Systematic assessment of long-read RNA-seq methods for transcript identification and quantification.

The Long-read RNA-Seq Genome Annotation Assessment Project Consortium was formed to evaluate the effectiveness of long-read approaches for transcriptome analysis. Using different protocols and sequencing platforms, the consortium generated over 427 million long-read sequences from complementary DNA and direct RNA datasets, encompassing human, mouse and manatee species. Developers utilized these data to address challenges in transcript isoform detection, quantification and de novo transcript detection. The study revealed that libraries with longer, more accurate sequences produce more accurate transcripts than those with increased read depth, whereas greater read depth improved quantification accuracy. In well-annotated genomes, tools based on reference sequences demonstrated the best performance. Incorporating additional orthogonal data and replicate samples is advised when aiming to detect rare and novel transcripts or using reference-free approaches. This collaborative study offers a benchmark for current practices and provides direction for future method development in transcriptome analysis.

An atlas of combinatorial transcriptional regulation in mouse and man.

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.

Two ovarian candidate enhancers, identified by time series enhancer RNA analyses, harbor rare genetic variations identified in ovarian insufficiency.

The genetic regulation of ovarian development remains largely unclear. Indeed, in most cases of impaired ovarian development-such as 46,XX disorders of sex development (DSD) without SRY, and premature ovarian insufficiency (POI)-the genetic causes have not been identified, and the vast majority of disease-associated sequence variants could lie within non-coding regulatory sequences. In this study, we aimed to identify enhancers of five ovarian genes known to play key roles in early ovarian development, basing our analysis on the expression of enhancer derived transcripts (eRNAs), which are considered to characterize active enhancers. Temporal expression profile changes in mouse WT1-positive ovarian cells were obtained from cap analysis of gene expression at E13.5, E16.5 and P0. We compared the chronological expression profiles of ovarian-specific eRNA with expression profiles for each of the ovarian-specific genes, yielding two candidate sequences for enhancers of Wnt4 and Rspo1. Both sequences are conserved between mouse and human, and we confirmed their enhancer activities using transient expression assays in murine granulosa cells. Furthermore, by sequencing the region in patients with impaired ovarian development in 24 patients, such as POI, gonadal dysgenesis and 46,XX DSD, we identified rare single nucleotide variants in both sequences. Our results demonstrate that combined analysis of the temporal expression profiles of eRNA and mRNA of target genes presents a powerful tool for locating cis-element enhancers, and a means of identifying disease-associated sequence variants that lie within non-coding regulatory sequences, thus advancing an important unmet need in forward human genetics.

Use of clinical variables for preoperative prediction of lymph node metastasis in endometrial cancer.

OBJECTIVE: Endometrial cancer is the most common gynaecological cancer, and most patients are identified during early disease stages. Noninvasive evaluation of lymph node metastasis likely will improve the quality of clinical treatment, for example, by omitting unnecessary lymphadenectomy. METHODS: The study population comprised 611 patients with endometrial cancer who underwent lymphadenectomy at four types of institutions, comprising seven hospitals in total. We systematically assessed the association of 18 preoperative clinical variables with postoperative lymph node metastasis. We then constructed statistical models for preoperative lymph node metastasis prediction and assessed their performance with a previously proposed system, in which the score was determined by counting the number of high-risk variables among the four predefined ones. RESULTS: Of the preoperative 18 variables evaluated, 10 were significantly associated with postoperative lymph node metastasis. A logistic regression model achieved an area under the curve of 0.85 in predicting lymph node metastasis; this value is significantly higher than that from the previous system (area under the curve, 0.74). When we set the false-negative rate to ~1%, the new predictive model increased the rate of true negatives to 21%, compared with 6.8% from the previous one. We also provide a spreadsheet-based tool for further evaluation of its ability to predict lymph node metastasis in endometrial cancer. CONCLUSIONS: Our new lymph node metastasis prediction method, which was based solely on preoperative clinical variables, performed significantly better than the previous method. Although additional evaluation is necessary for its clinical use, our noninvasive system may help improve the clinical treatment of endometrial cancer, complementing minimally invasive sentinel lymph node biopsy.

