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Related Concept Videos

Comparing Copy Number Variations and SNPs02:26

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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.
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Principles of Pharmacogenetics: Types of Genetic Variants01:27

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The human genome is over 99.9% identical between individuals, yet genetic differences exist at millions of bases. The human genome contains approximately 3 million variant positions per individual, many of which are heterozygous, contributing to genetic diversity and individual traits. Genetic variations include single-nucleotide polymorphisms (SNPs), insertions, deletions, and copy number variations (CNVs).SNPs, the most common variation, involve single-base changes in DNA. These can be...
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Genetic variation is the diversity in DNA sequences found among individuals of the same species. This diversity is crucial for a species' survival because it helps organisms adapt to environmental changes. Genetic variation begins with fertilization, where an egg and sperm cell merge. Each of these cells carries 23 chromosomes, up to 46 in the fertilized egg. Chromosomes are long DNA strands that contain genes, the basic units of heredity.
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When the fitness of a trait is influenced by how common it is (i.e., its frequency) relative to different traits within a population, this is referred to as frequency-dependent selection. Frequency-dependent selection may occur between species or within a single species. This type of selection can either be positive—with more common phenotypes having higher fitness—or negative, with rarer phenotypes conferring increased fitness.
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Genome-wide Association Studies-GWAS01:11

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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.
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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,...
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Detection of Rare Genomic Variants from Pooled Sequencing Using SPLINTER
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Identifying rare and common variants with Bayesian variable selection.

Cheongeun Oh1

  • 1Biostatistics, Department of Population Health, New York University, New York, NY 10016 USA.

BMC Proceedings
|December 17, 2016
PubMed
Summary
This summary is machine-generated.

This study introduces a Bayesian approach to identify rare and common genetic variants associated with quantitative traits. The method successfully detected variants in the MAP4 gene linked to blood pressure, demonstrating its power even with extremely rare variants.

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Area of Science:

  • Genetics
  • Biostatistics
  • Genomic Medicine

Background:

  • Next-generation sequencing generates vast data, including rare genetic variants.
  • Statistical analysis of rare variants for disease association is challenging due to low minor allele frequency.

Purpose of the Study:

  • To develop a Bayesian variable selection method for simultaneous association testing of rare and common genetic variants.
  • To model the relationship between phenotypes and genetic variants, considering multivariate effects.

Main Methods:

  • A Bayesian variable selection approach is proposed.
  • A risk index score is constructed for groups of rare variants.
  • Within-chain permutation is used to determine empirical thresholds for variant detection.

Main Results:

  • The method was applied to Genetic Analysis Workshop 19 data for blood pressure traits.
  • Associations between systolic and diastolic blood pressure and genetic variants were investigated.
  • Several rare and common variants in the MAP4 gene were identified as potentially associated with blood pressure.

Conclusions:

  • The Bayesian method is effective for identifying disease-associated variants, including those that are extremely rare.
  • The approach demonstrates power in detecting associations in complex genetic datasets.