Analysis of chromatin organization and gene expression in T cells identifies functional genes for rheumatoid arthritis

Yang, Jing; McGovern, Amanda; Martin, Paul; Duffus, Kate; Ge, Xin; Zarrineh, Peyman; Morris, Andrew P.; Adamson, Antony; Fraser, Peter; Rattray, Magnus; Eyre, Steve

doi:10.1101/827923

Cited by 10 publications

(17 citation statements)

References 56 publications

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“…Our CCA analysis shows that by aligning samples using shared structures we were able to identify known cell subtypes and characterise the transcriptome of these subtypes, as well as their response to stimulation. Again, while the effect of stimulation has been shown to be similar between samples in bulk RNA-seq 23 , increased sample numbers would be required to confirm this in scRNA-seq. Despite this, these findings suggest it is possible to directly compare samples with different disease activities, an essential step in studies investigating treatment response.…”

Section: Discussionmentioning

confidence: 99%

Characterisation of CD4+ T-cell subtypes using single cell RNA sequencing and the impact of cell number and sequencing depth

Ding

Smith

Orozco

et al. 2020

Sci Rep

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CD4+ T-cells represent a heterogeneous collection of specialised sub-types and are a key cell type in the pathogenesis of many diseases due to their role in the adaptive immune system. By investigating CD4+ T-cells at the single cell level, using RNA sequencing (scRNA-seq), there is the potential to identify specific cell states driving disease or treatment response. However, the impact of sequencing depth and cell numbers, two important factors in scRNA-seq, has not been determined for a complex cell population such as CD4+ T-cells. We therefore generated a high depth, high cell number dataset to determine the effect of reduced sequencing depth and cell number on the ability to accurately identify CD4+ T-cell subtypes. Furthermore, we investigated T-cell signatures under resting and stimulated conditions to assess cluster specific effects of stimulation. We found that firstly, cell number has a much more profound effect than sequencing depth on the ability to classify cells; secondly, this effect is greater when cells are unstimulated and finally, resting and stimulated samples can be combined to leverage additional power whilst still allowing differences between samples to be observed. While based on one individual, these results could inform future scRNA-seq studies to ensure the most efficient experimental design.

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Section: Discussionmentioning

confidence: 99%

Characterisation of CD4+ T-cell subtypes using single cell RNA sequencing and the impact of cell number and sequencing depth

Ding

Smith

Orozco

et al. 2020

Sci Rep

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“…To characterize the TF landscape of the survivin-ChIP peaks, we used the global ChIP-seq dataset for 1034 human transcriptional regulators in the ReMap database 24 to annotate the set of nonredundant survivin-ChIP peaks. We identi ed 146 TF candidates that were signi cantly enriched across the survivin-ChIP peaks with 0 kb (minimal threshold for the overlapping peaks 10%) and 100-kb anking regions (Fig.…”

Section: Survivin-bound Chromatin Is Predicted To Regulate Carbohydrate Metabolismmentioning

confidence: 99%

“…To identify TFs in open chromatin of CD4 + cells, we used the ATAC-seq dataset (GSE138767 24 ) to annotate nonredundant survivin-ChIP peaks. Survivin was tightly associated with a subset of TFs comparable to those identi ed by whole-genome analysis (Fig.…”

Section: Survivin-bound Chromatin Is Predicted To Regulate Carbohydrate Metabolismmentioning

confidence: 99%

“…To connect survivin peaks with transcription, we annotated the whole set of survivin-ChIP peaks to open chromatin in aCD3/aCD28 activated CD4 + cells, using ATAC-seq data (GSE138767 24 ). We found that 12.3% (2 h) and 21.5% (4 h of cell stimulation) of the peaks were located within 0-10 kb of open chromatin regions.…”

Section: Survivin-bound Chromatin Is Predicted To Regulate Carbohydrate Metabolismmentioning

confidence: 99%

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Chromatin bound by survivin regulates the glycolytic switch in interferon-γ producing CD4+ T cells

