ChIP-Atlas: a data-mining suite powered by full integration of public ChIP-seq data

TFTG: A comprehensive database for human transcription factors and their targets

Transcription factors (TFs) are major contributors to gene transcription, especially in controlling cell-specific gene expression and disease occurrence and development. Uncovering the relationship between TFs and their target genes is critical to understanding the mechanism of action of TFs. With the development of high-throughput sequencing techniques, a large amount of TF-related data has accumulated, which can be used to identify their target genes. In this study, we developed TFTG (Transcription Factor and Target Genes) database (http://tf.liclab.net/TFTG), which aimed to provide a large number of available human TF-target gene resources by multiple strategies, besides performing a comprehensive functional and epigenetic annotations and regulatory analyses of TFs. We identified extensive available TF-target genes by collecting and processing TF-associated ChIP-seq datasets, perturbation RNA-seq datasets and motifs. We also obtained experimentally confirmed relationships between TF and target genes from available resources. Overall, the target genes of TFs were obtained through integrating the relevant data of various TFs as well as fourteen identification strategies. Meanwhile, TFTG was embedded with user-friendly search, analysis, browsing, downloading and visualization functions. TFTG is designed to be a convenient resource for exploring human TF-target gene regulations, which will be useful for most users in the TF and gene expression regulation research.

MOCHA's advanced statistical modeling of scATAC-seq data enables functional genomic inference in large human cohorts

Single-cell assay for transposase-accessible chromatin using sequencing (scATAC-seq) is being increasingly used to study gene regulation. However, major analytical gaps limit its utility in studying gene regulatory programs in complex diseases. In response, MOCHA (Model-based single cell Open CHromatin Analysis) presents major advances over existing analysis tools, including: 1) improving identification of sample-specific open chromatin, 2) statistical modeling of technical drop-out with zero-inflated methods, 3) mitigation of false positives in single cell analysis, 4) identification of alternative transcription-starting-site regulation, and 5) modules for inferring temporal gene regulatory networks from longitudinal data. These advances, in addition to open chromatin analyses, provide a robust framework after quality control and cell labeling to study gene regulatory programs in human disease. We benchmark MOCHA with four state-of-the-art tools to demonstrate its advances. We also construct cross-sectional and longitudinal gene regulatory networks, identifying potential mechanisms of COVID-19 response. MOCHA provides researchers with a robust analytical tool for functional genomic inference from scATAC-seq data.

SETDB1 suppresses NK cell-mediated immunosurveillance in acute myeloid leukemia with granulo-monocytic differentiation

Monocytic acute myeloid leukemia (AML) responds poorly to current treatments, including venetoclax-based therapy. We conducted in vivo and in vitro CRISPR-Cas9 library screenings using a mouse monocytic AML model and identified SETDB1 and its binding partners (ATF7IP and TRIM33) as crucial tumor promoters in vivo. The growth-inhibitory effect of Setdb1 depletion in vivo is dependent mainly on natural killer (NK) cell-mediated cytotoxicity. Mechanistically, SETDB1 depletion upregulates interferon-stimulated genes and NKG2D ligands through the demethylation of histone H3 Lys9 at the enhancer regions, thereby enhancing their immunogenicity to NK cells and intrinsic apoptosis. Importantly, these effects are not observed in non-monocytic leukemia cells. We also identified the expression of myeloid cell nuclear differentiation antigen (MNDA) and its murine counterpart Ifi203 as biomarkers to predict the sensitivity of AML to SETDB1 depletion. Our study highlights the critical and selective role of SETDB1 in AML with granulo-monocytic differentiation and underscores its potential as a therapeutic target for current unmet needs.

Assessing next-generation sequencing-based computational methods for predicting transcriptional regulators with query gene sets

This article provides an in-depth review of computational methods for predicting transcriptional regulators (TRs) with query gene sets. Identification of TRs is of utmost importance in many biological applications, including but not limited to elucidating biological development mechanisms, identifying key disease genes, and predicting therapeutic targets. Various computational methods based on next-generation sequencing (NGS) data have been developed in the past decade, yet no systematic evaluation of NGS-based methods has been offered. We classified these methods into two categories based on shared characteristics, namely library-based and region-based methods. We further conducted benchmark studies to evaluate the accuracy, sensitivity, coverage, and usability of NGS-based methods with molecular experimental datasets. Results show that BART, ChIP-Atlas, and Lisa have relatively better performance. Besides, we point out the limitations of NGS-based methods and explore potential directions for further improvement.

Maternal high fat diet induces circadian clock-independent endocrine alterations impacting the metabolism of the offspring

Maternal obesity has long-term effects on offspring metabolic health. Among the potential mechanisms, prior research has indicated potential disruptions in circadian rhythms and gut microbiota in the offspring. To challenge this hypothesis, we implemented a maternal high fat diet regimen before and during pregnancy, followed by a standard diet after birth. Our findings confirm that maternal obesity impacts offspring birth weight and glucose and lipid metabolisms. However, we found minimal impact on circadian rhythms and microbiota that are predominantly driven by the feeding/fasting cycle. Notably, maternal obesity altered rhythmic liver gene expression, affecting mitochondrial function and inflammatory response without disrupting the hepatic circadian clock. These changes could be explained by a masculinization of liver gene expression similar to the changes observed in polycystic ovarian syndrome. Intriguingly, such alterations seem to provide the first-generation offspring with a degree of protection against obesity when exposed to a high fat diet.

Citrate metabolism controls the senescent microenvironment via the remodeling of pro-inflammatory enhancers

The senescent microenvironment and aged cells per se contribute to tissue remodeling, chronic inflammation, and age-associated dysfunction. However, the metabolic and epigenomic bases of the senescence-associated secretory phenotype (SASP) remain largely unknown. Here, we show that ATP-citrate lyase (ACLY), a key enzyme in acetyl-coenzyme A (CoA) synthesis, is essential for the pro-inflammatory SASP, independent of persistent growth arrest in senescent cells. Citrate-derived acetyl-CoA facilitates the action of SASP gene enhancers. ACLY-dependent de novo enhancers augment the recruitment of the chromatin reader BRD4, which causes SASP activation. Consistently, specific inhibitions of the ACLY-BRD4 axis suppress the STAT1-mediated interferon response, creating the pro-inflammatory microenvironment in senescent cells and tissues. Our results demonstrate that ACLY-dependent citrate metabolism represents a selective target for controlling SASP designed to promote healthy aging.

NFκB dynamics-dependent epigenetic changes modulate inflammatory gene expression and induce cellular senescence

Upregulation of nuclear factor κB (NFκB) signaling is a hallmark of aging and a major cause of age-related chronic inflammation. However, its effect on cellular senescence remains unclear. Here, we show that alteration of NFκB nuclear dynamics from oscillatory to sustained by depleting a negative feedback regulator of NFκB pathway, NFκB inhibitor alpha (IκBα), in the presence of tumor necrosis factor α (TNFα) promotes cellular senescence. Sustained NFκB activity enhanced inflammatory gene expression through increased NFκB-DNA binding and slowed the cell cycle. IκBα protein was decreased under replicative or oxidative stress in vitro. Furthermore, a decrease in IκBα protein and an increase in DNA-NFκB binding at the transcription start sites of age-associated genes in aged mouse hearts suggested that nuclear NFκB dynamics may play a critical role in the progression of aging. Our study suggests that nuclear NFκB dynamics-dependent epigenetic changes regulated over time in a living system, possibly through a decrease in IκBα, enhance the expression of inflammatory genes to advance the cells to a senescent state.

An atlas of transcribed enhancers across helper T cell diversity for decoding human diseases

Transcribed enhancer maps can reveal nuclear interactions underpinning each cell type and connect specific cell types to diseases. Using a 5' single-cell RNA sequencing approach, we defined transcription start sites of enhancer RNAs and other classes of coding and noncoding RNAs in human CD4+ T cells, revealing cellular heterogeneity and differentiation trajectories. Integration of these datasets with single-cell chromatin profiles showed that active enhancers with bidirectional RNA transcription are highly cell type-specific and that disease heritability is strongly enriched in these enhancers. The resulting cell type-resolved multimodal atlas of bidirectionally transcribed enhancers, which we linked with promoters using fine-scale chromatin contact maps, enabled us to systematically interpret genetic variants associated with a range of immune-mediated diseases.

