TULIPs decorate the three-dimensional genome of PFA ependymoma.

Posterior fossa group A (PFA) ependymoma is a lethal brain cancer diagnosed in infants and young children. The lack of driver events in the PFA linear genome led us to search its 3D genome for characteristic features. Here, we reconstructed 3D genomes from diverse childhood tumor types and uncovered a global topology in PFA that is highly reminiscent of stem and progenitor cells in a variety of human tissues. A remarkable feature exclusively present in PFA are type B ultra long-range interactions in PFAs (TULIPs), regions separated by great distances along the linear genome that interact with each other in the 3D nuclear space with surprising strength. TULIPs occur in all PFA samples and recur at predictable genomic coordinates, and their formation is induced by expression of EZHIP. The universality of TULIPs across PFA samples suggests a conservation of molecular principles that could be exploited therapeutically.

Genetic Drivers of Epigenetic and Transcriptional Variation in Human Immune Cells.

Characterizing the multifaceted contribution of genetic and epigenetic factors to disease phenotypes is a major challenge in human genetics and medicine. We carried out high-resolution genetic, epigenetic, and transcriptomic profiling in three major human immune cell types (CD14+ monocytes, CD16+ neutrophils, and naive CD4+ T cells) from up to 197 individuals. We assess, quantitatively, the relative contribution of cis-genetic and epigenetic factors to transcription and evaluate their impact as potential sources of confounding in epigenome-wide association studies. Further, we characterize highly coordinated genetic effects on gene expression, methylation, and histone variation through quantitative trait locus (QTL) mapping and allele-specific (AS) analyses. Finally, we demonstrate colocalization of molecular trait QTLs at 345 unique immune disease loci. This expansive, high-resolution atlas of multi-omics changes yields insights into cell-type-specific correlation between diverse genomic inputs, more generalizable correlations between these inputs, and defines molecular events that may underpin complex disease risk.

EpiVar Browser: advanced exploration of epigenomics data under controlled access.

MOTIVATION: Human epigenomic data has been generated by large consortia for thousands of cell types to be used as a reference map of normal and disease chromatin states. Since epigenetic data contains potentially identifiable information, similarly to genetic data, most raw files generated by these consortia are stored in controlled-access databases. It is important to protect identifiable information, but this should not hinder secure sharing of these valuable datasets. RESULTS: Guided by the Framework for responsible sharing of genomic and health-related data from the Global Alliance for Genomics and Health (GA4GH), we have developed an approach and a tool to facilitate the exploration of epigenomics datasets' aggregate results, while filtering out identifiable information. Specifically, the EpiVar Browser allows a user to navigate an epigenetic dataset from a cohort of individuals and enables direct exploration of genotype-chromatin phenotype relationships. Because individual genotypes and epigenetic signal tracks are not directly accessible, and rather aggregated in the portal output, no identifiable data is released, yet the interface allows for dynamic genotype-epigenome interrogation. This approach has the potential to accelerate analyses that would otherwise require a lengthy multi-step approval process and provides a generalizable strategy to facilitate responsible access to sensitive epigenomics data. AVAILABILITY AND IMPLEMENTATION: Online portal: https://computationalgenomics.ca/tools/epivar; EpiVar Browser source code: https://github.com/c3g/epivar-browser; bw-merge-window tool source code: https://github.com/c3g/bw-merge-window.

ZMYM2 is essential for methylation of germline genes and active transposons in embryonic development.

ZMYM2 is a transcriptional repressor whose role in development is largely unexplored. We found that Zmym2-/- mice show embryonic lethality by E10.5. Molecular characterization of Zmym2-/- embryos revealed two distinct defects. First, they fail to undergo DNA methylation and silencing of germline gene promoters, resulting in widespread upregulation of germline genes. Second, they fail to methylate and silence the evolutionarily youngest and most active LINE element subclasses in mice. Zmym2-/- embryos show ubiquitous overexpression of LINE-1 protein as well as aberrant expression of transposon-gene fusion transcripts. ZMYM2 homes to sites of PRC1.6 and TRIM28 complex binding, mediating repression of germline genes and transposons respectively. In the absence of ZMYM2, hypermethylation of histone 3 lysine 4 occurs at target sites, creating a chromatin landscape unfavourable for establishment of DNA methylation. ZMYM2-/- human embryonic stem cells also show aberrant upregulation and demethylation of young LINE elements, indicating a conserved role in repression of active transposons. ZMYM2 is thus an important new factor in DNA methylation patterning in early embryonic development.

