Biology subjects

Ritchie, M. E.

Publications and source records attributed to Ritchie, M. E..

At least 55 records · Page 3Linked to original sources

bioRxiv2022

NAb-seq: an accurate, rapid and cost-effective method for antibody long-read sequencing in hybridoma cell lines and single B cells

Despite their common use in research, monoclonal antibodies are currently not systematically sequenced. This can lead to issues with reproducibility and the occasional loss of antibodies with loss of cell lines. Hybridoma cell lines have been the primary means of generating monoclonal antibodies from immunized animals including mice, rats, rabbits and alpacas. Excluding therapeutic antibodies, few hybridoma-derived antibody sequences are known. Sanger sequencing has been "the gold standard" for antibody gene sequencing but relies on the availability of species-specific degenerate primer sets for amplification of light and heavy antibody genes, in addition to lengthy and expensive cDNA preparation. Here we leveraged recent improvements in long-read Oxford Nanopore Technologies (ONT) sequencing to develop NAb-seq: a three-day, species-independent, and cost-effective workflow to characterize paired full-length immunoglobulin light and heavy chain genes from hybridoma cell lines. When compared to Sanger sequencing of two hybridoma cell lines, long-read ONT sequencing was highly accurate, reliable, and amenable to high throughput. We further show that the method is applicable to single cells, allowing efficient antibody discovery in rare populations such as memory B cells. In summary, NAb-seq promises to accelerate identification and validation of hybridoma antibodies as well as antibodies from single B cells used in research, diagnostics and therapeutics.

bioinformatics↗

bioRxiv2022

Arginine-rich C9ORF72 ALS proteins stall ribosomes in a manner distinct from a canonical ribosome-associated quality control substrate

Hexanucleotide expansion mutations in C9ORF72 are a cause of familial amyotrophic lateral sclerosis. We previously reported that long arginine-rich dipeptide repeats (DPR), mimicking abnormal proteins expressed from the hexanucleotide expansion, caused translation stalling when expressed in cell culture models. Whether this stalling provides a mechanism of pathogenicity remains to be determined. Here we explored the molecular features of DPR-induced stalling and examined whether known regulatory mechanisms of ribosome quality control (RQC) are involved to sense and resolve the stalls. We demonstrate that arginine-containing DPRs lead to stalling in a length dependent manner, with lengths longer than 40 repeats invoking severe translation arrest. Mutational screening of 40xGly-Xxx DPRs shows that stalling is most pronounced where Xxx are positively charged amino acids (Arg or Lys). Through a genome-wide knockout screen we find that genes regulating stalling on polyadenosine mRNA coding for poly-Lys, a canonical RQC substrate, respond differently to the readthrough of arginine-rich DPRs. Indeed, we find evidence that DPR-mediated stalling has no natural regulatory responses even though the stalls may be sensed, as evidenced by an upregulation of RQC gene expression. These findings therefore implicate arginine-rich DPR-mediated stalled ribosomes as posing a particular danger to cellular health and viability.

biochemistry↗

bioRxiv2021

Maternal SMCHD1 controls both imprinted Xist expression and imprinted X chromosome inactivation

Embryonic development is dependent on the maternal supply of proteins through the oocyte, including factors setting up the adequate epigenetic patterning of the zygotic genome. We previously reported that one such factor is the epigenetic repressor SMCHD1, whose maternal supply controls autosomal imprinted expression in mouse preimplantation embryos and mid-gestation placenta. In mouse preimplantation embryos, X chromosome inactivation is also an imprinted process. Combining genomics and imaging, we show that maternal SMCHD1 is required not only for the imprinted expression of Xist in preimplantation embryos, but also for the efficient silencing of the inactive X in both the preimplantation embryo and mid-gestation placenta. These results expand the role of SMCHD1 in enforcing the silencing of Polycomb targets. The inability of zygotic SMCHD1 to fully restore imprinted X inactivation further points to maternal SMCHD1s role in setting up the appropriate chromatin environment during preimplantation development, a critical window of epigenetic remodelling.

genomics↗

bioRxiv2021

Large herbivore impact on plant biomass along multiple resource gradients in the Serengeti

