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1.
Int J Mol Sci ; 22(5)2021 Feb 24.
Artículo en Inglés | MEDLINE | ID: mdl-33668247

RESUMEN

Soil salinity is a serious menace in rice production threatening global food security. Rice responses to salt stress involve a series of biological processes, including antioxidation, osmoregulation or osmoprotection, and ion homeostasis, which are regulated by different genes. Understanding these adaptive mechanisms and the key genes involved are crucial in developing highly salt-tolerant cultivars. In this review, we discuss the molecular mechanisms of salt tolerance in rice-from sensing to transcriptional regulation of key genes-based on the current knowledge. Furthermore, we highlight the functionally validated salt-responsive genes in rice.


Asunto(s)
Regulación de la Expresión Génica de las Plantas , Oryza/fisiología , Osmorregulación , Proteínas de Plantas/metabolismo , Tolerancia a la Sal , Estrés Fisiológico , Fenotipo , Proteínas de Plantas/genética
2.
Front Plant Sci ; 9: 868, 2018.
Artículo en Inglés | MEDLINE | ID: mdl-30042770

RESUMEN

Association mapping using a multi-parent advanced generation intercross (MAGIC) population provides a promising tool in genetic dissection of rice cooking and eating quality (CEQ). In this study, QTLs were identified for ten physicochemical properties related to CEQ using 508 F6 MAGIC lines. The whole population and eight founder lines were genotyped with 6K Illumina Infinium HD Assay. All traits had high heritability estimates and showed a large genetic variation in the MAGIC population. Highly significant phenotypic correlations were present between traits. AC was significantly positively correlated with PKT, TV, FV, SBV, PKT, and RT but significantly negatively correlated with GC and BDV. Seventeen QTLs were identified for all traits. GBSSI locus was hosted or closely to nine QTLs, qAC6, qGC6.1, qPKT6.1, qPKV6, qBDV6.1, qTV6.1, qFV6, qSBV6, and qRT6, suggesting that GBSSI impacts the overall CEQ. Another locus closed to SSIIa, located at 6.99 Mb, affects five traits, GC, PKT, BDV, SBV, and PT. The identified QTLs revealed small to modest effects where the highest percentage of phenotypic variance explained was 17.18%. These QTLs are directly relevant and useful in breeding for CEQ in indica rice. These results also confirmed that QTL mapping via association mapping using a MAGIC population is a powerful method in genetic analysis of complex traits.

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