Whole-genome sequence analysis through online web interfaces: a review

Gunasekara, A.W.A.C.W.R.,Rajapaksha, L.G.T.G.,Tung, T.L. Korea Genome Organization 2022 Genomics & informatics Vol.20 No.1

The recent development of whole-genome sequencing technologies paved the way for understanding the genomes of microorganisms. Every whole-genome sequencing (WGS) project requires a considerable cost and a massive effort to address the questions at hand. The final step of WGS is data analysis. The analysis of whole-genome sequence is dependent on highly sophisticated bioinformatics tools that the research personal have to buy. However, many laboratories and research institutions do not have the bioinformatics capabilities to analyze the genomic data and therefore, are unable to take maximum advantage of whole-genome sequencing. In this aspect, this study provides a guide for research personals on a set of bioinformatics tools available online that can be used to analyze whole-genome sequence data of bacterial genomes. The web interfaces described here have many advantages and, in most cases exempting the need for costly analysis tools and intensive computing resources.

Transposable Elements and Genome Size Variations in Plants

Lee, Sung-Il,Kim, Nam-Soo Korea Genome Organization 2014 Genomics & informatics Vol.12 No.3

Although the number of protein-coding genes is not highly variable between plant taxa, the DNA content in their genomes is highly variable, by as much as 2,056-fold from a 1C amount of 0.0648 pg to 132.5 pg. The mean 1C-value in plants is 2.4 pg, and genome size expansion/contraction is lineage-specific in plant taxonomy. Transposable element fractions in plant genomes are also variable, as low as ~3% in small genomes and as high as ~85% in large genomes, indicating that genome size is a linear function of transposable element content. Of the 2 classes of transposable elements, the dynamics of class 1 long terminal repeat (LTR) retrotransposons is a major contributor to the 1C value differences among plants. The activity of LTR retrotransposons is under the control of epigenetic suppressing mechanisms. Also, genome-purging mechanisms have been adopted to counter-balance the genome size amplification. With a wealth of information on whole-genome sequences in plant genomes, it was revealed that several genome-purging mechanisms have been employed, depending on plant taxa. Two genera, Lilium and Fritillaria, are known to have large genomes in angiosperms. There were twice times of concerted genome size evolutions in the family Liliaceae during the divergence of the current genera in Liliaceae. In addition to the LTR retrotransposons, non-LTR retrotransposons and satellite DNAs contributed to the huge genomes in the two genera by possible failure of genome counter-balancing mechanisms.

Bioinformatics Resources of the Korean Bioinformation Center (KOBIC)

Lee, Byung-Wook,Chu, In-Sun,Kim, Nam-Shin,Lee, Jin-Hyuk,Kim, Seon-Yong,Kim, Wan-Kyu,Lee, Sang-Hyuk Korea Genome Organization 2010 Genomics & informatics Vol.8 No.4

The Korean Bioinformation Center (KOBIC) is a national bioinformatics research center in Korea. We developed many bioinformatics algorithms and applications to facilitate the biological interpretation of OMICS data. Here we present an introduction to major bioinformatics resources of databases and tools developed at KOBIC. These resources are classified into three main fields: genome, proteome, and literature. In the genomic resources, we constructed several pipelines for next generation sequencing (NGS) data processing and developed analysis algorithms and web-based database servers including miRGator, ESTpass, and CleanEST. We also built integrated databases and servers for microarray expression data such as MDCDP. As for the proteome data, VnD database, WDAC, Localizome, and CHARMM_HM web servers are available for various purposes. We constructed IntoPub server and Patome database in the literature field. We continue constructing and maintaining the bioinformatics infrastructure and developing algorithms.

