Transcription Factor Binding Profiles Research Articles

RUNX1-induced upregulation of PTGS2 enhances cell growth, migration and invasion in colorectal cancer cells

Colorectal cancer (CRC) arises via the progressive accumulation of dysregulation in key genes including oncogenes and tumor-suppressor genes. Prostaglandin-endoperoxide synthase 2 (PTGS2, also called COX2) acts as an oncogenic driver in CRC. Here, we explored the upstream transcription factors (TFs) responsible for elevating PTGS2 expression in CRC cells. The results showed that PTGS2 silencing repressed cell growth, migration and invasion in HCT116 and SW480 CRC cells. The two fragments (499–981 bp) and (1053–1434 bp) were confirmed as the core TF binding profiles of the PTGS2 promoter. PTGS2 expression positively correlated with RUNX1 level in colon adenocarcinoma (COAD) samples using the TCGA-COAD dataset. Furthermore, RUNX1 acted as a positive regulator of PTGS2 expression by promoting transcriptional activation of the PTGS2 promoter via the 1086–1096 bp binding motif. In conclusion, our study demonstrates that PTGS2 upregulation induced by the TF RUNX1 promotes CRC cell growth, migration and invasion, providing an increased rationale for the use of PTGS2 inhibitors in CRC prevention and treatment.

Abstract 1695: Genomic clustering tendency of transcription factors reflects phase-separated transcriptional condensates at cancer super-enhancers

Abstract Many transcription factors (TFs) have been shown to bind to super-enhancers, forming transcriptional condensates to activate transcription in various cellular systems including cancer. However, the genomic and epigenomic determinants of phase-separated transcriptional condensate formation remain poorly understood. Questions regarding which TFs tend to associate with transcriptional condensates and what factors influence their association are largely unanswered. Here we systematically analyzed 528 DNA sequence motifs across the human genome and 6,650 TF binding profiles across different cell types to identify the molecular features contributing to the formation of transcriptional condensates. We found that the genomic distributions of sequence motifs for different TFs exhibit distinct clustering tendencies. Notably, TF motifs with a high genomic clustering tendency are significantly associated with super-enhancers. TF binding profiles showing a high genomic clustering tendency are further enriched at cell-type-specific super-enhancers. TFs with a high binding clustering tendency also possess high liquid-liquid phase separation abilities. Compared to non-clustered TF binding, densely clustered TF binding sites are more enriched at cell-type-specific super-enhancers with higher chromatin accessibility, elevated chromatin interaction, and stronger association with cancer outcomes. Our results indicate that the clustered genomic binding patterns and the phase separation properties of TFs collectively contribute to the formation of transcriptional condensates at cancer super-enhancers. Citation Format: Zhenjia Wang, Shengyuan Wang, Chongzhi Zang. Genomic clustering tendency of transcription factors reflects phase-separated transcriptional condensates at cancer super-enhancers [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 1695.

Abstract 7355: Integration analysis of lncRNAs and R-loops in 3D genome organization and gene regulation in the cancer genome

Abstract Existing evidence shows that some long non-coding RNAs (lncRNAs) can recruit chromatin regulators and form R-loops to mediate CCTCC-binding factor (CTCF) binding at topologically associated domain (TAD) boundaries to activate transcription of target genes. However, it remains unclear to what extent such lncRNA-dependent chromatin organization events occur genome-wide in normal and cancer cells. By curated public data of lncRNA, CTCF, RAD21 profiles and integrative analysis of multi-omics data using innovative computational approaches, we investigated global associations of lncRNAs and R-loops with activities of transcription factors and chromatin regulators in gene expression regulations across multiple human cell types. We developed a comprehensive computational pipeline for cross-cell-type analysis of lncRNA and protein-coding gene expression profiles and transcription factor binding profiles. We identified a total of 542 candidate genomic regions where lncRNAs play a pivotal role in regulating target genes by facilitating CTCF/cohesin binding. R-loops are enriched at CTCF/cohesin binding sites, suggesting their potential contribution to CTCF binding. Additionally, our findings underscore the significant cell-type specificity of CTCF binding patterns across the genome. This work adds knowledge to cancer genome organization and gene regulation, and builds foundations for further functional and mechanistic studies of lncRNAs and R-loops in the human genome. Citation Format: Shengyuan Wang, Zhenjia Wang, Yuh-Hwa Wang, Hui Li, Peter Todd Stukenburg, Chongzhi Zang. Integration analysis of lncRNAs and R-loops in 3D genome organization and gene regulation in the cancer genome [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 7355.

