• Animal Systematics, Evolution and Diversity
• /
• v.36 no.4
• /
• pp.336-346
• /
• 2020

Mitochondrial genome is an important molecule for systematic and evolutionary studies in metazoans. The development of next-generation sequencing (NGS) technique has rapidly increased the number of mitogenome sequences. The process of generating mitochondrial genome based on NGS includes different steps, from DNA preparation, sequencing, assembly, and annotation. Despite the effort to improve sequencing, assembly, and annotation methods of mitogenome, the low quality and/or quantity sequence in the final map can still be generated through the work. Therefore, it is necessary to check and curate mitochondrial genome sequence after annotation for proofreading and feedback. In this study, we introduce the pipeline for sequencing and curation for mitogenome based on NGS. For this purpose, two mitogenome sequences of Dermatobranchus otome were sequenced by Illumina Miseq system with different amount of raw read data. Generated reads were targeted for assembly and annotation with commonly used programs. As abnormal repeat regions present in the mitogenomes after annotation, primers covering these regions were designed and conventional PCR followed by Sanger sequencing were performed to curate the mitogenome sequences. The obtained sequences were used to replace the abnormal region. Following the replacement, each mitochondrial genome was compared with the other as well as the sequences of close species available on the Genbank for confirmation. After curation, two mitogenomes of D. otome showed a typically circular molecule with 14,559 bp in size and contained 13 protein-coding genes, 22 tRNA genes, two rRNA genes. The phylogenetic tree revealed a close relationship between D. otome and Tritonia diomea. The finding of this study indicated the importance of caution and curation for the generation of mitogenome from NGS.

• Clinical and Experimental Pediatrics
• /
• v.63 no.6
• /
• pp.211-212
• /
• 2020

• BT NEWS
• /
• v.15 no.4
• /
• pp.6-12
• /
• 2008

• The Journal of the Korea Contents Association
• /
• v.22 no.2
• /
• pp.762-769
• /
• 2022

Genetic testing in prenatal diagnosis is a precious tool providing valuable information in clinical management and parental decision-making. For the last year, cytogenetic testing methods, such as G-banding karyotype analysis, fluorescent in situ hybridization, chromosomal microarray, and gene panels have evolved to become part of routine laboratory testing. However, the limitations of each of these methods demonstrate the need for a revolutionary technology that can alleviate the need for multiple technologies. The recent introduction of new genomic technologies based on next-generation sequencing has changed the current practice of prenatal testing. The promise of these innovations lies in the fast and cost-effective generation of genome-scale sequence data with exquisite resolution and accuracy for prenatal diagnosis. Here, we review the current state of sequencing-based pediatric diagnostics, associated challenges, as well as future prospects.

• Journal of Life Science
• /
• v.25 no.3
• /
• pp.357-367
• /
• 2015

With the ongoing development of next-generation sequencing (NGS) platforms and advancements in the latest bioinformatics tools at an unprecedented pace, the ultimate goal of sequencing the human genome for less than $1,000 can be feasible in the near future. The rapid technological advances in NGS have brought about increasing demands for statistical methods and bioinformatics tools for the analysis and management of NGS data. Even in the early stages of the commercial availability of NGS platforms, a large number of applications or tools already existed for analyzing, interpreting, and visualizing NGS data. However, the availability of this plethora of NGS data presents a significant challenge for storage, analyses, and data management. Intrinsically, the analysis of NGS data includes the alignment of sequence reads to a reference, base-calling, and/or polymorphism detection, de novo assembly from paired or unpaired reads, structural variant detection, and genome browsing. While the NGS technologies have allowed a massive increase in available raw sequence data, a number of new informatics challenges and difficulties must be addressed to improve the current state and fulfill the promise of genome research. This review aims to provide an overview of major NGS technologies and bioinformatics tools for NGS data analyses.

• Genomics & Informatics
• /
• v.13 no.3
• /
• pp.81-85
• /
• 2015

Molecular characterization technology in genetically modified organisms, in addition to how transgenic biotechnologies are developed now require full transparency to assess the risk to living modified and non-modified organisms. Next generation sequencing (NGS) methodology is suggested as an effective means in genome characterization and detection of transgenic insertion locations. In the present study, we applied NGS to insert transgenic loci, specifically the epidermal growth factor (EGF) in genetically modified rice cells. A total of 29.3 Gb (${\sim}72{\times}coverage$) was sequenced with a $2{\times}150bp$ paired end method by Illumina HiSeq2500, which was consecutively mapped to the rice genome and T-vector sequence. The compatible pairs of reads were successfully mapped to 10 loci on the rice chromosome and vector sequences were validated to the insertion location by polymerase chain reaction (PCR) amplification. The EGF transgenic site was confirmed only on chromosome 4 by PCR. Results of this study demonstrated the success of NGS data to characterize the rice genome. Bioinformatics analyses must be developed in association with NGS data to identify highly accurate transgenic sites.

