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Roach, M. J.

Publications and source records attributed to Roach, M. J..

18 recordsLinked to original sources
bioRxiv2026

OpusTaxa: A Unified Workflow for Taxonomic Profiling, Assembly, and Functional Analysis of Shotgun Metagenomes

Shotgun metagenomics has become a cornerstone of microbiome research, yet the complexity of existing workflows remains a major barrier for life scientists without dedicated bioinformatics support. Manual database setup, detailed sample sheet preparation, and management of software dependencies can make routine analysis difficult and time-consuming. Cross-study comparisons are further hampered by inconsistent processing pipelines, database versions, and profiling strategies, limiting reproducibility and the potential for large-scale meta-analyses. We present OpusTaxa, an open-source Snakemake workflow that provides end-to-end processing of short paired-end shotgun metagenomic data with minimal configuration. Users provide either FASTQ files or Sequence Read Archive accessions; OpusTaxa automatically downloads required databases, performs quality control, removes host reads, and executes taxonomic profiling, metagenome assembly, and functional analysis. All analysis modules can be independently toggled, and per-sample outputs are automatically merged into harmonised, cross-sample tables ready for downstream exploration. Across two public datasets, we demonstrate how OpusTaxa can be used to compare consistency across complementary taxonomic profilers and to estimate microbial load in addition to standard metagenomic workflows. AvailabilityOpusTaxa is freely available at https://github.com/yenkaiC/OpusTaxa. Documentation, test data, and example configurations are included in the repository.

bioinformatics↗
bioRxiv2026

The mood stabilizer lithium alters behaviour and physiology via the gut brain axis.

Lithium, introduced 75 years ago by John Cade1, remains the most effective mood stabilizer for bipolar disorder2. Lithium is proposed to modulate an array of cellular pathways, many ubiquitous to all cells, with pleiotropic roles unlinked to bipolar disorder or lithium responsiveness in genome-wide association studies3,4. These mechanisms cannot explain lithiums specific effects on mood and behaviour. We demonstrate that lithiums primary action is in the periphery, not in the brain itself. Lithium acts in the gut to trigger behavioural and physiological changes, akin to those associated with a torpor-like state, that protect individuals from ingested toxins. Lithium activates gastrointestinal enterochromaffin (EC) cells via their Trpm2 cation channels to modulate afferent vagal and area postrema inputs to the brain. Eliminating these inputs by focal brain lesions eliminates lithiums effects, as does ablation of EC cells or their Trpm2 expression. Lithiums Trpm2-dependent activation of EC cells also occurs in human gut tissue, providing translational relevance for our discovery. These findings challenge the prevailing perception that lithium acts directly on the brain. Via a previously unsuspected gut-brain pathway, lithium engages brain circuitry that reduces arousal and interaction with the external world, therapeutic goals in the manic phase of bipolar disorder.

neuroscience↗
bioRxiv2025

Monocrotaline treatment of the rat predisposes to altered lipopolysaccharide-induced lung responses.

There is a need to understand pathogen driven lung disease and the rat is a laboratory model, widely used to study acute lung injury (ALI). Here the monocrotaline (MCT) rat has been investigated as a model of an inflammatory lung with developing pulmonary hypertension (PH) on which an ALI is superimposed. 14 days following a single systemic dose of MCT, the lung is functionally normal, but stimulation with lipopolysaccharide (LPS) results in an altered response. The MCT/LPS lung is morphologically similar to LPS alone, with respiratory mechanics showing increased elastance, reduced compliance and increased tissue resistance. Bronchioalveolar lavage (BAL) fluid demonstrated a cellular infiltrate, with large macrophage-like cells, increased secreted angiotensin converting enzyme-2 (ACE2) and total protein. The lung transcriptome is pushed towards a pro-inflammatory M1 phenotype, (interferon (IFN)-{Upsilon}, interleukin 6 (IL6), CD68 and CD80) compared to LPS alone. Additionally, the MCT/LPS lung has gene transcription signatures for enhanced cell death and DNA damage responses, higher levels of multiple complement components, dysregulation of the renin-angiotensin pathway with reduced ACE2 and increased AGTR1, increased factors such as Erythroferrone that would increase iron levels, and increased fibrinogen and A2M, that would promote thrombosis. Thus, the MCT-treated rat represents an animal with no overt clinical distinction but following LPS stimulation elicits an exacerbated pathogenic lung response. The MCT-treated rat is a simple model that might be beneficial for understanding an M1 lung pathology with activated complement, low ACE2, high iron, and a propensity to clot in the context of developing cardiovascular disease.

