Evidence map›Paper›PMID 22152095›Full record

ReviewFEMS yeast research2012

Genome-wide analytical approaches for reverse metabolic engineering of industrially relevant phenotypes in yeast.

Bart Oud, Antonius J A van Maris, Jean-Marc Daran, Jack T Pronk

Abstract readReview
In one paragraph

Review in FEMS yeast research, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 27 papers.

0numbers the graph read from it
0cells of the map it votes in
27citing 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

27 citing papers in PubMed.

  1. Article
  2. A tractable physical model for the yeast polarity predicts epistasis and fitness.Philosophical transactions of the Royal Society of London. Series B, Biological sciences · 2023
    Article
  3. Article
  4. Article
  5. Laboratory Evolution and Reverse Engineering ofApplied and environmental microbiology · 2021
    Article
  6. Article
  7. Article
  8. Review
  9. Review
  10. Article
  11. Article
  12. Article
  13. Article
  14. Article
  15. Article
  16. Article
  17. Article
  18. Article
  19. Review
  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.

Bart OudDepartment of Biotechnology, Delft University of Technology and Kluyver Centre for Genomics of Industrial Fermentation, Delft, The Netherlands.
Antonius J A van Maris
Jean-Marc Daran
Jack T Pronk

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Successful reverse engineering of mutants that have been obtained by nontargeted strain improvement has long presented a major challenge in yeast biotechnology. This paper reviews the use of genome-wide approaches for analysis of Saccharomyces cerevisiae strains originating from evolutionary engineering or random mutagenesis. On the basis of an evaluation of the strengths and weaknesses of different methods, we conclude that for the initial identification of relevant genetic changes, whole genome sequencing is superior to other analytical techniques, such as transcriptome, metabolome, proteome, or array-based genome analysis. Key advantages of this technique over gene expression analysis include the independency of genome sequences on experimental context and the possibility to directly and precisely reproduce the identified changes in naive strains. The predictive value of genome-wide analysis of strains with industrially relevant characteristics can be further improved by classical genetics or simultaneous analysis of strains derived from parallel, independent strain improvement lineages.

Indexed as

Biological EvolutionBiotechnologyGenome, FungalGenome-Wide Association StudyGenomicsMetabolic EngineeringMutagenesisPhenotypeSaccharomyces cerevisiaeTranscriptome

Identifiers

PMID22152095
PMCPMC3615171

What OpenQuestion holds

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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.