Comparative transcriptomics of primary cells in vertebrates.

Gene expression profiles in homologous tissues have been observed to be different between species, which may be due to differences between species in the gene expression program in each cell type, but may also reflect differences in cell type composition of each tissue in different species. Here, we compare expression profiles in matching primary cells in human, mouse, rat, dog, and chicken using Cap Analysis Gene Expression (CAGE) and short RNA (sRNA) sequencing data from FANTOM5. While we find that expression profiles of orthologous genes in different species are highly correlated across cell types, in each cell type many genes were differentially expressed between species. Expression of genes with products involved in transcription, RNA processing, and transcriptional regulation was more likely to be conserved, while expression of genes encoding proteins involved in intercellular communication was more likely to have diverged during evolution. Conservation of expression correlated positively with the evolutionary age of genes, suggesting that divergence in expression levels of genes critical for cell function was restricted during evolution. Motif activity analysis showed that both promoters and enhancers are activated by the same transcription factors in different species. An analysis of expression levels of mature miRNAs and of primary miRNAs identified by CAGE revealed that evolutionary old miRNAs are more likely to have conserved expression patterns than young miRNAs. We conclude that key aspects of the regulatory network are conserved, while differential expression of genes involved in cell-to-cell communication may contribute greatly to phenotypic differences between species.

Functional annotation of human long noncoding RNAs via molecular phenotyping.

Long noncoding RNAs (lncRNAs) constitute the majority of transcripts in the mammalian genomes, and yet, their functions remain largely unknown. As part of the FANTOM6 project, we systematically knocked down the expression of 285 lncRNAs in human dermal fibroblasts and quantified cellular growth, morphological changes, and transcriptomic responses using Capped Analysis of Gene Expression (CAGE). Antisense oligonucleotides targeting the same lncRNAs exhibited global concordance, and the molecular phenotype, measured by CAGE, recapitulated the observed cellular phenotypes while providing additional insights on the affected genes and pathways. Here, we disseminate the largest-to-date lncRNA knockdown data set with molecular phenotyping (over 1000 CAGE deep-sequencing libraries) for further exploration and highlight functional roles for ZNF213-AS1 and lnc-KHDC3L-2.

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.

FANTOM enters 20th year: expansion of transcriptomic atlases and functional annotation of non-coding RNAs.

The Functional ANnoTation Of the Mammalian genome (FANTOM) Consortium has continued to provide extensive resources in the pursuit of understanding the transcriptome, and transcriptional regulation, of mammalian genomes for the last 20 years. To share these resources with the research community, the FANTOM web-interfaces and databases are being regularly updated, enhanced and expanded with new data types. In recent years, the FANTOM Consortium's efforts have been mainly focused on creating new non-coding RNA datasets and resources. The existing FANTOM5 human and mouse miRNA atlas was supplemented with rat, dog, and chicken datasets. The sixth (latest) edition of the FANTOM project was launched to assess the function of human long non-coding RNAs (lncRNAs). From its creation until 2020, FANTOM6 has contributed to the research community a large dataset generated from the knock-down of 285 lncRNAs in human dermal fibroblasts; this is followed with extensive expression profiling and cellular phenotyping. Other updates to the FANTOM resource includes the reprocessing of the miRNA and promoter atlases of human, mouse and chicken with the latest reference genome assemblies. To facilitate the use and accessibility of all above resources we further enhanced FANTOM data viewers and web interfaces. The updated FANTOM web resource is publicly available at https://fantom.gsc.riken.jp/.

CREB3L1 overexpression as a potential diagnostic marker of Philadelphia chromosome-negative myeloproliferative neoplasms.

