Multi-modular structure of the gene regulatory network for specification and commitment of murine T cells

Abstract

T cells develop from multipotent progenitors by a gradual process dependent on intrathymic Notch signaling and coupled with extensive proliferation. The stages leading them to T-cell lineage commitment are well characterized by single-cell and bulk RNA analyses of sorted populations and by direct measurements of precursor-product relationships. This process depends not only on Notch signaling but also on multiple transcription factors, some associated with stemness and multipotency, some with alternative lineages, and others associated with T-cell fate. These factors interact in opposing or semi-independent T cell gene regulatory network (GRN) subcircuits that are increasingly well defined. A newly comprehensive picture of this network has emerged. Importantly, because key factors in the GRN can bind to markedly different genomic sites at one stage than they do at other stages, the genes they significantly regulate are also stage-specific. Global transcriptome analyses of perturbations have revealed an underlying modular structure to the T-cell commitment GRN, separating decisions to lose “stem-ness” from decisions to block alternative fates. Finally, the updated network sheds light on the intimate relationship between the T-cell program, which depends on the thymus, and the innate lymphoid cell (ILC) program, which does not.

SciGeneX: Enhancing transcriptional analysis through gene module detection in single-cell and spatial transcriptomics data

“…Among them, module M11 is characterized by the presence of key factors associated with very early T-cell development, including the pivotal transcription factor NOTCH1 and its target HES1 as well as the transcription factor RUNX2 [36]. Module M03 is associated to the double-positive (DP) stage with prominent markers such as CD8A, CD8B, CD4, CD52, CCR9, and the transcription factors LEF1, TCF7, TCF12, SATB1, in addition to the VDJ recombination actors RAG1 and RAG2 [37]. Module M06, in turn, contains more mature T-cell markers, including CD5, CD6, CCR7, CD28, accompanied by interferon-inducible genes such as IFI44L, IFITM1, IFITM2, HLA-A, HLA-B, HLA-C, HLA-F, and IRF7.…”

“…Module M03 is associated to the double-positive (DP) stage with prominent markers such as CD8A, CD8B, CD4, CD52, CCR9, and the transcription factors LEF1, TCF7, TCF12, SATB1, in addition to the VDJ recombination actors RAG1 and RAG2 [37]. Module M06, in turn, contains more mature T-cell markers, including CD5, CD6, CCR7, CD28, accompanied by interferoninducible genes such as IFI44L, IFITM1, IFITM2, HLA-A, HLA-B, HLA-C, HLA-F, and IRF7.…”

Identification of Cellular Interactions in the Tumor Immune Microenvironment Underlying CD8 T Cell Exhaustion

“…Several of these are known to be responsible for maintaining the stem-like state of the progenitor exhausted CD8 T cells. LYL1 is responsible for stem / progenitor state and self-renewal in thymocytes and T cells [31, 32, 33]. BCL11A slows differentiation of T cells to maintain self-renewal [34].…”

Decoding mutational hotspots in human disease through the gene modules governing thymic regulatory T cells

“…Modelling of Gene Regulatory Networks via bulk or single-cell ATAC is usually based on a few TF, selected by the top frequency of consensus motifs in regions of open chromatin, enrichment at promoters, or expression level of respective TF (Chopp et al 2020; DiSpirito et al 2018; Miraldi et al 2019; Bravo González-Blas et al 2020; Shin and Rothenberg 2023). Our novel approach, based on differential TF occupancy in the chromatin landscape of tTregs and Tconvs, provides a computational tool to infer the GRM governing human regulatory T cells with meaningful biology significance.…”

“…It is assumed that TF occupancy/binding is a measure of TF activity and differences in TF binding at the same TFBS can be informative on the activity of the same TF in different lineages (Little et al 2021). This quantification, however, is so far surprisingly absent in published regulatory models for gene expression during thymocyte development (Shin and Rothenberg 2023).…”