Integrative analysis of single-cell expression data reveals distinct regulatory states in bidirectional promoters.

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.

Author Correction: The landscape of genomic alterations across childhood cancers.

In this Article, author Benedikt Brors was erroneously associated with affiliation number '8' (Department of Developmental Neurobiology, St Jude Children's Research Hospital, Memphis, Tennessee, USA); the author's two other affiliations (affiliations '3' and '7', both at the German Cancer Research Center (DKFZ)) were correct. This has been corrected online.

The landscape of genomic alterations across childhood cancers.

Pan-cancer analyses that examine commonalities and differences among various cancer types have emerged as a powerful way to obtain novel insights into cancer biology. Here we present a comprehensive analysis of genetic alterations in a pan-cancer cohort including 961 tumours from children, adolescents, and young adults, comprising 24 distinct molecular types of cancer. Using a standardized workflow, we identified marked differences in terms of mutation frequency and significantly mutated genes in comparison to previously analysed adult cancers. Genetic alterations in 149 putative cancer driver genes separate the tumours into two classes: small mutation and structural/copy-number variant (correlating with germline variants). Structural variants, hyperdiploidy, and chromothripsis are linked to TP53 mutation status and mutational signatures. Our data suggest that 7-8% of the children in this cohort carry an unambiguous predisposing germline variant and that nearly 50% of paediatric neoplasms harbour a potentially druggable event, which is highly relevant for the design of future clinical trials.

OTP: An automatized system for managing and processing NGS data.

The One Touch Pipeline (OTP) is an automation platform managing Next-Generation Sequencing (NGS) data and calling bioinformatic pipelines for processing these data. OTP handles the complete digital process from import of raw sequence data via alignment of sequencing reads to identify genomic events in an automated and scalable way. Three major goals are pursued: firstly, reduction of human resources required for data management by introducing automated processes. Secondly, reduction of time until the sequences can be analyzed by bioinformatic experts, by executing all operations more reliably and quickly. Thirdly, storing all information in one system with secure web access and search capabilities. From software architecture perspective, OTP is both information center and workflow management system. As a workflow management system, OTP call several NGS pipelines that can easily be adapted and extended according to new requirements. As an information center, it comprises a database for metadata information as well as a structured file system. Based on complete and consistent information, data management and bioinformatic pipelines within OTP are executed automatically with all steps book-kept in a database.

Combining transcription factor binding affinities with open-chromatin data for accurate gene expression prediction.

The binding and contribution of transcription factors (TF) to cell specific gene expression is often deduced from open-chromatin measurements to avoid costly TF ChIP-seq assays. Thus, it is important to develop computational methods for accurate TF binding prediction in open-chromatin regions (OCRs). Here, we report a novel segmentation-based method, TEPIC, to predict TF binding by combining sets of OCRs with position weight matrices. TEPIC can be applied to various open-chromatin data, e.g. DNaseI-seq and NOMe-seq. Additionally, Histone-Marks (HMs) can be used to identify candidate TF binding sites. TEPIC computes TF affinities and uses open-chromatin/HM signal intensity as quantitative measures of TF binding strength. Using machine learning, we find low affinity binding sites to improve our ability to explain gene expression variability compared to the standard presence/absence classification of binding sites. Further, we show that both footprints and peaks capture essential TF binding events and lead to a good prediction performance. In our application, gene-based scores computed by TEPIC with one open-chromatin assay nearly reach the quality of several TF ChIP-seq data sets. Finally, these scores correctly predict known transcriptional regulators as illustrated by the application to novel DNaseI-seq and NOMe-seq data for primary human hepatocytes and CD4+ T-cells, respectively.

Epigenomic Profiling of Human CD4+ T Cells Supports a Linear Differentiation Model and Highlights Molecular Regulators of Memory Development.

The impact of epigenetics on the differentiation of memory T (Tmem) cells is poorly defined. We generated deep epigenomes comprising genome-wide profiles of DNA methylation, histone modifications, DNA accessibility, and coding and non-coding RNA expression in naive, central-, effector-, and terminally differentiated CD45RA+ CD4+ Tmem cells from blood and CD69+ Tmem cells from bone marrow (BM-Tmem). We observed a progressive and proliferation-associated global loss of DNA methylation in heterochromatic parts of the genome during Tmem cell differentiation. Furthermore, distinct gradually changing signatures in the epigenome and the transcriptome supported a linear model of memory development in circulating T cells, while tissue-resident BM-Tmem branched off with a unique epigenetic profile. Integrative analyses identified candidate master regulators of Tmem cell differentiation, including the transcription factor FOXP1. This study highlights the importance of epigenomic changes for Tmem cell biology and demonstrates the value of epigenetic data for the identification of lineage regulators.

