Determination and inference of eukaryotic transcription factor sequence specificity

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 (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 new regulatory pathway involving rs2297550, Ikaros, and IKKϵ implicated by human genetics in risk for SLE.

Genetic variation is a key determinant of chromatin accessibility and drives differences in the regulatory landscape of C57BL/6J and 129S1/SvImJ mice

Most common genetic variants associated with disease are located in non-coding regions of the genome. One mechanism by which they function is through altering transcription factor (TF) binding. In this study, we explore how genetic variation is connected to differences in the regulatory landscape of livers from C57BL/6J and 129S1/SvImJ mice fed either chow or a high-fat diet. To identify sites where regulatory variation affects TF binding and nearby gene expression, we employed an integrative analysis of H3K27ac ChIP-seq (active enhancers), ATAC-seq (chromatin accessibility) and RNA-seq (gene expression). We show that, across all these assays, the genetically driven (i.e. strain-specific) differences in the regulatory landscape are more pronounced than those modified by diet. Most notably, our analysis revealed that differentially accessible regions (DARs, N = 29635, FDR < 0.01 and fold change > 50%) are almost always strain-specific and enriched with genetic variation. Moreover, proximal DARs are highly correlated with differentially expressed genes. We also show that TF binding is affected by genetic variation, which we validate experimentally using ChIP-seq for TCF7L2 and CTCF. This study provides detailed insights into how non-coding genetic variation alters the gene regulatory landscape, and demonstrates how this can be used to study the regulatory variation influencing TF binding.

Molecular phenotyping of small cell lung cancer using targeted cfDNA profiling of transcriptional regulatory regions

We report an approach for cancer phenotyping based on targeted sequencing of cell-free DNA (cfDNA) for small cell lung cancer (SCLC). In SCLC, differential activation of transcription factors (TFs), such as ASCL1, NEUROD1, POU2F3, and REST defines molecular subtypes. We designed a targeted capture panel that identifies chromatin organization signatures at 1535 TF binding sites and 13,240 gene transcription start sites and detects exonic mutations in 842 genes. Sequencing of cfDNA from SCLC patient-derived xenograft models captured TF activity and gene expression and revealed individual highly informative loci. Prediction models of ASCL1 and NEUROD1 activity using informative loci achieved areas under the receiver operating characteristic curve (AUCs) from 0.84 to 0.88 in patients with SCLC. As non-SCLC (NSCLC) often transforms to SCLC following targeted therapy, we applied our framework to distinguish NSCLC from SCLC and achieved an AUC of 0.99. Our approach shows promising utility for SCLC subtyping and transformation monitoring, with potential applicability to diverse tumor types.

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.

DNA binding analysis of rare variants in homeodomains reveals homeodomain specificity-determining residues

Homeodomains (HDs) are the second largest class of DNA binding domains (DBDs) among eukaryotic sequence-specific transcription factors (TFs) and are the TF structural class with the largest number of disease-associated mutations in the Human Gene Mutation Database (HGMD). Despite numerous structural studies and large-scale analyses of HD DNA binding specificity, HD-DNA recognition is still not fully understood. Here, we analyze 92 human HD mutants, including disease-associated variants and variants of uncertain significance (VUS), for their effects on DNA binding activity. Many of the variants alter DNA binding affinity and/or specificity. Detailed biochemical analysis and structural modeling identifies 14 previously unknown specificity-determining positions, 5 of which do not contact DNA. The same missense substitution at analogous positions within different HDs often exhibits different effects on DNA binding activity. Variant effect prediction tools perform moderately well in distinguishing variants with altered DNA binding affinity, but poorly in identifying those with altered binding specificity. Our results highlight the need for biochemical assays of TF coding variants and prioritize dozens of variants for further investigations into their pathogenicity and the development of clinical diagnostics and precision therapies.

Single-cell multiomics reveals the interplay of clonal evolution and cellular plasticity in hepatoblastoma

Hepatoblastomas (HB) display heterogeneous cellular phenotypes that influence the clinical outcome, but the underlying mechanisms are poorly understood. Here, we use a single-cell multiomic strategy to unravel the molecular determinants of this plasticity. We identify a continuum of HB cell states between hepatocytic (scH), liver progenitor (scLP) and mesenchymal (scM) differentiation poles, with an intermediate scH/LP population bordering scLP and scH areas in spatial transcriptomics. Chromatin accessibility landscapes reveal the gene regulatory networks of each differentiation pole, and the sequence of transcription factor activations underlying cell state transitions. Single-cell mapping of somatic alterations reveals the clonal architecture of each tumor, showing that each genetic subclone displays its own range of cellular plasticity across differentiation states. The most scLP subclones, overexpressing stem cell and DNA repair genes, proliferate faster after neo-adjuvant chemotherapy. These results highlight how the interplay of clonal evolution and epigenetic plasticity shapes the potential of HB subclones to respond to chemotherapy.

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 H3K27ac. Finally, we find that heterotypic clustering of CBP/P300-recruiting TFs is a strong predictor of total promoter H3K27ac. Our data supports 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.

The Putative GATA Transcription Factor SbGATA22 as a Novel Regulator of Dhurrin Biosynthesis

Cyanogenic glucosides are specialized metabolites produced by over 3000 species of higher plants from more than 130 families. The deployment of cyanogenic glucosides is influenced by biotic and abiotic factors in addition to being developmentally regulated, consistent with their roles in plant defense and stress mitigation. Despite their ubiquity, very little is known regarding the molecular mechanisms that regulate their biosynthesis. The biosynthetic pathway of dhurrin, the cyanogenic glucoside found in the important cereal crop sorghum (Sorghum bicolor (L.) Moench), was described over 20 years ago, and yet no direct regulator of the biosynthetic genes has been identified. To isolate regulatory proteins that bind to the promoter region of the key dhurrin biosynthetic gene of sorghum, SbCYP79A1, yeast one-hybrid screens were performed. A bait fragment containing 1204 base pairs of the SbCYP79A1 5' regulatory region was cloned upstream of a reporter gene and introduced into Saccharomyces cerevisiae. Subsequently, the yeast was transformed with library cDNA representing RNA from two different sorghum developmental stages. From these screens, we identified SbGATA22, an LLM domain B-GATA transcription factor that binds to the putative GATA transcription factor binding motifs in the SbCYP79A1 promoter region. Transient assays in Nicotiana benthamiana show that SbGATA22 localizes to the nucleus. The expression of SbGATA22, in comparison with SbCYP79A1 expression and dhurrin concentration, was analyzed over 14 days of sorghum development and in response to nitrogen application, as these conditions are known to affect dhurrin levels. Collectively, these findings suggest that SbGATA22 may act as a negative regulator of SbCYP79A1 expression and provide a preliminary insight into the molecular regulation of dhurrin biosynthesis in sorghum.

