1
|
Ara T, Kodama Y, Tokimatsu T, Fukuda A, Kosuge T, Mashima J, Tanizawa Y, Tanjo T, Ogasawara O, Fujisawa T, Nakamura Y, Arita M. DDBJ update in 2023: the MetaboBank for metabolomics data and associated metadata. Nucleic Acids Res 2024; 52:D67-D71. [PMID: 37971299 PMCID: PMC10767850 DOI: 10.1093/nar/gkad1046] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/12/2023] [Revised: 10/21/2023] [Accepted: 10/27/2023] [Indexed: 11/19/2023] Open
Abstract
The Bioinformation and DNA Data Bank of Japan (DDBJ) Center (https://www.ddbj.nig.ac.jp) provides database archives that cover a wide range of fields in life sciences. As a founding member of the International Nucleotide Sequence Database Collaboration (INSDC), DDBJ accepts and distributes nucleotide sequence data as well as their study and sample information along with the National Center for Biotechnology Information in the United States and the European Bioinformatics Institute (EBI). Besides INSDC databases, the DDBJ Center provides databases for functional genomics (GEA: Genomic Expression Archive), metabolomics (MetaboBank) and human genetic and phenotypic data (JGA: Japanese Genotype-phenotype Archive). These database systems have been built on the National Institute of Genetics (NIG) supercomputer, which is also open for domestic life science researchers to analyze large-scale sequence data. This paper reports recent updates on the archival databases and the services of the DDBJ Center, highlighting the newly redesigned MetaboBank. MetaboBank uses BioProject and BioSample in its metadata description making it suitable for multi-omics large studies. Its collaboration with MetaboLights at EBI brings synergy in locating and reusing public data.
Collapse
Affiliation(s)
- Takeshi Ara
- Bioinformation and DDBJ Center, National Institute of Genetics, Mishima, Shizuoka 411-8540, Japan
| | - Yuichi Kodama
- Bioinformation and DDBJ Center, National Institute of Genetics, Mishima, Shizuoka 411-8540, Japan
| | - Toshiaki Tokimatsu
- Bioinformation and DDBJ Center, National Institute of Genetics, Mishima, Shizuoka 411-8540, Japan
| | - Asami Fukuda
- Bioinformation and DDBJ Center, National Institute of Genetics, Mishima, Shizuoka 411-8540, Japan
| | - Takehide Kosuge
- Bioinformation and DDBJ Center, National Institute of Genetics, Mishima, Shizuoka 411-8540, Japan
| | - Jun Mashima
- Bioinformation and DDBJ Center, National Institute of Genetics, Mishima, Shizuoka 411-8540, Japan
| | - Yasuhiro Tanizawa
- Bioinformation and DDBJ Center, National Institute of Genetics, Mishima, Shizuoka 411-8540, Japan
| | - Tomoya Tanjo
- Bioinformation and DDBJ Center, National Institute of Genetics, Mishima, Shizuoka 411-8540, Japan
| | - Osamu Ogasawara
- Bioinformation and DDBJ Center, National Institute of Genetics, Mishima, Shizuoka 411-8540, Japan
| | - Takatomo Fujisawa
- Bioinformation and DDBJ Center, National Institute of Genetics, Mishima, Shizuoka 411-8540, Japan
| | - Yasukazu Nakamura
- Bioinformation and DDBJ Center, National Institute of Genetics, Mishima, Shizuoka 411-8540, Japan
| | - Masanori Arita
- Bioinformation and DDBJ Center, National Institute of Genetics, Mishima, Shizuoka 411-8540, Japan
| |
Collapse
|
2
|
Isogai H, Ogasawara O. Is There a Correlation Between Left Ventricular Outflow Tract Velocity Time Integral and Stroke Volume Index in Patients Undergoing Cardiac Surgery? Cureus 2022; 14:e27257. [PMID: 36039242 PMCID: PMC9403260 DOI: 10.7759/cureus.27257] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 07/23/2022] [Indexed: 11/28/2022] Open
Abstract
Introduction Left ventricular outflow tract velocity time integral (LVOT VTI) is a promising surrogate for stroke volume (SV). However, there is controversy in the literature regarding its correlation with thermodilution or newer cardiac output measurement techniques. This study was conducted to determine the correlation between LVOT VTI determined by transesophageal echocardiography (TEE) with stroke volume index (SVI) calculated by thermodilution. Methods Consecutive patients older than 17 years undergoing elective cardiac surgery with pulmonary artery catheter (PAC) and TEE monitoring between September 2021 and February 2022 were included in this prospective, descriptive, single-center study. LVOT VTI was measured using TEE after induction of anesthesia but before skin incision and at least four hours after initial LVOT VTI measurement. SVI was simultaneously measured using the continuous thermodilution technique with a PAC. The correlation between LVOT VTI and SVI was determined with Pearson’s correlation index. Results Twelve patients were included and 21 paired measurements were compared. Mean SVI was 31.62 ± 10.71 mL/m2 and mean LVOT VTI was 14.74 ± 4.79 cm. The Pearson's correlation index for the two measurements was r = 0.257, p = 0.262. Conclusion This prospective study demonstrated a weak correlation between LVOT VTI and SVI in patients undergoing cardiac surgery.
Collapse
|
3
|
Okido T, Kodama Y, Mashima J, Kosuge T, Fujisawa T, Ogasawara O. DNA Data Bank of Japan (DDBJ) update report 2021. Nucleic Acids Res 2021; 50:D102-D105. [PMID: 34751405 PMCID: PMC8689959 DOI: 10.1093/nar/gkab995] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/11/2021] [Revised: 10/08/2021] [Accepted: 10/12/2021] [Indexed: 11/29/2022] Open
Abstract
The Bioinformation and DDBJ (DNA Data Bank of Japan) Center (DDBJ Center; https://www.ddbj.nig.ac.jp) operates archival databases that collect nucleotide sequences, study and sample information, and distribute them without access restriction to progress life science research as a member of the International Nucleotide Sequence Database Collaboration (INSDC), in collaboration with the National Center for Biotechnology Information (NCBI) and the European Bioinformatics Institute. Besides the INSDC databases, the DDBJ Center also provides the Genomic Expression Archive for functional genomics data and the Japanese Genotype-phenotype Archive for human data requiring controlled access. Additionally, the DDBJ Center started a new public repository, MetaboBank, for experimental raw data and metadata from metabolomics research in October 2020. In response to the COVID-19 pandemic, the DDBJ Center openly shares SARS-CoV-2 genome sequences in collaboration with Shizuoka Prefecture and Keio University. The operation of DDBJ is based on the National Institute of Genetics (NIG) supercomputer, which is open for large-scale sequence data analysis for life science researchers. This paper reports recent updates on the archival databases and the services of DDBJ.
Collapse
Affiliation(s)
- Toshihisa Okido
- Bioinformation and DDBJ Center, National Institute of Genetics, Mishima, Shizuoka 411-8540, Japan
| | - Yuichi Kodama
- Bioinformation and DDBJ Center, National Institute of Genetics, Mishima, Shizuoka 411-8540, Japan
| | - Jun Mashima
- Bioinformation and DDBJ Center, National Institute of Genetics, Mishima, Shizuoka 411-8540, Japan
| | - Takehide Kosuge
- Bioinformation and DDBJ Center, National Institute of Genetics, Mishima, Shizuoka 411-8540, Japan
| | - Takatomo Fujisawa
- Bioinformation and DDBJ Center, National Institute of Genetics, Mishima, Shizuoka 411-8540, Japan
| | - Osamu Ogasawara
- Bioinformation and DDBJ Center, National Institute of Genetics, Mishima, Shizuoka 411-8540, Japan
| |
Collapse
|
4
|
Fukuda A, Kodama Y, Mashima J, Fujisawa T, Ogasawara O. DDBJ update: streamlining submission and access of human data. Nucleic Acids Res 2021; 49:D71-D75. [PMID: 33156332 PMCID: PMC7779041 DOI: 10.1093/nar/gkaa982] [Citation(s) in RCA: 19] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/10/2020] [Revised: 10/09/2020] [Accepted: 10/12/2020] [Indexed: 01/25/2023] Open
Abstract
The Bioinformation and DDBJ Center (DDBJ Center, https://www.ddbj.nig.ac.jp) provides databases that capture, preserve and disseminate diverse biological data to support research in the life sciences. This center collects nucleotide sequences with annotations, raw sequencing data, and alignment information from high-throughput sequencing platforms, and study and sample information, in collaboration with the National Center for Biotechnology Information (NCBI) and the European Bioinformatics Institute (EBI). This collaborative framework is known as the International Nucleotide Sequence Database Collaboration (INSDC). In collaboration with the National Bioscience Database Center (NBDC), the DDBJ Center also provides a controlled-access database, the Japanese Genotype–phenotype Archive (JGA), which archives and distributes human genotype and phenotype data, requiring authorized access. The NBDC formulates guidelines and policies for sharing human data and reviews data submission and use applications. To streamline all of the processes at NBDC and JGA, we have integrated the two systems by introducing a unified login platform with a group structure in September 2020. In addition to the public databases, the DDBJ Center provides a computer resource, the NIG supercomputer, for domestic researchers to analyze large-scale genomic data. This report describes updates to the services of the DDBJ Center, focusing on the NBDC and JGA system enhancements.
Collapse
Affiliation(s)
- Asami Fukuda
- Bioinformation and DDBJ Center, National Institute of Genetics, Mishima, Shizuoka 411-8540, Japan
| | - Yuichi Kodama
- Bioinformation and DDBJ Center, National Institute of Genetics, Mishima, Shizuoka 411-8540, Japan
| | - Jun Mashima
- Bioinformation and DDBJ Center, National Institute of Genetics, Mishima, Shizuoka 411-8540, Japan
| | - Takatomo Fujisawa
- Bioinformation and DDBJ Center, National Institute of Genetics, Mishima, Shizuoka 411-8540, Japan
| | - Osamu Ogasawara
- Bioinformation and DDBJ Center, National Institute of Genetics, Mishima, Shizuoka 411-8540, Japan
| |
Collapse
|
5
|
Tanjo T, Kawai Y, Tokunaga K, Ogasawara O, Nagasaki M. Practical guide for managing large-scale human genome data in research. J Hum Genet 2021; 66:39-52. [PMID: 33097812 PMCID: PMC7728600 DOI: 10.1038/s10038-020-00862-1] [Citation(s) in RCA: 16] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/24/2020] [Revised: 10/08/2020] [Accepted: 10/11/2020] [Indexed: 12/24/2022]
Abstract
Studies in human genetics deal with a plethora of human genome sequencing data that are generated from specimens as well as available on public domains. With the development of various bioinformatics applications, maintaining the productivity of research, managing human genome data, and analyzing downstream data is essential. This review aims to guide struggling researchers to process and analyze these large-scale genomic data to extract relevant information for improved downstream analyses. Here, we discuss worldwide human genome projects that could be integrated into any data for improved analysis. Obtaining human whole-genome sequencing data from both data stores and processes is costly; therefore, we focus on the development of data format and software that manipulate whole-genome sequencing. Once the sequencing is complete and its format and data processing tools are selected, a computational platform is required. For the platform, we describe a multi-cloud strategy that balances between cost, performance, and customizability. A good quality published research relies on data reproducibility to ensure quality results, reusability for applications to other datasets, as well as scalability for the future increase of datasets. To solve these, we describe several key technologies developed in computer science, including workflow engine. We also discuss the ethical guidelines inevitable for human genomic data analysis that differ from model organisms. Finally, the future ideal perspective of data processing and analysis is summarized.
Collapse
Affiliation(s)
- Tomoya Tanjo
- National Institute of Informatics, Tokyo, 101-8430, Japan
| | - Yosuke Kawai
- Genome Medical Science Project, National Center for Global Health and Medicine, Tokyo, 162-8655, Japan
| | - Katsushi Tokunaga
- Genome Medical Science Project, National Center for Global Health and Medicine, Tokyo, 162-8655, Japan
| | - Osamu Ogasawara
- The Bioinformation and DDBJ Center, National Institute of Genetics, Mishima, Shizuoka, 411-8540, Japan.
| | - Masao Nagasaki
- Center for the Promotion of Interdisciplinary Education and Research, Kyoto University, Sakyo-ku, Kyoto, 606-8507, Japan.
