Cargando…

Genomic Prediction Can Provide Precise Estimates of the Genotypic Value of Barley Lines Evaluated in Unreplicated Trials

Genomic prediction has been established in breeding programs to predict the genotypic values of selection candidates without phenotypic data. First results in wheat showed that genomic predictions can also prove useful to select among material for which phenotypic data are available. In such a scena...

Descripción completa

Detalles Bibliográficos
Autores principales: Terraillon, Jérôme, Frisch, Matthias, Falke, K. Christin, Jaiser, Heidi, Spiller, Monika, Cselényi, László, Krumnacker, Kerstin, Boxberger, Susanna, Habekuß, Antje, Kopahnke, Doris, Serfling, Albrecht, Ordon, Frank, Zenke-Philippi, Carola
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9072862/
https://www.ncbi.nlm.nih.gov/pubmed/35528936
http://dx.doi.org/10.3389/fpls.2022.735256
_version_ 1784701155405725696
author Terraillon, Jérôme
Frisch, Matthias
Falke, K. Christin
Jaiser, Heidi
Spiller, Monika
Cselényi, László
Krumnacker, Kerstin
Boxberger, Susanna
Habekuß, Antje
Kopahnke, Doris
Serfling, Albrecht
Ordon, Frank
Zenke-Philippi, Carola
author_facet Terraillon, Jérôme
Frisch, Matthias
Falke, K. Christin
Jaiser, Heidi
Spiller, Monika
Cselényi, László
Krumnacker, Kerstin
Boxberger, Susanna
Habekuß, Antje
Kopahnke, Doris
Serfling, Albrecht
Ordon, Frank
Zenke-Philippi, Carola
author_sort Terraillon, Jérôme
collection PubMed
description Genomic prediction has been established in breeding programs to predict the genotypic values of selection candidates without phenotypic data. First results in wheat showed that genomic predictions can also prove useful to select among material for which phenotypic data are available. In such a scenario, the selection candidates are evaluated with low intensity in the field. Genome-wide effects are estimated from the field data and are then used to predict the genotypic values of the selection candidates. The objectives of our simulation study were to investigate the correlations r(y, g) between genomic predictions y and genotypic values g and to compare these with the correlations r(p, g) between phenotypic values p and genotypic values g. We used data from a yield trial of 250 barley lines to estimate variance components and genome-wide effects. These parameters were used as basis for simulations. The simulations included multiple crossing schemes, population sizes, and varying sizes of the components of the masking variance. The genotypic values g of the selection candidates were obtained by genetic simulations, the phenotypic values p by simulating evaluation in the field, and the genomic predictions y by RR-BLUP effect estimation from the phenotypic values. The correlations r(y, g) were greater than the correlations r(p, g) for all investigated scenarios. We conclude that using genomic predictions for selection among candidates tested with low intensity in the field can proof useful for increasing the efficiency of barley breeding programs.
format Online
Article
Text
id pubmed-9072862
institution National Center for Biotechnology Information
language English
publishDate 2022
publisher Frontiers Media S.A.
record_format MEDLINE/PubMed
spelling pubmed-90728622022-05-07 Genomic Prediction Can Provide Precise Estimates of the Genotypic Value of Barley Lines Evaluated in Unreplicated Trials Terraillon, Jérôme Frisch, Matthias Falke, K. Christin Jaiser, Heidi Spiller, Monika Cselényi, László Krumnacker, Kerstin Boxberger, Susanna Habekuß, Antje Kopahnke, Doris Serfling, Albrecht Ordon, Frank Zenke-Philippi, Carola Front Plant Sci Plant Science Genomic prediction has been established in breeding programs to predict the genotypic values of selection candidates without phenotypic data. First results in wheat showed that genomic predictions can also prove useful to select among material for which phenotypic data are available. In such a scenario, the selection candidates are evaluated with low intensity in the field. Genome-wide effects are estimated from the field data and are then used to predict the genotypic values of the selection candidates. The objectives of our simulation study were to investigate the correlations r(y, g) between