Mammalian transcriptional hotspots are enriched for tissue specific enhancers near cell type specific highly expressed genes and are predicted to act as transcriptional activator hubs

The regulatory landscape of neurite development in Caenorhabditis elegans

Neuronal communication requires precise connectivity of neurite projections (axons and dendrites). Developing neurites express cell-surface receptors that interpret extracellular cues to enable correct guidance toward, and connection with, target cells. Spatiotemporal regulation of neurite guidance molecule expression by transcription factors (TFs) is critical for nervous system development and function. Here, we review how neurite development is regulated by TFs in the Caenorhabditis elegans nervous system. By collecting publicly available transcriptome and ChIP-sequencing data, we reveal gene expression dynamics during neurite development, providing insight into transcriptional mechanisms governing construction of the nervous system architecture.

Macrophage GIT1 Contributes to Bone Regeneration by Regulating Inflammatory Responses in an ERK/NRF2-Dependent Way

Despite the best treatment, approximately 10% of fractures still face undesirable repair. Recently, many studies have focused on the importance of macrophages in bone repair; however, the cellular mechanisms by which they work are not yet fully understood. In this study, we explored the functions of macrophage G-protein-coupled receptor interacting protein 1 (GIT1) in healing a tibial monocortical defect model. Using GIT1^flox/flox Lyz2-Cre (GIT1 CKO) mice, we observed that a GIT1 deficiency in the macrophages led to an exacerbation of interleukin 1β (IL1β) production, more M1-like macrophage infiltration, and impaired intramembranous ossification in vivo. The results of in vitro assays further indicated that the macrophage GIT1 plays a critical role in several cellular processes in response to lipopolysaccharide (LPS), such as anti-oxidation, IL1β production alleviation, and glycolysis control. Although GIT1 has been recognized as a scaffold protein, our data clarified that GIT1-mediated extracellular-signal-regulated kinase (ERK) phosphorylation could activate nuclear factor (erythroid-derived 2)-like 2 (NRF2) in macrophages after LPS treatment. Moreover, we demonstrated that macrophage GIT1-activated ERK/NRF2 negatively regulates the 6-phosphofructo-2-kinase/fructose-2, 6-biphosphatase 3 (PFKFB3), facilitating the decrease of glycolysis. Our findings uncovered a previously unrecognized role of GIT1 in regulating ERK/NRF2 in macrophages to control the inflammatory response, suggesting that macrophage GIT1 could be a potential target to improve bone regeneration. © 2020 The Authors. Journal of Bone and Mineral Research published by American Society for Bone and Mineral Research..

SKmDB: an integrated database of next generation sequencing information in skeletal muscle

MOTIVATION

Skeletal muscles have indispensable functions and also possess prominent regenerative ability. The rapid emergence of Next Generation Sequencing (NGS) data in recent years offers us an unprecedented perspective to understand gene regulatory networks governing skeletal muscle development and regeneration. However, the data from public NGS database are often in raw data format or processed with different procedures, causing obstacles to make full use of them.

RESULTS

We provide SKmDB, an integrated database of NGS information in skeletal muscle. SKmDB not only includes all NGS datasets available in the human and mouse skeletal muscle tissues and cells, but also provide preliminary data analyses including gene/isoform expression levels, gene co-expression subnetworks, as well as assembly of putative lincRNAs, typical and super enhancers and transcription factor hotspots. Users can efficiently search, browse and visualize the information with the well-designed user interface and server side. SKmDB thus will offer wet lab biologists useful information to study gene regulatory mechanisms in the field of skeletal muscle development and regeneration.

AVAILABILITY AND IMPLEMENTATION

Freely available on the web at http://sunlab.cpy.cuhk.edu.hk/SKmDB.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Computational Biology Solutions to Identify Enhancers-target Gene Pairs

Enhancers are non-coding regulatory elements that are distant from their target gene. Their characterization still remains elusive especially due to challenges in achieving a comprehensive pairing of enhancers and target genes. A number of computational biology solutions have been proposed to address this problem leveraging the increasing availability of functional genomics data and the improved mechanistic understanding of enhancer action. In this review we focus on computational methods for genome-wide definition of enhancer-target gene pairs. We outline the different classes of methods, as well as their main advantages and limitations. The types of information integrated by each method, along with details on their applicability are presented and discussed. We especially highlight the technical challenges that are still unresolved and hamper the effective achievement of a satisfactory and comprehensive solution. We expect this field will keep evolving in the coming years due to the ever-growing availability of data and increasing insights into enhancers crucial role in regulating genome functionality.

