Biology subjects

Robinson, M. D.

Publications and source records attributed to Robinson, M. D..

At least 55 records · Page 3Linked to original sources

bioRxiv2022

Transformation of alignment files improves performance of variant callers for long-read RNA sequencing data

Long-read RNA sequencing (lrRNA-seq) produces detailed information about full-length transcripts, including novel and sample-specific isoforms. Furthermore, there is opportunity to call variants directly from lrRNA-seq data. However, most state-of-the-art variant callers have been developed for genomic DNA. Here, there are two objectives: first, we perform a mini-benchmark on GATK, DeepVariant, Clair3, and NanoCaller primarily on PacBio Iso-Seq, data, but also on Nanopore and Illumina RNA-seq data; second, we propose a pipeline to process spliced-alignment files, making them suitable for variant calling with DNA-based callers. With such manipulations, high calling performance can be achieved using DeepVariant on Iso-seq data.

bioinformatics↗

bioRxiv2021

Human neural networks with sparse TDP-43 pathology reveal NPTX2 misregulation in ALS/FTLD

Human cellular models of neurodegeneration require reproducibility and longevity, which is necessary for simulating these age-dependent diseases. Such systems are particularly needed for TDP-43 proteinopathies1,2, which involve human-specific mechanisms3-6 that cannot be directly studied in animal models. To explore the emergence and consequences of TDP-43 pathologies, we generated iPSC-derived, colony morphology neural stem cells (iCoMoNSCs) via manual selection of neural precursors7. Single-cell transcriptomics (scRNA-seq) and comparison to independent NSCs8, showed that iCoMoNSCs are uniquely homogenous and self-renewing. Differentiated iCoMoNSCs formed a self-organized multicellular system consisting of synaptically connected and electrophysiologically active neurons, which matured into long-lived functional networks. Neuronal and glial maturation in iCoMoNSC-derived cultures was similar to that of cortical organoids9. Overexpression of wild-type TDP-43 in a minority of iCoMoNSC-derived neurons led to progressive fragmentation and aggregation, resulting in loss of function and neurotoxicity. scRNA-seq revealed a novel set of misregulated RNA targets coinciding in both TDP-43 overexpressing neurons and patient brains exhibiting loss of nuclear TDP-43. The strongest misregulated target encoded for the synaptic protein NPTX2, which was consistently misaccumulated in ALS and FTLD patient neurons with TDP-43 pathology. Our work directly links TDP-43 misregulation and NPTX2 accumulation, thereby highlighting a new pathway of neurotoxicity.

neuroscience↗

bioRxiv2021

Built on sand: the shaky foundations of simulating single-cell RNA sequencing data

With the emergence of hundreds of single-cell RNA-sequencing (scRNA-seq) datasets, the number of computational tools to analyse aspects of the generated data has grown rapidly. As a result, there is a recurring need to demonstrate whether newly developed methods are truly performant - on their own as well as in comparison to existing tools. Benchmark studies aim to consolidate the space of available methods for a given task, and often use simulated data that provide a ground truth for evaluations. Thus, demanding a high quality standard for synthetically generated data is critical to make simulation study results credible and transferable to real data. Here, we evaluated methods for synthetic scRNA-seq data generation in their ability to mimic experimental data. Besides comparing gene- and cell-level quality control summaries in both one- and two-dimensional settings, we further quantified these at the batch- and cluster-level. Secondly, we investigate the effect of simulators on clustering and batch correction method comparisons, and, thirdly, which and to what extent quality control summaries can capture reference-simulation similarity. Our results suggest that most simulators are unable to accommodate complex designs without introducing artificial effects; they yield over-optimistic performance of integration, and potentially unreliable ranking of clustering methods; and, it is generally unknown which summaries are important to ensure effective simulation-based method comparisons.

bioinformatics↗

bioRxiv2021

H3K4me3 enrichment defines neuronal age, while a youthful H3K27ac signature is recapitulated in aged neurons

