The Human Transcription Factors

Single-cell Transcriptomic Studies Unveil Potential Nodes of the Notochord Gene Regulatory Network

Transcription factors (TFs) are DNA-binding proteins able to modulate the timing, location, and levels of gene expression by binding to regulatory DNA regions. Therefore, the repertoire of TFs present in the genome of a multicellular organism and the expression of variable constellations of TFs in different cellular cohorts determine the distinctive characteristics of developing tissues and organs. The information on tissue-specific assortments of TFs, their cross-regulatory interactions, and the genes/regulatory regions targeted by each TF is summarized in gene regulatory networks (GRNs), which provide genetic blueprints for the specification, development, and differentiation of multicellular structures. In this study, we review recent transcriptomic studies focused on the complement of TFs expressed in the notochord, a distinctive feature of all chordates. We analyzed notochord-specific datasets available from organisms representative of the three chordate subphyla, and highlighted lineage-specific variations in the suite of TFs expressed in their notochord. We framed the resulting findings within a provisional evolutionary scenario, which allows the formulation of hypotheses on the genetic/genomic changes that sculpted the structure and function of the notochord on an evolutionary scale.

Ultradeep O-GlcNAc proteomics reveals widespread O-GlcNAcylation on tyrosine residues of proteins

As a unique type of glycosylation, O-linked β-N-acetylglucosamine (O-GlcNAc) modification (O-GlcNAcylation) on Ser/Thr residues of proteins was discovered 40 y ago. O-GlcNAcylation is catalyzed by two enzymes: O-GlcNAc transferase (OGT) and O-GlcNAcase (OGA), which add and remove O-GlcNAc, respectively. O-GlcNAcylation is an essential glycosylation that regulates the functions of many proteins in virtually all cellular processes. However, deep and site-specific characterization of O-GlcNAcylated proteins remains a challenge. We developed an ultradeep O-GlcNAc proteomics workflow by integrating digestion with multiple proteases, two mass spectrometric approaches (i.e., electron-transfer/higher-energy collision dissociation [EThcD] and HCD product-dependent electron-transfer/higher-energy collision dissociation [HCD-pd-EThcD]), and two data analysis tools (i.e., MaxQuant and Proteome Discoverer). The performance of this strategy was benchmarked by the analysis of whole lysates from PANC-1 (a pancreatic cancer cell line). In total, 2,831 O-GlcNAc sites were unambiguously identified, representing the largest O-GlcNAc dataset of an individual study reported so far. Unexpectedly, in addition to confirming known sites and identifying many other sites of Ser/Thr modification, O-GlcNAcylation was found on 121 tyrosine (Tyr) residues of 93 proteins. In vitro enzymatic assays showed that OGT catalyzes the transfer of O-GlcNAc onto Tyr residues of peptides and OGA catalyzes its removal. Taken together, our work reveals widespread O-GlcNAcylation on Tyr residues of proteins and that Tyr O-GlcNAcylation is mediated by OGT and OGA. As another form of glycosylation, Tyr O-GlcNAcylation is likely to have important regulatory roles.

Evolutionary trajectory of transcription factors and selection of targets for metabolic engineering

Transcription factors (TFs) provide potentially powerful tools for plant metabolic engineering as they often control multiple genes in a metabolic pathway. However, selecting the best TF for a particular pathway has been challenging, and the selection often relies significantly on phylogenetic relationships. Here, we offer examples where evolutionary relationships have facilitated the selection of the suitable TFs, alongside situations where such relationships are misleading from the perspective of metabolic engineering. We argue that the evolutionary trajectory of a particular TF might be a better indicator than protein sequence homology alone in helping decide the best targets for plant metabolic engineering efforts. This article is part of the theme issue 'The evolution of plant metabolism'.

Transcriptomic response of overexpression ZNF32 in breast cancer cells

Breast cancer is one of the deadliest malignancies in women worldwide. Zinc finger protein 32 (ZNF32) has been reported to be involved in autophagy and stem cell like properties of breast cancer cells. However, the effects, mechanisms, target genes and pathways of ZNF32 in breast cancer development have not been fully explored. In this study, stable ZNF32 overexpression breast cancer cell line was generated, and we used RNA-seq and RT-qPCR to quantify and verify the changes in transcription levels in breast cancer cells under ZNF32 overexpression. Transcriptome analysis showed that high expression of ZNF32 is accompanied by changes in downstream focal adhesion, ECM-receptor interaction, PI3K-AKT, HIPPO and TNF signaling pathways, which are critical for the occurrence and development of cancer. Multiple differentially expressed genes (DEGs) were significantly involved in cell proliferation, adhesion and migration, including 11 DEGs such as CA9, CRLF1 and ENPP2P with fundamental change of regulation modes. All the 11 DEGs were validated by RT-qPCR, and 9 of them contained potential transcriptional binding sequences of ZNF32 in their promoter region. This study provides a holistic perspective on the role and molecular mechanism of ZNF32 in breast cancer progression.

Luminal epithelial cells integrate variable responses to aging into stereotypical changes that underlie breast cancer susceptibility

Effects from aging in single cells are heterogenous, whereas at the organ- and tissue-levels aging phenotypes tend to appear as stereotypical changes. The mammary epithelium is a bilayer of two major phenotypically and functionally distinct cell lineages: luminal epithelial and myoepithelial cells. Mammary luminal epithelia exhibit substantial stereotypical changes with age that merit attention because these cells are the putative cells-of-origin for breast cancers. We hypothesize that effects from aging that impinge upon maintenance of lineage fidelity increase susceptibility to cancer initiation. We generated and analyzed transcriptomes from primary luminal epithelial and myoepithelial cells from younger <30 (y)ears old and older >55 y women. In addition to age-dependent directional changes in gene expression, we observed increased transcriptional variance with age that contributed to genome-wide loss of lineage fidelity. Age-dependent variant responses were common to both lineages, whereas directional changes were almost exclusively detected in luminal epithelia and involved altered regulation of chromatin and genome organizers such as SATB1. Epithelial expression variance of gap junction protein GJB6 increased with age, and modulation of GJB6 expression in heterochronous co-cultures revealed that it provided a communication conduit from myoepithelial cells that drove directional change in luminal cells. Age-dependent luminal transcriptomes comprised a prominent signal that could be detected in bulk tissue during aging and transition into cancers. A machine learning classifier based on luminal-specific aging distinguished normal from cancer tissue and was highly predictive of breast cancer subtype. We speculate that luminal epithelia are the ultimate site of integration of the variant responses to aging in their surrounding tissue, and that their emergent phenotype both endows cells with the ability to become cancer-cells-of-origin and represents a biosensor that presages cancer susceptibility.

Computational Identification of Milk Trait Regulation Through Transcription Factor Cooperation in Murciano-Granadina Goats

The Murciano-Granadina goat (MUG) is a renowned dairy breed, known for its adaptability and resilience, as well as for its exceptional milk traits characterized by high protein and fat content, along with low somatic cell counts. These traits are governed by complex biological processes, crucial in shaping phenotypic diversity. Thus, it is imperative to explore the factors regulating milk production and lactation for this breed. In this study, we investigated the genetic architecture of seven milk traits in MUGs, employing a two-step computational analysis to examine genotype-phenotype associations. Initially, a random forest algorithm identified the relative importance of each single-nucleotide polymorphism (SNP) in determining the traits of interest. The second step applied an information theory-based approach to exploring the complex genetic architecture of quantitative milk traits, focusing on epistatic interactions that may have been overlooked in the first step. These approaches allowed us to identify an almost distinct set of candidate genes for each trait. In contrast, by analyzing the promoter regions of these genes, we revealed common regulatory networks among the milk traits under study. These findings are crucial for understanding the molecular mechanisms underlying gene regulation, and they highlight the pivotal role of transcription factors (TFs) and their preferential interactions in the development of these traits. Notably, TFs such as DBP, HAND1E47, HOXA4, PPARA, and THAP1 were consistently identified for all traits, highlighting their important roles in immunity within the mammary gland and milk production during lactation.

