Article Summary
An SNP (Single Nucleotide Polymorphism) is a common type of genetic variation in which a single base in the DNA sequence differs between individuals. This article explains the basics of genes, DNA, genomes, and chromosomes, then looks at how SNP analysis is used in research and precision medicine.
We also cover “SNP-based NIPT,” a prenatal testing method that applies SNP analysis to distinguish maternal DNA from placenta-derived DNA, along with what its results can and cannot tell you.
What Is an SNP (Single Nucleotide Polymorphism)?
An SNP (pronounced “snip”) stands for Single Nucleotide Polymorphism. It refers to a single base within the genomic DNA sequence — often called the blueprint of life — being replaced by a different base. Because a single base substitution can influence physical traits and susceptibility to disease, researchers are actively studying SNPs as a foundation for precision, genetics-informed medicine.
Genes, DNA, Genome, and Chromosomes: What’s the Difference?
Genetic testing has become far more accessible in recent years, regardless of how reliable any individual test may be. Genome-edited foods, genetically modified crops, and DNA testing also come up regularly in the news. When it comes to chromosomes specifically, NIPT (Non-Invasive Prenatal Testing) is well known for its ability to detect the likelihood of fetal chromosomal abnormalities from a maternal blood sample with high accuracy.
Genes, DNA, genomes, and chromosomes have all become familiar terms as a result. Even so, few people can clearly explain how a genome, DNA, and a gene actually differ, and it is common to mistakenly equate DNA with “the cause of heredity.” Understanding what each term means is the first step toward understanding SNPs.
What Is a Gene?
A gene is the data that builds an organism’s body. From collagen, the elastic substance in skin, to the muscles that move the body, the hemoglobin that carries oxygen throughout the bloodstream, and even digestive enzymes and our sense of smell — our bodies are built from proteins.
Proteins are produced based on the data contained in genes, and this is what forms a living body. Humans are estimated to have around 20,000 genes.
What Is DNA?
DNA stands for deoxyribonucleic acid. It is easiest to picture as the double-helix shape shown in explainer videos. Within that helix are four bases — adenine (A), thymine (T), guanine (G), and cytosine (C) — and the order in which they appear (the base sequence) is what carries genetic information.
If a gene is the data, DNA is the blueprint used to build the organism. The human base sequence spans roughly 3 billion base pairs and contains the genetic information needed to produce offspring resembling their parents. The complete set of hereditary information passed down in this way is called “genomic DNA,” and it is why children tend to resemble their parents.
Based on the blueprint recorded in this DNA, the body determines where and how much of each protein structure to build. Differences in DNA base sequence are also what account for variation in facial features, body type, and constitution among individuals.
What Is a Genome?
“Genome” combines “gene” with the Greek/German-derived suffix “-ome,” meaning “all of.” It was coined in 1920 by German botanist Hans Winkler and is generally translated as “the complete set of genetic information.”
As the name suggests, a genome refers to “the entire set of genes an organism needs to be that organism.” A mouse’s offspring becomes a mouse, and a human’s offspring becomes a human — the genome can be thought of as the complete DNA set required for each species.
What Are Chromosomes?
A chromosome is a structure formed when strands of DNA are wound around proteins called histones. A single chromosome contains anywhere from several hundred to several thousand genes. Humans inherit one chromosome from each parent in every pair, giving a total of 46 chromosomes (23 pairs). Of these, 44 are autosomes, numbered from largest to smallest.
The remaining two are sex chromosomes, which determine biological sex. There are two types, X and Y: an XY combination results in male sex, while an XX combination results in female sex.
The Human Genome Project
The Human Genome Project was an international effort launched to fully decode the base sequence of DNA contained in the nucleus of every human cell. Its goal was to determine the order of all 3 billion bases, where each is located, and what information each segment encodes.
The full human genome sequence was completed in 2003. Since then, this data has driven advances in genetic medicine, including research into disease causes and the development of gene-based therapeutics.
What SNPs Give Rise To
The 3-billion-base sequence of human genomic DNA is not identical from person to person. When a single base at a given position differs from the standard sequence, the resulting variation is called an SNP (Single Nucleotide Polymorphism).
SNPs occur roughly once every 300 to 1,500 bases in human DNA. These single-base differences — differences in genetic information, in other words — are part of what shapes individual traits such as facial features, personality tendencies, hay fever susceptibility, and alcohol tolerance.
By definition, an SNP is a variation present in at least 1% of a population; base changes occurring in less than 1% of the population are classified instead as mutations.
