Global dynamics of stage-specific transcription factor binding during thymocyte development

Transcriptional network dynamics in early T cell development

The rate at which cells enter the T cell pathway depends not only on the immigration of hematopoietic precursors into the strong Notch signaling environment of the thymus but also on the kinetics with which each individual precursor cell reaches T-lineage commitment once it arrives. Notch triggers a complex, multistep gene regulatory network in the cells in which the steps are stereotyped but the transition speeds between steps are variable. Progenitor-associated transcription factors delay T-lineage differentiation even while Notch-induced transcription factors within the same cells push differentiation forward. Progress depends on regulator cross-repression, on breaching chromatin barriers, and on shifting, competitive collaborations between stage-specific and stably expressed transcription factors, as reviewed here.

RORγt up-regulates RAG gene expression in DP thymocytes to expand the Tcra repertoire

Recombination activating gene (RAG) expression increases as thymocytes transition from the CD4-CD8- double-negative (DN) to the CD4+CD8+ double-positive (DP) stage, but the physiological importance and mechanism of transcriptional up-regulation are unknown. Here, we show that a DP-specific component of the recombination activating genes antisilencer (DPASE) provokes elevated RAG expression in DP thymocytes. Mouse DP thymocytes lacking the DPASE display RAG expression equivalent to that in DN thymocytes, but this supports only a partial Tcra repertoire due to inefficient secondary Vα-Jα rearrangement. These data indicate that RAG up-regulation is required for a replete Tcra repertoire and that RAG expression is fine-tuned during lymphocyte development to meet the requirements of distinct antigen receptor loci. We further show that transcription factor RORγt directs RAG up-regulation in DP thymocytes by binding to the DPASE and that RORγt influences the Tcra repertoire by binding to the Tcra enhancer. These data, together with prior work showing RORγt to control Tcra rearrangement by regulating DP thymocyte proliferation and survival, reveal RORγt to orchestrate multiple pathways that support formation of the Tcra repertoire.

PTCL, NOS: An update on classification, risk-stratification, and treatment

The peripheral T-cell lymphomas (PTCL) are relatively rare, heterogeneous, and therapeutically challenging. While significant therapeutic gains and improved understanding of disease pathogenesis have been realized for selected PTCL subtypes, the most common PTCL in North America remains "not otherwise specified (NOS)" and is an unmet need. However, improved understanding of the genetic landscape and ontogeny for the PTCL subtypes currently classified as PTCL, NOS have been realized, and have significant therapeutic implications, which will be reviewed here.

Shifting gears: Id3 enables recruitment of E proteins to new targets during T cell development and differentiation

Shifting levels of E proteins and Id factors are pivotal in T cell commitment and differentiation, both in the thymus and in the periphery. Id2 and Id3 are two different factors that prevent E proteins from binding to their target gene cis-regulatory sequences and inducing gene expression. Although they use the same mechanism to suppress E protein activity, Id2 and Id3 play very different roles in T cell development and CD4 T cell differentiation. Id2 imposes an irreversible choice in early T cell precursors between innate and adaptive lineages, which can be thought of as a railway switch that directs T cells down one path or another. By contrast, Id3 acts in a transient fashion downstream of extracellular signals such as T cell receptor (TCR) signaling. TCR-dependent Id3 upregulation results in the dislodging of E proteins from their target sites while chromatin remodeling occurs. After the cessation of Id3 expression, E proteins can reassemble in the context of a new genomic landscape and molecular context that allows induction of different E protein target genes. To describe this mode of action, we have developed the “Clutch” model of differentiation. In this model, Id3 upregulation in response to TCR signaling acts as a clutch that stops E protein activity (“clutch in”) long enough to allow shifting of the genomic landscape into a different “gear”, resulting in accessibility to different E protein target genes once Id3 decreases (“clutch out”) and E proteins can form new complexes on the DNA. While TCR signal strength and cytokine signaling play a role in both peripheral and thymic lineage decisions, the remodeling of chromatin and E protein target genes appears to be more heavily influenced by the cytokine milieu in the periphery, whereas the outcome of Id3 activity during T cell development in the thymus appears to depend more on the TCR signal strength. Thus, while the Clutch model applies to both CD4 T cell differentiation and T cell developmental transitions within the thymus, changes in chromatin accessibility are modulated by biased inputs in these different environments. New emerging technologies should enable a better understanding of the molecular events that happen during these transitions, and how they fit into the gene regulatory networks that drive T cell development and differentiation.