Fine construction of gene coexpression network analysis using GTOM and RECODE detected a critical module of neuroblastoma stages 4 and 4S

BACKGROUND

Stage 4 neuroblastoma (NBL), a solid tumor of childhood, has a poor prognosis. Despite intensive molecular genetic studies, no targetable gene abnormalities have been identified. Stage 4S NBL has a characteristic of spontaneous regression, and elucidation of the mechanistic differences between stages 4 and 4S may improve treatment. Conventional NBL studies have mainly focused on the detection of abnormalities in individual genes and have rarely examined abnormalities in gene networks. While the gene coexpression network is expected to contribute to the detection of network abnormalities, the fragility of the network due to data noise and the extraction of arbitrary topological structures for the high-dimensional network are issues.

RESULTS

The present paper concerns the classification method of stages 4 and 4S NBL patients using highly accurate gene coexpression network analysis based on RNA-sequencing data of transcription factors (TFs). In particular, after applying a noise reduction method RECODE, generalized topological overlapping measure (GTOM), which weighs the connections of nodes in the network structure, succeeded in extracting a cluster of TFs that showed high classification performance for stages 4 and 4S. In addition, we investigated how these clusters correspond to clinical information and to TFs which control the normal adrenal tissue and NBL characters.

CONCLUSIONS

A clustering method is presented for finding intermediate-scale clusters of TFs that give considerable separation performance for distinguishing between stages 4 and 4S. It is suggested that this method is useful as a way to extract factors that contribute to the separation of groups from multiple pieces of information such as gene expression levels.

Fluctuating Chromatin Facilitates Enhancer-Promoter Communication by Regulating Transcriptional Clustering Dynamics

Enhancers regulate gene expression by forming contacts with distant promoters. Phase-separated condensates or clusters formed by transcription factors (TFs) and cofactors are thought to facilitate these enhancer-promoter (E-P) interactions. Using polymer physics, we developed distinct coarse-grained chromatin models that produce similar ensemble-averaged Hi-C maps but with "stable" and "dynamic" characteristics. Our findings, consistent with recent experiments, reveal a multistep E-P communication process. The dynamic model facilitates E-P proximity by enhancing TF clustering and subsequently promotes direct E-P interactions by destabilizing the TF clusters through chain flexibility. Our study promotes physical understanding of the molecular mechanisms governing E-P communication in transcriptional regulation.

Nascent transcript O-MAP reveals the molecular architecture of a single-locus subnuclear compartment built by RBM20 and the TTN RNA

Eukaryotic nuclei adopt a highly compartmentalized architecture that influences nearly all genomic processes. Understanding how this architecture impacts gene expression has been hindered by a lack of tools for elucidating the molecular interactions at individual genomic loci. Here, we adapt oligonucleotide-mediated proximity-interactome mapping (O-MAP) to biochemically characterize discrete, micron-scale nuclear neighborhoods. By targeting O-MAP to introns within the TTN pre-mRNA, we systematically map the chromatin loci, RNAs, and proteins within a muscle-specific RNA factory organized around the TTN locus. This reveals an unanticipated compartmental architecture that organizes cis - and trans -interacting chromosomal domains, including a hub of transcriptionally silenced chromatin. The factory also recruits dozens of unique RNA-binding and chromatin-scaffolding factors, including QKI and SAFB, along with their target transcripts. Loss of the cardiac-specific splicing factor RBM20-a master regulator of TTN splicing that is mutated in dilated cardiomyopathy-remodels nearly every facet of this architecture. This establishes O-MAP as a pioneering method for probing single-locus, microcompartment-level interactions that are opaque to conventional tools. Our findings suggest new mechanisms by which coding genes can "moonlight" in nuclear-architectural roles.

Functional characteristics and computational model of abundant hyperactive loci in the human genome

Enhancers and promoters are classically considered to be bound by a small set of transcription factors (TFs) in a sequence-specific manner. This assumption has come under increasing skepticism as the datasets of ChIP-seq assays of TFs have expanded. In particular, high-occupancy target (HOT) loci attract hundreds of TFs with often no detectable correlation between ChIP-seq peaks and DNA-binding motif presence. Here, we used a set of 1003 TF ChIP-seq datasets (HepG2, K562, H1) to analyze the patterns of ChIP-seq peak co-occurrence in combination with functional genomics datasets. We identified 43,891 HOT loci forming at the promoter (53%) and enhancer (47%) regions. HOT promoters regulate housekeeping genes, whereas HOT enhancers are involved in tissue-specific process regulation. HOT loci form the foundation of human super-enhancers and evolve under strong negative selection, with some of these loci being located in ultraconserved regions. Sequence-based classification analysis of HOT loci suggested that their formation is driven by the sequence features, and the density of mapped ChIP-seq peaks across TF-bound loci correlates with sequence features and the expression level of flanking genes. Based on the affinities to bind to promoters and enhancers we detected five distinct clusters of TFs that form the core of the HOT loci. We report an abundance of HOT loci in the human genome and a commitment of 51% of all TF ChIP-seq binding events to HOT locus formation thus challenging the classical model of enhancer activity and propose a model of HOT locus formation based on the existence of large transcriptional condensates.

Identification of Molecular Subtypes and Prognostic Traits Based on Chromosomal Instability Phenotype-Related Genes in Lung Adenocarcinoma

Lung adenocarcinoma (LUAD) exhibits significant molecular heterogeneity; however, previous studies have not fully explored its classification into distinct molecular subtypes. Here, we identified LUAD-significant chromosomal instability (CIN) phenotype genes (n = 24) using a TCGA-LUAD cohort (n = 592) and evaluated their ability to predict pathologic grade. Unsupervised clustering and principal component analysis revealed that LUAD patients could be classified into CIN phenotype-related subtypes (GroupLow, GroupModerate, and GroupHigh), each exhibiting distinct transcriptomic patterns. Notably, the GroupHigh showed significantly poor overall survival [OS; hazard ratio (HR) = 1.43, p-value < 10-3] and disease-free survival (DFS; HR = 1.27, p-value < 10-3). Univariate and multivariate analysis confirmed that its expression status was an independent prognostic predictor (p-value < 10-3, HR = 2.18, 95% C.I = 1.26-3.76) of the clinical outcomes, outperforming pathologic grade (p-value < 10-3, HR = 1.2, 95% C.I = 1.08-1.33). Moreover, analysis of surfactant metabolism-related genes revealed higher expression in the GroupLow, which was associated with a favorable prognosis. By integrating multiple independent cohorts (n = 779), we validated these findings and confirmed that CIN phenotype gene status serves as a critical prognostic marker in LUAD. Furthermore, genomic profiling showed that the GroupHigh exhibited frequent mutations in key genes such as KEAP1, LYST, SETD2, and TP53, with oncogenes in this group preferentially showing copy number gains. Our study highlights the significance of CIN phenotype gene status as a predictor of LUAD prognosis and its association with transcriptomic and genomic alterations, paving the way for further clinical validation and potential therapeutic interventions.

