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Daniel J Turner

Publications and source records attributed to Daniel J Turner.

5 recordsLinked to original sources

Nanopore DNA Sequencing and Genome Assembly on the International Space Station

The emergence of nanopore-based sequencers greatly expands the reach of sequencing into low-resource field environments, enabling in situ molecular analysis. In this work, we evaluated the performance of the MinION DNA sequencer (Oxford Nanopore Technologies) in-flight on the International Space Station (ISS), and benchmarked its performance off-Earth against the MinION, Illumina MiSeq, and PacBio RS II sequencing platforms in terrestrial laboratories. Samples contained mixtures of genomic DNA extracted from lambda bacteriophage, Escherichia coli (strain K12) and Mus musculus (BALB/c). The in-flight sequencing experiments generated more than 80,000 total reads with mean 2D accuracies of 85 - 90%, mean 1D accuracies of 75 - 80%, and median read lengths of approximately 6,000 bases. We were able to construct directed assemblies of the ~4.7 Mb E. coli genome, ~48.5 kb lambda genome, and a representative M. musculus sequence (the ~16.3 kb mitochondrial genome), at 100%, 100%, and 96.7% pairwise identity, respectively, and de novo assemblies of the lambda and E. coli genomes generated solely from nanopore reads yielded 100% and 99.8% genome coverage, respectively, at 100% and 98.5% pairwise identity. Across all surveyed metrics (base quality, throughput, stays/base, skips/base), no observable decrease in MinION performance was observed while sequencing DNA in space. Simulated runs of in-flight nanopore data using an automated bioinformatic pipeline and cloud or laptop based genomic assembly demonstrated the feasibility of real-time sequencing analysis and direct microbial identification in space. Applications of sequencing for space exploration include infectious disease diagnosis, environmental monitoring, evaluating biological responses to spaceflight, and even potentially the detection of extraterrestrial life on other planetary bodies.

Genomics

Highly parallel direct RNA sequencing on an array of nanopores

Ribonucleic acid sequencing can allow us to monitor the RNAs present in a sample. This enables us to detect the presence and nucleotide sequence of viruses, or to build a picture of how active transcriptional processes are changing - information that is useful for understanding the status and function of a sample. Oxford Nanopore Technologies sequencing technology is capable of electronically analysing a samples DNA directly, and in real-time. In this manuscript we demonstrate the ability of an array of nanopores to sequence RNA directly, and we apply it to a range of biological situations. Nanopore technology is the only available sequencing technology that can sequence RNA directly, rather than depending on reverse transcription and PCR. There are several potential advantages of this approach over other RNA-seq strategies, including the absence of amplification and reverse transcription biases, the ability to detect nucleotide analogues and the ability to generate full-length, strand-specific RNA sequences. Direct RNA sequencing is a completely new way of analysing the sequence of RNA samples and it will improve the ease and speed of RNA analysis, while yielding richer biological information.

Genomics

Exploratory analysis and error modeling of a sequencing technology

Next generation DNA sequencing methods have created an unprecedented leap in sequence data generation, thus novel computational tools and statistical models are required to optimize and assess the resulting data. In this report, we explore underlying causes of error for the Illumina Genome Analyzer (IGA) sequencing technology and attempt to quantify their effects using a human bacterial artificial chromosome sequenced to 60,000 fold coverage. Seven potential error predictors are considered: Phred score, read entropy, tile coordinates, local tile density, base position within read, nucleotide call, and lane. With these parameters, logistic regression and log-linear models are constructed and used to show that each of the potential predictors contributes to error (P<1x10-4). With this additional information, we apply the logistic model and achieve a 3% improvement in both the sensitivity and specificity to detect IGA errors. Further, we demonstrate that these modeling approaches can be used as a feedback loop to inform laboratory methods and identify specific machine or run bias.

Genomics

What’s in my pot? Real-time species identification on the MinION™

Whole genome sequencing on next-generation instruments provides an unbiased way to identify the organisms present in complex metagenomic samples. However, the time-to-result can be protracted because of fixed-time sequencing runs and cumbersome bioinformatics workflows. This limits the utility of the approach in settings where rapid species identification is crucial, such as in the quality control of food-chain components, or in during an outbreak of an infectious disease. Here we present Whats in my Pot? (WIMP), a laboratory and analysis workflow in which, starting with an unprocessed sample, sequence data is generated and bacteria, viruses and fungi present in the sample are classified to subspecies and strain level in a quantitative manner, without prior knowledge of the sample composition, in approximately 3.5 hours. This workflow relies on the combination of Oxford Nanopore Technologies MinION sensing device with a real-time species identification bioinformatics application.

Genomics

Complete assembly of novel environmental bacterial genomes by MinIONTM sequencing

In this study, we adapt a protocol for the growth of previously uncultured environmental bacterial isolates, to make it compatible with whole genome sequencing. We demonstrate that in combination with the MinION sequencing device, complete assemblies can be derived, allowing genomic comparisons to be made. This approach allows rapid, inexpensive and straightforward discovery, and genomic analysis, of previously uncultured prokaryotic genomes, and brings greater ownership of all parts of the sequencing process back to individual researchers.

Microbiology