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Search indexed bioRxiv preprints in genomics, neuroscience, cell biology and bioinformatics. Read source abstracts and check manuscript versions; preprints are not peer reviewed.

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bioRxiv2023

Bringing TB genomics to the clinic: A comprehensive pipeline to predict antimicrobial susceptibility from genomic data, validated and accredited to ISO standards.

BackgroundWhole genome sequencing (WGS) is increasingly contributing to the clinical management of tuberculosis. Whilst the availability of bioinformatic tools for analysis and clinical reporting of Mycobacterium tuberculosis sequence data is improving, However, there remains a need for accessible, flexible bioinformatic tools that can be easily tailored for clinical reporting needs in different settings and are suitable for accreditation to international standards. MethodsWe developed tbtAMR, a flexible yet comprehensive tool for analysis of Mycobacterium tuberculosis genomic data, including inference of phenotypic susceptibility and lineage calling. Validation was undertaken using local and publicly-available real-world data (phenotype and genotype) and synthetic genomic data to determine the appropriate quality control metrics and extensively validate the pipeline for clinical use. FindingstbtAMR accurately predicted lineages and phenotypic susceptibility for first- and second-line drugs, with equivalent computational and predictive performance compared to other bioinformatics tools currently available. tbtAMR is flexible with modifiable criteria to tailor results to users needs. InterpretationThe tbtAMR tool is suitable for use in clinical and public health microbiology laboratory settings, and can be tailored to specific local needs by non-programmers. We have accredited this tool to ISO standards in our laboratory, and it has been implemented for routine reporting of AMR from genomic sequence data in a clinically relevant timeframe. Reporting templates, validation methods and datasets are provided to offer a pathway for laboratories to adopt and seek their own accreditation for this critical test, to improve the management of tuberculosis globally. FundingVictorian Government Department of Health; Australian National Health and Medical Research Council and Medical Research Futures Fund. Research in contextO_ST_ABSEvidence before this studyC_ST_ABSWe searched PubMed for studies using the search terms: "Mycobacterium tuberculosis", "clinical", "bioinformatics", "genomics", "drug resistance (OR antimicrobial)", published prior to 31st July 2024 without language restrictions (n=258). We considered all studies from this search that used genomics to infer likely drug-resistance in M. tuberculosis. Many of these studies highlight the challenges in making meaningful interpretations from genomic data for the purpose of inferring AMR for clinical applications. Despite the development of bioinformatics tools and compilation of catalogues of resistance conferring mutations, few of these studies directly address the challenges specific to implementation of a whole genome sequencing (WGS) and bioinformatics pipelines to deliver validated and accredited results for use in clinical applications and none provide sustainable solutions. Added value of this studyTo the best of our knowledge, this study is the first to detail practical solutions to challenges to validating and accrediting the routine inference of AMR from WGS data for clinical applications for treatment of M. tuberculosis. We developed, validated and accredited a bioinformatics tool, tbtAMR, which is robust and flexible, using a data-driven approach to inferring resistance, allowing for simple customisation of behaviour on a large collection of in-house data supplemented with publicly available data. Furthermore, we have made this pipeline and the accompanying data available for use by the wider public health community to aid others in implementing similar programs. Consultation with infectious disease clinicians, microbiologists and epidemiologists has allowed us to develop a robust workflow, that encompasses sequencing, analysis, interpretation, reporting, discrepancy resolution and ongoing verification. Implications of all the available evidenceThis study addressed the specific needs of reporting genomic AMR for M. tuberculosis in a clinical and public health laboratory. Furthermore, this work makes available a pipeline and data for laboratories to utilise to implement genomic AMR for M. tuberculosis. Through the use and further development of publicly available and open-source bioinformatics software, we have demonstrated the feasibility of clinical reporting of genomic AMR results for M. tuberculosis in a low-incidence high-income setting. We believe that this work lays the foundation for making reporting of genomic AMR for M. tuberculosis more accessible to public health and reference laboratories in general.

genomics↗

bioRxiv2023

The black honey bee genome: insights on specific structural elements and a first step towards pan-genomes

