Short-read Whole-genome Sequencing Data Research Articles

Easy analysis of bacterial whole-genome sequencing data for clinical microbiologists using open-source Galaxy platform: Characterization of ESBL-producing Enterobacterales from bloodstream infections

ObjectivesClinical microbiologists require easy-to-use open access tools with graphical interfaces to perform bacterial whole-genome sequencing (WGS) in routine practice. This study aimed to build a bioinformatics pipeline on the open-source Galaxy platform, facilitating comprehensive and reproducible analysis of bacterial WGS data in a few steps. We then used it to characterize our local epidemiology of ESBL-producing Enterobacterales isolated from patients with bacteremia. MethodsWe built a bioinformatics pipeline consisting of the following sequential tools: Fastp (input data trimming); FastQC (read quality control); SPAdes (genome assembly); Quast (quality control of genome assembly); Prokka (gene annotation); Staramr (ResFinder database) and ABRicate (CARD database) for antimicrobial resistance (AMR) gene screening and molecular strain typing. Paired-end short read WGS data from all ESBL-producing Enterobacterales strains isolated from patients with bacteremia over one year were analysed. ResultsThe Galaxy platform does not require command line tools. The bioinformatics pipeline was constructed within one hour. It only required uploading fastq files and facilitated systematization of de novo assembly of genomes, MLST typing, and AMR gene screening in one step. Among the 66 ESBL-producing strains analysed, the two most frequent ESBL genes were blaCTX−M-15 (62.1%) and blaCTX−M-27 (13.6%). ConclusionsThe open-access Galaxy platform provides a graphical interface and easy-to-use tools suitable for routine use in clinical microbiology laboratories without bioinformatics specialists. We believe that this platform will facilitate fast and low-cost analysis of bacterial WGS data, especially in resource-limited settings.

Analysis of genomic copy number variations through whole-genome scan in Yunling cattle.

Yunling cattle is a new breed of beef cattle bred in Yunnan Province, China, which has the advantages of fast growth, excellent meat quality, improved tolerance ability, and important landscape value. Copy number variation (CNV) is a significant source of gene structural variation and plays a crucial role in evolution and phenotypic diversity. Based on the latest reference genome ARS-UCD2.0, this study analyzed the genome-wide distribution of CNVs in Yunling cattle using short-read whole-genome sequencing data (n = 129) and single-molecule long-read sequencing data (n = 1), and a total of 16,507 CNVs were detected. After merging CNVs with overlapping genomic positions, 3,728 CNV regions (CNVRs) were obtained, accounting for 0.61% of the reference genome. The functional analysis indicated significant enrichment of CNVRs in 96 GO terms and 57 KEGG pathways, primarily related to cell adhesion, signal transduction, neuromodulation, and nutritional metabolism. Additionally, 111 CNVRs overlapped with 76 quantitative trait loci (QTLs), including Subcutaneous fat thickness QTL, Longissimus muscle area QTL, and Marbling score QTL. Several CNVR-overlapping genes, including BZW1, AOX1, and LOC100138449, overlap with regions associated with meat color and quality QTLs. Furthermore, Vst analysis showed that PSMB4, ERICH1, SMC2, and PPP4R3A were highly divergent between Yunling and Brahman cattle. In summary, we have constructed the genomic CNV map of Yunling cattle for the first time using whole-genome resequencing. This provides valuable genetic variation resources for the study of the Yunling cattle genome and contributes to the study of economic traits in Yunling cattle.

RFC1 Repeat Distribution in the Cypriot Population: Study of a Large Cohort of Patients With Undiagnosed Ataxia and Non-Disease Controls.