SP3-induced Timeless transcription contributes to cell growth of lung adenocarcinoma cells.

Timeless is well-known for its key role in replication checkpoints. Recent studies reveal the involvement of Timeless and specificity protein (SP) 1 in human malignancies. However, no evidence proved the interaction between SP3 and Timeless in lung adenocarcinoma (LUAD). The expression and clinical significance of Timeless were analyzed using the LUAD dataset downloaded from the Cancer Genome Atlas (TCGA). Lentivirus-mediated Timeless knockdown in A549 cells was used to examine the role of Timeless in cell proliferation and pemetrexed (PEM) resistance. Transcription factors (TFs) bound to the Timeless promoter were identified by DNA pull-down technology with HPLC-MS/MS analysis and analyzed by the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway. Dual-luciferase reporter assay was used to determine the activity of SP3 in Timeless transcription. Timeless was overexpressed in LUAD samples, and it could serve as a potential diagnostic or prognostic biomarker for LUAD patients. shTimeless-mediated knockdown of Timeless reduced cell viability and proliferation and sensitized PEM-resistant A549 cells to PEM. Four fragments (F1: 1-373 bp), (F2: 374-962 bp), (F4: 1274-1645 bp), and (F5: 1646-2000bp) were confirmed as the TF binding profiles of the Timeless promoter. KEGG analysis showed that the TFs bound to the Timeless promoter had relevance to spliceosome, RNA transport, and mRNA surveillance pathways. SP3 promoted the transcription of Timeless via the F2 fragment (374-962 bp) binding motif. Upregulation of Timeless mediated by SP3 promotes LUAD cell proliferation, providing evidence to support that targeting the SP3/Timeless axis may be a potential therapeutic strategy against LUAD.

SNP Analysis of TLR4 Promoter and Its Transcriptional Factor Binding Profile in Relevance to Bovine Subclinical Mastitis.

Bovine mastitis is a complex infectious disease that develops in the mammary gland, predominantly caused by a bacterial infection of mammary tissue. Genetic variability of mastitis is well established and depends upon different quantitative trait loci (QTL) related to mastitis resistance or susceptibility. The susceptibility is often attributed to single-nucleotide polymorphisms (SNPs) in the variable cow breed genomes. Several global investigative attempts have resulted in studies mapping mastitis to the variations in the relevant genes. Reports have been attributed to dramatic genetic expression changes in Toll-Like Receptor 4 (TLR4) genes in mastitis-positive cows. However, the mechanism behind this variable genetic expression of TLR4 genes has been studied poorly. The present study aims to investigate SCM through various screening tests like somatic cell count (SCC), electric conductivity (EC), pH, and California mastitis test (CMT) in milk samples. This study also aims to investigate possible mechanisms behind this variable expression of TLR4 by comparative SNP evaluation and transcriptional factor profile mining. So that the important genetic mutations and effects thereof can be exploited in selecting specific breeds with higher mastitis resistance and milk yield. Seventy Holstein Frisian (HF) crossbred dairy cows were selected in the present study. The animals were screened based on various diagnostic tests (SCC, pH, EC, and CMT). Blood samples (5mL) were collected for extraction of DNA followed by amplification of PPR1 and PPR2 of the promoter region and 5'UTR of the bovine TLR4 gene using specific primers. Sanger's enzymatic DNA sequencing technique sequenced the amplified PCR products. Further, the identification of SNPs was done through various bioinformatic tools used in this study. The findings of the present study revealed that CMT, EC, pH, and SCC could be used for the early detection of subclinical mastitis. In the present study, a significant increase in the EC, pH, and SCC in milk samples of animals affected with SCM was found in comparison to the healthy animals. The present study also revealed 16 SNPs falling in TLR4 promoter and 5' untranslated region (5'UTR) sequences in mastitis-positive genotypes compared to reference genomes. The study also investigates the potential transcriptional factor program deployed in response to variable mastitis development resistance. In the present study, the allelic and genotype frequencies of all SNP variants in the three regions viz., PPR1, PPR2, and 5'UTR, were the same indicating the absence of heterozygous condition at the respective loci. The present study has wide applicability for researchers developing mastitis-resistant breeding programs and the data generated may aid in the selection of better genetic breeds. The transcription factor binding profiles can serve as concrete leads about the studies on bovine mastitis at the molecular level and may also aid global research groups working on transcription factor (TF)-based molecular pathology of mastitis.