Genomic Exploration: Unraveling the Intricacies of Indica Rice Oryza sativa L. Germin-Like Protein Gene 12-3 (OsGLP12-3) Promoter via Cloning, Sequencing, and In Silico Analysis

Germin and Germin-like proteins (GLPs) are a class of plant proteins that are part of the Cupins superfamily, found in several plant organs including roots, seeds, leaves, and nectar glands. They play a crucial role in plant defense against pathogens and environmental stresses. Herein, this study focused on the promoter analysis of OsGLP12-3 in rice cultivar Swat-1 to elucidate its regulation and functions. The region (1863bp) of the OsGLP12-3 promoter from Swat-1 genomic DNA was amplified, purified, quantified, and cloned using Topo cloning technology, followed by sequencing. Further in silico comparative analysis was conducted between the OsGLP12-3 promoters from Nipponbare and Swat-1 using the Plant CARE database, identifying 24 cis-acting regulatory elements with diverse functions. These elements exhibited distinct distribution patterns in the 2 rice varieties. The OsGLP12-3 promoter revealed an abundance of regulatory elements associated with biotic and abiotic stress responses. Computational tools were employed to analyze the regulatory features of this region. In silico expression analysis of OsGLP12-3, considering various developmental stages, stress conditions, hormones, and expression timing, was performed using the TENOR tool. Pairwise alignment indicated 86% sequence similarity between Nipponbare and Swat-1. Phylogenetic analysis was conducted to explore the evolutionary relationship between the OsGLP12-3 and other plant GLPs. Additionally, 2 unique regulatory elements were modeled and docked, GARE and MBS to understand their hydrogen bonding interactions in gene regulation. The study highlights the importance of OsGLP12-3 in plant defense against biotic and abiotic stresses, supported by its expression patterns in response to various stressors and the presence of specific regulatory elements within its promoter region.

The Methyltransferases METTL7A and METTL7B Confer Resistance to Thiol-Based Histone Deacetylase Inhibitors

Histone deacetylase inhibitors (HDACi) are part of a growing class of epigenetic therapies used for the treatment of cancer. Although HDACis are effective in the treatment of T-cell lymphomas, treatment of solid tumors with this class of drugs has not been successful. Overexpression of the multidrug resistance protein P-glycoprotein (P-gp), encoded by ABCB1, is known to confer resistance to the HDACi romidepsin in vitro, yet increased ABCB1 expression has not been associated with resistance in patients, suggesting that other mechanisms of resistance arise in the clinic. To identify alternative mechanisms of resistance to romidepsin, we selected MCF-7 breast cancer cells with romidepsin in the presence of the P-gp inhibitor verapamil to reduce the likelihood of P-gp-mediated resistance. The resulting cell line, MCF-7 DpVp300, does not express P-gp and was found to be selectively resistant to romidepsin but not to other HDACis such as belinostat, panobinostat, or vorinostat. RNA-sequencing analysis revealed upregulation of the mRNA coding for the putative methyltransferase, METTL7A, whose paralog, METTL7B, was previously shown to methylate thiol groups on hydrogen sulfide and captopril. As romidepsin has a thiol as the zinc-binding moiety, we hypothesized that METTL7A could inactivate romidepsin and other thiol-based HDACis via methylation of the thiol group. We demonstrate that expression of METTL7A or METTL7B confers resistance to thiol-based HDACis and that both enzymes are capable of methylating thiol-containing HDACis. We thus propose that METTL7A and METTL7B confer resistance to thiol-based HDACis by methylating and inactivating the zinc-binding thiol.

Enhancer-promoter interactions become more instructive in the transition from cell-fate specification to tissue differentiation

To regulate expression, enhancers must come in proximity to their target gene. However, the relationship between the timing of enhancer-promoter (E-P) proximity and activity remains unclear, with examples of uncoupled, anticorrelated and correlated interactions. To assess this, we selected 600 characterized enhancers or promoters with tissue-specific activity in Drosophila embryos and performed Capture-C in FACS-purified myogenic or neurogenic cells during specification and tissue differentiation. This enabled direct comparison between E-P proximity and activity transitioning from OFF-to-ON and ON-to-OFF states across developmental conditions. This showed remarkably similar E-P topologies between specified muscle and neuronal cells, which are uncoupled from activity. During tissue differentiation, many new distal interactions emerge where changes in E-P proximity reflect changes in activity. The mode of E-P regulation therefore appears to change as embryogenesis proceeds, from largely permissive topologies during cell-fate specification to more instructive regulation during terminal tissue differentiation, when E-P proximity is coupled to activation.

AIRE relies on Z-DNA to flag gene targets for thymic T cell tolerization

AIRE is an unconventional transcription factor that enhances the expression of thousands of genes in medullary thymic epithelial cells and promotes clonal deletion or phenotypic diversion of self-reactive T cells1-4. The biological logic of AIRE's target specificity remains largely unclear as, in contrast to many transcription factors, it does not bind to a particular DNA sequence motif. Here we implemented two orthogonal approaches to investigate AIRE's cis-regulatory mechanisms: construction of a convolutional neural network and leveraging natural genetic variation through analysis of F1 hybrid mice5. Both approaches nominated Z-DNA and NFE2-MAF as putative positive influences on AIRE's target choices. Genome-wide mapping studies revealed that Z-DNA-forming and NFE2L2-binding motifs were positively associated with the inherent ability of a gene's promoter to generate DNA double-stranded breaks, and promoters showing strong double-stranded break generation were more likely to enter a poised state with accessible chromatin and already-assembled transcriptional machinery. Consequently, AIRE preferentially targets genes with poised promoters. We propose a model in which Z-DNA anchors the AIRE-mediated transcriptional program by enhancing double-stranded break generation and promoter poising. Beyond resolving a long-standing mechanistic conundrum, these findings suggest routes for manipulating T cell tolerance.

A Meta-analysis of Transcriptome Data to Investigate the Effect of Soy Isoflavones on Breast Cancer Cell

Background

Breast cancer ranks as the second highest cause of cancer-linked deaths in women, with varying rates between Western and Asian countries. The consumption of phytoestrogens can influence breast cancer occurrence.

Objective

To comprehend how soy isoflavones impact breast cancer cells, we conducted a meta-analysis, combining gene expression data from multiple studies. This approach aimed to identify crucial transcriptional characteristics driving breast cancer cell response to soy phytoestrogens.

Materials and Methods

The gene expression profiles obtained from the Gene Expression Omnibus and Array Express and were grouped into control and isoflavones exposure conditions. We performed a meta-analysis based on the effect size combination method to identify the differentially expressed genes (DEGs). In addition, we performed Gene Ontology (GO) enrichment analysis, pathway analysis, weighted gene co-expression network analysis (WGCNA) and recursive support vector machine (R-SVM) algorithm.

Results

Based on this meta-analysis, we identified 3,890 DEGs, of which 2,173 were up-regulated and 1,717 were down-regulated. For example, SGCG, PLK2, and TBC1D9 were the most highly down-regulated genes and EGR3, WISP2, and FKBP4 were the most highly expressed genes in the isoflavones exposure condition. The functional enrichment and pathway analysis were revealed "cell division" and "cell cycle" among the most enriched terms. Among the identified DEGs, 269 transcription factor (TF) genes belonged to 42 TF families, where the C2H2 ZF, bZIP, and bHLH were the most prominent families. We also employed the R-SVM for detecting the most important genes to classify samples into isoflavones exposure and control conditions. It identified a subset of 100 DEGs related to regulation of cell growth, response to estradiol, and intermediate ribonucleoside monophosphate in the purine (IMP) metabolic process. Moreover, the WGCNA separated the DEGs into five discrete modules strongly enriched for genes involved in cell division, DNA replication, embryonic digit morphogenesis, and cell-cell adhesion.

Conclusion

Our analysis provides evidence suggesting that isoflavone affects various mechanisms in cells, including pathways associated with NF-κB, Akt, MAPK, Wnt, Notch, p53, and AR pathways, which can lead to the induction of apoptosis, the alteration of the cell cycle, the inhibition of angiogenesis, and interference in the redox state of cells. These findings can shed light on the molecular mechanisms that underlie the response of breast cancer cells to isoflavones.

