Biology subjects

Coin, L.

Publications and source records attributed to Coin, L..

14 recordsLinked to original sources

bioRxiv2025

Genome graphs reveal the importance of structural variation in Mycobacterium tuberculosis evolution and drug resistance

Structural variants (SVs) are increasingly recognized as key drivers of bacterial evolution, yet their role has not been explored thoroughly. This is due to limitations in traditional short-read sequencing and linear reference-based analyses, which can miss complex structural changes. Tuberculosis (TB), a disease caused by Mycobacterium tuberculosis (Mtb), remains a major global health concern. In this study, we harness long-read sequencing technologies and genome graph tools to construct a Mtb pangenome reference graph (PRG) from 859 high-quality, diverse, long-read assemblies. To enable accurate genotyping of SVs leveraging the PRG, we developed miniwalk, a tool that outperforms a traditional linear genome-based approach in precision for SV detection. We characterize patterns of structural variation genome-wide, revealing a virulence-associated ESX-5 deletion to be recurrent across the phylogeny, and fixed in a sub-lineage of L4. Systematic screens for additional genes that are recurrently affected by SVs implicated those related to metal homeostasis, including a copper exporter fixed in the widely distributed L1.2.1 sub-lineage. Lastly, we genotyped 41,134 isolates and found SVs putatively associated with resistance to various first and second-line drugs. These findings underscore the broader role of SVs in shaping Mtb diversity, highlighting their importance in both understanding evolution and designing strategies to combat drug-resistant TB.

genomics↗

bioRxiv2022

Genomic neighbor typing for bacterial outbreaksurveillance

Genomic neighbor typing enables heuristic inference of bacterial lineages and phenotypes from nanopore sequencing data. However, small reference databases may not be sufficiently representative of the diversity of lineages and genotypes present in a collection of isolates. In this study, we explore the use of genomic neighbor typing for surveillance of community-associated Staphylococcus aureus outbreaks in Papua New Guinea (PNG) and Far North Queensland, Australia (FNQ). We developed Sketchy, an implementation of genomic neighbor typing that queries exhaustive whole genome reference databases using MinHash. Evaluations were conducted using nanopore read simulations and six species-wide reference sketches (4832 - 47616 genomes), as well as two S. aureus outbreak data sets sequenced at low depth using a sequential multiplex library protocol on the MinION (n = 160, with matching Illumina data). Heuristic inference of lineages and antimicrobial resistance profiles allowed us to conduct multiplex genotyping in situ at the Papua New Guinea Institute of Medical Research in Goroka, on low-throughput Flongle adapters and using multiple successive libraries on the same MinION flow cell (n = 24 - 48). Comparison to phylogenetically informed genomic neighbor typing with RASE on the dominant outbreak sequence type suggests slightly better performance at predicting lineage-scale genotypes using large sketch sizes, but inferior performance in resolving clade-specific genotypes (methicillin resistance). Sketchy can be used for large-scale bacterial outbreak surveillance and in challenging sequencing scenarios, but improvements to clade-specific genotype inference are needed for diagnostic applications. Sketchy is available open-source at: https://github.com/esteinig/sketchy

bioinformatics↗

bioRxiv2021

Phylodynamic modelling of bacterial outbreaks using nanopore sequencing

Nanopore sequencing and phylodynamic modelling have been used to reconstruct the transmission dynamics of viral epidemics, but their application to bacterial pathogens has remained challenging. Here, we implement Random Forest models for single nucleotide polymorphism (SNP) polishing to estimate divergence and effective reproduction numbers (Re) of two community-associated, methicillin-resistant Staphylococcus aureus (MRSA) outbreaks in remote Far North Queensland and Papua New Guinea (n = 159). Successive bar-coded panels of S. aureus isolates (2 x 12 per MinION) sequenced at low-coverage (> 5x - 10x) provided sufficient data to accurately infer assembly genotypes with high recall when compared with Illumina references. De novo SNP calling with Clair was followed by SNP polishing using intra- and inter-species models trained on Snippy reference calls. Models achieved sufficient resolution on ST93 outbreak sequence types (> 70 - 90% accuracy and precision) for phylodynamic modelling from lineage-wide hybrid alignments and birth-death skyline models in BEAST2. Our method reproduced phylogenetic topology, geographical source of the outbreaks, and indications of sustained transmission (Re > 1). We provide Nextflow pipelines that implement SNP polisher training, evaluation, and outbreak alignments, enabling reconstruction of within-lineage transmission dynamics for infection control of bacterial disease outbreaks using nanopore sequencing.

