Evidence map›Paper›PMID 33607980›Full record

ArticleBMC biology2021

Assessing optimal: inequalities in codon optimization algorithms.

Matthew J Ranaghan, Jeffrey J Li, Dylan M Laprise, Colin W Garvie

Open access · goldAbstract read
In one paragraph

Article in BMC biology, 2021. 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
2.2field-weighted citation impact, top 12% 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

22 citing papers in PubMed, 43 citations in OpenAlex.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. Mechanistic Insights into the Bornyl Diphosphate Synthase fromCurrent issues in molecular biology · 2025
    Article
  11. Article
  12. Article
  13. Article
  14. Review
  15. Article
  16. Article
  17. Article
  18. Article
  19. Engineering ofMetabolic engineering communications · 2022
    Article
  20. Article
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

4 authors at 1 institution in 1 country.

Matthew J RanaghanCenter for the Development of Therapeutics, The Broad Institute of MIT and Harvard, 415 Main Street, Cambridge, MA, 02142, USA. ranaghan@broadinstitute.org.ORCID 0000-0003-3572-5127
Jeffrey J LiCenter for the Development of Therapeutics, The Broad Institute of MIT and Harvard, 415 Main Street, Cambridge, MA, 02142, USA.
Dylan M LapriseCenter for the Development of Therapeutics, The Broad Institute of MIT and Harvard, 415 Main Street, Cambridge, MA, 02142, USA.
Colin W GarvieCenter for the Development of Therapeutics, The Broad Institute of MIT and Harvard, 415 Main Street, Cambridge, MA, 02142, USA.
Broad Institute · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundCustom genes have become a common resource in recombinant biology over the last 20 years due to the plummeting cost of DNA synthesis. These genes are often "optimized" to non-native sequences for overexpression in a non-native host by substituting synonymous codons within the coding DNA sequence (CDS). A handful of studies have compared native and optimized CDSs, reporting different levels of soluble product due to the accumulation of misfolded aggregates, variable activity of enzymes, and (at least one report of) a change in substrate specificity. No study, to the best of our knowledge, has performed a practical comparison of CDSs generated from different codon optimization algorithms or reported the corresponding protein yields.

resultsIn our efforts to understand what factors constitute an optimized CDS, we identified that there is little consensus among codon-optimization algorithms, a roughly equivalent chance that an algorithm-optimized CDS will increase or diminish recombinant yields as compared to the native DNA, a near ubiquitous use of a codon database that was last updated in 2007, and a high variability of output CDSs by some algorithms. We present a case study, using KRas4B, to demonstrate that a median codon frequency may be a better predictor of soluble yields than the more commonly utilized CAI metric.

conclusionsWe present a method for visualizing, analyzing, and comparing algorithm-optimized DNA sequences for recombinant protein expression. We encourage researchers to consider if DNA optimization is right for their experiments, and work towards improving the reproducibility of published recombinant work by publishing non-native CDSs.

Indexed as

Gene ExpressionAlgorithmsCodonHumansSequence Analysis, DNACodonAlgorithmCodon optimizationCodon usageKRas4B%MinMaxViolin plot

Identifiers

PMID33607980
PMCPMC7893858
OpenAlexW3130059820

What OpenQuestion holds

Textmetadata
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.