- Center for Genomic Medicine, Kyoto University Graduate School of Medicine, Sakyo-ku, Kyoto, 606-8507, Japan.
| |
Collapse
|
6
|
Kodama Y, Mashima J, Kosuge T, Ogasawara O. DDBJ update: the Genomic Expression Archive (GEA) for functional genomics data. Nucleic Acids Res 2020; 47:D69-D73. [PMID: 30357349 PMCID: PMC6323915 DOI: 10.1093/nar/gky1002] [Citation(s) in RCA: 31] [Impact Index Per Article: 7.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/14/2018] [Accepted: 10/09/2018] [Indexed: 12/13/2022] Open
Abstract
The Genomic Expression Archive (GEA) for functional genomics data from microarray and high-throughput sequencing experiments has been established at the DNA Data Bank of Japan (DDBJ) Center (https://www.ddbj.nig.ac.jp), which is a member of the International Nucleotide Sequence Database Collaboration (INSDC) with the US National Center for Biotechnology Information and the European Bioinformatics Institute. The DDBJ Center collects nucleotide sequence data and associated biological information from researchers and also services the Japanese Genotype–phenotype Archive (JGA) with the National Bioscience Database Center for collecting human data. To automate the submission process, we have implemented the DDBJ BioSample validator which checks submitted records, auto-corrects their format, and issues error messages and warnings if necessary. The DDBJ Center also operates the NIG supercomputer, prepared for analyzing large-scale genome sequences. We now offer a secure platform specifically to handle personal human genomes. This report describes database activities for INSDC and JGA over the past year, the newly launched GEA, submission, retrieval, and analysis services available in our supercomputer system and their recent developments.
Collapse
Affiliation(s)
- Yuichi Kodama
- DDBJ Center, National Institute of Genetics, Shizuoka 411-8540, Japan
| | - Jun Mashima
- DDBJ Center, National Institute of Genetics, Shizuoka 411-8540, Japan
| | - Takehide Kosuge
- DDBJ Center, National Institute of Genetics, Shizuoka 411-8540, Japan
| | - Osamu Ogasawara
- DDBJ Center, National Institute of Genetics, Shizuoka 411-8540, Japan
| |
Collapse
|
7
|
Kaminuma E, Baba Y, Mochizuki M, Matsumoto H, Ozaki H, Okayama T, Kato T, Oki S, Fujisawa T, Nakamura Y, Arita M, Ogasawara O, Kashima H, Takagi T. DDBJ Data Analysis Challenge: a machine learning competition to predict Arabidopsis chromatin feature annotations from DNA sequences. Genes Genet Syst 2020; 95:43-50. [PMID: 32213716 DOI: 10.1266/ggs.19-00034] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/23/2022] Open
Abstract
Recently, the prospect of applying machine learning tools for automating the process of annotation analysis of large-scale sequences from next-generation sequencers has raised the interest of researchers. However, finding research collaborators with knowledge of machine learning techniques is difficult for many experimental life scientists. One solution to this problem is to utilise the power of crowdsourcing. In this report, we describe how we investigated the potential of crowdsourced modelling for a life science task by conducting a machine learning competition, the DNA Data Bank of Japan (DDBJ) Data Analysis Challenge. In the challenge, participants predicted chromatin feature annotations from DNA sequences with competing models. The challenge engaged 38 participants, with a cumulative total of 360 model submissions. The performance of the top model resulted in an area under the curve (AUC) score of 0.95. Over the course of the competition, the overall performance of the submitted models improved by an AUC score of 0.30 from the first submitted model. Furthermore, the 1st- and 2nd-ranking models utilised external data such as genomic location and gene annotation information with specific domain knowledge. The effect of incorporating this domain knowledge led to improvements of approximately 5%-9%, as measured by the AUC scores. This report suggests that machine learning competitions will lead to the development of highly accurate machine learning models for use by experimental scientists unfamiliar with the complexities of data science.
Collapse
Affiliation(s)
- Eli Kaminuma
- Center for Information Biology, National Institute of Genetics
| | - Yukino Baba
- Graduate School of Informatics, Kyoto University
| | | | - Hirotaka Matsumoto
- Laboratory for Bioinformatics Research, RIKEN Center for Biosystems Dynamics Research
| | - Haruka Ozaki
- Laboratory for Bioinformatics Research, RIKEN Center for Biosystems Dynamics Research
| | | | - Takuya Kato
- Graduate School of Information Science and Technology, The University of Tokyo
| | - Shinya Oki
- Graduate School of Medical Sciences, Kyushu University
| | | | | | - Masanori Arita
- Center for Information Biology, National Institute of Genetics
| | - Osamu Ogasawara
- Center for Information Biology, National Institute of Genetics
| | | | - Toshihisa Takagi
- Center for Information Biology, National Institute of Genetics.,Graduate School of Science, The University of Tokyo
| |
Collapse
|
8
|
Ogasawara O, Kojima T, Miyazu M, Sobue K. Impact of the stress ulcer prophylactic protocol on reducing the unnecessary administration of stress ulcer medications and gastrointestinal bleeding: a single-center, retrospective pre-post study. J Intensive Care 2020; 8:10. [PMID: 31988751 PMCID: PMC6966877 DOI: 10.1186/s40560-020-0427-8] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/21/2019] [Accepted: 01/09/2020] [Indexed: 12/11/2022] Open
Abstract
Background Clinically significant gastrointestinal bleeding from stress ulcers increases patient mortality in intensive care, and histamine type 2 receptor blockers and proton pump inhibitors as stress ulcer prophylaxes were reported to decrease the incidence of that. Although medical checklists are widely used to maintain high compliance with medications and interventions to improve patient outcome in the intensive care field, the efficacy of medical checklists regarding the incidence of gastrointestinal bleeding and the reduction of unnecessary administration of stress ulcer prophylaxis medications has not been sufficiently explored to date. This study aimed to investigate the incidence of gastrointestinal bleeding and the rate of administering stress ulcer prophylaxis medication before and after setting administration criteria for stress ulcer prophylaxis and introducing a medical checklist for critically ill adults. Methods This was a retrospective pre-post study at a single-center, tertiary adult and pediatric mixed ICU. Adult patients (≥ 18 years) who were admitted to the ICU for reasons other than gastrectomy, esophagectomy, pancreatoduodenectomy, and gastrointestinal bleeding were analyzed. A medical checklist and stress ulcer prophylaxis criteria were introduced on December 22, 2014, and the patients were classified into the preintervention group (from September to December 21, 2014) and the postintervention group (from December 22, 2014, to April 2015). The primary outcome was the incidence of upper gastrointestinal bleeding, and the secondary outcome was the proportion administered stress ulcer prophylaxis medications. Results One hundred adult patients were analyzed. The incidence of upper gastrointestinal bleeding in the pre- and postintervention groups was both 4.0% [95% confidence interval, 0.5–13.7%]. The proportion administered stress ulcer prophylaxis medications decreased from 100 to 38% between the pre- and post-intervention groups. Conclusions After the checklist and the criteria were introduced, the administration of stress ulcer prophylaxis medications decreased without an increase in upper gastrointestinal bleeding in critically ill adults. Prospective studies are necessary to evaluate the causal relationship between the introduction of them and gastrointestinal adverse events in critically ill adults.
Collapse
Affiliation(s)
- Osamu Ogasawara
- 1Department of Anesthesiology and Intensive Care Medicine, Nagoya City University Graduate School of Medical Science, 1-Kawasumi, Mizuho-cho, Mizuho-ku, Nagoya, Aichi 467-8601 Japan
| | - Taiki Kojima
- Department of Anesthesiology, Aichi Children's Health and Medical Center, 7-426, Morioka-cho, Obu, Aichi 474-0031 Japan
| | - Mitsunori Miyazu
- Department of Anesthesiology, Aichi Children's Health and Medical Center, 7-426, Morioka-cho, Obu, Aichi 474-0031 Japan
| | - Kazuya Sobue
- 1Department of Anesthesiology and Intensive Care Medicine, Nagoya City University Graduate School of Medical Science, 1-Kawasumi, Mizuho-cho, Mizuho-ku, Nagoya, Aichi 467-8601 Japan
| |
Collapse
|
9
|
Ogasawara O, Kodama Y, Mashima J, Kosuge T, Fujisawa T. DDBJ Database updates and computational infrastructure enhancement. Nucleic Acids Res 2020; 48:D45-D50. [PMID: 31724722 PMCID: PMC7145692 DOI: 10.1093/nar/gkz982] [Citation(s) in RCA: 19] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/26/2019] [Revised: 10/10/2019] [Accepted: 10/21/2019] [Indexed: 12/30/2022] Open
Abstract
The Bioinformation and DDBJ Center (https://www.ddbj.nig.ac.jp) in the National Institute of Genetics (NIG) maintains a primary nucleotide sequence database as a member of the International Nucleotide Sequence Database Collaboration (INSDC) in partnership with the US National Center for Biotechnology Information and the European Bioinformatics Institute. The NIG operates the NIG supercomputer as a computational basis for the construction of DDBJ databases and as a large-scale computational resource for Japanese biologists and medical researchers. In order to accommodate the rapidly growing amount of deoxyribonucleic acid (DNA) nucleotide sequence data, NIG replaced its supercomputer system, which is designed for big data analysis of genome data, in early 2019. The new system is equipped with 30 PB of DNA data archiving storage; large-scale parallel distributed file systems (13.8 PB in total) and 1.1 PFLOPS computation nodes and graphics processing units (GPUs). Moreover, as a starting point of developing multi-cloud infrastructure of bioinformatics, we have also installed an automatic file transfer system that allows users to prevent data lock-in and to achieve cost/performance balance by exploiting the most suitable environment from among the supercomputer and public clouds for different workloads.
Collapse
Affiliation(s)
- Osamu Ogasawara
- The Bioinformation and DDBJ Center, National Institute of Genetics, Mishima, Shizuoka, 411-8540, Japan
| | - Yuichi Kodama
- The Bioinformation and DDBJ Center, National Institute of Genetics, Mishima, Shizuoka, 411-8540, Japan
| | - Jun Mashima
- The Bioinformation and DDBJ Center, National Institute of Genetics, Mishima, Shizuoka, 411-8540, Japan
| | - Takehide Kosuge
- The Bioinformation and DDBJ Center, National Institute of Genetics, Mishima, Shizuoka, 411-8540, Japan
| | - Takatomo Fujisawa
- The Bioinformation and DDBJ Center, National Institute of Genetics, Mishima, Shizuoka, 411-8540, Japan
| |
Collapse
|
10
|
Inami C, Tanihira H, Kikuta S, Ogasawara O, Sobue K, Kume K, Osanai M, Ohsawa M. Visualization of Brain Activity in a Neuropathic Pain Model Using Quantitative Activity-Dependent Manganese Magnetic Resonance Imaging. Front Neural Circuits 2019; 13:74. [PMID: 31849617 PMCID: PMC6889800 DOI: 10.3389/fncir.2019.00074] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/12/2018] [Accepted: 10/31/2019] [Indexed: 11/13/2022] Open
Abstract
Human brain imaging studies have revealed several regions that are activated in patients with chronic pain. In rodent brains, functional changes due to chronic pain have not been fully elucidated, as brain imaging techniques such as functional magnetic resonance imaging and positron emission tomography (PET) require the use of anesthesia to suppress movement. Consequently, conclusions derived from existing imaging studies in rodents may not accurately reflect brain activity under awake conditions. In this study, we used quantitative activation-induced manganese-enhanced magnetic resonance imaging to directly capture the previous brain activity of awake mice. We also observed and quantified the brain activity of the spared nerve injury (SNI) neuropathic pain model during awake conditions. SNI-operated mice exhibited a robust decrease of mechanical nociceptive threshold 14 days after nerve injury. Imaging on SNI-operated mice revealed increased neural activity in the limbic system and secondary somatosensory, sensory-motor, piriform, and insular cortex. We present the first study demonstrating a direct measurement of awake neural activity in a neuropathic pain mouse model.
