Evidence map›Paper›PMID 33527897›Full record

ArticleeLife2021

Emergence and propagation of epistasis in metabolic networks.

Sergey Kryazhimskiy

Abstract read
In one paragraph

Article in eLife, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers.

0numbers the graph read from it
0cells of the map it votes in
21citing 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

21 citing papers in PubMed.

  1. Article
  2. Article
  3. Review
  4. Article
  5. Article
  6. Epistatic hotspots organize antibody fitness landscape and boost evolvability.Proceedings of the National Academy of Sciences of the United States of America · 2025
    Article
  7. Article
  8. Article
  9. Article
  10. Article
  11. Article
  12. DeconstructingiScience · 2023
    Article
  13. Review
  14. Review
  15. 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
  16. Article
  17. Article
  18. Review
  19. 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

1 author.

Sergey KryazhimskiyDivision of Biological Sciences, University of California, San Diego, La Jolla, United States.ORCID 0000-0001-9128-8705

Funding

Characterizing variation in the local structure of fitness landscapes to assess the predictability of evolutionR01GM137112 · NIGMS · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI KRYAZHIMSKIY, SERGEY A. · 2020 to 2023
$1.2M
NIGMS NIH HHS R01 GM137112
6 · The paper itself

Abstract

Epistasis is often used to probe functional relationships between genes, and it plays an important role in evolution. However, we lack theory to understand how functional relationships at the molecular level translate into epistasis at the level of whole-organism phenotypes, such as fitness. Here, I derive two rules for how epistasis between mutations with small effects propagates from lower- to higher-level phenotypes in a hierarchical metabolic network with first-order kinetics and how such epistasis depends on topology. Most importantly, weak epistasis at a lower level may be distorted as it propagates to higher levels. Computational analyses show that epistasis in more realistic models likely follows similar, albeit more complex, patterns. These results suggest that pairwise inter-gene epistasis should be common, and it should generically depend on the genetic background and environment. Furthermore, the epistasis coefficients measured for high-level phenotypes may not be sufficient to fully infer the underlying functional relationships.

Indexed as

Epistasis, GeneticComputational BiologyMetabolic Networks and PathwaysModels, TheoreticalMutationcomputational biologygenetic interactionsglycolysismetabolic control analysisnonesystems biology

Identifiers

PMID33527897
PMCPMC7924954

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.