Splice_sim: a nucleotide conversion-enabled RNA-seq simulation and evaluation framework.

Nucleotide conversion RNA sequencing techniques interrogate chemical RNA modifications in cellular transcripts, resulting in mismatch-containing reads. Biases in mapping the resulting reads to reference genomes remain poorly understood. We present splice_sim, a splice-aware RNA-seq simulation and evaluation pipeline that introduces user-defined nucleotide conversions at set frequencies, creates mixture models of converted and unconverted reads, and calculates mapping accuracies per genomic annotation. By simulating nucleotide conversion RNA-seq datasets under realistic experimental conditions, including metabolic RNA labeling and RNA bisulfite sequencing, we measure mapping accuracies of state-of-the-art spliced-read mappers for mouse and human transcripts and derive strategies to prevent biases in the data interpretation.

Mime-seq 2.0: a method to sequence microRNAs from specific mouse cell types.

Many microRNAs (miRNAs) are expressed with high spatiotemporal specificity during organismal development, with some being limited to rare cell types, often embedded in complex tissues. Yet, most miRNA profiling efforts remain at the tissue and organ levels. To overcome challenges in accessing the microRNomes from tissue-embedded cells, we had previously developed mime-seq (miRNome by methylation-dependent sequencing), a technique in which cell-specific miRNA methylation in C. elegans and Drosophila enabled chemo-selective sequencing without the need for cell sorting or biochemical purification. Here, we present mime-seq 2.0 for profiling miRNAs from specific mouse cell types. We engineered a chimeric RNA methyltransferase that is tethered to Argonaute protein and efficiently methylates miRNAs at their 3'-terminal 2'-OH in mouse and human cell lines. We also generated a transgenic mouse for conditional expression of this methyltransferase, which can be used to direct methylation of miRNAs in a cell type of choice. We validated the use of this mouse model by profiling miRNAs from B cells and bone marrow plasma cells.

The identification of protein and RNA interactors of the splicing factor Caper in the adult Drosophila nervous system.

Post-transcriptional gene regulation is a fundamental mechanism that helps regulate the development and healthy aging of the nervous system. Mutations that disrupt the function of RNA-binding proteins (RBPs), which regulate post-transcriptional gene regulation, have increasingly been implicated in neurological disorders including amyotrophic lateral sclerosis, Fragile X Syndrome, and spinal muscular atrophy. Interestingly, although the majority of RBPs are expressed widely within diverse tissue types, the nervous system is often particularly sensitive to their dysfunction. It is therefore critical to elucidate how aberrant RNA regulation that results from the dysfunction of ubiquitously expressed RBPs leads to tissue specific pathologies that underlie neurological diseases. The highly conserved RBP and alternative splicing factor Caper is widely expressed throughout development and is required for the development of Drosophila sensory and motor neurons. Furthermore, caper dysfunction results in larval and adult locomotor deficits. Nonetheless, little is known about which proteins interact with Caper, and which RNAs are regulated by Caper. Here we identify proteins that interact with Caper in both neural and muscle tissue, along with neural specific Caper target RNAs. Furthermore, we show that a subset of these Caper-interacting proteins and RNAs genetically interact with caper to regulate Drosophila gravitaxis behavior.

mRNA stability and m6A are major determinants of subcellular mRNA localization in neurons.

For cells to perform their biological functions, they need to adopt specific shapes and form functionally distinct subcellular compartments. This is achieved in part via an asymmetric distribution of mRNAs within cells. Currently, the main model of mRNA localization involves specific sequences called "zipcodes" that direct mRNAs to their proper locations. However, while thousands of mRNAs localize within cells, only a few zipcodes have been identified, suggesting that additional mechanisms contribute to localization. Here, we assess the role of mRNA stability in localization by combining the isolation of the soma and neurites of mouse primary cortical and mESC-derived neurons, SLAM-seq, m6A-RIP-seq, the perturbation of mRNA destabilization mechanisms, and the analysis of multiple mRNA localization datasets. We show that depletion of mRNA destabilization elements, such as m6A, AU-rich elements, and suboptimal codons, functions as a mechanism that mediates the localization of mRNAs associated with housekeeping functions to neurites in several types of neurons.

