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Julia N. Chapman, Alia Kamal, Archith Ramkumar, Owen L. Astrachan Duke University, Genome Revolution Focus, Department of Computer Science Sources

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Presentation on theme: "Julia N. Chapman, Alia Kamal, Archith Ramkumar, Owen L. Astrachan Duke University, Genome Revolution Focus, Department of Computer Science Sources"— Presentation transcript:

1 Julia N. Chapman, Alia Kamal, Archith Ramkumar, Owen L. Astrachan Duke University, Genome Revolution Focus, Department of Computer Science Sources http://www.ornl.gov/sci/techresources/Human_Genome/faq/snps.html http://www.affymetrix.com/corporate/media/genechip_essentials/snps/Tra cking_DNA_With_SNPs.affx Brookes, A. J. (26 February 1999) “The Essence of SNPs.” Department of Genetics and Pathology. (177-186) www.elsevier.com/locate/gene Reduced Representation Shotgun Sequencing (RRS) RRS re-samples specific subsets of the genome from several individuals, and compares the resulting sequences using a highly accurate SNP detection algorithm Rapid genotyping Inexpensive SNP map construction 47,172 SNPs have been discovered through RRS APT For a link to our APT, go to: www.duke.edu/~ak98 for APT Researchers and Applications Variations in the DNA sequences of humans Variations in the DNA sequences of humans can affect how humans develop disease, respond to pathogens, chemicals, drugs, etc. respond to pathogens, chemicals, drugs, etc. Evolutionarily stable --little change among generations --easier to track in population studies. Scientists believe SNP maps will help identify multiple genes associated with cancer, diabetes, vascular disease, and some forms of mental illness. Associations are difficult to establish with conventional gene-hunting methods because a single altered gene may make only a small contribution to the disease. Scientists believe SNP maps will help identify multiple genes associated with cancer, diabetes, vascular disease, and some forms of mental illness. 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 Several groups worked to find SNPs and ultimately create SNP maps of the human genome U.S. Human Genome Project (HGP) SNP Consortium SNP Consortium TSC project *Small likelihood of duplication among the groups because of estimated 3 million SNPs; high potential payoff Introduction Look at the two sequences below. What stands out? The sequences match up on every nucleotide except for the A and the T in black. AAATTTTGGGGGCCCCAAAA AAATTTTGGGGGCCCCATAA This nucleotide change in a sequence is known as a Single Nucleotide Polymorphism or a SNP (pronounced "snip"). SNPs are DNA sequence variations that occur when a single nucleotide (A,T,C,or G) in the genome sequence is altered. 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 both coding (gene) and noncoding regions of the genome. Summary: “The Essence of SNPs” The recent surge of interest in Single Nucleotide Polymorphisms is in large part due to potential uses in disease detection and prevention and population genetics. Currently projects such as the HapMap are searching for the best methods of locating and identifying SNPs in the human genome. As SNPs are discovered they are stored in databases which are growing rapidly and are becoming more and more accessible. (See databases at http://www.genome.wi.mit.edu/SNP/human/index.html and http://www.ibc.wstl.edu/SNP). By definition, a SNP must occur with a frequency >1% in a population. Therefore, SNPs can be used as markers to link populations and study evolutionary patterns because they don’t mutate over time. In conclusion, SNPs have the potential to solve some of genetics’ most vexing problems in the near future. Single Nucleotide Polymorphisms: The Essence of SNPs The fact that we inherit our DNA in these consistent, predictable blocks is key to understanding how SNPs are used to track down a disease-gene. Once a disease-causing mutation occurs in this block of DNA — either by chance or by environmental factors — that mutation is passed on to descendents who inherit that block of DNA generations later. The various SNPs that occur within the block of DNA will also be passed on. So when researchers see a SNP shared by a lot of people who have a disease like autism, (but not shared in a group of people that don't,) they think "These people share a similar block of inherited DNA and there may be a disease causing mutation in that block." In this way, SNPs from an ancestor who might have lived 5,000 years ago, canserve as a marker for a disease gene you could have inherited today. Regions from ancestral chromosomes that remain intact and are separated by regions of recombinant DNA Enable geneticists to establish correlations between specific genes and disease Shared by multiple persons in a given population Help to determine evolutionary patterns: younger populations tend to have longer haplotypes (less time for recombination ) Fig. 3. The red and blue ancestral chromosomes recombine over many generations. The region A labeled in the red parent chromosome corresponds to the region A in two of the resultant chromosomes. Therefore, if all three share a common disease, a correlation may be established between gene A and the particular disease. Cost effective: cheaper to locate linked regions of SNPs than to locate each of 10 million+ SNPs Approx 300,000 to 600,000 “tag SNPs” that uniquely identify haplotypes


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