Nuclear mTOR acts as a transcriptional integrator of the androgen signaling pathway in prostate cancer.

Androgen receptor (AR) signaling reprograms cellular metabolism to support prostate cancer (PCa) growth and survival. Another key regulator of cellular metabolism is mTOR, a kinase found in diverse protein complexes and cellular localizations, including the nucleus. However, whether nuclear mTOR plays a role in PCa progression and participates in direct transcriptional cross-talk with the AR is unknown. Here, via the intersection of gene expression, genomic, and metabolic studies, we reveal the existence of a nuclear mTOR-AR transcriptional axis integral to the metabolic rewiring of PCa cells. Androgens reprogram mTOR-chromatin associations in an AR-dependent manner in which activation of mTOR-dependent metabolic gene networks is essential for androgen-induced aerobic glycolysis and mitochondrial respiration. In models of castration-resistant PCa cells, mTOR was capable of transcriptionally regulating metabolic gene programs in the absence of androgens, highlighting a potential novel castration resistance mechanism to sustain cell metabolism even without a functional AR. Remarkably, we demonstrate that increased mTOR nuclear localization is indicative of poor prognosis in patients, with the highest levels detected in castration-resistant PCa tumors and metastases. Identification of a functional mTOR targeted multigene signature robustly discriminates between normal prostate tissues, primary tumors, and hormone refractory metastatic samples but is also predictive of cancer recurrence. This study thus underscores a paradigm shift from AR to nuclear mTOR as being the master transcriptional regulator of metabolism in PCa.

Ultrafast functional profiling of RNA-seq data for nonmodel organisms.

Computational time and cost remain a major bottleneck for RNA-seq data analysis of nonmodel organisms without reference genomes. To address this challenge, we have developed Seq2Fun, a novel, all-in-one, ultrafast tool to directly perform functional quantification of RNA-seq reads without transcriptome de novo assembly. The pipeline starts with raw read quality control: sequencing error correction, removing poly(A) tails, and joining overlapped paired-end reads. It then conducts a DNA-to-protein search by translating each read into all possible amino acid fragments and subsequently identifies possible homologous sequences in a well-curated protein database. Finally, the pipeline generates several informative outputs including gene abundance tables, pathway and species hit tables, an HTML report to visualize the results, and an output of clean reads annotated with mapped genes ready for downstream analysis. Seq2Fun does not have any intermediate steps of file writing and loading, making I/O very efficient. Seq2Fun is written in C++ and can run on a personal computer with a limited number of CPUs and memory. It can process >2,000,000 reads/min and is >120 times faster than conventional workflows based on de novo assembly, while maintaining high accuracy in our various test data sets.

RNAget: an API to securely retrieve RNA quantifications.

SUMMARY: Large-scale sharing of genomic quantification data requires standardized access interfaces. In this Global Alliance for Genomics and Health project, we developed RNAget, an API for secure access to genomic quantification data in matrix form. RNAget provides for slicing matrices to extract desired subsets of data and is applicable to all expression matrix-format data, including RNA sequencing and microarrays. Further, it generalizes to quantification matrices of other sequence-based genomics such as ATAC-seq and ChIP-seq. AVAILABILITY AND IMPLEMENTATION: https://ga4gh-rnaseq.github.io/schema/docs/index.html.

Computational tools to unmask transposable elements.

A substantial proportion of the genome of many species is derived from transposable elements (TEs). Moreover, through various self-copying mechanisms, TEs continue to proliferate in the genomes of most species. TEs have contributed numerous regulatory, transcript and protein innovations and have also been linked to disease. However, notwithstanding their demonstrated impact, many genomic studies still exclude them because their repetitive nature results in various analytical complexities. Fortunately, a growing array of methods and software tools are being developed to cater for them. This Review presents a summary of computational resources for TEs and highlights some of the challenges and remaining gaps to perform comprehensive genomic analyses that do not simply 'mask' repeats.

CircRNAome of Childhood Acute Lymphoblastic Leukemia: Deciphering Subtype-Specific Expression Profiles and Involvement in TCF3::PBX1 ALL.

