Determination and inference of eukaryotic transcription factor sequence specificity

Using methylation data to improve transcription factor binding prediction

Modelling the regulatory mechanisms that determine cell fate, response to external perturbation, and disease state depends on measuring many factors, a task made more difficult by the plasticity of the epigenome. Scanning the genome for the sequence patterns defined by Position Weight Matrices (PWM) can be used to estimate transcription factor (TF) binding locations. However, this approach does not incorporate information regarding the epigenetic context necessary for TF binding. CpG methylation is an epigenetic mark influenced by environmental factors that is commonly assayed in human cohort studies. We developed a framework to score inferred TF binding locations using methylation data. We intersected motif locations identified using PWMs with methylation information captured in both whole-genome bisulfite sequencing and Illumina EPIC array data for six cell lines, scored motif locations based on these data, and compared with experimental data characterizing TF binding (ChIP-seq). We found that for most TFs, binding prediction improves using methylation-based scoring compared to standard PWM-scores. We also illustrate that our approach can be generalized to infer TF binding when methylation information is only proximally available, i.e. measured for nearby CpGs that do not directly overlap with a motif location. Overall, our approach provides a framework for inferring context-specific TF binding using methylation data. Importantly, the availability of DNA methylation data in existing patient populations provides an opportunity to use our approach to understand the impact of methylation on gene regulatory processes in the context of human disease.

A multi-omic single-cell landscape of cellular diversification in the developing human cerebral cortex

The vast neuronal diversity in the human neocortex is vital for high-order brain functions, necessitating elucidation of the regulatory mechanisms underlying such unparalleled diversity. However, recent studies have yet to comprehensively reveal the diversity of neurons and the molecular logic of neocortical origin in humans at single-cell resolution through profiling transcriptomic or epigenomic landscapes, owing to the application of unimodal data alone to depict exceedingly heterogeneous populations of neurons. In this study, we generated a comprehensive compendium of the developing human neocortex by simultaneously profiling gene expression and open chromatin from the same cell. We computationally reconstructed the differentiation trajectories of excitatory projection neurons of cortical origin and inferred the regulatory logic governing lineage bifurcation decisions for neuronal diversification. We demonstrated that neuronal diversity arises from progenitor cell lineage specificity and postmitotic differentiation at distinct stages. Our data paves the way for understanding the primarily coordinated regulatory logic for neuronal diversification in the neocortex.

Genome-wide epigenetic dynamics of tea leaves under mechanical wounding stress during oolong tea postharvest processing

Understanding the epigenetic responses to mechanical wounding stress during the postharvest processing of oolong tea provides insight into the reprogramming of the tea genome and its impact on tea quality. Here, we characterized the 5mC DNA methylation and chromatin accessibility landscapes of tea leaves subjected to mechanical wounding stress during the postharvest processing of oolong tea. Analysis of the differentially methylated regions and preferentially accessible promoters revealed many overrepresented TF-binding motifs, highlighting sets of TFs that are likely important for the quality of oolong tea. Within these sets, we constructed a chromatin accessibility-mediated gene regulatory network specific to mechanical wounding stress. In combination with the results of the TF-centred yeast one-hybrid assay, we identified potential binding sites of CsMYC2 and constructed a gene regulatory network centred on CsMYC2, clarifying the potential regulatory role of CsMYC2 in the postharvest processing of oolong tea. Interestingly, highly accessible chromatin and hypomethylated cytosine were found to coexist in the promoter region of the indole biosynthesis gene (tryptophan synthase β-subunit, CsTSB) under wounding stress, which indicates that these two important epigenetic regulatory mechanisms are jointly involved in regulating the synthesis of indole during the postharvest processing of oolong tea. These findings improve our understanding of the epigenetic regulatory mechanisms involved in quality formation during the postharvest processing of oolong tea.

CircHTT(2,3,4,5,6) - co-evolving with the HTT CAG-repeat tract - modulates Huntington's disease phenotypes

Circular RNA (circRNA) molecules have critical functions during brain development and in brain-related disorders. Here, we identified and validated a circRNA, circHTT(2,3,4,5,6), stemming from the Huntington's disease (HD) gene locus that is most abundant in the central nervous system (CNS). We uncovered its evolutionary conservation in diverse mammalian species, and a correlation between circHTT(2,3,4,5,6) levels and the length of the CAG-repeat tract in exon-1 of HTT in human and mouse HD model systems. The mouse orthologue, circHtt(2,3,4,5,6), is expressed during embryogenesis, increases during nervous system development, and is aberrantly upregulated in the presence of the expanded CAG tract. While an IRES-like motif was predicted in circH TT (2,3,4,5,6), the circRNA does not appear to be translated in adult mouse brain tissue. Nonetheless, a modest, but consistent fraction of circHtt(2,3,4,5,6) associates with the 40S ribosomal subunit, suggesting a possible role in the regulation of protein translation. Finally, circHtt(2,3,4,5,6) overexpression experiments in HD-relevant STHdh striatal cells revealed its ability to modulate CAG expansion-driven cellular defects in cell-to-substrate adhesion, thus uncovering an unconventional modifier of HD pathology.

Architecture and dynamics of the abscisic acid gene regulatory network

The plant hormone abscisic acid (ABA) regulates essential processes in plant development and responsiveness to abiotic and biotic stresses. ABA perception triggers a post-translational signaling cascade that elicits the ABA gene regulatory network (GRN), encompassing hundreds of transcription factors (TFs) and thousands of transcribed genes. To further our knowledge of this GRN, we performed an RNA-seq time series experiment consisting of 14 time points in the 16 h following a one-time ABA treatment of 5-week-old Arabidopsis rosettes. During this time course, ABA rapidly changed transcription levels of 7151 genes, which were partitioned into 44 coexpressed modules that carry out diverse biological functions. We integrated our time-series data with publicly available TF-binding site data, motif data, and RNA-seq data of plants inhibited in translation, and predicted (i) which TFs regulate the different coexpression clusters, (ii) which TFs contribute the most to target gene amplitude, (iii) timing of engagement of different TFs in the ABA GRN, and (iv) hierarchical position of TFs and their targets in the multi-tiered ABA GRN. The ABA GRN was found to be highly interconnected and regulated at different amplitudes and timing by a wide variety of TFs, of which the bZIP family was most prominent, and upregulation of genes encompassed more TFs than downregulation. We validated our network models in silico with additional public TF-binding site data and transcription data of selected TF mutants. Finally, using a drought assay we found that the Trihelix TF GT3a is likely an ABA-induced positive regulator of drought tolerance.

Inhibition of Renin Expression Is Regulated by an Epigenetic Switch From an Active to a Poised State

BACKGROUND

Renin-expressing cells are myoendocrine cells crucial for the maintenance of homeostasis. Renin is regulated by cAMP, p300 (histone acetyltransferase p300)/CBP (CREB-binding protein), and Brd4 (bromodomain-containing protein 4) proteins and associated pathways. However, the specific regulatory changes that occur following inhibition of these pathways are not clear.

METHODS

We treated As4.1 cells (tumoral cells derived from mouse juxtaglomerular cells that constitutively express renin) with 3 inhibitors that target different factors required for renin transcription: H-89-dihydrochloride, PKA (protein kinase A) inhibitor; JQ1, Brd4 bromodomain inhibitor; and A-485, p300/CBP inhibitor. We performed assay for transposase-accessible chromatin with sequencing (ATAC-seq), single-cell RNA sequencing, cleavage under targets and tagmentation (CUT&Tag), and chromatin immunoprecipitation sequencing for H3K27ac (acetylation of lysine 27 of the histone H3 protein) and p300 binding on biological replicates of treated and control As4.1 cells.

RESULTS

In response to each inhibitor, Ren1 expression was significantly reduced and reversible upon washout. Chromatin accessibility at the Ren1 locus did not markedly change but was globally reduced at distal elements. Inhibition of PKA led to significant reductions in H3K27ac and p300 binding specifically within the Ren1 super-enhancer region. Further, we identified enriched TF (transcription factor) motifs shared across each inhibitory treatment. Finally, we identified a set of 9 genes with putative roles across each of the 3 renin regulatory pathways and observed that each displayed differentially accessible chromatin, gene expression, H3K27ac, and p300 binding at their respective loci.

