New DNA Mapping Project to Trace Genetic Ills

Nicholas Bakalar
for National Geographic News
October 26, 2005

Mapping the three billion letters of the human genome has helped researchers better understand the 99.9 percent of DNA that is identical in all humans.

Now a new project aims to map the 0.1 percent of DNA where differences occur. The International HapMap Project will look at variations that dictate susceptibility to genetic influences, such as environmental toxins and inherited diseases.

Researchers "read" DNA code by its structural units called nucleotides. These chemical building blocks are designated by the letters A (adenine), C (cytosine), G (guanine), and T (thymine).

Single-letter variations in genes—called single nucleotide polymorphisms, or SNPs (pronounced "snips")—are often the culprits behind a wide range of genetic diseases. For example, changing an A to a T in the gene for the blood molecule hemoglobin causes sickle cell anemia.

But most diseases and disorders are not caused by a single gene. Instead they are caused by a complex combination of linked genetic variations at multiple sites on different chromosomes.

Gene Mapping

Haplotypes are sets of adjacent SNPs that are closely associated and are inherited as a group.

Certain haplotypes are known to have a role in diseases, including Alzheimer's, deep vein thrombosis, type 2 diabetes, and age-related macular degeneration, a leading cause of blindness.

Identifying the haplotypes that lead to disease, or immunity from disease, will provide scientists with a deeper understanding of genetic illness.

Researchers hope a map of haplotypes will provide the raw material to answer basic questions, such as how many genes are involved in each disorder? How do gene variants interact with each other? How do genes and combinations of genes interact with environmental factors to cause disease or provide immunity?

The first phase of establishing a haplotype map is reported in tomorrow's issue of the journal Nature.

Human DNA contains about ten million common SNPs. It would be impossible, and impossibly expensive, to analyze all of them.

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