• Genomics & Informatics
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• v.11 no.4
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• pp.218-223
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• 2013

The rapid advances in genetic knowledge and technology raise various, sometimes unprecedented, ethical dilemmas in the scientific community as well as the public realm. To deal with these dilemmas, the international community has prepared and issued ethical standards in various formats. In this review, seven international standards regarding genetics and genomics will be briefly introduced in chronological order. Critical reflections on them will not be provided in this review, and naturally, they have their own problems and shortcomings. However, a common set of the principles expressed in them will be highlighted here, because they are still relevant, and many of them will be more relevant in the future. Some of the interesting contents will be selected and described. After that, the morality of one recent event related to whole-genome sequencing and person-identifiable genetic data will be explored based on those international standards.

• Journal of Microbiology and Biotechnology
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• v.12 no.6
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• pp.1022-1025
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• 2002

Club root is one of the major diseases that occur in crucifers. It is caused by Plasmodiophora brassicae. In order to discover microbial biopesticides against P. brassicae, forty-eight Streptomyces isolated from soil were screened. Among these, three strains showed excellent pesticidal activities. We report results on in vivo screening with fermentation broths of these strains and identification of the strain taxa.

• Genomics & Informatics
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• v.19 no.4
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• pp.51.1-51.8
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• 2021

This study explored the trends of Genomics & Informatics during the period of 2003-2018 in comparison with 11 other scholarly journals: BMC Bioinformatics, Algorithms for Molecular Biology: AMB, BMC Systems Biology, Journal of Computational Biology, Briefings in Bioinformatics, BMC Genomics, Nucleic Acids Research, American Journal of Human Genetics, Oncogenesis, Disease Markers, and Microarrays. In total, 22,423 research articles were reviewed. Content analysis was the main method employed in the current research. The results were interpreted using descriptive analysis, a clustering analysis, word embedding, and deep learning techniques. Trends are discussed for the 12 journals, both individually and collectively. This is an extension of our previous study (PMCID: PMC6808643).

• Genomics & Informatics
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• v.9 no.1
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• pp.39-43
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• 2011

MicroRNAs (miRNAs) are recently discovered small RNA molecules usually resulting in translational repression and gene silencing. Despite the fact that specific cloning of small RNA's is a method in practice, computational identification of miRNA's has been a major focus recent days, since is a rapid process following AB initio and sequence alignment methods. Here we developed new software called MiRPI that aims to identify the highly conserved miRNAs without any mismatches from given fasta formatted gene sequences by using non-repeated miRNA dataset of the user's interest. The new window embedded with the software is used to identify the targets for inputted mature miRNAs in the mRNA sequences. Also MiRPI is designed to measure the precursor miRNA statistics, majorly focusing the Adjusted Minimum Folding free Energy (AMFE) and Minimum Folding free Energy Index (MFEI), the most important parameters in miRNA confirmation. MiRPI is developed by PERL (Practical Extraction and Report Language) and Tk (Tool kit widgets) scripting languages. It is user friendly, portable offline software that works in all windows OS, sized to 3 MB.

• Genomics & Informatics
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• v.15 no.4
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• pp.170-177
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• 2017

HOTAIR is an lncRNA that has been known to have an oncogenic role in different cancers. There is limited knowledge of genetic and epigenetic elements and their interactions for the gene encoding HOTAIR. Therefore, understanding the molecular mechanism and its regulation remains to be challenging. We used different in silico analyses to find genetic and epigenetic elements of HOTAIR gene to gain insight into its regulation. We reported different regulatory elements including canonical promoters, transcription start sites, CpGIs as well as epigenetic marks that are potentially involved in the regulation of HOTAIR gene expression. We identified repeat sequences and single nucleotide polymorphisms that are located within or next to the CpGIs of HOTAIR. Our analyses may help to find potential interactions between genetic and epigenetic elements of HOTAIR gene in the human tissues and show opportunities and limitations for researches on HOTAIR gene in future studies.

• Genomics & Informatics
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• v.1 no.2
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• pp.108-112
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• 2003

We have constructed a molecular linkage map of pepper (Capsicum spp.) in an interspecific $F_2$ population of 107 plants with 320 RFLP, 136 AFLP, and 46 SSR markers. The resulting linkage map consists of 15 linkage groups covering 1,720 cM with an average map distance of 3.7 cM between framework markers. Most RFLP markers ($80\%$) were pepper-derived clones and these markers were evenly distributed all over the genome. Genes for defense and biosynthesis of carotenoids and capsaicinoids were mapped on this linkage map. By using 30 primer combinations, AFLP markers were generated in the $F_2$ population. For development of SSR markers in Capsicum, microsatellites were isolated from two small-insert genomic libraries and the GenBank database. This combined map provides a starting point for high-resolution QTL analysis, gene isolation, and molecular breeding.

• Genomics & Informatics
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• v.12 no.4
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• pp.261-267
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• 2014

MicroRNAs (miRNAs) are known for their role in mRNA silencing via interference pathways. Repetitive elements (REs) share several characteristics with endogenous precursor miRNAs. In this study, 406 previously identified and 1,494 novel RE-derived miRNAs were sorted from the GENCODE v.19 database using the RepeatMasker program. They were divided into six major types, based on their genomic structure. More novel RE-derived miRNAs were confirmed than identified as RE-derived miRNAs. In conclusion, many miRNAs have not yet been identified, most of which are derived from REs.

• Genomics & Informatics
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• v.11 no.2
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• pp.60-67
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• 2013

A decade-long project, led by several international research groups, called the Encyclopedia of DNA Elements (ENCODE), recently released an unprecedented amount of data. The ambitious project covers transcriptome, cistrome, epigenome, and interactome data from more than 1,600 sets of experiments in human. To make use of this valuable resource, it is important to understand the information it represents and the techniques that were used to generate these data. In this review, we introduce the data that ENCODE generated, summarize the observations from the data analysis, and revisit a computational approach that ENCODE used to predict gene expression, with a focus on the human transcriptome and its association with chromatin modifications.

• Genomics & Informatics
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• v.11 no.4
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• pp.191-199
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• 2013

High-throughput next-generation sequencing (NGS) technology produces a tremendous amount of raw sequence data. The challenges for researchers are to process the raw data, to map the sequences to genome, to discover variants that are different from the reference genome, and to prioritize/rank the variants for the question of interest. The recent development of many computational algorithms and programs has vastly improved the ability to translate sequence data into valuable information for disease gene identification. However, the NGS data analysis is complex and could be overwhelming for researchers who are not familiar with the process. Here, we outline the analysis pipeline and describe some of the most commonly used principles and tools for analyzing NGS data for disease gene identification.

• Genomics & Informatics
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• v.16 no.4
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• pp.17.1-17.6
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• 2018

Tumor heterogeneity, the cellular mosaic of multiple lineages arising from the process of clonal evolution, has continued to thwart multi-omics analyses using traditional bulk sequencing methods. The application of single-cell sequencing, in concert with existing genomics methods, has enabled high-resolution interrogation of the genome, transcriptome, epigenome, and proteome. Applied to cancers, these single-cell multi-omics methods bypass previous limitations on data resolution and have enabled a more nuanced understanding of the evolutionary dynamics of tumor progression, immune evasion, metastasis, and treatment resistance. This review details the growing number of novel single-cell multi-omics methods applied to tumors and further discusses recent discoveries emerging from these approaches, especially in regard to immunotherapy.