The transcriptional network that controls growth arrest and differentiation in a human myeloid leukemia cell line

Nucleic acid therapeutics as differentiation agents for myeloid leukemias

Differentiation therapy has proven to be a success story for patients with acute promyelocytic leukemia. However, the remaining subtypes of acute myeloid leukemia (AML) are treated with cytotoxic chemotherapies that have limited efficacy and a high likelihood of resistance. As differentiation arrest is a hallmark of AML, there is increased interest in developing differentiation-inducing agents to enhance disease-free survival. Here, we provide a comprehensive review of current reports and future avenues of nucleic acid therapeutics for AML, focusing on the use of targeted nucleic acid drugs to promote differentiation. Specifically, we compare and discuss the precision of small interfering RNA, small activating RNA, antisense oligonucleotides, and aptamers to modulate gene expression patterns that drive leukemic cell differentiation. We delve into preclinical and clinical studies that demonstrate the efficacy of nucleic acid-based differentiation therapies to induce leukemic cell maturation and reduce disease burden. By directly influencing the expression of key genes involved in myeloid maturation, nucleic acid therapeutics hold the potential to induce the differentiation of leukemic cells towards a more mature and less aggressive phenotype. Furthermore, we discuss the most critical challenges associated with developing nucleic acid therapeutics for myeloid malignancies. By introducing the progress in the field and identifying future opportunities, we aim to highlight the power of nucleic acid therapeutics in reshaping the landscape of myeloid leukemia treatment.

OVCH1 Antisense RNA 1 is differentially expressed between non-frail and frail old adults

While some old adults stay healthy and non-frail up to late in life, others experience multimorbidity and frailty often accompanied by a pro-inflammatory state. The underlying molecular mechanisms for those differences are still obscure. Here, we used gene expression analysis to understand the molecular underpinning between non-frail and frail individuals in old age. Twenty-four adults (50% non-frail and 50% frail) from InCHIANTI study were included. Total RNA extracted from whole blood was analyzed by Cap Analysis of Gene Expression (CAGE). CAGE identified transcription start site (TSS) and active enhancer regions. We identified a set of differentially expressed (DE) TSS and enhancer between non-frail and frail and male and female participants. Several DE TSSs were annotated as lncRNA (XIST and TTTY14) and antisense RNAs (ZFX-AS1 and OVCH1 Antisense RNA 1). The promoter region chr6:366,786,54-366,787,97;+ was DE and overlapping the longevity CDKN1A gene. GWAS-LD enrichment analysis identifies overlapping LD-blocks with the DE regions with reported traits in GWAS catalog (isovolumetric relaxation time and urinary tract infection frequency). Furthermore, we used weighted gene co-expression network analysis (WGCNA) to identify changes of gene expression associated with clinical traits and identify key gene modules. We performed functional enrichment analysis of the gene modules with significant trait/module correlation. One gene module is showing a very distinct pattern in hub genes. Glycogen Phosphorylase L (PYGL) was the top ranked hub gene between non-frail and frail. We predicted transcription factor binding sites (TFBS) and motif activity. TF involved in age-related pathways (e.g., FOXO3 and MYC) shows different expression patterns between non-frail and frail participants. Expanding the study of OVCH1 Antisense RNA 1 and PYGL may help understand the mechanisms leading to loss of homeostasis that ultimately causes frailty.

Molecular profiling of high-level athlete skeletal muscle after acute endurance or resistance exercise - A systems biology approach

OBJECTIVE

Long-term high-level exercise training leads to improvements in physical performance and multi-tissue adaptation following changes in molecular pathways. While skeletal muscle baseline differences between exercise-trained and untrained individuals have been previously investigated, it remains unclear how training history influences human multi-omics responses to acute exercise.

METHODS

We recruited and extensively characterized 24 individuals categorized as endurance athletes with >15 years of training history, strength athletes or control subjects. Timeseries skeletal muscle biopsies were taken from M. vastus lateralis at three time-points after endurance or resistance exercise was performed and multi-omics molecular analysis performed.

RESULTS

Our analyses revealed distinct activation differences of molecular processes such as fatty- and amino acid metabolism and transcription factors such as HIF1A and the MYF-family. We show that endurance athletes have an increased abundance of carnitine-derivates while strength athletes increase specific phospholipid metabolites compared to control subjects. Additionally, for the first time, we show the metabolite sorbitol to be substantially increased with acute exercise. On transcriptional level, we show that acute resistance exercise stimulates more gene expression than acute endurance exercise. This follows a specific pattern, with endurance athletes uniquely down-regulating pathways related to mitochondria, translation and ribosomes. Finally, both forms of exercise training specialize in diverging transcriptional directions, differentiating themselves from the transcriptome of the untrained control group.

CONCLUSIONS

We identify a "transcriptional specialization effect" by transcriptional narrowing and intensification, and molecular specialization effects on metabolomic level Additionally, we performed multi-omics network and cluster analysis, providing a novel resource of skeletal muscle transcriptomic and metabolomic profiling in highly trained and untrained individuals.

Computational tools for inferring transcription factor activity

Transcription factors (TFs) are essential players in orchestrating the regulatory landscape in cells. Still, their exact modes of action and dependencies on other regulatory aspects remain elusive. Since TFs act cell type-specific and each TF has its own characteristics, untangling their regulatory interactions from an experimental point of view is laborious and convoluted. Thus, there is an ongoing development of computational tools that estimate transcription factor activity (TFA) from a variety of data modalities, either based on a mapping of TFs to their putative target genes or in a genome-wide, gene-unspecific fashion. These tools can help to gain insights into TF regulation and to prioritize candidates for experimental validation. We want to give an overview of available computational tools that estimate TFA, illustrate examples of their application, debate common result validation strategies, and discuss assumptions and concomitant limitations.

Statistical learning quantifies transposable element-mediated cis-regulation

BACKGROUND

Transposable elements (TEs) have colonized the genomes of most metazoans, and many TE-embedded sequences function as cis-regulatory elements (CREs) for genes involved in a wide range of biological processes from early embryogenesis to innate immune responses. Because of their repetitive nature, TEs have the potential to form CRE platforms enabling the coordinated and genome-wide regulation of protein-coding genes by only a handful of trans-acting transcription factors (TFs).

RESULTS

Here, we directly test this hypothesis through mathematical modeling and demonstrate that differences in expression at protein-coding genes alone are sufficient to estimate the magnitude and significance of TE-contributed cis-regulatory activities, even in contexts where TE-derived transcription fails to do so. We leverage hundreds of overexpression experiments and estimate that, overall, gene expression is influenced by TE-embedded CREs situated within approximately 500 kb of promoters. Focusing on the cis-regulatory potential of TEs within the gene regulatory network of human embryonic stem cells, we find that pluripotency-specific and evolutionarily young TE subfamilies can be reactivated by TFs involved in post-implantation embryogenesis. Finally, we show that TE subfamilies can be split into truly regulatorily active versus inactive fractions based on additional information such as matched epigenomic data, observing that TF binding may better predict TE cis-regulatory activity than differences in histone marks.

CONCLUSION

Our results suggest that TE-embedded CREs contribute to gene regulation during and beyond gastrulation. On a methodological level, we provide a statistical tool that infers TE-dependent cis-regulation from RNA-seq data alone, thus facilitating the study of TEs in the next-generation sequencing era.