Mapping enhancer and chromatin accessibility landscapes charts the regulatory network of Alzheimer's disease

BackgroundEnhancers are regulatory elements that target and modulate gene expression and play a role in human health and disease. However, the roles of enhancer regulatory circuit abnormalities driven by epigenetic alterations in Alzheimer's disease (AD) are unclear. MethodsIn this study, a multiomic integrative analysis was performed to map enhancer and chromatin accessibility landscapes and identify regulatory network abnormalities in AD. We identified differentially methylated enhancers and constructed regulatory networks across brain regions using AD brain tissue samples. Through the integration of snATAC-seq and snRNA-seq datasets, we mapped enhancers with DNA methylation alterations (DMA) and chromatin accessibility landscapes. Core regulatory triplets that contributed to AD neuropathology in specific cell types were further prioritized. ResultsWe revealed widespread DNA methylation alterations (DMA) in the enhancers of AD patients across different brain regions. In addition, the genome-wide transcription factor (TF) binding profiles showed that enhancers with DMA are pervasively regulated by TFs. The TF-enhancer-gene regulatory network analysis identified core regulatory triplets that are associated with brain and immune cell proportions and play important roles in AD pathogenesis. Enhancer regulatory circuits with DMA exhibited distinct chromatin accessibility patterns, which were further characterized at single-cell resolutions. ConclusionsOur study comprehensively investigated DNA methylation-mediated regulatory circuit abnormalities and provided novel insights into the potential pathogenesis of AD.

JASPAR 2024: 20th anniversary of the open-access database of transcription factor binding profiles.

JASPAR (https://jaspar.elixir.no/) is a widely-used open-access database presenting manually curated high-quality and non-redundant DNA-binding profiles for transcription factors (TFs) across taxa. In this 10th release and 20th-anniversary update, the CORE collection has expanded with 329 new profiles. We updated three existing profiles and provided orthogonal support for 72 profiles from the previous release's UNVALIDATED collection. Altogether, the JASPAR 2024 update provides a 20% increase in CORE profiles from the previous release. A trimming algorithm enhanced profiles by removing low information content flanking base pairs, which were likely uninformative (within the capacity of the PFM models) for TFBS predictions and modelling TF-DNA interactions. This release includes enhanced metadata, featuring a refined classification for plant TFs' structural DNA-binding domains. The new JASPAR collections prompt updates to the genomic tracks of predicted TFbinding sites (TFBSs) in 8 organisms, with human and mouse tracks available as native tracks in the UCSC Genome browser. All data are available through the JASPAR web interface and programmatically through its API and the updated Bioconductor and pyJASPAR packages. Finally, a new TFBS extraction tool enables users to retrieve predicted JASPAR TFBSs intersecting their genomic regions of interest.

BloodChIP Xtra: an expanded database of comparative genome-wide transcription factor binding and gene-expression profiles in healthy human stem/progenitor subsets and leukemic cells.