ChIP-Atlas 3.0: a data-mining suite to explore chromosome architecture together with large-scale regulome data

ChIP-Atlas (https://chip-atlas.org/) presents a suite of data-mining tools for analyzing epigenomic landscapes, powered by the comprehensive integration of over 376 000 public ChIP-seq, ATAC-seq, DNase-seq and Bisulfite-seq experiments from six representative model organisms. To unravel the intricacies of chromatin architecture that mediates the regulome-initiated generation of transcriptional and phenotypic diversity within cells, we report ChIP-Atlas 3.0 that enhances clarity by incorporating additional tracks for genomic and epigenomic features within a newly consolidated 'annotation track' section. The tracks include chromosomal conformation (Hi-C and eQTL datasets), transcriptional regulatory elements (ChromHMM and FANTOM5 enhancers), and genomic variants associated with diseases and phenotypes (GWAS SNPs and ClinVar variants). These annotation tracks are easily accessible alongside other experimental tracks, facilitating better elucidation of chromatin architecture underlying the diversification of transcriptional and phenotypic traits. Furthermore, 'Diff Analysis,' a new online tool, compares the query epigenome data to identify differentially bound, accessible, and methylated regions using ChIP-seq, ATAC-seq and DNase-seq, and Bisulfite-seq datasets, respectively. The integration of annotation tracks and the Diff Analysis tool, coupled with continuous data expansion, renders ChIP-Atlas 3.0 a robust resource for mining the landscape of transcriptional regulatory mechanisms, thereby offering valuable perspectives, particularly for genetic disease research and drug discovery.

BRD9 regulates normal human hematopoietic stem cell function and lineage differentiation

Bromodomain containing protein 9 (BRD9), a member of the non-canonical BRG1/BRM-associated factor (ncBAF) chromatin remodeling complex, has been implicated as a synthetic lethal target in AML but its function in normal human hematopoiesis is unknown. In hematopoietic stem and progenitor cells (HSPC) genomic or chemical inhibition of BRD9 led to a proliferative disadvantage and loss of stem cells in vitro. Human HSPCs with reduced BRD9 protein levels produced lower numbers of immature mixed multipotent GEMM colonies in semi-solid media. In lineage-promoting culture conditions, cells with reduced BRD9 levels failed to differentiate into the megakaryocytic lineage and showed delayed differentiation into erythroid cells but enhanced terminal myeloid differentiation. HSPCs with BRD9 knock down (KD) had reduced long-term multilineage engraftment in a xenotransplantation assay. An increased number of downregulated genes in RNAseq analysis after BRD9 KD coupled with a gain in chromatin accessibility at the promoters of several repressive transcription factors (TF) suggest that BRD9 functions in the maintenance of active transcription during HSC differentiation. In particular, the hematopoietic master regulator GATA1 was identified as one of the core TFs regulating the gene networks modulated by BRD9 loss in HSPCs. BRD9 inhibition reduced a GATA1-luciferase reporter signal, further suggesting a role for BRD9 in regulating GATA1 activity. BRD9 is therefore an additional example of epigenetic regulation of human hematopoiesis.

TRIM33 plays a critical role in regulating dendritic cell differentiation and homeostasis by modulating Irf8 and Bcl2l11 transcription

The development of distinct dendritic cell (DC) subsets, namely, plasmacytoid DCs (pDCs) and conventional DC subsets (cDC1s and cDC2s), is controlled by specific transcription factors. IRF8 is essential for the fate specification of cDC1s. However, how the expression of Irf8 is regulated is not fully understood. In this study, we identified TRIM33 as a critical regulator of DC differentiation and maintenance. TRIM33 deletion in Trim33fl/fl Cre-ERT2 mice significantly impaired DC differentiation from hematopoietic progenitors at different developmental stages. TRIM33 deficiency downregulated the expression of multiple genes associated with DC differentiation in these progenitors. TRIM33 promoted the transcription of Irf8 to facilitate the differentiation of cDC1s by maintaining adequate CDK9 and Ser2 phosphorylated RNA polymerase II (S2 Pol II) levels at Irf8 gene sites. Moreover, TRIM33 prevented the apoptosis of DCs and progenitors by directly suppressing the PU.1-mediated transcription of Bcl2l11, thereby maintaining DC homeostasis. Taken together, our findings identified TRIM33 as a novel and crucial regulator of DC differentiation and maintenance through the modulation of Irf8 and Bcl2l11 expression. The finding that TRIM33 functions as a critical regulator of both DC differentiation and survival provides potential benefits for devising DC-based immune interventions and therapies.

Cell Type- and Age-Specific Expression of lncRNAs across Kidney Cell Types

Key Points

Background

Accumulated evidence demonstrates that long noncoding RNAs (lncRNAs) regulate cell differentiation and homeostasis, influencing kidney aging and disease. Despite their versatility, the function of lncRNA remains poorly understood because of the lack of a reference map of lncRNA transcriptome in various cell types.

Methods

In this study, we used a targeted single-cell RNA sequencing method to enrich and characterize lncRNAs in individual cells. We applied this method to various mouse tissues, including normal and aged kidneys.

Results

Through tissue-specific clustering analysis, we identified cell type–specific lncRNAs that showed a high correlation with known cell-type marker genes. Furthermore, we constructed gene regulatory networks to explore the functional roles of differentially expressed lncRNAs in each cell type. In the kidney, we observed dynamic expression changes of lncRNAs during aging, with specific changes in glomerular cells. These cell type– and age-specific expression patterns of lncRNAs suggest that lncRNAs may have a potential role in regulating cellular processes, such as immune response and energy metabolism, during kidney aging.

Conclusions

Our study sheds light on the comprehensive landscape of lncRNA expression and function and provides a valuable resource for future analysis of lncRNAs (https://gist-fgl.github.io/sc-lncrna-atlas/).

Differential role of glucocorticoid receptor based on its cell type specific expression on tumor cells and infiltrating lymphocytes

BACKGROUND

The glucocorticoid receptor (GR) is frequently expressed in breast cancer (BC), and its prognostic implications are contingent on estrogen receptor (ER) status. To address conflicting reports and explore therapeutic potential, a GR signature (GRsig) independent of ER status was developed. We also investigated cell type-specific GR protein expression in BC tumor epithelial cells and infiltrating lymphocytes.

METHODS

GRsig was derived from Dexamethasone treated cell lines through a bioinformatic pipeline. Immunohistochemistry assessed GR protein expression. Associations between GRsig and tumor phenotypes (proliferation, cytolytic activity (CYT), immune cell distribution, and epithelial-to-mesenchymal transition (EMT) were explored in public datasets. Single-cell RNA sequencing data evaluated context-dependent GR roles, and a cell type-specific prognostic role was assessed in an independent BC cohort.

RESULTS

High GRsig levels were associated with a favorable prognosis across BC subtypes. Tumor-specific high GRsig correlated with lower proliferation, increased CYT, and anti-tumorigenic immune cells. Single-cell data analysis revealed higher GRsig expression in immune cells, negatively correlating with EMT while a positive correlation was observed with EMT primarily in tumor and stromal cells. Univariate and multivariate analyses demonstrated the robust and independent predictive capability of GRsig for favorable prognosis. GR protein expression on immune cells in triple-negative tumors indicated a favorable prognosis.

CONCLUSION

This study underscores the cell type-specific role of GR, where its expression on tumor cells is associated with aggressive features like EMT, while in infiltrating lymphocytes, it predicts a better prognosis, particularly within TNBC tumors. The GRsig emerges as a promising independent prognostic indicator across diverse BC subtypes.