Hijacking of transcriptional condensates by endogenous retroviruses.

Most endogenous retroviruses (ERVs) in mammals are incapable of retrotransposition; therefore, why ERV derepression is associated with lethality during early development has been a mystery. Here, we report that rapid and selective degradation of the heterochromatin adapter protein TRIM28 triggers dissociation of transcriptional condensates from loci encoding super-enhancer (SE)-driven pluripotency genes and their association with transcribed ERV loci in murine embryonic stem cells. Knockdown of ERV RNAs or forced expression of SE-enriched transcription factors rescued condensate localization at SEs in TRIM28-degraded cells. In a biochemical reconstitution system, ERV RNA facilitated partitioning of RNA polymerase II and the Mediator coactivator into phase-separated droplets. In TRIM28 knockout mouse embryos, single-cell RNA-seq analysis revealed specific depletion of pluripotent lineages. We propose that coding and noncoding nascent RNAs, including those produced by retrotransposons, may facilitate 'hijacking' of transcriptional condensates in various developmental and disease contexts.

GREEN-DB: a framework for the annotation and prioritization of non-coding regulatory variants from whole-genome sequencing data.

Non-coding variants have long been recognized as important contributors to common disease risks, but with the expansion of clinical whole genome sequencing, examples of rare, high-impact non-coding variants are also accumulating. Despite recent advances in the study of regulatory elements and the availability of specialized data collections, the systematic annotation of non-coding variants from genome sequencing remains challenging. Here, we propose a new framework for the prioritization of non-coding regulatory variants that integrates information about regulatory regions with prediction scores and HPO-based prioritization. Firstly, we created a comprehensive collection of annotations for regulatory regions including a database of 2.4 million regulatory elements (GREEN-DB) annotated with controlled gene(s), tissue(s) and associated phenotype(s) where available. Secondly, we calculated a variation constraint metric and showed that constrained regulatory regions associate with disease-associated genes and essential genes from mouse knock-outs. Thirdly, we compared 19 non-coding impact prediction scores providing suggestions for variant prioritization. Finally, we developed a VCF annotation tool (GREEN-VARAN) that can integrate all these elements to annotate variants for their potential regulatory impact. In our evaluation, we show that GREEN-DB can capture previously published disease-associated non-coding variants as well as identify additional candidate disease genes in trio analyses.

Transcriptome-Wide Profiling of RNA Stability.

Gene expression is controlled at multiple levels, including RNA transcription and turnover. But determining the relative contributions of RNA biogenesis and decay to the steady-state abundance of cellular transcripts remains challenging because conventional transcriptomics approaches do not provide the temporal resolution to derive the kinetic parameters underlying steady-state gene expression.Here, we describe a protocol that combines metabolic RNA labeling by 4-thiouridine with chemical nucleoside conversion and whole-transcriptome sequencing followed by bioinformatics analysis to determine RNA stability in cultured cells at a genomic scale. Time-resolved transcriptomics by thiol (SH)-linked alkylation for the metabolic sequencing of RNA (SLAMseq) provides accurate information on transcript half-lives across annotated features in the genome, including by-products of transcription, such as introns. We provide a step-by-step instruction for time-resolved transcriptomics, which enhances traditional RNA sequencing protocols to acquire the temporal resolution required to directly measure the cellular kinetics of RNA turnover under physiological conditions.

Nanopanel2 calls phased low-frequency variants in Nanopore panel sequencing data.