Herbivores form an important link in the transfer of energy within a food web and are strongly influenced by bottom-up trophic cascades. Current hypotheses suggest that herbivore consumption and impact on plants should scale positively with plant resource availability. However, depending on the effect of resources on plant quantity and quality, herbivore impact may vary with different types of resources. We test four alternative hypotheses for the relationship between plant biomass, herbivore impact on plant biomass, and plant resource gradients, each based on how resources might affect plant abundance and quality to herbivores. We measured plant biomass for four non-consecutive years in a long-term grazing exclosure experiment in the Serengeti National Park that includes seven sites that vary substantially in rainfall and soil and plant nitrogen (N) and phosphorus (P). Our data supported the hypothesis that herbivore impact is controlled by plant quality, in this case driven by plant P, as herbivore effects on biomass decreased with higher rainfall but increased with greater plant P, but not N content. To our knowledge, this is the first experimental study to indicate that wild mammalian herbivory is associated with P availability rather than N. Our results suggest that P, in addition to water and N, may play a more important role in driving trophic interactions in terrestrial systems than previously realized.

ecology↗

bioRxiv2021

Dashboard-style interactive plots for RNA-seq analysis are R Markdown ready with Glimma 2.0

Glimma 1.0 introduced intuitive, point-and-click interactive graphics for differential gene expression analysis. Here, we present a major update to Glimma which brings improved inter-activity and reproducibility using high-level visualisation frame-works for R and JavaScript. Glimma 2.0 plots are now readily embeddable in R Markdown, thus allowing users to create reproducible reports containing interactive graphics. The revamped multidimensional scaling plot features dashboard-style controls allowing the user to dynamically change the colour, shape and size of sample points according to different experimental conditions. Interactivity was enhanced in the MA-style plot for comparing differences to average expression, which now supports selecting multiple genes, export options to PNG, SVG or CSV formats and includes a new volcano plot function. Feature-rich and user-friendly, Glimma makes exploring data for gene expression analysis more accessible and intuitive and is available on Bioconductor and GitHub.

bioinformatics↗

bioRxiv2021

Benchmarking UMI-based single cell RNA-sequencing preprocessing workflows

Single-cell RNA sequencing (scRNA-seq) technologies and associated analysis methods have undergone rapid development in recent years. This includes methods for data preprocessing, which assign sequencing reads to genes to create count matrices for downstream analysis. Several packaged preprocessing workflows have been developed that aim to provide users with convenient tools for handling this process. How different preprocessing workflows compare to one another and influence downstream analysis has been less well studied. Here, we systematically benchmark the performance of 9 end-to-end preprocessing workflows (Cell Ranger, Optimus, salmon alevin, kallisto bustools, dropSeqPipe, scPipe, zUMIs, celseq2 and scruff) using datasets with varying levels of biological complexity generated on the CEL-Seq2 and 10x Chromium platforms. We compare these workflows in terms of their quantification properties directly and their impact on normalization and clustering by evaluating the performance of different method combinations. We find that lowly expressed genes are discordant between workflows and observe that some workflows have systematic biases towards particular classes of genomics features. While the scRNA-seq preprocessing workflows compared varied in their detection and quantification of genes across datasets, after downstream analysis with performant normalization and clustering methods, almost all combinations produced clustering results that agreed well with the known cell type labels that provided the ground truth in our analysis. In summary, the choice of preprocessing method was found to be less influential than other steps in the scRNA-seq analysis process. Our study comprehensively compares common scRNA-seq preprocessing workflows and summarizes their characteristics to guide workflow users.

bioinformatics↗

bioRxiv2021

SMCHD1 has separable roles in chromatin architecture and gene silencing that could be targeted in disease

The interplay between 3D chromatin architecture and gene silencing is incompletely understood. Here, we report a novel point mutation in the non-canonical SMC protein SMCHD1 that enhances its silencing capacity at endogenous developmental targets and at the facioscapulohumeral muscular dystrophy associated macro-array, D4Z4. Heightened SMCHD1 silencing perturbs developmental Hox gene activation, causing a homeotic transformation in mice. Paradoxically, the mutant SMCHD1 appears to enhance insulation against another epigenetic regulator complex, PRC2, while depleting long range chromatin interactions akin to what is observed in the absence of SMCHD1. These data suggest that SMCHD1s role in long range chromatin interactions is not directly linked to gene silencing or insulating the chromatin, refining the model for how the different levels of SMCHD1-mediated chromatin regulation interact to bring about gene silencing in normal development and disease.