CONCLUSIONS

Inhibition of renin expression in cells that constitutively synthesize and release renin is regulated by an epigenetic switch from an active to poised state associated with decreased cell-cell communication and an epithelial-mesenchymal transition. This work highlights and helps define the factors necessary for renin cells to alternate between myoendocrine and contractile phenotypes.

Identification of transcription factor co-binding patterns with non-negative matrix factorization

Transcription factor (TF) binding to DNA is critical to transcription regulation. Although the binding properties of numerous individual TFs are well-documented, a more detailed comprehension of how TFs interact cooperatively with DNA is required. We present COBIND, a novel method based on non-negative matrix factorization (NMF) to identify TF co-binding patterns automatically. COBIND applies NMF to one-hot encoded regions flanking known TF binding sites (TFBSs) to pinpoint enriched DNA patterns at fixed distances. We applied COBIND to 5699 TFBS datasets from UniBind for 401 TFs in seven species. The method uncovered already established co-binding patterns and new co-binding configurations not yet reported in the literature and inferred through motif similarity and protein-protein interaction knowledge. Our extensive analyses across species revealed that 67% of the TFs shared a co-binding motif with other TFs from the same structural family. The co-binding patterns captured by COBIND are likely functionally relevant as they harbor higher evolutionarily conservation than isolated TFBSs. Open chromatin data from matching human cell lines further supported the co-binding predictions. Finally, we used single-molecule footprinting data from mouse embryonic stem cells to confirm that the COBIND-predicted co-binding events associated with some TFs likely occurred on the same DNA molecules.

Genomic background sequences systematically outperform synthetic ones in de novo motif discovery for ChIP-seq data

Efficient de novo motif discovery from the results of wide-genome mapping of transcription factor binding sites (ChIP-seq) is dependent on the choice of background nucleotide sequences. The foreground sequences (ChIP-seq peaks) represent not only specific motifs of target transcription factors, but also the motifs overrepresented throughout the genome, such as simple sequence repeats. We performed a massive comparison of the 'synthetic' and 'genomic' approaches to generate background sequences for de novo motif discovery. The 'synthetic' approach shuffled nucleotides in peaks, while in the 'genomic' approach selected sequences from the reference genome randomly or only from gene promoters according to the fraction of A/T nucleotides in each sequence. We compiled the benchmark collections of ChIP-seq datasets for mouse, human and Arabidopsis, and performed de novo motif discovery. We showed that the genomic approach has both more robust detection of the known motifs of target transcription factors and more stringent exclusion of the simple sequence repeats as possible non-specific motifs. The advantage of the genomic approach over the synthetic approach was greater in plants compared to mammals. We developed the AntiNoise web service (https://denovosea.icgbio.ru/antinoise/) that implements a genomic approach to extract genomic background sequences for twelve eukaryotic genomes.

Myeloid sarcoma with plasmacytoid dendritic cell-like proliferation associated with IKZF1, ETV6 and DNMT3A mutations

The classification of clonal plasmacytoid dendritic cell (pDC) proliferation associated with myeloid neoplasms remains a topic of ongoing debate. Although the fifth edition of the World Health Organization classification classifies clonal pDC proliferation into two categories, it is unclear whether this classification adequately captures the complexities of clonal pDC pathogenesis. We present a clinical case featuring myeloid sarcoma with pDC-like cells in cervical lymph nodes and bone marrow (BM). Analysis of biopsy specimens and BM aspirate revealed two distinct cellular populations expressing myeloid and pDC markers. One population exhibited myeloid leukemia and monocyte markers, including MPO, CD13, CD33, CD11b, and CD14, while the other manifested an immunophenotype reminiscent of pDCs, characterized by expression of CD56 and CD123. Additionally, whole exome sequencing and RNA sequencing of BM mononuclear cells were conducted to explore the pathophysiology of this rare malignancy, and unveiled pDC-like cell proliferation driven by IKZF1 and ETV6 mutations originating from clonal hematopoiesis initiated by a DNMT3A mutation. Notably, venetoclax-based therapy exhibited efficacy for achieving and sustaining complete remission. This case provides pivotal insights into the mechanistic aspects of pDC/pDC-like cell proliferation in myeloid sarcoma, offering valuable perspectives on therapeutic strategies.

Discovery of therapeutic targets in cancer using chromatin accessibility and transcriptomic data

Most cancer types lack targeted therapeutic options, and when first-line targeted therapies are available, treatment resistance is a huge challenge. Recent technological advances enable the use of assay for transposase-accessible chromatin with sequencing (ATAC-seq) and RNA sequencing (RNA-seq) on patient tissue in a high-throughput manner. Here, we present a computational approach that leverages these datasets to identify drug targets based on tumor lineage. We constructed gene regulatory networks for 371 patients of 22 cancer types using machine learning approaches trained with three-dimensional genomic data for enhancer-to-promoter contacts. Next, we identified the key transcription factors (TFs) in these networks, which are used to find therapeutic vulnerabilities, by direct targeting of either TFs or the proteins that they interact with. We validated four candidates identified for neuroendocrine, liver, and renal cancers, which have a dismal prognosis with current therapeutic options.

The landscape of RNA-binding proteins in mammalian spermatogenesis

Despite continuous expansion of the RNA-binding protein (RBP) world, there is a lack of systematic understanding of RBPs in mammalian testis, which harbors one of the most complex tissue transcriptomes. We adapted RNA interactome capture to mouse male germ cells, building an RBP atlas characterized by multiple layers of dynamics along spermatogenesis. Trapping of RNA-crosslinked peptides showed that the glutamic acid-arginine (ER) patch, a residue-coevolved polyampholytic element present in coiled-coils, enhances RNA binding of its host RBPs. Deletion of this element in NONO (non-POU domain-containing octamer-binding protein) led to a defective mitosis-to-meiosis transition due to compromised NONO-RNA interactions. Whole-exome sequencing of over 1000 infertile men revealed a prominent role of RBPs in the human genetic architecture of male infertility and identified risk ER patch variants.

CRISPR screening uncovers a long-range enhancer for ONECUT1 in pancreatic differentiation and links a diabetes risk variant

Functional enhancer annotation is critical for understanding tissue-specific transcriptional regulation and prioritizing disease-associated non-coding variants. However, unbiased enhancer discovery in disease-relevant contexts remains challenging. To identify enhancers pertinent to diabetes, we conducted a CRISPR interference (CRISPRi) screen in the human pluripotent stem cell (hPSC) pancreatic differentiation system. Among the enhancers identified, we focused on an enhancer we named ONECUT1e-664kb, ∼664 kb from the ONECUT1 promoter. Previous studies have linked ONECUT1 coding mutations to pancreatic hypoplasia and neonatal diabetes. We found that homozygous deletion of ONECUT1e-664kb in hPSCs leads to a near-complete loss of ONECUT1 expression and impaired pancreatic differentiation. ONECUT1e-664kb contains a type 2 diabetes-associated variant (rs528350911) disrupting a GATA motif. Introducing the risk variant into hPSCs reduced binding of key pancreatic transcription factors (GATA4, GATA6, and FOXA2), supporting its causal role in diabetes. This work highlights the utility of unbiased enhancer discovery in disease-relevant settings for understanding monogenic and complex disease.

Revisiting the model for coactivator recruitment: Med15 can select its target sites independent of promoter-bound transcription factors

Activation domains (ADs) within transcription factors (TFs) induce gene expression by recruiting coactivators such as the Mediator complex. Coactivators lack DNA binding domains (DBDs) and are assumed to passively follow their recruiting TFs. This is supported by direct AD-coactivator interactions seen in vitro but has not yet been tested in living cells. To examine that, we targeted two Med15-recruiting ADs to a range of budding yeast promoters through fusion with different DBDs. The DBD-AD fusions localized to hundreds of genomic sites but recruited Med15 and induced transcription in only a subset of bound promoters, characterized by a fuzzy-nucleosome architecture. Direct DBD-Med15 fusions shifted DBD localization towards fuzzy-nucleosome promoters, including promoters devoid of the endogenous Mediator. We propose that Med15, and perhaps other coactivators, possess inherent promoter preference and thus actively contribute to the selection of TF-induced genes.

