Transcriptional coupling of distant regulatory genes in living embryos.

The prevailing view of metazoan gene regulation is that individual genes are independently regulated by their own dedicated sets of transcriptional enhancers. Past studies have reported long-range gene-gene associations1-3, but their functional importance in regulating transcription remains unclear. Here we used quantitative single-cell live imaging methods to provide a demonstration of co-dependent transcriptional dynamics of genes separated by large genomic distances in living Drosophila embryos. We find extensive physical and functional associations of distant paralogous genes, including co-regulation by shared enhancers and co-transcriptional initiation over distances of nearly 250 kilobases. Regulatory interconnectivity depends on promoter-proximal tethering elements, and perturbations in these elements uncouple transcription and alter the bursting dynamics of distant genes, suggesting a role of genome topology in the formation and stability of co-transcriptional hubs. Transcriptional coupling is detected throughout the fly genome and encompasses a broad spectrum of conserved developmental processes, suggesting a general strategy for long-range integration of gene activity.

Landscape of transcription in human cells.

Eukaryotic cells make many types of primary and processed RNAs that are found either in specific subcellular compartments or throughout the cells. A complete catalogue of these RNAs is not yet available and their characteristic subcellular localizations are also poorly understood. Because RNA represents the direct output of the genetic information encoded by genomes and a significant proportion of a cell's regulatory capabilities are focused on its synthesis, processing, transport, modification and translation, the generation of such a catalogue is crucial for understanding genome function. Here we report evidence that three-quarters of the human genome is capable of being transcribed, as well as observations about the range and levels of expression, localization, processing fates, regulatory regions and modifications of almost all currently annotated and thousands of previously unannotated RNAs. These observations, taken together, prompt a redefinition of the concept of a gene.

High-fidelity promoter profiling reveals widespread alternative promoter usage and transposon-driven developmental gene expression.

Many eukaryotic genes possess multiple alternative promoters with distinct expression specificities. Therefore, comprehensively annotating promoters and deciphering their individual regulatory dynamics is critical for gene expression profiling applications and for our understanding of regulatory complexity. We introduce RAMPAGE, a novel promoter activity profiling approach that combines extremely specific 5'-complete cDNA sequencing with an integrated data analysis workflow, to address the limitations of current techniques. RAMPAGE features a streamlined protocol for fast and easy generation of highly multiplexed sequencing libraries, offers very high transcription start site specificity, generates accurate and reproducible promoter expression measurements, and yields extensive transcript connectivity information through paired-end cDNA sequencing. We used RAMPAGE in a genome-wide study of promoter activity throughout 36 stages of the life cycle of Drosophila melanogaster, and describe here a comprehensive data set that represents the first available developmental time-course of promoter usage. We found that >40% of developmentally expressed genes have at least two promoters and that alternative promoters generally implement distinct regulatory programs. Transposable elements, long proposed to play a central role in the evolution of their host genomes through their ability to regulate gene expression, contribute at least 1300 promoters shaping the developmental transcriptome of D. melanogaster. Hundreds of these promoters drive the expression of annotated genes, and transposons often impart their own expression specificity upon the genes they regulate. These observations provide support for the theory that transposons may drive regulatory innovation through the distribution of stereotyped cis-regulatory modules throughout their host genomes.

STAR: ultrafast universal RNA-seq aligner.

MOTIVATION: Accurate alignment of high-throughput RNA-seq data is a challenging and yet unsolved problem because of the non-contiguous transcript structure, relatively short read lengths and constantly increasing throughput of the sequencing technologies. Currently available RNA-seq aligners suffer from high mapping error rates, low mapping speed, read length limitation and mapping biases. RESULTS: To align our large (>80 billon reads) ENCODE Transcriptome RNA-seq dataset, we developed the Spliced Transcripts Alignment to a Reference (STAR) software based on a previously undescribed RNA-seq alignment algorithm that uses sequential maximum mappable seed search in uncompressed suffix arrays followed by seed clustering and stitching procedure. STAR outperforms other aligners by a factor of >50 in mapping speed, aligning to the human genome 550 million 2 × 76 bp paired-end reads per hour on a modest 12-core server, while at the same time improving alignment sensitivity and precision. In addition to unbiased de novo detection of canonical junctions, STAR can discover non-canonical splices and chimeric (fusion) transcripts, and is also capable of mapping full-length RNA sequences. Using Roche 454 sequencing of reverse transcription polymerase chain reaction amplicons, we experimentally validated 1960 novel intergenic splice junctions with an 80-90% success rate, corroborating the high precision of the STAR mapping strategy. AVAILABILITY AND IMPLEMENTATION: STAR is implemented as a standalone C++ code. STAR is free open source software distributed under GPLv3 license and can be downloaded from http://code.google.com/p/rna-star/.