The BloodChIP Xtra database (http://bloodchipXtra.vafaeelab.com/) facilitates genome-wide exploration and visualization of transcription factor (TF) occupancy and chromatin configuration in rare primary human hematopoietic stem (HSC-MPP) and progenitor (CMP, GMP, MEP) cells and acute myeloid leukemia (AML) cell lines (KG-1, ME-1, Kasumi1, TSU-1621-MT), along with chromatin accessibility and gene expression data from these and primary patient AMLs. BloodChIP Xtra features significantly more datasets than our earlier database BloodChIP (two primary cell types and two cell lines). Improved methodologies for determining TF occupancy and chromatin accessibility have led to increased availability of data for rare primary cell types across the spectrum of healthy and AML hematopoiesis. However, there is a continuing need for these data to be integrated in an easily accessible manner for gene-based queries and use in downstream applications. Here, we provide a user-friendly database based around genome-wide binding profiles of key hematopoietic TFs and histone marks in healthy stem/progenitor cell types. These are compared with binding profiles and chromatin accessibility derived from primary and cell line AML and integrated with expression data from corresponding cell types. All queries can be exported to construct TF-gene and protein-protein networks and evaluate the association of genes with specific cellular processes.

A hybrid RNA FISH immunofluorescence protocol on Drosophila polytene chromosomes

ObjectivesInvestigating protein-DNA interactions is imperative to understanding fundamental concepts such as cell growth, differentiation, and cell development in many systems. Sequencing techniques such as ChIP-seq can yield genome-wide DNA binding profiles of transcription factors; however this assay can be expensive, time-consuming, may not be informative for repetitive regions of the genome, and depend heavily upon antibody suitability. Combining DNA fluorescence in situ hybridization (FISH) with immunofluorescence (IF) is a quicker and inexpensive approach which has historically been used to investigate protein-DNA interactions in individual nuclei. However, these assays are sometimes incompatible due to the required denaturation step in DNA FISH that can alter protein epitopes, hindering primary antibody binding. Additionally, combining DNA FISH with IF may be challenging for less experienced trainees. Our goal was to develop an alternative technique to investigate protein-DNA interactions by combining RNA FISH with IF.ResultsWe developed a hybrid RNA FISH-IF protocol for use on Drosophila melanogaster polytene chromosome spreads in order to visualize colocalization of proteins and DNA loci. We demonstrate that this assay is sensitive enough to determine if our protein of interest, Multi sex combs (Mxc), localizes to single-copy target transgenes carrying histone genes. Overall, this study provides an alternative, accessible method for investigating protein-DNA interactions at the single gene level in Drosophila melanogaster polytene chromosomes.

Genome-wide transcription factor–binding maps reveal cell-specific changes in the regulatory architecture of human HSPCs

AbstractHematopoietic stem and progenitor cells (HSPCs) rely on a complex interplay among transcription factors (TFs) to regulate differentiation into mature blood cells. A heptad of TFs (FLI1, ERG, GATA2, RUNX1, TAL1, LYL1, LMO2) bind regulatory elements in bulk CD34+ HSPCs. However, whether specific heptad-TF combinations have distinct roles in regulating hematopoietic differentiation remains unknown. We mapped genome-wide chromatin contacts (HiC, H3K27ac, HiChIP), chromatin modifications (H3K4me3, H3K27ac, H3K27me3) and 10 TF binding profiles (heptad, PU.1, CTCF, STAG2) in HSPC subsets (stem/multipotent progenitors plus common myeloid, granulocyte macrophage, and megakaryocyte erythrocyte progenitors) and found TF occupancy and enhancer-promoter interactions varied significantly across cell types and were associated with cell-type–specific gene expression. Distinct regulatory elements were enriched with specific heptad-TF combinations, including stem-cell–specific elements with ERG, and myeloid- and erythroid-specific elements with combinations of FLI1, RUNX1, GATA2, TAL1, LYL1, and LMO2. Furthermore, heptad-occupied regions in HSPCs were subsequently bound by lineage-defining TFs, including PU.1 and GATA1, suggesting that heptad factors may prime regulatory elements for use in mature cell types. We also found that enhancers with cell-type–specific heptad occupancy shared a common grammar with respect to TF binding motifs, suggesting that combinatorial binding of TF complexes was at least partially regulated by features encoded in DNA sequence motifs. Taken together, this study comprehensively characterizes the gene regulatory landscape in rare subpopulations of human HSPCs. The accompanying data sets should serve as a valuable resource for understanding adult hematopoiesis and a framework for analyzing aberrant regulatory networks in leukemic cells.

