Crop management impacts the efficiency of quantitative trait loci (QTL) detection and use: case study of fruit load×QTL interactions

Abstract

Mapping studies using populations with introgressed marker-defined genomic regions are continuously increasing knowledge about quantitative trait loci (QTL) that correlate with variation in important crop traits. This knowledge is useful for plant breeding, although combining desired traits in one genotype might be complicated by the mode of inheritance and co-localization of QTL with antagonistic effects, and by physiological trade-offs, and feed-back or feed-forward mechanisms. Therefore, integrating advances at the genetic level with insight into influences of environment and crop management on crop performance remains difficult. Whereas mapping studies can pinpoint correlations between QTL and phenotypic traits for specific conditions, ignoring or overlooking the importance of environment or crop management can jeopardize the relevance of such assessments. Here, we focus on fruit load (a measure determining competition among fruits on one plant) and its strong modulation of QTL effects on fruit size and composition. Following an integral approach, we show which fruit traits are affected by fruit load, to which underlying processes these traits can be linked, and which processes at lower and higher integration levels are affected by fruit load (and subsequently influence fruit traits). This opinion paper (i) argues that a mechanistic framework to interpret interactions between fruit load and QTL effects is needed, (ii) pleads for consideration of the context of agronomic management when detecting QTL, (iii) makes a case for incorporating interacting factors in the experimental set-up of QTL mapping studies, and (iv) provides recommendations to improve efficiency in QTL detection and use, with particular focus on model-based marker-assisted breeding.

Genetic dissection of tomato rootstock effects on scion traits under moderate salinity

“…The negative correlation between fruit yield and soluble-solid content of the fruit juice was also found in citrus within a similar experiment on rootstock effects (Raga et al 2014). These results fit the hypothesis by Kromdijk et al (2014) that fruit composition is heavily influenced by fruit load and go further because at least part of this relationship is genetically supported by linked QTLs in chromosomes 3 and 6 of the tomato rootstock under moderate salinity. From the three fruit compositional traits influenced by the fruit load: water and solute accumulation, metabolic interconversions and the incorporation of solute into structural material discussed by Kromdijk et al (2014), it seems reasonable to assign to the rootstock an important role for the first one, water and nutrient availability.…”

“…Third, the TFW QTL detected for commercial fruits under moderate salinity in chromosome 1 was not detected under high salinity. Since both experiments were similar and uniform (fruit yield was evaluated at the same scion variety) it cannot be argued that crop management would be the reason of these differences (Kromdijk et al 2014). Instead, all those results together support the hypothesis that plants (grafted tomato plants) respond to different salinity levels through different receptors (Munnik and Meijer 2001) or different signaling systems that might depend on the stressinduced primary event (Kacperska 2004).…”

Inter-Species Comparative Analysis of Components of Soluble Sugar Concentration in Fleshy Fruits

“…Environments, growing conditions, and management practices may influence fruit growth and soluble sugar concentration, with different responses depending on species and genotype ( Coombe, 1976 ; Nookaraju et al, 2010 ; Beckles et al, 2012 ; Kromdijk et al, 2014 ; Kuhn et al, 2014 ; Soltis and Kliebenstein, 2015 ). This variability was clearly shown in the PCA analysis of mean cumulative values of sugar importation, metabolism and dilution ( Figure 5 ), confirming the analyses conducted in previous publications ( Quilot et al, 2004 ; Dai et al, 2009 ; Prudent et al, 2011 ) where the data were collected.…”

QTLs detected for individual sugars and soluble solids content in apple

“…All of the trees were grafted on M.9 dwarfing rootstocks and planted in 2008 at WSU's Sunrise Research Orchard, Wenatchee, WA (N 47 18.712 0 W 120 03.943 0 ). Fruitlets were hand-thinned to two to three fruitlets per cluster in an attempt to reduce the effects of crop load (Kromdijk et al 2014). …”