Transcriptome analysis of differentially expressed genes involved in selenium accumulation in tea plant (Camellia sinensis)

Abstract

Tea plant (Camellia sinensis) has strong enrichment ability for selenium (Se). Selenite is the main form of Se absorbed and utilized by tea plant. However, the mechanism of selenite absorption and accumulation in tea plant is still unknown. In this study, RNA sequencing (RNA-seq) was used to perform transcriptomic analysis on the molecular mechanism of selenite absorption and accumulation in tea plant. 397.98 million high-quality reads were obtained and assembled into 168,212 unigenes, 89,605 of which were extensively annotated. There were 60,582 and 1,362 differentially expressed genes (DEGs) in roots and leaves, respectively. RNA-seq results were further validated by quantitative RT-PCR. Based on GO terms, the unigenes were mainly involved in cell, binding and metabolic process. KEGG pathway enrichment analysis showed that predominant pathways included ribosome and protein processing in endoplasmic reticulum. Further analysis revealed that sulfur metabolism, glutathione metabolism, selenocompound metabolism and plant hormone signal transduction responded to selenite in tea plant. Additionally, a large number of genes of higher expressions associated with phosphate transporters, sulfur assimilation, antioxidant enzymes, antioxidant substances and responses to ethylene and jasmonic acid were identified. Stress-related plant hormones might play a signaling role in promoting sulfate/selenite uptake and assimilation in tea plant. Moreover, some other Se accumulation mechanisms of tea plant were found. Our study provides a possibility for controlling Se accumulation in tea plant through bio-technologies and will be helpful for breeding new tea cultivars.

Selenium affects the activity of black tea in preventing metabolic syndrome in high‐fat diet‐fed Sprague–Dawley rats

“…The Camellia sinensis plant (the raw material of tea) can absorb Se from the soil, and Se then accumulates in the leaves . Previous studies have demonstrated that the presence of Se enhances the antioxidant, prebiotic, and anti‐carcinogenic activity of tea .…”

Comparative Analysis of the 5’ Flanking Region in <i>Arabidopsis</i> and <i>O. sative</i> RP Genes Revealed Conserved and Divergent Regulating Mechanisms

“…As previous studies showed, the frequency of TTC repeat motif in Arabidopsis is higher in CDS than that in 5' UTR and intron. This may be as a result of codon usage bias [8]. However, compared to the genome background, there is no enrichment of this motif in the genic regions in RP genes, especially in the 5' UTR region, and only 10% RP genes has this motif in their 5' UTR regions and is significant lower than the genome background.…”

“…It also exhibits extremely strong positional bias in the [−200, 0] bp promoter regions of RP genes with a chi square value of 973.4. In addition to its general existence in RP genes, Motif3 is also found to be associated with dark-induced genes and over-represented in genes under circadian regulation in Arabidopsis [8]. Motif5 and motif6 are structurally related to motif2 and motif3 and can be considered as derivatives of these two motifs.…”

“…Recent studies in Arabidopsis have identified two cis elements presented in most of the RP genes promoters, suggesting that it could be involved in the coordinated expression of this class of genes at transcriptional level [7]. One of these cis elements is the proliferating cell nuclear antigen (PCNA) site II motif (5'-GCCCR-3') [8]. It is presented in most of the RP genes promoters and can be recognized by TCP-domain proteins [9].…”

Comparative de novo transcriptomics and untargeted metabolomic analyses elucidate complicated mechanisms regulating celery (Apium graveolens L.) responses to selenium stimuli

“…A total of 71 temperature stress-responsive proteins were identified through MALDI-TOF-TOF analysis[35]. Transcriptome sequencing has become a powerful technique for elucidating new genes and their related biochemical pathways in non-model plants because of its high throughput, low cost and large data output [36]. Metabolomics is a new field in the post-genome era that reveals the changing roles of metabolites in various tissues [37].…”