Academic Journal
View in EDS

Prediction of Toxin Genes from Chinese Yellow Catfish Based on Transcriptomic and Proteomic Sequencing.

Bibliographic Details
Title: Prediction of Toxin Genes from Chinese Yellow Catfish Based on Transcriptomic and Proteomic Sequencing.
Authors: Bing Xie, Xiaofeng Li, Zhilong Lin, Zhiqiang Ruan, Min Wang, Jie Liu, Ting Tong, Jia Li, Yu Huang, Bo Wen, Ying Sun, Qiong Shi
Source: International Journal of Molecular Sciences; 2016, Vol. 17 Issue 4, p556, 13p
Subject Terms: TOXICOLOGY of poisonous fishes, FLATHEAD catfish, TOXINS, FISH genetics, PROTEOMICS
Abstract: Fish venom remains a virtually untapped resource. There are so few fish toxin sequences for reference, which increases the difficulty to study toxins from venomous fish and to develop efficient and fast methods to dig out toxin genes or proteins. Here, we utilized Chinese yellow catfish (Pelteobagrus fulvidraco) as our research object, since it is a representative species in Siluriformes with its venom glands embedded in the pectoral and dorsal fins. In this study, we set up an in-house toxin database and a novel toxin-discovering protocol to dig out precise toxin genes by combination of transcriptomic and proteomic sequencing. Finally, we obtained 15 putative toxin proteins distributed in five groups, namely Veficolin, Ink toxin, Adamalysin, Za2G and CRISP toxin. It seems that we have developed a novel bioinformatics method, through which we could identify toxin proteins with high confidence. Meanwhile, these toxins can also be useful for comparative studies in other fish and development of potential drugs. [ABSTRACT FROM AUTHOR]
Copyright of International Journal of Molecular Sciences is the property of MDPI and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Database: Complementary Index
FullText Links:
  – Type: pdflink
Text:
  Availability: 0
CustomLinks:
  – Url: https://resolver.ebsco.com/c/xy5jbn/result?sid=EBSCO:edb&genre=article&issn=16616596&ISBN=&volume=17&issue=4&date=20160401&spage=556&pages=556-568&title=International Journal of Molecular Sciences&atitle=Prediction%20of%20Toxin%20Genes%20from%20Chinese%20Yellow%20Catfish%20Based%20on%20Transcriptomic%20and%20Proteomic%20Sequencing.&aulast=Bing%20Xie&id=DOI:10.3390/ijms17040556
    Name: Full Text Finder (for New FTF UI) (s8985755)
    Category: fullText
    Text: Find It @ SCU Libraries
    MouseOverText: Find It @ SCU Libraries
Header DbId: edb
DbLabel: Complementary Index
An: 114888424
RelevancyScore: 853
AccessLevel: 6
PubType: Academic Journal
PubTypeId: academicJournal
PreciseRelevancyScore: 853.187316894531
IllustrationInfo
Items – Name: Title
  Label: Title
  Group: Ti
  Data: Prediction of Toxin Genes from Chinese Yellow Catfish Based on Transcriptomic and Proteomic Sequencing.