Identification of methylation-sensitive human transcription factors using meSMiLE-seq

Transcription factors (TFs) are key players in eukaryotic gene regulation, but the DNA binding specificity of many TFs remains unknown. Here, we assayed 284 mostly poorly characterized, putative human TFs using selective microfluidics-based ligand enrichment followed by sequencing (SMiLE-seq), revealing 72 new DNA binding motifs. To investigate whether some of the 158 TFs for which we did not find motifs preferably bind epigenetically modified DNA (i.e. methylated CG dinucleotides), we developed methylation-sensitive SMiLE-seq (meSMiLE-seq). This microfluidic assay simultaneously probes the affinity of a protein to methylated and unmethylated DNA, augmenting the capabilities of the original method to infer methylation-aware binding sites. We assayed 114 TFs with meSMiLE-seq and identified DNA-binding models for 48 proteins, including the known methylation-sensitive binding modes for POU5F1 and RFX5. For 11 TFs, binding to methylated DNA was preferred or resulted in the discovery of alternative, methylation-dependent motifs (e.g. PRDM13), while aversion towards methylated sequences was found for 13 TFs (e.g. USF3). Finally, we uncovered a potential role for ZHX2 as a putative binder of Z-DNA, a left-handed helical DNA structure which is adopted more frequently upon CpG methylation. Altogether, our study significantly expands the human TF codebook by identifying DNA binding motifs for 98 TFs, while providing a versatile platform to quantitatively assay the impact of DNA modifications on TF binding.

Master regulators governing protein abundance across ten human cancer types

Protein abundance correlates only moderately with mRNA levels, and are modulated post-transcriptionally by a network of regulators including ribosomes, RNA-binding proteins (RBPs), and the proteasome. Here, we identified Master Protein abundance Regulators (MaPRs) across ten cancer types by devising a new computational pipeline that jointly analyzed transcriptomes and proteomes from 1,305 tumor samples. We identified 232 to 1,394 MaPRs per cancer type, mediating up to 79% of post-transcriptional regulatory networks. MaPRs exhibit high network connectivity, strong genetic dependency in cancer cells, and significant enrichment for RBPs. Combining tumor up-regulation, druggability, and target network analyses identified cancer-specific vulnerabilities. MaPRs predict tumor proteomic subtypes more accurately than other proteins. Finally, significant portions of RBP MaPR-target relationships were validated by experimental evidence from eCLIP binding and knockdown assays. Our findings uncover central MaPRs that govern post-transcriptional networks, highlighting diverse processes underlying human proteome regulation and identifying key regulators in cancer biology.

Extensive binding of uncharacterized human transcription factors to genomic dark matter

Most of the human genome is thought to be non-functional, and includes large segments often referred to as "dark matter" DNA. The genome also encodes hundreds of putative and poorly characterized transcription factors (TFs). We determined genomic binding locations of 166 uncharacterized human TFs in living cells. Nearly half of them associated strongly with known regulatory regions such as promoters and enhancers, often at conserved motif matches and co-localizing with each other. Surprisingly, the other half often associated with genomic dark matter, at largely unique sites, via intrinsic sequence recognition. Dozens of these, which we term "Dark TFs", mainly bind within regions of closed chromatin. Dark TF binding sites are enriched for transposable elements, and are rarely under purifying selection. Some Dark TFs are KZNFs, which contain the repressive KRAB domain, but many are not: the Dark TFs also include known or potential pioneer TFs. Compiled literature information supports that the Dark TFs exert diverse functions ranging from early development to tumor suppression. Thus, our results sheds light on a large fraction of previously uncharacterized human TFs and their unappreciated activities within the dark matter genome.

Disease-Linked Regulatory DNA Variants and Homeostatic Transcription Factors in Epidermis

Identifying noncoding single nucleotide variants ( SNVs ) in regulatory DNA linked to polygenic disease risk, the transcription factors ( TFs ) they bind, and the target genes they dysregulate is a goal in polygenic disease research. Massively parallel reporter gene analysis ( MPRA ) of 3,451 SNVs linked to risk for polygenic skin diseases characterized by disrupted epidermal homeostasis identified 355 differentially active SNVs ( daSNVs ). daSNV target gene analysis, combined with daSNV editing, underscored dysregulated epidermal differentiation as a pathomechanism shared across common polygenic skin diseases. CRISPR knockout screens of 1772 human TFs revealed 108 TFs essential for epidermal progenitor differentiation, uncovering novel roles for ZNF217, CXXC1, FOXJ2, IRX2 and NRF1. Population sampling CUT&RUN of 27 homeostatic TFs identified allele-specific DNA binding ( ASB ) differences at daSNVs enriched near epidermal homeostasis and monogenic skin disease genes, with notable representation of SP/KLF and AP-1/2 TFs. This resource implicates dysregulated differentiation in risk for diverse polygenic skin diseases.

Integrated multi-omics analysis of PBX1 in mouse adult neural stem- and progenitor cells identifies a transcriptional module that functionally links PBX1 to TCF3/4

Developmental transcription factors act in networks, but how these networks achieve cell- and tissue specificity is still poorly understood. Here, we explored pre-B cell leukemia homeobox 1 (PBX1) in adult neurogenesis combining genomic, transcriptomic, and proteomic approaches. ChIP-seq analysis uncovered PBX1 binding to numerous genomic sites. Integration of PBX1 ChIP-seq with ATAC-seq data predicted interaction partners, which were subsequently validated by mass spectrometry. Whole transcriptome spatial RNA analysis revealed shared expression dynamics of Pbx1 and interacting factors. Among these were class I bHLH proteins TCF3 and TCF4. RNA-seq following Pbx1, Tcf3 or Tcf4 knockdown identified proliferation- and differentiation associated genes as shared targets, while sphere formation assays following knockdown argued for functional cooperativity of PBX1 and TCF3 in progenitor cell proliferation. Notably, while physiological PBX1-TCF interaction has not yet been described, chromosomal translocation resulting in genomic TCF3::PBX1 fusion characterizes a subtype of acute lymphoblastic leukemia. Introducing Pbx1 into Nalm6 cells, a pre-B cell line expressing TCF3 but lacking PBX1, upregulated the leukemogenic genes BLK and NOTCH3, arguing that functional PBX1-TCF cooperativity likely extends to hematopoiesis. Our study hence uncovers a transcriptional module orchestrating the balance between progenitor cell proliferation and differentiation in adult neurogenesis with potential implications for leukemia etiology.

Shared genetic architecture of psychiatric disorders and hemorrhoidal disease: a large-scale genome-wide cross-trait analysis

Background

The genetic association between psychiatric disorders and hemorrhoidal disease (HEM) is still not well known. The work aims to investigate their comorbidity at a genetic level.

Methods

Utilizing recent large-scale genome-wide association studies (GWAS), we investigated the genetic overlap at the single nucleotide polymorphism (SNP), gene, and molecular level between depression and HEM, bipolar disorder (BD) and HEM, neuroticism and HEM, as well as schizophrenia (SCZ) and HEM. The cross-trait genes were validated through the utilization of transcriptome and proteome methodologies. The causal link was assessed using bidirectional two-sample Mendelian randomization analysis (MR) analysis. MRlap corrects for the potential bias in estimation caused by sample overlap.

Results

We discovered significant positive genetic associations between these four types of psychiatric disorders and HEM. Cross-phenotypic association analyses identified shared SNPs along with 17 specific loci between psychiatric disorders and HEM. MAGMA identified a total of 2304 pleiotropic genes, several of which showed significant expression in the results of transcriptome and proteome analyses. We observed that these genes are mostly associated with the regulation of transcription factors and particular DNA binding activities. Lastly, MR analysis provided evidence supporting a correlation between these conditions.