Use of gene regulatory network analysis to repurpose drugs to treat bipolar disorder

BACKGROUND

Bipolar disorder (BD) presents significant challenges in drug discovery, necessitating alternative approaches. Drug repurposing, leveraging computational techniques and expanding biomedical data, holds promise for identifying novel treatment strategies.

METHODS

This study utilized gene regulatory networks (GRNs) to identify significant regulatory changes in BD, using network-based signatures for drug repurposing. Employing the PANDA algorithm, we investigated the variations in transcription factor-GRNs between individuals with BD and unaffected individuals, incorporating binding motifs, protein interactions, and gene co-expression data. The differences in edge weights between BD and controls were then used as differential network signatures to identify drugs potentially targeting the disease-associated gene signature, employing the CLUEreg tool in the GRAND database.

RESULTS

Using a large RNA-seq dataset of 216 post-mortem brain samples from the CommonMind consortium, we constructed GRNs based on co-expression for individuals with BD and unaffected controls, involving 15,271 genes and 405 TFs. Our analysis highlighted significant influences of these TFs on immune response, energy metabolism, cell signalling, and cell adhesion pathways in the disorder. By employing drug repurposing, we identified 10 promising candidates potentially repurposed as BD treatments.

LIMITATIONS

Non-drug-naïve transcriptomics data, bulk analysis of BD samples, potential bias of GRNs towards well-studied genes.

CONCLUSIONS

Further investigation into repurposing candidates, especially those with preclinical evidence supporting their efficacy, like kaempferol and pramocaine, is warranted to understand their mechanisms of action and effectiveness in treating BD. Additionally, novel targets such as PARP1 and A2b offer opportunities for future research on their relevance to the disorder.

Transcription Factors behind MYB98 Regulation: What Does the Discovery of SaeM Suggest?

MYB98 is master regulator of the molecular network involved in pollen tube attraction. Until recently, it was unclear how this gene exhibits exclusively synergid cell-specific expression in ovule. Our recent study has established that a 16-bp-long SaeM element is crucial for its synergid cell-specific expression in ovule, and an 84-bp-long fragment harboring SaeM is sufficient to drive the process. In this study, we have developed a workflow to predict functional roles of potential transcription factors (TFs) putatively binding to the promoter region, taking MYB98 promoter as a test subject. After sequential assessment of co-expression pattern, network analysis, and potential master regulator identification, we have proposed a multi-TF model for MYB98 regulation. Our study suggests that ANL2, GT-1, and their respective homologs could be direct regulators of MYB98 and indicates that TCP15, TCP16, FRS9, and HB34 are likely master regulators of the majority of the TFs involved in its regulation. Comprehensive studies in the future are expected to offer more insights into such propositions. Developed workflow can be used while designing similar regulome-related studies for any other species and genes.

A Foxf1-Wnt-Nr2f1 cascade promotes atrial cardiomyocyte differentiation in zebrafish

Nr2f transcription factors (TFs) are conserved regulators of vertebrate atrial cardiomyocyte (AC) differentiation. However, little is known about the mechanisms directing Nr2f expression in ACs. Here, we identified a conserved enhancer 3' to the nr2f1a locus, which we call 3'reg1-nr2f1a (3'reg1), that can promote Nr2f1a expression in ACs. Sequence analysis of the enhancer identified putative Lef/Tcf and Foxf TF binding sites. Mutation of the Lef/Tcf sites within the 3'reg1 reporter, knockdown of Tcf7l1a, and manipulation of canonical Wnt signaling support that Tcf7l1a is derepressed via Wnt signaling to activate the transgenic enhancer and promote AC differentiation. Similarly, mutation of the Foxf binding sites in the 3'reg1 reporter, coupled with gain- and loss-of-function analysis supported that Foxf1 promotes expression of the enhancer and AC differentiation. Functionally, we find that Wnt signaling acts downstream of Foxf1 to promote expression of the 3'reg1 reporter within ACs and, importantly, both Foxf1 and Wnt signaling require Nr2f1a to promote a surplus of differentiated ACs. CRISPR-mediated deletion of the endogenous 3'reg1 abrogates the ability of Foxf1 and Wnt signaling to produce surplus ACs in zebrafish embryos. Together, our data support that downstream members of a conserved regulatory network involving Wnt signaling and Foxf1 function on a nr2f1a enhancer to promote AC differentiation in the zebrafish heart.

Overlapping binding sites underlie TF genomic occupancy

Sequence-specific DNA binding by transcription factors (TFs) is a crucial step in gene regulation. However, current high-throughput in vitro approaches cannot reliably detect lower affinity TF-DNA interactions, which play key roles in gene regulation. Here, we developed PADIT-seq ( p rotein a ffinity to D NA by in vitro transcription and RNA seq uencing) to assay TF binding preferences to all 10-bp DNA sequences at far greater sensitivity than prior approaches. The expanded catalogs of low affinity DNA binding sites for the human TFs HOXD13 and EGR1 revealed that nucleotides flanking high affinity DNA binding sites create overlapping lower affinity sites that together modulate TF genomic occupancy in vivo . Formation of such extended recognition sequences stems from an inherent property of TF binding sites to interweave each other and expands the genomic sequence space for identifying noncoding variants that directly alter TF binding.

One-Sentence Summary

Overlapping DNA binding sites underlie TF genomic occupancy through their inherent propensity to interweave each other.

ElemeNT 2023: an enhanced tool for detection and curation of core promoter elements

MOTIVATION

Prediction and identification of core promoter elements and transcription factor binding sites is essential for understanding the mechanism of transcription initiation and deciphering the biological activity of a specific locus. Thus, there is a need for an up-to-date tool to detect and curate core promoter elements/motifs in any provided nucleotide sequences.

RESULTS

Here, we introduce ElemeNT 2023-a new and enhanced version of the Elements Navigation Tool, which provides novel capabilities for assessing evolutionary conservation and for readily evaluating the quality of high-throughput transcription start site (TSS) datasets, leveraging preferential motif positioning. ElemeNT 2023 is accessible both as a fast web-based tool and via command line (no coding skills are required to run the tool). While this tool is focused on core promoter elements, it can also be used for searching any user-defined motif, including sequence-specific DNA binding sites. Furthermore, ElemeNT's CORE database, which contains predicted core promoter elements around annotated TSSs, is now expanded to cover 10 species, ranging from worms to human. In this applications note, we describe the new workflow and demonstrate a case study using ElemeNT 2023 for core promoter composition analysis of diverse species, revealing motif prevalence and highlighting evolutionary insights. We discuss how this tool facilitates the exploration of uncharted transcriptomic data, appraises TSS quality, and aids in designing synthetic promoters for gene expression optimization. Taken together, ElemeNT 2023 empowers researchers with comprehensive tools for meticulous analysis of sequence elements and gene expression strategies.

AVAILABILITY AND IMPLEMENTATION

ElemeNT 2023 is freely available at https://www.juven-gershonlab.org/resources/element-v2023/. The source code and command line version of ElemeNT 2023 are available at https://github.com/OritAdato/ElemeNT. No coding skills are required to run the tool.