The intronic biallelic AAGGG expansion in the replication factor C subunit 1 (RFC1) gene was recently associated with a phenotype combining cerebellar ataxia, neuropathy, and vestibular areflexia syndrome, as well as with late-onset ataxia. Following this discovery, studies in multiple populations extended the phenotypic and genotypic spectrum of this locus. Multiple benign and additional pathogenic configurations are currently known. Our main objectives were to study the prevalence of the pathogenic AAGGG expansion in the Cypriot population, to further characterize the RFC1 repeat locus allele distribution, and to search for possible novel repeat configurations. Cypriot undiagnosed patients, in the majority presenting at least with cerebellar ataxia and non-neurologic disease controls, were included in this study. A combination of conventional methods was used, including standard PCR flanking the repeat region, repeat-primed PCR, long-range PCR, and Sanger sequencing. Bioinformatics analysis of already available in-house short-read whole-genome sequencing data was also performed. A large group of undiagnosed patients (n = 194), mainly presenting with pure ataxia or with ataxia accompanied by neuropathy or additional symptoms, as well as a group of non-disease controls (n = 100), were investigated in the current study. Our findings include the diagnosis of 10 patients homozygous for the pathogenic AAGGG expansion and a high percentage of heterozygous AAGGG carriers in both groups. The benign AAAAGn, AAAGGn, and AAGAGn configurations were also identified in our cohorts. We also report and discuss the identification of 2 recently reported novel and possibly benign repeat configurations, AAAGGGn and AAGACn, thus confirming their existence in another distinct population, and we highlight an increased frequency of the AAAGGGn in the patient group, including a single case of homozygosity. Our findings indicate the existence of genetic heterogeneity regarding the RFC1 repeat configurations and that the AAGGG pathogenic expansion is a frequent cause of ataxia in the Cypriot population.

A novel framework for human leukocyte antigen (HLA) genotyping using probe capture-based targeted next-generation sequencing and computational analysis

Human leukocyte antigen (HLA) genes play pivotal roles in numerous immunological applications. Given the immense number of polymorphisms, achieving accurate high-throughput HLA typing remains challenging. This study aimed to harness the human pan-genome reference consortium (HPRC) resources as a potential benchmark for HLA reference materials. We meticulously annotated specific four field-resolution alleles for 11 HLA genes (HLA-A, -B, -C, -DPA1, -DPB1, -DQA1, -DQB1, -DRB1, -DRB3, -DRB4 and -DRB5) from 44 high-quality HPRC personal genome assemblies. For sequencing, we crafted HLA-specific probes and conducted capture-based targeted sequencing of the genomic DNA of the HPRC cohort, ensuring focused and comprehensive coverage of the HLA region of interest. We used publicly available short-read whole-genome sequencing (WGS) data from identical samples to offer a comparative perspective. To decipher the vast amount of sequencing data, we employed seven distinct software tools: OptiType, HLA-VBseq, HISAT genotype, SpecHLA, T1K, QzType, and DRAGEN. Each tool offers unique capabilities and algorithms for HLA genotyping, allowing comprehensive analysis and validation of the results. We then compared these results with benchmarks derived from personal genome assemblies. Our findings present a comprehensive four-field-resolution HLA allele annotation for 44 HPRC samples. Significantly, our innovative targeted next-generation sequencing (NGS) approach for HLA genes showed superior accuracy compared with conventional short-read WGS. An integrated analysis involving QzType, T1K, and DRAGEN was developed, achieving 100% accuracy for all 11 HLA genes. In conclusion, our study highlighted the combination of targeted short-read sequencing and astute computational analysis as a robust approach for HLA genotyping. Furthermore, the HPRC cohort has emerged as a valuable assembly-based reference in this realm.

On the distribution and diversity of tissue-specific somatic mutations in honey bee (Apis mellifera) drones

Somatic mutations originate from both exogenous (e.g. UV radiation, chemical agents) and endogenous (e.g., DNA replication, defective DNA repair) sources and can have significant impacts on an animal’s reproductive success. This may be especially true for haploid organisms that are susceptible to any deleterious alleles inherited from their parent and any that arise over their lifetime. Unfortunately, little is known about the rate of somatic mutation accumulation across individuals and tissues of haplodiploid animal populations, the functional processes through which they arise, and their distribution across tissues and the genome. Here, we generated short-read whole-genome sequencing data for four tissues of haploid honey bee males. We paired this with estimates of telomere length and tissue-specific DNA content to address three major questions: is there variance in somatic mutational load across haploid individuals and specific tissues therein, does increased DNA content in a tissue contribute to somatic mutational load, and does telomere length correlate with mutational load? Our results suggest that variance in somatic mutational load is better captured across individuals than across tissues, that tissue-specific DNA content is not associated with somatic mutation load, and that variance in telomere length does not correlate with somatic mutation loads across tissues. To our knowledge, this is the first observational study on somatic mutational load in Apoidea and likely Hymenoptera. It serves as a useful advent for additional studies understanding the processes through which haploids tolerate or repair somatic mutations.

