Evidence map›Paper›PMID 32877448›Full record

ArticlePloS one2020

Enabling one-pot Golden Gate assemblies of unprecedented complexity using data-optimized assembly design.

John M Pryor, Vladimir Potapov, Rebecca B Kucera, Katharina Bilotti, Eric J Cantor, Gregory J S Lohman

Open access · goldAbstract read
In one paragraph

Article in PloS one, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 61 papers.

0numbers the graph read from it
0cells of the map it votes in
61citing papers in PubMed
3.9field-weighted citation impact, top 5% of its field
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

61 citing papers in PubMed, 103 citations in OpenAlex.

  1. Article
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  12. A fully synthetic Golden Gate assembly system for engineering aProceedings of the National Academy of Sciences of the United States of America · 2026
    Article
  13. Article
  14. Review
  15. Article
  16. Article
  17. Genome synthesis, assembly, and rebooting of therapeutically useful high G+C% mycobacteriophages.Proceedings of the National Academy of Sciences of the United States of America · 2025
    Article
  18. One-pot cloning and protein expression platform for genetic engineering.bioRxiv : the preprint server for biology · 2025
    Article
  19. Article
  20. Combining Machine Learning and Multiplexed,bioRxiv : the preprint server for biology · 2025
    Article

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

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 at 1 institution in 1 country.

John M PryorResearch Department, New England Biolabs, Ipswich, Massachusetts, United States of America.ORCID 0000-0001-7000-9383
Vladimir PotapovResearch Department, New England Biolabs, Ipswich, Massachusetts, United States of America.
Rebecca B KuceraApplications and Product Development, New England Biolabs, Ipswich, Massachusetts, United States of America.
Katharina BilottiResearch Department, New England Biolabs, Ipswich, Massachusetts, United States of America.
Eric J CantorApplications and Product Development, New England Biolabs, Ipswich, Massachusetts, United States of America.
Gregory J S LohmanResearch Department, New England Biolabs, Ipswich, Massachusetts, United States of America.
New England Biolabs (United States) · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

DNA assembly is an integral part of modern synthetic biology, as intricate genetic engineering projects require robust molecular cloning workflows. Golden Gate assembly is a frequently employed DNA assembly methodology that utilizes a Type IIS restriction enzyme and a DNA ligase to generate recombinant DNA constructs from smaller DNA fragments. However, the utility of this methodology has been limited by a lack of resources to guide experimental design. For example, selection of the DNA sequences at fusion sites between fragments is based on broad assembly guidelines or pre-vetted sets of junctions, rather than being customized for a particular application or cloning project. To facilitate the design of robust assembly reactions, we developed a high-throughput DNA sequencing assay to examine reaction outcomes of Golden Gate assembly with T4 DNA ligase and the most commonly used Type IIS restriction enzymes that generate three-base and four-base overhangs. Next, we incorporated these findings into a suite of webtools that design assembly reactions using the experimental data. These webtools can be used to create customized assemblies from a target DNA sequence or a desired number of fragments. Lastly, we demonstrate how using these tools expands the limits of current assembly systems by carrying out one-pot assemblies of up to 35 DNA fragments. Full implementation of the tools developed here enables direct expansion of existing assembly standards for modular cloning systems (e.g. MoClo) as well as the formation of robust new high-fidelity standards.

Indexed as

DNADNA LigasesDNA Restriction EnzymesNucleotidesSynthetic BiologyDNADNA LigasesDNA Restriction EnzymesNucleotides

Identifiers

PMID32877448
PMCPMC7467295
OpenAlexW3081989981

What OpenQuestion holds

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LicenceCC BY
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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.