Integrative analysis of epigenetics data identifies gene-specific regulatory elements

A statistical approach for identifying single nucleotide variants that affect transcription factor binding

Non-coding variants located within regulatory elements may alter gene expression by modifying transcription factor (TF) binding sites, thereby leading to functional consequences. Different TF models are being used to assess the effect of DNA sequence variants, such as single nucleotide variants (SNVs). Often existing methods are slow and do not assess statistical significance of results. We investigated the distribution of absolute maximal differential TF binding scores for general computational models that affect TF binding. We find that a modified Laplace distribution can adequately approximate the empirical distributions. A benchmark on in vitro and in vivo datasets showed that our approach improves upon an existing method in terms of performance and speed. Applications on eQTLs and on a genome-wide association study illustrate the usefulness of our statistics by highlighting cell type-specific regulators and target genes. An implementation of our approach is freely available on GitHub and as bioconda package.

Churros: a Docker-based pipeline for large-scale epigenomic analysis

The epigenome, which reflects the modifications on chromatin or DNA sequences, provides crucial insight into gene expression regulation and cellular activity. With the continuous accumulation of epigenomic datasets such as chromatin immunoprecipitation followed by sequencing (ChIP-seq) data, there is a great demand for a streamlined pipeline to consistently process them, especially for large-dataset comparisons involving hundreds of samples. Here, we present Churros, an end-to-end epigenomic analysis pipeline that is environmentally independent and optimized for handling large-scale data. We successfully demonstrated the effectiveness of Churros by analyzing large-scale ChIP-seq datasets with the hg38 or Telomere-to-Telomere (T2T) human reference genome. We found that applying T2T to the typical analysis workflow has important impacts on read mapping, quality checks, and peak calling. We also introduced a useful feature to study context-specific epigenomic landscapes. Churros will contribute a comprehensive and unified resource for analyzing large-scale epigenomic data.

Atlas of nascent RNA transcripts reveals enhancer to gene linkages

Gene transcription is controlled and modulated by regulatory regions, including enhancers and promoters. These regions are abundant in unstable, non-coding bidirectional transcription. Using nascent RNA transcription data across hundreds of human samples, we identified over 800,000 regions containing bidirectional transcription. We then identify highly correlated transcription between bidirectional and gene regions. The identified correlated pairs, a bidirectional region and a gene, are enriched for disease associated SNPs and often supported by independent 3D data. We present these resources as an SQL database which serves as a resource for future studies into gene regulation, enhancer associated RNAs, and transcription factors.

MYB regulates the SUMO protease SENP1 and its novel interaction partner UXT, modulating MYB target genes and the SUMO landscape

SUMOylation is a post-translational modification frequently found on nuclear proteins, including transcription factors (TFs) and coactivators. By controlling the activity of several TFs, SUMOylation may have far-reaching effects. MYB is an example of a developmental TF subjected to SUMO-mediated regulation, through both SUMO conjugation and SUMO binding. How SUMO affects MYB target genes is unknown. Here, we explored the global effect of reduced SUMOylation of MYB on its downstream gene programs. RNA-Seq in K562 cells after MYB knockdown and rescue with mutants having an altered SUMO status revealed a number of differentially regulated genes and distinct gene ontology term enrichments. Clearly, the SUMO status of MYB both quantitatively and qualitatively affects its regulome. The transcriptome data further revealed that MYB upregulates the SUMO protease SENP1, a key enzyme that removes SUMO conjugation from SUMOylated proteins. Given this role of SENP1 in the MYB regulome, we expanded the analysis, mapped interaction partners of SENP1, and identified UXT as a novel player affecting the SUMO system by acting as a repressor of SENP1. MYB inhibits the expression of UXT suggesting that MYB is able not only to control a specific gene program directly but also indirectly by affecting the SUMO landscape through SENP1 and UXT. These findings suggest an autoactivation loop whereby MYB, through enhancing SENP1 and reducing UXT, is itself being activated by a reduced level of repressive SUMOylation. We propose that overexpressed MYB, seen in multiple cancers, may drive this autoactivation loop and contribute to oncogenic activation of MYB.