Remarkable Advances in SNP Analysis Methods
SNP analysis traditionally focused on one target SNP (or a handful) at a time, examined individually. Methods such as RFLP (amplifying the target region by PCR, then treating it with restriction enzymes) and SSCP (amplifying the target region by PCR, then running electrophoresis while preserving its three-dimensional structure) fall into this category. These methods, however, were labor-intensive and not especially accurate.
From the 2000s onward, demand grew for higher-throughput analysis methods. Rather than examining SNPs one at a time, researchers increasingly turned to comprehensive, genome-wide SNP analysis — an approach that remains central today. DNA microarray technology marked a particularly notable leap forward: many DNA fragments (probes) are arranged in a grid on a chip, hybridized with a sample’s DNA, and read out using fluorescent signals to determine the sequence contained in the sample. For SNP analysis specifically, using probes designed around the neighboring nucleotides of each SNP made comprehensive, genome-wide screening possible.
DNA microarray technology has since advanced further and become more accessible as costs have fallen. More recently, whole-genome sequencing using next-generation sequencers (NGS) has made it possible to detect even low-frequency SNPs, and the scope of what can be analyzed is expected to keep expanding. SNP databases built using these technologies are also becoming more comprehensive, laying the groundwork for wider use of SNP data in research and clinical medicine.
The Rise of SNP-Based Precision Medicine
Genome research has continued to accelerate ever since the human genome was fully decoded in 2003. The field has shifted from identifying the causes of single-gene disorders toward comprehensive, genome-wide analysis of complex diseases and drug response — differences in how individuals respond to medication, including both efficacy and side effects — and this research continues to expand.
Disease is not caused by genetic factors alone; environmental factors are also deeply involved, so SNP analysis alone will never explain everything. Even so, it holds real promise for understanding disease mechanisms and supporting prevention.
Analyzing and accumulating SNP data makes it possible to anticipate how a patient will respond to a drug — including potential side effects — before treatment even begins. This is opening the door to “precision medicine,” in which the right drug is given at the right dose and the right time based on a person’s genetic background, and this field is expected to keep growing. Beyond precision medicine, SNP analysis is also being applied to develop drugs whose effects are less dependent on genetic background and medications with more consistent efficacy across patients.
SNP Projects and Personal Data: From National Governments to Corporations
Governments are currently pursuing genome analysis of cancers and rare diseases as part of national research initiatives. Large corporations have also announced voluntary programs asking employees to share genomic data alongside health checkup results in support of workplace healthcare initiatives. Falling genome sequencing costs are a major factor behind this trend.
At the same time, an individual’s genomic data is arguably the ultimate form of personal information. Under Japan’s amended Act on the Protection of Personal Information (2015), the base sequence that makes up a person’s DNA is explicitly classified as an individual identification code.
Without specialized genetics knowledge, it is generally difficult to link genomic data back to a specific individual. However, if genomic data were to leak, it could potentially be used to infer a person’s predisposition to certain hereditary conditions. That, in turn, raises real — if not absolute — concerns about discrimination in employment, marriage, or access to financial services based on someone’s genetic profile.
SNP research, along with rapidly advancing genetic testing methods such as NIPT (Non-Invasive Prenatal Testing), will only keep expanding. Working through these ethical and legal questions may end up being just as transformative for medicine as the technology itself.
How SNPs Relate to NIPT
The SNP fundamentals covered above are actually put to direct use in one of the testing methods available under NIPT (Non-Invasive Prenatal Testing). This section explains how “SNP-based NIPT” works and what to keep in mind when interpreting your results.
What Is SNP-Based NIPT? How It Tells Maternal and Fetal DNA Apart
SNP-based NIPT is a testing method that compares SNP patterns between DNA in the mother’s blood and DNA derived from the placenta to estimate chromosomal changes. NIPT includes several different testing methods, and the SNP-based approach is one of them.
During pregnancy, a small amount of placenta-derived DNA fragments (cell-free DNA, or cfDNA) circulates in the mother’s blood alongside her own DNA. SNP-based testing distinguishes between the two by comparing how much the SNP patterns of the mother and the fetus (via the placenta) differ. One distinguishing feature of this method is that it can also determine whether a twin pregnancy is identical or fraternal. For a comparison of NIPT’s four main testing methods, see our article comparing the different types of NIPT and their accuracy.
The proportion of fetal-derived DNA in the mother’s blood is called the “fetal fraction.” If this proportion is too low, the test can sometimes come back inconclusive. For a full walkthrough of the NIPT testing process, see our article explaining how NIPT works step by step.