physiology↗
bioRxiv2025

Synteny-aware functional annotation of bacteriophage genomes with Phynteny

Accurate genome annotation is fundamental to decoding viral diversity and understanding bacteriophage biology; yet, the majority of bacteriophage genes remain functionally uncharacterised. Bacteriophage genomes often exhibit conserved gene order, or synteny, that reflects underlying constraints in genome architecture and expression. Here, we present Phynteny, a genome-scale, deep learning framework that leverages gene synteny to predict the function of unknown bacteriophage genes. Phynteny integrates protein language model embeddings with positional encoding, bidirectional long short-term memory, and transformer encoders featuring circular attention to learn genome-wide organisational patterns. Trained on a dereplicated dataset of over 280,000 bacteriophage genomes, Phynteny achieves high predictive performance (AUC > 0.84) across the nine PHROG functional categories and confidently assigns putative functions to improve the number of annotated genes in phage isolate genomes by 14%. To assess the validity of these predictions, we compared them with annotations derived independently using protein structural information, revealing broad functional concordance and additional confidence in Phynteny predictions. By incorporating genomic context into functional annotation, Phynteny offers a novel approach to illuminate the functional landscape of viral dark matter and is available at https://github.com/susiegriggo/Phynteny_transformer.

microbiology↗
bioRxiv2025

LeGO-Teknik reveals that the neurogenesis pathway is a clone-specific hallmark of brain metastasis in breast cancer

Breast cancer exhibits substantial inter- and intra-patient heterogeneity. Yet the molecular features underlying this diversity and their roles in tumour progression are not yet fully elucidated. Within a primary tumour, certain clones possess a unique capacity to metastasize to distant organs, such as the brain, and this propensity may be associated with specific gene expression profiles. To investigate this phenomenon, we developed a new optical barcoding library, LeGO-Teknik, compatible with high resolution imaging, flow cytometry, single-cell RNA sequencing and machine learning computational methods. Using this new tool, we systematically assessed the fitness and organ tropism of multiple human breast cancer clones in spontaneous metastasis assays. Linking transcriptomic profiles of individual cancer cells to their clonal identities and metastatic behaviours, we identified that clones predisposed to forming brain metastases exhibit distinct molecular signatures. Notably, individual cells from these clones showed enriched expression of neurogenesis-related genes. Using SCENIC transcription factor analysis, we found that some of these features are driven by the transcription factor SOX4. This hallmark, likely due to a process of cellular reprogramming, is a remarkable example of organ mimicry during clonal selection. Together, this work provides critical insights into brain metastasis and highlights the potential for identifying predictive biomarkers and therapeutic targets for metastatic breast cancer.

