• BMB Reports
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• v.37 no.1
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• pp.107-113
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• 2004

Since the completion of the genome project of the nematode C. elegans in 1998, functional genomic approaches have been applied to elucidate the gene and protein networks in this model organism. The recent completion of the whole genome of C. briggsae, a close sister species of C. elegans, now makes it possible to employ the comparative genomic approaches for identifying regulatory mechanisms that are conserved in these species and to make more precise annotation of the predicted genes. RNA interference (RNAi) screenings in C. elegans have been performed to screen the whole genome for the genes whose mutations give rise to specific phenotypes of interest. RNAi screens can also be used to identify genes that act genetically together with a gene of interest. Microarray experiments have been very useful in identifying genes that exhibit co-regulated expression profiles in given genetic or environmental conditions. Proteomic approaches also can be applied to the nematode, just as in other species whose genomes are known. With all these functional genomic tools, genetics will still remain an important tool for gene function studies in the post genome era. New breakthroughs in C. elegans biology, such as establishing a feasible gene knockout method, immortalized cell lines, or identifying viruses that can be used as vectors for introducing exogenous gene constructs into the worms, will augment the usage of this small organism for genome-wide biology.

• Genomics & Informatics
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• v.11 no.2
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• pp.68-75
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• 2013

Anaplastic thyroid cancer (ATC) belongs to the most malignant and rapidly progressive human thyroid cancers and its prognosis is very poor. Also, it shows high resistance to cancer treatments, so that effective treatment for ATC has not been found to date, and virtually all patients terminate their life rapidly after diagnosis. Although targeted treatment of genetic alterations has emerged as an extremely promising approach to human cancers, such as BRAF in metastatic melanoma, it remains unclear that how commonly genomic alterations are influenced in ATC tumorigenesis. In recent years, genome wide approaches have been exploited to find genetic alterations associated with complex diseases, including cancer. Here, we reviewed the comprehensive genetic alterations in ATC and recent approaches in the context of identifying genomic alterations associated with ATC. Since surprisingly few reports have been published on the genome wide study of ATC, this review puts emphasis on the urgent needs of genomic research for the prevention and treatment of ATC.

• Asian-Australasian Journal of Animal Sciences
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• v.32 no.7
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• pp.913-921
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• 2019

Objective: The objectives of this study were to compare identified informative regions through two genome-wide association study (GWAS) approaches and determine the accuracy and bias of the direct genomic value (DGV) for milk production traits in Korean Holstein cattle, using two genomic prediction approaches: single-step genomic best linear unbiased prediction (ss-GBLUP) and Bayesian Bayes-B. Methods: Records on production traits such as adjusted 305-day milk (MY305), fat (FY305), and protein (PY305) yields were collected from 265,271 first parity cows. After quality control, 50,765 single-nucleotide polymorphic genotypes were available for analysis. In GWAS for ss-GBLUP (ssGWAS) and Bayes-B (BayesGWAS), the proportion of genetic variance for each 1-Mb genomic window was calculated and used to identify informative genomic regions. Accuracy of the DGV was estimated by a five-fold cross-validation with random clustering. As a measure of accuracy for DGV, we also assessed the correlation between DGV and deregressed-estimated breeding value (DEBV). The bias of DGV for each method was obtained by determining regression coefficients. Results: A total of nine and five significant windows (1 Mb) were identified for MY305 using ssGWAS and BayesGWAS, respectively. Using ssGWAS and BayesGWAS, we also detected multiple significant regions for FY305 (12 and 7) and PY305 (14 and 2), respectively. Both single-step DGV and Bayes DGV also showed somewhat moderate accuracy ranges for MY305 (0.32 to 0.34), FY305 (0.37 to 0.39), and PY305 (0.35 to 0.36) traits, respectively. The mean biases of DGVs determined using the single-step and Bayesian methods were $1.50{\pm}0.21$ and $1.18{\pm}0.26$ for MY305, $1.75{\pm}0.33$ and $1.14{\pm}0.20$ for FY305, and $1.59{\pm}0.20$ and $1.14{\pm}0.15$ for PY305, respectively. Conclusion: From the bias perspective, we believe that genomic selection based on the application of Bayesian approaches would be more suitable than application of ss-GBLUP in Korean Holstein populations.

