2019 ASHS Annual Conference

There is a high consumer demand for sweet blackberries (Rubus subgenus Rubus). Fruit sugar production in related species is highly influenced by the environment and controlled by many genes, each providing small contributions to the phenotype. Many of the molecular pathways mediating sugar production are conserved across species. Therefore, a synteny-based approach was used to identify candidate genes responsible for sugar production in blackberry. Sugar quantitative trait loci (QTL) were identified from the Genome Database for the Rosaceae (GDR) QTL database for apple (Malus domestica), peach (Prunus persica), and alpine strawberry (Fragaria vesca) and synteny analysis was conducted to find conserved QTLs. Three syntenic QTLs that were conserved in at least two species were recovered. The physical regions for these QTLs were identified in the F. vesca v1.1 assembly and predicted genes within this region were annotated with Blast2GO. A total of 26 genes with functions associated with sugar production were extracted. Additionally, 789 sugar-associated genes were extracted from the M. domestica v3.0.a1 assembly. A BLAST search of the GDR Rubus reference transcriptome using the Fragaria and Malus genes was conducted. A total of 279 Rubus candidate transcripts were identified. Exons were predicted for each transcript using the Rubus occidentalis v 2 genome. The exons were separated into 2,122 individual sequences that were sent to Arbor Biosciences to design 9,355 Hyb-Seq baits with a 2X tiling density that covered 99.6% of the targeted regions. The Hyb-Seq baits were used in conjunction with a PacBio sequencing approach to genotype 40 cultivars with high and low sugar content from the University of Arkansas and USDA blackberry breeding programs. A total of 430,167 high quality circular consensus sequences were generated. The reads were mapped to the R occidentalis v 3 genome using MiniMap2 and polymorphisms were identified using FreeBayes. Polymorphism-trait associations are being identified for the high and low sugar groups for each breeding program. Future work will focus on developing diagnostic tests to predict sugar phenotypes.