Biology subjects

Reuter, V. P.

Publications and source records attributed to Reuter, V. P..

4 recordsLinked to original sources

bioRxiv2025

Cohesin guides homology search during DNA repairvia loops and sister chromatid linkages

Accurate repair of DNA double-strand breaks (DSBs) is essential for genome stability, and defective repair underlies diseases such as cancer. Homologous recombination uses an intact homologous sequence to faithfully restore damaged DNA, yet how broken DNA ends find homologous sites in a genome containing billions of non-homologous bases remains unclear. Here, we introduce sister-pore-C, a high-resolution method for mapping intra- and trans-molecular interactions in replicated chromosomes. We show that DSBs reshape chromosome architecture by recruiting two functionally distinct pools of cohesin. Loop-forming cohesin accumulates across a megabase-scale domain to control homology sampling within topologically associating domains (TADs) surrounding the break site, while cohesive cohesin concentrates at the break site to tether broken ends to the sister chromatid. This dual mechanism restricts the homology search space, highlighting how chromosome conformation helps preserve genomic integrity.

cell biology↗

bioRxiv2020

PEPATAC: An optimized ATAC-seq pipeline with serial alignments

MotivationAs chromatin accessibility data from ATAC-seq experiments continues to expand, there is continuing need for standardized analysis pipelines. Here, we present PEPATAC, an ATAC-seq pipeline that is easily applied to ATAC-seq projects of any size, from one-off experiments to large-scale sequencing projects. ResultsPEPATAC leverages unique features of ATAC-seq data to optimize for speed and accuracy, and it provides several unique analytical approaches. Output includes convenient quality control plots, summary statistics, and a variety of generally useful data formats to set the groundwork for subsequent project-specific data analysis. Downstream analysis is simplified by a standard definition format, modularity of components, and metadata APIs in R and Python. It is restartable, fault-tolerant, and can be run on local hardware, using any cluster resource manager, or in provided Linux containers. We also demonstrate the advantage of aligning to the mitochondrial genome serially, which improves the accuracy of alignment statistics and quality control metrics. PEPATAC is a robust and portable first step for any ATAC-seq project. AvailabilityBSD2-licensed code and documentation at https://pepatac.databio.org.

genomics↗

bioRxiv2020

Linking big biomedical datasets to modular analysis with Portable Encapsulated Projects

Organizing and annotating biological sample data is critical in data-intensive bioinformatics. Unfortunately, metadata formats from a data provider are often incompatible with requirements of a processing tool. There is no broadly accepted standard to organize metadata across biological projects and bioinformatics tools, restricting the portability and reusability of both annotated datasets and analysis software. To address this, we present Portable Encapsulated Projects (PEP), a formal specification for biological sample metadata structure. The PEP specification accommodates typical features of data-intensive bioinformatics projects with many samples, whether from individual experiments, organisms, or single cells. In addition to standardization, the PEP specification provides descriptors and modifiers for different organizational layers of a project, which improve portability among computing environments and facilitate use of different processing tools. PEP includes a schema validator framework, allowing formal definition of required metadata attributes for any type of biomedical data analysis. We have implemented packages for reading PEPs in both Python and R to provide a language-agnostic interface for organizing project metadata. PEP therefore presents an important step toward unifying data annotation and processing tools in data-intensive biological research projects.

bioinformatics↗

bioRxiv2019

Refgenie: a reference genome resource manager

Reference genome assemblies are essential for high-throughput sequencing analysis projects. Typically, genome assemblies are stored on disk alongside related resources; for example, many sequence aligners require the assembly to be indexed. The resulting indexes are broadly applicable for downstream analysis, so it makes sense to share them. However, there is no simple tool to do this. To this end, we introduce refgenie, a reference genome assembly asset manager. Refgenie makes it easier to organize, retrieve, and share genome analysis resources. In addition to genome indexes, refgenie can manage any files related to reference genomes, including sequences and annotation files. Refgenie includes a command-line interface and a server application that provides a RESTful API, so it is useful for both tool development and analysis.\n\nAvailabilityhttps://refgenie.databio.org

bioinformatics↗