Neurons live for the lifespan of the individual and underlie our ability for lifelong learning and memory. However, aging alters neuron morphology and function resulting in age-related cognitive decline. It is well established that epigenetic alterations are essential for learning and memory, yet few neuron-specific genome-wide epigenetic maps exist into old age. Comprehensive mapping of H3K4me3 and H3K27ac in mouse neurons across lifespan revealed plastic H3K4me3 marking that differentiates neuronal age linked to known characteristics of cellular and neuronal aging. We determined that neurons in old age recapitulate the H3K27ac enrichment at promoters, enhancers and super enhancers from young adult neurons, likely representing a re-activation of pathways to maintain neuronal output. Finally, this study identified new characteristics of neuronal aging, including altered rDNA regulation and epigenetic regulatory mechanisms. Collectively, these findings indicate a key role for epigenetic regulation in neurons, that is inextricably linked with aging.

molecular biology↗

bioRxiv2021

SampleQC: robust multivariate, multi-celltype, multi-sample quality control for single cell data

Quality control (QC) is a critical component of single-cell RNA-seq (scRNA-seq) processing pipelines. Current approaches to QC implicitly assume that datasets are comprised of one celltype, potentially resulting in biased exclusion of rare celltypes. We introduce SampleQC, which robustly fits a Gaussian mixture model across multiple samples, and improves sensitivity and reduces bias compared to current approaches. We show via simulations that SampleQC is less susceptible to exclusion of rarer celltypes. We also demonstrate SampleQC on a complex real dataset (867k cells over 172 samples). SampleQC is general, is implemented in R, and could be applied to other data types.

bioinformatics↗

bioRxiv2021

Mass Cytometric and Transcriptomic Profiling of Epithelial-Mesenchymal Transitions in Human Mammary Cell Lines

Epithelial-mesenchymal transition (EMT) equips breast cancer cells for metastasis and treatment resistance. Inhibition and elimination of EMT-undergoing cells are therefore promising therapy approaches. However, detecting EMT-undergoing cells is challenging due to the intrinsic heterogeneity of cancer cells and the phenotypic diversity of EMT programs. Here, we profiled EMT transition phenotypes in four non-cancerous human mammary epithelial cell lines using a FACS surface marker screen, RNA sequencing, and mass cytometry. EMT was induced in the HMLE and MCF10A cell lines and in the HMLE-Twist-ER and HMLE-Snail-ER cell lines by chronic exposure to TGF{beta}1 or 4-hydroxytamoxifen, respectively. We observed a spectrum of EMT transition phenotypes in each cell line and the spectrum varied across the time course. Our data provide multiparametric insights at single-cell level into the phenotypic diversity of EMT at different time points and in four human cellular models. These insights are valuable to better understand the complexity of EMT, to compare EMT transitions between the cellular models used herein, and for the design of EMT time course experiments. O_TBL View this table: org.highwire.dtl.DTLVardef@10d2b87org.highwire.dtl.DTLVardef@1a4cc67org.highwire.dtl.DTLVardef@67bc95org.highwire.dtl.DTLVardef@8df40dorg.highwire.dtl.DTLVardef@1919e7c_HPS_FORMAT_FIGEXP M_TBL C_TBL Mendeley Data: DOI: 10.17632/pt3gmyk5r2.1 ArrayExpress Data: Accession number E-MTAB-9365

cell biology↗

bioRxiv2021

Loss of C3aR induces immune infiltration and inflammatory microbiota in a novel spontaneous model of colon cancer

