Evidence map›Paper›PMID 25798935›Full record

ArticleNature biotechnology2015

Multiplexed tracking of combinatorial genomic mutations in engineered cell populations.

Ramsey I Zeitoun, Andrew D Garst, George D Degen, Gur Pines, Thomas J Mansell, Tirzah Y Glebes, Nanette R Boyle, Ryan T Gill

Abstract read
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In one paragraph

Article in Nature biotechnology, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.

0numbers the graph read from it
0cells of the map it votes in
16citing 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

16 citing papers in PubMed.

  1. Article
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  5. Review
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  9. Efficient Genome Editing ofFrontiers in microbiology · 2018
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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

8 authors.

Ramsey I ZeitounDepartment of Chemical and Biological Engineering, University of Colorado Boulder, Boulder, Colorado, USA.
Andrew D GarstDepartment of Chemical and Biological Engineering, University of Colorado Boulder, Boulder, Colorado, USA.
George D DegenDepartment of Chemical Engineering, Carnegie Mellon University, Pittsburgh, Pennsylvania, USA.
Gur PinesDepartment of Chemical and Biological Engineering, University of Colorado Boulder, Boulder, Colorado, USA.
Thomas J MansellDepartment of Chemical and Biological Engineering, University of Colorado Boulder, Boulder, Colorado, USA.ORCID 0000000188074570
Tirzah Y GlebesDepartment of Chemical and Biological Engineering, University of Colorado Boulder, Boulder, Colorado, USA.
Nanette R BoyleDepartment of Chemical and Biological Engineering, Colorado School of Mines, Golden, Colorado, USA.
Ryan T GillDepartment of Chemical and Biological Engineering, University of Colorado Boulder, Boulder, Colorado, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Multiplexed genome engineering approaches can be used to generate targeted genetic diversity in cell populations on laboratory timescales, but methods to track mutations and link them to phenotypes have been lacking. We present an approach for tracking combinatorial engineered libraries (TRACE) through the simultaneous mapping of millions of combinatorially engineered genomes at single-cell resolution. Distal genomic sites are assembled into individual DNA constructs that are compatible with next-generation sequencing strategies. We used TRACE to map growth selection dynamics for Escherichia coli combinatorial libraries created by recursive multiplex recombineering at a depth 10(4)-fold greater than before. TRACE was used to identify genotype-to-phenotype correlations and to map the evolutionary trajectory of two individual combinatorial mutants in E. coli. Combinatorial mutations in the human ES2 ovarian carcinoma cell line were also assessed with TRACE. TRACE completes the combinatorial engineering cycle and enables more sophisticated approaches to genome engineering in both bacteria and eukaryotic cells than are currently possible.

Indexed as

Genetic EngineeringGenetic VariationEscherichia coliGenetic Association StudiesGenome, BacterialGenomicsHigh-Throughput Nucleotide SequencingHumansMutationSingle-Cell Analysis

Identifiers

PMID25798935

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Registered trials

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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.