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BACKGROUND: MPT64 is a key protein used for Mycobacterium tuberculosis (MTB) complex strain identification. We describe protracted transmission of an MPT64 negative MTB strain in Queensland, Australia, and explore genomic factors related to its successful spread. METHODS: All MPT64 negative strains identified between 2002 and 2022 by the Queensland Mycobacteria Reference Laboratory, and an additional 2 isolates from New South Wales (NSW), were whole genome sequenced. Bayesian modelling and phylogeographical analyses were used to assess their evolutionary history and transmission dynamics. Protein structural modelling to understand the putative functional effects of the mutated gene coding for MPT64 protein was performed. FINDINGS: Forty-three MPT64 negative isolates were sequenced, belonging to a single MTB cluster of Lineage 4.1.1.1 strains. Combined with a UK dataset of the same lineage, molecular dating estimated 1990 (95% HPD 1987-1993) as the likely time of strain introduction into Australia. Although the strain has spread over a wide geographic area and new cases linked to the cluster continue to arise, phylodynamic analysis suggest the outbreak peaked around 2003. All MPT64 negative strains had a frame shift mutation (delAT, p.Val216fs) within the MPT64 gene, which confers two major structural rearrangements at the C-terminus of the protein. INTERPRETATION: This study uncovered the origins of an MPT64 negative MTB outbreak in Australia, providing a richer understanding of its biology and transmission dynamics, as well as guidance for clinical diagnosis and public health action. The potential spread of MPT64 negative strains undermines the diagnostic utility of the MPT64 immunochromatographic test. FUNDING: This study was funded from an operational budget provided to the Queensland Mycobacterium Reference Laboratory by Pathology Queensland, Queensland Department of Health.

BACKGROUND: Sepsis is defined as dysregulated host response to infection that leads to life-threatening organ dysfunction. Biomarkers characterising the dysregulated host response in sepsis are lacking. We aimed to develop host gene expression signatures to predict organ dysfunction in children with bacterial or viral infection. METHODS: This cohort study was done in emergency departments and intensive care units of four hospitals in Queensland, Australia, and recruited children aged 1 month to 17 years who, upon admission, underwent a diagnostic test, including blood cultures, for suspected sepsis. Whole-blood RNA sequencing of blood was performed with Illumina NovaSeq (San Diego, CA, USA). Samples with completed phenotyping, monitoring, and RNA extraction by March 31, 2020, were included in the discovery cohort; samples collected or completed thereafter and by Oct 27, 2021, constituted the Rapid Paediatric Infection Diagnosis in Sepsis (RAPIDS) internal validation cohort. An external validation cohort was assembled from RNA sequencing gene expression count data from the observational European Childhood Life-threatening Infectious Disease Study (EUCLIDS), which recruited children with severe infection in nine European countries between 2012 and 2016. Feature selection approaches were applied to derive novel gene signatures for disease class (bacterial vs viral infection) and disease severity (presence vs absence of organ dysfunction 24 h post-sampling). The primary endpoint was the presence of organ dysfunction 24 h after blood sampling in the presence of confirmed bacterial versus viral infection. Gene signature performance is reported as area under the receiver operating characteristic curves (AUCs) and 95% CI. FINDINGS: Between Sept 25, 2017, and Oct 27, 2021, 907 patients were enrolled. Blood samples from 595 patients were included in the discovery cohort, and samples from 312 children were included in the RAPIDS validation cohort. We derived a ten-gene disease

Continuous assessment of the impact of SARS-CoV-2 on the host at the cell-type level is crucial for understanding key mechanisms involved in host defense responses to viral infection. We investigated host response to ancestral-strain and Alpha-variant SARS-CoV-2 infections within air-liquid-interface human nasal epithelial cells from younger adults (26-32 Y) and older children (12-14 Y) using single-cell RNA-sequencing. Ciliated and secretory-ciliated cells formed the majority of highly infected cell-types, with the latter derived from ciliated lineages. Strong innate immune responses were observed across lowly infected and uninfected bystander cells and heightened in Alpha-infection. Alpha highly infected cells showed increased expression of protein-refolding genes compared with ancestral-strain-infected cells in children. Furthermore, oxidative phosphorylation-related genes were down-regulated in bystander cells versus infected and mock-control cells, underscoring the importance of these biological functions for viral replication. Overall, this study highlights the complexity of cell-type-, age- and viral strain-dependent host epithelial responses to SARS-CoV-2.

MOTIVATION: PE/PPE proteins, highly abundant in the Mycobacterium genome, play a vital role in virulence and immune modulation. Understanding their functions is key to comprehending the internal mechanisms of Mycobacterium. However, a lack of dedicated resources has limited research into PE/PPE proteins. RESULTS: Addressing this gap, we introduce MycobactERIal PE/PPE proTeinS (MERITS), a comprehensive 3D structure database specifically designed for PE/PPE proteins. MERITS hosts 22 353 non-redundant PE/PPE proteins, encompassing details like physicochemical properties, subcellular localization, post-translational modification sites, protein functions, and measures of antigenicity, toxicity, and allergenicity. MERITS also includes data on their secondary and tertiary structure, along with other relevant biological information. MERITS is designed to be user-friendly, offering interactive search and data browsing features to aid researchers in exploring the potential functions of PE/PPE proteins. MERITS is expected to become a crucial resource in the field, aiding in developing new diagnostics and vaccines by elucidating the sequence-structure-functional relationships of PE/PPE proteins. AVAILABILITY AND IMPLEMENTATION: MERITS is freely accessible at http://merits.unimelb-biotools.cloud.edu.au/.

