From Association to Causality: Next-Generation GWAS, Pangenomes, and Multi-Omics Driving Gene Discovery and Precision Breeding in Cereal Crops

Genome-wide association studies (GWASs) have become a central tool in plant genomics, providing high-resolution access to the genetic architecture of complex traits in cereal crops. This review observes the application of GWASs to biotic and abiotic stress responses and nutritional quality in rice (Oryza sativa), wheat (Triticum aestivum), maize (Zea mays), and barley (Hordeum vulgare). However, conventional SNP-based GWASs may overlook structural and presence–absence variation, and significant associations do not by themselves identify the causal gene or variant. Recent methodological developments, including multi-locus and environment-aware models, can improve the detection of complex genetic effects, while pan-genomic and graph-based references broaden the range of genomic variation available for association analysis. Integrating GWASs with transcriptomics, metabolomics, and proteomics provides additional functional evidence for candidate-gene prioritization and interpretation of associated loci. Fine mapping and functional validation, including genome-editing approaches, further help to test candidate-gene function. Together, these advances strengthen the progression from statistical association to biological interpretation and breeding-relevant genetic variation. This review discusses their current applications, limitations, and potential for improving cereal breeding.