Project description:Despite the widespread adoption of ChIP-seq there is still no consensus on quality assessment metrics. No single published metric can reliably discriminate the success or failure of an experiment, thus hampering objectivity and reproducibility of quality control. We introduce a new framework for ChIP-seq data quality assessment that overcomes the limitation of previous solutions. Our tool called "ChIC" incorporates a novel set of quality control metrics integrated into one single score summarizing the sample quality and a reference compendium with thousands of published ChIP-seq samples, for easier evaluation of new data. This test dataset contain an example of succesfull and non-succesfull ChIP-seq sample for mouse H3K27me3.
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.
Project description:We investigated differentially expressed sncRNAs in human sperm as candidate markers for evaluating sperm quality during IVF. We demonstrated that differentially expressed tsRNAs, rsRNAs and miRNAs are linked to sperm quality according to embryo quality, even though these sperm samples were all considered normal by the traditional semen-parameter assessment. Therefore, the sncRNAs, especially tsRNAs and rsRNAs, may be potential clinical biomarkers for the assessment of sperm quality in IVF.
Project description:The objective was to identify functional genes encoded by Fungi and fungal-like organisms to assess putative ecological roles Using the GeoChip microarray, we detected fungal genes involved in the complete assimilation of nitrate and the degradation of lignin, as well as evidence for Partitiviridae (a mycovirus) that likely regulates fungal populations in the marine environment. These results demonstrate the potential for fungi to degrade terrigenously-sourced molecules, such as permafrost and compete with algae for nitrate during blooms. Ultimately, these data suggest that marine fungi could be as important in oceanic ecosystems as they are in freshwater environments.
