1000 Genomes Project publishes analysis of completed pilot phase
Small genetic differences between individuals help explain why some people have a higher risk than others for developing illnesses. The 1000 Genomes Project published the most comprehensive map of these genetic differences, estimated to contain approximately 95 percent of the genetic variation of any person on Earth.
Produces tool for research into genetic contributors to
Small genetic differences between individuals help explain why some people have a higher risk than others for developing illnesses such as diabetes or cancer. Today in the journal Nature, the 1000 Genomes Project, an international public-private consortium, published the most comprehensive map of these genetic differences, called variations, estimated to contain approximately 95 percent of the genetic variation of any person on Earth.
Researchers produced the map using next-generation DNA sequencing technologies to systematically characterize human genetic variation in 180 people in three pilot studies. Moreover, the full scale-up from the pilots is already under way, with data already collected from more than 1,000 people.
“The pilot studies of the 1000 Genomes Project laid a critical foundation for studying human genetic variation,” said Richard Durbin, Ph.D., of the Wellcome Trust Sanger Institute and co-chair of the consortium. “These proof-of-principle studies are enabling consortium scientists to create a comprehensive, publicly available map of genetic variation that will ultimately collect sequence from 2,500 people from multiple populations worldwide and underpin future genetics research.”
Genetic variation between people refers to differences in the order of the chemical units – called bases – that make up DNA in the human genome. These differences can be as small as a single base being replaced by a different one – which is called a single nucleotide polymorphism (abbreviated SNP) – or is as large as whole sections of a chromosome being duplicated or relocated to another place in the genome. Some of these variations are common in the population and some are rare. By comparing many individuals to one another and by comparing one population to other populations, researchers can create a map of all types of genetic variation.
The 1000 Genomes Project’s aim is to provide a comprehensive public resource that supports researchers aiming to study all types of genetic variation that might cause human disease. The project’s approach goes beyond previous efforts in capturing and integrating data on all types of variation, and by studying samples from numerous human populations with informed consent allowing free data release without restriction on use. Already, these data have been used in studies of the genetic basis for disease.
“By making data from the project freely available to the research community, it is already impacting research for both rare and common diseases,” said David Altshuler, M.D., Ph.D., Deputy Director of the Broad Institute of Harvard and MIT, and a co-chair of the project. “Biotech companies have developed genotyping products to test common variants from the project for a role in disease. Every published study using next-generation sequencing to find rare disease mutations, and those in cancer, used project data to filter out variants that might obscure their results.”
The project has studied populations with European, West African and East Asian ancestry. Using the newest technologies for sequencing DNA, the project’s nine centers sequenced the whole genome of 179 people and the protein-coding genes of 697 people. Each region was sequenced several times, so that more than 4.5 terabases (4.5 million million base letters) of DNA sequence were collected. A consortium involving academic centers on multiple continents and technology companies that developed and sell the sequencing equipment carried out the work.
The improved map produced some surprises. For example, the researchers discovered that on average, each person carries between 250 and 300 genetic changes that would cause a gene to stop working normally, and that each person also carried between 50 and 100 genetic variations that had previously been associated with an inherited disease. No human carries a perfect set of genes. Fortunately, because each person carries at least two copies of every gene, individuals likely remain healthy, even while carrying these defective genes, if the second copy works normally.
“McGill is very proud to have played a leadership role in the Sampling and ELSI (Ethical, Legal, and Social Issues) Committee,” said Bartha Maria Knoppers, O.C., Ph.D., of the McGill University Centre of Genomics and Policy, and co-chair of the committee. “We played a unique role, putting the sampling design people with the ethics people – selecting populations and criteria and ensuring consistency across the ethical framework with people in the field. Our involvement will continue as we move into full-scale studies.” 2,500 samples from 27 populations will be studied over the next two years. Data from the pilot studies and the full-scale project are freely available on the project web site, www.1000genomes.org.
Organizations that committed major support to the project include: 454 Life Sciences, a Roche company, Branford, Conn.; Life Technologies Corporation, Carlsbad, Calif.; BGI-Shenzhen, Shenzhen, China; Illumina Inc., San Diego; the Max Planck Institute for Molecular Genetics, Berlin, Germany; the Wellcome Trust Sanger Institute, Hinxton, Cambridge, UK; and the National Human Genome Research Institute, which supports the work being done by Baylor College of Medicine, Houston, Texas; the Broad Institute, Cambridge, Mass.; and Washington University, St. Louis, Missouri. Researchers at many other institutions are also participating in the project including groups in Barbados, Canada, China, Colombia, Finland, the Gambia, India, Malawi, Pakistan, Peru, Puerto Rico, Spain, the UK, the US, and Vietnam.
This document was prepared from a press release issued by the National Institutes of Health. Please consult the original version here: http://www.eurekalert.org/pub_releases/2010-10/biom-1gp102610.php