A comparative investigation on H3K27ac enhancer activities in the brain and liver tissues between wild boars and domesticated pigs

Dramatic phenotypic differences between domestic pigs and wild boars (Sus scrofa) provide opportunities to investigate molecular mechanisms underlying the formation of complex traits, including morphology, physiology and behaviour. Most studies comparing domestic pigs and wild boars have focused on variations in DNA sequences and mRNA expression, but not on epigenetic changes. Here, we present a genome-wide comparative study on H3K27ac enhancer activities and the corresponding mRNA profiling in the brain and liver tissues of adult Bama Xiang pigs (BMXs) and Chinese wild boars (CWBs). We identified a total of 1,29,487 potential regulatory elements, among which 11,241 H3K27ac peaks showed differential activity between CWBs and BMXs in at least one tissue. These peaks were overrepresented by binding motifs of FOXA1, JunB, ATF3 and BATF, and overlapped with differentially expressed genes that are involved in female mating behaviour, response to growth factors and hormones, and lipid metabolism. We also identified 4118 nonredundant super-enhancers from ChIP-Seq data on H3K27ac. Notably, we identified differentially active peaks located close to or within candidate genes, including TBX19, MSTN, AHR and P2RY1, which were identified in DNA sequence-based population differentiation studies. This study generates a valuable dataset on H3K27ac profiles of the brain and liver from domestic pigs and wild boars, which helps gain insights into the changes in enhancer activities from wild boars to domestic pigs.

Transcriptional Regulation of Early T-Lymphocyte Development in Thymus

T-lymphocytes play crucial roles for maintaining immune homeostasis by fighting against various pathogenic microorganisms and establishing self-antigen tolerance. They will go through several stages and checkpoints in the thymus from progenitors to mature T cells, from CD4^-CD8^- double negative (DN) cells to CD4⁺CD8⁺ double positive (DP) cells, finally become CD4⁺ or CD8⁺ single positive (SP) cells. The mature SP cells then emigrate out of the thymus and further differentiate into distinct subsets under different environment signals to perform specific functions. Each step is regulated by various transcriptional regulators downstream of T cell receptors (TCRs) that have been extensively studied both in vivo and vitro via multiple mouse models and advanced techniques, such as single cell RNA sequencing (scRNA-seq) and Chromatin Immunoprecipitation sequencing (ChIP-seq). This review will summarize the transcriptional regulators participating in the early stage of T cell development reported in the past decade, trying to figure out cascade networks in each process and provide possible research directions in the future.

A Gata3 enhancer necessary for ILC2 development and function

The type 2 helper effector program is driven by the master transcription factor GATA3 and can be expressed by subsets of both innate lymphoid cells (ILCs) and adaptive CD4+ T helper (Th) cells. While ILC2s and Th2 cells acquire their type 2 differentiation program under very different contexts, the distinct regulatory mechanisms governing this common program are only partially understood. Here we show that the differentiation of ILC2s, and their concomitant high level of GATA3 expression, are controlled by a Gata3 enhancer, Gata3 +674/762, that plays only a minimal role in Th2 cell differentiation. Mice lacking this enhancer exhibited defects in several but not all type 2 inflammatory responses, depending on the respective degree of ILC2 and Th2 cell involvement. Our study provides molecular insights into the different gene regulatory pathways leading to the acquisition of the GATA3-driven type 2 helper effector program in innate and adaptive lymphocytes.

How transcription factors drive choice of the T cell fate

Recent evidence has elucidated how multipotent blood progenitors transform their identities in the thymus and undergo commitment to become T cells. Together with environmental signals, a core group of transcription factors have essential roles in this process by directly activating and repressing specific genes. Many of these transcription factors also function in later T cell development, but control different genes. Here, we review how these transcription factors work to change the activities of specific genomic loci during early intrathymic development to establish T cell lineage identity. We introduce the key regulators and highlight newly emergent insights into the rules that govern their actions. Whole-genome deep sequencing-based analysis has revealed unexpectedly rich relationships between inherited epigenetic states, transcription factor-DNA binding affinity thresholds and influences of given transcription factors on the activities of other factors in the same cells. Together, these mechanisms determine T cell identity and make the lineage choice irreversible.

