Transcriptome Analysis Revealed the Roles of Carbohydrate Metabolism on Differential Acetaldehyde Production Capacity in Persimmon Fruit in Response to High-CO2 Treatment

Transcriptome analysis of the effects of different carbon dioxide concentrations on paramylon accumulation in Euglena gracilis Z

Appropriate concentration of carbon dioxide (CO2) will promote algae growth and metabolism. Building upon this finding, the present study investigated the impact of different CO2 concentrations (5% and 20%) on the carbon sequestration capacity of E. gracilis through aeration culturing, employing a combination of physiological analyses and transcriptome analysis. The results demonstrated that under 5% CO2 concentration, the cell density of E. gracilis was 1.79 times higher than that achieved in an air culture condition, and the paramylon content of E. gracilis was found to be 6.18 times higher than that of the air group. Based on transcriptome analysis, the carbon metabolism of E. gracilis was discussed. Significant up-regulation expression of genes associated with carbon synthesis was validated by an increase in paramylon content. This study revealed that under 5% CO2 conditions, E. gracilis exhibited elevated growth rate and enhanced photosynthetic carbon assimilation efficiency.

Investigating phenotypic relationships in persimmon accessions through integrated proteomic and metabolomic analysis of corresponding fruits

Together with phenological and genomic approaches, gel-based and label-free proteomic as well metabolomic procedures were separately applied to plants to highlight differences between ecotypes, to estimate genetic variability within/between organism populations, or to characterize specific mutants/genetically modified lines at metabolic level. To investigate the possible use of tandem mass tag (TMT)-based quantitative proteomics in the above-mentioned contexts and based on the absence of combined proteo-metabolomic studies on Diospyros kaki cultivars, we here applied integrated proteomic and metabolomic approaches to fruits from Italian persimmon ecotypes with the aim to characterize plant phenotypic diversity at molecular level. We identified 2255 proteins in fruits, assigning 102 differentially represented components between cultivars, including some related to pomological, nutritional and allergenic characteristics. Thirty-three polyphenols were also identified and quantified, which belong to hydroxybenzoic acid, flavanol, hydroxycinnamic acid, flavonol, flavanone and dihydrochalcone sub-classes. Heat-map representation of quantitative proteomic and metabolomic results highlighted compound representation differences in various accessions, whose elaboration through Euclidean distance functions and other linkage methods defined dendrograms establishing phenotypic relationships between cultivars. Principal component analysis of proteomic and metabolomic data provided clear information on phenotypic differences/similarities between persimmon accessions. Coherent cultivar association results were observed between proteomic and metabolomic data, emphasizing the utility of integrating combined omic approaches to identify and validate phenotypic relationships between ecotypes, and to estimate corresponding variability and distance. Accordingly, this study describes an original, combined approach to outline phenotypic signatures in persimmon cultivars, which may be used for a further characterization of other ecotypes of the same species and an improved description of nutritional characteristics of corresponding fruits.

Transcriptional Memory in Taraxacum mongolicum in Response to Long-Term Different Grazing Intensities

Grazing, as an important land use method in grassland, has a significant impact on the morphological and physiological traits of plants. However, little is known about how the molecular mechanism of plant responds to different grazing intensities. Here, we investigated the response of Taraxacum mongolicum to light grazing and heavy grazing intensities in comparison with a non-grazing control. Using de novo transcriptome assembly, T. mongolicum leaves were compared for the expression of the different genes under different grazing intensities in natural grassland. In total, 194,253 transcripts were de novo assembled and comprised in nine leaf tissues. Among them, 11,134 and 9058 genes were differentially expressed in light grazing and heavy grazing grassland separately, with 5867 genes that were identified as co-expression genes in two grazing treatments. The Nr, SwissProt, String, GO, KEGG, and COG analyses by BLASTx searches were performed to determine and further understand the biological functions of those differentially expressed genes (DEGs). Analysis of the expression patterns of 10 DEGs by quantitative real-time RT-PCR (qRT-PCR) confirmed the accuracy of the RNA-Seq results. Based on a comparative transcriptome analysis, the most significant transcriptomic changes that were observed under grazing intensity were related to plant hormone and signal transduction pathways, carbohydrate and secondary metabolism, and photosynthesis. In addition, heavy grazing resulted in a stronger transcriptomic response compared with light grazing through increasing the of the secondary metabolism- and photosynthesis-related genes. These changes in key pathways and related genes suggest that they may synergistically respond to grazing to increase the resilience and stress tolerance of T. mongolicum. Our findings provide important clues for improving grassland use and protection and understanding the molecular mechanisms of plant response to grazing.

