Open Access Methodology article

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

Eric J Belfield1, Carly Brown1, Xiangchao Gan123, Caifu Jiang1, Dilair Baban2, Aziz Mithani14, Richard Mott2, Jiannis Ragoussis25 and Nicholas P Harberd1*

Author Affiliations

1 Department of Plant Sciences, University of Oxford, South Parks Road, Oxford OX1 3RB, UK

2 Wellcome Trust Centre for Human Genetics, University of Oxford, Roosevelt Drive, Oxford OX3 7BN, UK

3 Max Planck Institute for Plant Breeding Research, Carl-von-Linné-Weg, Cologne 50829, Germany

4 Department of Biology, LUMS School of Science and Engineering, Sector U-DHA, Lahore 54792, Pakistan

5 McGill University and Genome Quebec Innovation Centre, 740 DR Penfield Ave, Montreal H3A 0G1, Canada

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BMC Genomics 2014, 15:224  doi:10.1186/1471-2164-15-224

Published: 22 March 2014



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.


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.


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.

Mutation; Deletion; Microarray; Genome; Comparative genomic hybridization; Probe density