Conclusion

This study revealed a genetic correlation between four psychiatric disorders and HEM, identified pleiotropic loci, found multiple candidate genes, and confirmed causal relationships. This has enhanced our comprehension of the common genetic mechanisms of psychiatric disorders and HEM.

EAF2: a tumor suppressor gene with multi-aspect functions

Since ELL-associated factor 2 (EAF2) was identified in 1997 as an androgen response gene, it has been of medical and scientific interest. Early studies demonstrated the tumor-suppressing function of EAF2 in the prostate. Sequencing studies indicated an association between EAF2 and several other malignant diseases and multiple physiological processes, such as transcription, apoptosis, embryogenesis, and DNA repair. Further understanding of EAF2 will provide new opportunities and therapeutic approaches for cancers, especially prostate cancer. This narrative review summarizes the existing knowledge of EAF2 and outlines its potential significance. To our knowledge, this is the first review of the role of this novel tumor suppressor gene and its possible functions.

Lactate-mediated lactylation in human health and diseases: Progress and remaining challenges

BACKGROUND

Lactate was once considered as metabolic waste for a long time. In 2019, Professor Zhao Yingming's team from the University of Chicago found that lactate could also be used as a substrate to induce histone lactylation and regulate gene expression. Since then, researchers have discovered that lactate-mediated lactylation play important regulatory roles in various physiological and pathological processes.

AIM OF REVIEW

In this review, we aim to discuss the roles and mechanisms of lactylation in human health and diseases, as well as the effects of lactylation on proteins and metabolic modulators targeting lactylation.

KEY SCIENTIFIC CONCEPTS OF REVIEW

In this work, we emphasize the crucial regulatory roles of lactylation in the development of numerous physiological and pathological processes. Of relevance, we discuss the current issues and challenges pertaining to lactylation. This review provides directions and a theoretical basis for future research and clinical translation of lactylation.

Molecular signatures of cortical expansion in the human foetal brain

The third trimester of human gestation is characterised by rapid increases in brain volume and cortical surface area. Recent studies have revealed a remarkable molecular diversity across the prenatal cortex but little is known about how this diversity translates into the differential rates of cortical expansion observed during gestation. We present a digital resource, μBrain, to facilitate knowledge translation between molecular and anatomical descriptions of the prenatal brain. Using μBrain, we evaluate the molecular signatures of preferentially-expanded cortical regions, quantified in utero using magnetic resonance imaging. Our findings demonstrate a spatial coupling between areal differences in the timing of neurogenesis and rates of neocortical expansion during gestation. We identify genes, upregulated from mid-gestation, that are highly expressed in rapidly expanding neocortex and implicated in genetic disorders with cognitive sequelae. The μBrain atlas provides a tool to comprehensively map early brain development across domains, model systems and resolution scales.

Leveraging a comprehensive unbiased RNAseq database to characterize human monocyte-derived macrophage gene expression profiles within commonly employed in vitro polarization methods

Macrophages are pivotal innate immune cells which exhibit high phenotypic plasticity and can exist in different polarization states dependent on exposure to external stimuli. Numerous methods have been employed to simulate macrophage polarization states to test their function in vitro. However, limited research has explored whether these polarization methods yield comparable populations beyond key gene, cytokine, and cell surface marker expression. Here, we employ an unbiased comprehensive analysis using data organized through the all RNA-seq and ChIP-seq sample and signature search (ARCHS4) database, which compiles all RNAseq data deposited into the National Center for Biotechnology Information (NCBI) Sequence Read Archive (SRA). In silico analyses were carried out demonstrating that commonly employed macrophage polarization methods generate distinct gene expression profiles in macrophage subsets that remained poorly described until now. Our analyses confirm existing knowledge on broad macrophage polarization, while expanding nuanced differences between M2a and M2c subsets, suggesting non-interchangeable stimuli for M2a polarization. Furthermore, we characterize divergent gene expression patterns in M1 macrophages following standard polarization protocols, indicating significant subset distinctions. Consequently, equivalence cannot be assumed among polarization regimens for in vitro macrophage studies, particularly in simulating diverse pathogen responses.

Pituitary neuroendocrine tumors and granular cell pituicytomas at autopsy: Incidence, cell types, locations, and histogenesis in 150 pituitary glands

OBJECTIVES

The incidence of pituitary neuroendocrine tumors has been reported high at autopsy. This study aimed to detect many tumors in both anterior and posterior lobes to prove tumor histogenesis.

METHODS

In total, 150 pituitary glands were studied from the University of Kansas Medical Center from 1995 to 2000. The pituitary gland was sagittally sliced from anterior to posterior into 6 to 8 sections. When H&E-stained sections revealed tumors, the tumors were immunohistochemically stained for 6 pituitary hormones.

RESULTS

Among 150 autopsy cases, 38 (25.3%) harbored microadenomas, including 4 cases with double tumors. Twenty-three (54.7%) cases were negative to all pituitary hormones. Of the remaining 19 tumors, 13 (30.9%) were lactotrophs, with 4 cases being concomitantly somatotrophs and gonadotrophs, and 2 cases were corticotropes. More than 85% of pituitary neuroendocrine tumors were adjacent to the capsule. Thirteen (8.7%) granular cell pituicytomas were found in the posterior lobe. There were pituicytes transforming into granular cell tumors.

CONCLUSIONS

The incidence was 25.3% for pituitary neuroendocrine tumors and 8.7% for granular cell pituicytomas. Since most pituitary neuroendocrine tumors were adjacent to the pituitary capsule, the capsule appeared to be the germinal center. Both pituitary tumors belonged to the 2 different transcription factor lineages.

Single-cell, spatial, and fate-mapping analyses uncover niche dependent diversity of cochlear myeloid cells

Recent advances in fate mapping and single-cell technologies have revealed how the dynamics and function of tissue-resident macrophages are shaped by their environment. However, macrophages in sensory organs such as the cochlea where the central nervous system and peripheral nervous system meet remain understudied. Combining single-cell transcriptomics, fate mapping, and parabiosis experiments, we show that five types of myeloid cells including three tissue-resident macrophage subpopulations, coexist in the mouse cochlea. The three macrophage subsets showed different potential functions in relationship with their specific topography across cochlear compartments. Further analysis revealed that they were partially derived from yolk sac progenitors during development, while in adulthood, most cochlear macrophages were long-term resident. Finally, we showed that cochlear macrophage morphology and density changed during aging. Our findings show that cochlea is a microenvironment with a unique heterogeneity of macrophages in terms of gene expression, spatial distribution, ontogeny, and function.

A prenatal skin atlas reveals immune regulation of human skin morphogenesis

Human prenatal skin is populated by innate immune cells, including macrophages, but whether they act solely in immunity or have additional functions in morphogenesis is unclear. Here we assembled a comprehensive multi-omics reference atlas of prenatal human skin (7-17 post-conception weeks), combining single-cell and spatial transcriptomics data, to characterize the microanatomical tissue niches of the skin. This atlas revealed that crosstalk between non-immune and immune cells underpins the formation of hair follicles, is implicated in scarless wound healing and is crucial for skin angiogenesis. We systematically compared a hair-bearing skin organoid (SkO) model derived from human embryonic stem cells and induced pluripotent stem cells to prenatal and adult skin1. The SkO model closely recapitulated in vivo skin epidermal and dermal cell types during hair follicle development and expression of genes implicated in the pathogenesis of genetic hair and skin disorders. However, the SkO model lacked immune cells and had markedly reduced endothelial cell heterogeneity and quantity. Our in vivo prenatal skin cell atlas indicated that macrophages and macrophage-derived growth factors have a role in driving endothelial development. Indeed, vascular network remodelling was enhanced following transfer of autologous macrophages derived from induced pluripotent stem cells into SkO cultures. Innate immune cells are therefore key players in skin morphogenesis beyond their conventional role in immunity, a function they achieve through crosstalk with non-immune cells.

