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At their core, microarrays are simple devices used for measuring the relative concentrations of many different DNA or RNA sequences. While they have been incredibly useful in a wide variety of applications but they have a number of limitations.
First limitation is that arrays provide an indirect measure of relative concentration. That is the signal measured at a given position on a microarray is typically assumed to be proportional to the concentration of a presumed single species in solution that can hybridize to that location. However, due to the kinetics of hybridization, the signal level at a given location on the array is not linearly proportional to concentration of the species hybridizing to the array. At high concentrations the array will become saturated and at low concentrations, equilibrium favors no binding. Hence, the signal is linear only over a limited range of concentrations in solution.
Second, especially for complex mammalian genomes, it is often difficult (if not impossible) to design arrays in which multiple related DNA/RNA sequences will not bind to the same probe on the array. A sequence on an array that was designed to detect “gene A”, may also detect “genes B, C and D” if those genes have significant sequence homology to gene A. This can particularly problematic for gene families and for genes with multiple splice variants. It should be noted that it is possible to design arrays specifically to detect splice variants either by making array probes to each exon in the genome or to exon junctions. However, it is difficult to design arrays that will uniquely detect every exon or gene in genomes with multiple related genes.
Finally, a DNA array can only detect sequences that the array was designed to detect. That is, if the solution being hybridized to the array contains RNA or DNA species for which there is no complimentary sequence on the array, those species will not be detected. For gene expression analysis, this typically means that genes that have not yet been annotated in a genome will not be represented on the array. Moreover, non-coding RNA’s that aren't yet discovered as expressed are usually not represented on an array. In addition, for great variable genomes such as those from bacteria, arrays are mostly designed using data from the genome of a reference strain. Such, arrays may be missing a large fraction of the genes present in a given isolate of the same species. For example, in the bacterial species Aggregatibacteractinomycetemcomitans, the gene content differs by as much as twenty perc (20%) between any two isolates. Therefore, an array formed using gene annotation from a “reference isolate” will not consist many of the genes found in other isolates.
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