Genomic Prediction of Disease Resistance Provides a Path to Marker Assisted Restoration in a Wetland Foundation Tree Species

Abstract

Tree species worldwide are under threat from non‐native pathogens that impact forests and the ecosystem services they provide. Myrtle rust, caused by Austropuccinia psidii , is one example, first detected in Australia in 2010. This fungal pathogen infects immature tissue from a wide range of Myrtaceae hosts, including the wetland foundation species Melaleuca quinquenervia . Durable restoration action for this species would preferentially incorporate disease‐resistant individuals. Our aim for this study was to identify genetic markers and develop a genomic prediction model that could assist with selection for resistance. We conducted artificial inoculation of a panel of seedlings and measured their immune responses to myrtle rust. We then performed whole genome sequencing (3.2 M common SNPs) and conducted a Genome Wide Association Study ( N = 492), which revealed clusters of significantly associated SNPs in three chromosomal regions, including clusters of putative R genes. Associated SNPs were filtered to a panel of 1049 for a highly accurate genomic prediction model ( R = 0.83, precision = 0.65 for predicting which plants were in the top third for resistance). This provides a relatively inexpensive approach to identifying resistant individuals or seed lots for restoration and a template for managing myrtle rust impacts while maintaining population genetic diversity.

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