Genomic Selection for Quantitative Adult Plant Stem Rust Resistance in Wheat

Quantitative adult plant resistance (APR) to stem rust (Puccinia graminis f. sp. tritici) is an important breeding target in wheat (Triticum aestivum L.) and a potential target for genomic selection (GS). To evaluate the relative importance of known APR loci in applying GS, we characterized a set of CIMMYT germplasm at important APR loci and on a genome-wide profile using genotyping-by-sequencing (GBS). Using this germplasm, we describe the genetic architecture and evaluate prediction models for APR using data from the international Ug99 stem rust screening nurseries. Prediction models incorporating markers linked to important APR loci and seedling phenotype scores as fixed effects were evaluated along with the classic prediction models: Multiple linear regression (MLR), Genomic best linear unbiased prediction (G-BLUP), Bayesian Lasso (BL), and Bayes Cp (BCp). We found the Sr2 region to play an important role in APR in this germplasm. A model using Sr2 linked markers as fixed effects in G-BLUP was more accurate than MLR with Sr2 linked markers (p-value = 0.12), and ordinary G-BLUP (p-value = 0.15). Incorporating seedling phenotype information as fixed effects in G-BLUP did not consistently increase accuracy. Overall, levels of prediction accuracy found in this study indicate that GS can be effectively applied to improve stem rust APR in this germplasm, and if genotypes at Sr2 linked markers are available, modeling these genotypes as fixed effects could lead to better predictions. Stem rust is a globally widespread and highly damaging disease of wheat, capable of causing up to 100% yield losses in susceptible varieties (Park, 2007). After adoption of resistant varieties during the 1950s, outbreaks of stem rust became rare. However, the recent emergence of a new stem rust race group named Ug99 (Pretorius et al., 2000) capable of infecting the majority of the worlds’ wheat germplasm (Singh et al., 2006), has highlighted the need for breeding efforts focused on durable stem rust resistance. Resistance to stem rust generally falls into two categories: (i) all stage resistance, which is often conferred by race-specific genes involved in pathogen recognition and associated with a hypersensitive response, and (ii) slow rusting APR, which is quantitative resistance often conferred by multiple loci, and is not associated with a hypersensitive response. Quantitative resistance is usually considered more durable than that conferred by pathogen recognition genes (Parlevliet, 2002); however, it must be improved over multiple cycles of selection using well-managed screening nurseries for evaluation. Published in The Plant Genome 7 doi: 10.3835/plantgenome2014.02.0006 © Crop Science Society of America 5585 Guilford Rd., Madison, WI 53711 USA An open-access publication All rights reserved. No part of this periodical may be reproduced or transmitted in any form or by any means, electronic or mechanical, including photocopying, recording, or any information storage and retrieval system, without permission in writing from the publisher. Permission for printing and for reprinting the material contained herein has been obtained by the publisher. J.E. Rutkoski, M.E. Sorrells, and H. Barbier, Dep. of Plant Breeding and Genetics, Cornell Univ., Ithaca, NY 14853; J.A. Poland, Dep. of Plant Pathology, Kansas State Univ., Manhattan, KS 66506; R.P. Singh, International Maize and Wheat Improvement Center (CIMMYT), Apdo. Postal 6-641, 06600 El Batan, Mexico; J. Huerta Espino, Campo Experimental Valle de México INIFAP, Apdo. Postal 10, 56230 Chapingo, Edo de México, Mexico; S. Bhavani, CIMMYT, ICRAF House, United Nations Avenue, Gigiri, Village Market-00621, Nairobi, Kenya; M.N. Rouse, USDA-ARS, Cereal Disease Lab. and Dep. of Plant Pathology, Univ. of Minnesota, St. Paul, MN 55108; J.-L. Jannink, USDA-ARS, Ithaca, NY 14853. Received 9 Feb. 2014. *Corresponding author ([email protected]). Abbreviations: APR, adult plant resistance; BCp, Bayes Cp; BL, Bayesian Lasso; G-BLUP, genomic best linear unbiased prediction; GBS, genotyping-by-sequencing; GS, genomic selection; MLR, multiple linear regression; QTL, quantitative trait loci; STS, sequence tagged site. Published July 18, 2014