• Molecules and Cells
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• v.23 no.3
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• pp.349-356
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• 2007

Simple Sequence Repeats (SSRs) represent short tandem duplications found within all eukaryotic organisms. To examine the distribution of SSRs in the genome of Brassica rapa ssp. pekinensis, SSRs from different genomic regions representing 17.7 Mb of genomic sequence were surveyed. SSRs appear more abundant in non-coding regions (86.6%) than in coding regions (13.4%). Comparison of SSR densities in different genomic regions demonstrated that SSR density was greatest within the 5'-flanking regions of the predicted genes. The proportion of different repeat motifs varied between genomic regions, with trinucleotide SSRs more prevalent in predicted coding regions, reflecting the codon structure in these regions. SSRs were also preferentially associated with gene-rich regions, with peri-centromeric heterochromatin SSRs mostly associated with retrotransposons. These results indicate that the distribution of SSRs in the genome is non-random. Comparison of SSR abundance between B. rapa and the closely related species Arabidopsis thaliana suggests a greater abundance of SSRs in B. rapa, which may be due to the proposed genome triplication. Our results provide a comprehensive view of SSR genomic distribution and evolution in Brassica for comparison with the sequenced genomes of A. thaliana and Oryza sativa.

• Genes and Genomics
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• v.40 no.11
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• pp.1149-1155
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• 2018

Epileptic encephalopathies are genetically heterogeneous disorders which leads to epilepsy and cause neurological disorders. Seizure threshold 2 (SZT2) gene located on chromosome 1p34.2 encodes protein mainly expressed predominantly in the parietal and frontal cortex and dorsal root ganglia in the brain. Previous studies in mice showed that mutation in this gene can confers low seizure threshold, enhance epileptogenesis and in human may leads to facial dysmorphism, intellectual disability, seizure and macrocephaly. Objective of this study was to find out novel gene or novel mutation related to the gene phenotype. We have identified a large consanguineous Saudi family segregating developmental delay, intellectual disability, epilepsy, high forehead and macrocephaly. Exome sequencing was performed in affected siblings of the family to study the novel mutation. Whole exome sequencing data analysis, confirmed by subsequent Sanger sequencing validation study. Our results showed a novel homozygous mutation (c.9368G>A) in a substitution of a conserved glycine residue into a glutamic acid in the exon 67 of SZT2 gene. The mutation was ruled out in 100 unrelated healthy controls. The missense variant has not yet been reported as pathogenic in literature or variant databases. In conclusion, the here detected homozygous SZT2 variant might be the causative mutation that further explain epilepsy and developmental delay in this Saudi family.

• Korean Journal of Agricultural Science
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• v.48 no.4
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• pp.681-691
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• 2021

The estimated breeding value (EBV) and accuracy of Hanwoo steer (Korean cattle) is an indicator that can predict the slaughter time in the future and carcass performance outcomes. Recently, studies using pedigrees and genotypes are being actively conducted to improve the accuracy of the EBV. In this study, the pedigree and genotype of 46 steers obtained from livestock farm A in Gyeongnam were used for a pedigree best linear unbiased prediction (PBLUP) and a genomic best linear unbiased prediction (GBLUP) to estimate and analyze the breeding value and accuracy of the carcass weight (CWT), eye muscle area (EMA), back-fat thickness (BFT), and marbling score (MS). PBLUP estimated the EBV and accuracy by constructing a numeric relationship matrix (NRM) from the 46 steers and reference population I (545,483 heads) with the pedigree and phenotype. GBLUP estimated genomic EBV (GEBV) and accuracy by constructing a genomic relationship matrix (GRM) from the 46 steers and reference population II (16,972 heads) with the genotype and phenotype. As a result, in the order of CWT, EMA, BFT, and MS, the accuracy levels of PBLUP were 0.531, 0.519, 0.524 and 0.530, while the accuracy outcomes of GBLUP were 0.799, 0.779, 0.768, and 0.810. The accuracy estimated by GBLUP was 50.1 - 53.1% higher than that estimated by PBLUP. GEBV estimated with the genotype is expected to show higher accuracy than the EBV calculated using only the pedigree and is thus expected to be used as basic data for genomic selection in the future.

• Journal of English Language & Literature
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• v.53 no.2
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• pp.243-260
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• 2007

This article explores how Richard Powers' The Gold Bug Variations, an interdisciplinary novel through the new concepts of biocriticism and bioliterature is connected with literature/art and science/technology. Powers uses Edgar Allen Poe's "The Gold Bug" and Johann Sebastian Bach's "The Goldberg Variations" for decoding DNA in order to analogize a genomic metaphor. He imagines literature as "the book of life" genome, written by DNA code due to the complexity and multiplicity of the genome. His novel, as 'genomic narrative,' shows the articulation of the genomic reading, and expression in the life language through the discourses of the information technology and the rhetorical tropes in biology. New biological ideas are continually required to articulate these processes. In the present tendency of the Human Genome Project, such advanced devices as biocybernetics offer the potential to open up new possibilities to researching the complexity of the genome. This can only happen if the following two ideas are followed: One is to comply with advanced technologies for processing the rapidly increasing data of the genome sequence; The other is to admit the necessary paradigm shift in biology. As shown above, the complexity and multiplicity of the genomic reality is not so simple. We must go beyond determinism, even if representation of a biological reality reveals the possibility of expressing its constituent elements by the advanced biotechnology. Consequently, in the unstoppable advances of the art of decoding the genome, The Gold Bug Variations interrelates to the interdisciplinary approaches through the rhetorical tropes that unfold the complex discursive world of the genome. Powers shows that the complex mechanisms of the genome in the microworld of every cell as the plot of "the book of life" can be designed and written using DNA language. At the same time, his genomic reading and writing demonstrate the historical processes of the shifting center of new genomic development and polysemous interpretation.

