Cargando…
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...
Autores principales: | , , , , , , , |
---|---|
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 |
_version_ | 1783542578913738752 |
---|---|
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. |
format | Online Article Text |
id | pubmed-7274421 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
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 |
work_keys_str_mv | AT gemmermathiasruben canmetabolicpredictionbeanalternativetogenomicpredictioninbarley AT richterchris canmetabolicpredictionbeanalternativetogenomicpredictioninbarley AT jiangyong canmetabolicpredictionbeanalternativetogenomicpredictioninbarley AT schmutzerthomas canmetabolicpredictionbeanalternativetogenomicpredictioninbarley AT raoranemanishl canmetabolicpredictionbeanalternativetogenomicpredictioninbarley AT junkerbjorn canmetabolicpredictionbeanalternativetogenomicpredictioninbarley AT pillenklaus canmetabolicpredictionbeanalternativetogenomicpredictioninbarley AT maurerandreas canmetabolicpredictionbeanalternativetogenomicpredictioninbarley |