Analysis of differences in human leukocyte antigen between the two Wellcome Trust Case Control Consortium control datasets

Jang, Chloe Soohyun,Choi, Wanson,Cook, Seungho,Han, Buhm Korea Genome Organization 2019 Genomics & informatics Vol.17 No.3

The Wellcome Trust Case Control Consortium (WTCCC) study was a large genome-wide association study that aimed to identify common variants associated with seven diseases. That study combined two control datasets (58C and UK Blood Services) as shared controls. Prior to using the combined controls, the WTCCC performed analyses to show that the genomic content of the control datasets was not significantly different. Recently, the analysis of human leukocyte antigen (HLA) genes has become prevalent due to the development of HLA imputation technology. In this project, we extended the between-control homogeneity analysis of the WTCCC to HLA. We imputed HLA information in the WTCCC control dataset and showed that the HLA content was not significantly different between the two control datasets, suggesting that the combined controls can be used as controls for HLA fine-mapping analysis based on HLA imputation.

MPI-GWAS: a supercomputing-aided permutation approach for genome-wide association studies

Paik, Hyojung,Cho, Yongseong,Cho, Seong Beom,Kwon, Oh-Kyoung Korea Genome Organization 2022 Genomics & informatics Vol.20 No.1

Permutation testing is a robust and popular approach for significance testing in genomic research that has the advantage of reducing inflated type 1 error rates; however, its computational cost is notorious in genome-wide association studies (GWAS). Here, we developed a supercomputing-aided approach to accelerate the permutation testing for GWAS, based on the message-passing interface (MPI) on parallel computing architecture. Our application, called MPI-GWAS, conducts MPI-based permutation testing using a parallel computing approach with our supercomputing system, Nurion (8,305 compute nodes, and 563,740 central processing units [CPUs]). For 10⁷ permutations of one locus in MPI-GWAS, it was calculated in 600 s using 2,720 CPU cores. For 10⁷ permutations of ~30,000-50,000 loci in over 7,000 subjects, the total elapsed time was ~4 days in the Nurion supercomputer. Thus, MPI-GWAS enables us to feasibly compute the permutation-based GWAS within a reason-able time by harnessing the power of parallel computing resources.

COCAW: A Genome-wide Pattern Search System for Designing Microbial Probes

Ryu, Seung-Hee,Park, Kie-Jung,Lee, Do-Hoon,Kim, Cheol-Min Korea Genome Organization 2009 Genomics & informatics Vol.7 No.3

A few bioinformatics tools have been used to find out conserved regions as probes. We have developed a system based on a heuristic method with web interfaces to find out conserved regions against microbial genomes. The system runs in real time by using relative entropy in limited narrow regions and detecting similar regions between pair regions with local alignment. The system could be useful to find out conserved regions as genome-wide scale.

Gene Set Analyses of Genome-Wide Association Studies on 49 Quantitative Traits Measured in a Single Genetic Epidemiology Dataset

Kim, Jihye,Kwon, Ji-Sun,Kim, Sangsoo Korea Genome Organization 2013 Genomics & informatics Vol.11 No.3

Gene set analysis is a powerful tool for interpreting a genome-wide association study result and is gaining popularity these days. Comparison of the gene sets obtained for a variety of traits measured from a single genetic epidemiology dataset may give insights into the biological mechanisms underlying these traits. Based on the previously published single nucleotide polymorphism (SNP) genotype data on 8,842 individuals enrolled in the Korea Association Resource project, we performed a series of systematic genome-wide association analyses for 49 quantitative traits of basic epidemiological, anthropometric, or blood chemistry parameters. Each analysis result was subjected to subsequent gene set analyses based on Gene Ontology (GO) terms using gene set analysis software, GSA-SNP, identifying a set of GO terms significantly associated to each trait ($p_{corr}$ < 0.05). Pairwise comparison of the traits in terms of the semantic similarity in their GO sets revealed surprising cases where phenotypically uncorrelated traits showed high similarity in terms of biological pathways. For example, the pH level was related to 7 other traits that showed low phenotypic correlations with it. A literature survey implies that these traits may be regulated partly by common pathways that involve neuronal or nerve systems.

