MotivationTranscriptional regulation is performed by transcription factors (TF) binding to DNA in context-dependent regulatory regions and determines the activation or inhibition of gene expression. Current methods of transcriptional regulatory circuits inference, based on one or all of TF, regions and genes activity measurements require a large number of samples for ranking the candidate TF-gene regulation relations and rarely predict whether they are activations or inhibitions. We hypothesize that transcriptional regulatory circuits can be inferred from fewer samples by (1) fully integrating information on TF binding, gene expression and regulatory regions accessibility, (2) reducing data complexity and (3) using biology-based likelihood constraints to determine the global consistency between a candidate TF-gene relation and patterns of genes expressions and region activations, as well as qualify regulations as activations or inhibitions.ResultsWe introduce Regulus, a method which computes TF-gene relations from gene expressions, regulatory region activities and TF binding sites data, together with the genomic locations of all entities. After aggregating gene expressions and region activities into patterns, data are integrated into a RDF (Resource Description Framework) endpoint. A dedicated SPARQL (SPARQL Protocol and RDF Query Language) query retrieves all potential relations between expressed TF and genes involving active regulatory regions. These TF-region-gene relations are then filtered using biological likelihood constraints allowing to qualify them as activation or inhibition. Regulus provides signed relations consistent with public databases and, when applied to biological data, identifies both known and potential new regulators. Regulus is devoted to context-specific transcriptional circuits inference in human settings where samples are scarce and cell populations are closely related, using discretization into patterns and likelihood reasoning to decipher the most robust regulatory relations.

The differentiation of B cells into plasmablasts (PBs) and then plasma cells (PCs) is associated with extensive cell reprogramming and new cell functions. By using specific inhibition strategies (including a novel morpholino RNA antisense approach), we found that early, sustained upregulation of the proviral integrations of Moloney virus 2 (PIM2) kinase is a pivotal event during human B-cell in vitro differentiation and then continues in mature normal and malignant PCs in the bone marrow. In particular, PIM2 sustained the G1/S transition by acting on CDC25A and p27Kip1 and hindering caspase 3-driven apoptosis through BAD phosphorylation and cytoplasmic stabilization of p21Cip1. In PCs, interleukin-6 triggered PIM2 expression, resulting in antiapoptotic effects on which malignant PCs were particularly dependent. In multiple myeloma, pan-PIM and myeloid cell leukemia-1 (MCL1) inhibitors displayed synergistic activity. Our results highlight a cell-autonomous function that links kinase activity to the newly acquired secretion ability of the PBs and the adaptability observed in both normal and malignant PCs. These findings should finally prompt the reconsideration of PIM2 as a therapeutic target in multiple myeloma.

Memory B cells (MBCs) can persist for a lifetime, but the mechanisms that allow their long-term survival remain poorly understood. Here, we isolated and analyzed human splenic smallpox/vaccinia protein B5-specific MBCs in individuals who were vaccinated more than 40 years ago. Only a handful of clones persisted over such an extended period, and they displayed limited intra-clonal diversity with signs of extensive affinity-based selection. These long-lived MBCs appeared enriched in a CD21hiCD20hi IgG+ splenic B cell subset displaying a marginal-zone-like NOTCH/MYC-driven signature, but they did not harbor a unique longevity-associated transcriptional or metabolic profile. Finally, the telomeres of B5-specific, long-lived MBCs were longer than those in patient-paired naive B cells in all the samples analyzed. Overall, these results imply that separate mechanisms such as early telomere elongation, affinity selection during the contraction phase, and access to a specific niche contribute to ensuring the functional longevity of MBCs.