The Strong Activation of p53 Tumor Suppressor Drives the Synthesis of the Enigmatic Isoform of DUSP13 Protein

The p53 tumor suppressor protein activates various sets of genes depending on its covalent modifications, which are controlled by the nature and intensity of cellular stress. We observed that actinomycin D and nutlin-3a (A + N) collaborate in inducing activating phosphorylation of p53. Our recent transcriptomic data demonstrated that these substances strongly synergize in the upregulation of DUSP13, a gene with an unusual pattern of expression, coding for obscure phosphatase having two isoforms, one expressed in the testes and the other in skeletal muscles. In cancer cells exposed to A + N, DUSP13 is expressed from an alternative promoter in the intron, resulting in the expression of an isoform named TMDP-L1. Luciferase reporter tests demonstrated that this promoter is activated by both endogenous and ectopically expressed p53. We demonstrated for the first time that mRNA expressed from this promoter actually produces the protein, which can be detected with Western blotting, in all examined cancer cell lines with wild-type p53 exposed to A + N. In some cell lines, it is also induced by clinically relevant camptothecin, by nutlin-3a acting alone, or by a combination of actinomycin D and other antagonists of p53-MDM2 interaction-idasanutlin or RG7112. This isoform, fused with green fluorescent protein, localizes in the perinuclear region of cells.

Calcineurin/NFATc1 pathway represses cellular cytotoxicity by modulating histone H3 expression

Excess amounts of histones in the cell induce mitotic chromosome loss and genomic instability, and are therefore detrimental to cell survival. In yeast, excess histones are degraded by the proteasome mediated via the DNA damage response factor Rad53. Histone expression, therefore, is tightly regulated at the protein level. Our understanding of the transcriptional regulation of histone genes is far from complete. In this study, we found that calcineurin inhibitor treatment increased histone protein levels, and that the transcription factor NFATc1 (nuclear factor of activated T cells 1) repressed histone transcription and acts downstream of the calcineurin. We further revealed that NFATc1 binds to the promoter regions of many histone genes and that histone transcription is downregulated in a manner dependent on intracellular calcium levels. Indeed, overexpression of histone H3 markedly inhibited cell proliferation. Taken together, these findings suggest that NFATc1 prevents the detrimental effects of histone H3 accumulation by inhibiting expression of histone at the transcriptional level.

asteRIa enables robust interaction modeling between chromatin modifications and epigenetic readers

Chromatin, the nucleoprotein complex consisting of DNA and histone proteins, plays a crucial role in regulating gene expression by controlling access to DNA. Chromatin modifications are key players in this regulation, as they help to orchestrate DNA transcription, replication, and repair. These modifications recruit epigenetic 'reader' proteins, which mediate downstream events. Most modifications occur in distinctive combinations within a nucleosome, suggesting that epigenetic information can be encoded in combinatorial chromatin modifications. A detailed understanding of how multiple modifications cooperate in recruiting such proteins has, however, remained largely elusive. Here, we integrate nucleosome affinity purification data with high-throughput quantitative proteomics and hierarchical interaction modeling to estimate combinatorial effects of chromatin modifications on protein recruitment. This is facilitated by the computational workflow asteRIa which combines hierarchical interaction modeling, stability-based model selection, and replicate-consistency checks for a stable estimation of Robust Interactions among chromatin modifications. asteRIa identifies several epigenetic reader candidates responding to specific interactions between chromatin modifications. For the polycomb protein CBX8, we independently validate our results using genome-wide ChIP-Seq and bisulphite sequencing datasets. We provide the first quantitative framework for identifying cooperative effects of chromatin modifications on protein binding.

Ras-dependent activation of BMAL2 regulates hypoxic metabolism in pancreatic cancer

To identify drivers of malignancy in human pancreatic ductal adenocarcinoma (PDAC), we performed regulatory network analysis on a large collection of expression profiles from laser capture microdissected samples of PDAC and benign precursors. We discovered that BMAL2 plays a role in the initiation, progression, post resection survival, and KRAS activity in PDAC. Functional analysis of BMAL2 target genes led us to hypothesize that it plays a role in regulating the response to hypoxia, a critical but poorly understood feature of PDAC physiology. Knockout of BMAL2 in multiple human PDAC cell lines revealed effects on viability and invasion, particularly under hypoxic conditions. Loss of BMAL2 also affected glycolysis and other metabolic processes. We found that BMAL2 directly regulates hypoxia-responsive target genes. We also found that BMAL2 is necessary for the stabilization of HIF1A upon exposure to hypoxia, but destabilizes HIF2A under hypoxia. These data demonstrate that BMAL2 is a master transcriptional regulator of hypoxia responses in PDAC and may serve as a long-sought molecular switch that distinguishes HIF1A- and HIF2A-dependent modes of hypoxic metabolism.

Protein acylations induced by a ketogenic diet demonstrate diverse patterns depending on organs and differ between histones and global proteins

An essential ketone body, β-hydroxybutyrate (BOHB), plays various roles in physiological regulations via protein acylations such as lysine acetylation and β-hydroxybutyrylation. Here, to understand how BOHB systemically regulates acylations from an overarching perspective, we administered a ketogenic diet to mice to increase BOHB concentration and examined acylations. We found that global acetylation and β-hydroxybutyrylation dramatically increase in various organs except for the brains, where the increase was much smaller than in the other organs. Interestingly, we observe no increase in histone acetylation in the organs where significant global protein acetylation occurs despite a substantial rise in histone β-hydroxybutyrylation. Finally, we compared the transcriptome data of the mice's liver after the ketogenic diet to the public databases, showing that upregulated genes are enriched in those related to histone β-hydroxybutyrylation in starvation. Our data indicate that a ketogenic diet induces diverse patterns of acylations depending on organs and protein localizations, suggesting that different mechanisms regulate acylations and that the ketogenic diet is associated with starvation in terms of protein modifications.

Placental co-transcriptional activator Vestigial-like 1 (VGLL1) drives tumorigenesis via increasing transcription of proliferation and invasion genes

Introduction

Vestigial-like 1 (VGLL1) is a co-transcriptional activator that binds to TEA domain-containing transcription factors (TEADs). Its expression is upregulated in a variety of aggressive cancer types, including pancreatic and basal-like breast cancer, and increased transcription of VGLL1 is strongly correlated with poor prognosis and decreased overall patient survival. In normal tissues, VGLL1 is most highly expressed within placental trophoblast cells, which share the common attributes of rapid cellular proliferation and invasion with tumor cells. The impact of VGLL1 in cancer has not been fully elucidated and no VGLL1-targeted therapy currently exists.

Methods

The aim of this study was to evaluate the cellular function and downstream genomic targets of VGLL1 in placental, pancreatic, and breast cancer cells. Functional assays were employed to assess the role of VGLL1 in cellular invasion and proliferation, and ChIP-seq and RNAseq assays were performed to identify VGLL1 target genes and potential impact using pathway analysis.

Results

ChIP-seq analysis identified eight transcription factors with a VGLL1-binding motif that were common between all three cell types, including TEAD1-4, AP-1, and GATA6, and revealed ~3,000 shared genes with which VGLL1 interacts. Furthermore, increased VGLL1 expression led to an enhancement of cell invasion and proliferation, which was supported by RNAseq analysis showing transcriptional changes in several genes known to be involved in these processes.

Discussion

This work expands our mechanistic understanding of VGLL1 function in tumor cells and provides a strong rationale for developing VGLL1-targeted therapies for treating cancer patients.

BIT: Bayesian Identification of Transcriptional Regulators

BIT is a novel Bayesian hierarchical model capable of predicting transcriptional regulators (TRs) from the input of user-provided epigenomic regions. TRs are critical molecules in transcriptional regulation. Many diseases and cancers are linked to the dysfunction of TRs. Knowing TRs in certain biological process can help find new biomarkers or therapeutic targets. Thus, BIT formulates a novel Bayesian hierarchical model with the Pólya-gamma data augmentation strategy. Based on collected ChIP-seq datasets, BIT can identify TRs responsible for the genome-wide binding pattern within the user-provided epigenomic regions. BIT has been validated by using a simulation study and three applications.

