VEGF-C/VEGFR-3 signaling plays a central role in lymphatic development, regulating the budding of lymphatic progenitor cells from embryonic veins and maintaining the expression of PROX1 during later developmental stages. However, how VEGFR-3 activation translates into target gene expression is still not completely understood. We used cap analysis of gene expression (CAGE) RNA sequencing to characterize the transcriptional changes invoked by VEGF-C in LECs and to identify the transcription factors (TFs) involved. We found that MAFB, a TF involved in differentiation of various cell types, is rapidly induced and activated by VEGF-C. MAFB induced expression of PROX1 as well as other TFs and markers of differentiated LECs, indicating a role in the maintenance of the mature LEC phenotype. Correspondingly, E14.5 Mafb(-/-) embryos showed impaired lymphatic patterning in the skin. This suggests that MAFB is an important TF involved in lymphangiogenesis.

The capacity for plasticity in the adult brain is limited by the anatomical traces laid down during early postnatal life. Removing certain molecular brakes, such as histone deacetylases (HDACs), has proven to be effective in recapitulating juvenile plasticity in the mature visual cortex (V1). We investigated the chromatin structure and transcriptional control by genome-wide sequencing of DNase I hypersensitive sites (DHSS) and cap analysis of gene expression (CAGE) libraries after HDAC inhibition by valproic acid (VPA) in adult V1.

PIWI-interacting RNAs (piRNAs) are responsible for maintaining the genome stability by silencing retrotransposons in germline tissues- where piRNAs were first discovered and thought to be restricted. Recently, novel functions were reported for piRNAs in germline and somatic cells. Using deep sequencing of small RNAs and CAGE of postnatal development of mouse brain, we identified piRNAs only in adult mouse brain. These piRNAs have similar sequence length as those of MILI-bound piRNAs. In addition, we predicted novel candidate regulators and putative targets of adult brain piRNAs.

Functionality of the non-coding transcripts encoded by the human genome is the coveted goal of the modern genomics research. While commonly relied on the classical methods of forward genetics, integration of different genomics datasets in a global Systems Biology fashion presents a more productive avenue of achieving this very complex aim. Here we report application of a Systems Biology-based approach to dissect functionality of a newly identified vast class of very long intergenic non-coding (vlinc) RNAs. Using highly quantitative FANTOM5 CAGE dataset, we show that these RNAs could be grouped into 1542 novel human genes based on analysis of insulators that we show here indeed function as genomic barrier elements. We show that vlinc RNAs genes likely function in cisto activate nearby genes. This effect while most pronounced in closely spaced vlinc RNA-gene pairs can be detected over relatively large genomic distances. Furthermore, we identified 101 vlinc RNA genes likely involved in early embryogenesis based on patterns of their expression and regulation. We also found another 109 such genes potentially involved in cellular functions also happening at early stages of development such as proliferation, migration and apoptosis. Overall, we show that Systems Biology-based methods have great promise for functional annotation of non-coding RNAs.

The study of gene expression in mammalian single cells via genomic technologies now provides the possibility to investigate the patterns of allelic gene expression. We used single-cell RNA sequencing to detect the allele-specific mRNA level in 203 single human primary fibroblasts over 133,633 unique heterozygous single-nucleotide variants (hetSNVs). We observed that at the snapshot of analyses, each cell contained mostly transcripts from one allele from the majority of genes; indeed, 76.4% of the hetSNVs displayed stochastic monoallelic expression in single cells. Remarkably, adjacent hetSNVs exhibited a haplotype-consistent allelic ratio; in contrast, distant sites located in two different genes were independent of the haplotype structure. Moreover, the allele-specific expression in single cells correlated with the abundance of the cellular transcript. We observed that genes expressing both alleles in the majority of the single cells at a given time point were rare and enriched with highly expressed genes. The relative abundance of each allele in a cell was controlled by some regulatory mechanisms given that we observed related single-cell allelic profiles according to genes. Overall, these results have direct implications in cellular phenotypic variability.

