Marina Lizio

Gateways to the FANTOM5 promoter level mammalian expression atlas

The FANTOM5 project investigates transcription initiation activities in more than 1,000 human and mouse primary cells, cell lines and tissues using CAGE. Based on manual curation of sample information and development of an ontology for sample classification, we assemble the resulting data into a centralized data resource (http://fantom.gsc.riken.jp/5/). This resource contains web-based tools and data-access points for the research community to search and extract data related to samples, genes, promoter activities, transcription factors and enhancers across the FANTOM5 atlas.

An atlas of human long non-coding RNAs with accurate 5′ ends

Long non-coding RNAs (lncRNAs) are largely heterogeneous and functionally uncharacterized. Here, using FANTOM5 cap analysis of gene expression (CAGE) data, we integrate multiple transcript collections to generate a comprehensive atlas of 27,919 human lncRNA genes with high-confidence 5′ ends and expression profiles across 1,829 samples from the major human primary cell types and tissues. Genomic and epigenomic classification of these lncRNAs reveals that most intergenic lncRNAs originate from enhancers rather than from promoters. Incorporating genetic and expression data, we show that lncRNAs overlapping trait-associated single nucleotide polymorphisms are specifically expressed in cell types relevant to the traits, implicating these lncRNAs in multiple diseases. We further demonstrate that lncRNAs overlapping expression quantitative trait loci (eQTL)-associated single nucleotide polymorphisms of messenger RNAs are co-expressed with the corresponding messenger RNAs, suggesting their potential roles in transcriptional regulation. Combining these findings with conservation data, we identify 19,175 potentially functional lncRNAs in the human genome.

Interactive visualization and analysis of large-scale sequencing datasets using ZENBU

217 clustering (Fig. 1c and Supplementary Figs. 3 and 4), and collation (Fig. 1h and Supplementary Fig. 3). With an understanding of these atomic operations, more advanced users can combine them into complex processing scripts. These customized scripts can also be saved and shared allowing efficient re-use of optimized analyses and views. To demonstrate some of ZENBU’s functionality, we show multiple views on the same underlying data, ENCODE RNA-seq2 experiments loaded in BAM format (Fig. 1). One of the more powerful views in this figure is the dynamic projection of RNA-seq reads onto GENCODE11 transcript models to calculate RPKM (reads per kilobase transcript per million reads) values (Fig. 1h). Transcripts are then colored by support and the RPKM expression table for these models can be downloaded in a variety of formats. A variation of the same script projects CAGE expression signal into the proximal promoter regions (±500 bp of 5ʹ end) of the same models (Supplementary Fig. 2). Furthermore, an implementation of the parametric clustering approach paraclu12 allows ZENBU to identify peaks of CAGE signal (Fig. 1c) and extract their corresponding expression values per experiment. Paraclu imposes minimal prior assumptions and is flexible enough for use with small RNA and ChIP-seq data by varying the clustering parameters (Supplementary Fig. 3 and 4). ZENBU also allows investigators to fine tune these settings and rapidly inspect the results on specific loci before genome-wide computation. A more detailed case study recapitulating an integrated ChIP-seq and RNA-seq analysis13 is included in Supplementary Note 1 to demonstrate the power of the complex scripting possible in ZENBU. To enable fast and reliable downloading of data genome-wide and to speed up visualization and processing, we implemented a track caching system, which To the Editor: The advance of sequencing technology has spurred an ever-growing body of sequence tag–based data from protocols such as RNA-seq, chromatin immunoprecipitation (ChIP)-seq, DNaseI-hypersensitive site sequencing (DHS)-seq and cap analysis of gene expression (CAGE). Large-scale consortia are applying standardized versions of these protocols across broad collections of samples1,2 to elucidate genomic function. Beyond this, the affordability of these systems and availability of sequencing services has made these technologies accessible to smaller laboratories focusing on individual biological systems. Data generation is only the beginning, however, and a substantial bottleneck for many labs is going from sequence data to biological insight, especially when the volume of data overwhelms standard paradigms for data visualization. Here, we present a web-based system, ZENBU, which addresses this problem by extending the functionality of the genome browser (Supplementary Fig. 1). For users with limited bioinformatics skills, ZENBU provides a suite of predefined views and data-processing scripts optimized for RNA-seq (Fig. 1), CAGE, short-RNA and ChIP-seq experiments (Supplementary Figs. 2–4). These are available simply upon uploading data as BAM (binary version of the sequence alignment/map)3 files. The system can also generate an optimized set of views for each of the above data types. ZENBU provides a rich selection of data manipulation capabilities, including quality filtering, signal thresholding, signal normalization, peak finding, annotation, collation of signal under peaks or transcript models and expression difference visualization across multiple experiments. We designed ZENBU with large-scale transcriptome projects in mind. In particular, the FANTOM5 project (unpublished data) required a system that would allow rapid incremental data loading, visualization, interpretation and downloading of thousands of deep CAGE, RNA-seq and small-RNA data sets as they were produced. We reviewed available systems4, including genome browsers, such as University of Tokyo Genome Browser (UTGB)5, Gbrowse6, University of Santa Cruz (UCSC) genome browser7, Ensembl8 and Integrative Genome Viewer (IGV)9, and data management tools, such as Biomart10, and found none with the full set of functions that we sought (see Supplementary Table 1 for comparison). Therefore, we developed ZENBU, a stable, fast, efficient and secure system that is flexible enough to allow customization of data filters, views and analyses. A key feature of ZENBU is that it allows the user to combine multiple experiments on demand (up to thousands of experiments) within any single track and interpret the data through linked views (Fig. 1). Upon combining multiple experiments, the genome browser view shows the combined genomic distribution of tags from these experiments within a given genomic interval (Fig. 1d), conversely the linked expression view shows the relative abundance of tags observed in this region across these experiments (shown as a histogram, Fig. 1j). The genome browser and expression view are ‘linked’, meaning that as the user interacts with one view the other is updated in real-time. This facilitates interactive exploration of the data because selecting features or regions within a browser track results in data for only that region being displayed in the expression view. And symmetrically, hiding specific experiments in the expression view updates the data displayed in the browser track. Data processing and complex views are achieved by a flexible on-demand scripting system based on data transformation and analysis modules. A selection of predefined combinations of simple operations are provided to perform generic tasks such as data normalization (Fig. 1b–d,h,i), data filtering (Supplementary Fig. 2), data Interactive visualization and analysis of large-scale sequencing datasets using ZENBU correspondence

