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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,...
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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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Infinium Assay for Large-scale SNP Genotyping Applications
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Identification of polymorphic inversions from genotypes.

Alejandro Cáceres1, Suzanne S Sindi, Benjamin J Raphael

  • 1Center for Research in Environmental Epidemiology, and Institut Municipal d'Investigació Mèdica, Barcelona 08003, Spain. acaceres@creal.cat

BMC Bioinformatics
|February 11, 2012
PubMed
Summary
This summary is machine-generated.

This study introduces a new computational method to identify and classify polymorphic inversions using genome-wide genetic data. The approach accurately determines inversion status in individuals, improving genetic variability studies and association analyses.

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Area of Science:

  • Genetics
  • Bioinformatics
  • Computational Biology

Background:

  • Polymorphic inversions are key sources of genetic variation influencing recombination rates.
  • Experimental study of inversions is challenging, necessitating computational approaches.
  • Existing computational methods struggle with accurate individual classification, hindering association studies.

Purpose of the Study:

  • To develop a novel computational method for identifying polymorphic inversions from genome-wide genotype data.
  • To accurately classify individuals into normal or inverted allele groups.
  • To enhance the utility of inversion detection for genome-wide association studies (GWAS).

Main Methods:

  • A generalized method utilizing SNP linkage to partition individuals into subpopulations based on inversion status.
  • A sliding window scan approach to pinpoint potential inversion regions.
  • Accumulation of evidence from neighboring SNPs for precise individual inversion status determination.

Main Results:

  • The method accurately detects inversions and classifies individuals using simulated and real genotype data.
  • Applied to HapMap Phase III data, it characterized known inversions in specific chromosomal regions.
  • Genome-wide scans identified population-based evidence for 9/15 known autosomal inversions and 52 predicted regions.

Conclusions:

  • The developed method accurately identifies polymorphic inversions and classifies individuals.
  • It is directly applicable to genotype data, increasing usability for GWAS.
  • An R package, inveRsion, provides efficient implementations for both genotype and haplotype methods.