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Mining genes regulating root system architecture in maize based on data integration analysis

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Abstract

Key message

A new strategy that integrated multiple public data resources was established to construct root gene co-expression network and mine genes regulating root system architecture in maize. A root gene co-expression network, containing 13,874 genes, was constructed. A total of 53 root hub genes and 16 priority root candidate genes were identified. One priority root candidate was further functionally verified using overexpression transgenic maize lines.

Abstract

Root system architecture (RSA) is crucial for crops productivity and stress tolerance. In maize, few RSA genes are functionally cloned, and effective discovery of RSA genes remains a great of challenge. In this work, we established a strategy to mine maize RSA genes by integrating functionally characterized root genes, root transcriptome, weighted gene co-expression network analysis (WGCNA) and genome-wide association analysis (GWAS) of RSA traits based on public data resources. A total of 589 maize root genes were collected by searching well-characterized root genes in maize or homologous genes of other species. We performed WGCNA to construct a maize root gene co-expression network containing 13874 genes based on public available root transcriptome data, and further discovered the 53 hub genes related to root traits. In addition, by the prediction function of obtained root gene co-expression network, a total of 1082 new root candidate genes were explored. By further overlapping the obtained new root candidate gene with the root-related GWAS of RSA candidate genes, 16 priority root candidate genes were identified. Finally, a priority root candidate gene, Zm00001d023379 (encodes pyruvate kinase 2), was validated to modulate root open angle and shoot-borne roots number using its overexpression transgenic lines. Our results develop an integration analysis method for effectively exploring regulatory genes of RSA in maize and open a new avenue to mine the candidate genes underlying complex traits.

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Data supporting the findings of this work are available within the paper and its Supplementary Information files.

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Funding

The study was financially supported by the National Key Research and Development Program of China (grant no. 2021YFF1000500) and the National Natural Science Foundation of China (grant no. 31972485).

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Authors and Affiliations

  1. College of Resources and Environmental Sciences, National Academy of Agriculture Green Development, Key Laboratory of Plant-Soil Interactions, MOE, China Agricultural University, Beijing, 100193, China

    Kunhui He, Zheng Zhao, Wei Ren, Zhe Chen, Fanjun Chen, Guohua Mi, Qingchun Pan & Lixing Yuan

  2. Center for Crop Functional Genomics and Molecular Breeding, China Agricultural University, Beijing, 100193, China

    Limei Chen & Lixing Yuan

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  1. Kunhui He
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Contributions

LY, FC and GM designed the experiments; KH and ZZ performed the experiments; KH and WR performed data analysis; LC generated maize transgenic lines; ZC and QP provided the scientific advice; KH prepared and wrote the article and LY revised the manuscript. All authors read and approved the final manuscript.

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Correspondence to Lixing Yuan.

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He, K., Zhao, Z., Ren, W. et al. Mining genes regulating root system architecture in maize based on data integration analysis. Theor Appl Genet 136, 127 (2023). https://doi.org/10.1007/s00122-023-04376-0

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