Genome-wide association identifies key loci controlling blackberry postharvest quality

• Published in: Frontiers in plant science 2023-06, Vol.14, p.1182790-1182790
• Main Authors: Chizk, T Mason, Clark, John R, Johns, Carmen, Nelson, Lacy, Ashrafi, Hamid, Aryal, Rishi, Worthington, Margaret L
• Format: Article
• Language: English
• Subjects: firmness; GWAS; pectin methylesterase (PME); Plant Science; polygalacaturonase; red drupelet reversion; Rubus
• ISSN: 1664-462X; 1664-462X
• DOI: 10.3389/fpls.2023.1182790

Blackberry ( subgenus ) is a soft-fruited specialty crop that often suffers economic losses due to degradation in the shipping process. During transportation, fresh-market blackberries commonly leak, decay, deform, or become discolored through a disorder known as red drupelet reversion (RDR). Over the past 50 years, breeding programs have achieved better fruit firmness and postharvest quality through traditional selection methods, but the underlying genetic variation is poorly understood. We conducted a genome-wide association of fruit firmness and RDR measured in 300 tetraploid fresh-market blackberry genotypes from 2019-2021 with 65,995 SNPs concentrated in genic regions of the reference genome. Fruit firmness and RDR had entry-mean broad sense heritabilities of 68% and 34%, respectively. Three variants on homologs of polygalacturonase (PG), pectin methylesterase (PME), and glucan endo-1,3-β-glucosidase explained 27% of variance in fruit firmness and were located on chromosomes Ra06, Ra01, and Ra02, respectively. Another PG homolog variant on chromosome Ra02 explained 8% of variance in RDR, but it was in strong linkage disequilibrium with 212 other RDR-associated SNPs across a 23 Mb region. A large cluster of six PME and PME inhibitor homologs was located near the fruit firmness quantitative trait locus (QTL) identified on Ra01. RDR and fruit firmness shared a significant negative correlation ( = -0.28) and overlapping QTL regions on Ra02 in this study. Our work demonstrates the complex nature of postharvest quality traits in blackberry, which are likely controlled by many small-effect QTLs. This study is the first large-scale effort to map the genetic control of quantitative traits in blackberry and provides a strong framework for future GWAS. Phenotypic and genotypic datasets may be used to train genomic selection models that target the improvement of postharvest quality.