Circular RNA circPLOD2 regulates pericyte function by targeting the transcription factor KLF4

Circular RNAs are generated by backsplicing and control cellular signaling and phenotypes. Pericytes stabilize capillary structures and play important roles in the formation and maintenance of blood vessels. Here, we characterize hypoxia-regulated circular RNAs (circRNAs) in human pericytes and show that the circular RNA of procollagen-lysine,2-oxoglutarate 5-dioxygenase-2 (circPLOD2) is induced by hypoxia and regulates pericyte functions. Silencing of circPLOD2 affects pericytes and increases proliferation, migration, and secretion of soluble angiogenic proteins, thereby enhancing endothelial migration and network capability. Transcriptional and epigenomic profiling of circPLOD2-depleted cells reveals widespread changes in gene expression and identifies the transcription factor krüppel-like factor 4 (KLF4) as a key effector of the circPLOD2-mediated changes. KLF4 depletion mimics circPLOD2 silencing, whereas KLF4 overexpression reverses the effects of circPLOD2 depletion on proliferation and endothelial-pericyte interactions. Together, these data reveal an important function of circPLOD2 in controlling pericyte proliferation and capillary formation and show that the circPLOD2-mediated regulation of KLF4 significantly contributes to the transcriptional response to hypoxia.

CVD-associated SNPs with regulatory potential reveal novel non-coding disease genes

BACKGROUND

Cardiovascular diseases (CVDs) are the leading cause of death worldwide. Genome-wide association studies (GWAS) have identified many single nucleotide polymorphisms (SNPs) appearing in non-coding genomic regions in CVDs. The SNPs may alter gene expression by modifying transcription factor (TF) binding sites and lead to functional consequences in cardiovascular traits or diseases. To understand the underlying molecular mechanisms, it is crucial to identify which variations are involved and how they affect TF binding.

METHODS

The SNEEP (SNP exploration and analysis using epigenomics data) pipeline was used to identify regulatory SNPs, which alter the binding behavior of TFs and link GWAS SNPs to their potential target genes for six CVDs. The human-induced pluripotent stem cells derived cardiomyocytes (hiPSC-CMs), monoculture cardiac organoids (MCOs) and self-organized cardiac organoids (SCOs) were used in the study. Gene expression, cardiomyocyte size and cardiac contractility were assessed.

RESULTS

By using our integrative computational pipeline, we identified 1905 regulatory SNPs in CVD GWAS data. These were associated with hundreds of genes, half of them non-coding RNAs (ncRNAs), suggesting novel CVD genes. We experimentally tested 40 CVD-associated non-coding RNAs, among them RP11-98F14.11, RPL23AP92, IGBP1P1, and CTD-2383I20.1, which were upregulated in hiPSC-CMs, MCOs and SCOs under hypoxic conditions. Further experiments showed that IGBP1P1 depletion rescued expression of hypertrophic marker genes, reduced hypoxia-induced cardiomyocyte size and improved hypoxia-reduced cardiac contractility in hiPSC-CMs and MCOs.

CONCLUSIONS

IGBP1P1 is a novel ncRNA with key regulatory functions in modulating cardiomyocyte size and cardiac function in our disease models. Our data suggest ncRNA IGBP1P1 as a potential therapeutic target to improve cardiac function in CVDs.

MYB insufficiency disrupts proteostasis in hematopoietic stem cells, leading to age-related neoplasia

MYB plays a key role in gene regulation throughout the hematopoietic hierarchy and is critical for the maintenance of normal hematopoietic stem cells (HSC). Acquired genetic dysregulation of MYB is involved in the etiology of a number of leukemias, although inherited noncoding variants of the MYB gene are a susceptibility factor for many hematological conditions, including myeloproliferative neoplasms (MPN). The mechanisms that connect variations in MYB levels to disease predisposition, especially concerning age dependency in disease initiation, are completely unknown. Here, we describe a model of Myb insufficiency in mice that leads to MPN, myelodysplasia, and leukemia in later life, mirroring the age profile of equivalent human diseases. We show that this age dependency is intrinsic to HSC, involving a combination of an initial defective cellular state resulting from small effects on the expression of multiple genes and a progressive accumulation of further subtle changes. Similar to previous studies showing the importance of proteostasis in HSC maintenance, we observed altered proteasomal activity and elevated proliferation indicators, followed by elevated ribosome activity in young Myb-insufficient mice. We propose that these alterations combine to cause an imbalance in proteostasis, potentially creating a cellular milieu favoring disease initiation.