MOTIVATION: Clinical decision making is increasingly guided by accurate and recurrent determination of presence and frequency of (somatic) variants and their haplotype through panel sequencing of disease-relevant genomic regions. Haplotype calling (phasing), however, is difficult and error prone unless variants are located on the same read which limits the ability of short-read sequencing to detect, e.g. co-occurrence of drug-resistance variants. Long-read panel sequencing enables direct phasing of amplicon variants besides having multiple other benefits, however, high error rates of current technologies prevented their applicability in the past. RESULTS: We have developed Nanopanel2, a variant caller for Nanopore panel sequencing data. Nanopanel2 works directly on base-called FAST5 files and uses allele probability distributions and several other filters to robustly separate true from false positive (FP) calls. It effectively calls SNVs and INDELs with variant allele frequencies as low as 1% and 5%, respectively, and produces only few low-frequency false-positive calls (∼1 FP call with VAF<5% per kb amplicon). Haplotype compositions are then determined by direct phasing. Nanopanel2 is the first somatic variant caller for Nanopore data, enabling accurate, fast (turnaround <48 h) and cheap (sequencing costs ∼10$/sample) diagnostic workflows. AVAILABILITYAND IMPLEMENTATION: The data for this study have been deposited at zenodo.org under DOIs accession numbers 4110691 and 4110698. Nanopanel2 is open source and available at https://github.com/popitsch/nanopanel2. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Genomic and transcriptomic correlates of Richter transformation in chronic lymphocytic leukemia.

The transformation of chronic lymphocytic leukemia (CLL) to high-grade B-cell lymphoma is known as Richter syndrome (RS), a rare event with dismal prognosis. In this study, we conducted whole-genome sequencing (WGS) of paired circulating CLL (PB-CLL) and RS biopsies (tissue-RS) from 17 patients recruited into a clinical trial (CHOP-O). We found that tissue-RS was enriched for mutations in poor-risk CLL drivers and genes in the DNA damage response (DDR) pathway. In addition, we identified genomic aberrations not previously implicated in RS, including the protein tyrosine phosphatase receptor (PTPRD) and tumor necrosis factor receptor-associated factor 3 (TRAF3). In the noncoding genome, we discovered activation-induced cytidine deaminase-related and unrelated kataegis in tissue-RS affecting regulatory regions of key immune-regulatory genes. These include BTG2, CXCR4, NFATC1, PAX5, NOTCH-1, SLC44A5, FCRL3, SELL, TNIP2, and TRIM13. Furthermore, differences between the global mutation signatures of pairs of PB-CLL and tissue-RS samples implicate DDR as the dominant mechanism driving transformation. Pathway-based clonal deconvolution analysis showed that genes in the MAPK and DDR pathways demonstrate high clonal-expansion probability. Direct comparison of nodal-CLL and tissue-RS pairs from an independent cohort confirmed differential expression of the same pathways by RNA expression profiling. Our integrated analysis of WGS and RNA expression data significantly extends previous targeted approaches, which were limited by the lack of germline samples, and it facilitates the identification of novel genomic correlates implicated in RS transformation, which could be targeted therapeutically. Our results inform the future selection of investigative agents for a UK clinical platform study. This trial was registered at www.clinicaltrials.gov as #NCT03899337.

Targeting foam cell formation in inflammatory brain diseases by the histone modifier MS-275.

OBJECTIVE: To assess class I-histone deacetylase (HDAC) inhibition on formation of lipid-accumulating, disease-promoting phagocytes upon myelin load in vitro, relevant for neuroinflammatory disorders like multiple sclerosis (MS) and cerebral X-linked adrenoleukodystrophy (X-ALD). METHODS: Immunohistochemistry on postmortem brain tissue of acute MS (n = 6) and cerebral ALD (n = 4) cases to analyze activation and foam cell state of phagocytes. RNA-Seq of in vitro differentiated healthy macrophages (n = 8) after sustained myelin-loading to assess the metabolic shift associated with foam cell formation. RNA-Seq analysis of genes linked to lipid degradation and export in MS-275-treated human HAP1 cells and RT-qPCR analysis of HAP1 cells knocked out for individual members of class I HDACs or the corresponding enzymatically inactive knock-in mutants. Investigation of intracellular lipid/myelin content after MS-275 treatment of myelin-laden human foam cells. Analysis of disease characteristic very long-chain fatty acid (VLCFA) metabolism and inflammatory state in MS-275-treated X-ALD macrophages. RESULTS: Enlarged foam cells coincided with a pro-inflammatory, lesion-promoting phenotype in postmortem tissue of MS and cerebral ALD patients. Healthy in vitro myelin laden foam cells upregulated genes linked to LXRα/PPARγ pathways and mimicked a program associated with tissue repair. Treating these cells with MS-275, amplified this gene transcription program and significantly reduced lipid and cholesterol accumulation and, thus, foam cell formation. In macrophages derived from X-ALD patients, MS-275 improved the disease-associated alterations of VLCFA metabolism and reduced the pro-inflammatory status of these cells. INTERPRETATION: These findings identify class I-HDAC inhibition as a potential novel strategy to prevent disease promoting foam cell formation in CNS inflammation.