Human microglia maturation is underpinned by specific gene regulatory networks

Microglia phenotypes are highly regulated by the brain environment, but the transcriptional networks that specify the maturation of human microglia are poorly understood. Here, we characterized stage-specific transcriptomes and epigenetic landscapes of fetal and postnatal human microglia and acquired corresponding data in induced pluripotent stem cell (iPSC)-derived microglia, in cerebral organoids, and following engraftment into humanized mice. Parallel development of computational approaches that considered transcription factor (TF) co-occurrence and enhancer activity allowed prediction of shared and state-specific gene regulatory networks associated with fetal and postnatal microglia. Additionally, many features of the human fetal-to-postnatal transition were recapitulated in a time-dependent manner following the engraftment of iPSC cells into humanized mice. These data and accompanying computational approaches will facilitate further efforts to elucidate mechanisms by which human microglia acquire stage- and disease-specific phenotypes.

USP14-mediated deubiquitination of SIRT1 in macrophage promotes fatty acid oxidation amplification and M2 phenotype polarization

There is a trend of increasing young cases with gastric cancer globally. Sensitive early diagnosis methods and new therapeutic approaches are still the focus of clinical diagnosis and therapy of gastric cancer. USP14 plays an extensive role in tumor malignancy and fat metabolism regulation. However, researchers still have gaps in their knowledge of its substrates, which makes it difficult for deubiquitinases to become clinical targets. TAMs were isolated from tumor or polarized from primary THP1 cells by tumors cell lines under the control of IU1 and FAO inhibitor therapy. Cytokines controlled macrophages were compared to evaluate the capability to induce USP14 expression. Fatty acid uptake assay and OCR measurement were used to analyze macrophage metabolism. USP14 is found the correlation with tumor poor prognosis and poor immunophenotype in gastric cancer patients and mouse tumor models. Activation of USP14 determines elevated protein stability of SIRT1 and is required for activation of macrophage fatty acid oxidation and immunosuppressive phenotype. Although overexpression of USP14 is not sufficient to polarize macrophages to the M2 phenotype, inhibition of USP14 by IU1 in tumor-bearing mice disrupts the suppressive activity of cancer-promoting macrophages and effectively reshapes immune microenvironment characteristics. Our study provides evidence that a novel therapeutic strategy that targets to lipid metabolism of macrophages in tumors could be a potential option for emerging treatments for gastric cancer.

Single-cell sortChIC identifies hierarchical chromatin dynamics during hematopoiesis

Post-translational histone modifications modulate chromatin activity to affect gene expression. How chromatin states underlie lineage choice in single cells is relatively unexplored. We develop sort-assisted single-cell chromatin immunocleavage (sortChIC) and map active (H3K4me1 and H3K4me3) and repressive (H3K27me3 and H3K9me3) histone modifications in the mouse bone marrow. During differentiation, hematopoietic stem and progenitor cells (HSPCs) acquire active chromatin states mediated by cell-type-specifying transcription factors, which are unique for each lineage. By contrast, most alterations in repressive marks during differentiation occur independent of the final cell type. Chromatin trajectory analysis shows that lineage choice at the chromatin level occurs at the progenitor stage. Joint profiling of H3K4me1 and H3K9me3 demonstrates that cell types within the myeloid lineage have distinct active chromatin but share similar myeloid-specific heterochromatin states. This implies a hierarchical regulation of chromatin during hematopoiesis: heterochromatin dynamics distinguish differentiation trajectories and lineages, while euchromatin dynamics reflect cell types within lineages.

Characterization of human induced pluripotent stems cells: Current approaches, challenges, and future solutions

Human induced pluripotent stem cells (iPSC) have demonstrated massive potentials for use in regenerative and personalized medicine due to their ability to expand in culture and differentiate into specialized cells with therapeutic benefits. However, in order to industrialize iPSC-derived therapies, it is necessary to address the existing challenges surrounding the analytics implemented in the manufacturing process to evaluate and monitor cell expansion, differentiation, and quality of the final products. Here, we review some of the key analytical methods used as part of identity, potency, or safety for in-process or final product release testing and highlighted the challenges and potential solutions for consideration in the Chemistry, Manufacturing and Controls (CMC) strategy for iPSC-based therapies. Some of the challenges associated with characterization and testing of iPSC-based products are related to the choice of analytical technology (to ensure fit-for-purpose), assay reliability and robustness. Automation of analytical methods may be required to reduce hands on time, and improve reliability of the methods through reducing assay variability. Indeed, we have shown that automation of analytical methods is feasible (evaluated using an ELISA based assay) and would result in more precise measurements (demonstrated by lower co-efficient of Variation and standard deviation), less hands-on time, and swift compared to a manually run assay. Therefore, in order to support commercialization of iPSC-based therapies we suggest a well-designed testing strategy to be established in the development phase while incorporating robust, reproducible, reliable, and potentially automated analytics in the manufacturing process.

xcore: an R package for inference of gene expression regulators

BACKGROUND

Elucidating the Transcription Factors (TFs) that drive the gene expression changes in a given experiment is a common question asked by researchers. The existing methods rely on the predicted Transcription Factor Binding Site (TFBS) to model the changes in the motif activity. Such methods only work for TFs that have a motif and assume the TF binding profile is the same in all cell types.

RESULTS

Given the wealth of the ChIP-seq data available for a wide range of the TFs in various cell types, we propose that gene expression modeling can be done using ChIP-seq "signatures" directly, effectively skipping the motif finding and TFBS prediction steps. We present xcore, an R package that allows TF activity modeling based on ChIP-seq signatures and the user's gene expression data. We also provide xcoredata a companion data package that provides a collection of preprocessed ChIP-seq signatures. We demonstrate that xcore leads to biologically relevant predictions using transforming growth factor beta induced epithelial-mesenchymal transition time-courses, rinderpest infection time-courses, and embryonic stem cells differentiated to cardiomyocytes time-course profiled with Cap Analysis Gene Expression.

CONCLUSIONS

xcore provides a simple analytical framework for gene expression modeling using linear models that can be easily incorporated into differential expression analysis pipelines. Taking advantage of public ChIP-seq databases, xcore can identify meaningful molecular signatures and relevant ChIP-seq experiments.

Antisense-oligonucleotide-mediated perturbation of long non-coding RNA reveals functional features in stem cells and across cell types

Within the scope of the FANTOM6 consortium, we perform a large-scale knockdown of 200 long non-coding RNAs (lncRNAs) in human induced pluripotent stem cells (iPSCs) and systematically characterize their roles in self-renewal and pluripotency. We find 36 lncRNAs (18%) exhibiting cell growth inhibition. From the knockdown of 123 lncRNAs with transcriptome profiling, 36 lncRNAs (29.3%) show molecular phenotypes. Integrating the molecular phenotypes with chromatin-interaction assays further reveals cis- and trans-interacting partners as potential primary targets. Additionally, cell-type enrichment analysis identifies lncRNAs associated with pluripotency, while the knockdown of LINC02595, CATG00000090305.1, and RP11-148B6.2 modulates colony formation of iPSCs. We compare our results with previously published fibroblasts phenotyping data and find that 2.9% of the lncRNAs exhibit a consistent cell growth phenotype, whereas we observe 58.3% agreement in molecular phenotypes. This highlights that molecular phenotyping is more comprehensive in revealing affected pathways.

Epigenetic Regulation of Profibrotic Macrophages in Systemic Sclerosis-Associated Interstitial Lung Disease

OBJECTIVE

Systemic sclerosis-associated interstitial lung disease (SSc-ILD) is the leading cause of death in patients with SSc with unclear pathogenesis and limited treatment options. Evidence strongly supports an important role for profibrotic secreted phosphoprotein 1 (SPP1)-expressing macrophages in SSc-ILD. This study was undertaken to define the transcriptome and chromatin structural changes of SPP1 SSc-ILD macrophages in order to better understand their role in promoting fibrosis and to identify transcription factors associated with open chromatin driving their altered phenotype.

