Evidence map›Paper›PMID 39005366›Full record

ArticlebioRxiv : the preprint server for biology2024

A side-by-side comparison of variant function measurements using deep mutational scanning and base editing.

Ivan Sokirniy, Haider Inam, Marta Tomaszkiewicz, Joshua Reynolds, David McCandlish, Justin Pritchard

Abstract readPreprint
In one paragraph

Article in bioRxiv : the preprint server for biology, 2024. 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.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

6 authors.

Ivan SokirniyHuck Institute for the Life Sciences, University Park, PA 16802.ORCID 0000-0002-1846-5469
Haider InamHuck Institute for the Life Sciences, University Park, PA 16802.ORCID 0000-0003-3648-1857
Marta TomaszkiewiczHuck Institute for the Life Sciences, University Park, PA 16802.
Joshua ReynoldsHuck Institute for the Life Sciences, University Park, PA 16802.
David McCandlishSimons Center for Quantitative Biology, Cold Spring Harbor Laboratory, Cold Spring Harbor, NY 11724.ORCID 0009-0006-1474-0407
Justin PritchardHuck Institute for the Life Sciences, University Park, PA 16802.

Funding

Computational analysis of complex genetic interactionsR35GM133613 · NIGMS · COLD SPRING HARBOR LABORATORY · PI David Martin McCandlish · 2019 to 2026
$3.5M
Personalization and Failure Testing of Dual Switch Gene Drives in Lung CancerU01CA265709 · NCI · PENNSYLVANIA STATE UNIVERSITY, THE · PI PRITCHARD, JUSTIN · 2021 to 2025
$2.6M
Research Training in Physiological Adaptations to StressT32GM108563 · NIGMS · PENNSYLVANIA STATE UNIVERSITY, THE · PI CANTORNA, MARGHERITA T, KORZICK, DONNA HOPE · 2014 to 2023
$2.2M
NCI NIH HHS U01 CA265709NIGMS NIH HHS R35 GM133613NIGMS NIH HHS T32 GM108563
6 · The paper itself

Abstract

Variant annotation is a crucial objective in mammalian functional genomics. Deep Mutational Scanning (DMS) is a well-established method for annotating human gene variants, but CRISPR base editing (BE) is emerging as an alternative. However, questions remain about how well high-throughput base editing measurements can annotate variant function and the extent of downstream experimental validation required. This study presents the first direct comparison of DMS and BE in the same lab and cell line. Results indicate that focusing on the most likely edits and highest efficiency sgRNAs enhances the agreement between a "gold standard" DMS dataset and a BE screen. A simple filter for sgRNAs making single edits in their window could sufficiently annotate a large proportion of variants directly from sgRNA sequencing of large pools. When multi-edit guides are unavoidable, directly measuring the variants created in the pool, rather than sgRNA abundance, can recover high-quality variant annotation measurements in multiplexed pools. Taken together, our data show a surprising degree of correlation between base editor data and gold standard deep mutational scanning.

Identifiers

PMID39005366
PMCPMC11244880

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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.