Memory B cells can persist over a lifetime, but the mechanisms allowing their long-term survival remain poorly understood. We describe here the isolation and functional study of human splenic anti-Vaccinia memory B cells in individuals that were vaccinated more than forty years ago. Repertoire analysis demonstrated that a handful of clones with limited intra-clonal diversity and a narrow range of affinity persisted over such an extended period of time. These long-lived memory B cells appeared enriched in a CD21hiCD20hiIgG+ splenic B cell subset displaying a NOTCH/MYC-driven signature along with enhanced metabolic activity. Finally, analysis of their telomeres showed that they remain longer than in patient-paired naive B cells in all samples analyzed. Overall, these results imply that separate mechanisms such as affinity selection during the contraction phase, access to a specific niche and early telomere elongation are at play in order to ensure the functional longevity of memory B cells.Funding Information: This work was funded by the Fondation Princesse Grace, by a Mérieux grant and by ERC Advanced Grants (Memo-B and B-response). M.A.E was supported by a dotation from the Fondation EDF. MetaToul is part of the national infrastructure MetaboHUB-ANR- 11-INBS-0010 (The French National infrastructure for metabolomics and fluxomics). MetaToul is supported by grants from the Région Midi-Pyrénées, the European Regional Development Fund, the SICOVAL, the Infrastructures en Biologie Sante et Agronomie (IBiSa, France), the Centre National de la Recherche Scientifique (CNRS) and the Institut National de la Recherche Agronomique (INRA). P.R. is a scientist from Centre National de la Recherche Scientifique (CNRS).Conflict of Interests: M.M. received research funds from GSK, outside of the submitted work and personal fees from LFB and Amgen, outside of the submitted work. JC.W. received consulting fees from Institut Mérieux, outside of the submitted work.Ethical Approval: This study was conducted in compliance with the Declaration of Helsinki principles and was approved by the Agence de la Biomédecine and the Institutional Review Boards Comité de Protection des Personnes (CPP) Ile-de-France II. All parents from young children with sickle cell disease provided written informed consent before the collection of splenic samples.

B cell affinity maturation occurs in the germinal center (GC). Light-zone (LZ) GC B cells (B-GC-cells) interact with follicular dendritic cells (FDCs) and compete for the limited, sequential help from T follicular helper cells needed to escape from apoptosis and complete their differentiation. The highest-affinity LZ B-GC-cells enter the cell cycle and differentiate into PCs, following a dramatic epigenetic reorganization that induces transcriptome changes in general and the expression of the PRDM1 gene in particular. Human PC precursors are characterized by the loss of IL-4/STAT6 signaling and the absence of CD23 expression. Here, we studied the fate of human LZ B-GC-cells as a function of their CD23 expression. We first showed that CD23 expression was restricted to the GC LZ, where it was primarily expressed by FDCs; less than 10% of tonsil LZ B-GC-cells were positive. Sorted LZ B-GC-cells left in culture and stimulated upregulated CD23 expression but were unable to differentiate into PCs - in contrast to cells that did not upregulate CD23 expression. An in-depth analysis (including single-cell gene expression) showed that stimulated CD23-negative LZ B-GC-cells differentiated into plasmablasts and time course of gene expression changes delineates the transcriptional program that sustains PC differentiation. In particular, we identified a B cell proliferation signature supported by a transient MYC gene expression. Overall, the CD23 marker might be of value in answering questions about the differentiation of normal B-GC-cells and allowed us to propose an instructive LZ B-GC-cells maturation and fate model.

The terminal differentiation of B cells into antibody-secreting cells (ASCs) is a critical component of adaptive immune responses. However, it is a very sensitive process, and dysfunctions lead to a variety of lymphoproliferative neoplasias including germinal center-derived lymphomas. To better characterize the late genomic events that drive the ASC differentiation of human primary naive B cells, we used our in vitro differentiation system and a combination of RNA sequencing and Assay for Transposase-Accessible Chromatin with high-throughput sequencing (ATAC sequencing). We discovered 2 mechanisms that drive human terminal B-cell differentiation. First, after an initial response to interleukin-4 (IL-4), cells that were committed to an ASC fate downregulated the CD23 marker and IL-4 signaling, whereas cells that maintained IL-4 signaling did not differentiate. Second, human CD23(-) cells also increased IRF4 protein to levels required for ASC differentiation, but they did that independently of the ubiquitin-mediated degradation process previously described in mice. Finally, we showed that CD23(-) cells carried the imprint of their previous activated B-cell status, were precursors of plasmablasts, and had a phenotype similar to that of in vivo preplasmablasts. Altogether, our results provide an unprecedented genomic characterization of the fate decision between activated B cells and plasmablasts, which provides new insights into the pathological mechanisms that drive lymphoma biology.