– Name: Author
  Label: Authors
  Group: Au
  Data: <searchLink fieldCode="AR" term="%22Bing+Xie%22">Bing Xie</searchLink><br /><searchLink fieldCode="AR" term="%22Xiaofeng+Li%22">Xiaofeng Li</searchLink><br /><searchLink fieldCode="AR" term="%22Zhilong+Lin%22">Zhilong Lin</searchLink><br /><searchLink fieldCode="AR" term="%22Zhiqiang+Ruan%22">Zhiqiang Ruan</searchLink><br /><searchLink fieldCode="AR" term="%22Min+Wang%22">Min Wang</searchLink><br /><searchLink fieldCode="AR" term="%22Jie+Liu%22">Jie Liu</searchLink><br /><searchLink fieldCode="AR" term="%22Ting+Tong%22">Ting Tong</searchLink><br /><searchLink fieldCode="AR" term="%22Jia+Li%22">Jia Li</searchLink><br /><searchLink fieldCode="AR" term="%22Yu+Huang%22">Yu Huang</searchLink><br /><searchLink fieldCode="AR" term="%22Bo+Wen%22">Bo Wen</searchLink><br /><searchLink fieldCode="AR" term="%22Ying+Sun%22">Ying Sun</searchLink><br /><searchLink fieldCode="AR" term="%22Qiong+Shi%22">Qiong Shi</searchLink>
– Name: TitleSource
  Label: Source
  Group: Src
  Data: International Journal of Molecular Sciences; 2016, Vol. 17 Issue 4, p556, 13p
– Name: Subject
  Label: Subject Terms
  Group: Su
  Data: <searchLink fieldCode="DE" term="%22TOXICOLOGY+of+poisonous+fishes%22">TOXICOLOGY of poisonous fishes</searchLink><br /><searchLink fieldCode="DE" term="%22FLATHEAD+catfish%22">FLATHEAD catfish</searchLink><br /><searchLink fieldCode="DE" term="%22TOXINS%22">TOXINS</searchLink><br /><searchLink fieldCode="DE" term="%22FISH+genetics%22">FISH genetics</searchLink><br /><searchLink fieldCode="DE" term="%22PROTEOMICS%22">PROTEOMICS</searchLink>
– Name: Abstract
  Label: Abstract
  Group: Ab
  Data: Fish venom remains a virtually untapped resource. There are so few fish toxin sequences for reference, which increases the difficulty to study toxins from venomous fish and to develop efficient and fast methods to dig out toxin genes or proteins. Here, we utilized Chinese yellow catfish (Pelteobagrus fulvidraco) as our research object, since it is a representative species in Siluriformes with its venom glands embedded in the pectoral and dorsal fins. In this study, we set up an in-house toxin database and a novel toxin-discovering protocol to dig out precise toxin genes by combination of transcriptomic and proteomic sequencing. Finally, we obtained 15 putative toxin proteins distributed in five groups, namely Veficolin, Ink toxin, Adamalysin, Za2G and CRISP toxin. It seems that we have developed a novel bioinformatics method, through which we could identify toxin proteins with high confidence. Meanwhile, these toxins can also be useful for comparative studies in other fish and development of potential drugs. [ABSTRACT FROM AUTHOR]
– Name: Abstract
  Label:
  Group: Ab
  Data: <i>Copyright of International Journal of Molecular Sciences is the property of MDPI and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
PLink https://login.libproxy.scu.edu/login?url=https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&scope=site&db=edb&AN=114888424
RecordInfo BibRecord:
  BibEntity:
    Identifiers:
      – Type: doi
        Value: 10.3390/ijms17040556
    Languages:
      – Code: eng
        Text: English
    PhysicalDescription:
      Pagination:
        PageCount: 13
        StartPage: 556
    Subjects:
      – SubjectFull: TOXICOLOGY of poisonous fishes
        Type: general
      – SubjectFull: FLATHEAD catfish
        Type: general
      – SubjectFull: TOXINS
        Type: general
      – SubjectFull: FISH genetics
        Type: general
      – SubjectFull: PROTEOMICS
        Type: general
    Titles:
      – TitleFull: Prediction of Toxin Genes from Chinese Yellow Catfish Based on Transcriptomic and Proteomic Sequencing.
        Type: main
  BibRelationships:
    HasContributorRelationships:
      – PersonEntity:
          Name:
            NameFull: Bing Xie
      – PersonEntity:
          Name:
            NameFull: Xiaofeng Li
      – PersonEntity:
          Name:
            NameFull: Zhilong Lin
      – PersonEntity:
          Name:
            NameFull: Zhiqiang Ruan
      – PersonEntity:
          Name:
            NameFull: Min Wang
      – PersonEntity:
          Name:
            NameFull: Jie Liu
      – PersonEntity:
          Name:
            NameFull: Ting Tong
      – PersonEntity:
          Name:
            NameFull: Jia Li
      – PersonEntity:
          Name:
            NameFull: Yu Huang
      – PersonEntity:
          Name:
            NameFull: Bo Wen
      – PersonEntity:
          Name:
            NameFull: Ying Sun
      – PersonEntity:
          Name:
            NameFull: Qiong Shi
    IsPartOfRelationships:
      – BibEntity:
          Dates:
            – D: 01
              M: 04
              Text: 2016
              Type: published
              Y: 2016
          Identifiers:
            – Type: issn-print
              Value: 16616596
          Numbering:
            – Type: volume
              Value: 17
            – Type: issue
              Value: 4
          Titles:
            – TitleFull: International Journal of Molecular Sciences
              Type: main
ResultId 1