Bovine respiratory disease (BRD) is the leading cause of morbidity and mortality in feedlot cattle. Bovine herpesvirus-1 (BHV-1) is one of the main culprits of BRD; however, research on BHV-1 is hampered by the lack of suitable models for infection and drug testing. In this study, we established a novel bovine tracheal organoid culture grown in a basement membrane extract type 2 (BME2) matrix and compared it with the air–liquid interface (ALI) culture system. After differentiation, the matrix-embedded organoids developed beating cilia and demonstrated a transcriptomic profile similar to the ALI culture system. The matrix-embedded organoids were also highly susceptible to BHV-1 infection and immune stimulation by Pam2Cys, an immunomodulator, which resulted in robust cytokine production and tracheal antimicrobial peptide mRNA upregulation. However, treatment of bovine tracheal organoid cultures with Pam2Cys was not sufficient to inhibit viral infection or replication, suggesting a role of the non-epithelial cellular microenvironment in vivo.

A new variant of Streptococcus pyogenes serotype M1 (designated 'M1UK') has been reported in the United Kingdom, linked with seasonal scarlet fever surges, marked increase in invasive infections, and exhibiting enhanced expression of the superantigen SpeA. The progenitor S. pyogenes 'M1global' and M1UK clones can be differentiated by 27 SNPs and 4 indels, yet the mechanism for speA upregulation is unknown. Here we investigate the previously unappreciated expansion of M1UK in Australia, now isolated from the majority of serious infections caused by serotype M1 S. pyogenes. M1UK sub-lineages circulating in Australia also contain a novel toxin repertoire associated with epidemic scarlet fever causing S. pyogenes in Asia. A single SNP in the 5' transcriptional leader sequence of the transfer-messenger RNA gene ssrA drives enhanced SpeA superantigen expression as a result of ssrA terminator read-through in the M1UK lineage. This represents a previously unappreciated mechanism of toxin expression and urges enhanced international surveillance.

A new variant of Streptococcus pyogenes serotype M1 (designated 'M1UK') has been reported in the United Kingdom, linked with seasonal scarlet fever surges, marked increase in invasive infections, and exhibiting enhanced expression of the superantigen SpeA. The progenitor S. pyogenes 'M1global' and M1UK clones can be differentiated by 27 SNPs and 4 indels, yet the mechanism for speA upregulation is unknown. Here we investigate the previously unappreciated expansion of M1UK in Australia, now isolated from the majority of serious infections caused by serotype M1 S. pyogenes. M1UK sub-lineages circulating in Australia also contain a novel toxin repertoire associated with epidemic scarlet fever causing S. pyogenes in Asia. A single SNP in the 5' transcriptional leader sequence of the transfer-messenger RNA gene ssrA drives enhanced SpeA superantigen expression as a result of ssrA terminator read-through in the M1UK lineage. This represents a previously unappreciated mechanism of toxin expression and urges enhanced international surveillance.

Conventional supervised binary classification algorithms have been widely applied to address significant research questions using biological and biomedical data. This classification scheme requires two fully labeled classes of data (e.g. positive and negative samples) to train a classification model. However, in many bioinformatics applications, labeling data is laborious, and the negative samples might be potentially mislabeled due to the limited sensitivity of the experimental equipment. The positive unlabeled (PU) learning scheme was therefore proposed to enable the classifier to learn directly from limited positive samples and a large number of unlabeled samples (i.e. a mixture of positive or negative samples). To date, several PU learning algorithms have been developed to address various biological questions, such as sequence identification, functional site characterization and interaction prediction. In this paper, we revisit a collection of 29 state-of-the-art PU learning bioinformatic applications to address various biological questions. Various important aspects are extensively discussed, including PU learning methodology, biological application, classifier design and evaluation strategy. We also comment on the existing issues of PU learning and offer our perspectives for the future development of PU learning applications. We anticipate that our work serves as an instrumental guideline for a better understanding of the PU learning framework in bioinformatics and further developing next-generation PU learning frameworks for critical biological applications.

Better methods to interrogate host-pathogen interactions during Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) infections are imperative to help understand and prevent this disease. Here we implemented RNA-sequencing (RNA-seq) using Oxford Nanopore Technologies (ONT) long-reads to measure differential host gene expression, transcript polyadenylation and isoform usage within various epithelial cell lines permissive and non-permissive for SARS-CoV-2 infection. SARS-CoV-2-infected and mock-infected Vero (African green monkey kidney epithelial cells), Calu-3 (human lung adenocarcinoma epithelial cells), Caco-2 (human colorectal adenocarcinoma epithelial cells) and A549 (human lung carcinoma epithelial cells) were analyzed over time (0, 2, 24, 48 hours). Differential polyadenylation was found to occur in both infected Calu-3 and Vero cells during a late time point (48 hpi), with Gene Ontology (GO) terms such as viral transcription and translation shown to be significantly enriched in Calu-3 data. Poly(A) tails showed increased lengths in the majority of the differentially polyadenylated transcripts in Calu-3 and Vero cell lines (up to ~101 nt in mean poly(A) length, padj = 0.029). Of these genes, ribosomal protein genes such as RPS4X and RPS6 also showed downregulation in expression levels, suggesting the importance of ribosomal protein genes during infection. Furthermore, differential transcript usage was identified in Caco-2, Calu-3 and Vero cells, including transcripts of genes such as GSDMB and KPNA2, which have previously been implicated in SARS-CoV-2 infections. Overall, these results highlight the potential role of differential polyadenylation and transcript usage in host immune response or viral manipulation of host mechanisms during infection, and therefore, showcase the value of long-read sequencing in identifying less-explored host responses to disease.

