UC San Diego Undergraduates Forge New Area of Bioinformatics
Showing posts with label Genomics. Show all posts
Showing posts with label Genomics. Show all posts
What Is the HapMap?
What Is the HapMap?
This is an article that recently appeared on The International HapMap project, http://www.hapmap.org/.
The HapMap is a catalog of common genetic variants that occur in human beings. It describes what these variants are, where they occur in our DNA, and how they are distributed among people within populations and among populations in different parts of the world. The International HapMap Project is not using the information in the HapMap to establish connections between particular genetic variants and diseases. Rather, the Project is designed to provide information that other researchers can use to link genetic variants to the risk for specific illnesses, which will lead to new methods of preventing, diagnosing, and treating disease.
Figure 1: When DNA sequences on a part of chromosome 7 from two random individuals are compared, two single nucleotide polymorphisms (SNPs) occur in about 2,200 nucleotides.
The DNA in our cells contains long chains of four chemical building blocks -- adenine, thymine, cytosine, and guanine, abbreviated A, T, C, and G. More than 6 billion of these chemical bases, strung together in 23 pairs of chromosomes, exist in a human cell. (Seehttp://www.dnaftb.org/dnaftb/ for basic information about genetics.) These genetic sequences contain information that influences our physical traits, our likelihood of suffering from disease, and the responses of our bodies to substances that we encounter in the environment.
The genetic sequences of different people are remarkably similar. When the chromosomes of two humans are compared, their DNA sequences can be identical for hundreds of bases. But at about one in every 1,200 bases, on average, the sequences will differ (Figure 1). One person might have an A at that location, while another person has a G, or a person might have extra bases at a given location or a missing segment of DNA. Each distinct "spelling" of a chromosomal region is called an allele, and a collection of alleles in a person's chromosomes is known as a genotype.
Differences in individual bases are by far the most common type of genetic variation. These genetic differences are known as single nucleotide polymorphisms, or SNPs (pronounced "snips"). By identifying most of the approximately 10 million SNPs estimated to occur commonly in the human genome, the International HapMap Project is identifying the basis for a large fraction of the genetic diversity in the human species.
For geneticists, SNPs act as markers to locate genes in DNA sequences. Say that a spelling change in a gene increases the risk of suffering from high blood pressure, but researchers do not know where in our chromosomes that gene is located. They could compare the SNPs in people who have high blood pressure with the SNPs of people who do not. If a particular SNP is more common among people with hypertension, that SNP could be used as a pointer to locate and identify the gene involved in the disease.
However, testing all of the 10 million common SNPs in a person's chromosomes would be extremely expensive. The development of the HapMap will enable geneticists to take advantage of how SNPs and other genetic variants are organized on chromosomes. Genetic variants that are near each other tend to be inherited together. For example, all of the people who have an A rather than a G at a particular location in a chromosome can have identical genetic variants at other SNPs in the chromosomal region surrounding the A. These regions of linked variants are known as haplotypes (Figure 2).
In many parts of our chromosomes, just a handful of haplotypes are found in humans. [See The Origins of Haplotypes.] In a given population, 55 percent of people may have one version of a haplotype, 30 percent may have another, 8 percent may have a third, and the rest may have a variety of less common haplotypes. The International HapMap Project is identifying these common haplotypes in four populations from different parts of the world. It also is identifying "tag" SNPs that uniquely identify these haplotypes. By testing an individual's tag SNPs (a process known as genotyping), researchers will be able to identify the collection of haplotypes in a person's DNA. The number of tag SNPs that contain most of the information about the patterns of genetic variation is estimated to be about 300,000 to 600,000, which is far fewer than the 10 million common SNPs.
Once the information on tag SNPs from the HapMap is available, researchers will be able to use them to locate genes involved in medically important traits. Consider the researcher trying to find genetic variants associated with high blood pressure. Instead of determining the identity of all SNPs in a person's DNA, the researcher would genotype a much smaller number of tag SNPs to determine the collection of haplotypes present in each subject. The researcher could focus on specific candidate genes that may be associated with a disease, or even look across the entire genome to find chromosomal regions that may be associated with a disease. If people with high blood pressure tend to share a particular haplotype, variants contributing to the disease might be somewhere within or near that haplotype.
This is an article that recently appeared on The International HapMap project, http://www.hapmap.org/.
The HapMap is a catalog of common genetic variants that occur in human beings. It describes what these variants are, where they occur in our DNA, and how they are distributed among people within populations and among populations in different parts of the world. The International HapMap Project is not using the information in the HapMap to establish connections between particular genetic variants and diseases. Rather, the Project is designed to provide information that other researchers can use to link genetic variants to the risk for specific illnesses, which will lead to new methods of preventing, diagnosing, and treating disease.
Figure 1: When DNA sequences on a part of chromosome 7 from two random individuals are compared, two single nucleotide polymorphisms (SNPs) occur in about 2,200 nucleotides.
The DNA in our cells contains long chains of four chemical building blocks -- adenine, thymine, cytosine, and guanine, abbreviated A, T, C, and G. More than 6 billion of these chemical bases, strung together in 23 pairs of chromosomes, exist in a human cell. (Seehttp://www.dnaftb.org/dnaftb/ for basic information about genetics.) These genetic sequences contain information that influences our physical traits, our likelihood of suffering from disease, and the responses of our bodies to substances that we encounter in the environment.
The genetic sequences of different people are remarkably similar. When the chromosomes of two humans are compared, their DNA sequences can be identical for hundreds of bases. But at about one in every 1,200 bases, on average, the sequences will differ (Figure 1). One person might have an A at that location, while another person has a G, or a person might have extra bases at a given location or a missing segment of DNA. Each distinct "spelling" of a chromosomal region is called an allele, and a collection of alleles in a person's chromosomes is known as a genotype.