BackgroundThe actual honey bee reference genome, HAv3.1, was produced from a commercial line sample, thought to have a largely dominant Apis mellifera ligustica genetic background. Apis mellifera mellifera, often referred to as the black bee, has a separate evolutionary history and is the original type in western and northern Europe. Growing interest in this subspecies for conservation and non-professional apicultural practices, together with the necessity of deciphering genome backgrounds in hybrids, triggered the necessity for a specific genome assembly. Moreover, having several high-quality genomes is becoming key for taking structural variations into account in pan-genome analyses. ResultsPacific Bioscience technology long reads were produced from a single haploid black bee drone. Scaffolding contigs into chromosomes was done using a high-density genetic map. This allowed for a re-estimation of the honey recombination rate, over-estimated in some previous studies, due to mis-assemblies resulting in spurious inversions in the older reference genomes. The sequence continuity obtained is very high and the only limit towards continuous chromosome-wide sequences seem to be due to tandem repeat arrays usually longer than 10 kb and belonging to two main families, the 371 and 91 bp repeats, causing problems in the assembly process due to high internal sequence similarity. Our assembly was used together with the reference genome, for genotyping two structural variants by a pan-genome graph approach with Graphtyper2. Genotypes obtained were either correct or missing, when compared to an approach based on sequencing depth analysis, and genotyping rates were 89 and 76 % for the two variants respectively. ConclusionsOur new assembly for the Apis mellifera mellifera honey bee subspecies demonstrates the utility of multiple high-quality genomes for the genotyping of structural variants, with a test case on two insertions and deletions. It will therefore be an invaluable resource for future studies, for instance including structural variants in GWAS. Having used a single haploid drone for sequencing allowed a refined analysis of very large tandem repeat arrays, raising the question of their function in the genome. High quality genome assemblies for multiple subspecies such as presented here, are crucial for emerging projects using pan-genomes.

genomics↗

bioRxiv2023

Development of the Pneumococcal Genome Library, a core genome multilocus sequence typing scheme, and a taxonomic life identification number barcoding system to investigate and define pneumococcal population structure

Investigating the genomic epidemiology of major bacterial pathogens is integral to understanding transmission, evolution, colonisation, disease, antimicrobial resistance, and vaccine impact. Furthermore, the recent accumulation of large numbers of whole genome sequences for many bacterial species enhances the development of robust genome-wide typing schemes to define the overall bacterial population structure and lineages within it. Using previously published data, we developed the Pneumococcal Genome Library (PGL), a curated dataset of 30,976 genomes and contextual data for carriage and disease pneumococci recovered between 1916-2018 in 82 countries. We leveraged the size and diversity of the PGL to develop a core genome multilocus sequence typing (cgMLST) scheme comprised of 1,222 loci. Finally, using multilevel single-linkage clustering, we stratified pneumococci into hierarchical clusters based on allelic similarity thresholds, and defined these with a taxonomic life identification number (LIN) barcoding system. The PGL, cgMLST scheme, and LIN barcodes represent a high-quality genomic resource and fine-scale clustering approaches for the analysis of pneumococcal populations, which support the genomic epidemiology and surveillance of this leading global pathogen. Impact statementMany thousands of pneumococcal genomes are available in the public domain, and this creates opportunities for the scientific community to re-use existing data; however, these data are most useful when the contextual data (provenance and phenotype) are also linked to the genomes. Therefore, we created a curated, open-access database in PubMLST that contained nearly 31,000 published pneumococcal genomes and the corresponding contextual data for each genome. This large and diverse pneumococcal database was used to create a novel cgMLST scheme and multilevel clustering method to define genetic lineages with high resolution and a standardised nomenclature. These are open-access resources for all to use and provide a unified framework for the characterisation of global pneumococcal populations.

genomics↗

bioRxiv2024

Blended Genome Exome (BGE) as a Cost Efficient Alternative to Deep Whole Genomes or Arrays

Genomic scientists have long been promised cheaper DNA sequencing, but deep whole genomes are still costly, especially when considered for large cohorts in population-level studies. More affordable options include microarrays + imputation, whole exome sequencing (WES), or low-pass whole genome sequencing (WGS) + imputation. WES + array + imputation has recently been shown to yield 99% of association signals detected by WGS. However, a method free from ascertainment biases of arrays or the need for merging different data types that still benefits from deeper exome coverage to enhance novel coding variant detection does not exist. We developed a new, combined, "Blended Genome Exome" (BGE) in which a whole genome library is generated, an aliquot of that genome is amplified by PCR, the exome regions are selected and enriched, and the genome and exome libraries are combined back into a single tube for sequencing (33% exome, 67% genome). This creates a single CRAM with a low-coverage whole genome (2-3x) combined with a higher coverage exome (30-40x). This BGE can be used for imputing common variants throughout the genome as well as for calling rare coding variants. We tested this new method and observed >99% r2 concordance between imputed BGE data and existing 30x WGS data for exome and genome variants. BGE can serve as a useful and cost-efficient alternative sequencing product for genomic researchers, requiring ten-fold less sequencing compared to 30x WGS without the need for complicated harmonization of array and sequencing data.

