Abstract
Fruit quality represents an important aspect of any fruit species, due to its economical importance and direct impact on consumers’ appreciation. In order to generate a compendium about the genomic intervals putatively involved in the control of the several fruit quality components, a Meta-quantitative trait loci (QTL) analysis was performed starting from a QTL mapping survey individually conducted on four full-sib populations. These progenies were simultaneously genotyped with 1289 SNP markers, of which 52 % were in common for at least two maps. The combination of the genotypic and phenotypic datasets allowed the identification of 56 QTLs, which were subsequently projected into a consensus map, reducing the total number of genomic intervals to 27 MetaQTLs. The majority of these regions, associated to fruit quality traits such as fruit skin color and flesh firmness, resulted also consistent with previous reports presented to date to the scientific community. This MetaQTL overview would represents a valuable source for genome anchoring and data mining investigation, suitable for a further in silico identification of relevant causal genes. As example is reported the case of Md-PG1, a gene known to control fruit firmness in apple and retrieved within the confidence interval of a MetaQTL associated to fruit firmness.
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Acknowledgments
This research was supported by the post-Doc project CANDI-HAP founded by the Autonomous Province of Trento. The author wants to thank also Pierluigi Magnago and his team for plant maintenance, Livio Fadanelli for apple storage, and Massimo Pindo for the SNP genotyping facility.
Data Archiving Statement
Information about the SNP markers used in this work are available at the Genome Database for Rosaceae (GDR: www.rosaceae.org).
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Suppl. Fig. 1
Trait distribution for fruit weight (panel B, D, F, H) and fruit firmness at harvest (panel A; C; E; G) assessed for the four populations: ‘FD’ (A and B panel), ‘FPL’ (C and D), ‘GDS’ (E and F) and ‘GDB’ (G and H). For each panel, the y-axes indicate the number of observations. The x-axes reports, instead, the kgcm−2 and the g for fruit firmness and weight, respectively. On each distribution the position of the parental cultivars is shown by arrows, while the black line indicates the best-fit line (DOC 46 kb)
Suppl. Fig. 2
Genetic alignment between the four individual maps (‘FD’, ‘FPL’ ‘GDS’ and ‘GDB’) and the consensus (CONS). In the figure the comparison of LG 3, 6, 11 and 16 is shown (PPT 158 kb)
Suppl. Fig. 3
QTL mapping confidence interval of ‘Fuji’ x ‘Delearly’ (‘FD’) (PPT 315 kb)
Suppl. Fig. 4
QTL mapping confidence interval of ‘Fuji’ x ‘Cripps Pink’ (‘FPL’) (PPT 100 kb)
Suppl. Fig. 5
QTL mapping confidence interval of ‘Golden Delicious’ x ‘Scarlet’ (‘GDS’) (PPT 123 kb)
Suppl. Fig. 6
QTL mapping confidence interval of ‘Golden Delicious’ x ‘Braeburn’ (‘GDB’) (PPT 110 kb)
Suppl. Table 1
QTL mapping survey for the ‘Fuji’ x ‘Delearly’ population. For each trait the linkage groups where the QTL was identified (LG), the LOD value (LOD), the percentage of variance explained by the QTL (R2) and the marker close to the QTL peak (Marker) is reported (DOCX 55 kb)
Suppl. Table 2
QTL mapping survey for the ‘Fuji’ x ‘Cripps Pink’ population. The description of the table is the same as for Suppl. Table 1 (DOCX 49 kb)
Suppl. Table 3
QTL mapping survey for the ‘Golden Delicious’ x ‘Scarlet’ population. The description of the table is the same as for Suppl. Table 1 (DOCX 51 kb)
Suppl. Table 4
QTL mapping survey for the ‘Golden Delicious’ x ‘Braeburn’ population. The description of the table is the same as for Suppl. Table 1. (DOCX 388 kb)
Suppl. Table 5
QTL model computed in order to define the number of MetaQTL per each LG (DOCX 28 kb)
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Costa, F. MetaQTL analysis provides a compendium of genomic loci controlling fruit quality traits in apple. Tree Genetics & Genomes 11, 819 (2015). https://doi.org/10.1007/s11295-014-0819-9
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DOI: https://doi.org/10.1007/s11295-014-0819-9