1. Introduction

RNAi [1] is an innate biological process in which RNA molecules inhibit gene expression or translation [2] by suppressing targeted mRNA molecules. Since the discovery of RNAi by

© 2019 The Author(s). Licensee IntechOpen. This chapter is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Andrew Fire and Craig Mello, it has become evident that RNAi has immense potential in suppression of desired genes [3]. The first evidence that double-stranded RNA (dsRNA) could achieve efficient gene silencing through RNAi came from studies on the nematode Caenorhabditis elegans [4] and Drosophila melanogaster [5], which lead toward understanding the biochemical nature of the RNAi pathway. Two types of small ribonucleic acid (RNA) molecules—microRNA (miRNA) and small interfering RNA (siRNA)—are central to RNAi [6]. To compare two types of elicit RNAi, the siRNA must be fully complementary to its target mRNA, whereas, miRNA only needs to be partially complementary to its target mRNA. In organisms like C. elegans and D. melanogaster, RNAi can be induced by introducing long dsRNA complementary to the target mRNA to be degraded, however, in mammalian cells and organisms, introducing dsRNA longer than 30 bp activates a potent antiviral response. To solve this limitation, siRNAs are used to induce RNAi in mammalian cells and organisms [7–9].

The discovery of both siRNA and miRNA provides a new therapeutic approach [10, 11] for the treatment of diseases by targeting genes that have undesired mutated or overexpression of normal genes. The RNAi Process is as following. SiRNAs that induce the degradation of specific endogenous is very common phenomenon in eukaryotic cells to inhibit protein production at post transcriptional level [12]. The RNAi process is initiated by short dsRNAs, 21–25 nucleotides that lead to the sequence specific inhibition of their homologous mRNAs. These siRNAs are normally produced in cells from cleavage of longer dsRNA precursors by Dicer that is a ribonuclease III family member. The cleaved parts are incorporated into a multicomponent nuclease complex known as the RNA-induced silencing complexes (RISC), which contain the splicing protein Argonaute-2 (Ago-2) [13]. The ssRNA derived from the short dsRNA acts as a antisense strand directing the complex to the specific target mRNA; in where a RISC-associated endoribonuclease cleavages the target mRNA [14]. Therapeutic approaches based on siRNA involve the introduction of a synthetic siRNA into the target cells to elicit RNAi, thereby inhibiting the expression of a specific messenger RNA (mRNA) to produce a gene silencing effect [15]. RNAi is beneficial in accelerating cures in medicine, especially when a disease is thought to due to a defective gene [16]. For historical perspective, the first application of RNAi therapy was in age-related macular degeneration (AMD) by using siRNAs to suppress the vascular endothelial growth factor (VEGF) pathway that causes abnormal growth of blood vessels behind the retina, carried out directly to the patient's eye [17]. RNAi techniques have been used against the spread of tumor growth and increasing its sensitization toward drug treatment, RNAi technology will be beneficial to selectively affect cancer cells without damaging normal cells as the RNAi therapy against cancer cells is used for directly targeting the oncogenes; and therefore, found to stop progression and invasion of the tumor cells [18, 19] and also increase the sensitization of tumor against drug, as mentioned earlier [20]. As RNAi can silence disease-associated genes in tissue culture and animal models, the development of RNAi-based reagents for therapeutic applications involves technological enhancements that improve siRNA stability and delivery in vivo [21], while minimizing offtarget and nonspecific effects.

