Complementary approaches to dissect late leaf rust resistance in an interspecific raspberry population

Author:

Prado Melina1ORCID,da Silva Allison Vieira1,Campos Gabriela Romêro1,Borges Karina Lima Reis2,Yassue Rafael Massahiro3,Husein Gustavo1,Akens Felix Frederik4,Sposito Marcel Bellato1,Amorim Lilian1,Behrouzi Pariya4ORCID,Bustos-Korts Daniela5,Fritsche-Neto Roberto12

Affiliation:

1. Department of Genetics, Luiz de Queiroz College of Agriculture/University of São Paulo , Piracicaba 13418-900 , Brazil

2. Rice Research Station, Louisiana State University , Baton Rouge, LA 70803 , USA

3. GDM Seeds , Campinas 13092-599 , Brazil

4. Biometris, Wageningen University and Research , Wageningen 6708 PB , Netherlands

5. Facultad de Ciencias Agrarias y Alimantarias, Universidad Austral de Chile , Valdivia 5090000 , Chile

Abstract

Abstract Over the last 10 years, global raspberry production has increased by 47.89%, based mainly on the red raspberry species (Rubus idaeus). However, the black raspberry (Rubus occidentalis), although less consumed, is resistant to one of the most important diseases for the crop, the late leaf rust caused by Acculeastrum americanum fungus. In this context, genetic resistance is the most sustainable way to control the disease, mainly because there are no registered fungicides for late leaf rust in Brazil. Therefore, the aim was to understand the genetic architecture that controls resistance to late leaf rust in raspberries. For that, we used an interspecific multiparental population using the species mentioned above as parents, 2 different statistical approaches to associate the phenotypes with markers [GWAS (genome-wide association studies) and copula graphical models], and 2 phenotyping methodologies from the first to the 17th day after inoculation (high-throughput phenotyping with a multispectral camera and traditional phenotyping by disease severity scores). Our findings indicate that a locus of higher effect, at position 13.3 Mb on chromosome 5, possibly controls late leaf rust resistance, as both GWAS and the network suggested the same marker. Of the 12 genes flanking its region, 4 were possible receptors, 3 were likely defense executors, 1 gene was likely part of signaling cascades, and 4 were classified as nondefense related. Although the network and GWAS indicated the same higher effect genomic region, the network identified other different candidate regions, potentially complementing the genetic control comprehension.

Funder

FAPESP

Publisher

Oxford University Press (OUP)

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