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Can Metabolite- and Transcript-Based Selection for Drought Tolerance in Solanum tuberosum Replace Selection on Yield in Arid Environments?

Climate models predict an increased likelihood of drought, demanding efficient selection for drought tolerance to maintain yield stability. Classic tolerance breeding relies on selection for yield in arid environments, which depends on yield trials and takes decades. Breeding could be accelerated by...

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Autores principales: Haas, Manuela, Sprenger, Heike, Zuther, Ellen, Peters, Rolf, Seddig, Sylvia, Walther, Dirk, Kopka, Joachim, Hincha, Dirk K., Köhl, Karin I.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7385397/
https://www.ncbi.nlm.nih.gov/pubmed/32793257
http://dx.doi.org/10.3389/fpls.2020.01071
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author Haas, Manuela
Sprenger, Heike
Zuther, Ellen
Peters, Rolf
Seddig, Sylvia
Walther, Dirk
Kopka, Joachim
Hincha, Dirk K.
Köhl, Karin I.
author_facet Haas, Manuela
Sprenger, Heike
Zuther, Ellen
Peters, Rolf
Seddig, Sylvia
Walther, Dirk
Kopka, Joachim
Hincha, Dirk K.
Köhl, Karin I.
author_sort Haas, Manuela
collection PubMed
description Climate models predict an increased likelihood of drought, demanding efficient selection for drought tolerance to maintain yield stability. Classic tolerance breeding relies on selection for yield in arid environments, which depends on yield trials and takes decades. Breeding could be accelerated by marker-assisted selection (MAS). As an alternative to genomic markers, transcript and metabolite markers have been suggested for important crops but also for orphan corps. For potato, we suggested a random-forest-based model that predicts tolerance from leaf metabolite and transcript levels with a precision of more than 90% independent of the agro-environment. To find out how the model based selection compares to yield-based selection in arid environments, we applied this approach to a population of 200 tetraploid Solanum tuberosum ssp. tuberosum lines segregating for drought tolerance. Twenty-four lines were selected into a phenotypic subpopulation (PP(t)) for superior tolerance based on relative tuber starch yield data from three drought stress trials. Two subpopulations with superior (MP(t)) and inferior (MP(s)) tolerance were selected based on drought tolerance predictions based on leaf metabolite and transcript levels from two sites. The 60 selected lines were phenotyped for yield and drought tolerance in 10 multi-environment drought stress trials representing typical Central European drought scenarios. Neither selection affected development or yield potential. Lines with superior drought tolerance and high yields under stress were over-represented in both populations selected for superior tolerance, with a higher number in PP(t) compared to MP(t). However, selection based on leaf metabolites may still be an alternative to yield-based selection in arid environments as it works on leaves sampled in breeder’s fields independent of drought trials. As the selection against low tolerance was ineffective, the method is best used in combination with tools that select against sensitive genotypes. Thus, metabolic and transcript marker-based selection for drought tolerance is a viable alternative to the selection on yield in arid environments.
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spelling pubmed-73853972020-08-12 Can Metabolite- and Transcript-Based Selection for Drought Tolerance in Solanum tuberosum Replace Selection on Yield in Arid Environments? Haas, Manuela Sprenger, Heike Zuther, Ellen Peters, Rolf Seddig, Sylvia Walther, Dirk Kopka, Joachim Hincha, Dirk K. Köhl, Karin I. Front Plant Sci Plant Science Climate models predict an increased likelihood of drought, demanding efficient selection for drought tolerance to maintain yield stability. Classic tolerance breeding relies on selection for yield in arid environments, which depends on yield trials and takes decades. Breeding could be accelerated by marker-assisted selection (MAS). As an alternative to genomic markers, transcript and metabolite markers have been suggested for important crops but also for orphan corps. For potato, we suggested a random-forest-based model that predicts tolerance from leaf metabolite and transcript levels with a precision of more than 90% independent of the agro-environment. To find out how the model based selection compares to yield-based selection in arid environments, we applied this approach to a population of 200 tetraploid Solanum tuberosum ssp. tuberosum lines segregating for drought tolerance. Twenty-four lines were selected into a phenotypic subpopulation (PP(t)) for superior tolerance based on relative tuber starch yield data from three drought stress trials. Two subpopulations with superior (MP(t)) and inferior (MP(s)) tolerance were selected based on drought tolerance predictions based on leaf metabolite and transcript levels from two sites. The 60 selected lines were phenotyped for yield and drought tolerance in 10 multi-environment drought stress trials representing typical Central European drought scenarios. Neither selection affected development or yield potential. Lines with superior drought tolerance and high yields under stress were over-represented in both populations selected for superior tolerance, with a higher number in PP(t) compared to MP(t). However, selection based on leaf metabolites may still be an alternative to yield-based selection in arid environments as it works on leaves sampled in breeder’s fields independent of drought trials. As the selection against low tolerance was ineffective, the method is best used in combination with tools that select against sensitive genotypes. Thus, metabolic and transcript marker-based selection for drought tolerance is a viable alternative to the selection on yield in arid environments. Frontiers Media S.A. 2020-07-21 /pmc/articles/PMC7385397/ /pubmed/32793257 http://dx.doi.org/10.3389/fpls.2020.01071 Text en Copyright © 2020 Haas, Sprenger, Zuther, Peters, Seddig, Walther, Kopka, Hincha and Köhl http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Plant Science
Haas, Manuela
Sprenger, Heike
Zuther, Ellen
Peters, Rolf
Seddig, Sylvia
Walther, Dirk
Kopka, Joachim
Hincha, Dirk K.
Köhl, Karin I.
Can Metabolite- and Transcript-Based Selection for Drought Tolerance in Solanum tuberosum Replace Selection on Yield in Arid Environments?
title Can Metabolite- and Transcript-Based Selection for Drought Tolerance in Solanum tuberosum Replace Selection on Yield in Arid Environments?
title_full Can Metabolite- and Transcript-Based Selection for Drought Tolerance in Solanum tuberosum Replace Selection on Yield in Arid Environments?
title_fullStr Can Metabolite- and Transcript-Based Selection for Drought Tolerance in Solanum tuberosum Replace Selection on Yield in Arid Environments?
title_full_unstemmed Can Metabolite- and Transcript-Based Selection for Drought Tolerance in Solanum tuberosum Replace Selection on Yield in Arid Environments?
title_short Can Metabolite- and Transcript-Based Selection for Drought Tolerance in Solanum tuberosum Replace Selection on Yield in Arid Environments?
title_sort can metabolite- and transcript-based selection for drought tolerance in solanum tuberosum replace selection on yield in arid environments?
topic Plant Science
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7385397/
https://www.ncbi.nlm.nih.gov/pubmed/32793257
http://dx.doi.org/10.3389/fpls.2020.01071
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