Biology subjects

Dojer, N.

Publications and source records attributed to Dojer, N..

4 recordsLinked to original sources

bioRxiv2026

Homology-based perspective on pangenome graphs

Pangenome graphs conveniently represent genetic variation within a population. Several types of such graphs have been proposed, with varying properties and potential applications. Among them, variation graphs (VGs) seem best suited to replace reference genomes in sequencing data processing, while whole genome alignments (WGAs) are particularly practical for comparative genomics applications. For both models, no widely accepted optimization criteria for a graph representing a given set of genomes have been proposed. In the current paper we introduce the concept of homology relation induced by a pangenome graph on the characters of represented genomic sequences and define such relations for both VG and WGA model. Then, we use this concept to propose homology-based metrics for comparing different graphs representing the same genome collection, and to formulate the desired properties of transformations between VG and WGA models. Moreover, we propose several such transformations and examine their properties on pangenome graph data. Finally, we provide implementations of these transformations in a package WGAtools, available at https://github.com/anialisiecka/WGAtools.

bioinformatics↗

bioRxiv2020

Analyzing and interpreting DNA double-strand break sequencing data

DNA double-strand breaks (DSBs), are a major threat to genomic stability and may lead to cancer. Several technologies to accurately detect DSBs genome-wide have been developed recently, but still lacking publicly available tools for analysis of the resulting data. Here, we present a step-by-step iSeq package (http://breakome.utmb.edu/software.html), custom designed for analysis and interpretation of DSB-sequencing data. iSeq performs barcode trimming and read counting, and identifies DSB-enriched regions by statistical test and annotate them to the desired genomic features. Applying this package, users can identify and annotate DSB-enriched regions from base pair (eg. Cas9 cleavage sites) up to megabase (eg. DNA replication stress-induced) resolution, and if possible quantify DSB frequencies per cell genome-wide by combining with qDSB-Seq. iSeq can be used for any sequencing-based DSB detection techniques. The analysis for Steps 1-19 can be performed within ~4 hours.

bioinformatics↗

bioRxiv2017

Integrated analysis of DSB patterns reveals precisely DSB formation mechanisms following replication fork collapse

DNA double-strand breaks (DSBs) can be detected by label-based sequencing or pulsed-field gel electrophoresis (PFGE). Sequencing yields population-average DSB frequencies genome-wide, while PFGE reveals percentages of broken chromosomes. We constructed a mathematical framework to combine advantages of both: high-resolution DSB locations and their population distribution. We also use sequencing read patterns to identify replication-induced DSBs and active replication origins. We describe changes in spatiotemporal replication program upon hydroxyurea-induced replication stress. We found that one-ended DSBs, resulting from collapsed replication forks, are population-representative, while majority of two-ended DSBs (79-100%) are not. To study replication fork collapse, we used strains lacking the checkpoint protein Mec1 and the endonuclease Mus81 and quantified that 19% and 13% of hydroxyurea-induced one-ended DSBs are Mec1-and Mus81-dependent, respectively. We also clarified that Mus81-induced one-ended DSBs are Mec1-dependent.

genomics↗

bioRxiv2017

Quantitative DSB sequencing (qDSB-Seq): a method for genome-wide accurate estimation of absolute DNA double-strand break frequencies per cell

Sequencing-based methods for mapping DNA double-strand breaks (DSBs) allow measurement only of relative frequencies of DSBs between loci, which limits our understanding of the physiological relevance of detected DSBs. We propose quantitative DSB sequencing (qDSB-Seq), a method providing both DSB frequencies per cell and their precise genomic coordinates. We induced spike-in DSBs by a site-specific endonuclease and used them to quantify labeled DSBs (e.g. using i-BLESS). Utilizing qDSB-Seq, we determined numbers of DSBs induced by a radiomimetic drug and various forms of replication stress, and revealed several orders of magnitude differences in DSB frequencies. We also measured for the first time Top1-dependent absolute DSB frequencies at replication fork barriers. qDSB-Seq is compatible with various DSB labeling methods in different organisms and allows accurate comparisons of absolute DSB frequencies across samples.

genomics↗