Evidence map›Paper›PMID 29891664›Full record

ArticleProceedings of the National Academy of Sciences of the United States of America2018

Genomic and environmental determinants and their interplay underlying phenotypic plasticity.

Xin Li, Tingting Guo, Qi Mu, Xianran Li, Jianming Yu

Abstract read
In one paragraph

Article in Proceedings of the National Academy of Sciences of the United States of America, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 103 papers.

0numbers the graph read from it
0cells of the map it votes in
103citing 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

103 citing papers in PubMed.

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  10. Machine learning-based prediction of dynamic heterosis for plant height with pathway biomarkers in rice.TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2026
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  19. AdaptiveGS: an explainable genomic selection framework based on adaptive stacking ensemble machine learning.TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2025
    Article
  20. Article

43 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

5 authors.

Xin LiDepartment of Agronomy, Iowa State University, Ames, IA 50011.
Tingting GuoDepartment of Agronomy, Iowa State University, Ames, IA 50011.
Qi MuDepartment of Agronomy, Iowa State University, Ames, IA 50011.
Xianran LiDepartment of Agronomy, Iowa State University, Ames, IA 50011 lixr@iastate.edu jmyu@iastate.edu.
Jianming YuDepartment of Agronomy, Iowa State University, Ames, IA 50011 lixr@iastate.edu jmyu@iastate.edu.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Observed phenotypic variation in living organisms is shaped by genomes, environment, and their interactions. Flowering time under natural conditions can showcase the diverse outcome of the gene-environment interplay. However, identifying hidden patterns and specific factors underlying phenotypic plasticity under natural field conditions remains challenging. With a genetic population showing dynamic changes in flowering time, here we show that the integrated analyses of genomic responses to diverse environments is powerful to reveal the underlying genetic architecture. Specifically, the effect continuum of individual genes (

Indexed as

Gene-Environment InteractionPhenotypeEpistasis, GeneticFlowersGenetic Association StudiesInbreedingMidwestern United StatesPhotoperiodPlant BreedingPolymorphism, Single NucleotidePuerto RicoSeasonsSorghumTemperatureflowering timegenomic predictiongenomicsgenotype-by-environment interactionphenotypic plasticity

Identifiers

PMID29891664
PMCPMC6042117

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.