Single-cell integration reveals metaplasia in inflammatory gut diseases

The gastrointestinal tract is a multi-organ system crucial for efficient nutrient uptake and barrier immunity. Advances in genomics and a surge in gastrointestinal diseases1,2 has fuelled efforts to catalogue cells constituting gastrointestinal tissues in health and disease3. Here we present systematic integration of 25 single-cell RNA sequencing datasets spanning the entire healthy gastrointestinal tract in development and in adulthood. We uniformly processed 385 samples from 189 healthy controls using a newly developed automated quality control approach (scAutoQC), leading to a healthy reference atlas with approximately 1.1 million cells and 136 fine-grained cell states. We anchor 12 gastrointestinal disease datasets spanning gastrointestinal cancers, coeliac disease, ulcerative colitis and Crohn's disease to this reference. Utilizing this 1.6 million cell resource (gutcellatlas.org), we discover epithelial cell metaplasia originating from stem cells in intestinal inflammatory diseases with transcriptional similarity to cells found in pyloric and Brunner's glands. Although previously linked to mucosal healing4, we now implicate pyloric gland metaplastic cells in inflammation through recruitment of immune cells including T cells and neutrophils. Overall, we describe inflammation-induced changes in stem cells that alter mucosal tissue architecture and promote further inflammation, a concept applicable to other tissues and diseases.

NMR investigation of FOXO4-DNA interaction for discriminating target and non-target DNA sequences

Forkhead box O4 (FOXO4), a human transcription factor, recognizes target DNA through its forkhead domain (FHD) while maintaining comparable binding affinity to non-target DNA. The conserved region 3 (CR3), a transactivation domain, modulates DNA binding kinetics to FHD and contributes to target DNA selection, but the underlying mechanism of this selection remains elusive. Using paramagnetic relaxation enhancement analysis, we observed a minor state of CR3 close to FHD in the presence of non-target DNA, a state absent when FHD interacts with target DNA. This minor state suggests that CR3 effectively masks the non-target DNA-binding interface on FHD. The interaction weakens significantly under high salt concentration, implying that CR3 or high salt concentrations can modulate electrostatic interactions with non-target DNA. Our 15N relaxation measurements revealed FHD's flexibility with non-target DNA and increased rigidity with target DNA binding. Our findings offer insights into the role of FOXO4 as a transcription initiator.

Rapid and large-scale glycopeptide enrichment strategy based on chemical ligation

Protein glycosylation, the most universal post-translational modification, is thought to play a crucial role in regulating multiple essential cellular processes. However, the low abundance of glycoproteins and the heterogeneity of glycans complicate their comprehensive analysis. Here, we develop a rapid and large-scale glycopeptide enrichment strategy via bioorthogonal ligation and trypsin cleavage. The enrichment process is performed in one tube to minimize sample loss and time costs. This method combines convenience and practicality, identifying over 900 O-GlcNAc sites from a 500 μg sample. Surprisingly, it allows simultaneous identification of N-glycosites, O-GlcNAc sites, O-GalNAc sites and N-glycans via a two-step enzymatic release strategy. Combined with quantitative analysis, it reveals the distinct O-GlcNAcylation patterns in different compartments during oxidative stress. In summary, our study offers a convenient and robust tool for glycoproteome and glycome profiling, facilitating in-depth analysis to elucidate the biological functions of glycosylation.

Decoding the Role of NEIL1 Gene in DNA Repair and Lifespan: A Literature Review with Bioinformatics Analysis

Longevity, the length of an organism's lifespan, is impacted by environmental factors, metabolic processes, and genetic determinants. The base excision repair (BER) pathway is crucial for maintaining genomic integrity by repairing oxidatively modified base lesions. Nei-like DNA Glycosylase 1 (NEIL1), part of the BER pathway, is vital in repairing oxidative bases in G-rich DNA regions, such as telomeres and promoters. Hence, in this comprehensive review, it have undertaken a meticulous investigation of the intricate association between NEIL1 and longevity. The analysis delves into the multifaceted aspects of the NEIL1 gene, its various RNA transcripts, and the diverse protein isoforms. In addition, a combination of bioinformatic analysis is conducted to identify NEIL1 mutations, transcription factors, and epigenetic modifications, as well as its lncRNA/pseudogene/circRNA-miRNA-mRNA regulatory network. The findings suggest that the normal function of NEIL1 is a significant factor in human health and longevity, with defects in NEIL1 potentially leading to various cancers and related syndromes, Alzheimer's disease, obesity, and diabetes.

Transcription factor networks drive perforin activity in the anti-bacterial immune response of tilapia

Perforin, produced by natural killer (NK) cells and cytotoxic T lymphocytes (CTLs), is one of the effectors of cell-mediated cytotoxicity (CMC) in vertebrates, playing a paramount role in killing target cells. However, whether and how perforin is involved in adaptive immune responses in early vertebrates remains unclear. Using Nile tilapia (Oreochromis niloticus) as a model, we investigated the characteristics of perforin in early vertebrates. Oreochromis niloticus perforin (OnPRF) possesses 2 conserved functional domains, membrane attack complex/perforin (MACPF) and protein kinase C conserved region 2 (C2) domains, although they share low amino acid sequence similarity with other homologs. OnPRF was widely expressed in various immune tissues and could respond to lymphocyte activation and T-cell activation in vitro at both the transcriptional and protein levels, indicating that it may be involved in adaptive immune responses. Furthermore, after infection with Edwardsiella piscicida and Aeromonas hydrophila, the mRNA and protein levels of OnPRF were significantly up-regulated within the adaptive immune response period. Additionally, we revealed that many transcription factors were involved in the transcriptional regulation of OnPRF, including p65, c-Fos, c-Jun, STAT1 and STAT4, and there was a synergy among these transcription factors. Overall, these findings demonstrate the involvement of OnPRF in T-cell activation and adaptive immune response in tilapia, thus providing new evidence for comprehending the evolution of immune response in early vertebrates.

Overview of chromatin regulatory processes during surface ectodermal development and homeostasis

The ectoderm is the outermost of the three germ layers of the early embryo that arise during gastrulation. Once the germ layers are established, the complex interplay of cellular proliferation, differentiation, and migration results in organogenesis. The ectoderm is the progenitor of both the surface ectoderm and the neural ectoderm. Notably, the surface ectoderm develops into the epidermis and its associated appendages, nails, external exocrine glands, olfactory epithelium, and the anterior pituitary. Specification, development, and homeostasis of these organs demand a tightly orchestrated gene expression program that is often dictated by epigenetic regulation. In this review, we discuss the recent discoveries that have highlighted the importance of chromatin regulatory mechanisms mediated by transcription factors, histone and DNA modifications that aid in the development of surface ectodermal organs and maintain their homeostasis post-development.

