Automatic identification of informative regions with epigenomic changes associated to hematopoiesis

Esearch3D: propagating gene expression in chromatin networks to illuminate active enhancers

Most cell type-specific genes are regulated by the interaction of enhancers with their promoters. The identification of enhancers is not trivial as enhancers are diverse in their characteristics and dynamic in their interaction partners. We present Esearch3D, a new method that exploits network theory approaches to identify active enhancers. Our work is based on the fact that enhancers act as a source of regulatory information to increase the rate of transcription of their target genes and that the flow of this information is mediated by the folding of chromatin in the three-dimensional (3D) nuclear space between the enhancer and the target gene promoter. Esearch3D reverse engineers this flow of information to calculate the likelihood of enhancer activity in intergenic regions by propagating the transcription levels of genes across 3D genome networks. Regions predicted to have high enhancer activity are shown to be enriched in annotations indicative of enhancer activity. These include: enhancer-associated histone marks, bidirectional CAGE-seq, STARR-seq, P300, RNA polymerase II and expression quantitative trait loci (eQTLs). Esearch3D leverages the relationship between chromatin architecture and transcription, allowing the prediction of active enhancers and an understanding of the complex underpinnings of regulatory networks. The method is available at: https://github.com/InfOmics/Esearch3D and https://doi.org/10.5281/zenodo.7737123.

Computational methods to explore chromatin state dynamics

The human genome is marked by several singular and combinatorial histone modifications that shape the different states of chromatin and its three-dimensional organization. Genome-wide mapping of these marks as well as histone variants and open chromatin regions is commonly carried out via profiling DNA-protein binding or via chromatin accessibility methods. After the generation of epigenomic datasets in a cell type, statistical models can be used to annotate the noncoding regions of DNA and infer the combinatorial histone marks or chromatin states (CS). These methods involve partitioning the genome and labeling individual segments based on their CS patterns. Chromatin labels enable the systematic discovery of genomic function and activity and can label the gene body, promoters or enhancers without using other genomic maps. CSs are dynamic and change under different cell conditions, such as in normal, preneoplastic or tumor cells. This review aims to explore the available computational tools that have been developed to capture CS alterations under two or more cellular conditions.

Fast detection of differential chromatin domains with SCIDDO

MOTIVATION

The generation of genome-wide maps of histone modifications using chromatin immunoprecipitation sequencing is a standard approach to dissect the complexity of the epigenome. Interpretation and differential analysis of histone datasets remains challenging due to regulatory meaningful co-occurrences of histone marks and their difference in genomic spread. To ease interpretation, chromatin state segmentation maps are a commonly employed abstraction combining individual histone marks. We developed the tool SCIDDO as a fast, flexible and statistically sound method for the differential analysis of chromatin state segmentation maps.

RESULTS

We demonstrate the utility of SCIDDO in a comparative analysis that identifies differential chromatin domains (DCD) in various regulatory contexts and with only moderate computational resources. We show that the identified DCDs correlate well with observed changes in gene expression and can recover a substantial number of differentially expressed genes (DEGs). We showcase SCIDDO's ability to directly interrogate chromatin dynamics, such as enhancer switches in downstream analysis, which simplifies exploring specific questions about regulatory changes in chromatin. By comparing SCIDDO to competing methods, we provide evidence that SCIDDO's performance in identifying DEGs via differential chromatin marking is more stable across a range of cell-type comparisons and parameter cut-offs.

AVAILABILITY AND IMPLEMENTATION

The SCIDDO source code is openly available under github.com/ptrebert/sciddo.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Genome-wide enhancer maps link risk variants to disease genes

Genome-wide association studies (GWAS) have identified thousands of noncoding loci that are associated with human diseases and complex traits, each of which could reveal insights into the mechanisms of disease¹. Many of the underlying causal variants may affect enhancers^2,3, but we lack accurate maps of enhancers and their target genes to interpret such variants. We recently developed the activity-by-contact (ABC) model to predict which enhancers regulate which genes and validated the model using CRISPR perturbations in several cell types⁴. Here we apply this ABC model to create enhancer-gene maps in 131 human cell types and tissues, and use these maps to interpret the functions of GWAS variants. Across 72 diseases and complex traits, ABC links 5,036 GWAS signals to 2,249 unique genes, including a class of 577 genes that appear to influence multiple phenotypes through variants in enhancers that act in different cell types. In inflammatory bowel disease (IBD), causal variants are enriched in predicted enhancers by more than 20-fold in particular cell types such as dendritic cells, and ABC achieves higher precision than other regulatory methods at connecting noncoding variants to target genes. These variant-to-function maps reveal an enhancer that contains an IBD risk variant and that regulates the expression of PPIF to alter the membrane potential of mitochondria in macrophages. Our study reveals principles of genome regulation, identifies genes that affect IBD and provides a resource and generalizable strategy to connect risk variants of common diseases to their molecular and cellular functions.

