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Background <p>Maize seed oil plays a significant role in human nutrition, animal feed, and bioenergy applications. Despite extensive quantitative trait loci (QTL) studies conducted on this trait, the broad confidence intervals of the identified QTLs have made it difficult to precisely pinpoint candidate genes, thereby limiting their practical application in high-oil maize breeding.</p> Results <p>In this study, we integrated QTL data related to maize seed oil content reported over the past two decades, compiling a total of 339 QTLs from 31 studies. By integrating high-density genetic linkage maps, 72 oil content-related meta-QTLs (MQTLs) were identified. Compared with previous studies on seed oil content QTLs, the average confidence interval of the MQTLs was reduced by 5.89-fold. Through colocalization analysis with genome-wide association study (GWAS) marker-trait associations (MTAs), over 60% of the MQTLs were validated by GWAS-MTAs. Additionally, four known functional genes were identified within the MQTL regions, and 44 candidate genes were further uncovered through homologous gene comparison. These genes are likely involved in critical biological processes such as transcriptional regulation (e.g., <i>CADTFR7</i>), fatty acid biosynthesis (e.g., <i>Zm00001d036137</i>), and material transport (e.g., <i>Zm00001d013817</i>), thereby influencing seed oil content accumulation.</p> Conclusions <p>Collectively, these findings provide valuable insights into the genetic regulation of maize seed oil content and offer potential molecular targets for the development of high-oil maize varieties.</p>

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Meta-QTL analysis for mining key genes associated with seed oil content in maize

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2025年10月29日

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  • Zilong Zhao,
  • Ke Li,
  • Wei Wang,
  • Fei Yi,
  • Nan Zheng,
  • Jinsheng Lai,
  • Qiujie Liu,
  • Jian Chen

摘要

Background

Maize seed oil plays a significant role in human nutrition, animal feed, and bioenergy applications. Despite extensive quantitative trait loci (QTL) studies conducted on this trait, the broad confidence intervals of the identified QTLs have made it difficult to precisely pinpoint candidate genes, thereby limiting their practical application in high-oil maize breeding.

Results

In this study, we integrated QTL data related to maize seed oil content reported over the past two decades, compiling a total of 339 QTLs from 31 studies. By integrating high-density genetic linkage maps, 72 oil content-related meta-QTLs (MQTLs) were identified. Compared with previous studies on seed oil content QTLs, the average confidence interval of the MQTLs was reduced by 5.89-fold. Through colocalization analysis with genome-wide association study (GWAS) marker-trait associations (MTAs), over 60% of the MQTLs were validated by GWAS-MTAs. Additionally, four known functional genes were identified within the MQTL regions, and 44 candidate genes were further uncovered through homologous gene comparison. These genes are likely involved in critical biological processes such as transcriptional regulation (e.g., CADTFR7), fatty acid biosynthesis (e.g., Zm00001d036137), and material transport (e.g., Zm00001d013817), thereby influencing seed oil content accumulation.

Conclusions

Collectively, these findings provide valuable insights into the genetic regulation of maize seed oil content and offer potential molecular targets for the development of high-oil maize varieties.