The genomic studies concerning fruit species have been tremendously increased to characterize and analyze genetic diversity and conservation of fruit species germplasm resources; based on morphological characteristics and molecular markers [ 21- 23].
Consequently, additional phenotypic data on the application population are needed before drawing reliable conclusions on genomic selection for fruit cropping.
The application of genomic selection in fruit tree crops is expected to enhance breeding efficiency by increasing prediction accuracy, increasing selection intensity and decreasing generation interval.
Earlier high-throughput genomic efforts on fruit ripening and quality have been reported by several groups, with the first being Aharoni et al. who identified genes related to strawberry fruit quality [ 17].
Accuracies of genomic prediction for fruit cropping were also very low, except in AF4_31Ga (Table 1), while phenotypic variance was large for this trait and phenotypic distributions were almost symmetric in all application FS families, except in AF2_Pi63.
Our analysis of invertebrate genomic sequences (mosquito, fruit fly and nematode) indicates the presence of an additional downstream A-rich element (Fig. 3, mosquito element 7) with positioning similar to the mammalian G-rich sequences.
Based on the results of genomic selection for fruit acidity in apple, the SNP marker ss475882883 on LG08 (19658610) had the largest effect was co-localized with a RING finger and CHY zinc finger domain-containing protein gene (MDP0000294924) [ 28].
Despite active genomic studies of fruit-bearing Rosaceae, molecular studies of ornamental roses have been limited, except for those focused on supporting breeding strategies.
For example, 16, 16 and 13 chitinase and chitinase-like genes were identified in the genomic databases of the fruit fly, Drosophila melanogaster, the red flour beetle, Tribolium castaneum and the African malaria mosquito, An. gambiae, respectively [22].
Several CGs mapped to genomic regions corresponding to fruit quality QTLs reported in other studies.
This would include, for example, molecular mapping of genomic regions associated with fruit quality control and, eventually, marker assisted selection.