ZmC2H2-149 negatively regulates drought tolerance by repressing ZmHSD1 in maize

Drought is a major abiotic stress that limits maize production worldwide. Therefore, it is of great importance to improve drought tolerance in crop plants for sustainable agriculture. In this study, we examined the roles of Cys2 /His2 zinc-finger-proteins (C2H2-ZFPs) in maize's drought tolerance as C2H2-ZFPs have been implicated for plant stress tolerance. By subjecting 150 Ac/Ds mutant lines to drought stress, we successfully identified a Ds-insertion mutant, zmc2h2-149, which shows increased tolerance to drought stress. Overexpression of ZmC2H2-149 in maize led to a decrease in both drought tolerance and crop yield. DAP-Seq, RNA-Seq, Y1H and LUC assays additionally showed that ZmC2H2-149 directly suppresses the expression of a positive drought tolerance regulator, ZmHSD1 (hydroxysteroid dehydrogenase 1). Consistently, the zmhsd1 mutants exhibited decreased drought tolerance and grain yield under water deficit conditions compared to their respective wild-type plants. Our findings thus demonstrated that ZmC2H2-149 can regulate ZmHSD1 for drought stress tolerance in maize, offering valuable theoretical and genetic resources for maize breeding programmes that aim for improving drought tolerance.

ETS transcription factors regulate precise matrix metalloproteinase expression and follicle rupture in Drosophila

Drosophila matrix metalloproteinase 2 (MMP2) is specifically expressed in posterior follicle cells of stage-14 egg chambers (mature follicles) and is crucial for the breakdown of the follicular wall during ovulation, a process that is highly conserved from flies to mammals. The factors that regulate spatiotemporal expression of MMP2 in follicle cells remain unknown. Here, we demonstrate crucial roles for the ETS-family transcriptional activator Pointed (Pnt) and its endogenous repressor Yan in the regulation of MMP2 expression. We found that Pnt is expressed in posterior follicle cells and overlaps with MMP2 expression in mature follicles. Genetic analysis demonstrated that pnt is both required and sufficient for MMP2 expression in follicle cells. In addition, Yan was temporally upregulated in stage-13 follicle cells to fine-tune Pnt activity and MMP2 expression. Furthermore, we identified a 1.1 kb core enhancer that is responsible for the spatiotemporal expression of MMP2 and contains multiple pnt/yan binding motifs. Mutation of pnt/yan binding sites significantly impaired the Mmp2 enhancer activity. Our data reveal a mechanism of transcriptional regulation of Mmp2 expression in Drosophila ovulation, which could be conserved in other biological systems.

Regulatory activity is the default DNA state in eukaryotes

Genomes encode for genes and non-coding DNA, both capable of transcriptional activity. However, unlike canonical genes, many transcripts from non-coding DNA have limited evidence of conservation or function. Here, to determine how much biological noise is expected from non-genic sequences, we quantify the regulatory activity of evolutionarily naive DNA using RNA-seq in yeast and computational predictions in humans. In yeast, more than 99% of naive DNA bases were transcribed. Unlike the evolved transcriptome, naive transcripts frequently overlapped with opposite sense transcripts, suggesting selection favored coherent gene structures in the yeast genome. In humans, regulation-associated chromatin activity is predicted to be common in naive dinucleotide-content-matched randomized DNA. Here, naive and evolved DNA have similar co-occurrence and cell-type specificity of chromatin marks, challenging these as indicators of selection. However, in both yeast and humans, extreme high activities were rare in naive DNA, suggesting they result from selection. Overall, basal regulatory activity seems to be the default, which selection can hone to evolve a function or, if detrimental, repress.

Less-is-more: selecting transcription factor binding regions informative for motif inference

Numerous statistical methods have emerged for inferring DNA motifs for transcription factors (TFs) from genomic regions. However, the process of selecting informative regions for motif inference remains understudied. Current approaches select regions with strong ChIP-seq signal for a given TF, assuming that such strong signal primarily results from specific interactions between the TF and its motif. Additionally, these selection approaches do not account for non-target motifs, i.e. motifs of other TFs; they presume the occurrence of these non-target motifs infrequent compared to that of the target motif, and thus assume these have minimal interference with the identification of the target. Leveraging extensive ChIP-seq datasets, we introduced the concept of TF signal 'crowdedness', referred to as C-score, for each genomic region. The C-score helps in highlighting TF signals arising from non-specific interactions. Moreover, by considering the C-score (and adjusting for the length of genomic regions), we can effectively mitigate interference of non-target motifs. Using these tools, we find that in many instances, strong ChIP-seq signal stems mainly from non-specific interactions, and the occurrence of non-target motifs significantly impacts the accurate inference of the target motif. Prioritizing genomic regions with reduced crowdedness and short length markedly improves motif inference. This 'less-is-more' effect suggests that ChIP-seq region selection warrants more attention.

Optimizing sequence design strategies for perturbation MPRAs: a computational evaluation framework

The advent of perturbation-based massively parallel reporter assays (MPRAs) technique has facilitated the delineation of the roles of non-coding regulatory elements in orchestrating gene expression. However, computational efforts remain scant to evaluate and establish guidelines for sequence design strategies for perturbation MPRAs. In this study, we propose a framework for evaluating and comparing various perturbation strategies for MPRA experiments. Within this framework, we benchmark three different perturbation approaches from the perspectives of alteration in motif-based profiles, consistency of MPRA outputs, and robustness of models that predict the activities of putative regulatory motifs. While our analyses show very similar results across multiple benchmarking metrics, the predictive modeling for the approach involving random nucleotide shuffling shows significant robustness compared with the other two approaches. Thus, we recommend designing sequences by randomly shuffling the nucleotides of the perturbed site in perturbation-MPRA, followed by a coherence check to prevent the introduction of other variations of the target motifs. In summary, our evaluation framework and the benchmarking findings create a resource of computational pipelines and highlight the potential of perturbation-MPRA in predicting non-coding regulatory activities.

The gene regulatory basis of bystander activation in CD8+ T cells

CD8+ T cells are classically recognized as adaptive lymphocytes based on their ability to recognize specific foreign antigens and mount memory responses. However, recent studies indicate that some antigen-inexperienced CD8+ T cells can respond to innate cytokines alone in the absence of cognate T cell receptor stimulation, a phenomenon referred to as bystander activation. Here, we demonstrate that neonatal CD8+ T cells undergo a robust and diverse program of bystander activation, which corresponds to enhanced innate-like protection against unrelated pathogens. Using a multi-omics approach, we found that the ability of neonatal CD8+ T cells to respond to innate cytokines derives from their capacity to undergo rapid chromatin remodeling, resulting in the usage of a distinct set of enhancers and transcription factors typically found in innate-like T cells. We observed that the switch between innate and adaptive functions in the CD8+ T cell compartment is mediated by changes in the abundance of distinct subsets of cells. The innate CD8+ T cell subset that predominates in early life was also present in adult mice and humans. Our findings provide support for the layered immune hypothesis and indicate that the CD8+ T cell compartment is more functionally diverse than previously thought.

