Joukhadar Reem, Trethowan Richard M, Thistlethwaite Rebecca, Hayden Matthew J, Stangoulis James, Cu Suong, Tibbits Josquin, Daetwyler Hans D
Agriculture Victoria, Centre for AgriBioscience, AgriBio, Bundoora, VIC, Australia.
School of Life and Environmental Sciences, Plant Breeding Institute, Sydney Institute of Agriculture, The University of Sydney, Narrabri, NSW, Australia.
Theor Appl Genet. 2025 Apr 9;138(5):95. doi: 10.1007/s00122-025-04877-0.
Understanding the genetic basis of nutrient accumulation in wheat is crucial for improving its nutritional content and addressing global food security challenges. Here, we identified stable pleiotropic loci controlling the accumulation of 13 nutritional elements in wheat across diverse environments using a large wheat population of 1470 individuals. Our analysis revealed significant variability in SNP-based heritability values across 13 essential elements. Genetic correlations among elements uncovered complex relations, with positive correlations observed within two distinct groups, where calcium (Ca), cobalt (Co), potassium (K), and sodium (Na) formed one group, and copper (Cu), iron (Fe), magnesium (Mg), manganese (Mn), molybdenum (Mo), nickel (Ni), phosphorus (P), and zinc (Zn) formed the other. Negative correlations were observed among elements across both groups. Through MetaGWAS analysis, we identified stable QTL associated with individual elements and elements with high positive correlations. We identified 67 stable QTL across environments that are independent from grain yield, of which 56 were detected using the MetaGWAS analysis indicating their pleiotropic effect on multiple elements. A major QTL on chromosome 7D that can shift the phenotype up to one standard deviation compared to the mean phenotype in the population exhibited differential effects on multiple elements belonging to both groups. Our findings offer novel insights into the genetic architecture of nutrient accumulation in wheat and have practical implications for breeding programmes aimed at enhancing multiple nutrients simultaneously. By targeting stable QTL, breeders can develop wheat varieties with improved nutritional profiles, contributing to global food security and human health.
了解小麦营养元素积累的遗传基础对于提高其营养成分和应对全球粮食安全挑战至关重要。在此，我们使用一个由1470个个体组成的大型小麦群体，确定了在不同环境下控制小麦中13种营养元素积累的稳定多效性位点。我们的分析揭示了基于单核苷酸多态性（SNP）的13种必需元素遗传力值的显著变异性。元素之间的遗传相关性揭示了复杂的关系，在两个不同的组内观察到正相关，其中钙（Ca）、钴（Co）、钾（K）和钠（Na）形成一组，铜（Cu）、铁（Fe）、镁（Mg）、锰（Mn）、钼（Mo）、镍（Ni）、磷（P）和锌（Zn）形成另一组。两组元素之间均观察到负相关。通过Meta全基因组关联研究（MetaGWAS）分析，我们确定了与单个元素以及具有高正相关性的元素相关的稳定数量性状位点（QTL）。我们在不同环境中确定了67个与谷物产量无关的稳定QTL，其中56个是通过MetaGWAS分析检测到的，表明它们对多种元素具有多效性作用。位于7D染色体上的一个主要QTL，与群体中的平均表型相比，可使表型变化高达一个标准差，对两组中的多种元素均表现出不同的影响。我们的研究结果为小麦营养元素积累的遗传结构提供了新的见解，对旨在同时提高多种营养成分的育种计划具有实际意义。通过靶向稳定的QTL，育种者可以培育出营养特性得到改善的小麦品种，为全球粮食安全和人类健康做出贡献。
