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Human genome has been predicted to consist 69,073 genes,
of which an estimated 48,400 genes are believed to be transcribed,
out of which 22,740 transcripts are expected to be translated
into known and novel protein (www.ensembl.org). Extensive
informatics about the genome sequence of several species
has been accumulated so far and overlaps between such gene
and protein sequences across various species have also been
computed. As informatics about genomes continue to expand,
the utility for such data-pools is becoming realized as
it is becoming a need for functional genomics. Therefore,
the emerging trend in biological research is to perform
genomic level studies rather than traditional focused biology.
With a host of tools to perform and analyze genomic level
experiments, systems level pursuits have become easier,
allowing the interrogation of various complexities of cellular
function, and with the integration of computer science,
systems biologists are now able to deduce meaningful conclusions
at a whole genome level. Technological innovations modernized
systems biology by imparting powerful high-throughput platforms,
such as the microarray technologies allowing the analysis
of genes, transcripts, protein and gene-protein interactions
(Chip array), two hybrid technology for protein-protein
interaction, mass spectrometry for protein modification
and RNA interference (RNAi) for `loss of function' analyses
(Ivakhno, 2007). Of these genomic platforms, RNAi has an
arguable advantage, as it allows the direct assignation
of a phenotype to a gene. As such, this can provide novel
insights as to the relevance of the gene in the process
of interest. Therefore, RNAi has been used for gene pathway
and drug target discovery (Haney, 2007a; Iorns et al., 2007;
and Gomase and Tagore, 2008), development of RNAi-based
transgenic mice (Gao and Zhang, 2007) and to be pursued
as a drug itself for gene therapy (Jagannath and Wood, 2007;
and Huang, 2008). However, the scope of this review is limited
to discuss some of the emerging trends relevant to the use
of RNAi technology for genome-wide screens and their impacts
in studying the biology of diseases.
The biology of RNA interference was described by Andrew
Fire and Criag Mello in 1998 (Fire et al., 1998), who shared
the Nobel Prize for this discovery in 2006. RNAi is a biological
phenomenon by which gene expression is modulated by short
segments of RNA (21-22 nt) resulting in attenuated gene
expression (Elbashir et al., 2001). Earlier attempts to
block gene expression using antisense RNA triggered the
discovery of RNAi biology, since with antisense RNA, scientists
were intrigued to find that dsRNA was more potent in blocking
gene expression than just single stranded antisense stranded
RNA (Sen and Blau, 2006). This then led to studies to investigate
why a dsRNA can be more potent than a simple antisense RNA,
which directly complements the target mRNA sequence. Such
efforts resulted in an astounding discovery that RNAi is
a biological mechanism that regulates gene function routinely
in the plant and animal kingdoms (Sen and Blau, 2006). Further,
detailed studies on RNAi mechanisms revealed that short
21-22 nt RNAs, which are products from dsRNA, were the direct
mediators of gene silencing, and therefore such short RNAs
were designated as `short interfering RNA' (siRNA) (Elbashir
et al., 2001). Introduction of synthetic siRNA was found
to effectively result in RNAi without eliciting an interferon
response in mammalian cells, the natural mechanism by which
mammals fight dsRNA viral infection (Gantier and Williams,
2007). siRNA, therefore, became a popular commercial reagent
to perform gene function studies.
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