PAPD5-mediated 3′ adenylation and subsequent degradation of miR-21 is disrupted in proliferative disease

Significance MicroRNAs (miRNAs) are small RNAs that regulate genes by selectively silencing their target messenger RNAs. They are often produced as various sequence variants that differ at their 3′ or 5′ ends. While 5′ sequence variations affect which messenger RNAs are targeted by the miRNA, the functional significance of 3′ sequence variants remains largely elusive. Here, we analyze 3′ sequence variants of miR-21, a miRNA well known for its crucial role in cancer and other diseases. We show that tumor suppressor PAPD5 mediates adenosine addition to the 3′ end of miR-21, followed by its 3′-to-5′ trimming by an exoribonuclease. We find that this degradation pathway is disrupted across a wide variety of cancers, highlighting its importance in human disease. Next-generation sequencing experiments have shown that microRNAs (miRNAs) are expressed in many different isoforms (isomiRs), whose biological relevance is often unclear. We found that mature miR-21, the most widely researched miRNA because of its importance in human disease, is produced in two prevalent isomiR forms that differ by 1 nt at their 3′ end, and moreover that the 3′ end of miR-21 is posttranscriptionally adenylated by the noncanonical poly(A) polymerase PAPD5. PAPD5 knockdown caused an increase in the miR-21 expression level, suggesting that PAPD5-mediated adenylation of miR-21 leads to its degradation. Exoribonuclease knockdown experiments followed by small-RNA sequencing suggested that PARN degrades miR-21 in the 3′-to-5′ direction. In accordance with this model, microarray expression profiling demonstrated that PAPD5 knockdown results in a down-regulation of miR-21 target mRNAs. We found that disruption of the miR-21 adenylation and degradation pathway is a general feature in tumors across a wide range of tissues, as evidenced by data from The Cancer Genome Atlas, as well as in the noncancerous proliferative disease psoriasis. We conclude that PAPD5 and PARN mediate degradation of oncogenic miRNA miR-21 through a tailing and trimming process, and that this pathway is disrupted in cancer and other proliferative diseases.

Update of the FANTOM web resource: From mammalian transcriptional landscape to its dynamic regulation

The international Functional Annotation Of the Mammalian Genomes 4 (FANTOM4) research collaboration set out to better understand the transcriptional network that regulates macrophage differentiation and to uncover novel components of the transcriptome employing a series of high-throughput experiments. The primary and unique technique is cap analysis of gene expression (CAGE), sequencing mRNA 5′-ends with a second-generation sequencer to quantify promoter activities even in the absence of gene annotation. Additional genome-wide experiments complement the setup including short RNA sequencing, microarray gene expression profiling on large-scale perturbation experiments and ChIP–chip for epigenetic marks and transcription factors. All the experiments are performed in a differentiation time course of the THP-1 human leukemic cell line. Furthermore, we performed a large-scale mammalian two-hybrid (M2H) assay between transcription factors and monitored their expression profile across human and mouse tissues with qRT-PCR to address combinatorial effects of regulation by transcription factors. These interdependent data have been analyzed individually and in combination with each other and are published in related but distinct papers. We provide all data together with systematic annotation in an integrated view as resource for the scientific community (http://fantom.gsc.riken.jp/4/). Additionally, we assembled a rich set of derived analysis results including published predicted and validated regulatory interactions. Here we introduce the resource and its update after the initial release.

