**5. MicroRNA biogenesis in human cells**

MiRNAs are mostly transcribed from intragenic or intergenic regions by RNA polymerase II into primary transcripts (pri-miRNAs) of variable length (1 kb- 3 kb). In the nucleus PrimiRNA transcript is further processed by the nuclear ribo-nuclease enzyme 'Drosha' thereby resulting in a hairpin intermediate of about 70–100 nucleotides, called pre-miRNA. The pre-miRNA is then transported out of the nucleus by a transporting protein exportin-5.

MicroRNAs are Novel Biomarkers for Detection of Colorectal Cancer 5

(UTR) of their target mRNAs. When miRNA and its target mRNA sequence show perfect complementarities, the RISC induces mRNA degradation. Should an imperfect miRNA– mRNA target pairing occur, translation into a protein is blocked (Bartel, et al, 2004 & 2009). Regardless of which of these two events occur, the net result is a decrease in the amount of the proteins encoded by the mRNA targets. Each miRNA has the potential to target a large number of genes (on average about 500 for each miRNA family). Conversely, an estimated 60% of the mRNAs have one or more evolutionarily conserved sequences that are predicted to interact with miRNAs (Friedman, et al, 2009). MiRNAs have been shown to bind to the open reading frame or to the 5′ UTR of the target genes and, in some cases, they have been shown to activate rather than to inhibit gene expression (Ørom, et al, 2008). It has also reported that miRNAs can bind to ribonucleoproteins in a seed sequence and a RISCindependent manner and then interfere with their RNA binding functions (decoy activity) (Eiring, et al, 2010). MiRNAs can also regulate gene expression at the transcriptional level by

binding directly to the DNA (Khraiwesh, et al, 2010) as illustrated in Figure 1.

Numerous approaches have been developed to analyze and quantify the expression of miRNAs. A commonly adopted strategy is to perform mass scale expression profiling/signature of miRNAs on a small cohort of patients to identify most significantly dysregulated miRNAs. Expression profiling is usually followed by a validation of selected miRNAs on an independent cohort by using QRT-PCR. Expression profiling has been performed using Hybridization-Microarray, Real Time Polymerase Chain Reaction (QRT-PCR) Array and most recently Deep-Sequencing (Meyer, et al, 2010). Most of these approaches are developed against the gold standard 'Northern Blotting'. Each has its unique advantages and disadvantages, such as throughput, sensitivity, ease of use and cost. QRT-PCR can detect very low concentrations of molecules with much superior sensitivity and expenditure of time and money (Chen, et al, 2005). Microarray-based techniques have the advantage of being relatively cost-effective, quick and simple to utilize (Pradervand, et al, 2010). Ultra high throughput miRNA sequencing allows denovo detection and relative quantification of miRNAs, but requires a considerable amount of time and cost for data generation and data analysis (Wang, et al, 2007). A key issue of miRNA detection and quantification is the selection of endogenous controls for relative quantification. In QRT-PCR based detection systems, several small nuclear and small nucleolar RNAs (e.g. RNU6B) are recommended for normalising miRNA expression signature/profiles in tissues, cell lines, and human body fluids. However, RNU6B is heat unstable and rapidly degrades resulting in poor reproducibility of experiments. That's why many researchers have used the invariant and most stable miRNAs as endogenous controls (Meyer, et al, 2010). In order to overcome this problem of normalization in QRT-PCR and other detection systems, researchers have used different statistical strategies including: global mean expression; quantile; scaling; and normalizing factor. However, some normalization methods have been challenged whereas others were adapted to the specific nature of miRNA profiling experiments. At present, there is no generally agreed normalization strategy for any of the known detection approaches. Table 2 shows the comparison of different detection systems by practical application, throughput, cost and

**7. Methods of MicroRNA analysis and quantification** 

time expenditure.

In the cytoplasm, the pre-miRNA is once again processed by another ribonuclease enzyme 'Dicer' into a mature double-stranded miRNA. The two strands of double stranded miRNA (miRNA/miRNA\* complex) are separated by Dicer processing. After strand separation, the mature miRNA strand (miRNA- also called the guide strand) is incorporated into an RNAinduced silencing complex (RISC), whereas the passenger strand, denoted with a star (miRNA\*) is commonly degraded (Hammond, et al, 2000, Lee, et al, 2003, Bohnsack, et al, 2004 & Thimmaiah, et al, 2005). This miRNA/RISC complex is responsible for miRNA function. If on miRNA cloning or array the passenger strand is found at low frequency (less than 15% of the guide strand) it is named miR\*. However, if both passenger and guide strand are equal in distribution, then these two strands are named 3p and 5p version of miRNA depending on their location to either 5' or 3' of the miRNA molecule. In this case both strands can potentially incorporate in RISC complex and have a biological role. Nevertheless, quite a few miRNA\* strands are found to be conserved and play an important role in cell homeostasis. However, only recently studies have focussed on the functional role of the miRNA\* strand. Well-conserved miRNA\* strands may prove important links in cancer regulation networks (Stark, et al, 2007, Okamura, et al, 2008, Zhou, et al, 2010 & Guo, et al, 2010). Figure 1 illustrates the biogenesis of miRNAs in the cellular nucleous, its transport to cytoplasm, and processing by Drosha and Dicer Enzymes. Figure 1 also illustrates the RISC incorporation of miRNAs for functional activity in different pathways of translational inhibition or activation.

Fig. 1.