cancer biology↗
bioRxiv2025

Prophages as a source of antimicrobial resistance genes in the human microbiome

Prophages--viruses that integrate into bacterial genomes--are ubiquitous in the microbial realm. Prophages contribute significantly to horizontal gene transfer, including the potential spread of antimicrobial resistance (AMR) genes, because they can collect host genes. Understanding their role in the human microbiome is essential for fully understanding AMR dynamics and possible clinical implications. We analysed almost 15,000 bacterial genomes for prophages and AMR genes. The bacteria were isolated from diverse human body sites and geographical regions, and their genomes were retrieved from GenBank. AMR genes were detected in 6.6% of bacterial genomes, with a higher prevalence in people with symptomatic diseases. We found a wide variety of AMR genes combating multiple drug classes. We discovered AMR genes previously associated with plasmids, such as blaOXA-23 in Acinetobacter baumannii prophages or genes found in prophages in species they had not been previously described in, such as mefA-msrD in Gardnerella prophages, suggesting prophage-mediated gene transfer of AMR genes. Prophages encoding AMR genes were found at varying frequencies across body sites and geographical regions, with Asia showing the highest diversity of AMR genes. ImportanceAntimicrobial resistance (AMR) is a growing threat to public health, and understanding how resistance genes spread between bacteria is essential for controlling their dissemination. Bacteriophages, viruses that infect bacteria, have been recognised as potential vehicles for transferring these resistance genes, but their role in the human microbiome remains poorly understood. We examined nearly 15,000 bacterial genomes from various human body sites and regions worldwide to investigate how often prophages carry AMR genes in the human microbiome. Although AMR genes were uncommon in prophages, we identified diverse resistance genes across multiple bacterial species and drug classes, including some typically associated with plasmids. These findings reveal that prophages may contribute to the spread of resistance genes, highlighting an overlooked mechanism in the dynamics of AMR transmission. Ongoing monitoring of prophages is critical to fully understanding the pathways through which resistance genes move within microbial communities and impact human health.

bioinformatics↗
bioRxiv2024

Sphae: An automated toolkit for predicting phage therapy candidates from sequencing data

MotivationPhage therapy is a viable alternative for treating bacterial infections amidst the escalating threat of antimicrobial resistance. However, the therapeutic success of phage therapy depends on selecting safe and effective phage candidates. While experimental methods focus on isolating phages and determining their lifecycle and host range, comprehensive genomic screening is critical to identify markers that indicate potential risks, such as toxins, antimicrobial resistance, or temperate lifecycle traits. These analyses are often labor-intensive and time-consuming, limiting the rapid deployment of phage in clinical settings. ResultsWe developed Sphae, an automated bioinformatics pipeline designed to streamline therapeutic potential of a phage in under ten minutes. Using Snakemake workflow manager, Sphae integrates tools for quality control, assembly, genome assessment, and annotation tailored specifically for phage biology. Sphae automates the detection of key genomic markers, including virulence factors, antimicrobial resistance genes, and lysogeny indicators like integrase, recombinase, and transposase, which could preclude therapeutic use. Benchmarked on 65 phage sequences, 28 phage samples showed therapeutic potential, 8 failed during assembly due to low sequencing depth, 22 samples included prophage or virulent markers, and the remaining 23 samples included multiple phage genomes per sample. This workflow outputs a comprehensive report, enabling rapid assessment of phage safety and suitability for phage therapy under these criteria. Sphae is scalable, portable, facilitating efficient deployment across most high-performance computing (HPC) and cloud platforms, expediting the genomic evaluation process. AvailabilitySphae is source code and freely available at https://github.com/linsalrob/sphae, with installation supported on Conda, PyPi, Docker containers.

bioinformatics↗
bioRxiv2023

Hybracter: Enabling Scalable, Automated, Complete and Accurate Bacterial Genome Assemblies