Mycobacterium tuberculosis genome comprises approximately 10% of two families of poorly characterised genes due to their high GC content and highly repetitive nature. The largest sub-group, the proline-glutamic acid polymorphic guanine-cytosine-rich sequence (PE_PGRS) family, is thought to be involved in host response and disease pathogenicity. Due to their high genetic variability and complexity of analysis, they are typically disregarded for further research in genomic studies. There are currently limited online resources and homology computational tools that can identify and analyse PE_PGRS proteins. In addition, they are computational-intensive and time-consuming, and lack sensitivity. Therefore, computational methods that can rapidly and accurately identify PE_PGRS proteins are valuable to facilitate the functional elucidation of the PE_PGRS family proteins. In this study, we developed the first machine learning-based bioinformatics approach, termed PEPPER, to allow users to identify PE_PGRS proteins rapidly and accurately. PEPPER was built upon a comprehensive evaluation of 13 popular machine learning algorithms with various sequence and physicochemical features. Empirical studies demonstrated that PEPPER achieved significantly better performance than alignment-based approaches, BLASTP and PHMMER, in both prediction accuracy and speed. PEPPER is anticipated to facilitate community-wide efforts to conduct high-throughput identification and analysis of PE_PGRS proteins.

BACKGROUND: Circulating cell-free DNA (cfDNA) in the plasma of cancer patients contains cell-free tumour DNA (ctDNA) derived from tumour cells and it has been widely recognized as a non-invasive source of tumour DNA for diagnosis and prognosis of cancer. Molecular profiling of ctDNA is often performed using targeted sequencing or low-coverage whole genome sequencing (WGS) to identify tumour specific somatic mutations or somatic copy number aberrations (sCNAs). However, these approaches cannot efficiently detect all tumour-derived genomic changes in ctDNA. METHODS: We performed WGS analysis of cfDNA from 4 breast cancer patients and 2 patients with benign tumours. We sequenced matched germline DNA for all 6 patients and tumour samples from the breast cancer patients. All samples were sequenced on Illumina HiSeqXTen sequencing platform and achieved approximately 30x, 60x and 100x coverage on germline, tumour and plasma DNA samples, respectively. RESULTS: The mutational burden of the plasma samples (1.44 somatic mutations/Mb of genome) was higher than the matched tumour samples. However, 90% of high confidence somatic cfDNA variants were not detected in matched tumour samples and were found to comprise two background plasma mutational signatures. In contrast, cfDNA from the di-nucleosome fraction (300 bp-350 bp) had much higher proportion (30%) of variants shared with tumour. Despite high coverage sequencing we were unable to detect sCNAs in plasma samples. CONCLUSIONS: Deep sequencing analysis of plasma samples revealed higher fraction of unique somatic mutations in plasma samples, which were not detected in matched tumour samples. Sequencing of di-nucleosome bound cfDNA fragments may increase recovery of tumour mutations from plasma.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) uses subgenomic RNA (sgRNA) to produce viral proteins for replication and immune evasion. We apply long-read RNA and cDNA sequencing to in vitro human and primate infection models to study transcriptional dynamics. Transcription-regulating sequence (TRS)-dependent sgRNA upregulates earlier in infection than TRS-independent sgRNA. An abundant class of TRS-independent sgRNA consisting of a portion of open reading frame 1ab (ORF1ab) containing nsp1 joins to ORF10, and the 3' untranslated region (UTR) upregulates at 48 h post-infection in human cell lines. We identify double-junction sgRNA containing both TRS-dependent and -independent junctions. We find multiple sites at which the SARS-CoV-2 genome is consistently more modified than sgRNA and that sgRNA modifications are stable across transcript clusters, host cells, and time since infection. Our work highlights the dynamic nature of the SARS-CoV-2 transcriptome during its replication cycle.

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, that is, 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 (ENSE00003720745) as a pleiotropic locus associated with metabolomic regulation and show that its biology is associated with several metabolic diseases such as type 2 diabetes (T2D) and cancer. Our results further demonstrate the power of multivariate association models over univariate methods and define metabolomic signatures for variants in TSPAN8.

A streaming assembly pipeline utilising real-time Oxford Nanopore Technology (ONT) sequencing data is important for saving sequencing resources and reducing time-to-result. A previous approach implemented in npScarf provided an efficient streaming algorithm for hybrid assembly but was relatively prone to mis-assemblies compared to other graph-based methods. Here we present npGraph, a streaming hybrid assembly tool using the assembly graph instead of the separated pre-assembly contigs. It is able to produce more complete genome assembly by resolving the path finding problem on the assembly graph using long reads as the traversing guide. Application to synthetic and real data from bacterial isolate genomes show improved accuracy while still maintaining a low computational cost. npGraph also provides a graphical user interface (GUI) which provides a real-time visualisation of the progress of assembly. The tool and source code is available at https://github.com/hsnguyen/assembly.

