Structure-based screening for functional non-coding RNAs in fission yeast identifies a factor repressing untimely initiation of sexual differentiation.

Non-coding RNAs (ncRNAs) ubiquitously exist in normal and cancer cells. Despite their prevalent distribution, the functions of most long ncRNAs remain uncharacterized. The fission yeast Schizosaccharomyces pombe expresses >1800 ncRNAs annotated to date, but most unconventional ncRNAs (excluding tRNA, rRNA, snRNA and snoRNA) remain uncharacterized. To discover the functional ncRNAs, here we performed a combinatory screening of computational and biological tests. First, all S. pombe ncRNAs were screened in silico for those showing conservation in sequence as well as in secondary structure with ncRNAs in closely related species. Almost a half of the 151 selected conserved ncRNA genes were uncharacterized. Twelve ncRNA genes that did not overlap with protein-coding sequences were next chosen for biological screening that examines defects in growth or sexual differentiation, as well as sensitivities to drugs and stresses. Finally, we highlighted an ncRNA transcribed from SPNCRNA.1669, which inhibited untimely initiation of sexual differentiation. A domain that was predicted as conserved secondary structure by the computational operations was essential for the ncRNA to function. Thus, this study demonstrates that in silico selection focusing on conservation of the secondary structure over species is a powerful method to pinpoint novel functional ncRNAs.

Insights into transcription termination of Hfq-binding sRNAs of Escherichia coli and characterization of readthrough products.

The genes encoding Hfq-dependent sRNAs possess a typical Rho-independent transcription terminator. Here, we have studied the molecular events occurring at Rho-independent terminators of sRNA genes, focusing on two well-characterized Hfq-binding sRNAs, SgrS and RyhB. We constructed several hybrid genes in which the DNA sequence corresponding to a strong Rho-independent terminator was placed just downstream from the Rho-independent terminators of sRNA genes. By using this system, we demonstrate that transcripts frequently read through the Rho-independent terminators of sgrS and ryhB in normally growing cells. We show that Hfq does not affect the transcriptional readthrough event itself. We also find that the readthrough products no longer bind to Hfq in vivo. We have developed a competition assay based on a biotin-streptavidin system to analyze the interaction of Hfq and a particular RNA molecule in vitro. By using this method, we verify that the 3'-extended form of SgrS does not bind to Hfq in vitro. Finally, we demonstrate that transcription termination is significantly enhanced under stress conditions where transcription initiation of sRNA genes on the chromosome is induced. We conclude that the production of sRNAs is regulated not only at the step of transcription initiation but also at the step of transcription termination. The mechanism by which transcription termination is enhanced under stress conditions remains to be understood.

Bioinformatics approaches for unveiling virus-host interactions.

The coronavirus disease-2019 (COVID-19) pandemic has elucidated major limitations in the capacity of medical and research institutions to appropriately manage emerging infectious diseases. We can improve our understanding of infectious diseases by unveiling virus-host interactions through host range prediction and protein-protein interaction prediction. Although many algorithms have been developed to predict virus-host interactions, numerous issues remain to be solved, and the entire network remains veiled. In this review, we comprehensively surveyed algorithms used to predict virus-host interactions. We also discuss the current challenges, such as dataset biases toward highly pathogenic viruses, and the potential solutions. The complete prediction of virus-host interactions remains difficult; however, bioinformatics can contribute to progress in research on infectious diseases and human health.