Sanger
Definition
Sanger sequencing, also known as chain-termination sequencing or dideoxy sequencing, is a first-generation DNA sequencing method developed by Frederick Sanger in 1977. It uses fluorescently labeled dideoxynucleotides (ddNTPs) that terminate DNA strand elongation at specific bases, generating fragments of varying lengths that are separated by capillary electrophoresis. Despite being largely superseded by next-generation sequencing (NGS) for large-scale projects, Sanger sequencing remains the gold standard for validating variants, sequencing individual genes, and confirming NGS findings due to its high accuracy (99.9%), long read lengths (up to 1000 base pairs), and reliability for low-throughput applications. It is essential for clinical diagnostics, targeted mutation analysis, and quality control in genomics research.
Visualize Sanger in Nodes Bio
Researchers can use Nodes Bio to integrate Sanger sequencing validation data with NGS datasets, visualizing confirmed variants within gene regulatory networks or protein interaction maps. Network graphs can connect validated mutations to affected pathways, downstream targets, and phenotypic outcomes, enabling researchers to distinguish high-confidence variants from potential sequencing artifacts and trace their functional consequences through biological networks.
Visualization Ideas:
- Mutation validation networks connecting Sanger-confirmed variants to affected genes and pathways
- Quality control networks comparing Sanger and NGS results across genomic regions
- Gene-to-phenotype networks incorporating validated mutations and their functional consequences
Example Use Case
A cancer genomics team identifies potential driver mutations in TP53 using whole-exome sequencing across 200 tumor samples. To validate these findings before functional studies, they perform Sanger sequencing on 15 candidate variants. Using network visualization, they map the 12 confirmed mutations to TP53's protein domains, downstream apoptotic pathways, and known drug targets. This integrated view helps prioritize which variants to investigate in cell line models and reveals that three validated mutations cluster in the DNA-binding domain, suggesting a common mechanism of tumor suppression loss.