An Integrated Bioinformatics Approach to Identify Network-Derived Hub Genes in Starving Zebrafish

The present study was aimed at identifying causative hub genes within modules formed by co-expression and protein–protein interaction (PPI) networks, followed by Bayesian network (BN) construction in the liver transcriptome of starved zebrafish. To this end, the GSE11107 and GSE112272 datasets from...

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Bibliographic Details
Published in:Animals (Basel) 2022-10, Vol.12 (19), p.2724
Main Authors: Mortazavi, Amin, Ghaderi-Zefrehei, Mostafa, Muhaghegh Dolatabady, Mustafa, Golshan, Mahdi, Nazari, Sajad, Sadr, Ayeh Sadat, Kadkhodaei, Saeid, Imumorin, Ikhide G., Peters, Sunday O., Smith, Jacqueline
Format: Article
Language:English
Subjects:
Algorithms
Bayesian analysis
Bayesian network
bioinformatic analysis
Bioinformatics
co-expression
Danio rerio
Datasets
DNA chips
DNA microarrays
Fatty acids
Gene expression
Genes
hub genes
Liver
Metabolism
miRNA
Phosphorylation
Proteins
Software
starvation
Transcriptomes
Zebrafish
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Summary:The present study was aimed at identifying causative hub genes within modules formed by co-expression and protein–protein interaction (PPI) networks, followed by Bayesian network (BN) construction in the liver transcriptome of starved zebrafish. To this end, the GSE11107 and GSE112272 datasets from the GEO databases were downloaded and meta-analyzed using the MetaDE package, an add-on R package. Differentially expressed genes (DEGs) were identified based upon expression intensity N(µ = 0.2, σ2 = 0.4). Reconstruction of BNs was performed by the bnlearn R package on genes within modules using STRINGdb and CEMiTool. ndufs5 (shared among PPI, BN and COEX), rps26, rpl10, sdhc (shared between PPI and BN), ndufa6, ndufa10, ndufb8 (shared between PPI and COEX), skp1, atp5h, ndufb10, rpl5b, zgc:193613, zgc:123327, zgc:123178, wu:fc58f10, zgc:111986, wu:fc37b12, taldo1, wu:fb62f08, zgc:64133 and acp5a (shared between COEX and BN) were identified as causative hub genes affecting gene expression in the liver of starving zebrafish. Future work will shed light on using integrative analyses of miRNA and DNA microarrays simultaneously, and performing in silico and experimental validation of these hub-causative (CST) genes affecting starvation in zebrafish.
ISSN:2076-2615
2076-2615
DOI:10.3390/ani12192724