• Animal Bioscience
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• v.34 no.8
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• pp.1271-1282
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• 2021

Genome-wide studies provide considerable insights into the genetic background of animals; however, the inheritance of several heritable factors cannot be elucidated. Epigenetics explains these heritabilities, including those of genes influenced by environmental factors. Knowledge of the mechanisms underlying epigenetics enables understanding the processes of gene regulation through interactions with the environment. Recently developed next-generation sequencing (NGS) technologies help understand the interactional changes in epigenetic mechanisms. There are large sets of NGS data available; however, the integrative data analysis approaches still have limitations with regard to reliably interpreting the epigenetic changes. This review focuses on the epigenetic mechanisms and profiling methods and multi-omics integration methods that can provide comprehensive biological insights in animal genetic studies.

• Biomedical Science Letters
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• v.21 no.4
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• pp.181-187
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• 2015

Osteoporosis is one of the diseases caused by accumulation of effects from complex interactions between genetic and environmental factors. Aging is the major cause for osteoporosis, which normally increases skeletal fragility and bone fracture especially among the elder. "Omics" refers to a specialized research field dealing with high-throughput biological data, such as genomics, transcriptomics, proteomics or metabolomics. Integration of data from multi-omics has been approved to be a powerful strategy to colligate biological phenomenon with multiple aspects. Actually, integrative analyses of "omics" datasets were used to present pathogenesis of specific diseases or casual biomarkers including susceptible genes. In this study, we evaluated the proposed relationship of novel susceptible genes (TREML2, HTR1E, and GLO1) with osteoporosis, which genes were obtained using multi-omics integration analyses. To this end, SNPs of the susceptible genes in the Korean female cohort were analyzed. As a result, one SNP of HTR1E and five SNPs of TREML2 were identified to associate with osteoporosis. The highest significant SNP was $rs6938076^*$ of TREML2 (OR=0.63, CI: 0.45~0.89, recessive P=0.009). Consequently, the susceptible genes identified through the multi-omics analyses were confirmed to have association with osteoporosis. Therefore, multi-omics analysis might be a powerful tool to find new genes associated with a disease. We further identified that TREML2 has more associated with osteoporosis in females than did HTR1E.

• BMB Reports
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• v.53 no.6
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• pp.299-310
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• 2020

Chronic liver disease progresses through several stages, fatty liver, steatohepatitis, cirrhosis, and eventually, it leads to hepatocellular carcinoma (HCC) over a long period of time. Since a large proportion of patients with HCC are accompanied by cirrhosis, it is considered to be an important factor in the diagnosis of liver cancer. This is because cirrhosis leads to an irreversible harmful effect, but the early stages of chronic liver disease could be reversed to a healthy state. Therefore, the discovery of biomarkers that could identify the early stages of chronic liver disease is important to prevent serious liver damage. Biomarker discovery at liver cancer and cirrhosis has enhanced the development of sequencing technology. Next generation sequencing (NGS) is one of the representative technical innovations in the biological field in the recent decades and it is the most important thing to design for research on what type of sequencing methods are suitable and how to handle the analysis steps for data integration. In this review, we comprehensively summarized NGS techniques for identifying genome, transcriptome, DNA methylome and 3D/4D chromatin structure, and introduced framework of processing data set and integrating multi-omics data for uncovering biomarkers.