METHODS

We performed single-cell RNA sequencing (scRNA-Seq) on 11 explanted SSc-ILD and healthy control lung samples, as well as single-cell assay for transposase-accessible chromatin sequencing on 5 lung samples to define altered chromatin accessibility of SPP1 macrophages. We predicted transcription factors regulating SPP1 macrophages using single-cell regulatory network inference and clustering (SCENIC) and determined transcription factor binding sites associated with global alterations in SPP1 chromatin accessibility using Signac/Seurat.

RESULTS

We identified distinct macrophage subpopulations using scRNA-Seq analysis in healthy and SSc-ILD lungs and assessed gene expression changes during the change of healthy control macrophages into SPP1 macrophages. Analysis of open chromatin validated SCENIC predictions, indicating that microphthalmia-associated transcription factor, transcription factor EB, activating transcription factor 6, sterol regulatory element binding transcription factor 1, basic helix-loop-helix family member E40, Kruppel-like factor 6, ETS variant transcription factor 5, and/or members of the activator protein 1 family of transcription factors regulate SPP1 macrophage differentiation.

CONCLUSION

Our findings shed light on the underlying changes in chromatin structure and transcription factor regulation of profibrotic SPP1 macrophages in SSc-ILD. Similar alterations in SPP1 macrophages may underpin fibrosis in other organs involved in SSc and point to novel targets for the treatment of SSc-ILD, specifically targeting profibrotic macrophages.

Alternative transcription start sites contribute to acute-stress-induced transcriptome response in human skeletal muscle

Background

More than half of human protein-coding genes have an alternative transcription start site (TSS). We aimed to investigate the contribution of alternative TSSs to the acute-stress-induced transcriptome response in human tissue (skeletal muscle) using the cap analysis of gene expression approach. TSSs were examined at baseline and during recovery after acute stress (a cycling exercise).

Results

We identified 44,680 CAGE TSS clusters (including 3764 first defined) belonging to 12,268 genes and annotated for the first time 290 TSSs belonging to 163 genes. The transcriptome dynamically changes during the first hours after acute stress; the change in the expression of 10% of genes was associated with the activation of alternative TSSs, indicating differential TSSs usage. The majority of the alternative TSSs do not increase proteome complexity suggesting that the function of thousands of alternative TSSs is associated with the fine regulation of mRNA isoform expression from a gene due to the transcription factor-specific activation of various alternative TSSs. We identified individual muscle promoter regions for each TSS using muscle open chromatin data (ATAC-seq and DNase-seq). Then, using the positional weight matrix approach we predicted time course activation of “classic” transcription factors involved in response of skeletal muscle to contractile activity, as well as diversity of less/un-investigated factors.

Conclusions

Transcriptome response induced by acute stress related to activation of the alternative TSSs indicates that differential TSSs usage is an essential mechanism of fine regulation of gene response to stress stimulus. A comprehensive resource of accurate TSSs and individual promoter regions for each TSS in muscle was created. This resource together with the positional weight matrix approach can be used to accurate prediction of TFs in any gene(s) of interest involved in the response to various stimuli, interventions or pathological conditions in human skeletal muscle.

Supplementary Information

The online version contains supplementary material available at 10.1186/s40246-022-00399-8.

New insights from the single-cell level: Tumor associated macrophages heterogeneity and personalized therapy

Tumor-associated macrophages (TAMs) are important immune cells in the tumor microenvironment, and their invasion in tumors is closely related to poor prognosis. Although TAMs are recognized as therapeutic targets, their heterogeneity makes studying tumor mechanism and developing drugs targeting TAMs difficult. The study of TAMs heterogeneity can be used to analyze the mechanism of tumor progression and drug resistance, and may provide possible treatment strategies for cancer patients. Single-cell RNA sequencing (scRNA-seq) can reveal the RNA expression profile for each TAM to distinguish heterogeneity, thereby providing a more efficient detection method and more accurate information for TAM-related studies. In this review, by summarizing the research progress in macrophage heterogeneity and other aspects of scRNA-seq over the past five years, we introduced the development of scRNA-seq technology and its application status in solid tumors, analyzed the advantages and selections of scRNA-seq in TAMs, and summarized the detailed specific research fields. To explore the mechanism of tumor progression and drug intervention from single cell level will provide new perspective for personalized treatment strategies targeting macrophages.

Multiomic atlas with functional stratification and developmental dynamics of zebrafish cis-regulatory elements

Zebrafish, a popular organism for studying embryonic development and for modeling human diseases, has so far lacked a systematic functional annotation program akin to those in other animal models. To address this, we formed the international DANIO-CODE consortium and created a central repository to store and process zebrafish developmental functional genomic data. Our data coordination center ( https://danio-code.zfin.org ) combines a total of 1,802 sets of unpublished and re-analyzed published genomic data, which we used to improve existing annotations and show its utility in experimental design. We identified over 140,000 cis-regulatory elements throughout development, including classes with distinct features dependent on their activity in time and space. We delineated the distinct distance topology and chromatin features between regulatory elements active during zygotic genome activation and those active during organogenesis. Finally, we matched regulatory elements and epigenomic landscapes between zebrafish and mouse and predicted functional relationships between them beyond sequence similarity, thus extending the utility of zebrafish developmental genomics to mammals.

Genome-Wide Evolutionary Analysis of Putative Non-Specific Herbicide Resistance Genes and Compilation of Core Promoters between Monocots and Dicots

Herbicides are key weed-control tools, but their repeated use across large areas has favored the evolution of herbicide resistance. Although target-site has been the most prevalent and studied type of resistance, non-target-site resistance (NTSR) is increasing. However, the genetic factors involved in NTSR are widely unknown. In this study, four gene groups encoding putative NTSR enzymes, namely, cytochrome-P450, glutathione-S-transferase (GST), uridine 5'-diphospho-glucuronosyltransferase (UDPGT), and nitronate monooxygenase (NMO) were analyzed. The monocot and dicot gene sequences were downloaded from publicly available databases. Phylogenetic trees revealed that most of the CYP450 resistance-related sequences belong to CYP81 (5), and in GST, most of the resistance sequences belonged to GSTU18 (9) and GSTF6 (8) groups. In addition, the study of upstream promoter sequences of these NTSR genes revealed stress-related cis-regulatory motifs, as well as eight transcription factor binding sites (TFBS) were identified. The discovered TFBS were commonly present in both monocots and dicots, and the identified motifs are known to play key roles in countering abiotic stress. Further, we predicted the 3D structure for the resistant CYP450 and GST protein and identified the substrate recognition site through the homology approach. Our description of putative NTSR enzymes may be used to develop innovative weed control techniques to delay the evolution of NTSR.

Direct targeted therapy for MLL-fusion-driven high-risk acute leukaemias

BACKGROUND

Improving the poor prognosis of infant leukaemias remains an unmet clinical need. This disease is a prototypical fusion oncoprotein-driven paediatric cancer, with MLL (KMT2A)-fusions present in most cases. Direct targeting of these driving oncoproteins represents a unique therapeutic opportunity. This rationale led us to initiate a drug screening with the aim of discovering drugs that can block MLL-fusion oncoproteins.

