Evaluating Selection of a Quantitative Trait: Snow Mold Tolerance in Winter Wheat

Core Ideas Six quantitative trait loci for snow mold tolerance were detected in a winter wheat recombinant inbred line population. Marker‐assisted selection to incorporate QTL is unlikely to help breed for highly quantitative traits. Genomic selection could replace initial phenotyping for quantitati...

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Main Authors: Erika B. Kruse, Kathy L. Esvelt Klos, Juliet M. Marshall, Timothy D. Murray, Brian P. Ward, Arron H. Carter
Format: Article
Language:English
Published: Wiley 2019-01-01
Series:Agrosystems, Geosciences & Environment
Online Access:https://doi.org/10.2134/age2019.07.0059
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author Erika B. Kruse
Kathy L. Esvelt Klos
Juliet M. Marshall
Timothy D. Murray
Brian P. Ward
Arron H. Carter
author_facet Erika B. Kruse
Kathy L. Esvelt Klos
Juliet M. Marshall
Timothy D. Murray
Brian P. Ward
Arron H. Carter
author_sort Erika B. Kruse
collection DOAJ
description Core Ideas Six quantitative trait loci for snow mold tolerance were detected in a winter wheat recombinant inbred line population. Marker‐assisted selection to incorporate QTL is unlikely to help breed for highly quantitative traits. Genomic selection could replace initial phenotyping for quantitative traits. Selection for snow mold tolerance (SMT) in winter wheat (Triticum aestivum L.) is complicated by the influence of numerous quantitative trait loci (QTL) and of environmental conditions. The goals of this study were to identify QTL for SMT, determine the effectiveness of marker‐assisted selection (MAS), and model the effectiveness of genomic prediction for SMT. Quantitative trait loci analysis of a recombinant inbred line (RIL) subpopulation, derived from a cross between Xerpha and Münstertaler, detected six unique QTL. Progeny from the same cross were advanced by MAS and compared with the unselected subpopulation to evaluate the efficacy of MAS. No significant difference was found between the SMT means (p = 0.41). Similarly, genomic selection had very poor accuracy (−0.07) in the Xerpha–Münstertaler (XM) RIL subpopulation. This contrasts with the apparent effectiveness of genomic selection (0.65) in a Finch–Eltan RIL population, also evaluated for SMT. The failure of selection tools to improve SMT in the XM population is likely due to the challenges of rating a quantitative trait that requires highly specific environmental conditions for phenotype development.
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spelling doaj.art-5921665481b346128801546e11905aaf2022-12-22T00:26:19ZengWileyAgrosystems, Geosciences & Environment2639-66962019-01-01211810.2134/age2019.07.0059Evaluating Selection of a Quantitative Trait: Snow Mold Tolerance in Winter WheatErika B. Kruse0Kathy L. Esvelt Klos1Juliet M. Marshall2Timothy D. Murray3Brian P. Ward4Arron H. Carter5Washington State Univ.Dep. of Crop and Soil SciencePullmanWA99164Small Grains and Potato Germplasm ResearchUSDA‐ARSAberdeenID83210Univ. of IdahoDep. of EntomologyPlant Pathology, and NematologyAberdeenID83210Washington State Univ.Dep. of Plant PathologyPullmanWA99164USDA‐ARS Plant Science Research UnitRaleighNC27695Washington State Univ.Dep. of Crop and Soil SciencePullmanWA99164Core Ideas Six quantitative trait loci for snow mold tolerance were detected in a winter wheat recombinant inbred line population. Marker‐assisted selection to incorporate QTL is unlikely to help breed for highly quantitative traits. Genomic selection could replace initial phenotyping for quantitative traits. Selection for snow mold tolerance (SMT) in winter wheat (Triticum aestivum L.) is complicated by the influence of numerous quantitative trait loci (QTL) and of environmental conditions. The goals of this study were to identify QTL for SMT, determine the effectiveness of marker‐assisted selection (MAS), and model the effectiveness of genomic prediction for SMT. Quantitative trait loci analysis of a recombinant inbred line (RIL) subpopulation, derived from a cross between Xerpha and Münstertaler, detected six unique QTL. Progeny from the same cross were advanced by MAS and compared with the unselected subpopulation to evaluate the efficacy of MAS. No significant difference was found between the SMT means (p = 0.41). Similarly, genomic selection had very poor accuracy (−0.07) in the Xerpha–Münstertaler (XM) RIL subpopulation. This contrasts with the apparent effectiveness of genomic selection (0.65) in a Finch–Eltan RIL population, also evaluated for SMT. The failure of selection tools to improve SMT in the XM population is likely due to the challenges of rating a quantitative trait that requires highly specific environmental conditions for phenotype development.https://doi.org/10.2134/age2019.07.0059
spellingShingle Erika B. Kruse
Kathy L. Esvelt Klos
Juliet M. Marshall
Timothy D. Murray
Brian P. Ward
Arron H. Carter
Evaluating Selection of a Quantitative Trait: Snow Mold Tolerance in Winter Wheat
Agrosystems, Geosciences & Environment
title Evaluating Selection of a Quantitative Trait: Snow Mold Tolerance in Winter Wheat
title_full Evaluating Selection of a Quantitative Trait: Snow Mold Tolerance in Winter Wheat
title_fullStr Evaluating Selection of a Quantitative Trait: Snow Mold Tolerance in Winter Wheat
title_full_unstemmed Evaluating Selection of a Quantitative Trait: Snow Mold Tolerance in Winter Wheat
title_short Evaluating Selection of a Quantitative Trait: Snow Mold Tolerance in Winter Wheat
title_sort evaluating selection of a quantitative trait snow mold tolerance in winter wheat
url https://doi.org/10.2134/age2019.07.0059
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