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Combined GWAS and QTL analysis for dissecting the genetic architecture of kernel test weight in maize

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Abstract

Kernel weight in a unit volume is referred to as kernel test weight (KTW) that directly reflects maize (Zea mays L.) grain quality. In this study, an inter-mated B73 × Mo17 (IBM) Syn10 doubled haploid (DH) population and an association panel were used to identify loci responsible for KTW of maize across multiple environments. A total of 18 significant KTW-related single-nucleotide polymorphisms (SNPs) were identified using genome-wide association study (GWAS); they were closely linked to 12 candidate genes. In the IBM Syn10 DH population, linkage analysis detected 19 common quantitative trait loci (QTL), five of which were repeatedly detected among multiple environments. Several verified genes that regulate maize seed development were found in the confidence intervals of the mapped QTL and the LD regions of GWAS, such as ZmYUC1, BAP2, ZmTCRR-1, dek36 and ZmSWEET4c. Combined QTL map** and GWAS identified one significant SNP that was co-identified in the both populations. Based on the co-localized SNP across the both populations, 17 candidate genes were identified. Of them, Zm00001d044075, Zm00001d044086, and Zm00001d044081 were further identified by candidate gene association study for KTW. Zm00001d044081 encodes homeobox-leucine zipper protein ATHB-4, which has been demonstrated to control apical embryo development in Arabidopsis. Our findings provided insights into the mechanism underlying maize KTW and contributed to the application of molecular-assisted selection of high KTW breeding in maize.

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Acknowledgements

This work is supported by the Major Project of China on New Varieties of GMO Cultivation (2016ZX08003003), the National Natural Science Foundation of China (31871637), and the Science and Technology Research Program of Sichuan Municipal Education Commission (2018JY0170).

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  1. **aoxiang Zhang and Zhongrong Guan have contributed equally to this work.

Authors and Affiliations

  1. Key Laboratory of Biology and Genetic Improvement of Maize in Southwest Region, Maize Research Institute, Sichuan Agricultural University, Chengdu, 611130, China

    **aoxiang Zhang, Lei Wang, Jun Fu, Yinchao Zhang, Zhaoling Li, Langlang Ma, Peng Liu, Yanling Zhang, Min Liu, Peng Li, Chaoying Zou, Yongcong He, Haijian Lin, Guangsheng Yuan, Shibin Gao, Guangtang Pan & Yaou Shen

  2. State Key Laboratory of Crop Gene Exploration and Utilization in Southwest China, Chengdu, 611130, China

    Shibin Gao & Yaou Shen

  3. Chongqing Yudongnan Academy of Agricultural Sciences, Chongqing, 408000, China

    Zhongrong Guan

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  1. **aoxiang Zhang
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Contributions

Z-RG, LW, JF, Y-CZ, Z-LL, L-LM, Y-LZ, ML, PL, C-YZ, and YCH participated in the management of the experiment and KTW measurements in this work. This study was conceived by Y-OS and Z-RG. Collections of all plant materials were performed by H-JL, G-SY, S-BG, and G-TP. X-XZ and PL conducted the data analysis. X-XZ wrote the initial manuscript, and Y-OS reviewed the manuscript and made significant editorial contributions. All authors read and approved the final manuscript.

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Correspondence to Yaou Shen.

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Zhang, X., Guan, Z., Wang, L. et al. Combined GWAS and QTL analysis for dissecting the genetic architecture of kernel test weight in maize. Mol Genet Genomics 295, 409–420 (2020). https://doi.org/10.1007/s00438-019-01631-2

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