Discrimination of Philadelphia-negative myeloproliferative neoplasms (Ph-MPNs) from reactive hypercytosis and myelofibrosis requires a constellation of testing including driver mutation analysis and bone marrow biopsies. We searched for a biomarker that can more easily distinguish Ph-MPNs from reactive hypercytosis and myelofibrosis by using RNA-seq analysis utilizing platelet-rich plasma (PRP)-derived RNAs from patients with essential thrombocythemia (ET) and reactive thrombocytosis, and CREB3L1 was found to have an extremely high impact in discriminating the two disorders. To validate and further explore the result, expression levels of CREB3L1 in PRP were quantified by reverse-transcription quantitative PCR and compared among patients with ET, other Ph-MPNs, chronic myeloid leukemia (CML), and reactive hypercytosis and myelofibrosis. A CREB3L1 expression cutoff value determined based on PRP of 18 healthy volunteers accurately discriminated 150 driver mutation-positive Ph-MPNs from other entities (71 reactive hypercytosis and myelofibrosis, 6 CML, and 18 healthy volunteers) and showed both sensitivity and specificity of 1.0000. Importantly, CREB3L1 expression levels were significantly higher in ET compared with reactive thrombocytosis (P < .0001), and polycythemia vera compared with reactive erythrocytosis (P < .0001). Pathology-affirmed triple-negative ET (TN-ET) patients were divided into a high- and low-CREB3L1-expression group, and some patients in the low-expression group achieved a spontaneous remission during the clinical course. In conclusion, CREB3L1 analysis has the potential to single-handedly discriminate driver mutation-positive Ph-MPNs from reactive hypercytosis and myelofibrosis, and also may identify a subgroup within TN-ET showing distinct clinical features including spontaneous remission.

APOBEC3B is preferentially expressed at the G2/M phase of cell cycle.

APOBEC3B (A3B) is a cytosine deaminase that converts cytosine to uracil in single-stranded DNA. Cytosine-to-thymine and cytosine-to-guanine base substitution mutations in trinucleotide motifs (APOBEC mutational signatures) were found in various cancers including lymphoid hematological malignancies such as multiple myeloma and A3B has been shown to be an enzymatic source of mutations in those cancers. Although the importance of A3B is being increasingly recognized, it is unclear how A3B expression is regulated in cancer cells as well as normal cells. To answer these fundamental questions, we analyzed 1276 primary myeloma cells using single-cell RNA-sequencing (scRNA-seq) and found that A3B was preferentially expressed at the G2/M phase, in sharp contrast to the expression patterns of other APOBEC3 genes. Consistently, we demonstrated that A3B protein was preferentially expressed at the G2/M phase in myeloma cells by cell sorting. We also demonstrated that normal blood cells expressing A3B were also enriched in G2/M-phase cells by analyzing scRNA-seq data from 86,493 normal bone marrow mononuclear cells. Furthermore, we revealed that A3B was expressed mainly in plasma cells, CD10+ B cells and erythroid cells, but not in granulocyte-macrophage progenitors. A3B expression profiling in normal blood cells may contribute to understanding the defense mechanism of A3B against viruses, and partially explain the bias of APOBEC mutational signatures in lymphoid but not myeloid malignancies. This study identified the cells and cellular phase in which A3B is highly expressed, which may help reveal the mechanisms behind carcinogenesis and cancer heterogeneity, as well as the biological functions of A3B in normal blood cells.

Update of the FANTOM web resource: expansion to provide additional transcriptome atlases.

The FANTOM web resource (http://fantom.gsc.riken.jp/) was developed to provide easy access to the data produced by the FANTOM project. It contains the most complete and comprehensive sets of actively transcribed enhancers and promoters in the human and mouse genomes. We determined the transcription activities of these regulatory elements by CAGE (Cap Analysis of Gene Expression) for both steady and dynamic cellular states in all major and some rare cell types, consecutive stages of differentiation and responses to stimuli. We have expanded the resource by employing different assays, such as RNA-seq, short RNA-seq and a paired-end protocol for CAGE (CAGEscan), to provide new angles to study the transcriptome. That yielded additional atlases of long noncoding RNAs, miRNAs and their promoters. We have also expanded the CAGE analysis to cover rat, dog, chicken, and macaque species for a limited number of cell types. The CAGE data obtained from human and mouse were reprocessed to make them available on the latest genome assemblies. Here, we report the recent updates of both data and interfaces in the FANTOM web resource.

