Accurate CNV identification from only a few cells with low GC bias in a single-molecule sequencing platform
Year: 2020
Type: preprint
Abstract: ABSTRACT A technical problem of characterizing copy number variation of several cells with next-generation sequencing is the whole genome amplification induced bias. The result of CNVs and mosaicism detection is affected by the GC bias. Here, we report a rapid non-WGA sample preparation strategy for a single-molecule sequencing platform GenoCare1600. This approach, combined with a single-molecule sequencing platform that avoids the use of WGA and bridge PCR processes, can provide higher reliability with its lower GC bias. By combining our optimized Tn5-based transposon insertion approach with GenoCare, we successfully detected CNVs as small as 1.29M and mosaicism as small as 20%, which is consistent with next-generation sequencing (NGS) data. Moreover, our GenoCare-TTI protocol showed less GC bias and less Mad of Diff. These results suggest that the optimized TTI approach, together with the GenoCare1600 sequencing platform, is a promising option for CNV characterization from maybe one single cell.
Authors: Liang Hu, Qunting Lin, Pingyuan Xie, Lidong Zeng, Lichun Liu, Mengxian Huang, Qin Yan, Meng Zhang, Ge Lin
Language: English
Subfield: Genetics
Domain: Life Sciences
Open Access status: green
Awards: G1146660319, G5151778725
OpenAlex ID: W3001763584