Blueprint of human thymopoiesis reveals molecular mechanisms of stage-specific TCR enhancer activation

Cell differentiation is accompanied by epigenetic changes leading to precise lineage definition and cell identity. Here we present a comprehensive resource of epigenomic data of human T cell precursors along with an integrative analysis of other hematopoietic populations. Although T cell commitment is accompanied by large scale epigenetic changes, we observed that the majority of distal regulatory elements are constitutively unmethylated throughout T cell differentiation, irrespective of their activation status. Among these, the TCRA gene enhancer (Eα) is in an open and unmethylated chromatin structure well before activation. Integrative analyses revealed that the HOXA5-9 transcription factors repress the Eα enhancer at early stages of T cell differentiation, while their decommission is required for TCRA locus activation and enforced αβ T lineage differentiation. Remarkably, the HOXA-mediated repression of Eα is paralleled by the ectopic expression of homeodomain-related oncogenes in T cell acute lymphoblastic leukemia. These results highlight an analogous enhancer repression mechanism at play in normal and cancer conditions, but imposing distinct developmental constraints.

Methods for ChIP-seq analysis: A practical workflow and advanced applications

Chromatin immunoprecipitation followed by sequencing (ChIP-seq) is a central method in epigenomic research. Genome-wide analysis of histone modifications, such as enhancer analysis and genome-wide chromatin state annotation, enables systematic analysis of how the epigenomic landscape contributes to cell identity, development, lineage specification, and disease. In this review, we first present a typical ChIP-seq analysis workflow, from quality assessment to chromatin-state annotation. We focus on practical, rather than theoretical, approaches for biological studies. Next, we outline various advanced ChIP-seq applications and introduce several state-of-the-art methods, including prediction of gene expression level and chromatin loops from epigenome data and data imputation. Finally, we discuss recently developed single-cell ChIP-seq analysis methodologies that elucidate the cellular diversity within complex tissues and cancers.

Mutational mechanisms shaping the coding and noncoding genome of germinal center derived B-cell lymphomas

B cells have the unique property to somatically alter their immunoglobulin (IG) genes by V(D)J recombination, somatic hypermutation (SHM) and class-switch recombination (CSR). Aberrant targeting of these mechanisms is implicated in lymphomagenesis, but the mutational processes are poorly understood. By performing whole genome and transcriptome sequencing of 181 germinal center derived B-cell lymphomas (gcBCL) we identified distinct mutational signatures linked to SHM and CSR. We show that not only SHM, but presumably also CSR causes off-target mutations in non-IG genes. Kataegis clusters with high mutational density mainly affected early replicating regions and were enriched for SHM- and CSR-mediated off-target mutations. Moreover, they often co-occurred in loci physically interacting in the nucleus, suggesting that mutation hotspots promote increased mutation targeting of spatially co-localized loci (termed hypermutation by proxy). Only around 1% of somatic small variants were in protein coding sequences, but in about half of the driver genes, a contribution of B-cell specific mutational processes to their mutations was found. The B-cell-specific mutational processes contribute to both lymphoma initiation and intratumoral heterogeneity. Overall, we demonstrate that mutational processes involved in the development of gcBCL are more complex than previously appreciated, and that B cell-specific mutational processes contribute via diverse mechanisms to lymphomagenesis.

Inferring changes in histone modification during cell differentiation by ancestral state estimation based on phylogenetic trees of cell types: Human hematopoiesis as a model case

Revealing the landscape of epigenetic changes in cells during differentiation is important for understanding the development of organisms. In this study, to infer such epigenetic changes during human hematopoiesis, ancestral state estimation based on a phylogenetic tree was applied to map the epigenomic changes in six kinds of histone modifications onto the hierarchical cell differentiation process of hematopoiesis using epigenomes of eight types of differentiated hematopoietic cells. The histone modification changes inferred during hematopoiesis showed that changes that occurred on the branches separating different cell types reflected the characteristics of hematopoiesis in terms of genomic position and gene function. These results suggested that ancestral state estimation based on phylogenetic analysis of histone modifications in differentiated hematopoietic cells could reconstruct an appropriate landscape of histone modification changes during hematopoiesis. Since integration of the inferred changes of different histone modifications could reveal genes with specific histone marks such as active histone marks and bivalent histone marks on each internal branch of cell-type trees, this approach could provide valuable information for understanding the cell differentiation steps of each cell lineage.

