Evidence map›Paper›PMID 30245013›Full record

ArticleCell2018

Functional Genetic Variants Revealed by Massively Parallel Precise Genome Editing.

Eilon Sharon, Shi-An A Chen, Neil M Khosla, Justin D Smith, Jonathan K Pritchard, Hunter B Fraser

Abstract read
In one paragraph

Article in Cell, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 144 papers.

0numbers the graph read from it
0cells of the map it votes in
144citing 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

144 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. Review
  11. Article
  12. Article
  13. Article
  14. Article
  15. Review
  16. Article
  17. Article
  18. Article
  19. Article
  20. Article

84 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

6 authors.

Eilon SharonDepartment of Biology, Stanford University, Stanford, CA 94305, USA; Department of Genetics, Stanford University, Stanford, CA 94305, USA; Howard Hughes Medical Institute, Stanford University, Stanford, CA 94305, USA. Electronic address: eilon@stanford.edu.
Shi-An A ChenDepartment of Biology, Stanford University, Stanford, CA 94305, USA.
Neil M KhoslaDepartment of Biology, Stanford University, Stanford, CA 94305, USA.
Justin D SmithDepartment of Genetics, Stanford University, Stanford, CA 94305, USA.
Jonathan K PritchardDepartment of Biology, Stanford University, Stanford, CA 94305, USA; Department of Genetics, Stanford University, Stanford, CA 94305, USA; Howard Hughes Medical Institute, Stanford University, Stanford, CA 94305, USA.
Hunter B FraserDepartment of Biology, Stanford University, Stanford, CA 94305, USA. Electronic address: hbfraser@stanford.edu.

Funding

Supplement to Enhance Wellness and Resiliency in the Graduate EnvironmentT32GM007276 · NIGMS · STANFORD UNIVERSITY · PI MORRISON, ASHBY J. · 1985 to 2023
$32.9M
Yeast as a model for understanding gene expression adaptationR01GM097171 · NIGMS · STANFORD UNIVERSITY · PI FRASER, HUNTER B · 2012 to 2024
$4.2M
Howard Hughes Medical InstituteNIGMS NIH HHS R01 GM097171NIGMS NIH HHS T32 GM007276
6 · The paper itself

Abstract

A major challenge in genetics is to identify genetic variants driving natural phenotypic variation. However, current methods of genetic mapping have limited resolution. To address this challenge, we developed a CRISPR-Cas9-based high-throughput genome editing approach that can introduce thousands of specific genetic variants in a single experiment. This enabled us to study the fitness consequences of 16,006 natural genetic variants in yeast. We identified 572 variants with significant fitness differences in glucose media; these are highly enriched in promoters, particularly in transcription factor binding sites, while only 19.2% affect amino acid sequences. Strikingly, nearby variants nearly always favor the same parent's alleles, suggesting that lineage-specific selection is often driven by multiple clustered variants. In sum, our genome editing approach reveals the genetic architecture of fitness variation at single-base resolution and could be adapted to measure the effects of genome-wide genetic variation in any screen for cell survival or cell-sortable markers.

Indexed as

Chromosome MappingClustered Regularly Interspaced Short Palindromic RepeatsCRISPR-Cas SystemsGene EditingGenetic VariationGenetic VectorsGenomeHigh-Throughput Nucleotide SequencingSaccharomyces cerevisiaeYeastsCas9CRISPRevolutionfitnessgenetic variationgenome editingQTLyeast

Identifiers

PMID30245013
PMCPMC6563827

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.