FANTOM Consortium Research Articles

Implications of differential transcription start site selection on chronic myeloid leukemia and prostate cancer cell protein expression.

The relevance of minor transcription start sites in broad promoters is not well understood. We have studied AGAP2 expression in prostate cancer and chronic myeloid leukemia (CML), showing transcription is initiated from alternative transcription start sites (TSSs) within a single TSS cluster, producing cancer-type-specific AGAP2 mRNAs with small differences in their 5' UTR length. Interestingly, in the CML cell lines where the 5' UTR is longer, AGAP2 protein levels are lower. We demonstrate that the selection of an upstream TSS involved the formation of a G quadruplex in the 5' UTR, decreasing polysome formation. After developing a bioinformatics pipeline to query data from the FANTOM project and the NCl-60 human tumor cell lines screen, we found HK1 expression can also be regulated by the same mechanism. Overall, we present compelling data supporting TSS selection within a TSS cluster play a role in protein expression and should not be ignored.

The Comparative Anatomy of Nanopublications and FAIR Digital Objects

Beginning in 1995, early Internet pioneers proposed Digital Objects as encapsulations of data and metadata made accessible through persistent identifier resolution services (Kahn and Wilensky 2006). In recent years, this Digital Object Architecture has been extended to include the FAIR Guiding Principles (Wilkinson et al. 2016), resulting in the concept of a FAIR Digital Object (FDO), a minimal, uniform container making any digital resource machine-actionable. Intense effort is currently underway by a global community of experts to clarify definitions around an FDO Framework (FDOF) and to provide technical specifications (FAIR DO group 2020, FAIR Digital Object Forum 2020 , Bonino da Silva Santos (2021)) regarding their potential implementation. Beginning in 2009, nanopublications were independently conceived (Groth et al. 2010) as a minimal, uniform container making individual semantic assertions and their associated provenance metadata, machine-actionable. They represent minimal units of structured data as citable entities (Mons and Velterop 2009). A nanopublication consists of an assertion, the provenance of the assertion, and the provenance of the nanopublication (publication info). Nanopublications are implemented in and aligned with Semantic Web technologies such as RDF, OWL, and SPARQL (World Wide Web Consortium (W3C) 2015) and can be permanently and uniquely identified using resolvable Trusty URIs (Groth et al. 2021). The existing Nanopublication Server Network provides vital services orchestrating nanopublications (Kuhn et al. 2021) including identifier resolution, storage, search and access. Nanopublications can be used to expose quantitative and qualitative data, as well as hypotheses, claims, negative results, and opinions that are typically unavailable as structured data or go unpublished altogether. The first practical application of nanopublications occurred in 2014, with the publication of millions of nanopublications as part of the FANTOM5 Project (The FANTOM Consortium and the RIKEN PMI and CLST (DGT) 2014, Lizio et al. 2015). Since then, millions of real-world examples spanning diverse knowledge domains are now available on the nanopublication server network. Like nanopublication, the FDOF also posits an ultra-minimal approach to structured, self-contained, machine-readable data and metadata. An FDO consists of: the object itself (subsequently referred to here as the resource to avoid confusion with other meanings of the term “object”); the metadata describing the resource; and a globally unique and persistent identifier with predictable resolution behaviors. These two technologies share the same vision of a data infrastructure, and act as instances of Machine-Actionable Containers (MACs) that make use of minimal uniform standards to enable FAIR operations. Here, we compare the structure and computational behaviors of the existing nanopublication infrastructure, to those in the proposed FAIR Digital Object Framework. Although developed independently there are clear parallels between the vision and the approach of nanopublication and FDOF. Each aspires to minimal standards for the encapsulation of digital information into free-standing, publishable (citable, referenceable) entities. The minimal standards involve globally unique and persistent identifiers that resolve to standardized semantically enabled metadata descriptions that include machine actionable paths to the resource itself. At the same time, there are also differences. The scope of nanopublications is limited to the assertional data type and, as the name suggests, nanopublications should remain small in size (limited to single assertions as individual triples or small RDF graphs). In contrast FDOs are unlimited in their scope, accommodating digital resources of arbitrarily large size, type and complexity, so long as their type can be ontologically described. Furthermore, whereas nanopublications represent a moderately mature technology, the FDOF is a specification still under development. If it were possible to formally draw points of contact between the two approaches, then it would be possible to leverage the vast practical experience gained in the nanopublishing of assertions for the FDO community. Here, inspired by recent applications of nanopublications in the FIP Wizard tool (Schultes et al. 2020), and their extension to research claims (Kuhn 2022, McNamara 2022) and data using Schultes (2022a), Schultes (2022b), we attempt a point-by-point comparison of the specifications between nanopublication and FDOs. We find a remarkable congruence between the currently proposed FDO requirements and the existing nanopublication infrastructure, including several FDO-like qualities already embodied in the nanopublication ecosystem.

