Phenotyping for QTL identification: A case study of resistance to Plasmopara viticola and Erysiphe necator in grapevine

• Published in: Frontiers in plant science Vol. 13; p. 930954
• Main Authors: Possamai, Tyrone, Wiedemann-Merdinoglu, Sabine
• Format: Journal Article
• Language: English
• Published: Switzerland Frontiers 11.08.2022; Frontiers Media S.A
• Subjects: Erysiphe necator; Genetics; grapevine; Life Sciences; phenotyping; Phytopathology and phytopharmacy; Plant Science; Plants genetics; Plasmopara viticola; QTL; resistance breeding; Vegetal Biology; resistance breeding; grapevine; Plasmopara viticola; QTL; Erysiphe necator; Rpv; Ren/Run; phenotyping
• ISSN: 1664-462X; 1664-462X
• DOI: 10.3389/fpls.2022.930954

Vitis vinifera is the most widely cultivated grapevine species. It is highly susceptible to Plasmopara viticola and Erysiphe necator , the causal agents of downy mildew (DM) and powdery mildew (PM), respectively. Current strategies to control DM and PM mainly rely on agrochemical applications that are potentially harmful to humans and the environment. Breeding for resistance to DM and PM in wine grape cultivars by introgressing resistance loci from wild Vitis spp. is a complementary and more sustainable solution to manage these two diseases. During the last two decades, 33 loci of resistance to P. viticola ( Rpv ) and 15 loci of resistance to E. necator ( Ren and Run ) have been identified. Phenotyping is salient for QTL characterization and understanding the genetic basis of resistant traits. However, phenotyping remains a major bottleneck for research on Rpv and Ren/Run loci and disease resistance evaluation. A thorough analysis of the literature on phenotyping methods used for DM and PM resistance evaluation highlighted phenotyping performed in the vineyard, greenhouse or laboratory with major sources of variation, such as environmental conditions, plant material (organ physiology and age), pathogen inoculum (genetic and origin), pathogen inoculation (natural or controlled), and disease assessment method (date, frequency, and method of scoring). All these factors affect resistance assessment and the quality of phenotyping data. We argue that the use of new technologies for disease symptom assessment, and the production and adoption of standardized experimental guidelines should enhance the accuracy and reliability of phenotyping data. This should contribute to a better replicability of resistance evaluation outputs, facilitate QTL identification, and contribute to streamline disease resistance breeding programs.