Regulated transcription controls the diversity, developmental pathways and spatial organization of the hundreds of cell types that make up a mammal. Using single-molecule cDNA sequencing, we mapped transcription start sites (TSSs) and their usage in human and mouse primary cells, cell lines and tissues to produce a comprehensive overview of mammalian gene expression across the human body. We find that few genes are truly ‘housekeeping’, whereas many mammalian promoters are composite entities composed of several closely separated TSSs, with independent cell-type-specific expression profiles. TSSs specific to different cell types evolve at different rates, whereas promoters of broadly expressed genes are the most conserved. Promoter-based expression analysis reveals key transcription factors defining cell states and links them to binding-site motifs. The functions of identified novel transcripts can be predicted by coexpression and sample ontology enrichment analyses. The functional annotation of the mammalian genome 5 (FANTOM5) project provides comprehensive expression profiles and functional annotation of mammalian cell-type-specific transcriptomes with wide applications in biomedical research.

Mammalian promoters can be separated into two classes, conserved TATA box-enriched promoters, which initiate at a well-defined site, and more plastic, broad and evolvable CpG-rich promoters. We have sequenced tags corresponding to several hundred thousand transcription start sites (TSSs) in the mouse and human genomes, allowing precise analysis of the sequence architecture and evolution of distinct promoter classes. Different tissues and families of genes differentially use distinct types of promoters. Our tagging methods allow quantitative analysis of promoter usage in different tissues and show that differentially regulated alternative TSSs are a common feature in protein-coding genes and commonly generate alternative N termini. Among the TSSs, we identified new start sites associated with the majority of exons and with 3' UTRs. These data permit genome-scale identification of tissue-specific promoters and analysis of the cis-acting elements associated with them.

This study describes comprehensive polling of transcription start and termination sites and analysis of previously unidentified full-length complementary DNAs derived from the mouse genome. We identify the 5' and 3' boundaries of 181,047 transcripts with extensive variation in transcripts arising from alternative promoter usage, splicing, and polyadenylation. There are 16,247 new mouse protein-coding transcripts, including 5154 encoding previously unidentified proteins. Genomic mapping of the transcriptome reveals transcriptional forests, with overlapping transcription on both strands, separated by deserts in which few transcripts are observed. The data provide a comprehensive platform for the comparative analysis of mammalian transcriptional regulation in differentiation and development.

Antisense transcription (transcription from the opposite strand to a protein-coding or sense strand) has been ascribed roles in gene regulation involving degradation of the corresponding sense transcripts (RNA interference), as well as gene silencing at the chromatin level. Global transcriptome analysis provides evidence that a large proportion of the genome can produce transcripts from both strands, and that antisense transcripts commonly link neighboring "genes" in complex loci into chains of linked transcriptional units. Expression profiling reveals frequent concordant regulation of sense/antisense pairs. We present experimental evidence that perturbation of an antisense RNA can alter the expression of sense messenger RNAs, suggesting that antisense transcription contributes to control of transcriptional outputs in mammals.

SUMMARY Combinatorial interactions among transcription factors are critical to directing tissue-specific gene expression. To build a global atlas of these combinations, we have screened for physical interactions among the majority of human and mouse DNA-binding transcription factors (TFs). The complete networks contain 762 human and 877 mouse interactions. Analysis of the networks reveals that highly connected TFs are broadly expressed across tissues, and that roughly half of the measured interactions are conserved between mouse and human. The data highlight the importance of TF combinations for determining cell fate, and they lead to the identification of a SMAD3/FLI1 complex expressed during development of immunity. The availability of large TF combinatorial networks in both human and mouse will provide many opportunities to study gene regulation, tissue differentiation, and mammalian evolution.

