Bernard J. Pope

SRST2: Rapid genomic surveillance for public health and hospital microbiology labs

Rapid molecular typing of bacterial pathogens is critical for public health epidemiology, surveillance and infection control, yet routine use of whole genome sequencing (WGS) for these purposes poses significant challenges. Here we present SRST2, a read mapping-based tool for fast and accurate detection of genes, alleles and multi-locus sequence types (MLST) from WGS data. Using >900 genomes from common pathogens, we show SRST2 is highly accurate and outperforms assembly-based methods in terms of both gene detection and allele assignment. We include validation of SRST2 within a public health laboratory, and demonstrate its use for microbial genome surveillance in the hospital setting. In the face of rising threats of antimicrobial resistance and emerging virulence among bacterial pathogens, SRST2 represents a powerful tool for rapidly extracting clinically useful information from raw WGS data.Source code is available from http://katholt.github.io/srst2/.

Rare Mutations in XRCC2 Increase the Risk of Breast Cancer

An exome-sequencing study of families with multiple breast-cancer-affected individuals identified two families with XRCC2 mutations, one with a protein-truncating mutation and one with a probably deleterious missense mutation. We performed a population-based case-control mutation-screening study that identified six probably pathogenic coding variants in 1,308 cases with early-onset breast cancer and no variants in 1,120 controls (the severity grading was p < 0.02). We also performed additional mutation screening in 689 multiple-case families. We identified ten breast-cancer-affected families with protein-truncating or probably deleterious rare missense variants in XRCC2. Our identification of XRCC2 as a breast cancer susceptibility gene thus increases the proportion of breast cancers that are associated with homologous recombination-DNA-repair dysfunction and Fanconi anemia and could therefore benefit from specific targeted treatments such as PARP (poly ADP ribose polymerase) inhibitors. This study demonstrates the power of massively parallel sequencing for discovering susceptibility genes for common, complex diseases.

MYRF Is a Membrane-Associated Transcription Factor That Autoproteolytically Cleaves to Directly Activate Myelin Genes

Oligodendrocyte development and myelination rely on an unusual membrane-associated transcription factor that shares functional domains with bacteriophage proteins.

Bpipe : A Tool for Running and Managing Bioinformatics Pipelines

SUMMARY Bpipe is a simple, dedicated programming language for defining and executing bioinformatics pipelines. It specializes in enabling users to turn existing pipelines based on shell scripts or command line tools into highly flexible, adaptable and maintainable workflows with a minimum of effort. Bpipe ensures that pipelines execute in a controlled and repeatable fashion and keeps audit trails and logs to ensure that experimental results are reproducible. Requiring only Java as a dependency, Bpipe is fully self-contained and cross-platform, making it very easy to adopt and deploy into existing environments. AVAILABILITY AND IMPLEMENTATION Bpipe is freely available from http://bpipe.org under a BSD License.

Practical aspects of declarative debugging in Haskell 98

Non-strict purely functional languages pose many challenges to the designers of debugging tools. Declarative debugging has long been considered a suitable candidate for the task due to its abstraction over the evaluation order of the program, although the provision of practical implementations has been lagging. In this paper we discuss the solutions used in our declarative debugger for Haskell to tackle the problems of printing values, memory usage and I/O. The debugger is based on program transformation, although much leverage is gained by interfacing with the runtime environment of the language implementation through a foreign function interface.

A high-plex PCR approach for massively parallel sequencing

Current methods for targeted massively parallel sequencing (MPS) have several drawbacks, including limited design flexibility, expense, and protocol complexity, which restrict their application to settings involving modest target size and requiring low cost and high throughput. To address this, we have developed Hi-Plex, a PCR-MPS strategy intended for high-throughput screening of multiple genomic target regions that integrates simple, automated primer design software to control product size. Featuring permissive thermocycling conditions and clamp bias reduction, our protocol is simple, cost- and time-effective, uses readily available reagents, does not require expensive instrumentation, and requires minimal optimization. In a 60-plex assay targeting the breast cancer predisposition genes PALB2 and XRCC2, we applied Hi-Plex to 100 ng LCL-derived DNA, and 100 ng and 25 ng FFPE tumor-derived DNA. Altogether, at least 86.94% of the human genome-mapped reads were on target, and 100% of targeted amplicons were represented within 25-fold of the mean. Using 25 ng FFPE-derived DNA, 95.14% of mapped reads were on-target and relative representation ranged from 10.1-fold lower to 5.8-fold higher than the mean. These results were obtained using only the initial automatically-designed primers present in equal concentration. Hi-Plex represents a powerful new approach for screening panels of genomic target regions.