Several lines of evidence suggest that inflammation plays a pivotal role in the development and progression of colorectal cancer (CRC) and can be unleashed by the loss of innate immunosurveillance. The complement system is a well characterized first line of defense against pathogens and a central component of the immune response. Emerging evidence suggests that complement anaphylatoxin C3a produced upon complement activation and acting via its receptor (C3aR) may play a role in intestinal homeostasis. However, to date, it is unknown whether and how the C3a/C3aR axis can affect CRC. By mining publicly available datasets, we found that CpG island methylation of c3ar1 occurs in CRC patients and is associated with significant downregulation of C3aR. By reverse-translating this finding we were able to shift in APCMin/+ mice the tumorigenesis from the small intestine to the colon therefore generating a novel mouse model, which more closely mirrors the CRC in humans. Transcriptomic analysis on colorectal polyps from our newly developed genetic mouse model revealed a significant increase in innate and adaptive immune signatures in absence of C3aR. Furthermore, loss of C3aR significantly impacted the fecal and tumor-associated microbiota and supported the blooming of pro-inflammatory bacterial species as confirmed by experiments of fecal microbiota transplantation. Future studies will elucidate whether loss of C3aR can be exploited as a biomarker for sub-groups of CRC and whether the C3a/C3aR axis may be exploited for the generation of more effective therapeutic interventions.

immunology↗

bioRxiv2020

CellMixS: quantifying and visualizing batch effects in single cell RNA-seq data

A key challenge in single cell RNA-sequencing (scRNA-seq) data analysis are dataset- and batch-specific differences that can obscure the biological signal of interest. While there are various tools and methods to perform data integration and correct for batch effects, their performance can vary between datasets and according to the nature of the bias. Therefore, it is important to understand how batch effects manifest in order to adjust for them in a reliable way. Here, we systematically explore batch effects in a variety of scRNA-seq datasets according to magnitude, cell type specificity and complexity. We developed a cell-specific mixing score (cms) that quantifies how well cells from multiple batches are mixed. By considering distance distributions (in a lower dimensional space), the score is able to detect local batch bias and differentiate between unbalanced batches (i.e., when one cell type is more abundant in a batch) and systematic differences between cells of the same cell type. We implemented cms and related metrics to detect batch effects or measure structure preservation in the CellMixS R/Bioconductor package. We systematically compare different metrics that have been proposed to quantify batch effects or bias in scRNA-seq data using real datasets with known batch effects and synthetic data that mimic various real data scenarios. While these metrics target the same question and are used interchangeably, we find differences in inter- and intra-dataset scalability, sensitivity and in a metrics ability to handle batch effects with differentially abundant cell types. We find that cell-specific metrics outperform cell type-specific and global metrics and recommend them for both method benchmarks and batch exploration.

bioinformatics↗

bioRxiv2020

distinct: a novel approach to differential distribution analyses

We present distinct, a general method for differential analysis of full distributions that is well suited to applications on single-cell data, such as single-cell RNA sequencing and high-dimensional flow or mass cytometry data. High-throughput single-cell data reveal an unprecedented view of cell identity and allow complex variations between conditions to be discovered; nonetheless, most methods for differential expression target differences in the mean and struggle to identify changes where the mean is only marginally affected. distinct is based on a hierarchical non-parametric permutation approach and, by comparing empirical cumulative distribution functions, identifies both differential patterns involving changes in the mean, as well as more subtle variations that do not involve the mean. We performed extensive bench-marks across both simulated and experimental datasets from single-cell RNA sequencing and mass cytometry data, where distinct shows favourable performance, identifies more differential patterns than competitors, and displays good control of false positive and false discovery rates. distinct is available as a Bioconductor R package.