Childhood B-cell acute lymphoblastic leukemia (B-ALL) is a heterogeneous disease comprising multiple molecular subgroups with subtype-specific expression profiles. Recently, a new type of ncRNA, termed circular RNA (circRNA), has emerged as a promising biomarker in cancer, but little is known about their role in childhood B-ALL. Here, through RNA-seq analysis in 105 childhood B-ALL patients comprising six genetic subtypes and seven B-cell controls from two independent cohorts we demonstrated that circRNAs properly stratified B-ALL subtypes. By differential expression analysis of each subtype vs. controls, 156 overexpressed and 134 underexpressed circRNAs were identified consistently in at least one subtype, most of them with subtype-specific expression. TCF3::PBX1 subtype was the one with the highest number of unique and overexpressed circRNAs, and the circRNA signature could effectively discriminate new patients with TCF3::PBX1 subtype from others. Our results indicated that NUDT21, an RNA-binding protein (RBP) involved in circRNA biogenesis, may contribute to this circRNA enrichment in TCF3::PBX1 ALL. Further functional characterization using the CRISPR-Cas13d system demonstrated that circBARD1, overexpressed in TCF3::PBX1 patients and regulated by NUDT21, might be involved in leukemogenesis through the activation of p38 via hsa-miR-153-5p. Our results suggest that circRNAs could play a role in the pathogenesis of childhood B-ALL.

The amino acid sensor GCN2 suppresses terminal oligopyrimidine (TOP) mRNA translation via La-related protein 1 (LARP1).

La-related protein 1 (LARP1) has been identified as a key translational inhibitor of terminal oligopyrimidine (TOP) mRNAs downstream of the nutrient sensing protein kinase complex, mTORC1. LARP1 exerts this inhibitory effect on TOP mRNA translation by binding to the mRNA cap and the adjacent 5'TOP motif, resulting in the displacement of the cap-binding protein eIF4E from TOP mRNAs. However, the involvement of additional signaling pathway in regulating LARP1-mediated inhibition of TOP mRNA translation is largely unexplored. In the present study, we identify a second nutrient sensing kinase GCN2 that converges on LARP1 to control TOP mRNA translation. Using chromatin-immunoprecipitation followed by massive parallel sequencing (ChIP-seq) analysis of activating transcription factor 4 (ATF4), an effector of GCN2 in nutrient stress conditions, in WT and GCN2 KO mouse embryonic fibroblasts, we determined that LARP1 is a GCN2-dependent transcriptional target of ATF4. Moreover, we identified GCN1, a GCN2 activator, participates in a complex with LARP1 on stalled ribosomes, suggesting a role for GCN1 in LARP1-mediated translation inhibition in response to ribosome stalling. Therefore, our data suggest that the GCN2 pathway controls LARP1 activity via two mechanisms: ATF4-dependent transcriptional induction of LARP1 mRNA and GCN1-mediated recruitment of LARP1 to stalled ribosomes.

Genetic variation in the Y chromosome and sex-biased DNA methylation in somatic cells in the mouse.

Several lines of evidence suggest that the presence of the Y chromosome influences DNA methylation of autosomal loci. To better understand the impact of the Y chromosome on autosomal DNA methylation patterns and its contribution to sex bias in methylation, we identified Y chromosome dependent differentially methylated regions (yDMRs) using whole-genome bisulfite sequencing methylation data from livers of mice with different combinations of sex-chromosome complement and gonadal sex. Nearly 90% of the autosomal yDMRs mapped to transposable elements (TEs) and most of them had lower methylation in XY compared to XX or XO mice. Follow-up analyses of four reporter autosomal yDMRs showed that Y-dependent methylation levels were consistent across most somatic tissues but varied in strains with different origins of the Y chromosome, suggesting that genetic variation in the Y chromosome influenced methylation levels of autosomal regions. Mice lacking the q-arm of the Y chromosome (B6.NPYq-2) as well as mice with a loss-of-function mutation in Kdm5d showed no differences in methylation levels compared to wild type mice. In conclusion, the Y-linked modifier of TE methylation is likely to reside on the short arm of Y chromosome and further studies are required to identify this gene.

Integration of external signaling pathways with the core transcriptional network in embryonic stem cells.

Transcription factors (TFs) and their specific interactions with targets are crucial for specifying gene-expression programs. To gain insights into the transcriptional regulatory networks in embryonic stem (ES) cells, we use chromatin immunoprecipitation coupled with ultra-high-throughput DNA sequencing (ChIP-seq) to map the locations of 13 sequence-specific TFs (Nanog, Oct4, STAT3, Smad1, Sox2, Zfx, c-Myc, n-Myc, Klf4, Esrrb, Tcfcp2l1, E2f1, and CTCF) and 2 transcription regulators (p300 and Suz12). These factors are known to play different roles in ES-cell biology as components of the LIF and BMP signaling pathways, self-renewal regulators, and key reprogramming factors. Our study provides insights into the integration of the signaling pathways into the ES-cell-specific transcription circuitries. Intriguingly, we find specific genomic regions extensively targeted by different TFs. Collectively, the comprehensive mapping of TF-binding sites identifies important features of the transcriptional regulatory networks that define ES-cell identity.

