Comparative analysis of human and mouse transcriptomes of Th17 cell priming

Abstract

Uncontrolled Th17 cell activity is associated with cancer and autoimmune and inflammatory diseases. To validate the potential relevance of mouse models of targeting the Th17 pathway in human diseases we used RNA sequencing to compare the expression of coding and non-coding transcripts during the priming of Th17 cell differentiation in both human and mouse. In addition to already known targets, several transcripts not previously linked to Th17 cell polarization were found in both species. Moreover, a considerable number of human-specific long non-coding RNAs were identified that responded to cytokines stimulating Th17 cell differentiation. We integrated our transcriptomics data with known disease-associated polymorphisms and show that conserved regulation pinpoints genes that are relevant to Th17 cell-mediated human diseases and that can be modelled in mouse. Substantial differences observed in non-coding transcriptomes between the two species as well as increased overlap between Th17 cell-specific gene expression and disease-associated polymorphisms underline the need of parallel analysis of human and mouse models. Comprehensive analysis of genes regulated during Th17 cell priming and their classification to conserved and non-conserved between human and mouse facilitates translational research, pointing out which candidate targets identified in human are worth studying by using in vivo mouse models.

Transcriptional Repressor HIC1 Contributes to Suppressive Function of Human Induced Regulatory T Cells

“…To identify potential TFs required for the development and function of iTreg cells, we studied the expression of all the TFs during iTreg development. To identify iTreg-specific factors, we compared the iTreg RNA sequencing (RNA-seq) data with our recently published human Th17 data ( Tuomela et al., 2016 ). Seventy-eight TFs were DE in both iTreg cells (compared with Th0) as well as Th17 cells (compared with Th0), and 149 and 84 TFs were DE only in the iTreg or Th17 cell subsets, respectively ( Figure 1 E; Table S2 ).…”

Quantitative proteomic characterization and comparison of T helper 17 and induced regulatory T cells

“…Characterization of the molecular mechanisms directing the differentiation of naïve Th cells toward their distinct subsets—namely, Th1, Th2, Th17, and Treg cells—has been studied in some depth by using transcriptomic and epigenomic strategies [ 9 – 14 ]. However, the regulation of gene expression is also controlled at the posttranscriptional, translational, and posttranslational levels.…”

Perspectives on Systems Modeling of Human Peripheral Blood Mononuclear Cells

“…Moreover, comparative transcriptomics of mouse and human Th17 cells marked novel transcripts related to Th17 polarization. Several human long non-coding RNAs were identified in response to cytokines stimulating Th17 cell differentiation (Tuomela and Lahesmaa, 2013 ; Tuomela et al, 2016 ).…”

“…This model was used to study carbohydrate metabolism, fatty acid metabolism and glutaminolysis (Han et al, 2016 ). Availability of the omics data for immune cell subsets, particularly CD4+ T helper cells (Th1, Th2, Th17) (Kanduri et al, 2015 ; Tuomela et al, 2016 ) provides an opportunity to reconstruct T helper specific GEMs, that could be used to characterize metabolic phenotypes of Th subsets and predict differences between them.…”