• Journal of KIISE
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• v.45 no.3
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• pp.200-210
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• 2018

Given a set of DNA read sequences, de novo sequence assembly reconstructs a target sequence without a reference sequence. For reconstruction, the assembly needs the overlap phase, which computes all overlaps between every pair of reads. Since the overlap phase is the most time-consuming part of the whole assembly, the performance of the assembly depends on that of the overlap phase. There have been extensive studies on the overlap phase in various fields. Among them, three state-of-the-art results for the overlap phase are Readjoiner, SOF, and Lim-Park algorithm. Recently, a rapid development of sequencing technology has made it possible to produce a large read dataset at a low cost, and many platforms for generating a DNA read dataset have been developed. Since the platforms produce datasets with different statistical characteristics, a performance evaluation for the overlap phase should consider datasets with these characteristics. In this paper, we compare and analyze the performances of the three algorithms with various large datasets.

• Genomics & Informatics
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• v.10 no.1
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• pp.1-8
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• 2012

Recently, the technologies of DNA sequence variation and gene expression profiling have been used widely as approaches in the expertise of genome biology and genetics. The application to genome study has been particularly developed with the introduction of the nextgeneration DNA sequencer (NGS) Roche/454 and Illumina/ Solexa systems, along with bioinformation analysis technologies of whole-genome $de$ $novo$ assembly, expression profiling, DNA variation discovery, and genotyping. Both massive whole-genome shotgun paired-end sequencing and mate paired-end sequencing data are important steps for constructing $de$ $novo$ assembly of novel genome sequencing data. It is necessary to have DNA sequence information from a multiplatform NGS with at least $2{\times}$ and $30{\times}$ depth sequence of genome coverage using Roche/454 and Illumina/Solexa, respectively, for effective an way of de novo assembly. Massive shortlength reading data from the Illumina/Solexa system is enough to discover DNA variation, resulting in reducing the cost of DNA sequencing. Whole-genome expression profile data are useful to approach genome system biology with quantification of expressed RNAs from a wholegenome transcriptome, depending on the tissue samples. The hybrid mRNA sequences from Rohce/454 and Illumina/Solexa are more powerful to find novel genes through $de$ $novo$ assembly in any whole-genome sequenced species. The $20{\times}$ and $50{\times}$ coverage of the estimated transcriptome sequences using Roche/454 and Illumina/Solexa, respectively, is effective to create novel expressed reference sequences. However, only an average $30{\times}$ coverage of a transcriptome with short read sequences of Illumina/Solexa is enough to check expression quantification, compared to the reference expressed sequence tag sequence.

• Journal of the Korea Society of Computer and Information
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• v.25 no.8
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• pp.1-8
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• 2020

In this paper, we propose a gene family based RNA-seq read distribution method in means to accelerate the overal transcriptome assembly computation time. To measure the performance of our transcriptome sequence data distribution method, we evaluated the performance by testing four types of data sets of the Arabidopsis thaliana genome (Whole Unclassified Reads, Family-Classified Reads, Model-Classified Reads, and Randomly Classified Reads). As a result of de novo transcript assembly in distributed nodes using model classification data, the generated gene contigs matched 95% compared to the contig generated by WUR, and the execution time was reduced by 4.2 times compared to a single node environment using the same resources.

• KIISE Transactions on Computing Practices
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• v.20 no.9
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• pp.513-518
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• 2014

It has become possible for small scale laboratories to interpret large scale genomic DNA, thanks to the reduction of the sequencing cost by the development of next generation sequencing (NGS). De novo assembly is a method which creates a putative original sequence by reconstructing reads without using a reference sequence. There have been various study results on de novo assembly, however, it is still difficult to get the desired results even by using the same assembly procedures and the analysis tools which were suggested in the studies reported. This is mainly because there are no specific guidelines for the assembly procedures or know-hows for the use of such analysis tools. In this study, to resolve these problems, we introduce steps to finding whole genome of an unknown DNA via NGS technology and de novo assembly, while providing the pros and cons of the various analysis tools used in each step. We used 350Mbp of Toxocara canis DNA as an application case for the detailed explanations of each stated step. We also extend our works for prediction of protein-coding genes and their functions from the draft genome sequence by comparing its homology with reference sequences of other nematodes.

• Proceedings of the Plant Resources Society of Korea Conference
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• 2018.04a
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• pp.5-5
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• 2018

Ginseng (Panax ginseng C.A. Meyer), one of the most widely used medicinal plants in traditional oriental medicine, is used for the treatment of various diseases. It has been classified according to its cultivation environment, such as field cultivated ginseng (FCG) and mountain cultivated ginseng (MCG). However, little is known about differences in gene expression in ginseng roots between field cultivated and mountain cultivated ginseng. In order to investigate the whole transcriptome landscape of ginseng, we employed High-Throughput sequencing technologies using the Illumina HiSeqTM2500 system, and generated a large amount of sequenced transcriptome from ginseng roots. Approximately 77 million and 87 million high-quality reads were produced in the FCG and MCG roots transcriptome analyses, respectively, and we obtained 256,032 assembled unigenes with an average length of 1,171 bp by de novo assembly methods. Functional annotations of the unigenes were performed using sequence similarity comparisons against the following databases: the non-redundant nucleotide database, the InterPro domains database, the Gene Ontology Consortium database, and the Kyoto Encyclopedia of Genes and Genomes pathway database. A total of 4,207 unigenes were assigned to specific metabolic pathways, and all of the known enzymes involved in starch and sucrose metabolism pathways were also identified in the KEGG library. This study indicated that alpha-glucan phosphorylase 1, putative pectinesterase/pectinesterase inhibitor 17, beta-amylase, and alpha-glucan phosphorylase isozyme H might be important factors involved in starch and sucrose metabolism between FCG and MCG in different environments.

