Evidence map›Paper›PMID 30782640›Full record

ArticleGenome research2019

Improved discovery of genetic interactions using CRISPRiSeq across multiple environments.

Mia Jaffe, Adam Dziulko, Justin D Smith, Robert P St Onge, Sasha F Levy, Gavin Sherlock

Abstract read
In one paragraph

Article in Genome research, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers.

0numbers the graph read from it
0cells of the map it votes in
22citing 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

22 citing papers in PubMed.

  1. Article
  2. Review
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
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  9. Article
  10. Review
  11. Article
  12. High-content CRISPR screening.Nature reviews. Methods primers · 2022
    Article
  13. Article
  14. Article
  15. Review
  16. Article
  17. Article
  18. Article
  19. Article
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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

6 authors.

Mia JaffeDepartment of Genetics, Stanford University School of Medicine, Stanford, California 94305, USA.ORCID 0000-0002-0836-2458
Adam DziulkoJoint Initiative for Metrology in Biology, Stanford, California 94305, USA.
Justin D SmithStanford Genome Technology Center, Stanford University, Palo Alto, California 94305, USA.ORCID 0000-0003-3079-3534
Robert P St OngeStanford Genome Technology Center, Stanford University, Palo Alto, California 94305, USA.ORCID 0000-0003-1626-3107
Sasha F LevyDepartment of Genetics, Stanford University School of Medicine, Stanford, California 94305, USA.ORCID 0000-0002-0923-1636
Gavin SherlockDepartment of Genetics, Stanford University School of Medicine, Stanford, California 94305, USA.ORCID 0000-0002-1692-4983

Funding

WHOLE YEAST GENOME TRANSCRIPTIONAL AND FUNCTIONAL GENE MAPS--A FEASIBILITY STUDYP01HG000205 · NHGRI · STANFORD UNIVERSITY · PI DAVIS, RONALD WAYNE, HOWE, ROGER THOMAS · 1990 to 2016
$120.9M
Translational Oncology Research Program (Project-005)P30CA124435 · NCI · STANFORD UNIVERSITY · PI Vittorio Sebastiano · 2007 to 2026
$71.4M
INSTITUTIONAL TRAINING GRANT IN GENOME SCIENCET32HG000044 · NHGRI · STANFORD UNIVERSITY · PI MICHAEL P. SNYDER · 1995 to 2026
$32.2M
Genomic and synthetic biology tools for expressing natural product gene clustersU01GM110706 · NIGMS · STANFORD UNIVERSITY · PI DAVIS, RONALD WAYNE, STEINMETZ, LARS M · 2014 to 2018
$10.9M
Systematic Molecular Analysis of Antagonistic PleiotropyR01GM110275 · NIGMS · STANFORD UNIVERSITY · PI SHERLOCK, GAVIN J · 2014 to 2017
$1.6M
PPiSeq: High-Throughput Protein-Protein Interaction SequencingR01HG008354 · NHGRI · STATE UNIVERSITY NEW YORK STONY BROOK · PI LEVY, SASHA F · 2015 to 2018
$1.5M
High-throughput genetic interaction sequencing in mammalian cellsR21HG009255 · NHGRI · STATE UNIVERSITY NEW YORK STONY BROOK · PI LEVY, SASHA F, POWERS, SCOTT · 2016 to 2017
$399k
NCI NIH HHS P30 CA124435NHGRI NIH HHS P01 HG000205NHGRI NIH HHS R01 HG008354NHGRI NIH HHS R21 HG009255NHGRI NIH HHS T32 HG000044NIGMS NIH HHS R01 GM110275NIGMS NIH HHS U01 GM110706
6 · The paper itself

Abstract

Large-scale genetic interaction (GI) screens in yeast have been invaluable for our understanding of molecular systems biology and for characterizing novel gene function. Owing in part to the high costs and long experiment times required, a preponderance of GI data has been generated in a single environmental condition. However, an unknown fraction of GIs may be specific to other conditions. Here, we developed a pooled-growth CRISPRi-based sequencing assay for GIs, CRISPRiSeq, which increases throughput such that GIs can be easily assayed across multiple growth conditions. We assayed the fitness of approximately 17,000 strains encompassing approximately 7700 pairwise interactions in five conditions and found that the additional conditions increased the number of GIs detected nearly threefold over the number detected in rich media alone. In addition, we found that condition-specific GIs are prevalent and improved the power to functionally classify genes. Finally, we found new links during respiratory growth between members of the Ras nutrient-sensing pathway and both the COG complex and a gene of unknown function. Our results highlight the potential of conditional GI screens to improve our understanding of cellular genetic networks.

Indexed as

Clustered Regularly Interspaced Short Palindromic RepeatsEnvironmentEpistasis, GeneticGene Regulatory NetworksGenetic TechniquesGenes, FungalSaccharomyces cerevisiaeSequence Analysis, DNA

Identifiers

PMID30782640
PMCPMC6442382

What OpenQuestion holds

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LicenceCC BY
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.