BACKGROUND: Sepsis contributes significantly to morbidity and mortality globally. In Australia, 20,000 develop sepsis every year, resulting in 5,000 deaths, and more than AUD$846 million in expenditure. Prompt, appropriate antibiotic therapy is effective in improving outcomes in sepsis. Conventional culture-based methods to identify appropriate therapy have limited yield and take days to complete. Recently, nanopore technology has enabled rapid sequencing with real-time analysis of pathogen DNA. We set out to demonstrate the feasibility and diagnostic accuracy of pathogen sequencing direct from clinical samples, and estimate the impact of this approach on time to effective therapy when integrated with personalised software-guided antimicrobial dosing in children and adults on ICU with sepsis. METHODS: The DIRECT study is a pilot prospective, non-randomized multicentre trial of an integrated diagnostic and therapeutic algorithm combining rapid direct pathogen sequencing and software-guided, personalised antibiotic dosing in children and adults with sepsis on ICU. PARTICIPANTS AND INTERVENTIONS: DIRECT will collect microbiological and pharmacokinetic samples from approximately 200 children and adults with sepsis admitted to one of four ICUs in Brisbane. In Phase 1, we will evaluate Oxford Nanopore Technologies MinION sequencing direct from blood in 50 blood culture-proven sepsis patients recruited from consecutive patients with suspected sepsis. In Phase 2, a further 50 consecutive patients with suspected sepsis will be recruited in whom MinION sequencing will be combined with Bayesian software-guided (ID-ODS) personalised antimicrobial dosing. OUTCOME MEASURES: The primary outcome is time to effective antimicrobial therapy, defined as trough drug concentrations above the MIC of the pathogen. Secondary outcomes are diagnostic accuracy of MinION sequencing from whole blood, time to pathogen identification and susceptibility testing using sequencing direct from whole bl

Better methods to interrogate host-pathogen interactions during Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) infections are imperative to help understand and prevent this disease. Here we implemented RNA-sequencing (RNA-seq) combined with the Oxford Nanopore Technologies (ONT) long-reads to measure differential host gene expression, transcript polyadenylation and isoform usage within various epithelial cell lines permissive and non-permissive for SARS-CoV-2 infection. SARS-CoV-2-infected and mock-infected Vero (African green monkey kidney epithelial cells), Calu-3 (human lung adenocarcinoma epithelial cells), Caco-2 (human colorectal adenocarcinoma epithelial cells) and A549 (human lung carcinoma epithelial cells) were analysed over time (0, 2, 24, 48 hours). Differential polyadenylation was found to occur in both infected Calu-3 and Vero cells during a late time point (48 hpi), with Gene Ontology (GO) terms such as viral transcription and translation shown to be significantly enriched in Calu-3 data. Poly(A) tails showed increased lengths in the majority of the differentially polyadenylated transcripts in Calu-3 and Vero cell lines (up to ~136 nt in mean poly(A) length, padj = 0.029). Of these genes, ribosomal protein genes such as RPS4X and RPS6 also showed downregulation in expression levels, suggesting the importance of ribosomal protein genes during infection. Furthermore, differential transcript usage was identified in Caco-2, Calu-3 and Vero cells, including transcripts of genes such as GSDMB and KPNA2 , which have previously been implicated in SARS-CoV-2 infections. Overall, these results highlight the potential role of differential polyadenylation and transcript usage in host immune response or viral manipulation of host mechanisms during infection, and therefore, showcase the value of long-read sequencing in identifying less-explored host responses to disease.

SARS-CoV-2 uses subgenomic (sg)RNA to produce viral proteins for replication and immune evasion. We applied long-read RNA and cDNA sequencing to in vitro human and primate infection models to study transcriptional dynamics. Transcription-regulating sequence (TRS)-dependent sgRNA was upregulated earlier in infection than TRS-independent sgRNA. An abundant class of TRS-independent sgRNA consisting of a portion of ORF1ab containing nsp1 joined to ORF10 and 3’UTR was upregulated at 48 hours post infection in human cell lines. We identified double-junction sgRNA containing both TRS-dependent and independent junctions. We found multiple sites at which the SARS-CoV-2 genome is consistently more modified than sgRNA, and that sgRNA modifications are stable across transcript clusters, host cells and time since infection. Our work highlights the dynamic nature of the SARS-CoV-2 transcriptome during its replication cycle. Our results are available via an interactive web-app at http://coinlab.mdhs.unimelb.edu.au/ .

Pandoraea fibrosis is a newly identified Gram-negative bacterial species that was isolated from the respiratory tract of an Australian cystic fibrosis patient. The complete assembled genome sequences of two consecutive isolates (second isolate collected 11 months after antibiotic treatment) from the same individual are presented here.

BACKGROUND: Sequencing technologies have advanced to the point where it is possible to generate high-accuracy, haplotype-resolved, chromosome-scale assemblies. Several long-read sequencing technologies are available, and a growing number of algorithms have been developed to assemble the reads generated by those technologies. When starting a new genome project, it is therefore challenging to select the most cost-effective sequencing technology, as well as the most appropriate software for assembly and polishing. It is thus important to benchmark different approaches applied to the same sample. RESULTS: Here, we report a comparison of 3 long-read sequencing technologies applied to the de novo assembly of a plant genome, Macadamia jansenii. We have generated sequencing data using Pacific Biosciences (Sequel I), Oxford Nanopore Technologies (PromethION), and BGI (single-tube Long Fragment Read) technologies for the same sample. Several assemblers were benchmarked in the assembly of Pacific Biosciences and Nanopore reads. Results obtained from combining long-read technologies or short-read and long-read technologies are also presented. The assemblies were compared for contiguity, base accuracy, and completeness, as well as sequencing costs and DNA material requirements. CONCLUSIONS: The 3 long-read technologies produced highly contiguous and complete genome assemblies of M. jansenii. At the time of sequencing, the cost associated with each method was significantly different, but continuous improvements in technologies have resulted in greater accuracy, increased throughput, and reduced costs. We propose updating this comparison regularly with reports on significant iterations of the sequencing technologies.

