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Investigating the multi-disease challenge in apricot through single and multienvironment genome wide association studies

Authors
  • Serrie, Marie
  • Segura, Vincent
  • Blanc, Alain
  • Brun, Laurent
  • Combe, Freddy
  • Fleury, Amandine
  • Le-Pans, Mathilde
  • Signoret, Véronique
  • Viret, Sabrina
  • Audergon, Jean-Marc
  • Quilot-Turion, Bénédicte
  • Roth, Morgane
Publication Date
Apr 22, 2024
Source
HAL-Descartes
Keywords
Language
English
License
Unknown
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Abstract

Over their entire lifetime, apricot trees are exposed to a wide range of pests and diseases incurring for significant sanitary impacts and economic losses. Several sources of partial resistances have been identified but the underlying genetic architecture has yet to be elucidated for most diseases. In this study, the objective is to identify the genetic components underlying resistance – or low susceptibility – of two major diseases in apricot: blossom blight (Monilinia spp.) and leaf rust (Tranzschelia spp.). To do so, a core collection composed by 150 accessions replicated in 5 randomized blocs was grown under low phytosanitary conditions in two environmentally contrasted locations in South-East of France. These accessions have been densely sequenced with the Illumina HiSeq 2000 NGS technique. After monitoring rust and blossom blight damages from 2020 to 2023, we dissected the observed phenotypic variation into genotype, environment and their interactions effects via descriptive statistics and variance decompositions. To identify genetic markers linked to resistance components, we firstly performed genome wide association studies (GWAS) for each environment separately. We found stable genetic effects across the environment, reflected by robust quantitative trait loci (QTLs). In contrasts, some QTLs were only detected in a specific set of trial. To jointly analyse site-specific GWAS results and improve statistical power, we used a meta-analysis GWAS approach. By using a random effect procedure, we were able to consider the heterogeneity of the QTL effects across environments and the correlation between the single-environment GWAS. In the last approach we performed multi-environment GWAS with the MTMM package to dissociate QTLs from QTL by environment interactions effects. The present results provide insights into the genetic basis of blossom blight and rust susceptibility in apricot and therefore contribute to the development of genomics-assisted breeding to improve biotic resilience in apricot varieties.

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