bioinformatics↗

bioRxiv2020

Signatures Of TSPAN8 Variants Associated With Human Metabolic Regulation And Diseases

Here, with the example of common copy number variation (CNV) in the TSPAN8 gene, we present an important piece of work in the field of CNV detection, CNV association with complex human traits such as 1H NMR metabolomic phenotypes and an example of functional characterization of CNVs among human induced pluripotent stem cells (HipSci). We report TSPAN8 exon 11 as a new locus associated with metabolomic regulation and show that its biology is associated with several metabolic diseases such as type 2 diabetes (T2D), obesity and cancer. Our results further demonstrate the power of multivariate association models over univariate methods and define new metabolomic signatures for several new genomic loci, which can act as a catalyst for new diagnostics and therapeutic approaches.

genomics↗

bioRxiv2020

Direct RNA sequencing and early evolution of SARS-CoV-2

Fundamental aspects of SARS-CoV-2 biology remain to be described, having the potential to provide insight to the response effort for this high-priority pathogen. Here we describe the first native RNA sequence of SARS-CoV-2, detailing the coronaviral transcriptome and epitranscriptome, and share these data publicly. A data-driven inference of viral genetic features and evolutionary rate is also made. The rapid sharing of sequence information throughout the SARS-CoV-2 pandemic represents an inflection point for public health and genomic epidemiology, providing early insights into the biology and evolution of this emerging pathogen.

microbiology↗

bioRxiv2019

Genotype-free demultiplexing of pooled single-cell RNA-seq

A variety of experimental and computational methods have been developed to demultiplex samples from pooled individuals in a single-cell RNA sequencing (scRNA-Seq) experiment which either require adding information (such as hashtag barcodes) or measuring information (such as genotypes) prior to pooling. We introduce scSplit which utilises genetic differences inferred from scRNA-Seq data alone to demultiplex pooled samples. scSplit also extracts a minimal set of high confidence presence/absence genotypes in each cluster which can be used to map clusters to original samples. Using a range of simulated, merged individual-sample as well as pooled multi-individual scRNA-Seq datasets, we show that scSplit is highly accurate and concordant with demuxlet predictions. Furthermore, scSplit predictions are highly consistent with the known truth in cell-hashing dataset. We also show that multiplexed-scRNA-Seq can be used to reduce batch effects caused by technical biases. scSplit is ideally suited to samples for which external genome-wide genotype data cannot be obtained (for example non-model organisms), or for which it is impossible to obtain unmixed samples directly, such as mixtures of genetically distinct tumour cells, or mixed infections. scSplit is available at: https://github.com/jon-xu/scSplit

bioinformatics↗

bioRxiv2018

Evaluating the Genome and Resistome of Extensively Drug-Resistant Klebsiella pneumoniae using Native DNA and RNA Nanopore Sequencing

