• Clinical and Experimental Pediatrics
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• v.57 no.1
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• pp.46-49
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• 2014

CHARGE syndrome has been estimated to occur in 1:10,000 births worldwide and shows various clinical manifestations. It is a genetic disorder characterized by a specific and a recognizable pattern of anomalies. The major clinical features are ocular coloboma, heart malformations, atresia of the choanae, growth retardation, genital hypoplasia, and ear abnormalities. The chromodomain helicase DNA-binding protein 7 (CHD7) gene, located on chromosome 8q12.1, causes CHARGE syndrome. The CHD7 protein is an adenosine triphosphate (ATP)-dependent chromatin remodeling protein. A total of 67% of patients clinically diagnosed with CHARGE syndrome have CHD7 mutations. Five hundred twenty-eight pathogenic and unique CHD7 alterations have been identified so far. We describe a patient with a CHARGE syndrome diagnosis who carried a novel de novo mutation, a c.3896T>C (p. leu1299Pro) missense mutation, in the CHD7 gene. This finding will provide more information for genetic counseling and expand our understanding of the pathogenesis and development of CHARGE syndrome.

• Journal of Genetic Medicine
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• v.17 no.2
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• pp.79-82
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• 2020

In epilepsy-aphasia spectrum (EAS) disorders, mutations in the glutamate receptor ionotropic N-methyl-D-aspartate type subunit 2A (GRIN2A) have become important for screening the disease. Research into the phenotypic variability of several types of neurologic impairment involving these mutations is in progress. However, the non-neurological problems related to these mutations are poorly understood. EAS disorders usually have epileptic, cognitive, or behavioral manifestations. In this case report, we present a female patient with epilepsy, delay in expressive language and social development, and intellectual disability with low intelligence quotient and memory quotient, but normal motor development. Through genetic analysis, she was found to have a missense and a nonsense mutation in GRIN2A (c.1770A>C; p.Lys509Asn and c.3187G>T; p.Glu1063∗, respectively) and we consider the nonsense mutation as 'pathogenic variant'. She was also discovered to have congenital hypothyroidism, growth hormone deficiency and Rathke's cleft cyst in the brain, which were previously unknown features of GRIN2A mutation. Our findings should widen understanding of the spectrum of GRIN2A phenotypes, and emphasize the need for more research into the association between GRIN2A mutations and non-neurologic clinical presentations.

• Journal of Genetic Medicine
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• v.17 no.2
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• pp.92-96
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• 2020

Hypotonia, Ataxia, and Delayed Development Syndrome (HADDS) is an autosomal-dominant, extremely rare neurodevelopmental disorder caused by the heterozygous EBF3 gene mutation. EBF3 is located on chromosome 10q26.3 and acts as a transcription factor that regulates neurogenesis and differentiation. This syndrome is characterized by dysmorphism, cerebellar hypoplasia, urogenital anomaly, hypotonia, ataxia, intellectual deficit, and speech delay. The current report describes a 3-year-old Korean male carrying a de novo EBF3 mutation, c.589A>G (p.Asn197Asp), which was identified by whole exome sequencing. He manifested facial dysmorphism, hypotonia, strabismus, vermis hypoplasia, and urogenital anomalies, including vesicoureteral reflux, cryptorchidism, and areflexic bladder. This is the first report of a case of HADDS cause by an EBF3 mutation in the Korean population.

• Clinical and Experimental Pediatrics
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• v.60 no.3
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• pp.94-97
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• 2017

Trimethylaminuria (TMAuria), known as "fish odor syndrome," is a congenital metabolic disorder characterized by an odor resembling that of rotting fish. This odor is caused by the secretion of trimethylamine (TMA) in the breath, sweat, and body secretions and the excretion of TMA along with urine. TMAuria is an autosomal recessive disorder caused by mutations in flavin-containing monooxygenase 3 (FMO3). Most TMAuria cases are caused by missense mutations, but nonsense mutations have also been reported in these cases. Here, we describe the identification of a novel FMO3 gene mutation in a patient with TMAuria and her family. A 3-year-old girl presented with a strong corporal odor after ingesting fish. Genomic DNA sequence analysis revealed that she had compound heterozygous FMO3 mutations; One mutation was the missense mutation p.Val158Ile in exon 3, and the other was a novel nonsense mutation, p.Ser364X, in exon 7 of the FMO3 gene. Familial genetic analyses showed that the p.Val158Ile mutation was derived from the same allele in the father, and the p.Ser364X mutation was derived from the mother. This is the first description of the p.Ser364X mutation, and the first report of a Korean patient with TMAuria caused by novel compound heterozygous mutations.