genomics↗

bioRxiv2024

Genomic Diversity and Antimicrobial Resistance of Vibrio cholerae Isolates from Africa: A PulseNet Africa Initiative Using Nanopore Sequencing to Enhance Genomic Surveillance

ObjectivesVibrio cholerae remains a significant public health threat in Africa, with antimicrobial resistance (AMR) complicating treatment. This study leverages whole-genome sequencing (WGS) of V. cholerae isolates from Cote dIvoire, Ghana, Zambia and South Africa to assess genomic diversity, AMR profiles, and virulence, demonstrating the utility of WGS for enhanced surveillance within the PulseNet Africa network. MethodsWe analysed Vibrio isolates from clinical and environmental sources (2010-2024) using Oxford Nanopore sequencing and hybracter assembly. Phylogenetic analysis, multilocus sequence typing (MLST), virulence and AMR gene detection were performed using Terra, Pathogenwatch, and Cloud Infrastructure for Microbial Bioinformatics (CLMB) platforms, with comparisons against 88 global reference genomes for broader genomic context. ResultsOf 79 high-quality assemblies, 67 were confirmed as V. cholerae, with serogroup O1 accounting for the majority (43/67, 67%). ST69 accounted for 60% (40/67) of isolates, with eight sequence types identified overall. Thirty-seven isolates formed novel sub-clades within AFR12 and AFR15 O1 lineages, suggesting local clonal expansions. AMR gene analysis revealed high resistance to trimethoprim (96%) and quinolones (83%), while resistance to azithromycin, rifampicin, and tetracycline remained low ([≤]7%). A significant proportion of the serogroup O1 isolates (41/43, 95%) harboured resistance genes in at least three antibiotic classes. ConclusionsThis study highlights significant genetic diversity and AMR prevalence in African V. cholerae isolates, with expanding AFR12 and AFR15 clades in the region. The widespread resistance to trimethoprim and quinolones raises concerns for treatment efficacy, although azithromycin and tetracycline remain viable options. WGS enables precise identification of species and genotyping, reinforcing PulseNet Africas pivotal role in advancing genomic surveillance and enabling timely public health responses to cholera outbreaks. Data summaryAll supporting data and protocols have been provided within the article or as supplementary data files. The ONT reads have been deposited under BioProject accession PRJNA1192988, while the high-quality Vibrio spp. assemblies have been shared via figshare (Foster-Nyarko, Ebenezer (2024). Genomic Diversity and Antimicrobial Resistance of Vibrio spp. Isolates from Africa: A PulseNet Africa Initiative Using Nanopore Sequencing to Enhance Genomic Surveillance. figshare. Dataset. https://doi.org/10.6084/m9.figshare.27941376.v1). Individual accession numbers for these reads and Biosample IDs are provided in File S2, available with the online version of this article. The accession numbers for the 88 reference genome assemblies included in our analysis are also provided in File S3. Impact statementCholera remains a significant public health challenge in Africa, disproportionately affecting the region due to the ongoing transmission of Vibrio cholerae O1 and the emergence of antimicrobial resistance (AMR). This study demonstrates the utility of Oxford Nanopore Technology (ONT) sequencing in providing high-resolution insights into the genomic diversity, transmission dynamics, and AMR profiles of V. cholerae isolates across Africa. By generating and analysing whole-genome sequences, we identified novel sublineages, high prevalence rates of AMR genes, and virulence traits critical to cholera pathogenesis. These findings contribute to a deeper understanding of the epidemiology and evolution of V. cholerae in Africa, informing targeted intervention strategies. Furthermore, the study highlights the growing threat posed by AMR among V. cholerae isolates, including resistance to key therapeutic antibiotics, such as quinolones and trimethoprim, which could undermine current treatment protocols. Despite this, the absence of resistance to azithromycin and rifampicin among the O1 isolates suggests these drugs may remain viable treatment options, offering a critical avenue for preserving treatment efficacy. This research also underscores the importance of sustained genomic surveillance, capacity building, and regional collaboration to mitigate the public health impact of cholera and other foodborne pathogens. By leveraging WGS technologies and training initiatives, such as the PulseNet Africa genomics workshop, this study provides a framework for strengthening regional capacities to detect, monitor, and respond to cholera outbreaks and the spread of AMR. These efforts align with the African Union and Africa CDCs strategic priorities on health security and AMR, contributing to improved public health systems and cholera control across the continent.

genomics↗

bioRxiv2025

Genomic feature of filled regions of telomere-to-telomere genomes in five model species