A Human atlas of smooth muscle cell gene expression; insights from the FANTOM consortium CAGE dataset

Abstract Background Under normal physiological conditions, smooth muscle cells (SMC's) have a role in both vessel contraction and generation of the extra-cellular matrix. It has now become apparent that SMCs throughout the vasculature play a key role in several cardiovascular conditions including hypertension, atherosclerosis, vasculopathy and myocardial infarction. However, how SMC gene expression compares in different vascular and non-vascular anatomical regions remains unknown. Purpose To create a human SMC gene expression map using data from the FANTOM consortium Cap-analysis gene expression (CAGE) dataset, a primary database of almost 600 human primary cell samples. Methods The gene level expression data was obtained by aggregating expression levels of all the promoters belonging to same gene as defined by the FANTOM CAGE dataset. The anatomical regions (n: 13) included the following vascular sites: aortic, brachiocephalic, carotid, coronary, internal thoracic & pulmonary arteries. Non-vascular regions included colon, oesophagus, prostate, uterine, trachea and bronchial. Weighted correlation network analysis (WGCNA) was used as an unsupervised approach to identify clustering of gene sets. Results Hierarchical clustering (Figure 1) demonstrates a distinct clustering of vascular SMC gene sets (aortic, carotid, coronary, internal thoracic, pulmonary & subclavian arteries). The same pattern of vascular SMC clustering was also seen in WGCNA (Figure 2). Gene ontology enrichment of vascular SMCs that clustered in WGCNA identified common gene sets relating to cytokine and chemokine activity. KEGG pathway analysis highlighted several pathways linked to inflammation (TNF, IL17 & NF-κB signalling) as well as pathways linked to atherosclerosis and lipid metabolism. Conclusion Vascular SMCs distinctly cluster away from non-vascular SMC types in humans and the separation is primarily driven by gene sets relating to inflammation, lipid metabolism & atherosclerosis. Mapping SMC gene expression at various anatomical regions in both healthy and diseased states may give us better insight into the role of SMCs in disease progression and could identify novel mechanistic targets for future therapy. Funding Acknowledgement Type of funding sources: Foundation. Main funding source(s): British Heart Foundation

Pleiotropic Enhancers are Ubiquitous Regulatory Elements in the Human Genome.

Enhancers are regulatory elements of genomes that determine spatio-temporal patterns of gene expression. The human genome contains a vast number of enhancers, which largely outnumber protein-coding genes. Historically, enhancers have been regarded as highly tissue-specific. However, recent evidence has demonstrated that many enhancers are pleiotropic, with activity in multiple developmental contexts. Yet, the extent and impact of pleiotropy remain largely unexplored. In this study we analyzed active enhancers across human organs based on the analysis of both eRNA transcription (FANTOM5 consortium data sets) and chromatin architecture (ENCODE consortium data sets). We show that pleiotropic enhancers are pervasive in the human genome and that most enhancers active in a particular organ are also active in other organs. In addition, our analysis suggests that the proportion of context-specific enhancers of a given organ is explained, at least in part, by the proportion of context-specific genes in that same organ. The notion that such a high proportion of human enhancers can be pleiotropic suggests that small regions of regulatory DNA contain abundant regulatory information and that these regions evolve under important evolutionary constraints.

Identification and Functional Characterization of Two Noncoding RNAs Transcribed from Putative Active Enhancers in Hepatocellular Carcinoma.