Cacao pod transcriptome profiling of seven genotypes identifies features associated with post-penetration resistance to Phytophthora palmivora

The oomycete Phytophthora palmivora infects the fruit of cacao trees (Theobroma cacao) causing black pod rot and reducing yields. Cacao genotypes vary in their resistance levels to P. palmivora, yet our understanding of how cacao fruit respond to the pathogen at the molecular level during disease establishment is limited. To address this issue, disease development and RNA-Seq studies were conducted on pods of seven cacao genotypes (ICS1, WFT, Gu133, Spa9, CCN51, Sca6 and Pound7) to better understand their reactions to the post-penetration stage of P. palmivora infection. The pod tissue-P. palmivora pathogen assay resulted in the genotypes being classified as susceptible (ICS1, WFT, Gu133 and Spa9) or resistant (CCN51, Sca6 and Pound7). The number of differentially expressed genes (DEGs) ranged from 1625 to 6957 depending on genotype. A custom gene correlation approach identified 34 correlation groups. De novo motif analysis was conducted on upstream promoter sequences of differentially expressed genes, identifying 76 novel motifs, 31 of which were over-represented in the upstream sequences of correlation groups and associated with gene ontology terms related to oxidative stress response, defense against fungal pathogens, general metabolism and cell function. Genes in one correlation group (Group 6) were strongly induced in all genotypes and enriched in genes annotated with defense-responsive terms. Expression pattern profiling revealed that genes in Group 6 were induced to higher levels in the resistant genotypes. An additional analysis allowed the identification of 17 candidate cis-regulatory modules likely to be involved in cacao defense against P. palmivora. This study is a comprehensive exploration of the cacao pod transcriptional response to P. palmivora spread after infection. We identified cacao genes, promoter motifs, and promoter motif combinations associated with post-penetration resistance to P. palmivora in cacao pods and provide this information as a resource to support future and ongoing efforts to breed P. palmivora-resistant cacao.

G-quadruplex DNA structure is a positive regulator of MYC transcription

DNA structure can regulate genome function. Four-stranded DNA G-quadruplex (G4) structures have been implicated in transcriptional regulation; however, previous studies have not directly addressed the role of an individual G4 within its endogenous cellular context. Using CRISPR to genetically abrogate endogenous G4 structure folding, we directly interrogate the G4 found within the upstream regulatory region of the critical human MYC oncogene. G4 loss leads to suppression of MYC transcription from the P1 promoter that is mediated by the deposition of a de novo nucleosome alongside alterations in RNA polymerase recruitment. We also show that replacement of the endogenous MYC G4 with a different G4 structure from the KRAS oncogene restores G4 folding and MYC transcription. Moreover, we demonstrate that the MYC G4 structure itself, rather than its sequence, recruits transcription factors and histone modifiers. Overall, our work establishes that G4 structures are important features of transcriptional regulation that coordinate recruitment of key chromatin proteins and the transcriptional machinery through interactions with DNA secondary structure, rather than primary sequence.

Predicting proximal tubule failed repair drivers through regularized regression analysis of single cell multiomic sequencing

Renal proximal tubule epithelial cells have considerable intrinsic repair capacity following injury. However, a fraction of injured proximal tubule cells fails to undergo normal repair and assumes a proinflammatory and profibrotic phenotype that may promote fibrosis and chronic kidney disease. The healthy to failed repair change is marked by cell state-specific transcriptomic and epigenomic changes. Single nucleus joint RNA- and ATAC-seq sequencing offers an opportunity to study the gene regulatory networks underpinning these changes in order to identify key regulatory drivers. We develop a regularized regression approach to construct genome-wide parametric gene regulatory networks using multiomic datasets. We generate a single nucleus multiomic dataset from seven adult human kidney samples and apply our method to study drivers of a failed injury response associated with kidney disease. We demonstrate that our approach is a highly effective tool for predicting key cis- and trans-regulatory elements underpinning the healthy to failed repair transition and use it to identify NFAT5 as a driver of the maladaptive proximal tubule state.

Single-cell transcriptome analysis dissects lncRNA-associated gene networks in Arabidopsis

The plant genome produces an extremely large collection of long noncoding RNAs (lncRNAs) that are generally expressed in a context-specific manner and have pivotal roles in regulation of diverse biological processes. Here, we mapped the transcriptional heterogeneity of lncRNAs and their associated gene regulatory networks at single-cell resolution. We generated a comprehensive cell atlas at the whole-organism level by integrative analysis of 28 published single-cell RNA sequencing (scRNA-seq) datasets from juvenile Arabidopsis seedlings. We then provided an in-depth analysis of cell-type-related lncRNA signatures that show expression patterns consistent with canonical protein-coding gene markers. We further demonstrated that the cell-type-specific expression of lncRNAs largely explains their tissue specificity. In addition, we predicted gene regulatory networks on the basis of motif enrichment and co-expression analysis of lncRNAs and mRNAs, and we identified putative transcription factors orchestrating cell-type-specific expression of lncRNAs. The analysis results are available at the single-cell-based plant lncRNA atlas database (scPLAD; https://biobigdata.nju.edu.cn/scPLAD/). Overall, this work demonstrates the power of integrative single-cell data analysis applied to plant lncRNA biology and provides fundamental insights into lncRNA expression specificity and associated gene regulation.

Embryo-endometrial interaction associated with the location of the embryo during the mobility phase in mares

Embryo-maternal crosstalk is essential to establish pregnancy, with the equine embryo moving throughout the uterus on days 9-15 (ovulation = day 0) as part of this interaction. We hypothesized that the presence of a mobile embryo induces local changes in the gene expression of the endometrium. On Day 12, the endometrial transcripts were compared among three groups: uterine horn with an embryo (P+, n = 7), without an embryo (P-, n = 7) in pregnant mares, and both uterine horns of nonbred mares (NB, n = 6). We identified 1,101 differentially expressed genes (DEGs) between P+ vs. NB and 1,229 DEGs between P- vs. NB. The genes upregulated in both P+ and P- relative to NB were involved in growth factor pathway and fatty acid activation, while downregulated genes were associated with oxytocin signaling pathway and estrogen receptor signaling. Comparing the transcriptome of P+ to that of P-, we found 59 DEGs, of which 30 genes had a higher expression in P+. These genes are associated with regulating vascular growth factors and the immune system, all known to be essential in early pregnancy. Overall, this study suggests that the mobile embryo influences the endometrial gene expression locally.

Data integration and inference of gene regulation using single-cell temporal multimodal data with scTIE

Single-cell technologies offer unprecedented opportunities to dissect gene regulatory mechanisms in context-specific ways. Although there are computational methods for extracting gene regulatory relationships from scRNA-seq and scATAC-seq data, the data integration problem, essential for accurate cell type identification, has been mostly treated as a standalone challenge. Here we present scTIE, a unified method that integrates temporal multimodal data and infers regulatory relationships predictive of cellular state changes. scTIE uses an autoencoder to embed cells from all time points into a common space by using iterative optimal transport, followed by extracting interpretable information to predict cell trajectories. Using a variety of synthetic and real temporal multimodal data sets, we show scTIE achieves effective data integration while preserving more biological signals than existing methods, particularly in the presence of batch effects and noise. Furthermore, on the exemplar multiome data set we generated from differentiating mouse embryonic stem cells over time, we show scTIE captures regulatory elements highly predictive of cell transition probabilities, providing new potentials to understand the regulatory landscape driving developmental processes.

Cell-type-directed design of synthetic enhancers

Transcriptional enhancers act as docking stations for combinations of transcription factors and thereby regulate spatiotemporal activation of their target genes1. It has been a long-standing goal in the field to decode the regulatory logic of an enhancer and to understand the details of how spatiotemporal gene expression is encoded in an enhancer sequence. Here we show that deep learning models2-6, can be used to efficiently design synthetic, cell-type-specific enhancers, starting from random sequences, and that this optimization process allows detailed tracing of enhancer features at single-nucleotide resolution. We evaluate the function of fully synthetic enhancers to specifically target Kenyon cells or glial cells in the fruit fly brain using transgenic animals. We further exploit enhancer design to create 'dual-code' enhancers that target two cell types and minimal enhancers smaller than 50 base pairs that are fully functional. By examining the state space searches towards local optima, we characterize enhancer codes through the strength, combination and arrangement of transcription factor activator and transcription factor repressor motifs. Finally, we apply the same strategies to successfully design human enhancers, which adhere to enhancer rules similar to those of Drosophila enhancers. Enhancer design guided by deep learning leads to better understanding of how enhancers work and shows that their code can be exploited to manipulate cell states.

