Comparing whole genomes using DNA microarrays

Abstract

The rapid accumulation of complete genomic sequences offers the opportunity to carry out an analysis of inter- and intra-individual genome variation within a species on a routine basis. Sequencing whole genomes requires resources that are currently beyond those of a single laboratory and therefore it is not a practical approach for resequencing hundreds of individual genomes. DNA microarrays present an alternative way to study differences between closely related genomes. Advances in microarray-based approaches have enabled the main forms of genomic variation (amplifications, deletions, insertions, rearrangements and base-pair changes) to be detected using techniques that are readily performed in individual laboratories using simple experimental approaches.

MR connectomics: Principles and challenges

“…We entered the twenty first century with the capacity to map any person's individual genetic profile (Gresham et al, 2008;Hutchison, 2007). This genomic information serves, at individual and at population levels, as a structural scaffold that helps us understanding, characterizing and predicting normal and pathologic function at multiple levels like the transcriptional, proteomic, cellular and systemic level (Mo and Palsson, 2009).…”

The ‘thousand-dollar genome’: an ethical exploration

“…20 Such an array can, for example, be designed to specifically look for genetic factors known to play a role in the development of hereditary heart disease and the successful treatment thereof. 21,22 that may explain the condition.…”

Utilization of the oncoscan microarray assay in cancer diagnostics

“…CMA can be divided into two major categories [2]: first is a two-color experiment also referred to as array Comparative Genomic Hybridization (aCGH), in which patient and normal samples are differentially labeled and hybridized to probes on a single microarray, and second is a one-color experiment also known as single nucleotide polymorphism (SNP)-based microarray or SNP-array in which instead of including a control sample as a reference in every run, reference intensity data has been built from a population of normal samples and used as a reference for the patient sample [4]. The two-color analysis generates results as a signal ratio, while most of the one-color assays provide absolute signal intensity information [2]. The aCGH consists of CNV probes, while SNP-arrays have mainly SNP probes.…”

“…Chromosomal microarray analysis (CMA) enables simultaneous detection of variations in cancers at a genome-wide level, compared to detection of a limited number of genes and gene variants by fluorescence in situ hybridization (FISH), realtime-PCR, and Sanger sequencing [2,3]. CMA can be divided into two major categories [2]: first is a two-color experiment also referred to as array Comparative Genomic Hybridization (aCGH), in which patient and normal samples are differentially labeled and hybridized to probes on a single microarray, and second is a one-color experiment also known as single nucleotide polymorphism (SNP)-based microarray or SNP-array in which instead of including a control sample as a reference in every run, reference intensity data has been built from a population of normal samples and used as a reference for the patient sample [4].…”