Cereal pan-genomics, powered by long-read sequencing and multi-omics integration, provides high-resolution maps of structural variants, regulatory elements, and adaptive alleles across cultivated and wild germplasm. Here, we review how these comprehensive resources uncover trait-associated variation inaccessible to single- reference approaches, enabling haplotype-informed breeding, pathway engineering, and targeted introgression of wild alleles. Integration with regulatory genomics — the study of noncoding elements controlling gene expression — and 3D genome architecture further enables precision editing of noncoding elements for phenotypic fine-tuning. Together, these advances position cereal pan-genomics as a foundational platform for predictive crop design, accelerating the development of high- yielding, climate-resilient varieties while providing actionable guidance for breeding strategies.
Zhu et al. (Thu,) studied this question.