A number of different approaches have been developed for the in vivo delivery of siRNA, among which, rapid infusion by hydrodynamic injection of siRNA achieves the best delivery in rodents [22]. However, this way, the delivery is restricted to highly vascularized tissues, such as the liver [23] and also, it is currently not a viable method for delivery in human clinical studies. Lipid-based in vivo applications have been devised [24], which have been used extensively for cell culture experiments, with some issues, like the cationic nature of the lipids used in cell culture leads to aggregation when used in animals and results in rapid serum clearance and lung accumulation. Even then, there are an increasing number of reports citing success with lipid-mediated delivery of siRNAs in vivo. To improve the delivery of siRNA into human liver cells [25] without transfection agents, lipophilic siRNAs were conjugated with derivatives of cholesterol, lithocholic acid, or lauric acid, where the lipid moieties were covalently linked to the 5<sup>0</sup> -ends of the RNAs using phosphoramidite chemistry [26]. These could down-regulate the expression of a LacZ expression construct. By conjugating cholesterol to the 3<sup>0</sup> -end of the sense strand of siRNA by means of a pyrrolidine linker, the pharmacological properties of siRNA molecules was improved by Soutschek et al. [27]. Advantages of cholesterol attachments are evident as being more resistant to nuclease degradation, more stable in the blood by increasing binding to human serum albumin and increased uptake of siRNA molecules by the liver. Intravascular delivery of siRNA molecules is a very simple technique, which was used to protect mice from fulminant hepatitis using siRNAs against Fas receptors by Song et al. [28], who administer Fas siRNA by intravenous injection into mice over a 24-hour period. The authors could show the persist effects for 10 days and protected mice against experimentally induced liver fibrosis. Local delivery of siRNAs have also been tried into the eye to target the VEGF pathway and shown that it could be therapeutically beneficial in neovascularizationrelated eye diseases. SiRNA topical gels have also been used to deliver them to cells in dermatological applications and cervical cancer treatment [29]. Gene gun method was used for an intradermal administration of nucleic acids to enhance cancer vaccine potency [30]. The other technique is an electroporation, which has been used to deliver siRNAs into the brain [31] and muscles of rodents. Injecting viral vectors for the in vivo delivery of siRNA directly have been tried, where an adeno-associated virus (AAV) associated shRNA vector injected directly into the midbrain neurons of adult mice to silence of the tyrosine hydroxylase gene near the site of injection for several weeks. However, there exist an alternative to injection, called as an ex vivo approach to generate human immunodeficiency virus (HIV)-1-resistant lymphocytes and macrophages [32]. It was accomplished through using a lentiviral vector, an anti-rev siRNA construct into CD34(+) hematopoietic progenitor cells. The siRNA-transduced progenitor cells were allowed to mature into macrophages in vitro and T-cells in vivo, [33].

Many machine learning, bio-statistical [34] and association rule mining methods [35] are available that have been developed to solve different problems related to gene silencing and disease discovery. In this book chapter, we provided a comprehensive survey of different machine learning and association rule mining algorithms developed for tackling various biological challenges such as detection of gene signature, biomarker, gene module, potentially disordered protein detection, differentially methylated region, multi-omics data integration, etc. We also described a comparative study of different well-known classifiers along with other used methods for the study. Meanwhile, many gene module discovery based approaches are also developed that employs several machine learning, deep learning and soft computing approaches. In addition, many multi-objective algorithms are also developed to find optimal multi-omics genetic signatures for the respective disease. Furthermore, we demonstrated the

Figure 1. Flowchart of the RNAi mechanism [37, 38].

brief biological information regarding the immense biological challenges for gene activation and their advantages, disadvantages and possible therapeutic strategies. There are certain challenges exist, such as off-target effects, cytotoxicity, need for efficient delivery methods, their clinical implementation need efficient delivery vehicles and siRNA activity, itself, nonspecific gene silencing, activation of innate immune system, the lack of efficient in vivo delivery systems still remain to be handled. Apart from these challenges, the development of efficient tissue-specific and differentiation dependent expression of siRNA is essential for transgenic and therapeutic approaches. However, there are successful in vitro and in vivo experiments for raising hopes in treating human diseases with RNAi [36]. Moreover, our study is useful for the researchers to understand the central idea about RNAi and gene silencing, along with the current machine/deep learning and association rule mining algorithms related to these (Figure 1).