T2T genome is a telomere-to-telomere high-quality genome with exceptional accuracy, continuity and integrity. It significantly filled some gaps of chromosome. However, the genomic features unique to the filled regions assembled in the T2T genome across species remain unclear. Here, we collected and compared T2T genomes with their older version from human (Homo sapiens), animal (Mus musculus), and plants (Arabidopsis thaliana, Musa acuminata, and Fragaria vesca). We explored the newly filled regions generated by the T2T genome in comparison to the old one, and focused on: (1) the comparison of their locations, (2) the distribution of genomic features, and (3) gene annotation and gene function for filled regions. Research indicated that the filled regions of the T2T genome ordinarily appear in the centromere and telomere regions, contain a great number of repetitive sequences. The T2T genome revealed the identification of a certain number of newly annotated genes, alongside significant variations in common annotated genes. Interestingly, the genomic features of filled regions exhibit distinct patterns between plants and human/animal. T2T genomes feature analysis serves as a crucial resource for studying pattern characteristics across diverse species and advancing the in-depth development of genomics.

genomics↗

bioRxiv2025

End-to-end genomic prediction: direct prediction of images and text from genome-wide molecular markers

BackgroundMethods to predict the heritable component of phenotypes from genetic markers, collectively known as genomic prediction, have been widely applied in plant and animal breeding and in human genetics. Currently, genomic prediction is limited to numeric phenotypes. In some cases, though, plant and animal phenotypes are better understood through images and text rather than numbers. The current best practice for incorporating images and text in genomic prediction is to first extract scalar numeric phenotypes from images and text, and then to perform genomic prediction on the numeric phenotypes. While this approach is effective for some traits, it involves discarding most of the information in the image or text, including potentially useful information. Additionally, numeric phenotypes derived from images and text may not be as interpretable as the images and text themselves. ApproachWe present a novel approach for predicting images and text from SNP markers, which we refer to as end-to-end genomic prediction, and validate this approach using genotypes, text, and image phenotypes derived from a strawberry (Fragaria x ananassa) diversity panel. Our approach combines nonlinear latent space encoding with linear genomic prediction to generate accurate breeding values for a high-dimensional phenotype, for example, images or text. ResultsFor both genome-to-image and genome-to-text prediction, we found that predicting images and text and then extracting numeric traits from them was in some cases as accurate as directly predicting extracted numeric phenotypes, demonstrating for the first time that genome-to-image prediction accuracy can be comparable to conventional genomic prediction accuracy. ConclusionsBased on our proof-of-concept using the same core end-to-end method in both images and text, we believe end-to-end genomic prediction could be of use in a wide range of visual and multidimensional phenotypes in plants and animals, although further work to improve the accuracy of the embedding and genomic prediction steps is needed.

genomics↗

bioRxiv2018

The whale shark genome reveals how genomic and physiological properties scale with body size

The endangered whale shark (Rhincodon typus) is the largest fish on Earth and is a long-lived member of the ancient Elasmobranchii clade. To characterize the relationship between genome features and biological traits, we sequenced and assembled the genome of the whale shark and compared its genomic and physiological features to those of 81 animals and yeast. We examined scaling relationships between body size, temperature, metabolic rates, and genomic features and found both general correlations across the animal kingdom and features specific to the whale shark genome. Among animals, increased lifespan is positively correlated to body size and metabolic rate. Several genomic features also significantly correlated with body size, including intron and gene length. Our large-scale comparative genomic analysis uncovered general features of metazoan genome architecture: GC content and codon adaptation index are negatively correlated, and neural connectivity genes are longer than average genes in most genomes. Focusing on the whale shark genome, we identified multiple features that significantly correlate with lifespan. Among these were very long gene length, due to large introns highly enriched in repetitive elements such as CR1-like LINEs, and considerably longer neural genes of several types, including connectivity, activity, and neurodegeneration genes. The whale sharks genome had an expansion of gene families related to fatty acid metabolism and neurogenesis, with the slowest evolutionary rate observed in vertebrates to date. Our comparative genomics approach uncovered multiple genetic features associated with body size, metabolic rate, and lifespan, and showed that the whale shark is a promising model for studies of neural architecture and lifespan.

genomics↗

bioRxiv2017

The genomic landscape at a late stage of stickleback speciation: high genomic divergence interspersed by small localized regions of introgression