Improvements in the accuracy and availability of long-read sequencing mean that complete bacterial genomes are now routinely reconstructed using hybrid (i.e. short- and long-reads) assembly approaches. Complete genomes allow a deeper understanding of bacterial evolution and genomic variation beyond single nucleotide variants (SNVs). They are also crucial for identifying plasmids, which often carry medically significant antimicrobial resistance (AMR) genes. However, small plasmids are often missed or misassembled by long-read assembly algorithms. Here, we present Hybracter which allows for the fast, automatic, and scalable recovery of near-perfect complete bacterial genomes using a long-read first assembly approach. Hybracter can be run either as a hybrid assembler or as a long-read only assembler. We compared Hybracter to existing automated hybrid and long-read only assembly tools using a diverse panel of samples of varying levels of long-read accuracy with manually curated ground truth reference genomes. We demonstrate that Hybracter as a hybrid assembler is more accurate and faster than the existing gold standard automated hybrid assembler Unicycler. We also show that Hybracter with long-reads only is the most accurate long-read only assembler and is comparable to hybrid methods in accurately recovering small plasmids. Data SummaryO_LIHybracter is developed using Python and Snakemake as a command-line software tool for Linux and MacOS systems. C_LIO_LIHybracter is freely available under an MIT License on GitHub (https://github.com/gbouras13/hybracter) and the documentation is available at Read the Docs (https://hybracter.readthedocs.io/en/latest/). C_LIO_LIHybracter is available to install via PyPI (https://pypi.org/project/hybracter/) and Bioconda (https://anaconda.org/bioconda/hybracter). A Docker/Singularity container is also available at https://quay.io/repository/gbouras13/hybracter. C_LIO_LIAll code used to benchmark Hybracter, including the reference genomes, is publicly available on GitHub (https://github.com/gbouras13/hybracter_benchmarking) with released DOI (https://zenodo.org/doi/10.5281/zenodo.10910108) available at Zenodo. C_LIO_LIThe subsampled FASTQ files used for benchmarking are publicly available at Zenodo with DOI (https://doi.org/10.5281/zenodo.10906937). C_LIO_LIAll super accuracy simplex ATCC FASTQ reads sequenced as a part of this study can be found under BioProject PRJNA1042815. C_LIO_LIAll Hall et al. fast accuracy simplex and super accuracy duplex ATCC FASTQ read files (prior to subsampling) can be found in the SRA under BioProject PRJNA1087001. C_LIO_LIAll raw Lermaniaux et al. FASTQ read files and genomes (prior to subsampling) can be found in the SRA under BioProject PRJNA1020811. C_LIO_LIAll Staphylococcus aureus JKD6159 FASTQ read files and genomes can be found under BioProject PRJNA50759. C_LIO_LIAll Mycobacterium tuberculosis H37R2 FASTQ read files and genomes can be found under BioProject PRJNA836783. C_LIO_LIThe complete list of BioSample accession numbers for each benchmarked sample can be found in Supplementary Table 1. C_LIO_LIThe benchmarking assembly output files are publicly available on Zenodo with DOI (https://doi.org/10.5281/zenodo.10906937). C_LIO_LIAll Pypolca benchmarking outputs and code are publicly available on Zenodo with DOI (https://zenodo.org/doi/10.5281/zenodo.10072192). C_LI Impact StatementComplete bacterial genome assembly using hybrid sequencing is a routine and vital part of bacterial genomics, especially for identification of mobile genetic elements and plasmids. As sequencing becomes cheaper, easier to access and more accurate, automated assembly methods are crucial. With Hybracter, we present a new long-read first automated assembly tool that is faster and more accurate than the widely-used Unicycler. Hybracter can be used both as a hybrid assembler and with long-reads only. Additionally, it solves the problems of long-read assemblers struggling with small plasmids, with plasmid recovery from long-reads only performing on par with hybrid methods. Hybracter can natively exploit the parallelisation of high-performance computing (HPC) clusters and cloud-based environments, enabling users to assemble hundreds or thousands of genomes with one line of code. Hybracter is available freely as source code on GitHub, via Bioconda or PyPi.

bioinformatics↗
bioRxiv2023

Bioenergetic mapping of 'healthy microbiomes' via compound processing potential imprinted in gut and soil metagenomes