Genome organization controls transcriptional dynamics during development.

Past studies offer contradictory claims for the role of genome organization in the regulation of gene activity. Here, we show through high-resolution chromosome conformation analysis that the Drosophila genome is organized by two independent classes of regulatory sequences, tethering elements and insulators. Quantitative live imaging and targeted genome editing demonstrate that this two-tiered organization is critical for the precise temporal dynamics of Hox gene transcription during development. Tethering elements mediate long-range enhancer-promoter interactions and foster fast activation kinetics. Conversely, the boundaries of topologically associating domains (TADs) prevent spurious interactions with enhancers and silencers located in neighboring TADs. These two levels of genome organization operate independently of one another to ensure precision of transcriptional dynamics and the reliability of complex patterning processes.

Conserved noncoding transcription and core promoter regulatory code in early Drosophila development.

Multicellular development is driven by regulatory programs that orchestrate the transcription of protein-coding and noncoding genes. To decipher this genomic regulatory code, and to investigate the developmental relevance of noncoding transcription, we compared genome-wide promoter activity throughout embryogenesis in 5 Drosophila species. Core promoters, generally not thought to play a significant regulatory role, in fact impart restrictions on the developmental timing of gene expression on a global scale. We propose a hierarchical regulatory model in which core promoters define broad windows of opportunity for expression, by defining a range of transcription factors from which they can receive regulatory inputs. This two-tiered mechanism globally orchestrates developmental gene expression, including extremely widespread noncoding transcription. The sequence and expression specificity of noncoding RNA promoters are evolutionarily conserved, implying biological relevance. Overall, this work introduces a hierarchical model for developmental gene regulation, and reveals a major role for noncoding transcription in animal development.

RAMPAGE: promoter activity profiling by paired-end sequencing of 5'-complete cDNAs.

RNA annotation and mapping of promoters for analysis of gene expression (RAMPAGE) is a method that harnesses highly specific sequencing of 5'-complete complementary DNAs to identify transcription start sites (TSSs) genome-wide. Although TSS mapping has historically relied on detection of 5'-complete cDNAs, current genome-wide approaches typically have limited specificity and provide only scarce information regarding transcript structure. RAMPAGE allows for highly stringent selection of 5'-complete molecules, thus allowing base-resolution TSS identification with a high signal-to-noise ratio. Paired-end sequencing of medium-length cDNAs yields transcript structure information that is essential to interpreting the relationship of TSSs to annotated genes and transcripts. As opposed to standard RNA-seq, RAMPAGE explicitly yields accurate and highly reproducible expression level estimates for individual promoters. Moreover, this approach offers a streamlined 2- to 3-day protocol that is optimized for extensive sample multiplexing, and is therefore adapted for large-scale projects. This method has been applied successfully to human and Drosophila samples, and in principle should be applicable to any eukaryotic system.

Evidence for transcript networks composed of chimeric RNAs in human cells.

The classic organization of a gene structure has followed the Jacob and Monod bacterial gene model proposed more than 50 years ago. Since then, empirical determinations of the complexity of the transcriptomes found in yeast to human has blurred the definition and physical boundaries of genes. Using multiple analysis approaches we have characterized individual gene boundaries mapping on human chromosomes 21 and 22. Analyses of the locations of the 5' and 3' transcriptional termini of 492 protein coding genes revealed that for 85% of these genes the boundaries extend beyond the current annotated termini, most often connecting with exons of transcripts from other well annotated genes. The biological and evolutionary importance of these chimeric transcripts is underscored by (1) the non-random interconnections of genes involved, (2) the greater phylogenetic depth of the genes involved in many chimeric interactions, (3) the coordination of the expression of connected genes and (4) the close in vivo and three dimensional proximity of the genomic regions being transcribed and contributing to parts of the chimeric RNAs. The non-random nature of the connection of the genes involved suggest that chimeric transcripts should not be studied in isolation, but together, as an RNA network.