Collapse
Affiliation(s)
- Chihiro Inami
- Department of Neuropharmacology, Graduate School of Pharmaceutical Sciences, Nagoya City University, Nagoya, Japan
| | - Hiroki Tanihira
- Graduate School of Medicine, Tohoku University, Sendai, Japan
| | - Satomi Kikuta
- Graduate School of Medicine, Tohoku University, Sendai, Japan.,Systems Neuroscience Section, Primate Research Institute, Kyoto University, Inuyama, Japan
| | - Osamu Ogasawara
- Department of Anesthesiology, Graduate School of Medicine, Nagoya City University, Nagoya, Japan
| | - Kazuya Sobue
- Department of Anesthesiology, Graduate School of Medicine, Nagoya City University, Nagoya, Japan
| | - Kazuhiko Kume
- Department of Neuropharmacology, Graduate School of Pharmaceutical Sciences, Nagoya City University, Nagoya, Japan
| | - Makoto Osanai
- Graduate School of Medicine, Tohoku University, Sendai, Japan.,Graduate School of Biomedical Engineering, Tohoku University, Sendai, Japan.,Division of Health Sciences, Department of Medical Physics and Engineering, Graduate School of Medicine, Osaka University, Suita, Japan
| | - Masahiro Ohsawa
- Department of Neuropharmacology, Graduate School of Pharmaceutical Sciences, Nagoya City University, Nagoya, Japan
| |
Collapse
|
11
|
Kodama Y, Mashima J, Kosuge T, Kaminuma E, Ogasawara O, Okubo K, Nakamura Y, Takagi T. DNA Data Bank of Japan: 30th anniversary. Nucleic Acids Res 2019; 46:D30-D35. [PMID: 29040613 PMCID: PMC5753283 DOI: 10.1093/nar/gkx926] [Citation(s) in RCA: 44] [Impact Index Per Article: 8.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/15/2017] [Accepted: 10/02/2017] [Indexed: 11/17/2022] Open
Abstract
The DNA Data Bank of Japan (DDBJ) Center (http://www.ddbj.nig.ac.jp) has been providing public data services for 30 years since 1987. We are collecting nucleotide sequence data and associated biological information from researchers as a member of the International Nucleotide Sequence Database Collaboration (INSDC), in collaboration with the US National Center for Biotechnology Information and the European Bioinformatics Institute. The DDBJ Center also services the Japanese Genotype-phenotype Archive (JGA) with the National Bioscience Database Center to collect genotype and phenotype data of human individuals. Here, we outline our database activities for INSDC and JGA over the past year, and introduce submission, retrieval and analysis services running on our supercomputer system and their recent developments. Furthermore, we highlight our responses to the amended Japanese rules for the protection of personal information and the launch of the DDBJ Group Cloud service for sharing pre-publication data among research groups.
Collapse
Affiliation(s)
- Yuichi Kodama
- DDBJ Center, National Institute of Genetics, Shizuoka 411-8540, Japan
| | - Jun Mashima
- DDBJ Center, National Institute of Genetics, Shizuoka 411-8540, Japan
| | - Takehide Kosuge
- DDBJ Center, National Institute of Genetics, Shizuoka 411-8540, Japan
| | - Eli Kaminuma
- DDBJ Center, National Institute of Genetics, Shizuoka 411-8540, Japan
| | - Osamu Ogasawara
- DDBJ Center, National Institute of Genetics, Shizuoka 411-8540, Japan
| | - Kousaku Okubo
- DDBJ Center, National Institute of Genetics, Shizuoka 411-8540, Japan
| | - Yasukazu Nakamura
- DDBJ Center, National Institute of Genetics, Shizuoka 411-8540, Japan
| | - Toshihisa Takagi
- DDBJ Center, National Institute of Genetics, Shizuoka 411-8540, Japan.,National Bioscience Database Center, Japan Science and Technology Agency, Tokyo 102-8666, Japan
| |
Collapse
|
12
|
Ohta T, Tanjo T, Ogasawara O. Accumulating computational resource usage of genomic data analysis workflow to optimize cloud computing instance selection. Gigascience 2019; 8:giz052. [PMID: 31222199 PMCID: PMC6479428 DOI: 10.1093/gigascience/giz052] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/30/2018] [Revised: 03/13/2019] [Accepted: 04/08/2019] [Indexed: 01/22/2023] Open
Abstract
BACKGROUND Container virtualization technologies such as Docker are popular in the bioinformatics domain because they improve the portability and reproducibility of software deployment. Along with software packaged in containers, the standardized workflow descriptors Common Workflow Language (CWL) enable data to be easily analyzed on multiple computing environments. These technologies accelerate the use of on-demand cloud computing platforms, which can be scaled according to the quantity of data. However, to optimize the time and budgetary restraints of cloud usage, users must select a suitable instance type that corresponds to the resource requirements of their workflows. RESULTS We developed CWL-metrics, a utility tool for cwltool (the reference implementation of CWL), to collect runtime metrics of Docker containers and workflow metadata to analyze workflow resource requirements. To demonstrate the use of this tool, we analyzed 7 transcriptome quantification workflows on 6 instance types. The results revealed that choice of instance type can deliver lower financial costs and faster execution times using the required amount of computational resources. CONCLUSIONS CWL-metrics can generate a summary of resource requirements for workflow executions, which can help users to optimize their use of cloud computing by selecting appropriate instances. The runtime metrics data generated by CWL-metrics can also help users to share workflows between different workflow management frameworks.
Collapse
Affiliation(s)
- Tazro Ohta
- Database Center for Life Science, Joint Support-Center for Data Science Research, Research Organization of Information and Systems, Mishima, Shizuoka 411–8540, Japan
| | - Tomoya Tanjo
- National Institute of Informatics, Research Organization of Information and Systems, Tokyo 101–8430, Japan
| | - Osamu Ogasawara
- DNA Data Bank of Japan, National Institute of Genetics, Research Organization of Information and Systems, Mishima, Shizuoka 411–8540, Japan
| |
Collapse
|
13
|
Oki S, Ohta T, Shioi G, Hatanaka H, Ogasawara O, Okuda Y, Kawaji H, Nakaki R, Sese J, Meno C. ChIP-Atlas: a data-mining suite powered by full integration of public ChIP-seq data. EMBO Rep 2018; 19:e46255. [PMID: 30413482 PMCID: PMC6280645 DOI: 10.15252/embr.201846255] [Citation(s) in RCA: 383] [Impact Index Per Article: 63.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/09/2018] [Revised: 10/03/2018] [Accepted: 10/12/2018] [Indexed: 01/21/2023] Open
Abstract
We have fully integrated public chromatin chromatin immunoprecipitation sequencing (ChIP-seq) and DNase-seq data (n > 70,000) derived from six representative model organisms (human, mouse, rat, fruit fly, nematode, and budding yeast), and have devised a data-mining platform-designated ChIP-Atlas (http://chip-atlas.org). ChIP-Atlas is able to show alignment and peak-call results for all public ChIP-seq and DNase-seq data archived in the NCBI Sequence Read Archive (SRA), which encompasses data derived from GEO, ArrayExpress, DDBJ, ENCODE, Roadmap Epigenomics, and the scientific literature. All peak-call data are integrated to visualize multiple histone modifications and binding sites of transcriptional regulators (TRs) at given genomic loci. The integrated data can be further analyzed to show TR-gene and TR-TR interactions, as well as to examine enrichment of protein binding for given multiple genomic coordinates or gene names. ChIP-Atlas is superior to other platforms in terms of data number and functionality for data mining across thousands of ChIP-seq experiments, and it provides insight into gene regulatory networks and epigenetic mechanisms.
Collapse
Affiliation(s)
- Shinya Oki
- Department of Developmental Biology, Graduate School of Medical Sciences, Kyushu University, Fukuoka, Japan
| | - Tazro Ohta
- Database Center for Life Science, Joint-Support Center for Data Science Research, Research Organization of Information and Systems, Mishima, Shizuoka, Japan
| | - Go Shioi
- Genetic Engineering Team, RIKEN Center for Life Science Technologies, Kobe, Japan
| | - Hideki Hatanaka
- National Bioscience Database Center, Japan Science and Technology Agency, Tokyo, Japan
| | - Osamu Ogasawara
- DNA Data Bank of Japan, National Institute of Genetics, Mishima, Shizuoka, Japan
| | - Yoshihiro Okuda
- DNA Data Bank of Japan, National Institute of Genetics, Mishima, Shizuoka, Japan
| | - Hideya Kawaji
- Preventive Medicine and Applied Genomics Unit, RIKEN Center for Integrative Medical Sciences, Kanagawa, Japan
- RIKEN Preventive Medicine and Diagnosis Innovation Program, Saitama, Japan
| | - Ryo Nakaki
- Genome Science Division, Research Center for Advanced Science and Technology, The University of Tokyo, Tokyo, Japan
- Rhelixa Inc., Tokyo, Japan
| | - Jun Sese
- Artificial Intelligence Research Center, National Institute of Advanced Industrial Science and Technology, Tokyo, Japan
- Humanome Lab Inc., Tokyo, Japan
| | - Chikara Meno
- Department of Developmental Biology, Graduate School of Medical Sciences, Kyushu University, Fukuoka, Japan
| |
Collapse
|
14
|
Iida N, Okuda Y, Ogasawara O, Yamashita S, Takeshima H, Ushijima T. MACON: a web tool for computing DNA methylation data obtained by the Illumina Infinium Human DNA methylation BeadArray. Epigenomics 2018; 10:249-258. [DOI: 10.2217/epi-2017-0093] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/11/2022] Open
Abstract
Aim: Bioinformatics analysis for Illumina Infinium Human DNA methylation BeadArray is essential, but still remains difficult task for many experimental researchers. We here aimed to develop a browser-accessible bioinformatics tool for analyzing the BeadArray data. Materials & methods: The tool was established as an analytical pipeline using R, Perl and Python programming languages. Results: We introduced a method that groups neighboring probes into a genomic block, which facilitated efficient identification of densely methylated/unmethylated regions. The tool, MACON, provided probe filtering, β-mixture quantile normalization, grouping into genomic blocks, annotation and production of a data subset. Conclusion: MACON allows researchers to analyze the BeadArray data using a web browser ( http://epigenome.ncc.go.jp/macon ).
Collapse
Affiliation(s)
- Naoko Iida
- Division of Epigenomics, National Cancer Center Research Institute, Tokyo, Japan
| | | | | | - Satoshi Yamashita
- Division of Epigenomics, National Cancer Center Research Institute, Tokyo, Japan
| | - Hideyuki Takeshima
- Division of Epigenomics, National Cancer Center Research Institute, Tokyo, Japan
| | - Toshikazu Ushijima
- Division of Epigenomics, National Cancer Center Research Institute, Tokyo, Japan
| |
Collapse
|
15
|
Ono H, Ogasawara O, Okubo K, Bono H. RefEx, a reference gene expression dataset as a web tool for the functional analysis of genes. Sci Data 2017; 4:170105. [PMID: 28850115 PMCID: PMC5574374 DOI: 10.1038/sdata.2017.105] [Citation(s) in RCA: 44] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/24/2016] [Accepted: 06/29/2017] [Indexed: 12/28/2022] Open
Abstract
Gene expression data are exponentially accumulating; thus, the functional annotation of such sequence data from metadata is urgently required. However, life scientists have difficulty utilizing the available data due to its sheer magnitude and complicated access. We have developed a web tool for browsing reference gene expression pattern of mammalian tissues and cell lines measured using different methods, which should facilitate the reuse of the precious data archived in several public databases. The web tool is called Reference Expression dataset (RefEx), and RefEx allows users to search by the gene name, various types of IDs, chromosomal regions in genetic maps, gene family based on InterPro, gene expression patterns, or biological categories based on Gene Ontology. RefEx also provides information about genes with tissue-specific expression, and the relative gene expression values are shown as choropleth maps on 3D human body images from BodyParts3D. Combined with the newly incorporated Functional Annotation of Mammals (FANTOM) dataset, RefEx provides insight regarding the functional interpretation of unfamiliar genes. RefEx is publicly available at http://refex.dbcls.jp/.
