A high-resolution mRNA expression time course of embryonic development in zebrafish.

We have produced an mRNA expression time course of zebrafish development across 18 time points from 1 cell to 5 days post-fertilisation sampling individual and pools of embryos. Using poly(A) pulldown stranded RNA-seq and a 3' end transcript counting method we characterise temporal expression profiles of 23,642 genes. We identify temporal and functional transcript co-variance that associates 5024 unnamed genes with distinct developmental time points. Specifically, a class of over 100 previously uncharacterised zinc finger domain containing genes, located on the long arm of chromosome 4, is expressed in a sharp peak during zygotic genome activation. In addition, the data reveal new genes and transcripts, differential use of exons and previously unidentified 3' ends across development, new primary microRNAs and temporal divergence of gene paralogues generated in the teleost genome duplication. To make this dataset a useful baseline reference, the data can be browsed and downloaded at Expression Atlas and Ensembl

A proteomics sample metadata representation for multiomics integration and big data analysis

The amount of public proteomics data is rapidly increasing but there is no standardized format to describe the sample metadata and their relationship with the dataset files in a way that fully supports their understanding or reanalysis. Here we propose to develop the transcriptomics data format MAGE-TAB into a standard representation for proteomics sample metadata. We implement MAGE-TAB-Proteomics in a crowdsourcing project to manually curate over 200 public datasets. We also describe tools and libraries to validate and submit sample metadata-related information to the PRIDE repository. We expect that these developments will improve the reproducibility and facilitate the reanalysis and integration of public proteomics datasets.publishedVersio

Expression Atlas update: from tissues to single cells.

Expression Atlas is EMBL-EBI's resource for gene and protein expression. It sources and compiles data on the abundance and localisation of RNA and proteins in various biological systems and contexts and provides open access to this data for the research community. With the increased availability of single cell RNA-Seq datasets in the public archives, we have now extended Expression Atlas with a new added-value service to display gene expression in single cells. Single Cell Expression Atlas was launched in 2018 and currently includes 123 single cell RNA-Seq studies from 12 species. The website can be searched by genes within or across species to reveal experiments, tissues and cell types where this gene is expressed or under which conditions it is a marker gene. Within each study, cells can be visualized using a pre-calculated t-SNE plot and can be coloured by different features or by cell clusters based on gene expression. Within each experiment, there are links to downloadable files, such as RNA quantification matrices, clustering results, reports on protocols and associated metadata, such as assigned cell types

A user guide for the online exploration and visualization of PCAWG data.

Funder: U.S. Department of Health & Human Services | NIH | National Cancer Institute (NCI)Funder: Ontario Institute for Cancer Research (Institut Ontarien de Recherche sur le Cancer); doi: https://doi.org/10.13039/100012118Funder: EMBL Member States EU FP7 Programme projects EurocanPlatform (260791) CAGEKID (241669)Funder: European Union’s Framework Programme For Research and Innovation Horizon 2020 under the Marie Sklodowska-Curie grant agreement no. 703543Funder: Michael & Susan Dell Foundation; Mary K. Chapman Foundation; CCSG Grant P30 CA016672 (Bioinformatics Shared Resource); ITCR U24 CA199461; GDAN U24 CA210949; GDAN U24 CA210950Funder: European Commission's H2020 Programme, project SOUND, Grant Agreement no 633974Funder: Spanish Government (SEV 2015-0493) BSC-Lenovo Master Collaboration Agreement (2015)The Pan-Cancer Analysis of Whole Genomes (PCAWG) project generated a vast amount of whole-genome cancer sequencing resource data. Here, as part of the ICGC/TCGA Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium, which aggregated whole genome sequencing data from 2658 cancers across 38 tumor types, we provide a user's guide to the five publicly available online data exploration and visualization tools introduced in the PCAWG marker paper. These tools are ICGC Data Portal, UCSC Xena, Chromothripsis Explorer, Expression Atlas, and PCAWG-Scout. We detail use cases and analyses for each tool, show how they incorporate outside resources from the larger genomics ecosystem, and demonstrate how the tools can be used together to understand the biology of cancers more deeply. Together, the tools enable researchers to query the complex genomic PCAWG data dynamically and integrate external information, enabling and enhancing interpretation

Common and distinct transcriptional signatures of mammalian embryonic lethality

Abstract: The Deciphering the Mechanisms of Developmental Disorders programme has analysed the morphological and molecular phenotypes of embryonic and perinatal lethal mouse mutant lines in order to investigate the causes of embryonic lethality. Here we show that individual whole-embryo RNA-seq of 73 mouse mutant lines (>1000 transcriptomes) identifies transcriptional events underlying embryonic lethality and associates previously uncharacterised genes with specific pathways and tissues. For example, our data suggest that Hmgxb3 is involved in DNA-damage repair and cell-cycle regulation. Further, we separate embryonic delay signatures from mutant line-specific transcriptional changes by developing a baseline mRNA expression catalogue of wild-type mice during early embryogenesis (4–36 somites). Analysis of transcription outside coding sequence identifies deregulation of repetitive elements in Morc2a mutants and a gene involved in gene-specific splicing. Collectively, this work provides a large scale resource to further our understanding of early embryonic developmental disorders

A proteomics sample metadata representation for multiomics integration and big data analysis

