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Genetic control of morphometric diversity in the maize shoot apical meristem

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Listed:
  • Samuel Leiboff

    (Cornell University)

  • Xianran Li

    (Iowa State University)

  • Heng-Cheng Hu

    (Iowa State University)

  • Natalie Todt

    (Cornell University)

  • Jinliang Yang

    (Iowa State University)

  • Xiao Li

    (Iowa State University)

  • Xiaoqing Yu

    (Iowa State University)

  • Gary J. Muehlbauer

    (University of Minnesota)

  • Marja C. P. Timmermans

    (Cold Spring Harbor Laboratory)

  • Jianming Yu

    (Iowa State University)

  • Patrick S. Schnable

    (Iowa State University)

  • Michael J. Scanlon

    (Cornell University)

Abstract

The maize shoot apical meristem (SAM) comprises a small pool of stem cells that generate all above-ground organs. Although mutational studies have identified genetic networks regulating SAM function, little is known about SAM morphological variation in natural populations. Here we report the use of high-throughput image processing to capture rich SAM size variation within a diverse maize inbred panel. We demonstrate correlations between seedling SAM size and agronomically important adult traits such as flowering time, stem size and leaf node number. Combining SAM phenotypes with 1.2 million single nucleotide polymorphisms (SNPs) via genome-wide association study reveals unexpected SAM morphology candidate genes. Analyses of candidate genes implicated in hormone transport, cell division and cell size confirm correlations between SAM morphology and trait-associated SNP alleles. Our data illustrate that the microscopic seedling SAM is predictive of adult phenotypes and that SAM morphometric variation is associated with genes not previously predicted to regulate SAM size.

Suggested Citation

  • Samuel Leiboff & Xianran Li & Heng-Cheng Hu & Natalie Todt & Jinliang Yang & Xiao Li & Xiaoqing Yu & Gary J. Muehlbauer & Marja C. P. Timmermans & Jianming Yu & Patrick S. Schnable & Michael J. Scanlo, 2015. "Genetic control of morphometric diversity in the maize shoot apical meristem," Nature Communications, Nature, vol. 6(1), pages 1-10, December.
    • Handle: RePEc:nat:natcom:v:6:y:2015:i:1:d:10.1038_ncomms9974
    DOI: 10.1038/ncomms9974
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    Cited by:

    1. Li, Xinyi & Wang, Li & Nettleton, Dan, 2019. "Sparse model identification and learning for ultra-high-dimensional additive partially linear models," Journal of Multivariate Analysis, Elsevier, vol. 173(C), pages 204-228.

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