Collapse
Affiliation(s)
- Hiromasa Ono
- Database Center for Life Science, Joint Support-Center for Data Science Research, Research Organization of Information and Systems, 1111 Yata, Mishima 411-8540, Japan
| | - Osamu Ogasawara
- Center for Information Biology, National Institute of Genetics, Research Organization for Information and Systems, 1111 Yata, Mishima 411-8540, Japan
| | - Kosaku Okubo
- Database Center for Life Science, Joint Support-Center for Data Science Research, Research Organization of Information and Systems, 1111 Yata, Mishima 411-8540, Japan
- Center for Information Biology, National Institute of Genetics, Research Organization for Information and Systems, 1111 Yata, Mishima 411-8540, Japan
| | - Hidemasa Bono
- Database Center for Life Science, Joint Support-Center for Data Science Research, Research Organization of Information and Systems, 1111 Yata, Mishima 411-8540, Japan
| |
Collapse
|
16
|
Mashima J, Kodama Y, Fujisawa T, Katayama T, Okuda Y, Kaminuma E, Ogasawara O, Okubo K, Nakamura Y, Takagi T. DNA Data Bank of Japan. Nucleic Acids Res 2016; 45:D25-D31. [PMID: 27924010 PMCID: PMC5210514 DOI: 10.1093/nar/gkw1001] [Citation(s) in RCA: 44] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/16/2016] [Revised: 10/13/2016] [Accepted: 10/15/2016] [Indexed: 12/27/2022] Open
Abstract
The DNA Data Bank of Japan (DDBJ) (http://www.ddbj.nig.ac.jp) has been providing public data services for thirty years (since 1987). We are collecting nucleotide sequence data from researchers as a member of the International Nucleotide Sequence Database Collaboration (INSDC, http://www.insdc.org), in collaboration with the US National Center for Biotechnology Information (NCBI) and European Bioinformatics Institute (EBI). The DDBJ Center also services Japanese Genotype-phenotype Archive (JGA), with the National Bioscience Database Center to collect human-subjected data from Japanese researchers. Here, we report our database activities for INSDC and JGA over the past year, and introduce retrieval and analytical services running on our supercomputer system and their recent modifications. Furthermore, with the Database Center for Life Science, the DDBJ Center improves semantic web technologies to integrate and to share biological data, for providing the RDF version of the sequence data.
Collapse
Affiliation(s)
- Jun Mashima
- DDBJ Center, National Institute of Genetics, Shizuoka 411-8540, Japan
| | - Yuichi Kodama
- DDBJ Center, National Institute of Genetics, Shizuoka 411-8540, Japan
| | - Takatomo Fujisawa
- DDBJ Center, National Institute of Genetics, Shizuoka 411-8540, Japan
| | | | - Yoshihiro Okuda
- DDBJ Center, National Institute of Genetics, Shizuoka 411-8540, Japan
| | - Eli Kaminuma
- DDBJ Center, National Institute of Genetics, Shizuoka 411-8540, Japan
| | - Osamu Ogasawara
- DDBJ Center, National Institute of Genetics, Shizuoka 411-8540, Japan
| | - Kousaku Okubo
- DDBJ Center, National Institute of Genetics, Shizuoka 411-8540, Japan
| | - Yasukazu Nakamura
- DDBJ Center, National Institute of Genetics, Shizuoka 411-8540, Japan
| | - Toshihisa Takagi
- DDBJ Center, National Institute of Genetics, Shizuoka 411-8540, Japan .,National Bioscience Database Center, Japan Science and Technology Agency, Tokyo 102-8666, Japan
| |
Collapse
|
17
|
Mashima J, Kodama Y, Kosuge T, Fujisawa T, Katayama T, Nagasaki H, Okuda Y, Kaminuma E, Ogasawara O, Okubo K, Nakamura Y, Takagi T. DNA data bank of Japan (DDBJ) progress report. Nucleic Acids Res 2015; 44:D51-7. [PMID: 26578571 PMCID: PMC4702806 DOI: 10.1093/nar/gkv1105] [Citation(s) in RCA: 55] [Impact Index Per Article: 6.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/18/2015] [Accepted: 10/09/2015] [Indexed: 01/07/2023] Open
Abstract
The DNA Data Bank of Japan Center (DDBJ Center; http://www.ddbj.nig.ac.jp) maintains and provides public archival, retrieval and analytical services for biological information. The contents of the DDBJ databases are shared with the US National Center for Biotechnology Information (NCBI) and the European Bioinformatics Institute (EBI) within the framework of the International Nucleotide Sequence Database Collaboration (INSDC). Since 2013, the DDBJ Center has been operating the Japanese Genotype-phenotype Archive (JGA) in collaboration with the National Bioscience Database Center (NBDC) in Japan. In addition, the DDBJ Center develops semantic web technologies for data integration and sharing in collaboration with the Database Center for Life Science (DBCLS) in Japan. This paper briefly reports on the activities of the DDBJ Center over the past year including submissions to databases and improvements in our services for data retrieval, analysis, and integration.
Collapse
Affiliation(s)
- Jun Mashima
- DDBJ Center, National Institute of Genetics, Shizuoka 411-8540, Japan
| | - Yuichi Kodama
- DDBJ Center, National Institute of Genetics, Shizuoka 411-8540, Japan
| | - Takehide Kosuge
- DDBJ Center, National Institute of Genetics, Shizuoka 411-8540, Japan
| | - Takatomo Fujisawa
- DDBJ Center, National Institute of Genetics, Shizuoka 411-8540, Japan
| | | | - Hideki Nagasaki
- DDBJ Center, National Institute of Genetics, Shizuoka 411-8540, Japan
| | - Yoshihiro Okuda
- DDBJ Center, National Institute of Genetics, Shizuoka 411-8540, Japan
| | - Eli Kaminuma
- DDBJ Center, National Institute of Genetics, Shizuoka 411-8540, Japan
| | - Osamu Ogasawara
- DDBJ Center, National Institute of Genetics, Shizuoka 411-8540, Japan
| | - Kousaku Okubo
- DDBJ Center, National Institute of Genetics, Shizuoka 411-8540, Japan
| | - Yasukazu Nakamura
- DDBJ Center, National Institute of Genetics, Shizuoka 411-8540, Japan
| | - Toshihisa Takagi
- DDBJ Center, National Institute of Genetics, Shizuoka 411-8540, Japan National Bioscience Database Center, Japan Science and Technology Agency, Tokyo 102-8666, Japan
| |
Collapse
|
18
|
Kodama Y, Mashima J, Kosuge T, Katayama T, Fujisawa T, Kaminuma E, Ogasawara O, Okubo K, Takagi T, Nakamura Y. The DDBJ Japanese Genotype-phenotype Archive for genetic and phenotypic human data. Nucleic Acids Res 2014; 43:D18-22. [PMID: 25477381 PMCID: PMC4383935 DOI: 10.1093/nar/gku1120] [Citation(s) in RCA: 48] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/08/2023] Open
Abstract
The DNA Data Bank of Japan Center (DDBJ Center; http://www.ddbj.nig.ac.jp) maintains and provides public archival, retrieval and analytical services for biological information. Since October 2013, DDBJ Center has operated the Japanese Genotype-phenotype Archive (JGA) in collaboration with our partner institute, the National Bioscience Database Center (NBDC) of the Japan Science and Technology Agency. DDBJ Center provides the JGA database system which securely stores genotype and phenotype data collected from individuals whose consent agreements authorize data release only for specific research use. NBDC has established guidelines and policies for sharing human-derived data and reviews data submission and usage requests from researchers. In addition to the JGA project, DDBJ Center develops Semantic Web technologies for data integration and sharing in collaboration with the Database Center for Life Science. This paper describes the overview of the JGA project, updates to the DDBJ databases, and services for data retrieval, analysis and integration.
Collapse
Affiliation(s)
- Yuichi Kodama
- DDBJ Center, National Institute of Genetics, Shizuoka 411-8540, Japan
| | - Jun Mashima
- DDBJ Center, National Institute of Genetics, Shizuoka 411-8540, Japan
| | - Takehide Kosuge
- DDBJ Center, National Institute of Genetics, Shizuoka 411-8540, Japan
| | - Toshiaki Katayama
- National Bioscience Database Center, Japan Science and Technology Agency, Tokyo 102-8666, Japan
| | - Takatomo Fujisawa
- DDBJ Center, National Institute of Genetics, Shizuoka 411-8540, Japan
| | - Eli Kaminuma
- DDBJ Center, National Institute of Genetics, Shizuoka 411-8540, Japan
| | - Osamu Ogasawara
- DDBJ Center, National Institute of Genetics, Shizuoka 411-8540, Japan
| | - Kousaku Okubo
- DDBJ Center, National Institute of Genetics, Shizuoka 411-8540, Japan
| | - Toshihisa Takagi
- DDBJ Center, National Institute of Genetics, Shizuoka 411-8540, Japan Database Center for Life Science, Chiba 277-0871, Japan
| | - Yasukazu Nakamura
- DDBJ Center, National Institute of Genetics, Shizuoka 411-8540, Japan
| |
Collapse
|
19
|
Kosuge T, Mashima J, Kodama Y, Fujisawa T, Kaminuma E, Ogasawara O, Okubo K, Takagi T, Nakamura Y. DDBJ progress report: a new submission system for leading to a correct annotation. Nucleic Acids Res 2013; 42:D44-9. [PMID: 24194602 PMCID: PMC3964987 DOI: 10.1093/nar/gkt1066] [Citation(s) in RCA: 34] [Impact Index Per Article: 3.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/17/2023] Open
Abstract
The DNA Data Bank of Japan (DDBJ; http://www.ddbj.nig.ac.jp) maintains and provides archival, retrieval and analytical resources for biological information. This database content is shared with the US National Center for Biotechnology Information (NCBI) and the European Bioinformatics Institute (EBI) within the framework of the International Nucleotide Sequence Database Collaboration (INSDC). DDBJ launched a new nucleotide sequence submission system for receiving traditional nucleotide sequence. We expect that the new submission system will be useful for many submitters to input accurate annotation and reduce the time needed for data input. In addition, DDBJ has started a new service, the Japanese Genotype–phenotype Archive (JGA), with our partner institute, the National Bioscience Database Center (NBDC). JGA permanently archives and shares all types of individual human genetic and phenotypic data. We also introduce improvements in the DDBJ services and databases made during the past year.
Collapse
Affiliation(s)
- Takehide Kosuge
- DDBJ Center, National Institute of Genetics, Yata 1111, Mishima, Shizuoka 411-8540, Japan and National Bioscience Database Center, Japan Science and Technology Agency, Tokyo 102-8666, Japan
| | | | | | | | | | | | | | | | | |
Collapse
|
20
|
Abstract
The DNA data bank of Japan (DDBJ, http://www.ddbj.nig.ac.jp) maintains a primary nucleotide sequence database and provides analytical resources for biological information to researchers. This database content is exchanged with the US National Center for Biotechnology Information (NCBI) and the European Bioinformatics Institute (EBI) within the framework of the International Nucleotide Sequence Database Collaboration (INSDC). Resources provided by the DDBJ include traditional nucleotide sequence data released in the form of 27 316 452 entries or 16 876 791 557 base pairs (as of June 2012), and raw reads of new generation sequencers in the sequence read archive (SRA). A Japanese researcher published his own genome sequence via DDBJ-SRA on 31 July 2012. To cope with the ongoing genomic data deluge, in March 2012, our computer previous system was totally replaced by a commodity cluster-based system that boasts 122.5 TFlops of CPU capacity and 5 PB of storage space. During this upgrade, it was considered crucial to replace and refactor substantial portions of the DDBJ software systems as well. As a result of the replacement process, which took more than 2 years to perform, we have achieved significant improvements in system performance.