Klebsiella pneumoniae frequently harbour multidrug resistance and current methodologies are struggling to rapidly discern feasible antibiotics to treat these infections. While rapid DNA sequencing has been proposed for prediction of resistance profile; the role of rapid RNA sequencing has yet to be fully explored. The MinION sequencer can sequence native DNA and RNA in real-time, providing an opportunity to contrast the utility of DNA and RNA for prediction of drug susceptibility. This study interrogated the genome and transcriptome of four extensively drug-resistant (XDR) K. pneumoniae clinical isolates. The majority of acquired resistance ([≥]75%) resided on plasmids including several megaplasmids ([≥]100 kbp). DNA sequencing identified most resistance genes ([≥]70%) within 2 hours of sequencing. Direct RNA sequencing (with a [~]6x slower pore translocation) was able to identify [≥]35% of resistance genes, including aminoglycoside, {beta}-lactam, trimethoprim and sulphonamide and also quinolone, rifampicin, fosfomycin and phenicol in some isolates, within 10 hours of sequencing. Polymyxin-resistant isolates showed a heightened transcription of phoPQ ([≥]2-fold) and the pmrHFIJKLM operon ([≥]8-fold). Expression levels estimated from direct RNA sequencing displayed strong correlation (Pearson: 0.86) compared to qRT-PCR across 11 resistance genes. Overall, MinION sequencing rapidly detected the XDR K. pneumoniae resistome and direct RNA sequencing revealed differential expression of these genes.

genomics↗

bioRxiv2018

Octapeptin C4 Induces Less Resistance and Novel Mutations in an Epidemic Carbapenemase-producing Klebsiella pneumoniae ST258 Clinical Isolate Compared to Polymyxins

Polymyxin B and E (colistin) have been pivotal in the treatment of extensively drug-resistant (XDR) Gram-negative bacterial infections, with increasing use over the past decade. Unfortunately, resistance to these antibiotics is rapidly emerging. The structurally-related octapeptin C4 (OctC4) has shown significant potency against XDR bacteria, including against polymyxin-resistant (Pmx-R) strains, but its mode of action remains undefined. We sought to compare and contrast the acquisition of XDR Klebsiella pneumoniae (ST258) resistance in vitro with all three lipopeptides to help elucidate the mode of action of the drugs and potential mechanisms of resistance evolution. Strikingly, 20 days of exposure to the polymyxins resulted in a dramatic (1000-fold) increase in the minimum inhibitory concentration (MIC) for the polymyxins, reflecting the evolution of resistance seen in clinical isolates, whereas for OctC4 only a 4-fold increase was witnessed. There was no cross-resistance observed between the polymyxin - and octapeptin-induced resistant strains. Sequencing revealed previously known gene alterations for polymyxin resistance, including crrB, mgrB, pmrB, phoPQ and yciM, and novel mutations in qseC. In contrast, mutations in mlaDF and pqiB, 1genes related to phospholipid transport, were found in octapeptin-resistant isolates. Mutation effects were validated via complementation assays. These genetic variations were reflected in phenotypic changes to lipid A. Pmx-R isolates increased 4-amino-4-deoxy-arabinose fortification to phosphate groups of lipid A, whereas OctC4 induced strains harbored a higher abundance of hydroxymyristate and palmitoylate. The results reveal a differing mode of action compared to polymyxins which provides hope for future therapeutics to combat the increasingly threat of XDR bacteria.

microbiology↗

bioRxiv2018

Profiling copy number alterations in cell-free tumour DNA using a single-reference