Differential impact of quiescent non-coding loci on chromatin entropy

Non-coding regions of the human genome are important for functional regulations, but their mechanisms remain elusive. We used machine learning to guide a CRISPR screening on hubs (i.e. non-coding loci forming many 3D contacts) and significantly increased the discovery rate of hubs essential for cell growth. We found no clear genetic or epigenetic differences between essential and nonessential hubs, but we observed that some neighboring hubs in the linear genome have distinct spatial contacts and opposite effects on cell growth. One such pair in an epigenetically quiescent region showed different impacts on gene expression, chromatin accessibility and chromatin organization. We also found that deleting the essential hub altered the genetic network activity and increased the entropy of chromatin accessibility, more severe than that caused by deletion of the nonessential hub, suggesting that they are critical for maintaining an ordered chromatin structure. Our study reveals new insights into the system-level roles of non-coding regions in the human genome.

Disordered sequences of transcription factors regulate genomic binding by integrating diverse sequence grammars and interaction types

Intrinsically disordered regions (IDRs) guide transcription factors (TFs) to their genomic binding sites, raising the question of how structure-lacking regions encode for complex binding patterns. We investigated this using the TF Gln3, revealing sets of IDR-embedded determinants that direct Gln3 binding to respective groups of functionally related promoters, and enable tuning binding preferences between environmental conditions, phospho-mimicking mutations, and orthologs. Through targeted mutations, we defined the role of short linear motifs (SLiMs) and co-binding TFs (Hap2) in stabilizing Gln3 at respiration-chain promoters, while providing evidence that Gln3 binding at nitrogen-associated promoters is encoded by the IDR amino-acid composition, independent of SLiMs or co-binding TFs. Therefore, despite their apparent simplicity, TF IDRs can direct and regulate complex genomic binding patterns through a combination of SLiM-mediated and composition-encoded interactions.

SexAnnoDB, a knowledgebase of sex-specific regulations from multi-omics data of human cancers

BACKGROUND

Sexual differences across molecular levels profoundly impact cancer biology and outcomes. Patient gender significantly influences drug responses, with divergent reactions between men and women to the same drugs. Despite databases on sex differences in human tissues, understanding regulations of sex disparities in cancer is limited. These resources lack detailed mechanistic studies on sex-biased molecules.

METHODS

In this study, we conducted a comprehensive examination of molecular distinctions and regulatory networks across 27 cancer types, delving into sex-biased effects. Our analyses encompassed sex-biased competitive endogenous RNA networks, regulatory networks involving sex-biased RNA binding protein-exon skipping events, sex-biased transcription factor-gene regulatory networks, as well as sex-biased expression quantitative trait loci, sex-biased expression quantitative trait methylation, sex-biased splicing quantitative trait loci, and the identification of sex-biased cancer therapeutic drug target genes. All findings from these analyses are accessible on SexAnnoDB ( https://ccsm.uth.edu/SexAnnoDB/ ).

RESULTS

From these analyses, we defined 126 cancer therapeutic target sex-associated genes. Among them, 9 genes showed sex-biased at both the mRNA and protein levels. Specifically, S100A9 was the target of five drugs, of which calcium has been approved by the FDA for the treatment of colon and rectal cancers. Transcription factor (TF)-gene regulatory network analysis suggested that four TFs in the SARC male group targeted S100A9 and upregulated the expression of S100A9 in these patients. Promoter region methylation status was only associated with S100A9 expression in KIRP female patients. Hypermethylation inhibited S100A9 expression and was responsible for the downregulation of S100A9 in these female patients.

CONCLUSIONS

Comprehensive network and association analyses indicated that the sex differences at the transcriptome level were partially the result of corresponding sex-biased epigenetic and genetic molecules. Overall, SexAnnoDB offers a discipline-specific search platform that could potentially assist basic experimental researchers or physicians in developing personalized treatment plans.

Rapid profiling of transcription factor-cofactor interaction networks reveals principles of epigenetic regulation

Transcription factor (TF)-cofactor (COF) interactions define dynamic, cell-specific networks that govern gene expression; however, these networks are understudied due to a lack of methods for high-throughput profiling of DNA-bound TF-COF complexes. Here, we describe the Cofactor Recruitment (CoRec) method for rapid profiling of cell-specific TF-COF complexes. We define a lysine acetyltransferase (KAT)-TF network in resting and stimulated T cells. We find promiscuous recruitment of KATs for many TFs and that 35% of KAT-TF interactions are condition specific. KAT-TF interactions identify NF-κB as a primary regulator of acutely induced histone 3 lysine 27 acetylation (H3K27ac). Finally, we find that heterotypic clustering of CBP/P300-recruiting TFs is a strong predictor of total promoter H3K27ac. Our data support clustering of TF sites that broadly recruit KATs as a mechanism for widespread co-occurring histone acetylation marks. CoRec can be readily applied to different cell systems and provides a powerful approach to define TF-COF networks impacting chromatin state and gene regulation.

Interspecies regulatory landscapes and elements revealed by novel joint systematic integration of human and mouse blood cell epigenomes

Knowledge of locations and activities of cis-regulatory elements (CREs) is needed to decipher basic mechanisms of gene regulation and to understand the impact of genetic variants on complex traits. Previous studies identified candidate CREs (cCREs) using epigenetic features in one species, making comparisons difficult between species. In contrast, we conducted an interspecies study defining epigenetic states and identifying cCREs in blood cell types to generate regulatory maps that are comparable between species, using integrative modeling of eight epigenetic features jointly in human and mouse in our Validated Systematic Integration (VISION) Project. The resulting catalogs of cCREs are useful resources for further studies of gene regulation in blood cells, indicated by high overlap with known functional elements and strong enrichment for human genetic variants associated with blood cell phenotypes. The contribution of each epigenetic state in cCREs to gene regulation, inferred from a multivariate regression, was used to estimate epigenetic state regulatory potential (esRP) scores for each cCRE in each cell type, which were used to categorize dynamic changes in cCREs. Groups of cCREs displaying similar patterns of regulatory activity in human and mouse cell types, obtained by joint clustering on esRP scores, harbor distinctive transcription factor binding motifs that are similar between species. An interspecies comparison of cCREs revealed both conserved and species-specific patterns of epigenetic evolution. Finally, we show that comparisons of the epigenetic landscape between species can reveal elements with similar roles in regulation, even in the absence of genomic sequence alignment.

High-throughput identification of functional regulatory SNPs in systemic lupus erythematosus

Genome-wide association studies implicate multiple loci in risk for systemic lupus erythematosus (SLE), but few contain exonic variants, rendering systematic identification of non-coding variants essential to decoding SLE genetics. We utilized SNP-seq and bioinformatic enrichment to interrogate 2180 single-nucleotide polymorphisms (SNPs) from 87 SLE risk loci for potential binding of transcription factors and related proteins from B cells. 52 SNPs that passed initial screening were tested by electrophoretic mobility shift and luciferase reporter assays. To validate the approach, we studied rs2297550 in detail, finding that the risk allele enhanced binding to the transcription factor Ikaros (encoded by IKZF1), thereby modulating expression of IKBKE. Correspondingly, primary cells from genotyped healthy donors bearing the risk allele expressed higher levels of the interferon / NF-κB regulator IKKε. Together, these findings define a set of likely functional non-coding lupus risk variants and identify a regulatory pathway involving rs2297550, Ikaros, and IKKε implicated by human genetics in risk for SLE.

