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RNA Sequencing
With the recognition of importance of RNA metabolism for brain function, as well
as malfunction, there is an interest in understanding post-transcriptional gene regu-
lation through many new and recently discovered mechanisms. Earlier transcrip-
tomics studies were mostly based on hybridization-based microarray technologies
and offered a limited ability to fully catalogue and quantify the diverse RNA mole-
cules that are expressed from genomes over wide ranges of levels. Introduction of
high-throughput NGS technologies have revolutionized transcriptomics by enabling
RNA analysis through cDNA sequencing at massive scale (RNA-seq). This devel-
opment has overcome several challenges posed by microarray technologies, includ-
ing the limited dynamic range of detection (Ozsolak and Milos 2011 ). NGS
platforms used for RNA-seq are commercially available from several companies,
whereas new technologies are in development by others.
RNA-seq is a powerful tool for studying the effect of the transcriptome on phe-
notypes such as disease susceptibility, cancer progression and response to pharma-
ceuticals. Applications include the following:
- Transcript identifi cation: mapping results reveal the identity of transcripts pres-
ent in a sample, with ability to detect rare transcripts by increasing sequencing
depth. - Splice variant analysis: relative expression of exons across a single transcript can
elucidate the presence of splice variants. - Differential expression: differential expression levels of two transcripts in a sin-
gle sample or of a single transcript in two disparate samples can be ascertained
from relative sequencing depths. - RNA measurements for clinical diagnostics, e.g. analysis of circulating extracel-
lular nucleic acid and cells, such as fetal RNA. By enabling earlier diagnosis,
disease recurrence or mutational status, this will help realization of the full
potential of genomic information and its growing impact on the personalization
of healthcare.
Whole Exome Sequencing and Personalized Disease Risk
NGS is commonly used for researching the causes of genetic disorders. However,
its usefulness in clinical practice for medical diagnosis is in early development.
Replacing traditional methods for genetic testing of inheritable disorders with NGS
will reduce the cost of genetic testing and increase the information available for the
patients. NGS will become an invaluable resource for the patient and physicians,
especially if the sequencing information is stored properly and reanalyzed as bioin-
formatics tools and annotations improve. NGS is still at the early stages of develop-
ment, and it is full of false-positive and -negative results and requires infrastructure
and specialized personnel to properly analyze the results.