BackgroundThe accurate detection of copy number alterations from the analysis of circulating cell free tumour DNA (ctDNA) in blood is essential to realising the potential of liquid biopsies. However, currently available approaches require a large number of plasma samples from healthy individuals, sequenced using the same platform and protocols to act as a reference panel. Obtaining this reference panel can be challenging, prohibitively expensive and limits the ability to migrate to improved sequencing platforms and improved protocols.\n\nMethodsWe developed qCNV and sCNA-seq, two distinct tools that together provide a new approach for profiling somatic copy number alterations (sCNA) through the analysis of cell free DNA (cfDNA) without a reference panel. Our approach was designed to identify sCNA from cfDNA through the analysis of a single plasma sample and a matched normal DNA sample -both of which can be obtained from the same blood draw. qCNV is an efficient method for extracting read-depth from BAM files and sCNA-seq is a method that uses a probabilistic model of read depth to infer the copy number segmentation of the tumour. We compared the results from our pipeline to the established copy number profile of a cell-line, as well as the results from the plasma-Seq analysis of cfDNA-like mixtures and real, clinical data-sets.\n\nResultsWith a single, unmatched, germline reference sample, our pipeline recapitulated the known copy number profile of a cell-line and demonstrated similar results to those obtained from plasma-Seq. With less than 1X genome coverage, our approach identified clinically relevant sCNA in samples with as little as 20 % tumour DNA. When applied to plasma samples from cancer patients, our pipeline identified clinically significant mutations.\n\nConclusionsThese results show it is possible to identify therapeutically-relevant copy number mutations from plasma samples without the need to generate a reference panel from a large number of healthy individuals. Together with the range of sequencing platforms supported by our qCNV+sCNA-Seq pipeline, as well as the Galaxy implementation of this solution, this pipeline makes cfDNA profiling more accessible and makes it easier to identify sCNA from the plasma of cancer patients.

bioinformatics↗

bioRxiv2018

A complete nanonpore-only assembly of an XDR Mycobacterium tuberculosis Beijing lineage strain identifies novel genetic variation in repetitive PE/PPE gene regions

A better understanding of the genomic changes that facilitate the emergence and spread of drug resistant M. tuberculosis strains is required. Short-read sequencing methods have limited capacity to identify long, repetitive genomic regions and gene duplications. We sequenced an extensively drug resistant (XDR) Beijing sub-lineage 2.2.1.1 \"epidemic strain\" from the Western Province of Papua New Guinea using long-read sequencing (Oxford Nanopore MinION(R)). With up to 274 fold coverage from a single flow-cell, we assembled a 4404947bp circular genome containing 3670 coding sequences that include the highly repetitive PE/PPE genes. Comparison with Illumina reads indicated a base-level accuracy of 99.95%. Mutations known to confer drug resistance to first and second line drugs were identified and concurred with phenotypic resistance assays. We identified mutations in efflux pump genes (Rv0194), transporters (secA1, glnQ, uspA), cell wall biosynthesis genes (pdk, mmpL, fadD) and virulence genes (mce-gene family, mycp1) that may contribute to the drug resistance phenotype and successful transmission of this strain. Using the newly assembled genome as reference to map raw Illumina reads from representative M. tuberculosis lineages, we detect large insertions relative to the reference genome. We provide a fully annotated genome of a transmissible XDR M. tuberculosis strain from Papua New Guinea using Oxford Nanopore MinION sequencing and provide insight into genomic mechanisms of resistance and virulence.\n\nData SummaryO_LISample Illumina and MinION sequencing reads generated and analyzed are available in NCBI under project accession number PRJNA386696 (https://www.ncbi.nlm.nih.gov/sra/?term=PRJNA386696)\nC_LIO_LIThe assembled complete genome and its annotations are available in NCBI under accession number CP022704.1 (https://www.ncbi.nlm.nih.gov/sra/?term=CP022704.1)\nC_LI\n\nImpact statementWe recently characterized a Modern Beijing lineage strain responsible for the drug resistance outbreaks in the Western province, Papua New Guinea. With some of the genomic markers responsible for its drug resistance and transmissibility are known, there is need to elucidate all molecular mechanisms that account for the resistance phenotype, virulence and transmission. Whole genome sequencing using short reads has widely been utilized to study MTB genome but it does not generally capture long repetitive regions as variants in these regions are eliminated using analysis. Illumina instruments are known to have a GC bias so that regions with high GC or AT rich are under sampled and this effect is exacerbated in MTB, which has approximately 65% GC content. In this study, we utilized Oxford Nanopore Technologies (ONT) MinION sequencing to assemble a high-quality complete genome of an extensively drug resistant strain of a modern Beijing lineage. We were able to able to assemble all PE/PPE (proline-glutamate/proline-proline-glutamate) gene families that have high GC content and repetitive in nature. We show the genomic utility of ONT in offering a more comprehensive understanding of genetic mechanisms that contribute to resistance, virulence and transmission. This is important for settings up predictive analytics platforms and services to support diagnostics and treatment.