Background: Tandem repeats (TRs) are highly prone to variation in copy numbers due to their repetitive and unstable nature, which makes them a major source of genomic variation between individuals. However, population variation of TRs has not been widely explored due to the limitations of existing approaches, which are either low-throughput or restricted to a small subset of TRs. Here, we demonstrate a targeted sequencing approach combined with Nanopore sequencing to overcome these limitations. Methods: We selected 142 TR targets and enriched these regions using Agilent SureSelect target enrichment approach with only 200 ng of input DNA. We barcoded the enriched products and sequenced on Oxford Nanopore MinION sequencer. We used VNTRTyper and Tandem-genotypes to genotype TRs from long-read sequencing data. Gold standard PCR sizing analysis was used to validate genotyping results from targeted sequencing data. Results: We achieved an average of 3062-fold target enrichment on a panel of 142 TR loci, generating an average of 97X coverage per sample with 200 ng of input DNA per sample. We successfully genotyped an average of 75% targets and genotyping rate increased to 91% for the highest-coverage sample for targets with length less than 2 kb, and GC content greater than 25%. Alleles estimated from targeted long-read sequencing were concordant with gold standard PCR sizing analysis and highly correlated with alleles estimated from whole genome long-read sequencing. Conclusions: We demonstrate a targeted long-read sequencing approach that enables simultaneous analysis of hundreds of TRs and accuracy is comparable to PCR sizing analysis. Our approach is feasible to scale for more targets and more samples facilitating large-scale analysis of TRs.

In this retrospective study, we used whole-genome sequencing (WGS) to delineate transmission dynamics, characterize drug-resistance markers, and identify risk factors of transmission among Papua New Guinea residents of the Torres Strait Protected Zone (TSPZ) who had tuberculosis diagnoses during 2010-2015. Of 117 isolates collected, we could acquire WGS data for 100; 79 were Beijing sublineage 2.2.1.1, which was associated with active transmission (odds ratio 6.190, 95% CI 2.221-18.077). Strains were distributed widely throughout the TSPZ. Clustering occurred more often within than between villages (p = 0.0013). Including 4 multidrug-resistant tuberculosis isolates from Australia citizens epidemiologically linked to the TSPZ into the transmission network analysis revealed 2 probable cross-border transmission events. All multidrug-resistant isolates (33/104) belonged to Beijing sublineage 2.2.1.1 and had high-level isoniazid and ethionamide co-resistance; 2 isolates were extensively drug resistant. Including WGS in regional surveillance could improve tuberculosis transmission tracking and control strategies within the TSPZ.

A variety of methods have been developed to demultiplex pooled samples in a single cell RNA sequencing (scRNA-seq) experiment which either require hashtag barcodes or sample genotypes prior to pooling. We introduce scSplit which utilizes genetic differences inferred from scRNA-seq data alone to demultiplex pooled samples. scSplit also enables mapping clusters to original samples. Using simulated, merged, and pooled multi-individual datasets, we show that scSplit prediction is highly concordant with demuxlet predictions and is highly consistent with the known truth in cell-hashing dataset. scSplit is ideally suited to samples without external genotype information and is available at: https://github.com/jon-xu/scSplit.

BACKGROUND: Rapid diagnosis and appropriate treatment is imperative in bacterial sepsis due increasing risk of mortality with every hour without appropriate antibiotic therapy. Atypical infections with fastidious organisms may take more than 4 days to diagnose leading to calls for improved methods for rapidly diagnosing sepsis. Capnocytophaga canimorsus is a slow-growing, fastidious gram-negative bacillus which is a common commensal within the mouths of dogs, but rarely cause infections in humans. C. canimorsus sepsis risk factors include immunosuppression, alcoholism and elderly age. Here we report on the application of emerging nanopore sequencing methods to rapidly diagnose an atypical case of C. canimorsus septic shock. CASE PRESENTATION: A 62 year-old female patient was admitted to an intensive care unit with septic shock and multi-organ failure six days after a reported dog bite. Blood cultures were unable to detect a pathogen after 3 days despite observed intracellular bacilli on blood smears. Real-time nanopore sequencing was subsequently employed on whole blood to detect Capnocytophaga canimorsus in 19 h. The patient was not immunocompromised and did not have any other known risk factors. Whole-genome sequencing of clinical sample and of the offending dog's oral swabs showed near-identical C. canimorsus genomes. The patient responded to antibiotic treatment and was discharged from hospital 31 days after admission. CONCLUSIONS: Use of real-time nanopore sequencing reduced the time-to-diagnosis of Capnocytophaga canimorsus in this case from 6.25 days to 19 h. Capnocytophaga canimorsus should be considered in cases of suspected sepsis involving cat or dog contact, irrespective of the patient's known risk factors.