The CUT&RUN suspect list of problematic regions of the genome

BackgroundCleavage Under Targets and Release Using Nuclease (CUT&RUN) is an increasingly popular technique to map genome-wide binding profiles of histone modifications, transcription factors, and co-factors. The ENCODE project and others have compiled blacklists for ChIP-seq which have been widely adopted: these lists contain regions of high and unstructured signal, regardless of cell type or protein target, indicating that these are false positives. While CUT&RUN obtains similar results to ChIP-seq, its biochemistry and subsequent data analyses are different. We found that this results in a CUT&RUN-specific set of undesired high-signal regions.ResultsWe compile suspect lists based on CUT&RUN data for the human and mouse genomes, identifying regions consistently called as peaks in negative controls. Using published CUT&RUN data from our and other labs, we show that the CUT&RUN suspect regions can persist even when peak calling is performed with SEACR or MACS2 against a negative control and after ENCODE blacklist removal. Moreover, we experimentally validate the CUT&RUN suspect lists by performing reiterative negative control experiments in which no specific protein is targeted, showing that they capture more than 80% of the peaks identified.ConclusionsWe propose that removing these problematic regions can substantially improve peak calling in CUT&RUN experiments, resulting in more reliable datasets.

Multimodal single cell analysis infers widespread enhancer co-activity in a lymphoblastoid cell line

Non-coding regulatory elements such as enhancers are key in controlling the cell-type specificity and spatio-temporal expression of genes. To drive stable and precise gene transcription robust to genetic variation and environmental stress, genes are often targeted by multiple enhancers with redundant action. However, it is unknown whether enhancers targeting the same gene display simultaneous activity or whether some enhancer combinations are more often co-active than others. Here, we take advantage of recent developments in single cell technology that permit assessing chromatin status (scATAC-seq) and gene expression (scRNA-seq) in the same single cells to correlate gene expression to the activity of multiple enhancers. Measuring activity patterns across 24,844 human lymphoblastoid single cells, we find that the majority of enhancers associated with the same gene display significant correlation in their chromatin profiles. For 6944 expressed genes associated with enhancers, we predict 89,885 significant enhancer-enhancer associations between nearby enhancers. We find that associated enhancers share similar transcription factor binding profiles and that gene essentiality is linked with higher enhancer co-activity. We provide a set of predicted enhancer-enhancer associations based on correlation derived from a single cell line, which can be further investigated for functional relevance.

The interaction between enhancer variants and environmental factors as an overlooked aetiological paradigm in human complex disease.

The interactions between genetic and environmental risk factors contribute to the aetiology of complex human diseases. Genome-wide association studies (GWAS) have revealed that most of the genetic variants associated with complex diseases are located in the non-coding part of the genome, preferentially within enhancers. Enhancers are distal cis-regulatory elements composed of clusters of transcription factors binding sites that positively regulate the expression of their target genes. The generation of genome-wide maps for histone marks (e.g., H3K27ac), chromatin accessibility and transcription factor and coactivator (e.g., p300) binding profiles have enabled the identification of enhancers across many human cell types and tissues. Nonetheless, the functional and pathological consequences of the majority of disease-associated genetic variants located within enhancers seem to be rather minor under normal conditions, thus questioning their medical relevance. Here we propose that, due to the prevalence of enhancer redundancy, the pathological effects of many disease-associated non-coding genetic variants might be preferentially (or even only) manifested under environmental stress.

