No abstract available.
Coat Protein Complex I

No abstract available.
Coat Protein Complex I

Human personal genome sequencing can be done with high efficiency by aligning a huge number of short reads derived from various next generation sequencing (NGS) technologies to the reference genome sequence. One of the major obstacles is the incompleteness of human reference genome. We tried to analyze the effect of hidden gene duplication on the NGS data using the known example of hydin gene. Hydin2 , a duplicated copy of hydin on chromosome 16q22, has been recently found to be localized to chromosome 1q21, and is not included in the current version of standard human genome reference. We found that all of eight personal genome data published so far do not contain hydin2, and there is large number of nsSNPs in hydin. The heterozygosity of those nsSNPs was significantly higher than expected. The sequence coverage depth in hydin gene was about two fold of average depth. We believe that these unique finding of hydin can be used as useful indicators to discover new hidden multiplication in human genome.
Coat Protein Complex I ; Gene Duplication ; Genome ; Genome, Human ; Humans

Precise and reliable identification of CNV is still important to fully understand the effect of CNV on genetic diversity and background of complex diseases. SNP marker has been used frequently to detect CNVs, but the analysis of SNP chip data for identifying CNV has not been well established. We compared various normalization methods for CNV analysis and suggest optimal normalization procedure for reliable CNV call. Four normal Koreans and NA10851 HapMap male samples were genotyped using Affymetrix Genome-Wide Human SNP array 5.0. We evaluated the effect of median and quantile normalization to find the optimal normalization for CNV detection based on SNP array data. We also explored the effect of Robust Multichip Average (RMA) background correction for each normalization process. In total, the following 4 combinations of normalization were tried: 1) Median normalization without RMA background correction, 2) Quantile normalization without RMA background correction, 3) Median normalization with RMA background correction, and 4) Quantile ormalization with RMA background correction. CNV was called using SW-ARRAY algorithm. We applied 4 different combinations of normalization and compared the effect using intensity ratio profile, box plot, and MA plot. When we applied median and quantile normalizations without RMA background correction, both methods showed similar normalization effect and the final CNV calls were also similar in terms of number and size. In both median and quantile normalizations, RMA background correction resulted in widening the range of intensity ratio distribution, which may suggest that RMA background correction may help to detect more CNVs compared to no correction.
Coat Protein Complex I ; Genetic Variation ; HapMap Project ; Humans ; Male

PURPOSE: Recently, orbital wall fracture is common injuries in the face. Facial CT is essential for the accurate diagnosis and appropriate treatment to reconstruct of the orbital wall. The objective of this study was to report the method for accurate measurement of area and shape of the bony defect in the blow-out fractures using facial CT in prior to surgery. METHODS: The authors experienced 46 cases of orbital wall fractures and examined for diplopia, sensory disturbance in the area of distribution of the infraorbital nerve, and enophthalmos in the preoperation and followed 1 months after surgery, from August 2007 to May 2008. Bony defect was predicted by measuring continuous defect size from 3mm interval facial CT. Copying from the defect model(template), we reconstructed orbital wall with resorbable sheet(Inion CPS(R), Inion Oy, Tampere, Finland). RESULTS: One months after surgery using this method, 26(100%) of the 26 patients improved in the diplopia and sensory disturbance in the area of distribution of the infraorbital nerve. Also 8(72.7%) of the 11 patients had enophthalmos took favorable turn. CONCLUSION: This accurate and time-saving method is practicable for determining the location, shape and size of the bony defect. Using this method, we can reconstruc
Coat Protein Complex I ; Diplopia ; Enophthalmos ; Humans ; Orbit ; Orbital Fractures

PURPOSE: Recently, orbital wall fracture is common injuries in the face. Facial CT is essential for the accurate diagnosis and appropriate treatment to reconstruct of the orbital wall. The objective of this study was to report the method for accurate measurement of area and shape of the bony defect in the blow-out fractures using facial CT in prior to surgery. METHODS: The authors experienced 46 cases of orbital wall fractures and examined for diplopia, sensory disturbance in the area of distribution of the infraorbital nerve, and enophthalmos in the preoperation and followed 1 months after surgery, from August 2007 to May 2008. Bony defect was predicted by measuring continuous defect size from 3mm interval facial CT. Copying from the defect model(template), we reconstructed orbital wall with resorbable sheet(Inion CPS(R), Inion Oy, Tampere, Finland). RESULTS: One months after surgery using this method, 26(100%) of the 26 patients improved in the diplopia and sensory disturbance in the area of distribution of the infraorbital nerve. Also 8(72.7%) of the 11 patients had enophthalmos took favorable turn. CONCLUSION: This accurate and time-saving method is practicable for determining the location, shape and size of the bony defect. Using this method, we can reconstruc
Coat Protein Complex I ; Diplopia ; Enophthalmos ; Humans ; Orbit ; Orbital Fractures