MOM: A user-friendly Galaxy workflow to detect modifiers from genome sequencing data using C. elegans.

Genetic modifiers are variants modulating phenotypic outcomes of a primary detrimental variant. They contribute to rare diseases phenotypic variability, but their identification is challenging. Genetic screening with model organisms is a widely used method for demystifying genetic modifiers. Forward genetics screening followed by whole genome sequencing (WGS) allows the detection of variants throughout the genome, but typically produces thousands of candidate variants making the interpretation and prioritization process very time consuming and tedious. Despite WGS being more time and cost efficient, usage of computational pipelines specific to modifier identification remains a challenge for biological-experiment-focused laboratories doing research with model organisms. To facilitate a broader implementation of WGS in genetic screens, we have developed MOM, a Model Organism Modifier pipeline as a user-friendly Galaxy workflow. MOM analyses raw short-read WGS data and implements tailored filtering to provide a Candidate Variant List (CVL) short enough to be further manually curated. We provide a detailed tutorial to run the Galaxy workflow MOM and guidelines to manually curate the CVLs. We have tested MOM on published and validated C. elegans modifiers screening datasets. As WGS facilitates high-throughput identification of genetic modifiers in model organisms, MOM provides a user-friendly solution to implement the bioinformatics analysis of the short-read datasets in laboratories without expertise or support in Bioinformatics.

Surveillance of antimicrobial resistant Shiga toxin-producing E. coli O157:H7 in England, 2016-2020.

Shiga toxin-producing Escherichia coli (STEC) O157:H7 are zoonotic pathogens and transmission to humans occurs via contaminated food or contact with infected animals. The aim of this study was to describe the frequency, and distribution across the phylogeny, of antimicrobial resistance (AMR) determinants in STEC O157:H7 isolated from human cases in England. Short-read whole-genome sequencing data from 1473 isolates of STEC O157:H7 from all seven sub-lineages (Ia-Ic, IIa-IIc and I/II) were mapped to genes known to confer phenotypic resistance to 10 different classes of antibiotic. Long-read sequencing was used to determine the location and genomic architecture of the AMR determinants within phylogenetic clusters exhibiting multidrug resistance. Overall, 216/1473 (14.7%) isolates had at least one AMR determinant, although the proportion of isolates exhibiting AMR varied by sub-lineage. The highest proportion of AMR determinants were detected in sub-lineages Ib (28/64, 43.7%), I/II (18/51, 35.3%) and IIc (122/440, 27.7%). In all sub-lineages, the most commonly detected AMR determinants conferred resistance to the aminoglycosides, tetracyclines and sulphonamides, while AMR determinants conferring resistance to fluroquinolones, macrolides and third-generation cephalosporins were rarely detected. Long-read sequencing analysis showed that the AMR determinants were co-located on the chromosome in sub-lineages Ib and lineage I/II, whereas those associated with sub-lineage IIc were encoded on the chromosome and/or large plasmids. AMR genes were unevenly distributed across the different sub-lineages of STEC O157:H7 and between different clades within the same sub-lineage. Long-read sequencing facilitates tracking the transmission of AMR at the pathogen and mobile genetic element level.

Comparative Analysis of Structural Variant Callers on the Short-Read Whole-Genome Sequencing Data

In this study three structural variant callers (Manta, Smoove, Delly) were analysed on the whole-genome sequencing data using four different alignment algorithms: DRAGEN, GDC DNA-Seq Alignment Workflow, GDC DNA-Seq Alignment Workflow + GDC DNA-Seq Co-Cleaning Workflow, NovoAlign, different lengths of raw reads: 2 × 150 bp and 2 × 250 bp, different mean genome coverage values. Results were compared to etalon results of GIAB team. Structural variants validation was hold also with Sanger sequencing. Structural variants deletions and insertions as it turned out were best determined with Manta tool. We’ve got 89–96% of accuracy and 59–70% of sensitivity for analysed deletions, and also 96–99% of accuracy and 15–36% of sensitivity for insertions. Smoove and Delly showed less accurate and sensitive results (Smoove: 91–95% of accuracy and 8–54% of sensitivity for deletions, Delly: 78–87% of accuracy and 31–66% of sensitivity for deletions, 99–100% of accuracy and 1–13% of sensitivity for insertions). Simultaneous using of two or even three structural variant callers didn’t give a rise of accuracy and sensitivity for deletions. Analysis showed that accuracy and sensitivity of structural variant callers rise with the rising of mean genome coverage value, increasing of reads length from 150 to 250 bp influence in to varying degrees on the accuracy and sensitivity of individual tools. Another inference of this study was that accuracy of structural variants callers vary depends on structural variants size range. For example, Manta finds better deletions in the range from 200 and more bp, Delly – from 1000 to 10 000 bp, Smoove – from 200 to 10 000 bp.