METHODS

A screen for inhibition of MLL-fusion proteins was developed that overcomes the traditional limitations of targeting transcription factors. This luciferase reporter-based screen, together with a secondary western blot screen, was used to prioritize compounds. We characterized the lead compound, disulfiram (DSF), based on its efficient ablation of MLL-fusion proteins. The consequences of drug-induced MLL-fusion inhibition were confirmed by cell proliferation, colony formation, apoptosis assays, RT-qPCR, in vivo assays, RNA-seq and ChIP-qPCR and ChIP-seq analysis. All statistical tests were two-sided.

RESULTS

Drug-induced inhibition of MLL-fusion proteins by DSF resulted in a specific block of colony formation in MLL-rearranged cells in vitro, induced differentiation and impeded leukaemia progression in vivo. Mechanistically, DSF abrogates MLL-fusion protein binding to DNA, resulting in epigenetic changes and down-regulation of leukaemic programmes setup by the MLL-fusion protein.

CONCLUSION

DSF can directly inhibit MLL-fusion proteins and demonstrate antitumour activity both in vitro and in vivo, providing, to our knowledge, the first evidence for a therapy that directly targets the initiating oncogenic MLL-fusion protein.

FindIT2: an R/Bioconductor package to identify influential transcription factor and targets based on multi-omics data

BACKGROUND

Transcription factors (TFs) play central roles in regulating gene expression. With the rapid growth in the use of high-throughput sequencing methods, there is a need to develop a comprehensive data processing and analyzing framework for inferring influential TFs based on ChIP-seq/ATAC-seq datasets.

RESULTS

Here, we introduce FindIT2 (Find Influential TFs and Targets), an R/Bioconductor package for annotating and processing high-throughput multi-omics data. FindIT2 supports a complete framework for annotating ChIP-seq/ATAC-seq peaks, identifying TF targets by the combination of ChIP-seq and RNA-seq datasets, and inferring influential TFs based on different types of data input. Moreover, benefited from the annotation framework based on Bioconductor, FindIT2 can be applied to any species with genomic annotations, which is particularly useful for the non-model species that are less well-studied.

CONCLUSION

FindIT2 provides a user-friendly and flexible framework to generate results at different levels according to the richness of the annotation information of user's species. FindIT2 is compatible with all the operating systems and is released under Artistic-2.0 License. The source code and documents are freely available through Bioconductor ( https://bioconductor.org/packages/devel/bioc/html/FindIT2.html ).

Interleukin-1 Is Overexpressed in Injured Muscles Following Spinal Cord Injury and Promotes Neurogenic Heterotopic Ossification

Neurogenic heterotopic ossifications (NHOs) form in periarticular muscles after severe spinal cord (SCI) and traumatic brain injuries. The pathogenesis of NHO is poorly understood with no effective preventive treatment. The only curative treatment remains surgical resection of pathological NHOs. In a mouse model of SCI-induced NHO that involves a transection of the spinal cord combined with a muscle injury, a differential gene expression analysis revealed that genes involved in inflammation such as interleukin-1β (IL-1β) were overexpressed in muscles developing NHO. Using mice knocked-out for the gene encoding IL-1 receptor (IL1R1) and neutralizing antibodies for IL-1α and IL-1β, we show that IL-1 signaling contributes to NHO development after SCI in mice. Interestingly, other proteins involved in inflammation that were also overexpressed in muscles developing NHO, such as colony-stimulating factor-1, tumor necrosis factor, or C-C chemokine ligand-2, did not promote NHO development. Finally, using NHO biopsies from SCI and TBI patients, we show that IL-1β is expressed by CD68⁺ macrophages. IL-1α and IL-1β produced by activated human monocytes promote calcium mineralization and RUNX2 expression in fibro-adipogenic progenitors isolated from muscles surrounding NHOs. Altogether, these data suggest that interleukin-1 promotes NHO development in both humans and mice. © 2021 American Society for Bone and Mineral Research (ASBMR).

Identification of a c-MYB-directed therapeutic for acute myeloid leukemia

A significant proportion of patients suffering from acute myeloid leukemia (AML) cannot be cured by conventional chemotherapy, relapsed disease being a common problem. Molecular targeting of essential oncogenic mediators is an attractive approach to improving outcomes for this disease. The hematopoietic transcription factor c-MYB has been revealed as a central component of complexes maintaining aberrant gene expression programs in AML. We have previously screened the Connectivity Map database to identify mebendazole as an anti-AML therapeutic targeting c-MYB. In the present study we demonstrate that another hit from this screen, the steroidal lactone withaferin A (WFA), induces rapid ablation of c-MYB protein and consequent inhibition of c-MYB target gene expression, loss of leukemia cell viability, reduced colony formation and impaired disease progression. Although WFA has been reported to have pleiotropic anti-cancer effects, we demonstrate that its anti-AML activity depends on c-MYB modulation and can be partially reversed by a stabilized c-MYB mutant. c-MYB ablation results from disrupted HSP/HSC70 chaperone protein homeostasis in leukemia cells following induction of proteotoxicity and the unfolded protein response by WFA. The widespread use of WFA in traditional medicines throughout the world indicates that it represents a promising candidate for repurposing into AML therapy.

Analysis of Enhancers and Transcriptional Networks in Thermogenic Adipocytes

Transcription factor (TF) networks orchestrate the regulation of gene programs in mammalian cells, including white and brown adipocytes. In this protocol, we outline how genomics and transcriptomics data can be integrated to infer causal TFs of a given cellular response or cell type using "Integrated analysis of Motif Activity and Gene Expression changes of transcription factors" (IMAGE). Here, we show how key regulatory TFs controlling white and brown adipocyte gene programs can be predicted from chromatin accessibility and RNA-seq data. Furthermore, we demonstrate how information about target sites and target genes of the predicted key regulators can be integrated to propose testable hypotheses regarding the role and mechanisms of TFs.

Genome-wide gene expression noise in Escherichia coli is condition-dependent and determined by propagation of noise through the regulatory network

Although it is well appreciated that gene expression is inherently noisy and that transcriptional noise is encoded in a promoter’s sequence, little is known about the extent to which noise levels of individual promoters vary across growth conditions. Using flow cytometry, we here quantify transcriptional noise in Escherichia coli genome-wide across 8 growth conditions and find that noise levels systematically decrease with growth rate, with a condition-dependent lower bound on noise. Whereas constitutive promoters consistently exhibit low noise in all conditions, regulated promoters are both more noisy on average and more variable in noise across conditions. Moreover, individual promoters show highly distinct variation in noise across conditions. We show that a simple model of noise propagation from regulators to their targets can explain a significant fraction of the variation in relative noise levels and identifies TFs that most contribute to both condition-specific and condition-independent noise propagation. In addition, analysis of the genome-wide correlation structure of various gene properties shows that gene regulation, expression noise, and noise plasticity are all positively correlated genome-wide and vary independently of variations in absolute expression, codon bias, and evolutionary rate. Together, our results show that while absolute expression noise tends to decrease with growth rate, relative noise levels of genes are highly condition-dependent and determined by the propagation of noise through the gene regulatory network.

Genome-wide flow cytometry measurements reveal that gene expression noise in bacteria is highly condition-dependent; while absolute noise levels of all genes decrease with growth-rate, theoretical modeling shows that the relative noise levels of different genes are determined by the propagation of noise through the gene regulatory network (GRN). Thus GRN structure controls not only mean expression but also noise levels.

