Similar Datasets
Project description:Population Architecture using Genomics and Epidemiology, summary data (PAGE-summary)
| PRJNA168052 | ENA
Project description:Population Architecture using Genomics and Epidemiology, summary data (PAGE-summary)
| PRJNA168051 | ENA
Project description:Gene expression estimates detected by RNA-sequencing technology vary with the updates of reference genome and gene annotation, which might confound existing expression-based prognostic signatures, making them inapplicable to clinical practice. In this study, we proposed a method to decrease these effects and developed a qualitative signature for stage I lung adenocarcinoma, whose classification was based on within-sample relative expression orderings (REOs) of gene pairs. The signature was validated in 471 stage I samples derived from public RNA-sequencing and microarray data (both log-rank p < 0.001). Notably, our signature could effectively predict prognosis for 30 stage I patients with severely degraded FFPE tissues (log-rank p = 0.0177). More important, the risk classification was stable in the latest annotation. In summary, our signature would be a promising signature for clinical individualized application because of its excellent prognostic performance and classification robustness.
2020-01-13 | GSE143486 | GEO
Project description:DNA methylation has recently emerged as a powerful regulatory mechanism controlling the expression of key regulators of various developmental processes, including nodulation. However, the functional role of DNA methylation in regulating the expression of microRNA (miRNA) genes during the formation and development of nitrogen-fixing nodules remains largely unknown. In this study, we profiled DNA methylation patterns of miRNA genes during nodule formation, development, and early senescence stages in soybean (Glycine max) through the analysis of methylC-seq data. Absolute DNA methylation levels in the CG, CHH, and CHH sequence contexts over the promoter and primary transcript regions of miRNA genes were significantly higher in the nodules compared with the corresponding root tissues at these three distinct nodule developmental stages. We identified a total of 82 differentially methylated miRNAs in the nodules compared with roots. Differential DNA methylation of these 82 miRNAs was detected only in the promoter (69), primary transcript region (3), and both in the promoter and primary transcript regions (10). The large majority of these differentially methylated miRNAs were hypermethylated in nodules compared with the corresponding root tissues and were found mainly in the CHH context and showed stage-specific methylation patterns. Differentially methylated regions in the promoters of 25 miRNAs overlapped with transposable elements, a finding that may explain the vulnerability of miRNAs to DNA methylation changes during nodule development. Gene expression analysis of a set of promoter-differentially methylated miRNAs pointed to a negative association between DNA methylation and miRNA expression. Gene Ontology and pathways analyses indicate that changes in DNA methylation of miRNA genes are reprogrammed and contribute to nodule development through indirect regulation of genes involved in cellular processes and pathways with well-established roles in nodulation.
| S-EPMC8076613 | biostudies-literature