Inference of Gene Regulatory Networks Based on Multi-view Hierarchical Hypergraphs

Since gene regulation is a complex process in which multiple genes act simultaneously, accurately inferring gene regulatory networks (GRNs) is a long-standing challenge in systems biology. Although graph neural networks can formally describe intricate gene expression mechanisms, current GRN inference methods based on graph learning regard only transcription factor (TF)-target gene interactions as pairwise relationships, and cannot model the many-to-many high-order regulatory patterns that prevail among genes. Moreover, these methods often rely on limited prior regulatory knowledge, ignoring the structural information of GRNs in gene expression profiles. Therefore, we propose a multi-view hierarchical hypergraphs GRN (MHHGRN) inference model. Specifically, multiple heterogeneous biological information is integrated to construct multi-view hierarchical hypergraphs of TFs and target genes, using hypergraph convolution networks to model higher order complex regulatory relationships. Meanwhile, the coupled information diffusion mechanism and the cross-domain messaging mechanism facilitate the information sharing between genes to optimise gene embedding representations. Finally, a unique channel attention mechanism is used to adaptively learn feature representations from multiple views for GRN inference. Experimental results show that MHHGRN achieves better results than the baseline methods on the E. coli and S. cerevisiae benchmark datasets of the DREAM5 challenge, and it has excellent cross-species generalization, achieving comparable or better performance on scRNA-seq datasets from five mouse and two human cell lines.

CVGAE: A Self-Supervised Generative Method for Gene Regulatory Network Inference Using Single-Cell RNA Sequencing Data

Gene regulatory network (GRN) inference based on single-cell RNA sequencing data (scRNAseq) plays a crucial role in understanding the regulatory mechanisms between genes. Various computational methods have been employed for GRN inference, but their performance in terms of network accuracy and model generalization is not satisfactory, and their poor performance is caused by high-dimensional data and network sparsity. In this paper, we propose a self-supervised method for gene regulatory network inference using single-cell RNA sequencing data (CVGAE). CVGAE uses graph neural network for inductive representation learning, which merges gene expression data and observed topology into a low-dimensional vector space. The well-trained vectors will be used to calculate mathematical distance of each gene, and further predict interactions between genes. In overall framework, FastICA is implemented to relief computational complexity caused by high dimensional data, and CVGAE adopts multi-stacked GraphSAGE layers as an encoder and an improved decoder to overcome network sparsity. CVGAE is evaluated on several single cell datasets containing four related ground-truth networks, and the result shows that CVGAE achieve better performance than comparative methods. To validate learning and generalization capabilities, CVGAE is applied in few-shot environment by change the ratio of train set and test set. In condition of few-shot, CVGAE obtains comparable or superior performance.

Regulation of Myc transcription by an enhancer cluster dedicated to pluripotency and early embryonic expression

MYC plays various roles in pluripotent stem cells, including the promotion of somatic cell reprogramming to pluripotency, the regulation of cell competition and the control of embryonic diapause. However, how Myc expression is regulated in this context remains unknown. The Myc gene lies within a ~ 3-megabase gene desert with multiple cis-regulatory elements. Here we use genomic rearrangements, transgenesis and targeted mutation to analyse Myc regulation in early mouse embryos and pluripotent stem cells. We identify a topologically-associated region that homes enhancers dedicated to Myc transcriptional regulation in stem cells of the pre-implantation and early post-implantation embryo. Within this region, we identify elements exclusively dedicated to Myc regulation in pluripotent cells, with distinct enhancers that sequentially activate during naive and formative pluripotency. Deletion of pluripotency-specific enhancers dampens embryonic stem cell competitive ability. These results identify a topologically defined enhancer cluster dedicated to early embryonic expression and uncover a modular mechanism for the regulation of Myc expression in different states of pluripotency.

Functional dissection of complex and molecular trait variants at single nucleotide resolution

Identifying the causal variants and mechanisms that drive complex traits and diseases remains a core problem in human genetics. The majority of these variants have individually weak effects and lie in non-coding gene-regulatory elements where we lack a complete understanding of how single nucleotide alterations modulate transcriptional processes to affect human phenotypes. To address this, we measured the activity of 221,412 trait-associated variants that had been statistically fine-mapped using a Massively Parallel Reporter Assay (MPRA) in 5 diverse cell-types. We show that MPRA is able to discriminate between likely causal variants and controls, identifying 12,025 regulatory variants with high precision. Although the effects of these variants largely agree with orthogonal measures of function, only 69% can plausibly be explained by the disruption of a known transcription factor (TF) binding motif. We dissect the mechanisms of 136 variants using saturation mutagenesis and assign impacted TFs for 91% of variants without a clear canonical mechanism. Finally, we provide evidence that epistasis is prevalent for variants in close proximity and identify multiple functional variants on the same haplotype at a small, but important, subset of trait-associated loci. Overall, our study provides a systematic functional characterization of likely causal common variants underlying complex and molecular human traits, enabling new insights into the regulatory grammar underlying disease risk.

The genetic dissection of fetal haemoglobin persistence in sickle cell disease in Nigeria

The clinical severity of sickle cell disease (SCD) is strongly influenced by the level of fetal haemoglobin (HbF) persistent in each patient. Three major HbF loci (BCL11A, HBS1L-MYB, and Xmn1-HBG2) have been reported, but a considerable hidden heritability remains. We conducted a genome-wide association study for HbF levels in 1006 Nigerian patients with SCD (HbSS/HbSβ0), followed by a replication and meta-analysis exercise in four independent SCD cohorts (3,582 patients). To dissect association signals at the major loci, we performed stepwise conditional and haplotype association analyses and included public functional annotation datasets. Association signals were detected for BCL11A (lead SNP rs6706648, β = -0.39, P = 4.96 × 10-34) and HBS1L-MYB (lead SNP rs61028892, β = 0.73, P = 1.18 × 10-9), whereas the variant allele for Xmn1-HBG2 was found to be very rare. In addition, we detected three putative new trait-associated regions. Genetically, dissecting the two major loci BCL11A and HBS1L-MYB, we defined trait-increasing haplotypes (P < 0.0001) containing so far unidentified causal variants. At BCL11A, in addition to a haplotype harbouring the putative functional variant rs1427407-'T', we identified a second haplotype, tagged by the rs7565301-'A' allele, where a yet-to-be-discovered causal DNA variant may reside. Similarly, at HBS1L-MYB, one HbF-increasing haplotype contains the likely functional small indel rs66650371, and a second tagged by rs61028892-'C' is likely to harbour a presently unknown functional allele. Together, variants at BCL11A and HBS1L-MYB SNPs explained 24.1% of the trait variance. Our findings provide a path for further investigation of the causes of variable fetal haemoglobin persistence in sickle cell disease.

Inferring gene regulatory networks from single-cell transcriptomics based on graph embedding

MOTIVATION

Gene regulatory networks (GRNs) encode gene regulation in living organisms, and have become a critical tool to understand complex biological processes. However, due to the dynamic and complex nature of gene regulation, inferring GRNs from scRNA-seq data is still a challenging task. Existing computational methods usually focus on the close connections between genes, and ignore the global structure and distal regulatory relationships.

RESULTS

In this study, we develop a supervised deep learning framework, IGEGRNS, to infer GRNs from scRNA-seq data based on graph embedding. In the framework, contextual information of genes is captured by GraphSAGE, which aggregates gene features and neighborhood structures to generate low-dimensional embedding for genes. Then, the k most influential nodes in the whole graph are filtered through Top-k pooling. Finally, potential regulatory relationships between genes are predicted by stacking CNNs. Compared with nine competing supervised and unsupervised methods, our method achieves better performance on six time-series scRNA-seq datasets.

AVAILABILITY AND IMPLEMENTATION

Our method IGEGRNS is implemented in Python using the Pytorch machine learning library, and it is freely available at https://github.com/DHUDBlab/IGEGRNS.

