seqr: A web-based analysis and collaboration tool for rare disease genomics.

Exome and genome sequencing have become the tools of choice for rare disease diagnosis, leading to large amounts of data available for analyses. To identify causal variants in these datasets, powerful filtering and decision support tools that can be efficiently used by clinicians and researchers are required. To address this need, we developed seqr - an open-source, web-based tool for family-based monogenic disease analysis that allows researchers to work collaboratively to search and annotate genomic callsets. To date, seqr is being used in several research pipelines and one clinical diagnostic lab. In our own experience through the Broad Institute Center for Mendelian Genomics, seqr has enabled analyses of over 10,000 families, supporting the diagnosis of more than 3,800 individuals with rare disease and discovery of over 300 novel disease genes. Here, we describe a framework for genomic analysis in rare disease that leverages seqr's capabilities for variant filtration, annotation, and causal variant identification, as well as support for research collaboration and data sharing. The seqr platform is available as open source software, allowing low-cost participation in rare disease research, and a community effort to support diagnosis and gene discovery in rare disease.

ClinGen advancing genomic data-sharing standards as a GA4GH driver project.

The Clinical Genome Resource (ClinGen)'s work to develop a knowledge base to support the understanding of genes and variants for use in precision medicine and research depends on robust, broadly applicable, and adaptable technical standards for sharing data and information. To forward this goal, ClinGen has joined with the Global Alliance for Genomics and Health (GA4GH) to support the development of open, freely-available technical standards and regulatory frameworks for secure and responsible sharing of genomic and health-related data. In its capacity as one of the 15 inaugural GA4GH "Driver Projects," ClinGen is providing input on the key standards needs of the global genomics community, and has committed to participate on GA4GH Work Streams to support the development of: (1) a standard model for computer-readable variant representation; (2) a data model for linking variant data to annotations; (3) a specification to enable sharing of genomic variant knowledge and associated clinical interpretations; and (4) a set of best practices for use of phenotype and disease ontologies. ClinGen's participation as a GA4GH Driver Project will provide a robust environment to test drive emerging genomic knowledge sharing standards and prove their utility among the community, while accelerating the construction of the ClinGen evidence base.

matchbox: An open-source tool for patient matching via the Matchmaker Exchange.

Rare disease investigators constantly face challenges in identifying additional cases to build evidence for gene-disease causality. The Matchmaker Exchange (MME) addresses this limitation by providing a mechanism for matching patients across genomic centers via a federated network. The MME has revolutionized searching for additional cases by making it possible to query across institutional boundaries, so that what was once a laborious and manual process of contacting researchers is now automated and computable. However, while the MME network is beginning to scale, the growth of additional nodes is limited by the lack of easy-to-use solutions that can be implemented by any rare disease database owner, even one without significant software engineering resources. Here, we describe matchbox, which is an open-source, platform-independent, portable bridge between any given rare disease genomic center and the MME network, which has already led to novel gene discoveries. We also describe how matchbox greatly reduces the barrier to participation by overcoming challenges for new databases to join the MME.

Matchmaker Exchange.

In well over half of the individuals with rare disease who undergo clinical or research next-generation sequencing, the responsible gene cannot be determined. Some reasons for this relatively low yield include unappreciated phenotypic heterogeneity; locus heterogeneity; somatic and germline mosaicism; variants of uncertain functional significance; technically inaccessible areas of the genome; incorrect mode of inheritance investigated; and inadequate communication between clinicians and basic scientists with knowledge of particular genes, proteins, or biological systems. To facilitate such communication and improve the search for patients or model organisms with similar phenotypes and variants in specific candidate genes, we have developed the Matchmaker Exchange (MME). MME was created to establish a federated network connecting databases of genomic and phenotypic data using a common application programming interface (API). To date, seven databases can exchange data using the API (GeneMatcher, PhenomeCentral, DECIPHER, MyGene2, matchbox, Australian Genomics Health Alliance Patient Archive, and Monarch Initiative; the latter included for model organism matching). This article guides usage of the MME for rare disease gene discovery. © 2017 by John Wiley & Sons, Inc.

Bacteriophages to reduce gut carriage of antibiotic resistant uropathogens with low impact on microbiota composition.