• Journal of Animal Science and Technology
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• v.48 no.1
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• pp.1-8
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• 2006

KIT encodes a mast/stem cell growth factor receptor and is known as a possible candidate gene responsible for dominant white coat color in mammals. To investigate the genetic variation of KIT gene in Korean wild boars(Sus scrofa coreanus), we carried out PCR-RFLP and DNA sequencing for three exons(exons 17, 19, and 20) and intron 19 of the KIT gene in Korean wild boars. PCR-RFLP results using NlaⅢ restriction enzyme in the breakpoint region between exon 17 and intron 17 and AciⅠ restriction enzyme in exon 19 indicate that Korean wild boars did not have previously identified white coat color related splicing mutation and missense mutation, respectively. These results also indicate matings between Korean wild boars could not give white coat color offsprings. We also found new SNPs in exons 19(C2661T) and 20(A2760G). Of these, the SNP in exon 20 is a missense mutation which might induce the change of amino acid iso-leucine to valine. However, no relationship was identified with this missense mutation and coat color. In this study, breed specific new SNPs were identified in exons 19, 20 and intron 19 and these results will give important information for genetic variation of porcine KIT gene.

• Journal of Korean Society of Water and Wastewater
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• v.12 no.1
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• pp.70-80
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• 1998

Many algorithms to find a minimum cost design of water distribution network (WDN) have been developed during the last decades. Most of them have tried to optimize cost only while satisfying other constraining conditions. For this, a certain degree of simplification is required in their calculation process which inevitably limits the real application of the algorithms, especially, to large networks. In this paper, an optimum design method using the Genetic Algorithms (GA) is developed which is designed to increase the applicability, especially for the real world large WDN. The increased to applicability is due to the inherent characteristics of GA consisting of selection, reproduction, crossover and mutation. Just for illustration, the GA method is applied to find an optimal solution of the New York City water supply tunnel. For the calculation, the parameter of population size and generation number is fixed to 100 and the probability of crossover is 0.7, the probability of mutation is 0.01. The yielded optimal design is found to be superior to the least cost design obtained from the Linear Program method by $4.276 million.

• Journal of Microbiology and Biotechnology
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• v.17 no.6
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• pp.1041-1044
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• 2007

To assess the effects of a proton beam on oyster mushrooms (Pleurotus ostreatus), the genetic diversity and phylogenetic relationships among strains induced by a proton beam were investigated based on a clustering analysis. According to an AFLP DNA polymorphism analysis, the induced strains were divided into four groups that coincided with the dose. When applying proton-beam radiation, the dissimilarity among the induced strains increased when increasing the dose. When using more than 400 Gy, the genetic dissimilarity of the irradiated strains was 46-58%. Thus, evaluating the induced strains using the AFLP technique was effective in revealing the mutation effect of the proton beam.

• Proceedings of the IEEK Conference
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• 1999.06a
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• pp.474-478
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• 1999

Genetic algorithm is an efficient search method using principles of natural selection and population genetics. In conventional genetic algorithms, however, the size of gene pool should be increased to insure a convergency. Therefore, many memory spaces and much computation time were needed. Also, since child chromosomes were generated by chromosome crossover and gene mutation, the algorithms have a complex structure. Thus, in this paper, a compact stereo matching algorithm using a population-based incremental teaming based on probability vector is proposed to reduce these problems. The PBIL method is modified for matching environment. Since the Proposed algorithm uses a probability vector and eliminates gene pool, chromosome crossover, and gene mutation, the matching algorithm is simple and the computation load is considerably reduced. Even if the characteristics of images are changed, stable outputs are obtained without the modification of the matching algorithm.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2002.12a
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• pp.383-386
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• 2002

In this paper, we investigated the pattern recognition performance of the numeric patterns (from 0 to 9) using DNA coding method. The pattern recognition performance of the DNA coding method is compared to the that of the GA(Genetic Algorithm). GA searches effectively an optimal solution via the artificial evolution of individual group of binary string using binary coding, while DNA coding method uses four-type bases denoted by A(Adenine), C(Cytosine), G(Guanine) and T(Thymine), The pattern recognition performance of GA and DNA coding method is evaluated by using the same genetic operators(crossover and mutation) and the crossover probability and mutation probability are set the same value to the both methods. The DNA coding method has better characteristics over genetic algorithms (GA). The reasons for this outstanding performance is multiple possible solution presentation in one string and variable solution string length.

• Journal of the Korean Institute of Intelligent Systems
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• v.7 no.5
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• pp.28-33
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• 1997

This paper presents an application of genetic algorithms for optimal configuration of distribution network. Optimal nehvork is defined to satisfy the condition of load balancing. Three problems are suggested to show the performance of genetic algorithms. To resolve the problems, we propose two different mutation operators, in stead of crossover and mutation operators, which are utilized in both global and local search operations. In addition, arc pattern list is also proposed for an efficient search.