Detection of trait-associated structural variations using short-read sequencing

Genomic structural variation (SV) affects genetic and phenotypic characteristics in diverse organisms, but the lack of reliable methods to detect SV has hindered genetic analysis. We developed a computational algorithm (MOPline) that includes missing call recovery combined with high-confidence SV call selection and genotyping using short-read whole-genome sequencing (WGS) data. Using 3,672 high-coverage WGS datasets, MOPline stably detected ∼16,000 SVs per individual, which is over ∼1.7-3.3-fold higher than previous large-scale projects while exhibiting a comparable level of statistical quality metrics. We imputed SVs from 181,622 Japanese individuals for 42 diseases and 60 quantitative traits. A genome-wide association study with the imputed SVs revealed 41 top-ranked or nearly top-ranked genome-wide significant SVs, including 8 exonic SVs with 5 novel associations and enriched mobile element insertions. This study demonstrates that short-read WGS data can be used to identify rare and common SVs associated with a variety of traits.

Software Choice and Sequencing Coverage Can Impact Plastid Genome Assembly-A Case Study in the Narrow Endemic Calligonum bakuense.

Most plastid genome sequences are assembled from short-read whole-genome sequencing data, yet the impact that sequencing coverage and the choice of assembly software can have on the accuracy of the resulting assemblies is poorly understood. In this study, we test the impact of both factors on plastid genome assembly in the threatened and rare endemic shrub Calligonum bakuense. We aim to characterize the differences across plastid genome assemblies generated by different assembly software tools and levels of sequencing coverage and to determine if these differences are large enough to affect the phylogenetic position inferred for C. bakuense compared to congeners. Four assembly software tools (FastPlast, GetOrganelle, IOGA, and NOVOPlasty) and seven levels of sequencing coverage across the plastid genome (original sequencing depth, 2,000x, 1,000x, 500x, 250x, 100x, and 50x) are compared in our analyses. The resulting assemblies are evaluated with regard to reproducibility, contig number, gene complement, inverted repeat length, and computation time; the impact of sequence differences on phylogenetic reconstruction is assessed. Our results show that software choice can have a considerable impact on the accuracy and reproducibility of plastid genome assembly and that GetOrganelle produces the most consistent assemblies for C. bakuense. Moreover, we demonstrate that a sequencing coverage between 500x and 100x can reduce both the sequence variability across assembly contigs and computation time. When comparing the most reliable plastid genome assemblies of C. bakuense, a sequence difference in only three nucleotide positions is detected, which is less than the difference potentially introduced through software choice.

Unravelling the tumour genome: The evolutionary and clinical impacts of structural variants in tumourigenesis.

Structural variants (SVs) represent a major source of aberration in tumour genomes. Given the diversity in the size and type of SVs present in tumours, the accurate detection and interpretation of SVs in tumours is challenging. New classes of complex structural events in tumours are discovered frequently, and the definitions of the genomic consequences of complex events are constantly being refined. Detailed analyses of short‐read whole‐genome sequencing (WGS) data from large tumour cohorts facilitate the interrogation of SVs at orders of magnitude greater scale and depth. However, the inherent technical limitations of short‐read WGS prevent us from accurately detecting and investigating the impact of all the SVs present in tumours. The expanded use of long‐read WGS will be critical for improving the accuracy of SV detection, and in fully resolving complex SV events, both of which are crucial for determining the impact of SVs on tumour progression and clinical outcome. Despite the present limitations, we demonstrate that SVs play an important role in tumourigenesis. In particular, SVs contribute significantly to late‐stage tumour development and to intratumoural heterogeneity. The evolutionary trajectories of SVs represent a window into the clonal dynamics in tumours, a comprehensive understanding of which will be vital for influencing patient outcomes in the future. Recent findings have highlighted many clinical applications of SVs in cancer, from early detection to biomarkers for treatment response and prognosis. As the methods to detect and interpret SVs improve, elucidating the full breadth of the complex SV landscape and determining how these events modulate tumour evolution will improve our understanding of cancer biology and our ability to capitalise on the utility of SVs in the clinical management of cancer patients. © 2022 The Authors. The Journal of Pathology published by John Wiley & Sons Ltd on behalf of The Pathological Society of Great Britain and Ireland.

