Buisine N et al. (2021), Transcriptome and Methylome Analysis Reveal Com...

XB-ART-58489

Cells 2021 Sep 09;109:. doi: 10.3390/cells10092375.

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Transcriptome and Methylome Analysis Reveal Complex Cross-Talks between Thyroid Hormone and Glucocorticoid Signaling at Xenopus Metamorphosis.

Buisine N , Grimaldi A , Jonchere V , Rigolet M , Blugeon C , Hamroune J , Sachs LM .

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BACKGROUND: Most work in endocrinology focus on the action of a single hormone, and very little on the cross-talks between two hormones. Here we characterize the nature of interactions between thyroid hormone and glucocorticoid signaling during Xenopus tropicalis metamorphosis. METHODS: We used functional genomics to derive genome wide profiles of methylated DNA and measured changes of gene expression after hormonal treatments of a highly responsive tissue, tailfin. Clustering classified the data into four types of biological responses, and biological networks were modeled by system biology. RESULTS: We found that gene expression is mostly regulated by either T3 or CORT, or their additive effect when they both regulate the same genes. A small but non-negligible fraction of genes (12%) displayed non-trivial regulations indicative of complex interactions between the signaling pathways. Strikingly, DNA methylation changes display the opposite and are dominated by cross-talks. CONCLUSION: Cross-talks between thyroid hormones and glucocorticoids are more complex than initially envisioned and are not limited to the simple addition of their individual effects, a statement that can be summarized with the pseudo-equation: TH ∙ GC > TH + GC. DNA methylation changes are highly dynamic and buffered from genome expression.

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Species referenced: Xenopus tropicalis
Genes referenced: agr2 ctrl dnmt1 ezh2 mecp2 smarca4 uhrf1 usp7
GO keywords: thyroid hormone mediated signaling pathway [+]

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	Figure 1. Experimental setup to address T3 and CORT cross-talks. An experimental and data analysis workflow. Tailfin (green) response to treatments was characterized by functional genomics. For each experiment, samples were collected from pools of five tailfins.
	Figure 2. Transcriptome analysis following T3 and/or CORT. (A) Principal Component Analysis (PCA) of RNA-Seq variance from tailfin dissected from cultured tail explants. The two main components capture the effects of both hormones, corresponding to 77% of the total variance. Square, circle, and diamond: biological replicates. (B) Independent validation of RNA-Seq data by RT-qPCR. Scatter plot of the relationship between RNA-Seq versus RT-qPCR expression changes, also shown in box plots. (C) Average expression value versus fold change (MA plot). DE genes are in blue. (D) Gene Ontology analysis.
	Figure 3. Gene expression is modulated by one, the other, or both hormones. Only genes displaying consistent expression between explants culture and whole animals were kept. (A) Types of gene regulation by T3 and CORT. (B) Gene regulation by either T3 or CORT. (C) Gene regulation by T3 and CORT. (D) Complex regulation by both hormones (X-talks).
	Figure 4. System level modeling of transcriptional responses identify the DNA methylation dynamic as a major mediator of tailfin regression. Only transcriptional responses displaying consistent expression between explants culture and whole animals are considered. (A) Network of KEGG pathways. (B) DE genes together with their first neighbors in the network, forming densely connected sub-networks. (C) GO analysis of the sub-networks highlighting terms such as cell death, DNA damages, and DNA repair. (D) Tail regression test in vitro. Synergistic action of T3 and CORT after 3 day treatments. (E,F) Protein-Protein Interactions network and identification of hubs. Most DE protein complexes relate to DNA methylation. (G) Heatmap of expression levels of genes involved in DNA methylation.
	Figure 5. T3 and CORT induce genome wide changes of DNA methylation levels. (A–C) Three independent loci with local changes of DNA methylation (green arrow). Tracks order: gene annotation, DNA methylation changes relative to CTRL (T3, CORT, and T3-CORT), mRNA abundance (CTRL, T3, CORT, and T3-CORT). (D) Relationship between the genomic span and the amplitude of differentially methylated regions (DMR). (E) Differential dinucleotide frequency found in DMRs and exonic sequences. DMRs are enriched in CpG.
	Figure 6. The complex dynamics of DNA methylation levels at DMRs. (A) Types of gene regulation by T3 and CORT. (B) Gene regulation by either T3 or CORT. (C) Gene regulation by T3 and CORT. (D) Complex regulation by both hormones (X-talks).
	Figure 7. DMRs are located close to and far away from genes. (A) Distance between DMRs and the nearest gene. (B) Overlap between DMRs and known transposable element (TE) sequences. (C) TE content of DMRs. (D) Nuclear receptor binding sites predicted in DMRs. Only DMR containing predicted NRBS are shown.

References [+] :

Anders, Count-based differential expression analysis of RNA sequencing data using R and Bioconductor. 2013, Pubmed