Targeted individual molecule sequencing enables the detection of ultra-rare variants
dc.contributor.author | Bi, Chongwei | |
dc.date.accessioned | 2020-01-27T08:09:16Z | |
dc.date.available | 2020-01-27T08:09:16Z | |
dc.date.issued | 2020-1-20 | |
dc.identifier.uri | http://hdl.handle.net/10754/661200 | |
dc.description.abstract | Targeted individual molecule sequencing enables the detection of ultra-rare variants Chongwei Bi, Lin Wang, Baolei Yuan, and Mo Li Biological and Environmental Science and Engineering Division, King Abdullah University of Science and Technology, Thuwal, KSA Abstract Genome contains hereditary information of the species, and its integrity is vital to life. With the developing of next-generation sequencing (NGS) technologies, we are gaining an unprecedented advance in decoding the genomic information in recent years. However, the current sequencing strategies are mainly population-based, in which samples come from DNA pools of bulk cells. They are not suitable for detecting rare mutations in a subpopulation of cells. Here we introduce targeted individual DNA molecule sequencing (IDMseq), which is a strategy to label and sequence individual DNA molecules from a pool. We applied IDMseq to detect rare mutations. Results showed that IDMseq is broadly applicable to any high-throughput sequencing platforms, and is capable to detect ultra-rare mutations at 1:10,000 allele frequency. Conclusion Inourpreliminaryworkwehave demonstrated that IDMseq is efficient and sensitive in detecting ultra-rare mutations, without limitation in the sequencing platform. IDMseqalsoshowedtheability to detect somatic mutations within the genome. The somatic SNP load calculated from IDMseq is comparable with the published data2. IDMseqwithlongamplicon showed the ability in detecting large SVs at allele resolution, which will potentially benefit other studies in the field. | |
dc.relation.url | https://epostersonline.com//dh2020/node/21 | |
dc.title | Targeted individual molecule sequencing enables the detection of ultra-rare variants | |
dc.type | Poster | |
dc.conference.date | JAN 20 - 22, 2020 | |
dc.conference.name | Digital Health 2020 | |
dc.conference.location | KAUST | |
dc.contributor.institution | ||
refterms.dateFOA | 2020-01-27T08:09:16Z |