The transcriptomic landscape of Galectin-3-treated versus vehicle-treated Tregs
Data files
Nov 24, 2025 version files 35.44 MB
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counts_anno.CSV
17.32 MB
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FPKM_anno.CSV
18.12 MB
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README.md
1.75 KB
Abstract
Galectin-3, a β-galactoside-binding lectin, has been implicated in several inflammatory and autoimmune diseases. However, the significance of circulating Galectin-3 in type 1 diabetes (T1D) remains unclear. Pharmacological inhibition (TD139) as well as knockout of the Galectin-3 gene both attenuated Galectin-3-mediated suppression of regulatory T cells (Tregs) and protected from insulitis and diabetes onset in NOD mice. To further elucidate the downstream mechanisms, we performed RNA-seq analysis to profile the transcriptomic landscape of Galectin-3-treated versus vehicle-treated Tregs. Mechanistically, Galectin-3 binds to and activates lymphocyte activation gene-3 (LAG3), a receptor expressed on activated T cells, subsequently suppressing the MEK/ERK signaling pathway and thereby hindering Treg differentiation and function.
Dataset DOI: 10.5061/dryad.7pvmcvf67
Description of the data and file structure
In this study, transcriptomic analysis was performed using a reference-based approach on six samples. A total of 40.21 GB of clean sequencing data was obtained, with individual sample data volumes ranging from 5.87 to 7.04 GB. The Q30 score per base varied between 96.92% and 97.24%, with an average GC content of 49.35%. The reads were aligned to the reference genome, yielding mapping rates of 98.83% to 98.95% across all samples. Based on the alignment results, protein-coding gene expression levels were quantified. Differential expression analysis was conducted using one comparative group, identifying a total of 619 differentially expressed genes.
Files and variables
File: counts_anno.CSV
Description: counts_anno data of RNA-seq. The table contains Expression data (G3 and Treg samples); Gene identity & description; Gene type (protein-coding or non-coding); Pathway annotations (KEGG, WikiPathways, Reactome); GO functional annotations.
File: FPKM_anno.CSV
Description: FPKM_anno data of RNA-seq. The table contains Gene expression (log normalized) for G3 and Treg replicates; Gene identity + RIKEN clone name; Whether the gene is protein-coding or non-coding; KEGG / GO / Reactome / WikiPathways annotations; TF family classification
Code/software
The clean reads were mapped to the reference genome using HISAT22. FPKM3 of each gene was calculated, and the read counts of each gene were obtained by HTSeq-count4. PCA analysis was performed using R (v 3.2.0) to evaluate the biological duplication of samples.