Genomic prediction of resistance to Phytophthora megakarya in cacao from a sparse host-pathogen screen

Genomic prediction of cacao resistance to black pod rot by Phytophthora megakarya achieved predictive ability 0.41 for phenotypically untested clones using 947 cacao clones and 58 isolates.

• Why it matters: Most genomic prediction work in plant breeding uses only host genotypes, leaving unclear whether modeling pathogen genomic relatedness improves quantitative disease prediction in a structured host–pathogen system.
• What they did: The study genotyped 947 cacao clones with a 10K-SNP panel and sequenced 67 P. megakarya isolates at 3,505 virulence-associated genes and 2,774 SNP loci, then fit mixed linear models to lesion diameters from 30 detached-pod bioassays.
• The result: Isolate differences explained more lesion-size variance than clone differences (0.34 vs 0.27), and adding within-subpopulation isolate genomic relatedness did not improve fit or prediction, while host genomic relationships enabled prediction and stable clone rankings (genomic correlation 0.86 ± 0.06).

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