Systematic dissection of sequence features affecting binding specificity of a pioneer factor reveals binding synergy between FOXA1 and AP-1

Despite the unique ability of pioneer factors (PFs) to target nucleosomal sites in closed chromatin, they only bind a small fraction of their genomic motifs. The underlying mechanism of this selectivity is not well understood. Here, we design a high-throughput assay called chromatin immunoprecipitation with integrated synthetic oligonucleotides (ChIP-ISO) to systematically dissect sequence features affecting the binding specificity of a classic PF, FOXA1, in human A549 cells. Combining ChIP-ISO with in vitro and neural network analyses, we find that (1) FOXA1 binding is strongly affected by co-binding transcription factors (TFs) AP-1 and CEBPB; (2) FOXA1 and AP-1 show binding cooperativity in vitro; (3) FOXA1's binding is determined more by local sequences than chromatin context, including eu-/heterochromatin; and (4) AP-1 is partially responsible for differential binding of FOXA1 in different cell types. Our study presents a framework for elucidating genetic rules underlying PF binding specificity and reveals a mechanism for context-specific regulation of its binding.

Gene regulatory networks reveal sex difference in lung adenocarcinoma

BACKGROUND

Lung adenocarcinoma (LUAD) has been observed to have significant sex differences in incidence, prognosis, and response to therapy. However, the molecular mechanisms responsible for these disparities have not been investigated extensively.

METHODS

Sample-specific gene regulatory network methods were used to analyze RNA sequencing data from non-cancerous human lung samples from The Genotype Tissue Expression Project (GTEx) and lung adenocarcinoma primary tumor samples from The Cancer Genome Atlas (TCGA); results were validated on independent data.

RESULTS

We found that genes associated with key biological pathways including cell proliferation, immune response and drug metabolism are differentially regulated between males and females in both healthy lung tissue and tumor, and that these regulatory differences are further perturbed by tobacco smoking. We also discovered significant sex bias in transcription factor targeting patterns of clinically actionable oncogenes and tumor suppressor genes, including AKT2 and KRAS. Using differentially regulated genes between healthy and tumor samples in conjunction with a drug repurposing tool, we identified several small-molecule drugs that might have sex-biased efficacy as cancer therapeutics and further validated this observation using an independent cell line database.

CONCLUSIONS

These findings underscore the importance of including sex as a biological variable and considering gene regulatory processes in developing strategies for disease prevention and management.

Cell-specific gene networks and drivers in rheumatoid arthritis synovial tissues

Rheumatoid arthritis (RA) is a common autoimmune and inflammatory disease characterized by inflammation and hyperplasia of the synovial tissues. RA pathogenesis involves multiple cell types, genes, transcription factors (TFs) and networks. Yet, little is known about the TFs, and key drivers and networks regulating cell function and disease at the synovial tissue level, which is the site of disease. In the present study, we used available RNA-seq databases generated from synovial tissues and developed a novel approach to elucidate cell type-specific regulatory networks on synovial tissue genes in RA. We leverage established computational methodologies to infer sample-specific gene regulatory networks and applied statistical methods to compare network properties across phenotypic groups (RA versus osteoarthritis). We developed computational approaches to rank TFs based on their contribution to the observed phenotypic differences between RA and controls across different cell types. We identified 18 (fibroblast-like synoviocyte), 16 (T cells), 19 (B cells) and 11 (monocyte) key regulators in RA synovial tissues. Interestingly, fibroblast-like synoviocyte (FLS) and B cells were driven by multiple independent co-regulatory TF clusters that included MITF, HLX, BACH1 (FLS) and KLF13, FOSB, FOSL1 (B cells). However, monocytes were collectively governed by a single cluster of TF drivers, responsible for the main phenotypic differences between RA and controls, which included RFX5, IRF9, CREB5. Among several cell subset and pathway changes, we also detected reduced presence of Natural killer T (NKT) cells and eosinophils in RA synovial tissues. Overall, our novel approach identified new and previously unsuspected Key driver genes (KDG), TF and networks and should help better understanding individual cell regulation and co-regulatory networks in RA pathogenesis, as well as potentially generate new targets for treatment.

BertSNR: an interpretable deep learning framework for single-nucleotide resolution identification of transcription factor binding sites based on DNA language model

MOTIVATION

Transcription factors are pivotal in the regulation of gene expression, and accurate identification of transcription factor binding sites (TFBSs) at high resolution is crucial for understanding the mechanisms underlying gene regulation. The task of identifying TFBSs from DNA sequences is a significant challenge in the field of computational biology today. To address this challenge, a variety of computational approaches have been developed. However, these methods face limitations in their ability to achieve high-resolution identification and often lack interpretability.

RESULTS

We propose BertSNR, an interpretable deep learning framework for identifying TFBSs at single-nucleotide resolution. BertSNR integrates sequence-level and token-level information by multi-task learning based on pre-trained DNA language models. Benchmarking comparisons show that our BertSNR outperforms the existing state-of-the-art methods in TFBS predictions. Importantly, we enhanced the interpretability of the model through attentional weight visualization and motif analysis, and discovered the subtle relationship between attention weight and motif. Moreover, BertSNR effectively identifies TFBSs in promoter regions, facilitating the study of intricate gene regulation.

AVAILABILITY AND IMPLEMENTATION

The BertSNR source code can be found at https://github.com/lhy0322/BertSNR.

Integrated single-cell analysis defines the epigenetic basis of castration-resistant prostate luminal cells

Understanding prostate response to castration and androgen receptor signaling inhibitors (ARSI) is critical to improving long-term prostate cancer (PCa) patient survival. Here, we use a multi-omics approach on 229,794 single cells to create a mouse single-cell reference atlas for interpreting mouse prostate biology and castration response. Our reference atlas refines single-cell annotations and provides a chromatin context, which, when coupled with mouse lineage tracing, demonstrates that castration-resistant luminal cells are distinct from the pre-existent urethra-proximal stem/progenitor cells. Molecular pathway analysis and therapeutic studies further implicate AP1 (JUN/FOS), WNT/β-catenin, FOXQ1, NF-κB, and JAK/STAT pathways as major drivers of castration-resistant luminal populations with relevance to human PCa. Our datasets, which can be explored through an interactive portal (https://visportal.roswellpark.org/data/tang/), can aid in developing combination treatments with ARSI for advanced PCa patients.

Gene regulation in regeneration after acute kidney injury

Acute kidney injury (AKI) is a common condition associated with significant morbidity, mortality, and cost. Injured kidney tissue can regenerate after many forms of AKI. However, there are no treatments in routine clinical practice to encourage recovery. In part, this shortcoming is due to an incomplete understanding of the genetic mechanisms that orchestrate kidney recovery. The advent of high-throughput sequencing technologies and genetic mouse models has opened an unprecedented window into the transcriptional dynamics that accompany both successful and maladaptive repair. AKI recovery shares similar cell-state transformations with kidney development, which can suggest common mechanisms of gene regulation. Several powerful bioinformatic strategies have been developed to infer the activity of gene regulatory networks by combining multiple forms of sequencing data at single-cell resolution. These studies highlight not only shared stress responses but also key changes in gene regulatory networks controlling metabolism. Furthermore, chromatin immunoprecipitation studies in injured kidneys have revealed dynamic epigenetic modifications at enhancer elements near target genes. This review will highlight how these studies have enhanced our understanding of gene regulation in injury response and regeneration.

Rewiring gene circuitry for plant improvement

Aspirations for high crop growth and yield, nutritional quality and bioproduction of materials are challenged by climate change and limited adoption of new technologies. Here, we review recent advances in approaches to profile and model gene regulatory activity over developmental and response time in specific cells, which have revealed the basis of variation in plant phenotypes: both redeployment of key regulators to new contexts and their repurposing to control different slates of genes. New synthetic biology tools allow tunable, spatiotemporal regulation of transgenes, while recent gene-editing technologies enable manipulation of the regulation of native genes. Ultimately, understanding how gene circuitry is wired to control form and function across varied plant species, combined with advanced technology to rewire that circuitry, will unlock solutions to our greatest challenges in agriculture, energy and the environment.