We introduce cap analysis gene expression (CAGE), which is based on preparation and sequencing of concatamers of DNA tags deriving from the initial 20 nucleotides from 5 end mRNAs. CAGE allows high-throughout gene expression analysis and the profiling of transcriptional start points (TSP), including promoter usage analysis. By analyzing four libraries (brain, cortex, hippocampus, and cerebellum), we redefined more accurately the TSPs of 11-27% of the analyzed transcriptional units that were hit. The frequency of CAGE tags correlates well with results from other analyses, such as serial analysis of gene expression, and furthermore maps the TSPs more accurately, including in tissue-specific cases. The highthroughput nature of this technology paves the way for understanding gene networks via correlation of promoter usage and gene transcriptional factor expression.full-length cDNA ͉ transcriptome ͉ sequencing ͉ cap-trapping E ven the comparison of mammalian genome draft sequences (1) has left many unanswered questions with regard to the exact identification of expressed genes, their promoter elements, and the network of promoter͞transcriptional factor usage that underlies gene expression. Partial identification of the promoter sites has been provided by gene discovery programs based on the sequencing of full-length cDNA libraries (2-4); these have been instrumental in identifying the sequence of promoter regions, including potentially different promoters (5). Several thousand promoters can be determined by sequencing 5Ј ends from full-length cDNA libraries and mapping the sequences to the genome, thus determining which correspond to coding and regulatory regions, respectively. These analyses can produce statistics on transcriptional start sites derived from large numbers of 5Ј end sequences. However, these methods lack the throughput to provide significantly abundant data for intermediately͞lowly expressed genes, chiefly because the comprehensive sequencing of cDNA libraries is prohibitively expensive. On the other hand, microarrays for high-throughput tissue expression analysis do exist (6), but these cannot determine transcription starting points and therefore cannot be used to accurately identify the cis regulatory elements that will be essential for computing gene networks. Another limitation of microarrays is that the only genes͞transcripts that can be studied are those that have already been identified by the sequencing, which is far from completion (2). Serial analysis of gene expression (SAGE) allows partial sequence information of short tags at the 3Ј ends of mRNAs (7) to be obtained. Although the information is partial, it is amenable to relatively cheap high-throughput digital data collection, because it is based on the cloning and subsequent sequencing of concatamers of short DNA fragments derived from 3Ј ends of multiple mRNAs (http:͞͞cgap.nci.nih.gov͞ SAGE). This method was further improved on by Long-SAGE, which allows for the cloning of 20-nt SAGE tags (8), which mainly identify single loci on the ge...

Recent large-scale analyses of mainly full-length cDNA libraries generated from a variety of mouse tissues indicated that almost half of all representative cloned sequences did not contain an apparent protein-coding sequence, and were putatively derived from non-protein-coding RNA (ncRNA) genes. However, many of these clones were singletons and the majority were unspliced, raising the possibility that they may be derived from genomic DNA or unprocessed pre-mRNA contamination during library construction, or alternatively represent nonspecific "transcriptional noise." Here we show, using reverse transcriptase-dependent PCR, microarray, and Northern blot analyses, that many of these clones were derived from genuine transcripts of unknown function whose expression appears to be regulated. The ncRNA transcripts have larger exons and fewer introns than protein-coding transcripts. Analysis of the genomic landscape around these sequences indicates that some cDNA clones were produced not from terminal poly(A) tracts but internal priming sites within longer transcripts, only a minority of which is encompassed by known genes. A significant proportion of these transcripts exhibit tissue-specific expression patterns, as well as dynamic changes in their expression in macrophages following lipopolysaccharide stimulation. Taken together, the data provide strong support for the conclusion that ncRNAs are an important, regulated component of the mammalian transcriptome.[Supplemental material is available online at www.genome.org. The microarray data from this study have been submitted to the Gene Expression Omnibus under accession nos. GSD275 and GSE3098.] In recent years there have been increasing reports of functional non-protein-coding RNAs (ncRNAs) that are involved or implicated in developmental, tissue-specific, and disease processes, including X-chromosome dosage compensation, germ cell development and embryogenesis, neural and immune cell development, kidney and testis development, B-cell neoplasia, lung cancer, prostate cancer, cartilage-hair hypoplasia, spinocerebellar ataxia type 8, DiGeorge syndrome, autism, and schizophrenia (see Pang et al. 2005). Many putative ncRNAs are alternatively spliced and/or polyadenylated (Sutherland et al. 1996;Tam et al. 1997;Bussemakers et al. 1999;Raho et al. 2000;Charlier et al. 2001;Wolf et al. 2001). Smaller ncRNAs, termed microRNAs, have also been shown to be involved in developmental processes in both plants and animals, as well as implicated in disease (Carrington and Ambros 2003;Mattick and Makunin 2005). Recent evidence suggests that these microRNAs are derived from the introns of capped and polyadenylated protein-coding transcripts as well as the exons and introns of non-protein-coding transcripts, many of which are derived from "intergenic" regions (Cai et al. 2004;Rodriguez et al. 2004;Seitz et al. 2004;Mattick and Makunin 2005;Ying and Lin 2005). In addition, many complex genetic phenomena, including cosuppression, imprinting, methylation, and gene silencing (see Mattick...

Using deep sequencing (deepCAGE), the FANTOM4 study measured the genome-wide dynamics of transcription-start-site usage in the human monocytic cell line THP-1 throughout a time course of growth arrest and differentiation. Modeling the expression dynamics in terms of predicted cis-regulatory sites, we identified the key transcription regulators, their time-dependent activities and target genes. Systematic siRNA knockdown of 52 transcription factors confirmed the roles of individual factors in the regulatory network. Our results indicate that cellular states are constrained by complex networks involving both positive and negative regulatory interactions among substantial numbers of transcription factors and that no single transcription factor is both necessary and sufficient to drive the differentiation process.