Speciation is a continuous process and analysis of species pairs at different stages of divergence provides insight into how it unfolds. Genomic studies on young species pairs have often revealed peaks of divergence and heterogeneous genomic differentiation. Yet it remains unclear how localised peaks of differentiation progress to genome-wide divergence during the later stages of speciation with gene flow. Spanning the speciation continuum, stickleback species pairs are ideal for investigating how genomic divergence builds up during speciation. However, attention has largely focused on young postglacial species pairs, with little known of the genomic signatures of divergence and introgression in older systems. The Japanese stickleback species pair, composed of the Pacific Ocean three-spined stickleback (Gasterosteus aculeatus) and the Japan Sea stickleback (G. nipponicus), which co-occur in the Japanese islands, is at a late stage of speciation. Divergence likely started well before the end of the last glacial period and crosses between Japan Sea females and Pacific Ocean males result in hybrid male sterility. Here we use coalescent analyses and Approximate Bayesian computation to show that the two species split approximately 0.68-1 million years ago but that they have continued to hybridise at a low rate throughout divergence. Population genomic data revealed that high levels of genomic differentiation are maintained across the majority of the genome when gene flow occurs. However despite this, we identified multiple, small regions of introgression, strongly correlated with recombination rate. Our results demonstrate that a high level of genome-wide divergence can establish in the face of persistent introgression and that gene flow can be localized to small genomic regions at the later stages of speciation with gene flow.\n\nAuthor summaryWhen species evolve, reproductive isolation leads to a build-up of differentiation in the genome where genes involved in the process occur. Much of our understanding of this comes from early stage speciation, with relatively few examples from more divergent species pairs that still exchange genes. To address this, we focused on Pacific Ocean and Japan Sea sticklebacks, which co-occur in the Japanese islands. We established that they are the oldest and most divergent known stickleback species pair, that they evolved in the face of gene flow and that this gene flow is still on going. We found introgression is confined to small, localised genomic regions where recombination rate is high. Our results show high divergence can be maintained between species, despite extensive gene flow.

evolutionary biology↗

bioRxiv2017

Fast and Accurate Genomic Analyses using Genome Graphs

The human reference genome serves as the foundation for genomics by providing a scaffold for alignment of sequencing reads, but currently only reflects a single consensus haplotype, which impairs read alignment and downstream analysis accuracy. Reference genome structures incorporating known genetic variation have been shown to improve the accuracy of genomic analyses, but have so far remained computationally prohibitive for routine large-scale use. Here we present a graph genome implementation that enables read alignment across 2,800 diploid genomes encompassing 12.6 million SNPs and 4.0 million indels. Our Graph Genome Pipeline requires 6.5 hours to process a 30x coverage WGS sample on a system with 36 CPU cores compared with 11 hours required by the GATK Best Practices pipeline. Using complementary benchmarking experiments based on real and simulated data, we show that using a graph genome reference improves read mapping sensitivity and produces a 0.5% increase in variant calling recall, or about 20,000 additional variants being detected per sample, while variant calling specificity is unaffected. Structural variations (SVs) incorporated into a graph genome can be genotyped accurately under a unified framework. Finally, we show that iterative augmentation of graph genomes yields incremental gains in variant calling accuracy. Our implementation is a significant advance towards fulfilling the promise of graph genomes to radically enhance the scalability and accuracy of genomic analyses.

bioinformatics↗

bioRxiv2021

Nuclear genome of a pedinophyte pinpoints genomic innovation and streamlining in the green algae

The genomic diversity underpinning high ecological and species diversity in the green algae (Chlorophyta) remains little known. Here, we aimed to track genome evolution in the Chlorophyta, focusing on loss and gain of homologous genes, and lineage-specific innovations of the Core Chlorophyta. We generated a high-quality nuclear genome for pedinophyte YPF701, a sister lineage to others in the Core Chlorophyta, and incorporated this genome in a comparative analysis with 25 other genomes from diverse Viridiplantae taxa. The nuclear genome of pedinophyte YPF701 has an intermediate size and gene number between those of most early-diverging prasinophytes and the remainder of the Core Chlorophyta. Our results suggest positive selection for genome streamlining in Pedinophyceae, independent from genome minimisation observed among prasinophyte lineages. Genome expansion was predicted along the branch leading to the UTC clade (classes Ulvophyceae, Trebouxiophyceae and Chlorophyceae) after divergence from their common ancestor with pedinophytes, with genomic novelty implicated in a range of basic biological functions. These results emphasise multiple independent signals of genome minimisation within the Chlorophyta, as well as the genomic novelty arising prior to diversification in the UTC clade, which may underpin the success of this species-rich clade in a diversity of habitats.

evolutionary biology↗

bioRxiv2021

Large-scale comparative genomics unravels great genomic diversity across the Rickettsia and Ca. Megaira genera and identifies Torix group as an evolutionarily distinct clade.

