Analysis of ChIP-seq Data in R/Bioconductor

Human T-bet governs the generation of a distinct subset of CD11chighCD21low B cells

High-level expression of the transcription factor T-bet characterizes a phenotypically distinct murine B cell population known as "age-associated B cells" (ABCs). T-bet-deficient mice have reduced ABCs and impaired humoral immunity. We describe a patient with inherited T-bet deficiency and largely normal humoral immunity including intact somatic hypermutation, affinity maturation and memory B cell formation in vivo, and B cell differentiation into Ig-producing plasmablasts in vitro. Nevertheless, the patient exhibited skewed class switching to IgG1, IgG4, and IgE, along with reduced IgG2, both in vivo and in vitro. Moreover, T-bet was required for the in vivo and in vitro development of a distinct subset of human B cells characterized by reduced expression of CD21 and the concomitantly high expression of CD19, CD20, CD11c, FCRL5, and T-bet, a phenotype that shares many features with murine ABCs. Mechanistically, human T-bet governed CD21^loCD11c^hi B cell differentiation by controlling the chromatin accessibility of lineage-defining genes in these cells: FAS, IL21R, SEC61B, DUSP4, DAPP1, SOX5, CD79B, and CXCR4. Thus, human T-bet is largely redundant for long-lived protective humoral immunity but is essential for the development of a distinct subset of human CD11c^hiCD21^lo B cells.

High Th2 cytokine levels and upper airway inflammation in human inherited T-bet deficiency

We have described a child suffering from Mendelian susceptibility to mycobacterial disease (MSMD) due to autosomal recessive, complete T-bet deficiency, which impairs IFN-γ production by innate and innate-like adaptive, but not mycobacterial-reactive purely adaptive, lymphocytes. Here, we explore the persistent upper airway inflammation (UAI) and blood eosinophilia of this patient. Unlike wild-type (WT) T-bet, the mutant form of T-bet from this patient did not inhibit the production of Th2 cytokines, including IL-4, IL-5, IL-9, and IL-13, when overexpressed in T helper 2 (Th2) cells. Moreover, Herpesvirus saimiri-immortalized T cells from the patient produced abnormally large amounts of Th2 cytokines, and the patient had markedly high plasma IL-5 and IL-13 concentrations. Finally, the patient's CD4+ αβ T cells produced most of the Th2 cytokines in response to chronic stimulation, regardless of their antigen specificities, a phenotype reversed by the expression of WT T-bet. T-bet deficiency thus underlies the excessive production of Th2 cytokines, particularly IL-5 and IL-13, by CD4+ αβ T cells, causing blood eosinophilia and UAI. The MSMD of this patient results from defective IFN-γ production by innate and innate-like adaptive lymphocytes, whereas the UAI and eosinophilia result from excessive Th2 cytokine production by adaptive CD4+ αβ T lymphocytes.

Global Analyses to Identify Direct Transcriptional Targets of p53

The transcription factor p53 controls a gene expression program with pleiotropic effects on cell biology including cell cycle arrest and apoptosis. Identifying direct p53 target genes within this network and determining how they influence cell fate decisions downstream of p53 activation is a prerequisite for designing therapeutic approaches that target p53 to effectively kill cancer cells. Here we describe a comprehensive multi-omics approach for identifying genes that are direct transcriptional targets of p53. We provide detailed procedures for measuring global RNA polymerase activity, defining p53 binding sites across the genome, and quantifying changes in steady-state mRNA in response to p53 activation.

Multi-omics analysis reveals contextual tumor suppressive and oncogenic gene modules within the acute hypoxic response

Cellular adaptation to hypoxia is a hallmark of cancer, but the relative contribution of hypoxia-inducible factors (HIFs) versus other oxygen sensors to tumorigenesis is unclear. We employ a multi-omics pipeline including measurements of nascent RNA to characterize transcriptional changes upon acute hypoxia. We identify an immediate early transcriptional response that is strongly dependent on HIF1A and the kinase activity of its cofactor CDK8, includes indirect repression of MYC targets, and is highly conserved across cancer types. HIF1A drives this acute response via conserved high-occupancy enhancers. Genetic screen data indicates that, in normoxia, HIF1A displays strong cell-autonomous tumor suppressive effects through a gene module mediating mTOR inhibition. Conversely, in advanced malignancies, expression of a module of HIF1A targets involved in collagen remodeling is associated with poor prognosis across diverse cancer types. In this work, we provide a valuable resource for investigating context-dependent roles of HIF1A and its targets in cancer biology.

The response to hypoxia can significantly impact oncogenic processes. Here, the authors define the early transcriptional response to acute hypoxia and identify HIF1A target genes as part of this acute response, providing a resource for investigating context-dependent roles of HIF1A in the biology of cancer.

Organotypic Models in Drug Development "Tumor Models and Cancer Systems Biology for the Investigation of Anticancer Drugs and Resistance Development"

The landscape of cancer treatment has improved over the past decades, aiming to reduce systemic toxicity and enhance compatibility with the quality of life of the patient. However, at the therapeutic level, metastatic cancer remains hugely challenging, based on the almost inevitable emergence of therapy resistance. A small subpopulation of cells able to survive drug treatment termed the minimal residual disease may either harbor resistance-associated mutations or be phenotypically resistant, allowing them to regrow and become the dominant population in the therapy-resistant tumor. Characterization of the profile of minimal residual disease represents the key to the identification of resistance drivers that underpin cancer evolution. Therapeutic regimens must, therefore, be dynamic and tailored to take into account the emergence of resistance as tumors evolve within a complex microenvironment in vivo. This requires the adoption of new technologies based on the culture of cancer cells in ways that more accurately reflect the intratumor microenvironment, and their analysis using omics and system-based technologies to enable a new era in the diagnostics, classification, and treatment of many cancer types by applying the concept "from the cell plate to the patient." In this chapter, we will present and discuss 3D model building and use, and provide comprehensive information on new genomic techniques that are increasing our understanding of drug action and the emergence of resistance.

The R package Rsubread is easier, faster, cheaper and better for alignment and quantification of RNA sequencing reads

We present Rsubread, a Bioconductor software package that provides high-performance alignment and read counting functions for RNA-seq reads. Rsubread is based on the successful Subread suite with the added ease-of-use of the R programming environment, creating a matrix of read counts directly as an R object ready for downstream analysis. It integrates read mapping and quantification in a single package and has no software dependencies other than R itself. We demonstrate Rsubread’s ability to detect exon–exon junctions de novo and to quantify expression at the level of either genes, exons or exon junctions. The resulting read counts can be input directly into a wide range of downstream statistical analyses using other Bioconductor packages. Using SEQC data and simulations, we compare Rsubread to TopHat2, STAR and HTSeq as well as to counting functions in the Bioconductor infrastructure packages. We consider the performance of these tools on the combined quantification task starting from raw sequence reads through to summary counts, and in particular evaluate the performance of different combinations of alignment and counting algorithms. We show that Rsubread is faster and uses less memory than competitor tools and produces read count summaries that more accurately correlate with true values.