Chromoanagenesis Event Underlies a de novo Pericentric and Multiple Paracentric Inversions in a Single Chromosome Causing Coffin-Siris Syndrome.

Chromoanagenesis is a descriptive term that encompasses classes of catastrophic mutagenic processes that generate localized and complex chromosome rearrangements in both somatic and germline genomes. Herein, we describe a 5-year-old female presenting with a constellation of clinical features consistent with a clinical diagnosis of Coffin–Siris syndrome 1 (CSS1). Initial G-banded karyotyping detected a 90-Mb pericentric and a 47-Mb paracentric inversion on a single chromosome. Subsequent analysis of short-read whole-genome sequencing data and genomic optical mapping revealed additional inversions, all clustered on chromosome 6, one of them disrupting ARID1B for which haploinsufficiency leads to the CSS1 disease trait (MIM:135900). The aggregate structural variant data show that the resolved, the resolved derivative chromosome architecture presents four de novo inversions, one pericentric and three paracentric, involving six breakpoint junctions in what appears to be a shuffling of genomic material on this chromosome. Each junction was resolved to nucleotide-level resolution with mutational signatures suggestive of non-homologous end joining. The disruption of the gene ARID1B is shown to occur between the fourth and fifth exon of the canonical transcript with subsequent qPCR studies confirming a decrease in ARID1B expression in the patient versus healthy controls. Deciphering the underlying genomic architecture of chromosomal rearrangements and complex structural variants may require multiple technologies and can be critical to elucidating the molecular etiology of a patient’s clinical phenotype or resolving unsolved Mendelian disease cases.

A benchmark and an algorithm for detecting germline transposon insertions and measuring de novo transposon insertion frequencies.

Transposons are genomic parasites, and their new insertions can cause instability and spur the evolution of their host genomes. Rapid accumulation of short-read whole-genome sequencing data provides a great opportunity for studying new transposon insertions and their impacts on the host genome. Although many algorithms are available for detecting transposon insertions, the task remains challenging and existing tools are not designed for identifying de novo insertions. Here, we present a new benchmark fly dataset based on PacBio long-read sequencing and a new method TEMP2 for detecting germline insertions and measuring de novo ‘singleton’ insertion frequencies in eukaryotic genomes. TEMP2 achieves high sensitivity and precision for detecting germline insertions when compared with existing tools using both simulated data in fly and experimental data in fly and human. Furthermore, TEMP2 can accurately assess the frequencies of de novo transposon insertions even with high levels of chimeric reads in simulated datasets; such chimeric reads often occur during the construction of short-read sequencing libraries. By applying TEMP2 to published data on hybrid dysgenic flies inflicted by de-repressed P-elements, we confirmed the continuous new insertions of P-elements in dysgenic offspring before they regain piRNAs for P-element repression. TEMP2 is freely available at Github: https://github.com/weng-lab/TEMP2.

An integrated personal and population-based Egyptian genome reference

A small number of de novo assembled human genomes have been reported to date, and few have been complemented with population-based genetic variation, which is particularly important for North Africa, a region underrepresented in current genome-wide references. Here, we combine long- and short-read whole-genome sequencing data with recent assembly approaches into a de novo assembly of an Egyptian genome. The assembly demonstrates well-balanced quality metrics and is complemented with variant phasing via linked reads into haploblocks, which we associate with gene expression changes in blood. To construct an Egyptian genome reference, we identify genome-wide genetic variation within a cohort of 110 Egyptian individuals. We show that differences in allele frequencies and linkage disequilibrium between Egyptians and Europeans may compromise the transferability of European ancestry-based genetic disease risk and polygenic scores, substantiating the need for multi-ethnic genome references. Thus, the Egyptian genome reference will be a valuable resource for precision medicine.

