There is an urgent need to improve the infrastructure supporting the reuse of scholarly data. A diverse set of stakeholders—representing academia, industry, funding agencies, and scholarly publishers—have come together to design and jointly endorse a concise and measureable set of principles that we refer to as the FAIR Data Principles. The intent is that these may act as a guideline for those wishing to enhance the reusability of their data holdings. Distinct from peer initiatives that focus on the human scholar, the FAIR Principles put specific emphasis on enhancing the ability of machines to automatically find and use the data, in addition to supporting its reuse by individuals. This Comment is the first formal publication of the FAIR Principles, and includes the rationale behind them, and some exemplar implementations in the community.
Summary
Genome sequencing projects are discovering millions of genetic variants in humans, and interpretation of their functional effects is essential for understanding the genetic basis of variation in human traits. Here we report sequencing and deep analysis of mRNA and miRNA from lymphoblastoid cell lines of 462 individuals from the 1000 Genomes Project – the first uniformly processed RNA-seq data from multiple human populations with high-quality genome sequences. We discovered extremely widespread genetic variation affecting regulation of the majority of genes, with transcript structure and expression level variation being equally common but genetically largely independent. Our characterization of causal regulatory variation sheds light on cellular mechanisms of regulatory and loss-of-function variation, and allowed us to infer putative causal variants for dozens of disease-associated loci. Altogether, this study provides a deep understanding of the cellular mechanisms of transcriptome variation and of the landscape of functional variants in the human genome.
The FANTOM5 project investigates transcription initiation activities in more than 1,000 human and mouse primary cells, cell lines and tissues using CAGE. Based on manual curation of sample information and development of an ontology for sample classification, we assemble the resulting data into a centralized data resource (http://fantom.gsc.riken.jp/5/). This resource contains web-based tools and data-access points for the research community to search and extract data related to samples, genes, promoter activities, transcription factors and enhancers across the FANTOM5 atlas.Electronic supplementary materialThe online version of this article (doi:10.1186/s13059-014-0560-6) contains supplementary material, which is available to authorized users.
Cells release RNA-carrying vesicles and membrane-free RNA/protein complexes into the extracellular milieu. Horizontal vesicle-mediated transfer of such shuttle RNA between cells allows dissemination of genetically encoded messages, which may modify the function of target cells. Other studies used array analysis to establish the presence of microRNAs and mRNA in cell-derived vesicles from many sources. Here, we used an unbiased approach by deep sequencing of small RNA released by immune cells. We found a large variety of small non-coding RNA species representing pervasive transcripts or RNA cleavage products overlapping with protein coding regions, repeat sequences or structural RNAs. Many of these RNAs were enriched relative to cellular RNA, indicating that cells destine specific RNAs for extracellular release. Among the most abundant small RNAs in shuttle RNA were sequences derived from vault RNA, Y-RNA and specific tRNAs. Many of the highly abundant small non-coding transcripts in shuttle RNA are evolutionary well-conserved and have previously been associated to gene regulatory functions. These findings allude to a wider range of biological effects that could be mediated by shuttle RNA than previously expected. Moreover, the data present leads for unraveling how cells modify the function of other cells via transfer of specific non-coding RNA species.
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