Title : Evaluating low-coverage whole-genome sequencing and genotype imputation for cost-effective genomic selection in apple
Abstract:
Genomic selection has considerable potential to accelerate genetic improvement in perennial fruit crops such as apple, where long generation intervals and extensive field evaluation can substantially increase the time and cost required for cultivar development. However, the cost of obtaining high density genomic information across large breeding populations remains an important consideration. Low coverage whole genome sequencing combined with genotype imputation may provide a flexible and cost effective alternative to fixed SNP genotyping arrays while retaining genome wide marker information.
This study evaluates the feasibility of low coverage whole genome sequencing and genotype imputation for genomic applications in apple. Oxford Nanopore Technologies (ONT) sequencing data from multiple apple cultivars were systematically subsampled across a range of sequencing depths and aligned to the apple reference genome. Genotypes were inferred using reference panel based imputation approaches and benchmarked against genotypes obtained using a high density apple SNP array. Imputation performance was assessed across sequencing depths using genotype concordance and correlation with independently generated array genotypes. The effects of reference panel composition, allele frequency and cultivar genetic relatedness were also investigated to identify factors influencing imputation performance.
Preliminary analyses demonstrate a progressive improvement in genotype recovery as sequencing depth increases, while also indicating that useful genomic information can be recovered from very low sequencing coverage when an appropriate reference haplotype panel is available. Performance varies across genomic regions and allele frequency classes, highlighting the importance of reference panel composition and population diversity when designing low cost sequencing strategies for genetically diverse apple germplasm.
These results provide a framework for determining the sequencing depth required to balance genotyping accuracy and sequencing cost in apple breeding populations. By combining low coverage sequencing with genotype imputation, this approach has the potential to increase the number of breeding individuals that can be genotyped within a fixed budget and facilitate broader implementation of genomic selection. More broadly, the study demonstrates how advances in whole genome sequencing and computational genomics can be integrated into practical breeding strategies for perennial fruit crops.
