Characterization of RNA - Animal Models of Acute Neurological Injuries: Injury and Mechanistic Assessments - page 141

3.2. High-Throughput
RNA Sequencing

High-throughput or deep sequencing is a relatively new application
that can be used to characterize and quantify RNA in a massively
parallel fashion. Sequencing has advantages over other methods
discussed in this chapter, for example, both the estimation of alter-
native splicing and unbiased transcript discovery within a single
experiment making it the future of profi ling at both the RNA and
DNA level.
Currently, high-throughput sequencing technologies are
offered by only a handful of companies. Though usage of this
technology is becoming widespread, it may be considered in its
infancy compared to the other RNA analysis methods discussed in
this chapter. Thus, protocols remain platform specifi c and subject
to frequent revisions, concomitant with the rapid pace of innova-
tion of next-generation sequencing. We may however discuss the
methodologies, and general techniques that are common to any
RNA sequencing experiment (RNAseq). A comprehensive compari-
son of the current competing technologies has been covered else-
where ( 39-41 ), but put simply, the defi ning feature that distinguishes
high-throughput sequencing from traditional Sanger sequencing is
its basis in the production and assembly of vast numbers of short
(26-300 nt) sequences. Choosing to utilize RNAseq over the other
profi ling methods discussed here yields many advantages, with the
most obvious being sensitivity. Comparing RNAseq and the most
common profi ling technology available (microarrays) makes it clear
that RNAseq has little, to no signal attributable to background
noise, as the presence of a single unique sequence fragment among
millions of others indicates the presence of the “parent” RNA in
the original sample ( 42 ). Concomitantly, RNAseq does not have
an upper limit for detection and quantifi cation while array-based
platforms may reach saturation of their probes. Nevertheless, the
expense and low sample throughput of this technology will not
make it suitable for all RNA profi ling studies. In this chapter, we
outline the key concepts involved in an RNAseq experiment.

To date there are fi ve major platforms available for RNA
sequencing: The Genome Analyzer (Illumina, CA), SOLiD3
(Applied Biosystems, CA), HeliScope (Helicos, MA), 454 (Roche,
CT) and the open source Polonator. Each read (or sequencing tag)
is short compared to conventional capillary-based sequencing.
Lengths differ across the platforms, but 26-330 nt reads are typical
(for a summary, see ref. ( 41 )). Traditionally, reads as short as this
would be considered a limitation, in terms of uniqueness and use-
fulness. This, however, is mostly absolved by the sheer weight of
numbers—from hundreds of thousands to tens of millions of reads
yielding massive redundancy and comprehensive coverage of most
expressed transcripts. Consequently, this generates 0.5-50 Gb of
data per sequencing run, which may take 2 days to greater than a
week of machine run time.

3.2.1. Materials
and Instruments

Available Platforms