Enhancers have been conventionally perceived as cis-acting elements that provide binding sites for trans-acting factors. However, recent studies have shown that enhancers are transcribed and that these transcripts, called enhancer RNAs (eRNAs), have a regulatory function. Here, we identified putative eRNAs by profiling and determining the overlap between noncoding RNA expression loci and eRNA-associated histone marks such as H3K27ac and H3K4me1 in hepatocellular carcinoma (HCC) cell lines. Of the 132 HCC-derived noncoding RNAs, 74 overlapped with the eRNA loci defined by the FANTOM consortium, and 65 were located in the proximal regions of genes differentially expressed between normal and tumor tissues in TCGA dataset. Interestingly, knockdown of two selected putative eRNAs, THUMPD3-AS1 and LINC01572, led to downregulation of their target mRNAs and to a reduction in the proliferation and migration of HCC cells. Additionally, the expression of these two noncoding RNAs and target mRNAs was elevated in tumor samples in the TCGA dataset, and high expression was associated with poor survival of patients. Collectively, our study suggests that noncoding RNAs such as THUMPD3-AS1 and LINC01572 (i.e., putative eRNAs) can promote the transcription of genes involved in cell proliferation and differentiation and that the dysregulation of these noncoding RNAs can cause cancers such as HCC.

Transcriptional landscape of PTEN loss in primary prostate cancer

BackgroundPTEN is the most frequently lost tumor suppressor in primary prostate cancer (PCa) and its loss is associated with aggressive disease. However, the transcriptional changes associated with PTEN loss in PCa have not been described in detail. In this study, we highlight the transcriptional changes associated with PTEN loss in PCa.MethodsUsing a meta-analysis approach, we leveraged two large PCa cohorts with experimentally validated PTEN and ERG status by Immunohistochemistry (IHC), to derive a transcriptomic signature of PTEN loss, while also accounting for potential confounders due to ERG rearrangements. This signature was expanded to lncRNAs using the TCGA quantifications from the FC-R2 expression atlas.ResultsThe signatures indicate a strong activation of both innate and adaptive immune systems upon PTEN loss, as well as an expected activation of cell-cycle genes. Moreover, we made use of our recently developed FC-R2 expression atlas to expand this signature to include many non-coding RNAs recently annotated by the FANTOM consortium. Highlighting potential novel lncRNAs associated with PTEN loss and PCa progression.ConclusionWe created a PCa specific signature of the transcriptional landscape of PTEN loss that comprises both the coding and an extensive non-coding counterpart, highlighting potential new players in PCa progression. We also show that contrary to what is observed in other cancers, PTEN loss in PCa leads to increased activation of the immune system. These findings can help the development of new biomarkers and help guide therapy choices.

Discovery of widespread transcription initiation at microsatellites predictable by sequence-based deep neural network

Using the Cap Analysis of Gene Expression (CAGE) technology, the FANTOM5 consortium provided one of the most comprehensive maps of transcription start sites (TSSs) in several species. Strikingly, ~72% of them could not be assigned to a specific gene and initiate at unconventional regions, outside promoters or enhancers. Here, we probe these unassigned TSSs and show that, in all species studied, a significant fraction of CAGE peaks initiate at microsatellites, also called short tandem repeats (STRs). To confirm this transcription, we develop Cap Trap RNA-seq, a technology which combines cap trapping and long read MinION sequencing. We train sequence-based deep learning models able to predict CAGE signal at STRs with high accuracy. These models unveil the importance of STR surrounding sequences not only to distinguish STR classes, but also to predict the level of transcription initiation. Importantly, genetic variants linked to human diseases are preferentially found at STRs with high transcription initiation level, supporting the biological and clinical relevance of transcription initiation at STRs. Together, our results extend the repertoire of non-coding transcription associated with DNA tandem repeats and complexify STR polymorphism.

Modeling the Evolutionary Architectures of Transcribed Human Enhancer Sequences Reveals Distinct Origins, Functions, and Associations with Human Trait Variation.

