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<p>Maize is one of the important source of human calories, but it is prone to climate change. The increased heat and drought events adversely affect maize productivity. Conventional breeding approaches had limited success in developing maize varieties resilient to combined stresses due to the polygenic and complex nature of the traits involved. Meta-QTL analysis approach integrates the data from multiple QTL/linkage mapping studies to identify stable QTLs associated with stress tolerance, providing detailed insights into the genetic architecture underlying stress responses and enhancing the precision and reliability of detected loci, facilitating the identification and selection of robust candidate genes for breeding programs. The present investigation collected 760 QTLs mapped under drought stress (DS) and heat stress (HS) environments in maize from different published studies. Meta-QTL analysis was carried out, which revealed 30 Meta-QTL hotspot regions, with reduced confidence interval (CI), and 1489 candidate genes. The genomic regions associated with combined DS and HS were validated through GWAS, provided SNPs associated with combined DS and HS supporting the strong evidence of genomic regions involved in combined DS and HS tolerance. Further, selected candidate genes were also validated in anther tissues by qRT-PCR in the CAH 192 inbred, and results showed upregulation of genes under combined DS and HS stress conditions. The identified flanking markers of Meta-QTL hotspots in the present study could be useful for marker-assisted selection, gene cloning, functional validation, and improving selection efficiency in abiotic&#xa0;stress breeding programs of maize.</p>

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Identification and validation of candidate genes for combined drought and heat stress tolerance in maize (Zea mays L.)

  • 期刊论文

  • 发表日期：

    2025年10月3日

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  • Sahil Singh Mandyal,
  • Anurag Mishra,
  • Yogesh Dashrath Naik,
  • Ashutosh Singh

摘要

Maize is one of the important source of human calories, but it is prone to climate change. The increased heat and drought events adversely affect maize productivity. Conventional breeding approaches had limited success in developing maize varieties resilient to combined stresses due to the polygenic and complex nature of the traits involved. Meta-QTL analysis approach integrates the data from multiple QTL/linkage mapping studies to identify stable QTLs associated with stress tolerance, providing detailed insights into the genetic architecture underlying stress responses and enhancing the precision and reliability of detected loci, facilitating the identification and selection of robust candidate genes for breeding programs. The present investigation collected 760 QTLs mapped under drought stress (DS) and heat stress (HS) environments in maize from different published studies. Meta-QTL analysis was carried out, which revealed 30 Meta-QTL hotspot regions, with reduced confidence interval (CI), and 1489 candidate genes. The genomic regions associated with combined DS and HS were validated through GWAS, provided SNPs associated with combined DS and HS supporting the strong evidence of genomic regions involved in combined DS and HS tolerance. Further, selected candidate genes were also validated in anther tissues by qRT-PCR in the CAH 192 inbred, and results showed upregulation of genes under combined DS and HS stress conditions. The identified flanking markers of Meta-QTL hotspots in the present study could be useful for marker-assisted selection, gene cloning, functional validation, and improving selection efficiency in abiotic stress breeding programs of maize.