Hypoxia-induced CTCF promotes EMT in breast cancer

Cancer cells experiencing hypoxic stress employ epithelial-mesenchymal transition (EMT) to undergo metastasis through rewiring of the chromatin landscape, epigenetics, and importantly, gene expression. Here, we showed that hypoxia modulates the epigenetic landscape on CTCF promoter and upregulates its expression. Hypoxia-driven epigenetic regulation, specifically DNA demethylation mediated by TET2, is a prerequisite for CTCF induction. Mechanistically, in hypoxic conditions, Hypoxia-inducible factor 1-alpha (HIF1α) binds to the unmethylated CTCF promoter, causing transcriptional upregulation. Further, we uncover the pivotal role of CTCF in promoting EMT as loss of CTCF abrogated invasiveness of hypoxic breast cancer cells. These findings highlight the functional contribution of HIF1α-CTCF axis in promoting EMT in hypoxic breast cancer cells. Lastly, CTCF expression is alleviated and the potential for EMT is diminished when the HIF1α binding is particularly disrupted through the dCas9-DNMT3A system-mediated maintenance of DNA methylation on the CTCF promoter. This axis may offer a unique therapeutic target in breast cancer.

Transcription factor binding specificities of the oomycete Phytophthora infestans reflect conserved and divergent evolutionary patterns and predict function

BACKGROUND

Identifying the DNA-binding specificities of transcription factors (TF) is central to understanding gene networks that regulate growth and development. Such knowledge is lacking in oomycetes, a microbial eukaryotic lineage within the stramenopile group. Oomycetes include many important plant and animal pathogens such as the potato and tomato blight agent Phytophthora infestans, which is a tractable model for studying life-stage differentiation within the group.

RESULTS

Mining of the P. infestans genome identified 197 genes encoding proteins belonging to 22 TF families. Their chromosomal distribution was consistent with family expansions through unequal crossing-over, which were likely ancient since each family had similar sizes in most oomycetes. Most TFs exhibited dynamic changes in RNA levels through the P. infestans life cycle. The DNA-binding preferences of 123 proteins were assayed using protein-binding oligonucleotide microarrays, which succeeded with 73 proteins from 14 families. Binding sites predicted for representatives of the families were validated by electrophoretic mobility shift or chromatin immunoprecipitation assays. Consistent with the substantial evolutionary distance of oomycetes from traditional model organisms, only a subset of the DNA-binding preferences resembled those of human or plant orthologs. Phylogenetic analyses of the TF families within P. infestans often discriminated clades with canonical and novel DNA targets. Paralogs with similar binding preferences frequently had distinct patterns of expression suggestive of functional divergence. TFs were predicted to either drive life stage-specific expression or serve as general activators based on the representation of their binding sites within total or developmentally-regulated promoters. This projection was confirmed for one TF using synthetic and mutated promoters fused to reporter genes in vivo.

CONCLUSIONS

We established a large dataset of binding specificities for P. infestans TFs, representing the first in the stramenopile group. This resource provides a basis for understanding transcriptional regulation by linking TFs with their targets, which should help delineate the molecular components of processes such as sporulation and host infection. Our work also yielded insight into TF evolution during the eukaryotic radiation, revealing both functional conservation as well as diversification across kingdoms.

The developmental and evolutionary characteristics of transcription factor binding site clustered regions based on an explainable machine learning model

Gene expression is temporally and spatially regulated by the interaction of transcription factors (TFs) and cis-regulatory elements (CREs). The uneven distribution of TF binding sites across the genome poses challenges in understanding how this distribution evolves to regulate spatio-temporal gene expression and consequent heritable phenotypic variation. In this study, chromatin accessibility profiles and gene expression profiles were collected from several species including mammals (human, mouse, bovine), fish (zebrafish and medaka), and chicken. Transcription factor binding sites clustered regions (TFCRs) at different embryonic stages were characterized to investigate regulatory evolution. The study revealed dynamic changes in TFCR distribution during embryonic development and species evolution. The synchronization between TFCR complexity and gene expression was assessed across species using RegulatoryScore. Additionally, an explainable machine learning model highlighted the importance of the distance between TFCR and promoter in the coordinated regulation of TFCRs on gene expression. Our results revealed the developmental and evolutionary dynamics of TFCRs during embryonic development from fish, chicken to mammals. These data provide valuable resources for exploring the relationship between transcriptional regulation and phenotypic differences during embryonic development.

Genome-Wide Methylation Analysis Reveals a KCNK3-Prominent Causal Cascade on Hypertension

BACKGROUND

Despite advances in understanding hypertension's genetic structure, how noncoding genetic variants influence it remains unclear. Studying their interaction with DNA methylation is crucial to deciphering this complex disease's genetic mechanisms.

METHODS

We investigated the genetic and epigenetic interplay in hypertension using whole-genome bisulfite sequencing. Methylation profiling in 918 males revealed allele-specific methylation and methylation quantitative trait loci. We engineered rs1275988T/C mutant mice using CRISPR (clustered regularly interspaced short palindromic repeats)/Cas9 (CRISPR-associated protein 9), bred them for homozygosity, and subjected them to a high-salt diet. Telemetry captured their cardiovascular metrics. Protein-DNA interactions were elucidated using DNA pull-downs, mass spectrometry, and Western blots. A wire myograph assessed vascular function, and analysis of the Kcnk3 gene methylation highlighted the mutation's role in hypertension.

RESULTS

We discovered that DNA methylation-associated genetic effects, especially in non-cytosine-phosphate-guanine (non-CpG) island and noncoding distal regulatory regions, significantly contribute to hypertension predisposition. We identified distinct methylation quantitative trait locus patterns in the hypertensive population and observed that the onset of hypertension is influenced by the transmission of genetic effects through the demethylation process. By evidence-driven prioritization and in vivo experiments, we unearthed rs1275988 in a cell type-specific enhancer as a notable hypertension causal variant, intensifying hypertension through the modulation of local DNA methylation and consequential alterations in Kcnk3 gene expression and vascular remodeling. When exposed to a high-salt diet, mice with the rs1275988C/C genotype exhibited exacerbated hypertension and significant vascular remodeling, underscored by increased aortic wall thickness. The C allele of rs1275988 was associated with elevated DNA methylation levels, driving down the expression of the Kcnk3 gene by attenuating Nr2f2 (nuclear receptor subfamily 2 group F member 2) binding at the enhancer locus.

CONCLUSIONS

Our research reveals new insights into the complex interplay between genetic variations and DNA methylation in hypertension. We underscore hypomethylation's potential in hypertension onset and identify rs1275988 as a causal variant in vascular remodeling. This work advances our understanding of hypertension's molecular mechanisms and encourages personalized health care strategies.

Aging-associated Alterations in the Gene Regulatory Network Landscape Associate with Risk, Prognosis and Response to Therapy in Lung Adenocarcinoma

Aging is the primary risk factor for many individual cancer types, including lung adenocarcinoma (LUAD). To understand how aging-related alterations in the regulation of key cellular processes might affect LUAD risk and survival outcomes, we built individual (person)-specific gene regulatory networks integrating gene expression, transcription factor protein-protein interaction, and sequence motif data, using PANDA/LIONESS algorithms, for both non-cancerous lung tissue samples from the Genotype Tissue Expression (GTEx) project and LUAD samples from The Cancer Genome Atlas (TCGA). In GTEx, we found that pathways involved in cell proliferation and immune response are increasingly targeted by regulatory transcription factors with age; these aging-associated alterations are accelerated by tobacco smoking and resemble oncogenic shifts in the regulatory landscape observed in LUAD and suggests that dysregulation of aging pathways might be associated with an increased risk of LUAD. Comparing normal adjacent samples from individuals with LUAD with healthy lung tissue samples from those without LUAD, we found that aging-associated genes show greater aging-biased targeting patterns in younger individuals with LUAD compared to their healthy counterparts of similar age, a pattern suggestive of age acceleration. This implies that an accelerated aging process may be responsible for tumor incidence in younger individuals. Using drug repurposing tool CLUEreg, we found small molecule drugs with potential geroprotective effects that may alter the accelerating aging profiles we found. We also observed that, in contrast to chronological age, a network-informed aging signature was associated with survival and response to chemotherapy in LUAD.

