4.7 Article

Comprehensive QTL mapping survey dissects the complex fruit texture physiology in apple (Malus x domestica Borkh.).

Journal

JOURNAL OF EXPERIMENTAL BOTANY
Volume 63, Issue 3, Pages 1107-1121

Publisher

OXFORD UNIV PRESS
DOI: 10.1093/jxb/err326

Keywords

Apple fruit texture; cell wall genes; ethylene; in silico gene mining; mechanical and acoustic components; phenomics; QTL mapping; transcription assay

Categories

Funding

  1. CANDI-HAP
  2. Autonomous Province of Trento

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Fruit ripening is a complex physiological process in plants whereby cell wall programmed changes occur mainly to promote seed dispersal. Cell wall modification also directly regulates the textural properties, a fundamental aspect of fruit quality. In this study, two full-sib populations of apple, with 'Fuji' as the common maternal parent, crossed with 'Delearly' and 'Pink Lady', were used to understand the control of fruit texture by QTL mapping and in silico gene mining. Texture was dissected with a novel high resolution phenomics strategy, simultaneously profiling both mechanical and acoustic fruit texture components. In 'FujixDelearly' nine linkage groups were associated with QTLs accounting from 15.6% to 49% of the total variance, and a highly significant QTL cluster for both textural components was mapped on chromosome 10 and co-located with Md-PG1, a polygalacturonase gene that, in apple, is known to be involved in cell wall metabolism processes. In addition, other candidate genes related to Md-NOR and Md-RIN transcription factors, Md-Pel (pectate lyase), and Md-ACS1 were mapped within statistical intervals. In 'FujixPink Lady', a smaller set of linkage groups associated with the QTLs identified for fruit texture (15.9-34.6% variance) was observed. The analysis of the phenotypic variance over a two-dimensional PCA plot highlighted a transgressive segregation for this progeny, revealing two QTL sets distinctively related to both mechanical and acoustic texture components. The mining of the apple genome allowed the discovery of the gene inventory underlying each QTL, and functional profile assessment unravelled specific gene expression patterns of these candidate genes.

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