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. 2023 Apr 24:2023:baad025.
doi: 10.1093/database/baad025.

RNA-Chrom: a manually curated analytical database of RNA-chromatin interactome

G K Ryabykh  1   2 , S V Kuznetsov  1 , Y D Korostelev  2 , A I Sigorskikh  1 , A A Zharikova  1   2   3 , A A Mironov  1   2
Affiliations

RNA-Chrom: a manually curated analytical database of RNA-chromatin interactome

G K Ryabykh et al. Database (Oxford). .

Erratum in

Abstract

Every year there is more and more evidence that non-coding RNAs play an important role in biological processes affecting various levels of organization of living systems: from the cellular (regulation of gene expression, remodeling and maintenance of chromatin structure, co-transcriptional suppression of transposons, splicing, post-transcriptional RNA modifications, etc.) to cell populations and even organismal ones (development, aging, cancer, cardiovascular and many other diseases). The development and creation of mutually complementary databases that will aggregate, unify and structure different types of data can help to reach the system level of studying non-coding RNAs. Here we present the RNA-Chrom manually curated analytical database, which contains the coordinates of billions of contacts of thousands of human and mouse RNAs with chromatin. Through the user-friendly web interface (https://rnachrom2.bioinf.fbb.msu.ru/), two approaches to the analysis of the RNA-chromatin interactome were implemented. Firstly, to find out whether the RNA of interest to a user contacts with chromatin, and if so, with which genes or DNA loci? Secondly, to find out which RNAs are in contact with the DNA locus of interest to a user (and probably participate in its regulation), and if there are such, what is the nature of their interaction? For a more detailed study of contact maps and their comparison with other data, the web interface allows a user to view them in the UCSC Genome Browser. Database URL https://genome.ucsc.edu/.

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Figures

Figure 1.
Figure 1.
XXX RNA interacts with the DNA locus and forms contact #1. In the case of one-to-all methods, we see only the DNA-parts of the contacts, while in the case of all-to-all methods, we see both DNA-parts and RNA-parts of the contacts. Cis- and trans-migration is the migration of RNA within and outside the parent chromosome, respectively.
Figure 2.
Figure 2.
RNA–chromatin interactions data processing protocol. Dotted arrows correspond to all-to-all data processing steps and solid arrows are related to one-to-all data.
Figure 3.
Figure 3.
The distribution of the number of reads in the data sets left after the corresponding processing step and all the previous ones. Upper panel: boxplots plotted from all-to-all data, namely 17 human data sets and 18 mouse data sets. Lower panel: boxplots plotted from one-to-all data, namely 159 human data sets and 291 mouse data sets.
Figure 4.
Figure 4.
RNA-Chrom functionality and downstream analysis.
Figure 5.
Figure 5.
‘From RNA’ analysis for X_17_3984_a_mm10 RNA (Mus musculus). The arrows reflect the workflow. A. A user chooses ‘from RNA’ analysis. B. Then the user either enters the RNA name of interest in the ‘Select RNA’ field or presses ‘BROWSE ALL RNAS’ button. C. ‘Complete table of RNAs’. Here a user selects RNA for analysis. D. The ‘Graphical Summary’ page consists of the ‘Contacts Summary’ and three analytical plots. By selecting one or more contact maps of X_17_3984_a_mm10 RNA in the ‘Contacts Summary’ table, a user continues to analyze them by clicking on one of the four buttons located to the right of the table. E. ‘All target genes’ page displays the association of contacts with genes and their upstream and downstream regions. By applying several filters, a user downloads a list of target genes. From this point, the user can switch to ‘from DNA’ analysis. To do this, the user clicks on the target gene of interest. F. Distribution of X_17_3984_a_mm10 RNA-parts across their source gene body (may reflect the exon–intron structure, the multiple isoforms of the transcribed gene, etc.) A user can send distributions for all experiments to the UCSC Genome Browser for a more detailed study or download them. G. A user sends X_17_3984_a_mm10 contact maps (DNA-parts) to the UCSC Genome Browser if they want to view them in the higher resolution or visually match them to genomic annotations (gene sets, epigenetic marks, etc.) or data (ChIP-seq, Hi-C, etc.)
Figure 6.
Figure 6.
‘From DNA’ analysis for HoxA cluster (chr6:52 015 389-52 270 886, M. musculus). The arrows reflect the workflow. A. A user chooses ‘from DNA’ analysis and B. clicks on the ‘CHOOSE A DNA LOCUS’ button, selects the organism, enters the approximate coordinates of the HoxA cluster and clicks on the ‘APPLY’ button. C. All RNAs that contact with the chosen locus are presented in the table. A user applies filters if necessary. To go to the ‘Graphical Summary’ page, the user clicks on the RNA name of interest (for example, Halr1). D. The ‘Graphic Summary’ page is divided into two blocks: ‘Contacts Summary’ and ‘Contacts Distribution’. Five buttons located to the right of the ‘Contacts Summary’ table represent five options for further work with the Halr1 contacts. E. To get more details about the locus, a user sends contact maps to the UCSC Genome Browser. F. ‘All target genes’ page displays the association of contacts with genes located at the selected locus and their upstream and downstream regions. The gene list can be filtered in different ways. From this point, a user continues the analysis in the ‘from DNA’ way. G. ‘Distribution of Halr1 RNA-parts across their source gene body’ bar chart is plotted both for all contacts and for contacts with the target locus. These distributions can be downloaded or sent to the UCSC Genome Browser for a more detailed study.
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