The amount of public proteomics data is rapidly increasing but there is no standardized format to describe the sample metadata and their relationship with the dataset files in a way that fully supports their understanding or reanalysis. Here we propose to develop the transcriptomics data format MAGE-TAB into a standard representation for proteomics sample metadata. We implement MAGE-TAB-Proteomics in a crowdsourcing project to manually curate over 200 public datasets. We also describe tools and libraries to validate and submit sample metadata-related information to the PRIDE repository. We expect that these developments will improve the reproducibility and facilitate the reanalysis and integration of public proteomics datasets

Dynamics of Lgr6⁺ progenitor populations in skin

The dynamics and interactions between stem cell pools in the hair follicle (HF), sebaceous gland (SG), and interfollicular epidermis (IFE) of murine skin are still poorly understood. In this study, we used multicolor lineage tracing to mark Lgr6-expressing basal cells in the HF isthmus, SG, and IFE. We show that these Lgr6⁺ cells constitute long-term self-renewing populations within each compartment in adult skin. Quantitative analysis of clonal dynamics revealed that the Lgr6⁺ progenitor cells compete neutrally in the IFE, isthmus, and SG, indicating population asymmetry as the underlying mode of tissue renewal. Transcriptional profiling of Lgr6⁺and Lgr6⁻ cells did not reveal a distinct Lgr6-associated gene expression signature, raising the question of whether Lgr6 expression requires extrinsic niche signals. Our results elucidate the interrelation and behavior of Lgr6⁺ populations in the IFE, HF, and SG and suggest population asymmetry as a common mechanism for homeostasis in several epithelial skin compartments.We thank Åsa Bergström for technical help and assistance with mouse strains, Viljar Jaks for his help with FACS analysis, and Anna Johnsson and Peter Lönnerberg for conducting RNA-seq. This work was supported by grants from the Swedish Cancer Society, Swedish Research Council, H&G Jeanssons Foundation, Swedish Foundation for Strategic Research and Ragnar Söderberg Foundation (to M.K.), the Swedish Cancer Society, Swedish Research Council (to R.T.), the European Molecular Biology Organization (to A.H.), the Swedish Research Council (STARGET to M.K. and S.L.), and the Wellcome Trust (grant number 098357/Z/12/Z to B.D.S.). A.F. was supported by the EU FP7 ITN Healing Network. Parts of this study were performed at the (1) Live Cell Imaging unit, Department of Biosciences and Nutrition, Karolinska Institutet, Sweden, supported by grants from the Knut and Alice Wallenberg Foundation, the Swedish Research Council, the Center for Innovative Medicine and the Jonasson donation to the School of Technology and Health, Royal Institute of Technology, Sweden, and (2) Wallenberg Institute for Regenerative Medicine Flow Cytometry Facility financed by Knut and Alice Wallenberg Foundation, Karolinska Institutet, Huddinge, Sweden.This is the final version of the article. It was first available from Elsevier via http://dx.doi.org/10.1016/j.stemcr.2015.09.01

Dynamics of Lgr6⁺ progenitor populations in skin

The dynamics and interactions between stem cell pools in the hair follicle (HF), sebaceous gland (SG), and interfollicular epidermis (IFE) of murine skin are still poorly understood. In this study, we used multicolor lineage tracing to mark Lgr6⁺ -expressing basal cells in the HF isthmus, SG, and IFE.We show that these Lgr6⁺ cells constitute long-term self-renewing populations within each compartment in adult skin. Quantitative analysis of clonal dynamics revealed that the Lgr6⁺ progenitor cells compete neutrally in the IFE, isthmus, and SG, indicating population asymmetry as the underlying mode of tissue renewal. Transcriptional profiling of Lgr6⁺ and Lgr6⁺ cells did not reveal a distinct Lgr6⁺ -associated gene expression signature, raising the question of whether Lgr6⁺ expression requires extrinsic niche signals. Our results elucidate the interrelation and behavior of Lgr6⁺ populations in the IFE, HF, and SG and suggest population asymmetry as a common mechanism for homeostasis in several epithelial skin compartments.We thank Åsa Bergström for technical help and assistance with mouse strains, Viljar Jaks for his help with FACS analysis, and Anna Johnsson and Peter Lönnerberg for conducting RNA-seq. This work was supported by grants from the Swedish Cancer Society, Swedish Research Council, H&G Jeanssons Foundation, Swedish Foundation for Strategic Research and Ragnar Söderberg Foundation (to M.K.), the Swedish Cancer Society, Swedish Research Council (to R.T.), the European Molecular Biology Organization (to A.H.), the Swedish Research Council (STARGET to M.K. and S.L.), and the Wellcome Trust (grant number 098357/Z/12/Z to B.D.S.). A.F. was supported by the EU FP7 ITN Healing Network. Parts of this study were performed at the (1) Live Cell Imaging unit, Department of Biosciences and Nutrition, Karolinska Institutet, Sweden, supported by grants from the Knut and Alice Wallenberg Foundation, the Swedish Research Council, the Center for Innovative Medicine and the Jonasson donation to the School of Technology and Health, Royal Institute of Technology, Sweden, and (2) Wallenberg Institute for Regenerative Medicine Flow Cytometry Facility financed by Knut and Alice Wallenberg Foundation, Karolinska Institutet, Huddinge, Sweden.This is the final version of the article. It was first available from Elsevier via http://dx.doi.org/10.1016/j.stemcr.2015.09.01