EMPIAR: the Electron Microscopy Public Image Archive.

Public archiving in structural biology is well established with the Protein Data Bank (PDB; wwPDB.org) catering for atomic models and the Electron Microscopy Data Bank (EMDB; emdb-empiar.org) for 3D reconstructions from cryo-EM experiments. Even before the recent rapid growth in cryo-EM, there was an expressed community need for a public archive of image data from cryo-EM experiments for validation, software development, testing and training. Concomitantly, the proliferation of 3D imaging techniques for cells, tissues and organisms using volume EM (vEM) and X-ray tomography (XT) led to calls from these communities to publicly archive such data as well. EMPIAR (empiar.org) was developed as a public archive for raw cryo-EM image data and for 3D reconstructions from vEM and XT experiments and now comprises over a thousand entries totalling over 2 petabytes of data. EMPIAR resources include a deposition system, entry pages, facilities to search, visualize and download datasets, and a REST API for programmatic access to entry metadata. The success of EMPIAR also poses significant challenges for the future in dealing with the very fast growth in the volume of data and in enhancing its reusability.

Ten recommendations for organising bioimaging data for archival.

Organised data is easy to use but the rapid developments in the field of bioimaging, with improvements in instrumentation, detectors, software and experimental techniques, have resulted in an explosion of the volumes of data being generated, making well-organised data an elusive goal. This guide offers a handful of recommendations for bioimage depositors, analysts and microscope and software developers, whose implementation would contribute towards better organised data in preparation for archival. Based on our experience archiving large image datasets in EMPIAR, the BioImage Archive and BioStudies, we propose a number of strategies that we believe would improve the usability (clarity, orderliness, learnability, navigability, self-documentation, coherence and consistency of identifiers, accessibility, succinctness) of future data depositions more useful to the bioimaging community (data authors and analysts, researchers, clinicians, funders, collaborators, industry partners, hardware/software producers, journals, archive developers as well as interested but non-specialist users of bioimaging data). The recommendations that may also find use in other data-intensive disciplines. To facilitate the process of analysing data organisation, we present bandbox, a Python package that provides users with an assessment of their data by flagging potential issues, such as redundant directories or invalid characters in file or folder names, that should be addressed before archival. We offer these recommendations as a starting point and hope to engender more substantial conversations across and between the various data-rich communities.

EMDB Web Resources.

The Electron Microscopy Data Bank (EMDB; http://emdb-empiar.org) is a global openly-accessible archive of biomolecular and cellular 3D reconstructions derived from electron microscopy (EM) data. EMBL-EBI develops web-based resources to facilitate the reuse of EMDB data. Here we provide protocols for how these resources can be used for searching EMDB, visualising EMDB structures, statistically analysing EMDB content and checking the validity of EMDB structures. Protocols for searching include quick link categories from the main page, links to latest entries released during the weekly cycle, filtered browsing of the entire archive and a form-based search. For visualisation, the 'Volume Slicer' enables slices of EMDB entries to be visualised interactively and in three orthogonal directions. The EMstats web service (https://emdb-empiar.org/emstats) provides up-to-date interactive statistical charts analysing EMDB. All EMDB entries have 'visual analysis' pages that provide basic validation information for the entry.

Building bridges between cellular and molecular structural biology.

The integration of cellular and molecular structural data is key to understanding the function of macromolecular assemblies and complexes in their in vivo context. Here we report on the outcomes of a workshop that discussed how to integrate structural data from a range of public archives. The workshop identified two main priorities: the development of tools and file formats to support segmentation (that is, the decomposition of a three-dimensional volume into regions that can be associated with defined objects), and the development of tools to support the annotation of biological structures.

PDBe: improved accessibility of macromolecular structure data from PDB and EMDB.

The Protein Data Bank in Europe (http://pdbe.org) accepts and annotates depositions of macromolecular structure data in the PDB and EMDB archives and enriches, integrates and disseminates structural information in a variety of ways. The PDBe website has been redesigned based on an analysis of user requirements, and now offers intuitive access to improved and value-added macromolecular structure information. Unique value-added information includes lists of reviews and research articles that cite or mention PDB entries as well as access to figures and legends from full-text open-access publications that describe PDB entries. A powerful new query system not only shows all the PDB entries that match a given query, but also shows the 'best structures' for a given macromolecule, ligand complex or sequence family using data-quality information from the wwPDB validation reports. A PDBe RESTful API has been developed to provide unified access to macromolecular structure data available in the PDB and EMDB archives as well as value-added annotations, e.g. regarding structure quality and up-to-date cross-reference information from the SIFTS resource. Taken together, these new developments facilitate unified access to macromolecular structure data in an intuitive way for non-expert users and support expert users in analysing macromolecular structure data.

