Evidence map›Paper›PMID 26080438›Full record

ArticleProceedings of the National Academy of Sciences of the United States of America2015

Next-generation libraries for robust RNA interference-based genome-wide screens.

Martin Kampmann, Max A Horlbeck, Yuwen Chen, Jordan C Tsai, Michael C Bassik, Luke A Gilbert, Jacqueline E Villalta, S Chul Kwon, Hyeshik Chang, V Narry Kim and 1 more

Abstract read
In one paragraph

Article in Proceedings of the National Academy of Sciences of the United States of America, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 60 papers.

0numbers the graph read from it
0cells of the map it votes in
60citing 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

60 citing papers in PubMed.

  1. Article
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  8. Frontiers in microbiology · 2024
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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

11 authors.

Martin KampmannDepartment of Cellular and Molecular Pharmacology, California Institute for Quantitative Biomedical Research, University of California, San Francisco, CA 94158; Howard Hughes Medical Institute, University of California, San Francisco, CA 94158; Martin.Kampmann@ucsf.edu jonathan.weissman@ucsf.edu.
Max A HorlbeckDepartment of Cellular and Molecular Pharmacology, California Institute for Quantitative Biomedical Research, University of California, San Francisco, CA 94158; Howard Hughes Medical Institute, University of California, San Francisco, CA 94158;
Yuwen ChenDepartment of Cellular and Molecular Pharmacology, California Institute for Quantitative Biomedical Research, University of California, San Francisco, CA 94158; Howard Hughes Medical Institute, University of California, San Francisco, CA 94158;
Jordan C TsaiDepartment of Cellular and Molecular Pharmacology, California Institute for Quantitative Biomedical Research, University of California, San Francisco, CA 94158; Howard Hughes Medical Institute, University of California, San Francisco, CA 94158;
Michael C BassikDepartment of Cellular and Molecular Pharmacology, California Institute for Quantitative Biomedical Research, University of California, San Francisco, CA 94158; Howard Hughes Medical Institute, University of California, San Francisco, CA 94158;
Luke A GilbertDepartment of Cellular and Molecular Pharmacology, California Institute for Quantitative Biomedical Research, University of California, San Francisco, CA 94158; Howard Hughes Medical Institute, University of California, San Francisco, CA 94158;
Jacqueline E VillaltaDepartment of Cellular and Molecular Pharmacology, California Institute for Quantitative Biomedical Research, University of California, San Francisco, CA 94158; Howard Hughes Medical Institute, University of California, San Francisco, CA 94158;
S Chul KwonCenter for RNA Research, Institute for Basic Science, Seoul 151-742, South Korea; School of Biological Sciences, Seoul National University, Seoul 151-742, South Korea.
Hyeshik ChangCenter for RNA Research, Institute for Basic Science, Seoul 151-742, South Korea; School of Biological Sciences, Seoul National University, Seoul 151-742, South Korea.
V Narry KimCenter for RNA Research, Institute for Basic Science, Seoul 151-742, South Korea; School of Biological Sciences, Seoul National University, Seoul 151-742, South Korea.
Jonathan S WeissmanDepartment of Cellular and Molecular Pharmacology, California Institute for Quantitative Biomedical Research, University of California, San Francisco, CA 94158; Howard Hughes Medical Institute, University of California, San Francisco, CA 94158; Martin.Kampmann@ucsf.edu jonathan.weissman@ucsf.edu.

Funding

SYNTHETIC AND RECOMBINANT PRP PEPTIDES AND PROTEINSP01AG010770 · NIA · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI PRUSINER, STANLEY B · 1993 to 2015
$30.3M
MEDICAL SCIENTIST TRAINING PROGRAMT32GM007618 · NIGMS · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI ANDERSON, MARK S · 1985 to 2020
$29.6M
STRUCTURAL BIOLOGY TRAINING PROGRAMT32GM008284 · NIGMS · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI KORTEMME, TANJA · 1988 to 2022
$10.1M
Bay Area Cancer Target Discovery and Development NetworkU01CA168370 · NCI · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI MCCORMICK, FRANK PATRICK, MCMANUS, MICHAEL T · 2012 to 2016
$3.9M
Integrative Program in Complex Biological System (ipCBS)T32EB009383 · NIBIB · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI MARSHALL, WALLACE, WEINER, ORION D · 2009 to 2022
$3.2M
Accelerating drug development and repurposing using systematic genetic interactioDP2HD084069 · NICHD · STANFORD UNIVERSITY · PI BASSIK, MICHAEL C · 2014 to 2014
$2.4M
Stress response networks in cancer: systematic mapping and therapeutic potentialR00CA181494 · NCI · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI KAMPMANN, MARTIN · 2015 to 2017
$747k
Stress response networks in cancer: systematic mapping and therapeutic potentialK99CA181494 · NCI · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI KAMPMANN, MARTIN · 2014 to 2014
$139k
Howard Hughes Medical InstituteNCI NIH HHS K99 CA181494NCI NIH HHS R00 CA181494NCI NIH HHS U01 CA168370NIA NIH HHS P01 AG010770NIBIB NIH HHS T32 EB009383NICHD NIH HHS DP2 HD084069NIGMS NIH HHS T32 GM007618NIGMS NIH HHS T32 GM008284
6 · The paper itself

Abstract

Genetic screening based on loss-of-function phenotypes is a powerful discovery tool in biology. Although the recent development of clustered regularly interspaced short palindromic repeats (CRISPR)-based screening approaches in mammalian cell culture has enormous potential, RNA interference (RNAi)-based screening remains the method of choice in several biological contexts. We previously demonstrated that ultracomplex pooled short-hairpin RNA (shRNA) libraries can largely overcome the problem of RNAi off-target effects in genome-wide screens. Here, we systematically optimize several aspects of our shRNA library, including the promoter and microRNA context for shRNA expression, selection of guide strands, and features relevant for postscreen sample preparation for deep sequencing. We present next-generation high-complexity libraries targeting human and mouse protein-coding genes, which we grouped into 12 sublibraries based on biological function. A pilot screen suggests that our next-generation RNAi library performs comparably to current CRISPR interference (CRISPRi)-based approaches and can yield complementary results with high sensitivity and high specificity.

Indexed as

GenomeRNA InterferenceAnimalsArtificial IntelligenceHumansMiceRNA, Small InterferingRNA, Small Interferingfunctional genomicsgenetic screenmicroRNApooled screenshRNA

Identifiers

PMID26080438
PMCPMC4491794

What OpenQuestion holds

Textmetadata
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.