The Regulatory Circuits project is among the most recent and the most complete attempts to identify cell-type specific regulatory networks in Human. It is one of the largest efforts of public genomics data integration, based on data from the major consortia FANTOM5, ENCODE and Roadmap Epigenomics. This project is a main provider of biological data, cited more than 224 times (Google Scholar) and its resulting networks were used in at least 42 other articles. For such a general resource, reproducibility of both the outputs (regulation networks) and methods (data integration pipeline) is a major issue, since biological data are updated regularly. In addition, users may want to introduce new data into the Regulatory Circuits framework to provide networks about previously uncharacterized cell types or to add information about specific regulators, which require to re-execute the whole pipeline on the new data. In this article, we analyze the various factors limiting reproducibility of the Regulatory Circuits data and methods. Starting from a factual description of our understanding of the methods used in Regulatory Circuits, our contribution is two-fold: we propose (1) a characterization of the different levels of reusability, reproducibility and conceptual issues in the original workflow and (2) a new implementation of the workflow ensuring its consistency with the published description and allowing for an easier reuse and reproduction of the published outputs. Both are applicable beyond the case of Regulatory Circuits.

MotivationTranscriptional regulation is performed by transcription factors (TF) binding to DNA in context-dependent regulatory regions and determines the activation or inhibition of gene expression. Current methods of transcriptional regulatory networks inference, based on one or all of TF, regions and genes activity measurements require a large number of samples for ranking the candidate TF-gene regulation relations and rarely predict whether they are activations or inhibitions. We hypothesize that transcriptional regulatory networks can be inferred from fewer samples by (1) fully integrating information on TF binding, gene expression and regulatory regions accessibility, (2) reducing data complexity and (3) using biology-based logical constraints to determine the global consistency of the candidate TF-gene relations and qualify them as activations or inhibitions.ResultsWe introduce Regulus, a method which computes TF-gene relations from gene expressions, regulatory region activities and TF binding sites data, together with the genomic locations of all entities. After aggregating gene expressions and region activities into patterns, data are integrated into a RDF endpoint. A dedicated SPARQL query retrieves all potential relations between expressed TF and genes involving active regulatory regions. These TF-region-gene relations are then filtered using a logical consistency check translated from biological knowledge, also allowing to qualify them as activation or inhibition. Regulus compares favorably to the closest network inference method, provides signed relations consistent with public databases and, when applied to biological data, identifies both known and potential new regulators. Altogether, Regulus is devoted to transcriptional network inference in settings where samples are scarce and cell populations are closely related. Regulus is available at https://gitlab.com/teamDyliss/regulus

Antibody therapy, where artificially-produced immunoglobulins (Ig) are used to treat pathological conditions such as auto-immune diseases and cancers, is a very innovative and competitive field. Although substantial efforts have been made in recent years to obtain specific and efficient antibodies, there is still room for improvement especially when considering a precise tissular targeting or increasing antigen affinity. A better understanding of the cellular and molecular steps of terminal B cell differentiation, in which an antigen-activated B cell becomes an antibody secreting cell, may improve antibody therapy. In this review, we use our recently published data about human B cell differentiation, to show that the mechanisms necessary to adapt a metamorphosing B cell to its new secretory function appear quite early in the differentiation process i.e., at the pre-plasmablast stage. After characterizing the molecular pathways appearing at this stage, we will focus on recent findings about two main processes involved in antibody production: unfolded protein response (UPR) and endoplasmic reticulum (ER) stress. We’ll show that many genes coding for factors involved in UPR and ER stress are induced at the pre-plasmablast stage, sustaining our hypothesis. Finally, we propose to use this recently acquired knowledge to improve productivity of industrialized therapeutic antibodies.