The Long Non-Coding RNA Gene AC027288.3 Plays a Role in Human Endometrial Stromal Fibroblast Decidualization

During the secretory phase of the menstrual cycle, endometrial fibroblast cells begin to change into large epithelial-like cells called decidual cells in a process called decidualization. This differentiation continues more broadly in the endometrium and forms the decidual tissue during early pregnancy. The cells undergoing decidualization as well as the resulting decidual cells, support successful implantation and placentation during early pregnancy. This study was carried out to identify new potentially important long non-coding RNA (lncRNA) genes that may play a role in human endometrial stromal fibroblast cells (hESF) undergoing decidualization in vitro, and several were found. The expression of nine was further characterized. One of these, AC027288.3, showed a dramatic increase in the expression of hESF cells undergoing decidualization. When AC027288.3 expression was targeted, the ability of the cells to undergo decidualization as determined by the expression of decidualization marker protein-coding genes was significantly altered. The most affected markers of decidualization whose expression was significantly reduced were FOXO1, FZD4, and INHBA. Therefore, AC027288.3 may be a major upstream regulator of the WNT-FOXO1 pathway and activin-SMAD3 pathways previously shown as critical for hESF decidualization. Finally, we explored possible regulators of AC027288.3 expression during human ESF decidualization. Expression was regulated by cAMP and progesterone. Our results suggest that AC027288.3 plays a role in hESF decidualization and identifies several other lncRNA genes that may also play a role.

Chromatin accessibility during human first-trimester neurodevelopment

The human brain develops through a tightly organized cascade of patterning events, induced by transcription factor expression and changes in chromatin accessibility. Although gene expression across the developing brain has been described at single-cell resolution1, similar atlases of chromatin accessibility have been primarily focused on the forebrain2-4. Here we describe chromatin accessibility and paired gene expression across the entire developing human brain during the first trimester (6-13 weeks after conception). We defined 135 clusters and used multiomic measurements to link candidate cis-regulatory elements to gene expression. The number of accessible regions increased both with age and along neuronal differentiation. Using a convolutional neural network, we identified putative functional transcription factor-binding sites in enhancers characterizing neuronal subtypes. We applied this model to cis-regulatory elements linked to ESRRB to elucidate its activation mechanism in the Purkinje cell lineage. Finally, by linking disease-associated single nucleotide polymorphisms to cis-regulatory elements, we validated putative pathogenic mechanisms in several diseases and identified midbrain-derived GABAergic neurons as being the most vulnerable to major depressive disorder-related mutations. Our findings provide a more detailed view of key gene regulatory mechanisms underlying the emergence of brain cell types during the first trimester and a comprehensive reference for future studies related to human neurodevelopment.

Analysis of blood methylation quantitative trait loci in East Asians reveals ancestry-specific impacts on complex traits

Methylation quantitative trait loci (mQTLs) are essential for understanding the role of DNA methylation changes in genetic predisposition, yet they have not been fully characterized in East Asians (EAs). Here we identified mQTLs in whole blood from 3,523 Chinese individuals and replicated them in additional 1,858 Chinese individuals from two cohorts. Over 9% of mQTLs displayed specificity to EAs, facilitating the fine-mapping of EA-specific genetic associations, as shown for variants associated with height. Trans-mQTL hotspots revealed biological pathways contributing to EA-specific genetic associations, including an ERG-mediated 233 trans-mCpG network, implicated in hematopoietic cell differentiation, which likely reflects binding efficiency modulation of the ERG protein complex. More than 90% of mQTLs were shared between different blood cell lineages, with a smaller fraction of lineage-specific mQTLs displaying preferential hypomethylation in the respective lineages. Our study provides new insights into the mQTL landscape across genetic ancestries and their downstream effects on cellular processes and diseases/traits.

A 50-gene biomarker identifies estrogen receptor-modulating chemicals in a microarray compendium

High throughput transcriptomics (HTTr) profiling has the potential to rapidly and comprehensively identify molecular targets of environmental chemicals that can be linked to adverse outcomes. We describe here the construction and characterization of a 50-gene expression biomarker designed to identify estrogen receptor (ER) active chemicals in HTTr datasets. Using microarray comparisons, the genes in the biomarker were identified as those that exhibited consistent directional changes when ER was activated (4 ER agonists; 4 ESR1 gene constitutively active mutants) and opposite directional changes when ER was suppressed (4 antagonist treatments; 4 ESR1 knockdown experiments). The biomarker was evaluated as a predictive tool using the Running Fisher algorithm by comparison to annotated gene expression microarray datasets including those evaluating the transcriptional effects of hormones and chemicals in MCF-7 cells. Depending on the reference dataset used, the biomarker had a predictive accuracy for activation of up to 96%. To demonstrate applicability for HTTr data analysis, the biomarker was used to identify ER activators in a set of 15 chemicals that are considered potential bisphenol A (BPA) alternatives examined at up to 10 concentrations in MCF-7 cells and analyzed by full-genome TempO-Seq. Using benchmark dose (BMD) modeling, the biomarker genes stratified the ER potency of BPA alternatives consistent with previous studies. These results demonstrate that the ER biomarker can be used to accurately identify ER activators in transcript profile data derived from MCF-7 cells.

Her2 amplification, Rel-A, and Bach1 can influence APOBEC3A expression in breast cancer cells

APOBEC-induced mutations occur in 50% of sequenced human tumors, with APOBEC3A (A3A) being a major contributor to mutagenesis in breast cancer cells. The mechanisms that cause A3A activation and mutagenesis in breast cancers are still unknown. Here, we describe factors that influence basal A3A mRNA transcript levels in breast cancer cells. We found that basal A3A mRNA correlates with A3A protein levels and predicts the amount of APOBEC signature mutations in a panel of breast cancer cell lines, indicating that increased basal transcription may be one mechanism leading to breast cancer mutagenesis. We also show that alteration of ERBB2 expression can drive A3A mRNA levels, suggesting the enrichment of the APOBEC mutation signature in Her2-enriched breast cancer could in part result from elevated A3A transcription. Hierarchical clustering of transcripts in primary breast cancers determined that A3A mRNA was co-expressed with other genes functioning in viral restriction and interferon responses. However, reduction of STAT signaling via inhibitors or shRNA in breast cancer cell lines had only minor impact on A3A abundance. Analysis of single cell RNA-seq from primary tumors indicated that A3A mRNA was highest in infiltrating immune cells within the tumor, indicating that correlations of A3A with STAT signaling in primary tumors may be result from higher immune infiltrates and are not reflective of STAT signaling controlling A3A expression in breast cancer cells. Analysis of ATAC-seq data in multiple breast cancer cell lines identified two transcription factor sites in the APOBEC3A promoter region that could promote A3A transcription. We determined that Rel-A, and Bach1, which have binding sites in these peaks, elevated basal A3A expression. Our findings highlight a complex and variable set of transcriptional activators for A3A in breast cancer cells.

The c.1617del variant of TMEM260 is identified as the most frequent single gene determinant for Japanese patients with a specific type of congenital heart disease

Although the molecular mechanisms underlying congenital heart disease (CHD) remain poorly understood, recent advances in genetic analysis have facilitated the exploration of causative genes for CHD. We reported that the pathogenic variant c.1617del of TMEM260, which encodes a transmembrane protein, is highly associated with CHD, specifically persistent truncus arteriosus (PTA), the most severe cardiac outflow tract (OFT) defect. Using whole-exome sequencing, the c.1617del variant was identified in two siblings with PTA in a Japanese family and in three of the 26 DNAs obtained from Japanese individuals with PTA. The c.1617del of TMEM260 has been found only in East Asians, especially Japanese and Korean populations, and the frequency of this variant in PTA is estimated to be next to that of the 22q11.2 deletion, the most well-known genetic cause of PTA. Phenotype of patients with c.1617del appears to be predominantly in the heart, although TMEM260 is responsible for structural heart defects and renal anomalies syndrome (SHDRA). The mouse TMEM260 variant (p.W535Cfs*56), synonymous with the human variant (p.W539Cfs*9), exhibited truncation and downregulation by western blotting, and aggregation by immunocytochemistry. In situ hybridization demonstrated that Tmem260 is expressed ubiquitously during embryogenesis, including in the development of cardiac OFT implicated in PTA. This expression may be regulated by a ~ 0.8 kb genomic region in intron 3 of Tmem260 that includes multiple highly conserved binding sites for essential cardiac transcription factors, thus revealing that the c.1617del variant of TMEM260 is the major single-gene variant responsible for PTA in the Japanese population.