The adapted Activity-By-Contact model for enhancer-gene assignment and its application to single-cell data

MOTIVATION

Identifying regulatory regions in the genome is of great interest for understanding the epigenomic landscape in cells. One fundamental challenge in this context is to find the target genes whose expression is affected by the regulatory regions. A recent successful method is the Activity-By-Contact (ABC) model which scores enhancer-gene interactions based on enhancer activity and the contact frequency of an enhancer to its target gene. However, it describes regulatory interactions entirely from a gene's perspective, and does not account for all the candidate target genes of an enhancer. In addition, the ABC model requires two types of assays to measure enhancer activity, which limits the applicability. Moreover, there is neither implementation available that could allow for an integration with transcription factor (TF) binding information nor an efficient analysis of single-cell data.

RESULTS

We demonstrate that the ABC score can yield a higher accuracy by adapting the enhancer activity according to the number of contacts the enhancer has to its candidate target genes and also by considering all annotated transcription start sites of a gene. Further, we show that the model is comparably accurate with only one assay to measure enhancer activity. We combined our generalized ABC model with TF binding information and illustrated an analysis of a single-cell ATAC-seq dataset of the human heart, where we were able to characterize cell type-specific regulatory interactions and predict gene expression based on TF affinities. All executed processing steps are incorporated into our new computational pipeline STARE.

AVAILABILITY AND IMPLEMENTATION

The software is available at https://github.com/schulzlab/STARE.

CONTACT

marcel.schulz@em.uni-frankfurt.de.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

De novo annotation of lncRNA HOTAIR transcripts by long-read RNA capture-seq reveals a differentiation-driven isoform switch

Background

LncRNAs are tissue-specific and emerge as important regulators of various biological processes and as disease biomarkers. HOTAIR is a well-established pro-oncogenic lncRNA which has been attributed a variety of functions in cancer and native contexts. However, a lack of an exhaustive, cell type-specific annotation questions whether HOTAIR functions are supported by the expression of multiple isoforms.

Results

Using a capture long-read sequencing approach, we characterize HOTAIR isoforms expressed in human primary adipose stem cells. We find HOTAIR isoforms population displays varied splicing patterns, frequently leading to the exclusion or truncation of canonical LSD1 and PRC2 binding domains. We identify a highly cell type-specific HOTAIR isoform pool regulated by distinct promoter usage, and uncover a shift in the HOTAIR TSS usage that modulates the balance of HOTAIR isoforms at differentiation onset.

Conclusion

Our results highlight the complexity and cell type-specificity of HOTAIR isoforms and open perspectives on functional implications of these variants and their balance to key cellular processes.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12864-022-08887-w.

Pioneer transcription factors are associated with the modulation of DNA methylation patterns across cancers

Methylation of cytosines on DNA is a prominent modification associated with gene expression regulation. Aberrant DNA methylation patterns have recurrently been linked to dysregulation of the regulatory program in cancer cells. To shed light on the underlying molecular mechanism driving this process, we hypothesised that aberrant methylation patterns could be controlled by the binding of specific transcription factors (TFs) across cancer types. By combining DNA methylation arrays and gene expression data with TF binding sites (TFBSs), we explored the interplay between TF binding and DNA methylation in 19 cancer types. We performed emQTL (expression–methylation quantitative trait loci) analyses independently in each cancer type and identified 13 TFs whose expression levels are correlated with local DNA methylation patterns around their binding sites in at least 2 cancer types. The 13 TFs are mainly associated with local demethylation and are enriched for pioneer function, suggesting a specific role for these TFs in modulating chromatin structure and transcription in cancer patients. Furthermore, we confirmed that de novo methylation is precluded across cancers at CpGs lying in genomic regions enriched for TF binding signatures associated with SP1, CTCF, NRF1, GABPA, KLF9, and/or YY1. The modulation of DNA methylation associated with TF binding was observed at cis-regulatory regions controlling immune- and cancer-associated pathways, corroborating that the emQTL signals were derived from both cancer and tumor-infiltrating cells. As a case example, we experimentally confirmed that FOXA1 knock-down is associated with higher methylation in regions bound by FOXA1 in breast cancer MCF-7 cells. Finally, we reported physical interactions between FOXA1 with TET1 and TET2 both in an in vitro setup and in vivo at physiological levels in MCF-7 cells, adding further support for FOXA1 attracting TET1 and TET2 to induce local demethylation in cancer cells.