Assessment of Pre-Analytical Sample Handling Conditions for Comprehensive Liquid Biopsy Analysis.

Liquid biopsies as a minimally invasive approach have the potential to revolutionize molecular diagnostics. Yet, although protocols for sample handling and the isolation of circulating tumor DNA (ctDNA) are numerous, comprehensive guidelines for diagnostics and research considering all aspects of real-life multicenter clinical studies are currently not available. These include limitations in sample volume, transport, and blood collection tubes. We tested the impact of commonly used (EDTA and heparin) and specialized blood collection tubes and storage conditions on the yield and purity of cell-free DNA for the application in down-stream analysis. Moreover, we evaluated the feasibility of a combined workflow for ctDNA and tumor cell genomic testing and parallel flow cytometric analysis of leukocytes. For genomic analyses, EDTA tubes showed good results if stored for a maximum of 4 hours at room temperature or for up to 24 hours when stored at 4°C. Spike-in experiments revealed that EDTA tubes in combination with density gradient centrifugation allowed the parallel isolation of ctDNA, leukocytes, and low amounts of tumor cells (0.1%) and their immunophenotyping by flow cytometry and down-stream genomic analysis by whole genome sequencing. In conclusion, adhering to time and temperature limits allows the use of routine EDTA blood samples for liquid biopsy analyses. We further provide a workflow enabling the parallel analysis of cell-free and cellular features for disease monitoring and for clonal evolution studies.

A-to-I RNA Editing Uncovers Hidden Signals of Adaptive Genome Evolution in Animals.

In animals, the most common type of RNA editing is the deamination of adenosines (A) into inosines (I). Because inosines basepair with cytosines (C), they are interpreted as guanosines (G) by the cellular machinery and genomically encoded G alleles at edited sites mimic the function of edited RNAs. The contribution of this hardwiring effect on genome evolution remains obscure. We looked for population genomics signatures of adaptive evolution associated with A-to-I RNA edited sites in humans and Drosophila melanogaster. We found that single nucleotide polymorphisms at edited sites occur 3 (humans) to 15 times (Drosophila) more often than at unedited sites, the nucleotide G is virtually the unique alternative allele at edited sites and G alleles segregate at higher frequency at edited sites than at unedited sites. Our study reveals that a significant fraction of coding synonymous and nonsynonymous as well as silent and intergenic A-to-I RNA editing sites are likely adaptive in the distantly related human and Drosophila lineages.

The complete costs of genome sequencing: a microcosting study in cancer and rare diseases from a single center in the United Kingdom.