We have discovered copy number variations (CNVs) in 3,578 Korean individuals with the Affymetrix Genome-Wide SNP array 5.0, and 4,003 copy number variation regions (CNVRs) were defined in a previous study. To explore the details of the variants easily in related studies, we built a database, cataloging the CNVs and related information. This system helps researchers browsing these variants with gene and structure variant annotations. Users can easily find specific regions with search options and verify them from system-integrated genome browsers with annotations.
Asian Continental Ancestry Group ; Cataloging ; Coat Protein Complex I ; Genome ; Humans

OBJECTIVES: The CLOX (an executive clock drawing task) consists of an unprompted task that is sensitive to executive function (CLOX1) and a copied version that is more dependent on visuoconstructive function (CLOX2). This study aimed to explore the effects of age, education, and gender on the performance of the CLOX and to provide normative information on the test in the Korean elderly. METHODS: We administered the CLOX to 608 community-dwelling healthy volunteers aged 60-90, excluding people with serious neurological, medical, and psychiatric disorders, including dementia. Multiple linear regression analysis was performed to assess the relative contributions of the demographic factors to the CLOX scores. RESULTS: Education had a considerable influence on performance of both CLOX1 and CLOX2. Age and gender also had significant effect on both. There were significant interactions between education and gender for both CLOX1 and CLOX2. We also found interactions between education and age on CLOX2. Based on these results, we created normative data for the CLOX, stratified by age (60-74 and 75-90 years), education (0-3, 4-9, and 10+ years), and gender. CONCLUSION: Our normative data, based on a large, healthy elderly population, provides accurate reference information on CLOX performance and should be very useful for proper interpretation of CLOX scores in the Korean elderly.
Aged ; Coat Protein Complex I ; Dementia ; Demography ; Executive Function ; Humans ; Linear Models

The robust identification and comprehensive profiling of copy number alterations (CNAs) is highly challenging. The amount of data obtained from high-throughput technologies such as array-based comparative genomic hybridization is often too large and it is required to develop a comprehensive and versatile tool for the detection and visualization of CNAs in a genome-wide scale. With this respective, we introduce a software framework, CGHscape that was originally developed to explore the CNAs for the study of copy number variation (CNV) or tumor biology. As a standalone program, CGHscape can be easily installed and run in Microsoft Windows platform. With a user-friendly interface, CGHscape provides a method for data smoothing to cope with the intrinsic noise of array data and CNA detection based on SW-ARRAY algorithm. The analysis results can be demonstrated as log2 plots for individual chromosomes or genomic distribution of identified CNAs. With extended applicability, CGHscape can be used for the initial screening and visualization of CNAs facilitating the cataloguing and characterizing chromosomal alterations of a cohort of samples.
Biology ; Coat Protein Complex I ; Cohort Studies ; Comparative Genomic Hybridization ; Mass Screening ; Noise ; Phosphatidylethanolamines

Together with single nucleotide polymorphism (SNP), copy number variations (CNV) are recognized to be the major component of human genetic diversity and used as a genetic marker in many disease association studies. Affymetrix Genome-wide SNP 5.0 is one of the commonly used SNP array platforms for SNP-GWAS as well as CNV analysis. However, there has been no report that validated the accuracy and reproducibility of CNVs identified by Affymetrix SNP array 5.0. In this study, we compared the characteristics of CNVs from the same set of genomic DNAs detected by three different array platforms; Affymetrix SNP array 5.0, Agilent 2X244K CNV array and NimbleGen 2.1M CNV array. In our analysis, Affymetrix SNP array 5.0 seems to detect CNVs in a reliable manner, which can be applied for association studies. However, for the purpose of defining CNVs in detail, Affymetrix Genome-wide SNP 5.0 might be relatively less ideal than NimbleGen 2.1M CNV array and Agilent 2X244K CNV array, which outperform Affymetrix array for defining the small-sized single copy variants. This result will help researchers to select a suitable array platform for CNV analysis.
Coat Protein Complex I ; DNA ; Genetic Markers ; Genetic Variation ; Humans ; Polymorphism, Single Nucleotide