ArticleJournal of experimental botany2024
Environmental context of phenotypic plasticity in flowering time in sorghum and rice.
Article in Journal of experimental botany, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
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Who cites it
11 citing papers in PubMed.
- Dissecting the genetic basis of yield stability in faba bean by multi-environment analysis.Genome biology · 2026Article
- Integrated phenomic and genomic analyses unveil modes of altered phenotypic plasticity during wheat improvement.Genome biology · 2025Article
- GPS: Harnessing data fusion strategies to improve the accuracy of machine learning-based genomic and phenotypic selection.Plant communications · 2025Article
- A reaction norm for flowering time plasticity reveals physiological footprints of maize adaptation.G3 (Bethesda, Md.) · 2025Article
- Genomic selection: Essence, applications, and prospects.The plant genome · 2025Review
- Leveraging Automated Machine Learning for Environmental Data-Driven Genetic Analysis and Genomic Prediction in Maize Hybrids.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2025Article
- Growth strategies and phenotypic plasticity of improved Chinese fir families across soil types.Forestry research · 2025Article
- Review
- Strawberry phenotypic plasticity in flowering time is driven by the interaction between genetic loci and temperature.Journal of experimental botany · 2024Article
- Article
- Importance of phenotypic plasticity in crop resilience.Journal of experimental botany · 2024Article
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4 authors.
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Abstract
Phenotypic plasticity is an important topic in biology and evolution. However, how to generate broadly applicable insights from individual studies remains a challenge. Here, with flowering time observed from a large geographical region for sorghum and rice genetic populations, we examine the consistency of parameter estimation for reaction norms of genotypes across different subsets of environments and searched for potential strategies to inform the study design. Both sample size and environmental mean range of the subset affected the consistency. The subset with either a large range of environmental mean or a large sample size resulted in genetic parameters consistent with the overall pattern. Furthermore, high accuracy through genomic prediction was obtained for reaction norm parameters of untested genotypes using models built from tested genotypes under the subsets of environments with either a large range or a large sample size. With 1428 and 1674 simulated settings, our analyses suggested that the distribution of environmental index values of a site should be considered in designing experiments. Overall, we showed that environmental context was critical, and considerations should be given to better cover the intended range of the environmental variable. Our findings have implications for the genetic architecture of complex traits, plant-environment interaction, and climate adaptation.
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