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2014 ; 116
(ä): 1-19
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Introduction to sequencing the brain transcriptome
#MMPMID25172469
Hitzemann R
; Darakjian P
; Walter N
; Iancu OD
; Searles R
; McWeeney S
Int Rev Neurobiol
2014[]; 116
(ä): 1-19
PMID25172469
show ga
High-throughput next-generation sequencing is now entering its second decade.
However, it was not until 2008 that the first report of sequencing the brain
transcriptome appeared (Mortazavi, Williams, Mccue, Schaeffer, & Wold, 2008).
These authors compared short-read RNA-Seq data for mouse whole brain with
microarray results for the same sample and noted both the advantages and
disadvantages of the RNA-Seq approach. While RNA-Seq provided exon level
resolution, the majority of the reads were provided by a small proportion of
highly expressed genes and the data analysis was exceedingly complex. Over the
past 6 years, there have been substantial improvements in both RNA-Seq technology
and data analysis. This volume contains 11 chapters that detail various aspects
of sequencing the brain transcriptome. Some of the chapters are very methods
driven, while others focus on the use of RNA-Seq to study such diverse areas as
development, schizophrenia, and drug abuse. This chapter briefly reviews the
transition from microarrays to RNA-Seq as the preferred method for analyzing the
brain transcriptome. Compared with microarrays, RNA-Seq has a greater dynamic
range, detects both coding and noncoding RNAs, is superior for gene network
construction, detects alternative spliced transcripts, and can be used to extract
genotype information, e.g., nonsynonymous coding single nucleotide polymorphisms.
RNA-Seq embraces the complexity of the brain transcriptome and provides a
mechanism to understand the underlying regulatory code; the potential to inform
the brain-behavior-disease relationships is substantial.
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