MicroRNAs are small non-coding RNAs that inhibit the translation of target mRNAs. In humans, most microRNAs are transcribed by RNA polymerase II as long primary transcripts and processed by sequential cleavage of the two RNase III enzymes, DROSHA and DICER, into precursor and mature microRNAs, respectively. Although the fundamental functions of microRNAs in RNA silencing have been gradually uncovered, less is known about the regulatory mechanisms of microRNA expression. Here, we report that telomerase reverse transcriptase (TERT) extensively affects the expression levels of mature microRNAs. Deep sequencing-based screens of short RNA populations revealed that the suppression of TERT resulted in the downregulation of microRNAs expressed in THP-1 cells and HeLa cells. Primary and precursor microRNA levels were also reduced under the suppression of TERT. Similar results were obtained with the suppression of either BRG1 (also called SMARCA4) or nucleostemin, which are proteins interacting with TERT and functioning beyond telomeres. These results suggest that TERT regulates microRNAs at the very early phases in their biogenesis, presumably through non-telomerase mechanism(s).

The analysis of CAGE (Cap Analysis of Gene Expression) time-course has been proposed by the FANTOM5 Consortium to extend the understanding of the sequence of events facilitating cell state transition at the level of promoter regulation. To identify the most prominent transcriptional regulations induced by growth factors in human breast cancer, we apply here the Complexity Invariant Dynamic Time Warping motif EnRichment (CIDER) analysis approach to the CAGE time-course datasets of MCF-7 cells stimulated by epidermal growth factor (EGF) or heregulin (HRG). We identify a multi-level cascade of regulations rooted by the Serum Response Factor (SRF) transcription factor, connecting the MAPK-mediated transduction of the HRG stimulus to the negative regulation of the MAPK pathway by the members of the DUSP family phosphatases. The finding confirms the known primary role of FOS and FOSL1, members of AP-1 family, in shaping gene expression in response to HRG induction. Moreover, we identify a new potential regulation of DUSP5 and RARA (known to antagonize the transcriptional regulation induced by the estrogen receptors) by the activity of the AP-1 complex, specific to HRG response. The results indicate that a divergence in AP-1 regulation determines cellular changes of breast cancer cells stimulated by ErbB receptors.

The HSA21 encoded Single-minded 2 (SIM2) transcription factor has key neurological functions and is a good candidate to be involved in the cognitive impairment of Down syndrome. We aimed to explore the functional capacity of SIM2 by mapping its DNA binding sites in mouse embryonic stem cells. ChIP-sequencing revealed 1229 high-confidence SIM2-binding sites. Analysis of the SIM2 target genes confirmed the importance of SIM2 in developmental and neuronal processes and indicated that SIM2 may be a master transcription regulator. Indeed, SIM2 DNA binding sites share sequence specificity and overlapping domains of occupancy with master transcription factors such as SOX2, OCT4 (Pou5f1), NANOG or KLF4. The association between SIM2 and these pioneer factors is supported by co-immunoprecipitation of SIM2 with SOX2, OCT4, NANOG or KLF4. Furthermore, the binding of SIM2 marks a particular sub-category of enhancers known as super-enhancers. These regions are characterized by typical DNA modifications and Mediator co-occupancy (MED1 and MED12). Altogether, we provide evidence that SIM2 binds a specific set of enhancer elements thus explaining how SIM2 can regulate its gene network in neuronal features.

The generation of myeloid cells from their progenitors is regulated at the level of transcription by combinatorial control of key transcription factors influencing cell-fate choice. To unravel the global dynamics of this process at the transcript level, we generated transcription profiles for 91 human cell types of myeloid origin by use of CAGE profiling. The CAGE sequencing of these samples has allowed us to investigate diverse aspects of transcription control during myelopoiesis, such as identification of novel transcription factors, miRNAs, and noncoding RNAs specific to the myeloid lineage. We further reconstructed a transcription regulatory network by clustering coexpressed transcripts and associating them with enriched cis-regulatory motifs. With the use of the bidirectional expression as a proxy for enhancers, we predicted over 2000 novel enhancers, including an enhancer 38 kb downstream of IRF8 and an intronic enhancer in the KIT gene locus. Finally, we highlighted relevance of these data to dissect transcription dynamics during progressive maturation of granulocyte precursors. A multifaceted analysis of the myeloid transcriptome is made available (www.myeloidome.roslin.ed.ac.uk). This high-quality dataset provides a powerful resource to study transcriptional regulation during myelopoiesis and to infer the likely functions of unannotated genes in human innate immunity.