Early childhood growth patterns are associated with adult health, yet the genetic factors and the developmental stages involved are not fully understood. Here, we combine genome-wide association studies with modeling of longitudinal growth traits to study the genetics of infant and child growth, followed by functional, pathway, genetic correlation, risk score, and colocalization analyses to determine how developmental timings, molecular pathways, and genetic determinants of these traits overlap with those of adult health. We found a robust overlap between the genetics of child and adult body mass index (BMI), with variants associated with adult BMI acting as early as 4 to 6 years old. However, we demonstrated a completely distinct genetic makeup for peak BMI during infancy, influenced by variation at the LEPR/LEPROT locus. These findings suggest that different genetic factors control infant and child BMI. In light of the obesity epidemic, these findings are important to inform the timing and targets of prevention strategies.

Sweetpotato [Ipomoea batatas (L.) Lam.] is a globally important staple food crop, especially for sub-Saharan Africa. Agronomic improvement of sweetpotato has lagged behind other major food crops due to a lack of genomic and genetic resources and inherent challenges in breeding a heterozygous, clonally propagated polyploid. Here, we report the genome sequences of its two diploid relatives, I. trifida and I. triloba, and show that these high-quality genome assemblies are robust references for hexaploid sweetpotato. Comparative and phylogenetic analyses reveal insights into the ancient whole-genome triplication history of Ipomoea and evolutionary relationships within the Batatas complex. Using resequencing data from 16 genotypes widely used in African breeding programs, genes and alleles associated with carotenoid biosynthesis in storage roots are identified, which may enable efficient breeding of varieties with high provitamin A content. These resources will facilitate genome-enabled breeding in this important food security crop.

BACKGROUND: Detection of genomic inversions remains challenging. Many existing methods primarily target inzversions with a non repetitive breakpoint, leaving inverted repeat (IR) mediated non-allelic homologous recombination (NAHR) inversions largely unexplored. RESULT: We present npInv, a novel tool specifically for detecting and genotyping NAHR inversion using long read sub-alignment of long read sequencing data. We benchmark npInv with other tools in both simulation and real 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 the presence of two of these novel inversions. We show that there is a near linear relationship between the length of flanking IR and the minimum inversion size, without inverted repeats. CONCLUSION: The application of npInv shows high accuracy in both simulation and real data. The results give deeper insight into understanding inversion.

MOTIVATION: Targeted sequencing using capture probes has become increasingly popular in clinical applications due to its scalability and cost-effectiveness. The approach also allows for higher sequencing coverage of the targeted regions resulting in better analysis statistical power. However, because of the dynamics of the hybridization process, it is difficult to evaluate the efficiency of the probe design prior to the experiments which are time consuming and costly. RESULTS: We developed CapSim, a software package for simulation of targeted sequencing. Given a genome sequence and a set of probes, CapSim simulates the fragmentation, the dynamics of probe hybridization and the sequencing of the captured fragments on Illumina and PacBio sequencing platforms. The simulated data can be used for evaluating the performance of the analysis pipeline, as well as the efficiency of the probe design. Parameters of the various stages in the sequencing process can also be evaluated in order to optimize the experiments. AVAILABILITY AND IMPLEMENTATION: CapSim is publicly available under BSD license at https://github.com/Devika1/capsim. CONTACT: l.coin@imb.uq.edu.au. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Extensively drug-resistant Klebsiella pneumoniae (XDR-KP) infections cause high mortality and are disseminating globally. Identifying the genetic basis underpinning resistance allows for rapid diagnosis and treatment. XDR isolates sourced from Greece and Brazil, including 19 polymyxin-resistant and five polymyxin-susceptible strains, were subjected to whole genome sequencing. Seventeen of the 19 polymyxin-resistant isolates harboured variations upstream or within mgrB. The most common mutation identified was an insertion at nucleotide position 75 in mgrB via an ISKpn26-like element in the ST258 lineage and ISKpn13 in one ST11 isolate. Three strains acquired an IS1 element upstream of mgrB and another strain had an ISKpn25 insertion at 133 bp. Other isolates had truncations (C28STOP, Q30STOP) or a missense mutation (D29E) affecting mgrB. Complementation assays revealed all mgrB perturbations contributed to resistance. Missense mutations in phoQ (T281M, G385C) were also found to facilitate resistance. Several variants in phoPQ co-segregating with the ISKpn26-like insertion were identified as potential partial suppressor mutations. Three ST258 samples were found to contain subpopulations with different resistance-conferring mutations, including the ISKpn26-like insertion colonizing with a novel mutation in pmrB (P158R), both confirmed via complementation assays. These findings highlight the broad spectrum of chromosomal modifications which can facilitate and regulate resistance against polymyxins in K. pneumoniae.

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. At least 11 BioNano assembled chromosome ends are structurally divergent from the reference genome, including both missing sequence and extensions. These extensions are heritable and in some cases divergent between Asian and European samples. Six out of nine predicted extension sequences from NA12878 can be confirmed and filled by nanopore data. We identify two multi-kilobase sequence families both enriched more than 100-fold in extension sequence (p-values < 1e-5) whose origins can be traced to interstitial sequence on ancestral primate chromosome 7. Extensive sub-telomeric duplication of these families has occurred in the human lineage subsequent to divergence from chimpanzees.

Sequencing by translocating DNA fragments through an array of nanopores is a rapidly maturing technology that 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 and directly translate the raw signal to DNA sequence without the error-prone segmentation step. Trained with only a small set of 4,000 reads, we show that our model provides state-of-the-art basecalling accuracy, even on previously unseen species. Chiron achieves basecalling speeds of more than 2,000 bases per second using desktop computer graphics processing units.