Despite the importance of gene regulatory enhancers in human biology and evolution, we lack a comprehensive model of enhancer evolution and function. This substantially limits our understanding of the genetic basis of species divergence and our ability to interpret the effects of noncoding variants on human traits.To explore enhancer sequence evolution and its relationship to regulatory function, we traced the evolutionary origins of transcribed human enhancer sequences with activity across diverse tissues and cellular contexts from the FANTOM5 consortium. The transcribed enhancers are enriched for sequences of a single evolutionary age (“simple” evolutionary architectures) compared with enhancers that are composites of sequences of multiple evolutionary ages (“complex” evolutionary architectures), likely indicating constraint against genomic rearrangements. Complex enhancers are older, more pleiotropic, and more active across species than simple enhancers. Genetic variants within complex enhancers are also less likely to associate with human traits and biochemical activity. Transposable-element-derived sequences (TEDS) have made diverse contributions to enhancers of both architectures; the majority of TEDS are found in enhancers with simple architectures, while a minority have remodeled older sequences to create complex architectures. Finally, we compare the evolutionary architectures of transcribed enhancers with histone-mark-defined enhancers.Our results reveal that most human transcribed enhancers are ancient sequences of a single age, and thus the evolution of most human enhancers was not driven by increases in evolutionary complexity over time. Our analyses further suggest that considering enhancer evolutionary histories provides context that can aid interpretation of the effects of variants on enhancer function. Based on these results, we propose a framework for analyzing enhancer evolutionary architecture.

Abstract 2535: Screening PTEN-loss associated lncRNAs in prostate cancer

Abstract Phosphatase and tensin homologue (PTEN) is a tumor suppressor gene that is frequently inactivated by deletion in prostate cancer (PCa). Occurring in around 20% of primary PCa tumors, and up to 50% in castration resistant tumors, it is the most frequent genomic aberration in PCa. Loss of PTEN activates the phosphoinositide 3-kinase-RAC-alpha serine/threonine-protein kinase (PI3K-AKT) pathway, which is associated with poor clinical outcomes. Despite the consequences of PTEN loss being well studied, most of what is known is restricted to protein-coding genes, with relatively little information about the role of non-coding genes. Using our recently created resource - the FC-R2 expression atlas, which encompasses expression levels for thousands of lncRNAs recently unveiled by the FANTOM consortium - we analyzed differential gene expression of PTEN-null vs PTEN-intact tumors with the goal of characterizing the molecular landscape of PTEN loss. First, we generated a consensus signature using two large PCa cohorts with experimentally validated PTEN status by Immunohistochemistry (IHC), applying a meta-analysis approach. This signature encompassed mainly protein coding genes due it being microarray based. In order to expand this signature beyond the coding genes, we relied on FC-R2-based TCGA-PRAD data. Since PTEN status was not available by IHC, we opted to call the status based on CNV. Then, we proceed to generate a PTEN-null signature using a generalized linear model approach. Both signatures were compared for concordance using correspondence-at-the-top plots and hypergeometric confidence intervals. Gene set enrichment analysis was performed in both signatures using a collection of obtained from the MSigDB database in order to characterize pathways involved in this event. Our results showed that the signature based on IHC validated samples agreed significantly with the CNV-based signature from TCGA for the genes in common. In the differential gene expression analysis on the TCGA cohort we observed 203 significant coding genes and 171 significant non-coding genes (FDR ≤ 0.01, LogFC ≥ 1). Notably, we identified several lncRNAs that have not been associated with PCa or PTEN loss, these include many classes of non-coding RNAs characterized by the FANTOM consortium such as: enhancers and promoters genes. Gene set enrichment analysis revealed that PTEN-null tumors are associated with epithelial-mesenchymal transition suggesting a possible role for these lncRNAs. In conclusion, by leveraging our resources, we were able to obtain comprehensive landscape of the PTEN loss in PCa for both the coding and non-coding counterpart. Furthermore, the association of many lncRNAs with PTEN loss was observed, many recently annotated by the FANTOM consortium, which can help us understand how genes are regulated in this event. In this work we show that despite being widely studied, there are still many components of PTEN loss in the form of lncRNAs highlighting potential markers for PTEN loss and clinical outcomes. Citation Format: Eddie Luidy Imada, Diego Fernando Sanchez, Wikum Dinalankara, Tamara Lotan, Luigi Marchionni. Screening PTEN-loss associated lncRNAs in prostate cancer [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 2535.