PURPOSE: The translation of genome sequencing into routine health care has been slow, partly because of concerns about affordability. The aspirational cost of sequencing a genome is $1000, but there is little evidence to support this estimate. We estimate the cost of using genome sequencing in routine clinical care in patients with cancer or rare diseases. METHODS: We performed a microcosting study of Illumina-based genome sequencing in a UK National Health Service laboratory processing 399 samples/year. Cost data were collected for all steps in the sequencing pathway, including bioinformatics analysis and reporting of results. Sensitivity analysis identified key cost drivers. RESULTS: Genome sequencing costs £6841 per cancer case (comprising matched tumor and germline samples) and £7050 per rare disease case (three samples). The consumables used during sequencing are the most expensive component of testing (68-72% of the total cost). Equipment costs are higher for rare disease cases, whereas consumable and staff costs are slightly higher for cancer cases. CONCLUSION: The cost of genome sequencing is underestimated if only sequencing costs are considered, and likely surpasses $1000/genome in a single laboratory. This aspirational sequencing cost will likely only be achieved if consumable costs are considerably reduced and sequencing is performed at scale.

An inhibitor of complement C5 provides structural insights into activation.

The complement system is a crucial part of innate immune defenses against invading pathogens. The blood-meal of the tick Rhipicephalus pulchellus lasts for days, and the tick must therefore rely on inhibitors to counter complement activation. We have identified a class of inhibitors from tick saliva, the CirpT family, and generated detailed structural data revealing their mechanism of action. We show direct binding of a CirpT to complement C5 and have determined the structure of the C5-CirpT complex by cryoelectron microscopy. This reveals an interaction with the peripheral macro globulin domain 4 (C5_MG4) of C5. To achieve higher resolution detail, the structure of the C5_MG4-CirpT complex was solved by X-ray crystallography (at 2.7 Å). We thus present the fold of the CirpT protein family, and provide detailed mechanistic insights into its inhibitory function. Analysis of the binding interface reveals a mechanism of C5 inhibition, and provides information to expand our biological understanding of the activation of C5, and thus the terminal complement pathway.

Sequencing of human genomes with nanopore technology.

Whole-genome sequencing (WGS) is becoming widely used in clinical medicine in diagnostic contexts and to inform treatment choice. Here we evaluate the potential of the Oxford Nanopore Technologies (ONT) MinION long-read sequencer for routine WGS by sequencing the reference sample NA12878 and the genome of an individual with ataxia-pancytopenia syndrome and severe immune dysregulation. We develop and apply a novel reference panel-free analytical method to infer and then exploit phase information which improves single-nucleotide variant (SNV) calling performance from otherwise modest levels. In the clinical sample, we identify and directly phase two non-synonymous de novo variants in SAMD9L, (OMIM #159550) inferring that they lie on the same paternal haplotype. Whilst consensus SNV-calling error rates from ONT data remain substantially higher than those from short-read methods, we demonstrate the substantial benefits of analytical innovation. Ongoing improvements to base-calling and SNV-calling methodology must continue for nanopore sequencing to establish itself as a primary method for clinical WGS.

VARAN-GIE: curation of genomic interval sets.

SUMMARY: Genomic interval sets are fundamental elements of genome annotation and are the output of countless bioinformatics applications. Nevertheless, tool support for the manual curation of these data is currently limited. We developed VARAN-GIE, an extension of the popular Integrative Genomics Viewer (IGV) that adds functionality to edit, annotate and merge genomic interval sets. Data can easily be shared with other users and imported/exported from/to multiple common data formats. AVAILABILITY AND IMPLEMENTATION: VARAN-GIE binary releases, source-code, user guides and tutorials are available at https://github.com/popitsch/varan-gie/.

DeepSNP: An End-to-End Deep Neural Network with Attention-Based Localization for Breakpoint Detection in Single-Nucleotide Polymorphism Array Genomic Data.

Clinical decision-making in cancer and other diseases relies on timely and cost-effective genome-wide testing. Classical bioinformatic algorithms, such as Rawcopy, can support genomic analysis by calling genomic breakpoints and copy-number variations (CNVs), but often require manual data curation, which is error prone, time-consuming, and thus substantially increasing costs of genomic testing and hampering timely delivery of test results to the treating physician. We aimed to investigate whether deep learning algorithms can be used to learn from genome-wide single-nucleotide polymorphism array (SNPa) data and improve state-of-the-art algorithms. We developed, applied, and validated a novel deep neural network (DNN), DeepSNP. A manually curated data set of 50 SNPa analyses was used as truth-set. We show that DeepSNP can learn from SNPa data and classify the presence or absence of genomic breakpoints within large genomic windows with high precision and recall. DeepSNP was compared with well-known neural network models as well as with Rawcopy. Moreover, the use of a localization unit indicates the ability to pinpoint genomic breakpoints despite their exact location not being provided while training. DeepSNP results demonstrate the potential of DNN architectures to learn from genomic SNPa data and encourage further adaptation for CNV detection in SNPa and other genomic data types.