• Animal Bioscience
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• v.37 no.4
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• pp.622-630
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• 2024

Objective: Pig breeders cannot obtain phenotypic information at the time of selection for sow lifetime productivity (SLP). They would benefit from obtaining genetic information of candidate sows. Genomic data interpreted using deep learning (DL) techniques could contribute to the genetic improvement of SLP to maximize farm profitability because DL models capture nonlinear genetic effects such as dominance and epistasis more efficiently than conventional genomic prediction methods based on linear models. This study aimed to investigate the usefulness of DL for the genomic prediction of two SLP-related traits; lifetime number of litters (LNL) and lifetime pig production (LPP). Methods: Two bivariate DL models, convolutional neural network (CNN) and local convolutional neural network (LCNN), were compared with conventional bivariate linear models (i.e., genomic best linear unbiased prediction, Bayesian ridge regression, Bayes A, and Bayes B). Phenotype and pedigree data were collected from 40,011 sows that had husbandry records. Among these, 3,652 pigs were genotyped using the PorcineSNP60K BeadChip. Results: The best predictive correlation for LNL was obtained with CNN (0.28), followed by LCNN (0.26) and conventional linear models (approximately 0.21). For LPP, the best predictive correlation was also obtained with CNN (0.29), followed by LCNN (0.27) and conventional linear models (approximately 0.25). A similar trend was observed with the mean squared error of prediction for the SLP traits. Conclusion: This study provides an example of a CNN that can outperform against the linear model-based genomic prediction approaches when the nonlinear interaction components are important because LNL and LPP exhibited strong epistatic interaction components. Additionally, our results suggest that applying bivariate DL models could also contribute to the prediction accuracy by utilizing the genetic correlation between LNL and LPP.

• Animal Bioscience
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• v.37 no.4
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• pp.555-566
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• 2024

Objective: This study aimed to assess the genetic parameters and accuracy of genomic predictions for twenty-four linear body conformation traits and overall conformation scores in Korean Holstein dairy cows. Methods: A dataset of 2,206 Korean Holsteins was collected, and genotyping was performed using the Illumina Bovine 50K single nucleotide polymorphism (SNP) chip. The traits investigated included body traits (stature, height at front end, chest width, body depth, angularity, body condition score, and locomotion), rump traits (rump angle, rump width, and loin strength), feet and leg traits (rear leg set, rear leg rear view, foot angle, heel depth, and bone quality), udder traits (udder depth, udder texture, udder support, fore udder attachment, front teat placement, front teat length, rear udder height, rear udder width, and rear teat placement), and overall conformation score. Accuracy of genomic predictions was assessed using the single-trait animal model genomic best linear unbiased prediction method implemented in the ASReml-SA v4.2 software. Results: Heritability estimates ranged from 0.10 to 0.50 for body traits, 0.21 to 0.35 for rump traits, 0.13 to 0.29 for feet and leg traits, and 0.05 to 0.46 for udder traits. Rump traits exhibited the highest average heritability (0.29), while feet and leg traits had the lowest estimates (0.21). Accuracy of genomic predictions varied among the twenty-four linear body conformation traits, ranging from 0.26 to 0.49. The heritability and prediction accuracy of genomic estimated breeding value (GEBV) for the overall conformation score were 0.45 and 0.46, respectively. The GEBVs for body conformation traits in Korean Holstein cows had low accuracy, falling below the 50% threshold. Conclusion: The limited response to selection for body conformation traits in Korean Holsteins may be attributed to both the low heritability of these traits and the lower accuracy estimates for GEBVs. Further research is needed to enhance the accuracy of GEBVs and improve the selection response for these traits.

• Proceedings of the Korean Society of Plant Biotechnology Conference
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• 2003.04a
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• pp.73-74
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• 2003

• Proceedings of the Zoological Society Korea Conference
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• 2001.10a
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• pp.77-77
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• 2001

No Abstract, See Full Text

• BMB Reports
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• v.49 no.2
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• pp.111-115
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• 2016

Caffeine has been proposed to have several beneficial effects on obesity and its related metabolic diseases; however, how caffeine affects adipocyte differentiation has not been elucidated. In this study, we demonstrated that caffeine suppressed 3T3-L1 adipocyte differentiation and inhibited the expression of CCAAT/enhancer binding protein (C/EBP)α and peroxisome proliferator-activated receptor (PPAR)γ, two main adipogenic transcription factors. Anti-adipogenic markers, such as preadipocyte secreted factor (Pref)-1 and Krüppel-like factor 2, remained to be expressed in the presence of caffeine. Furthermore, 3T3-L1 cells failed to undergo typical mitotic clonal expansion in the presence of caffeine. Investigation of hormonal signaling revealed that caffeine inhibited the activation of AKT and glycogen synthase kinase (GSK) 3 in a dose-dependent manner, but not extracellular signal-regulated kinase (ERK). Our data show that caffeine is an anti-adipogenic bioactive compound involved in the modulation of mitotic clonal expansion during adipocyte differentiation through the AKT/GSK3 pathway.

• 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.