Abstract 4491: Characterizing long non-coding RNA expression of tumor-infiltrating lymphocytes across solid cancers

Abstract Usually recognized as transcripts of length more than 200 bp and devoid of open reading frames, long non-coding RNAs (lncRNAs) span a vast range of the human genome. Once thought to be of relatively little biological importance, they have been shown to be involved in many biological processes and diseases, highlighting their important regulatory function, which is now gradually starting to be understood. For instance, the recent discovery of immune gene priming lncRNAs (IPLs) – a subset of lncRNAs that facilitate epigenetic priming of immune gene promoters – has demonstrated the hitherto unappreciated role of lncRNAs in orchestrating inflammatory and immune responses. In this study we generated and analyzed bulk RNA sequencing data from a collection of purified cell populations obtained from patients with prostate cancer, glioblastoma, bladder cancer, and renal cell carcinoma. Each cohort was comprised of tumor infiltrating lymphocytes (TILs) and paired circulating lymphocytes, derived from matched peripheral blood samples, obtained by fluorescence-activated cell sorting (FACS). The high depth of coverage in our data allowed the examination of expression patterns of CD4 and CD8 cell types at a level not possible with single cell sequencing, across relevant tumor phenotypes including T-cell exhaustion. To this end, we used the FANTOM CAGE-Associated Transcriptome (FANTOM-CAT) annotation, quantifying expression levels for over 100,000 coding and non-coding genes, encompassing enhancers and promoters recently characterized by the FANTOM consortium and examined their behavior with respect to immune function. We compared the behavior of coding genes and various categories of lncRNAs against each other, and identified important candidate lncRNAs for further functional study. Overall, our comprehensive study of TILs gene expression provides novel insights into lncRNA-directed networks controlling immune response mechanisms in cancer. Citation Format: Wikum Dinalankara, Eddie-Luidy Imada, Christopher M. Jackson, Thomas R. Nirschl, Michael Lim, Charles G. Drake, Luigi Marchionni. Characterizing long non-coding RNA expression of tumor-infiltrating lymphocytes across solid cancers [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 4491.

MountainClimber Identifies Alternative Transcription Start and Polyadenylation Sites in RNA-Seq.

Alternative transcription start (ATS) and alternative polyadenylation (APA) create alternative RNA isoforms and modulate many aspects of RNA expression and protein production. However, ATS and APA remain difficult to detect in RNA sequencing (RNA-seq). Here, we developed mountainClimber, a de novo cumulative-sum-based approach to identify ATS and APA as change points. Unlike many existing methods, mountainClimber runs on a single sample and identifies multiple ATS or APA sites anywhere in the transcript. We analyzed 2,342 GTEx samples (36 tissues, 215 individuals) and found that tissue type is the predominant driver of transcript end variations. 75% and 65% of genes exhibited differential APA and ATS across tissues, respectively. In particular, testis displayed longer 5' untranslated regions (UTRs) and shorter 3' UTRs, often in genes related to testis-specific biology. Overall, we report the largest study of transcript ends across human tissues to our knowledge. mountainClimber is available at github.com/gxiaolab/mountainClimber.

Identification of novel cerebellar developmental transcriptional regulators with motif activity analysis

BackgroundThe work of the FANTOM5 Consortium has brought forth a new level of understanding of the regulation of gene transcription and the cellular processes involved in creating diversity of cell types. In this study, we extended the analysis of the FANTOM5 Cap Analysis of Gene Expression (CAGE) transcriptome data to focus on understanding the genetic regulators involved in mouse cerebellar development.ResultsWe used the HeliScopeCAGE library sequencing on cerebellar samples over 8 embryonic and 4 early postnatal times. This study showcases temporal expression pattern changes during cerebellar development. Through a bioinformatics analysis that focused on transcription factors, their promoters and binding sites, we identified genes that appear as strong candidates for involvement in cerebellar development. We selected several candidate transcriptional regulators for validation experiments including qRT-PCR and shRNA transcript knockdown. We observed marked and reproducible developmental defects in Atf4, Rfx3, and Scrt2 knockdown embryos, which support the role of these genes in cerebellar development.ConclusionsThe successful identification of these novel gene regulators in cerebellar development demonstrates that the FANTOM5 cerebellum time series is a high-quality transcriptome database for functional investigation of gene regulatory networks in cerebellar development.