Using GARDEN-NET and ChAseR to explore human haematopoietic 3D chromatin interaction networks

We introduce an R package and a web-based visualization tool for the representation, analysis and integration of epigenomic data in the context of 3D chromatin interaction networks. GARDEN-NET allows for the projection of user-submitted genomic features on pre-loaded chromatin interaction networks, exploiting the functionalities of the ChAseR package to explore the features in combination with chromatin network topology properties. We demonstrate the approach using published epigenomic and chromatin structure datasets in haematopoietic cells, including a collection of gene expression, DNA methylation and histone modifications data in primary healthy myeloid cells from hundreds of individuals. These datasets allow us to test the robustness of chromatin assortativity, which highlights which epigenomic features, alone or in combination, are more strongly associated with 3D genome architecture. We find evidence for genomic regions with specific histone modifications, DNA methylation, and gene expression levels to be forming preferential contacts in 3D nuclear space, to a different extent depending on the cell type and lineage. Finally, we examine replication timing data and find it to be the genomic feature most strongly associated with overall 3D chromatin organization at multiple scales, consistent with previous results from the literature.

Epigenetic Priming in Childhood Acute Lymphoblastic Leukemia

Leukemogenesis is considered to be a process by which a normal cell acquires new but aberrant identity in order to disseminate a malignant clonal population. Under this setting, the phenotype of the leukemic cells is identical to the leukemia-initiating cell in which the genetic insult is taking place. Thus, with some exceptions, B-cell and T-cell childhood leukemias are supposed to arise from B- or T-committed cells. In contrast, several recent studies have revealed that genetic alterations may act in a “hit-and-run” way in the cell-of-origin by imposing the tumor cell identity giving rise to either B-cell or T-cell leukemias. This novel mechanism of cell transformation is mediated by an epigenetic priming mechanism that is established by the initial genetic lesion. This initial hit might be unnecessary for the subsequent tumor evolution and conservation, being the epigenetic priming the engine for the tumor evolution.

Automatic detection of genomic regions with informative epigenetic patterns

BACKGROUND

Epigenetic phenomena are crucial for explaining the phenotypic plasticity seen in the cells of different tissues, developmental stages and diseases, all holding the same DNA sequence. As technology is allowing to retrieve epigenetic information in a genome-wide fashion, massive epigenomic datasets are being accumulated in public repositories. New approaches are required to mine those data to extract useful knowledge. We present here an automatic approach for detecting genomic regions with epigenetic variation patterns across samples related to a grouping of these samples, as a way of detecting regions functionally associated to the phenomenon behind the classification.

RESULTS

We show that the regions automatically detected by the method in the whole human genome associated to three different classifications of a set of epigenomes (cancer vs. healthy, brain vs. other organs, and fetal vs. adult tissues) are enriched in genes associated to these processes.

CONCLUSIONS

The method is fully automatic and can exhaustively scan the whole human genome at any resolution using large collections of epigenomes as input, although it also produces good results with small datasets. Consequently, it will be valuable for obtaining functional information from the incoming epigenomic information as it continues to accumulate.

Dynamics of Transcription Regulation in Human Bone Marrow Myeloid Differentiation to Mature Blood Neutrophils

Neutrophils are short-lived blood cells that play a critical role in host defense against infections. To better comprehend neutrophil functions and their regulation, we provide a complete epigenetic overview, assessing important functional features of their differentiation stages from bone marrow-residing progenitors to mature circulating cells. Integration of chromatin modifications, methylation, and transcriptome dynamics reveals an enforced regulation of differentiation, for cellular functions such as release of proteases, respiratory burst, cell cycle regulation, and apoptosis. We observe an early establishment of the cytotoxic capability, while the signaling components that activate these antimicrobial mechanisms are transcribed at later stages, outside the bone marrow, thus preventing toxic effects in the bone marrow niche. Altogether, these data reveal how the developmental dynamics of the chromatin landscape orchestrate the daily production of a large number of neutrophils required for innate host defense and provide a comprehensive overview of differentiating human neutrophils.