER · 2018 to 2022
$3.5M
High-throughput investigation of human genetic variants affecting cholesterol uptake and effluxR01HL164409 · NHLBI · BRIGHAM AND WOMEN'S HOSPITAL · PI SHERWOOD, RICHARD I · 2022 to 2025
$3.1M
Multiscale exploration of the functional non-coding genomeR35HG010717 · NHGRI · MASSACHUSETTS GENERAL HOSPITAL · PI PINELLO, LUCA · 2019 to 2023
$2.6M
Development of potent and predictable Cas9 gene activation tools through high-throughput screeningR01GM143249 · NIGMS · BRIGHAM AND WOMEN'S HOSPITAL · PI SHERWOOD, RICHARD I · 2022 to 2024
$1.3M
NHGRI NIH HHS R01 HG010372NHGRI NIH HHS R35 HG010717NHGRI NIH HHS UM1 HG012010NHLBI NIH HHS R01 HL164409NIGMS NIH HHS R01 GM143249
6 · The paper itself

Abstract

CRISPR base editing screens are powerful tools for studying disease-associated variants at scale. However, the efficiency and precision of base editing perturbations vary, confounding the assessment of variant-induced phenotypic effects. Here, we provide an integrated pipeline that improves the estimation of variant impact in base editing screens. We perform high-throughput ABE8e-SpRY base editing screens with an integrated reporter construct to measure the editing efficiency and outcomes of each gRNA alongside their phenotypic consequences. We introduce BEAN, a Bayesian network that accounts for per-guide editing outcomes and target site chromatin accessibility to estimate variant impacts. We show this pipeline attains superior performance compared to existing tools in variant classification and effect size quantification. We use BEAN to pinpoint common variants that alter LDL uptake, implicating novel genes. Additionally, through saturation base editing of

Identifiers

PMID37732177
PMCPMC10508837
OpenAlexW4386587299

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.