Background: Tuberculosis remains one of the leading causes of morbidity and mortality worldwide. Therefore, understanding the pathophysiology of Mycobacterium tuberculosis is imperative for developing new drugs. Posttranscriptional regulation plays a significant role in microbial adaptation to different growth conditions. While the proteins associated with gene expression regulation have been extensively studied in the pathogenic strain M. tuberculosis H37Rv, post-transcriptional regulation involving small RNAs (sRNAs) remains poorly understood.
Results:We developed a novel moving-window based approach to detect sRNA expression using RNA-Seq data.Overlaying ChIP-seq data of RNAP (RNA Polymerase) and NusA suggest that these putative sRNA coding regions are significantly bound by the transcription machinery. Besides capturing many experimentally validated sRNAs, we observe the context-dependent expression of novel sRNAs in the intergenic regions of M. tuberculosis genome. For example, ncRv11806 shows expression only in the stationary phase, suggesting its role in mycobacterial latency which is a key attribute to long term pathogenicity. Also, ncRv11875C showed expression in the iron-limited condition, which is prevalent inside the macrophages of the host cells. Conclusion: The systems level analysis of sRNA highlights the condition-specific expression of sRNAs which might enable the pathogen survival by rewiring regulatory circuits.
The role of non-coding RNAs in neuropsychiatric disorders (NPDs) is an emerging field of study. The long non-coding RNAs (lncRNAs) are shown to sponge the microRNAs (miRNAs) from interacting with their target mRNAs. Investigating the sponge activity of lncRNAs in NPDs will provide further insights into biological mechanisms and help identify disease biomarkers. In this study, a large-scale inference of the lncRNA-related miRNA sponge network of pan-neuropsychiatric disorders, including autism spectrum disorder (ASD), schizophrenia (SCZ), and bipolar disorder (BD), was carried out using brain transcriptomic (RNA-Seq) data. The candidate miRNA sponge modules were identified based on the co-expression pattern of non-coding RNAs, sharing of miRNA binding sites, and sensitivity canonical correlation. miRNA sponge modules are associated with chemical synaptic transmission, nervous system development, metabolism, immune system response, ribosomes, and pathways in cancer. The identified modules showed similar and distinct gene expression patterns depending on the neuropsychiatric condition. The preservation of miRNA sponge modules was shown in the independent brain and blood-transcriptomic datasets of NPDs. We also identified miRNA sponging lncRNAs that may be potential diagnostic biomarkers for NPDs. Our study provides a comprehensive resource on miRNA sponging in NPDs.
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