Fan, Bin;Du, Zhi-Qiang;Gorbach, Danielle M.;Rothschild, Max F.
Asian-Australasian Journal of Animal Sciences
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v.23
no.7
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pp.833-847
/
2010
In the past decade, there have been many advances in whole-genome sequencing in domestic animals, as well as the development of "next-generation" sequencing technologies and high-throughput genotyping platforms. Consequently, these advances have led to the creation of the high-density SNP array as a state-of-the-art tool for genetics and genomics analyses of domestic animals. The emergence and utilization of SNP arrays will have significant impacts not only on the scale, speed, and expense of SNP genotyping, but also on theoretical and applied studies of quantitative genetics, population genetics and molecular evolution. The most promising applications in agriculture could be genome-wide association studies (GWAS) and genomic selection for the improvement of economically important traits. However, some challenges still face these applications, such as incorporating linkage disequilibrium (LD) information from HapMap projects, data storage, and especially appropriate statistical analyses on the high-dimensional, structured genomics data. More efforts are still needed to make better use of the high-density SNP arrays in both academic studies and industrial applications.
Purpose : To investigate the feasibility and accuracy of Proton Resonance Frequency (PRF) shift based magnetic resonance (MR) temperature mapping utilizing the self-developed center array-sequencing phase unwrapping (PU) method for non-invasive temperature monitoring. Materials and Methods : The computer simulation was done on the PU algorithm for performance evaluation before further application to MR thermometry. The MR experiments were conducted in two approaches namely PU experiment, and temperature mapping experiment based on the PU technique with all the image postprocessing implemented in MATLAB. A 1.5T MR scanner employing a knee coil with $T2^*$ GRE (Gradient Recalled Echo) pulse sequence were used throughout the experiments. Various subjects such as water phantom, orange, and agarose gel phantom were used for the assessment of the self-developed PU algorithm. The MR temperature mapping experiment was initially attempted on the agarose gel phantom only with the application of a custom-made thermoregulating water pump as the heating source. Heat was generated to the phantom via hot water circulation whilst temperature variation was observed with T-type thermocouple. The PU program was implemented on the reconstructed wrapped phase images prior to map the temperature distribution of subjects. As the temperature change is directly proportional to the phase difference map, the absolute temperature could be estimated from the summation of the computed temperature difference with the measured ambient temperature of subjects. Results : The PU technique successfully recovered and removed the phase wrapping artifacts on MR phase images with various subjects by producing a smooth and continuous phase map thus producing a more reliable temperature map. Conclusion : This work presented a rapid, and robust self-developed center array-sequencing PU algorithm feasible for the application of MR temperature mapping according to the PRF phase shift property.
This study proposed an improved center array-sequencing phase unwrapping (ICASPU) algorithm. 2% agarose phantom dopped with 0.6mM/l MnCl2 was used with clinical 1.5T MRI system and commercial knee coil. Obtained k-space data(raw-data) was transmitted to PC and reconstructed into phase image with MATLAB software. Previous center array-sequence phase unwrapping algorithm wascompared with proposed ICASP algorithm using second order regression analysis. As a result, we found that the amount of error on proposed ICASPU method is less about 5 times than that of previous CASPU method. In this study, we exploit improved Center array-sequence phase unwrapping algorithm and expect to apply to images including phase informations.
Cho, Suhyung;Cho, Yoobok;Lee, Sooin;Kim, Jayoung;Yum, Hyeji;Kim, Sun Chang;Cho, Byung-Kwan
Genomics & Informatics
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v.11
no.2
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pp.76-82
/
2013
Over the past decade or so, dramatic developments in our ability to experimentally determine the content and function of genomes have taken place. In particular, next-generation sequencing technologies are now inspiring a new understanding of bacterial transcriptomes on a global scale. In bacterial cells, whole-transcriptome studies have not received attention, owing to the general view that bacterial genomes are simple. However, several recent RNA sequencing results are revealing unexpected levels of complexity in bacterial transcriptomes, indicating that the transcribed regions of genomes are much larger and complex than previously anticipated. In particular, these data show a wide array of small RNAs, antisense RNAs, and alternative transcripts. Here, we review how current transcriptomics are now revolutionizing our understanding of the complexity and regulation of bacterial transcriptomes.
Many antibiotics contain partially deoxygenated sugar components that are usually essential for biological activity, affinity, structural stability, and solubility of antibiotics. Gene probes of the biosynthetic genes related with the deoxysugar were obtained from PCR. Primers were designed from the conserved peptide sequences of the known dTDP-D-glucose 4,6-dehydratases, which are the key step enzymes in the biosynthesis of deoxysugar. The primers were applied to amplify parts of dehydratase genes to 27 actinomycetes that produce the metabolites containing deoxysugar as structural constituents. About 180 and 340 bp DNA fragments from all of the actinomycetes were produced by PCR and analyzed by Southern blot and DNA sequencing. The PCR products were used as gene probes to clone the biosynthetic gene clusters for the antibiotic mithramycin, rubradirin, spectinomycin, and elaiophyrin. This method should allow for detecting of the biosynthetic gene clusters of a vast array of secondary metabolites isolated from actinomycetes because of the widespread existence of deoxysugar constituents in secondary metabolites.
