ArticleG3 (Bethesda, Md.)2016
The Interaction of Genotype and Environment Determines Variation in the Maize Kernel Ionome.
Article in G3 (Bethesda, Md.), 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 26 papers.
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Who cites it
26 citing papers in PubMed.
- A comparative approach for selecting orthologous candidate genes in genome-wide association studies across multiple species.Plant physiology · 2026Article
- An atlas of plant selenium metabolism.The New phytologist · 2026Review
- Combining ability and heterosis analysis for mineral content in the leafy vegetable Gynandropsis gynandra (L.) Briq.PloS one · 2025Article
- Calcium modulation of bacterial wilt disease on potato.Applied and environmental microbiology · 2024Article
- Genetic dissection of maize (Zea maysL.) trace element traits using genome-wide association studies.BMC plant biology · 2023Article
- Mycorrhizal status and host genotype interact to shape plant nutrition in field grown maize (Zea mays ssp. mays).Mycorrhiza · 2023Article
- Temporal and environmental factors interact with rootstock genotype to shape leaf elemental composition in grafted grapevines.Plant direct · 2022Article
- Leaf elemental composition analysis in spider plant [Frontiers in plant science · 2022Article
- Genome-Wide Association Study Reveals Genomic Regions Associated With Molybdenum Accumulation in Wheat Grains.Frontiers in plant science · 2022Article
- The genetic architecture of leaf stable carbon isotope composition in Zea mays and the effect of transpiration efficiency on leaf elemental accumulation.G3 (Bethesda, Md.) · 2021Article
- Genetic architecture of root and shoot ionomes in rice (Oryza sativa L.).TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2021Article
- High-resolution genome-wide association study pinpoints metal transporter and chelator genes involved in the genetic control of element levels in maize grain.G3 (Bethesda, Md.) · 2021Article
- Ionomic variation in leaves of 819 plant species growing in the botanical garden of Hokkaido University, Japan.Journal of plant research · 2021Article
- Characterization of pea seed nutritional value within a diverse population of Pisum sativum.PloS one · 2021Article
- Use of hydraulic traits for modeling genotype-specific acclimation in cotton under drought.The New phytologist · 2020Article
- Integrated Genome-Scale Analysis Identifies Novel Genes and Networks Underlying Senescence in Maize.The Plant cell · 2019Article
- Multivariate analysis reveals environmental and genetic determinants of element covariation in the maize grain ionome.Plant direct · 2019Article
- Article
- Novel organ-specific genetic factors for quantitative resistance to late blight in potato.PloS one · 2019Article
- Integrating Coexpression Networks with GWAS to Prioritize Causal Genes in Maize.The Plant cell · 2018Article
Corrections and comments
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Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Plants obtain soil-resident elements that support growth and metabolism from the water-flow facilitated by transpiration and active transport processes. The availability of elements in the environment interacts with the genetic capacity of organisms to modulate element uptake through plastic adaptive responses, such as homeostasis. These interactions should cause the elemental contents of plants to vary such that the effects of genetic polymorphisms will be dramatically dependent on the environment in which the plant is grown. To investigate genotype by environment interactions underlying elemental accumulation, we analyzed levels of elements in maize kernels of the Intermated B73 × Mo17 (IBM) recombinant inbred population grown in 10 different environments, spanning a total of six locations and five different years. In analyses conducted separately for each environment, we identified a total of 79 quantitative trait loci (QTL) controlling seed elemental accumulation. While a set of these QTL was found in multiple environments, the majority were specific to a single environment, suggesting the presence of genetic by environment interactions. To specifically identify and quantify QTL by environment interactions (QEIs), we implemented two methods: linear modeling with environmental covariates, and QTL analysis on trait differences between growouts. With these approaches, we found several instances of QEI, indicating that elemental profiles are highly heritable, interrelated, and responsive to the environment.
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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.