Pearl millet is a crucial food crop in arid and semi-arid tropical regions, playing a vital role in food security and nutrition. It's naturally rich in iron (Fe) and zinc (Zn), essential micronutrients combating micronutrient malnutrition, a significant global health concern affecting over 2 billion people. Deficiencies in Fe and Zn, often coupled with protein deficiency, lead to serious health issues like anemia and Kwashiorkor. Biofortification, genetically enhancing micronutrient and protein content in crops, presents a promising solution. While conventional breeding is time-consuming and costly, molecular breeding offers a faster, more cost-effective approach. This study uses a genome-wide association study (GWAS) to identify specific genomic regions associated with Fe, Zn, and protein content in pearl millet, aiming to accelerate biofortification efforts through marker-assisted selection. Previous QTL mapping studies have identified some regions, but lacked the resolution to pinpoint specific genes. The availability of the pearl millet genome sequence allows for gene-level analysis, increasing the precision of marker identification. GWAS, leveraging high-throughput genotyping technologies and a large, diverse germplasm panel, is a powerful tool for this purpose. The study focuses on identifying SNPs (single nucleotide polymorphisms) strongly associated with Fe, Zn, and protein content, paving the way for marker-assisted breeding strategies to develop biofortified pearl millet varieties.

The literature review highlights the importance of pearl millet as a climate-resilient crop and its nutritional value, particularly its high Fe and Zn content compared to other cereals. The significant global health burden of micronutrient malnutrition, particularly Fe and Zn deficiency, is emphasized. Existing literature on biofortification strategies, including conventional and molecular breeding, is reviewed, highlighting the limitations of conventional methods and the potential of marker-assisted selection. Previous studies using QTL mapping have provided some insights into the genetic architecture of Fe and Zn content in pearl millet, but these studies have limitations due to lower mapping resolution. The availability of the pearl millet genome sequence and the potential of GWAS for high-resolution mapping of complex traits are discussed, positioning this study within the broader context of biofortification research.

A diverse panel of 281 advanced pearl millet inbred lines, including restorer and seed parents, was evaluated for Fe, Zn, and protein content across two seasons (rainy 2017 and summer 2018). The experimental design used was an alpha lattice with three replications. Standard agronomic practices were followed. Grain Fe and Zn content were analyzed using Inductively Coupled Plasma Optical Emission Spectrometry (ICP-OES) after wet acid digestion. Protein content was measured using Near-Infrared Spectroscopy (NIRS). Genomic DNA was extracted from leaf tissue, and genotyping was performed using the Diversity Arrays Technology (DArT) seq assay, generating 87,748 DArT seq markers. After filtering for quality, 58,719 high-quality SNPs were retained for analysis. Population structure was analyzed using ADMIXTURE, revealing six major genetic groups. Linkage disequilibrium (LD) was evaluated using pairwise R² values. Genome-wide association analysis was conducted using both General Linear Model (GLM) and Mixed Linear Model (MLM), with MLM chosen due to its superior ability to control for population structure and kinship effects. The significance threshold was set to -log10(p) < 10-3. Candidate genes were identified by comparing the physical positions of significantly associated SNPs to the pearl millet genome sequence annotations.

Significant variability and high heritability (>90%) were observed for Fe, Zn, and protein content across the inbred lines. A significant positive correlation (P<0.01) was found among the three traits. Genome-wide association mapping using MLM identified 78 significant MTAs: 18 for Fe, 43 for Zn, and 17 for protein content. Four SNPs were co-located for both Fe and Zn, suggesting shared genetic control. These SNPs explained 5.07% to 8.23% of phenotypic variation for Fe and 5.09% to 8.00% for Zn. The SNPs associated with protein content explained 5.11% to 5.68% of phenotypic variation. Candidate gene analysis revealed several genes associated with Fe and Zn homeostasis, including 'Late embryogenesis abundant protein', 'Myb domain', 'pentatricopeptide repeat', and 'iron ion binding'. Linkage disequilibrium decay analysis showed rapid decay, averaging 2.9 kb. The study also identified promising SNPs for marker assisted selection. For instance, Pgl05_135500493 and Pgl05_144482656 were promising for Fe content, while Pgl07_101483782, Pgl07_101483780 and Pgl07_147179490 were promising for Zn content. Finally, Pgl06_71295563 was identified as a promising SNP for protein content.

The findings demonstrate the feasibility of using GWAS to identify genomic regions and candidate genes associated with improved Fe, Zn, and protein content in pearl millet. The high variability and heritability of these traits suggest significant potential for genetic improvement through breeding. The identified SNPs and associated genes provide valuable targets for marker-assisted selection (MAS) in biofortification breeding programs. The co-localization of SNPs for Fe and Zn supports the possibility of simultaneously enhancing both traits. The rapid linkage disequilibrium decay observed suggests a high resolution in mapping these traits. This study complements and extends previous QTL mapping studies by providing gene-level resolution, facilitating a more precise approach to biofortification breeding. The identified SNPs can be used to develop diagnostic markers for efficient screening of breeding populations, reducing the reliance on costly and time-consuming phenotypic evaluation. The combination of MAS with the identification of promising genes will accelerate the development of biofortified pearl millet varieties for improved nutrition in vulnerable populations.

This GWAS study successfully identified genomic regions and candidate genes associated with Fe, Zn, and protein content in pearl millet. The results provide a foundation for developing marker-assisted selection strategies to accelerate the breeding of biofortified pearl millet varieties. The identification of promising SNPs and co-localized regions associated with both Fe and Zn is particularly valuable for simultaneous improvement of these traits. Further research should focus on fine-mapping these regions, validating the identified markers in diverse genetic backgrounds, and investigating the functional roles of the candidate genes to optimize biofortification strategies.

The study was conducted in two environments at a single location. The generalizability of the findings to other environments could be limited due to potential genotype-by-environment (GxE) interactions. Further validation of the identified markers in diverse environments and genetic backgrounds is necessary before widespread implementation in breeding programs. The study relied on a specific genotyping platform (DArT seq), and the results might vary with different genotyping technologies.