Evaluation of off-target effects of gapmer antisense oligonucleotides using human cells.

Antisense oligonucleotide (ASO) has the potential to induce off-target effects due to complementary binding between the ASO and unintended RNA with a sequence similar to the target RNA. Conventional animal studies cannot be used to assess toxicity induced by off-target effects because of differences in the genome sequence between humans and other animals. Consequently, the assessment of off-target effects with in silico analysis using a human RNA database and/or in vitro expression analysis using human cells has been proposed. Our previous study showed that the number of complementary regions of ASOs with mismatches in the human RNA sequences increases dramatically as the number of tolerated mismatches increases. However, to what extent the expression of genes with mismatches is affected by off-target effects at the cellular level is not clear. In this study, we evaluated off-target effects of gapmer ASOs, which cleave the target RNA in an RNase H-dependent manner, by introducing the ASO into human cells and performing microarray analysis. Our data indicate that gapmer ASOs induce off-target effects depending on the degree of complementarity between the ASO and off-target candidate genes. Based on our results, we also propose a scheme for the assessment of off-target effects of gapmer ASOs.

Systematic analysis of transcription start sites in avian development.

Cap Analysis of Gene Expression (CAGE) in combination with single-molecule sequencing technology allows precision mapping of transcription start sites (TSSs) and genome-wide capture of promoter activities in differentiated and steady state cell populations. Much less is known about whether TSS profiling can characterize diverse and non-steady state cell populations, such as the approximately 400 transitory and heterogeneous cell types that arise during ontogeny of vertebrate animals. To gain such insight, we used the chick model and performed CAGE-based TSS analysis on embryonic samples covering the full 3-week developmental period. In total, 31,863 robust TSS peaks (>1 tag per million [TPM]) were mapped to the latest chicken genome assembly, of which 34% to 46% were active in any given developmental stage. ZENBU, a web-based, open-source platform, was used for interactive data exploration. TSSs of genes critical for lineage differentiation could be precisely mapped and their activities tracked throughout development, suggesting that non-steady state and heterogeneous cell populations are amenable to CAGE-based transcriptional analysis. Our study also uncovered a large set of extremely stable housekeeping TSSs and many novel stage-specific ones. We furthermore demonstrated that TSS mapping could expedite motif-based promoter analysis for regulatory modules associated with stage-specific and housekeeping genes. Finally, using Brachyury as an example, we provide evidence that precise TSS mapping in combination with Clustered Regularly Interspaced Short Palindromic Repeat (CRISPR)-on technology enables us, for the first time, to efficiently target endogenous avian genes for transcriptional activation. Taken together, our results represent the first report of genome-wide TSS mapping in birds and the first systematic developmental TSS analysis in any amniote species (birds and mammals). By facilitating promoter-based molecular analysis and genetic manipulation, our work also underscores the value of avian models in unravelling the complex regulatory mechanism of cell lineage specification during amniote development.

ChIP-Atlas: a data-mining suite powered by full integration of public ChIP-seq data.

We have fully integrated public chromatin chromatin immunoprecipitation sequencing (ChIP-seq) and DNase-seq data (n > 70,000) derived from six representative model organisms (human, mouse, rat, fruit fly, nematode, and budding yeast), and have devised a data-mining platform-designated ChIP-Atlas (http://chip-atlas.org). ChIP-Atlas is able to show alignment and peak-call results for all public ChIP-seq and DNase-seq data archived in the NCBI Sequence Read Archive (SRA), which encompasses data derived from GEO, ArrayExpress, DDBJ, ENCODE, Roadmap Epigenomics, and the scientific literature. All peak-call data are integrated to visualize multiple histone modifications and binding sites of transcriptional regulators (TRs) at given genomic loci. The integrated data can be further analyzed to show TR-gene and TR-TR interactions, as well as to examine enrichment of protein binding for given multiple genomic coordinates or gene names. ChIP-Atlas is superior to other platforms in terms of data number and functionality for data mining across thousands of ChIP-seq experiments, and it provides insight into gene regulatory networks and epigenetic mechanisms.

