Evidence map›Paper›PMID 35134181›Full record

ArticleG3 (Bethesda, Md.)2022

Analysis of genotype-by-environment interactions in a maize mapping population.

Asher I Hudson, Sarah G Odell, Pierre Dubreuil, Marie-Helene Tixier, Sebastien Praud, Daniel E Runcie, Jeffrey Ross-Ibarra

Abstract read
In one paragraph

Article in G3 (Bethesda, Md.), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers.

0numbers the graph read from it
0cells of the map it votes in
23citing 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

23 citing papers in PubMed.

  1. Article
  2. Genetic determinants of aerial root morphology in Sierra Mixe-derived maize.TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2026
    Article
  3. Genetic dissection of grain yield and correlated proxy traits under suboptimal conditions.TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2026
    Article
  4. Article
  5. Article
  6. The Promise of Synthetic Biology for Redesigning Plant Architecture.International journal of molecular sciences · 2026
    Review
  7. Article
  8. Article
  9. Article
  10. Review
  11. Review
  12. Article
  13. Article
  14. Article
  15. Article
  16. Tools and Techniques to Accelerate Crop Breeding.Plants (Basel, Switzerland) · 2024
    Review
  17. Molecular breeding of flower load related traits in dioecious autotetraploidMolecular breeding : new strategies in plant improvement · 2024
    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

7 authors.

Asher I HudsonDepartment of Evolution and Ecology, University of California, Davis, CA 95616, USA.ORCID 0000-0001-9520-8901
Sarah G OdellDepartment of Evolution and Ecology, University of California, Davis, CA 95616, USA.ORCID 0000-0002-0316-7506
Pierre DubreuilCenter of Research of Chappes, Limagrain, Chappes 63720, France.
Marie-Helene TixierCenter of Research of Chappes, Limagrain, Chappes 63720, France.
Sebastien PraudCenter of Research of Chappes, Limagrain, Chappes 63720, France.ORCID 0000-0002-4474-9115
Daniel E RuncieDepartment of Plant Sciences, University of California, Davis, CA 95616, USA.ORCID 0000-0002-3008-9312
Jeffrey Ross-IbarraDepartment of Evolution and Ecology, University of California, Davis, CA 95616, USA.ORCID 0000-0003-1656-4954

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Genotype-by-environment interactions are a significant challenge for crop breeding as well as being important for understanding the genetic basis of environmental adaptation. In this study, we analyzed genotype-by-environment interactions in a maize multiparent advanced generation intercross population grown across 5 environments. We found that genotype-by-environment interactions contributed as much as genotypic effects to the variation in some agronomically important traits. To understand how genetic correlations between traits change across environments, we estimated the genetic variance-covariance matrix in each environment. Changes in genetic covariances between traits across environments were common, even among traits that show low genotype-by-environment variance. We also performed a genome-wide association study to identify markers associated with genotype-by-environment interactions but found only a small number of significantly associated markers, possibly due to the highly polygenic nature of genotype-by-environment interactions in this population.

Indexed as

Genome-Wide Association StudyZea maysGene-Environment InteractionGenotypePhenotypePlant Breedingenvironment interactionsgenotype ×maizemultiparental populations

Identifiers

PMID35134181
PMCPMC8895993

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.