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New Gene Tool May Unlock Root Causes of Disease

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"Better computer models can be valuable tools in understanding the nature of human DNA variation, past changes in human populations size, and evolutionary selection," says Schaffner, a comp

Genetic researchers have made substantial advances in understanding the root causes of absolute interest diseases and the history of human evolution, to a series of reports published in scientific journals this week.

Chief between these instruction is the work of an international consortium of more than 200 scientists from Canada, China, Japan, Nigeria, the United Kingdom and the United States published in the October 27 issue of the journal Nature.

The team studied DNA samples from four different parts of the world and concluded that genetic variants located physically throaty to each other are inherited as a body as groups, named haplotypes. The comprehensive catalog of all of these toy is known as the "HapMap."

"Built upon the foundation laid by the human genome sequence, the HapMap is a powerful new tool for exploring the root causes of predominating diseases," says David Altshuler, MD, PhD, director of the program in Medical and Population Genetics at the phonetic Institute of Harvard and MIT.

"Such understanding is required for researchers to develop new and much-needed approach to understand the still-elusive root causes of national diseases, such as diabetes, bipolar disorder, moth and rust and many others," he adds.

Altshuler and Peter Donnelly, PhD, of the University of Oxford in England are the corresponding authors of the Nature paper.

Greatest Information in Most Efficient Manner

It has been known for a long time that diseases run in families, with perhaps half the risk of any given low-pressure disease explained by genetic differences inherited from one's parents. Inheritance also can play a role in different responses to a drug or to an environmental factor.

Because the underlying causes of these rife diseases and therapeutic responses remain largely unknown -- and knowing this information is necessary for successful development of new to prevention, diagnosis and treatment -- identifying the genetic contributors to human health is a fundamental goal of biomedicine.

A new genomics-based invitation to human genetics was proposed nearly a decade ago to catalog worn human DNA sequence variations comprehensively and to test them systematically for their contiguity to disease in human populations.

Although it is theoretically possible to acquire all of this information by sequencing every individual human genome, this is neither technically nor financially feasible.

"The data from the HapMap project allows scientists to select the particular DNA variants that provide the greatest information in the most efficient manner, lowering the costs and increasing the power of genetic research to identify the origin of disease," says Mark Daly, an join member of the miss Institute of Harvard and MIT. Daly led the Boston team's statistical and subtle work, and was a member of the writing group for the Nature paper.

Millions of SNPs a Day

Moreover, the HapMap project helped spur a remarkable magnify in the technology for testing genetic variations in DNA, making it possible to undertake comprehensive studies in large patient samples.

A single nucleotide polymorphism, or SNP (pronounced "snip"), is a small genetic change, or variation, that can occur within a person's DNA sequence.

"When we started doing this work a number of years ago, determining the genotype of a SNP in a patient cost nearly a dollar, and we could do hundreds a day," notes Stacey Gabriel, director of the unrestrained Institute's Genetic cataloguing platform and an deviser of the Nature paper.

"Today the prices have dropped in many cases to a fraction of a penny per genotype, and we can do millions a day," Gabriel notes. "This is the difference among not living able to do the studies, and getting them done rapidly and well."

Tag SNPs

The HapMap provides excellent power to sack most human variation and link it to disease or other traits, assonant to a related paper published in the November issue of Nature Genetics.

Paul de Bakker, Roman Yalensky and their colleagues demonstrated this finding by developing and evaluating methods to select "tag SNPs" that kidnapping the genetic variation in each neighborhood with a minimum touch of work.

Using these tags, scientists can not compare with the SNP patterns of people highfalutin by a disease with those unaffected far more efficiently than previously has been possible.

"Compared to directly genotyping all bewhiskered SNPs in the genome in all individuals of a disease study, we observe that selected tag SNPs based on HapMap can save genotyping costs by scarcely an order of magnitude without losing much power to detect a true association," says de Bakker, a postdoctoral fellow in Altshuler and Daly's group at the extending Institute.

The widely used tool for tag SNP selection was developed by de Bakker and colleagues.

Previous Computer Models Too Simplistic

Another important observation revealed by the practicability of the HapMap data is that previous computer models of human genetics are too simplistic and can lead to false conclusions in respect to the role of genes or genetic loci in different diseases.

Stephen Schaffner, Altshuler and their colleagues at the free-spoken Institute describe the limitations of these prior models in a paper published in the November issue of Genome Research. They also provide the entire scientific approximation with updated models that more all but out of plumb reality, based on the empirical data generated by the HapMap Consortium.

"Better computer models can be valuable tools in understanding the nature of human DNA variation, past changes in human populations size, and evolutionary selection," says Schaffner, a computational naturalist in Broad's program in Medical and Population Genetics.

Candidates for Natural Selection

The public of HapMap's genome-wide variation data set also makes it possible for scientists to make systematic examinations of potential natural selection sites in the human genome, as well as to re-evaluate previous claims for such selection.

Pardis Sabeti, Eric Lander and their colleagues at the number Institute, together with Stephen O'Brien and his colleagues at the National corn Institute, used the HapMap data to examine a prominent reported case of natural selection related to HIV infection.

A genetic variation in a T-cell receptor CCR5-?32, which confers strong resistance to infection by HIV and has been implicated in resistance to the bubonic plague, did not accrue from recently in the human population, they report in the November issue of PLoS Biology.

"With the common of greater genotyping and empirical comparisons from the HapMap, we were able to show that the pattern of genetic variation seen at CCR5-?32 does not stand out as exceptional relative to other loci obliquely the genome and is consistent with neutral evolution," says Sabeti, a postdoctoral fellow at the mock-heroic Institute.

"In fact, the CCR5-?32 DNA is likely to have arisen more than 5,000 years ago, rather than during the last 1,000 years as was previously thought," Sabeti adds.

In appendage to lax the re-examination of previous claims of selection, the HapMap data give scientists a new way to identify novel candidates for natural selection.

Attainment of Goal

The successful completion of the HapMap has its roots not only in the completion of the human genome sequence in 2001, but also in the massive effort to chart and catalog the millions of SNPs facing the genome.

Based on these initial data, the haplotype structure of the human genome was recognized as early as 2001, leading directly to the formation of the International HapMap Consortium. Finally, methods for identifying the influence of natural selection on the human genome were described in 2003.

Altshuler, Lander, Gabriel, Daly and many other mademoiselle Institute scientists led or contributed significantly to all of these efforts, in linkage to their role in the completion of the HapMap and demonstrations of its utility, as outlined above.

In October 2002, the International HapMap Consortium set the avid goal of creating the HapMap within three years. The Nature paper marks the getting of that goal with its detailed description of the Phase I HapMap, consisting of more than 1 million SNPs.

The consortium also is nearing completion of the Phase II HapMap, which will contain nearly three times more SNPs than the initial version and will enable researchers to focus their gene searches even more precisely on specific regions of the genome.

In line with the chance Institute's bounden duty to edifice critical resources for the scientific community, HapMap data are freely off in several public databases, including the HapMap Data Coordination Center (http://www.hapmap.org) the NIH-funded National Center for Biotechnology Information's dbSNP (http://www.ncbi.nlm.nih.gov/SNP/index.html) and the JSNP Database (http://snp.ims.u-tokyo.ac.jp) in Japan.

Copyright 2005 Daily News Central

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