High-throughput methods for detection of genetic variation

Understanding human genetic variation is currently believed to reveal the cause of individual susceptibility to disease and the large variation observed in response to treatment. In this review, we will focus on different approaches to identify and visualize genetic alterations. The various approach...

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Veröffentlicht in:BioTechniques. - 1988. - 30(2001), 2 vom: 09. Feb., Seite 318-22, 324, 326 passim
1. Verfasser: Kristensen, V N (VerfasserIn)
Weitere Verfasser: Kelefiotis, D, Kristensen, T, Børresen-Dale, A L
Format: Aufsatz
Sprache:English
Veröffentlicht: 2001
Zugriff auf das übergeordnete Werk:BioTechniques
Schlagworte:Journal Article Research Support, Non-U.S. Gov't DNA 9007-49-2
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520 |a Understanding human genetic variation is currently believed to reveal the cause of individual susceptibility to disease and the large variation observed in response to treatment. In this review, we will focus on different approaches to identify and visualize genetic alterations. The various approaches for allele discrimination are formally systematically divided into (i) enzymatic approaches, in which the properties of different enzymes to discriminate between nucleotides are used (restriction enzymes type II, Cleavase and Resolvase, DNA polymerase, and ligase); (ii) electrophoretic methods, in which the allele discrimination is based on the difference in mobility in polymeric gels or capillaries (single- and double-stranded conformation assays, heteroduplex analysis, and DNA sequencing); (iii) solid-phase determination of allelic variants, including high-density oligonucleotide arrays for hybridization analysis, minisequencing primer extension analysis, and fiberoptic DNA sensor array; (iv) chromatographic methods such as denaturing high-performance liquid chromatography (DHPLC); (v) other physical methods of discrimination of allelic variants such as mass spectrometry (mass and charge) or fluorescence exchange-based techniques; and (vi) in silico methods such as high-throughput analysis of expressed sequence tag data. The most frequently used techniques and instrumental settings applied in different combinations are described, and other methods that are less broadly used but have interesting potentials are discussed 
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