Rickettsia are intracellular bacteria originally described as arthropod borne pathogens that are emerging as a diverse group of often biologically important, non-pathogenic symbionts of invertebrates and microeukaryotes. However, sparse genomic resources for symbiotic strains and for the sister genus (Candidatus Megaira) inhibit our understanding of Rickettsia evolution and biology. Here, we present the first closed genomes of Ca. Megaira from an alga (Mesostigma viride), and Torix Rickettsia from midge (Culicoides impunctatus) and bed bug (Cimex lectularius) hosts. Additionally, we sequenced and constructed draft genomes for Ca. Megaira from another alga (Carteria cerasiformis), Transitional group Rickettsia from tsetse fly (Glossina morsitans submorsitans), and Torix Rickettsia from a spider mite (Bryobia graminum). We further extract 22 draft genomes from arthropod genome sequencing projects, including 1 Adalia, 4 Transitional, 1 Spotted Fever, 7 Torix, 7 Belli and the first Rhyzobius and Meloidae Rickettsia group genomes. We used new and existing Rickettsia genomes to estimate the phylogeny and metabolic potential across groups and reveal transitions in genomic properties. These data reveal Torix as unique amongst currently described Rickettsia, with highly distinct and diverse accessory genomes. We confirm the presence of a third subclade of Torix, previously only known from gene marker sequences. Further, Torix share an intact pentose phosphate pathway with Ca. Megaira, not observed in other Rickettsia. Considering the distinctness and diversity of Torix, we propose that the group be named Candidatus Tisiphia. The wide host range of Ca. Tisiphia symbionts necessitates onward research to understand the biological and physiological bases of Ca. Tisiphia-host interactions. Importance statementMembers of the genus Rickettsia were originally identified as causative agents of mammalian vector-borne disease. In the last 25 years we have recognised that many Rickettsia are arthropod symbionts, and sit alongside a sister taxon, Ca. Megaira, which are symbiotic associates of microeukaryotes. The lack of genomic information for symbiotic strains affects our ability to determine the evolutionary relationships between strains and understand the biological underpinnings of the different symbioses. We clarify these relationships by assembling 26 genomes of Rickettsia from understudied groups, and the first two Ca. Megaira, from various insects and microeukaryotes. Of note, the accessory genome diversity and broad host range of Torix Rickettsia parallels all other Rickettsia combined. This diversity, alongside the breadth of host species, make the Torix clade an important hidden player in invertebrate biology and physiology. We argue this clade should be given its own genus status, for which we propose Ca. Tisiphia.

microbiology↗

bioRxiv2022

Welcome to the big leaves: best practices for improving genome annotation in non-model plant genomes

* Premise of the studyRobust standards to evaluate quality and completeness are lacking for eukaryotic structural genome annotation. Genome annotation software is developed with model organisms and does not typically include benchmarking to comprehensively evaluate the quality and accuracy of the final predictions. Plant genomes are particularly challenging with their large genome sizes, abundant transposable elements (TEs), and variable ploidies. This study investigates the impact of genome quality, complexity, sequence read input, and approach on protein-coding gene prediction. * MethodsThe impact of repeat masking, long-read, and short-read inputs, de novo, and genome-guided protein evidence was examined in the context of the popular BRAKER and MAKER workflows for five plant genomes. Annotations were benchmarked for structural traits and sequence similarity. * ResultsBenchmarks that reflect gene structures, reciprocal similarity search alignments, and mono-exonic/multi-exonic gene counts provide a more complete view of annotation accuracy. Transcripts derived from RNA-read alignments alone are not sufficient for genome annotation. Gene prediction workflows that combine evidence-based and ab initio approaches are recommended, and a combination of short and long-reads can improve genome annotation. Adding protein evidence from de novo assemblies, genome-guided transcriptome assemblies, or full-length proteins from OrthoDB generates more putative false positives as implemented in the current workflows. Post-processing with functional and structural filters is highly recommended. * DiscussionWhile annotation of non-model plant genomes remains complex, this study provides recommendations for inputs and methodological approaches. We discuss a set of best practices to generate an optimal plant genome annotation, and present a more robust set of metrics to evaluate the resulting predictions.

bioinformatics↗

bioRxiv2024

Chlomito: a novel tool for precise elimination of organelle genome contamination in nuclear genome assemblies

