A Diagnosis for All Rare Genetic Diseases: The Horizon and the Next Frontiers.

The introduction of exome sequencing in the clinic has sparked tremendous optimism for the future of rare disease diagnosis, and there is exciting opportunity to further leverage these advances. To provide diagnostic clarity to all of these patients, however, there is a critical need for the field to develop and implement strategies to understand the mechanisms underlying all rare diseases and translate these to clinical care.

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.

SAMStat 2: quality control for next generation sequencing data.

MOTIVATION: SAMStat is an efficient program to extract quality control metrics from fastq and SAM/BAM files. A distinguishing feature is that it displays sequence composition, base quality composition and mapping error profiles split by mapping quality. This allows users to rapidly identify reasons for poor mapping including the presence of untrimmed adapters or poor sequencing quality at individual read positions. RESULTS: Here, we present a major update to SAMStat. The new version now supports paired-end and long-read data. Quality control plots are drawn using the ploty javascript library. AVAILABILITY AND IMPLEMENTATION: The source code of SAMStat and code to reproduce the results are found here: https://github.com/timolassmann/samstat.

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.

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.

An expanded phenotype centric benchmark of variant prioritisation tools.

Identifying the causal variant for diagnosis of genetic diseases is challenging when using next-generation sequencing approaches and variant prioritization tools can assist in this task. These tools provide in silico predictions of variant pathogenicity, however they are agnostic to the disease under study. We previously performed a disease-specific benchmark of 24 such tools to assess how they perform in different disease contexts. We found that the tools themselves show large differences in performance, but more importantly that the best tools for variant prioritization are dependent on the disease phenotypes being considered. Here we expand the assessment to 37 tools and refine our assessment by separating performance for nonsynonymous single nucleotide variants (nsSNVs) and missense variants (i.e., excluding nonsense variants). We found differences in performance for missense variants compared to nsSNVs and recommend three tools that stand out in terms of their performance (BayesDel, CADD, and ClinPred).

Zika Virus Changes Methylation of Genes Involved in Immune Response and Neural Development in Brazilian Babies Born With Congenital Microcephaly.

The recent increase in babies born with brain and eye malformations in Brazil is associated with Zika virus (ZIKV) infection in utero. ZIKV alters host DNA methylation in vitro. Using genome-wide DNA methylation profiling we compared 18 babies born with congenital ZIKV microcephaly with 20 controls. We found ZIKV-associated alteration of host methylation patterns, notably at RABGAP1L which is important in brain development, at viral host immunity genes MX1 and ISG15, and in an epigenetic module containing the causal microcephaly gene MCPH1. Our data support the hypothesis that clinical signs of congenital ZIKV are associated with changes in DNA methylation.

Common and Rare Genetic Variants That Could Contribute to Severe Otitis Media in an Australian Aboriginal Population.

BACKGROUND: Our goal was to identify genetic risk factors for severe otitis media (OM) in Aboriginal Australians. METHODS: Illumina® Omni2.5 BeadChip and imputed data were compared between 21 children with severe OM (multiple episodes chronic suppurative OM and/or perforations or tympanic sclerosis) and 370 individuals without this phenotype, followed by FUnctional Mapping and Annotation (FUMA). Exome data filtered for common (EXaC_all ≥ 0.1) putative deleterious variants influencing protein coding (CADD-scaled scores ≥15] were used to compare 15 severe OM cases with 9 mild cases (single episode of acute OM recorded over ≥3 consecutive years). Rare (ExAC_all ≤ 0.01) such variants were filtered for those present only in severe OM. Enrichr was used to determine enrichment of genes contributing to pathways/processes relevant to OM. RESULTS: FUMA analysis identified 2 plausible genetic risk loci for severe OM: NR3C1 (Pimputed_1000G = 3.62 × 10-6) encoding the glucocorticoid receptor, and NREP (Pimputed_1000G = 3.67 × 10-6) encoding neuronal regeneration-related protein. Exome analysis showed: (i) association of severe OM with variants influencing protein coding (CADD-scaled ≥ 15) in a gene-set (GRXCR1, CDH23, LRP2, FAT4, ARSA, EYA4) enriched for Mammalian Phenotype Level 4 abnormal hair cell stereociliary bundle morphology and related phenotypes; (ii) rare variants influencing protein coding only seen in severe OM provided gene-sets enriched for "abnormal ear" (LMNA, CDH23, LRP2, MYO7A, FGFR1), integrin interactions, transforming growth factor signaling, and cell projection phenotypes including hair cell stereociliary bundles and cilium assembly. CONCLUSIONS: This study highlights interacting genes and pathways related to cilium structure and function that may contribute to extreme susceptibility to OM in Aboriginal Australian children.

Kalign 3: multiple sequence alignment of large data sets.

MOTIVATION: Kalign is an efficient multiple sequence alignment (MSA) program capable of aligning thousands of protein or nucleotide sequences. However, current alignment problems involving large numbers of sequences are exceeding Kalign's original design specifications. Here we present a completely re-written and updated version to meet current and future alignment challenges. RESULTS: Kalign now uses a SIMD accelerated version of the bit-parallel Gene Myers algorithm to estimate pariwise distances, adopts a sequence embedding strategy and the bi-secting K-means algorithm to rapidly construct guide trees for thousands of sequences. The new version maintains high alignment accuracy on both protein and nucleotide alignments and scales better than other MSA tools. AVAILABILITY: The source code of Kalign and code to reproduce the results are found here: https://github.com/timolassmann/kalign.

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.

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.

Shared activity patterns arising at genetic susceptibility loci reveal underlying genomic and cellular architecture of human disease.

