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Related Concept Videos

Single Nucleotide Polymorphisms-SNPs01:05

Single Nucleotide Polymorphisms-SNPs

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,...
Comparing Copy Number Variations and SNPs02:26

Comparing Copy Number Variations and SNPs

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%...
Genome-wide Association Studies-GWAS01:11

Genome-wide Association Studies-GWAS

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...
Mutation, Gene Flow, and Genetic Drift01:09

Mutation, Gene Flow, and Genetic Drift

In a population that is not at Hardy-Weinberg equilibrium, the frequency of alleles changes over time. Therefore, any deviations from the five conditions of Hardy-Weinberg equilibrium can alter the genetic variation of a given population. Conditions that change the genetic variability of a population include mutations, natural selection, non-random mating, gene flow, and genetic drift (small population size).Mechanisms of Genetic VariationThe original sources of genetic variation are mutations,...
Hardy-Weinberg Principle01:49

Hardy-Weinberg Principle

Diploid organisms have two alleles of each gene, one from each parent, in their somatic cells. Therefore, each individual contributes two alleles to the gene pool of the population. The gene pool of a population is the sum of every allele of all genes within that population and has some degree of variation. Genetic variation is typically expressed as a relative frequency, which is the percentage of the total population that has a given allele, genotype or phenotype.In the early 20th century,...
Principles of Pharmacogenetics: Types of Genetic Variants01:27

Principles of Pharmacogenetics: Types of Genetic Variants

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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Detection of Rare Genomic Variants from Pooled Sequencing Using SPLINTER
14:06

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Identification and frequency estimation of inversion polymorphisms from haplotype data.

Suzanne S Sindi1, Benjamin J Raphael

  • 1Division of Applied Mathematics, Brown University, Providence, Rhode Island 02912, USA.

Journal of Computational Biology : a Journal of Computational Molecular Cell Biology
|April 10, 2010
PubMed
Summary
This summary is machine-generated.

Researchers developed a new method to detect inversion polymorphisms using single nucleotide polymorphism (SNP) data. This approach accurately estimates inversion frequencies in populations, advancing the study of human genetic variation.

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Area of Science:

  • Human Genetics
  • Genomic Variation
  • Population Genetics

Background:

  • Structural rearrangements, including copy-number alterations and inversions, are key contributors to human genetic variation.
  • Copy number variants are easily measured, but copy-neutral variants like inversions require whole genome sequencing.
  • Identifying inversion polymorphisms and their frequencies is crucial for understanding genetic diversity.

Purpose of the Study:

  • To introduce a novel method for identifying inversion polymorphisms using single nucleotide polymorphism (SNP) data.
  • To estimate the frequency of inversion polymorphisms in populations.
  • To overcome limitations of existing methods for detecting copy-neutral variants.

Main Methods:

  • Developed a probabilistic model treating populations as mixtures of forward and inverted chromosomes.
  • Identified inversions by analyzing characteristic differences in haplotype frequencies around breakpoints.
  • Utilized readily available SNP data, avoiding the need for whole genome sequencing.

Main Results:

  • Accurately predicted inversions with population frequencies as low as 25% in simulated data.
  • Reliably estimated inversion frequencies across a wide range.
  • Identified 88–142 inversion polymorphisms in human HapMap Phase 2 data with frequencies from 20% to 81%.

Conclusions:

  • The developed method effectively identifies inversion polymorphisms and estimates their frequencies using SNP data.
  • Many identified inversions align with known variants or have supporting evidence.
  • The findings contribute to a better understanding of structural variation in the human genome.