A draft network of ligand–receptor-mediated multicellular signalling in human

Cell-to-cell communication across multiple cell types and tissues strictly governs proper functioning of metazoans and extensively relies on interactions between secreted ligands and cell-surface receptors. Herein, we present the first large-scale map of cell-to-cell communication between 144 human primary cell types. We reveal that most cells express tens to hundreds of ligands and receptors to create a highly connected signalling network through multiple ligand–receptor paths. We also observe extensive autocrine signalling with approximately two-thirds of partners possibly interacting on the same cell type. We find that plasma membrane and secreted proteins have the highest cell-type specificity, they are evolutionarily younger than intracellular proteins, and that most receptors had evolved before their ligands. We provide an online tool to interactively query and visualize our networks and demonstrate how this tool can reveal novel cell-to-cell interactions with the prediction that mast cells signal to monoblastic lineages via the CSF1–CSF1R interacting pair.

Reduction of non-insert sequence reads by dimer eliminator LNA oligonucleotide for small RNA deep sequencing.

Here we describe a method for constructing small RNA libraries for high-throughput sequencing in which we have made a significant improvement to commonly available standard protocols. We added a locked nucleic acid (LNA) oligonucleotide--named dimer eliminator--that is complementary to the adapter-dimer ligation products during the reverse transcription reaction. It reduces adapter-dimers, which often contaminate standard libraries and increase the number of non-insert sequence reads. This simple technology can be used for simultaneous multiplex sequencing of various barcoded samples as well as nonbarcoded small RNA library sequencing. In this study we also evaluated the reproducibility and quantitative design of the eight barcoded tags by comparing the Pearsons correlation values in the expression analysis between each barcoded sample. This method improves the sequencing yield and efficiency, while simplifying library construction, and makes it easier to perform large-scale small RNA analysis under multiple conditions with next-generation sequencers.

An integrated expression atlas of miRNAs and their promoters in human and mouse

MicroRNAs (miRNAs) are short non-coding RNAs with key roles in cellular regulation. As part of the fifth edition of the Functional Annotation of Mammalian Genome (FANTOM5) project, we created an integrated expression atlas of miRNAs and their promoters by deep-sequencing 492 short RNA (sRNA) libraries, with matching Cap Analysis Gene Expression (CAGE) data, from 396 human and 47 mouse RNA samples. Promoters were identified for 1,357 human and 804 mouse miRNAs and showed strong sequence conservation between species. We also found that primary and mature miRNA expression levels were correlated, allowing us to use the primary miRNA measurements as a proxy for mature miRNA levels in a total of 1,829 human and 1,029 mouse CAGE libraries. We thus provide a broad atlas of miRNA expression and promoters in primary mammalian cells, establishing a foundation for detailed analysis of miRNA expression patterns and transcriptional control regions.

Update of the FANTOM web resource: high resolution transcriptome of diverse cell types in mammals

Upon the first publication of the fifth iteration of the Functional Annotation of Mammalian Genomes collaborative project, FANTOM5, we gathered a series of primary data and database systems into the FANTOM web resource (http://fantom.gsc.riken.jp) to facilitate researchers to explore transcriptional regulation and cellular states. In the course of the collaboration, primary data and analysis results have been expanded, and functionalities of the database systems enhanced. We believe that our data and web systems are invaluable resources, and we think the scientific community will benefit for this recent update to deepen their understanding of mammalian cellular organization. We introduce the contents of FANTOM5 here, report recent updates in the web resource and provide future perspectives.

FANTOM5 transcriptome catalog of cellular states based on Semantic MediaWiki

The Functional Annotation of the Mammalian Genome project (FANTOM5) mapped transcription start sites (TSSs) and measured their activities in a diverse range of biological samples. The FANTOM5 project generated a large data set; including detailed information about the profiled samples, the uncovered TSSs at high base-pair resolution on the genome, their transcriptional initiation activities, and further information of transcriptional regulation. Data sets to explore transcriptome in individual cellular states encoded in the mammalian genomes have been enriched by a series of additional analysis, based on the raw experimental data, along with the progress of the research activities. To make the heterogeneous data set accessible and useful for investigators, we developed a web-based database called Semantic catalog of Samples, Transcription initiation And Regulators (SSTAR). SSTAR utilizes the open source wiki software MediaWiki along with the Semantic MediaWiki (SMW) extension, which provides flexibility to model, store, and display a series of data sets produced during the course of the FANTOM5 project. Our use of SMW demonstrates the utility of the framework for dissemination of large-scale analysis results. SSTAR is a case study in handling biological data generated from a large-scale research project in terms of maintenance and growth alongside research activities. Database URL: http://fantom.gsc.riken.jp/5/sstar/