Genome-Wide Association Study of Liver Enzymes in Korean Children

Park, Tae-Joon,Hwang, Joo-Yeon,Go, Min Jin,Lee, Hye-Ja,Jang, Han Byul,Choi, Youngshim,Kang, Jae Heon,Park, Kyung Hee,Choi, Min-Gyu,Song, Jihyun,Kim, Bong-Jo,Lee, Jong-Young Korea Genome Organization 2013 Genomics & informatics Vol.11 No.3

Liver enzyme elevations, as an indicator of liver function, are widely associated with metabolic diseases. Genome-wide population-based association studies have identified a genetic susceptibility to liver enzyme elevations and their related traits; however, the genetic architecture in childhood remains largely unknown. We performed a genome-wide association study to identify new genetic loci for liver enzyme levels in a Korean childhood cohort (n = 484). We observed three novel loci (rs4949718, rs80311637, and rs596406) that were multiply associated with elevated levels of alanine transaminase and aspartate transaminase. Although there are some limitations, including genetic power, additional replication and functional characterization will support the clarity on the genetic contribution that the ST6GALNAC3, ADAMTS9, and CELF2 genes have in childhood liver function.

Current Status, Challenges, Policies, and Bioethics of Biobanks

Kang, Byunghak,Park, Jaesun,Cho, Sangyun,Lee, Meehee,Kim, Namhee,Min, Haesook,Lee, Sooyoun,Park, Ok,Han, Bokghee Korea Genome Organization 2013 Genomics & informatics Vol.11 No.4

Many biobanks were established as biorepositories for biomedical research, and a number of biobanks were founded in the 1990s. The main aim of the biobank is to store and to maintain biomaterials for studying chronic disease, identifying risk factors of specific diseases, and applying personalized drug therapies. This report provides a review of biobanks, including Korean biobanks and an analysis of sample volumes, regulations, policies, and ethical issues of the biobank. Until now, the top 6 countries according to the number of large-scale biobanks are the United Kingdom, United States, Sweden, France, the Netherlands, and Italy, and there is one major National Biobank of Korea (NBK) and 17 regional biobanks in Korea. Many countries have regulations and guidelines for the biobanks, and the importance of good management of biobanks is increasing. Meanwhile, according to a first survey of 456 biobank managers in the United States, biobankers are concerned with the underuse of the samples in their repositories, which need to be advertised for researchers. Korea Biobank Network (KBN) project phase II (2013-2015) was also planned for the promotion to use biospecimens in the KBN. The KBN is continuously introducing for researchers to use biospecimens in the biobank. An accreditation process can also be introduced for biobanks to harmonize collections and encourage use of biospecimens in the biobanks. KBN is preparing an on-line application system for the distribution of biospecimens and a biobank accreditation program and is trying to harmonize the biobanks.

In silico approach to calculate the transcript capacity

Lee, Young-Sup,Won, Kyung-Hye,Oh, Jae-Don,Shin, Donghyun Korea Genome Organization 2019 Genomics & informatics Vol.17 No.3

We sought the novel concept, transcript capacity (TC) and analyzed TC. Our approach to estimate TC was through an in silico method. TC refers to the capacity that a transcript exerts in a cell as enzyme or protein function after translation. We used the genome-wide association study (GWAS) beta effect and transcription level in RNA-sequencing to estimate TC. The trait was body fat percent and the transcript reads were obtained from the human protein atlas. The assumption was that the GWAS beta effect is the gene's effect and TC was related to the corresponding gene effect and transcript reads. Further, we surveyed gene ontology (GO) in the highest TC and the lowest TC genes. The most frequent GOs with the highest TC were neuronal-related and cell projection organization related. The most frequent GOs with the lowest TC were wound-healing related and embryo development related. We expect that our analysis contributes to estimating TC in the diverse species and playing a benevolent role to the new bioinformatic analysis.