Genetic Analysis of Variants of the MYH6 Gene Promoter in Congenital Atrial Septal Defects

Background: Atrial septal defect (ASD) is one of the common congenital heart diseases. The MYH6 gene has a critical role in cardiac development but the role of MYH6 promoter variants in patients with ASD has not been explored. Methods: In 613 subjects including 320 ASD patients, we investigated the MYH6 gene promoter variants and verified the effect on gene expression by using cellular functional experiments and bioinformatics analysis. Results: Eleven variants were identified in the MYH6 gene promoter, of which four variants were found only in ASD patients, and two variants (g.3434G>C and g.4524C>T) were identified for the first time. Cellular functional experiments indicated that all four variants reduced the transcriptional activity of the MYH6 gene promoter (p < 0.05). Subsequent analysis through the JASPAR (A database of transcription factor binding profiles) suggests that these variants may alter transcription factor binding sites, which may in turn lead to changes in myocardin subunit expression and ASD formation. Conclusions: Our study for the first time focuses on variants in the promoter region of the MYH6 gene in Chinese patients with ASD and the discovered variants have functional significance. The study provides new insights in the role of the MYH6 gene promoter region to better understand the genetic basis of ASD formation and facilitates clinical diagnosis.

Hi-TrAC reveals division of labor of transcription factors in organizing chromatin loops

The three-dimensional genomic structure plays a critical role in gene expression, cellular differentiation, and pathological conditions. It is pivotal to elucidate fine-scale chromatin architectures, especially interactions of regulatory elements, to understand the temporospatial regulation of gene expression. In this study, we report Hi-TrAC as a proximity ligation-free, robust, and sensitive technique to profile genome-wide chromatin interactions at high-resolution among regulatory elements. Hi-TrAC detects chromatin looping among accessible regions at single nucleosome resolution. With almost half-million identified loops, we reveal a comprehensive interaction network of regulatory elements across the genome. After integrating chromatin binding profiles of transcription factors, we discover that cohesin complex and CTCF are responsible for organizing long-range chromatin loops, related to domain formation; whereas ZNF143 and HCFC1 are involved in structuring short-range chromatin loops between regulatory elements, which directly regulate gene expression. Thus, we introduce a methodology to identify a delicate and comprehensive network of cis-regulatory elements, revealing the complexity and a division of labor of transcription factors in organizing chromatin loops for genome organization and gene expression.

Changes in chromatin accessibility are not concordant with transcriptional changes for single-factor perturbations.

A major goal in the field of transcriptional regulation is the mapping of changes in the binding of transcription factors to the resultant changes in gene expression. Recently, methods for measuring chromatin accessibility have enabled us to measure changes in accessibility across the genome, which are thought to correspond to transcription factor‐binding events. In concert with RNA‐sequencing, these data in principle enable such mappings; however, few studies have looked at their concordance over short‐duration treatments with specific perturbations. Here, we used tandem, bulk ATAC‐seq, and RNA‐seq measurements from MCF‐7 breast carcinoma cells to systematically evaluate the concordance between changes in accessibility and changes in expression in response to retinoic acid and TGF‐β. We found two classes of genes whose expression showed a significant change: those that showed some changes in the accessibility of nearby chromatin, and those that showed virtually no change despite strong changes in expression. The peaks associated with genes in the former group had lower baseline accessibility prior to exposure to signal. Focusing the analysis specifically on peaks with motifs for transcription factors associated with retinoic acid and TGF‐β signaling did not reduce the lack of correspondence. Analysis of paired chromatin accessibility and gene expression data from distinct paths along the hematopoietic differentiation trajectory showed a much stronger correspondence, suggesting that the multifactorial biological processes associated with differentiation may lead to changes in chromatin accessibility that reflect rather than driving altered transcriptional status. Together, these results show many gene expression changes can happen independently of changes in the accessibility of local chromatin in the context of a single‐factor perturbation.

CisCross: A gene list enrichment analysis to predict upstream regulators in Arabidopsis thaliana.

Having DNA-binding profiles for a sufficient number of genome-encoded transcription factors (TFs) opens up the perspectives for systematic evaluation of the upstream regulators for the gene lists. Plant Cistrome database, a large collection of TF binding profiles detected using the DAP-seq method, made it possible for Arabidopsis. Here we re-processed raw DAP-seq data with MACS2, the most popular peak caller that leads among other ones according to quality metrics. In the benchmarking study, we confirmed that the improved collection of TF binding profiles supported a more precise gene list enrichment procedure, and resulted in a more relevant ranking of potential upstream regulators. Moreover, we consistently recovered the TF binding profiles that were missing in the previous collection of DAP-seq peak sets. We developed the CisCross web service (https://plamorph.sysbio.ru/ciscross/) that gives more flexibility in the analysis of potential upstream TF regulators for Arabidopsis thaliana genes.