Accurate genome assemblies are crucial for understanding biological evolution, mechanisms of disease, and biodiversity. However, contamination from organelle genomes in nuclear genome analyses often leads to inaccuracies and unreliability in results. To address this issue, we developed a tool named Chlomito, which employs innovative algorithms to precisely identify and eliminate organelle genome contamination sequences from nuclear genome assemblies. Compared to conventional approaches, Chlomito can not only detect and eliminate organelle sequences but also effectively distinguish true organelle sequences from those transferred into the nucleus via horizontal gene transfer. To evaluate the accuracy of Chlomito, we conducted tests using sequencing data from Plum and Mango. The results confirmed that Chlomito can accurately detect contigs originating from the organelle genome, and the identified contigs covered most regions of the organelle reference genomes, demonstrating its efficiency and precision in comprehensively recognizing organelle genome sequences. Additionally, for user convenience, we packaged this method into a Docker image, simplifying the data processing workflow. Overall, Chlomito provides a highly efficient and accurate method for identifying and removing contigs derived from organelle genomes in genomic assembly data, thereby contributing to the improvement of genome assembly quality and advancing research in genomics and evolutionary biology.

bioinformatics↗

bioRxiv2024

Genomic Analysis of Human-infecting Leptospira borgpetersenii isolates in Sri Lanka expanded PF07598 gene family repertoire, less overall genome reduction than bovine isolates

Leptospira borgpetersenii commonly causes human leptospirosis, including severe disease. The first published analysis of L. borgpetersenii, performed on two strains of serovar Hardjo (L550 and JB197), concluded that the L. borgpetersenii genome is in the process of genome decay with functional consequences leading to a more obligately host-dependent life cycle. Yet whole genome analysis has only been carried out on few strains of L. borgpetersenii, with limited closed genomes and comprehensive analysis. Herein we report the complete, circularized genomes of seven non-Hardjo Leptospira borgpetersenii isolates from human leptospirosis patients in Sri Lanka. These isolates (all ST144) were found to be nearly identical by whole genome analysis; serotyping showed they are a novel serovar. We show that the L. borgpetersenii isolated from humans in Sri Lanka are less genomically decayed than previously reported isolates: fewer pseudogenes (N=141) and Insertion Sequence (IS) elements (N=46) compared to N=248, N=270, and N=400 pseudogenes, and N=121 and N=116 IS elements in published L. borgpetersenii Hardjo genomes (L550, JB197 and TC112). Compared to previously published L. borgpetersenii whole genome analyses showing two to three VM proteins in L. borgpetersenii isolates from cattle, rats and humans, we found that all of the human L. borgpetersenii isolates from Sri Lanka, including previously reported serovar Piyasena, have 4 encoded VM proteins, one ortholog of L. interrogans Copenhageni LIC12339 and 3 orthologs of LIC12844. Our findings of fewer pseudogenes, IS elements and expansion of the LIC12844 homologs of the PF07598 family in these human isolates suggests that this newly identified L. borgpetersenii serovar from Sri Lanka has unique pathogenicity. Comparative genome analysis and experimental studies of these L. borgpetersenii isolates will enable deeper insights into the molecular and cellular mechanisms of leptospirosis pathogenesis. Author SummaryLeptospirosis is an emerging bacterial zoonosis worldwide. Leptospira borgpetersenii predominates as the cause of human leptospirosis in some agricultural contexts. We address here the relatively neglected comparative genome analysis of L. borgpetersenii. We show here that L. borgpetersenii isolated from humans in Sri Lanka have less genome reduction compared to available cattle isolates and have novel virulence characteristics compared to isolates from other animals including cattle and rats.

microbiology↗

bioRxiv2018

Proteomics as a metrological tool to evaluate genome annotation accuracy following de novo genome assembly: a case study using the Atlantic bottlenose dolphin (Tursiops truncatus)

BackgroundThe last decade has witnessed dramatic improvements in whole-genome sequencing capabilities coupled to drastically decreased costs, leading to an inundation of high-quality de novo genomes. For this reason, continued development of genome quality metrics is imperative. The current study utilized the recently updated Atlantic bottlenose dolphin (Tursiops truncatus) genome and annotation to evaluate a proteomics-based metric of genome accuracy.\n\nResultsProteomic analysis of six tissues provided experimental confirmation of 10 402 proteins from 4 711 protein groups, almost 1/3 of the possible predicted proteins in the genome. There was an increased median molecular weight and number of identified peptides per protein using the current T. truncatus annotation versus the previous annotation. Identification of larger proteins with more identified peptides implied reduced database fragmentation and improved gene annotation accuracy. A metric is proposed, NP10, that attempts to capture this quality improvement. When using the new T. truncatus genome there was a 21 % improvement in NP10. This metric was further demonstrated by using a publicly available proteomic data set to compare human genome annotations from 2004, 2013 and 2016, which had a 33 % improvement in NP10.\n\nConclusionsThese results demonstrate that new whole-genome sequencing techniques can rapidly generate high quality de novo genome assemblies and emphasizes the speed of advancing bioanalytical measurements in a non-model organism. Moreover, proteomics may be a useful metrological tool to benchmark genome accuracy, though there is a need for reference proteomic datasets to facilitate this utility in new de novo and existing genomes.