Hyun Jung Lee;Hye Rim Cho;Minji Bang;Yeo Song Lee; Youn Jin Kim; Kyuha Chong
Journal of Korean Neurosurgical Society
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v.67
no.4
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pp.418-430
/
2024
Objective : Isoflurane, a widely used common inhalational anesthetic agent, can induce brain toxicity. The challenge lies in protecting neurologically compromised patients from neurotoxic anesthetics. Choline alfoscerate (L-α-Glycerophosphorylcholine, α-GPC) is recognized for its neuroprotective properties against oxidative stress and inflammation, but its optimal therapeutic window and indications are still under investigation. This study explores the impact of α-GPC on human astrocytes, the most abundant cells in the brain that protect against oxidative stress, under isoflurane exposure. Methods : This study was designed to examine changes in factors related to isoflurane-induced toxicity following α-GPC administration. Primary human astrocytes were pretreated with varying doses of α-GPC (ranging from 0.1 to 10.0 µM) for 24 hours prior to 2.5% isoflurane exposure. In vitro analysis of cell morphology, water-soluble tetrazolium salt-1 assay, quantitative real-time polymerase chain reaction, proteome profiler array, and transcriptome sequencing were conducted. Results : A significant morphological damage to human astrocytes was observed in the group that had been pretreated with 10.0 mM of α-GPC and exposed to 2.5% isoflurane. A decrease in cell viability was identified in the group pretreated with 10.0 µM of α-GPC and exposed to 2.5% isoflurane compared to the group exposed only to 2.5% isoflurane. Quantitative real-time polymerase chain reaction revealed that mRNA expression of heme-oxygenase 1 and hypoxia-inducible factor-1α, which were reduced by isoflurane, was further suppressed by 10.0 µM α-GPC pretreatment. The proteome profiler array demonstrated that α-GPC pretreatment influenced a variety of factors associated with apoptosis induced by oxidative stress. Additionally, transcriptome sequencing identified pathways significantly related to changes in isoflurane-induced toxicity caused by α-GPC pretreatment. Conclusion : The findings suggest that α-GPC pretreatment could potentially enhance the vulnerability of primary human astrocytes to isoflurane-induced toxicity by diminishing the expression of antioxidant factors, potentially leading to amplified cell damage.
Genome-wide association studies (GWASs) have greatly contributed to the identification of common variants responsible for numerous complex traits. There are, however, unavoidable limitations in detecting causal and/or rare variants for traits in this approach, which depends on an LD-based tagging SNP microarray chip. In an effort to detect potential casual and/or rare variants for complex traits, such as type 2 diabetes (T2D) and triglycerides (TGs), we conducted a targeted resequencing of loci identified by the Korea Association REsource (KARE) GWAS. The target regions for resequencing comprised whole exons, exon-intron boundaries, and regulatory regions of genes that appeared within 1 Mb of the GWA signal boundary. From 124 individuals selected in population-based cohorts, a total of 0.7 Mb target regions were captured by the NimbleGen sequence capture 385K array. Subsequent sequencing, carried out by the Roche 454 Genome Sequencer FLX, generated about 110,000 sequence reads per individual. Mapping of sequence reads to the human reference genome was performed using the SSAHA2 program. An average of 62.2% of total reads was mapped to targets with an average 22X-fold coverage. A total of 5,983 SNPs (average 846 SNPs per individual) were called and annotated by GATK software, with 96.5% accuracy that was estimated by comparison with Affymetrix 5.0 genotyped data in identical individuals. About 51% of total SNPs were singletons that can be considered possible rare variants in the population. Among SNPs that appeared in exons, which occupies about 20% of total SNPs, 304 nonsynonymous singletons were tested with Polyphen to predict the protein damage caused by mutation. In total, we were able to detect 9 and 6 potentially functional rare SNPs for T2D and triglycerides, respectively, evoking a further step of replication genotyping in independent populations to prove their bona fide relevance to traits.
