ArticlePloS one2012
A gene regulatory network model for floral transition of the shoot apex in maize and its dynamic modeling.
Article in PloS one, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 63 papers.
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Who cites it
63 citing papers in PubMed, 146 citations in OpenAlex.
- Ensemble-based genomic prediction for maize flowering time improves prediction accuracy and reveals novel insights into trait genetic variation.G3 (Bethesda, Md.) · 2026Article
- Back to the future 2: the implications of germplasm structure on the balance between short- and long-term genetic gain in a changing target population of environments.G3 (Bethesda, Md.) · 2026Article
- Dynamic and cell-type specific transcriptional reprogramming underlies the floral transition in the maize shoot apical meristem.Genome biology · 2026Article
- Unlocking tropical adaptation: novel flowering time genes implicate JA and ROS signaling in maize.BMC plant biology · 2026Article
- Ensemble AnalySis with Interpretable Genomic Prediction (EasiGP): Computational tool for interpreting ensembles of genomic prediction models.The plant genome · 2025Article
- Vegetative to generative1 (Vgt1) is an enhancer affecting flowering time and jasmonate signaling in maize by promoting the expression of Zea mays Related to APETALA 2.7.Plant physiology · 2025Article
- A reaction norm for flowering time plasticity reveals physiological footprints of maize adaptation.G3 (Bethesda, Md.) · 2025Article
- Breeding perspectives on tackling trait genome-to-phenome (G2P) dimensionality using ensemble-based genomic prediction.TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2025Review
- Toward a general framework for AI-enabled prediction in crop improvement.TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2025Article
- Individual plant genetics reveal the control of local adaptation in European maize landraces.BMC biology · 2025Article
- Improved genomic prediction performance with ensembles of diverse models.G3 (Bethesda, Md.) · 2025Article
- A LTR retrotransposon insertion leads to leafy phenotype in maize by elevating ZmOM66 expression.Nature communications · 2025Article
- Harnessing the predicted maize pan-interactome for putative gene function prediction and prioritization of candidate genes for important traits.G3 (Bethesda, Md.) · 2024Article
- Photoperiodic and lighting treatments for flowering control and its genetic regulation in sugarcane breeding.Heliyon · 2024Review
- Establishing an optimized ATAC-seq protocol for the maize.Frontiers in plant science · 2024Article
- QTL mapping for plant height and ear height using bi-parental immortalized heterozygous populations in maize.Frontiers in plant science · 2024Article
- Breeding crops for drought-affected environments and improved climate resilience.The Plant cell · 2023Review
- Structure and character analysis of cotton response regulator genes family reveals that GhRR7 responses to draught stress.Biological research · 2022Article
- Linkage mapping combined with GWAS revealed the genetic structural relationship and candidate genes of maize flowering time-related traits.BMC plant biology · 2022Article
- Genetic Determinants of Biomass in CFrontiers in plant science · 2022Review
3 more citing papers are in PubMed but not listed here.
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Authors and funding
6 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The transition from the vegetative to reproductive development is a critical event in the plant life cycle. The accurate prediction of flowering time in elite germplasm is important for decisions in maize breeding programs and best agronomic practices. The understanding of the genetic control of flowering time in maize has significantly advanced in the past decade. Through comparative genomics, mutant analysis, genetic analysis and QTL cloning, and transgenic approaches, more than 30 flowering time candidate genes in maize have been revealed and the relationships among these genes have been partially uncovered. Based on the knowledge of the flowering time candidate genes, a conceptual gene regulatory network model for the genetic control of flowering time in maize is proposed. To demonstrate the potential of the proposed gene regulatory network model, a first attempt was made to develop a dynamic gene network model to predict flowering time of maize genotypes varying for specific genes. The dynamic gene network model is composed of four genes and was built on the basis of gene expression dynamics of the two late flowering id1 and dlf1 mutants, the early flowering landrace Gaspe Flint and the temperate inbred B73. The model was evaluated against the phenotypic data of the id1 dlf1 double mutant and the ZMM4 overexpressed transgenic lines. The model provides a working example that leverages knowledge from model organisms for the utilization of maize genomic information to predict a whole plant trait phenotype, flowering time, of maize genotypes.
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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.