Time-series analysis of the transcriptome of the re-establishment of desiccation tolerance by ABA in germinated Arabidopsis thaliana seeds

Transcriptomic Analysis of the Dehydration Rate of Mature Rice (Oryza sativa) Seeds

In this study, a transcriptomic analysis of the dehydration rate of mature rice seeds was conducted to explore candidate genes related to the dehydration rate and provide a theoretical basis for breeding and utilization. We selected two rice cultivars for testing (Baghlani Nangarhar, an extremely rapid dehydration genotype, and Saturn, a slow dehydration genotype) based on the results determined by previous studies conducted on the screening of 165 germplasm materials for dehydration rate phenotypes. A rapid dehydration experiment performed on these two types of seeds was conducted. Four comparative groups were set up under control and dehydration conditions. The differentially expressed genes (DEGs) were quantified via transcriptome sequencing and real-time quantitative PCR (RT-qPCR). GO (Gene ontology) and KEGG(Kyoto Encyclopedia of Genes and Genomes) analyses were also conducted. In Baghlani Nangarhar, 53 DEGs were screened, of which 33 were up-regulated and 20 were down-regulated. In Saturn, 25 DEGs were screened, of which 19 were up-regulated and 6 were down-regulated. The results of the GO analysis show that the sites of action of the differentially expressed genes enriched in the rapid dehydration modes are concentrated in the cytoplasm, internal components of the membrane, and nucleosomes. They play regulatory roles in the processes of catalysis, binding, translocation, transcription, protein folding, degradation, and replication. They are also involved in adaptive responses to adverse external environments, such as reactive oxygen species and high temperature. The KEGG analysis showed that protein processing in the endoplasmic reticulum, amino acid biosynthesis, and oxidative phosphorylation were the main metabolic pathways that were enriched. The key differentially expressed genes and the most important metabolic pathways identified in the rapidly and slowly dehydrated genotypes were protein processing in the endoplasmic reticulum and oxidative phosphorylation metabolism. They were presumed to have important regulatory roles in the mechanisms of stress/defense, energy metabolism, protein synthesis/folding, and signal transduction during the dehydration and drying of mature seeds. The results of this study can potentially provide valuable information for further research on the genes and metabolic pathways related to the dehydration rate of mature rice seeds, and provide theoretical guidance for the selection and breeding of new rice germplasm that can be rapidly dehydrated at the mature stage.

Mechanistic insights derived from re-establishment of desiccation tolerance in germinating xerophytic seeds: Caragana korshinskii as an example

Germplasm conservation strongly depends on the desiccation tolerance (DT) of seeds. Xerophytic seeds have strong desiccation resistance, which makes them excellent models to study DT. Although some experimental strategies have been applied previously, most methods are difficult to apply to xerophytic seeds. In this review, we attempted to synthesize current strategies for the study of seed DT and provide an in-depth look at Caragana korshinskii as an example. First, we analyze congenital advantages of xerophytes in the study of seed DT. Second, we summarize several strategies used to study DT and illustrate a suitable strategy for xerophytic species. Then, based on our previous studies work with C. korshinskii, a feasible technical strategy for DT re-establishment is provided and we provide illustrate some special molecular mechanisms seen in xerophytic seeds. Finally, several steps to unveil the DT mechanism of xerophytic seeds are suggested, and three scientific questions that the field should consider are listed. We hope to optimize and utilize this strategy for more xerophytic species to more systematically decipher the physiological and molecular processes of seed DT and provide more candidate genes for molecular breeding.

Transcriptome profiling during mangrove viviparity in response to abscisic acid

Mangrove plants adapt to coastal tidal mudflats with specially evolved viviparity seed development. However, very little is known about the genetic and molecular mechanisms of mangrove viviparity. Here, we tested a hypothesis that plant hormone abscisic acid (ABA) plays a significant role in precocious germination of viviparous Kandelia obovata seeds by exogenous applications. Through transcriptome analysis of ABA treated seeds, it was found that ABA repressed mangrove fruit growth and development, and there were thousands of genes differentially expressed. As a result, dynamics of the pathways were dramatically altered. In particular, "Plant hormone signal transduction" and "MAPK signaling pathway" were represented significantly. Among differentially expressed genes, some key genes of ABA signal transduction were induced, while ABA biosynthesis genes were repressed. Take ABI1 and ABI2, key negative regulators in ABA signal pathway, as examples, homologous alignment and a phylogenetic tree in various species showed that ABI1 and ABI2 are highly conserved among various species. The functional similarity of these genes was confirmed by transgenic work in Arabidopsis. Taken together, ABA inhibited mangrove viviparity, but mangroves developed a mechanism to prevent accidently increase of ABA in the harsh environment for maintaining viviparous reproductive strategy.

CyLineUp: A Cytoscape app for visualizing data in network small multiples

CyLineUp is a Cytoscape 3 app for the projection of high-throughput measurement data from multiple experiments/samples on a network or pathway map using "small multiples". This visualization method allows for easy comparison of different experiments in the context of the network or pathway. The user can import various kinds of measurement data and select any appropriate Cytoscape network or WikiPathways pathway map. CyLineUp creates small multiples by replicating the loaded network as many times as there are experiments/samples (e.g. time points, stress conditions, tissues, etc.). The measurement data for each experiment are then mapped onto the nodes (genes, proteins etc.) of the corresponding network using a color gradient. Each step of creating the visualization can be customized to the user's needs. The results can be exported as a high quality vector image.