Rapid Genomic Characterization and Global Surveillance of Klebsiella Using Pathogenwatch.

BACKGROUND: Klebsiella species, including the notable pathogen K. pneumoniae, are increasingly associated with antimicrobial resistance (AMR). Genome-based surveillance can inform interventions aimed at controlling AMR. However, its widespread implementation requires tools to streamline bioinformatic analyses and public health reporting. METHODS: We developed the web application Pathogenwatch, which implements analytics tailored to Klebsiella species for integration and visualization of genomic and epidemiological data. We populated Pathogenwatch with 16 537 public Klebsiella genomes to enable contextualization of user genomes. We demonstrated its features with 1636 genomes from 4 low- and middle-income countries (LMICs) participating in the NIHR Global Health Research Unit (GHRU) on AMR. RESULTS: Using Pathogenwatch, we found that GHRU genomes were dominated by a small number of epidemic drug-resistant clones of K. pneumoniae. However, differences in their distribution were observed (eg, ST258/512 dominated in Colombia, ST231 in India, ST307 in Nigeria, ST147 in the Philippines). Phylogenetic analyses including public genomes for contextualization enabled retrospective monitoring of their spread. In particular, we identified hospital outbreaks, detected introductions from abroad, and uncovered clonal expansions associated with resistance and virulence genes. Assessment of loci encoding O-antigens and capsule in K. pneumoniae, which represent possible vaccine candidates, showed that 3 O-types (O1-O3) represented 88.9% of all genomes, whereas capsule types were much more diverse. CONCLUSIONS: Pathogenwatch provides a free, accessible platform for real-time analysis of Klebsiella genomes to aid surveillance at local, national, and global levels. We have improved representation of genomes from GHRU participant countries, further facilitating ongoing surveillance.

Rare Variant Analysis of Human and Rodent Obesity Genes in Individuals with Severe Childhood Obesity.

Obesity is a genetically heterogeneous disorder. Using targeted and whole-exome sequencing, we studied 32 human and 87 rodent obesity genes in 2,548 severely obese children and 1,117 controls. We identified 52 variants contributing to obesity in 2% of cases including multiple novel variants in GNAS, which were sometimes found with accelerated growth rather than short stature as described previously. Nominally significant associations were found for rare functional variants in BBS1, BBS9, GNAS, MKKS, CLOCK and ANGPTL6. The p.S284X variant in ANGPTL6 drives the association signal (rs201622589, MAF~0.1%, odds ratio = 10.13, p-value = 0.042) and results in complete loss of secretion in cells. Further analysis including additional case-control studies and population controls (N = 260,642) did not support association of this variant with obesity (odds ratio = 2.34, p-value = 2.59 × 10-3), highlighting the challenges of testing rare variant associations and the need for very large sample sizes. Further validation in cohorts with severe obesity and engineering the variants in model organisms will be needed to explore whether human variants in ANGPTL6 and other genes that lead to obesity when deleted in mice, do contribute to obesity. Such studies may yield druggable targets for weight loss therapies.

'Pop-Up' Governance: developing internal governance frameworks for consortia: the example of UK10K.

Innovations in information technologies have facilitated the development of new styles of research networks and forms of governance. This is evident in genomics where increasingly, research is carried out by large, interdisciplinary consortia focussing on a specific research endeavour. The UK10K project is an example of a human genomics consortium funded to provide insights into the genomics of rare conditions, and establish a community resource from generated sequence data. To achieve its objectives according to the agreed timetable, the UK10K project established an internal governance system to expedite the research and to deal with the complex issues that arose. The project's governance structure exemplifies a new form of network governance called 'pop-up' governance. 'Pop-up' because: it was put together quickly, existed for a specific period, was designed for a specific purpose, and was dismantled easily on project completion. In this paper, we use UK10K to describe how 'pop-up' governance works on the ground and how relational, hierarchical and contractual governance mechanisms are used in this new form of network governance.

Whole-genome sequence-based analysis of thyroid function.

