Although the potato chip industry is booming, and distinct chip-processing clones have been released over the past 60 years, the genetic architecture of their chip-processing characteristics remains largely unknown. Case-control genome-wide association studies (GWAS) with SolCAP SNP array data for chip-processing clones versus all other market classes in the 393-line potato diversity panel were performed using the GWASpoly R package, enabling detection of significant signals on chromosome 10. Our results were replicated using internal replication of a strata-corrected 190-line panel. Furthermore, the genomic scans employing selective sweep approaches such as the cross-population composite likelihood ratio method (XP-CLR) and PCAdapt redetected the same signals as those in our GWAS. Through applications of four selective sweep approaches, various genetic variants were found across the genome that had been differentially selected. These genomic regions under selection along with transcriptomic data analysis are involved in carbohydrate metabolism-related genes or loci and transcription factors, indicating to be associated with the improvement of chip-processing performance of potato cultivars. Kompetitive allele-specific PCR (KASP) assays were designed for the causal SNPs to use in validating the chip-processing clones. The results could have implications for genomics-assisted breeding of the promising chip-processing cultivars in potato.

Key message A Chip Processing phenotype in potato was characterized using both the case-control genome-wide association study and selective sweep approaches, pinpointing the associated genetic variants on chromosome 10, as well as finding variants under selection across the genome. Although with booming potato chip industry, distinct chip processing clones have been released over the past 60 years, the genetic architecture of their chip processing characteristics remains largely unknown. The case-control genome-wide association studies (GWAS) using SolCAP SNP array data for Chip Processing clones versus all other market classes in the 359-line potato diversity panel (Jo et al. 2022) were performed to detect significant signals on chromosome 10. The signals were redetected in the GWAS test using the strata-corrected 190-line panel and also genomic scans employing selective sweep approaches such as the cross-population composite likelihood ratio method (XP-CLR) and PCAdapt. Through applications of four selective sweep approaches including XP-CLR, PCAdapt, the integrated haplotype homozygosity score (iHS), and the cross-population extended haplotype homozygosity (XP-EHH) for a 227-line panel separated into two groups (chip processing vs non-chip processing) by principal component analysis, various genetic variants were found across the genome that had been differentially selected. These genomic regions under selection are involved in carbohydrate-related genes or loci and transcription factors, indicating to be associated with the improvement of chip processing performance of potato cultivars. The results could have implications for genomics-assisted breeding of the promising chip processing cultivars in potato.