Collapse
Affiliation(s)
- Osamu Ogasawara
- DDBJ Center, National Institute of Genetics, Yata 1111, Mishima, Shizuoka 411-8540, Japan.
| | | | | | | | | | | | | |
Collapse
|
21
|
Kodama Y, Mashima J, Kaminuma E, Gojobori T, Ogasawara O, Takagi T, Okubo K, Nakamura Y. The DNA Data Bank of Japan launches a new resource, the DDBJ Omics Archive of functional genomics experiments. Nucleic Acids Res 2011; 40:D38-42. [PMID: 22110025 PMCID: PMC3244990 DOI: 10.1093/nar/gkr994] [Citation(s) in RCA: 39] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/04/2023] Open
Abstract
The DNA Data Bank of Japan (DDBJ; http://www.ddbj.nig.ac.jp) maintains and provides archival, retrieval and analytical resources for biological information. The central DDBJ resource consists of public, open-access nucleotide sequence databases including raw sequence reads, assembly information and functional annotation. Database content is exchanged with EBI and NCBI within the framework of the International Nucleotide Sequence Database Collaboration (INSDC). In 2011, DDBJ launched two new resources: the ‘DDBJ Omics Archive’ (DOR; http://trace.ddbj.nig.ac.jp/dor) and BioProject (http://trace.ddbj.nig.ac.jp/bioproject). DOR is an archival database of functional genomics data generated by microarray and highly parallel new generation sequencers. Data are exchanged between the ArrayExpress at EBI and DOR in the common MAGE-TAB format. BioProject provides an organizational framework to access metadata about research projects and the data from the projects that are deposited into different databases. In this article, we describe major changes and improvements introduced to the DDBJ services, and the launch of two new resources: DOR and BioProject.
Collapse
Affiliation(s)
- Yuichi Kodama
- Center for Information Biology and DNA Data Bank of Japan, National Institute of Genetics, Research Organization for Information and Systems, Yata, Mishima 411-8510, Japan
| | | | | | | | | | | | | | | |
Collapse
|
22
|
Kaminuma E, Kosuge T, Kodama Y, Aono H, Mashima J, Gojobori T, Sugawara H, Ogasawara O, Takagi T, Okubo K, Nakamura Y. DDBJ progress report. Nucleic Acids Res 2010; 39:D22-7. [PMID: 21062814 PMCID: PMC3013661 DOI: 10.1093/nar/gkq1041] [Citation(s) in RCA: 36] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/14/2022] Open
Abstract
The DNA Data Bank of Japan (DDBJ, http://www.ddbj.nig.ac.jp) provides a nucleotide sequence archive database and accompanying database tools for sequence submission, entry retrieval and annotation analysis. The DDBJ collected and released 3 637 446 entries/2 272 231 889 bases between July 2009 and June 2010. A highlight of the released data was archive datasets from next-generation sequencing reads of Japanese rice cultivar, Koshihikari submitted by the National Institute of Agrobiological Sciences. In this period, we started a new archive for quantitative genomics data, the DDBJ Omics aRchive (DOR). The DOR stores quantitative data both from the microarray and high-throughput new sequencing platforms. Moreover, we improved the content of the DDBJ patent sequence, released a new submission tool of the DDBJ Sequence Read Archive (DRA) which archives massive raw sequencing reads, and enhanced a cloud computing-based analytical system from sequencing reads, the DDBJ Read Annotation Pipeline. In this article, we describe these new functions of the DDBJ databases and support tools.
Collapse
Affiliation(s)
- Eli Kaminuma
- Center for Information Biology and DNA Data Bank of Japan, National Institute of Genetics, Research Organization for Information and Systems, Yata, Mishima 411-8510, Japan
| | | | | | | | | | | | | | | | | | | | | |
Collapse
|
23
|
Ogasawara O, Okubo K. On theoretical models of gene expression evolution with random genetic drift and natural selection. PLoS One 2009; 4:e7943. [PMID: 19936214 PMCID: PMC2776274 DOI: 10.1371/journal.pone.0007943] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/10/2009] [Accepted: 10/26/2009] [Indexed: 11/19/2022] Open
Abstract
BACKGROUND The relative contributions of natural selection and random genetic drift are a major source of debate in the study of gene expression evolution, which is hypothesized to serve as a bridge from molecular to phenotypic evolution. It has been suggested that the conflict between views is caused by the lack of a definite model of the neutral hypothesis, which can describe the long-run behavior of evolutionary change in mRNA abundance. Therefore previous studies have used inadequate analogies with the neutral prediction of other phenomena, such as amino acid or nucleotide sequence evolution, as the null hypothesis of their statistical inference. METHODOLOGY/PRINCIPAL FINDINGS In this study, we introduced two novel theoretical models, one based on neutral drift and the other assuming natural selection, by focusing on a common property of the distribution of mRNA abundance among a variety of eukaryotic cells, which reflects the result of long-term evolution. Our results demonstrated that (1) our models can reproduce two independently found phenomena simultaneously: the time development of gene expression divergence and Zipf's law of the transcriptome; (2) cytological constraints can be explicitly formulated to describe long-term evolution; (3) the model assuming that natural selection optimized relative mRNA abundance was more consistent with previously published observations than the model of optimized absolute mRNA abundances. CONCLUSIONS/SIGNIFICANCE The models introduced in this study give a formulation of evolutionary change in the mRNA abundance of each gene as a stochastic process, on the basis of previously published observations. This model provides a foundation for interpreting observed data in studies of gene expression evolution, including identifying an adequate time scale for discriminating the effect of natural selection from that of random genetic drift of selectively neutral variations.
Collapse
Affiliation(s)
- Osamu Ogasawara
- Center for Information Biology and DNA Data Bank of Japan, National Institute of Genetics, Mishima, Shizuoka, Japan.
| | | |
Collapse
|
24
|
Kaminuma E, Mashima J, Kodama Y, Gojobori T, Ogasawara O, Okubo K, Takagi T, Nakamura Y. DDBJ launches a new archive database with analytical tools for next-generation sequence data. Nucleic Acids Res 2009; 38:D33-8. [PMID: 19850725 PMCID: PMC2808917 DOI: 10.1093/nar/gkp847] [Citation(s) in RCA: 67] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022] Open
Abstract
The DNA Data Bank of Japan (DDBJ) (http://www.ddbj.nig.ac.jp) has collected and released 1 701 110 entries/1 116 138 614 bases between July 2008 and June 2009. A few highlighted data releases from DDBJ were the complete genome sequence of an endosymbiont within protist cells in the termite gut and Cap Analysis Gene Expression tags for human and mouse deposited from the Functional Annotation of the Mammalian cDNA consortium. In this period, we started a novel user announcement service using Really Simple Syndication (RSS) to deliver a list of data released from DDBJ on a daily basis. Comprehensive visualization of a DDBJ release data was attempted by using a word cloud program. Moreover, a new archive for sequencing data from next-generation sequencers, the ‘DDBJ Read Archive’ (DRA), was launched. Concurrently, for read data registered in DRA, a semi-automatic annotation tool called the ‘DDBJ Read Annotation Pipeline’ was released as a preliminary step. The pipeline consists of two parts: basic analysis for reference genome mapping and de novo assembly and high-level analysis of structural and functional annotations. These new services will aid users’ research and provide easier access to DDBJ databases.
Collapse
Affiliation(s)
- Eli Kaminuma
- Center for Information Biology and DNA Data Bank of Japan, National Institute of Genetics, Research Organization for Information and Systems, Yata, Mishima 411-8510, Japan
| | | | | | | | | | | | | | | |
Collapse
|
25
|
Abstract
DDBJ (http://www.ddbj.nig.ac.jp) collected and released 1 880 115 entries or 1 134 086 245 bases in the period from July 2006 to June 2007. The released data contains the high-throughput cDNAs of cricket and high-quality draft genome of medaka among others. Our computer system has been upgraded since March 2007. Another new aspect is an efficient data retrieval tool that has recently been equipped and served at DDBJ. It is called All-round Retrieval for Sequence and Annotation, which enables the user to search for keywords also in the Feature/Qualifier of the International Nucleotide Sequence Database Collaboration (http://www.insdc.org/). We will also replace our home page with a more efficient one by the end of 2007.
Collapse
Affiliation(s)
- H Sugawara
- Center for Information Biology and DNA Data Bank of Japan, National Institute of Genetics, Research Organization of Information and Systems, Yata, Mishima 411-8540, Japan
| | | | | | | | | |
Collapse
|
26
|
Ogasawara O, Otsuji M, Watanabe K, Iizuka T, Tamura T, Hishiki T, Kawamoto S, Okubo K. BodyMap-Xs: anatomical breakdown of 17 million animal ESTs for cross-species comparison of gene expression. Nucleic Acids Res 2006; 34:D628-31. [PMID: 16381946 PMCID: PMC1347499 DOI: 10.1093/nar/gkj137] [Citation(s) in RCA: 23] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022] Open
Abstract
BodyMap-Xs () is a database for cross-species gene expression comparison. It was created by the anatomical breakdown of 17 million animal expressed sequence tag (EST) records in DDBJ using a sorting program tailored for this purpose. In BodyMap-Xs, users are allowed to compare the expression patterns of orthologous and paralogous genes in a coherent manner. This will provide valuable insights for the evolutionary study of gene expression and identification of a responsive motif for a particular expression pattern. In addition, starting from a concise overview of the taxonomical and anatomical breakdown of all animal ESTs, users can navigate to obtain gene expression ranking of a particular tissue in a particular animal. This method may lead to the understanding of the similarities and differences between the homologous tissues across animal species. BodyMap-Xs will be automatically updated in synchronization with the major update in DDBJ, which occurs periodically.
Collapse
Affiliation(s)
- Osamu Ogasawara
- Center for Information Biology and DNA Data Bank of Japan, National Institute of Genetics1111 Yata, Mishima, Shizuoka 411-8540, Japan
| | - Makiko Otsuji
- Center for Information Biology and DNA Data Bank of Japan, National Institute of Genetics1111 Yata, Mishima, Shizuoka 411-8540, Japan
| | - Kouji Watanabe
- Center for Information Biology and DNA Data Bank of Japan, National Institute of Genetics1111 Yata, Mishima, Shizuoka 411-8540, Japan
| | - Takayasu Iizuka
- Center for Information Biology and DNA Data Bank of Japan, National Institute of Genetics1111 Yata, Mishima, Shizuoka 411-8540, Japan
| | - Takuro Tamura
- Center for Information Biology and DNA Data Bank of Japan, National Institute of Genetics1111 Yata, Mishima, Shizuoka 411-8540, Japan
| | - Teruyoshi Hishiki
- Biological Information Research Center, National Institute of Advanced Industrial Science and Technology (AIST)2-42 Aomi, Koto, Tokyo 135-0064, Japan
| | - Shoko Kawamoto
- National Institute of Informatics2-1-2 Hitotsubashi, Chiyoda-ku, Tokyo 101-8430, Japan
| | - Kousaku Okubo
- Center for Information Biology and DNA Data Bank of Japan, National Institute of Genetics1111 Yata, Mishima, Shizuoka 411-8540, Japan
- Biological Information Research Center, National Institute of Advanced Industrial Science and Technology (AIST)2-42 Aomi, Koto, Tokyo 135-0064, Japan
- To whom correspondence should be addressed. Tel: +81 559 815 838; Fax: +81 559 815 837; E-mail:
| |
Collapse
|
27
|
Tanino M, Debily MA, Tamura T, Hishiki T, Ogasawara O, Murakawa K, Kawamoto S, Itoh K, Watanabe S, de Souza SJ, Imbeaud S, Graudens E, Eveno E, Hilton P, Sudo Y, Kelso J, Ikeo K, Imanishi T, Gojobori T, Auffray C, Hide W, Okubo K. The Human Anatomic Gene Expression Library (H-ANGEL), the H-Inv integrative display of human gene expression across disparate technologies and platforms. Nucleic Acids Res 2005; 33:D567-72. [PMID: 15608263 PMCID: PMC540058 DOI: 10.1093/nar/gki104] [Citation(s) in RCA: 15] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/26/2022] Open
Abstract
The Human Anatomic Gene Expression Library (H-ANGEL) is a resource for information concerning the anatomical distribution and expression of human gene transcripts. The tool contains protein expression data from multiple platforms that has been associated with both manually annotated full-length cDNAs from H-InvDB and RefSeq sequences. Of the H-Inv predicted genes, 18 897 have associated expression data generated by at least one platform. H-ANGEL utilizes categorized mRNA expression data from both publicly available and proprietary sources. It incorporates data generated by three types of methods from seven different platforms. The data are provided to the user in the form of a web-based viewer with numerous query options. H-ANGEL is updated with each new release of cDNA and genome sequence build. In future editions, we will incorporate the capability for expression data updates from existing and new platforms. H-ANGEL is accessible at http://www.jbirc.aist.go.jp/hinv/h-angel/.