Signatures of Recent Positive Selection in Enhancers Across 41 Human Tissues.

Evolutionary changes in enhancers are widely associated with variation in human traits and diseases. However, studies comprehensively quantifying levels of selection on enhancers at multiple evolutionary periods during recent human evolution and how enhancer evolution varies across human tissues are lacking. To address these questions, we integrated a dataset of 41,561 transcribed enhancers active in 41 different human tissues (FANTOM Consortium) with whole genome sequences of 1,668 individuals from the African, Asian, and European populations (1000 Genomes Project). Our analyses based on four different metrics (Tajima’s D, FST, H12, nSL) showed that ∼5.90% of enhancers showed evidence of recent positive selection and that genes associated with enhancers under very recent positive selection are enriched for diverse immune-related functions. The distributions of these metrics for brain and testis enhancers were often statistically significantly different and in the direction suggestive of less positive selection compared to those of other tissues; the same was true for brain and testis enhancers that are tissue-specific compared to those that are tissue-broad and for testis enhancers associated with tissue-enriched and non-tissue-enriched genes. These differences varied considerably across metrics and tissues and were generally in the form of changes in distributions’ shapes rather than shifts in their values. Collectively, these results suggest that many human enhancers experienced recent positive selection throughout multiple time periods in human evolutionary history, that this selection occurred in a tissue-dependent and immune-related functional context, and that much like the evolution of their protein-coding gene counterparts, the evolution of brain and testis enhancers has been markedly different from that of enhancers in other tissues.

Causal Transcription Regulatory Network Inference Using Enhancer Activity as a Causal Anchor.

Transcription control plays a crucial role in establishing a unique gene expression signature for each of the hundreds of mammalian cell types. Though gene expression data have been widely used to infer cellular regulatory networks, existing methods mainly infer correlations rather than causality. We developed statistical models and likelihood-ratio tests to infer causal gene regulatory networks using enhancer RNA (eRNA) expression information as a causal anchor and applied the framework to eRNA and transcript expression data from the FANTOM Consortium. Predicted causal targets of transcription factors (TFs) in mouse embryonic stem cells, macrophages and erythroblastic leukaemia overlapped significantly with experimentally-validated targets from ChIP-seq and perturbation data. We further improved the model by taking into account that some TFs might act in a quantitative, dosage-dependent manner, whereas others might act predominantly in a binary on/off fashion. We predicted TF targets from concerted variation of eRNA and TF and target promoter expression levels within a single cell type, as well as across multiple cell types. Importantly, TFs with high-confidence predictions were largely different between these two analyses, demonstrating that variability within a cell type is highly relevant for target prediction of cell type-specific factors. Finally, we generated a compendium of high-confidence TF targets across diverse human cell and tissue types.

TELS: A Novel Computational Framework for Identifying Motif Signatures of Transcribed Enhancers

In mammalian cells, transcribed enhancers (TrEns) play important roles in the initiation of gene expression and maintenance of gene expression levels in a spatiotemporal manner. One of the most challenging questions is how the genomic characteristics of enhancers relate to enhancer activities. To date, only a limited number of enhancer sequence characteristics have been investigated, leaving space for exploring the enhancers’ DNA code in a more systematic way. To address this problem, we developed a novel computational framework, Transcribed Enhancer Landscape Search (TELS), aimed at identifying predictive cell type/tissue-specific motif signatures of TrEns. As a case study, we used TELS to compile a comprehensive catalog of motif signatures for all known TrEns identified by the FANTOM5 consortium across 112 human primary cells and tissues. Our results confirm that combinations of different short motifs characterize in an optimized manner cell type/tissue-specific TrEns. Our study is the first to report combinations of motifs that maximize classification performance of TrEns exclusively transcribed in one cell type/tissue from TrEns exclusively transcribed in different cell types/tissues. Moreover, we also report 31 motif signatures predictive of enhancers’ broad activity. TELS codes and material are publicly available at http://www.cbrc.kaust.edu.sa/TELS.