Transcriptional regulation -a major field of investigation in life science-is performed by binding of specialized proteins called transcription factors (TF) to DNA in specific, context-dependent regulatory regions, leading to either activation or inhibition of gene expression. Relations between TF, regions and genes can be described as regulatory networks, which are basically knowledge graphs containing the relationships between the different entities. Current methods of transcriptional regulatory networks inference rarely use information about TF binding or regulatory regions, often require a large number of samples and most of time do not indicate if the TF-gene relation is an activation or an inhibition. The resulting networks may then contain inconsistent relations and the methods are not applicable for common experimental or clinical settings, where the number of samples is limited. Therefore, based on our previous experience of formalizing the Regulatory Circuits data-sets with Semantic Web Technologies, we decided to create a new tool for transcriptional networks inference, that could solve these issues. Results: Our tool, Regulus, provides candidate signed TF-gene relations computed from gene expressions, regulatory region activities and TF binding sites data, together with the genomic location of all entities. After creating expressions and activities patterns, data are integrated into a RDF endpoint. A dedicated SPARQL query retrieves all potential TF-region relations for a given gene expression pattern. These ternary TF-region-gene pattern relations are then filtered and signed using a logical consistency check translated from biological knowledge. Regulus compares favorably to its closest network inference method, provides signs which are consistent with public databases and, when applied to real biological data, identifies both known and potential new regulators. We also provide several means to more stringently filter the output regulators. Altogether, we propose a new tool devoted to transcriptional network inference in settings where samples are scarce and cell populations may be closely related.The Regulus package is available at https://gitlab.com/gcollet/regulus

