ArticlePlant physiology2016
Combined Large-Scale Phenotyping and Transcriptomics in Maize Reveals a Robust Growth Regulatory Network.
Article in Plant physiology, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 28 papers.
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Who cites it
28 citing papers in PubMed, 59 citations in OpenAlex.
- A deficient CP24 allele defines variation for dynamic nonphotochemical quenching and photosystem II efficiency in maize.The Plant cell · 2025Article
- BREEDIT: a multiplex genome editing strategy to improve complex quantitative traits in maize.The Plant cell · 2023Article
- A common language: Cross-species network analysis reveals growth regulators.Plant physiology · 2022Article
- Leaf Development inGenes · 2022Review
- Using breeding and quantitative genetics to understand the C4 pathway.Journal of experimental botany · 2022Article
- A forward genetics approach integrating genome-wide association study and expression quantitative trait locus mapping to dissect leaf development in maize (Zea mays).The Plant journal : for cell and molecular biology · 2021Article
- Using single-plant-omics in the field to link maize genes to functions and phenotypes.Molecular systems biology · 2020Article
- Translational gene regulation in plants: A green new deal.Wiley interdisciplinary reviews. RNA · 2020Review
- Leaf shape inEcology and evolution · 2020Article
- Identification of transcription factors controlling floral morphology in wild Petunia species with contrasting pollination syndromes.The Plant journal : for cell and molecular biology · 2020Article
- Enabling reusability of plant phenomic datasets with MIAPPE 1.1.The New phytologist · 2020Article
- Meta Gene Regulatory Networks in Maize Highlight Functionally Relevant Regulatory Interactions.The Plant cell · 2020Article
- Linking crop traits to transcriptome differences in a progeny population of tetraploid potato.BMC plant biology · 2020Article
- Comparative transcriptomics enables the identification of functional orthologous genes involved in early leaf growth.Plant biotechnology journal · 2020Article
- Leveraging GWAS data to identify metabolic pathways and networks involved in maize lipid biosynthesis.The Plant journal : for cell and molecular biology · 2019Article
- A systems biology approach uncovers a gene co-expression network associated with cell wall degradability in maize.PloS one · 2019Article
- Extrapolation of significant genes and transcriptional regulatory networks involved in Zea mays in response in UV-B stress.Genes & genomics · 2018Article
- Co-expression network of transcription factors reveal ethylene-responsive element-binding factor as key regulator of wood phenotype in3 Biotech · 2018Article
- Genome-Wide Association and Metabolic Pathway Analysis of Corn Earworm Resistance in Maize.The plant genome · 2018Article
- The reduction in maize leaf growth under mild drought affects the transition between cell division and cell expansion and cannot be restored by elevated gibberellic acid levels.Plant biotechnology journal · 2018Article
Corrections and comments
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Authors and funding
10 authors at 2 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Leaves are vital organs for biomass and seed production because of their role in the generation of metabolic energy and organic compounds. A better understanding of the molecular networks underlying leaf development is crucial to sustain global requirements for food and renewable energy. Here, we combined transcriptome profiling of proliferative leaf tissue with in-depth phenotyping of the fourth leaf at later stages of development in 197 recombinant inbred lines of two different maize (Zea mays) populations. Previously, correlation analysis in a classical biparental mapping population identified 1,740 genes correlated with at least one of 14 traits. Here, we extended these results with data from a multiparent advanced generation intercross population. As expected, the phenotypic variability was found to be larger in the latter population than in the biparental population, although general conclusions on the correlations among the traits are comparable. Data integration from the two diverse populations allowed us to identify a set of 226 genes that are robustly associated with diverse leaf traits. This set of genes is enriched for transcriptional regulators and genes involved in protein synthesis and cell wall metabolism. In order to investigate the molecular network context of the candidate gene set, we integrated our data with publicly available functional genomics data and identified a growth regulatory network of 185 genes. Our results illustrate the power of combining in-depth phenotyping with transcriptomics in mapping populations to dissect the genetic control of complex traits and present a set of candidate genes for use in biomass improvement.
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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.