RESUMEN
Tick-borne encephalitis virus (TBEV), the most medically relevant tick-transmitted flavivirus in Eurasia, targets the host central nervous system and frequently causes severe encephalitis. The severity of TBEV-induced neuropathogenesis is highly cell-type specific and the exact mechanism responsible for such differences has not been fully described yet. Thus, we performed a comprehensive analysis of alterations in host poly-(A)/miRNA/lncRNA expression upon TBEV infection in vitro in human primary neurons (high cytopathic effect) and astrocytes (low cytopathic effect). Infection with severe but not mild TBEV strain resulted in a high neuronal death rate. In comparison, infection with either of TBEV strains in human astrocytes did not. Differential expression and splicing analyses with an in silico prediction of miRNA/mRNA/lncRNA/vd-sRNA networks found significant changes in inflammatory and immune response pathways, nervous system development and regulation of mitosis in TBEV Hypr-infected neurons. Candidate mechanisms responsible for the aforementioned phenomena include specific regulation of host mRNA levels via differentially expressed miRNAs/lncRNAs or vd-sRNAs mimicking endogenous miRNAs and virus-driven modulation of host pre-mRNA splicing. We suggest that these factors are responsible for the observed differences in the virulence manifestation of both TBEV strains in different cell lines. This work brings the first complex overview of alterations in the transcriptome of human astrocytes and neurons during the infection by two TBEV strains of different virulence. The resulting data could serve as a starting point for further studies dealing with the mechanism of TBEV-host interactions and the related processes of TBEV pathogenesis.
RESUMEN
Intron retention (IR) occurs when an intron is transcribed into pre-mRNA and remains in the final mRNA. An increasing body of literature has demonstrated a major role for IR in numerous biological functions and in disease. Here we give an overview of the different computational approaches for detecting IR events from sequencing data. We show that these are based on different biological and computational assumptions that may lead to dramatically different results. We describe the various approaches for mitigating errors in detecting intron retention and for discovering IR signatures between different conditions.