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Can metabolic prediction be an alternative to genomic prediction in barley?

Like other crop species, barley, the fourth most important crop worldwide, suffers from the genetic bottleneck effect, where further improvements in performance through classical breeding methods become difficult. Therefore, indirect selection methods are of great interest. Here, genomic prediction...

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Autores principales: Gemmer, Mathias Ruben, Richter, Chris, Jiang, Yong, Schmutzer, Thomas, Raorane, Manish L., Junker, Björn, Pillen, Klaus, Maurer, Andreas
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7274421/
https://www.ncbi.nlm.nih.gov/pubmed/32502173
http://dx.doi.org/10.1371/journal.pone.0234052
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author Gemmer, Mathias Ruben
Richter, Chris
Jiang, Yong
Schmutzer, Thomas
Raorane, Manish L.
Junker, Björn
Pillen, Klaus
Maurer, Andreas
author_facet Gemmer, Mathias Ruben
Richter, Chris
Jiang, Yong
Schmutzer, Thomas
Raorane, Manish L.
Junker, Björn
Pillen, Klaus
Maurer, Andreas
author_sort Gemmer, Mathias Ruben
collection PubMed
description Like other crop species, barley, the fourth most important crop worldwide, suffers from the genetic bottleneck effect, where further improvements in performance through classical breeding methods become difficult. Therefore, indirect selection methods are of great interest. Here, genomic prediction (GP) based on 33,005 SNP markers and, alternatively, metabolic prediction (MP) based on 128 metabolites with sampling at two different time points in one year, were applied to predict multi-year agronomic traits in the nested association mapping (NAM) population HEB-25. We found prediction abilities of up to 0.93 for plant height with SNP markers and of up to 0.61 for flowering time with metabolites. Interestingly, prediction abilities in GP increased after reducing the number of incorporated SNP markers. The estimated effects of GP and MP were highly concordant, indicating MP as an interesting alternative to GP, being able to reflect a stable genotype-specific metabolite profile. In MP, sampling at an early developmental stage outperformed sampling at a later stage. The results confirm the value of GP for future breeding. With MP, an interesting alternative was also applied successfully. However, based on our results, usage of MP alone cannot be recommended in barley. Nevertheless, MP can assist in unravelling physiological pathways for the expression of agronomically important traits.
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spelling pubmed-72744212020-06-09 Can metabolic prediction be an alternative to genomic prediction in barley? Gemmer, Mathias Ruben Richter, Chris Jiang, Yong Schmutzer, Thomas Raorane, Manish L. Junker, Björn Pillen, Klaus Maurer, Andreas PLoS One Research Article Like other crop species, barley, the fourth most important crop worldwide, suffers from the genetic bottleneck effect, where further improvements in performance through classical breeding methods become difficult. Therefore, indirect selection methods are of great interest. Here, genomic prediction (GP) based on 33,005 SNP markers and, alternatively, metabolic prediction (MP) based on 128 metabolites with sampling at two different time points in one year, were applied to predict multi-year agronomic traits in the nested association mapping (NAM) population HEB-25. We found prediction abilities of up to 0.93 for plant height with SNP markers and of up to 0.61 for flowering time with metabolites. Interestingly, prediction abilities in GP increased after reducing the number of incorporated SNP markers. The estimated effects of GP and MP were highly concordant, indicating MP as an interesting alternative to GP, being able to reflect a stable genotype-specific metabolite profile. In MP, sampling at an early developmental stage outperformed sampling at a later stage. The results confirm the value of GP for future breeding. With MP, an interesting alternative was also applied successfully. However, based on our results, usage of MP alone cannot be recommended in barley. Nevertheless, MP can assist in unravelling physiological pathways for the expression of agronomically important traits. Public Library of Science 2020-06-05 /pmc/articles/PMC7274421/ /pubmed/32502173 http://dx.doi.org/10.1371/journal.pone.0234052 Text en © 2020 Gemmer et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Gemmer, Mathias Ruben
Richter, Chris
Jiang, Yong
Schmutzer, Thomas
Raorane, Manish L.
Junker, Björn
Pillen, Klaus
Maurer, Andreas
Can metabolic prediction be an alternative to genomic prediction in barley?
title Can metabolic prediction be an alternative to genomic prediction in barley?
title_full Can metabolic prediction be an alternative to genomic prediction in barley?
title_fullStr Can metabolic prediction be an alternative to genomic prediction in barley?
title_full_unstemmed Can metabolic prediction be an alternative to genomic prediction in barley?
title_short Can metabolic prediction be an alternative to genomic prediction in barley?
title_sort can metabolic prediction be an alternative to genomic prediction in barley?
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7274421/
https://www.ncbi.nlm.nih.gov/pubmed/32502173
http://dx.doi.org/10.1371/journal.pone.0234052
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