Despite mounting evidence of their importance in human health and ecosystem functioning, the definition and measurement of healthy microbiomes remain unclear. More advanced knowledge exists on health associations for compounds used or produced by microbes. Environmental microbiome exposures (especially via soils) also help shape, and may supplement, the functional capacity of human microbiomes. Given the synchronous interaction between microbes, their feedstocks, and micro-environments, with functional genes facilitating chemical transformations, there exists an intriguing opportunity to examine microbiomes in terms of their capacity to process compounds relevant to human health. Here we integrate functional genomics and biochemistry frameworks to derive new quantitative measures of the potential for human gut and environmental soil metagenomes to process major compound classes (e.g., lipids, carbohydrates) and selected biomolecules (e.g., vitamins, short-chain fatty acids) linked to human health. Metagenome functional potential profile data were translated into a universal compound mapping landscape based on bioenergetic van Krevelen mapping of function-level meta-compounds and corresponding functional relative abundances, reflecting imprinted genetic capacity of microbiomes to metabolize an array of different compounds. We show that measures of compound processing potential associated with human health and disease (examining atherosclerotic cardiovascular disease, colorectal cancer, type 2 diabetes and anxious-depressive behavior case studies), and displayed seemingly predictable shifts along gradients of ecological disturbance in plant-soil ecosystems (three case studies). Ecosystem quality explained 60-92% of variation in soil metagenome compound processing potential measures in a post-mining restoration case study dataset. With growing knowledge of the varying proficiency of environmental microbiota to process human health associated compounds, we might design environmental interventions or nature prescriptions to modulate our exposures, thereby advancing microbiota-oriented approaches to human health. Compound processing potential offers a simplified, integrative approach for applying metagenomics in ongoing efforts to understand and quantify the role and linkages of microbiota in environmental- and human-health.

bioinformatics↗
bioRxiv2023

Prophage rates in the human microbiome vary by body site and host health.

Phages integrated into a bacterial genome-called prophages-continuously monitor the health of the host bacteria to determine when to escape the genome, protect their host from other phage infections, and may provide genes that promote bacterial growth. Prophages are essential to almost all microbiomes, including the human microbiome. However, most human microbiome studies focus on bacteria, ignoring free and integrated phages, so we know little about how these prophages affect the human microbiome. We compared the prophages identified in 11,513 bacterial genomes isolated from human body sites to characterise prophage DNA in the human microbiome. Here, we show that prophage DNA comprised an average of 1-5% of each bacterial genome. The prophage content per genome varies with the isolation site on the human body, the health of the human, and whether the disease was symptomatic. The presence of prophages promotes bacterial growth and sculpts the microbiome. However, the disparities caused by prophages vary throughout the body.

genomics↗
bioRxiv2023

The Promise and Pitfalls of Prophages

Phages dominate every ecosystem on the planet. While virulent phages sculpt the microbiome by killing their bacterial hosts, temperate phages provide unique growth advantages to their hosts through lysogenic conversion. Many prophages benefit their host, and prophages are responsible for genotypic and phenotypic differences that separate individual microbial strains. However, the microbes also endure a cost to maintain those phages: additional DNA to replicate and proteins to transcribe and translate. We have never quantified those benefits and costs. Here, we analysed over two and a half million prophages from over half a million bacterial genome assemblies. Analysis of the whole dataset and a representative subset of taxonomically diverse bacterial genomes demonstrated that the normalised prophage density was uniform across all bacterial genomes above 2 Mbp. We identified a constant carrying capacity of phage DNA per bacterial DNA. We estimated that each prophage provides cellular services equivalent to approximately 2.4 % of the cells energy or 0.9 ATP per bp per hour. We demonstrate analytical, taxonomic, geographic, and temporal disparities in identifying prophages in bacterial genomes that provide novel targets for identifying new phages. We anticipate that the benefits bacteria accrue from the presence of prophages balance the energetics involved in supporting prophages. Furthermore, our data will provide a new framework for identifying phages in environmental datasets, diverse bacterial phyla, and from different locations.