Collapse
Affiliation(s)
- Motohiko Tanino
- Integrated Database Group, Japan Biological Information Research Center, Japan Biological Informatics Consortium, Time24 Building 10F, 2-45 Aomi, Koto-ku, Tokyo 135-0064, Japan.
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | |
Collapse
|
28
|
Abstract
Detailed analysis of human gene expression data reveals several patterns of relationship between transcript frequency and abundance rank. In muscle and liver, organs composed primarily of a homogeneous population of differentiated cells, they obey Zipf's law. In cell lines, epithelial tissue and compiled transcriptome data, only high-rankers deviate from it. We propose an evolutionary process model during which expression level changes stochastically proportionally to its intensity, providing a novel interpretation of transcriptome data and of evolutionary constraints on gene expression.
Collapse
Affiliation(s)
- Osamu Ogasawara
- Division of Gene Expression analysis, The Center for Information Biology and DNA Data Bank of Japan, National Institute of Genetics, Mishima 411-8540, Shizuoka, Japan
| | | | | |
Collapse
|
29
|
Imanishi T, Itoh T, Suzuki Y, O'Donovan C, Fukuchi S, Koyanagi KO, Barrero RA, Tamura T, Yamaguchi-Kabata Y, Tanino M, Yura K, Miyazaki S, Ikeo K, Homma K, Kasprzyk A, Nishikawa T, Hirakawa M, Thierry-Mieg J, Thierry-Mieg D, Ashurst J, Jia L, Nakao M, Thomas MA, Mulder N, Karavidopoulou Y, Jin L, Kim S, Yasuda T, Lenhard B, Eveno E, Suzuki Y, Yamasaki C, Takeda JI, Gough C, Hilton P, Fujii Y, Sakai H, Tanaka S, Amid C, Bellgard M, Bonaldo MDF, Bono H, Bromberg SK, Brookes AJ, Bruford E, Carninci P, Chelala C, Couillault C, de Souza SJ, Debily MA, Devignes MD, Dubchak I, Endo T, Estreicher A, Eyras E, Fukami-Kobayashi K, R. Gopinath G, Graudens E, Hahn Y, Han M, Han ZG, Hanada K, Hanaoka H, Harada E, Hashimoto K, Hinz U, Hirai M, Hishiki T, Hopkinson I, Imbeaud S, Inoko H, Kanapin A, Kaneko Y, Kasukawa T, Kelso J, Kersey P, Kikuno R, Kimura K, Korn B, Kuryshev V, Makalowska I, Makino T, Mano S, Mariage-Samson R, Mashima J, Matsuda H, Mewes HW, Minoshima S, Nagai K, Nagasaki H, Nagata N, Nigam R, Ogasawara O, Ohara O, Ohtsubo M, Okada N, Okido T, Oota S, Ota M, Ota T, Otsuki T, Piatier-Tonneau D, Poustka A, Ren SX, Saitou N, Sakai K, Sakamoto S, Sakate R, Schupp I, Servant F, Sherry S, Shiba R, Shimizu N, Shimoyama M, Simpson AJ, Soares B, Steward C, Suwa M, Suzuki M, Takahashi A, Tamiya G, Tanaka H, Taylor T, Terwilliger JD, Unneberg P, Veeramachaneni V, Watanabe S, Wilming L, Yasuda N, Yoo HS, Stodolsky M, Makalowski W, Go M, Nakai K, Takagi T, Kanehisa M, Sakaki Y, Quackenbush J, Okazaki Y, Hayashizaki Y, Hide W, Chakraborty R, Nishikawa K, Sugawara H, Tateno Y, Chen Z, Oishi M, Tonellato P, Apweiler R, Okubo K, Wagner L, Wiemann S, Strausberg RL, Isogai T, Auffray C, Nomura N, Gojobori T, Sugano S. Integrative annotation of 21,037 human genes validated by full-length cDNA clones. PLoS Biol 2004; 2:e162. [PMID: 15103394 PMCID: PMC393292 DOI: 10.1371/journal.pbio.0020162] [Citation(s) in RCA: 267] [Impact Index Per Article: 13.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/19/2003] [Accepted: 04/01/2004] [Indexed: 01/08/2023] Open
Abstract
The human genome sequence defines our inherent biological potential; the realization of the biology encoded therein requires knowledge of the function of each gene. Currently, our knowledge in this area is still limited. Several lines of investigation have been used to elucidate the structure and function of the genes in the human genome. Even so, gene prediction remains a difficult task, as the varieties of transcripts of a gene may vary to a great extent. We thus performed an exhaustive integrative characterization of 41,118 full-length cDNAs that capture the gene transcripts as complete functional cassettes, providing an unequivocal report of structural and functional diversity at the gene level. Our international collaboration has validated 21,037 human gene candidates by analysis of high-quality full-length cDNA clones through curation using unified criteria. This led to the identification of 5,155 new gene candidates. It also manifested the most reliable way to control the quality of the cDNA clones. We have developed a human gene database, called the H-Invitational Database (H-InvDB; http://www.h-invitational.jp/). It provides the following: integrative annotation of human genes, description of gene structures, details of novel alternative splicing isoforms, non-protein-coding RNAs, functional domains, subcellular localizations, metabolic pathways, predictions of protein three-dimensional structure, mapping of known single nucleotide polymorphisms (SNPs), identification of polymorphic microsatellite repeats within human genes, and comparative results with mouse full-length cDNAs. The H-InvDB analysis has shown that up to 4% of the human genome sequence (National Center for Biotechnology Information build 34 assembly) may contain misassembled or missing regions. We found that 6.5% of the human gene candidates (1,377 loci) did not have a good protein-coding open reading frame, of which 296 loci are strong candidates for non-protein-coding RNA genes. In addition, among 72,027 uniquely mapped SNPs and insertions/deletions localized within human genes, 13,215 nonsynonymous SNPs, 315 nonsense SNPs, and 452 indels occurred in coding regions. Together with 25 polymorphic microsatellite repeats present in coding regions, they may alter protein structure, causing phenotypic effects or resulting in disease. The H-InvDB platform represents a substantial contribution to resources needed for the exploration of human biology and pathology.
Collapse
Affiliation(s)
- Tadashi Imanishi
- 1Integrated Database Group, Biological Information Research Center, National Institute of Advanced Industrial Science and TechnologyTokyoJapan
| | - Takeshi Itoh
- 1Integrated Database Group, Biological Information Research Center, National Institute of Advanced Industrial Science and TechnologyTokyoJapan
- 2Bioinformatics Laboratory, Genome Research Department, National Institute of Agrobiological SciencesIbarakiJapan
| | - Yutaka Suzuki
- 3Human Genome Center, The Institute of Medical Science, The University of TokyoTokyoJapan
- 68Department of Medical Genome Sciences, Graduate School of Frontier Sciences, University of TokyoTokyoJapan
| | - Claire O'Donovan
- 4EMBL Outstation—European Bioinformatics Institute, Wellcome Trust Genome CampusCambridgeUnited Kingdom
| | - Satoshi Fukuchi
- 5Center for Information Biology and DNA Data Bank of Japan, National Institute of GeneticsShizuokaJapan
| | | | - Roberto A Barrero
- 5Center for Information Biology and DNA Data Bank of Japan, National Institute of GeneticsShizuokaJapan
| | - Takuro Tamura
- 7Integrated Database Group, Japan Biological Information Research Center, Japan Biological Informatics ConsortiumTokyoJapan
- 8BITS CompanyShizuokaJapan
| | - Yumi Yamaguchi-Kabata
- 1Integrated Database Group, Biological Information Research Center, National Institute of Advanced Industrial Science and TechnologyTokyoJapan
| | - Motohiko Tanino
- 1Integrated Database Group, Biological Information Research Center, National Institute of Advanced Industrial Science and TechnologyTokyoJapan
- 7Integrated Database Group, Japan Biological Information Research Center, Japan Biological Informatics ConsortiumTokyoJapan
| | - Kei Yura
- 9Quantum Bioinformatics Group, Center for Promotion of Computational Science and Engineering, Japan Atomic Energy Research InstituteKyotoJapan
| | - Satoru Miyazaki
- 5Center for Information Biology and DNA Data Bank of Japan, National Institute of GeneticsShizuokaJapan
| | - Kazuho Ikeo
- 5Center for Information Biology and DNA Data Bank of Japan, National Institute of GeneticsShizuokaJapan
| | - Keiichi Homma
- 5Center for Information Biology and DNA Data Bank of Japan, National Institute of GeneticsShizuokaJapan
| | - Arek Kasprzyk
- 4EMBL Outstation—European Bioinformatics Institute, Wellcome Trust Genome CampusCambridgeUnited Kingdom
| | - Tetsuo Nishikawa
- 10Reverse Proteomics Research InstituteChibaJapan
- 11Central Research Laboratory, HitachiTokyoJapan
| | - Mika Hirakawa
- 12Bioinformatics Center, Institute for Chemical Research, Kyoto UniversityKyotoJapan
| | - Jean Thierry-Mieg
- 13National Center for Biotechnology Information, National Library of Medicine, National Institutes of HealthBethesda, MarylandUnited States of America
- 14Centre National de la Recherche Scientifique (CNRS), Laboratoire de Physique MathematiqueMontpellierFrance
| | - Danielle Thierry-Mieg
- 13National Center for Biotechnology Information, National Library of Medicine, National Institutes of HealthBethesda, MarylandUnited States of America
- 14Centre National de la Recherche Scientifique (CNRS), Laboratoire de Physique MathematiqueMontpellierFrance
| | - Jennifer Ashurst
- 15The Wellcome Trust Sanger Institute, Wellcome Trust Genome CampusCambridgeUnited Kingdom
| | - Libin Jia
- 16National Cancer Institute, National Institutes of HealthBethesda, MarylandUnited States of America
| | - Mitsuteru Nakao
- 3Human Genome Center, The Institute of Medical Science, The University of TokyoTokyoJapan
| | - Michael A Thomas
- 17Department of Biological Sciences, Idaho State UniversityPocatello, IdahoUnited States of America
| | - Nicola Mulder
- 4EMBL Outstation—European Bioinformatics Institute, Wellcome Trust Genome CampusCambridgeUnited Kingdom
| | - Youla Karavidopoulou
- 4EMBL Outstation—European Bioinformatics Institute, Wellcome Trust Genome CampusCambridgeUnited Kingdom
| | - Lihua Jin
- 5Center for Information Biology and DNA Data Bank of Japan, National Institute of GeneticsShizuokaJapan
| | - Sangsoo Kim
- 18Korea Research Institute of Bioscience and BiotechnologyTaejeonKorea
| | | | - Boris Lenhard
- 19Center for Genomics and Bioinformatics, Karolinska InstitutetStockholmSweden
| | - Eric Eveno
- 20Genexpress—CNRS—Functional Genomics and Systemic Biology for HealthVillejuif CedexFrance
- 21Sino-French Laboratory in Life Sciences and GenomicsShanghaiChina
| | - Yoshiyuki Suzuki
- 5Center for Information Biology and DNA Data Bank of Japan, National Institute of GeneticsShizuokaJapan
| | - Chisato Yamasaki
- 1Integrated Database Group, Biological Information Research Center, National Institute of Advanced Industrial Science and TechnologyTokyoJapan
| | - Jun-ichi Takeda
- 1Integrated Database Group, Biological Information Research Center, National Institute of Advanced Industrial Science and TechnologyTokyoJapan
| | - Craig Gough
- 1Integrated Database Group, Biological Information Research Center, National Institute of Advanced Industrial Science and TechnologyTokyoJapan
- 7Integrated Database Group, Japan Biological Information Research Center, Japan Biological Informatics ConsortiumTokyoJapan
| | - Phillip Hilton
- 1Integrated Database Group, Biological Information Research Center, National Institute of Advanced Industrial Science and TechnologyTokyoJapan
- 7Integrated Database Group, Japan Biological Information Research Center, Japan Biological Informatics ConsortiumTokyoJapan
| | - Yasuyuki Fujii
- 1Integrated Database Group, Biological Information Research Center, National Institute of Advanced Industrial Science and TechnologyTokyoJapan
