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G3 (Bethesda). 2019 Feb 7;9(2):473-489. doi: 10.1534/g3.118.200835.

Determining the Genetic Architecture of Reproductive Stage Drought Tolerance in Wheat Using a Correlated Trait and Correlated Marker Effect Model.

Author information

1
CSIRO Agriculture and Food, GPO Box 1700, Canberra ACT 2601, Australia rudy.dolferus@csiro.au.
2
CSIRO Agriculture and Food, GPO Box 1700, Canberra ACT 2601, Australia.
3
Department of Environment and Primary Industry, AgriBioSciences, La Trobe R&D Park, Bundoora, VIC 3083, Australia.
4
National Institute for Applied Statistics Research Australia (NIASRA), School of Mathematics & Applied Statistics, Faculty of Engineering & Information Sciences, University of Wollongong NSW 2522, Australia.

Abstract

Water stress during reproductive growth is a major yield constraint for wheat (Triticum aestivum L). We previously established a controlled environment drought tolerance phenotyping method targeting the young microspore stage of pollen development. This method eliminates stress avoidance based on flowering time. We substituted soil drought treatments by a reproducible osmotic stress treatment using hydroponics and NaCl as osmolyte. Salt exclusion in hexaploid wheat avoids salt toxicity, causing osmotic stress. A Cranbrook x Halberd doubled haploid (DH) population was phenotyped by scoring spike grain numbers of unstressed (SGNCon) and osmotically stressed (SGNTrt) plants. Grain number data were analyzed using a linear mixed model (LMM) that included genetic correlations between the SGNCon and SGNTrt traits. Viewing this as a genetic regression of SGNTrt on SGNCon allowed derivation of a stress tolerance trait (SGNTol). Importantly, and by definition of the trait, the genetic effects for SGNTol are statistically independent of those for SGNCon. Thus they represent non-pleiotropic effects associated with the stress treatment that are independent of the control treatment. QTL mapping was conducted using a whole genome approach in which the LMM included all traits and all markers simultaneously. The marker effects within chromosomes were assumed to follow a spatial correlation model. This resulted in smooth marker profiles that could be used to identify positions of putative QTL. The most influential QTL were located on chromosome 5A for SGNTol (126cM; contributed by Halberd), 5A for SGNCon (141cM; Cranbrook) and 2A for SGNTrt (116cM; Cranbrook). Sensitive and tolerant population tail lines all showed matching soil drought tolerance phenotypes, confirming that osmotic stress is a valid surrogate screening method.

KEYWORDS:

osmotic stress/drought tolerance/wheat/grain number/QTL/mixed model/WGAIM

PMID:
30541928
DOI:
10.1534/g3.118.200835
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