An epigenetic barrier sets the timing of human neuronal maturation

The pace of human brain development is highly protracted compared with most other species1-7. The maturation of cortical neurons is particularly slow, taking months to years to develop adult functions3-5. Remarkably, such protracted timing is retained in cortical neurons derived from human pluripotent stem cells (hPSCs) during in vitro differentiation or upon transplantation into the mouse brain4,8,9. Those findings suggest the presence of a cell-intrinsic clock setting the pace of neuronal maturation, although the molecular nature of this clock remains unknown. Here we identify an epigenetic developmental programme that sets the timing of human neuronal maturation. First, we developed a hPSC-based approach to synchronize the birth of cortical neurons in vitro which enabled us to define an atlas of morphological, functional and molecular maturation. We observed a slow unfolding of maturation programmes, limited by the retention of specific epigenetic factors. Loss of function of several of those factors in cortical neurons enables precocious maturation. Transient inhibition of EZH2, EHMT1 and EHMT2 or DOT1L, at progenitor stage primes newly born neurons to rapidly acquire mature properties upon differentiation. Thus our findings reveal that the rate at which human neurons mature is set well before neurogenesis through the establishment of an epigenetic barrier in progenitor cells. Mechanistically, this barrier holds transcriptional maturation programmes in a poised state that is gradually released to ensure the prolonged timeline of human cortical neuron maturation.

Systematic identification of genotype-dependent enhancer variants in eosinophilic esophagitis

Eosinophilic esophagitis (EoE) is a rare atopic disorder associated with esophageal dysfunction, including difficulty swallowing, food impaction, and inflammation, that develops in a small subset of people with food allergies. Genome-wide association studies (GWASs) have identified 9 independent EoE risk loci reaching genome-wide significance (p < 5 × 10-8) and 27 additional loci of suggestive significance (5 × 10-8 < p < 1 × 10-5). In the current study, we perform linkage disequilibrium (LD) expansion of these loci to nominate a set of 531 variants that are potentially causal. To systematically interrogate the gene regulatory activity of these variants, we designed a massively parallel reporter assay (MPRA) containing the alleles of each variant within their genomic sequence context cloned into a GFP reporter library. Analysis of reporter gene expression in TE-7, HaCaT, and Jurkat cells revealed cell-type-specific gene regulation. We identify 32 allelic enhancer variants, representing 6 genome-wide significant EoE loci and 7 suggestive EoE loci, that regulate reporter gene expression in a genotype-dependent manner in at least one cellular context. By annotating these variants with expression quantitative trait loci (eQTL) and chromatin looping data in related tissues and cell types, we identify putative target genes affected by genetic variation in individuals with EoE. Transcription factor enrichment analyses reveal possible roles for cell-type-specific regulators, including GATA3. Our approach reduces the large set of EoE-associated variants to a set of 32 with allelic regulatory activity, providing functional insights into the effects of genetic variation in this disease.

Transcription factor CEBPB mediates intracranial aneurysm rupture by inflammatory and immune response

INTRODUCTION

Genetic factors play a major part in mediating intracranial aneurysm (IA) rupture. However, research on the role of transcription factors (TFs) in IA rupture is rare.

AIMS

Bioinformatics analysis was performed to explore the TFs and related functional pathways involved in IA rupture.

RESULTS

A total of 63 differentially expressed transcription factors (DETFs) were obtained. Significantly enriched biological processes of these DETFs were related to regulation of myeloid leukocyte differentiation. The top 10 DETFs were screened based on the MCC algorithm from the protein-protein interaction network. After screening and validation, it was finally determined that CEBPB may be the hub gene for aneurysm rupture. The GSEA results of CEBPB were mainly associated with the inflammatory response, which was also verified by the experimental model of cellular inflammation in vitro.

CONCLUSION

The inflammatory and immune response may be closely associated with aneurysm rupture. CEBPB may be the hub gene for aneurysm rupture and may have diagnostic value. Therefore, CEBPB may serve as the diagnostic signature for RIAs and a potential target for intervention.

Cotton GhNAC4 promotes drought tolerance by regulating secondary cell wall biosynthesis and ribosomal protein homeostasis

Drought has a severe impact on the quality and yield of cotton. Deciphering the key genes related to drought tolerance is important for understanding the regulation mechanism of drought stress and breeding drought-tolerant cotton cultivars. Several studies have demonstrated that NAC transcription factors are crucial in the regulation of drought stress, however, the related functional mechanisms are still largely unexplored. Here, we identified that NAC transcription factor GhNAC4 positively regulated drought stress tolerance in cotton. The expression of GhNAC4 was significantly induced by abiotic stress and plant hormones. Silencing of GhNAC4 distinctly impaired the resistance to drought stress and overexpressing GhNAC4 in cotton significantly enhanced the stress tolerance. RNA-seq analysis revealed that overexpression of GhNAC4 enriched the expression of genes associated with the biosynthesis of secondary cell walls and ribosomal proteins. We confirmed that GhNAC4 positively activated the expressions of GhNST1, a master regulator reported previously in secondary cell wall formation, and two ribosomal protein-encoding genes GhRPL12 and GhRPL18p, by directly binding to their promoter regions. Overexpression of GhNAC4 promoted the expression of downstream genes associated with the secondary wall biosynthesis, resulting in enhancing secondary wall deposition in the roots, and silencing of GhRPL12 and GhRPL18p significantly impaired the resistance to drought stress. Taken together, our study reveals a novel pathway mediated by GhNAC4 that promotes secondary cell wall biosynthesis to strengthen secondary wall development and regulates the expression of ribosomal protein-encoding genes to maintain translation stability, which ultimately enhances drought tolerance in cotton.

Endothelial cells adopt a pro-reparative immune responsive signature during cardiac injury

Modulation of the heart's immune microenvironment is crucial for recovery after ischemic events such as myocardial infarction (MI). Endothelial cells (ECs) can have immune regulatory functions; however, interactions between ECs and the immune environment in the heart after MI remain poorly understood. We identified an EC-specific IFN responsive and immune regulatory gene signature in adult and pediatric heart failure (HF) tissues. Single-cell transcriptomic analysis of murine hearts subjected to MI uncovered an EC population (IFN-ECs) with immunologic gene signatures similar to those in human HF. IFN-ECs were enriched in regenerative-stage mouse hearts and expressed genes encoding immune responsive transcription factors (Irf7, Batf2, and Stat1). Single-cell chromatin accessibility studies revealed an enrichment of these TF motifs at IFN-EC signature genes. Expression of immune regulatory ligand genes by IFN-ECs suggests bidirectional signaling between IFN-ECs and macrophages in regenerative-stage hearts. Our data suggest that ECs may adopt immune regulatory signatures after cardiac injury to accompany the reparative response. The presence of these signatures in human HF and murine MI models suggests a potential role for EC-mediated immune regulation in responding to stress induced by acute injury in MI and chronic adverse remodeling in HF.

