Project description:Porcine reproductive and respiratory syndrome virus (PRRSV) is the causative agent of one of the most widespread and economically devastating diseases in the swine industry. Typing circulating PRRSV strains by means of sequencing is crucial for developing adequate control strategies. Most genetic studies only target the highly variable open reading frame (ORF) 5, for which an extensive database is available. In this study, we performed whole-genome sequencing (WGS) on a collection of 124 PRRSV-1 positive serum samples that were collected over a 5-year period (2015-2019) in Belgium. Our results show that (nearly) complete PRRSV genomes can be obtained directly from serum samples with a high success rate. Analysis of the coding regions confirmed the exceptionally high genetic diversity, even among Belgian PRRSV-1 strains. To gain more insight into the added value of WGS, we performed phylogenetic cluster analyses on separate ORF datasets as well as on a single, concatenated dataset (CDS) containing all ORFs. A comparison between the CDS and ORF clustering schemes revealed numerous discrepancies. To explain these differences, we performed a large-scale recombination analysis, which allowed us to identify a large number of potential recombination events that were scattered across the genome. As PRRSV does not contain typical recombination hot-spots, typing PRRSV strains based on a single ORF is not recommended. Although the typing accuracy can be improved by including multiple regions, our results show that the full genetic diversity among PRRSV strains can only be captured by analysing (nearly) complete genomes. Finally, we also identified several vaccine-derived recombinant strains, which once more raises the question of the safety of these vaccines.
Project description:With the development of next-generation sequencing (NGS) technologies it became possible to simultaneously analyze millions of variants. Despite the quality improvement, it is generally still required to confirm the variants before reporting. However, in recent years the dominant idea is that one could define the quality thresholds for "high quality" variants which do not require orthogonal validation. Despite that, no works to date report the concordance between variants from whole genome sequencing and their gold-standard Sanger validation. In this study we analyzed the concordance for 1756 WGS variants in order to establish the appropriate thresholds for high-quality variants filtering. Resulting thresholds allowed us to drastically reduce the number of variants which require validation, to 4.8% and 1.2% of the initial set for caller-agnostic (DP, AF) and caller-dependent (QUAL) thresholds, respectively.
Project description:BackgroundSalmonella Infantis (S. Infantis) is one of the most frequent Salmonella serovars isolated from human cases of salmonellosis and the most detected serovar from animal and food sources in Europe. The serovar is commonly associated with poultry and there is increasing concern over multidrug resistant clones spreading worldwide, as the dominating clones are characterized by presence of large plasmids carrying multiple resistance genes. Increasing the knowledge of the S. Infantis population and evolution is important for understanding and preventing further spread. In this study, we analysed a collection of strains representing different decades, sources and geographic locations. We analysed the population structure and the accessory genome, in particular we identified prophages with a view to understand the role of prophages in relation to the evolution of this serovar.ResultsWe sequenced a global collection of 100 S. Infantis strains. A core-genome SNP analysis separated five strains in e-Burst Group (eBG) 297 with a long branch. The remaining strains, all in eBG31, were divided into three lineages that were estimated to have separated approximately 150 years ago. One lineage contained the vast majority of strains. In five of six clusters, no obvious correlation with source or geographical locations was seen. However, one cluster contained mostly strains from human and avian sources, indicating a clone with preference for these sources. The majority of strains within this cluster harboured a pESI-like plasmid with multiple resistance genes. Another lineage contained three genetic clusters with more rarely isolated strains of mainly animal origin, possibly less sampled or less infectious clones. Conserved prophages were identified in all strains, likely representing bacteriophages which integrated into the chromosome of a common ancestor to S. Infantis. We also saw that some prophages were specific to clusters and were probably introduced when the clusters were formed.ConclusionsThis study analysed a global S. Infantis population and described its genetic structure. We hypothesize that the population has evolved in three separate lineages, with one more successfully emerging lineage. We furthermore detected conserved prophages present in the entire population and cluster specific prophages, which probably shaped the population structure.
Project description:Detecting structural variants (SVs) in whole-genome sequencing poses significant challenges. We present a protocol for variant calling, merging, genotyping, sensitivity analysis, and laboratory validation for generating a high-quality SV call set in whole-genome sequencing from the Alzheimer's Disease Sequencing Project comprising 578 individuals from 111 families. Employing two complementary pipelines, Scalpel and Parliament, for SV/indel calling, we assessed sensitivity through sample replicates (N = 9) with in silico variant spike-ins. We developed a novel metric, D-score, to evaluate caller specificity for deletions. The accuracy of deletions was evaluated by Sanger sequencing. We generated a high-quality call set of 152,301 deletions of diverse sizes. Sanger sequencing validated 114 of 146 detected deletions (78.1%). Scalpel excelled in accuracy for deletions ≤100 bp, whereas Parliament was optimal for deletions >900 bp. Overall, 83.0% and 72.5% of calls by Scalpel and Parliament were validated, respectively, including all 11 deletions called by both Parliament and Scalpel between 101 and 900 bp. Our flexible protocol successfully generated a high-quality deletion call set and a truth set of Sanger sequencing-validated deletions with precise breakpoints spanning 1-17,000 bp.