IgCaller for reconstructing immunoglobulin gene rearrangements and oncogenic translocations from whole-genome sequencing in lymphoid neoplasms

Immunoglobulin (Ig) gene rearrangements and oncogenic translocations are routinely assessed during the characterization of B cell neoplasms and stratification of patients with distinct clinical and biological features, with the assessment done using Sanger sequencing, targeted next-generation sequencing, or fluorescence in situ hybridization (FISH). Currently, a complete Ig characterization cannot be extracted from whole-genome sequencing (WGS) data due to the inherent complexity of the Ig loci. Here, we introduce IgCaller, an algorithm designed to fully characterize Ig gene rearrangements and oncogenic translocations from short-read WGS data. Using a cohort of 404 patients comprising different subtypes of B cell neoplasms, we demonstrate that IgCaller identifies both heavy and light chain rearrangements to provide additional information on their functionality, somatic mutational status, class switch recombination, and oncogenic Ig translocations. Our data thus support IgCaller to be a reliable alternative to Sanger sequencing and FISH for studying the genetic properties of the Ig loci.

Gplas: a comprehensive tool for plasmid analysis using short-read graphs.

SummaryPlasmids can horizontally transmit genetic traits, enabling rapid bacterial adaptation to new environments and hosts. Short-read whole-genome sequencing data are often applied to large-scale bacterial comparative genomics projects but the reconstruction of plasmids from these data is facing severe limitations, such as the inability to distinguish plasmids from each other in a bacterial genome. We developed gplas, a new approach to reliably separate plasmid contigs into discrete components using sequence composition, coverage, assembly graph information and network partitioning based on a pruned network of plasmid unitigs. Gplas facilitates the analysis of large numbers of bacterial isolates and allows a detailed analysis of plasmid epidemiology based solely on short-read sequence data.Availability and implementationGplas is written in R, Bash and uses a Snakemake pipeline as a workflow management system. Gplas is available under the GNU General Public License v3.0 at https://gitlab.com/sirarredondo/gplas.git.Supplementary information Supplementary data are available at Bioinformatics online.

New genomic features of the polled intersex syndrome variant in goats unraveled by long-read whole-genome sequencing.

In domestic goats, the polled intersex syndrome (PIS) refers to XX female-to-male sex reversal associated with the absence of horn growth (polled). The causal variant was previously reported as a 11.7kb deletion at approximately 129Mb on chromosome 1 that affects the transcription of both FOXL2 and several long non-coding RNAs. In the meantime the presence of different versions of the PIS deletion was postulated and trials to establish genetic testing with the existing molecular genetic information failed. Therefore, we revisited this variant by long-read whole-genome sequencing of two genetically female (XX) goats, a PIS-affected and a horned control. This revealed the presence of a more complex structural variant consisting of a deletion with a total length of 10159bp and an inversely inserted approximately 480kb-sized duplicated segment of a region located approximately 21Mb further downstream on chromosome 1 containing two genes, KCNJ15 and ERG. Publicly available short-read whole-genome sequencing data, Sanger sequencing of the breakpoints and FISH using BAC clones corresponding to both involved genome regions confirmed this structural variant. A diagnostic PCR was developed for simultaneous genotyping of carriers for this variant and determination of their genetic sex. We showed that the variant allele was present in all 334 genotyped polled goats of diverse breeds and that all analyzed 15 PIS-affected XX goats were homozygous. Our findings enable for the first time a precise genetic diagnosis for polledness and PIS in goats and add a further genomic feature to the complexity of the PIS phenomenon.

Discordant bioinformatic predictions of antimicrobial resistance from whole-genome sequencing data of bacterial isolates: an inter-laboratory study.