Background: The chloroplast (cp) genome is an important resource for studying plant diversity and phylogeny. Assembly of the cp genomes from next-generation sequencing data is complicated by the presence of two large inverted repeats contained in the cp DNA. Methods: We constructed a complete circular cp genome assembly for the hexaploid sweetpotato using extremely low coverage (<1×) Oxford Nanopore whole-genome sequencing (WGS) data coupled with Illumina sequencing data for polishing. Results: The sweetpotato cp genome of 161,274 bp contains 152 genes, of which there are 96 protein coding genes, 8 rRNA genes and 48 tRNA genes. Using the cp genome assembly as a reference, we constructed complete cp genome assemblies for a further 17 sweetpotato cultivars from East Africa and an I. triloba line using Illumina WGS data. Analysis of the sweetpotato cp genomes demonstrated the presence of two distinct subpopulations in East Africa. Phylogenetic analysis of the cp genomes of the species from the Convolvulaceae Ipomoea section Batatas revealed that the most closely related diploid wild species of the hexaploid sweetpotato is I. trifida. Conclusions: Nanopore long reads are helpful in construction of cp genome assemblies, especially in solving the two long inverted repeats. We are generally able to extract cp sequences from WGS data of sufficiently high coverage for assembly of cp genomes. The cp genomes can be used to investigate the population structure and the phylogenetic relationship for the sweetpotato.

Third generation sequencing technologies provide the opportunity to improve genome assemblies by generating long reads spanning most repeat sequences. However, current analysis methods require substantial amounts of sequence data and computational resources to overcome the high error rates. Furthermore, they can only perform analysis after sequencing has completed, resulting in either over-sequencing, or in a low quality assembly due to under-sequencing. Here we present npScarf, which can scaffold and complete short read assemblies while the long read sequencing run is in progress. It reports assembly metrics in real-time so the sequencing run can be terminated once an assembly of sufficient quality is obtained. In assembling four bacterial and one eukaryotic genomes, we show that npScarf can construct more complete and accurate assemblies while requiring less sequencing data and computational resources than existing methods. Our approach offers a time- and resource-effective strategy for completing short read assemblies.

Accurate identification of copy number alterations is an essential step in understanding the events driving tumor progression. While a variety of algorithms have been developed to use high-throughput sequencing data to profile copy number changes, no tool is able to reliably characterize ploidy and genotype absolute copy number from tumor samples that contain less than 40% tumor cells. To increase our power to resolve the copy number profile from low-cellularity tumor samples, we developed a novel approach that pre-phases heterozygote germline single nucleotide polymorphisms (SNPs) in order to replace the commonly used 'B-allele frequency' with a more powerful 'parental-haplotype frequency'. We apply our tool-sCNAphase-to characterize the copy number and loss-of-heterozygosity profiles of four publicly available breast cancer cell-lines. Comparisons to previous spectral karyotyping and microarray studies revealed that sCNAphase reliably identified overall ploidy as well as the individual copy number mutations from each cell-line. Analysis of artificial cell-line mixtures demonstrated the capacity of this method to determine the level of tumor cellularity, consistently identify sCNAs and characterize ploidy in samples with as little as 10% tumor cells. This novel methodology has the potential to bring sCNA profiling to low-cellularity tumors, a form of cancer unable to be accurately studied by current methods.

The recently introduced Oxford Nanopore MinION platform generates DNA sequence data in real-time. This has great potential to shorten the sample-to-results time and is likely to have benefits such as rapid diagnosis of bacterial infection and identification of drug resistance. However, there are few tools available for streaming analysis of real-time sequencing data. Here, we present a framework for streaming analysis of MinION real-time sequence data, together with probabilistic streaming algorithms for species typing, strain typing and antibiotic resistance profile identification. Using four culture isolate samples, as well as a mixed-species sample, we demonstrate that bacterial species and strain information can be obtained within 30 min of sequencing and using about 500 reads, initial drug-resistance profiles within two hours, and complete resistance profiles within 10 h. While strain identification with multi-locus sequence typing required more than 15x coverage to generate confident assignments, our novel gene-presence typing could detect the presence of a known strain with 0.5x coverage. We also show that our pipeline can process over 100 times more data than the current throughput of the MinION on a desktop computer.

Targeted resequencing technologies have allowed for efficient and cost-effective detection of genomic variants in specific regions of interest. Although capture sequencing has been primarily used for investigating single nucleotide variants and indels, it has the potential to elucidate a broader spectrum of genetic variation, including copy number variants (CNVs). Various methods exist for detecting CNV in whole-genome and exome sequencing datasets. However, no algorithms have been specifically designed for contiguous target sequencing, despite its increasing importance in clinical and research applications. We have developed cnvCapSeq, a novel method for accurate and sensitive CNV discovery and genotyping in long-range targeted resequencing. cnvCapSeq was benchmarked using a simulated contiguous capture sequencing dataset comprising 21 genomic loci of various lengths. cnvCapSeq was shown to outperform the best existing exome CNV method by a wide margin both in terms of sensitivity (92.0 versus 48.3%) and specificity (99.8 versus 70.5%). We also applied cnvCapSeq to a real capture sequencing cohort comprising a contiguous 358 kb region that contains the Complement Factor H gene cluster. In this dataset, cnvCapSeq identified 41 samples with CNV, including two with duplications, with a genotyping accuracy of 99%, as ascertained by quantitative real-time PCR.

