Climate sensitivity of Cryptomeria japonica in two contrasting environments: Perspectives from QTL mapping.
PLoS One
; 15(1): e0228278, 2020.
Article
em En
| MEDLINE
| ID: mdl-31990959
Long-lived forest tree species experience a wide range of environmental conditions throughout their lifespan. Evaluation of the underlying growth and development mechanisms of these species is essential to predict tree growth under climate change. This study investigated climate sensitivity to temperature, precipitation, dry periods, and the associated genomic regions in Cryptomeria japonica, Japan's most commercially important tree. We used tree rings and common garden experiments with three clonal replicates planted in two contrasting environments in Kyushu (Kumamoto site) and Honshu (Chiba site), Japan. Tree growth showed a significant negative correlation with the dry period (>4 days) in March of the year of tree-ring formation at the Chiba site. In contrast, temperature and precipitation had little influence on tree growth. Quantitative trait locus (QTL) analysis was performed to investigate climate sensitivity to dry periods at the Chiba site, revealing 13 significant QTLs. One QTL showed a substantially large contribution to the overall climate sensitivity, accounting for 12.4% of the total phenotypic variation. The phenotypic variance explained (PVE) by other QTLs ranged from 0.9% to 2.9%, and the total PVE by all QTLs was 35.6%. These findings indicate that the tree population at the Chiba site could be vulnerable to drought in early spring and that the QTL showing the greatest impact on climate sensitivity may be closely related to genes associated with tolerance or adaptation to drought stress. The QTLs identified in this study could be useful for molecular breeding, forest management, and predicting the growth of C. japonica under a changing climate.
Texto completo:
1
Coleções:
01-internacional
Base de dados:
MEDLINE
Assunto principal:
Mapeamento Cromossômico
/
Clima
/
Cryptomeria
/
Locos de Características Quantitativas
Tipo de estudo:
Diagnostic_studies
/
Prognostic_studies
Idioma:
En
Revista:
PLoS One
Assunto da revista:
CIENCIA
/
MEDICINA
Ano de publicação:
2020
Tipo de documento:
Article
País de afiliação:
Japão
País de publicação:
Estados Unidos