bioinformatics↗

bioRxiv2020

Hand2 delineates mesothelium progenitors and is reactivated in mesothelioma

The mesothelium forms epithelial membranes that line the bodies cavities and surround the internal organs. Mesothelia widely contribute to organ homeostasis and regeneration, and their dysregulation can result in congenital anomalies of the viscera, ventral wall defects, and mesothelioma tumors. Nonetheless, the embryonic ontogeny and developmental regulation of mesothelium formation has remained uncharted. Here, we combine genetic lineage tracing, in toto live imaging, and single-cell transcriptomics in zebrafish to track mesothelial progenitor origins from the lateral plate mesoderm (LPM). Our single-cell analysis uncovers a post-gastrulation gene expression signature centered on hand2 that delineates distinct progenitor populations within the forming LPM. Combining gene expression analysis and imaging of transgenic reporter zebrafish embryos, we chart the origin of mesothelial progenitors to the lateral-most, hand2-expressing LPM and confirm evolutionary conservation in mouse. Our time-lapse imaging of transgenic hand2 reporter embryos captures zebrafish mesothelium formation, documenting the coordinated cell movements that form pericardium and visceral and parietal peritoneum. We establish that the primordial germ cells migrate associated with the forming mesothelium as ventral migration boundary. Functionally, hand2 mutants fail to close the ventral mesothelium due to perturbed migration of mesothelium progenitors. Analyzing mouse and human mesothelioma tumors hypothesized to emerge from transformed mesothelium, we find de novo expression of LPM-associated transcription factors, and in particular of Hand2, indicating the re-initiation of a developmental transcriptional program in mesothelioma. Taken together, our work outlines a genetic and developmental signature of mesothelial origins centered around Hand2, contributing to our understanding of mesothelial pathologies and mesothelioma.

developmental biology↗

bioRxiv2020

A cis-regulatory element promoting increased transcription at low temperature in cultured ectothermic Drosophila cells

Cells of many ectothermic species, including Drosophila melanogaster, maintain homeostatic function within a considerable temperature range. The cellular mechanisms enabling temperature acclimation are still poorly understood. At the transcriptional level, the heat shock response has been extensively analyzed. The opposite has received less attention. Here, using cultured Drosophila cells, we have identified genes with increased transcript levels at the lower end of the readily tolerated temperature range, as well as chromatin regions with increased DNA accessibility. Candidate cis-regulatory elements (CREs) for transcriptional upregulation at low temperature were selected and evaluated with a novel reporter assay for accurate assessment of their temperature-dependency. Robust transcriptional upregulation at low temperature could be demonstrated for a fragment from the pastrel gene, which expresses more transcript and protein at reduced temperatures. The CRE is controlled by the JAK/STAT signaling pathway and antagonizing activities of the transcription factors Pointed and Ets97D.

cell biology↗

bioRxiv2020

Synaptic accumulation of FUS triggers age-dependent misregulation of inhibitory synapses in ALS-FUS mice

FUS is a primarily nuclear RNA-binding protein with important roles in RNA processing and transport. FUS mutations disrupting its nuclear localization characterize a subset of amyotrophic lateral sclerosis (ALS-FUS) patients, through an unidentified pathological mechanism. FUS regulates nuclear RNAs, but its role at the synapse is poorly understood. Here, we used super-resolution imaging to determine the physiological localization of extranuclear, neuronal FUS and found it predominantly near the vesicle reserve pool of presynaptic sites. Using CLIP-seq on synaptoneurosome preparations, we identified synaptic RNA targets of FUS that are associated with synapse organization and plasticity. Synaptic FUS was significantly increased in a knock-in mouse model of ALS-FUS, at presymptomatic stages, accompanied by alterations in density and size of GABAergic synapses. RNA-seq of synaptoneurosomes highlighted age-dependent dysregulation of glutamatergic and GABAergic synapses. Our study indicates that FUS accumulation at the synapse in early stages of ALS-FUS results in synaptic impairment, potentially representing an initial trigger of neurodegeneration.