A single-cell atlas of chromatin accessibility in mouse organogenesis

Organogenesis is a highly complex and precisely regulated process. Here we profiled the chromatin accessibility in >350,000 cells derived from 13 mouse embryos at four developmental stages from embryonic day (E) 10.5 to E13.5 by SPATAC-seq in a single experiment. The resulting atlas revealed the status of 830,873 candidate cis-regulatory elements in 43 major cell types. By integrating the chromatin accessibility atlas with the previous transcriptomic dataset, we characterized cis-regulatory sequences and transcription factors associated with cell fate commitment, such as Nr5a2 in the development of gastrointestinal tract, which was preliminarily supported by the in vivo experiment in zebrafish. Finally, we integrated this atlas with the previous single-cell chromatin accessibility dataset from 13 adult mouse tissues to delineate the developmental stage-specific gene regulatory programmes within and across different cell types and identify potential molecular switches throughout lineage development. This comprehensive dataset provides a foundation for exploring transcriptional regulation in organogenesis.

Lipid-nanoparticle-enabled nucleic acid therapeutics for liver disorders

Inherited genetic disorders of the liver pose a significant public health burden. Liver transplantation is often limited by the availability of donor livers and the exorbitant costs of immunosuppressive therapy. To overcome these limitations, nucleic acid therapy provides a hopeful alternative that enables gene repair, gene supplementation, and gene silencing with suitable vectors. Though viral vectors are the most efficient and preferred for gene therapy, pre-existing immunity debilitating immune responses limit their use. As a potential alternative, lipid nanoparticle-mediated vectors are being explored to deliver multiple nucleic acid forms, including pDNA, mRNA, siRNA, and proteins. Herein, we discuss the broader applications of lipid nanoparticles, from protein replacement therapy to restoring the disease mechanism through nucleic acid delivery and gene editing, as well as multiple preclinical and clinical studies as a potential alternative to liver transplantation.

Multiomic profiling of transcription factor binding and function in human brain

Transcription factors (TFs) orchestrate gene expression programs crucial for brain function, but we lack detailed information about TF binding in human brain tissue. We generated a multiomic resource (ChIP-seq, ATAC-seq, RNA-seq, DNA methylation) on bulk tissues and sorted nuclei from several postmortem brain regions, including binding maps for more than 100 TFs. We demonstrate improved measurements of TF activity, including motif recognition and gene expression modeling, upon identification and removal of high TF occupancy regions. Further, predictive TF binding models demonstrate a bias for these high-occupancy sites. Neuronal TFs SATB2 and TBR1 bind unique regions depleted for such sites and promote neuronal gene expression. Binding sites for TFs, including TBR1 and PKNOX1, are enriched for risk variants associated with neuropsychiatric disorders, predominantly in neurons. This work, titled BrainTF, is a powerful resource for future studies seeking to understand the roles of specific TFs in regulating gene expression in the human brain.

Advances in computational and experimental approaches for deciphering transcriptional regulatory networks: Understanding the roles of cis-regulatory elements is essential, and recent research utilizing MPRAs, STARR-seq, CRISPR-Cas9, and machine learning has yielded valuable insights

Understanding the influence of cis-regulatory elements on gene regulation poses numerous challenges given complexities stemming from variations in transcription factor (TF) binding, chromatin accessibility, structural constraints, and cell-type differences. This review discusses the role of gene regulatory networks in enhancing understanding of transcriptional regulation and covers construction methods ranging from expression-based approaches to supervised machine learning. Additionally, key experimental methods, including MPRAs and CRISPR-Cas9-based screening, which have significantly contributed to understanding TF binding preferences and cis-regulatory element functions, are explored. Lastly, the potential of machine learning and artificial intelligence to unravel cis-regulatory logic is analyzed. These computational advances have far-reaching implications for precision medicine, therapeutic target discovery, and the study of genetic variations in health and disease.

A continuum of zinc finger transcription factor retention on native chromatin underlies dynamic genome organization

Transcription factor (TF) residence on chromatin translates into quantitative transcriptional or structural outcomes on genome. Commonly used formaldehyde crosslinking fixes TF-DNA interactions cumulatively and compromises the measured occupancy level. Here we mapped the occupancy level of global or individual zinc finger TFs like CTCF and MAZ, in the form of highly resolved footprints, on native chromatin. By incorporating reinforcing perturbation conditions, we established S-score, a quantitative metric to proxy the continuum of CTCF or MAZ retention across different motifs on native chromatin. The native chromatin-retained CTCF sites harbor sequence features within CTCF motifs better explained by S-score than the metrics obtained from other crosslinking or native assays. CTCF retention on native chromatin correlates with local SUMOylation level, and anti-correlates with transcriptional activity. The S-score successfully delineates the otherwise-masked differential stability of chromatin structures mediated by CTCF, or by MAZ independent of CTCF. Overall, our study established a paradigm continuum of TF retention across binding sites on native chromatin, explaining the dynamic genome organization.

CRISPR Screening Uncovers a Long-Range Enhancer for ONECUT1 in Pancreatic Differentiation and Links a Diabetes Risk Variant

Functional enhancer annotation is a valuable first step for understanding tissue-specific transcriptional regulation and prioritizing disease-associated non-coding variants for investigation. However, unbiased enhancer discovery in physiologically relevant contexts remains a major challenge. To discover regulatory elements pertinent to diabetes, we conducted a CRISPR interference screen in the human pluripotent stem cell (hPSC) pancreatic differentiation system. Among the enhancers uncovered, we focused on a long-range enhancer ∼664 kb from the ONECUT1 promoter, since coding mutations in ONECUT1 cause pancreatic hypoplasia and neonatal diabetes. Homozygous enhancer deletion in hPSCs was associated with a near-complete loss of ONECUT1 gene expression and compromised pancreatic differentiation. This enhancer contains a confidently fine-mapped type 2 diabetes associated variant (rs528350911) which disrupts a GATA motif. Introduction of the risk variant into hPSCs revealed substantially reduced binding of key pancreatic transcription factors (GATA4, GATA6 and FOXA2) on the edited allele, accompanied by a slight reduction of ONECUT1 transcription, supporting a causal role for this risk variant in metabolic disease. This work expands our knowledge about transcriptional regulation in pancreatic development through the characterization of a long-range enhancer and highlights the utility of enhancer discovery in disease-relevant settings for understanding monogenic and complex disease.

REUNION: transcription factor binding prediction and regulatory association inference from single-cell multi-omics data

MOTIVATION

Profiling of gene expression and chromatin accessibility by single-cell multi-omics approaches can help to systematically decipher how transcription factors (TFs) regulate target gene expression via cis-region interactions. However, integrating information from different modalities to discover regulatory associations is challenging, in part because motif scanning approaches miss many likely TF binding sites.

RESULTS

We develop REUNION, a framework for predicting genome-wide TF binding and cis-region-TF-gene "triplet" regulatory associations using single-cell multi-omics data. The first component of REUNION, Unify, utilizes information theory-inspired complementary score functions that incorporate TF expression, chromatin accessibility, and target gene expression to identify regulatory associations. The second component, Rediscover, takes Unify estimates as input for pseudo semi-supervised learning to predict TF binding in accessible genomic regions that may or may not include detected TF motifs. Rediscover leverages latent chromatin accessibility and sequence feature spaces of the genomic regions, without requiring chromatin immunoprecipitation data for model training. Applied to peripheral blood mononuclear cell data, REUNION outperforms alternative methods in TF binding prediction on average performance. In particular, it recovers missing region-TF associations from regions lacking detected motifs, which circumvents the reliance on motif scanning and facilitates discovery of novel associations involving potential co-binding transcriptional regulators. Newly identified region-TF associations, even in regions lacking a detected motif, improve the prediction of target gene expression in regulatory triplets, and are thus likely to genuinely participate in the regulation.

AVAILABILITY AND IMPLEMENTATION

All source code is available at https://github.com/yangymargaret/REUNION.

