No abstract

Abstract Non-coding RNAs (ncRNAs) participate in various biological processes, including regulating transcription and sustaining genome 3D organization. Here, we present a method termed Red-C that exploits proximity ligation to identify contacts with the genome for all RNA molecules present in the nucleus. Using Red-C, we uncovered the RNA–DNA interactome of human K562 cells and identified hundreds of ncRNAs enriched in active or repressed chromatin, including previously undescribed RNAs. Analysis of the RNA–DNA interactome also allowed us to trace the kinetics of messenger RNA production. Our data support the model of co-transcriptional intron splicing, but not the hypothesis of the circularization of actively transcribed genes.

An important antibiotic target, DNA gyrase is an essential bacterial enzyme that introduces negative supercoils into DNA and relaxes positive supercoils accumulating in front of moving DNA and RNA polymerases. By altering the superhelical density, gyrase may regulate expression of bacterial genes. The information about how gyrase is distributed along genomic DNA and whether its distribution is affected by drugs is scarce. During catalysis, gyrase cleaves both DNA strands forming a covalently bound intermediate. By exploiting the ability of several topoisomerase poisons to stabilize this intermediate we developed a ChIP-Seq-based approach to locate, with single nucleotide resolution, DNA gyrase cleavage sites (GCSs) throughout the Escherichia coli genome. We identified an extended gyrase binding motif with phased 10-bp G/C content variation, indicating that bending ability of DNA contributes to gyrase binding. We also found that GCSs are enriched in extended regions located downstream of highly transcribed operons. Transcription inhibition leads to redistribution of gyrase suggesting that the enrichment is functionally significant. Our method can be applied for precise mapping of prokaryotic and eukaryotic type II topoisomerases cleavage sites in a variety of organisms and paves the way for future studies of various topoisomerase inhibitors.

Target binding by CRISPR-Cas ribonucleoprotein effectors is initiated by the recognition of double-stranded PAM motifs by the Cas protein moiety followed by destabilization, localized melting, and interrogation of the target by the guide part of CRISPR RNA moiety. The latter process depends on seed sequences, parts of the target that must be strictly complementary to CRISPR RNA guide. Mismatches between the target and CRISPR RNA guide outside the seed have minor effects on target binding, thus contributing to off-target activity of CRISPR-Cas effectors. Here, we define the seed sequence of the Type V Cas12b effector from Bacillus thermoamylovorans. While the Cas12b seed is just five bases long, in contrast to all other effectors characterized to date, the nucleotide base at the site of target cleavage makes a very strong contribution to target binding. The generality of this additional requirement was confirmed during analysis of target recognition by Cas12b effector from Alicyclobacillus acidoterrestris. Thus, while the short seed may contribute to Cas12b promiscuity, the additional specificity determinant at the site of cleavage may have a compensatory effect making Cas12b suitable for specialized genome editing applications.

Functional genomics employs several experimental techniques to investigate gene functions. These techniques such as loss-of-function screening and transcriptome profiling performed in a high-throughput manner give as result a list of genes involved in the biological process of interest. There exist several computational methods for analysis and interpretation of the list. The most widespread methods aim at investigation of biological processes significantly represented in the list or at extracting significantly represented subnetworks. Here we present a new exploratory network analysis method that employs the shortest path approach and centrality measure to uncover members of active molecular pathways leading to the studied phenotype based on the results of functional genomics screening data. We present the method and we demonstrate what data can be retrieved by its application to the terminal muscle differentiation miRNA loss-of-function screening and transcriptomic profiling data and to the 'druggable' loss-of-function RNAi screening data of the DNA repair process.All rights reserved. No reuse allowed without permission.(which was not peer-reviewed) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity.

Many notions and concepts for network analysis, including the shortest path approach, came to systems biology from the theory of graphs — the field of mathematics that studies graphs. We studied the relationship between the shortest paths and a biologically meaningful molecular path between vertices in human molecular interaction networks. We analyzed the sets of the shortest paths in the human interactome derived from HPRD and HIPPIE databases between all possible combinations of start and end proteins in eight signaling pathways in the KEGG database — NF-kappa B, MAPK, Jak-STAT, mTOR, ErbB, Wnt, TGF-beta, and the signaling part of the apoptotic process. We investigated whether the shortest paths match the canonical paths. We studied whether centrality of vertices and paths in the subnetworks induced by the shortest paths can highlight vertices and paths that are part of meaningful molecular paths. We found that the shortest paths match canonical counterparts only for canonical paths of length 2 or 3 interactions. The shortest paths match longer canonical counterparts with shortcuts or substitutions by protein complex members. We found that high centrality vertices are part of the canonical paths for up to 80% of the canonical paths depending on the database and the length.

A network is one of the most convenient way to represent interactions between biological entities in systems biology. A network of molecular interactions is a graph in which the vertices are biological component and the edges correspond to the interactions between them. Many notions and approaches for network analysis came to systems biology from the theory of graphs -a field of mathematics that study graphs. We focused on the study of the shortest path approach in this work. We investigated whether this approach yields valid molecular paths. To perform this, the shortest paths in the human interactome (derived from HPRD and HIPPIE databases) were found between all relevant combinations of proteins taken from eight well-studied highly conserved signaling pathways from the KEGG database (NF-kappa B, MAPK, Jak-STAT, mTOR, ErbB, Wnt, TGF-beta and the signaling part of the apoptotic process). Canonical paths were systematically compared with the shortest counterparts and centrality of vertices and paths in subnetworks induced by the shortest paths were analyzed. We found that the sets of the shortest paths contain the canonical counterparts only for very short canonical paths (length 2-3 interactions). We also found that high centrality vertices tend to belong to canonical counterparts, to less extent this can also be said about high centrality paths.