Although it is generally accepted that cellular differentiation requires changes to transcriptional networks, dynamic regulation of promoters and enhancers at specific sets of genes has not been previously studied en masse. Exploiting the fact that active promoters and enhancers are transcribed, we simultaneously measured their activity in 19 human and 14 mouse time courses covering a wide range of cell types and biological stimuli. Enhancer RNAs, then messenger RNAs encoding transcription factors, dominated the earliest responses. Binding sites for key lineage transcription factors were simultaneously overrepresented in enhancers and promoters active in each cellular system. Our data support a highly generalizable model in which enhancer transcription is the earliest event in successive waves of transcriptional change during cellular differentiation or activation.

MicroRNAs (miRNAs) modulate the post-transcriptional regulation of target genes and are related to biology of complex human traits, but genetic landscape of miRNAs remains largely unknown. Given the strikingly tissue-specific miRNA expression profiles, we here expand a previous method to quantitatively evaluate enrichment of genome-wide association study (GWAS) signals on miRNA-target gene networks (MIGWAS) to further estimate tissue-specific enrichment. Our approach integrates tissue-specific expression profiles of miRNAs (∼1800 miRNAs in 179 cells) with GWAS to test whether polygenic signals enrich in miRNA-target gene networks and whether they fall within specific tissues. We applied MIGWAS to 49 GWASs (nTotal = 3 520 246), and successfully identified biologically relevant tissues. Further, MIGWAS could point miRNAs as candidate biomarkers of the trait. As an illustrative example, we performed differentially expressed miRNA analysis between rheumatoid arthritis (RA) patients and healthy controls (n = 63). We identified novel biomarker miRNAs (e.g. hsa-miR-762) by integrating differentially expressed miRNAs with MIGWAS results for RA, as well as novel associated loci with significant genetic risk (rs56656810 at MIR762 at 16q11; n = 91 482, P = 3.6 × 10-8). Our result highlighted that miRNA-target gene network contributes to human disease genetics in a cell type-specific manner, which could yield an efficient screening of miRNAs as promising biomarkers.

Parkinson's disease (PD) is an age-related, chronic and progressive neurodegenerative disorder characterized by a loss of multifocal neurons, resulting in both non-motor and motor symptoms. While several genetic and environmental contributory risk factors have been identified, more exact methods for diagnosing and assessing prognosis of PD have yet to be established. Here we describe the generation and validation of a dataset comprising whole-blood transcriptomes originally intended for use in detection of blood biomarkers and transcriptomic network changes indicative of PD. Whole-blood samples extracted from both early-stage PD patients and healthy controls were sequenced using no-amplification non-tagging cap analysis of gene expression (nAnT-iCAGE) to analyse differences in global RNA expression patterns across the conditions. Subsequent sampling of a subset of PD patients one-year later provides the opportunity to study changes in transcriptomes arising due to disease progression.

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.

Statistical models have been used to quantify the relationship between gene expression and transcription factor (TF) binding signals. Here we apply the models to the large-scale data generated by the ENCODE project to study transcriptional regulation by TFs. Our results reveal a notable difference in the prediction accuracy of expression levels of transcription start sites (TSSs) captured by different technologies and RNA extraction protocols. In general, the expression levels of TSSs with high CpG content are more predictable than those with low CpG content. For genes with alternative TSSs, the expression levels of downstream TSSs are more predictable than those of the upstream ones. Different TF categories and specific TFs vary substantially in their contributions to predicting expression. Between two cell lines, the differential expression of TSS can be precisely reflected by the difference of TF-binding signals in a quantitative manner, arguing against the conventional on-and-off model of TF binding. Finally, we explore the relationships between TF-binding signals and other chromatin features such as histone modifications and DNase hypersensitivity for determining expression. The models imply that these features regulate transcription in a highly coordinated manner.

Deciphering the most common modes by which chromatin regulates transcription, and how this is related to cellular status and processes is an important task for improving our understanding of human cellular biology. The FANTOM5 and ENCODE projects represent two independent large scale efforts to map regulatory and transcriptional features to the human genome. Here we investigate chromatin features around a comprehensive set of transcription start sites in four cell lines by integrating data from these two projects.

