Biology subjects

Zywicki, M.

Publications and source records attributed to Zywicki, M..

4 recordsLinked to original sources

bioRxiv2024

Transcriptome-wide analysis of circRNA and RBP profiles and their molecular and clinical relevance for GBM

Glioblastoma (GBM) is the most aggressive and lethal type of glioma, characterized by aberrant expression of non-coding RNAs including circular RNAs (circRNAs). They might impact cellular processes by interacting with other molecules - like microRNAs or RNA-binding proteins (RBPs). The diagnostic value of circRNAs and circRNAs/RBPs complexes is still largely unknown. To explore circRNAs and RBPs transcripts expression in GBM, we performed and further analyzed RNA-seq data from GBM patients primary and recurrent tumor samples. We identified circRNAs differentially expressed in primary tumors, the circRNA progression markers in recurrent GBM samples as well as the expression profile of RBP transcripts. Subsequent analysis allowed us to generate a comprehensive catalog of circRNA-RBP interactions regarding both the RBPs sequestration by circRNA as well as the RBPs involvement in circRNA biogenesis. Furthermore, we demonstrated the clinical potential of circRNAs and RBPs in GBM and proposed them as the stratification markers in the de novo assembled tumor subtypes. Therefore, our transcriptome-wide study specified circRNA-RBP interactions that could play a significant regulatory role in gliomagenesis and GBM progression.

cancer biology↗

bioRxiv2024

Characterization of bacterial intrinsic transcription terminators identified with TERMITe - a novel method for comprehensive analysis of Term-seq data

In recent years, Term-seq became a standard experimental approach for high-throughput identification of 3 ends of bacterial transcripts. It was widely adopted to study transcription termination events and 3 maturation of bacterial RNAs. Despite widespread utilization, a universal bioinformatics toolkit for comprehensive analysis of Term-seq sequencing data is still lacking. Here, we describe TERMITe, a novel method for the identification of stable 3 RNA ends based on bacterial Term-seq data. TERMITe works with data obtained from both currently available Term-seq protocols and provides robust identification of the 3 RNA termini. Unique features of TERMITe include the calculation of the transcription termination efficiency using matched RNA-seq data and the comprehensive annotation of the identified 3 RNA ends, allowing functional analysis of the results. We have applied TERMITe to the comparative analysis of experimentally validated intrinsic terminators spanning different species across the bacterial domain of life, revealing substantial differences in their sequence and secondary structure. We also provide a complete atlas of experimentally validated intrinsic transcription termination sites for 13 bacterial species, including Escherichia coli, Bacillus subtilis, Listeria monocytogenes, Enterococcus faecalis, Synechocystis sp., Streptomyces clavuligerus, Streptomyces griseus, Streptomyces coelicolor, Streptomyces avermitilis, Streptomyces lividans, Streptomyces tsukubaensis, Streptomyces venezuelae, and Zymomonas mobilis.

bioinformatics↗

bioRxiv2022

AGouTI - flexible Annotation of Genomic and Transcriptomic Intervals

SummaryThe recent development of high-throughput workflows in genomics and transcriptomics revealed that efficient annotation is essential for effective data processing and analysis. Although a variety of tools dedicated to this purpose is available, their functionality is limited. Here, we present AGouTI - a universal tool for flexible annotation of any genomic or transcriptomic coordinates using known genomic features deposited in different publicly available databases in the form of GTF or GFF files. In contrast to currently available tools, AGouTI is designed to provide a flexible selection of genomic features overlapping or adjacent to annotated intervals, can be used on custom column-based text files obtained from different data analysis pipelines, and supports operations on transcriptomic coordinate systems. Availability and ImplementationAGouTI was implemented using Python 3 and is freely available on GitHub (https://github.com/zywicki-lab/agouti), from the Python Package Index (https://pypi.org/project/AGouTI/) or Anaconda Cloud (https://anaconda.org/bioconda/agouti). We also provide a Galaxy wrapper available from the Galaxy Tool Shed (https://toolshed.g2.bx.psu.edu/view/janktoolshed/agouti/c204da8f836d). Supplementary informationSupplementary Data are available at Publisher site online. Files for replicating the use-case scenario described in Supplementary Data are available at Zenodo: https://doi.org/10.5281/zenodo.7317210. ContactMarek.Zywicki@amu.edu.pl

bioinformatics↗

bioRxiv2018

FUS controls the processing of snoRNAs into smaller RNA fragments that can regulate gene expression

FUS is a multifunctional protein involved in many steps of RNA metabolism, including transcription, splicing, miRNA processing and replication-dependent histone gene expression. In this paper, we show for the first time that FUS binds and negatively regulates the levels of a subset of snoRNAs in cells. Scanning of available human small RNA databases revealed the existence of smaller RNA fragments that can be processed from FUS-dependent snoRNAs. Therefore, we suggest that FUS mediates the biogenesis of snoRNA-derived small RNAs, called sdRNAs. Further in silico approaches enabled us to predict putative targets of selected FUS-dependent sdRNAs. Our results indicate that sdRNAs may bind to different regions of target mRNAs as well as to noncoding transcripts and influence the posttranscriptional level or translation of these targets. SIGNIFICANCE STATEMENTRNA metabolism is orchestrated by a complex network of RNA-protein interactions and involves various classes of RNA molecules. Small nucleolar RNAs (snoRNAs) are commonly considered essential components of the ribosome biogenesis pathway. However, recent studies have revealed that snoRNAs can also be fragmented into small entities called snoRNA-derived RNAs (sdRNAs), which have been linked to multiple cancer types and thus may serve as next-generation prognostic or diagnostic biomarkers. In this paper, a multifunctional protein, FUS, was shown to be involved in the biogenesis of snoRNA-derived fragments. Furthermore, we combined bioinformatic analyses with complementary experimental approaches to elucidate the role of FUS-dependent sdRNAs in gene expression regulation. Our findings reveal the considerable regulatory potential of this new class of small noncoding RNAs.

molecular biology↗