R. Hitzemann∗,†,‡, D. Bottomly¶,P.Darakjian†,N. Walter†,‡, O. Iancu†, R. Searles§,B.Wilmot¶,††and S. McWeeney¶,∗∗,††
Advances in next-generation sequencing suggest that
RNA-Seq is poised to supplant microarray-based
approaches for transcriptome analysis. This article
briefly reviews the use of microarrays in the brain-
behavior context and then illustrates why RNA-Seq is a
superior strategy. Compared with microarrays, RNA-Seq
has a greater dynamic range, detects both coding and
noncoding RNAs, is superior for gene network construc-
tion, detects alternative spliced transcripts, detects allele
specific expression and can be used to extract geno-
type information, e.g. nonsynonymous coding single
nucleotide polymorphisms. Examples of where RNA-
Seq has been used to assess brain gene expression
are provided. Despite the advantages of RNA-Seq, some
disadvantages remain. These include the high cost of
RNA-Seq and the computational complexities associated
with data analysis. RNA-Seq embraces the complexity of
the transcriptome and provides a mechanism to under-
stand the underlying regulatory code; the potential to
inform the brain-behavior relationship is substantial.
Keywords: RNA-Seq, genetics, behavior, microarrays, brain
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