LncRNA Hmrhl regulates expression of cancer related genes in chronic myelogenous leukemia through chromatin association

Long non-coding RNA has emerged as a key regulator of myriad gene functions. One such lncRNA mrhl, reported by our group, was found to have important role in spermatogenesis and embryonic development in mouse. Recently, its human homolog, Hmrhl was shown to have differential expression in several type of cancers. In the present study, we further characterize molecular features of Hmrhl and gain insight into its functional role in leukemia by gene silencing and transcriptome-based studies. Results indicate its high expression in CML patient samples as well as in K562 cell line. Silencing experiments suggest role of Hmrhl in cell proliferation, migration & invasion. RNA-seq and ChiRP-seq data analysis further revealed its association with important biological processes, including perturbed expression of crucial TFs and cancer-related genes. Among them ZIC1, PDGRFβ and TP53 were identified as regulatory targets, with high possibility of triplex formation by Hmrhl at their promoter site. Further, overexpression of PDGRFβ in Hmrhl silenced cells resulted in rescue effect of cancer associated cellular phenotypes. In addition, we also found TAL-1 to be a potential regulator of Hmrhl expression in K562 cells. Thus, we hypothesize that Hmrhl lncRNA may play a significant role in the pathobiology of CML.

Enhancer recruitment of transcription repressors RUNX1 and TLE3 by mis-expressed FOXC1 blocks differentiation in acute myeloid leukemia

Despite absent expression in normal hematopoiesis, the Forkhead factor FOXC1, a critical mesenchymal differentiation regulator, is highly expressed in ∼30% of HOXAhigh acute myeloid leukemia (AML) cases to confer blocked monocyte/macrophage differentiation. Through integrated proteomics and bioinformatics, we find that FOXC1 and RUNX1 interact through Forkhead and Runt domains, respectively, and co-occupy primed and active enhancers distributed close to differentiation genes. FOXC1 stabilizes association of RUNX1, HDAC1, and Groucho repressor TLE3 to limit enhancer activity: FOXC1 knockdown induces loss of repressor proteins, gain of CEBPA binding, enhancer acetylation, and upregulation of nearby genes, including KLF2. Furthermore, it triggers genome-wide redistribution of RUNX1, TLE3, and HDAC1 from enhancers to promoters, leading to repression of self-renewal genes, including MYC and MYB. Our studies highlight RUNX1 and CEBPA transcription factor swapping as a feature of leukemia cell differentiation and reveal that FOXC1 prevents this by stabilizing enhancer binding of a RUNX1/HDAC1/TLE3 transcription repressor complex to oncogenic effect.

Cap analysis of gene expression (CAGE) and noncoding regulatory elements

Cap analysis of gene expression (CAGE) was developed to detect the 5' end of RNA. Trapping of the RNA 5'-cap structure enables the enrichment and selective sequencing of complete transcripts. Upscaled high-throughput versions of CAGE have enabled the genome-wide identification of transcription start sites, including transcriptionally active promoters and enhancers. CAGE sequencing can be exploited to draw comprehensive maps of active genomic regulatory elements in a cell type- and activation-specific manner. The cells of the immune system are among the best candidates to be analyzed in humans, since they are easily accessible. In this review, we discuss how CAGE data are instrumental for integrative analyses with quantitative trait loci and omics data, and their usefulness in the mechanistic interpretation of the effects of genetic variations over the entire human genome. Integrating CAGE data with the currently available omics information will contribute to better understanding of the genome-wide association study variants that lie outside of annotated genes, deepening our knowledge on human diseases, and enabling the targeted design of more specific therapeutic interventions.

ANANSE: an enhancer network-based computational approach for predicting key transcription factors in cell fate determination

Proper cell fate determination is largely orchestrated by complex gene regulatory networks centered around transcription factors. However, experimental elucidation of key transcription factors that drive cellular identity is currently often intractable. Here, we present ANANSE (ANalysis Algorithm for Networks Specified by Enhancers), a network-based method that exploits enhancer-encoded regulatory information to identify the key transcription factors in cell fate determination. As cell type-specific transcription factors predominantly bind to enhancers, we use regulatory networks based on enhancer properties to prioritize transcription factors. First, we predict genome-wide binding profiles of transcription factors in various cell types using enhancer activity and transcription factor binding motifs. Subsequently, applying these inferred binding profiles, we construct cell type-specific gene regulatory networks, and then predict key transcription factors controlling cell fate transitions using differential networks between cell types. This method outperforms existing approaches in correctly predicting major transcription factors previously identified to be sufficient for trans-differentiation. Finally, we apply ANANSE to define an atlas of key transcription factors in 18 normal human tissues. In conclusion, we present a ready-to-implement computational tool for efficient prediction of transcription factors in cell fate determination and to study transcription factor-mediated regulatory mechanisms. ANANSE is freely available at https://github.com/vanheeringen-lab/ANANSE.

A KMT2A-AFF1 gene regulatory network highlights the role of core transcription factors and reveals the regulatory logic of key downstream target genes

Regulatory interactions mediated by transcription factors (TFs) make up complex networks that control cellular behavior. Fully understanding these gene regulatory networks (GRNs) offers greater insight into the consequences of disease-causing perturbations than can be achieved by studying single TF binding events in isolation. Chromosomal translocations of the lysine methyltransferase 2A (KMT2A) gene produce KMT2A fusion proteins such as KMT2A-AFF1 (previously MLL-AF4), causing poor prognosis acute lymphoblastic leukemias (ALLs) that sometimes relapse as acute myeloid leukemias (AMLs). KMT2A-AFF1 drives leukemogenesis through direct binding and inducing the aberrant overexpression of key genes, such as the anti-apoptotic factor BCL2 and the proto-oncogene MYC However, studying direct binding alone does not incorporate possible network-generated regulatory outputs, including the indirect induction of gene repression. To better understand the KMT2A-AFF1-driven regulatory landscape, we integrated ChIP-seq, patient RNA-seq, and CRISPR essentiality screens to generate a model GRN. This GRN identified several key transcription factors such as RUNX1 that regulate target genes downstream of KMT2A-AFF1 using feed-forward loop (FFL) and cascade motifs. A core set of nodes are present in both ALL and AML, and CRISPR screening revealed several factors that help mediate response to the drug venetoclax. Using our GRN, we then identified a KMT2A-AFF1:RUNX1 cascade that represses CASP9, as well as KMT2A-AFF1-driven FFLs that regulate BCL2 and MYC through combinatorial TF activity. This illustrates how our GRN can be used to better connect KMT2A-AFF1 behavior to downstream pathways that contribute to leukemogenesis, and potentially predict shifts in gene expression that mediate drug response.

CRISPR-Cas9 Editing of Human Histone Deubiquitinase Gene USP16 in Human Monocytic Leukemia Cell Line THP-1

USP16 is a histone deubiquitinase which facilitates G2/M transition during the cell cycle, regulates DNA damage repair and contributes to inducible gene expression. We mutated the USP16 gene in a high differentiation clone of the acute monocytic leukemia cell line THP-1 using the CRISPR-Cas9 system and generated four homozygous knockout clones. All were able to proliferate and to differentiate in response to phorbol ester (PMA) treatment. One line was highly proliferative prior to PMA treatment and shut down proliferation upon differentiation, like wild type. Three clones showed sustained expression of the progenitor cell marker MYB, indicating that differentiation had not completely blocked proliferation in these clones. Network analysis of transcriptomic differences among wild type, heterozygotes and homozygotes showed clusters of genes that were up- or down-regulated after differentiation in all cell lines. Prior to PMA treatment, the homozygous clones had lower levels than wild type of genes relating to metabolism and mitochondria, including SRPRB, encoding an interaction partner of USP16. There was also apparent loss of interferon signaling. In contrast, a number of genes were up-regulated in the homozygous cells compared to wild type at baseline, including other deubiquitinases (USP12, BAP1, and MYSM1). However, three homozygotes failed to fully induce USP3 during differentiation. Other network clusters showed effects prior to or after differentiation in the homozygous clones. Thus the removal of USP16 affected the transcriptome of the cells, although all these lines were able to survive, which suggests that the functions attributed to USP16 may be redundant. Our analysis indicates that the leukemic line can adapt to the extreme selection pressure applied by the loss of USP16, and the harsh conditions of the gene editing and selection protocol, through different compensatory pathways. Similar selection pressures occur during the evolution of a cancer in vivo, and our results can be seen as a case study in leukemic cell adaptation. USP16 has been considered a target for cancer chemotherapy, but our results suggest that treatment would select for escape mutants that are resistant to USP16 inhibitors.