- 7Integrated Database Group, Japan Biological Information Research Center, Japan Biological Informatics ConsortiumTokyoJapan
| | - Hiroaki Sakai
- 1Integrated Database Group, Biological Information Research Center, National Institute of Advanced Industrial Science and TechnologyTokyoJapan
- 7Integrated Database Group, Japan Biological Information Research Center, Japan Biological Informatics ConsortiumTokyoJapan
- 22Tokyo Research Laboratories, Kyowa Hakko Kogyo CompanyTokyoJapan
| | - Susumu Tanaka
- 1Integrated Database Group, Biological Information Research Center, National Institute of Advanced Industrial Science and TechnologyTokyoJapan
- 7Integrated Database Group, Japan Biological Information Research Center, Japan Biological Informatics ConsortiumTokyoJapan
| | - Clara Amid
- 23MIPS—Institute for Bioinformatics, GSF—National Research Center for Environment and HealthNeuherbergGermany
| | - Matthew Bellgard
- 24Centre for Bioinformatics and Biological Computing, School of Information Technology, Murdoch UniversityMurdoch, Western AustraliaAustralia
| | - Maria de Fatima Bonaldo
- 25Medical Education and Biomedical Research Facility, University of IowaIowa City, IowaUnited States of America
| | - Hidemasa Bono
- 26Genome Exploration Research Group, RIKEN Genomic Sciences Center, RIKEN Yokohama InstituteKanagawaJapan
| | - Susan K Bromberg
- 27Medical College of Wisconsin, MilwaukeeWisconsinUnited States of America
| | - Anthony J Brookes
- 19Center for Genomics and Bioinformatics, Karolinska InstitutetStockholmSweden
| | - Elspeth Bruford
- 28HUGO Gene Nomenclature Committee, University College LondonLondonUnited Kingdom
| | | | - Claude Chelala
- 20Genexpress—CNRS—Functional Genomics and Systemic Biology for HealthVillejuif CedexFrance
| | - Christine Couillault
- 20Genexpress—CNRS—Functional Genomics and Systemic Biology for HealthVillejuif CedexFrance
- 21Sino-French Laboratory in Life Sciences and GenomicsShanghaiChina
| | | | - Marie-Anne Debily
- 20Genexpress—CNRS—Functional Genomics and Systemic Biology for HealthVillejuif CedexFrance
| | | | - Inna Dubchak
- 32Lawrence Berkeley National Laboratory, BerkeleyCaliforniaUnited States of America
| | - Toshinori Endo
- 33Department of Bioinformatics, Medical Research Institute, Tokyo Medical and Dental UniversityTokyoJapan
| | | | - Eduardo Eyras
- 15The Wellcome Trust Sanger Institute, Wellcome Trust Genome CampusCambridgeUnited Kingdom
| | - Kaoru Fukami-Kobayashi
- 35Bioresource Information Division, RIKEN BioResource Center, RIKEN Tsukuba InstituteIbarakiJapan
| | - Gopal R. Gopinath
- 36Genome Knowledgebase, Cold Spring Harbor LaboratoryCold Spring Harbor, New YorkUnited States of America
| | - Esther Graudens
- 20Genexpress—CNRS—Functional Genomics and Systemic Biology for HealthVillejuif CedexFrance
- 21Sino-French Laboratory in Life Sciences and GenomicsShanghaiChina
| | - Yoonsoo Hahn
- 18Korea Research Institute of Bioscience and BiotechnologyTaejeonKorea
| | - Michael Han
- 23MIPS—Institute for Bioinformatics, GSF—National Research Center for Environment and HealthNeuherbergGermany
| | - Ze-Guang Han
- 21Sino-French Laboratory in Life Sciences and GenomicsShanghaiChina
- 37Chinese National Human Genome Center at ShanghaiShanghaiChina
| | - Kousuke Hanada
- 5Center for Information Biology and DNA Data Bank of Japan, National Institute of GeneticsShizuokaJapan
| | - Hideki Hanaoka
- 1Integrated Database Group, Biological Information Research Center, National Institute of Advanced Industrial Science and TechnologyTokyoJapan
| | - Erimi Harada
- 1Integrated Database Group, Biological Information Research Center, National Institute of Advanced Industrial Science and TechnologyTokyoJapan
- 7Integrated Database Group, Japan Biological Information Research Center, Japan Biological Informatics ConsortiumTokyoJapan
| | - Katsuyuki Hashimoto
- 38Division of Genetic Resources, National Institute of Infectious DiseasesTokyoJapan
| | - Ursula Hinz
- 34Swiss Institute of BioinformaticsGenevaSwitzerland
| | - Momoki Hirai
- 39Graduate School of Frontier Sciences, Department of Integrated Biosciences, University of TokyoChibaJapan
| | - Teruyoshi Hishiki
- 40Functional Genomics Group, Biological Information Research Center, National Institute of Advanced Industrial Science and TechnologyTokyoJapan
| | - Ian Hopkinson
- 41Department of Primary Care and Population Sciences, Royal Free University College Medical School, University College LondonLondonUnited Kingdom
- 42Clinical and Molecular Genetics Unit, The Institute of Child HealthLondonUnited Kingdom
| | - Sandrine Imbeaud
- 20Genexpress—CNRS—Functional Genomics and Systemic Biology for HealthVillejuif CedexFrance
- 21Sino-French Laboratory in Life Sciences and GenomicsShanghaiChina
| | - Hidetoshi Inoko
- 1Integrated Database Group, Biological Information Research Center, National Institute of Advanced Industrial Science and TechnologyTokyoJapan
- 7Integrated Database Group, Japan Biological Information Research Center, Japan Biological Informatics ConsortiumTokyoJapan
- 43Department of Genetic Information, Division of Molecular Life Science, School of Medicine, Tokai UniversityKanagawaJapan
| | - Alexander Kanapin
- 4EMBL Outstation—European Bioinformatics Institute, Wellcome Trust Genome CampusCambridgeUnited Kingdom
| | - Yayoi Kaneko
- 1Integrated Database Group, Biological Information Research Center, National Institute of Advanced Industrial Science and TechnologyTokyoJapan
- 7Integrated Database Group, Japan Biological Information Research Center, Japan Biological Informatics ConsortiumTokyoJapan
| | - Takeya Kasukawa
- 26Genome Exploration Research Group, RIKEN Genomic Sciences Center, RIKEN Yokohama InstituteKanagawaJapan
| | - Janet Kelso
- 44South African National Bioinformatics Institute, University of the Western CapeBellvilleSouth Africa
| | - Paul Kersey
- 4EMBL Outstation—European Bioinformatics Institute, Wellcome Trust Genome CampusCambridgeUnited Kingdom
| | | | | | - Bernhard Korn
- 46RZPD Resource Center for Genome ResearchHeidelbergGermany
| | - Vladimir Kuryshev
- 47Molecular Genome Analysis, German Cancer Research Center-DKFZHeidelbergGermany
| | - Izabela Makalowska
- 48Pennsylvania State UniversityUniversity Park, PennsylvaniaUnited States of America
| | - Takashi Makino
- 5Center for Information Biology and DNA Data Bank of Japan, National Institute of GeneticsShizuokaJapan
| | - Shuhei Mano
- 43Department of Genetic Information, Division of Molecular Life Science, School of Medicine, Tokai UniversityKanagawaJapan
| | - Regine Mariage-Samson
- 20Genexpress—CNRS—Functional Genomics and Systemic Biology for HealthVillejuif CedexFrance
| | - Jun Mashima
- 5Center for Information Biology and DNA Data Bank of Japan, National Institute of GeneticsShizuokaJapan
| | - Hideo Matsuda
- 49Department of Bioinformatic Engineering, Graduate School of Information Science and Technology, Osaka UniversityOsakaJapan
| | - Hans-Werner Mewes
- 23MIPS—Institute for Bioinformatics, GSF—National Research Center for Environment and HealthNeuherbergGermany
| | - Shinsei Minoshima
- 50Medical Photobiology Department, Photon Medical Research Center, Hamamatsu University School of MedicineShizuokaJapan
- 52Department of Molecular Biology, Keio University School of MedicineTokyoJapan
| | | | - Hideki Nagasaki
- 51Computational Biology Research Center, National Institute of Advanced Industrial Science and TechnologyTokyoJapan
| | - Naoki Nagata
- 1Integrated Database Group, Biological Information Research Center, National Institute of Advanced Industrial Science and TechnologyTokyoJapan
| | - Rajni Nigam
- 27Medical College of Wisconsin, MilwaukeeWisconsinUnited States of America
| | - Osamu Ogasawara
- 3Human Genome Center, The Institute of Medical Science, The University of TokyoTokyoJapan
| | | | - Masafumi Ohtsubo
- 52Department of Molecular Biology, Keio University School of MedicineTokyoJapan
| | - Norihiro Okada
- 53Department of Biological Sciences, Graduate School of Bioscience and Biotechnology, Tokyo Institute of TechnologyKanagawaJapan
| | - Toshihisa Okido
- 5Center for Information Biology and DNA Data Bank of Japan, National Institute of GeneticsShizuokaJapan
| | - Satoshi Oota
- 35Bioresource Information Division, RIKEN BioResource Center, RIKEN Tsukuba InstituteIbarakiJapan
| | - Motonori Ota
- 54Global Scientific Information and Computing Center, Tokyo Institute of TechnologyTokyoJapan
| | - Toshio Ota
- 22Tokyo Research Laboratories, Kyowa Hakko Kogyo CompanyTokyoJapan
| | - Tetsuji Otsuki
- 55Molecular Biology Laboratory, Medicinal Research Laboratories, Taisho Pharmaceutical CompanySaitamaJapan
| | | | - Annemarie Poustka
- 47Molecular Genome Analysis, German Cancer Research Center-DKFZHeidelbergGermany
| | - Shuang-Xi Ren
- 21Sino-French Laboratory in Life Sciences and GenomicsShanghaiChina
- 37Chinese National Human Genome Center at ShanghaiShanghaiChina
| | - Naruya Saitou
- 56Department of Population Genetics, National Institute of GeneticsShizuokaJapan
| | - Katsunaga Sakai
- 5Center for Information Biology and DNA Data Bank of Japan, National Institute of GeneticsShizuokaJapan
| | - Shigetaka Sakamoto
- 5Center for Information Biology and DNA Data Bank of Japan, National Institute of GeneticsShizuokaJapan
| | - Ryuichi Sakate
- 39Graduate School of Frontier Sciences, Department of Integrated Biosciences, University of TokyoChibaJapan
| | - Ingo Schupp
- 47Molecular Genome Analysis, German Cancer Research Center-DKFZHeidelbergGermany
| | - Florence Servant
- 4EMBL Outstation—European Bioinformatics Institute, Wellcome Trust Genome CampusCambridgeUnited Kingdom
| | - Stephen Sherry
- 13National Center for Biotechnology Information, National Library of Medicine, National Institutes of HealthBethesda, MarylandUnited States of America
| | - Rie Shiba
- 1Integrated Database Group, Biological Information Research Center, National Institute of Advanced Industrial Science and TechnologyTokyoJapan
- 7Integrated Database Group, Japan Biological Information Research Center, Japan Biological Informatics ConsortiumTokyoJapan
| | - Nobuyoshi Shimizu
- 52Department of Molecular Biology, Keio University School of MedicineTokyoJapan
| | - Mary Shimoyama
- 27Medical College of Wisconsin, MilwaukeeWisconsinUnited States of America
| | | | - Bento Soares
- 25Medical Education and Biomedical Research Facility, University of IowaIowa City, IowaUnited States of America
| | - Charles Steward
- 15The Wellcome Trust Sanger Institute, Wellcome Trust Genome CampusCambridgeUnited Kingdom
| | - Makiko Suwa
- 51Computational Biology Research Center, National Institute of Advanced Industrial Science and TechnologyTokyoJapan
| | - Mami Suzuki
- 5Center for Information Biology and DNA Data Bank of Japan, National Institute of GeneticsShizuokaJapan
| | - Aiko Takahashi
- 1Integrated Database Group, Biological Information Research Center, National Institute of Advanced Industrial Science and TechnologyTokyoJapan
- 7Integrated Database Group, Japan Biological Information Research Center, Japan Biological Informatics ConsortiumTokyoJapan
| | - Gen Tamiya
- 1Integrated Database Group, Biological Information Research Center, National Institute of Advanced Industrial Science and TechnologyTokyoJapan
