• Journal of Plant Biotechnology
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• v.42 no.4
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• pp.312-325
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• 2015

In this review, we summarized the trends of genomics and transcriptomics research on peach, a model species of Rosaceae. Peach genome maps have been developed from various progeny groups with many next-generation sequencing (NGS) based single nucleotide polymorphism markers. Molecular markers of qualitative traits and quantitative trait loci (QTL) such as fruit characteristics, blooming date, and disease resistance have been analyzed. Among many characteristics, markers related to flesh softening and flesh adhesion are useful for marker assisted selection. Through comparative genomics, peach genome has been compared to the genome of Arabidopsis, Populus, Malus, and Fragaria species. Through transcriptomics and proteomics, fruit growth and development, and flavonoid synthesis, postharvest related transcriptomes and disease resistance related proteins have been reported. Recently, development of NGS based markers, construction of core collection of germplasm, and genotyping of various progenies have been preceded. In the near future, accurate QTL analysis and identification of useful genes are expected to establish a foundation for effective molecular breeding.

• Journal of Plant Biotechnology
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• v.44 no.4
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• pp.372-378
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• 2017

For comparison of the transcription profiles in apple (Malus domestica L.) cultivars differing in flesh color expression, two cDNA libraries were constructed. Differences in gene expression between red flesh apple cultivar, 'Redfield' and white flesh apple cultivar, 'Granny Smith' were investigated by next-generation sequencing (NGS). Expressed sequence tag (EST) of clones from the red flesh apple cultivar and white flesh apple cultivar were selected for nucleotide sequence determination and homology searches. High resolution melting (HRM) technique measures temperature induced strand separation of short PCR amplicons, and is able to detect variation as small as one base difference between red flesh apple cultivars and white flesh apple cultivars. We applied high resolution melting (HRM) analysis to discover single nucleotide polymorphisms (SNP) based on the predicted SNP information derived from the apple EST database. All 103 pairs of SNPs were discriminated, and the HRM profiles of amplicons were established. Putative SNPs were screened from the apple EST contigs by HRM analysis displayed specific difference between 10 red flesh apple cultivars and 11 white flesh apple cultivars. In this study, we report an efficient method to develop SNP markers from an EST database with HRM analysis in apple. These SNP markers could be useful for apple marker assisted breeding and provide a good reference for relevant research on molecular mechanisms of color variation in apple cultivars.

• Journal of Plant Biotechnology
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• v.47 no.2
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• pp.131-140
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• 2020

Solanum stoloniferum, one of the wild tetraploid Solanum species belonging to the Solanaceae family, is an excellent resource for potato breeding owing to its resistance to several important pathogens. However, the sexual hybridization of S. stoloniferum with S. tuberosum (potato) is hampered due to the sexual incompatibility between the two species. To overcome this and introgress the various novel traits of S. stoloniferum in cultivated potatoes, cell fusion can be performed. The identification of the fusion products is crucial and can be achieved with the aid of molecular markers. In this study, the chloroplast genome sequence of S. stoloniferum was obtained by next-generation sequencing technology, and compared with that of six other Solanum species to identify S. stoloniferum-specific molecular markers. The length of the complete chloroplast genome of S. stoloniferum was found to be 155,567 bp. The structural organization of the chloroplast genome of S. stoloniferum was similar to that of the six other Solanum species studied. Phylogenetic analysis of S. stoloniferum with nine other Solanaceae family members revealed that S. stoloniferum was most closely related to S. berthaultii. Additional comparison of the complete chloroplast genome sequence of S. stoloniferum with that of five Solanum species revealed the presence of six InDels and 39 SNPs specific to S. stoloniferum. Based on these InDels and SNPs, four PCR-based markers were developed to differentiate S. stoloniferum from other Solanum species. These markers will facilitate the selection of fusion products and accelerate potato breeding using S. stoloniferum.

• Journal of Plant Biotechnology
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• v.47 no.2
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• pp.141-149
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• 2020

Solanum hougasii, one of the wild Solanum species, has been widely used in potato breeding since it exhibits excellent resistance to diverse important pathogens. S. hougasii can be directly crossed with the cultivated tetraploid potato (S. tuberosum) owing to its EBN (Endosperm Balanced Number) value of 4, which is same as that of S. tuberosum although it is an allohexaploid. In this study, the complete chloroplast genome sequence of S. hougasii was obtained by next-generation sequencing technology, and compared with that of the chloroplast genome of seven other Solanum species to identify S. hougasii-specific PCR markers. The length of the complete chloroplast genome of S. hougasii was 155,549 bp. The structural organization of the chloroplast genome in S. hougasii was found to be similar to that of seven other Solanum species studied. Phylogenetic analysis of S. hougasii with ten other Solanaceae family members revealed that S. hougasii was most closely related to S. stoloniferum, followed by S. berthaultii, and S. tuberosum. Additional comparison of the chloroplast genome sequence with that of five other Solanum species revealed five InDels and 43 SNPs specific to S. hougasii. Based on these SNPs, four PCR-based markers were developed for the differentiation of S. hougasii from other Solanum species. The results obtained in this study will aid in exploring the evolutionary and breeding aspects of Solanum species.

