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结合测序技术可与 SMOR 纠错合成测序技术相媲美,可准确检测和定量分析(< 0.1%)亚群的变异体。

Sequencing by binding rivals SMOR error-corrected sequencing by synthesis technology for accurate detection and quantification of minor (< 0.1%) subpopulation variants.

机构信息

Pathogen and Microbiome Division, Translational Genomics Research Institute, 3051 W. Shamrell Blvd., Suite 106, Flagstaff, AZ, 86005, USA.

Emerging Opportunities Division, Translational Genomics Research Institute, 445 N 5th Street, Phoenix, AZ, USA.

出版信息

BMC Genomics. 2024 Aug 19;25(1):789. doi: 10.1186/s12864-024-10697-1.

Abstract

BACKGROUND

Detecting very minor (< 1%) subpopulations using next-generation sequencing is a critical need for multiple applications, including the detection of drug resistant pathogens and somatic variant detection in oncology. A recently available sequencing approach termed 'sequencing by binding (SBB)' claims to have higher base calling accuracy data "out of the box." This paper evaluates the utility of using SBB for the detection of ultra-rare drug resistant subpopulations in Mycobacterium tuberculosis (Mtb) using a targeted amplicon assay and compares the performance of SBB to single molecule overlapping reads (SMOR) error corrected sequencing by synthesis (SBS) data.

RESULTS

SBS displayed an elevated error rate when compared to SMOR error-corrected SBS and SBB techniques. SMOR error-corrected SBS and SBB technologies performed similarly within the linear range studies and error rate studies.

CONCLUSIONS

With lower sequencing error rates within SBB sequencing, this technique looks promising for both targeted and unbiased whole genome sequencing, leading to the identification of minor (< 1%) subpopulations without the need for error correction methods.

摘要

背景

使用下一代测序技术检测非常小的(<1%)亚群是多种应用的关键需求,包括耐药病原体的检测和肿瘤学中的体细胞变异检测。最近可用的一种测序方法称为“结合测序(SBB)”,据称其“开箱即用”的数据具有更高的碱基调用准确性。本文评估了使用靶向扩增子检测结核分枝杆菌(Mtb)中超低耐药亚群的 SBB 的实用性,并将 SBB 与单分子重叠读取(SMOR)纠错合成测序(SBS)数据进行了比较。

结果

与 SMOR 纠错 SBS 和 SBB 技术相比,SBS 显示出更高的错误率。在线性范围研究和错误率研究中,SMOR 纠错 SBS 和 SBB 技术的性能相似。

结论

SBB 测序的测序错误率较低,这项技术有望用于靶向和非靶向全基因组测序,在无需纠错方法的情况下,能够识别出亚群比例<1%的次要亚群。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7288/11331594/b15f59afb696/12864_2024_10697_Fig1_HTML.jpg

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