Deducing genotypes for loci of interest from SNP array data via haplotype sharing, demonstrated for apple and cherry.

Breeders, collection curators, and other germplasm users require genetic information, both genome-wide and locus-specific, to effectively manage their genetically diverse plant material. SNP arrays have become the preferred platform to provide genome-wide genetic profiles for elite germplasm and could also provide locus-specific genotypic information. However, genotypic information for loci of interest such as those within PCR-based DNA fingerprinting panels and trait-predictive DNA tests is not readily extracted from SNP array data, thus creating a disconnect between historic and new data sets. This study aimed to establish a method for deducing genotypes at loci of interest from their associated SNP haplotypes, demonstrated for two fruit crops and three locus types: quantitative trait loci Ma and Ma3 for acidity in apple, apple fingerprinting microsatellite marker GD12, and Mendelian trait locus Rf for sweet cherry fruit color. Using phased data from an apple 8K SNP array and sweet cherry 6K SNP array, unique haplotypes spanning each target locus were associated with alleles of important breeding parents. These haplotypes were compared via identity-by-descent (IBD) or identity-by-state (IBS) to haplotypes present in germplasm important to U.S. apple and cherry breeding programs to deduce target locus alleles in this germplasm. While IBD segments were confidently tracked through pedigrees, confidence in allele identity among IBS segments used a shared length threshold. At least one allele per locus was deduced for 64-93% of the 181 individuals. Successful validation compared deduced Rf and GD12 genotypes with reported and newly obtained genotypes. Our approach can efficiently merge and expand genotypic data sets, deducing missing data and identifying errors, and is appropriate for any crop with SNP array data and historic genotypic data sets, especially where linkage disequilibrium is high. Locus-specific genotypic information extracted from genome-wide SNP data is expected to enhance confidence in management of genetic resources.

As It Stands: The Palouse Wild Cider Apple Breeding Program.

Providing hands-on education for the next generation of plant breeders would help maximize effectiveness of future breeding efforts. Such education should include training in introgression of crop wild relative alleles, which can increase genetic diversity while providing cultivar attributes that meet industry and consumer demands in a crop such as cider apple. Incorporation of DNA information in breeding decisions has become more common and is another skill future plant breeders need. The Palouse Wild Cider apple breeding program (PWCabp) was established at Washington State University in early 2014 as a student-run experiential learning opportunity. The objectives of this study were to describe the PWCabp's approaches, outcomes, and student involvement to date that has relied on a systematic operational structure, utilization of wild relatives, and incorporation of DNA information. Students chose the crop (cider apple) and initial target market and stakeholders (backyard growers and hobbyists of the Palouse region). Twelve target attributes were defined including high phenolics and red flesh. Phase one and two field trials were established. Two promising high-bitterness selections were identified and propagated. By running the PWCabp, more than 20 undergraduate and graduate students gained experience in the decisions and operations of a fruit breeding program. PWCabp activities have produced desirable new germplasm via utilization of highly diverse Malus germplasm and trained new plant breeding professionals via experiential learning.