Development of compact transcriptional effectors using high-throughput measurements in diverse contexts

Transcriptional effectors are protein domains known to activate or repress gene expression; however, a systematic understanding of which effector domains regulate transcription across genomic, cell type and DNA-binding domain (DBD) contexts is lacking. Here we develop dCas9-mediated high-throughput recruitment (HT-recruit), a pooled screening method for quantifying effector function at endogenous target genes and test effector function for a library containing 5,092 nuclear protein Pfam domains across varied contexts. We also map context dependencies of effectors drawn from unannotated protein regions using a larger library tiling chromatin regulators and transcription factors. We find that many effectors depend on target and DBD contexts, such as HLH domains that can act as either activators or repressors. To enable efficient perturbations, we select context-robust domains, including ZNF705 KRAB, that improve CRISPRi tools to silence promoters and enhancers. We engineer a compact human activator called NFZ, by combining NCOA3, FOXO3 and ZNF473 domains, which enables efficient CRISPRa with better viral delivery and inducible control of chimeric antigen receptor T cells.

DELE1 maintains muscle proteostasis to promote growth and survival in mitochondrial myopathy

Mitochondrial dysfunction causes devastating disorders, including mitochondrial myopathy, but how muscle senses and adapts to mitochondrial dysfunction is not well understood. Here, we used diverse mouse models of mitochondrial myopathy to show that the signal for mitochondrial dysfunction originates within mitochondria. The mitochondrial proteins OMA1 and DELE1 sensed disruption of the inner mitochondrial membrane and, in response, activated the mitochondrial integrated stress response (mt-ISR) to increase the building blocks for protein synthesis. In the absence of the mt-ISR, protein synthesis in muscle was dysregulated causing protein misfolding, and mice with early-onset mitochondrial myopathy failed to grow and survive. The mt-ISR was similar following disruptions in mtDNA maintenance (Tfam knockout) and mitochondrial protein misfolding (CHCHD10 G58R and S59L knockin) but heterogenous among mitochondria-rich tissues, with broad gene expression changes observed in heart and skeletal muscle and limited changes observed in liver and brown adipose tissue. Taken together, our findings identify that the DELE1 mt-ISR mediates a similar response to diverse forms of mitochondrial stress and is critical for maintaining growth and survival in early-onset mitochondrial myopathy.

Benchmarking and building DNA binding affinity models using allele-specific and allele-agnostic transcription factor binding data

BACKGROUND

Transcription factors (TFs) bind to DNA in a highly sequence-specific manner. This specificity manifests itself in vivo as differences in TF occupancy between the two alleles at heterozygous loci. Genome-scale assays such as ChIP-seq currently are limited in their power to detect allele-specific binding (ASB) both in terms of read coverage and representation of individual variants in the cell lines used. This makes prediction of allelic differences in TF binding from sequence alone desirable, provided that the reliability of such predictions can be quantitatively assessed.

RESULTS

We here propose methods for benchmarking sequence-to-affinity models for TF binding in terms of their ability to predict allelic imbalances in ChIP-seq counts. We use a likelihood function based on an over-dispersed binomial distribution to aggregate evidence for allelic preference across the genome without requiring statistical significance for individual variants. This allows us to systematically compare predictive performance when multiple binding models for the same TF are available. To facilitate the de novo inference of high-quality models from paired-end in vivo binding data such as ChIP-seq, ChIP-exo, and CUT&Tag without read mapping or peak calling, we introduce an extensible reimplementation of our biophysically interpretable machine learning framework named PyProBound. Explicitly accounting for assay-specific bias in DNA fragmentation rate when training on ChIP-seq yields improved TF binding models. Moreover, we show how PyProBound can leverage our threshold-free ASB likelihood function to perform de novo motif discovery using allele-specific ChIP-seq counts.

CONCLUSION

Our work provides new strategies for predicting the functional impact of non-coding variants.

Chromatin interaction maps identify oncogenic targets of enhancer duplications in cancer

As a major type of structural variants, tandem duplication plays a critical role in tumorigenesis by increasing oncogene dosage. Recent work has revealed that noncoding enhancers are also affected by duplications leading to the activation of oncogenes that are inside or outside of the duplicated regions. However, the prevalence of enhancer duplication and the identity of their target genes remains largely unknown in the cancer genome. Here, by analyzing whole-genome sequencing data in a non-gene-centric manner, we identify 881 duplication hotspots in 13 major cancer types, most of which do not contain protein-coding genes. We show that the hotspots are enriched with distal enhancer elements and are highly lineage-specific. We develop a HiChIP-based methodology that navigates enhancer-promoter contact maps to prioritize the target genes for the duplication hotspots harboring enhancer elements. The methodology identifies many novel enhancer duplication events activating oncogenes such as ESR1, FOXA1, GATA3, GATA6, TP63, and VEGFA, as well as potentially novel oncogenes such as GRHL2, IRF2BP2, and CREB3L1 In particular, we identify a duplication hotspot on Chromosome 10p15 harboring a cluster of enhancers, which skips over two genes, through a long-range chromatin interaction, to activate an oncogenic isoform of the NET1 gene to promote migration of gastric cancer cells. Focusing on tandem duplications, our study substantially extends the catalog of noncoding driver alterations in multiple cancer types, revealing attractive targets for functional characterization and therapeutic intervention.

Genomic insights into genes expressed specifically during infancy highlight their dominant influence on the neuronal system

BACKGROUND

Elucidating the dynamics of gene expression across developmental stages, including the genomic characteristics of brain expression during infancy, is pivotal in deciphering human psychiatric and neurological disorders and providing insights into developmental disorders.

RESULTS

Leveraging comprehensive human GWAS associations with temporal and spatial brain expression data, we discovered a distinctive co-expression cluster comprising 897 genes highly expressed specifically during infancy, enriched in functions related to the neuronal system. This gene cluster notably harbors the highest ratio of genes linked to psychiatric and neurological disorders. Through computational analysis, MYT1L emerged as a potential central transcription factor governing these genes. Remarkably, the infancy-specific expressed genes, including SYT1, exhibit prominent colocalization within human accelerated regions. Additionally, chromatin state analysis unveiled prevalent epigenetic markers associated with enhancer-specific modifications. In addition, this cluster of genes has demonstrated to be specifically highly expressed in cell-types including excitatory neurons, medial ganglionic eminence and caudal ganglionic eminence.

CONCLUSIONS

This study comprehensively characterizes the genomics and epigenomics of genes specifically expressed during infancy, identifying crucial hub genes and transcription factors. These findings offer valuable insights into early detection strategies and interventions for psychiatric and neurological disorders.

Combinatorial effector targeting (COMET) for transcriptional modulation and locus-specific biochemistry

Understanding how human gene expression is coordinately regulated by functional units of proteins across the genome remains a major biological goal. Here, we present COMET, a high-throughput screening platform for combinatorial effector targeting for the identification of transcriptional modulators. We generate libraries of combinatorial dCas9-based fusion proteins, containing two to six effector domains, allowing us to systematically investigate more than 110,000 combinations of effector proteins at endogenous human loci for their influence on transcription. Importantly, we keep full proteins or domains intact, maintaining catalytic cores and surfaces for protein-protein interactions. We observe more than 5800 significant hits that modulate transcription, we demonstrate cell type specific transcriptional modulation, and we further investigate epistatic relationships between our effector combinations. We validate unexpected combinations as synergistic or buffering, emphasizing COMET as both a method for transcriptional effector discovery, and as a functional genomics tool for identifying novel domain interactions and directing locus-specific biochemistry.