Erlandsson

Andersson²,

Oparina

et al. 2021

Preprint

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Upon activation, CD4+ T cells adapt metabolically to fulfill their effector function in autoimmunity. Here we show that nuclear survivin is essential for transcriptional regulation of glucose utilization. We found that the glycolytic switch in interferon (IFN) g–producing CD4+ cells is dependent on a complex of survivin with interferon regulatory factor 1 (IRF1), and Smad3 and was reversed by survivin inhibition. Transcriptome analysis of CD4+ cells and sequencing of survivin-bound chromatin identified a hub of metabolism regulating genes whose transcription depended on survivin. Direct binding of survivin to IRF1 and SMAD3 promoted IRF1-mediated transcription, repressed SMAD3 activity, and lowered PFKFB3 production. Inhibiting survivin upregulated PFKFB3, restored glycolysis, and reduced glucose uptake, improving control over IFNg-dependent T-cell functions. Thus, IRF1-survivin-SMAD3 interactions are important for metabolic adaptation of CD4+ cells and provide an attractive strategy to counteract IFNg-dependent inflammation.

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“…Besides, the polymorphisms of CTLA-4 have already been proved to be candidates of the risk of the common autoimmune diseases at the genetic level [12][13][14][15]. As RA is a T cell mediated autoimmune disorder and CTLA-4 play a vital role in regulating T cell function [11,12,16], it suggests that CTLA-4 expression or function is most likely associated with the pathogenesis of RA.…”

Section: Introductionmentioning

confidence: 99%

Association Between CTLA-4 Gene Polymorphism and Risk of Rheumatoid Arthritis (RA): Evidence from a Meta-analysis Involving 21681 Cases and 23457 Controls.

Zhou¹,

Gao²,

Yuan³

et al. 2020

Preprint

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Background: Genetic predisposition was well known to be involved in the pathogenesis of Rheumatoid arthritis (RA). Lots of genetic studies on association between Cytotoxic T lymphocyte-associated protein 4 (CTLA-4) polymorphisms and RA susceptibility had been accumulated in the past few decades, yet reporting inconsistent results. Therefore, we summarized the most-often 3 polymorphisms and performed a meta-analysis to comprehensively evaluate the effect of CTLA-4 gene polymorphisms on RA risk.Methods: Five electronic databases were searched for eligible studies till Oct. 2020. The pooled odds ratios (ORs) and 95% confidence intervals (CIs) were calculated to assess the strength of association. Stratified analysis was conducted by ethnicity.Results: In total, 42 case-control studies including 21681 cases and 23457 controls were obtained. For rs3087243 polymorphism, significant association was detected in Asians (A vs. G: OR=0.77, 95%CI=0.65-0.90, P=0.001; AA vs. GG: OR=0.67, 95%CI=0.48-0.94, P=0.02) and Caucasians (A vs. G: OR=0.89, 95%CI=0.86-0.93, P<0.00001; AA vs. GG: OR=0.81, 95%CI=0.75-0.88, P<0.00001). For rs231775 polymorphism, significant association was observed in the overall (G vs. A: OR =1.16, 95%CI=1.08-1.25, P<0.0001; GG vs. AA: OR=1.29, 95%CI=1.12-1.50, P=0.0006), in Asians (G vs. A: OR=1.27, 95%CI=1.10-1.47, P=0.001; GG vs. AA: OR=1.58, 95%CI=1.24-2.01, P=0.0002), and not in Caucasians. However, there was no association between rs5742909 polymorphism and RA risk.Conclusion: This meta-analysis confirmed that rs3087243 and rs231775 polymorphism were associated with the risk of RA in both overall population and ethnic-specific analysis, but there was no association between rs5742909 polymorphism and RA risk.

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Analysis of chromatin organization and gene expression in T cells identifies functional genes for rheumatoid arthritis

Cited by 10 publications

References 56 publications

Characterisation of CD4+ T-cell subtypes using single cell RNA sequencing and the impact of cell number and sequencing depth

Characterisation of CD4+ T-cell subtypes using single cell RNA sequencing and the impact of cell number and sequencing depth

Chromatin bound by survivin regulates the glycolytic switch in interferon-γ producing CD4+ T cells

Association Between CTLA-4 Gene Polymorphism and Risk of Rheumatoid Arthritis (RA): Evidence from a Meta-analysis Involving 21681 Cases and 23457 Controls.

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