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A high-resolution anatomical atlas of the transcriptome in the mouse embryo.

Graciana Diez-Roux | Sandro Banfi | Marc Sultan | Lars Geffers | Santosh Anand | David Rozado | Alon Magen | Elena Canidio | Massimiliano Pagani | Ivana Peluso | Nathalie Lin-Marq | Muriel Koch | Marchesa Bilio | Immacolata Cantiello | Roberta Verde | Cristian De Masi | Salvatore A Bianchi | Juliette Cicchini | Elodie Perroud | Shprese Mehmeti | Emilie Dagand | Sabine Schrinner | Asja Nürnberger | Katja Schmidt | Katja Metz | Christina Zwingmann | Norbert Brieske | Cindy Springer | Ana Martinez Hernandez | Sarah Herzog | Frauke Grabbe | Cornelia Sieverding | Barbara Fischer | Kathrin Schrader | Maren Brockmeyer | Sarah Dettmer | Christin Helbig | Violaine Alunni | Marie-Annick Battaini | Carole Mura | Charlotte N Henrichsen | Raquel Garcia-Lopez | Diego Echevarria | Eduardo Puelles | Elena Garcia-Calero | Stefan Kruse | Markus Uhr | Christine Kauck | Guangjie Feng | Nestor Milyaev | Chuang Kee Ong | Lalit Kumar | MeiSze Lam | Colin A Semple | Attila Gyenesei | Stefan Mundlos | Uwe Radelof | Hans Lehrach | Paolo Sarmientos | Alexandre Reymond | Duncan R Davidson | Pascal Dollé | Stylianos E Antonarakis | Marie-Laure Yaspo | Salvador Martinez | Richard A Baldock | Gregor Eichele | Andrea Ballabio
PLoS biology | 2011

Ascertaining when and where genes are expressed is of crucial importance to understanding or predicting the physiological role of genes and proteins and how they interact to form the complex networks that underlie organ development and function. It is, therefore, crucial to determine on a genome-wide level, the spatio-temporal gene expression profiles at cellular resolution. This information is provided by colorimetric RNA in situ hybridization that can elucidate expression of genes in their native context and does so at cellular resolution. We generated what is to our knowledge the first genome-wide transcriptome atlas by RNA in situ hybridization of an entire mammalian organism, the developing mouse at embryonic day 14.5. This digital transcriptome atlas, the Eurexpress atlas (http://www.eurexpress.org), consists of a searchable database of annotated images that can be interactively viewed. We generated anatomy-based expression profiles for over 18,000 coding genes and over 400 microRNAs. We identified 1,002 tissue-specific genes that are a source of novel tissue-specific markers for 37 different anatomical structures. The quality and the resolution of the data revealed novel molecular domains for several developing structures, such as the telencephalon, a novel organization for the hypothalamus, and insight on the Wnt network involved in renal epithelial differentiation during kidney development. The digital transcriptome atlas is a powerful resource to determine co-expression of genes, to identify cell populations and lineages, and to identify functional associations between genes relevant to development and disease.

Pubmed ID: 21267068 RIS Download

Research resources used in this publication

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Antibodies used in this publication

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Associated grants

  • Agency: Medical Research Council, United Kingdom
    Id: MC_U127527203
  • Agency: Telethon, Italy
    Id: TGM11S03

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This is a list of tools and resources that we have found mentioned in this publication.


GenitoUrinary Development Molecular Anatomy Project (tool)

RRID:SCR_001554

Project aggregates and provides experimental gene expression data from genito-urinary system. International consortium providing molecular atlas of gene expression for developing organs of GenitoUrinary (GU) tract. Mouse strains to facilitate developmental and functional studies within GU system. Experimental protocols and standard specifications. Tutorials describing GU organogenesis and primary data via database. Data are from large-scale in situ hybridization screens (wholemount and section) and microarray gene expression data of microdissected, laser-captured and FACS-sorted components of developing mouse genitourinary (GU) system.

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TM4 Microarray Software Suite - TIGR MultiExperiment Viewer (tool)

RRID:SCR_001915

A desktop application for the analysis, visualization and data-mining of large-scale genomic data. It is a versatile microarray tool, incorporating sophisticated algorithms for clustering, visualization, classification, statistical analysis and biological theme discovery. MeV generates informative and interrelated displays of expression and annotation data from single or multiple experiments. A huge array of alrogithms are included in MeV modules, and are available at a button-click, such as K-means clustering, Hierarchical clustering, t-Tests, Significance Analysis of Microarrays, Gene Set Enrichment Analysis, and EASE. Extensive documentation is available for helping new users get started with MeV. A Quickstart Guide provides the tutorial a brand new person will need to get their first dataset loaded and displayed in the program. Returning MEV users will want to check out the release notes to see what new features are available in the latest versions of the program. Tutorials have been written about several of its more involved features.

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InterPro (tool)

RRID:SCR_006695

Service providing functional analysis of proteins by classifying them into families and predicting domains and important sites. They combine protein signatures from a number of member databases into a single searchable resource, capitalizing on their individual strengths to produce a powerful integrated database and diagnostic tool. This integrated database of predictive protein signatures is used for the classification and automatic annotation of proteins and genomes. InterPro classifies sequences at superfamily, family and subfamily levels, predicting the occurrence of functional domains, repeats and important sites. InterPro adds in-depth annotation, including GO terms, to the protein signatures. You can access the data programmatically, via Web Services. The member databases use a number of approaches: # ProDom: provider of sequence-clusters built from UniProtKB using PSI-BLAST. # PROSITE patterns: provider of simple regular expressions. # PROSITE and HAMAP profiles: provide sequence matrices. # PRINTS provider of fingerprints, which are groups of aligned, un-weighted Position Specific Sequence Matrices (PSSMs). # PANTHER, PIRSF, Pfam, SMART, TIGRFAMs, Gene3D and SUPERFAMILY: are providers of hidden Markov models (HMMs). Your contributions are welcome. You are encouraged to use the ''''Add your annotation'''' button on InterPro entry pages to suggest updated or improved annotation for individual InterPro entries.

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Entrez Gene (tool)

RRID:SCR_002473

Database for genomes that have been completely sequenced, have active research community to contribute gene-specific information, or that are scheduled for intense sequence analysis. Includes nomenclature, map location, gene products and their attributes, markers, phenotypes, and links to citations, sequences, variation details, maps, expression, homologs, protein domains and external databases. All entries follow NCBI's format for data collections. Content of Entrez Gene represents result of curation and automated integration of data from NCBI's Reference Sequence project (RefSeq), from collaborating model organism databases, and from many other databases available from NCBI. Records are assigned unique, stable and tracked integers as identifiers. Content is updated as new information becomes available.

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