• Journal of Microbiology and Biotechnology
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• v.30 no.10
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• pp.1467-1479
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• 2020

Profiling the transcriptome changes involved in xylose metabolism by the fungus Trichoderma reesei allows for the identification of potential targets for ethanol production processing. In the present study, the transcriptome of T. reesei HJ-48 grown on xylose versus glucose was analyzed using next-generation sequencing technology. During xylose fermentation, numerous genes related to central metabolic pathways, including xylose reductase (XR) and xylitol dehydrogenase (XDH), were expressed at higher levels in T. reesei HJ-48. Notably, growth on xylose did not fully repress the genes encoding enzymes of the tricarboxylic acid and respiratory pathways. In addition, increased expression of several sugar transporters was observed during xylose fermentation. This study provides a valuable dataset for further investigation of xylose fermentation and provides a deeper insight into the various genes involved in this process.

• Genomics & Informatics
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• v.15 no.3
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• pp.87-97
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• 2017

Multiple myeloma (MM) is a malignant disease caused by an abnormal proliferation of plasma cells, of which the prognostic factors include chromosomal abnormality, ${\beta}$-2 microglobulin, and albumin. Recently, the term chromothripsis has emerged, which is the massive but highly localized chromosomal rearrangement in response to a one-step catastrophic event. Many studies have shown an association of chromothripsis with the prognosis in several cancers; however, few studies have investigated it in MM. Here, we studied the association between chromothripsis-like patterns and treatment resistance or prognosis. First, we analyzed nine MM cell lines (U266, MM.1S, RPMI8226, KMS-11, KMS-12-BM, KMS-12-PE, KMS-28-BM, KMS-28-PE, and NCI-H929) and bone marrow samples of four patients who were diagnosed with MM by next-generation sequencing-based copy number variation analysis. The frequency of the chromothripsis-like pattern was observed in seven cell lines. We analyzed the treatment-induced chromothripsis-like patterns in KMS-12-BM and KMS-12-PE cells. As a result, breakpoints and chromothripsis-like patterns were increased after drug treatment in the relatively resistant KMS-12-BM. We further analyzed the patients' results according to the therapeutic response, which was divided into sensitive and resistant, as suggested by the International Myeloma Working Group. The chromothripsis-like pattern was more frequently observed in the resistant group. In the sensitive group, the frequency of the chromothripsis-like pattern decreased after treatment, whereas the resistant group showed increased chromothripsis-like patterns after the treatment. These results suggest that the chromothripsis-like pattern is associated with treatment response in MM.

• Research in Plant Disease
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• v.22 no.4
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• pp.289-292
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• 2016

We surveyed the occurrence of Japanese yam mosaic virus (JYMV) on Yam in Gyeongsangbukdo pronvince from 2013 to 2015. The symptoms of JYMV were yellow stripes and chlorosis in yam leaves and the infection rate was ranged from 33.6% to 40.8%. We determined nucleotide sequence encoding the polyprotein of JYMV isolate BRI from yam leaves using next-generation sequencing (NGS) method. The partial nucleotide portion (7,736 nucleotides) of the genomic RNA of the JYMV isolate BRI has been sequenced (accession No. KU309315). The region sequenced includes a single open reading frame (ORF) encoding a polyprotein composed of 2,497 amino acids containing the coat protein (CP) and 3' untranslated region (UTR). The genomic organization of this isolate shows almost the same to that of other members of JYMV. The JYMV isolate BRI showed 77% to 79% nucleotide identity with the Japanese and Chinese strains and isolates. This is the first report of the genome nucleotide sequence of JYMV from Dioscorea opposita in Korea.

• Korean Journal of Clinical Laboratory Science
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• v.52 no.3
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• pp.202-213
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• 2020

Although technological advances have allowed the efficient collection of large amounts of microbiome data for microbiological studies, proper analysis tools for such big data are still lacking. Additionally, analyses of microbial communities using poor databases can lead to misleading results. Hence, this study aimed to design an appropriate method for the analysis of big microbial databases. Bacteria were collected from the fingertips and personal belongings (mobile phones and laptop keyboards) of individuals. The genomic DNA was extracted from these bacteria and subjected to next-generation sequencing by targeting the 16S rRNA gene. The accuracy of the bacterial matching percentage between the fingertips and personal belongings was verified using a formula and an environment-related and human-related database. To design appropriate analysis, the bacterial matching accuracy was calculated based on the following three categories: comparison between qualitative and quantitative analysis, comparisons within same-gender participants as well as all participants regardless of gender, and comparison between the use of a human-related bacterial database (hDB) and environment-related bacterial database (eDB). The results showed that qualitative analysis, comparisons within same-gender participants, and the use of hDB provided relatively accurate results. This study provides an analytical method to obtain accurate results when conducting studies involving big microbiological data using human-derived microorganisms.

• Journal of KIISE:Databases
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• v.41 no.4
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• pp.249-255
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• 2014

Copy number variations(CNVs) are a recently recognized class of human structural variations and are associated with a variety of human diseases, including cancer. To find important cancer genes, researchers identify novel CNVs in patients with a particular cancer and analyze large amounts of genomic and clinical data. We present a tool called CNVDAT which is able to detect CNVs from NGS data and systematically analyze the genomic and clinical data associated with variations. CNVDAT consists of two modules, CNV Detection Engine and Sequence Analyser. CNV Detection Engine extracts CNVs by using the multi-resolution system of scale-space filtering, enabling the detection of the types and the exact locations of CNVs of all sizes even when the coverage level of read data is low. Sequence Analyser is a user-friendly program to view and compare variation regions between tumor and matched normal samples. It also provides a complete analysis function of refGene and OMIM data and makes it possible to discover CNV-gene-phenotype relationships. CNVDAT source code is freely available from http://dblab.hallym.ac.kr/CNVDAT/.

• Journal of Animal Science and Technology
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• v.52 no.5
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• pp.357-366
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• 2010

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.