neuroscience↗

bioRxiv2020

treeclimbR pinpoints the data-dependent resolution of hierarchical hypotheses

The arrangement of hypotheses in a hierarchical structure (e.g., phylogenies, cell types) appears in many research fields and indicates different resolutions at which data can be interpreted. A common goal is to find a representative resolution that gives high sensitivity to identify relevant entities (e.g., microbial taxa or cell subpopulations) that are related to a phenotypic outcome (e.g. disease status) while controlling false detections, therefore providing a more compact view of detected entities and summarizing characteristics shared among them. Current methods, either performing hypothesis tests at an arbitrary resolution or testing hypotheses at all possible resolutions leading to nested results, are suboptimal. Moreover, they are not flexible enough to work in situations where each entity has multiple features to consider and different resolutions might be required for different features. For example, in single cell RNA-seq data, an increasing focus is to find differential state genes that change expression within a cell subpopulation in response to an external stimulus. Such differential expression might occur at different resolutions (e.g., all cells or a small set of cells) for different genes. Our new algorithm treeclimbR is designed to fill this gap by exploiting a hierarchical tree of entities, proposing multiple candidates that capture the latent signal and pinpointing branches or leaves that contain features of interest, in a data-driven way. It outperforms currently available methods on synthetic data, and we highlight the approach on various applications, including microbiome and microRNA surveys as well as single cell cytometry and RNA-seq datasets. With the emergence of various multi-resolution genomic datasets, treeclimbR provides a thorough inspection on entities across resolutions and gives additional flexibility to uncover biological associations.

bioinformatics↗

bioRxiv2020

pipeComp, a general framework for the evaluation of computational pipelines, reveals performant single-cell RNA-seq preprocessing tools

The massive growth of single-cell RNA-sequencing (scRNAseq) and the methods for its analysis still lack sufficient and up-to-date benchmarks that could guide analytical choices. Numerous benchmark studies already exist and cover most of scRNAseq processing and analytical methods but only a few give advice on a comprehensive pipeline. Moreover, current studies often focused on isolated steps of the process and do not address the impact of a tool on both the intermediate and the final steps of the analysis. Here, we present a flexible R framework for pipeline comparison with multi-level evaluation metrics. We apply it to the benchmark of scRNAseq analysis pipelines using simulated and real datasets with known cell identities, covering common methods of filtering, doublet detection, normalization, feature selection, denoising, dimensionality reduction and clustering. We evaluate the choice of these tools with multi-purpose metrics to assess their ability to reveal cell population structure and lead to efficient clustering. On the basis of our systematic evaluations of analysis pipelines, we make a number of practical recommendations about current analysis choices and for a comprehensive pipeline. The evaluation framework that we developed, pipeComp (https://github.com/plger/pipeComp), has been implemented so as to easily integrate any other step, tool, or evaluation metric allowing extensible benchmarks and easy applications to other fields of research in Bioinformatics, as we demonstrate through a study of the impact of removal of unwanted variation on differential expression analysis.

bioinformatics↗

bioRxiv2019

DAMEfinder: A Method to Detect Differential Allele-Specific Methylation

DNA methylation is a highly studied epigenetic signature that is associated with regulation of gene expression, whereby genes with high levels of promoter methylation are generally repressed. Genomic imprinting occurs when one of the parental alleles is methylated, i.e, when there is inherited allele-specific methylation (ASM). A special case of imprinting occurs during X chromosome inactivation in females, where one of the two X chromosomes is silenced, in order to achieve dosage compensation between the sexes. Another more widespread form of ASM is sequence dependent (SD-ASM), where ASM is linked to a nearby heterozygous single nucleotide polymorphism (SNP).\n\nWe developed a method to screen for genomic regions that exhibit loss or gain of ASM in samples from two conditions (treatments, diseases, etc.). The method relies on the availability of bisulfite sequencing data from multiple samples of the two conditions. We leverage other established computational methods to screen for these regions within a new R package called DAMEfinder. It calculates an ASM score for all CpG sites or pairs in the genome of each sample, and then quantifies the change in ASM between conditions. It then clusters nearby CpG sites with consistent change into regions.\n\nIn the absence of SNP information, our method relies only on reads to quantify ASM. This novel ASM score compares favourably to current methods that also screen for ASM. Not only does it easily discern between imprinted and non-imprinted regions, but also females from males based on X chromosome inactivation. We also applied DAMEfinder to a colorectal cancer dataset and observed that colorectal cancer subtypes are distinguishable according to their ASM signature. We also re-discover known cases of loss of imprinting.\n\nWe have designed DAMEfinder to detect regions of differential ASM (DAMEs), which is a more refined definition of differential methylation, and can therefore help in breaking down the complexity of DNA methylation and its influence in development and disease.