bioinformatics↗
bioRxiv2023

Phables: from fragmented assemblies to high-quality bacteriophage genomes

MotivationMicrobial communities influence both human health and different environments. Viruses infecting bacteria, known as bacteriophages or phages, play a key role in modulating bacterial communities within environments. High-quality phage genome sequences are essential for advancing our understanding of phage biology, enabling comparative genomics studies, and developing phage-based diagnostic tools. Most available viral identification tools consider individual sequences to determine whether they are of viral origin. As a result of the challenges in viral assembly, fragmentation of genomes can occur, leading to the need for new approaches in viral identification. Therefore, the identification and characterisation of novel phages remain a challenge. ResultsWe introduce Phables, a new computational method to resolve phage genomes from fragmented viral metagenome assemblies. Phables identifies phage-like components in the assembly graph, models each component as a flow network, and uses graph algorithms and flow decomposition techniques to identify genomic paths. Experimental results of viral metagenomic samples obtained from different environments show that Phables recovers on average over 49% more high-quality phage genomes compared to existing viral identification tools. Furthermore, Phables can resolve variant phage genomes with over 99% average nucleotide identity, a distinction that existing tools are unable to make. Availability and ImplementationPhables is available on GitHub at https://github.com/Vini2/phables. Contactvijini.mallawaarachchi@flinders.edu.au

bioinformatics↗
bioRxiv2023

Novel crAssphage isolates exhibit conserved gene order and purifying selection of the host specificity protein

Bacteroides, the prominent bacteria in the human gut, play a crucial role in degrading complex polysaccharides. Their abundance is influenced by phages belonging to the Crassvirales order. Despite identifying over 600 Crassvirales genomes computationally, only few have been successfully isolated. Continued efforts in isolation of more Crassvirales genomes can provide insights into phage-host-evolution and infection mechanisms. We focused on wastewater samples, as potential sources of phages infecting various Bacteroides hosts. Sequencing, assembly, and characterization of isolated phages revealed 14 complete genomes belonging to three novel Crassvirales species infecting Bacteroides cellulosilyticus WH2. These species, Kehishuvirus sp. tikkala strain Bc01, Kolpuevirus sp. frurule strain Bc03, and Rudgehvirus jaberico strain Bc11, spanned two families, and three genera, displaying a broad range of virion productions. Upon testing all successfully cultured Crassvirales species and their respective bacterial hosts, we discovered that they do not exhibit co-evolutionary patterns with their bacterial hosts. Furthermore, we observed variations in gene similarity, with greater shared similarity observed within genera. However, despite belonging to different genera, the three novel species shared a unique structural gene that encodes the tail spike protein. When investigating the relationship between this gene and host interaction, we discovered evidence of purifying selection, indicating its functional importance. Moreover, our analysis demonstrated that this tail spike protein binds to the TonB-dependent receptors present on the bacterial host surface. Combining these observations, our findings provide insights into phage-host interactions and present three Crassvirales species as an ideal system for controlled infectivity experiments on one of the most dominant members of the human enteric virome. Impact statementBacteriophages play a crucial role in shaping microbial communities within the human gut. Among the most dominant bacteriophages in the human gut microbiome are Crassvirales phages, which infect Bacteroides. Despite being widely distributed, only a few Crassvirales genomes have been isolated, leading to a limited understanding of their biology, ecology, and evolution. This study isolated and characterized three novel Crassvirales genomes belonging to two different families, and three genera, but infecting one bacterial host, Bacteroides cellulosilyticus WH2. Notably, the observation confirmed the phages are not co-evolving with their bacterial hosts, rather have a shared ability to exploit similar features in their bacterial host. Additionally, the identification of a critical viral protein undergoing purifying selection and interacting with the bacterial receptors opens doors to targeted therapies against bacterial infections. Given Bacteroides role in polysaccharide degradation in the human gut, our findings advance our understanding of the phage-host interactions and could have important implications for the development of phage-based therapies. These discoveries may hold implications for improving gut health and metabolism to support overall well-being. Data summaryThe genomes used in this research are available on Sequence Read Archive (SRA) within the project, PRJNA737576. Bacteroides cellulosilyticus WH2, Kehishuvirus sp. tikkala strain Bc01, Kolpuevirus sp. frurule strain Bc03, and Rudgehvirus jaberico strain Bc11 are all available on GenBank with accessions NZ_CP072251.1 (B. cellulosilyticus WH2), QQ198717 (Bc01), QQ198718 (Bc03), and QQ198719 (Bc11), and we are working on making the strains available through ATCC. The 3D protein structures for the three Crassvirales genomes are available to download at doi.org/10.25451/flinders.21946034.

