Evidence map›Paper›PMID 38352467›Full record

ArticlebioRxiv : the preprint server for biology2024

Dissecting quantitative trait nucleotides by saturation genome editing.

Kevin R Roy, Justin D Smith, Shengdi Li, Sibylle C Vonesch, Michelle Nguyen, Wallace T Burnett, Kevin M Orsley, Cheng-Sheng Lee, James E Haber, Robert P St Onge and 1 more

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

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

11 authors.

Kevin R RoyStanford Genome Technology Center, Stanford University, Palo Alto, California, USA.ORCID 0000-0001-8799-6207
Justin D SmithStanford Genome Technology Center, Stanford University, Palo Alto, California, USA.ORCID 0000-0003-3079-3534
Shengdi LiEuropean Molecular Biology Laboratory (EMBL), Genome Biology Unit, Heidelberg, Germany.ORCID 0000-0001-8993-3525
Sibylle C VoneschEuropean Molecular Biology Laboratory (EMBL), Genome Biology Unit, Heidelberg, Germany.ORCID 0000-0003-2485-1048
Michelle NguyenStanford Genome Technology Center, Stanford University, Palo Alto, California, USA.
Wallace T BurnettStanford Genome Technology Center, Stanford University, Palo Alto, California, USA.ORCID 0000-0001-6932-9347
Kevin M OrsleyStanford Genome Technology Center, Stanford University, Palo Alto, California, USA.
Cheng-Sheng LeeBrandeis University, Rosenstiel Basic Medical Sciences Research Center and Department of Biology, Waltham, MA.ORCID 0000-0002-0765-2410
James E HaberBrandeis University, Rosenstiel Basic Medical Sciences Research Center and Department of Biology, Waltham, MA.ORCID 0000-0002-1878-0610
Robert P St OngeStanford Genome Technology Center, Stanford University, Palo Alto, California, USA.ORCID 0000-0003-1626-3107
Lars M SteinmetzStanford Genome Technology Center, Stanford University, Palo Alto, California, USA.ORCID 0000-0002-3962-2865

Funding

Capturing the phenotypic landscape of single-nucleotide variation via systematic genome editingR01GM121932 · NIGMS · STANFORD UNIVERSITY · PI STEINMETZ, LARS M · 2017 to 2021
$3.4M
EDGE CMT: Dissecting complex traits in wild isolates of yeast by high-throughput genome editingR01HG012446 · NHGRI · STANFORD UNIVERSITY · PI STEINMETZ, LARS M · 2022 to 2025
$2.0M
NHGRI NIH HHS R01 HG012446NIGMS NIH HHS R01 GM121932
6 · The paper itself

Abstract

Genome editing technologies have the potential to transform our understanding of how genetic variation gives rise to complex traits through the systematic engineering and phenotypic characterization of genetic variants. However, there has yet to be a system with sufficient efficiency, fidelity, and throughput to comprehensively identify causal variants at the genome scale. Here we explored the ability of templated CRISPR editing systems to install natural variants genome-wide in budding yeast. We optimized several approaches to enhance homology-directed repair (HDR) with donor DNA templates, including donor recruitment to target sites, single-stranded donor production by bacterial retrons, and in vivo plasmid assembly. We uncovered unique advantages of each system that we integrated into a single superior system named MAGESTIC 3.0. We used MAGESTIC 3.0 to dissect causal variants residing in 112 quantitative trait loci across 32 environmental conditions, revealing an enrichment for missense variants and loci with multiple causal variants. MAGESTIC 3.0 will facilitate the functional analysis of the genome at single-nucleotide resolution and provides a roadmap for improving template-based genome editing systems in other organisms.

Indexed as

barcode sequencing (Bar-seq)complex traitsCRISPR genome editingDNA repairdonor DNAdonor recruitmentforkhead-associated (FHA) domainhomology-directed repair (HDR)MS2 coat protein (MCP)plasmid assemblyquantitative geneticsquantitative trait lociretron

Identifiers

PMID38352467
PMCPMC10862795

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.