4.4 Article

Identification and meta-analysis of QTLs for four leaf shape traits in two maize populations under contracting watering environments

Journal

GENETIC RESOURCES AND CROP EVOLUTION
Volume 68, Issue 4, Pages 1557-1575

Publisher

SPRINGER
DOI: 10.1007/s10722-020-01085-1

Keywords

Maize; Leaf shape; QTLs; Meta-analysis; Drought

Funding

  1. Gansu Provincial Key Laboratory of Aridland Crop Science, Gansu Agricultural University, China [GSCS-2020-5, GSCS-2019-8]
  2. National Natural Science Foundation of China [32060486]
  3. Scientific Research Start-up Funds for Openly-recruited Doctors, Science and Technology Innovation Funds of Gansu Agricultural University, China [GAU-KYQD-2018-12, GAUKYQD-2018-19]
  4. Developmental Funds of Innovation Capacity in Higher Education of Gansu, China [2019A-054, 2019A-052]

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This study identified 72 QTLs related to leaf shape, with the majority identified under drought conditions. Thirty-three joint QTLs were found through joint analysis, with 7 showing interactions across different environments and 11 pairs exhibiting additive-by-additive effects. In addition, potential QTLs for improving maize leaf development, as well as meta-QTLs and candidate genes, were also discovered.
Maize leaf length, leaf width, leaf angle, and leaf orientation value are determinant traits influencing leaf shape, yield potential, and can sense water stress signals. However, little is known regarding their genetic controls under drought stress. Using two F-3 populations, we identified 72 QTLs under contrasting environments at V18 and R1 stages by single-environment mapping, 58.3% QTLs were identified under drought-stressed environments. Thirty-three joint QTLs were detected by joint analysis of all environments, 7 QTLs involved in QTL-by-environment interactions, 11 pair epistasis exhibited additive-by-additive effects. Twelve constitutive QTLs were dissected that will be potentially useful for genetic improvement of maize leaf development through QTL pyramiding. Additionally, 13 meta-QTLs were identified via meta-analysis, 15 candidate genes were identified in these meta-QTLs. These results provide valuable information for QTLs fine mapping, revealing genetic mechanisms of leaf shape under contrasting watering environments, and alleles provide useful targets for marker-assisted selection breeding.

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