Comparing Apples to Apples and Oranges to Oranges.

A new study sequenced and assembled two rodent genomes to better understand the evolutionary forces shaping mammalian genomes. Their results suggest multiple roles for genomic repeats.

Whole Exome Sequencing Reveals the Major Genetic Contributors to Nonsyndromic Tetralogy of Fallot.

RATIONALE: Familial recurrence studies provide strong evidence for a genetic component to the predisposition to sporadic, nonsyndromic Tetralogy of Fallot (TOF), the most common cyanotic congenital heart disease phenotype. Rare genetic variants have been identified as important contributors to the risk of congenital heart disease, but relatively small numbers of TOF cases have been studied to date. OBJECTIVE: We used whole exome sequencing to assess the prevalence of unique, deleterious variants in the largest cohort of nonsyndromic TOF patients reported to date. METHODS AND RESULTS: Eight hundred twenty-nine TOF patients underwent whole exome sequencing. The presence of unique, deleterious variants was determined; defined by their absence in the Genome Aggregation Database and a scaled combined annotation-dependent depletion score of ≥20. The clustering of variants in 2 genes, NOTCH1 and FLT4, surpassed thresholds for genome-wide significance (assigned as P<5×10-8) after correction for multiple comparisons. NOTCH1 was most frequently found to harbor unique, deleterious variants. Thirty-one changes were observed in 37 probands (4.5%; 95% CI, 3.2%-6.1%) and included 7 loss-of-function variants 22 missense variants and 2 in-frame indels. Sanger sequencing of the unaffected parents of 7 cases identified 5 de novo variants. Three NOTCH1 variants (p.G200R, p.C607Y, and p.N1875S) were subjected to functional evaluation, and 2 showed a reduction in Jagged1-induced NOTCH signaling. FLT4 variants were found in 2.4% (95% CI, 1.6%-3.8%) of TOF patients, with 21 patients harboring 22 unique, deleterious variants. The variants identified were distinct to those that cause the congenital lymphoedema syndrome Milroy disease. In addition to NOTCH1, FLT4 and the well-established TOF gene, TBX1, we identified potential association with variants in several other candidates, including RYR1, ZFPM1, CAMTA2, DLX6, and PCM1. CONCLUSIONS: The NOTCH1 locus is the most frequent site of genetic variants predisposing to nonsyndromic TOF, followed by FLT4. Together, variants in these genes are found in almost 7% of TOF patients.

Global characterization of copy number variants in epilepsy patients from whole genome sequencing.

Epilepsy will affect nearly 3% of people at some point during their lifetime. Previous copy number variants (CNVs) studies of epilepsy have used array-based technology and were restricted to the detection of large or exonic events. In contrast, whole-genome sequencing (WGS) has the potential to more comprehensively profile CNVs but existing analytic methods suffer from limited accuracy. We show that this is in part due to the non-uniformity of read coverage, even after intra-sample normalization. To improve on this, we developed PopSV, an algorithm that uses multiple samples to control for technical variation and enables the robust detection of CNVs. Using WGS and PopSV, we performed a comprehensive characterization of CNVs in 198 individuals affected with epilepsy and 301 controls. For both large and small variants, we found an enrichment of rare exonic events in epilepsy patients, especially in genes with predicted loss-of-function intolerance. Notably, this genome-wide survey also revealed an enrichment of rare non-coding CNVs near previously known epilepsy genes. This enrichment was strongest for non-coding CNVs located within 100 Kbp of an epilepsy gene and in regions associated with changes in the gene expression, such as expression QTLs or DNase I hypersensitive sites. Finally, we report on 21 potentially damaging events that could be associated with known or new candidate epilepsy genes. Our results suggest that comprehensive sequence-based profiling of CNVs could help explain a larger fraction of epilepsy cases.

A point mutation in the linker domain of mouse STAT5A is associated with impaired NK-cell regulation.

