Bottleneck Sequencing for Rare Mutation Detection Across Genomes
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Solution Overview
Problem
Current next-generation sequencing (NGS) technologies struggle to accurately and sensitively detect rare somatic mutations in normal human tissues due to high sequencing error rates and limitations in unbiased detection across the human genome.
Innovation Solution
The Bottleneck Sequencing System (BotSeqS) method involves ligating adaptors to DNA fragments, diluting the library, and amplifying family members to sequence both strands, allowing for the identification of rare mutations by aligning nucleotide sequences to a reference and identifying differences across strands.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional NGS sequencing is used, then sequencing throughput is high, but detection sensitivity for rare mutations is insufficient due to high error rates
Solution Approach 1:
The DNA library is divided into individual single-stranded templates, each amplified independently into a family of identical sequences. This segmentation allows error detection by comparing multiple copies of the same template, as sequencing errors occur randomly and will not be present in all family members, whereas true mutations will be consistent across all members of a family.
Solution Approach 2:
Each single-stranded DNA template is copied multiple times through PCR amplification to generate a family of identical sequences. These copies serve as replicates that can be sequenced independently, allowing statistical identification of true mutations versus sequencing errors by consensus calling across multiple family members.
2Measurement precision
If single cell genomic sequencing is used, then genome-wide detection capability is achieved, but point mutations are introduced during whole-genome amplification
Solution Approach 1:
The method performs preliminary dilution of the library to ensure that each amplification reaction starts from a single template molecule. This preliminary action prevents co-amplification of multiple templates that would lead to mixed signals and makes it possible to distinguish true mutations from amplification errors by comparing family members.
Solution Approach 2:
The sequencing data from multiple family members is used as feedback to identify and correct amplification errors. By requiring that a mutation be present in a significant proportion of family members (consensus threshold), the method can distinguish true biological mutations from artifacts introduced during amplification.
3Measurement precision
If consensus sequencing with molecular barcodes is used, then rare point mutations can be accurately detected, but the method is limited to targeted loci or small pre-defined genomic regions
Solution Approach 1:
The bottleneck sequencing method uses universal adapter sequences that can ligate to any fragmented DNA, making the approach applicable to genome-wide sequencing rather than just targeted regions. The same amplification and sequencing protocol works for both targeted and whole-genome applications, providing versatility while maintaining high sensitivity for rare mutation detection.
Data Source
AI summary
Bottleneck Sequencing System (BotSeqS) is a next-generation sequencing method that simultaneously quantifies rare somatic point mutations across the mitochondrial and nuclear genomes. BotSeqS combines molecular barcoding with a simple dilution step immediately prior to library amplification. BotSeqS can be used to show age and tissue-dependent accumulations of rare mutations and demonstrate that somatic mutational burden in normal tissues can vary by several orders of magnitude, depending on biologic and environmental factors. BotSeqS has been used to show major differences between the mutational patterns of the mitochondrial and nuclear genomes in normal tissues. Lastly, BotSeqS has shown that the mutation spectra of normal tissues were different from each other, but similar to those of the cancers that arose in them.