Analyzing and interpreting DNA double-strand break sequencing data

Abstract

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.Recently, we presented a general method, qDSB-Seq 13 , to quantify DSBs genome-wide, which provides both DSB frequencies per cell and their precise genomic coordinates. qDSB-Seq has been applied to BLESS 4 and i-BLESS 5 , it is also available for END-Seq 6 , Break-Seq 7 , DSBCapture 8 , BLISS 15 , and so on. In this work, we induced spike-in DSBs by a site-specific endonuclease and used these induced DSBs to quantify studied DSBs. qDSB-Seq method has

DSB profiles in human spermatozoa highlight the role of TMEJ in the male germline

“…The NGS data was scanned for adapter sequences and processed into unique DSBs for subsequent analysis. To identify clusters of recurrent DSB formation in a model-free method as proposed by Mitra et al (2020) , we established a topological method by identifying regions corresponding to local maxima of DSBs in the genome-wide DSB distribution that exhibited significantly elevated levels relative to the surrounding distribution.…”

“…The resulting DSB positions were depleted from blacklisted regions using BEDTools intersect ( Quinlan and Hall, 2010 ) and the reference “GRCh38-blacklist.v2.bed” ( https://github.com/igordot/reference-genomes/blob/master/GRCh38/blacklist.v2.bed ). To subsequently identify genomic regions enriched in DSBs, a topological-based workflow was developed as a model-free method, following the proposal by Mitra et al (2020) . Therefore, we identified local maxima in the genome wide DSB distribution.…”