Genomic Characterization of the Fruity Aroma Gene, FaFAD1, Reveals a Gene Dosage Effect on γ-Decalactone Production in Strawberry (Fragaria × ananassa)

Abstract

Strawberries produce numerous volatile compounds that contribute to the unique flavors of fruits. Among the many volatiles, γ-decalactone (γ-D) has the greatest contribution to the characteristic fruity aroma in strawberry fruit. The presence or absence of γ-D is controlled by a single locus, FaFAD1. However, this locus has not yet been systematically characterized in the octoploid strawberry genome. It has also been reported that the volatile content greatly varies among the strawberry varieties possessing FaFAD1, suggesting that another genetic factor could be responsible for the different levels of γ-D in fruit. In this study, we explored the genomic structure of FaFAD1 and determined the allele dosage of FaFAD1 that regulates variations of γ-D production in cultivated octoploid strawberry. The genome-wide association studies confirmed the major locus FaFAD1 that regulates the γ-D production in cultivated strawberry. With the hybrid capture-based next-generation sequencing analysis, a major presence–absence variation of FaFAD1 was discovered among γ-D producers and non-producers. To explore the genomic structure of FaFAD1 in the octoploid strawberry, three bacterial artificial chromosome (BAC) libraries were developed. A deletion of 8,262 bp was consistently found in the FaFAD1 region of γ-D non-producing varieties. With the newly developed InDel-based codominant marker genotyping, along with γ-D metabolite profiling data, we revealed the impact of gene dosage effect for the production of γ-D in the octoploid strawberry varieties. Altogether, this study provides systematic information of the prominent role of FaFAD1 presence and absence polymorphism in producing γ-D and proposes that both alleles of FaFAD1 are required to produce the highest content of fruity aroma in strawberry fruit.

Profiles of Volatile and Phenolic Compounds as Markers of Ripening Stage in Candonga Strawberries

“…Specifically, nonanal (Ald3) and benzaldehyde (Ald4) have been recently identified as volatiles, which enhance sweetness independently of the sugar content together with γ-decalactone (L2) and γ-dodecalactone (L3), which are among the three lactones directly correlated to the Red-H1 and Red-H2 samples ( Figure 3 B) [ 38 , 39 ]. Specifically, γ-decalactone (L2) gives the major contribution to the desirable “fruity”, “sweet” or “peach-like” aroma in strawberries [ 40 ]. In general, several lactone compounds are commonly described as key odorants, determining the pleasant and fruity notes to strawberries [ 28 ].…”

Quality Traits, Volatile Organic Compounds, and Expression of Key Flavor Genes in Strawberry Genotypes over Harvest Period

“…FaFAD1 expression had a strong correlation (0.716, p = 0.000) with decalactone levels which is in accordance with previous studies [55][56][57]; more importantly, we confirm the previous findings that the FaFAD1 gene is present in every genotype where γ-decalactone has been detected, and it is missing in non-producers. Recently, a deletion of 8262 bp was consistently found in the FaFAD1 region of γ-decalactone non-producing varieties [58]. Another interesting observation was the strong correlation of FaFAD1 expression with nerolidol levels (0.665, p < 0.001) and a low negative correlation with trans-cinnamic acid and phenylpropanes (−0.316 and −0.327, p < 0.05).…”

Images carried before the fire: The power, promise, and responsibility of latent phenotyping in plants

“…These conventional traits capture only a limited slice of true variability yet represent the traits of primary interest to plant breeders because of their commercial and economic value. However, other traits that are also key selection targets, such as quality (e.g., taste, smell, texture), root and shoot system architectures (e.g., leaf and root angle, branching complexity, compactness), and organ form (e.g., size and shape), are more challenging to define with a single variable (Fan et al, 2021;Farneti et al, 2017;Klee & Tieman, 2013;Larsen et al, 2019;Li et al, 2020;Migicovsky et al, 2016;Migicovsky, Sawler, et al, 2017;Oh et al, 2021;Schwieterman et al, 2014;Tieman et al, 2017;Verma et al, 2017;Yano et al, 2019;Zhao et al, 2019). These traits, unlike yield, plant height, or time to flowering, are inherently multidimensional, resulting in a proliferation of potentially oversimplified definitions and interpretations.…”