Project description:Current clinical next-generation sequencing is done by using gene panels and exome analysis, both of which involve selective capturing of target regions. However, capturing has limitations in sufficiently covering coding exons, especially GC-rich regions. We compared whole exome sequencing (WES) with the most recent PCR-free whole genome sequencing (WGS), showing that only the latter is able to provide hitherto unprecedented complete coverage of the coding region of the genome. Thus, from a clinical/technical point of view, WGS is the better WES so that capturing is no longer necessary for the most comprehensive genomic testing of Mendelian disorders.
Project description:Technological advances in Next-Generation Sequencing dramatically increased clinical efficiency of genetic testing, allowing detection of a wide variety of variants, from single nucleotide events to large structural aberrations. Whole Genome Sequencing (WGS) has allowed exploration of areas of the genome that might not have been targeted by other approaches, such as intergenic regions. A single technique detecting all genetic variants at once is intended to expedite the diagnostic process while making it more comprehensive and efficient. Nevertheless, there are still several shortcomings that cannot be effectively addressed by short read sequencing, such as determination of the precise size of short tandem repeat (STR) expansions, phasing of potentially compound recessive variants, resolution of some structural variants and exact determination of their boundaries, etc. Therefore, in some cases variants can only be tentatively detected by short reads sequencing and require orthogonal confirmation, particularly for clinical reporting purposes. Moreover, certain regulatory authorities, for example, New York state CLIA, require orthogonal confirmation of every reportable variant. Such orthogonal confirmations often involve numerous different techniques, not necessarily available in the same laboratory and not always performed in an expedited manner, thus negating the advantages of "one-technique-for-all" approach, and making the process lengthy, prone to logistical and analytical faults, and financially inefficient. Fortunately, those weak spots of short read sequencing can be compensated by long read technology that have comparable or better detection of some types of variants while lacking the mentioned above limitations of short read sequencing. At Variantyx we have developed an integrated clinical genetic testing approach, augmenting short read WGS-based variant detection with Oxford Nanopore Technologies (ONT) long read sequencing, providing simultaneous orthogonal confirmation of all types of variants with the additional benefit of improved identification of exact size and position of the detected aberrations. The validation study of this augmented test has demonstrated that Oxford Nanopore Technologies sequencing can efficiently verify multiple types of reportable variants, thus ensuring highly reliable detection and a quick turnaround time for WGS-based clinical genetic testing.
Project description:ObjectivesThe objective of this study was to determine the effectiveness of WGS in identifying resistance genotypes of MDR Escherichia coli and whether these correlate with observed phenotypes.MethodsSeventy-six E. coli strains were isolated from farm cattle and measured for phenotypic resistance to 15 antimicrobials with the Sensititre(®) system. Isolates with resistance to at least four antimicrobials in three classes were selected for WGS using an Illumina MiSeq. Genotypic analysis was conducted with in-house Perl scripts using BLAST analysis to identify known genes and mutations associated with clinical resistance.ResultsOver 30 resistance genes and a number of resistance mutations were identified among the E. coli isolates. Resistance genotypes correlated with 97.8% specificity and 99.6% sensitivity to the identified phenotypes. The majority of discordant results were attributable to the aminoglycoside streptomycin, whereas there was a perfect genotype-phenotype correlation for most antibiotic classes such as tetracyclines, quinolones and phenicols. WGS also revealed information about rare resistance mechanisms, such as structural mutations in chromosomal copies of ampC conferring third-generation cephalosporin resistance.ConclusionsWGS can provide comprehensive resistance genotypes and is capable of accurately predicting resistance phenotypes, making it a valuable tool for surveillance. Moreover, the data presented here showing the ability to accurately predict resistance suggest that WGS may be used as a screening tool in selecting anti-infective therapy, especially as costs drop and methods improve.
Project description:BackgroundTracking the spread of antimicrobial-resistant Neisseria gonorrhoeae is a major priority for national surveillance programmes.ObjectivesWe investigate whether WGS and simultaneous analysis of multiple resistance determinants can be used to predict antimicrobial susceptibilities to the level of MICs in N. gonorrhoeae.MethodsWGS was used to identify previously reported potential resistance determinants in 681 N. gonorrhoeae isolates, from England, the USA and Canada, with phenotypes for cefixime, penicillin, azithromycin, ciprofloxacin and tetracycline determined as part of national surveillance programmes. Multivariate linear regression models were used to identify genetic predictors of MIC. Model performance was assessed using leave-one-out cross-validation.ResultsOverall 1785/3380 (53%) MIC values were predicted to the nearest doubling dilution and 3147 (93%) within ±1 doubling dilution and 3314 (98%) within ±2 doubling dilutions. MIC prediction performance was similar across the five antimicrobials tested. Prediction models included the majority of previously reported resistance determinants. Applying EUCAST breakpoints to MIC predictions, the overall very major error (VME; phenotypically resistant, WGS-prediction susceptible) rate was 21/1577 (1.3%, 95% CI 0.8%-2.0%) and the major error (ME; phenotypically susceptible, WGS-prediction resistant) rate was 20/1186 (1.7%, 1.0%-2.6%). VME rates met regulatory thresholds for all antimicrobials except cefixime and ME rates for all antimicrobials except tetracycline. Country of testing was a strongly significant predictor of MIC for all five antimicrobials.ConclusionsWe demonstrate a WGS-based MIC prediction approach that allows reliable MIC prediction for five gonorrhoea antimicrobials. Our approach should allow reasonably precise prediction of MICs for a range of bacterial species.