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Related Concept Videos

Single Nucleotide Polymorphisms-SNPs01:05

Single Nucleotide Polymorphisms-SNPs

17.9K
A single nucleotide polymorphism or SNP is a single nucleotide variation at a specific genomic position in a large population. It is the most prevalent type of sequence variation found in the human genome. Point mutations that occur in more than 1% of the population qualify as SNPs. These are present once every 1000 nucleotides on an average in the human genome. Replacement of a purine with another purine (A/G) or a pyrimidine with another pyrimidine (C/T) is known as a transition. In contrast,...
17.9K
Genome-wide Association Studies-GWAS01:11

Genome-wide Association Studies-GWAS

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Genome-wide association studies or GWAS are used to identify whether common SNPs are associated with certain diseases. Suppose specific SNPs are more frequently observed in individuals with a particular disease than those without the disease. In that case, those SNPs are said to be associated with the disease. Chi-square analysis is performed to check the probability of the allele likely to be associated with the disease.
GWAS does not require the identification of the target gene involved in...
15.3K
Comparing Copy Number Variations and SNPs02:26

Comparing Copy Number Variations and SNPs

18.6K
Sequencing of the human genome has opened up several best-kept secrets of the genome. Scientists have identified thousands of genome variations that exist within a population. These variations can be a single nucleotide or a larger chromosomal variation.
Copy number variations or CNVs are the structural variations that cover more than 1kb of DNA sequence. The single nucleotide polymorphism (SNP), on the other hand, is a single nucleotide change or a point mutation that is found in more than 1%...
18.6K
Cancers Originate from Somatic Mutations in a Single Cell02:21

Cancers Originate from Somatic Mutations in a Single Cell

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Cancer arises from mutations in the critical genes that allow healthy cells to escape cell cycle regulation and acquire the ability to proliferate indefinitely. Though originating from a single mutation event in one of the originator cells, cancer progresses when the mutant cell lines continue to gain more and more mutations, and finally, become malignant. For example, chronic myelogenous leukemia (CML) develops initially as a non-lethal increase in white blood cells, which progressively...
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Related Experiment Videos

Single-nucleotide polymorphism (SNP) analysis to associate cancer risk.

Julie Earl1, William Greenhalf

  • 1Division of Surgery and Oncology, University of Liverpool, Liverpool, UK.

Methods in Molecular Biology (Clifton, N.J.)
|November 3, 2009
PubMed
Summary
This summary is machine-generated.

Identifying genetic predispositions to cancer through single nucleotide polymorphisms (SNPs) aids targeted screening. This chapter compares Affymetrix and Illumina platforms for SNP analysis, highlighting key differences in methods and materials for cancer risk assessment.

Related Experiment Videos

Area of Science:

  • Genetics
  • Oncology
  • Bioinformatics

Background:

  • Hereditary factors significantly influence cancer predisposition.
  • Identifying specific genetic variations, such as single nucleotide polymorphisms (SNPs), is crucial for understanding cancer etiology.
  • Understanding familial cancer segregation aids in identifying high-risk genetic loci.

Purpose of the Study:

  • To discuss platforms for analyzing single nucleotide polymorphisms (SNPs) relevant to cancer predisposition.
  • To compare the Affymetrix and Illumina SNP analysis systems.
  • To highlight differences in materials and methods between the two platforms.

Main Methods:

  • Discussion of two major SNP analysis platforms: Affymetrix and Illumina.
  • Emphasis on the principles of good laboratory practice applicable to both systems.
  • Detailed comparison of the specific materials and methodologies employed by each platform.

Main Results:

  • Both Affymetrix and Illumina platforms require adherence to stringent laboratory practices.
  • Significant differences exist in the materials and methods utilized by the Affymetrix and Illumina systems for SNP analysis.
  • The choice of platform can impact the identification of cancer-associated SNPs and high-risk loci.

Conclusions:

  • Effective SNP analysis is vital for identifying hereditary cancer predispositions.
  • Understanding the nuances between SNP analysis platforms like Affymetrix and Illumina is important for researchers.
  • This comparative analysis provides insights for selecting appropriate tools in cancer genetics research.