• Asian-Australasian Journal of Animal Sciences
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• v.27 no.12
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• pp.1678-1683
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• 2014

This study considers a problem of genomic selection (GS) for adjacent genetic markers of Yorkshire pigs which are typically correlated. The GS has been widely used to efficiently estimate target variables such as molecular breeding values using markers across the entire genome. Recently, GS has been applied to animals as well as plants, especially to pigs. For efficient selection of variables with specific traits in pig breeding, it is required that any such variable selection retains some properties: i) it produces a simple model by identifying insignificant variables; ii) it improves the accuracy of the prediction of future data; and iii) it is feasible to handle high-dimensional data in which the number of variables is larger than the number of observations. In this paper, we applied several variable selection methods including least absolute shrinkage and selection operator (LASSO), fused LASSO and elastic net to data with 47K single nucleotide polymorphisms and litter size for 519 observed sows. Based on experiments, we observed that the fused LASSO outperforms other approaches.

• Korean Journal of Plant Tissue Culture
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• v.27 no.4
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• pp.317-323
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• 2000

Molecular genetic techniques can now be applied to the development of advanced plant genotypes, either through genetic transformation or genomic approaches which allow researchers to transfer specific traits using molecular markers. In this paper, we discuss the use of these techniques towards understanding the genetics of blackleg resistance in Brassica. In a comparative mapping study between Arabidopsis thaliana and Brassica napus, 6 R-ESTs, 7 B. napus RFLP markers and a B. napus EST were located in a collinear region of N7 (B. napus) and chromosome 1 (A. thaliana). One of the A. thaliana R-ESTs and 4 of the B. napus RFLPs co-segregated and mapped to the LmRl locus for blackleg resistance. Introgression of blackleg resistance from wild relatives is also investigated with the possibility of accelerating the introgression process via marker assisted selection.

• Journal of Information Processing Systems
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• v.13 no.2
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• pp.204-214
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• 2017

Artificial intelligence, especially deep learning technology, is penetrating the majority of research areas, including the field of bioinformatics. However, deep learning has some limitations, such as the complexity of parameter tuning, architecture design, and so forth. In this study, we analyze these issues and challenges in regards to its applications in bioinformatics, particularly genomic analysis and medical image analytics, and give the corresponding approaches and solutions. Although these solutions are mostly rule of thumb, they can effectively handle the issues connected to training learning machines. As such, we explore the tendency of deep learning technology by examining several directions, such as automation, scalability, individuality, mobility, integration, and intelligence warehousing.

• BMB Reports
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• v.37 no.1
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• pp.53-58
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• 2004

With advances in determining the entire DNA sequence of the human genome, it is now critical to systematically identify the function of a number of genes in the human genome. These biological challenges, especially those in human diseases, should be addressed in human cells in which conventional (e.g. genetic) approaches have been extremely difficult to implement. To overcome this, several approaches have been initiated. This review will focus on the development of a novel 'chemical genetic/genomic approach' that uses small molecules to 'probe and identify' the function of genes in specific biological processes or pathways in human cells. Due to the close relationship of small molecules with drugs, these systematic and integrative studies will lead to the 'medicinal systems biology approach' which is critical to 'formulate and modulate' complex biological (disease) networks by small molecules (drugs) in human bio-systems.

• Journal of Interdisciplinary Genomics
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• v.4 no.2
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• pp.19-23
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• 2022

Pseudogenes are genomic regions that contain gene-like sequences that have a high similarity to the known genes but are nonfunctional. They are categorized into processed, unprocessed, and unitary pseudogenes. Unprocessed pseudogenes generated by duplications can be problematic in sequencing approaches in molecular diagnostics. We discuss the risk of misdiagnosis when investigating genes with pseudogenes of high homology, and describe a method for identifying these small and annoying differences between parent genes and pseudogenes, including parent gene-specific assay design.

• The Korea Genome Conference
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• 2006.09a
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• pp.56-56
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• 2006

• Proceedings of the Korean Society for Applied Microbiology Conference
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• 2003.06a
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• pp.18-19
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• 2003