MMR vaccination induces trained immunity via functional and metabolic reprogramming of γδ T cells

The measles, mumps, and rubella (MMR) vaccine protects against all-cause mortality in children, but the immunological mechanisms mediating these effects are poorly known. We systematically investigated whether MMR can induce long-term functional changes in innate immune cells, a process termed trained immunity, that could at least partially mediate this heterologous protection. In a randomized, placebo-controlled trial, 39 healthy adults received either the MMR vaccine or a placebo. Using single-cell RNA-Seq, we found that MMR caused transcriptomic changes in CD14+ monocytes and NK cells, but most profoundly in γδ T cells. Monocyte function was not altered by MMR vaccination. In contrast, the function of γδ T cells was markedly enhanced by MMR vaccination, with higher production of TNF and IFN-γ, as well as upregulation of cellular metabolic pathways. In conclusion, we describe a trained immunity program characterized by modulation of γδ T cell function induced by MMR vaccination.

Predicting the DNA binding specificity of mutated transcription factors using family-level biophysically interpretable machine learning

Sequence-specific interactions of transcription factors (TFs) with genomic DNA underlie many cellular processes. High-throughput in vitro binding assays coupled with computational analysis have made it possible to accurately define such sequence recognition in a biophysically interpretable yet mechanism-agonistic way for individual TFs. The fact that such sequence-to-affinity models are now available for hundreds of TFs provides new avenues for predicting how the DNA binding specificity of a TF changes when its protein sequence is mutated. To this end, we developed an analytical framework based on a tetrahedron embedding that can be applied at the level of a given structural TF family. Using bHLH as a test case, we demonstrate that we can systematically map dependencies between the protein sequence of a TF and base preference within the DNA binding site. We also develop a regression approach to predict the quantitative energetic impact of mutations in the DNA binding domain of a TF on its DNA binding specificity, and perform SELEX-seq assays on mutated TFs to experimentally validate our results. Our results point to the feasibility of predicting the functional impact of disease mutations and allelic variation in the cell-wide TF repertoire by leveraging high-quality functional information across sets of homologous wild-type proteins.

Harnessing genetic engineering to drive economic bioproduct production in algae

Our reliance on agriculture for sustenance, healthcare, and resources has been essential since the dawn of civilization. However, traditional agricultural practices are no longer adequate to meet the demands of a burgeoning population amidst climate-driven agricultural challenges. Microalgae emerge as a beacon of hope, offering a sustainable and renewable source of food, animal feed, and energy. Their rapid growth rates, adaptability to non-arable land and non-potable water, and diverse bioproduct range, encompassing biofuels and nutraceuticals, position them as a cornerstone of future resource management. Furthermore, microalgae's ability to capture carbon aligns with environmental conservation goals. While microalgae offers significant benefits, obstacles in cost-effective biomass production persist, which curtails broader application. This review examines microalgae compared to other host platforms, highlighting current innovative approaches aimed at overcoming existing barriers. These approaches include a range of techniques, from gene editing, synthetic promoters, and mutagenesis to selective breeding and metabolic engineering through transcription factors.

Joint-specific rheumatoid arthritis fibroblast-like synoviocyte regulation identified by integration of chromatin access and transcriptional activity

The mechanisms responsible for the distribution and severity of joint involvement in rheumatoid arthritis (RA) are not known. To explore whether site-specific FLS biology might be associated with location-specific synovitis and explain the predilection for hand (wrist/metacarpal phalangeal joints) involvement in RA, we generated transcriptomic and chromatin accessibility data from FLS to identify the transcription factors (TFs) and pathways. Networks were constructed by integration of chromatin accessibility and gene expression data. Analysis revealed joint-specific patterns of FLS phenotype, with proliferative, migratory, proinflammatory, and matrix-degrading characteristics observed in resting FLS derived from the hand joints compared with hip or knee. TNF-stimulation amplified these differences, with greater enrichment of proinflammatory and proliferative genes in hand FLS compared with hip and knee FLS. Hand FLS also had the greatest expression of markers associated with an 'activated' state relative to the 'resting' state, with the greatest cytokine and MMP expression in TNF-stimulated hand FLS. Predicted differences in proliferation and migration were biologically validated with hand FLS exhibiting greater migration and cell growth than hip or knee FLS. Distinctive joint-specific FLS biology associated with a more aggressive inflammatory response might contribute to the distribution and severity of joint involvement in RA.

Comparative analysis of models in predicting the effects of SNPs on TF-DNA binding using large-scale in vitro and in vivo data

Non-coding variants associated with complex traits can alter the motifs of transcription factor (TF)-deoxyribonucleic acid binding. Although many computational models have been developed to predict the effects of non-coding variants on TF binding, their predictive power lacks systematic evaluation. Here we have evaluated 14 different models built on position weight matrices (PWMs), support vector machines, ordinary least squares and deep neural networks (DNNs), using large-scale in vitro (i.e. SNP-SELEX) and in vivo (i.e. allele-specific binding, ASB) TF binding data. Our results show that the accuracy of each model in predicting SNP effects in vitro significantly exceeds that achieved in vivo. For in vitro variant impact prediction, kmer/gkm-based machine learning methods (deltaSVM_HT-SELEX, QBiC-Pred) trained on in vitro datasets exhibit the best performance. For in vivo ASB variant prediction, DNN-based multitask models (DeepSEA, Sei, Enformer) trained on the ChIP-seq dataset exhibit relatively superior performance. Among the PWM-based methods, tRap demonstrates better performance in both in vitro and in vivo evaluations. In addition, we find that TF classes such as basic leucine zipper factors could be predicted more accurately, whereas those such as C2H2 zinc finger factors are predicted less accurately, aligning with the evolutionary conservation of these TF classes. We also underscore the significance of non-sequence factors such as cis-regulatory element type, TF expression, interactions and post-translational modifications in influencing the in vivo predictive performance of TFs. Our research provides valuable insights into selecting prioritization methods for non-coding variants and further optimizing such models.

Binding profiles for 954 Drosophila and C. elegans transcription factors reveal tissue specific regulatory relationships

A catalog of transcription factor (TF) binding sites in the genome is critical for deciphering regulatory relationships. Here we present the culmination of the modERN (model organism Encyclopedia of Regulatory Networks) consortium that systematically assayed TF binding events in vivo in two major model organisms, Drosophila melanogaster (fly) and Caenorhabditis elegans (worm). We describe key features of these datasets, comprising 604 TFs identifying 3.6M sites in the fly and 350 TFs identifying 0.9 M sites in the worm. Applying a machine learning model to these data identifies sets of TFs with a prominent role in promoting target gene expression in specific cell types. TF binding data are available through the ENCODE Data Coordinating Center and at https://epic.gs.washington.edu/modERNresource, which provides access to processed and summary data, as well as widgets to probe cell type-specific TF-target relationships. These data are a rich resource that should fuel investigations into TF function during development.

Three linked variants have opposing regulatory effects on isovaleryl-CoA dehydrogenase gene expression

While genome-wide association studies (GWAS) and positive selection scans identify genomic loci driving human phenotypic diversity, functional validation is required to discover the variant(s) responsible. We dissected the IVD gene locus-which encodes the isovaleryl-CoA dehydrogenase enzyme-implicated by selection statistics, multiple GWAS, and clinical genetics as important to function and fitness. We combined luciferase assays, CRISPR/Cas9 genome-editing, massively parallel reporter assays (MPRA), and a deletion tiling MPRA strategy across regulatory loci. We identified three regulatory variants, including an indel, that may underpin GWAS signals for pulmonary fibrosis and testosterone, and that are linked on a positively selected haplotype in the Japanese population. These regulatory variants exhibit synergistic and opposing effects on IVD expression experimentally. Alleles at these variants lie on a haplotype tagged by the variant most strongly associated with IVD expression and metabolites, but with no functional evidence itself. This work demonstrates how comprehensive functional investigation and multiple technologies are needed to discover the true genetic drivers of phenotypic diversity.

