Feedforward regulation of Myc coordinates lineage-specific with housekeeping gene expression during B cell progenitor cell differentiation

EBF1, PAX5, and MYC: regulation on B cell development and association with hematologic neoplasms

During lymphocyte development, a diverse repertoire of lymphocyte antigen receptors is produced to battle against pathogens, which is the basis of adaptive immunity. The diversity of the lymphocyte antigen receptors arises primarily from recombination-activated gene (RAG) protein-mediated V(D)J rearrangement in early lymphocytes. Furthermore, transcription factors (TFs), such as early B cell factor 1 (EBF1), paired box gene 5 (PAX5), and proto-oncogene myelocytomatosis oncogene (MYC), play critical roles in regulating recombination and maintaining normal B cell development. Therefore, the aberrant expression of these TFs may lead to hematologic neoplasms.

A FOXO1-dependent transcription network is a targetable vulnerability of mantle cell lymphomas

Targeting lineage-defined transcriptional dependencies has emerged as an effective therapeutic strategy in cancer treatment. Through screening for molecular vulnerabilities of mantle cell lymphoma (MCL), we identified a set of transcription factors (TFs) including FOXO1, EBF1, PAX5, and IRF4 that are essential for MCL propagation. Integrated chromatin immunoprecipitation and sequencing (ChIP-Seq) with transcriptional network reconstruction analysis revealed FOXO1 as a master regulator that acts upstream in the regulatory TF hierarchy. FOXO1 is both necessary and sufficient to drive MCL lineage commitment through supporting the lineage-specific transcription programs. We further show that FOXO1, but not its close paralog FOXO3, can reprogram myeloid leukemia cells and induce B-lineage gene expression. Finally, we demonstrate that cpd10, a small molecule identified from an enriched FOXO1 inhibitor library, induces a robust cytotoxic response in MCL cells in vitro and suppresses MCL progression in vivo. Our findings establish FOXO1 inhibition as a therapeutic strategy targeting lineage-driven transcriptional addiction in MCL.

Quality-controlled R-loop meta-analysis reveals the characteristics of R-loop consensus regions

R-loops are three-stranded nucleic acid structures formed from the hybridization of RNA and DNA. While the pathological consequences of R-loops have been well-studied to date, the locations, classes, and dynamics of physiological R-loops remain poorly understood. R-loop mapping studies provide insight into R-loop dynamics, but their findings are challenging to generalize. This is due to the narrow biological scope of individual studies, the limitations of each mapping modality, and, in some cases, poor data quality. In this study, we reprocessed 810 R-loop mapping datasets from a wide array of biological conditions and mapping modalities. From this data resource, we developed an accurate R-loop data quality control method, and we reveal the extent of poor-quality data within previously published studies. We then identified a set of high-confidence R-loop mapping samples and used them to define consensus R-loop sites called 'R-loop regions' (RL regions). In the process, we identified a stark divergence between RL regions detected by S9.6 and dRNH-based mapping methods, particularly with respect to R-loop size, location, and colocalization with RNA binding factors. Taken together, this work provides a much-needed method to assess R-loop data quality and offers novel context regarding the differences between dRNH- and S9.6-based R-loop mapping approaches.

PaintOmics 4: new tools for the integrative analysis of multi-omics datasets supported by multiple pathway databases

PaintOmics is a web server for the integrative analysis and visualisation of multi-omics datasets using biological pathway maps. PaintOmics 4 has several notable updates that improve and extend analyses. Three pathway databases are now supported: KEGG, Reactome and MapMan, providing more comprehensive pathway knowledge for animals and plants. New metabolite analysis methods fill gaps in traditional pathway-based enrichment methods. The metabolite hub analysis selects compounds with a high number of significant genes in their neighbouring network, suggesting regulation by gene expression changes. The metabolite class activity analysis tests the hypothesis that a metabolic class has a higher-than-expected proportion of significant elements, indicating that these compounds are regulated in the experiment. Finally, PaintOmics 4 includes a regulatory omics module to analyse the contribution of trans-regulatory layers (microRNA and transcription factors, RNA-binding proteins) to regulate pathways. We show the performance of PaintOmics 4 on both mouse and plant data to highlight how these new analysis features provide novel insights into regulatory biology. PaintOmics 4 is available at https://paintomics.org/.

EBF1 and Pax5 safeguard leukemic transformation by limiting IL-7 signaling, Myc expression, and folate metabolism

In this study, Ramamoorthy et al. investigate EBF1 and PAX5 combined haploinsufficiency in the development of a B-ALL phenotype in mice. Using transcriptional and metabolomic profiling, the authors report that EBF1 and Pax5 may safeguard early stage B cells from transformation to B-ALL by limiting IL-7 signaling, folate metabolism, and Myc expression.

EBF1 and PAX5 mutations are associated with the development of B progenitor acute lymphoblastic leukemia (B-ALL) in humans. To understand the molecular networks driving leukemia in the Ebf1^+/−Pax5^+/− (dHet) mouse model for B-ALL, we interrogated the transcriptional profiles and chromatin status of leukemic cells, preleukemic dHet pro-B, and wild-type pro-B cells with the corresponding EBF1 and Pax5 cistromes. In dHet B-ALL cells, many EBF1 and Pax5 target genes encoding pre-BCR signaling components and transcription factors were down-regulated, whereas Myc and genes downstream from IL-7 signaling or associated with the folate pathway were up-regulated. We show that blockade of IL-7 signaling in vivo and methotrexate treatment of leukemic cells in vitro attenuate the expansion of leukemic cells. Single-cell RNA-sequencing revealed heterogeneity of leukemic cells and identified a subset of wild-type pro-B cells with reduced Ebf1 and enhanced Myc expression that show hallmarks of dHet B-ALL cells. Thus, EBF1 and Pax5 may safeguard early stage B cells from transformation to B-ALL by limiting IL-7 signaling, folate metabolism and Myc expression.

STATegra, a comprehensive multi-omics dataset of B-cell differentiation in mouse

Multi-omics approaches use a diversity of high-throughput technologies to profile the different molecular layers of living cells. Ideally, the integration of this information should result in comprehensive systems models of cellular physiology and regulation. However, most multi-omics projects still include a limited number of molecular assays and there have been very few multi-omic studies that evaluate dynamic processes such as cellular growth, development and adaptation. Hence, we lack formal analysis methods and comprehensive multi-omics datasets that can be leveraged to develop true multi-layered models for dynamic cellular systems. Here we present the STATegra multi-omics dataset that combines measurements from up to 10 different omics technologies applied to the same biological system, namely the well-studied mouse pre-B-cell differentiation. STATegra includes high-throughput measurements of chromatin structure, gene expression, proteomics and metabolomics, and it is complemented with single-cell data. To our knowledge, the STATegra collection is the most diverse multi-omics dataset describing a dynamic biological system.