DNA sequencing methods determine the order of nucleotides in DNA, but different technologies are best suited for different research questions. This cheat sheet compares Sanger chain-termination sequencing with next-generation sequencing so students can connect method design to data output. It is useful for interpreting figures, planning experiments, and understanding why read length, cost, throughput, and accuracy matter in genomics.
Sanger sequencing uses fluorescently labeled chain-terminating ddNTPs to generate fragments that reveal one DNA sequence at high accuracy. Next-generation sequencing, or NGS, sequences millions of DNA fragments in parallel, producing very large datasets for genomes, transcriptomes, and variant discovery. Choosing the right method depends on the target size, number of samples, required depth, read length, turnaround time, and acceptable error profile.
Key Facts
- Sanger sequencing stops DNA synthesis when DNA polymerase incorporates a ddNTP, producing fragments that differ by one nucleotide.
- In Sanger sequencing, the sequence is read from shortest to longest fragment, giving the newly synthesized strand in the 5' to 3' direction.
- NGS uses massively parallel sequencing, meaning millions to billions of DNA molecules are sequenced at the same time.
- Read length is the number of bases produced in one sequencing read, and longer reads make assembly and repetitive-region analysis easier.
- Coverage, also called depth, is calculated as coverage = total bases sequenced / target genome or region size.
- Sanger sequencing is usually best for one gene, one plasmid insert, or confirming a small number of variants.
- NGS is usually best for whole genomes, exomes, transcriptomes, metagenomes, or many samples analyzed at once.
- Higher coverage improves confidence in variant calls because true variants should appear repeatedly across independent reads.
Vocabulary
- Sanger sequencing
- A DNA sequencing method that uses chain-terminating ddNTPs to generate labeled fragments whose lengths identify the nucleotide order.
- Next-generation sequencing
- A group of high-throughput methods that sequence many DNA fragments in parallel to generate large amounts of sequence data.
- Read
- A single sequence output from a sequencing instrument, usually representing one DNA fragment or part of one fragment.
- Coverage
- The average number of times each base in a target region is sequenced, often used to measure confidence in the data.
- Library preparation
- The process of fragmenting DNA or RNA-derived cDNA and adding adapters so molecules can be sequenced by an instrument.
- Variant calling
- The process of identifying differences between sequencing reads and a reference genome, such as SNPs, insertions, or deletions.
Common Mistakes to Avoid
- Assuming Sanger sequencing is always outdated is wrong because it remains excellent for short targets, plasmid verification, and confirming specific variants.
- Choosing NGS for a single small amplicon can be inefficient because the setup, library preparation, and data analysis may cost more than Sanger sequencing.
- Confusing read length with coverage is wrong because read length describes how many bases are in one read, while coverage describes how many times a region is sampled.
- Ignoring error profiles can lead to false conclusions because different platforms may make different types of errors, such as substitutions, insertions, or deletions.
- Treating raw NGS output as final results is wrong because quality filtering, alignment or assembly, and statistical analysis are needed before biological interpretation.
Practice Questions
- 1 A sequencing run produces 12,000,000 total bases for a 60,000-base bacterial plasmid collection target. What is the average coverage?
- 2 A lab needs to confirm a 750-base PCR product from 8 colonies. Which method is usually more appropriate, Sanger sequencing or NGS, and why?
- 3 An exome sequencing experiment targets 50,000,000 bases and aims for 100x coverage. How many total bases of sequence are needed?
- 4 A researcher wants to identify rare variants in a mixed tumor sample. Explain why high coverage and parallel sequencing are more important here than simply having one very long read.