Antimicrobial resistance (AMR) poses a threat to public health. Clinical microbiology laboratories typically rely on culturing bacteria for antimicrobial-susceptibility testing (AST). As the implementation costs and technical barriers fall, whole-genome sequencing (WGS) has emerged as a ‘one-stop’ test for epidemiological and predictive AST results. Few published comparisons exist for the myriad analytical pipelines used for predicting AMR. To address this, we performed an inter-laboratory study providing sets of participating researchers with identical short-read WGS data from clinical isolates, allowing us to assess the reproducibility of the bioinformatic prediction of AMR between participants, and identify problem cases and factors that lead to discordant results. We produced ten WGS datasets of varying quality from cultured carbapenem-resistant organisms obtained from clinical samples sequenced on either an Illumina NextSeq or HiSeq instrument. Nine participating teams (‘participants’) were provided these sequence data without any other contextual information. Each participant used their choice of pipeline to determine the species, the presence of resistance-associated genes, and to predict susceptibility or resistance to amikacin, gentamicin, ciprofloxacin and cefotaxime. We found participants predicted different numbers of AMR-associated genes and different gene variants from the same clinical samples. The quality of the sequence data, choice of bioinformatic pipeline and interpretation of the results all contributed to discordance between participants. Although much of the inaccurate gene variant annotation did not affect genotypic resistance predictions, we observed low specificity when compared to phenotypic AST results, but this improved in samples with higher read depths. Had the results been used to predict AST and guide treatment, a different antibiotic would have been recommended for each isolate by at least one participant. These challenges, at the final analytical stage of using WGS to predict AMR, suggest the need for refinements when using this technology in clinical settings. Comprehensive public resistance sequence databases, full recommendations on sequence data quality and standardization in the comparisons between genotype and resistance phenotypes will all play a fundamental role in the successful implementation of AST prediction using WGS in clinical microbiology laboratories.

ConFindr: rapid detection of intraspecies and cross-species contamination in bacterial whole-genome sequence data.

Whole-genome sequencing (WGS) of bacterial pathogens is currently widely used to support public-health investigations. The ability to assess WGS data quality is critical to underpin the reliability of downstream analyses. Sequence contamination is a quality issue that could potentially impact WGS-based findings; however, existing tools do not readily identify contamination from closely-related organisms. To address this gap, we have developed a computational pipeline, ConFindr, for detection of intraspecies contamination. ConFindr determines the presence of contaminating sequences based on the identification of multiple alleles of core, single-copy, ribosomal-protein genes in raw sequencing reads. The performance of this tool was assessed using simulated and lab-generated Illumina short-read WGS data with varying levels of contamination (0–20% of reads) and varying genetic distance between the designated target and contaminant strains. Intraspecies and cross-species contamination was reliably detected in datasets containing 5% or more reads from a second, unrelated strain. ConFindr detected intraspecies contamination with higher sensitivity than existing tools, while also being able to automatically detect cross-species contamination with similar sensitivity. The implementation of ConFindr in quality-control pipelines will help to improve the reliability of WGS databases as well as the accuracy of downstream analyses. ConFindr is written in Python, and is freely available under the MIT License at github.com/OLC-Bioinformatics/ConFindr.

TETyper: a bioinformatic pipeline for classifying variation and genetic contexts of transposable elements from short-read whole-genome sequencing data.

Much of the worldwide dissemination of antibiotic resistance has been driven by resistance gene associations with mobile genetic elements (MGEs), such as plasmids and transposons. Although increasing, our understanding of resistance spread remains relatively limited, as methods for tracking mobile resistance genes through multiple species, strains and plasmids are lacking. We have developed a bioinformatic pipeline for tracking variation within, and mobility of, specific transposable elements (TEs), such as transposons carrying antibiotic-resistance genes. TETyper takes short-read whole-genome sequencing data as input and identifies single-nucleotide mutations and deletions within the TE of interest, to enable tracking of specific sequence variants, as well as the surrounding genetic context(s), to enable identification of transposition events. A major advantage of TETyper over previous methods is that it does not require a genome reference. To investigate global dissemination of Klebsiella pneumoniae carbapenemase (KPC) and its associated transposon Tn4401, we applied TETyper to a collection of over 3000 publicly available Illumina datasets containing blaKPC. This revealed surprising diversity, with over 200 distinct flanking genetic contexts for Tn4401, indicating high levels of transposition. Integration of sample metadata revealed insights into associations between geographic locations, host species, Tn4401 sequence variants and flanking genetic contexts. To demonstrate the ability of TETyper to cope with high-copy-number TEs and to track specific short-term evolutionary changes, we also applied it to the insertion sequence IS26 within a defined K. pneumoniae outbreak. TETyper is implemented in python and is freely available at https://github.com/aesheppard/TETyper.