Haplotype Bias Detection Using Pedigree-Based Transmission Simulation: Traces of Selection That Occurred in Apple Breeding
With the increasing ability to integrate pedigree and genomic data, it is essential to evaluate their potential to uncover valuable genetic insights that can drive the advancement of crop breeding and conservation of genetic diversity. Pedigree analysis remains a fundamental approach for investigating the inheritance of phenotypic traits, exploring evolutionary history, and understanding hybridization processes in crop plants. Among these approaches, gene drop simulations using pedigree and allele origin data enable the construction of genetic maps and provide insights into complex genetic backgrounds. In this study, we developed a new method to identify useful genetic regions associated with single-nucleotide polymorphism (SNP) markers based on gene drop simulations, focusing on 185 Japanese domestic apple cultivars. By performing 10 million gene drop simulations, we generated null distributions for each founder haplotype, which revealed SNP markers with significant frequency biases, which is a potential signal for selection. Frequency biases were identified in eight founder haplotypes that were particularly consistent with genome-wide association studies peaks associated with key fruit traits such as malic acid and fructose content. Gene Ontology enrichment analysis suggested that these SNPs are not only associated with fruit traits but may also play a role in critical biological functions, including stress tolerance and reproductive processes, highlighting their broader relevance to crop resilience. Our integrative approach, which combines founder haplotype analysis with extensive gene drop simulations, effectively detects selection pressure, provides new insights into the genetic basis of apple breeding, and identifies SNP markers with strong potential to improve breeding programs.