Abstract 2297: Differential analysis of gene expression across the human genome using recount2 and FANTOM-CAT

Abstract In recent years, in depth exploration of genomes structure and function has revealed a central role for non-coding RNAs (ncRNAs) in orchestrating key biological and cellular processes through the fine tuning of gene expression regulation. Most importantly a role for ncRNAs has also started to emerge in human disease pathogenesis. This further speaks to the importance of an in-depth characterization of ncRNA involvement in human diseases, including cancer. In this work, we have built a comprehensive atlas of gene expression across the human transcriptome containing over 100,000 genes by leveraging two publicly available resources: the FANTOM CAGE Associated Transcriptome (FANTOM-CAT), and recount2. The FANTOM-CAT is a comprehensive meta-assembly of the human transcriptome encompassing coding and non-coding genes, including promoters, enhancers, and lncRNAs. recount2 is the largest, available collection of human RNA-seq data processed and quantified using a unified pipeline, containing over 4.4 trillion reads from over 70,000 human samples from the SRA, GTEx and TCGA projects. Using FANTOM-CAT/recount2 gene expression summaries across human tissue samples from the GTEx project, we validated our approach by reproducing key findings recently described by the FANTOM consortium. In particular, we could identify and confirm the reported tissue specific transcription patterns for the distinct classes of coding and non-coding genes, such as messenger RNAs, intergenic long ncRNAs, and expressed divergent promoters and enhancers. Most importantly, we have leveraged the FANTOM-CAT/recount2 atlas to perform differential gene expression analysis across 13 cancer types in TCGA, identifying a comprehensive list of mRNAs, promoters, enhancers, and other ncRNAs differentially expressed between cancer and normal samples. Overall, this analysis revealed a set of molecular signatures encompassing coding and non-coding genes that are shared across cancer types or restricted to specific tissues of origin. In summary, our findings establish the FANTOM-CAT/recount2 gene expression atlas as a reliable resource to study the role ncRNAs play in cancer and other human diseases, providing important cues to understand their biological function. Finally, we make the FANTOM-CAT/recount2 atlas available as a public tool to empower other researchers to study important biological and clinical phenotypes and identify new candidate ncRNAs for further investigation. Citation Format: Eddie Luidy-Imada, Tejasvi Matam, Leonardo Collado-Torres, Wikum Dinalankara, Aleksei Stupnikov, Christopher Wilks, Andrew E. Jaffe, Ben Langmead, Jeffrey T. Leek, Alexander Favorov, Luigi Marchionni. Differential analysis of gene expression across the human genome using recount2 and FANTOM-CAT [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr 2297.

Human Enhancers Harboring Specific Sequence Composition, Activity, and Genome Organization Are Linked to the Immune Response.

The FANTOM5 consortium recently characterized 65,423 human enhancers from 1829 cell and tissue samples using the Cap Analysis of Gene Expression technology. We showed that the guanine and cytosine content at enhancer regions distinguishes two classes of enhancers harboring distinct DNA structural properties at flanking regions. A functional analysis of their predicted gene targets highlighted one class of enhancers as significantly enriched for associations with immune response genes. Moreover, these enhancers were specifically enriched for regulatory motifs recognized by transcription factors involved in immune response. We observed that enhancers enriched for links to immune response genes were more cell-type specific, preferentially activated upon bacterial infection, and with specific response activity. Looking at chromatin capture data, we found that the two classes of enhancers were lying in distinct topologically associating domains and chromatin loops. Our results suggest that specific nucleotide compositions encode for classes of enhancers that are functionally distinct and specifically organized in the human genome.

Alternative start and termination sites of transcription drive most transcript isoform differences across human tissues.