Deep molecular learning of transcriptional control of a synthetic CRE enhancer and its variants

Massively parallel reporter assay measures transcriptional activities of various cis-regulatory modules (CRMs) in a single experiment. We developed a thermodynamic computational model framework that calculates quantitative levels of gene expression directly from regulatory DNA sequences. Using the framework, we investigated the molecular mechanisms of cis-regulatory mutations of a synthetic enhancer that cause abnormal gene expression. We found that, in a human cell line, competitive binding between family transcription factors (TFs) with slightly different binding preferences significantly increases the accuracy of recapitulating the transcriptional effects of thousands of single- or multi-mutations. We also discovered that even if various harmful mutations occurred in an activator binding site, CRM could stably maintain or even increase gene expression through a certain form of competitive binding between family TFs. These findings enhance understanding the effect of SNPs and indels on CRMs and would help building robust custom-designed CRMs for biologics production and gene therapy.

Tissue-specific RNA-seq defines genes governing male tail tip morphogenesis in C. elegans

Caenorhabditis elegans males undergo sex-specific tail tip morphogenesis (TTM) under the control of the transcription factor DMD-3. To find genes regulated by DMD-3, We performed RNA-seq of laser-dissected tail tips. We identified 564 genes differentially expressed (DE) in wild-type males vs. dmd-3(-) males and hermaphrodites. The transcription profile of dmd-3(-) tail tips is similar to that in hermaphrodites. For validation, we analyzed transcriptional reporters for 49 genes and found male-specific or male-biased expression for 26 genes. Only 11 DE genes overlapped with genes found in a previous RNAi screen for defective TTM. GO enrichment analysis of DE genes finds upregulation of genes within the UPR (unfolded protein response) pathway and downregulation of genes involved in cuticle maintenance. Of the DE genes, 40 are transcription factors, indicating that the gene network downstream of DMD-3 is complex and potentially modular. We propose modules of genes that act together in TTM and are coregulated by DMD-3, among them the chondroitin synthesis pathway and the hypertonic stress response.

A Rapid and Simplified Method to Isolate Specific Regulators Based on Biotin-Avidin Binding Affinities in Crops

Transcription factors (TFs) are indispensable components of transcriptional regulatory pathways involved in crop growth and development. Herein, we developed a new method for the identification of upstream TFs specific to genes in crops based on the binding affinities of biotin and avidin. First, we constructed and verified the new biotin and avidin system (BAS) by a coprecipitation assay. Subsequently, the feasibility of DNA-based BAS (DBAS) was further proved by in vivo and in vitro assays. Furthermore, we cloned the promoter of rice OsNRT1.1B and the possible regulators were screened and identified. Additionally, partial candidates were validated by the electrophoresis mobility shift assay (EMSA), yeast one-hybrid, and luciferase activity assays. Remarkably, the results showed that the candidates PIP3 and PIP19 both responded to nitrate immediately and overexpression of PIP3 caused retard growth, which indicates that the candidates are functional and the new DBAS method is useful to isolate regulators in crops.

Notch signaling and Bsh homeodomain activity are integrated to diversify Drosophila lamina neuron types

Notch signaling is an evolutionarily conserved pathway for specifying binary neuronal fates, yet how it specifies different fates in different contexts remains elusive. In our accompanying paper, using the Drosophila lamina neuron types (L1-L5) as a model, we show that the primary homeodomain transcription factor (HDTF) Bsh activates secondary HDTFs Ap (L4) and Pdm3 (L5) and specifies L4/L5 neuronal fates. Here we test the hypothesis that Notch signaling enables Bsh to differentially specify L4 and L5 fates. We show asymmetric Notch signaling between newborn L4 and L5 neurons, but they are not siblings; rather, Notch signaling in L4 is due to Delta expression in adjacent L1 neurons. While Notch signaling and Bsh expression are mutually independent, Notch is necessary and sufficient for Bsh to specify L4 fate over L5. The NotchON L4, compared to NotchOFF L5, has a distinct open chromatin landscape which allows Bsh to bind distinct genomic loci, leading to L4-specific identity gene transcription. We propose a novel model in which Notch signaling is integrated with the primary HDTF activity to diversify neuron types by directly or indirectly generating a distinct open chromatin landscape that constrains the pool of genes that a primary HDTF can activate.

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 18,16,19,11 key regulators of fibroblast-like synoviocyte (FLS), T cells, B cells, and monocyte signatures and networks, respectively, in RA synovial tissues. Interestingly, FLS and B cells were driven by multiple independent co-regulatory TF clusters that included MITF, HLX, BACH1 (FLS) and KLF13, FOSB, FOSL1 (synovial 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 NKT cell and eosinophils in RA synovial tissues. Overall, our novel approach identified new and previously unsuspected 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.

Gene Network Analyses Identify Co-regulated Transcription Factors and BACH1 as a Key Driver in Rheumatoid Arthritis Fibroblast-like Synoviocytes

RNA-sequencing and differential gene expression studies have significantly advanced our understanding of pathogenic pathways underlying Rheumatoid Arthritis (RA). Yet, little is known about cell-specific regulatory networks and their contributions to disease. In this study, we focused on fibroblast-like synoviocytes (FLS), a cell type central to disease pathogenesis and joint damage in RA. We used a strategy that computed sample-specific gene regulatory networks (GRNs) to compare network properties between RA and osteoarthritis FLS. We identified 28 transcription factors (TFs) as key regulators central to the signatures of RA FLS. Six of these TFs are new and have not been previously implicated in RA, and included BACH1, HLX, and TGIF1. Several of these TFs were found to be co-regulated, and BACH1 emerged as the most significant TF and regulator. The main BACH1 targets included those implicated in fatty acid metabolism and ferroptosis. The discovery of BACH1 was validated in experiments with RA FLS. Knockdown of BACH1 in RA FLS significantly affected the gene expression signatures, reduced cell adhesion and mobility, interfered with the formation of thick actin fibers, and prevented the polarized formation of lamellipodia, all required for the RA destructive behavior of FLS. This is the first time that BACH1 is shown to have a central role in the regulation of FLS phenotypes, and gene expression signatures, as well as in ferroptosis and fatty acid metabolism. These new discoveries have the potential to become new targets for treatments aimed at selectively targeting the RA FLS.

HOCOMOCO in 2024: a rebuild of the curated collection of binding models for human and mouse transcription factors

We present a major update of the HOCOMOCO collection that provides DNA binding specificity patterns of 949 human transcription factors and 720 mouse orthologs. To make this release, we performed motif discovery in peak sets that originated from 14 183 ChIP-Seq experiments and reads from 2554 HT-SELEX experiments yielding more than 400 thousand candidate motifs. The candidate motifs were annotated according to their similarity to known motifs and the hierarchy of DNA-binding domains of the respective transcription factors. Next, the motifs underwent human expert curation to stratify distinct motif subtypes and remove non-informative patterns and common artifacts. Finally, the curated subset of 100 thousand motifs was supplied to the automated benchmarking to select the best-performing motifs for each transcription factor. The resulting HOCOMOCO v12 core collection contains 1443 verified position weight matrices, including distinct subtypes of DNA binding motifs for particular transcription factors. In addition to the core collection, HOCOMOCO v12 provides motif sets optimized for the recognition of binding sites in vivo and in vitro, and for annotation of regulatory sequence variants. HOCOMOCO is available at https://hocomoco12.autosome.org and https://hocomoco.autosome.org.