Mapping of QTLs for citrus quality traits throughout the fruit maturation process on clementine (Citrus reticulata × C. sinensis) and mandarin (C. reticulata Blanco) genetic maps

Abstract

Citrus fruit quality is defined as the combination of physical and chemical traits; some of which may change during the ripening phase, e.g., acidity and sugar content. A clear understanding of their genetic control would be very helpful for marker-assisted breeding programs especially with regard to the juvenile phase and some reproductive features that hamper the selection of improved hybrids. A genetic study was thus performed on the heredity of quality traits and QTL detection based on segregation in a progeny generated from a cross between clementine cv “Commun” (Citrus × reticulata cv clementine) and mandarin cv “Willow leaf” (C. reticulata Blanco). Parental and consensus genetic linkage maps were constructed using 645 SNP and SSR markers. These maps were represented by 10 linkage groups in clementine and 12 linkage groups in mandarin, representing 75% and 58% respectively of the previously published clementine reference map. A total of 16 traits, including fruit mass, equatorial diameter, juice percentage, total soluble solids, acidity, pH, glucose, fructose, sucrose, and citric and malic acid concentrations were evaluated at three maturation dates. High variations indicating transgressive segregation were found for all traits, with normal or close to normal distributions. QTL analysis performed using the multiple QTL model allowed the detection of 34 QTLs on the three maps. QTLs were distributed in different linkage groups and generally detected at only one date of the ripening phase. The percentage of total variation explained ranged from 12 to 37% per QTL. Major QTLs (R2 ≥ 30%) were detected for equatorial diameter, glucose, and fructose (expressed in percentage dry matter) on linkage groups 8 and 9. Co-localization of QTLs controlling correlated and uncorrelated traits were mainly found on linkage groups 2, 4, 8, and 9, particularly between fruit mass and acidity.

Marker-Assisted Selection in Breeding for Fruit Trait Improvement: A Review

“…In Citrus, four significant QTLs for fruit weight were identified using GWAS analysis, in part confirming previous reports [79]. Major QTLs (R 2 ≥ 30%) were detected for equatorial diameter [108]. A QTL for yield was detected on LG2 in coffee, and it was significant in two different locations.…”

Inheritance and Quantitative Trait Loci Mapping of Aromatic Compounds from Clementine (Citrus × clementina Hort. ex Tan.) and Sweet Orange (C. × sinensis (L.) Osb.) Fruit Essential Oils

“…However, the complexity of an aromatic profile based on numerous compounds, some of which are at very low concentrations and sometimes undetectable, cannot be reproduced because most of the QTLs of these compounds are not detectable. Previous studies also revealed the complexity of the inheritance of sugar content and acidity, which are other key components of fruit quality [ 32 , 33 , 34 , 35 ]. QTLs vary among studies, as well as over the fruit-ripening period.…”

“…The observed segregation for major compounds suggests that essential oil production could also have polygenic control. In citrus, the genetic architecture of internal and external quality traits of mandarin fruits is being increasingly studied [ 32 , 33 , 34 , 35 ].…”

Discovery and exploration of genes related to important agronomic traits in fruit trees

“…Furthermore, the use of BLUPs improved the QTL detection power by blurring the environmental variance. Indeed, several studies have demonstrated the effectiveness of using BLUPs for QTL localization in different fruit species such as apple (Segura et al, 2009), citrus (Khefifi et al, 2022), and grapevine , where the experimental material had been phenotyped under different environments. The observed instability in common QTL detection might be due to a complex quantitative genetic model and different physiological mechanisms in the determination of different fruit-quality components in response to environmental variations between years (Fanizza et al, 2005).…”