Copy-Number-Variation Microarrays in Basic Research and Clinical Applications
A special issue of BioTech (ISSN 2673-6284).
Deadline for manuscript submissions: closed (30 September 2013) | Viewed by 214
Special Issue Information
Over the last years microarray technology has greatly improved the fields of structural genetic research and chromosomal disorders. Established cytogenetic and molecular techniques suffer of low resolution, limited to 5–10 megabases, like Giemsa-banded chromosome analysis, or are restricted in detecting only a few specific DNA regions like fluorescence in situ hybridization. Oligonucleotide microarrays containing millions of probes enabled the detection of sub-microscopic structural genetic variations, genome-wide, at ultra-high resolution down to a few hundred till thousand bases. Although high coverage next generation DNA sequencing can detect structural genetic variations, microarray screening is expected to be the main approach for several years due to its user-friendly workflow, lower cost and straightforward data interpretation.
This special issue invites contributions to the application and evaluation of microarrays for the discovery and diagnosis of structural genetic variations with a focus on Copy Number Variations (CNVs). These variations account for a substantial proportion of genetic variability in human and animal populations and range from seemingly neutral polymorphisms over polymorphisms correlating with phenotypic differences to pathological variations predisposing or causing disease.
It will be interesting to the reader of this special issue to increase the understanding of how microarray technology helped revealing the biological meaning of CNVs but also to learn about recent advances in CNV calling, database aided classification, and CNV phenotype correlations.
Dr. Tobias Heckel
Guest Editor
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Keywords
- array Comparative Genomic Hybridization
- SNP genotyping arrays
- clinical cytogenetics
- chromosomal disorders
- CNV calling algorithms
- neurobehavioral phenotypes
- genomic instability
- genotype-phenotype correlations
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