bioinformatics↗

bioRxiv2018

Fusobacterium genomics using MinION and Illumina sequencing enables genome completion and correction

Understanding the virulence mechanisms of human pathogens from the genus Fusobacterium has been hindered by a lack of properly assembled and annotated genomes. Here we report the first complete genomes for seven Fusobacterium strains, as well as resequencing of the reference strain F. nucleatum subsp. nucleatum ATCC 25586 (seven total species, eight total genomes). A highly efficient and cost-effective sequencing pipeline was achieved using sample multiplexing for short-read Illumina (150 bp) and long-read Oxford Nanopore MinION (>80 kbp) platforms, coupled with genome assembly using the open-source software Unicycler. When compared to currently available draft assemblies (previously 24-67 contigs), these genomes are highly accurate and consist of only one complete chromosome. We present the complete genome sequence of F. nucleatum 23726, a genetically tractable and biomedically important strain, and in addition, reveal that the previous F. nucleatum 25586 genome assembly contains a 452 kb genomic inversion that has been corrected using our sequencing and assembly pipeline. To enable the scientific community, we concurrently use these genomes to launch FusoPortal, a repository of interactive and downloadable genomic data, genome maps, gene annotations, and protein functional analysis and classification. In summary, this study provides detailed methods for accurately sequencing, assembling, and annotating Fusobacterium genomes, which will enhance efforts to properly identify virulence proteins that may contribute to a repertoire of diseases including periodontitis, pre-term birth, and colorectal cancer.

microbiology↗

bioRxiv2019

Robust Genome-Wide Ancestry Inference for Heterogeneous Datasets and Ancestry Facial Imaging based on the 1000 Genomes Project

Accurate inference of genomic ancestry is critically important in human genetics, epidemiology, and related fields. Geneticists today have access to multiple heterogeneous population-based datasets from studies collected under different protocols. Therefore, joint analyses of these datasets require robust and consistent inference of ancestry, where a common strategy is to yield an ancestry space generated by a reference dataset. However, such a strategy is sensitive to batch artefacts introduced by different protocols. In this work, we propose a novel robust genome-wide ancestry inference method; referred to as SUGIBS, based on an unnormalized genomic (UG) relationship matrix whose spectral (S) decomposition is generalized by an Identity-by-State (IBS) similarity degree matrix. SUGIBS robustly constructs an ancestry space from a single reference dataset, and provides a robust projection of new samples, from different studies. In experiments and simulations, we show that, SUGIBS is robust against individual outliers and batch artifacts introduced by different genotyping protocols. The performance of SUGIBS is equivalent to the widely used principal component analysis (PCA) on normalized genotype data in revealing the underlying structure of an admixed population and in adjusting for false positive findings in a case-control admixed GWAS. We applied SUGIBS on the 1000 Genome project, as a reference, in combination with a large heterogeneous dataset containing auxiliary 3D facial images, to predict population stratified average or ancestry faces. In addition, we projected eight ancient DNA profiles into the 1000 Genome ancestry space and reconstructed their ancestry face. Based on the visually strong and recognizable human facial phenotype, comprehensive facial illustrations of the populations embedded in the 1000 Genome project are provided. Furthermore, ancestry facial imaging has important applications in personalized and precision medicine along with forensic and archeological DNA phenotyping. Author SummaryEstimates of individual-level genomic ancestry are routinely used in human genetics, epidemiology, and related fields. The analysis of population structure and genomic ancestry can yield significant insights in terms of modern and ancient population dynamics, allowing us to address questions regarding the timing of the admixture events, and the numbers and identities of the parental source populations. Unrecognized or cryptic population structure is also an important confounder to correct for in genome-wide association studies (GWAS). However, to date, it remains challenging to work with heterogeneous datasets from multiple studies collected by different laboratories with diverse genotyping and imputation protocols. This work presents a new approach and an accompanying open-source software toolbox that facilitates a robust integrative analysis for population structure and genomic ancestry estimates for heterogeneous datasets. Given that visually evident and easily recognizable patterns of human facial characteristics covary with genomic ancestry, we can generate predicted ancestry faces on both the population and individual levels as we illustrate for the 26 1000 Genome populations and for eight eminent ancient-DNA profiles, respectively.

genetics↗