E2F transcription factors promote tumorigenicity in pancreatic ductal adenocarcinoma

BACKGROUND

Pancreatic ductal adenocarcinoma (PDAC) is one of the most lethal cancers with limited treatment options, illustrating an urgent need to identify new drugable targets in PDACs.

OBJECTIVE

Using the similarities between tumor development and normal embryonic development, which is accompanied by rapid cell expansion, we aimed to identify and characterize embryonic signaling pathways that were reinitiated during tumor formation and expansion.

METHODS AND RESULTS

Here, we report that the transcription factors E2F1 and E2F8 are potential key regulators in PDAC. E2F1 and E2F8 RNA expression is mainly localized in proliferating cells in the developing pancreas and in malignant ductal cells in PDAC. Silencing of E2F1 and E2F8 in PANC-1 pancreatic tumor cells inhibited cell proliferation and impaired cell spreading and migration. Moreover, loss of E2F1 also affected cell viability and apoptosis with E2F expression in PDAC tissues correlating with expression of apoptosis and mitosis pathway genes, suggesting that E2F factors promote cell cycle regulation and tumorigenesis in PDAC cells.

CONCLUSION

Our findings illustrate that E2F1 and E2F8 transcription factors are expressed in pancreatic progenitor and PDAC cells, where they contribute to tumor cell expansion by regulation of cell proliferation, viability, and cell migration making these genes attractive therapeutic targets and potential prognostic markers for pancreatic cancer.

Identification of a chromatin-bound ERRα interactome network in mouse liver

OBJECTIVES

Estrogen-related-receptor α (ERRα) plays a critical role in the transcriptional regulation of cellular bioenergetics and metabolism, and perturbations in its activity have been associated with metabolic diseases. While several coactivators and corepressors of ERRα have been identified to date, a knowledge gap remains in understanding the extent to which ERRα cooperates with coregulators in the control of gene expression. Herein, we mapped the primary chromatin-bound ERRα interactome in mouse liver.

METHODS

RIME (Rapid Immuno-precipitation Mass spectrometry of Endogenous proteins) analysis using mouse liver samples from two circadian time points was used to catalog ERRα-interacting proteins on chromatin. The genomic crosstalk between ERRα and its identified cofactors in the transcriptional control of precise gene programs was explored through cross-examination of genome-wide binding profiles from chromatin immunoprecipitation-sequencing (ChIP-seq) studies. The dynamic interplay between ERRα and its newly uncovered cofactor Host cell factor C1 (HCFC1) was further investigated by loss-of-function studies in hepatocytes.

RESULTS

Characterization of the hepatic ERRα chromatin interactome led to the identification of 48 transcriptional interactors of which 42 were previously unknown including HCFC1. Interrogation of available ChIP-seq binding profiles highlighted oxidative phosphorylation (OXPHOS) under the control of a complex regulatory network between ERRα and multiple cofactors. While ERRα and HCFC1 were found to bind to a large set of common genes, only a small fraction showed their colocalization, found predominately near the transcriptional start sites of genes particularly enriched for components of the mitochondrial respiratory chain. Knockdown studies demonstrated inverse regulatory actions of ERRα and HCFC1 on OXPHOS gene expression ultimately dictating the impact of their loss-of-function on mitochondrial respiration.

CONCLUSIONS

Our work unveils a repertoire of previously unknown transcriptional partners of ERRα comprised of chromatin modifiers and transcription factors thus advancing our knowledge of how ERRα regulates metabolic transcriptional programs.

Histone proteoform analysis reveals epigenetic changes in adult mouse brown adipose tissue in response to cold stress

BACKGROUND

Regulation of the thermogenic response by brown adipose tissue (BAT) is an important component of energy homeostasis with implications for the treatment of obesity and diabetes. Our preliminary analyses of RNA-Seq data uncovered many nodes representing epigenetic modifiers that are altered in BAT in response to chronic thermogenic activation. Thus, we hypothesized that chronic thermogenic activation broadly alters epigenetic modifications of DNA and histones in BAT.

RESULTS

Motivated to understand how BAT function is regulated epigenetically, we developed a novel method for the first-ever unbiased top-down proteomic quantitation of histone modifications in BAT and validated our results with a multi-omic approach. To test our hypothesis, wildtype male C57BL/6J mice were housed under chronic conditions of thermoneutral temperature (TN, 28°C), mild cold/room temperature (RT, 22°C), or severe cold (SC, 8°C) and BAT was analyzed for DNA methylation and histone modifications. Methylation of promoters and intragenic regions in genomic DNA decrease in response to chronic cold exposure. Integration of DNA methylation and RNA expression datasets suggest a role for epigenetic modification of DNA in regulation of gene expression in response to cold. In response to cold housing, we observe increased bulk acetylation of histones H3.2 and H4, increased histone H3.2 proteoforms with di- and trimethylation of lysine 9 (K9me2 and K9me3), and increased histone H4 proteoforms with acetylation of lysine 16 (K16ac) in BAT.

CONCLUSIONS

Our results reveal global epigenetically-regulated transcriptional "on" and "off" signals in murine BAT in response to varying degrees of chronic cold stimuli and establish a novel methodology to quantitatively study histones in BAT, allowing for direct comparisons to decipher mechanistic changes during the thermogenic response. Additionally, we make histone PTM and proteoform quantitation, RNA splicing, RRBS, and transcriptional footprint datasets available as a resource for future research.

Cell non-autonomous control of autophagy and metabolism by glial cells

Glia are the protectors of the nervous system, providing neurons with support and protection from cytotoxic insults. We previously discovered that four astrocyte-like glia can regulate organismal proteostasis and longevity in C. elegans. Expression of the UPRER transcription factor, XBP-1s, in these glia increases stress resistance, and longevity, and activates the UPRER in intestinal cells via neuropeptides. Autophagy, a key regulator of metabolism and aging, has been described as a cell autonomous process. Surprisingly, we find that glial XBP-1s enhances proteostasis and longevity by cell non-autonomously reprogramming organismal lipid metabolism and activating autophagy. Glial XBP-1s regulates the activation of another transcription factor, HLH-30/TFEB, in the intestine. HLH-30 activates intestinal autophagy, increases intestinal lipid catabolism, and upregulates a robust transcriptional program. Our study reveals a novel role for glia in regulating peripheral lipid metabolism, autophagy, and organellar health through peripheral activation of HLH-30 and autophagy.

scGREAT: Transformer-based deep-language model for gene regulatory network inference from single-cell transcriptomics

Gene regulatory networks (GRNs) involve complex and multi-layer regulatory interactions between regulators and their target genes. Precise knowledge of GRNs is important in understanding cellular processes and molecular functions. Recent breakthroughs in single-cell sequencing technology made it possible to infer GRNs at single-cell level. Existing methods, however, are limited by expensive computations, and sometimes simplistic assumptions. To overcome these obstacles, we propose scGREAT, a framework to infer GRN using gene embeddings and transformer from single-cell transcriptomics. scGREAT starts by constructing gene expression and gene biotext dictionaries from scRNA-seq data and gene text information. The representation of TF gene pairs is learned through optimizing embedding space by transformer-based engine. Results illustrated scGREAT outperformed other contemporary methods on benchmarks. Besides, gene representations from scGREAT provide valuable gene regulation insights, and external validation on spatial transcriptomics illuminated the mechanism behind scGREAT annotation. Moreover, scGREAT identified several TF target regulations corroborated in studies.

Widespread variation in molecular interactions and regulatory properties among transcription factor isoforms

Most human Transcription factors (TFs) genes encode multiple protein isoforms differing in DNA binding domains, effector domains, or other protein regions. The global extent to which this results in functional differences between isoforms remains unknown. Here, we systematically compared 693 isoforms of 246 TF genes, assessing DNA binding, protein binding, transcriptional activation, subcellular localization, and condensate formation. Relative to reference isoforms, two-thirds of alternative TF isoforms exhibit differences in one or more molecular activities, which often could not be predicted from sequence. We observed two primary categories of alternative TF isoforms: "rewirers" and "negative regulators", both of which were associated with differentiation and cancer. Our results support a model wherein the relative expression levels of, and interactions involving, TF isoforms add an understudied layer of complexity to gene regulatory networks, demonstrating the importance of isoform-aware characterization of TF functions and providing a rich resource for further studies.