Insights into mammalian transcription control by systematic analysis of ChIP sequencing data

Background

Transcription regulation is a major controller of gene expression dynamics during development and disease, where transcription factors (TFs) modulate expression of genes through direct or indirect DNA interaction. ChIP sequencing has become the most widely used technique to get a genome wide view of TF occupancy in a cell type of interest, mainly due to established standard protocols and a rapid decrease in the cost of sequencing. The number of available ChIP sequencing data sets in public domain is therefore ever increasing, including data generated by individual labs together with consortia such as the ENCODE project.

Results

A total of 1735 ChIP-sequencing datasets in mouse and human cell types and tissues were used to perform bioinformatic analyses to unravel diverse features of transcription control. 1- We used the Heat*seq webtool to investigate global relations across the ChIP-seq samples. 2- We demonstrated that factors have a specific genomic location preferences that are, for most factors, conserved across species. 3- Promoter proximal binding of factors was more conserved across cell types while the distal binding sites are more cell type specific. 4- We identified combinations of factors preferentially acting together in a cellular context. 5- Finally, by integrating the data with disease-associated gene loci from GWAS studies, we highlight the value of this data to associate novel regulators to disease.

Conclusion

In summary, we demonstrate how ChIP sequencing data integration and analysis is powerful to get new insights into mammalian transcription control and demonstrate the utility of various bioinformatic tools to generate novel testable hypothesis using this public resource.

Subsets of Visceral Adipose Tissue Nuclei with Distinct Levels of 5-Hydroxymethylcytosine

The reprogramming of cellular memory in specific cell types, and in visceral adipocytes in particular, appears to be a fundamental aspect of obesity and its related negative health outcomes. We explored the hypothesis that adipose tissue contains epigenetically distinct subpopulations of adipocytes that are differentially potentiated to record cellular memories of their environment. Adipocytes are large, fragile, and technically difficult to efficiently isolate and fractionate. We developed fluorescence nuclear cytometry (FNC) and fluorescence activated nuclear sorting (FANS) of cellular nuclei from visceral adipose tissue (VAT) using the levels of the pan-adipocyte protein, peroxisome proliferator-activated receptor gamma-2 (PPARg2), to distinguish classes of PPARg2-Positive (PPARg2-Pos) adipocyte nuclei from PPARg2-Negative (PPARg2-Neg) leukocyte and endothelial cell nuclei. PPARg2-Pos nuclei were 10-fold enriched for most adipocyte marker transcripts relative to PPARg2-Neg nuclei. PPARg2-Pos nuclei showed 2- to 50-fold higher levels of transcripts encoding most of the chromatin-remodeling factors assayed, which regulate the methylation of histones and DNA cytosine (e.g., DNMT1, TET1, TET2, KDM4A, KMT2C, SETDB1, PAXIP1, ARID1A, JMJD6, CARM1, and PRMT5). PPARg2-Pos nuclei were large with decondensed chromatin. TAB-seq demonstrated 5-hydroxymethylcytosine (5hmC) levels were remarkably dynamic in gene bodies of various classes of VAT nuclei, dropping 3.8-fold from the highest quintile of expressed genes to the lowest. In short, VAT-derived adipocytes appear to be more actively remodeling their chromatin than non-adipocytes.

Cell type-selective disease-association of genes under high regulatory load

We previously showed that disease-linked metabolic genes are often under combinatorial regulation. Using the genome-wide ChIP-Seq binding profiles for 93 transcription factors in nine different cell lines, we show that genes under high regulatory load are significantly enriched for disease-association across cell types. We find that transcription factor load correlates with the enhancer load of the genes and thereby allows the identification of genes under high regulatory load by epigenomic mapping of active enhancers. Identification of the high enhancer load genes across 139 samples from 96 different cell and tissue types reveals a consistent enrichment for disease-associated genes in a cell type-selective manner. The underlying genes are not limited to super-enhancer genes and show several types of disease-association evidence beyond genetic variation (such as biomarkers). Interestingly, the high regulatory load genes are involved in more KEGG pathways than expected by chance, exhibit increased betweenness centrality in the interaction network of liver disease genes, and carry longer 3' UTRs with more microRNA (miRNA) binding sites than genes on average, suggesting a role as hubs integrating signals within regulatory networks. In summary, epigenetic mapping of active enhancers presents a promising and unbiased approach for identification of novel disease genes in a cell type-selective manner.