Normal thyroid function is essential for health, but its genetic architecture remains poorly understood. Here, for the heritable thyroid traits thyrotropin (TSH) and free thyroxine (FT4), we analyse whole-genome sequence data from the UK10K project (N=2,287). Using additional whole-genome sequence and deeply imputed data sets, we report meta-analysis results for common variants (MAF≥1%) associated with TSH and FT4 (N=16,335). For TSH, we identify a novel variant in SYN2 (MAF=23.5%, P=6.15 × 10(-9)) and a new independent variant in PDE8B (MAF=10.4%, P=5.94 × 10(-14)). For FT4, we report a low-frequency variant near B4GALT6/SLC25A52 (MAF=3.2%, P=1.27 × 10(-9)) tagging a rare TTR variant (MAF=0.4%, P=2.14 × 10(-11)). All common variants explain ≥20% of the variance in TSH and FT4. Analysis of rare variants (MAF<1%) using sequence kernel association testing reveals a novel association with FT4 in NRG1. Our results demonstrate that increased coverage in whole-genome sequence association studies identifies novel variants associated with thyroid function.

Managing clinically significant findings in research: the UK10K example.

Recent advances in sequencing technology allow data on the human genome to be generated more quickly and in greater detail than ever before. Such detail includes findings that may be of significance to the health of the research participant involved. Although research studies generally do not feed back information on clinically significant findings (CSFs) to participants, this stance is increasingly being questioned. There may be difficulties and risks in feeding clinically significant information back to research participants, however, the UK10K consortium sought to address these by creating a detailed management pathway. This was not intended to create any obligation upon the researchers to feed back any CSFs they discovered. Instead, it provides a mechanism to ensure that any such findings can be passed on to the participant where appropriate. This paper describes this mechanism and the specific criteria, which must be fulfilled in order for a finding and participant to qualify for feedback. This mechanism could be used by future research consortia, and may also assist in the development of sound principles for dealing with CSFs.

A rare variant in APOC3 is associated with plasma triglyceride and VLDL levels in Europeans.

The analysis of rich catalogues of genetic variation from population-based sequencing provides an opportunity to screen for functional effects. Here we report a rare variant in APOC3 (rs138326449-A, minor allele frequency ~0.25% (UK)) associated with plasma triglyceride (TG) levels (-1.43 s.d. (s.e.=0.27 per minor allele (P-value=8.0 × 10(-8))) discovered in 3,202 individuals with low read-depth, whole-genome sequence. We replicate this in 12,831 participants from five additional samples of Northern and Southern European origin (-1.0 s.d. (s.e.=0.173), P-value=7.32 × 10(-9)). This is consistent with an effect between 0.5 and 1.5 mmol l(-1) dependent on population. We show that a single predicted splice donor variant is responsible for association signals and is independent of known common variants. Analyses suggest an independent relationship between rs138326449 and high-density lipoprotein (HDL) levels. This represents one of the first examples of a rare, large effect variant identified from whole-genome sequencing at a population scale.

Implementing a successful data-management framework: the UK10K managed access model.

This paper outlines the history behind open access principles and describes the development of a managed access data-sharing process for the UK10K Project, currently Britain's largest genomic sequencing consortium (2010 to 2013). Funded by the Wellcome Trust, the purpose of UK10K was two-fold: to investigate how low-frequency and rare genetic variants contribute to human disease, and to provide an enduring data resource for future research into human genetics. In this paper, we discuss the challenge of reconciling data-sharing principles with the practicalities of delivering a sequencing project of UK10K's scope and magnitude. We describe the development of a sustainable, easy-to-use managed access system that allowed rapid access to UK10K data, while protecting the interests of participants and data generators alike. Specifically, we focus in depth on the three key issues that emerge in the data pipeline: study recruitment, data release and data access.

Finding and sharing: new approaches to registries of databases and services for the biomedical sciences.

The recent explosion of biological data and the concomitant proliferation of distributed databases make it challenging for biologists and bioinformaticians to discover the best data resources for their needs, and the most efficient way to access and use them. Despite a rapid acceleration in uptake of syntactic and semantic standards for interoperability, it is still difficult for users to find which databases support the standards and interfaces that they need. To solve these problems, several groups are developing registries of databases that capture key metadata describing the biological scope, utility, accessibility, ease-of-use and existence of web services allowing interoperability between resources. Here, we describe some of these initiatives including a novel formalism, the Database Description Framework, for describing database operations and functionality and encouraging good database practise. We expect such approaches will result in improved discovery, uptake and utilization of data resources. Database URL: http://www.casimir.org.uk/casimir_ddf.