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Transcriptomic Analysis of Long Non-Coding RNA during Candida albicans Infection

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Candida albicans is one of the most commonly found species in fungal infections. Due to its clinical importance, molecular aspects of the host immune defense against the fungus are of… Click to show full abstract

Candida albicans is one of the most commonly found species in fungal infections. Due to its clinical importance, molecular aspects of the host immune defense against the fungus are of interest to biomedical sciences. Long non-coding RNAs (lncRNAs) have been investigated in different pathologies and gained widespread attention regarding their role as gene regulators. However, the biological processes in which most lncRNAs perform their function are still unclear. This study investigates the association between lncRNAs with host response to C. albicans using a public RNA-Seq dataset from lung samples of female C57BL/6J wild-type Mus musculus with induced C. albicans infection. The animals were exposed to the fungus for 24 h before sample collection. We selected lncRNAs and protein-coding genes related to the host immune response by combining the results from different computational approaches used for gene selection: differential expression gene analysis, co-expression genes network analysis, and machine learning-based gene selection. Using a guilt by association strategy, we inferred connections between 41 lncRNAs and 25 biological processes. Our results indicated that nine up-regulated lncRNAs were associated with biological processes derived from the response to wounding: 1200007C13Rik, 4833418N02Rik, Gm12840, Gm15832, Gm20186, Gm38037, Gm45774, Gm4610, Mir22hg, and Mirt1. Additionally, 29 lncRNAs were related to genes involved in immune response, while 22 lncRNAs were associated with processes related to reactive species production. These results support the participation of lncRNAs during C. albicans infection, and may contribute to new studies investigating lncRNA functions in the immune response.

Keywords: non coding; albicans infection; analysis; response; candida albicans; long non

Journal Title: Genes
Year Published: 2023

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