genomic predictions y and genotypic values g and to compare these with the correlations r(p, g) between phenotypic values p and genotypic values g. We used data from a yield trial of 250 barley lines to estimate variance components and genome-wide effects. These parameters were used as basis for simulations. The simulations included multiple crossing schemes, population sizes, and varying sizes of the components of the masking variance. The genotypic values g of the selection candidates were obtained by genetic simulations, the phenotypic values p by simulating evaluation in the field, and the genomic predictions y by RR-BLUP effect estimation from the phenotypic values. The correlations r(y, g) were greater than the correlations r(p, g) for all investigated scenarios. We conclude that using genomic predictions for selection among candidates tested with low intensity in the field can proof useful for increasing the efficiency of barley breeding programs. Frontiers Media S.A. 2022-04-22 /pmc/articles/PMC9072862/ /pubmed/35528936 http://dx.doi.org/10.3389/fpls.2022.735256 Text en Copyright © 2022 Terraillon, Frisch, Falke, Jaiser, Spiller, Cselényi, Krumnacker, Boxberger, Habekuß, Kopahnke, Serfling, Ordon and Zenke-Philippi. https://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
Terraillon, Jérôme
Frisch, Matthias
Falke, K. Christin
Jaiser, Heidi
Spiller, Monika
Cselényi, László
Krumnacker, Kerstin
Boxberger, Susanna
Habekuß, Antje
Kopahnke, Doris
Serfling, Albrecht
Ordon, Frank
Zenke-Philippi, Carola
Genomic Prediction Can Provide Precise Estimates of the Genotypic Value of Barley Lines Evaluated in Unreplicated Trials
title Genomic Prediction Can Provide Precise Estimates of the Genotypic Value of Barley Lines Evaluated in Unreplicated Trials
title_full Genomic Prediction Can Provide Precise Estimates of the Genotypic Value of Barley Lines Evaluated in Unreplicated Trials
title_fullStr Genomic Prediction Can Provide Precise Estimates of the Genotypic Value of Barley Lines Evaluated in Unreplicated Trials
title_full_unstemmed Genomic Prediction Can Provide Precise Estimates of the Genotypic Value of Barley Lines Evaluated in Unreplicated Trials
title_short Genomic Prediction Can Provide Precise Estimates of the Genotypic Value of Barley Lines Evaluated in Unreplicated Trials
title_sort genomic prediction can provide precise estimates of the genotypic value of barley lines evaluated in unreplicated trials
topic Plant Science
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9072862/
https://www.ncbi.nlm.nih.gov/pubmed/35528936
http://dx.doi.org/10.3389/fpls.2022.735256
work_keys_str_mv AT terraillonjerome genomicpredictioncanprovidepreciseestimatesofthegenotypicvalueofbarleylinesevaluatedinunreplicatedtrials
AT frischmatthias genomicpredictioncanprovidepreciseestimatesofthegenotypicvalueofbarleylinesevaluatedinunreplicatedtrials
AT falkekchristin genomicpredictioncanprovidepreciseestimatesofthegenotypicvalueofbarleylinesevaluatedinunreplicatedtrials
AT jaiserheidi genomicpredictioncanprovidepreciseestimatesofthegenotypicvalueofbarleylinesevaluatedinunreplicatedtrials
AT spillermonika genomicpredictioncanprovidepreciseestimatesofthegenotypicvalueofbarleylinesevaluatedinunreplicatedtrials
AT cselenyilaszlo genomicpredictioncanprovidepreciseestimatesofthegenotypicvalueofbarleylinesevaluatedinunreplicatedtrials
AT krumnackerkerstin genomicpredictioncanprovidepreciseestimatesofthegenotypicvalueofbarleylinesevaluatedinunreplicatedtrials
AT boxbergersusanna genomicpredictioncanprovidepreciseestimatesofthegenotypicvalueofbarleylinesevaluatedinunreplicatedtrials
AT habekußantje genomicpredictioncanprovidepreciseestimatesofthegenotypicvalueofbarleylinesevaluatedinunreplicatedtrials
AT kopahnkedoris genomicpredictioncanprovidepreciseestimatesofthegenotypicvalueofbarleylinesevaluatedinunreplicatedtrials
AT serflingalbrecht genomicpredictioncanprovidepreciseestimatesofthegenotypicvalueofbarleylinesevaluatedinunreplicatedtrials
AT ordonfrank genomicpredictioncanprovidepreciseestimatesofthegenotypicvalueofbarleylinesevaluatedinunreplicatedtrials
AT zenkephilippicarola genomicpredictioncanprovidepreciseestimatesofthegenotypicvalueofbarleylinesevaluatedinunreplicatedtrials