We report here that the pituitary hormone prolactin (PRL) has an important, conserved role in regulating adrenal gland function. The adrenal plays a pivotal role in endocrine homeostasis and stress response, which vary across lifespan and have different features in the two sexes.[1] Furthermore, most adrenal disorders have a higher prevalence in women.[2] To get deeper insight into the mechanisms of age- and sex-dependent adrenal function, we performed an integrative analysis of the mouse adrenal transcriptome by RNA-seq and active enhancer (as defined by H3K27ac ChIP-seq) usage at different ages (from E18.5 to P12 weeks) in both sexes. Multivariate analysis showed that age, but not sex, had a significant effect on adrenal global gene expression profiles (Figure and Supporting information S1; Tables S1, S2). Expression of genes related to lipid metabolism and immunity was progressively enriched with age (Figure 1C and Supporting information Table S3), with the proportion of macrophages increasing and neutrophils/mast cells decreasing at older ages (Figure 1D). The expression of different classes of secreted proteins, ion channels and enzymes showed a lower level of sex-dependent enrichment (Figure 1E and Supporting information Table S4). Age-and sex-dependent long non-coding RNA differentially expressed genes (DEG) followed the same pattern as coding DEG, being mostly specific for each age and sex (Supporting information Figure S2 and Table S5). Remarkably, P12 weeks adrenals of both sexes showed increased percentages of novel gene transcripts compared to previous ages (Supporting information Figure S2E). Sexually dimorphic expression pervades all cell populations of the mouse adrenal gland (Supporting information Figure S3 and Table S6). We identified a few thousand enhancers active in the adrenal gland at each temporal stage and in each sex (Supporting information Table S7). A subset among those belong to the super-enhancer class (SEC), genomic regions highly enriched in active chromatin, which regulate developmental and tissue-specific programs and often encompass disease-associated genomic loci.[3] At all ages and in both sexes, adrenal SEC have a much higher level of overlap than typical-enhancer class (TEC) elements (Figure 2A), while adrenal TEC are significantly more conserved than SEC (Figure 2B). Adrenal SEC-associated genes are enriched in genes involved in transcriptional regulation, cell-cell adhesion, protein phosphorylation, biological rhythms and steroid hormone receptor function at all ages and in both sexes (Figure 2C and Supporting information Table S8). Mouse adrenal SEC-associated genes are expressed at significantly higher levels in the adrenal gland (Supporting information Figure S4A) and include a higher percentage of tissue-specific genes (Supporting information Figure S4B) than TEC-associated genes. Human adrenal SEC are also preferentially associated to genes encoding proteins with adrenal-enriched expression than to genes with higher expression in other tissues (Supporting information Figure S4C) and SEC-associated genes are enriched with age-dependent DEG at most times and sex-dependent DEG at P12 weeks compared to TEC (Supporting information Figure S4D,E). Examples of SEC associated to genes important in adrenal physiology are shown in Supporting information Figure S5. Of note, some adrenal SEC-associated genes are expressed preferentially in the adrenal and are involved in blood pressure regulation (Supporting information Table S9). In particular, non-coding SNPs associated with blood pressure traits with very high significance are located inside a conserved SEC encompassing the KCNK3 gene (Supporting information Figure S6 and Table S10). By comparing our list of adrenal sexually dimorphic DEG with data in mouse[4, 5] and rat,[6] we could highlight a core conserved sexually dimorphic gene expression program (Figure 3A and Supporting information Table S11). We focused on the role of the PRL receptor (PRLR), because of its conserved sexually dimorphic expression in the human adrenal (Figure 3B) and the well-known role of PRL signalling in physiological adaptations and response to stress.[7] All Prlr isoforms were upregulated in the female adrenal compared to male at P12, but not P2 weeks of age (Figure 3C). Adrenal gland weight was significantly reduced in adult female Prlr -/- mice compared to WT (Figure 3D), while total body weight was normal in all Prlr -/- animals (Supporting information Figure S7). Signalling pathway impact analysis revealed that the JAK-STAT pathway is significantly activated in female adrenals compared to male at P12 weeks of age (Supporting information Figure S8). The mean area of adrenocortical cells in female Prlr -/- adrenals was significantly decreased (Figure 3E,F). This is consistent with significantly reduced circulating corticosterone levels and a trend toward an increased ACTH/corticosterone ratio in female Prlr -/- mice compared to WT (Figure 3G,H). These results show that PRL signalling through the PRLR has a crucial role in shaping the sexually dimorphic mouse adrenal phenotype. To assess the translational relevance of the mouse model results and to investigate the role of prolactin signalling in human physiopathology, we compared circulating adrenal steroid hormone levels in patients with PRL-secreting (prolactinoma; PRLA) and non-functioning pituitary adenomas (NFPA) (Supporting information Figure S9 and Table S12). Dehydroepiandrosterone sulphate (DHEAS) levels were significantly higher in patients with PRLA compared to NFPA (Figure 4A). In the PRLA group, men had higher circulating PRL levels than women (Figure 4B) and the PRL/DHEAS ratio was significantly more elevated in men than in women (Figure 4C). DHEAS levels were significantly reduced after therapy with dopamine agonists which inhibit PRL, but not ACTH, secretion (Figure 4D-F). Overall, these data suggest that the female adrenal may be more sensitive to PRL effects also in humans. This parallels what we have shown in mice in this study and points on the sexual dimorphic expression of PRLR in the human adrenal gland as a key component of this increased response.[1, 8] In humans, the effect of high PRL to preferentially increase DHEAS levels may be related to the enriched expression of PRLR in the adrenocortical zona reticularis.[9] Modulation of adrenal steroid secretion by PRL may, thus, contribute to the positive effects of physiological concentrations of this hormone on metabolic homeostasis in basal conditions and under stress, while its deregulation in hypo- and hyperprolactinemic states may play an important role in the clinical manifestations of PRL deficiency or excess, respectively. In conclusion, we have unveiled a crucial role for PRL signalling in the sexually dimorphic phenotype of the adult adrenal gland. Our results open new perspectives for the therapy of disorders characterized by adrenal hormones hypersecretion through the use of drugs modulating prolactin release. We thank Frédéric Brau for plugin development for image analysis, Marcin Rucinski for sharing rat adrenal gland microarray data, Xarubet Ruiz-Herrera for animal breeding and genotyping, Matthias Kroiss and Bonald Figueiredo for discussions and critical reading of the manuscript. Funding: This study was supported by the Fondation ARC Project PJA 20191209289 grant to C.R., grants from the Agence Nationale de la Recherche (ANR) ANR15-CE14-0017 (LOCALDO) and ANR20-CE14-0007 (Goldilocks), CNRS EXPOGEN-CANCER International Research Project, Fondation Jérôme Lejeune #1944 to E.L and by the Deutsche Forschungsgemeinschaft (DFG) within the CRC/Transregio (project number: 314061271). The Galaxy server that was used for data analysis is in part funded by Collaborative Research Centre 992 Medical Epigenetics (DFG grant SFB 992/1 2012) and German Federal Ministry of Education and Research [BMBF grants 031 A538A/A538C RBC, 031L0101B/031L0101C de.NBI-epi, 031L0106 de.STAIR (de.NBI)]. The authors declare that they have no conflict of interest. Conceptualization: E.L.; methodology: C.R, E.A., L. S.-M., M.D.-B., N.D., M.J., M.K.; data analysis: C.R., B.A., M.D., F.C., T.D, C.C, E.L.; supervision: T.D., C.C., E.L; writing-original draft: E.L; writing-review and editing: all authors. RNA-seq data: Gene Expression Omnibus GSE173691 (https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE173691). ChIP-seq data: Gene Expression Omnibus GSE173704 (https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE173704). Please note: The publisher is not responsible for the content or functionality of any supporting information supplied by the authors. Any queries (other than missing content) should be directed to the corresponding author for the article.

