Of buds and bits: a meta-QTL study identifies stable QTL for berry quality and yield traits in cranberry mapping populations ( Ait.).

INTRODUCTION

For nearly two centuries, cranberry ( Ait.) breeders have improved fruit quality and yield by selecting traits on fruiting stems, termed "reproductive uprights." Crop improvement is accelerating rapidly in contemporary breeding programs due to modern genetic tools and high-throughput phenotyping methods, improving selection efficiency and accuracy.

METHODS

We conducted genotypic evaluation on 29 primary traits encompassing fruit quality, yield, and chemical composition in two full-sib cranberry breeding populations- ( 168) and ( 67)-over 3 years. Genetic characterization was further performed on 11 secondary traits derived from these primary traits.

RESULTS

For , 170 major quantitative trait loci (QTL; 0.10) were found with interval mapping, 150 major QTL were found with model mapping, and 9 QTL were found to be stable across multiple years. In , 69 major QTL were found with interval mapping, 81 major QTL were found with model mapping, and 4 QTL were found to be stable across multiple years. Meta-QTL represent stable genomic regions consistent across multiple years, populations, studies, or traits. Seven multi-trait meta-QTL were found in , one in , and one in the combined analysis of both populations. A total of 22 meta-QTL were identified in cross-study, cross-population analysis using digital traits for berry shape and size (8 meta-QTL), digital images for berry color (2 meta-QTL), and three-study cross-analysis (12 meta-QTL).

DISCUSSION

Together, these meta-QTL anchor high-throughput fruit quality phenotyping techniques to traditional phenotyping methods, validating state-of-the-art methods in cranberry phenotyping that will improve breeding accuracy, efficiency, and genetic gain in this globally significant fruit crop.