- 7Integrated Database Group, Japan Biological Information Research Center, Japan Biological Informatics ConsortiumTokyoJapan
- 43Department of Genetic Information, Division of Molecular Life Science, School of Medicine, Tokai UniversityKanagawaJapan
| | - Hiroshi Tanaka
- 33Department of Bioinformatics, Medical Research Institute, Tokyo Medical and Dental UniversityTokyoJapan
| | - Todd Taylor
- 57Human Genome Research Group, Genomic Sciences Center, RIKEN Yokohama InstituteKanagawaJapan
| | - Joseph D Terwilliger
- 58Columbia University and Columbia Genome CenterNew York, New YorkUnited States of America
| | - Per Unneberg
- 59Department of Biotechnology, Royal Institute of TechnologyStockholmSweden
| | - Vamsi Veeramachaneni
- 48Pennsylvania State UniversityUniversity Park, PennsylvaniaUnited States of America
| | - Shinya Watanabe
- 3Human Genome Center, The Institute of Medical Science, The University of TokyoTokyoJapan
| | - Laurens Wilming
- 15The Wellcome Trust Sanger Institute, Wellcome Trust Genome CampusCambridgeUnited Kingdom
| | - Norikazu Yasuda
- 1Integrated Database Group, Biological Information Research Center, National Institute of Advanced Industrial Science and TechnologyTokyoJapan
- 7Integrated Database Group, Japan Biological Information Research Center, Japan Biological Informatics ConsortiumTokyoJapan
| | - Hyang-Sook Yoo
- 18Korea Research Institute of Bioscience and BiotechnologyTaejeonKorea
| | - Marvin Stodolsky
- 60Biology Division and Genome Task Group, Office of Biological and Environmental Research, United States Department of EnergyWashington, D.CUnited States of America
| | - Wojciech Makalowski
- 48Pennsylvania State UniversityUniversity Park, PennsylvaniaUnited States of America
| | - Mitiko Go
- 61Faculty of Bio-Science, Nagahama Institute of Bio-Science and TechnologyShigaJapan
| | - Kenta Nakai
- 3Human Genome Center, The Institute of Medical Science, The University of TokyoTokyoJapan
| | - Toshihisa Takagi
- 3Human Genome Center, The Institute of Medical Science, The University of TokyoTokyoJapan
| | - Minoru Kanehisa
- 12Bioinformatics Center, Institute for Chemical Research, Kyoto UniversityKyotoJapan
| | - Yoshiyuki Sakaki
- 3Human Genome Center, The Institute of Medical Science, The University of TokyoTokyoJapan
- 57Human Genome Research Group, Genomic Sciences Center, RIKEN Yokohama InstituteKanagawaJapan
| | - John Quackenbush
- 62Institute for Genomic ResearchRockville, MarylandUnited States of America
| | - Yasushi Okazaki
- 26Genome Exploration Research Group, RIKEN Genomic Sciences Center, RIKEN Yokohama InstituteKanagawaJapan
| | - Yoshihide Hayashizaki
- 26Genome Exploration Research Group, RIKEN Genomic Sciences Center, RIKEN Yokohama InstituteKanagawaJapan
| | - Winston Hide
- 44South African National Bioinformatics Institute, University of the Western CapeBellvilleSouth Africa
| | - Ranajit Chakraborty
- 63Center for Genome Information, Department of Environmental Health, University of CincinnatiCincinnati, OhioUnited States of America
| | - Ken Nishikawa
- 5Center for Information Biology and DNA Data Bank of Japan, National Institute of GeneticsShizuokaJapan
| | - Hideaki Sugawara
- 5Center for Information Biology and DNA Data Bank of Japan, National Institute of GeneticsShizuokaJapan
| | - Yoshio Tateno
- 5Center for Information Biology and DNA Data Bank of Japan, National Institute of GeneticsShizuokaJapan
| | - Zhu Chen
- 21Sino-French Laboratory in Life Sciences and GenomicsShanghaiChina
- 37Chinese National Human Genome Center at ShanghaiShanghaiChina
- 64State Key Laboratory of Medical Genomics, Shanghai Institute of Hematology, Rui-Jin Hospital, Shanghai Second Medical UniversityShanghaiChina
| | | | - Peter Tonellato
- 65PointOne SystemsWauwatosa, WisconsinUnited States of America
| | - Rolf Apweiler
- 4EMBL Outstation—European Bioinformatics Institute, Wellcome Trust Genome CampusCambridgeUnited Kingdom
| | - Kousaku Okubo
- 5Center for Information Biology and DNA Data Bank of Japan, National Institute of GeneticsShizuokaJapan
- 40Functional Genomics Group, Biological Information Research Center, National Institute of Advanced Industrial Science and TechnologyTokyoJapan
| | - Lukas Wagner
- 13National Center for Biotechnology Information, National Library of Medicine, National Institutes of HealthBethesda, MarylandUnited States of America
| | - Stefan Wiemann
- 47Molecular Genome Analysis, German Cancer Research Center-DKFZHeidelbergGermany
| | - Robert L Strausberg
- 16National Cancer Institute, National Institutes of HealthBethesda, MarylandUnited States of America
| | - Takao Isogai
- 10Reverse Proteomics Research InstituteChibaJapan
- 66Graduate School of Life and Environmental Sciences, University of TsukubaIbarakiJapan
| | - Charles Auffray
- 20Genexpress—CNRS—Functional Genomics and Systemic Biology for HealthVillejuif CedexFrance
- 21Sino-French Laboratory in Life Sciences and GenomicsShanghaiChina
| | - Nobuo Nomura
- 40Functional Genomics Group, Biological Information Research Center, National Institute of Advanced Industrial Science and TechnologyTokyoJapan
| | - Takashi Gojobori
- 1Integrated Database Group, Biological Information Research Center, National Institute of Advanced Industrial Science and TechnologyTokyoJapan
- 5Center for Information Biology and DNA Data Bank of Japan, National Institute of GeneticsShizuokaJapan
- 67Department of Genetics, Graduate University for Advanced StudiesShizuokaJapan
| | - Sumio Sugano
- 3Human Genome Center, The Institute of Medical Science, The University of TokyoTokyoJapan
- 40Functional Genomics Group, Biological Information Research Center, National Institute of Advanced Industrial Science and TechnologyTokyoJapan
- 68Department of Medical Genome Sciences, Graduate School of Frontier Sciences, University of TokyoTokyoJapan
| |
Collapse
|
30
|
Hishiki T, Ogasawara O, Tsuruoka Y, Okubo K. Indexing anatomical concepts to OMIM Clinical Synopsis using the UMLS Metathesaurus. In Silico Biol 2004; 4:31-54. [PMID: 15089752] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/29/2023]
Abstract
As a first step toward the quantitative comparison of clinical features of diseases, we indexed the text descriptions in the Clinical Synopsis section of the Online Mendelian Inheritance in Man (OMIM) with concepts for the body parts, organs, and tissues contained in the Metathesaurus of the Unified Medical Language System (UMLS). We also indexed the text with the diseases and disorders having links to body parts specified in the thesaurus. The vocabulary size was approximately 177,540 representations for 81,435 concepts, and 2,161 concepts were indexed to 3,779 OMIM entries. The indexed concepts included 134 concepts for the noun forms of anatomical concepts and 985 indexed concepts for diseases and disorders that were linked to 132 and 408 anatomical concepts, respectively. We report herein that the retrieval of OMIM entries for diseases affecting specific organs can be made more comprehensive through the anatomical concepts indexed to the Clinical Synopsis or linked to the indexed concepts, as compared to simply matching organ names to the Clinical Synopsis text. The recall and precision of identifying relevant body parts in the Clinical Synopsis were calculated as 78% and 92.5%, respectively, based on random sampling. The examination of the unidentified body parts due to lack of indexed diseases and disorders showed that although most of the concepts for diseases and disorders were contained in the Metathesaurus, their relations to body parts were not. The indexing result proved the effectiveness of the Metathesaurus as a resource for the identification of concepts indicating body parts, diseases, and disorders.
Collapse
Affiliation(s)
- Teruyoshi Hishiki
- Biological Information Research Center, National Institute of Advanced Industrial Science and Technology.
| | | | | | | |
Collapse
|
31
|
Kanda I, Akazome Y, Ogasawara O, Mori T. Expression of cytochrome P450 cholesterol side chain cleavage and 3beta-hydroxysteroid dehydrogenase during embryogenesis in chicken adrenal glands and gonads. Gen Comp Endocrinol 2000; 118:96-104. [PMID: 10753571 DOI: 10.1006/gcen.1999.7448] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/22/2022]
Abstract
Expression of cytochrome P450 cholesterol side chain cleavage (P450scc) and 3beta-hydroxysteroid dehydrogenase (3beta-HSD) mRNAs was examined in chicken embryonic adrenal glands and gonads between days 4 and 12 of incubation. In situ hybridization analysis showed that 3beta-HSD mRNA appeared on day 5 of incubation in the adrenal glands and on day 6 in the gonads, while P450scc mRNA was expressed on day 7 in both the adrenal glands and the gonads. Cells expressing both enzyme mRNAs were distributed in the steroidogenic tissues of the adrenal glands and in the medullary cords of the gonads. From days 9 to 11 of incubation, P450scc mRNA expression was not found in the majority of both the adrenal glands and the gonads, but was detected again in both on day 12, although 3beta-HSD mRNA was constitutively expressed during this period. Changes in the expression pattern of P450scc mRNA are paralleled by changes in the plasma corticosterone level reported previously. Therefore, it is suggested that P450scc is essential to embryogenesis.
Collapse
Affiliation(s)
- I Kanda
- Department of Biological Sciences, Graduate School of Science, University of Tokyo, Bunkyo-ku, Tokyo, 113-0033, Japan
| | | | | | | |
Collapse
|
32
|
Abstract
The primary structure of the N-terminal extracellular region of the follitropin receptor (FSH-R), which is thought to be responsible for hormone binding specificity, was determined in three reptilian species (tortoise, gecko, and lizard). Remarkably low sequence homologies were detected in the C-terminal part of the extracellular domain. This region was estimated to be a part of exon 10, which is the last exon of the FSH-R gene. In this region, not only were low homologies detected among the three reptilian species, but also specific deletions and/or insertions were found. In particular, large deletions were detected in squamate (gecko and lizard) FSH-Rs. Phylogenetic analysis indicated that these large deletions occurred recently, i.e., after the Triassic period. In another region characterized, sequence homologies were high, with tortoise-rat homology 78.4%, gecko-rat 64.7%, and lizard-rat 69.1%. In this highly conserved region, however, some reptile-specific alterations were detected, such as the loss of a cysteine residue in putative exon 7 and the existence of potential N-linked glycosylation sites in putative exon 9.
Collapse
Affiliation(s)
- Y Akazome
- Department of Biological Sciences, Graduate School of Science, University of Tokyo, Japan
| | | | | | | |
Collapse
|
33
|
Kimura K, Ogasawara O, Inoue K, Abe S, Ohsaki Y, Murao M, Nasuhara K. [A case of pericardial cyst presenting with a sensation of chest compression oppression sensation (author's transl)]. Nihon Kyobu Shikkan Gakkai Zasshi 1979; 17:589-93. [PMID: 529630] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [MESH Headings] [Subscribe] [Scholar Register] [Indexed: 12/15/2022]
|