Follicular lymphoma (FL), the most frequent indolent non-Hodgkin’s B cell lymphoma, is considered as a prototypical centrocyte-derived lymphoma, dependent on a specific microenvironment mimicking the normal germinal center (GC). In agreement, several FL genetic alterations affect the crosstalk between malignant B cells and surrounding cells, including stromal cells and follicular helper T cells (Tfh). In our study, we sought to deconvolute this complex FL supportive synapse by comparing the transcriptomic profiles of GC B cells, Tfh, and stromal cells, isolated from normal versus FL tissues, in order to identify tumor-specific pathways. In particular, we highlighted a high expression of IL-6 and IL-7 in FL B cells that could favor the activation of FL Tfh overexpressing IFNG, able in turn to stimulate FL B cells without triggering MHC (major histocompatibility) class II expression. Moreover, the glycoprotein clusterin was found up-regulated in FL stromal cells and could promote FL B cell adhesion. Finally, besides its expression on Tfh, CD200 was found overexpressed on tumor B cells and could contribute to the induction of the immunosuppressive enzyme indoleamine-2,3 dioxygenase by CD200R-expressing dendritic cells. Altogether our findings led us to outline the contribution of major signals provided by the FL microenvironment and their interactions with malignant FL B cells.

Cell identity relies on the cross-talk between genetics and epigenetics and their impact on gene expression. Oxidation of 5-methylcytosine (5mC) into 5-hydroxymethylcytosine (5hmC) is the first step of an active DNA demethylation process occurring mainly at enhancers and gene bodies and, as such, participates in processes governing cell identity in normal and pathological conditions. Although genetic alterations are well documented in multiple myeloma (MM), epigenetic alterations associated with this disease have not yet been thoroughly analyzed. To gain insight into the biology of MM, genome-wide 5hmC profiles were obtained and showed that regions enriched in this modified base overlap with MM enhancers and super enhancers and are close to highly expressed genes. Through the definition of a MM-specific 5hmC signature, we identified FAM72D as a poor prognostic gene located on 1q21, a region amplified in high risk myeloma. We further uncovered that FAM72D functions as part of the FOXM1 transcription factor network controlling cell proliferation and survival and we evidenced an increased sensitivity of cells expressing high levels of FOXM1 and FAM72 to epigenetic drugs targeting histone deacetylases and DNA methyltransferases.

In life sciences, current standardization and integration efforts are directed towards reference data and knowledge bases. However, original studies results are generally provided in non standardized and specific formats. In addition, the only formalization of analysis pipelines is often limited to textual descriptions in the method sections. Both factors impair the results reproducibility, their maintenance and their reuse for advancing other studies. Semantic Web technologies have proven their efficiency for facilitating the integration and reuse of reference data and knowledge bases. We thus hypothesize that Semantic Web technologies also facilitate reproducibility and reuse of life sciences studies involving pipelines that compute associations between entities according to intermediary relations and dependencies. In order to assess this hypothesis, we considered a case-study in systems biology (http://regulatorycircuits.org), which provides tissue-specific regulatory interaction networks to elucidate perturbations across complex diseases. Our approach consisted in surveying the complete set of provided supplementary files to reveal the underlying structure between the biological entities described in the data. We relied on this structure and used Semantic Web technologies (i) to integrate the Regulatory Circuits data, and (ii) to formalize the analysis pipeline as SPARQL queries. Our result was a 335,429,988 triples dataset on which two SPARQL queries were sufficient to extract each single tissuespecific regulatory network.