genomics↗

bioRxiv2017

Chiron: Translating nanopore raw signal directly into nucleotide sequence using deep learning

Sequencing by translocating DNA fragments through an array of nanopores is a rapidly maturing technology which offers faster and cheaper sequencing than other approaches. However, accurately deciphering the DNA sequence from the noisy and complex electrical signal is challenging. Here, we report Chiron, the first deep learning model to achieve end-to-end basecalling: directly translating the raw signal to DNA sequence without the error-prone segmentation step. Trained with only a small set of 4000 reads, we show that our model provides state-of-the-art basecalling accuracy even on previously unseen species. Chiron achieves basecalling speeds of over 2000 bases per second using desktop computer graphics processing units.

bioinformatics↗

bioRxiv2017

npInv: accurate detection and genotyping of inversions mediated by non-allelic homologous recombination using long read sub-alignment

Detection of genomic inversions remains challenging. Many existing methods primarily target inversions with a non repetitive breakpoint, leaving inverted repeat (IR) mediated non-allelic homologous recombination (NAHR) inversions largely unexplored. We present npInv, a novel tool specifically for detecting and genotyping NAHR inversion using long read sub-alignment of long read sequencing data. We use npInv to generate a whole-genome inversion map for NA12878 consisting of 30 NAHR inversions (of which 15 are novel), including all previously known NAHR mediated inversions in NA12878 with flanking IR less than 7kb. Our genotyping accuracy on this dataset was 94%. We used PCR to confirm presence of two of these novel NAHR inversions. We show that there is a near linear relationship between the length of flanking IR and the size of the NAHR inversion.

bioinformatics↗

bioRxiv2017

Assembly Of Whole-Chromosome Pseudomolecules For Polyploid Plant Genomes Using Outcrossed Mapping Populations

The assembly of whole-chromosome pseudomolecules for plant genomes remains challenging due to polyploidy and high repeat content. We developed an approach for constructing complete pseudomolecules for polyploid species using genotyping-by-sequencing data from outcrossing mapping populations coupled with high coverage whole genome sequence data of a reference genome. Our approach combines de novo assembly with linkage mapping to arrange scaffolds into pseudomolecules. We show that the method is able to reconstruct simulated chromosomes for both diploid and tetraploid genomes. Comparisons to three existing genetic mapping tools show that our method outperforms the other methods in accuracy on both grouping and ordering, and is robust to the presence of substantial amounts of missing data and genotyping errors. We applied our method to three real datasets including a diploid Ipomoea trifida and two tetraploid potato mapping populations. The linkage maps show significant concordance with the reference chromosomes. We resolved seven assembly errors for the published Ipomoea trifida genome assembly as well as anchored an unplaced scaffold in the published potato genome.

bioinformatics↗

bioRxiv2017

Ongoing human chromosome end extension driven by a primate ancestral genomic region revealed by analysis of BioNano genomics data

The majority of human chromosome ends remain incompletely assembled due to their highly repetitive structure. In this study, we use BioNano data to anchor and extend chromosome ends from two European trios as well as two unrelated Asian genomes. BioNano assembled chromosome ends are structurally divergent from the reference genome, including both missing sequence (10%) and extensions(22%). These extensions are heritable and in some cases divergent between Asian and European samples. Six ninths of the extension sequence in NA12878 can be confirmed and filled by nanopore data. We identify two sequence families in these sequences which have undergone substantial duplication in multiple primate lineages. We show that these sequence families have arisen from progenitor interstitial sequence on the ancestral primate chromosome 7. Comparison of chromosome end sequences from 15 species revealed that chromosome end missing sequence matches the corresponding phylogenetic relationship and revealed a rate of chromosome extension per chromosome of 0.0020 bp per year in average.

genomics↗