• The Plant Pathology Journal
• /
• v.37 no.6
• /
• pp.521-532
• /
• 2021

Knowledge and better understanding of functions of the microbial community are pivotal for crop management. This study was conducted to study bacterial structures including Acidovorax species community structures and diversity from the watermelon cultivated soils in different regions of South Korea. In this study, soil samples were collected from watermelon cultivation areas from various places of South Korea and microbiome analysis was performed to analyze bacterial communities including Acidovorax species community. Next generation sequencing (NGS) was performed by extracting genomic DNA from 92 soil samples from 8 different provinces using a fast genomic DNA extraction kit. NGS data analysis results revealed that, total, 39,367 operational taxonomic unit (OTU), were obtained. NGS data results revealed that, most dominant phylum in all the soil samples was Proteobacteria (37.3%). In addition, most abundant genus was Acidobacterium (1.8%) in all the samples. In order to analyze species diversity among the collected soil samples, OTUs, community diversity, and Shannon index were measured. Shannon (9.297) and inverse Simpson (0.996) were found to have the highest diversity scores in the greenhouse soil sample of Gyeonggi-do province (GG4). Results from NGS sequencing suggest that, most of the soil samples consists of similar trend of bacterial community and diversity. Environmental factors play a key role in shaping the bacterial community and diversity. In order to address this statement, further correlation analysis between soil physical and chemical parameters with dominant bacterial community will be carried out to observe their interactions.

• Genomics & Informatics
• /
• v.11 no.3
• /
• pp.102-113
• /
• 2013

Metagenomics has become one of the indispensable tools in microbial ecology for the last few decades, and a new revolution in metagenomic studies is now about to begin, with the help of recent advances of sequencing techniques. The massive data production and substantial cost reduction in next-generation sequencing have led to the rapid growth of metagenomic research both quantitatively and qualitatively. It is evident that metagenomics will be a standard tool for studying the diversity and function of microbes in the near future, as fingerprinting methods did previously. As the speed of data accumulation is accelerating, bioinformatic tools and associated databases for handling those datasets have become more urgent and necessary. To facilitate the bioinformatics analysis of metagenomic data, we review some recent tools and databases that are used widely in this field and give insights into the current challenges and future of metagenomics from a bioinformatics perspective.

• Clinical and Experimental Pediatrics
• /
• v.58 no.11
• /
• pp.407-414
• /
• 2015

Early-onset epileptic encephalopathies are one of the most severe early onset epilepsies that can lead to progressive psychomotor impairment. These syndromes result from identifiable primary causes, such as structural, neurodegenerative, metabolic, or genetic defects, and an increasing number of novel genetic causes continue to be uncovered. A typical diagnostic approach includes documentation of anamnesis, determination of seizure semiology, electroencephalography, and neuroimaging. If primary biochemical investigations exclude precipitating conditions, a trial with the administration of a vitaminic compound (pyridoxine, pyridoxal-5-phosphate, or folinic acid) can then be initiated regardless of presumptive seizure causes. Patients with unclear etiologies should be considered for a further workup, which should include an evaluation for inherited metabolic defects and genetic analyses. Targeted next-generation sequencing panels showed a high diagnostic yield in patients with epileptic encephalopathy. Mutations associated with the emergence of epileptic encephalopathies can be identified in a targeted fashion by sequencing the most likely candidate genes. Next-generation sequencing technologies offer hope to a large number of patients with cryptogenic encephalopathies and will eventually lead to new therapeutic strategies and more favorable long-term outcomes.

• Journal of Genetic Medicine
• /
• v.12 no.1
• /
• pp.12-18
• /
• 2015

Malformations of cortical development (MCD) cover a broad spectrum of developmental disorders which cause the various clinical manifestations including epilepsy, developmental delay, and intellectual disability. MCD have been clinically classified based on the disruption of developmental processes such as proliferation, migration, and organization. Molecular genetic studies of MCD have improved our understanding of these disorders at a molecular level beyond the clinical classification. These recent advances are resulted from the development of massive parallel sequencing technology, also known as next-generation sequencing (NGS), which has allowed researchers to uncover novel molecular genetic pathways associated with inherited or de novo mutations. Although an increasing number of disease-related genes or genetic variations have been identified, genotype-phenotype correlation is hampered when the biological or pathological functions of identified genetic variations are not fully understood. To elucidate the causality of genetic variations, in vivo disease models that reflect these variations are required. In the current review, we review the use of NGS technology to identify genes involved in MCD, and discuss how the functions of these identified genes can be validated through in vivo disease modeling.