Uropathogenic Escherichia coli (UPEC) is the leading cause of urinary tract infections (UTIs) worldwide, causing over 150 million clinical cases annually. There is currently no specific treatment addressing the asymptomatic carriage in the gut of UPEC before they initiate UTIs. This study investigates the efficacy of virulent bacteriophages to decrease carriage of gut pathogens. Three virulent bacteriophages infecting an antibiotic-resistant UPEC strain were isolated and characterized both in vitro and in vivo. A new experimental murine model of gut carriage of E. coli was elaborated and the impact of virulent bacteriophages on colonization levels and microbiota diversity was assessed. A single dose of a cocktail of the three bacteriophages led to a sharp decrease in E. coli levels throughout the gut. We also observed that microbiota diversity was much less affected by bacteriophages than by antibiotics. Therefore, virulent bacteriophages can efficiently target UPEC strains residing in the gut, with potentially profound public health and economic impacts. These results open a new area with the possibility to manipulate specifically the microbiota using virulent bacteriophages, which could have broad applications in many gut-related disorders/diseases and beyond.

Genomic epidemiology of the Escherichia coli O104:H4 outbreaks in Europe, 2011.

The degree to which molecular epidemiology reveals information about the sources and transmission patterns of an outbreak depends on the resolution of the technology used and the samples studied. Isolates of Escherichia coli O104:H4 from the outbreak centered in Germany in May-July 2011, and the much smaller outbreak in southwest France in June 2011, were indistinguishable by standard tests. We report a molecular epidemiological analysis using multiplatform whole-genome sequencing and analysis of multiple isolates from the German and French outbreaks. Isolates from the German outbreak showed remarkably little diversity, with only two single nucleotide polymorphisms (SNPs) found in isolates from four individuals. Surprisingly, we found much greater diversity (19 SNPs) in isolates from seven individuals infected in the French outbreak. The German isolates form a clade within the more diverse French outbreak strains. Moreover, five isolates derived from a single infected individual from the French outbreak had extremely limited diversity. The striking difference in diversity between the German and French outbreak samples is consistent with several hypotheses, including a bottleneck that purged diversity in the German isolates, variation in mutation rates in the two E. coli outbreak populations, or uneven distribution of diversity in the seed populations that led to each outbreak.

High quality draft genome sequence of Segniliparus rugosus CDC 945(T)= (ATCC BAA-974(T)).

Segniliparus rugosus represents one of two species in the genus Segniliparus, the sole genus in the family Segniliparaceae. A unique and interesting feature of this family is the presence of extremely long carbon-chain length mycolic acids bound in the cell wall. S. rugosus is also a medically important species because it is an opportunistic pathogen associated with mammalian lung disease. This report represents the second species in the genus to have its genome sequenced. The 3,567,567 bp long genome with 3,516 protein-coding and 49 RNA genes is part of the NIH Roadmap for Medical Research, Human Microbiome Project.

Closing gaps in the human genome using sequencing by synthesis.

The most recent release of the finished human genome contains 260 euchromatic gaps (excluding chromosome Y). Recent work has helped explain a large number of these unresolved regions as 'structural' in nature. Another class of gaps is likely to be refractory to clone-based approaches, and cannot be approached in ways previously described. We present an approach for closing these gaps using 454 sequencing. As a proof of principle, we closed all three remaining non-structural gaps in chromosome 15.

Analysis of the DNA sequence and duplication history of human chromosome 15.

Here we present a finished sequence of human chromosome 15, together with a high-quality gene catalogue. As chromosome 15 is one of seven human chromosomes with a high rate of segmental duplication, we have carried out a detailed analysis of the duplication structure of the chromosome. Segmental duplications in chromosome 15 are largely clustered in two regions, on proximal and distal 15q; the proximal region is notable because recombination among the segmental duplications can result in deletions causing Prader-Willi and Angelman syndromes. Sequence analysis shows that the proximal and distal regions of 15q share extensive ancient similarity. Using a simple approach, we have been able to reconstruct many of the events by which the current duplication structure arose. We find that most of the intrachromosomal duplications seem to share a common ancestry. Finally, we demonstrate that some remaining gaps in the genome sequence are probably due to structural polymorphisms between haplotypes; this may explain a significant fraction of the gaps remaining in the human genome.