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What are SNPs?
Single nucleotide polymorphisms, or SNPs (pronounced "snips"), are
DNA sequence variations that occur when a single nucleotide (A,T,C,or G) in
the genome sequence is altered. For example a SNP might change the DNA sequence
AAGGCTAA to ATGGCTAA.
For a variation to be considered a SNP, it must occur in at least 1% of the
population. SNPs, which make up about 90% of all human genetic variation, occur
every 100 to 300 bases along the 3-billion-base human genome. Two of every three
SNPs involve the replacement of cytosine (C) with thymine (T). SNPs can occur
in coding (gene) and noncoding regions of the genome. Many SNPs have no
effect on cell function, but scientists believe others could predispose people
to disease or influence their response to a drug.
Although more than 99% of human DNA sequences are the same,
variations in DNA sequence can have a major impact on how humans respond to
disease; environmental factors such as bacteria, viruses, toxins, and chemicals;
and drugs and other therapies. This makes SNPs valuable for biomedical
research and for developing pharmaceutical products or medical diagnostics.
SNPs are also evolutionarily stable—not changing much from generation to generation—making them easier to follow in population studies.
Scientists believe SNP maps will help them identify the multiple genes associated
with complex ailments such as cancer, diabetes, vascular disease, and some forms
of mental illness. These associations are difficult to establish with conventional
gene-hunting methods because a single altered gene may make only a small contribution
to the disease.
Several groups worked to find SNPs and ultimately create SNP maps of
the human genome. Among these were the U.S. Human Genome Project
(HGP) and a large group of pharmaceutical companies called the SNP Consortium
or TSC project. The likelihood of duplication among the groups was small
because of the estimated 3 million SNPs, and the potential payoff of a SNP map was
In addition to pharmacogenomic, diagnostic, and biomedical research implications,
SNP maps are helping to identify thousands of additional markers in the genome,
thus simplifying navigation of the much larger genome map generated by HGP researchers.
How can SNPs be used as risk factors in disease
SNPs do not cause disease, but they can help determine the likelihood that
someone will develop a particular illness. One of the genes associated with
Alzheimer's disease, apolipoprotein E or ApoE, is a good example of how SNPs
affect disease development. ApoE contains two SNPs that result in three
possible alleles for this gene: E2, E3, and E4. Each allele differs by one DNA
base, and the protein product of each gene differs by one amino acid.
Each individual inherits one maternal copy of ApoE and one paternal
copy of ApoE. Research has shown that a person who inherits at
least one E4 allele will have a greater chance of developing Alzheimer's disease. Apparently,
the change of one amino acid in the E4 protein alters its structure and function
enough to make disease development more likely. Inheriting the E2 allele, on
the other hand, seems to indicate that a person is less likely to develop
Of course, SNPs are not absolute indicators of disease development. Someone
who has inherited two E4 alleles may never develop Alzheimer's disease, while another
who has inherited two E2 alleles may. ApoE is just one gene that has
been linked to Alzheimer's. Like most common chronic disorders such as heart
disease, diabetes, or cancer, Alzheimer's is a disease that can be caused by
variations in several genes. The polygenic nature of these disorders is what
makes genetic testing for them so complicated.
The answer to this question is based on information provided
by the Genome
Human Genome Project SNP Mapping Goals
In 1998, as part of their last 5-year plan, the DOE and NIH Human
Genome programs established goals to identify and map SNPs. These goals
- Develop technologies for rapid, large-scale identification and scoring
of SNPs and other DNA sequence variants.
- Identify common variants in the coding regions of most identified genes.
- Create a SNP map of at least 100,000 markers.
- Develop the intellectual foundations for studies of sequence variation.
- Create public resources of DNA samples and cell lines.
What is The SNP consortium (TSC)?
In April 1999, ten large pharmaceutical companies and the U.K. Wellcome Trust
philanthropy announced the establishment of a consortium lead by Arthur L.
Holden to find and map 300,000 common SNPs. The goal was to generate a widely
accepted, high-quality, extensive, publicly available map using SNPs as markers
evenly distributed throughout the human genome. In the end, many more SNPs (1.8
million total) were discovered. Now that the SNP discovery
phase of the TSC project is essentially complete, emphasis has shifted to
studying SNPs in populations. Various TSC member laboratories are genotyping
a subset of SNPs as part of the Allele
Frequency Project. The goal of the TSC allele frequency/genotype project
is to determine the frequency of certain SNPs in three major world populations.
See the TSC website for more information.
Who are members of the SNP consortium?
The international member companies, which together committed at least
$30 million to the consortium's efforts, are APBiotech, AstraZeneca Group PLC, Aventis, Bayer Group
AG, Bristol-Myers Squibb Co., F. Hoffmann-La Roche, Glaxo Wellcome PLC,
IBM, Motorola, Novartis AG, Pfizer Inc., Searle, and SmithKline Beecham
PLC. The Wellcome Trust contributed at least $14 million.
Laboratories funded by these companies to identify SNPs are located at
the Whitehead Institute, Sanger Centre, Washington University (St. Louis),
and Stanford University. Data management and analysis take place at Cold
Spring Harbor Laboratory.
See Consortium Updates:
Why should private companies fund a publicly accessible genome map?
The SNP consortium views its map as a way to make available an important,
precompetitive, high-quality research tool that will spark innovative
work throughout the research and industrial communities. The map will
be a powerful research tool to enhance the understanding of disease processes
and facilitate the discovery and development of safer and more effective
Whose DNA was analyzed to create the consortium's SNP map?
The SNP consortium used DNA resources from a pool of samples obtained
from 24 people representing several racial groups. This is a subset
of the DNA reference panel for SNP identification collected by the NIH
National Human Genome Research Institute. The anonymous, voluntary DNA
contributions were made with informed consent specifically for this use.
Are SNP data available to the public?
SNP data were made available through a consortium website at quarterly intervals during the project's first year and at monthly
intervals during the second year. This cycle of releases ceased in fall
2001 once the discovery phase was finished, but with recent additions
of genotype and allele frequency information, new data were released in fall
Besides the TSC website, SNP data are also available from the following resources:
- dbSNP database - From the
National Center for Biotechnology Information (NCBI).
- HGVbase (Human Genome Variation
Database) - A human gene-based polymorphism database.
For tips on how to use these and other databases, see the Gene
Mutation Resources at Gene
Gateway, an online guide for learning about genes, proteins, and genetic
Meeting Proceedings and Reports
Fifth International Meeting on Single Nucleotide Polymorphism and Complex
October 11-14, 2002; Reykjavik, Iceland
Fourth International Meeting on Single Nucleotide Polymorphism and Complex
October 10-13, 2001; Stockholm, Sweden
Third International Meeting on Single Nucleotide Polymorphism and Complex Genome
September 8-11, 2000; Taos, New Mexico
2000. Hum. Mutat. 17(4), 241-42; 2001. Eur.
J. Hum. Genet. 9, 316-18.
Meeting on Single Nucleotide Polymorphism and Complex Genome Analysis;
September 17-20, 1999; Schloß Hohenkammer, Germany
Eur. J. Hum. Genet. 8(2), 154-165 (2000).
Previous Meetings: 1998. Science 281, 1787-89; 1998. Nat. Genet. 20,
217-18; 1999. Eur. J. Hum. Genet. 7, 98-101.