ArticleParasites & vectors2021
Gene co-expression network analysis of Trypanosoma brucei in tsetse fly vector.
Article in Parasites & vectors, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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Who cites it
7 citing papers in PubMed, 10 citations in OpenAlex.
- Conserved and divergent mitochondrial assemblies in kinetoplastid parasites.Molecular cell · 2026Article
- Exploring a gene co-expression network throughout the trypanosoma cruzi life cycle.BMC genomics · 2025Article
- Prioritization of Trypanosoma brucei editosome protein interactions interfaces at residue resolution through proteome-scale network analysis.BMC molecular and cell biology · 2024Article
- Weighted gene co-expression network analysis reveals immune evasion related genes inExperimental biology and medicine (Maywood, N.J.) · 2024Article
- Article
- Gene coexpression network during ontogeny in the yellow fever mosquito, Aedes aegypti.BMC genomics · 2023Article
- In silico-driven analysis of thePeerJ · 2021Article
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Authors and funding
3 authors at 2 institutions in 1 country.
Funding
Abstract
backgroundTrypanosoma brucei species are motile protozoan parasites that are cyclically transmitted by tsetse fly (genus Glossina) causing human sleeping sickness and nagana in livestock in sub-Saharan Africa. African trypanosomes display digenetic life cycle stages in the tsetse fly vector and in their mammalian host. Experimental work on insect-stage trypanosomes is challenging because of the difficulty in setting up successful in vitro cultures. Therefore, there is limited knowledge on the trypanosome biology during its development in the tsetse fly. Consequently, this limits the development of new strategies for blocking parasite transmission in the tsetse fly.
methodsIn this study, RNA-Seq data of insect-stage trypanosomes were used to construct a T. brucei gene co-expression network using the weighted gene co-expression analysis (WGCNA) method. The study identified significant enriched modules for genes that play key roles during the parasite's development in tsetse fly. Furthermore, potential 3' untranslated region (UTR) regulatory elements for genes that clustered in the same module were identified using the Finding Informative Regulatory Elements (FIRE) tool.
resultsA fraction of gene modules (12 out of 27 modules) in the constructed network were found to be enriched in functional roles associated with the cell division, protein biosynthesis, mitochondrion, and cell surface. Additionally, 12 hub genes encoding proteins such as RNA-binding protein 6 (RBP6), arginine kinase 1 (AK1), brucei alanine-rich protein (BARP), among others, were identified for the 12 significantly enriched gene modules. In addition, the potential regulatory elements located in the 3' untranslated regions of genes within the same module were predicted.
conclusionsThe constructed gene co-expression network provides a useful resource for network-based data mining to identify candidate genes for functional studies. This will enhance understanding of the molecular mechanisms that underlie important biological processes during parasite's development in tsetse fly. Ultimately, these findings will be key in the identification of potential molecular targets for disease control.
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