An enigma in the genetic responses of plants to salt stresses

Soil salinity is one of the main factors restricting crop production throughout the world. Various salt tolerance traits and the genes controlling these traits are responsible for coping with salinity stress in plants. These coping mechanisms include osmotic tolerance, ion exclusion, and tissue tolerance. Plants exposed to salinity stress sense the stress conditions, convey specific stimuli signals, and initiate responses against stress through the activation of tolerance mechanisms that include multiple genes and pathways. Advances in our understanding of the genetic responses of plants to salinity and their connections with yield improvement are essential for attaining sustainable agriculture. Although a wide range of studies have been conducted that demonstrate genetic variations in response to salinity stress, numerous questions need to be answered to fully understand plant tolerance to salt stress. This chapter provides an overview of previous studies on the genetic control of salinity stress in plants, including signaling, tolerance mechanisms, and the genes, pathways, and epigenetic regulators necessary for plant salinity tolerance

Transcriptomic and metabolic flux analyses reveal shift of metabolic patterns during rice grain development

Abstract Background Rice (Oryza sativa) is one of the most important grain crops, which serves as food source for nearly half of the world population. The study of rice development process as well as related strategies for production has made significant progress. However, the comprehensive study on development of different rice tissues at both transcriptomic and metabolic flux level across different stages was lacked. Results In this study, we performed RNA-Seq and characterized the expression profiles of differentiated tissues from Oryza sativa Zhonghua 11, including leaves, sheath, stamen, pistil, lemma and palea of the booting stage, and embryo, endosperm, lemma and palea of the mature grain stage. By integrating this set of transcriptome data of different rice tissues at different stages with a genome-scale rice metabolic model, we generated tissue-specific models and investigated the shift of metabolic patterns, and the discrepancy between transcriptomic and metabolic level. We found although the flux patterns are not very similar with the gene expression pattern, the tissues at booting stage and mature grain stage can be separately clustered by primary metabolism at either level. While the gene expression and flux distribution of secondary metabolism is more diverse across tissues and stages. The critical rate-limiting reactions and pathways were also identified. In addition, we compared the patterns of the same tissue at different stages and the different tissues at same stage. There are more altered pathways at gene expression level than metabolic level, which indicate the metabolism is more robust to reflect the phenotype, and might largely because of the complex post-transcriptional modification. Conclusions The tissue-specific models revealed more detail metabolic pattern shift among different tissues and stages, which is of great significance to uncover mechanism of rice grain development and further improve production and quality of rice