The transcription factor BCL-6 controls early development of innate-like T cells

Innate T cells, including invariant natural killer T (iNKT) and mucosal-associated innate T (MAIT) cells, are a heterogeneous T lymphocyte population with effector properties pre-programmed during their thymic differentiation. How this program is initiated is currently unclear. Here, we show that the transcription factor BCL-6 was transiently expressed in iNKT cells upon exit from positive selection and was required for their proper development beyond stage 0. Notably, development of MAIT cells was also impaired in the absence of Bcl6. BCL-6–deficient iNKT cells had reduced expression of genes that were associated with the innate T cell lineage, including Zbtb16, which encodes PLZF, and PLZF-targeted genes. BCL-6 contributed to a chromatin accessibility landscape that was permissive for the expression of development-related genes and inhibitory for genes associated with naïve T cell programs. Our results revealed novel functions for BCL-6 and illuminated how this transcription factor controls early iNKT cell development.

ATAC-seq normalization method can significantly affect differential accessibility analysis and interpretation

BACKGROUND

Chromatin dysregulation is associated with developmental disorders and cancer. Numerous methods for measuring genome-wide chromatin accessibility have been developed in the genomic era to interrogate the function of chromatin regulators. A recent technique which has gained widespread use due to speed and low input requirements with native chromatin is the Assay for Transposase-Accessible Chromatin, or ATAC-seq. Biologists have since used this method to compare chromatin accessibility between two cellular conditions. However, approaches for calculating differential accessibility can yield conflicting results, and little emphasis is placed on choice of normalization method during differential ATAC-seq analysis, especially when global chromatin alterations might be expected.

RESULTS

Using an in vivo ATAC-seq data set generated in our recent report, we observed differences in chromatin accessibility patterns depending on the data normalization method used to calculate differential accessibility. This observation was further verified on published ATAC-seq data from yeast. We propose a generalized workflow for differential accessibility analysis using ATAC-seq data. We further show this workflow identifies sites of differential chromatin accessibility that correlate with gene expression and is sensitive to differential analysis using negative controls.

CONCLUSIONS

We argue that researchers should systematically compare multiple normalization methods before continuing with differential accessibility analysis. ATAC-seq users should be aware of the interpretations of potential bias within experimental data and the assumptions of the normalization method implemented.

Leveraging mouse chromatin data for heritability enrichment informs common disease architecture and reveals cortical layer contributions to schizophrenia

Genome-wide association studies have implicated thousands of noncoding variants across common human phenotypes. However, they cannot directly inform the cellular context in which disease-associated variants act. Here, we use open chromatin profiles from discrete mouse cell populations to address this challenge. We applied stratified linkage disequilibrium score regression and evaluated heritability enrichment in 64 genome-wide association studies, emphasizing schizophrenia. We provide evidence that mouse-derived human open chromatin profiles can serve as powerful proxies for difficult to obtain human cell populations, facilitating the illumination of common disease heritability enrichment across an array of human phenotypes. We demonstrate that signatures from discrete subpopulations of cortical excitatory and inhibitory neurons are significantly enriched for schizophrenia heritability with maximal enrichment in cortical layer V excitatory neurons. We also show that differences between schizophrenia and bipolar disorder are concentrated in excitatory neurons in cortical layers II-III, IV, and V, as well as the dentate gyrus. Finally, we leverage these data to fine-map variants in 177 schizophrenia loci nominating variants in 104/177. We integrate these data with transcription factor binding site, chromatin interaction, and validated enhancer data, placing variants in the cellular context where they may modulate risk.

From reads to insight: a hitchhiker's guide to ATAC-seq data analysis

Assay of Transposase Accessible Chromatin sequencing (ATAC-seq) is widely used in studying chromatin biology, but a comprehensive review of the analysis tools has not been completed yet. Here, we discuss the major steps in ATAC-seq data analysis, including pre-analysis (quality check and alignment), core analysis (peak calling), and advanced analysis (peak differential analysis and annotation, motif enrichment, footprinting, and nucleosome position analysis). We also review the reconstruction of transcriptional regulatory networks with multiomics data and highlight the current challenges of each step. Finally, we describe the potential of single-cell ATAC-seq and highlight the necessity of developing ATAC-seq specific analysis tools to obtain biologically meaningful insights.

Applications of ENCODE data to Systematic Analyses via Data Integration

Large-scale genomic data have been utilized to generate unprecedented biological findings and new hypotheses. To delineate functional elements in the human genome, the Encyclopedia of DNA Elements (ENCODE) project has generated an enormous amount of genomic data, yielding around 7,000 data profiles in different cell and tissue types. In this article, we reviewed the systematic analyses that have integrated ENCODE data with other data sources to reveal new biological insights, ranging from human genome annotation to the identification of new candidate drugs. These analyses demonstrate the critical impact of ENCODE data on basic biology and translational research.