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Inference of Rift Valley Fever pathogenesis in Bos taurus using a gene co-expression network

John K. Gitau, Rosaline W. Macharia, Kennedy W. Mwangi, Nehemiah M. Ongeso, Edwin Murungi
doi: https://doi.org/10.1101/2021.11.28.470222
John K. Gitau
1University of Nairobi, Biochemistry department, P.O Box 30197 – 00100, Nairobi, Kenya
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  • For correspondence: johngitau51@gmail.com
Rosaline W. Macharia
1University of Nairobi, Biochemistry department, P.O Box 30197 – 00100, Nairobi, Kenya
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Kennedy W. Mwangi
3Jomo Kenyatta University of Agriculture and Technology, P.O Box 62000 – 00200, Nairobi, Kenya
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Nehemiah M. Ongeso
1University of Nairobi, Biochemistry department, P.O Box 30197 – 00100, Nairobi, Kenya
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Edwin Murungi
2Kisii University, Department of Medical Biochemistry, P.O Box 408 – 40200, Kisii, Kenya
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Abstract

Background Rift Valley Fever (RVF) is a viral disease caused by the Rift Valley Fever virus and spread mainly by the Aedes and Culex mosquito species. The disease primarily infects domestic animals such as sheep, goats, and cattle, resulting in a spectrum of clinical outcomes including morbidity, massive storm abortions, and neonatal fatalities. RVF outbreaks are closely linked to above-average rainfall and flooding, which create an ideal environment for mosquitos to breed, multiply, and transmit the virus to animals. The outcomes of human RVF infection range from self-limiting febrile illness to potentially fatal hemorrhagic diatheses and miscarriage in pregnant women. Collectively, the economic losses due to the zoonotic RVF disease is immense.

Methods Using the Weighted Gene Co-expression Network Analysis (WGCNA) package, RNA-Seq data generated from five healthy Bos taurus steer calves aged 4-6 months was obtained from the Gene Expression Omnibus (GEO) database (Accession number GSE71417). The data was utilized to construct a gene co-expression network. Enriched modules containing genes potentially involved in RVF infection progression were identified. Moreover, using the Multiple Expectation Maximizations for Motif Elicitation (MEME) suite, consensus regulatory motifs of enriched gene clusters were deciphered and the most abundant putative regulatory motif in each enriched module unveiled by comparative analysis with publicly available motifs using the TOMTOM motif comparison tool. The potential roles of the identified regulatory motifs were inferred by literature mining.

Results The constructed gene co-expression network revealed thirty-three (33) modules, nine of which were enriched for Gene Ontology terms linked to RVF pathogenesis. Functional enrichment in two (red and turquoise) of the nine modules was significant. ASH1-like histone lysine methyltransferase and Astrotactin were the hub genes for the red and turquoise modules respectively. ASH1-like histone lysine methyltransferase gene is involved in chromatin epigenetic modification while Astrotactin is a vertebrate-specific gene that plays an important role in neurodevelopment. Additionally, consensus regulatory motifs located on the 3' end of genes in each enriched module was identified.

Conclusions In this study, we have developed a gene co-expression network that has aided in the unveiling of functionally related genes, intramodular hub genes, and immunity genes potentially involved in RVF pathogenesis. The discovery of functional genes with putative critical roles in the establishment of RVF infection establishment will contribute to the understanding of the molecular mechanism of RVF pathogenesis. Importantly, the putative regulatory motifs identified are plausible targets for RVF drug and vaccine development.

Competing Interest Statement

The authors have declared no competing interest.

Footnotes

  • Emails: JKG: johngitau51{at}gmail.com, KWM: wanjaukm{at}gmail.com, NMO: nehemiahongeso{at}gmail.com, EM: edwinmurungi{at}kisiiuniversity.ac.ke, RWM: rosaline{at}uonbi.ac.ke

  • https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE71417

  • Abbreviations

    RVF
    Rift Valley Fever
    RVFV
    Rift Valley Fever Virus
    PPI
    Protein-Protein Interactions
    WGCNA
    Weighted Gene Co-Expression Network Analysis
    GPCR
    G-protein coupled receptor
    GO
    Gene Ontology
    MEME
    Multiple Expectation Maximizations for Motif Elicitation
    TOM
    Topological overlap matrix
  • Copyright 
    The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-NC 4.0 International license.
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    Inference of Rift Valley Fever pathogenesis in Bos taurus using a gene co-expression network
    John K. Gitau, Rosaline W. Macharia, Kennedy W. Mwangi, Nehemiah M. Ongeso, Edwin Murungi
    bioRxiv 2021.11.28.470222; doi: https://doi.org/10.1101/2021.11.28.470222
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    Inference of Rift Valley Fever pathogenesis in Bos taurus using a gene co-expression network
    John K. Gitau, Rosaline W. Macharia, Kennedy W. Mwangi, Nehemiah M. Ongeso, Edwin Murungi
    bioRxiv 2021.11.28.470222; doi: https://doi.org/10.1101/2021.11.28.470222

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