Literature DB >> 20975904

An integrated database for the enhanced identification of silkworm gene resources.

Changkug Kim1, Keeyoung Kim, Dongsuk Park, Youngjoo Seol, Jangho Hahn, Soochul Park, Pildon Kang.   

Abstract

UNLABELLED: The National Academy of Agricultural Science (NAAS) has developed a web-based database to provide characterization information in silkworm. The silkworm database has four major function menus: variety searching, characterization viewing, general information and photo gallery. It provides 321 silkworm varieties characterization information for six different regions namely, Korean, Japanese, Chinese, European, Tropical and non-classified group. Additionally, the database provides 1,132 photo images regarding life cycle of various silkworm varieties. A specific characterization information table provides accession number, variety, strain and larval marking, blood color, cocoon color, cocoon shape, egg colors, remarks and image table provides photos which consist of shape and color in the different stages of larval, egg and cocoon stages. AVAILABILITY: The database is available for free at http://www.naas.go.kr/silkworm/english/

Entities:  

Keywords:  gene resources; silkworm database; silkworm races; silkworm variety

Year:  2010        PMID: 20975904      PMCID: PMC2951706          DOI: 10.6026/97320630004336

Source DB:  PubMed          Journal:  Bioinformation        ISSN: 0973-2063


Background

The silkworm is one of the most economically important, beneficial insects in many developing countries owing to for silk production and source of biomaterials. With advances in genomic technologies, there is a rapid increase in silkworm­related data including genome sequences and genetic markers. The SilkDB database is a web based repository for the curation, integration and study of silkworm genetic and genomic data [1]. KAIKObase is an integrated silkworm genome database and data mining tool with 4 map browsers, 1 gene viewer, and 2 independent databases [2]. The Central Sericultural Germplasm Resources Centre (CSGRC) provides 1,120 mulberry and 432 silkworm germplasm resources [3]. The WildSilkbase provides the database is provided with 57,113 ESTs which are clustered and assembled into 4,019 contigs and 10,019 singletons derived from 3 major wild silk­moth [4]. The SilkSatDb is a relational database of microsatellites extracted from the available expressed sequence tags and whole genome shotgun sequences of the silk­moth [5]. The National Academy of Agricultural Science (NAAS) has developed a database system to provide integrated information about various gene resources [6-8]and has launched the silkworm gene resources project [9]. Towards this effort, we developed a web­based database to provide characterization and images information in silkworm.

Methodology

Dataset

The silkworm varieties collected from the silkworm gene resources project of NAAS. As a result of this project, we have investigated the characterization of silkworms as variety, strain and larval marking including shape and color in the different stage images. The silkworm database provides 321 silkworm variety information for six different regions namely, Korean (4 varieties), Japanese (90 varieties), Chinese (96 varieties), European (32 varieties), Tropical (9 varieties) and non­classified (90 varieties). The 1,132 photo images of shape and color information collected from the life cycle of various silkworm varieties. Additionally, the database was distinguished four different race types, namely univoltine (32 races), bivoltine (188 races), multivoltine (11 races) and others (90 races).

Database development

Using the collected silkworm varieties characterization and image information, we have developed a silkworm gene resources database with four main features: variety searching, characterization viewing, general information and photo gallery. The platform was developed using MYSQL and JAVA languages. The data was stored in Oracle relational database management system (RDBMS). The logical and physical schema of the database followed the standard principles of relational database by ERWin Data Modeler software.

Implementation and features

The silkworm database [10] has four major function menus: variety searching, characterization viewing, general information and photo gallery. The variety searching viewer allows that users can access the information of 321 silkworm gene resources. Characterization viewer provides silkworm gene resources characterization information including images in the life cycle such as larval, egg and cocoon stages. General information menu provides a table of detailed information such as description of silkworm, brushing, rearing of young silkworms, rearing of advanced silkworms, mounting, cocoon harvesting and cocoon sorting. The photo gallery menu provides 1,132 images regarding shape and color in the life cycle of various silkworm varieties. All images of database provide an enlargement photograph by clicking a specific image. When using category search or clicking identification number, users can view a table of detailed characterization table and image table of three life cycle stages in silkworm. A specific characterization information table provides accession number, variety, strain and larval marking, blood color, cocoon color, cocoon shape, egg colors, remarks and image table provides photos which consist of shape and color in the different stages of larval, egg and cocoon stages Figure 1.
Figure 1

A snap shot of the specific characterization information table through silkworm database. The characterization and image information table show sample (Hansung banmun) by clicking a specific identification number (No. 143).