Proceedings of the Korean Society for Bioinformatics Conference
/
2003.10a
/
pp.1-1
/
2003
It is clear that computers will play a key role in the biology of the future. Even now, it is virtually impossible to keep track of the key proteins, their names and associated gene names, physical constants(e.g. binding constants, reaction constants, etc.), and hewn physical and genetic interactions without computational assistance. In this sense, computers act as an auxiliary brain, allowing one to keep track of thousands of complex molecules and their interactions. With the advent of gene expression array technology, many experiments are simply impossible without this computer assistance. In the future, as we seek to integrate the reductionist description of life provided by genomic sequencing into complex and sophisticated models of living systems, computers will play an increasingly important role in both analyzing data and generating experimentally testable hypotheses. The future of bioinformatics is thus being driven by potent technological and scientific forces. On the technological side, new experimental technologies such as microarrays, protein arrays, high-throughput expression and three-dimensional structure determination prove rapidly increasing amounts of detailed experimental information on a genomic scale. On the computational side, faster computers, ubiquitous computing systems, high-speed networks provide a powerful but rapidly changing environment of potentially immense power. The challenges we face are enormous: How do we create stable data resources when both the science and computational technology change rapidly? How do integrate and synthesize information from many disparate subdisciplines, each with their own vocabulary and viewpoint? How do we 'liberate' the scientific literature so that it can be incorporated into electronic resources? How do we take advantage of advances in computing and networking to build the international infrastructure needed to support a complete understanding of biological systems. The seeds to the solutions of these problems exist, at least partially, today. These solutions emphasize ubiquitous high-speed computation, database interoperation, federation, and integration, and the development of research networks that capture scientific knowledge rather than just the ABCs of genomic sequence. 1 will discuss a number of these solutions, with examples from existing resources, as well as area where solutions do not currently exist with a view to defining what bioinformatics and biology will look like in the future.
Helicobacter pylori as the second most common cause of gastric cancer in the world infects approximately half of the developed countries population and 80% of the population living in developing countries. Integrons as genetic reservoirs play major roles in dissemination of antimicrobial resistance genes. To the best of our knowledge, this is the first study to report carriage of class 1 and 2 integrons and associated gene cassettes in H. pylori isolates from Iran. This cross-sectional study was conducted in Tehran among 110 patients with H. pylori infection. Antimicrobial susceptibility testing (AST) for H. pylori strains were assessed by the micro broth dilution method. Class 1 and 2 integrons were detected using PCR. In order to determine gene cassettes, amplified fragments were subjected to DNA sequencing of both amplicon strands. The prevalence of resistance to clarithromycin, metronidazole, clarithromycin, tetracycline, amoxicillin, rifampin, and levofloxacin were 68.2% (n=75), 25.5% (n=28), 24.5% (n=27), 19.1% (n=21), 18.2% (n=20) and 16.4% (n=18), respectively. Frequency of multidrug resistance among H. pylori isolates was 12.7%. Class 2 integron was detected in 50 (45.5%) and class 1 integron in 10 (9.1%) H. pylori isolates. The most predominant gene cassette arrays in class 2 integron-bearing H. pylori were included sat-era-aadA1, dfrA1-sat2-aadA1, blaoxa2 and, aadB whereas common gene cassette arrays in class 1 integron were aadB-aadA1-cmlA6, aacA4, blaoxa2, and catB3. The high frequency of class 2 integron and multidrug resistance in the present study should be considered as a warning for clinicians that continuous surveillance is necessary to prevent the further spread of resistant isolates.
The emergence of next-generation sequencing technologies has lead to application of new computational and statistical methodologies that allow incorporating genetic information from entire genomes of many individuals composing the population. For example, using single-nucleotide polymorphisms (SNP) obtained from whole genome amplification platforms such as the Ilummina BovineSNP50 chip, many researchers are actively engaged in the genetic evaluation of cattle livestock using whole genome relationship analyses. In this study, we estimated the genomic relationship matrix (GRM) and compared it with one computed using a pedigree relationship matrix (PRM) using a population of Hanwoo. This project is a preliminary study that will eventually include future work on genomic selection and prediction. Data used in this study were obtained from 187 blood samples consisting of the progeny of 20 young bulls collected after parentage testing from the Hanwoo improvement center, National Agriculture Cooperative Federation as well as 103 blood samples from the progeny of 12 proven bulls collected from farms around the Kyong-buk area in South Korea. The data set was divided into two cases for analysis. In the first case missing genotypes were included. In the second case missing genotypes were excluded. The effect of missing genotypes on the accuracy of genomic relationship estimation was investigated. Estimation of relationships using genomic information was also carried out chromosome by chromosome for whole genomic SNP markers based on the regression method using allele frequencies across loci. The average correlation coefficient and standard deviation between relationships using pedigree information and chromosomal genomic information using data which was verified using a parentage test andeliminated missing genotypes was $0.81{\pm}0.04$ and their correlation coefficient when using whole genomic information was 0.98, which was higher. Variation in relationships between non-inbred half sibs was $0.22{\pm}0.17$ on chromosomal and $0.22{\pm}0.04$ on whole genomic SNP markers. The variations were larger and unusual values were observed when non-parentage test data were included. So, relationship matrix by genomic information can be useful for genetic evaluation of animal breeding.
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