Pedigree Validation in Polyploid Biparental Populations: A Framework for Error Detection, Diagnosis, and Resolution

Pedigree integrity is fundamental to genetic analysis and plant breeding. Yet pedigree errors do occur often and, if undetected, can compromise downstream genomic analyses. In breeding programs that are transitioning from phenotypic selection to genomic selection, many previously undetectable pedigree errors are suddenly “found” when genetic data are acquired. The challenge is particularly acute in autopolyploid species, in which complex inheritance patterns and uncertainty in allele dosage complicate the identification and interpretation of pedigree. In this study, we developed and evaluated a pedigree-validation framework for a tetraploid blueberry ( Vaccinium corymbosum ) dataset consisting of 15 biparental families, 1580 individuals, and 2451 targeted Diversity Arrays Technology (DArTag) markers. Sequential evaluation of population structure, parent–progeny compatibility, ancestry composition, and segregation patterns uncovered widespread pedigree inconsistencies, including mislabeled parental replicates, progeny misassignments, and the complete absence of one parental genotype from the dataset. The missing parent affected five independent families and was not detected by routine genotypic quality control procedures. Using segregation information from progeny, the missing parental genotype was reconstructed with ∼98% accuracy and independently validated across all affected families. Correction of pedigree assignments and recovery of the missing parent rescued five mapping populations that would otherwise have been discarded. The resulting dataset exhibited clearer population structure, reduced linkage-map inflation, and stronger quantitative trait locus (QTL) signals than the original dataset. These findings demonstrate that substantial pedigree errors can persist despite standard quality control procedures and highlight the value of integrating pedigree validation into polyploid breeding pipelines. More broadly, the study shows that datasets compromised by pedigree errors often can be recovered rather than discarded, preserving valuable breeding populations and time and effort invested, while improving the reliability of downstream genetic analyses.