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Epigenetics Research: Open Access

Genetics encompasses study of structure and function of genes; causative factors, physiological consequences of genetic variations as well as various other aspects of heredity. Genetic studies involve in depth analysis of diverse features of DNA and chromosomes, reproduction and heredity, recombination and genetic linkage, gene expression, the central dogma of life, genetic mutations, evolution, genomics and DNA sequencing. Genetics helps in comprehending the molecular aspects of various diseases and helps us to formulate specific treatment and management strategies. Scientists are currently engaged in finding the cure for chronic diseases by modifying the associated genes, a process referred to as gene therapy and it is speculated as the future of medical treatment practices.<br>Genetic mutation is a permanent change in the DNA. Mutations may or may not produce changes in the organism. Hereditary mutations and Somatic mutations are the two types of Gene mutations. Former types are inherited from the parents and are present in every cell of the human body whereas latter type may occur at some point of life time due to environmental factors.<br>Submit manuscript at: https://www.longdom.org/submissions/epigenetics-research-open-access.html or send as an e-mail attachment to the Editorial Office publisher@longdom.org<br>

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Epigenetics Research: Open Access

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  1. Ghani, J Epigenetics Res 2018, 1:1 EpigeneticsResearch:OpenAccess Epigenetics Research : Open Access Editorial Open Access Next-Generation Sequencing: The Future of Precise Medicine? Hamidah Ghani* Institute of Biological Sciences, University of Malaya, Malaysia In the recent years, NGS have opened a route to a new dimension of molecular study, enabling the determination of the nucleotides (A, In the last few years, there has been an increasing area to exploit the concepts of network biology to understand disease module. Disease module can be explained by the existence of specific regions for the disease proteins based on the network study. The identification of these modules is the starting point for the discovery of drug targets and has provided deep insights into the molecular level for underlying diseases mechanism. For example, network approaches form the big data analysis to identify disease module have successfully in Parkinson’s disease, progressive supranuclear palsy and cancer therapy. However, not all big data analysis can be directly translated into the clinical or drug developments due to the several factors such as experimental design, the total size of cohort study using patient and healthy control, and the relationship or the mechanism of the disease itself. This approach may need the larger collaboration of different research institutes and pharmaceutical industry depending on their expertise to help minimize costs and risks for drug developments, thus, lead to the precise medicine. C, G, and T) orders in the entire genome of the species and has helped researchers in their molecular genetic studies. These technologies cost- effective for the DNA sequencing since high throughput data yield can be produced in massively parallel technology involving simultaneous sequencing of a large number of template DNA. NGS describes platforms that produce large amounts (typically millions) of DNA reads, commonly known as short reads compared to the traditional Sanger sequencing method (150bp to 1,000 bp). NGS can be divided into three main categories for the human study; Whole-Genome Sequencing (WGS), Whole-Exome Sequencing (WES) and transcriptomic study (RNA-seq).The benefits of NGS have driven the clinical understanding of human physiology, anatomy and subsequently system biology of human diseases to a new dimension of study and thus have made significance improvements in monitoring the health treatment. The structure and nature of protein interaction networks is one of the best interests and is a considerable subject in the understanding of system biology, which is due to the availability of the dataset of protein interactions for the majority of protein study. Protein-Protein Interaction (PPI) networks act as a powerful tool for exploring protein functions and disease-gene relationship as shown in the Figure 1. This method may allow researchers to link the genes with their associated biological pathways and the corresponding diseases, which is used to improve the biomedical applications. Major advantages of studying PPI is may assign the unknown roles to uncharacterized proteins, availability of detailed information within a signaling pathway, and define the relationships between genes that arise from multi-molecular complexes. Network analysis may underline the existence of genes interaction harboring molecular alterations in common or rare diseases. However, one potential drawback of PPI is the underlying mechanisms of complex and rare diseases, which are come from the interaction of multiple genes with the environmental factors, cannot be revealed by such approaches. Figure 1: Example of genes network study:CD19 gene network representation showing more complex relationship between each gene. *Corresponding author: Hamidah Ghani, Institute of Biological Sciences, Faculty of Science, University of Malaya, 50603 Kuala Lumpur, Malaysia, Tel: (+06) 0139524623; E-mail: hamidah.ghani@siswa.um.edu.my Received: August 29, 2018; Accepted: August 30, 2018; Published: September 09, 2018 Citation: Ghani H (2018) Next-Generation Sequencing: The Future of Precise Medicine? J Epigenetics Res 1: e101. Copyright: © 2018 Ghani H. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. J Epigenetics Res, an open access journal Volume 1 • Issue 1 • 1000e101

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