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transcriptomics can be used to determine how the expression patterns of these transcripts
change under different conditions (such as disease or drug treatment) and to develop bio-
markers. The original emphasis on genome-wide mRNA transcript profiling is now exten-
sively applied to other areas of study, such as evaluating different biological functions,
understanding disease processes, the development of diagnostic markers, and therapeutic
targets
[38-40]
. Further complexity in the biology of the transcriptome is aided by alterna-
tive mRNA splicing, the effects of epigenetics and epigenomics on the regulation of tran-
scription, and posttranslational modifications. Various technologies have been developed to
deduce and quantify the transcriptome. Generally speaking, they can be divided into two
categories: hybridization-based and sequencing-based approaches.
6.3.1.1 Microarray Technology - Hybridization-based Approaches
Microarrays have been the stalwarts of high-throughput, genome-wide expression inves-
tigations since the mid-1990s
[41,42]
. This technology allows for rapid and simultaneous
monitoring of tens of thousands of gene expressions in a single experiment. With the aid of
sophisticated bioinformatics approaches, the amount of mRNA bound to the spots on the
microarray is precisely measured, generating a profile of gene expression in the cell. These
captured transcript changes reflect the activity of transcription across the whole genome at the
defined time to a given condition. It allows hypothesis-generating research without any prior
selection of candidate genes or gene sets.
Many commercial suppliers have made standard microarrays and analysis tools available
[43,44]
. The array platforms differ in design, manufacturing, hybridization, scanning, and
data handling
[45-47]
. Nonetheless, the technology has notable limitations
[48-51]
:
1.
It depends on existing knowledge about genome sequences and hence does not identify
novel mRNAs - i.e., transcripts absent from databases cannot be detected.
2.
It has a limited dynamic range, with the detection range limited by background for low
expression transcripts and by saturation in the high expression transcripts.
3.
Expression is indirectly measured as the scanned intensity of fluorescent hybridized
probes, a process that may require complex normalizations.
To this end, specialized microarrays have also been developed to study different types of
splicing, either to assess the effect of splicing events on transcript structure in a given sam-
ple or to compare the changes in transcript composition between two or more conditions
(differential alternative splicing). There are three main array types available to study splic-
ing, exon arrays
[52,53]
, tiling arrays
[54]
and exon-junction arrays
[55-58]
. They are briefly
described below:
●
Exon arrays have probes designed to identify all the known or predicted exons that are
expressed in a given cell or tissue sample
[59,60]
. They work similarly to gene expression
microarrays except regarding the number and distribution of probes along all exons.
These arrays have been used in recent years, not only to study splicing events but also as a
substitute for gene expression arrays, given that they also allow the measurement of global
expression using all probes
[53,61]
.
●
Genomic tiling arrays are designed to detect exon usage by setting contiguous matching
probes at fixed distances across the genomes. These arrays, representing the genome at
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