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Mapping QTLs and meta-QTLs for two inflorescence architecture traits in multiple maize populations under different watering environments

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Abstract

Drought significantly affects the architectural development of maize inflorescence, which leads to massive losses in grain yield. However, the genetic mechanism for traits involved in inflorescence architecture in different watering environments, remains poorly understood in maize. In this study, 19 QTLs for tassel primary branch number (TBN) and ear number per plant (EN) were detected in 2 F2:3 populations under both well-watered and water-stressed environments by single environment mapping with composite interval mapping (CIM); 11/19 QTLs were detected under water-stressed environments. Moreover, 21 QTLs were identified in the 2 F2:3 populations by joint analysis of all environments with a mixed linear model based on composite interval mapping (MCIM), 11 QTLs were involved in QTL × environment interactions, seven epistatic interactions were identified with additive by additive/dominance effects. Remarkably, 12 stable QTLs (sQTLs) were simultaneously detected by single environment mapping with CIM and joint analysis through MCIM, which were concentrated in ten bins across the chromosomes: 1.05_1.07, 1.08_1.10, 2.01_2.04, 3.01, 4.06, 4.09, 5.06_5.07, 6.05, 7.00, and 7.04 regions. Twenty meta-QTLs (mQTLs) were detected across 19 populations under 51 watering environments using a meta-analysis, and 34 candidate genes were predicted in corresponding mQTLs regions to be involved in the regulation of inflorescence development and drought resistance. Therefore, these results provide valuable information for finding quantitative trait genes and to reveal the genetic mechanisms responsible for TBN and EN under different watering environments. Furthermore, alleles for TBN and EN provide useful targets for marker-assisted selection to generate high-yielding maize varieties.

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Acknowledgments

This work was supported by grants from the National Science Foundation of China (31260330 and 31301333), and the International Scientific and Technological Cooperation Project of Gansu, China (1504WKCA009).

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  1. Xiaoqiang Zhao and Yunling Peng have contributed equally to this work.

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  1. Gansu Key Lab of Crop Improvement and Germplasm Enhancement, Gansu Provincial Key Lab of Aridland Crop Science, College of Agronomy, Gansu Agricultural University, Lanzhou, 730070, China

    Xiaoqiang Zhao, Yunling Peng, Jinwen Zhang, Peng Fang & Boyang Wu

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Zhao, X., Peng, Y., Zhang, J. et al. Mapping QTLs and meta-QTLs for two inflorescence architecture traits in multiple maize populations under different watering environments. Mol Breeding 37, 91 (2017). https://doi.org/10.1007/s11032-017-0686-9

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