Most human genes generate multiple transcript isoforms. The differential expression of these isoforms can help specify cell types. Diverse transcript isoforms arise from the use of alternative transcription start sites, polyadenylation sites and splice sites; however, the relative contribution of these processes to isoform diversity in normal human physiology is unclear. To address this question, we investigated cell type-dependent differences in exon usage of over 18 000 protein-coding genes in 23 cell types from 798 samples of the Genotype-Tissue Expression Project. We found that about half of the expressed genes displayed tissue-dependent transcript isoforms. Alternative transcription start and termination sites, rather than alternative splicing, accounted for the majority of tissue-dependent exon usage. We confirmed the widespread tissue-dependent use of alternative transcription start sites in a second, independent dataset, Cap Analysis of Gene Expression data from the FANTOM consortium. Moreover, our results indicate that most tissue-dependent splicing involves untranslated exons and therefore may not increase proteome complexity. Thus, alternative transcription start and termination sites are the principal drivers of transcript isoform diversity across tissues, and may underlie the majority of cell type specific proteomes and functions.

Highlights of This Issue

Epigenetic cancer drivers represent a widely unexplored territory with a high potential for finding theranostic targets. Horie and colleagues combined the powers of promoter resolution Cap Analysis of Gene Expression (CAGE) data from the FANTOM5 consortium with RNA-seq and DNA-methylation data from The Cancer Genome Atlas (TCGA) project and reported a number of epigenetically regulated genes in non-small cell lung cancer (NSCLC); such genes may complement the known mutational drivers. The data also demonstrate that multiple DNA repeats of the REP522 family are epigenetically activated in NSCLC cells and act as promoters for cancer-specific lncRNAs such as RP1-90G24.10, AL022344.4, and PCAT7.Synonymous mutations do not change a protein sequence but can have wide-ranging effects on protein expression, and evidence indicates that synonymous mutations are enriched in tumors. However, previous studies have generally failed to determine whether these mutations have functional effects. In the current Rapid Impact, Bhagavatula and colleagues develop a massively parallel fluorescence assay to measure the effects of synonymous mutations in exon 6 of the tumor suppressor gene TP53, and identify several mutations that cause decreased protein expression due to splicing defects. This methodology suggests a general framework to assay synonymous mutations for their functional role in oncogenesis.Interferon signaling has been shown to be critical in immune-mediated elimination of early malignancies. Here, Walter and colleagues have identified a novel subset of genes, normally produced during active interferon signaling (interferon-stimulated genes, ISG), to be transcriptionally repressed by the progesterone receptor (PR) in both breast cancer cells and patient specimens. PR modulation of interferon transcriptional machinery and subsequent down-regulation of ISG expression represents a mechanism by which early malignant breast lesions evade immunosurveillance processes and progress to clinically relevant tumors.Inhibition of ciliogenesis is common in breast cancers. In this study, it is demonstrated that inhibition of ciliogenesis leads to earlier tumor formation, faster tumor growth, higher grade tumors, and increased metastasis. Furthermore, it is revealed that inhibition of ciliogenesis results in increased expression of Hedgehog-target genes through cross-talk with the TGF-alpha signaling pathway. Activation of the Hedgehog pathway is most frequently observed in the triple-negative breast cancer (TNBC) subtype and is associated with decreased overall survival. These mechanistic insights into how Hedgehog signaling is activated open the door to novel strategies to treat this aggressive form of breast cancer.

FANTOM5 CAGE profiles of human and mouse reprocessed for GRCh38 and GRCm38 genome assemblies

The FANTOM5 consortium described the promoter-level expression atlas of human and mouse by using CAGE (Cap Analysis of Gene Expression) with single molecule sequencing. In the original publications, GRCh37/hg19 and NCBI37/mm9 assemblies were used as the reference genomes of human and mouse respectively; later, the Genome Reference Consortium released newer genome assemblies GRCh38/hg38 and GRCm38/mm10. To increase the utility of the atlas in forthcoming researches, we reprocessed the data to make them available on the recent genome assemblies. The data include observed frequencies of transcription starting sites (TSSs) based on the realignment of CAGE reads, and TSS peaks that are converted from those based on the previous reference. Annotations of the peak names were also updated based on the latest public databases. The reprocessed results enable us to examine frequencies of transcription initiations on the recent genome assemblies and to refer promoters with updated information across the genome assemblies consistently.