Variants in tubule epithelial regulatory elements mediate most heritable differences in human kidney function

Kidney disease is highly heritable; however, the causal genetic variants, the cell types in which these variants function, and the molecular mechanisms underlying kidney disease remain largely unknown. To identify genetic loci affecting kidney function, we performed a GWAS using multiple kidney function biomarkers and identified 462 loci. To begin to investigate how these loci affect kidney function, we generated single-cell chromatin accessibility (scATAC-seq) maps of the human kidney and identified candidate cis-regulatory elements (cCREs) for kidney podocytes, tubule epithelial cells, and kidney endothelial, stromal, and immune cells. Kidney tubule epithelial cCREs explained 58% of kidney function SNP-heritability and kidney podocyte cCREs explained an additional 6.5% of SNP-heritability. In contrast, little kidney function heritability was explained by kidney endothelial, stromal, or immune cell-specific cCREs. Through functionally informed fine-mapping, we identified putative causal kidney function variants and their corresponding cCREs. Using kidney scATAC-seq data, we created a deep learning model (which we named ChromKid) to predict kidney cell type-specific chromatin accessibility from sequence. ChromKid and allele specific kidney scATAC-seq revealed that many fine-mapped kidney function variants locally change chromatin accessibility in tubule epithelial cells. Enhancer assays confirmed that fine-mapped kidney function variants alter tubule epithelial regulatory element function. To map the genes which these regulatory elements control, we used CRISPR interference (CRISPRi) to target these regulatory elements in tubule epithelial cells and assessed changes in gene expression. CRISPRi of enhancers harboring kidney function variants regulated NDRG1 and RBPMS expression. Thus, inherited differences in tubule epithelial NDRG1 and RBPMS expression may predispose to kidney disease in humans. We conclude that genetic variants affecting tubule epithelial regulatory element function account for most SNP-heritability of human kidney function. This work provides an experimental approach to identify the variants, regulatory elements, and genes involved in polygenic disease.

Identification of endothelial and mesenchymal FOXF1 enhancers involved in alveolar capillary dysplasia

Mutations in the FOXF1 gene, a key transcriptional regulator of pulmonary vascular development, cause Alveolar Capillary Dysplasia with Misalignment of Pulmonary Veins, a lethal lung disease affecting newborns and infants. Identification of new FOXF1 upstream regulatory elements is critical to explain why frequent non-coding FOXF1 deletions are linked to the disease. Herein, we use multiome single-nuclei RNA and ATAC sequencing of mouse and human patient lungs to identify four conserved endothelial and mesenchymal FOXF1 enhancers. We demonstrate that endothelial FOXF1 enhancers are autoactivated, whereas mesenchymal FOXF1 enhancers are regulated by EBF1 and GLI1. The cell-specificity of FOXF1 enhancers is validated by disrupting these enhancers in mouse embryonic stem cells using CRISPR/Cpf1 genome editing followed by lineage-tracing of mutant embryonic stem cells in mouse embryos using blastocyst complementation. This study resolves an important clinical question why frequent non-coding FOXF1 deletions that interfere with endothelial and mesenchymal enhancers can lead to the disease.

Identification of DNA motif pairs on paired sequences based on composite heterogeneous graph

Motivation

The interaction between DNA motifs (DNA motif pairs) influences gene expression through partnership or competition in the process of gene regulation. Potential chromatin interactions between different DNA motifs have been implicated in various diseases. However, current methods for identifying DNA motif pairs rely on the recognition of single DNA motifs or probabilities, which may result in local optimal solutions and can be sensitive to the choice of initial values. A method for precisely identifying DNA motif pairs is still lacking.

Results

Here, we propose a novel computational method for predicting DNA Motif Pairs based on Composite Heterogeneous Graph (MPCHG). This approach leverages a composite heterogeneous graph model to identify DNA motif pairs on paired sequences. Compared with the existing methods, MPCHG has greatly improved the accuracy of motifs prediction. Furthermore, the predicted DNA motifs demonstrate heightened DNase accessibility than the background sequences. Notably, the two DNA motifs forming a pair exhibit functional consistency. Importantly, the interacting TF pairs obtained by predicted DNA motif pairs were significantly enriched with known interacting TF pairs, suggesting their potential contribution to chromatin interactions. Collectively, we believe that these identified DNA motif pairs held substantial implications for revealing gene transcriptional regulation under long-range chromatin interactions.

pTDP-43 levels correlate with cell type specific molecular alterations in the prefrontal cortex of C9orf72 ALS/FTD patients

Repeat expansions in the C9orf72 gene are the most common genetic cause of amyotrophic lateral sclerosis and familial frontotemporal dementia (ALS/FTD). To identify molecular defects that take place in the dorsolateral frontal cortex of patients with C9orf72 ALS/FTD, we compared healthy controls with C9orf72 ALS/FTD donor samples staged based on the levels of cortical phosphorylated TAR DNA binding protein (pTDP-43), a neuropathological hallmark of disease progression. We identified distinct molecular changes in different cell types that take place during FTD development. Loss of neurosurveillance microglia and activation of the complement cascade take place early, when pTDP-43 aggregates are absent or very low, and become more pronounced in late stages, suggesting an initial involvement of microglia in disease progression. Reduction of layer 2-3 cortical projection neurons with high expression of CUX2/LAMP5 also occurs early, and the reduction becomes more pronounced as pTDP-43 accumulates. Several unique features were observed only in samples with high levels of pTDP-43, including global alteration of chromatin accessibility in oligodendrocytes, microglia, and astrocytes; higher ratios of premature oligodendrocytes; increased levels of the noncoding RNA NEAT1 in astrocytes and neurons, and higher amount of phosphorylated ribosomal protein S6. Our findings reveal previously unknown progressive functional changes in major cell types found in the frontal cortex of C9orf72 ALS/FTD patients that shed light on the mechanisms underlying the pathology of this disease.

Mechanistic analysis of enhancer sequences in the estrogen receptor transcriptional program

Estrogen Receptor α (ERα) is a major lineage determining transcription factor (TF) in mammary gland development. Dysregulation of ERα-mediated transcriptional program results in cancer. Transcriptomic and epigenomic profiling of breast cancer cell lines has revealed large numbers of enhancers involved in this regulatory program, but how these enhancers encode function in their sequence remains poorly understood. A subset of ERα-bound enhancers are transcribed into short bidirectional RNA (enhancer RNA or eRNA), and this property is believed to be a reliable marker of active enhancers. We therefore analyze thousands of ERα-bound enhancers and build quantitative, mechanism-aware models to discriminate eRNAs from non-transcribing enhancers based on their sequence. Our thermodynamics-based models provide insights into the roles of specific TFs in ERα-mediated transcriptional program, many of which are supported by the literature. We use in silico perturbations to predict TF-enhancer regulatory relationships and integrate these findings with experimentally determined enhancer-promoter interactions to construct a gene regulatory network. We also demonstrate that the model can prioritize breast cancer-related sequence variants while providing mechanistic explanations for their function. Finally, we experimentally validate the model-proposed mechanisms underlying three such variants.

Altered salivary microbiota associated with high-sugar beverage consumption

The human oral microbiome may alter oral and systemic disease risk. Consuming high sugar content beverages (HSB) can lead to caries development by altering the microbial composition in dental plaque, but little is known regarding HSB-specific oral microbial alterations. Therefore, we conducted a large, population-based study to examine associations of HSB intake with oral microbiome diversity and composition. Using mouthwash samples of 989 individuals in two nationwide U.S. cohorts, bacterial 16S rRNA genes were amplified, sequenced, and assigned to bacterial taxa. HSB intake was quantified from food frequency questionnaires as low (< 1 serving/week), medium (1-3 servings/week), or high (> 3 servings/week). We assessed overall bacterial diversity and presence of specific taxa with respect to HSB intake in each cohort separately and combined in a meta-analysis. Consistently in the two cohorts, we found lower species richness in high HSB consumers (> 3 cans/week) (p = 0.027), and that overall bacterial community profiles differed from those of non-consumers (PERMANOVA p = 0.040). Specifically, presence of a network of commensal bacteria (Lachnospiraceae, Peptostreptococcaceae, and Alloprevotella rava) was less common in high compared to non-consumers, as were other species including Campylobacter showae, Prevotella oulorum, and Mycoplasma faucium. Presence of acidogenic bacteria Bifodobacteriaceae and Lactobacillus rhamnosus was more common in high consumers. Abundance of Fusobacteriales and its genus Leptotrichia, Lachnoanaerobaculum sp., and Campylobacter were lower with higher HSB consumption, and their abundances were correlated. No significant interaction was found for these associations with diabetic status or with microbial markers for caries (S. mutans) and periodontitis (P. gingivalis). Our results suggest that soft drink intake may alter the salivary microbiota, with consistent results across two independent cohorts. The observed perturbations of overrepresented acidogenic bacteria and underrepresented commensal bacteria in high HSB consumers may have implications for oral and systemic disease risk.

