High accuracy of genome-enabled prediction of belowground and physiological traits in barley seedlings

In plants, the study of belowground traits is gaining momentum due to their importance on yield formation and the uptake of water and nutrients. In several cereal crops, seminal root number and seminal root angle are proxy traits of the root system architecture at the mature stages, which in turn co...

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Autores principales: Puglisi, Damiano, Visioni, Andrea, Özkan, Hakan, Kara, Ibrahim, Roberta Lo Piero, Angela, Rachdad, Fatima Ezzahra, Tondelli, Alessandro, Valè, Giampiero, Cattivelli, Luigi, Fricano, Agostino
Formato: Journal Article
Lenguaje:Inglés
Publicado: Genetics Society of America 2022
Materias:
Acceso en línea:https://hdl.handle.net/10568/126058
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author Puglisi, Damiano
Visioni, Andrea
Özkan, Hakan
Kara, Ibrahim
Roberta Lo Piero, Angela
Rachdad, Fatima Ezzahra
Tondelli, Alessandro
Valè, Giampiero
Cattivelli, Luigi
Fricano, Agostino
author_browse Cattivelli, Luigi
Fricano, Agostino
Kara, Ibrahim
Puglisi, Damiano
Rachdad, Fatima Ezzahra
Roberta Lo Piero, Angela
Tondelli, Alessandro
Valè, Giampiero
Visioni, Andrea
Özkan, Hakan
author_facet Puglisi, Damiano
Visioni, Andrea
Özkan, Hakan
Kara, Ibrahim
Roberta Lo Piero, Angela
Rachdad, Fatima Ezzahra
Tondelli, Alessandro
Valè, Giampiero
Cattivelli, Luigi
Fricano, Agostino
author_sort Puglisi, Damiano
collection Repository of Agricultural Research Outputs (CGSpace)
description In plants, the study of belowground traits is gaining momentum due to their importance on yield formation and the uptake of water and nutrients. In several cereal crops, seminal root number and seminal root angle are proxy traits of the root system architecture at the mature stages, which in turn contributes to modulating the uptake of water and nutrients. Along with seminal root number and seminal root angle, experimental evidence indicates that the transpiration rate response to evaporative demand or vapor pressure deficit is a key physiological trait that might be targeted to cope with drought tolerance as the reduction of the water flux to leaves for limiting transpiration rate at high levels of vapor pressure deficit allows to better manage soil moisture. In the present study, we examined the phenotypic diversity of seminal root number, seminal root angle, and transpiration rate at the seedling stage in a panel of 8-way Multiparent Advanced Generation Inter-Crosses lines of winter barley and correlated these traits with grain yield measured in different site-by-season combinations. Second, phenotypic and genotypic data of the Multiparent Advanced Generation Inter-Crosses population were combined to fit and cross-validate different genomic prediction models for these belowground and physiological traits. Genomic prediction models for seminal root number were fitted using threshold and log-normal models, considering these data as ordinal discrete variable and as count data, respectively, while for seminal root angle and transpiration rate, genomic prediction was implemented using models based on extended genomic best linear unbiased predictors. The results presented in this study show that genome-enabled prediction models of seminal root number, seminal root angle, and transpiration rate data have high predictive ability and that the best models investigated in the present study include first-order additive × additive epistatic interaction effects. Our analyses indicate that beyond grain yield, genomic prediction models might be used to predict belowground and physiological traits and pave the way to practical applications for barley improvement.
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language Inglés
publishDate 2022
publishDateRange 2022
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spelling CGSpace1260582026-01-15T02:20:11Z High accuracy of genome-enabled prediction of belowground and physiological traits in barley seedlings Puglisi, Damiano Visioni, Andrea Özkan, Hakan Kara, Ibrahim Roberta Lo Piero, Angela Rachdad, Fatima Ezzahra Tondelli, Alessandro Valè, Giampiero Cattivelli, Luigi Fricano, Agostino barley transpiration rate barley genomic prediction magic seminal root angle seminal root number threshold gblup mpp multiparental populations multiparent advanced generation inter-cross (magic) In plants, the study of belowground traits is gaining momentum due to their importance on yield formation and the uptake of water and nutrients. In several cereal crops, seminal root number and seminal root angle are proxy traits of the root system architecture at the mature stages, which in turn contributes to modulating the uptake of water and nutrients. Along with seminal root number and seminal root angle, experimental evidence indicates that the transpiration rate response to evaporative demand or vapor pressure deficit is a key physiological trait that might be targeted to cope with drought tolerance as the reduction of the water flux to leaves for limiting transpiration rate at high levels of vapor pressure deficit allows to better manage soil moisture. In the present study, we examined the phenotypic diversity of seminal root number, seminal root angle, and transpiration rate at the seedling stage in a panel of 8-way Multiparent Advanced Generation Inter-Crosses lines of winter barley and correlated these traits with grain yield measured in different site-by-season combinations. Second, phenotypic and genotypic data of the Multiparent Advanced Generation Inter-Crosses population were combined to fit and cross-validate different genomic prediction models for these belowground and physiological traits. Genomic prediction models for seminal root number were fitted using threshold and log-normal models, considering these data as ordinal discrete variable and as count data, respectively, while for seminal root angle and transpiration rate, genomic prediction was implemented using models based on extended genomic best linear unbiased predictors. The results presented in this study show that genome-enabled prediction models of seminal root number, seminal root angle, and transpiration rate data have high predictive ability and that the best models investigated in the present study include first-order additive × additive epistatic interaction effects. Our analyses indicate that beyond grain yield, genomic prediction models might be used to predict belowground and physiological traits and pave the way to practical applications for barley improvement. 2022-12-16T21:55:24Z 2022-12-16T21:55:24Z Journal Article https://hdl.handle.net/10568/126058 en Open Access application/pdf Genetics Society of America Damiano Puglisi, Andrea Visioni, Hakan Özkan, Ibrahim Kara, Angela Roberta Lo Piero, Fatima Ezzahra Rachdad, Alessandro Tondelli, Giampiero Valè, Luigi Cattivelli, Agostino Fricano. (31/1/2022). High accuracy of genome-enabled prediction of belowground and physiological traits in barley seedlings. G3: Genes | Genomes | Genetics, 12 (3).
spellingShingle barley
transpiration rate
barley
genomic prediction
magic
seminal root angle
seminal root number
threshold gblup
mpp
multiparental populations
multiparent advanced generation inter-cross (magic)
Puglisi, Damiano
Visioni, Andrea
Özkan, Hakan
Kara, Ibrahim
Roberta Lo Piero, Angela
Rachdad, Fatima Ezzahra
Tondelli, Alessandro
Valè, Giampiero
Cattivelli, Luigi
Fricano, Agostino
High accuracy of genome-enabled prediction of belowground and physiological traits in barley seedlings
title High accuracy of genome-enabled prediction of belowground and physiological traits in barley seedlings
title_full High accuracy of genome-enabled prediction of belowground and physiological traits in barley seedlings
title_fullStr High accuracy of genome-enabled prediction of belowground and physiological traits in barley seedlings
title_full_unstemmed High accuracy of genome-enabled prediction of belowground and physiological traits in barley seedlings
title_short High accuracy of genome-enabled prediction of belowground and physiological traits in barley seedlings
title_sort high accuracy of genome enabled prediction of belowground and physiological traits in barley seedlings
topic barley
transpiration rate
barley
genomic prediction
magic
seminal root angle
seminal root number
threshold gblup
mpp
multiparental populations
multiparent advanced generation inter-cross (magic)
url https://hdl.handle.net/10568/126058
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