Shep interacts with posttranscriptional regulators to control dendrite morphogenesis in sensory neurons.

RNA binding proteins (RBPs) mediate posttranscriptional gene regulatory events throughout development. During neurogenesis, many RBPs are required for proper dendrite morphogenesis within Drosophila sensory neurons. Despite their fundamental role in neuronal morphogenesis, little is known about the molecular mechanisms in which most RBPs participate during neurogenesis. In Drosophila, alan shepard (shep) encodes a highly conserved RBP that regulates dendrite morphogenesis in sensory neurons. Moreover, the C. elegans ortholog sup-26 has also been implicated in sensory neuron dendrite morphogenesis. Nonetheless, the molecular mechanism by which Shep/SUP-26 regulate dendrite development is not understood. Here we show that Shep interacts with the RBPs Trailer Hitch (Tral), Ypsilon schachtel (Yps), Belle (Bel), and Poly(A)-Binding Protein (PABP), to direct dendrite morphogenesis in Drosophila sensory neurons. Moreover, we identify a conserved set of Shep/SUP-26 target RNAs that include regulators of cell signaling, posttranscriptional gene regulators, and known regulators of dendrite development.

Impaired plasticity of macrophages in X-linked adrenoleukodystrophy.

X-linked adrenoleukodystrophy is caused by ATP-binding cassette transporter D1 (ABCD1) mutations and manifests by default as slowly progressive spinal cord axonopathy with associated demyelination (adrenomyloneuropathy). In 60% of male cases, however, X-linked adrenoleukodystrophy converts to devastating cerebral inflammation and demyelination (cerebral adrenoleukodystrophy) with infiltrating blood-derived monocytes and macrophages and cytotoxic T cells that can only be stopped by allogeneic haematopoietic stem cell transplantation or gene therapy at an early stage of the disease. Recently, we identified monocytes/macrophages but not T cells to be severely affected metabolically by ABCD1 deficiency. Here we found by whole transcriptome analysis that, although monocytes of patients with X-linked adrenoleukodystrophy have normal capacity for macrophage differentiation and phagocytosis, they are pro-inflammatory skewed also in patients with adrenomyloneuropathy in the absence of cerebral inflammation. Following lipopolysaccharide activation, the ingestion of myelin debris, normally triggering anti-inflammatory polarization, did not fully reverse the pro-inflammatory status of X-linked adrenoleukodystrophy macrophages. Immunohistochemistry on post-mortem cerebral adrenoleukodystrophy lesions reflected the activation pattern by prominent presence of enlarged lipid-laden macrophages strongly positive for the pro-inflammatory marker co-stimulatory molecule CD86. Comparative analyses of lesions with matching macrophage density in cases of cerebral adrenoleukodystrophy and acute multiple sclerosis showed a similar extent of pro-inflammatory activation but a striking reduction of anti-inflammatory mannose receptor (CD206) and haemoglobin-haptoglobin receptor (CD163) expression on cerebral adrenoleukodystrophy macrophages. Accordingly, ABCD1-deficiency leads to an impaired plasticity of macrophages that is reflected in incomplete establishment of anti-inflammatory responses, thus possibly contributing to the devastating rapidly progressive demyelination in cerebral adrenoleukodystrophy that only in rare cases arrests spontaneously. These findings emphasize monocytes/macrophages as crucial therapeutic targets for preventing or stopping myelin destruction in patients with X-linked adrenoleukodystrophy.