Long non-coding RNAs: regulators of autophagy and potential biomarkers in therapy resistance and urological cancers

The non-coding RNAs (ncRNAs) comprise a large part of human genome that mainly do not code for proteins. Although ncRNAs were first believed to be non-functional, the more investigations highlighted tthe possibility of ncRNAs in controlling vital biological processes. The length of long non-coding RNAs (lncRNAs) exceeds 200 nucleotidesand can be present in nucleus and cytoplasm. LncRNAs do not translate to proteins and they have been implicated in the regulation of tumorigenesis. On the other hand, One way cells die is by a process called autophagy, which breaks down proteins and other components in the cytoplasm., while the aberrant activation of autophagy allegedly involved in the pathogenesis of diseases. The autophagy exerts anti-cancer activity in pre-cancerous lesions, while it has oncogenic function in advanced stages of cancers. The current overview focuses on the connection between lncRNAs and autophagy in urological cancers is discussed. Notably, one possible role for lncRNAs is as diagnostic and prognostic variablesin urological cancers. The proliferation, metastasis, apoptosis and therapy response in prostate, bladder and renal cancers are regulated by lncRNAs. The changes in autophagy levels can also influence the apoptosis, proliferation and therapy response in urological tumors. Since lncRNAs have modulatory functions, they can affect autophagy mechanism to determine progression of urological cancers.

Direct and indirect regulation of β-glucocerebrosidase by the transcription factors USF2 and ONECUT2

Mutations in GBA1 encoding the lysosomal enzyme β-glucocerebrosidase (GCase) are among the most prevalent genetic susceptibility factors for Parkinson's disease (PD), with 10-30% of carriers developing the disease. To identify genetic modifiers contributing to the incomplete penetrance, we examined the effect of 1634 human transcription factors (TFs) on GCase activity in lysates of an engineered human glioblastoma line homozygous for the pathogenic GBA1 L444P variant. Using an arrayed CRISPR activation library, we uncovered 11 TFs as regulators of GCase activity. Among these, activation of MITF and TFEC increased lysosomal GCase activity in live cells, while activation of ONECUT2 and USF2 decreased it. While MITF, TFEC, and USF2 affected GBA1 transcription, ONECUT2 might control GCase trafficking. The effects of MITF, TFEC, and USF2 on lysosomal GCase activity were reproducible in iPSC-derived neurons from PD patients. Our study provides a systematic approach to identifying modulators of GCase activity and deepens our understanding of the mechanisms regulating GCase.

IL-1β-induced epithelial cell and fibroblast transdifferentiation promotes neutrophil recruitment in chronic rhinosinusitis with nasal polyps

Neutrophilic inflammation contributes to multiple chronic inflammatory airway diseases, including asthma and chronic rhinosinusitis with nasal polyps (CRSwNP), and is associated with an unfavorable prognosis. Here, using single-cell RNA sequencing (scRNA-seq) to profile human nasal mucosa obtained from the inferior turbinates, middle turbinates, and nasal polyps of CRSwNP patients, we identify two IL-1 signaling-induced cell subsets-LY6D+ club cells and IDO1+ fibroblasts-that promote neutrophil recruitment by respectively releasing S100A8/A9 and CXCL1/2/3/5/6/8 into inflammatory regions. IL-1β, a pro-inflammatory cytokine involved in IL-1 signaling, induces the transdifferentiation of LY6D+ club cells and IDO1+ fibroblasts from primary epithelial cells and fibroblasts, respectively. In an LPS-induced neutrophilic CRSwNP mouse model, blocking IL-1β activity with a receptor antagonist significantly reduces the numbers of LY6D+ club cells and IDO1+ fibroblasts and mitigates nasal inflammation. This study implicates the function of two cell subsets in neutrophil recruitment and demonstrates an IL-1-based intervention for mitigating neutrophilic inflammation in CRSwNP.

PRDM1 promotes nucleus pulposus cell pyroptosis leading to intervertebral disc degeneration via activating CASP1 transcription

Intervertebral disc degeneration (IVDD) is a primary contributor to low back pain and poses a considerable burden to society. However, the molecular mechanisms underlying IVDD remain to be elucidated. PR/SET domain 1 (PRDM1) regulates cell proliferation, apoptosis, and inflammatory responses in various diseases. Despite these regulatory functions, the mechanism of action of PRDM1 in IVDD remains unexplored. In this study, we investigated the role and underlying mechanisms of action of PRDM1 in IVDD progression. The expression of PRDM1 in nucleus pulposus (NP) tissues and NP cells (NPCs) was assessed using western blotting, immunohistochemistry, and immunofluorescence. The effects of PRDM1 on IVDD progression were investigated in vitro and in vivo. Mechanistically, mRNA sequencing, chromatin immunoprecipitation, and dual-luciferase reporter assays were performed to confirm that PRDM1 triggered CASP1 transcription. Our study demonstrated for the first time that PRDM1 expression was substantially upregulated in degenerated NP tissues and NPCs. PRDM1 overexpression promoted NPCs pyroptosis by inhibiting mitophagy and exacerbating IVDD progression, whereas PRDM1 silencing exerted the opposite effect. Furthermore, PRDM1 activated CASP1 transcription, thereby promoting NPCs pyroptosis in vitro. Notably, CASP1 silencing reversed the effects of PRDM1 on the NPCs. To the best of our knowledge, this study is the first to demonstrate that PRDM1 silencing inhibits NPCs pyroptosis by repressing CASP1 transcription, which may be a promising new therapeutic target for IVDD.

The homeodomain regulates stable DNA binding of prostate cancer target ONECUT2

The CUT and homeodomain are ubiquitous DNA binding elements often tandemly arranged in multiple transcription factor families. However, how the CUT and homeodomain work concertedly to bind DNA remains unknown. Using ONECUT2, a driver and therapeutic target of advanced prostate cancer, we show that while the CUT initiates DNA binding, the homeodomain thermodynamically stabilizes the ONECUT2-DNA complex through allosteric modulation of CUT. We identify an arginine pair in the ONECUT family homeodomain that can adapt to DNA sequence variations. Base interactions by this ONECUT family-specific arginine pair as well as the evolutionarily conserved residues are critical for optimal DNA binding and ONECUT2 transcriptional activity in a prostate cancer model. The evolutionarily conserved base interactions additionally determine the ONECUT2-DNA binding energetics. These findings provide insights into the cooperative DNA binding by CUT-homeodomain proteins.

DFF-ChIP: a method to detect and quantify complex interactions between RNA polymerase II, transcription factors, and chromatin

Recently, we introduced a chromatin immunoprecipitation (ChIP) technique utilizing the human DNA Fragmentation Factor (DFF) to digest the DNA prior to immunoprecipitation (DFF-ChIP) that provides the precise location of transcription complexes and their interactions with neighboring nucleosomes. Here we expand the technique to new targets and provide useful information concerning purification of DFF, digestion conditions, and the impact of crosslinking. DFF-ChIP analysis was performed individually for subunits of Mediator, DSIF, and NELF that that do not interact with DNA directly, but rather interact with RNA polymerase II (Pol II). We found that Mediator was associated almost exclusively with preinitiation complexes (PICs). DSIF and NELF were associated with engaged Pol II and, in addition, potential intermediates between PICs and early initiation complexes. DFF-ChIP was then used to analyze the occupancy of a tight binding transcription factor, CTCF, and a much weaker binding factor, glucocorticoid receptor (GR), with and without crosslinking. These results were compared to those from standard ChIP-Seq that employs sonication and to CUT&RUN which utilizes MNase to fragment the genomic DNA. Our findings indicate that DFF-ChIP reveals details of occupancy that are not available using other methods including information revealing pertinent protein:protein interactions.

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.

MethylSeqLogo: DNA methylation smart sequence logos

BACKGROUND

Some transcription factors, MYC for example, bind sites of potentially methylated DNA. This may increase binding specificity as such sites are (1) highly under-represented in the genome, and (2) offer additional, tissue specific information in the form of hypo- or hyper-methylation. Fortunately, bisulfite sequencing data can be used to investigate this phenomenon.