MOTIVATION: Exome sequencing technologies have transformed the field of Mendelian genetics and allowed for efficient detection of genomic variants in protein-coding regions. The target enrichment process that is intrinsic to exome sequencing is inherently imperfect, generating large amounts of unintended off-target sequence. Off-target data are characterized by very low and highly heterogeneous coverage and are usually discarded by exome analysis pipelines. We posit that off-target read depth is a rich, but overlooked, source of information that could be mined to detect intergenic copy number variation (CNV). We propose cnvOffseq, a novel normalization framework for off-target read depth that is based on local adaptive singular value decomposition (SVD). This method is designed to address the heterogeneity of the underlying data and allows for accurate and precise CNV detection and genotyping in off-target regions. RESULTS: cnvOffSeq was benchmarked on whole-exome sequencing samples from the 1000 Genomes Project. In a set of 104 gold standard intergenic deletions, our method achieved a sensitivity of 57.5% and a specificity of 99.2%, while maintaining a low FDR of 5%. For gold standard deletions longer than 5 kb, cnvOffSeq achieves a sensitivity of 90.4% without increasing the FDR. cnvOffSeq outperforms both whole-genome and whole-exome CNV detection methods considerably and is shown to offer a substantial improvement over naïve local SVD. AVAILABILITY AND IMPLEMENTATION: cnvOffSeq is available at http://sourceforge.net/p/cnvoffseq/. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Allergy is a complex disease that is likely to involve dysregulated CD4+ T cell activation. Here we propose a novel methodology to gain insight into how coordinated behaviour emerges between disease-dysregulated pathways in response to pathophysiological stimuli. Using peripheral blood mononuclear cells of allergic rhinitis patients and controls cultured with and without pollen allergens, we integrate CD4+ T cell gene expression from microarray data and genetic markers of allergic sensitisation from GWAS data at the pathway level using enrichment analysis; implicating the complement system in both cellular and systemic response to pollen allergens. We delineate a novel disease network linking T cell activation to the complement system that is significantly enriched for genes exhibiting correlated gene expression and protein-protein interactions, suggesting a tight biological coordination that is dysregulated in the disease state in response to pollen allergen but not to diluent. This novel disease network has high predictive power for the gene and protein expression of the Th2 cytokine profile (IL-4, IL-5, IL-10, IL-13) and of the Th2 master regulator (GATA3), suggesting its involvement in the early stages of CD4+ T cell differentiation. Dissection of the complement system gene expression identifies 7 genes specifically associated with atopic response to pollen, including C1QR1, CFD, CFP, ITGB2, ITGAX and confirms the role of C3AR1 and C5AR1. Two of these genes (ITGB2 and C3AR1) are also implicated in the network linking complement system to T cell activation, which comprises 6 differentially expressed genes. C3AR1 is also significantly associated with allergic sensitisation in GWAS data.

BACKGROUND: Y haplogroup analyses are an important component of genealogical reconstruction, population genetic analyses, medical genetics and forensics. These fields are increasingly moving towards use of low-coverage, high throughput sequencing. While there have been methods recently proposed for assignment of Y haplogroups on the basis of high-coverage sequence data, assignment on the basis of low-coverage data remains challenging. RESULTS: We developed a new algorithm, YHap, which uses an imputation framework to jointly predict Y chromosome genotypes and assign Y haplogroups using low coverage population sequence data. We use data from the 1000 genomes project to demonstrate that YHap provides accurate Y haplogroup assignment with less than 2x coverage. CONCLUSIONS: Borrowing information across multiple samples within a population using an imputation framework enables accurate Y haplogroup assignment.

The limited ability of common variants to account for the genetic contribution to complex disease has prompted searches for rare variants of large effect, to partly explain the 'missing heritability'. Analyses of genome-wide genotyping data have identified genomic structural variants (GSVs) as a source of such rare causal variants. Recent studies have reported multiple GSV loci associated with risk of obesity. We attempted to replicate these associations by similar analysis of two familial-obesity case-control cohorts and a population cohort, and detected GSVs at 11 out of 18 loci, at frequencies similar to those previously reported. Based on their reported frequencies and effect sizes (OR≥25), we had sufficient statistical power to detect the large majority (80%) of genuine associations at these loci. However, only one obesity association was replicated. Deletion of a 220 kb region on chromosome 16p11.2 has a carrier population frequency of 2×10(-4) (95% confidence interval [9.6×10(-5)-3.1×10(-4)]); accounts overall for 0.5% [0.19%-0.82%] of severe childhood obesity cases (P = 3.8×10(-10); odds ratio = 25.0 [9.9-60.6]); and results in a mean body mass index (BMI) increase of 5.8 kg.m(-2) [1.8-10.3] in adults from the general population. We also attempted replication using BMI as a quantitative trait in our population cohort; associations with BMI at or near nominal significance were detected at two further loci near KIF2B and within FOXP2, but these did not survive correction for multiple testing. These findings emphasise several issues of importance when conducting rare GSV association, including the need for careful cohort selection and replication strategy, accurate GSV identification, and appropriate correction for multiple testing and/or control of false discovery rate. Moreover, they highlight the potential difficulty in replicating rare CNV associations across different populations. Nevertheless, we show that such studies are potentially valuable for the ide