Seq-ing improved gene expression estimates from microarrays using machine learning.

BACKGROUND: Quantifying gene expression by RNA-Seq has several advantages over microarrays, including greater dynamic range and gene expression estimates on an absolute, rather than a relative scale. Nevertheless, microarrays remain in widespread use, demonstrated by the ever-growing numbers of samples deposited in public repositories. RESULTS: We propose a novel approach to microarray analysis that attains many of the advantages of RNA-Seq. This method, called Machine Learning of Transcript Expression (MaLTE), leverages samples for which both microarray and RNA-Seq data are available, using a Random Forest to learn the relationship between the fluorescence intensity of sets of microarray probes and RNA-Seq transcript expression estimates. We trained MaLTE on data from the Genotype-Tissue Expression (GTEx) project, consisting of Affymetrix gene arrays and RNA-Seq from over 700 samples across a broad range of human tissues. CONCLUSION: This approach can be used to accurately estimate absolute expression levels from microarray data, at both gene and transcript level, which has not previously been possible. This methodology will facilitate re-analysis of archived microarray data and broaden the utility of the vast quantities of data still being generated.

A mutation in a splicing factor that causes retinitis pigmentosa has a transcriptome-wide effect on mRNA splicing.

BACKGROUND: Substantial progress has been made in the identification of sequence elements that control mRNA splicing and the genetic variants in these elements that alter mRNA splicing (referred to as splicing quantitative trait loci - sQTLs). Genetic variants that affect mRNA splicing in trans are harder to identify because their effects can be more subtle and diffuse, and the variants are not co-located with their targets. We carried out a transcriptome-wide analysis of the effects of a mutation in a ubiquitous splicing factor that causes retinitis pigmentosa (RP) on mRNA splicing, using exon microarrays. RESULTS: Exon microarray data was generated from whole blood samples obtained from four individuals with a mutation in the splicing factor PRPF8 and four sibling controls. Although the mutation has no known phenotype in blood, there was evidence of widespread differences in splicing between cases and controls (affecting approximately 20% of exons). Most probesets with significantly different inclusion (defined as the expression intensity of the exon divided by the expression of the corresponding transcript) between cases and controls had higher inclusion in cases and corresponded to exons that were shorter than average, AT rich, located towards the 5' end of the gene and flanked by long introns. Introns flanking affected probesets were particularly depleted for the shortest category of introns, associated with splicing via intron definition. CONCLUSIONS: Our results show that a mutation in a splicing factor, with a phenotype that is restricted to retinal tissue, acts as a trans-sQTL cluster in whole blood samples. Characteristics of the affected exons suggest that they are spliced co-transcriptionally and via exon definition. However, due to the small sample size available for this study, further studies are required to confirm the widespread impact of this PRPF8 mutation on mRNA splicing outside the retina.

Inference of allele-specific expression from RNA-seq data.

The differential abundance of transcripts from alternative alleles of a gene, for example in a hybrid plant or an outbred natural population, can provide information about the nature of interindividual or interstrain variation in gene expression. Allele-specific expression (ASE) can result from epigenetic phenomena, such as imprinting (when the overexpressed allele is inherited consistently from one parent) or allele-specific chromatin modifications. Alternatively, DNA sequence variants in the promoter or within the transcribed region of a gene can affect the rate of transcription or the rate of decay of the transcript, respectively. The existence of this allelic variation and the insights it provides into the nature of the gene regulation are of significant interest. With the recent widespread availability of sequencing based transcriptomics, the power to detect ASE has increased; however, inference of ASE from transcriptome sequencing data is subject to several caveats and potential biases and the results need to be interpreted with care.

Evidence for intron length conservation in a set of mammalian genes associated with embryonic development.

BACKGROUND: We carried out an analysis of intron length conservation across a diverse group of nineteen mammalian species. Motivated by recent research suggesting a role for time delays associated with intron transcription in gene expression oscillations required for early embryonic patterning, we searched for examples of genes that showed the most extreme conservation of total intron content in mammals. RESULTS: Gene sets annotated as being involved in pattern specification in the early embryo or containing the homeobox DNA-binding domain, were significantly enriched among genes with highly conserved intron content. We used ancestral sequences reconstructed with probabilistic models that account for insertion and deletion mutations to distinguish insertion and deletion events on lineages leading to human and mouse from their last common ancestor. Using a randomization procedure, we show that genes containing the homeobox domain show less change in intron content than expected, given the number of insertion and deletion events within their introns. CONCLUSIONS: Our results suggest selection for gene expression precision or the existence of additional development-associated genes for which transcriptional delay is functionally significant.