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Shifts in isoform usage underlie transcriptional differences in regulatory T cells in type 1 diabetes.

ABSTRACT: Genome-wide association studies have identified numerous loci with allelic associations to Type 1 Diabetes (T1D) risk. Most disease-associated variants are enriched in regulatory sequences active in lymphoid cell types, suggesting that lymphocyte gene expression is altered in T1D. Here we assay gene expression between T1D cases and healthy controls in two autoimmunity-relevant lymphocyte cell types, memory CD4⁺/CD25⁺ regulatory T cells (Treg) and memory CD4⁺/CD25^- T cells, using a splicing event-based approach to characterize tissue-specific transcriptomes. Limited differences in isoform usage between T1D cases and controls are observed in memory CD4⁺/CD25^- T-cells. In Tregs, 402 genes demonstrate differences in isoform usage between cases and controls, particularly RNA recognition and splicing factor genes. Many of these genes are regulated by the variable inclusion of exons that can trigger nonsense mediated decay. Our results suggest that dysregulation of gene expression, through shifts in alternative splicing in Tregs, contributes to T1D pathophysiology.

SUBMITTER: Newman JRB

PROVIDER: S-EPMC10533491 | biostudies-literature | 2023 Sep

REPOSITORIES: biostudies-literature

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Shifts in isoform usage underlie transcriptional differences in regulatory T cells in type 1 diabetes.

Newman Jeremy R B JRB Long S Alice SA Speake Cate C Greenbaum Carla J CJ Cerosaletti Karen K Rich Stephen S SS Onengut-Gumuscu Suna S McIntyre Lauren M LM Buckner Jane H JH Concannon Patrick P

Communications biology 20230927 1

Genome-wide association studies have identified numerous loci with allelic associations to Type 1 Diabetes (T1D) risk. Most disease-associated variants are enriched in regulatory sequences active in lymphoid cell types, suggesting that lymphocyte gene expression is altered in T1D. Here we assay gene expression between T1D cases and healthy controls in two autoimmunity-relevant lymphocyte cell types, memory CD4+/CD25+ regulatory T cells (Treg) and memory CD4+/CD25 ...[more]

PMID: 37758901

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Project description:BACKGROUND: Dysregulation of transcriptional programs leads to cell malfunctioning and can have an impact in cancer development. Our study aims to characterize global differences between transcriptional regulatory programs of normal and tumor cells of the colon. METHODS: Affymetrix Human Genome U219 expression arrays were used to assess gene expression in 100 samples of colon tumor and their paired adjacent normal mucosa. Transcriptional networks were reconstructed using ARACNe algorithm using 1,000 bootstrap replicates consolidated into a consensus network. Networks were compared regarding topology parameters and identified well-connected clusters. Functional enrichment was performed with SIGORA method. ENCODE ChIP-Seq data curated in the hmChIP database was used for in silico validation of the most prominent transcription factors. RESULTS: The normal network contained 1,177 transcription factors, 5,466 target genes and 61,226 transcriptional interactions. A large loss of transcriptional interactions in the tumor network was observed (11,585; 81% reduction), which also contained fewer transcription factors (621; 47% reduction) and target genes (2,190; 60% reduction) than the normal network. Gene silencing was not a main determinant of this loss of regulatory activity, since the average gene expression was essentially conserved. Also, 91 transcription factors increased their connectivity in the tumor network. These genes revealed a tumor-specific emergent transcriptional regulatory program with significant functional enrichment related to colorectal cancer pathway. In addition, the analysis of clusters again identified subnetworks in the tumors enriched for cancer related pathways (immune response, Wnt signaling, DNA replication, cell adherence, apoptosis, DNA repair, among others). Also multiple metabolism pathways show differential clustering between the tumor and normal network. CONCLUSIONS: These findings will allow a better understanding of the transcriptional regulatory programs altered in colon cancer and could be an invaluable methodology to identify potential hubs with a relevant role in the field of cancer diagnosis, prognosis and therapy.

Dataset Information

Shifts in isoform usage underlie transcriptional differences in regulatory T cells in type 1 diabetes.

Publications

Shifts in isoform usage underlie transcriptional differences in regulatory T cells in type 1 diabetes.

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