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

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.

Prediction of alternative isoforms from exon expression levels in RNA-Seq experiments.

Alternative splicing, polyadenylation of pre-messenger RNA molecules and differential promoter usage can produce a variety of transcript isoforms whose respective expression levels are regulated in time and space, thus contributing specific biological functions. However, the repertoire of mammalian alternative transcripts and their regulation are still poorly understood. Second-generation sequencing is now opening unprecedented routes to address the analysis of entire transcriptomes. Here, we developed methods that allow the prediction and quantification of alternative isoforms derived solely from exon expression levels in RNA-Seq data. These are based on an explicit statistical model and enable the prediction of alternative isoforms within or between conditions using any known gene annotation, as well as the relative quantification of known transcript structures. Applying these methods to a human RNA-Seq dataset, we validated a significant fraction of the predictions by RT-PCR. Data further showed that these predictions correlated well with information originating from junction reads. A direct comparison with exon arrays indicated improved performances of RNA-Seq over microarrays in the prediction of skipped exons. Altogether, the set of methods presented here comprehensively addresses multiple aspects of alternative isoform analysis. The software is available as an open-source R-package called Solas at http://cmb.molgen.mpg.de/2ndGenerationSequencing/Solas/.

A gene expression map of human chromosome 21 orthologues in the mouse.

The DNA sequence of human chromosome 21 (HSA21) has opened the route for a systematic molecular characterization of all of its genes. Trisomy 21 is associated with Down's syndrome, the most common genetic cause of mental retardation in humans. The phenotype includes various organ dysmorphies, stereotypic craniofacial anomalies and brain malformations. Molecular analysis of congenital aneuploidies poses a particular challenge because the aneuploid region contains many protein-coding genes whose function is unknown. One essential step towards understanding their function is to analyse mRNA expression patterns at key stages of organism development. Seminal works in flies, frogs and mice showed that genes whose expression is restricted spatially and/or temporally are often linked with specific ontogenic processes. Here we describe expression profiles of mouse orthologues to HSA21 genes by a combination of large-scale mRNA in situ hybridization at critical stages of embryonic and brain development and in silico (computed) mining of expressed sequence tags. This chromosome-scale expression annotation associates many of the genes tested with a potential biological role and suggests candidates for the pathogenesis of Down's syndrome.