Rare Mutations in RINT1 Predispose Carriers to Breast and Lynch Syndrome–Spectrum Cancers

UNLABELLED Approximately half of the familial aggregation of breast cancer remains unexplained. A multiple-case breast cancer family exome-sequencing study identified three likely pathogenic mutations in RINT1 (NM_021930.4) not present in public sequencing databases: RINT1 c.343C>T (p.Q115X), c.1132_1134del (p.M378del), and c.1207G>T (p.D403Y). On the basis of this finding, a population-based case-control mutation-screening study was conducted that identified 29 carriers of rare (minor allele frequency < 0.5%), likely pathogenic variants: 23 in 1,313 early-onset breast cancer cases and six in 1,123 frequency-matched controls [OR, 3.24; 95% confidence interval (CI), 1.29-8.17; P = 0.013]. RINT1 mutation screening of probands from 798 multiple-case breast cancer families identified four additional carriers of rare genetic variants. Analysis of the incidence of first primary cancers in families of women carrying RINT1 mutations estimated that carriers were at increased risk of Lynch syndrome-spectrum cancers [standardized incidence ratio (SIR), 3.35; 95% CI, 1.7-6.0; P = 0.005], particularly for relatives diagnosed with cancer under the age of 60 years (SIR, 10.9; 95% CI, 4.7-21; P = 0.0003). SIGNIFICANCE The work described in this study adds RINT1 to the growing list of genes in which rare sequence variants are associated with intermediate levels of breast cancer risk. Given that RINT1 is also associated with a spectrum of cancers with mismatch repair defects, these findings have clinical applications and raise interesting biological questions.

A lightweight interactive debugger for haskell

This paper describes the design and construction of a Haskell source-level debugger built into the GHCi interactive environment. We have taken a pragmatic approach: the debugger is based on the traditional stop-examine-continue model of online debugging, which is simple and intuitive, but has traditionally been shunned in the context of Haskell because it exposes the lazy evaluation order. We argue that this drawback is not as severe as it may seem, and in some cases is an advantage. The design focuses on availability: our debugger is intended to work on all programs that can be compiled with GHC, and without requiring the programmer to jump through additional hoops to debug their program. The debugger has a novel approach for reconstructing the type of runtime values in a polymorphic context. Our implementation is light on complexity, and was integrated into GHC without significant upheaval.

Performance of Hybrid Programming Models for Multiscale Cardiac Simulations: Preparing for Petascale Computation

Future multiscale and multiphysics models that support research into human disease, translational medical science, and treatment can utilize the power of high-performance computing (HPC) systems. We anticipate that computationally efficient multiscale models will require the use of sophisticated hybrid programming models, mixing distributed message-passing processes [e.g., the message-passing interface (MPI)] with multithreading (e.g., OpenMP, Pthreads). The objective of this study is to compare the performance of such hybrid programming models when applied to the simulation of a realistic physiological multiscale model of the heart. Our results show that the hybrid models perform favorably when compared to an implementation using only the MPI and, furthermore, that OpenMP in combination with the MPI provides a satisfactory compromise between performance and code complexity. Having the ability to use threads within MPI processes enables the sophisticated use of all processor cores for both computation and communication phases. Considering that HPC systems in 2012 will have two orders of magnitude more cores than what was used in this study, we believe that faster than real-time multiscale cardiac simulations can be achieved on these systems.

ROVER variant caller: read-pair overlap considerate variant-calling software applied to PCR-based massively parallel sequencing datasets.

BackgroundWe recently described Hi-Plex, a highly multiplexed PCR-based target-enrichment system for massively parallel sequencing (MPS), which allows the uniform definition of library size so that subsequent paired-end sequencing can achieve complete overlap of read pairs. Variant calling from Hi-Plex-derived datasets can thus rely on the identification of variants appearing in both reads of read-pairs, permitting stringent filtering of sequencing chemistry-induced errors. These principles underly ROVER software (derived from Read Overlap PCR-MPS variant caller), which we have recently used to report the screening for genetic mutations in the breast cancer predisposition gene PALB2. Here, we describe the algorithms underlying ROVER and its usage.ResultsROVER enables users to quickly and accurately identify genetic variants from PCR-targeted, overlapping paired-end MPS datasets. The open-source availability of the software and threshold tailorability enables broad access for a range of PCR-MPS users.MethodsROVER is implemented in Python and runs on all popular POSIX-like operating systems (Linux, OS X). The software accepts a tab-delimited text file listing the coordinates of the target-specific primers used for targeted enrichment based on a specified genome-build. It also accepts aligned sequence files resulting from mapping to the same genome-build. ROVER identifies the amplicon a given read-pair represents and removes the primer sequences by using the mapping co-ordinates and primer co-ordinates. It considers overlapping read-pairs with respect to primer-intervening sequence. Only when a variant is observed in both reads of a read-pair does the signal contribute to a tally of read-pairs containing or not containing the variant. A user-defined threshold informs the minimum number of, and proportion of, read-pairs a variant must be observed in for a ‘call’ to be made. ROVER also reports the depth of coverage across amplicons to facilitate the identification of any regions that may require further screening.ConclusionsROVER can facilitate rapid and accurate genetic variant calling for a broad range of PCR-MPS users.