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Identification of quantitative trait locus and prediction of candidate genes for grain mineral concentration in maize across multiple environments

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A Correction to this article was published on 15 March 2018

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Abstract

Trace metal elements are essential in daily diets for human health and normal growth. Maize is staple food for people in many countries. However, maize has low mineral concentration which makes it difficult to meet human requirements for micronutrients. The objective of this study was to identify quantitative trait locus (QTL) and predict candidate genes associated with mineral concentration in maize grain. Here, a recombinant inbred line population was used to test phenotype of zinc (Zn), iron (Fe), copper (Cu) and manganese (Mn) concentrations in six environments and then a QTL analysis was conducted using single environment analysis along with multiple environment trial (MET) analysis. These two strategies detected a total of 64 and 67 QTLs for target traits, respectively. Single environment analysis revealed 13 QTL bins distributed on seven chromosomes. We found that five candidate genes associated with mineral concentration were located in the same intervals identified by Comparative mapping of meta-QTLs in our previous study. The genetic and phenotypic correlation coefficients were depended on the nutrient traits and they were significant between Fe and Zn, Fe and Cu, Fe and Mn in all environments. The results of this study illustrated the genetic correlation between maize grain mineral concentrations, and identified some promising genomic regions and candidate genes for further studies on the biofortification of mineral concentration in maize grain.

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  • 15 March 2018

    By mistake this article had a note indicating that the article is part of the following topical collection: “This article is part of the Topical Collection on Plant Breeding: the Art of Bringing Science to Life. Highlights of the 20th EUCARPIA General Congress, Zurich, Switzerland, 29 August–1 September 2016 Edited by Roland Kölliker, Richard G. F. Visser, Achim Walter & Beat Boller” The article however is not part of this collection and should be seen as such by the reader.

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Acknowledgements

This work was supported by a Grant from the Hebei Province Science and Technology Support Program, China (16226323D-2, 14226305D-5).

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    1. Hebei Branch of Chinese National Maize Improvement Center, Agricultural University of Hebei, Baoding, 071001, China

      Huaduo Zhang, Jingxian Liu, Tiantian Jin, Yaqun Huang, Jingtang Chen, Liying Zhu, Yongfeng Zhao & Jinjie Guo

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    1. Huaduo Zhang
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    Correspondence to Yaqun Huang.

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    Huaduo Zhang and Jingxian Liu have contributed equally to the work.

    A correction to this article is available online at https://doi.org/10.1007/s10681-018-2143-1.

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    Zhang, H., Liu, J., Jin, T. et al. Identification of quantitative trait locus and prediction of candidate genes for grain mineral concentration in maize across multiple environments. Euphytica 213, 90 (2017). https://doi.org/10.1007/s10681-017-1875-7

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