molecular biology↗

bioRxiv2021

NanoMethViz: an R/Bioconductor package for visualizing long-read methylation data

MotivationA key benefit of long-read nanopore sequencing technology is the ability to detect modified DNA bases, such as 5-methylcytosine. Tools for effective visualization of data generated by this platform to assess changes in methylation profiles between samples from different experimental groups remains a challenge. ResultsTo make visualization of methylation changes more straightforward, we developed the R/Bioconductor package NanoMethViz. Our software can handle methylation calls generated from a range of different methylation callers and manages large datasets using a compressed data format. To fully explore the methylation patterns in a dataset, NanoMethViz allows plotting of data at various resolutions. At the sample-level, we use multidimensional scaling to look at the relationships between methylation profiles in an unsupervised way. We visualize methylation profiles of classes of features such as genes or CpG islands by scaling them to relative positions and aggregating their profiles. At the finest resolution, we visualize methylation patterns across individual reads along the genome using the spaghetti plot, allowing users to explore particular genes or genomic regions of interest. In summary, our software makes the handling of methylation signal more convenient, expands upon the visualization options for nanopore data and works seamlessly with existing methylation analysis tools available in the Bioconductor project. Our software is available at https://bioconductor.org/packages/NanoMethViz.

bioinformatics↗

bioRxiv2020

Comprehensive characterization of single cell full-length isoforms in human and mouse with long-read sequencing

Alternative splicing shapes the phenotype of cells in development and disease. Long-read RNA-sequencing recovers full-length transcripts but has limited throughput at the single-cell level. Here we developed single-cell full-length transcript sequencing by sampling (FLT-seq), together with the computational pipeline FLAMES to overcome these issues and perform isoform discovery and quantification, splicing analysis and mutation detection in single cells. With FLT-seq and FLAMES, we performed the first comprehensive characterization of the full-length isoform landscape in single cells of different types and species and identified thousands of unannotated isoforms. We found conserved functional modules that were enriched for alternative transcript usage in different cell populations, including ribosome biogenesis and mRNA splicing. Analysis at the transcript-level allowed data integration with scATAC-seq on individual promoters, improved correlation with protein expression data and linked mutations known to confer drug resistance to transcriptome heterogeneity. Our methods reveal previously unseen isoform complexity and provide a better framework for multi-omics data integration.

genomics↗

bioRxiv2020

The long and the short of it: unlocking nanopore long-read RNA sequencing data with short-read tools

Application of Oxford Nanopore Technologies long-read sequencing platform to transcriptomic analysis is increasing in popularity. However, such analysis can be challenging due to small library sizes and high sequence error, which decreases quantification accuracy and reduces power for statistical testing. Here, we report the analysis of two nanopore sequencing RNA-seq datasets with the goal of obtaining gene-level and isoform-level differential expression information. A dataset of synthetic, spliced, spike-in RNAs ("sequins") as well as a mouse neural stem cell dataset from samples with a null mutation of the epigenetic regulator Smchd1 were analysed using a mix of long-read specific tools for preprocessing together with established short-read RNA-seq methods. We used limma-voom to perform differential gene expression analysis, and the novel FLAMES pipeline to perform isoform identification and quantification, followed by DRIMSeq and limma-diffSplice (with stageR) to perform differential transcript usage analysis. We compared results from the sequins dataset to the ground truth, and results of the mouse dataset to a previous short-read study on equivalent samples. Overall, our work shows that transcriptomic analysis of long-read nanopore data using short-read software and methods that are already in wide use can yield meaningful results.

bioinformatics↗

bioRxiv2020

A burning question: Can natural climate solutions and carbon financing save the lion from extinction?

