Deciphering and prediction of transcriptome dynamics under fluctuating field conditions.
Cell
; 151(6): 1358-69, 2012 Dec 07.
Article
em En
| MEDLINE
| ID: mdl-23217716
ABSTRACT
Determining the drivers of gene expression patterns is more straightforward in laboratory conditions than in the complex fluctuating environments where organisms typically live. We gathered transcriptome data from the leaves of rice plants in a paddy field along with the corresponding meteorological data and used them to develop statistical models for the endogenous and external influences on gene expression. Our results indicate that the transcriptome dynamics are predominantly governed by endogenous diurnal rhythms, ambient temperature, plant age, and solar radiation. The data revealed diurnal gates for environmental stimuli to influence transcription and pointed to relative influences exerted by circadian and environmental factors on different metabolic genes. The model also generated predictions for the influence of changing temperatures on transcriptome dynamics. We anticipate that our models will help translate the knowledge amassed in laboratories to problems in agriculture and that our approach to deciphering the transcriptome fluctuations in complex environments will be applicable to other organisms.
Texto completo:
1
Base de dados:
MEDLINE
Assunto principal:
Oryza
/
Modelos Estatísticos
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Regulação da Expressão Gênica de Plantas
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Transcriptoma
Tipo de estudo:
Prognostic_studies
/
Risk_factors_studies
Idioma:
En
Ano de publicação:
2012
Tipo de documento:
Article