Molecular basis of the formation and removal of fruit astringency

Astringency is a dry puckering mouthfeel mainly generated by the binding of tannins with proteins in the mouth. Tannins confer benefits such as resistance to biotic stresses and have antioxidant activity, and moderate concentrations of tannins can improve the flavor of fruits or their products. However, fruits with high contents of tannins have excessive astringency, which is undesirable. Thus, the balance of astringency formation and removal is extremely important for human consumption of fruit and fruit-based products. In recent years, the understanding of fruit astringency has moved beyond the biochemical aspects to focus on the genetic characterization of key structural genes and their transcriptional regulators that cause astringency. This article provides an overview of astringency formation and evaluation. We summarize the methods of astringency regulation and strategies and mechanisms for astringency removal, and discuss perspectives for future exploration and modulation of astringency for fruit quality improvement.

C-CorA: A Cluster-Based Method for Correlation Analysis of RNA-Seq Data

Correlation analysis is a routine method of biological data analysis. In the process of RNA-Seq analysis, differentially expressed genes could be identified by calculating the correlation coefficients in the comparison of gene expression vs. phenotype or gene expression vs. gene expression. However, due to the complicated genetic backgrounds of perennial fruit, the correlation coefficients between phenotypes and genes are usually not high in fruit quality studies. In this study, a cluster-based correlation analysis method (C-CorA) is presented for fruit RNA-Seq analysis. C-CorA is composed of two main parts: the clustering analysis and the correlation analysis. The algorithm is described and then integrated into the MATLAB code and the C# WPF project. The C-CorA method was applied to RNA-Seq datasets of loquat (Eriobotrya japonica) fruit stored or ripened under different conditions. Low temperature conditioning or heat treatment of loquat fruit can alleviate the extent of lignification that occurs because of postharvest storage under low temperatures (0 °C). The C-CorA method generated correlation coefficients and identified many candidate genes correlated with lignification, including EjCAD3 and EjCAD4 and transcription factors such as MYB (UN00328). C-CorA is an effective new method for the correlation analysis of various types of data with different dimensions and can be applied to RNA-Seq data for candidate gene detection in fruit quality studies.

Transcription factors AcERF74/75 respond to waterlogging stress and trigger alcoholic fermentation-related genes in kiwifruit

Kiwifruit plants have a fleshy, shallow root system which is sensitive to waterlogging stress, which results in a decrease in crop yield or even plants death. Although the waterlogging stress responses in kiwifruit have attracted much attention, the underlying molecular mechanism remains unclear. In this study, waterlogging led to drastic inhibition of root growth of 'Donghong' kiwifruit (Actinidia chinensis) plants grown in vitro, which was accompanied by significant elevation of endogenous acetaldehyde and ethanol contents. RNA-seq of roots of plants waterlogged for 0, 1 and 2 days revealed that a total of 149 genes were up- or down-regulated, including seven biosynthetic genes related to the glycolysis/gluconeogenesis pathway and 10 transcription factors. Analyses with real-time PCR, dual-luciferase assays and EMSA demonstrated that AcERF74 and AcERF75, two members of the ERF-VII subfamily, directly upregulated AcADH1 (alcohol dehydrogenase). Moreover, the overexpression of AcERF74/75 in transgenic calli resulted in dramatic increase of endogenous ethanol contents through the triggering of AcADH1 and AcADH2 expression. Although the AcPDC2 (pyruvate decarboxylase) expression was also enhanced in transgenic lines, the endogenous acetaldehyde contents showed no significant changes. These results illustrated that AcERF74/75 are two transcriptional activators on alcoholic fermentation related genes and are responsive to waterlogging stress in kiwifruit.