Lions (Panthera leo) in Africa have lost nearly half their population in just the last two decades, and effective management of the protected areas (PAs) where lions live will cost an estimated USD >$1 B/year in new funding. We explore the potential for launching a fire management and habitat restoration carbon-financing program to help fill this PA management funding gap. We demonstrate how introducing early dry season fire management programs could produce potential carbon revenues (PCR) from either a single carbon-financing method (avoided emissions) or from multiple sequestration methods of USD $59.6-$655.9 M/year (at USD $5/ton) or USD $155.0 M-$1.7 B/year (at USD $13/ton). We highlight variable but significant PCR for PAs with the greatest potential for restoring lion numbers between USD $1.5-$44.4 M per PA. We suggest investing in lion-centric fire management programs to jump-start the United Nations Decade of Ecological Restoration and help preserve African lions across their range. SCIENCE FOR SOCIETYThe United Nations recently launched the Decade of Ecological Restoration in response to planet-wide land degradation. This study analyses the potential for savanna fire management programs to restore fire regimes that can generate new sources of revenue from carbon financing for chronically under-funded protected areas in Africa with lions, as lions are a key indicator of savanna ecosystem health. We estimated the amount of carbon saved by shifting fires that normally burn in the late dry season (and emit more carbon) to the early dry season (that accrue more carbon in the soil and woody vegetation). Based on current carbon market values we found substantial potential to eliminate or significantly reduce the $>1B annual funding gap needed to save the lion from extinction. Given additional benefits for nature and people from new savanna fire programs, we recommend integrated conservation and development projects direct more funding to some of the least developed countries with high biodiversity and support fire management programs in Africa.

ecology↗

bioRxiv2020

The clonal and molecular aetiology of emergency dendritic cell development

Extrinsic regulation of single haematopoietic stem and progenitor cell (HSPC) fate is crucial for immune cell development. Here, we examine the aetiology of Flt3 ligand (Flt3L)-mediated emergency development of type 1 conventional dendritic cells (cDC1s), which results in enhanced immunity against infections and cancer. Using cellular barcoding, we demonstrate a predominant role of enhanced clonal expansion and moderate contribution via recruitment of additional cDC1-generating HSPCs. The selective cDC1 expansion occurs primarily via multi-/oligo-potent clones, without compromising output to other lineages. To understand the molecular hallmarks early during a Flt3L response, we develop Divi-Seq to simultaneously profile cell division history, surface phenotype and transcriptional state of single HSPCs. We discover that Flt3L-responsive HSPCs maintain a proliferative early progenitor-like state, which leads to selective emergence of CD11c+cKit+ transitional precursors with high cellular output to cDC1s. These findings inform the mechanistic action of Flt3L in natural immunity and immunotherapy at a clonal level.

immunology↗

bioRxiv2020

Smchd1 is a maternal effect gene required for autosomal imprinting

Genomic imprinting establishes parental allele-biased expression of a suite of mammalian genes based on parent-of-origin specific epigenetic marks. These marks are under the control of maternal effect proteins supplied in the oocyte. Here we report the epigenetic repressor Smchd1 as a novel maternal effect gene that regulates imprinted expression of 16 genes. Most Smchd1-sensitive genes only show loss of imprinting post-implantation, indicating maternal Smchd1s long-lived epigenetic effect. Sm-chd1-sensitive genes include both those controlled by germline polycomb marks and germline DNA methylation imprints; however, Smchd1 differs to other maternal effect genes that regulate the latter group, as Smchd1 does not affect germline DNA methylation imprints. Instead, Smchd1-sensitive genes are united by their reliance on polycomb-mediated histone methylation marks as germline or secondary imprints. We propose that Smchd1 translates these imprints to establish a heritable chromatin state required for imprinted expression later in development, revealing a new mechanism for maternal effect genes.

genomics↗

bioRxiv2019

Xmas ESC: A new female embryonic stem cell system that reveals the BAF complex as a key regulator of the establishment of X chromosome inactivation

Although female pluripotency significantly differs to male, complications with in vitro culture of female embryonic stem cells (ESC) have severely limited the use and study of these cells. We report a replenishable female ESC system, Xmas, that has enabled us to optimise a protocol for preserving the XX karyotype. Our protocol also improves male ESC fitness. We utilised our Xmas ESC system to screen for regulators of the female-specific process of X chromosome inactivation, revealing chromatin remodellers Smarcc1 and Smarca4 as key regulators of establishment of X inactivation. The remodellers create a nucleosome depleted region at gene promotors on the inactive X during exit from pluripotency, without which gene silencing fails. Our female ESC system provides a tractable model for XX ESC culture that will expedite study of female pluripotency and has enabled us to discover new features of the female-specific process of X inactivation.

cell biology↗

bioRxiv2019

Vasoactive intestinal peptide confers anticipatory mucosal immunity by regulating ILC3 activity