The latest project from the FANTOM consortium, an international collaborative effort initiated by RIKEN, generated atlases of transcriptomes, in particular promoters, transcribed enhancers, and long-noncoding RNAs, across a diverse set of mammalian cell types. Here, we introduce the FANTOM5 collection, bringing together data descriptors, articles and analyses of FANTOM5 data published across the Nature Research journals. Associated data are openly available for reuse by all.

Drug combination therapy for treatment of cancers and other multifactorial diseases has the potential of increasing the therapeutic effect, while reducing the likelihood of drug resistance. In order to reduce time and cost spent in comprehensive screens, methods are needed which can model additive effects of possible drug combinations.

The FANTOM5 expression atlas is a quantitative measurement of the activity of nearly 200,000 promoter regions across nearly 2,000 different human primary cells, tissue types and cell lines. Generation of this atlas was made possible by the use of CAGE, an experimental approach to localise transcription start sites at single-nucleotide resolution by sequencing the 5' ends of capped RNAs after their conversion to cDNAs. While 50% of CAGE-defined promoter regions could be confidently associated to adjacent transcriptional units, nearly 100,000 promoter regions remained gene-orphan. To address this, we used the CAGEscan method, in which random-primed 5'-cDNAs are paired-end sequenced. Pairs starting in the same region are assembled in transcript models called CAGEscan clusters. Here, we present the production and quality control of CAGEscan libraries from 56 FANTOM5 RNA sources, which enhances the FANTOM5 expression atlas by providing experimental evidence associating core promoter regions with their cognate transcripts.

RNA interference (RNAi) pathways have evolved as important modulators of gene expression that operate in the cytoplasm by degrading RNA target molecules through the activity of short (21-30 nucleotide) RNAs. RNAi components have been reported to have a role in the nucleus, as they are involved in epigenetic regulation and heterochromatin formation. However, although RNAi-mediated post-transcriptional gene silencing is well documented, the mechanisms of RNAi-mediated transcriptional gene silencing and, in particular, the role of RNAi components in chromatin dynamics, especially in animal multicellular organisms, are elusive. Here we show that the key RNAi components Dicer 2 (DCR2) and Argonaute 2 (AGO2) associate with chromatin (with a strong preference for euchromatic, transcriptionally active, loci) and interact with the core transcription machinery. Notably, loss of function of DCR2 or AGO2 showed that transcriptional defects are accompanied by the perturbation of RNA polymerase II positioning on promoters. Furthermore, after heat shock, both Dcr2 and Ago2 null mutations, as well as missense mutations that compromise the RNAi activity, impaired the global dynamics of RNA polymerase II. Finally, the deep sequencing of the AGO2-associated small RNAs (AGO2 RIP-seq) revealed that AGO2 is strongly enriched in small RNAs that encompass the promoter regions and other regions of heat-shock and other genetic loci on both the sense and antisense DNA strands, but with a strong bias for the antisense strand, particularly after heat shock. Taken together, our results show that DCR2 and AGO2 are globally associated with transcriptionally active loci and may have a pivotal role in shaping the transcriptome by controlling the processivity of RNA polymerase II.

We report a catalog of the mouse embryonic pituitary gland transcriptome consisting of five cDNA libraries including wild type tissue from E12.5 and E14.5, Prop1(df/df) mutant at E14.5, and two cDNA subtractions: E14.5 WT-E14.5 Prop1(df/df) and E14.5 WT-E12.5 WT. DNA sequence information is assembled into a searchable database with gene ontology terms representing 12,009 expressed genes. We validated coverage of the libraries by detecting most known homeobox gene transcription factor cDNAs. A total of 45 homeobox genes were detected as part of the pituitary transcriptome, representing most expected ones, which validated library coverage, and many novel ones, underscoring the utility of this resource as a discovery tool. We took a similar approach for signaling-pathway members with novel pituitary expression and found 157 genes related to the BMP, FGF, WNT, SHH and NOTCH pathways. These genes are exciting candidates for regulators of pituitary development and function.