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Microarray-based ultra-high resolution discovery of genomic deletion mutations.


ABSTRACT:

Background

Oligonucleotide microarray-based comparative genomic hybridization (CGH) offers an attractive possible route for the rapid and cost-effective genome-wide discovery of deletion mutations. CGH typically involves comparison of the hybridization intensities of genomic DNA samples with microarray chip representations of entire genomes, and has widespread potential application in experimental research and medical diagnostics. However, the power to detect small deletions is low.

Results

Here we use a graduated series of Arabidopsis thaliana genomic deletion mutations (of sizes ranging from 4 bp to ~5 kb) to optimize CGH-based genomic deletion detection. We show that the power to detect smaller deletions (4, 28 and 104 bp) depends upon oligonucleotide density (essentially the number of genome-representative oligonucleotides on the microarray chip), and determine the oligonucleotide spacings necessary to guarantee detection of deletions of specified size.

Conclusions

Our findings will enhance a wide range of research and clinical applications, and in particular will aid in the discovery of genomic deletions in the absence of a priori knowledge of their existence.

SUBMITTER: Belfield EJ 

PROVIDER: S-EPMC3998191 | biostudies-literature | 2014 Mar

REPOSITORIES: biostudies-literature

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Publications

Microarray-based ultra-high resolution discovery of genomic deletion mutations.

Belfield Eric J EJ   Brown Carly C   Gan Xiangchao X   Jiang Caifu C   Baban Dilair D   Mithani Aziz A   Mott Richard R   Ragoussis Jiannis J   Harberd Nicholas P NP  

BMC genomics 20140322


<h4>Background</h4>Oligonucleotide microarray-based comparative genomic hybridization (CGH) offers an attractive possible route for the rapid and cost-effective genome-wide discovery of deletion mutations. CGH typically involves comparison of the hybridization intensities of genomic DNA samples with microarray chip representations of entire genomes, and has widespread potential application in experimental research and medical diagnostics. However, the power to detect small deletions is low.<h4>R  ...[more]

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