Transcriptomics Integrated With Metabolomics Reveal the Effects of Ultraviolet-B Radiation on Flavonoid Biosynthesis in Antarctic Moss

Abstract

Bryophytes are the dominant vegetation in the Antarctic continent. They have suffered more unpleasant ultraviolet radiation due to the Antarctic ozone layer destruction. However, it remains unclear about the molecular mechanism of Antarctic moss acclimation to UV-B light. Here, the transcriptomics and metabolomics approaches were conducted to uncover transcriptional and metabolic profiling of the Antarctic moss Leptobryum pyriforme under UV-B radiation. Totally, 67,290 unigenes with N₅₀ length of 2,055 bp were assembled. Of them, 1,594 unigenes were significantly up-regulated and 3353 unigenes were markedly down-regulated under UV-B radiation. These differentially expressed genes (DEGs) involved in UV-B signaling, flavonoid biosynthesis, ROS scavenging, and DNA repair. In addition, a total of 531 metabolites were detected, while flavonoids and anthocyanins accounted for 10.36% of the total compounds. There were 49 upregulated metabolites and 41 downregulated metabolites under UV-B radiation. Flavonoids were the most significantly changed metabolites. qPCR analysis showed that UVR8-COP1-HY5 signaling pathway genes and photolyase genes (i.e., LpUVR3, LpPHR1, and LpDPL) were significantly up-regulated under UV-B light. In addition, the expression levels of JA signaling pathway-related genes (i.e., OPR and JAZ) and flavonoid biosynthesis-related genes were also significantly increased under UV-B radiation. The integrative data analysis showed that UVR8-mediated signaling, jasmonate signaling, flavonoid biosynthesis pathway and DNA repair system might contribute to L. pyriforme acclimating to UV-B radiation. Therefore, these findings present a novel knowledge for understanding the adaption of Antarctic moss to polar environments and provide a foundation for assessing the impact of global climate change on Antarctic land plants.

Keywords: abiotic stress; bryophytes; flavonoids; metabolome; transcriptome; ultraviolet-B radiation.

FIGURE 1

The field picture of Antarctic moss sampling site.

FIGURE 2

The Antarctic moss L. pyriforme can tolerance strong UV-B radiation. (A) Photo of L. pyriforme under nornal condition. (B) Morphological changes of L. pyriforme under UV-B radiation. (C–F) The physiological parameters of L. pyriforme under UV-B radiation. Bar = 1.0 cm.

FIGURE 3

The statistics of functional annotation of the Antarctic moss genes. (A) The statistics of gene annotation rate in seven databases. (B) Venn diagram of five database annotation results. (C) The statistics of species classification. (D) The statistics of similarity distribution. Bar = 0.5 cm.

FIGURE 4

Transcriptome sequencing of the Antarctic moss under UV-B light. (A) The classification of Gene Ontology of L. pyriforme unigenes. (B) The volcano plot showing the DEGs between UV-B radiation group and control group. The X-axis indicates fold change of gene expression (threshold, | log₂(Treat/Control)| > 1), while the Y-axis means the statistically significant level (threshold, q-value < 0.005). (C) KEGG pathway enrichment of DEGs. Rich factor represents the ratio of the number of DEGs to the total number of annotated genes in this pathway.

FIGURE 5

Phylogenetic relationship of flavonoid biosynthesis-related enzymes in representative plants. 2-OGD, 2-oxoglutarate-dependent dioxygenase; ANS, anthocyanidin synthase; CHS, chalcone synthase; CHI, chalcone isomerase; F3H, flavanone 3-hydroxylase; FNS, flavone synthase; FLS, flavonol synthase; F 3′H, flavonoid 3′-hydroxylase; F3′,5′H, flavonoid 3′,5′-hydroxylase.

FIGURE 6

Widely targeted metabolomic analysis of the Antarctic moss under UV-B radiation. (A) Statistical analysis of the classes of total metabolites. (B) The differences between UV-B radiation group and control group were calculated using OPLS-DA model. R²X and R²Y indicate the interpretation rate of X and Y matrix, respectively. Q²Y represents the prediction ability of the model. A value closer to 1 means that the model is more stable and reliable. In addition, Q²Y > 0.5 can be regarded as an effective model, and Q²Y > 0.9 is an excellent model. (C) The volcano plot showing the contents of metabolites and the statistical significance. Each point represents a metabolite. Horizontal ordinate indicates the fold change of metabolites between two groups, while VIP value represents significant difference in statistical analysis. (D) The fold change of the top 20 significantly changed metabolites (SCMs) between two groups. (E) The VIP scores of the top 20 SCMs between two groups. (F) Statistics of KEGG enrichment for the SCMs.

FIGURE 7

Key genes of UVR8 and Jasmonate signaling pathway were up-regulated after UV-B treatment. The gene expression levels were analyzed by quantitative RT-PCR analysis; the Y-axis indicates the relative expression level; the X-axis indicates UV-B treatment time (h); The data were calculated from three biological replicates. Vertical bars are means ± SE. Significant difference (*P < 0.05, **P < 0.01).

FIGURE 8

Key enzyme genes of flavonoid synthesis pathway were up-regulated after UV-B treatment. The gene expression levels were analyzed by quantitative RT-PCR analysis; the Y-axis indicates the relative expression level; the X-axis indicates UV-B treatment time (h); The data were calculated from three biological replicates. Vertical bars are means ± SE. Significant difference (*P < 0.05, **P < 0.01).

FIGURE 9

Integrated transcriptome and metabolome analysis showed that flavonoid biosynthesis might contribute the resistance of Antarctic moss against UV-B radiation. The left block of each gene and metabolite indicated the log₂(fold change) of this gene and metabolite between control and UV-B radiation. Genes labeled in solid line box and metabolites showed in dotted box.