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231225s2020 xx |||||o 00| ||eng c |
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|a 10.1093/jxb/eraa388
|2 doi
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|a pubmed25n1046.xml
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|a (NLM)32827031
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|a DE-627
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|e rakwb
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|a eng
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| 100 |
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|a Zhao, Xiongwei
|e verfasserin
|4 aut
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| 245 |
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|a Natural variation and genomic prediction of growth, physiological traits, and nitrogen-use efficiency in perennial ryegrass under low-nitrogen stress
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|c 2020
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|a Text
|b txt
|2 rdacontent
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|a ƒaComputermedien
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|2 rdamedia
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|a ƒa Online-Ressource
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|2 rdacarrier
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|a Date Completed 14.05.2021
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|a Date Revised 14.05.2021
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|a published: Print
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|a Citation Status MEDLINE
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|a © The Author(s) 2020. Published by Oxford University Press on behalf of the Society for Experimental Biology. All rights reserved. For permissions, please email: journals.permissionsoup.com.
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|a Genomic prediction of nitrogen-use efficiency (NUE) has not previously been studied in perennial grass species exposed to low-N stress. Here, we conducted a genomic prediction of physiological traits and NUE in 184 global accessions of perennial ryegrass (Lolium perenne) in response to a normal (7.5 mM) and low (0.75 mM) supply of N. After 21 d of treatment under greenhouse conditions, significant variations in plant height increment (ΔHT), leaf fresh weight (LFW), leaf dry weight (LDW), chlorophyll index (Chl), chlorophyll fluorescence, leaf N and carbon (C) contents, C/N ratio, and NUE were observed in accessions , but to a greater extent under low-N stress. Six genomic prediction models were applied to the data, namely the Bayesian method Bayes C, Bayesian LASSO, Bayesian Ridge Regression, Ridge Regression-Best Linear Unbiased Prediction, Reproducing Kernel Hilbert Spaces, and randomForest. These models produced similar prediction accuracy of traits within the normal or low-N treatments, but the accuracy differed between the two treatments. ΔHT, LFW, LDW, and C were predicted slightly better under normal N with a mean Pearson r-value of 0.26, compared with r=0.22 under low N, while the prediction accuracies for Chl, N, C/N, and NUE were significantly improved under low-N stress with a mean r=0.45, compared with r=0.26 under normal N. The population panel contained three population structures, which generally had no effect on prediction accuracy. The moderate prediction accuracies obtained for N, C, and NUE under low-N stress are promising, and suggest a feasible means by which germplasm might be initially assessed for further detailed studies in breeding programs
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|a Journal Article
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|a Research Support, Non-U.S. Gov't
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|a Lolium perenne
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|a Genomic prediction
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|a low nitrogen
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|a natural variation
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|a perennial ryegrass
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| 650 |
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|a population structure
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| 650 |
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|a Nitrogen
|2 NLM
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| 650 |
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|a N762921K75
|2 NLM
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| 700 |
1 |
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|a Nie, Gang
|e verfasserin
|4 aut
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| 700 |
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|a Yao, Yanyu
|e verfasserin
|4 aut
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| 700 |
1 |
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|a Ji, Zhongjie
|e verfasserin
|4 aut
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| 700 |
1 |
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|a Gao, Jianhua
|e verfasserin
|4 aut
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| 700 |
1 |
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|a Wang, Xingchun
|e verfasserin
|4 aut
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| 700 |
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|a Jiang, Yiwei
|e verfasserin
|4 aut
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| 773 |
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|i Enthalten in
|t Journal of experimental botany
|d 1985
|g 71(2020), 20 vom: 22. Okt., Seite 6670-6683
|w (DE-627)NLM098182706
|x 1460-2431
|7 nnas
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| 773 |
1 |
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|g volume:71
|g year:2020
|g number:20
|g day:22
|g month:10
|g pages:6670-6683
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|u http://dx.doi.org/10.1093/jxb/eraa388
|3 Volltext
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