Novel risk factors for craniofacial microsomia and assessment of their utility in clinic diagnosis

Craniofacial microsomia (CFM, OMIM%164 210) is one of the most common congenital facial abnormalities worldwide, but it's genetic risk factors and environmental threats are poorly investigated, as well as their interaction, making the diagnosis and prenatal screening of CFM impossible. We perform a comprehensive association study on the largest CFM cohort of 6074 samples. We identify 15 significant (P < 5 × 10-8) associated genomic loci (including eight previously reported) and decipher 107 candidates based on multi-omics data. Gene Ontology term enrichment found that these candidates are mainly enriched in neural crest cell (NCC) development and hypoxic environment. Single-cell RNA-seq data of mouse embryo demonstrate that nine of them show dramatic expression change during early cranial NCC development whose dysplasia is involved in pathogeny of CFM. Furthermore, we construct a well-performed CFM risk-predicting model based on polygenic risk score (PRS) method and estimate seven environmental risk factors that interacting with PRS. Single-nucleotide polymorphism-based PRS is significantly associated with CFM [P = 7.22 × 10-58, odds ratio = 3.15, 95% confidence interval (CI) 2.74-3.63], and the top fifth percentile has a 6.8-fold CFM risk comparing with the 10th percentile. Father's smoking increases CFM risk as evidenced by interaction parameter of -0.324 (95% CI -0.578 to -0.070, P = 0.011) with PRS. In conclusion, the newly identified risk loci will significantly improve our understandings of genetics contribution to CFM. The risk prediction model is promising for CFM prediction, and father's smoking is a key environmental risk factor for CFM through interacting with genetic factors.

c-Myb interferes with inflammatory IL1α-NF-κB pathway in breast cancer cells

The transcription factor c-Myb can be involved in the activation of many genes with protumorigenic function; however, its role in breast cancer (BC) development is still under discussion. c-Myb is considered as a tumor-promoting factor in the early phases of BC, on the other hand, its expression in BC patients relates to a good prognosis. Previously, we have shown that c-Myb controls the capacity of BC cells to form spontaneous lung metastasis. Reduced seeding of BC cells to the lungs is linked to high expression of c-Myb and a decline in expression of a specific set of inflammatory genes. Here, we unraveled a c-Myb-IL1α-NF-κB signaling axis that takes place in tumor cells. We report that an overexpression of c-Myb interfered with the activity of NF-κB in several BC cell lines. We identified IL1α to be essential for this interference since it was abrogated in the IL1α-deficient cells. Overexpression of IL1α, as well as addition of recombinant IL1α protein, activated NF-κB signaling and restored expression of the inflammatory signature genes suppressed by c-Myb. The endogenous levels of c-Myb negatively correlated with IL1α on both transcriptional and protein levels across BC cell lines. We concluded that inhibition of IL1α expression by c-Myb reduces NF-κB activity and disconnects the inflammatory circuit, a potentially targetable mechanism to mimic the antimetastatic effect of c-Myb with therapeutic perspective.

Combinatorial transcription factor activities on open chromatin induce embryonic heterogeneity in vertebrates

During vertebrate gastrulation, mesoderm is induced in pluripotent cells, concomitant with dorsal‐ventral patterning and establishing of the dorsal axis. We applied single‐cell chromatin accessibility and transcriptome analyses to explore the emergence of cellular heterogeneity during gastrulation in Xenopus tropicalis. Transcriptionally inactive lineage‐restricted genes exhibit relatively open chromatin in animal caps, whereas chromatin accessibility in dorsal marginal zone cells more closely reflects transcriptional activity. We characterized single‐cell trajectories and identified head and trunk organizer cell clusters in early gastrulae. By integrating chromatin accessibility and transcriptome data, we inferred the activity of transcription factors in single‐cell clusters and tested the activity of organizer‐expressed transcription factors in animal caps, alone or in combination. The expression profile induced by a combination of Foxb1 and Eomes most closely resembles that observed in the head organizer. Genes induced by Eomes, Otx2, or the Irx3‐Otx2 combination are enriched for maternally regulated H3K4me3 modifications, whereas Lhx8‐induced genes are marked more frequently by zygotically controlled H3K4me3. Taken together, our results show that transcription factors cooperate in a combinatorial fashion in generally open chromatin to orchestrate zygotic gene expression.

FANTOM enters 20th year: expansion of transcriptomic atlases and functional annotation of non-coding RNAs

The Functional ANnoTation Of the Mammalian genome (FANTOM) Consortium has continued to provide extensive resources in the pursuit of understanding the transcriptome, and transcriptional regulation, of mammalian genomes for the last 20 years. To share these resources with the research community, the FANTOM web-interfaces and databases are being regularly updated, enhanced and expanded with new data types. In recent years, the FANTOM Consortium's efforts have been mainly focused on creating new non-coding RNA datasets and resources. The existing FANTOM5 human and mouse miRNA atlas was supplemented with rat, dog, and chicken datasets. The sixth (latest) edition of the FANTOM project was launched to assess the function of human long non-coding RNAs (lncRNAs). From its creation until 2020, FANTOM6 has contributed to the research community a large dataset generated from the knock-down of 285 lncRNAs in human dermal fibroblasts; this is followed with extensive expression profiling and cellular phenotyping. Other updates to the FANTOM resource includes the reprocessing of the miRNA and promoter atlases of human, mouse and chicken with the latest reference genome assemblies. To facilitate the use and accessibility of all above resources we further enhanced FANTOM data viewers and web interfaces. The updated FANTOM web resource is publicly available at https://fantom.gsc.riken.jp/.

Differentiation of ciliated human midbrain-derived LUHMES neurons

Many human cell types are ciliated, including neural progenitors and differentiated neurons. Ciliopathies are characterized by defective cilia and comprise various disease states, including brain phenotypes, where the underlying biological pathways are largely unknown. Our understanding of neuronal cilia is rudimentary, and an easy-to-maintain, ciliated human neuronal cell model is absent. The Lund human mesencephalic (LUHMES) cell line is a ciliated neuronal cell line derived from human fetal mesencephalon. LUHMES cells can easily be maintained and differentiated into mature, functional neurons within one week. They have a single primary cilium as proliferating progenitor cells and as postmitotic, differentiating neurons. These developmental stages are completely separable within one day of culture condition change. The sonic hedgehog (SHH) signaling pathway is active in differentiating LUHMES neurons. RNA-sequencing timecourse analyses reveal molecular pathways and gene-regulatory networks critical for ciliogenesis and axon outgrowth at the interface between progenitor cell proliferation, polarization and neuronal differentiation. Gene expression dynamics of cultured LUHMES neurons faithfully mimic the corresponding in vivo dynamics of human fetal midbrain. In LUHMES cells, neuronal cilia biology can be investigated from proliferation through differentiation to mature neurons.