Epigenetic dynamics of monocyte-to-macrophage differentiation.

BACKGROUND: Monocyte-to-macrophage differentiation involves major biochemical and structural changes. In order to elucidate the role of gene regulatory changes during this process, we used high-throughput sequencing to analyze the complete transcriptome and epigenome of human monocytes that were differentiated in vitro by addition of colony-stimulating factor 1 in serum-free medium. RESULTS: Numerous mRNAs and miRNAs were significantly up- or down-regulated. More than 100 discrete DNA regions, most often far away from transcription start sites, were rapidly demethylated by the ten eleven translocation enzymes, became nucleosome-free and gained histone marks indicative of active enhancers. These regions were unique for macrophages and associated with genes involved in the regulation of the actin cytoskeleton, phagocytosis and innate immune response. CONCLUSIONS: In summary, we have discovered a phagocytic gene network that is repressed by DNA methylation in monocytes and rapidly de-repressed after the onset of macrophage differentiation.

Enhancer hijacking activates GFI1 family oncogenes in medulloblastoma.

Medulloblastoma is a highly malignant paediatric brain tumour currently treated with a combination of surgery, radiation and chemotherapy, posing a considerable burden of toxicity to the developing child. Genomics has illuminated the extensive intertumoral heterogeneity of medulloblastoma, identifying four distinct molecular subgroups. Group 3 and group 4 subgroup medulloblastomas account for most paediatric cases; yet, oncogenic drivers for these subtypes remain largely unidentified. Here we describe a series of prevalent, highly disparate genomic structural variants, restricted to groups 3 and 4, resulting in specific and mutually exclusive activation of the growth factor independent 1 family proto-oncogenes, GFI1 and GFI1B. Somatic structural variants juxtapose GFI1 or GFI1B coding sequences proximal to active enhancer elements, including super-enhancers, instigating oncogenic activity. Our results, supported by evidence from mouse models, identify GFI1 and GFI1B as prominent medulloblastoma oncogenes and implicate 'enhancer hijacking' as an efficient mechanism driving oncogene activation in a childhood cancer.

Transcriptome assemblies for studying sex-biased gene expression in the guppy, Poecilia reticulata.

BACKGROUND: Sexually dimorphic phenotypes are generally associated with differential gene expression between the sexes. The study of molecular evolution and genomic location of these differentially expressed, or sex-biased, genes is important for understanding inter-sexual divergence under sex-specific selection pressures. Teleost fish provide a unique opportunity to examine this divergence in the presence of variable sex-determination mechanisms of recent origin. The guppy, Poecilia reticulata, displays sexual dimorphism in size, ornaments, and behavior, traits shaped by natural and sexual selection in the wild. RESULTS: To gain insight into molecular mechanisms underlying the guppy's sexual dimorphism, we assembled a reference transcriptome combining genome-independent as well as genome-guided assemblies and analyzed sex-biased gene expression between different tissues of adult male and female guppies. We found tissue-associated sex-biased expression of genes related to pigmentation, signal transduction, and spermatogenesis in males; and growth, cell-division, extra-cellular matrix organization, nutrient transport, and folliculogenesis in females. While most sex-biased genes were randomly distributed across linkage groups, we observed accumulation of ovary-biased genes on the sex linkage group, LG12. Both testis-biased and ovary-biased genes showed a significantly higher rate of non-synonymous to synonymous substitutions (dN/dS) compared to unbiased genes. However, in somatic tissues only female-biased genes, including those co-expressed in multiple tissues, showed elevated ratios of non-synonymous substitutions. CONCLUSIONS: Our work identifies a set of annotated gene products that are candidate factors affecting sexual dimorphism in guppies. The differential genomic distribution of gonad-biased genes provides evidence for sex-specific selection pressures acting on the nascent sex chromosomes of the guppy. The elevated rates of evolution of testis-biased and female-biased genes indicate differing evolution under distinct selection pressures on the reproductive versus non-reproductive tissues.