EXPRESSO: a multi-omics database to explore multi-layered 3D genomic organization

Abstract

The three-dimensional (3D) organization of the human genome plays a crucial role in gene regulation. EXPloration of Regulatory Epigenome with Spatial and Sequence Observations (EXPRESSO) is a novel multi-omics database for exploration and visualization of multi-layered 3D genomic features across 46 different human tissues. Integrating 1360 3D genomic datasets (Hi-C, HiChIP, ChIA-PET) and 842 1D genomic and transcriptomic datasets (ChIP-seq, ATAC-seq, RNA-seq) from the same biosample, EXPRESSO provides a comprehensive resource for studying the interplay between 3D genome architecture and transcription regulation. This database offers diverse 3D genomic feature types (compartments, contact matrix, contact domains, stripes as diagonal lines extending from a genomic locus in contact matrix, chromatin loops, etc.) and user-friendly interface for both data exploration and download. Other key features include REpresentational State Transfer application programming interfaces for programmatic access, advanced visualization tools for 3D genomic features and web-based applications that correlate 3D genomic features with gene expression and epigenomic modifications. By providing extensive datasets and tools, EXPRESSO aims to deepen our understanding of 3D genomic architecture and its implications for human health and disease, serving as a vital resource for the research community. EXPRESSO is freely available at https://expresso.sustech.edu.cn.

Graphical Abstract

Figure 1.

Overview of the functionalities in EXPRESSO database EXPRESSO integrates multiple types of 3D genomic datasets and 1D genomic datasets across various human tissues. The database provides a user-friendly interface for data exploration and visualization, as well as REST APIs for programmatic access.

Figure 2.

Biosample search features in EXPRESSO. (A) Bar plot displaying the count of 3D genomic datasets across various tissues. (B) An interactive summary table for filtering biosamples under various criteria.

Figure 3.

Individual biosample page overview, (A) Navigation bar of the EXPRESSO browser. (B) Configuration panel of the gene annotation track. (C and D). Example of compartment switch between healthy prostate cells (C) and PCa cell (D). The gene Wnt5a is highlighted. (E and F) Example of neo contact domain formation in DCM heart (F) compared with healthy heart (E). The neo domain that wrapped NPPA and NPPB gene is highlighted. (G and H) Example of multi-level 3D genome organization of AFP gene. Panel G displayed compartment and contact domain in Hi-C data. Panel H displayed chromatin interactions and 1D coverage using RNAPII ChIA-PET data.

Figure 4.

Gene search functionality. (A) Bar plot demonstrating the compartment E1 score of NEAT1 across Hi-C samples, where E1>0 represents A compartment and E1<0 represents B compartment.. (B) Proportion of samples where NEAT1 is in the A or B compartment. (C) Corresponding sample metadata, indicating the number of samples by tissue where NEAT1 is in the A or B compartment, as well as the number of samples by health status where NEAT1 is in the A or B compartment.

Figure 5.

Visualization of CCAT1-MYC associated stripes. Screenshot of a stripe associated with CCAT1 and MYC gene in cervical cancer cells.

Figure 6.

Exploration of transcription factor-mediated chromatin loops, (A) Bar plot of the top 20 TFs ranked by the prevalence of their enrichment across biosamples. (B) Detailed view of the top ten samples in IKZF1 enrichment table, featuring the IKZF1 motif logo and relevant statistics for each biosample. Meaning of the table columns: P-value, Probability of observing the motif by chance. logP, Logarithm of the P-value. Target Ratio, Proportion of target sequences containing the motif. Background Ratio: Proportion of background sequences containing the motif. bgSTD, Variability of motif occurrence in the background sequences.