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Background: Bidirectional promoters (BPs) are prevalent in eukaryotic genomes. However, it is poorly understood how the cell integrates different epigenomic information, such as transcription factor (TF) binding and chromatin marks, to drive gene expression at BPs. Single-cell sequencing technologies are revolutionizing the field of genome biology. Therefore, this study focuses on the integration of single-cell RNA-seq data with bulk ChIP-seq and other epigenetics data, for which single-cell technologies are not yet established, in the context of BPs.
Results: We performed integrative analyses of novel human single-cell RNA-seq (scRNA-seq) data with bulk ChIP-seq and other epigenetics data. scRNA-seq data revealed distinct transcription states of BPs that were previously not recognized. We find associations between these transcription states to distinct patterns in structural gene features, DNA accessibility, histone modification, DNA methylation and TF binding profiles.
Conclusions: Our results suggest that a complex interplay of all of these elements is required to achieve BP-specific transcriptional output in this specialized promoter configuration. Further, our study implies that novel statistical methods can be developed to deconvolute masked subpopulations of cells measured with different bulk epigenomic assays using scRNA-seq data.
Self-extracellular RNA (eRNA), released from stressed or injured cells upon various pathological situations such as ischemia-reperfusion-injury, has been shown to act as an alarmin by inducing procoagulatory and proinflammatory responses. In particular, M1-polarization of macrophages by eRNA resulted in the expression and release of a variety of cytokines, including tumor necrosis factor (TNF)-α or interleukin-6 (IL-6). The present study now investigates in which way self-eRNA may influence the response of macrophages towards various Toll-like receptor (TLR)-agonists. Isolated agonists of TLR2 (Pam2CSK4), TLR3 (PolyIC), TLR4 (LPS), or TLR7 (R848) induced the release of TNF-α in a concentration-dependent manner in murine macrophages, differentiated from bone marrow-derived stem cells by mouse colony stimulating factor. Here, the presence of eRNA shifted the dose-response curve for Pam2CSK4 (Pam) considerably to the left, indicating that eRNA synergistically enhanced the cytokine liberation from macrophages even at very low Pam-levels. The synergistic activation of TLR2 by eRNA/Pam was duplicated by other TLR2-agonists such as FSL-1 or Pam3CSK4. In contrast, for TLR4-agonists such as LPS a synergistic effect of eRNA was much weaker, and was not existent for TLR3-, or TLR7-agonists. The synergistic eRNA/Pam action was dependent on the NFκB-signaling pathway as well as on p38MAP- and MEK1/ERK-kinases and was prevented by predigestion of eRNA with RNase1 or by antibodies against TLR2. Thus, the presence of self-eRNA as alarming molecule sensitizes innate immune responses towards pathogen-associated molecular patterns (PAMPs) in a synergistic way and may thereby contribute to the differentiated outcome of inflammatory responses.
Motivation DNA CpG methylation (CpGm) has proven to be a crucial epigenetic factor in the gene regulatory system. Assessment of DNA CpG methylation values via whole-genome bisulfite sequencing (WGBS) is, however, computationally extremely demanding.
Results We present FAst MEthylation calling (FAME), the first approach to quantify CpGm values directly from bulk or single-cell WGBS reads without intermediate output files. FAME is very fast but as accurate as standard methods, which first produce BS alignment files before computing CpGm values. We present experiments on bulk and single-cell bisulfite datasets in which we show that data analysis can be significantly sped-up and help addressing the current WGBS analysis bottleneck for large-scale datasets without compromising accuracy.
Availability An implementation of FAME is open source and licensed under GPL-3.0 at https://github.com/FischerJo/FAME.