HOTAIR interacts with PRC2 complex regulating the regional preadipocyte transcriptome and human fat distribution.

Mechanisms governing regional human adipose tissue (AT) development remain undefined. Here, we show that the long non-coding RNA HOTAIR (HOX transcript antisense RNA) is exclusively expressed in gluteofemoral AT, where it is essential for adipocyte development. We find that HOTAIR interacts with polycomb repressive complex 2 (PRC2) and we identify core HOTAIR-PRC2 target genes involved in adipocyte lineage determination. Repression of target genes coincides with PRC2 promoter occupancy and H3K27 trimethylation. HOTAIR is also involved in modifying the gluteal adipocyte transcriptome through alternative splicing. Gluteal-specific expression of HOTAIR is maintained by defined regions of open chromatin across the HOTAIR promoter. HOTAIR expression levels can be modified by hormonal (estrogen, glucocorticoids) and genetic variation (rs1443512 is a HOTAIR eQTL associated with reduced gynoid fat mass). These data identify HOTAIR as a dynamic regulator of the gluteal adipocyte transcriptome and epigenome with functional importance for human regional AT development.

Statistical estimates of multiple transcription factors binding in the model plant genomes based on ChIP-seq data.

The development of high-throughput genomic sequencing coupled with chromatin immunoprecipitation technologies allows studying the binding sites of the protein transcription factors (TF) in the genome scale. The growth of data volume on the experimentally determined binding sites raises qualitatively new problems for the analysis of gene expression regulation, prediction of transcription factors target genes, and regulatory gene networks reconstruction. Genome regulation remains an insufficiently studied though plants have complex molecular regulatory mechanisms of gene expression and response to environmental stresses. It is important to develop new software tools for the analysis of the TF binding sites location and their clustering in the plant genomes, visualization, and the following statistical estimates. This study presents application of the analysis of multiple TF binding profiles in three evolutionarily distant model plant organisms. The construction and analysis of non-random ChIP-seq binding clusters of the different TFs in mammalian embryonic stem cells were discussed earlier using similar bioinformatics approaches. Such clusters of TF binding sites may indicate the gene regulatory regions, enhancers and gene transcription regulatory hubs. It can be used for analysis of the gene promoters as well as a background for transcription networks reconstruction. We discuss the statistical estimates of the TF binding sites clusters in the model plant genomes. The distributions of the number of different TFs per binding cluster follow same power law distribution for all the genomes studied. The binding clusters in Arabidopsis thaliana genome were discussed here in detail.

JASPAR 2022: the 9th release of the open-access database of transcription factor binding profiles.

JASPAR (http://jaspar.genereg.net/) is an open-access database containing manually curated, non-redundant transcription factor (TF) binding profiles for TFs across six taxonomic groups. In this 9th release, we expanded the CORE collection with 341 new profiles (148 for plants, 101 for vertebrates, 85 for urochordates, and 7 for insects), which corresponds to a 19% expansion over the previous release. We added 298 new profiles to the Unvalidated collection when no orthogonal evidence was found in the literature. All the profiles were clustered to provide familial binding profiles for each taxonomic group. Moreover, we revised the structural classification of DNA binding domains to consider plant-specific TFs. This release introduces word clouds to represent the scientific knowledge associated with each TF. We updated the genome tracks of TFBSs predicted with JASPAR profiles in eight organisms; the human and mouse TFBS predictions can be visualized as native tracks in the UCSC Genome Browser. Finally, we provide a new tool to perform JASPAR TFBS enrichment analysis in user-provided genomic regions. All the data is accessible through the JASPAR website, its associated RESTful API, the R/Bioconductor data package, and a new Python package, pyJASPAR, that facilitates serverless access to the data.