Future work

The silkworm gene resources database consists of four major functional categories: variety searching, characterization viewing, general information and photo gallery. The database provides of 321 silkworm gene resources and 1,132 images regarding life cycle of various silkworm varieties. Users are assisted in tracing any new variety and utilization on basic such as silkworm breeding using specific characterization information. In the future, we plans to develop an integrated silkworm database not only commercial silkworm genes but also wild silkworms and other rare insect species.
  7 in total

1.  SilkSatDb: a microsatellite database of the silkworm, Bombyx mori.

Authors:  M D Prasad; M Muthulakshmi; K P Arunkumar; M Madhu; V B Sreenu; V Pavithra; B Bose; H A Nagarajaram; K Mita; T Shimada; J Nagaraju
Journal:  Nucleic Acids Res       Date:  2005-01-01       Impact factor: 16.971

2.  PlantGM: a database for genetic markers in rice (Oryza sativa) and Chinese cabbage (Brassica rapa).

Authors:  Chang Kug Kim; Jung Sun Kim; Gang Seob Lee; Beom Seok Park; Jang Ho Hahn
Journal:  Bioinformation       Date:  2008-10-17

3.  A database for allergenic proteins and tools for allergenicity prediction.

Authors:  ChangKug Kim; SooJin Kwon; GangSeob Lee; HwanKi Lee; JiWeon Choi; YongHwan Kim; JangHo Hahn
Journal:  Bioinformation       Date:  2009-04-21

4.  KAIKObase: an integrated silkworm genome database and data mining tool.

Authors:  Michihiko Shimomura; Hiroshi Minami; Yoshitaka Suetsugu; Hajime Ohyanagi; Chikatada Satoh; Baltazar Antonio; Yoshiaki Nagamura; Keiko Kadono-Okuda; Hideyuki Kajiwara; Hideki Sezutsu; Javaregowda Nagaraju; Marian R Goldsmith; Qingyou Xia; Kimiko Yamamoto; Kazuei Mita
Journal:  BMC Genomics       Date:  2009-10-21       Impact factor: 3.969

5.  SilkDB v2.0: a platform for silkworm (Bombyx mori ) genome biology.

Authors:  Jun Duan; Ruiqiang Li; Daojun Cheng; Wei Fan; Xingfu Zha; Tingcai Cheng; Yuqian Wu; Jun Wang; Kazuei Mita; Zhonghuai Xiang; Qingyou Xia
Journal:  Nucleic Acids Res       Date:  2009-09-30       Impact factor: 16.971

6.  PlantGI: a database for searching gene indices in agricultural plants developed at NIAB, Korea.

Authors:  Chang Kug Kim; Ji Weon Choi; DongSuk Park; Man Jung Kang; Young-Joo Seol; Do Yoon Hyun; Jang Ho Hahn
Journal:  Bioinformation       Date:  2008-05-27

7.  WildSilkbase: an EST database of wild silkmoths.

Authors:  K P Arunkumar; Archana Tomar; Takaaki Daimon; Toru Shimada; J Nagaraju
Journal:  BMC Genomics       Date:  2008-07-17       Impact factor: 3.969

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Review 1.  A comprehensive view of the web-resources related to sericulture.

Authors:  Deepika Singh; Hasnahana Chetia; Debajyoti Kabiraj; Swagata Sharma; Anil Kumar; Pragya Sharma; Manab Deka; Utpal Bora
Journal:  Database (Oxford)       Date:  2016-06-15       Impact factor: 3.451

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