Predicting Flowering Behavior and Exploring Its Genetic Determinism in an Apple Multi-family Population Based on Statistical Indices and Simplified Phenotyping

• Main Authors: Jean-Baptiste Durand, Alix Allard, Baptiste Guitton, Eric van de Weg, Marco C. A. M. Bink, Evelyne Costes
• Format: Article
• Language: English
• Published: Frontiers Media S.A. 2017-06-01
• Series: Frontiers in Plant Science
• Subjects: bayes factor; biennial bearing; entropy; Malus × domestica; markov models; pedigree based analysis
• Online Access: http://journal.frontiersin.org/article/10.3389/fpls.2017.00858/full

Irregular flowering over years is commonly observed in fruit trees. The early prediction of tree behavior is highly desirable in breeding programmes. This study aims at performing such predictions, combining simplified phenotyping and statistics methods. Sequences of vegetative vs. floral annual shoots (AS) were observed along axes in trees belonging to five apple related full-sib families. Sequences were analyzed using Markovian and linear mixed models including year and site effects. Indices of flowering irregularity, periodicity and synchronicity were estimated, at tree and axis scales. They were used to predict tree behavior and detect QTL with a Bayesian pedigree-based analysis, using an integrated genetic map containing 6,849 SNPs. The combination of a Biennial Bearing Index (BBI) with an autoregressive coefficient (γg) efficiently predicted and classified the genotype behaviors, despite few misclassifications. Four QTLs common to BBIs and γg and one for synchronicity were highlighted and revealed the complex genetic architecture of the traits. Irregularity resulted from high AS synchronism, whereas regularity resulted from either asynchronous locally alternating or continual regular AS flowering. A relevant and time-saving method, based on a posteriori sampling of axes and statistical indices is proposed, which is efficient to evaluate the tree breeding values for flowering regularity and could be transferred to other species.