A promoter-level mammalian expression atlas.

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.

An atlas of active enhancers across human cell types and tissues.

Enhancers control the correct temporal and cell-type-specific activation of gene expression in multicellular eukaryotes. Knowing their properties, regulatory activity and targets is crucial to understand the regulation of differentiation and homeostasis. Here we use the FANTOM5 panel of samples, covering the majority of human tissues and cell types, to produce an atlas of active, in vivo-transcribed enhancers. We show that enhancers share properties with CpG-poor messenger RNA promoters but produce bidirectional, exosome-sensitive, relatively short unspliced RNAs, the generation of which is strongly related to enhancer activity. The atlas is used to compare regulatory programs between different cells at unprecedented depth, to identify disease-associated regulatory single nucleotide polymorphisms, and to classify cell-type-specific and ubiquitous enhancers. We further explore the utility of enhancer redundancy, which explains gene expression strength rather than expression patterns. The online FANTOM5 enhancer atlas represents a unique resource for studies on cell-type-specific enhancers and gene regulation.

Integration of genetics and miRNA-target gene network identified disease biology implicated in tissue specificity.

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.

Analysis of the human monocyte-derived macrophage transcriptome and response to lipopolysaccharide provides new insights into genetic aetiology of inflammatory bowel disease.

The FANTOM5 consortium utilised cap analysis of gene expression (CAGE) to provide an unprecedented insight into transcriptional regulation in human cells and tissues. In the current study, we have used CAGE-based transcriptional profiling on an extended dense time course of the response of human monocyte-derived macrophages grown in macrophage colony-stimulating factor (CSF1) to bacterial lipopolysaccharide (LPS). We propose that this system provides a model for the differentiation and adaptation of monocytes entering the intestinal lamina propria. The response to LPS is shown to be a cascade of successive waves of transient gene expression extending over at least 48 hours, with hundreds of positive and negative regulatory loops. Promoter analysis using motif activity response analysis (MARA) identified some of the transcription factors likely to be responsible for the temporal profile of transcriptional activation. Each LPS-inducible locus was associated with multiple inducible enhancers, and in each case, transient eRNA transcription at multiple sites detected by CAGE preceded the appearance of promoter-associated transcripts. LPS-inducible long non-coding RNAs were commonly associated with clusters of inducible enhancers. We used these data to re-examine the hundreds of loci associated with susceptibility to inflammatory bowel disease (IBD) in genome-wide association studies. Loci associated with IBD were strongly and specifically (relative to rheumatoid arthritis and unrelated traits) enriched for promoters that were regulated in monocyte differentiation or activation. Amongst previously-identified IBD susceptibility loci, the vast majority contained at least one promoter that was regulated in CSF1-dependent monocyte-macrophage transitions and/or in response to LPS. On this basis, we concluded that IBD loci are strongly-enriched for monocyte-specific genes, and identified at least 134 additional candidate genes associated with IBD susceptibility from reanalysis of published GWA studies. We propose that dysregulation of monocyte adaptation to the environment of the gastrointestinal mucosa is the key process leading to inflammatory bowel disease.

Identification of novel cerebellar developmental transcriptional regulators with motif activity analysis.

BACKGROUND: The 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. RESULTS: We 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. CONCLUSIONS: The 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.

Enhanced Identification of Transcriptional Enhancers Provides Mechanistic Insights into Diseases.

Enhancers are distal cis-regulatory DNA elements that increase the expression of target genes. Various experimental and computational approaches including chromatin signature profiling have been developed to predict enhancers on a genome-wide scale, although each method has its advantages and disadvantages. Here we overview an emerging method to identify transcribed enhancers at exceedingly high nucleotide resolution based on enhancer RNA transcripts captured by Cap Analysis of Gene Expression (CAGE) technology. We further argue that disease-causative regulatory mutations at enhancers are increasingly recognized, emphasizing the importance of enhancer identification in functional and clinical genomics including, but not limited to, genome-wide association studies (GWASs) and cancer genomics studies.