Comparative transcriptomics of primary cells in vertebrates

Gene expression profiles in homologous tissues have been observed to be different between species, which may be due to differences between species in the gene expression program in each cell type, but may also reflect differences in cell type composition of each tissue in different species. Here, we compare expression profiles in matching primary cells in human, mouse, rat, dog, and chicken using Cap Analysis Gene Expression (CAGE) and short RNA (sRNA) sequencing data from FANTOM5. While we find that expression profiles of orthologous genes in different species are highly correlated across cell types, in each cell type many genes were differentially expressed between species. Expression of genes with products involved in transcription, RNA processing, and transcriptional regulation was more likely to be conserved, while expression of genes encoding proteins involved in intercellular communication was more likely to have diverged during evolution. Conservation of expression correlated positively with the evolutionary age of genes, suggesting that divergence in expression levels of genes critical for cell function was restricted during evolution. Motif activity analysis showed that both promoters and enhancers are activated by the same transcription factors in different species. An analysis of expression levels of mature miRNAs and of primary miRNAs identified by CAGE revealed that evolutionary old miRNAs are more likely to have conserved expression patterns than young miRNAs. We conclude that key aspects of the regulatory network are conserved, while differential expression of genes involved in cell-to-cell communication may contribute greatly to phenotypic differences between species.

Functional annotation of human long noncoding RNAs via molecular phenotyping

Long noncoding RNAs (lncRNAs) constitute the majority of transcripts in the mammalian genomes, and yet, their functions remain largely unknown. As part of the FANTOM6 project, we systematically knocked down the expression of 285 lncRNAs in human dermal fibroblasts and quantified cellular growth, morphological changes, and transcriptomic responses using Capped Analysis of Gene Expression (CAGE). Antisense oligonucleotides targeting the same lncRNAs exhibited global concordance, and the molecular phenotype, measured by CAGE, recapitulated the observed cellular phenotypes while providing additional insights on the affected genes and pathways. Here, we disseminate the largest-to-date lncRNA knockdown data set with molecular phenotyping (over 1000 CAGE deep-sequencing libraries) for further exploration and highlight functional roles for ZNF213-AS1 and lnc-KHDC3L-2.

The Transcriptional Network That Controls Growth Arrest and Macrophage Differentiation in the Human Myeloid Leukemia Cell Line THP-1

The response of the human acute myeloid leukemia cell line THP-1 to phorbol esters has been widely studied to test candidate leukemia therapies and as a model of cell cycle arrest and monocyte-macrophage differentiation. Here we have employed Cap Analysis of Gene Expression (CAGE) to analyze a dense time course of transcriptional regulation in THP-1 cells treated with phorbol myristate acetate (PMA) over 96 h. PMA treatment greatly reduced the numbers of cells entering S phase and also blocked cells exiting G2/M. The PMA-treated cells became adherent and expression of mature macrophage-specific genes increased progressively over the duration of the time course. Within 1–2 h PMA induced known targets of tumor protein p53 (TP53), notably CDKN1A, followed by gradual down-regulation of cell-cycle associated genes. Also within the first 2 h, PMA induced immediate early genes including transcription factor genes encoding proteins implicated in macrophage differentiation (EGR2, JUN, MAFB) and down-regulated genes for transcription factors involved in immature myeloid cell proliferation (MYB, IRF8, GFI1). The dense time course revealed that the response to PMA was not linear and progressive. Rather, network-based clustering of the time course data highlighted a sequential cascade of transient up- and down-regulated expression of genes encoding feedback regulators, as well as transcription factors associated with macrophage differentiation and their inferred target genes. CAGE also identified known and candidate novel enhancers expressed in THP-1 cells and many novel inducible genes that currently lack functional annotation and/or had no previously known function in macrophages. The time course is available on the ZENBU platform allowing comparison to FANTOM4 and FANTOM5 data.

Advancing Stem Cell Research through Multimodal Single-Cell Analysis

Technological advances play a key role in furthering our understanding of stem cell biology, and advancing the prospects of regenerative therapies. Highly parallelized methods, developed in the last decade, can profile DNA, RNA, or proteins in thousands of cells and even capture data across two or more modalities (multiomics). This allows unbiased and precise definition of molecular cell states, thus allowing classification of cell types, tracking of differentiation trajectories, and discovery of underlying mechanisms. Despite being based on destructive techniques, novel experimental and bioinformatic approaches enable embedding and extraction of temporal information, which is essential for deconvolution of complex data and establishing cause and effect relationships. Here, we provide an overview of recent studies pertinent to stem cell biology, followed by an outlook on how further advances in single-cell molecular profiling and computational analysis have the potential to shape the future of both basic and translational research.

Human Brain Organoids to Decode Mechanisms of Microcephaly

Brain organoids are stem cell-based self-assembling 3D structures that recapitulate early events of human brain development. Recent improvements with patient-specific 3D brain organoids have begun to elucidate unprecedented details of the defective mechanisms that cause neurodevelopmental disorders of congenital and acquired microcephaly. In particular, brain organoids derived from primary microcephaly patients have uncovered mechanisms that deregulate neural stem cell proliferation, maintenance, and differentiation. Not only did brain organoids reveal unknown aspects of neurogenesis but also have illuminated surprising roles of cellular structures of centrosomes and primary cilia in regulating neurogenesis during brain development. Here, we discuss how brain organoids have started contributing to decoding the complexities of microcephaly, which are unlikely to be identified in the existing non-human models. Finally, we discuss the yet unresolved questions and challenges that can be addressed with the use of brain organoids as in vitro models of neurodevelopmental disorders.

Investigating the effect of dependence between conditions with Bayesian Linear Mixed Models for motif activity analysis

MOTIVATION

Cellular identity and behavior is controlled by complex gene regulatory networks. Transcription factors (TFs) bind to specific DNA sequences to regulate the transcription of their target genes. On the basis of these TF motifs in cis-regulatory elements we can model the influence of TFs on gene expression. In such models of TF motif activity the data is usually modeled assuming a linear relationship between the motif activity and the gene expression level. A commonly used method to model motif influence is based on Ridge Regression. One important assumption of linear regression is the independence between samples. However, if samples are generated from the same cell line, tissue, or other biological source, this assumption may be invalid. This same assumption of independence is also applied to different yet similar experimental conditions, which may also be inappropriate. In theory, the independence assumption between samples could lead to loss in signal detection. Here we investigate whether a Bayesian model that allows for correlations results in more accurate inference of motif activities.

RESULTS

We extend the Ridge Regression to a Bayesian Linear Mixed Model, which allows us to model dependence between different samples. In a simulation study, we investigate the differences between the two model assumptions. We show that our Bayesian Linear Mixed Model implementation outperforms Ridge Regression in a simulation scenario where the noise, which is the signal that can not be explained by TF motifs, is uncorrelated. However, we demonstrate that there is no such gain in performance if the noise has a similar covariance structure over samples as the signal that can be explained by motifs. We give a mathematical explanation to why this is the case. Using four representative real datasets we show that at most ∼​40% of the signal is explained by motifs using the linear model. With these data there is no advantage to using the Bayesian Linear Mixed Model, due to the similarity of the covariance structure.

AVAILABILITY & IMPLEMENTATION

The project implementation is available at https://github.com/Sim19/SimGEXPwMotifs.

