Identification of QTN-by-environment interactions for yield related traits in maize under multiple abiotic stresses

Yang-Jun Wen; Xinyi Wu; Shengmeng Wang; Le Han; Bolin Shen; Yuan Wang; Jin Zhang

doi:10.3389/fpls.2023.1050313

Identification of QTN-by-environment interactions for yield related traits in maize under multiple abiotic stresses

Front Plant Sci. 2023 Feb 15:14:1050313. doi: 10.3389/fpls.2023.1050313. eCollection 2023.

Authors

Yang-Jun Wen^{1

2}, Xinyi Wu¹, Shengmeng Wang¹, Le Han¹, Bolin Shen¹, Yuan Wang¹, Jin Zhang^{1

2}

Affiliations

¹ College of Science, Nanjing Agricultural University, Nanjing, China.
² Key Laboratory of Crop Genetics and Germplasm Enhancement, Nanjing Agricultural University, Nanjing, China.

Abstract

Introduction: Quantitative trait nucleotide (QTN)-by-environment interactions (QEIs) play an increasingly essential role in the genetic dissection of complex traits in crops as global climate change accelerates. The abiotic stresses, such as drought and heat, are the major constraints on maize yields. Multi-environment joint analysis can improve statistical power in QTN and QEI detection, and further help us to understand the genetic basis and provide implications for maize improvement.

Methods: In this study, 3VmrMLM was applied to identify QTNs and QEIs for three yield-related traits (grain yield, anthesis date, and anthesis-silking interval) of 300 tropical and subtropical maize inbred lines with 332,641 SNPs under well-watered and drought and heat stresses.

Results: Among the total 321 genes around 76 QTNs and 73 QEIs identified in this study, 34 known genes were reported in previous maize studies to be truly associated with these traits, such as ereb53 (GRMZM2G141638) and thx12 (GRMZM2G016649) associated with drought stress tolerance, and hsftf27 (GRMZM2G025685) and myb60 (GRMZM2G312419) associated with heat stress. In addition, among 127 homologs in Arabidopsis out of 287 unreported genes, 46 and 47 were found to be significantly and differentially expressed under drought vs well-watered treatments, and high vs. normal temperature treatments, respectively. Using functional enrichment analysis, 37 of these differentially expressed genes were involved in various biological processes. Tissue-specific expression and haplotype difference analysis further revealed 24 candidate genes with significantly phenotypic differences across gene haplotypes under different environments, of which the candidate genes GRMZM2G064159, GRMZM2G146192, and GRMZM2G114789 around QEIs may have gene-by-environment interactions for maize yield.

Discussion: All these findings may provide new insights for breeding in maize for yield-related traits adapted to abiotic stresses.

Keywords: 3VmrMLM; GWAS; QTN-by-environment interaction; maize; multiple abiotic stresses; yield-related traits.

Grants and funding

The work was supported by the National Natural Science Foundation of China (32270694, 32070688, and 31701071), the Postdoctoral Science Foundation of Jiangsu (2020Z330), and the Fundamental Research Funds for the Central Universities (JCQY202108).