ILC3-mediated IL-22 cytokine production is critical for the maintenance of immune homeostasis in the gastrointestinal tract. Here, we show that group 3 ILC (ILC3) constitutive function is not constant across the day but instead oscilliates between active and resting phases. Coordinate responsiveness of ILC3 in the intestine depended on food-induced expression of the neuronal hormone vasoactive intestinal peptide (VIP). Intestinal ILC3 expressed high levels of the G protein-coupled receptor, VIPR2, and activation via enteric neuronal VIP markedly enhanced IL-22 production and conferred gut protection. Conversely, deficiency of VIPR2 signalling led to impaired production of IL-22 by ILC3 and increased susceptibility to inflammatory gut disease. As such, intrinsic cellular rhythms synergise with the cyclic patterns of food intake to drive IL-22 thereby syncronizing intestinal epithelial protection via the ILC3 VIP-VIPR2 pathway.

immunology↗

bioRxiv2019

BiocPkgTools: Toolkit for Mining the Bioconductor Package Ecosystem

MotivationThe Bioconductor project, a large collection of open source software for the comprehension of large-scale biological data, continues to grow with new packages added each week, motivating the development of software tools focused on exposing package metadata to developers and users. The resulting BiocPkgTools package facilitates access to extensive metadata in computable form covering the Bioconductor package ecosystem, facilitating downstream applications such as custom reporting, data and text mining of Bioconductor package text descriptions, graph analytics over package dependencies, and custom search approaches.\n\nResultsThe BiocPkgTools package has been incorporated into the Bioconductor project, installs using standard procedures, and runs on any system supporting R. It provides functions to load detailed package metadata, longitudinal package download statistics, package dependencies, and Bioconductor build reports, all in \"tidy data\" form. BiocPkgTools can convert from tidy data structures to graph structures, enabling graphbased analytics and visualization. An end-user-friendly graphical package explorer aids in task-centric package discovery. Full documentation and example use cases are included.\n\nAvailabilityThe BiocPkgTools software and complete documentation are available from Bioconductor (https://bioconductor.org/packages/BiocPkgTools).

bioinformatics↗

bioRxiv2018

scRNA-seq mixology: towards better benchmarking of single cell RNA-seq protocols and analysis methods

Single cell RNA sequencing (scRNA-seq) technology has undergone rapid development in recent years, bringing with it new challenges in data processing and analysis. This has led to an explosion of tailored analysis methods for scRNA-seq to address various biological questions. However, the current lack of gold-standard benchmarking datasets makes it difficult for researchers to evaluate the performance of the many methods. Here, we designed and carried out a realistic benchmark experiment that included mixtures of single cells or pseudo-cells created by sampling admixtures of cells or RNA from 3 distinct cancer cell lines. Altogether we generated 10 datasets using a combination of droplet and plate-based scRNA-seq protocols, with varying data quality, population heterogeneity and noise levels. Using these benchmark datasets, we compared different protocols, evaluated the spike-in standard and multiple data analysis methods for tasks ranging from normalization and imputation, to clustering, trajectory analysis and data integration. Evaluation of methods across multiple datasets revealed some that performed well in general and others that suited specific situations. Our dataset and analysis provide a comprehensive comparison framework for benchmarking most popular scRNA-seq analysis tasks.

bioinformatics↗

bioRxiv2018

A data-driven approach to characterising intron signal in RNA-seq data

RNA-seq datasets can contain millions of intron reads per sequenced library that are typically removed from downstream analysis. Only reads overlapping annotated exons are considered to be informative since mature mRNA is assumed to be the major component sequenced, especially when examining poly(A) RNA samples. In this paper, we demonstrate that intron reads are informative and that pre-mRNA is the major source of intron signal. Making use of pre-mRNA signal, our index method combines differential expression analyses from intron and exon counts to categorise changes observed in each count set, giving additional genes with evidence of transcriptional changes when compared to a classic approach. Considering the importance of intron retention in some biological systems, another novel method, superintronic, looks for evidence of intron retention after accounting for the presence of pre-mRNA signal. The results presented here overcomes deficiencies and biases in previous works related to intron reads by exploring multiple sources for intron reads simultaneously using a data-driven approach, and provides a broad overview into how intron reads can be utilised in relation to multiple aspects of transcriptional biology.

bioinformatics↗