METHOD

We developed MethylSeqLogo, an extension of sequence logos which includes new elements to indicate DNA methylation and under-represented dimers in each position of a set binding sites. Our method displays information from both DNA strands, and takes into account the sequence context (CpG or other) and genome region (promoter versus whole genome) appropriate to properly assess the expected background dimer frequency and level of methylation. MethylSeqLogo preserves sequence logo semantics-the relative height of nucleotides within a column represents their proportion in the binding sites, while the absolute height of each column represents information (relative entropy) and the height of all columns added together represents total information RESULTS: We present figures illustrating the utility of using MethylSeqLogo to summarize data from several CpG binding transcription factors. The logos show that unmethylated CpG binding sites are a feature of transcription factors such as MYC and ZBTB33, while some other CpG binding transcription factors, such as CEBPB, appear methylation neutral.

CONCLUSIONS

Our software enables users to explore bisulfite and ChIP sequencing data sets-and in the process obtain publication quality figures.

BIT: Bayesian Identification of Transcriptional Regulators from Epigenomics-Based Query Region Sets

Transcriptional regulators (TRs) are master controllers of gene expression and play a critical role in both normal tissue development and disease progression. However, existing computational methods for identification of TRs regulating specific biological processes have significant limitations, such as relying on distance on a linear chromosome or binding motifs that have low specificity. Many also use statistical tests in ways that lack interpretability and rigorous confidence measures. We introduce BIT, a novel Bayesian hierarchical model for in-silico TR identification. Leveraging a comprehensive library of TR ChIP-seq data, BIT offers a fully integrated Bayesian approach to assess genome-wide consistency between user-provided epigenomic profiling data and the TR binding library, enabling the identification of critical TRs while quantifying uncertainty. It avoids estimation and inference in a sequential manner or numerous isolated statistical tests, thereby enhancing accuracy and interpretability. BIT successfully identified critical TRs in perturbation experiments, functionally essential TRs in various cancer types, and cell-type-specific TRs within heterogeneous cell populations, offering deeper biological insights into transcriptional regulation.

Codon Bias of the DDR1 Gene and Transcription Factor EHF in Multiple Species

Milk production is an essential economic trait in cattle, and understanding the genetic regulation of this trait can enhance breeding strategies. The discoidin domain receptor 1 (DDR1) gene has been identified as a key candidate gene that influences milk production, and ETS homologous factor (EHF) is recognized as a critical transcription factor that regulates DDR1 expression. Codon usage bias, which affects gene expression and protein function, has not been fully explored in cattle. This study aims to examine the codon usage bias of DDR1 and EHF transcription factors to understand their roles in dairy production traits. Data from 24 species revealed that both DDR1 and EHF predominantly used G/C-ending codons, with the GC3 content averaging 75.49% for DDR1 and 61.72% for EHF. Synonymous codon usage analysis identified high-frequency codons for both DDR1 and EHF, with 17 codons common to both genes. Correlation analysis indicated a negative relationship between the effective number of codons and codon adaptation index for both DDR1 and EHF. Phylogenetic and clustering analyses revealed similar codon usage patterns among closely related species. These findings suggest that EHF plays a crucial role in regulating DDR1 expression, offering new insights into genetically regulating milk production in cattle.

Evolutionary Innovations in Conserved Regulatory Elements Associate With Developmental Genes in Mammals

Transcriptional enhancers orchestrate cell type- and time point-specific gene expression programs. Genetic variation within enhancer sequences is an important contributor to phenotypic variation including evolutionary adaptations and human disease. Certain genes and pathways may be more prone to regulatory evolution than others, with different patterns across diverse organisms, but whether such patterns exist has not been investigated at a sufficient scale. To address this question, we identified signatures of accelerated sequence evolution in conserved enhancer elements throughout the mammalian phylogeny at an unprecedented scale. While different genes and pathways were enriched for regulatory evolution in different parts of the tree, we found a striking overall pattern of pleiotropic genes involved in gene regulatory and developmental processes being enriched for accelerated enhancer evolution. These genes were connected to more enhancers than other genes, which was the basis for having an increased amount of sequence acceleration over all their enhancers combined. We provide evidence that sequence acceleration is associated with turnover of regulatory function. Detailed study of one acceleration event in an enhancer of HES1 revealed that sequence evolution led to a new activity domain in the developing limb that emerged concurrently with the evolution of digit reduction in hoofed mammals. Our results provide evidence that enhancer evolution has been a frequent contributor to regulatory innovation at conserved developmental signaling genes in mammals.

Integrated multi-omics analysis of zinc-finger proteins uncovers roles in RNA regulation

RNA interactome studies have revealed that hundreds of zinc-finger proteins (ZFPs) are candidate RNA-binding proteins (RBPs), yet their RNA substrates and functional significance remain largely uncharacterized. Here, we present a systematic multi-omics analysis of the DNA- and RNA-binding targets and regulatory roles of more than 100 ZFPs representing 37 zinc-finger families. We show that multiple ZFPs are previously unknown regulators of RNA splicing, alternative polyadenylation, stability, or translation. The examined ZFPs show widespread sequence-specific RNA binding and preferentially bind proximal to transcription start sites. Additionally, several ZFPs associate with their targets at both the DNA and RNA levels. We highlight ZNF277, a C2H2 ZFP that binds thousands of RNA targets and acts as a multi-functional RBP. We also show that ZNF473 is a DNA/RNA-associated protein that regulates the expression and splicing of cell cycle genes. Our results reveal diverse roles for ZFPs in transcriptional and post-transcriptional gene regulation.

An RNA-centric view of transcription and genome organization

Foundational models of transcriptional regulation involve the assembly of protein complexes at DNA elements associated with specific genes. These assemblies, which can include transcription factors, cofactors, RNA polymerase, and various chromatin regulators, form dynamic spatial compartments that contribute to both gene regulation and local genome architecture. This DNA-protein-centric view has been modified with recent evidence that RNA molecules have important roles to play in gene regulation and genome structure. Here, we discuss evidence that gene regulation by RNA occurs at multiple levels that include assembly of transcriptional complexes and genome compartments, feedback regulation of active genes, silencing of genes, and control of protein kinases. We thus provide an RNA-centric view of transcriptional regulation that must reside alongside the more traditional DNA-protein-centric perspectives on gene regulation and genome architecture.

Network modeling links kidney developmental programs and the cancer type-specificity of VHL mutations

Elucidating the molecular dependencies behind the cancer-type specificity of driver mutations may reveal new therapeutic opportunities. We hypothesized that developmental programs would impact the transduction of oncogenic signaling activated by a driver mutation and shape its cancer-type specificity. Therefore, we designed a computational analysis framework by combining single-cell gene expression profiles during fetal organ development, latent factor discovery, and information theory-based differential network analysis to systematically identify transcription factors that selectively respond to driver mutations under the influence of organ-specific developmental programs. After applying this approach to VHL mutations, which are highly specific to clear cell renal cell carcinoma (ccRCC), we revealed important regulators downstream of VHL mutations in ccRCC and used their activities to cluster patients with ccRCC into three subtypes. This classification revealed a more significant difference in prognosis than the previous mRNA profile-based method and was validated in an independent cohort. Moreover, we found that EP300, a key epigenetic factor maintaining the regulatory network of the subtype with the worst prognosis, can be targeted by a small inhibitor, suggesting a potential treatment option for a subset of patients with ccRCC. This work demonstrated an intimate relationship between organ development and oncogenesis from the perspective of systems biology, and the method can be generalized to study the influence of other biological processes on cancer driver mutations.