Pre-clinical activity of combined LSD1 and mTORC1 inhibition in MLL-translocated acute myeloid leukaemia

The histone demethylase lysine-specific demethylase 1 (LSD1 or KDM1A) has emerged as a candidate therapeutic target in acute myeloid leukaemia (AML); tranylcypromine-derivative inhibitors induce loss of clonogenic activity and promote differentiation, in particular in the MLL-translocated molecular subtype of AML. In AML, the use of drugs in combination often delivers superior clinical activity. To identify genes and cellular pathways that collaborate with LSD1 to maintain the leukaemic phenotype, and which could be targeted by combination therapies, we performed a genome-wide CRISPR-Cas9 dropout screen. We identified multiple components of the amino acid sensing arm of mTORC1 signalling-RRAGA, MLST8, WDR24 and LAMTOR2-as cellular sensitizers to LSD1 inhibition. Knockdown of mTORC1 components, or mTORC1 pharmacologic inhibition, in combination with LSD1 inhibition enhanced differentiation in both cell line and primary cell settings, in vitro and in vivo, and substantially reduced the frequency of clonogenic primary human AML cells in a modelled minimal residual disease setting. Synergistic upregulation of a set of transcription factor genes associated with terminal monocytic lineage differentiation was observed. Thus, dual mTORC1 and LSD1 inhibition represents a candidate combination approach for enhanced differentiation in MLL-translocated AML which could be evaluated in early phase clinical trials.

Adhesion, motility and matrix-degrading gene expression changes in CSF-1-induced mouse macrophage differentiation

Migratory macrophages play critical roles in tissue development, homeostasis and disease, so it is important to understand how their migration machinery is regulated. Whole-transcriptome sequencing revealed that CSF-1-stimulated differentiation of bone marrow-derived precursors into mature macrophages is accompanied by widespread, profound changes in the expression of genes regulating adhesion, actin cytoskeletal remodeling and extracellular matrix degradation. Significantly altered expression of almost 40% of adhesion genes, 60-86% of Rho family GTPases, their regulators and effectors and over 70% of extracellular proteases occurred. The gene expression changes were mirrored by changes in macrophage adhesion associated with increases in motility and matrix-degrading capacity. IL-4 further increased motility and matrix-degrading capacity in mature macrophages, with additional changes in migration machinery gene expression. Finally, siRNA-induced reductions in the expression of the core adhesion proteins paxillin and leupaxin decreased macrophage spreading and the number of adhesions, with distinct effects on adhesion and their distribution, and on matrix degradation. Together, the datasets provide an important resource to increase our understanding of the regulation of migration in macrophages and to develop therapies targeting disease-enhancing macrophages.

A human minisatellite hosts an alternative transcription start site for NPRL3 driving its expression in a repeat number-dependent manner

Minisatellites, also called variable number of tandem repeats (VNTRs), are a class of repetitive elements that may affect gene expression at multiple levels and have been correlated to disease. Their identification and role as expression quantitative trait loci (eQTL) have been limited by their absence in comparative genomic hybridization and single nucleotide polymorphisms arrays. By taking advantage of cap analysis of gene expression (CAGE), we describe a new example of a minisatellite hosting a transcription start site (TSS) which expression is dependent on the repeat number. It is located in the third intron of the gene nitrogen permease regulator like protein 3 (NPRL3). NPRL3 is a component of the GAP activity toward rags 1 protein complex that inhibits mammalian target of rapamycin complex 1 (mTORC1) activity and it is found mutated in familial focal cortical dysplasia and familial focal epilepsy. CAGE tags represent an alternative TSS identifying TAGNPRL3 messenger RNAs (mRNAs). TAGNPRL3 is expressed in red blood cells both at mRNA and protein levels, it interacts with its protein partner NPRL2 and its overexpression inhibits cell proliferation. This study provides an example of a minisatellite that is both a TSS and an eQTL as well as identifies a new VNTR that may modify mTORC1 activity.

Cap Analysis of Gene Expression (CAGE): A Quantitative and Genome-Wide Assay of Transcription Start Sites

Cap analysis of gene expression (CAGE) is an approach to identify and monitor the activity (transcription initiation frequency) of transcription start sites (TSSs) at single base-pair resolution across the genome. It has been effectively used to identify active promoter and enhancer regions in cancer cells, with potential utility to identify key factors to immunotherapy. Here, we overview a series of CAGE protocols and describe detailed experimental steps of the latest protocol based on the Illumina sequencing platform; both experimental steps (see Subheadings 3.1-3.11) and computational processing steps (see Subheadings 3.12-3.20) are described.

A framework for identification of on- and off-target transcriptional responses to drug treatment

Owing to safety concerns or insufficient efficacy, few drug candidates are approved for marketing. Drugs already on the market may be withdrawn due to adverse effects (AEs) discovered after market introduction. Comprehensively investigating the on-/off-target effects of drugs can help expose AEs during the drug development process. We have developed an integrative framework for systematic identification of on-/off-target pathways and elucidation of the underlying regulatory mechanisms, by combining promoter expression profiling after drug treatment with gene perturbation of the primary drug target. Expression profiles from statin-treated cells and HMG-CoA reductase knockdowns were analyzed using the framework, allowing for identification of not only reported adverse effects but also novel candidates of off-target effects from statin treatment, including key regulatory elements of on- and off-targets. Our findings may provide new insights for finding new usages or potential side effects of drug treatment.

Experimental and Computational Approaches to Direct Cell Reprogramming: Recent Advancement and Future Challenges

The process of direct cell reprogramming, also named transdifferentiation, permits for the conversion of one mature cell type directly into another, without returning to a dedifferentiated state. This makes direct reprogramming a promising approach for the development of several cellular and tissue engineering therapies. To achieve the change in the cell identity, direct reprogramming requires an arsenal of tools that combine experimental and computational techniques. In the recent years, several methods of transdifferentiation have been developed. In this review, we will introduce the concept of direct cell reprogramming and its background, and cover the recent developments in the experimental and computational prediction techniques with their applications. We also discuss the challenges of translating this technology to clinical setting, accompanied with potential solutions.

Spatiotemporal structure of cell fate decisions in murine neural crest

Neural crest cells are embryonic progenitors that generate numerous cell types in vertebrates. With single-cell analysis, we show that mouse trunk neural crest cells become biased toward neuronal lineages when they delaminate from the neural tube, whereas cranial neural crest cells acquire ectomesenchyme potential dependent on activation of the transcription factor Twist1. The choices that neural crest cells make to become sensory, glial, autonomic, or mesenchymal cells can be formalized as a series of sequential binary decisions. Each branch of the decision tree involves initial coactivation of bipotential properties followed by gradual shifts toward commitment. Competing fate programs are coactivated before cells acquire fate-specific phenotypic traits. Determination of a specific fate is achieved by increased synchronization of relevant programs and concurrent repression of competing fate programs.

The AAA+ATPase RUVBL2 is essential for the oncogenic function of c-MYB in acute myeloid leukemia

Subtype-specific leukemia oncogenes drive aberrant gene expression profiles that converge on common essential mediators to ensure leukemia self-renewal and inhibition of differentiation. The transcription factor c-MYB functions as one such mediator in a diverse range of leukemias. Here we show for the first time that transcriptional repression of myeloid differentiation associated c-MYB target genes in AML is enforced by the AAA+ ATPase RUVBL2. Silencing RUVBL2 expression resulted in increased binding of c-MYB to these loci and their transcriptional activation. RUVBL2 inhibition resulted in AML cell apoptosis and severely impaired disease progression of established AML in engrafted mice. In contrast, such inhibition had little impact on normal hematopoietic progenitor differentiation. These data demonstrate that RUVBL2 is essential for the oncogenic function of c-MYB in AML by governing inhibition of myeloid differentiation. They also indicate that targeting the control of c-MYB function by RUVBL2 is a promising approach to developing future anti-AML therapies.