Detection of deleted genomic DNA using a semiautomated computational analysis of GeneChip data

Salamon, H., Kato-Maeda, M., Small, P. M., Drenkow, J., Gingeras, T. R. (2000) Detection of deleted genomic DNA using a semiautomated computational analysis of GeneChip data. Genome Research, 10 (12). pp. 2044-2054. ISSN 10889051 (ISSN)

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URL: http://www.ncbi.nlm.nih.gov/pubmed/11116098
DOI: 10.1101/gr.GR-1529R

Abstract

Genomic diversity within and between populations is caused by single nucleotide mutations, changes in repetitive DNA systems, recombination mechanisms, and insertion and deletion events. The contribution of these sources to diversity, whether purely genetic or of phenotypic consequence, can only be investigated if we have the means to quantitate and characterize diversity in many samples. With the advent of complete sequence characterization of representative genomes of different species, the possibility of developing protocols to screen for genetic polymorphism across entire genomes is actively being pursued. The large numbers of measurements such approaches yield demand that we pay careful attention to the numerical analysis of data. In this paper we present a novel application of an Affymetrix GeneChip to perform genome-wide screens for deletion polymorphism. A high-density oligonucleotide array formatted for mRNA expression and targeted at a fully sequenced 4.4-million-base pair Mycobacterium tuberculosis standard strain genome was adapted to compare genomic DNA. Hybridization intensities to 111,000 probe pairs (perfect complement and mismatch complement) were measured for genomic DNA from a clinical strain and from a vaccine organism. Because individual probe-pair hybridization intensities exhibit limited sensitivity/specificity characteristics to detect deletions, data-analytical methodology to exploit measurements from multiple probes in tandem locations across the genome was developed. The TSTEP (Tandem Set Terminal Extreme Probability) algorithm designed specifically to analyze the tandem hybridization measurements data was applied and shown to discover genomic deletions with high sensitivity. The TSTEP algorithm provides a foundation for similar efforts to characterize deletions in many hybridization measures in similar-sized and larger genomes. Issues relating to the design of genome content screening experiments and the implications of these methods for studying population genomics and the evolution of genomes are discussed.

Item Type: Paper
Uncontrolled Keywords: bacterial DNA messenger RNA Mycobacterium vaccine nucleotide repetitive DNA algorithm article automation base pairing calculation clinical protocol data analysis DNA hybridization DNA microarray DNA probe gene deletion gene insertion gene mutation genetic polymorphism genetic recombination genome measurement Mycobacterium tuberculosis nonhuman phenotype priority journal sensitivity and specificity Tandem Set Terminal Extreme Probability Algorithms Computational Biology DNA, Bacterial Genes, Bacterial Genome, Bacterial Mycobacterium bovis Oligonucleotide Array Sequence Analysis Sequence Deletion Actinobacteria (class) Bacteria (microorganisms) Mycobacterium uncultured actinomycete
Subjects: bioinformatics > genomics and proteomics > annotation > sequence annotation
bioinformatics > computational biology
bioinformatics > genomics and proteomics > genetics & nucleic acid processing > DNA, RNA structure, function, modification > mRNA dynamics
bioinformatics > genomics and proteomics > genetics & nucleic acid processing > DNA, RNA structure, function, modification > mutations
CSHL Authors:
Communities: CSHL labs > Gingeras lab
Depositing User: CSHL Librarian
Date: 2000
Date Deposited: 13 Mar 2012 15:03
Last Modified: 27 Mar 2014 20:25
PMCID: PMC313082
Related URLs:
URI: http://repository.cshl.edu/id/eprint/25278

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