Research is also underway to extend SNP-based analysis toward estimating single-gene disorders. @SRH_Research, an account on X that shares medical research updates, recently shared findings on next-generation NIPT research: an approach that analyzes DNA in maternal blood to estimate the fetal genotype, screening for single-gene disorders, structural chromosomal abnormalities, and aneuploidy all at once. SNP-based analysis techniques are gradually expanding what this kind of testing can offer in exactly this way.
The Limits of SNP-Based NIPT, and What Happens After a Positive Result
Regardless of testing method, every version of NIPT — including the SNP-based approach — is a non-diagnostic screening test. A positive result requires a confirmatory test such as amniocentesis. This holds true across all testing methods.
In outpatient consultations, I sometimes hear patients say something like, “I heard SNP-based testing is highly accurate, so I assumed it was basically a diagnosis.” In reality, though, every version of NIPT has a positive predictive value (the probability that a condition is actually present given a positive result) that varies by condition and maternal age, so it needs to be considered separately from a definitive diagnosis.
@fetus7, an account on X focused on obstetrics-related information, made a useful point along these lines: even with SNP-based cfDNA testing, the positive predictive value for monosomy X (a numerical change in the sex chromosomes) can sometimes be lower than expected. That kind of variation in positive predictive value by chromosome type is worth keeping in mind when interpreting a result.
The explanatory page on NIPT from the Japan Association of Obstetricians and Gynecologists’ Prenatal Testing Certification Operating Committee explains this in similar terms. A positive result can still mean the condition is absent (a false positive), so a confirmatory test is needed either way. A negative result, on the other hand, is not typically followed up with amniocentesis for confirmation. A report from Japan’s Ministry of Health, Labour and Welfare expert panel on prenatal testing, available here, likewise positions NIPT as a non-diagnostic test.
If a result comes back positive, the typical next steps are as follows. First, genetic counseling helps you understand what the result actually means. From there, you and your partner can decide together, with guidance from a specialist, whether to pursue a confirmatory amniocentesis. There is no need to rush — take the time to work through each step with a specialist.
Frequently Asked Questions
Are SNPs and genes the same thing?
No, they are different concepts. A gene is a functional unit of DNA that serves as the body’s blueprint, while an SNP refers to a single-base difference occurring within a DNA sequence. SNPs can occur both inside genes and in regions outside of genes.
How common are SNPs?
The human genome contains around 3 billion base pairs, and SNPs are estimated to occur at several million to over 10 million positions within it. They are extremely common and widely distributed across the entire genome.
How is SNP-based NIPT different from standard NIPT?
NIPT includes several different testing methods, and the SNP-based approach is one of them. It compares SNP patterns between maternal and placenta-derived DNA, and one notable feature is its ability to determine whether a twin pregnancy is identical or fraternal. You can compare it against other testing methods using each provider’s materials or our comparison article on this site.
Does a positive SNP-based NIPT result mean a definitive diagnosis?
No. Every version of NIPT, including the SNP-based method, is a non-diagnostic screening test. If the result is positive, a confirmatory test such as amniocentesis is needed to establish a definitive diagnosis.
Are SNPs used directly to diagnose disease?
Generally, no single SNP on its own can confirm the presence or absence of a disease. For most conditions, multiple SNPs combine with other factors to influence overall risk, so SNP data is mainly used for risk assessment and as a lead for further research rather than as a standalone diagnostic tool.
What technologies are used to analyze SNPs?
Common approaches include DNA sequencing, SNP arrays, and methods that combine PCR with RFLP. In recent years, the growing use of next-generation sequencers (NGS) has made it possible to analyze large numbers of SNPs in a much shorter time.
Medical supervision: Hiroshi Oka — Director-General, Hiro Clinic NIPT (Fukubikai Medical Corporation), and Lab Director. A graduate of Keio University School of Medicine, Dr. Oka has passed the medical licensing examinations in both Japan and the United States and holds a Ph.D. He is one of a small number of Lab Director-qualified specialists in Japan and serves as a visiting faculty member at a professional graduate school. This article was prepared with attention to Japan’s medical advertising guidelines and references public and academic sources, including BioBank Japan (Institute of Medical Science, The University of Tokyo), RIKEN, Japan’s Ministry of Health, Labour and Welfare, and the Japan Association of Obstetricians and Gynecologists’ Prenatal Testing Certification Operating Committee. Figures and technology trends described here may change as research progresses, so please consult your physician for the latest information and for guidance on interpreting your individual test results.
日本皮膚科学会 皮膚科専門医／日本医師会 産業医／東京衛生検査所 指導監督医
この記事は、 ヒロクリニックNIPTの編集・監修体制 にもとづき、資格を持つ医師が内容を確認しています。