bioinformatics↗
bioRxiv2022

Hecatomb: An End-to-End Research Platform for Viral Metagenomics

BackgroundAnalysis of viral diversity using modern sequencing technologies offers extraordinary opportunities for discovery. However, these analyses present a number of bioinformatic challenges due to viral genetic diversity and virome complexity. Due to the lack of conserved marker sequences, metagenomic detection of viral sequences requires a non-targeted, random (shotgun) approach. Annotation and enumeration of viral sequences relies on rigorous quality control and effective search strategies against appropriate reference databases. Virome analysis also benefits from the analysis of both individual metagenomic sequences as well as assembled contigs. Combined, virome analysis results in large amounts of data requiring sophisticated visualization and statistical tools. ResultsHere we introduce Hecatomb, a bioinformatics platform enabling both read and contig based analysis. Hecatomb integrates query information from both amino acid and nucleotide reference sequence databases. Hecatomb integrates data collected throughout the workflow enabling analyst driven virome analysis and discovery. Hecatomb is available on GitHub at https://github.com/shandley/hecatomb. ConclusionsHecatomb provides a single, modular software solution to the complex tasks required of many virome analysis. We demonstrate the value of the approach by applying Hecatomb to both a host-associated (enteric) and an environmental (marine) virome data set. Hecatomb provided data to determine true- or false-positive viral sequences in both data sets and revealed complex virome structure at distinct marine reef sites.

bioinformatics↗
bioRxiv2021

Philympics 2021: Prophage Predictions Perplex Programs

Most bacterial genomes contain integrated bacteriophages--prophages--in various states of decay. Many are active and able to excise from the genome and replicate, while others are cryptic prophages, remnants of their former selves. Over the last two decades, many computational tools have been developed to identify the prophage components of bacterial genomes, and it is a particularly active area for the application of machine learning approaches. However, progress is hindered and comparisons thwarted because there are no manually curated bacterial genomes that can be used to test new prophage prediction algorithms. Here, we present a library of gold-standard bacterial genome annotations that include manually curated prophage annotations, and a computational framework to compare the predictions from different algorithms. We use this suite to compare all extant stand-alone prophage prediction algorithms to identify their strengths and weaknesses. We provide a FAIR dataset for prophage identification, and demonstrate the accuracy, precision, recall, and f1 score from the analysis of seven different algorithms for the prediction of prophages. We discuss caveats and concerns in this analysis and how those concerns may be mitigated.

bioinformatics↗
bioRxiv2019

New genome assemblies reveal patterns of domestication and adaptation across Brettanomyces (Dekkera) species

BackgroundYeast of the genus Brettanomyces are of significant interest, both for their capacity to spoil, as well as their potential to positively contribute to different industrial fermentations. However, considerable variance exists in the depth of research and knowledgebase of the five currently known species of Brettanomyces. For instance, Brettanomyces bruxellensis has been heavily studied and many resources are available for this species, whereas Brettanomyces nanus is rarely studied and lacks a publicly available genome assembly altogether. The purpose of this study is to fill this knowledge gap and explore the genomic adaptations that have shaped the evolution of this genus.\n\nResultsStrains for each of the five widely accepted species of Brettanomyces (Brettanomyces anomalus, B. bruxellensis, Brettanomyces custersianus, Brettanomyces naardenensis, and B. nanus) were sequenced using a combination of long- and short-read sequencing technologies. Highly contiguous assemblies were produced for each species. Sweeping and extensive structural variation between the species genomes were observed and gene expansions in fermentation-relevant genes (particularly in B. bruxellensis and B. nanus) were identified. Numerous horizontal gene transfer (HGT) events in all Brettanomyces species, including an HGT event that is probably responsible for allowing B. bruxellensis and B. anomalus to utilize sucrose were also observed.\n\nConclusionsGenomic adaptations and some evidence of domestication that have taken place in Brettanomycesare outlined. These new genome assemblies form a valuable resource for future research in Brettanomyces.

