Project description:Small non-coding RNAs (sncRNAs) are key molecules regulating gene expression. High-throughput RNA-seq greatly advanced sncRNA discovery; however, traditional cDNA library construction protocols generate biased sequencing results, in part due to RNA modifications that interfere with adapter ligation and reverse transcription processes, preventing the detection of sncRNAs bearing these modifications. Here, we present PANDORA-seq (Panoramic RNA Display by Overcoming RNA modification Aborted Sequencing), employing a combination of enzymatic treatments to remove key RNA modifications that block adapter ligation and reverse transcription during cDNA library construction. PANDORA-Seq enables the discovery of thousands of modified sncRNAs previously undetected, mostly tRNA-derived small RNAs (tsRNAs) and rRNA-derived small RNAs (rsRNAs), which are tissue/cell-specifically detected across mouse brain, liver, spleen, sperm, mouse and human embryonic stem cells, and HeLa cells. Moreover, PANDORA-Seq reveals dynamic changes of tsRNAs and rsRNAs during reprogramming of induced pluripotent stem cells (iPSCs), pointing to future investigations on their potential regulatory functions.
Project description:Endometriosis is a common gynecological disease and there is no reliable non-invasive biomarker for its unknown pathogenesis. TsRNA is differentially expressed in a variety of cancers and is a new non-invasive biomarker. The aim of this study was to reveal the full landscape of tsRNA expression profile in endometriosis using PANDORA-seq, which will provide strong target support for early diagnosis and treatment.
Project description:Emerging small noncoding RNAs (sncRNAs), including tRNA-derived small RNAs (tsRNAs) and rRNA-derived small RNAs (rsRNAs), are critical in diverse biological processes, such as neurological diseases. Traditional sncRNA-seq protocols often miss these sncRNAs due to their modifications. We have recently developed PANDORA-seq, a method enabling more comprehensive detection of modified sncRNAs by overcoming the RNA modifications. Using PANDORA-seq, we have revealed an updated sncRNA profile enriched by tsRNAs/rsRNAs in the mouse cortex and found a particularly significant downregulation of mitochondrial tsRNAs and rsRNAs in an Alzheimer's disease (AD) mouse model, compared to genomic tsRNAs and rsRNAs. Moreover, our integrated analysis of cortex gene expression and sncRNA profiles reveals that those downregulated mitochondrial sncRNAs are negatively correlated with enhanced lysosomal activity, suggesting a crucial interplay between mitochondrial RNA dynamics and lysosomal function in AD. Given the versatile tsRNA/tsRNA molecular actions in cellular regulation, our data provides insights for future mechanistic study of AD with potential therapeutic strategies.
Project description:Sperm aging impacts male fertility and offspring health, highlighting the need for reliable aging biomarkers to guide reproductive decisions. Using PANDORA-seq, a novel method to comprehensively profile small non-coding RNAs (sncRNAs), we identified an "aging cliff" in mouse sperm RNA profiles-a sharp age-specific transition marked by significant shifts in genomic and mitochondrial tRNA-derived small RNAs (tsRNAs) and rRNA-derived small RNAs (rsRNAs). Notably, rsRNAs embedded in sperm heads exhibited a transformative length shift, with longer rsRNAs increasing and shorter ones decreasing with age, suggesting altered biogenesis with age. Remarkably, this sperm rsRNA length shift was consistently observed in two independent human aging cohorts, highlighting its evolutionary significance. Moreover, a combination of tsRNAs and rsRNAs (tsRNA/rsRNA cocktails) resembling those in aged sperm induced transcriptomic changes in embryonic stem cells, impacting metabolism and neurodegeneration pathways, mirroring the phenotypes observed in offspring of aged sperm. These results reveal new insights of sperm aging, highlighting the conserved rsRNA length shift in mice and humans, with translational potential for fertility and intergenerational health
Project description:Accurate embryo selection is vital for successful in vitro fertilization (IVF), but current morphological scoring methods are somewhat subjective and do not reflect molecular changes. This study employs ultra-sensitive Pandora sequencing to detect highly modified rsRNAs in culture media, aiming to identify molecular markers for non-invasive embryo quality assessment. Machine learning identified four candidate rsRNAs (5S, 5.8S, 28-1S, 28-2S) associated with embryo quality, with cross-validation demonstrating high predictive accuracy (AUC = 0.955). Quantitative RT-PCR further confirmed that 5.8S and 28-2S levels were significantly higher in the culture media of high-quality embryos. These findings suggest that specific rsRNAs could serve as non-invasive markers for embryo selection, offering new insights into rsRNA functions in embryo development.