FOXO1 promotes cancer cell growth through MDM2-mediated p53 degradation

FOXO1 is a transcription factor and potential tumor suppressor that is negatively regulated downstream of PI3K-PKB/AKT signaling. Paradoxically, FOXO also promotes tumor growth, but the detailed mechanisms behind this role of FOXO are not fully understood. In this study, we revealed a molecular cascade by which the Thr24 residue of FOXO1 is phosphorylated by AKT and is dephosphorylated by calcineurin, which is a Ca2+-dependent protein phosphatase. Curiously, single nucleotide somatic mutations of FOXO1 in cancer occur frequently at and near Thr24. Using a calcineurin inhibitor and shRNA directed against calcineurin, we revealed that calcineurin-mediated dephosphorylation of Thr24 regulates FOXO1 protein stability. We also found that FOXO1 binds to the promoter region of MDM2 and activates transcription, which in turn promotes MDM2-mediated ubiquitination and degradation of p53. FOXO3a and FOXO4 are shown to control p53 activity; however, the significance of FOXO1 in p53 regulation remains largely unknown. Supporting this notion, FOXO1 depletion increased p53 and p21 protein levels in association with the inhibition of cell proliferation. Taken together, these results indicate that FOXO1 is stabilized by calcineurin-mediated dephosphorylation and that FOXO1 supports cancer cell proliferation by promoting MDM2 transcription and subsequent p53 degradation.

Mitochondrial S-adenosylmethionine deficiency induces mitochondrial unfolded protein response and extends lifespan in Caenorhabditis elegans

S-adenosylmethionine (SAM), generated from methionine and ATP by S-adenosyl methionine synthetase (SAMS), is the universal methyl group donor required for numerous cellular methylation reactions. In Caenorhabditis elegans, silencing sams-1, the major isoform of SAMS, genetically or via dietary restriction induces a robust mitochondrial unfolded protein response (UPRmt) and lifespan extension. In this study, we found that depleting SAMS-1 markedly decreases mitochondrial SAM levels. Moreover, RNAi knockdown of SLC-25A26, a carrier protein responsible for transporting SAM from the cytoplasm into the mitochondria, significantly lowers the mitochondrial SAM levels and activates UPRmt, suggesting that the UPRmt induced by sams-1 mutations might result from disrupted mitochondrial SAM homeostasis. Through a genetic screen, we then identified a putative mitochondrial tRNA methyltransferase TRMT-10C.2 as a major downstream effector of SAMS-1 to regulate UPRmt and longevity. As disruption of mitochondrial tRNA methylation likely leads to impaired mitochondrial tRNA maturation and consequently reduced mitochondrial translation, our findings suggest that depleting mitochondrial SAM level might trigger UPRmt via attenuating protein translation in the mitochondria. Together, this study has revealed a potential mechanism by which SAMS-1 regulates UPRmt and longevity.

Transcriptomic and proteomic study of cancer cell lines exposed to actinomycin D and nutlin-3a reveals numerous, novel candidates for p53-regulated genes

Transcriptomic analyses have revealed hundreds of p53-regulated genes; however, these studies used a limited number of cell lines and p53-activating agents. Therefore, we searched for candidate p53-target genes by employing stress factors and cell lines never before used in a high-throughput search for p53-regulated genes. We performed RNA-Seq on A549 cells exposed to camptothecin, actinomycin D, nutlin-3a, as well as a combination of actinomycin D and nutlin-3a (A + N). The latter two substances synergise upon the activation of selected p53-target genes. A similar analysis was performed on other cell lines (U-2 OS, NCI-H460, A375) exposed to A + N. To identify proteins in cell lysates or those secreted into a medium of A549 cells in control conditions or treated with A + N, we employed mass spectrometry. The expression of selected genes strongly upregulated by A + N or camptothecin was examined by RT-PCR in p53-deficient cells and their controls. We found that p53 participates in the upregulation of: ACP5, APOL3, CDH3, CIBAR2, CRABP2, CTHRC1, CTSH, FAM13C, FBXO2, FRMD8, FRZB, GAST, ICOSLG, KANK3, KCNK6, KLRG2, MAFB, MR1, NDRG4, PTAFR, RETSAT, TMEM52, TNFRSF14, TRANK1, TYSND1, WFDC2, WFDC5, WNT4 genes. Twelve of these proteins were detected in the secretome and/or proteome of treated cells. Our data generated new hypotheses concerning the functioning of p53. Many genes activated by A + N or camptothecin are also activated by interferons, indicating a noticeable overlap between transcriptional programs of p53 and these antiviral cytokines. Moreover, several identified genes code for antagonists of WNT/β-catenin signalling pathways, which suggests new connections between these two cancer-related signalling systems. One of these antagonists is DRAXIN. Previously, we found that its gene is activated by p53. In this study, using mass spectrometry and Western blotting, we detected expression of DRAXIN in a medium of A549 cells exposed to A + N. Thus, this protein functions not only in the development of the nervous system, but it may also have a new cancer-related function.

Remodeling of the postsynaptic proteome in male mice and marmosets during synapse development

Postsynaptic proteins play crucial roles in synaptic function and plasticity. During brain development, alterations in synaptic number, shape, and stability occur, known as synapse maturation. However, the postsynaptic protein composition changes during development are not fully understood. Here, we show the trajectory of the postsynaptic proteome in developing male mice and common marmosets. Proteomic analysis of mice at 2, 3, 6, and 12 weeks of age shows that proteins involved in synaptogenesis are differentially expressed during this period. Analysis of published transcriptome datasets shows that the changes in postsynaptic protein composition in the mouse brain after 2 weeks of age correlate with gene expression changes. Proteomic analysis of marmosets at 0, 2, 3, 6, and 24 months of age show that the changes in the marmoset brain can be categorized into two parts: the first 2 months and after that. The changes observed in the first 2 months are similar to those in the mouse brain between 2 and 12 weeks of age. The changes observed in marmoset after 2 months old include differential expression of synaptogenesis-related molecules, which hardly overlap with that in mice. Our results provide a comprehensive proteomic resource that underlies developmental synapse maturation in rodents and primates.

Assessing NGS-based computational methods for predicting transcriptional regulators with query gene sets

This article provides an in-depth review of computational methods for predicting transcriptional regulators with query gene sets. Identification of transcriptional regulators is of utmost importance in many biological applications, including but not limited to elucidating biological development mechanisms, identifying key disease genes, and predicting therapeutic targets. Various computational methods based on next-generation sequencing (NGS) data have been developed in the past decade, yet no systematic evaluation of NGS-based methods has been offered. We classified these methods into two categories based on shared characteristics, namely library-based and region-based methods. We further conducted benchmark studies to evaluate the accuracy, sensitivity, coverage, and usability of NGS-based methods with molecular experimental datasets. Results show that BART, ChIP-Atlas, and Lisa have relatively better performance. Besides, we point out the limitations of NGS-based methods and explore potential directions for further improvement.

Key points

An introduction to available computational methods for predicting functional TRs from a query gene set.A detailed walk-through along with practical concerns and limitations.A systematic benchmark of NGS-based methods in terms of accuracy, sensitivity, coverage, and usability, using 570 TR perturbation-derived gene sets.NGS-based methods outperform motif-based methods. Among NGS methods, those utilizing larger databases and adopting region-centric approaches demonstrate favorable performance. BART, ChIP-Atlas, and Lisa are recommended as these methods have overall better performance in evaluated scenarios.