genomics↗
bioRxiv2018

Population sequencing reveals clonal diversity and ancestral inbreeding in the grapevine cultivar Chardonnay

Chardonnay is the basis of some of the worlds most iconic wines and its success is underpinned by a historic program of clonal selection. There are numerous clones of Chardonnay available that exhibit differences in key viticultural and oenological traits that have arisen from the accumulation of somatic mutations during centuries of asexual propagation. However, the genetic variation that underlies these differences remains largely unknown. To address this knowledge gap, a high-quality, diploid-phased Chardonnay genome assembly was produced from single-molecule real time sequencing, and combined with re-sequencing data from 15 different commercial Chardonnay clones. There were 1620 markers identified that distinguish the 15 Chardonnay clones. These markers were reliably used for clonal identification of validation genomic material, as well as in identifying a potential genetic basis for some clonal phenotypic differences. The predicted parentage of the Chardonnay haplomes was elucidated by mapping sequence data from the predicted parents of Chardonnay (Gouais blanc and Pinot noir) against the Chardonnay reference genome. This enabled the detection of instances of heterosis, with differentially-expanded gene families being inherited from the parents of Chardonnay. Most surprisingly however, the patterns of nucleotide variation present in the Chardonnay genome indicate that Pinot noir and Gouais blanc share an extremely high degree of kinship that has resulted in the Chardonnay genome displaying characteristics that are indicative of inbreeding.\n\nAuthor SummaryPhenotypic variation within a grapevine cultivar arises from an accumulation of mutations from serial vegetative propagation. Old cultivars such as Chardonnay have been propagated for centuries resulting in hundreds of available clones containing unique genetic mutations and a range of various phenotypic peculiarities. The genetic mutations can be leveraged as genetic markers and are useful in identifying specific clones for authenticity testing, or as breeding markers for new clonal selections where particular mutations are known to confer a phenotypic trait. We produced a high-quality genome assembly for Chardonnay, and using re-sequencing data for 15 popular clones, were able to identify a large selection of markers that are unique to at least one clone. We identified mutations that may confer phenotypic effects, and were able to identify clones from material independently sourced from nurseries and vineyards. The marker detection framework we describe for authenticity testing would be applicable to other grapevine cultivars or even other agriculturally important woody-plant crops that are vegetatively propagated such as fruit orchards. Finally, we show that the Chardonnay genome contains extensive evidence for parental inbreeding, such that its parents, Gouais blanc and Pinot noir, may even represent first-degree relatives.

genomics↗
bioRxiv2018

Purge Haplotigs: Synteny Reduction for Third-gen Diploid Genome Assemblies

Recent developments in third-gen long read sequencing and diploid-aware assemblers have resulted in the rapid release of numerous reference-quality assemblies for diploid genomes. However, assembling highly heterozygous genomes is still facing a major problem where the two haplotypes for a region are highly polymorphic and the synteny is not recognised during assembly. This causes issues with downstream analysis, for example variant discovery using the haploid assembly, or haplotype reconstruction using the diploid assembly. A new pipeline--Purge Haplotigs--was developed specifically for third-gen assemblies to identify and reassign the duplicate contigs. The pipeline takes a draft haplotype-fused assembly or a diploid assembly, and read alignments to produce an improved assembly. The pipeline was tested on a simulated dataset and on four recent diploid (phased) de novo assemblies from third-generation long-read sequencing. All assemblies after processing with Purge Haplotigs were less duplicated with minimal impact on genome completeness. The software is available at https://bitbucket.org/mroachawri/purge_haplotigs under a permissive MIT licence.

bioinformatics↗