The transcription factor STAT5 is critical for peripheral NK-cell survival, proliferation, and cytotoxic function. STAT5 refers to two highly related proteins, STAT5A and STAT5B. In this study, we verified the importance of STAT5A isoform for NK cells. We characterized an incidental chemically induced W484G mutation in the Stat5a gene and found that this mutation was associated with a reduction of STAT5A protein expression. Closer examination of NK-cell subsets from Stat5a mutant mice showed marked reductions in NK-cell number and maturation. IL-15 treatment of Stat5a mutant NK cells exhibited defective induction of both STAT5 and mTOR signaling pathways and reduced expression of granzyme B and IFN-γ. Finally, we observed that Stat5a mutant mice revealed more tumor growth upon injection of RMA-S tumor cell line. Overall, our results demonstrate that the W484G mutation in the linker domain of STAT5A is sufficient to compromise STAT5A function in NK-cell homeostasis, responsiveness, and tumoricidal function.

eFORGE v2.0: updated analysis of cell type-specific signal in epigenomic data.

SUMMARY: The Illumina Infinium EPIC BeadChip is a new high-throughput array for DNA methylation analysis, extending the earlier 450k array by over 400 000 new sites. Previously, a method named eFORGE was developed to provide insights into cell type-specific and cell-composition effects for 450k data. Here, we present a significantly updated and improved version of eFORGE that can analyze both EPIC and 450k array data. New features include analysis of chromatin states, transcription factor motifs and DNase I footprints, providing tools for epigenome-wide association study interpretation and epigenome editing. AVAILABILITY AND IMPLEMENTATION: eFORGE v2.0 is implemented as a web tool available from https://eforge.altiusinstitute.org and https://eforge-tf.altiusinstitute.org/. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

The epiGenomic Efficient Correlator (epiGeEC) tool allows fast comparison of user datasets with thousands of public epigenomic datasets.

SUMMARY: In recent years, major initiatives such as the International Human Epigenome Consortium have generated thousands of high-quality genome-wide datasets for a large variety of assays and cell types. This data can be used as a reference to assess whether the signal from a user-provided dataset corresponds to its expected experiment, as well as to help reveal unexpected biological associations. We have developed the epiGenomic Efficient Correlator (epiGeEC) tool to enable genome-wide comparisons of very large numbers of datasets. A public Galaxy implementation of epiGeEC allows comparison of user datasets with thousands of public datasets in a few minutes. AVAILABILITY AND IMPLEMENTATION: The source code is available at https://bitbucket.org/labjacquespe/epigeec and the Galaxy implementation at http://epigeec.genap.ca. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Human copy number variants are enriched in regions of low mappability.

Copy number variants (CNVs) are known to affect a large portion of the human genome and have been implicated in many diseases. Although whole-genome sequencing (WGS) can help identify CNVs, most analytical methods suffer from limited sensitivity and specificity, especially in regions of low mappability. To address this, we use PopSV, a CNV caller that relies on multiple samples to control for technical variation. We demonstrate that our calls are stable across different types of repeat-rich regions and validate the accuracy of our predictions using orthogonal approaches. Applying PopSV to 640 human genomes, we find that low-mappability regions are approximately 5 times more likely to harbor germline CNVs, in stark contrast to the nearly uniform distribution observed for somatic CNVs in 95 cancer genomes. In addition to known enrichments in segmental duplication and near centromeres and telomeres, we also report that CNVs are enriched in specific types of satellite and in some of the most recent families of transposable elements. Finally, using this comprehensive approach, we identify 3455 regions with recurrent CNVs that were missing from existing catalogs. In particular, we identify 347 genes with a novel exonic CNV in low-mappability regions, including 29 genes previously associated with disease.

MetaboAnalyst 4.0: towards more transparent and integrative metabolomics analysis.

We present a new update to MetaboAnalyst (version 4.0) for comprehensive metabolomic data analysis, interpretation, and integration with other omics data. Since the last major update in 2015, MetaboAnalyst has continued to evolve based on user feedback and technological advancements in the field. For this year's update, four new key features have been added to MetaboAnalyst 4.0, including: (1) real-time R command tracking and display coupled with the release of a companion MetaboAnalystR package; (2) a MS Peaks to Pathways module for prediction of pathway activity from untargeted mass spectral data using the mummichog algorithm; (3) a Biomarker Meta-analysis module for robust biomarker identification through the combination of multiple metabolomic datasets and (4) a Network Explorer module for integrative analysis of metabolomics, metagenomics, and/or transcriptomics data. The user interface of MetaboAnalyst 4.0 has been reengineered to provide a more modern look and feel, as well as to give more space and flexibility to introduce new functions. The underlying knowledgebases (compound libraries, metabolite sets, and metabolic pathways) have also been updated based on the latest data from the Human Metabolome Database (HMDB). A Docker image of MetaboAnalyst is also available to facilitate download and local installation of MetaboAnalyst. MetaboAnalyst 4.0 is freely available at http://metaboanalyst.ca.