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Targeted DNA Methylation Analysis by Next-generation Sequencing
Published on: February 24, 2015
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Comparison of structural variants detected by optical mapping with long-read next-generation sequencing
Jakub Savara1,2, Tomáš Novosád1, Petr Gajdoš1
1Department of Computer Science, VSB-Technical University of Ostrava, Ostrava, 708 00, Czech Republic.
Bioinformatics (Oxford, England)
|May 13, 2021
Summary
This study compares optical mapping and long-read whole-genome sequencing for detecting structural variants in cancer. A new tool confirms that optical mapping largely agrees with sequencing, aiding in variant analysis.
Area of Science:
- Genomics
- Bioinformatics
- Cancer Research
Background:
- Long-read whole-genome sequencing (WGS) and optical mapping (OM) show promise for detecting structural variants (SVs) in cancer.
- Key platforms include PacBio, Oxford Nanopore Technologies (ONT), and 10x Genomics for WGS, alongside Bionano Genomics for OM.
- Comparative accuracy and interchangeability of these long-read technologies for SV detection remain key questions.
Purpose of the Study:
- To compare the accuracy of optical mapping (OM) with various long-read whole-genome sequencing (WGS) platforms for structural variant (SV) detection.
- To develop and evaluate a novel software tool for comparing SVs identified by OM and WGS.
- To assess the concordance and complementarity of OM and WGS in identifying clinically relevant SVs.
Main Methods:
- Comparison of optical maps from the SKBR3 breast cancer cell line with AnnotSV outputs from PacBio, ONT, and 10x Genomics WGS data.
- Development of a software tool for comparative analysis and filtering of SVs detected by OM and WGS.
- Utilizing the developed tool to confirm SVs and filter disease-associated variants.
Main Results:
- A high degree of concordance was observed between OM and WGS for SVs within a 50 kbp variance threshold.
- OM-detected translocations (~99%) and deletions (~80%) were largely confirmed by PacBio and ONT, with ~70% confirmed by 10x Genomics.
- Long deletions (>100 kbp) were uniquely identified by 10x Genomics, while insertions showed high concordance between OM, PacBio, and ONT (~74%).
- Inversions and duplications detected by OM were not identified by WGS platforms.
- The developed tool facilitated SV confirmation, gene overlap analysis, and filtering of disease-associated variants.
Conclusions:
- Optical mapping and long-read WGS are complementary for comprehensive SV detection in cancer genomics.
- The developed comparative tool enhances the accuracy and utility of SV analysis by integrating data from different platforms.
- This approach aids in identifying and filtering clinically relevant SVs for cancer research and diagnostics.
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