A bioinformatic approach for the prediction and functional classification of Toxoplasma gondii long non-coding RNAs.

ABSTRACT: Long non-coding RNAs (lncRNAs) have emerged as significant players in diverse cellular processes, including cell differentiation. Advancements in computational methodologies have facilitated the prediction of lncRNA functions, enabling insights even in non-model organisms like pathogenic parasites, in roles such as parasite development, antigenic variation, and epigenetics. In this work, we focus on the apicomplexan Toxoplasma gondii differentiation process, where the infective stage, tachyzoite, can develop into the cysted stage, bradyzoite, under stress conditions. Using a publicly available transcriptome dataset, we predicted putative lncRNA sequences associated with this differentiation process. Notably, a substantial proportion of these putative lncRNAs exhibited stage-specific expres

SUBMITTER: Vanagas L 

PROVIDER: S-EPMC11557611 | biostudies-literature | 2024 Nov

REPOSITORIES: biostudies-literature