Improving wheat grain composition for human health by constructing a QTL atlas for essential minerals

Mineral deficiencies, particularly iron (Fe) and zinc (Zn), pose significant global health challenges, impacting billions worldwide. Wheat, a staple crop, is a crucial source of dietary minerals, making its biofortification a critical area of research. Current strategies include agronomic biofortification (mineral fertilization) and genetic biofortification (improving the plant's ability to absorb and transport minerals). While agronomic approaches offer benefits, they increase production costs and aren't accessible to all farmers. Genetic biofortification is therefore a priority. Existing research shows variation in mineral content among wheat cultivars, but exploiting this variation for breeding has proved challenging due to multigenic control and environmental influences. This study utilizes the A. E. Watkins landrace collection, known for its genetic diversity, to identify QTLs and associated genes influencing mineral accumulation in wheat grain. The focus is on Fe, Zn, Ca, Mg, K, and Cu, minerals frequently deficient in human and livestock diets.

Extensive research has explored the genetic basis of mineral concentration in wheat. Numerous studies have reported QTLs and Marker-Trait Associations (MTAs) for Fe and Zn across various chromosomes. Positive correlations between Fe and Zn concentrations have been consistently observed, suggesting shared transport mechanisms. While QTLs for other minerals like Mg and Ca have been less extensively studied, the literature indicates significant genetic variability that can be exploited for biofortification. The impact of processing (milling) on mineral bioavailability is also recognized, with significant losses occurring during the refining of flour. The location of minerals within the grain (embryo, aleurone layer) affects their bioavailability, with phytates binding metals and reducing their uptake. This review highlights the importance of genetic biofortification as a sustainable solution to mineral deficiency, emphasizing the need for identifying and characterizing QTLs for enhanced nutrient content and bioavailability.

Three biparental populations derived from crosses between the UK spring wheat cv. Paragon and three A. E. Watkins landraces (W160, W239, W292) were used. These populations comprised 94 F4 recombinant inbred lines (RILs) each grown in replicated multi-environment field trials over three years with one or two nitrogen fertilization levels. This generated 11 datasets analyzed for nine minerals (Ca, Cu, Fe, K, Mg, Mn, Na, S, Zn) using ICP-OES. Mineral concentrations were measured in grain and straw. Various traits were measured, including grain yield, plant height, straw biomass, and the calculated total mineral amount in grain per square meter (off-take). Grain mineral deviation, reflecting mineral accumulation relative to yield, was also calculated. QTL analysis was performed using R software, focusing on QTLs consistently mapped in at least two datasets with LOD scores exceeding 5 in at least one. Gene content analysis focused on 5 Mb of DNA on either side of the QTL with the highest LOD score. Candidate gene verification was performed via mutagenesis using TILLING lines for the major 5A Ca QTL. Genomic comparisons between Paragon and landraces were performed to identify SNPs and copy number variations in the identified QTL regions.

The study identified 774 QTLs across various traits and 23 consistent QTLs for essential minerals (Fe, Zn, Ca, Mg, K, Cu) with LOD scores above 5 in at least one dataset. These 23 QTLs, with 16 increasing alleles from landraces and seven from Paragon, were located on 14 of the 21 chromosomes. Clusters of QTLs were found on chromosomes 5A, 6A, and 7A. The highest LOD score and most consistent QTL was found on chromosome 5A for Ca, which was validated by mutagenesis studies using TILLING lines. This confirmed *TraesCS5A02G543300*, a cation transporter/plasma membrane ATPase gene, as the candidate gene responsible for this QTL. The study also identified QTLs for Cu on chromosomes 4B, 5B, 7A, 7B, and 7D; Fe on chromosomes 2D, 3A, 5D, and 6A; Mg on chromosomes 5A, 6A, 6D, and 7A; K on chromosomes 3D, 4B, and 5A; and Zn on chromosomes 5A, 6A, and 7A. Genomic analysis of these QTL regions revealed SNPs, gene deletions, and copy number variations that may contribute to mineral variation. Positive correlations were observed between Fe and Zn, and between Ca and Mg concentrations. The results suggest significant variation in modern elite genotypes for several minerals (Cu, Ca, Mg, K), in addition to that found in landraces (Fe, Zn).

This study provides a comprehensive QTL atlas for essential minerals in wheat, advancing the understanding of the genetic architecture underlying mineral accumulation. The identification of QTLs with high LOD scores, confirmed in multiple environments, offers valuable targets for wheat biofortification breeding programs. The successful validation of *TraesCS5A02G543300* as the candidate gene for the major Ca QTL demonstrates the feasibility of using this approach to identify and manipulate genes for improving mineral content. The positive correlations between some minerals suggest the possibility of pleiotropic effects or shared transport mechanisms, opening avenues for simultaneous improvement of multiple minerals. The findings have implications for enhancing the nutritional value of wheat, addressing prevalent mineral deficiencies in human and livestock populations. The inclusion of µg/grain as an additional measure of mineral content is crucial as it accounts for the impact of yield on mineral concentration, providing breeders with more robust targets.

This research provides a valuable resource for wheat breeders, offering a comprehensive QTL atlas for essential minerals. The identification of specific candidate genes, such as *TraesCS5A02G543300* for Ca, highlights the potential for marker-assisted selection to accelerate the development of biofortified wheat varieties. Future research should focus on fine-mapping of these QTLs, identifying additional candidate genes, and investigating the interactions between these genes and environmental factors. Investigating the regulatory networks of these genes and mechanisms determining bioavailability is also warranted.

The study focused on a limited number of populations and environments. Although multiple years and nitrogen treatments were included, the findings might not fully capture the extent of genetic diversity across diverse geographic regions and soil conditions. Further investigation across a broader range of genetic backgrounds and environments is warranted to validate these QTLs and assess their applicability in different agricultural settings. The analysis focused on 5 Mb regions around QTLs; some candidate genes potentially outside this range may have been missed.