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      Model-Assisted Estimation of the Genetic Variability in Physiological Parameters Related to Tomato Fruit Growth under Contrasted Water Conditions

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          Abstract

          Drought stress is a major abiotic stress threatening plant and crop productivity. In case of fleshy fruits, understanding mechanisms governing water and carbon accumulations and identifying genes, QTLs and phenotypes, that will enable trade-offs between fruit growth and quality under Water Deficit (WD) condition is a crucial challenge for breeders and growers. In the present work, 117 recombinant inbred lines of a population of Solanum lycopersicum were phenotyped under control and WD conditions. Plant water status, fruit growth and composition were measured and data were used to calibrate a process-based model describing water and carbon fluxes in a growing fruit as a function of plant and environment. Eight genotype-dependent model parameters were estimated using a multiobjective evolutionary algorithm in order to minimize the prediction errors of fruit dry and fresh mass throughout fruit development. WD increased the fruit dry matter content (up to 85%) and decreased its fresh weight (up to 60%), big fruit size genotypes being the most sensitive. The mean normalized root mean squared errors of the predictions ranged between 16–18% in the population. Variability in model genotypic parameters allowed us to explore diverse genetic strategies in response to WD. An interesting group of genotypes could be discriminated in which (i) the low loss of fresh mass under WD was associated with high active uptake of sugars and low value of the maximum cell wall extensibility, and (ii) the high dry matter content in control treatment (C) was associated with a slow decrease of mass flow. Using 501 SNP markers genotyped across the genome, a QTL analysis of model parameters allowed to detect three main QTLs related to xylem and phloem conductivities, on chromosomes 2, 4, and 8. The model was then applied to design ideotypes with high dry matter content in C condition and low fresh mass loss in WD condition. The ideotypes outperformed the RILs especially for large and medium fruit-size genotypes, by combining high pedicel conductance and high active uptake of sugars. Interestingly, five small fruit-size RILs were close to the selected ideotypes, and likely bear interesting traits and alleles for adaptation to WD.

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          Most cited references41

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          Mapping mendelian factors underlying quantitative traits using RFLP linkage maps.

          The advent of complete genetic linkage maps consisting of codominant DNA markers [typically restriction fragment length polymorphisms (RFLPs)] has stimulated interest in the systematic genetic dissection of discrete Mendelian factors underlying quantitative traits in experimental organisms. We describe here a set of analytical methods that modify and extend the classical theory for mapping such quantitative trait loci (QTLs). These include: (i) a method of identifying promising crosses for QTL mapping by exploiting a classical formula of SEWALL WRIGHT; (ii) a method (interval mapping) for exploiting the full power of RFLP linkage maps by adapting the approach of LOD score analysis used in human genetics, to obtain accurate estimates of the genetic location and phenotypic effect of QTLs; and (iii) a method (selective genotyping) that allows a substantial reduction in the number of progeny that need to be scored with the DNA markers. In addition to the exposition of the methods, explicit graphs are provided that allow experimental geneticists to estimate, in any particular case, the number of progeny required to map QTLs underlying a quantitative trait.
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            fw2.2: a quantitative trait locus key to the evolution of tomato fruit size.

            Domestication of many plants has correlated with dramatic increases in fruit size. In tomato, one quantitative trait locus (QTL), fw2.2, was responsible for a large step in this process. When transformed into large-fruited cultivars, a cosmid derived from the fw2.2 region of a small-fruited wild species reduced fruit size by the predicted amount and had the gene action expected for fw2.2. The cause of the QTL effect is a single gene, ORFX, that is expressed early in floral development, controls carpel cell number, and has a sequence suggesting structural similarity to the human oncogene c-H-ras p21. Alterations in fruit size, imparted by fw2.2 alleles, are most likely due to changes in regulation rather than in the sequence and structure of the encoded protein.
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              Any trait or trait-related allele can confer drought tolerance: just design the right drought scenario.

              Most traits associated with drought tolerance have a dual effect, positive in very severe scenarios and negative in milder scenarios, or the opposite trend. Their effects also depend on other climatic conditions such as evaporative demand or light, and on management practices. This is the case for processes associated with cell protection and with avoidance, but also for the maintenance of growth or photosynthesis, high water use efficiency, large root systems or reduced abortion rate under water deficit. Therefore, spectacular results obtained in one drought scenario may have a limited interest for improving food security in other geographical areas with water scarcity. The most relevant questions on drought tolerance are probably, 'Does a given allele confer a positive effect on yield in an appreciable proportion of years/scenarios in a given area or target population of environment (TPE)?'; 'In a given site or TPE, what is the trade-off between risk avoidance and maintained performance?'; and 'Will a given allele or trait have an increasingly positive effect with climate change?' Considerable progress has already occurred in drought tolerance. Nevertheless, explicitly associating traits for tolerance to drought scenarios may have profound consequences on the genetic strategies, with a necessary involvement of modelling.
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                Author and article information

                Contributors
                Journal
                Front Plant Sci
                Front Plant Sci
                Front. Plant Sci.
                Frontiers in Plant Science
                Frontiers Media S.A.
                1664-462X
                09 December 2016
                2016
                : 7
                : 1841
                Affiliations
                [1] 1Plantes et Systèmes de Culture Horticoles, Institut National de la Recherche Agronomique - Centre PACA Avignon, France
                [2] 2Unité Génétique et Amélioration des Fruits et Légumes, Institut National de la Recherche Agronomique – Centre PACA Montfavet, France
                Author notes

                Edited by: Lifeng Xu, Zhejiang University of Technology, China

                Reviewed by: Teemu Hölttä, University of Helsinki, Finland; Tsu-Wei Chen, Leibniz University of Hanover, Germany

                *Correspondence: Nadia Bertin nadia.bertin@ 123456inra.fr

                This article was submitted to Plant Biophysics and Modeling, a section of the journal Frontiers in Plant Science

                Article
                10.3389/fpls.2016.01841
                5145867
                c57ff742-041c-4ed2-9f5a-f3452cdca44f
                Copyright © 2016 Constantinescu, Memmah, Vercambre, Génard, Baldazzi, Causse, Albert, Brunel, Valsesia and Bertin.

                This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

                History
                : 26 August 2016
                : 22 November 2016
                Page count
                Figures: 8, Tables: 3, Equations: 12, References: 52, Pages: 17, Words: 12258
                Funding
                Funded by: Institut National de la Recherche Agronomique 10.13039/501100006488
                Funded by: Agence Nationale de la Recherche 10.13039/501100001665
                Categories
                Plant Science
                Original Research

                Plant science & Botany
                fleshy fruit,quality,ideotype,solanum lycopersicum,virtual fruit model,water stress,multiobjective optimization

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