Genetic variants underlying complex traits, including disease susceptibility, are enriched within the transcriptional regulatory elements, promoters and enhancers. There is emerging evidence that regulatory elements associated with particular traits or diseases share similar patterns of transcriptional activity. Accordingly, shared transcriptional activity (coexpression) may help prioritise loci associated with a given trait, and help to identify underlying biological processes. Using cap analysis of gene expression (CAGE) profiles of promoter- and enhancer-derived RNAs across 1824 human samples, we have analysed coexpression of RNAs originating from trait-associated regulatory regions using a novel quantitative method (network density analysis; NDA). For most traits studied, phenotype-associated variants in regulatory regions were linked to tightly-coexpressed networks that are likely to share important functional characteristics. Coexpression provides a new signal, independent of phenotype association, to enable fine mapping of causative variants. The NDA coexpression approach identifies new genetic variants associated with specific traits, including an association between the regulation of the OCT1 cation transporter and genetic variants underlying circulating cholesterol levels. NDA strongly implicates particular cell types and tissues in disease pathogenesis. For example, distinct groupings of disease-associated regulatory regions implicate two distinct biological processes in the pathogenesis of ulcerative colitis; a further two separate processes are implicated in Crohn's disease. Thus, our functional analysis of genetic predisposition to disease defines new distinct disease endotypes. We predict that patients with a preponderance of susceptibility variants in each group are likely to respond differently to pharmacological therapy. Together, these findings enable a deeper biological understanding of the causal basis of complex traits.

Correction to: Relatively frequent switching of transcription start sites during cerebellar development.

CORRECTION: The authors of the original article [1] would like to recognize the critical contribution of core members of the FANTOM5 Consortium, who played the critical role of HeliScopeCAGE sequencing experiments, quality control of tag reads and processing of the raw sequencing data.

DeepCAGE transcriptomics identify HOXD10 as a transcription factor regulating lymphatic endothelial responses to VEGF-C.

Lymphangiogenesis plays a crucial role during development, in cancer metastasis and in inflammation. Activation of VEGFR-3 (also known as FLT4) by VEGF-C is one of the main drivers of lymphangiogenesis, but the transcriptional events downstream of VEGFR-3 activation are largely unknown. Recently, we identified a wave of immediate early transcription factors that are upregulated in human lymphatic endothelial cells (LECs) within the first 30 to 80 min after VEGFR-3 activation. Expression of these transcription factors must be regulated by additional pre-existing transcription factors that are rapidly activated by VEGFR-3 signaling. Using transcription factor activity analysis, we identified the homeobox transcription factor HOXD10 to be specifically activated at early time points after VEGFR-3 stimulation, and to regulate expression of immediate early transcription factors, including NR4A1. Gain- and loss-of-function studies revealed that HOXD10 is involved in LECs migration and formation of cord-like structures. Furthermore, HOXD10 regulates expression of VE-cadherin, claudin-5 and NOS3 (also known as e-NOS), and promotes lymphatic endothelial permeability. Taken together, these results reveal an important and unanticipated role of HOXD10 in the regulation of VEGFR-3 signaling in lymphatic endothelial cells, and in the control of lymphangiogenesis and permeability.

The frequent evolutionary birth and death of functional promoters in mouse and human.

Promoters are central to the regulation of gene expression. Changes in gene regulation are thought to underlie much of the adaptive diversification between species and phenotypic variation within populations. In contrast to earlier work emphasizing the importance of enhancer evolution and subtle sequence changes at promoters, we show that dramatic changes such as the complete gain and loss (collectively, turnover) of functional promoters are common. Using quantitative measures of transcription initiation in both humans and mice across 52 matched tissues, we discriminate promoter sequence gains from losses and resolve the lineage of changes. We also identify expression divergence and functional turnover between orthologous promoters, finding only the latter is associated with local sequence changes. Promoter turnover has occurred at the majority (>56%) of protein-coding genes since humans and mice diverged. Tissue-restricted promoters are the most evolutionarily volatile where retrotransposition is an important, but not the sole, source of innovation. There is considerable heterogeneity of turnover rates between promoters in different tissues, but the consistency of these in both lineages suggests that the same biological systems are similarly inclined to transcriptional rewiring. The genes affected by promoter turnover show evidence of adaptive evolution. In mice, promoters are primarily lost through deletion of the promoter containing sequence, whereas in humans, many promoters appear to be gradually decaying with weak transcriptional output and relaxed selective constraint. Our results suggest that promoter gain and loss is an important process in the evolutionary rewiring of gene regulation and may be a significant source of phenotypic diversification.

Discovery of Transcription Factors Novel to Mouse Cerebellar Granule Cell Development Through Laser-Capture Microdissection.

Laser-capture microdissection was used to isolate external germinal layer tissue from three developmental periods of mouse cerebellar development: embryonic days 13, 15, and 18. The cerebellar granule cell-enriched mRNA library was generated with next-generation sequencing using the Helicos technology. Our objective was to discover transcriptional regulators that could be important for the development of cerebellar granule cells-the most numerous neuron in the central nervous system. Through differential expression analysis, we have identified 82 differentially expressed transcription factors (TFs) from a total of 1311 differentially expressed genes. In addition, with TF-binding sequence analysis, we have identified 46 TF candidates that could be key regulators responsible for the variation in the granule cell transcriptome between developmental stages. Altogether, we identified 125 potential TFs (82 from differential expression analysis, 46 from motif analysis with 3 overlaps in the two sets). From this gene set, 37 TFs are considered novel due to the lack of previous knowledge about their roles in cerebellar development. The results from transcriptome-wide analyses were validated with existing online databases, qRT-PCR, and in situ hybridization. This study provides an initial insight into the TFs of cerebellar granule cells that might be important for development and provide valuable information for further functional studies on these transcriptional regulators.