We describe an update of MirGeneDB, the manually curated microRNA gene database. Adhering to uniform and consistent criteria for microRNA annotation and nomenclature, we substantially expanded MirGeneDB with 30 additional species representing previously missing metazoan phyla such as sponges, jellyfish, rotifers and flatworms. MirGeneDB 2.1 now consists of 75 species spanning over ∼800 million years of animal evolution, and contains a total number of 16 670 microRNAs from 1549 families. Over 6000 microRNAs were added in this update using ∼550 datasets with ∼7.5 billion sequencing reads. By adding new phylogenetically important species, especially those relevant for the study of whole genome duplication events, and through updating evolutionary nodes of origin for many families and genes, we were able to substantially refine our nomenclature system. All changes are traceable in the specifically developed MirGeneDB version tracker. The performance of read-pages is improved and microRNA expression matrices for all tissues and species are now also downloadable. Altogether, this update represents a significant step toward a complete sampling of all major metazoan phyla, and a widely needed foundation for comparative microRNA genomics and transcriptomics studies. MirGeneDB 2.1 is part of RNAcentral and Elixir Norway, publicly and freely available at http://www.mirgenedb.org/.
Non-coding RNA (ncRNA) molecules have fundamental roles in cells and many are also stable in body fluids as extracellular RNAs. In this study, we used RNA sequencing (RNA-seq) to investigate the profile of small non-coding RNA (sncRNA) in human serum. We analyzed 10 billion Illumina reads from 477 serum samples, included in the Norwegian population-based Janus Serum Bank (JSB). We found that the core serum RNA repertoire includes 258 micro RNAs (miRNA), 441 piwi-interacting RNAs (piRNA), 411 transfer RNAs (tRNA), 24 small nucleolar RNAs (snoRNA), 125 small nuclear RNAs (snRNA) and 123 miscellaneous RNAs (misc-RNA). We also investigated biological and technical variation in expression, and the results suggest that many RNA molecules identified in serum contain signs of biological variation. They are therefore unlikely to be random degradation by-products. In addition, the presence of specific fragments of tRNA, snoRNA, Vault RNA and Y_RNA indicates protection from degradation. Our results suggest that many circulating RNAs in serum can be potential biomarkers.
MotivationThe aim of this study is to assess the performance of RNA–RNA interaction prediction tools for all domains of life.ResultsMinimum free energy (MFE) and alignment methods constitute most of the current RNA interaction prediction algorithms. The MFE tools that include accessibility (i.e. RNAup, IntaRNA and RNAplex) to the final predicted binding energy have better true positive rates (TPRs) with a high positive predictive values (PPVs) in all datasets than other methods. They can also differentiate almost half of the native interactions from background. The algorithms that include effects of internal binding energies to their model and alignment methods seem to have high TPR but relatively low associated PPV compared to accessibility based methods.Availability and ImplementationWe shared our wrapper scripts and datasets at Github (github.com/UCanCompBio/RNA_Interactions_Benchmark). All parameters are documented for personal use.Supplementary information Supplementary data are available at Bioinformatics online.
Noncoding RNAs are integral to a wide range of biological processes, including translation, gene regulation, host-pathogen interactions and environmental sensing. While genomics is now a mature field, our capacity to identify noncoding RNA elements in bacterial and archaeal genomes is hampered by the difficulty of de novo identification. The emergence of new technologies for characterizing transcriptome outputs, notably RNA-seq, are improving noncoding RNA identification and expression quantification. However, a major challenge is to robustly distinguish functional outputs from transcriptional noise. To establish whether annotation of existing transcriptome data has effectively captured all functional outputs, we analysed over 400 publicly available RNA-seq datasets spanning 37 different Archaea and Bacteria. Using comparative tools, we identify close to a thousand highly-expressed candidate noncoding RNAs. However, our analyses reveal that capacity to identify noncoding RNA outputs is strongly dependent on phylogenetic sampling. Surprisingly, and in stark contrast to protein-coding genes, the phylogenetic window for effective use of comparative methods is perversely narrow: aggregating public datasets only produced one phylogenetic cluster where these tools could be used to robustly separate unannotated noncoding RNAs from a null hypothesis of transcriptional noise. Our results show that for the full potential of transcriptomics data to be realized, a change in experimental design is paramount: effective transcriptomics requires phylogeny-aware sampling.
HPV genomic variability and chromosomal integration are important in the HPV-induced carcinogenic process. To uncover these genomic events in an HPV infection, we have developed an innovative and cost-effective sequencing approach named TaME-seq (tagmentation-assisted multiplex PCR enrichment sequencing). TaME-seq combines tagmentation and multiplex PCR enrichment for simultaneous analysis of HPV variation and chromosomal integration, and it can also be adapted to other viruses. For method validation, cell lines (n = 4), plasmids (n = 3), and HPV16, 18, 31, 33 and 45 positive clinical samples (n = 21) were analysed. Our results showed deep HPV genome-wide sequencing coverage. Chromosomal integration breakpoints and large deletions were identified in HPV positive cell lines and in one clinical sample. HPV genomic variability was observed in all samples allowing identification of low frequency variants. In contrast to other approaches, TaME-seq proved to be highly efficient in HPV target enrichment, leading to reduced sequencing costs. Comprehensive studies on HPV intra-host variability generated during a persistent infection will improve our understanding of viral carcinogenesis. Efficient identification of both HPV variability and integration sites will be important for the study of HPV evolution and adaptability and may be an important tool for use in cervical cancer diagnostics.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.