Unlocking diversity from wild relatives of perennial fruit crops in the pan-genomics era.

Breeding perennial fruit crops runs into several big hurdles. The plants are highly heterozygous, they take a long time to reach maturity, and crossing them with wild relatives often brings along unwanted linked genes (linkage drag). A single reference genome can’t show the many structural differences and the full genetic diversity found in wild germplasm. This work supports building and studying pan‑genomes for these crops. By combining high‑throughput long‑read sequencing with Hi‑C chromosome‑conformation data, we can create a graph‑based pan‑genome that includes both core and dispensable regions. The method looks for structural variations, copy‑number changes, and single‑nucleotide polymorphisms that affect important traits such as disease resistance and climate resilience. The

computational workflow checks how efficiently reads align, how accurately variants are detected, and how wild alleles evolve over time. Using pan‑genomic graphs helps avoid the limits of traditional breeding, making marker‑assisted selection and genomic prediction more precise. Overall, this approach provides a solid foundation for modernizing perennial crop breeding programs with advanced bioinformatics pipelines.

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