Differences in individual bases are by far the most common type of genetic variation. These genetic differences are known as single nucleotide polymorphisms, or SNPs (pronounced "snips"). By identifying most of the approximately 10 million SNPs estimated to occur commonly in the human genome, the International HapMap Project is identifying the basis for a large fraction of the genetic diversity in the human species.
For geneticists, SNPs act as markers to locate genes in DNA sequences. Say that a spelling change in a gene increases the risk of suffering from high blood pressure, but researchers do not know where in our chromosomes that gene is located. They could compare the SNPs in people who have high blood pressure with the SNPs of people who do not. If a particular SNP is more common among people with hypertension, that SNP could be used as a pointer to locate and identify the gene involved in the disease.
However, testing all of the 10 million common SNPs in a person's chromosomes would be extremely expensive. The development of the HapMap will enable geneticists to take advantage of how SNPs and other genetic variants are organized on chromosomes. Genetic variants that are near each other tend to be inherited together. For example, all of the people who have an A rather than a G at a particular location in a chromosome can have identical genetic variants at other SNPs in the chromosomal region surrounding the A. These regions of linked variants are known as haplotypes (Figure 2).
In many parts of our chromosomes, just a handful of haplotypes are found in humans. [See The Origins of Haplotypes.] In a given population, 55 percent of people may have one version of a haplotype, 30 percent may have another, 8 percent may have a third, and the rest may have a variety of less common haplotypes. The International HapMap Project is identifying these common haplotypes in four populations from different parts of the world. It also is identifying "tag" SNPs that uniquely identify these haplotypes. By testing an individual's tag SNPs (a process known as genotyping), researchers will be able to identify the collection of haplotypes in a person's DNA. The number of tag SNPs that contain most of the information about the patterns of genetic variation is estimated to be about 300,000 to 600,000, which is far fewer than the 10 million common SNPs.
Once the information on tag SNPs from the HapMap is available, researchers will be able to use them to locate genes involved in medically important traits. Consider the researcher trying to find genetic variants associated with high blood pressure. Instead of determining the identity of all SNPs in a person's DNA, the researcher would genotype a much smaller number of tag SNPs to determine the collection of haplotypes present in each subject. The researcher could focus on specific candidate genes that may be associated with a disease, or even look across the entire genome to find chromosomal regions that may be associated with a disease. If people with high blood pressure tend to share a particular haplotype, variants contributing to the disease might be somewhere within or near that haplotype.
BioXseed India Launches Biotech Finishing School
Certified Advanced Program in Genomics and Proteomics
Aristogene Biosciences is known in the industry for most authentic and practical training in the field of Biosciences. It has a well equipped 8000 sq.ft lab with the required infrastructure to support Research & Training activities. Aristogene also has an
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Course Content:
- Tools in Genetic Engineering & Microbiology- Pure culture techniques, Working with phages, Cloning fundamentals, PCR
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- Immunotechnology- Immunoprecipitaion and Agglutination techniques, Use of immunotechniques in diagnosis, ELISA, Blotting techniques
- Protein Purification Techniques-Various chromatography techniques, Protein analysis by SDS-PAGE and western blotting, Enzymology.
- Polymerase chain reaction & Hybridization techniques-A strong foundation for PCR based experiments - Gene amplification, RAPD analysis and related experiments, PCR - RFLP and related experiments, Southern hybridization.
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o Creative problem solving skills
o Business Etiquettes and personal grooming and the like.
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- Dr CR Subhashini with 15 years of experience specializing in Molecular Diagnostics & Immunology.
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Travel & accommodation assistance can be provided for outstation students.
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CIRCOS - VISUALIZING THE GENOME, AMONG OTHER THINGS
Circos is designed for visualizing genomic data such as alignments, conservation, and generalized 2D data, such as line, scatter, heatmap and histogram plots. Circos is very flexible — you can use it to visualize any kind of data, not just genomics. Circos has been used to visualize customer flow in the auto industry, volume of courier shipments, database schemas, and presidential debates.
The creation of Circos was motivated by a need to visualize intra- and inter-chromosomal relationships within one or more genomes, or between any two or more sets of objects with a corresponding distance scale. Circos is similar to chromowheel and, to a lesser extent, genopix.
Circos uses a circular composition of ideograms to mitigate the fact that some data, like combinations of intra- and inter-chromosomal relationships (alignments, duplications, assembly paired-ends, etc) are very difficult to organize when the underlying ideograms (or contigs) are arranged as lines. In many cases, it is impossible to keep the relationship lines from crossing other structures and this deteriorates the effectiveness of the graphic.
Specific features are included to help viewing data on the genome. The genome is a large structure with localized regions of interest, frequently separated by large oceans of uninteresting sequence. To help visualize data in this context, Circos can create images with variable axis scaling, permitting local magnification of genomic regions to be controlled without cropping. Scale smoothing ensures that the magnification level changes smoothly. In combination with axis breaks and custom ideogram order, the final image can be easily tuned to offer the clearest illustration of your data.
All aspects of the output image are tunable, making Circos a flexible and extensible tool for the generation of publication-quality, circularly composited renditions of genomic data and related annotations.
Circos is written in Perl and produces bitmap (PNG) and vector (SVG) images using plain text configuration and input files.
The Human Genome Project
About the Lecture
Dr. Lander is a geneticist, molecular biologist and a mathematician, with research interests in human genetics, mouse genetics, population genetics and computational and mathematical methods in biology.He and his research group have developed many of the tools of modern genome research including genomic maps of the human, mouse and rat genomes in connection with the Human Genome Project and techniques for genetic analyses of complex, multigenic traits. He has applied these techniques to the understanding of cancer, diabetes, hypertension, renal failure and dwarfism.
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