Optimizing genomic selection for blight resistance in American chestnut backcross populations: A trade-off with American chestnut ancestry implies resistance is polygenic.

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ID: 73435
2020
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Abstract
American chestnut was once a foundation species of eastern North American forests, but was rendered functionally extinct in the early 20th century by an exotic fungal blight (). Over the past 30 years, the American Chestnut Foundation (TACF) has pursued backcross breeding to generate hybrids that combine the timber-type form of American chestnut with the blight resistance of Chinese chestnut based on a hypothesis of major gene resistance. To accelerate selection within two backcross populations that descended from two Chinese chestnuts, we developed genomic prediction models for five presence/absence blight phenotypes of 1,230 BCF selection candidates and average canker severity of their BCF progeny. We also genotyped pure Chinese and American chestnut reference panels to estimate the proportion of BCF genomes inherited from parent species. We found that genomic prediction from a method that assumes an infinitesimal model of inheritance (HBLUP) has similar accuracy to a method that tends to perform well for traits controlled by major genes (Bayes C). Furthermore, the proportion of BCF trees' genomes inherited from American chestnut was negatively correlated with the blight resistance of these trees and their progeny. On average, selected BCF trees inherited 83% of their genome from American chestnut and have blight resistance that is intermediate between F hybrids and American chestnut. Results suggest polygenic inheritance of blight resistance. The blight resistance of restoration populations will be enhanced through recurrent selection, by advancing additional sources of resistance through fewer backcross generations, and by potentially by breeding with transgenic blight-tolerant trees.
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westbrook2020optimizingevolutionary Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors Westbrook, Jared W;Zhang, Qian;Mandal, Mihir K;Jenkins, Eric V;Barth, Laura E;Jenkins, Jerry W;Grimwood, Jane;Schmutz, Jeremy;Holliday, Jason A;
Journal evolutionary applications
Year 2020
DOI
10.1111/eva.12886
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