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HiFi long-read amplicon sequencing for full-spectrum variants of human mtDNA

Authors :
Yan Lin
Jiayin Wang
Ran Xu
Zhe Xu
Yifan Wang
Shirang Pan
Yan Zhang
Qing Tao
Yuying Zhao
Chuanzhu Yan
Zhenhua Cao
Kunqian Ji
Source :
BMC Genomics, Vol 25, Iss 1, Pp 1-12 (2024)
Publication Year :
2024
Publisher :
BMC, 2024.

Abstract

Abstract Background Mitochondrial diseases (MDs) can be caused by single nucleotide variants (SNVs) and structural variants (SVs) in the mitochondrial genome (mtDNA). Presently, identifying deletions in small to medium-sized fragments and accurately detecting low-percentage variants remains challenging due to the limitations of next-generation sequencing (NGS). Methods In this study, we integrated targeted long-range polymerase chain reaction (LR-PCR) and PacBio HiFi sequencing to analyze 34 participants, including 28 patients and 6 controls. Of these, 17 samples were subjected to both targeted LR-PCR and NGS to compare the mtDNA variant detection efficacy. Results Among the 28 patients tested by long-read sequencing (LRS), 2 patients were found positive for the m.3243 A > G hotspot variant, and 20 patients exhibited single or multiple deletion variants with a proportion exceeding 4%. Comparison between the results of LRS and NGS revealed that both methods exhibited similar efficacy in detecting SNVs exceeding 5%. However, LRS outperformed NGS in detecting SNVs with a ratio below 5%. As for SVs, LRS identified single or multiple deletions in 13 out of 17 cases, whereas NGS only detected single deletions in 8 cases. Furthermore, deletions identified by LRS were validated by Sanger sequencing and quantified in single muscle fibers using real-time PCR. Notably, LRS also effectively and accurately identified secondary mtDNA deletions in idiopathic inflammatory myopathies (IIMs). Conclusions LRS outperforms NGS in detecting various types of SNVs and SVs in mtDNA, including those with low frequencies. Our research is a significant advancement in medical comprehension and will provide profound insights into genetics.

Details

Language :
English
ISSN :
14712164
Volume :
25
Issue :
1
Database :
Directory of Open Access Journals
Journal :
BMC Genomics
Publication Type :
Academic Journal
Accession number :
edsdoj.151e2d63e5074240b424bf794c3afc60
Document Type :
article
Full Text :
https://doi.org/10.1186/s12864-024-10433-9