Genotyping Single Nucleotide Polymorphisms (SNPs) focuses on reading specific variations in an individual’s DNA sequence. Instead of mapping the entire genome, this method targets a select set of known locations where variations are common among people. This targeted approach is a cost-effective and rapid way to survey an individual’s genetic landscape at millions of predetermined sites. The resulting information creates a unique genetic profile that can be compared against large databases to reveal insights into a person’s health risks and biological origins.
What Are SNPs and Why They Matter
A Single Nucleotide Polymorphism, or SNP, represents a difference in a single nucleotide at a specific position in the DNA sequence. If a variation occurs at a particular site in at least one percent of the population, it is classified as an SNP. These variations occur frequently throughout the human genome, with an estimated 10 million SNPs existing across the three billion base pairs of DNA. Most SNPs do not directly affect a person’s health or physical traits, but they act as powerful biological markers used to locate genes that do.
SNPs are valuable because they are often inherited together with nearby genes, a phenomenon known as linkage disequilibrium. An SNP that is harmless may be so close to a disease-causing gene that they are rarely separated during genetic shuffling between generations. Detecting the presence of a specific SNP can therefore act as a proxy, or “tag,” for the presence of that nearby gene variant. This association allows researchers to pinpoint genetic regions responsible for complex traits and diseases without needing to sequence the entire genome.
How Scientists Identify SNPs
Genotyping involves determining which specific nucleotide an individual possesses at a set of pre-selected SNP locations. The two primary methods used for this targeted analysis are DNA microarrays and focused sequencing techniques, which offer distinct trade-offs between scale and resolution. DNA microarrays, often called SNP chips, are designed to analyze hundreds of thousands to over a million known SNPs simultaneously in a high-throughput and cost-effective manner. The technology uses a small chip embedded with microscopic spots, each containing a DNA probe that corresponds to a specific SNP location.
In a microarray assay, an individual’s DNA is fragmented, labeled with a fluorescent dye, and washed over the chip’s surface. The labeled fragments bind only to the complementary probes on the chip, and the specific nucleotide at the SNP site is identified by the resulting fluorescent signal. For example, different dyes signal whether an Adenine (A) or a Guanine (G) is present at a particular location. This method is highly efficient for quickly scanning a large number of common variations.
Targeted DNA sequencing is a more precise approach that reads the exact sequence of bases around a specific SNP or small genomic region. This method involves amplifying the DNA segment of interest and then using Next-Generation Sequencing (NGS) technology to determine the sequence base-by-base. While more expensive and slower than microarrays for large-scale common SNP analysis, targeted sequencing offers greater resolution. It is particularly useful for confirming complex SNPs or for analyzing a small panel of variants that are too rare or complex for microarray probes to detect.
Applications in Personalized Health
Genotyping SNPs provides insights into individual drug response and disease predisposition, leading to a more tailored approach to medicine. The field of pharmacogenomics uses SNP data to predict how a person will metabolize and respond to medications. For instance, variations in the $CYP2D6$ gene, which encodes a liver enzyme, can dramatically affect the breakdown of common drugs like certain antidepressants and the breast cancer medication tamoxifen.
Due to specific $CYP2D6$ SNPs, an individual might be an “ultra-rapid metabolizer,” causing a drug to be processed too quickly and become ineffective. Conversely, they might be a “poor metabolizer,” leading to drug buildup and an increased risk of severe side effects. By genotyping these relevant SNPs, physicians can adjust drug dosages or select alternative medications to optimize efficacy and safety. This proactive approach moves beyond traditional one-size-fits-all dosing to enhance patient outcomes.
SNP genotyping also helps assess an individual’s genetic predisposition for conditions like type 2 diabetes, heart disease, and Alzheimer’s disease. Scientists use a Polygenic Risk Score (PRS), which aggregates risk contributions from thousands of different SNPs across the genome. This score provides an estimate of an individual’s inherited susceptibility compared to the general population. This information can empower individuals and healthcare providers to implement preventative strategies, such as lifestyle changes or earlier screening, years before symptoms appear.
Genotyping for Ancestry and Population Studies
The SNP variations used for health analysis also hold clues about human history and migration patterns. Genotyping for ancestry works by comparing an individual’s SNP profile to reference panels of genetic data collected from hundreds of worldwide populations. Scientists use a subset of highly informative SNPs, called Ancestry Informative Markers (AIMs), which show significant frequency differences between geographically distinct populations. The presence or absence of specific AIMs acts as an inherited signature of a particular continental or regional origin.
By analyzing these markers, researchers estimate the proportion of an individual’s genome that originated from different parts of the world. This data allows for the reconstruction of ancestral paths, tracing the movement of human populations across continents over tens of thousands of years. Studying how SNPs vary across different groups helps population geneticists understand how genetic diversity is distributed globally, providing insights into the evolutionary forces that shaped modern human populations.