Comprehensive multimodal and multiomic profiling reveals epigenetic and transcriptional reprogramming in lung tumors

Epigenomic mechanisms are critically involved in mediation of genetic and environmental factors that underlie cancer development. Histone modifications represent highly informative epigenomic marks that reveal activation and repression of gene activities and dysregulation of transcriptional control due to tumorigenesis. Here, we present a comprehensive epigenomic and transcriptomic mapping of 18 tumor and 20 non-neoplastic tissues from non-small cell lung adenocarcinoma patients. Our profiling covers 5 histone marks including activating (H3K4me3, H3K4me1, and H3K27ac) and repressive (H3K27me3 and H3K9me3) marks and the transcriptome using only 20 mg of tissue per sample, enabled by low-input omic technologies. Using advanced integrative bioinformatic analysis, we uncovered cancer-driving signaling cascade networks, changes in 3D genome modularity, and differential expression and functionalities of transcription factors and noncoding RNAs. Many of these identified genes and regulatory molecules showed no significant change in their expression or a single epigenomic modality, emphasizing the power of integrative multimodal and multiomic analysis using patient samples.

Multi-dimensional cell-free DNA-based liquid biopsy for sensitive early detection of gastric cancer

BACKGROUND

Gastric cancer is the fifth most common cancer type. Most patients are diagnosed at advanced stages with poor prognosis. A non-invasive assay for the detection of early-stage gastric cancer is highly desirable for reducing associated mortality.

METHODS

We collected a prospective study cohort of 110 stage I-II gastric cancer patients and 139 non-cancer individuals. We performed whole-genome sequencing with plasma samples and profiled four types of cell-free DNA (cfDNA) characteristics, fragment size pattern, copy number variation, nucleosome coverage pattern, and single nucleotide substitution. With these differential profiles, we developed an ensemble model to detect gastric cancer signals. Further, we validated the assay in an in-house first validation cohort of 73 gastric cancer patients and 94 non-cancer individuals and an independent second validation cohort of 47 gastric cancer patients and 49 non-cancer individuals. Additionally, we evaluated the assay in a hypothetical 100,000 screening population by Monte Carlo simulation.

RESULTS

Our cfDNA-based assay could distinguish early-stage gastric cancer from non-cancer at an AUROC of 0.962 (95% CI: 0.942-0.982) in the study cohort, 0.972 (95% CI: 0.953-0.992) in the first validation cohort and 0.937 (95% CI: 0.890-0.983) in the second validation cohort. The model reached a specificity of 92.1% (128/139) and a sensitivity of 88.2% (97/110) in the study cohort. In the first validation cohort, 91.5% (86/94) of non-cancer individuals and 91.8% (67/73) of gastric cancer patients were correctly identified. In the second validation cohort, 89.8% (44/49) of non-cancer individuals and 87.2% (41/47) of gastric cancer patients were accurately classified.

CONCLUSIONS

We introduced a liquid biopsy assay using multiple dimensions of cfDNA characteristics that could accurately identify early-stage gastric cancer from non-cancerous conditions. As a cost-effective non-invasive approach, it may provide population-wide benefits for the early detection of gastric cancer.

TRIAL REGISTRATION

This study was registered on ClinicalTrials.gov under the identifier NCT05269056 on March 7, 2022.

Time-course swRNA-seq uncovers a hierarchical gene regulatory network in controlling the response-repair-remodeling after wounding

Wounding initiates intricate responses crucial for tissue repair and regeneration. Yet, the gene regulatory networks governing wound healing remain poorly understood. Here, employing single-worm RNA sequencing (swRNA-seq) across 12 time-points, we delineated a three-stage wound repair process in C. elegans: response, repair, and remodeling. Integrating diverse datasets, we constructed a dynamic regulatory network comprising 241 transcription regulators and their inferred targets. We identified potentially seven autoregulatory TFs and five cross-autoregulatory loops involving pqm-1 and jun-1. We revealed that TFs might interact with chromatin factors and form TF-TF combinatory modules via intrinsically disordered regions to enhance response robustness. We experimentally validated six regulators functioning in transcriptional and translocation-dependent manners. Notably, nhr-76, daf-16, nhr-84, and oef-1 are potentially required for efficient repair, while elt-2 may act as an inhibitor. These findings elucidate transcriptional responses and hierarchical regulatory networks during C. elegans wound repair, shedding light on mechanisms underlying tissue repair and regeneration.

Recent advances in exploring transcriptional regulatory landscape of crops

Crop breeding entails developing and selecting plant varieties with improved agronomic traits. Modern molecular techniques, such as genome editing, enable more efficient manipulation of plant phenotype by altering the expression of particular regulatory or functional genes. Hence, it is essential to thoroughly comprehend the transcriptional regulatory mechanisms that underpin these traits. In the multi-omics era, a large amount of omics data has been generated for diverse crop species, including genomics, epigenomics, transcriptomics, proteomics, and single-cell omics. The abundant data resources and the emergence of advanced computational tools offer unprecedented opportunities for obtaining a holistic view and profound understanding of the regulatory processes linked to desirable traits. This review focuses on integrated network approaches that utilize multi-omics data to investigate gene expression regulation. Various types of regulatory networks and their inference methods are discussed, focusing on recent advancements in crop plants. The integration of multi-omics data has been proven to be crucial for the construction of high-confidence regulatory networks. With the refinement of these methodologies, they will significantly enhance crop breeding efforts and contribute to global food security.

Transcription factor binding site divergence across maize inbred lines drives transcriptional and phenotypic variation

Regulatory elements are important constituents of plant genomes that have shaped ancient and modern crops. Their identification, function, and diversity in crop genomes however are poorly characterized, thus limiting our ability to harness their power for further agricultural advances using induced or natural variation. Here, we use DNA affinity purification-sequencing (DAP-seq) to map transcription factor (TF) binding events for 200 maize TFs belonging to 30 distinct families and heterodimer pairs in two distinct inbred lines historically used for maize hybrid plant production, providing empirical binding site annotation for 5.3% of the maize genome. TF binding site comparison in B73 and Mo17 inbreds reveals widespread differences, driven largely by structural variation, that correlate with gene expression changes. TF binding site presence-absence variation helps clarify complex QTL such as vgt1, an important determinant of maize flowering time, and DICE, a distal enhancer involved in herbivore resistance. Modification of TF binding regions via CRISPR-Cas9 mediated editing alters target gene expression and phenotype. Our functional catalog of maize TF binding events enables collective and comparative TF binding analysis, and highlights its value for agricultural improvement.

A disease-associated gene desert directs macrophage inflammation through ETS2

Increasing rates of autoimmune and inflammatory disease present a burgeoning threat to human health1. This is compounded by the limited efficacy of available treatments1 and high failure rates during drug development2, highlighting an urgent need to better understand disease mechanisms. Here we show how functional genomics could address this challenge. By investigating an intergenic haplotype on chr21q22-which has been independently linked to inflammatory bowel disease, ankylosing spondylitis, primary sclerosing cholangitis and Takayasu's arteritis3-6-we identify that the causal gene, ETS2, is a central regulator of human inflammatory macrophages and delineate the shared disease mechanism that amplifies ETS2 expression. Genes regulated by ETS2 were prominently expressed in diseased tissues and more enriched for inflammatory bowel disease GWAS hits than most previously described pathways. Overexpressing ETS2 in resting macrophages reproduced the inflammatory state observed in chr21q22-associated diseases, with upregulation of multiple drug targets, including TNF and IL-23. Using a database of cellular signatures7, we identified drugs that might modulate this pathway and validated the potent anti-inflammatory activity of one class of small molecules in vitro and ex vivo. Together, this illustrates the power of functional genomics, applied directly in primary human cells, to identify immune-mediated disease mechanisms and potential therapeutic opportunities.