• The Plant Pathology Journal
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• v.33 no.5
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• pp.478-487
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• 2017

Soybean is the most important legume crop in the world. Several diseases in soybean lead to serious yield losses in major soybean-producing countries. Moreover, soybean can be infected by diverse viruses. Recently, we carried out a large-scale screening to identify viruses infecting soybean using available soybean transcriptome data. Of the screened transcriptomes, a soybean transcriptome for soybean seed development analysis contains several virus-associated sequences. In this study, we identified five viruses, including soybean mosaic virus (SMV), infecting soybean by de novo transcriptome assembly followed by blast search. We assembled a nearly complete consensus genome sequence of SMV China using transcriptome data. Based on phylogenetic analysis, the consensus genome sequence of SMV China was closely related to SMV isolates from South Korea. We examined single nucleotide variations (SNVs) for SMVs in the soybean seed transcriptome revealing 780 SNVs, which were evenly distributed on the SMV genome. Four SNVs, C-U, U-C, A-G, and G-A, were frequently identified. This result demonstrated the quasispecies variation of the SMV genome. Taken together, this study carried out bioinformatics analyses to identify viruses using soybean transcriptome data. In addition, we demonstrated the application of soybean transcriptome data for virus genome assembly and SNV analysis.

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

• Horticultural Science & Technology
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• v.32 no.4
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• pp.535-543
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• 2014

Backcross breeding is the method most commonly used to introgress new traits into elite lines. Conventional backcross breeding requires at least 4-5 generations to recover the genomic background of the recurrent parent. Marker-assisted backcrossing (MABC) represents a new breeding approach that can substantially reduce breeding time and cost. For successful MABC, highly polymorphic markers with known positions in each chromosome are essential. Single nucleotide polymorphism (SNP) markers have many advantages over other marker systems for MABC due to their high abundance and amenability to genotyping automation. To facilitate MABC in hot pepper (Capsicum annuum), we utilized expressed sequence tags (ESTs) to develop SNP markers in this study. For SNP identification, we used Bukang $F_1$-hybrid pepper ESTs to prepare a reference sequence through de novo assembly. We performed large-scale transcriptome sequencing of eight accessions using the Illumina Genome Analyzer (IGA) IIx platform by Solexa, which generated small sequence fragments of about 90-100 bp. By aligning each contig to the reference sequence, 58,151 SNPs were identified. After filtering for polymorphism, segregation ratio, and lack of proximity to other SNPS or exon/intron boundaries, a total of 1,910 putative SNPs were chosen and positioned to a pepper linkage map. We further selected 412 SNPs evenly distributed on each chromosome and primers were designed for high throughput SNP assays and tested using a genetic diversity panel of 27 Capsicum accessions. The SNP markers clearly distinguished each accession. These results suggest that the SNP marker set developed in this study will be valuable for MABC, genetic mapping, and comparative genome analysis.

• Korean Journal of Poultry Science
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• v.41 no.4
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• pp.305-311
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• 2014

Copy number variation (CNV) is a form of structural variation that shows various numbers of copies in segments of the DNA. It has been shown to account for phenotypic variations in human diseases and agricultural production traits. Currently, most of chicken breeds in the poultry industry are based on European-origin breeds that have been mostly provided from several international breeding companies. Therefore, National Institute of Animal Science, RDA has been trying to restore and improve Korean native chicken breeds (12 lines of 5 breeds) for about 20 years. Thanks to the recent advance of sequencing technologies, genome-wide CNV can be accessed in the higher resolution throughout the genome of species of interest. However, there is no systematic study available to dissect the CNV in the native chicken breed in Korea. Here, we report genome-wide copy number variations identified from a genome of Korean native chicken (Line L) by comparing between the chicken reference sequence assembly (Gallus gallus) and a de novo sequencing assembly of the Korean native chicken (Line L). Throughout all twenty eight chicken autosomes, we identified a total of 501 CNVs; defined as gain and loss of duplication and deletion respectively. Furthermore, we performed gene ontology (GO) analysis for the putative CNVs using DAVID, leading to 68 GO terms clustered independently. Of the clustered GO terms, genes related to transcription and gene regulation were mainly detected. This study provides useful genomic resource to investigate potential biological implications of CNVs with traits of interest in the Korean native chicken.

• Genomics & Informatics
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• v.18 no.1
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• pp.5.1-5.5
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• 2020

Highly pathogenic avian influenza (HPAI) viruses have caused severe respiratory disease and death in poultry and human beings. Although most of the avian influenza viruses (AIVs) are of low pathogenicity and cause mild infections in birds, some subtypes including hemagglutinin H5 and H7 subtype cause HPAI. Therefore, sensitive and accurate subtyping of AIV is important to prepare and prevent for the spread of HPAI. Next-generation sequencing (NGS) can analyze the full-length sequence information of entire AIV genome at once, so this technology is becoming a more common in detecting AIVs and predicting subtypes. However, an analysis pipeline of NGS-based AIV sequencing data, including AIV subtyping, has not yet been established. Here, in order to support the pre-processing of NGS data and its interpretation, we developed a user-friendly tool, named prediction of avian influenza virus subtype (PAIVS). PAIVS has multiple functions that support the pre-processing of NGS data, reference-guided AIV subtyping, de novo assembly, variant calling and identifying the closest full-length sequences by BLAST, and provide the graphical summary to the end users.