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Topalis, P.

Publications and source records attributed to Topalis, P..

3 recordsLinked to original sources

The Splicing Factor XAB2 interacts with ERCC1-XPF and XPG for RNA-loop processing during mammalian development

RNA splicing, transcription and the DNA damage response are intriguingly linked in mammals but the underlying mechanisms remain poorly understood. Using an in vivo biotinylation tagging approach in mice, we show that the splicing factor XAB2 interacts with the core spliceosome and that it binds to spliceosomal U4 and U6 snRNAs and pre-mRNAs in developing livers. XAB2 depletion leads to aberrant intron retention, R-loop formation and DNA damage in cells. Studies in illudin S-treated cells and Csbm/m developing livers reveal that transcription-blocking DNA lesions trigger the release of XAB2 from all RNA targets tested. Immunoprecipitation studies reveal that XAB2 interacts with ERCC1-XPF and XPG endonucleases outside nucleotide excision repair and that the trimeric protein complex binds RNA:DNA hybrids under conditions that favor the formation of R-loops. Thus, XAB2 functionally links the spliceosomal response to DNA damage with R-loop processing with important ramifications for mammalian development and transcription-coupled DNA repair disorders.

genetics↗

ERCC1-XPF Interacts with Topoisomerase IIβ to Facilitate the Repair of Activity-induced DNA Breaks

Type II DNA Topoisomerases (TOP II) generate transient double-strand DNA breaks (DSBs) to resolve topological constraints during transcription. Using genome-wide mapping of DSBs and functional genomics approaches, we show that, in the absence of exogenous genotoxic stress, transcription leads to DSB accumulation and to the recruitment of the structure-specific ERCC1-XPF endonuclease on active gene promoters. Instead, we find that the complex is released from regulatory or gene body elements in UV-irradiated cells. Abrogation of ERCC1 or re-ligation blockage of TOP II-mediated DSBs aggravates the accumulation of transcription-associated {gamma}H2Ax and 53BP1 foci, which dissolve when TOP II-mediated DNA cleavage is inhibited. An in vivo biotinylation tagging strategy coupled to a high-throughput proteomics approach reveals that ERCC1-XPF interacts with TOP II{beta} and the CTCF/cohesin complex, which co-localize with the heterodimer on DSBs. Together; our findings provide a rational explanation for the remarkable clinical heterogeneity seen in human disorders with ERCC1-XPF defects.

genetics↗

PEMA: from the raw .fastq files of 16S rRNA and COI marker genes to the (M)OTU-table, a thorough metabarcoding analysis

BackgroundEnvironmental DNA (eDNA) and metabarcoding, allow the identification of a mixture of individuals and launch a new era in bio- and eco-assessment. A number of steps are required to obtain taxonomically assigned (Molecular) Operational Taxonomic Unit ((M)OTU) tables from raw data. For most of these, a plethora of tools is available; each tools execution parameters need to be tailored to reflect each experiments idiosyncrasy. Adding to this complexity, for such analyses, the computation capacity of High Performance Computing (HPC) systems is frequently required.\n\nSoftware containerization technologies ease the sharing and running of software packages across operating systems; thus, they strongly facilitate pipeline development and usage. Likewise are programming languages specialized for big data pipelines, incorporating features like roll-back checkpoints and on-demand partial pipeline execution.\n\nFindingsPEMA is a containerized assembly of key metabarcoding analysis tools with a low effort in setting up, running and customizing to researchers needs. Based on third party tools, PEMA performs reads pre-processing, clustering to (M)OTUs and taxonomy assignment for 16S rRNA and COI marker gene data. Due to its simplified parameterisation and checkpoint support, PEMA allows users to explore alternative algorithms for specific steps of the pipeline without the need of a complete re-execution. PEMA was evaluated against previously published datasets and achieved comparable quality results.\n\nConclusionsGiven its time-efficient performance and its quality results, it is suggested that PEMA can be used for accurate eDNA metabarcoding analysis, thus enhancing the applicability of next-generation biodiversity assessment studies.

bioinformatics↗