• Türkçe
    • English
  • English 
    • Türkçe
    • English
  • Login
View Item 
  •   DSpace@Muğla
  • Araştırma Çıktıları | TR-Dizin | WoS | Scopus | PubMed
  • WoS İndeksli Yayınlar Koleksiyonu
  • View Item
  •   DSpace@Muğla
  • Araştırma Çıktıları | TR-Dizin | WoS | Scopus | PubMed
  • WoS İndeksli Yayınlar Koleksiyonu
  • View Item
JavaScript is disabled for your browser. Some features of this site may not work without it.

Integrative Analysis of Axolotl Gene Expression Data from Regenerative and Wound Healing Limb Tissues

Thumbnail

View/Open

Tam Metin / Full Text (4.402Mb)

Date

2019

Author

Sibai, Mustafa
Parlayan, Cüneyd
Tuğlu, Pelin
Özturk, Gürkan
Demircan, Turan

Metadata

Show full item record

Abstract

Axolotl (Ambystoma mexicanum) is a urodele amphibian endowed with remarkable regenerative capacities manifested in scarless wound healing and restoration of amputated limbs, which makes it a powerful experimental model for regenerative biology and medicine. Previous studies have utilized microarrays and RNA-Seq technologies for detecting differentially expressed (DE) genes in different phases of the axolotl limb regeneration. However, sufficient consistency may be lacking due to statistical limitations arising from intra-laboratory analyses. This study aims to bridge such gaps by performing an integrative analysis of publicly available microarray and RNA-Seq data from axolotl limb samples having comparable study designs using the "merging" method. A total of 351 genes were found DE in regenerative samples compared to the control in data of both technologies, showing an adjusted p-value < 0.01 and log fold change magnitudes >1. Downstream analyses illustrated consistent correlations of the directionality of DE genes within and between data of both technologies, as well as concordance with the literature on regeneration related biological processes. qRT-PCR analysis validated the observed expression level differences of five of the top DE genes. Future studies may benefit from the utilized concept and approach for enhanced statistical power and robust discovery of biomarkers of regeneration.

Source

Scientific Reports

Volume

9

URI

https://doi.org/10.1038/s41598-019-56829-6
https://hdl.handle.net/20.500.12809/733

Collections

  • PubMed İndeksli Yayınlar Koleksiyonu [2082]
  • Scopus İndeksli Yayınlar Koleksiyonu [6219]
  • Temel Tıp Bilimleri Bölümü Koleksiyonu [193]
  • WoS İndeksli Yayınlar Koleksiyonu [6466]



DSpace software copyright © 2002-2015  DuraSpace
Contact Us | Send Feedback
Theme by 
@mire NV
 

 




| Policy | Guide | Contact |

DSpace@Muğla

by OpenAIRE
Advanced Search

sherpa/romeo

Browse

All of DSpaceCommunities & CollectionsBy Issue DateAuthorsTitlesSubjectsTypeLanguageDepartmentCategoryPublisherAccess TypeInstitution AuthorThis CollectionBy Issue DateAuthorsTitlesSubjectsTypeLanguageDepartmentCategoryPublisherAccess TypeInstitution Author

My Account

LoginRegister

DSpace software copyright © 2002-2015  DuraSpace
Contact Us | Send Feedback
Theme by 
@mire NV
 

 


|| Policy || Guide|| Instruction || Library || Muğla Sıtkı Koçman University || OAI-PMH ||

Muğla Sıtkı Koçman University, Muğla, Turkey
If you find any errors in content, please contact:

Creative Commons License
Muğla Sıtkı Koçman University Institutional Repository is licensed under a Creative Commons Attribution-NonCommercial-NoDerivs 4.0 Unported License..

DSpace@Muğla:


DSpace 6.2

tarafından İdeal DSpace hizmetleri çerçevesinde özelleştirilerek kurulmuştur.