bioinformatics↗

bioRxiv2019

A comprehensive examination of Nanopore native RNA sequencing for characterization of complex transcriptomes

A platform for highly parallel direct sequencing of native RNA strands was recently described by Oxford Nanopore Technologies (ONT); in order to assess overall performance in transcript-level investigations, the technology was applied for sequencing sets of synthetic transcripts as well as a yeast transcriptome. However, despite initial efforts it remains crucial to further investigate characteristics of ONT native RNA sequencing when applied to much more complex transcriptomes. Here we thus undertook extensive native RNA sequencing of polyA+ RNA from two human cell lines, and thereby analysed ~5.2 million aligned native RNA reads which consisted of a total of ~4.6 billion bases. To enable informative comparisons, we also performed relevant ONT direct cDNA- and Illumina-sequencing. We find that while native RNA sequencing does enable some of the anticipated advantages, key unexpected aspects hamper its performance, most notably the quite frequent inability to obtain full-length transcripts from single reads, as well as difficulties to unambiguously infer their true transcript of origin. While characterising issues that need to be addressed when investigating more complex transcriptomes, our study highlights that with some defined improvements, native RNA sequencing could be an important addition to the mammalian transcriptomics toolbox.

bioinformatics↗

bioRxiv2019

TNFR2 induced priming of NLRP3-inflammasome via RIPK1 leads to pyroptosis in XIAP deficient cells

Recent data suggests that LPS stimulation can trigger inflammasome activation through a TNFR2/TNF/TNFR1 mediated loop in xiap-/- macrophages. Yet, the direct role TNFR2-specific activation plays in the absence of XIAP is unknown. We found TNFR2-specific activation lead to cell death in xiap-/- myeloid cells, particularly in the absence the RING domain. RIPK1/TAK1 kinase activity downstream of TNFR2 resulted in a TNF/TNFR1 cell death independent of necroptosis. TNFR2-specific activation lead to a similar inflammatory NF-kB driven transcriptional profile as TNFR1 activation with the exception of up-regulation of NLRP3 and caspase-11. Activation and up-regulation of the canonical inflammasome was mediated by RIPK1 kinase activity and ROS production. While both RIPK1 kinase activity and ROS production reduced cell death as well as release of IL-1{beta}, the release of IL-18 was not reduced to basal levels. This study supports, targeting TNFR2 specifically to reduce IL-18 release in XIAP deficient (XLP-2) patients.

immunology↗

bioRxiv2019

Maleness-on-the-Y (MoY) orchestrates male sex determination in major agricultural fruit fly pests

In insects, rapidly evolving primary sex-determining signals are transduced by a conserved regulatory module producing sex-specific proteins that direct sex determination and sexual differentiation1-4. In the agricultural pest Ceratitis capitata (medfly), a Y-linked maleness factor (M) is thought to repress the autoregulatory splicing of transformer (Cctra), which is required in XX individuals to establish and maintain female sex determination5,6. Despite previous attempts of isolating Y-linked genes using the medfly whole genome, the M factor has remained elusive7. Here, we report the identification of a Y-linked gene, Maleness-on the-Y (MoY), and show that it encodes a small novel protein which is both necessary and sufficient for medfly male sex determination. Transient silencing of MoY in XY individuals leads to the development of fertile females while transient expression of MoY in XX individuals results in fertile males. Notably, a cross between these sex reverted individuals gives rise to both fertile males and females indicating that a functional MoY can be maternally transmitted. In contrast to the diversity of M factors found in dipteran species8-11, we discovered MoY orthologues in seven other Tephritid species spanning [~]111 millions of years of evolution (Mya). We confirmed their male determining function in the olive fly (Bactrocera oleae) and the oriental fruit fly (Bactrocera dorsalis). This unexpected conservation of the primary MoY signal in a large number of important agricultural pests12 will facilitate the development of transferable genetic control strategies in these species, for example sterile male releases or sex-ratio-distorting gene drives.

genetics↗