eISSN: 2353-9461
ISSN: 0860-7796
BioTechnologia
Current issue Archive About the journal Editorial board Abstracting and indexing Subscription Contact Instructions for authors Ethical standards and procedures
 
2/2018
vol. 99
 
Share:
Share:
more
 
 
abstract:
RESEARCH PAPERS

Transcriptome signature of the lactation process, identified by meta-analysis of microarray and RNA-Seq data

Mohammad Farhadian
,
Seyed Abbas Rafat
,
Karim Hasanpur
,
Esmaeil Ebrahimie

BioTechnologia vol. 99(2) C pp. 153–163 C 2018
Online publish date: 2018/06/26
View full text
Get citation
ENW
EndNote
BIB
JabRef, Mendeley
RIS
Papers, Reference Manager, RefWorks, Zotero
AMA
APA
Chicago
Harvard
MLA
Vancouver
 
Lactation plays the crucial role in mammals’ life. Uncovering the transcriptome signature of lactation process helps to understand the molecular basis of milk production. To identify the genes that express differentially between early and late lactation, publicly available microarray transcriptomic datasets of dairy cattle were investigated and the array results were validated by a next-generation sequencing dataset (RNA-Seq data from sheep). Limma and edgeR packages were used for the analysis of the microarray and RNA-Seq datasets, respectively. Five common differentially expressed genes (DEGs), namely glutathione s-transferase mu 3 (GSTM3 ), EGF containing fibulin-like extracellular matrix protein 1(EFEMP1 ), fibulin 1(FBLN1 ), gelsolin (GSN ), and fibrinogen-like 2 (FGL2 ), were identified. The involvement of EFEMP1 in the lactation process has been reported for the first time. The identified DEGs are involved in the development of the immune system and cell differentiation of the mammary gland. A gene ontology network analysis revealed the key role of the GSN gene in the regulation of two important functions of actin nucleation and barbed-end actin filament capping. The gene ontology enrichment analysis showed that the function of calcium ion binding is statistically (P < 0.05) enriched by the identified transcriptomic signature. The approach presented in this study provides an integrative framework for finding the signature of the lactation process by utilizing global transcriptome data, gene ontology (GO) regulatory network, and enrichment analysis.
keywords:

co-expression network, microarray, milk production, RNA-Seq

 
Stosujemy się do standardu HONcode dla wiarygodnej informacji zdrowotnej This site complies with the HONcode standard for trustworthy health information: verify here