SMRT–AgRenSeq-d in potato (Solanum tuberosum) as a method to identify candidates for the nematode resistance Gpa5

Abstract

Potato is the third most important food crop in the world. Diverse pathogens threaten sustainable crop production but can be controlled, in many cases, through the deployment of disease resistance genes belonging to the family of nucleotide-binding, leucine-rich-repeat (NLR) genes. To identify effective disease resistance genes in established varieties, we have successfully established SMRT–AgRenSeq in tetraploid potatoes and have further enhanced the methodology by including dRenSeq in an approach that we term SMR–AgRenSeq-d. The inclusion of dRenSeq enables the filtering of candidates after the association analysis by establishing a presence/absence matrix across resistant and susceptible varieties that is translated into an F1 score. Using a SMRT–RenSeq-based sequence representation of the NLRome from the cultivar Innovator, SMRT–AgRenSeq-d analyses reliably identified the late blight resistance benchmark genes Rpi-R1, Rpi-R2-like, Rpi-R3a, and Rpi-R3b in a panel of 117 varieties with variable phenotype penetrations. All benchmark genes were identified with an F1 score of 1, which indicates absolute linkage in the panel. This method also identified nine strong candidates for Gpa5 that controls the potato cyst nematode (PCN) species Globodera pallida (pathotypes Pa2/3). Assuming that NLRs are involved in controlling many types of resistances, SMRT–AgRenSeq-d can readily be applied to diverse crops and pathogen systems.

Acknowledgements

The authors thank John T. Jones for providing critical feedback on the manuscript. Further, we acknowledge the Research/Scientific Computing teams at The James Hutton Institute and NIAB for providing computational resources and technical support for the ‘UK’s Crop Diversity Bioinformatics HPC’ (BBSRC grant BB/S019669/1), use of which has contributed to the results reported within this paper. This work was supported by the Rural & Environment Science & Analytical Services (RESAS) Division of the Scottish Government through project JHI-B1-1, the Biotechnology and Biological Sciences Research Council (BBSRC) through award BB/S015663/1 and the Royal Society through award NAF\R1\201061. YW was supported through the CSC scholarship program, China. LB was supported through the East of Scotland Bioscience Doctoral Training Partnership (EASTBIO DTP), funded by the BBSRC award BB/T00875X/1. AK was supported through a Research Leaders 2025 fellowship funded by European Union’s Horizon 2020 research and innovation programme under Marie Sklodowska-Curie grant agreement no. 754380.

Author Contributions

Y.W., L.B., T.M.A., Y.W.C., M.A., A.K. conducted the computational analyses, developed the association panel and the F1 score. J.L., X.W., B.H. provided material for this study and contributed towards the writing of the manuscript and the independent validation. V.Y., D.T., and Y.W. conducted the PCN score and HC marker analysis. T.M.A. and K.N. conducted the phylogenetic analysis. S.O. provided genomic data and recombination analysis for this study. M.B. and I.H. conceived this work and secured funding. All authors have read and endorsed the manuscript.

Data availability

BioProjects: ERP141787-Illumina Reads/contigs. ERP141789-HiFi Reads/contigs. Code: https://github.com/TMAdams/gpa5_smrt_agrenseq_paper

Conflict of interest statements

The authors declare that they have no competing interests.

Supplementary data

Supplementary data is available at Horticulture Research online.

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