B-cell activation yields abundant cell death in parallel to clonal amplification and remodeling of immunoglobulin (Ig) genes by activation-induced deaminase (AID). AID promotes affinity maturation of Ig variable regions and class switch recombination (CSR) in mature B lymphocytes. In the IgH locus, these processes are under control of the 3’ regulatory region (3’RR) super-enhancer, a region demonstrated in the mouse to be both transcribed and itself targeted by AID-mediated recombination. Alternatively to CSR, IgH deletions joining Sμ to “like-switch” DNA repeats that flank the 3’ super-enhancer can thus accomplish so-called “locus suicide recombination” (LSR) in mouse B-cells. Using an optimized LSR-seq high throughput method, we now show that AID-mediated LSR is evolutionarily conserved and also actively occurs in humans, providing an activation-induced cell death pathway in multiple conditions of B-cell activation. LSR either focuses on the functional IgH allele or is bi-allelic, and its signature is mainly detected when LSR is ongoing while it vanishes from fully differentiated plasma cells or from “resting” blood memory B-cells. Highly diversified breakpoints are distributed either within the upstream (3’RR1) or downstream (3’RR2) copies of the IgH 3’ super-enhancer and all conditions activating CSR in vitro also seem to trigger LSR although TLR ligation appeared the most efficient. Molecular analysis of breakpoints and junctions confirms that LSR is AID-dependent and reveals junctional sequences somehow similar to CSR junctions but with increased usage of microhomologies.

The developing and adult brain is a main target organ of thyroid hormones (including the prohormone thyroxine and its active derivative tri-iodo-thyronine or T3). Mouse genetics offers a number of promising possibilities to study their pleiotropic influence on the central nervous system, and to distinguish it from their peripheral function. In the following, we review recent advances brought by mouse genetics in our understanding of thyroid hormone signaling in the brain, both during development and in the adult. We particularly emphasize on the latest findings about thyroid hormone transporters and synthesis pathway which bring a new view on the regulation of thyroid hormone levels sensed by brain cells. Roles of the thyroid hormone receptors, which have been reviewed elsewhere are only briefly discussed.

Molecular mechanisms underlying terminal differentiation of B cells into plasma cells are major determinants of adaptive immunity but remain only partially understood. Here we present the transcriptional and epigenomic landscapes of cell subsets arising from activation of human naive B cells and differentiation into plasmablasts. Cell proliferation of activated B cells was linked to a slight decrease in DNA methylation levels, but followed by a committal step in which an S phase-synchronized differentiation switch was associated with an extensive DNA demethylation and local acquisition of 5-hydroxymethylcytosine at enhancers and genes related to plasma cell identity. Downregulation of both TGF-b1/SMAD3 signaling and p53 pathway supported this final step, allowing the emergence of a CD23-negative subpopulation in transition from B cells to plasma cells. Remarkably, hydroxymethylation of PRDM1, a gene essential for plasma cell fate, was coupled to progression in S phase, revealing an intricate connection among cell cycle, DNA (hydroxy) methylation, and cell fate determination.

•Thousands of thyroid hormone regulated genes have been reported in brain cells.•We present of a curated list of 734 genes reported more than once.•Comparison with other neural and non-neural systems identifies a shared subset.•Comparison with amphibians identifies few conserved regulations.

T3, the active form of thyroid hormone, binds nuclear receptors that regulate the transcription of a large number of genes in many cell types. Unraveling the direct and indirect effect of this hormonal stimulation, and establishing links between these molecular events and the developmental and physiological functions of the hormone, is a major challenge. New mouse genetics tools, notably those based on Cre/loxP technology, are suitable to perform a multiscale analysis of T3 signaling and achieve this task.

Brominated flame retardants are suspected to act as disruptors of thyroid hormone signaling. This raises the concern that they might affect children's cognitive functions by influencing thyroid hormone signaling in the developing brain. We present here an in vitro analysis of the ability of the most common compounds, tetrabromobisphenol A (TBBPA) and BDE-209, to alter thyroid hormone response based on a model neural cell line and genome-wide analysis of gene expression.