Unraveling the genetic architecture of blueberry fruit quality traits: major loci control organic acid content while more complex genetic mechanisms control texture and sugar content.

BACKGROUND

Fruit quality traits, including taste, flavor, texture, and shelf-life, have emerged as important breeding priorities in blueberry (Vaccinium corymbosum). Organic acids and sugars play crucial roles in the perception of blueberry taste/flavor, where low and high consumer liking are correlated with high organic acids and high sugars, respectively. Blueberry texture and appearance are also critical for shelf-life quality and consumers' willingness-to-pay. As the genetic mechanisms that determine these fruit quality traits remain largely unknown, in this study, an F mapping population was used to perform quantitative trait loci (QTL) mapping for pH, titratable acidity (TA), organic acids, total soluble solids (TSS), sugars, fruit size, and texture at harvest and/or post-storage and weight loss.

RESULTS

Twenty-eight QTLs were detected for acidity-related parameters (pH, TA, and organic acid content). Six QTLs for pH, TA, and citric acid, two for quinic acid, and two for shikimic acid with major effects were consistently detected across two years on the same genomic regions on chromosomes 3, 4, and 5, respectively. Putative candidate genes for these QTLs were also identified using comparative transcriptomic analysis. No QTL was detected for malic acid content, TSS, or individual sugar content. A total of 146 QTLs with minor effects were identified for texture- and size-related parameters. With a few exceptions, these QTLs were generally inconsistent over years and post-storage, indicating a highly quantitative nature.

CONCLUSIONS

Our findings enhance the understanding of the genetic basis underlying fruit quality traits in blueberry and guide future work to exploit DNA-informed selection strategies in blueberry breeding programs. The major-effect QTLs identified for acidity-related fruit characteristics could be potential targets to develop DNA markers for marker-assisted selection (MAS). On the other hand, genomic selection may be a more suitable approach than MAS when targeting fruit texture, sugars, or size.