Trans-omic analysis reveals opposite metabolic dysregulation between feeding and fasting in liver associated with obesity

Dysregulation of liver metabolism associated with obesity during feeding and fasting leads to the breakdown of metabolic homeostasis. However, the underlying mechanism remains unknown. Here, we measured multi-omics data in the liver of wild-type and leptin-deficient obese (ob/ob) mice at ad libitum feeding and constructed a differential regulatory trans-omic network of metabolic reactions. We compared the trans-omic network at feeding with that at 16 h fasting constructed in our previous study. Intermediate metabolites in glycolytic and nucleotide metabolism decreased in ob/ob mice at feeding but increased at fasting. Allosteric regulation reversely shifted between feeding and fasting, generally showing activation at feeding while inhibition at fasting in ob/ob mice. Transcriptional regulation was similar between feeding and fasting, generally showing inhibiting transcription factor regulations and activating enzyme protein regulations in ob/ob mice. The opposite metabolic dysregulation between feeding and fasting characterizes breakdown of metabolic homeostasis associated with obesity.

MLL1 regulates cytokine-driven cell migration and metastasis

Cell migration is a critical contributor to metastasis. Cytokine production and its role in cancer cell migration have been traditionally associated with immune cells. We find that the histone methyltransferase Mixed-Lineage Leukemia 1 (MLL1) controls 3D cell migration via cytokines, IL-6, IL-8, and TGF-β1, secreted by the cancer cells themselves. MLL1, with its scaffold protein Menin, controls actin filament assembly via the IL-6/8/pSTAT3/Arp3 axis and myosin contractility via the TGF-β1/Gli2/ROCK1/2/pMLC2 axis, which together regulate dynamic protrusion generation and 3D cell migration. MLL1 also regulates cell proliferation via mitosis-based and cell cycle-related pathways. Mice bearing orthotopic MLL1-depleted tumors exhibit decreased lung metastatic burden and longer survival. MLL1 depletion leads to lower metastatic burden even when controlling for the difference in primary tumor growth rates. Combining MLL1-Menin inhibitor with paclitaxel abrogates tumor growth and metastasis, including preexistent metastasis. These results establish MLL1 as a potent regulator of cell migration and highlight the potential of targeting MLL1 in patients with metastatic disease.

FOXO1 stimulates tip cell-enriched gene expression in endothelial cells

Forkhead box O (FOXO) family proteins are expressed in various cells, and play crucial roles in cellular metabolism, apoptosis, and aging. FOXO1-null mice exhibit embryonic lethality due to impaired endothelial cell (EC) maturation and vascular remodeling. However, FOXO1-mediated genome-wide regulation in ECs remains unclear. Here, we demonstrate that VEGF dynamically regulates FOXO1 cytosol-nucleus translocation. FOXO1 re-localizes to the nucleus via PP2A phosphatase. RNA-seq combined with FOXO1 overexpression/knockdown in ECs demonstrated that FOXO1 governs the VEGF-responsive tip cell-enriched genes, and further inhibits DLL4-NOTCH signaling. Endogenous FOXO1 ChIP-seq revealed that FOXO1 binds to the EC-unique tip-enriched genes with co-enrichment of EC master regulators, and the condensed chromatin region as a pioneer factor. We identified new promoter/enhancer regions of the VEGF-responsive tip cell genes regulated by FOXO1: ESM1 and ANGPT2. This is the first study to identify cell type-specific FOXO1 functions, including VEGF-mediated tip cell definition in primary cultured ECs.

Uncovering co-regulatory modules and gene regulatory networks in the heart through machine learning-based analysis of large-scale epigenomic data

The availability of large-scale epigenomic data from various cell types and conditions has yielded valuable insights for evaluating and learning features predicting the co-binding of transcription factors (TF). However, prior attempts to develop models predicting motif co-occurrence lacked scalability for globally analyzing any motif combination or making cross-species predictions. Moreover, mapping co-regulatory modules (CRM) to gene regulatory networks (GRN) is crucial for understanding underlying function. Currently, no comprehensive pipeline exists for large-scale, rapid, and accurate CRM and GRN identification. In this study, we analyzed and evaluated different TF binding characteristics facilitating biologically significant co-binding to identify all potential clusters of co-binding TFs. We curated the UniBind database, containing ChIP-Seq data from over 1983 samples and 232 TFs, and implemented two machine learning models to predict CRMs and the potential regulatory networks they operate on. Two machine learning models, Convolution Neural Networks (CNN) and Random Forest Classifier(RFC), used to predict co-binding between TFs, were compared using precision-recall Receiver Operating Characteristic (ROC) curves. CNN outperformed RFC (AUC 0.94 vs. 0.88) and achieved higher F1 scores (0.938 vs. 0.872). The CRMs generated by the clustering algorithm were validated against ChipAtlas and MCOT, revealing additional motifs forming CRMs. We predicted 200k CRMs for 50k+ human genes, validated against recent CRM prediction methods with 100% overlap. Further, we narrowed our focus to study heart-related regulatory motifs, filtering the generated CRMs to report 1784 Cardiac CRMs containing at least four cardiac TFs. Identified cardiac CRMs revealed potential novel regulators like ARID3A and RXRB for SCAD, including known TFs like PPARG for F11R. Our findings highlight the importance of the NKX family of transcription factors in cardiac development and provide potential targets for further investigation in cardiac disease.

Venetoclax efficacy on acute myeloid leukemia is enhanced by the combination with butyrate

Venetoclax has been approved recently for treatment of Acute myeloid leukemia (AML). Venetoclax is a BH3-mimetic and induces apoptosis via Bcl-2 inhibition. However, venetoclax's effect is still restrictive and a novel strategy is needed. In the present study, we demonstrate that sodium butyrate (NaB) facilitates the venetoclax's efficacy of cell death in AML cells. As a single agent, NaB or venetoclax exerted just a weak effect on cell death induction for AML cell line KG-1. The combination with NaB and venetoclax drastically induced cell death. NaB upregulated pro-apoptotic factors, Bax and Bak, indicating the synergistic effect by the collaboration with Bcl-2 inhibition by venetoclax. The combined treatment with NaB and venetoclax strongly cleaved a caspase substrate poly (ADP-ribose) polymerase (PARP) and a potent pan-caspase inhibitor Q-VD-OPh almost completely blocked the cell death induced by the combination, meaning that the combination mainly induced apoptosis. The combination with NaB and venetoclax also strongly induced cell death in another AML cell line SKNO-1 but did not affect chronic myeloid leukemia (CML) cell line K562, indicating that the effect was specific for AML cells. Our results provide a novel strategy to strengthen the effect of venetoclax for AML treatment.

Lactic acid induces transcriptional repression of macrophage inflammatory response via histone acetylation

Lactic acid has emerged as an important modulator of immune cell function. It can be produced by both gut microbiota and the host metabolism at homeostasis and during disease states. The production of lactic acid in the gut microenvironment is vital for tissue homeostasis. In the present study, we examined how lactic acid integrates cellular metabolism to shape the epigenome of macrophages during pro-inflammatory response. We found that lactic acid serves as a primary fuel source to promote histone H3K27 acetylation, which allows the expression of immunosuppressive gene program including Nr4a1. Consequently, macrophage pro-inflammatory function was transcriptionally repressed. Furthermore, the histone acetylation induced by lactic acid promotes a form of long-term immunosuppression ("trained immunosuppression"). Pre-exposure to lactic acid induces lipopolysaccharide tolerance. These findings thus indicate that lactic acid sensing and its effect on chromatin remodeling in macrophages represent a key homeostatic mechanism that can provide a tolerogenic tissue microenvironment.

Noncanonical functions of microRNAs in the nucleus

MicroRNAs (miRNAs) are small noncoding RNAs (ncRNAs) that play their roles in the regulation of physiological and pathological processes. Originally, it was assumed that miRNAs only modulate gene expression posttranscriptionally in the cytoplasm by inducing target mRNA degradation. However, with further research, evidence shows that mature miRNAs also exist in the cell nucleus, where they can impact gene transcription and ncRNA maturation in several ways. This review provides an overview of novel models of nuclear miRNA functions. Some of the models remain to be verified by experimental evidence, and more details of the miRNA regulation network remain to be discovered in the future.