Biology subjects

Kaiser, M. D.

Publications and source records attributed to Kaiser, M. D..

3 recordsLinked to original sources

bioRxiv2020

Duplications drive diversity in Bordetella pertussis on an underestimated scale.

Bacterial genetic diversity is often described using solely base pair changes despite a wide variety of other mutation types likely being major contributors. Tandem duplications of genomic loci are thought to be widespread among bacteria but due to their often intractable size and instability, comprehensive studies of the range and genome dynamics of these mutations are rare. We define a methodology to investigate duplications in bacterial genomes based on read depth of genome sequence data as a proxy for copy number. We demonstrate the approach with Bordetella pertussis, whose insertion sequence element-rich genome provides extensive scope for duplications to occur. Analysis of genome sequence data for 2430 B. pertussis isolates identified 272 putative duplications, of which 94% were located at 11 hotspot loci. We demonstrate limited phylogenetic connection for the occurrence of duplications, suggesting unstable and sporadic characteristics. Genome instability was further described in-vitro using long read sequencing via the Nanopore platform. Clonally derived laboratory cultures produced heterogenous populations containing multiple structural variants. Short read data was used to predict 272 duplications, whilst long reads generated on the Nanopore platform enabled the in-depth study of the genome dynamics of tandem duplications in B. pertussis. Our work reveals the unrecognised and dynamic genetic diversity of B. pertussis and, as the complexity of the B. pertussis genome is not unique, highlights the need for a holistic and fundamental understanding of bacterial genetics.

microbiology↗

bioRxiv2017

Automated Structural Variant Verification In Human Genomes Using Single-Molecule Electronic DNA Mapping

The importance of structural variation in human disease and the difficulty of detecting structural variants larger than 50 base pairs has led to the development of several long-read sequencing technologies and optical mapping platforms. Frequently, multiple technologies and ad hoc methods are required to obtain a consensus regarding the location, size and nature of a structural variant, with no approach able to reliably bridge the gap of variant sizes between the domain of short-read approaches and the largest rearrangements observed with optical mapping.\n\nTo address this unmet need, we have developed a new software package, SV-Verify, which utilizes data collected with the Nabsys High Definition Mapping (HD-Mapping) system, to perform hypothesis-based verification of putative deletions. We demonstrate that whole genome maps, constructed from electronic detection of tagged DNA, hundreds of kilobases in length, can be used effectively to facilitate calling of structural variants ranging in size from 300 base pairs to hundreds of kilobase pairs. SV-Verify implements hypothesis-based verification of putative structural variants using a set of support vector machines and is capable of concurrently testing several thousand independent hypotheses. We describe support vector machine training, utilizing a well-characterized human genome, and application of the resulting classifiers to another human genome, demonstrating high sensitivity and specificity for deletions [≥]300 base pairs.

genomics↗

bioRxiv2017

High-Definition Electronic Genome Maps From Single Molecule Data

With the advent of routine short-read genome sequencing has come a growing recognition of the importance of long-range, structural information in applications ranging from sequence assembly to the detection of structural variation. Here we describe the Nabsys solid-state detector capable of detecting tags on single molecules of DNA 100s of kilobases in length as they translocate through the detector at a velocity greater than 1 megabase pair per second. Sequence-specific tags are detected with a high signal-to-noise ratio. The physical distance between tags is determined after accounting for viscous drag-induced intramolecular velocity fluctuations. The accurate measurement of the physical distance between tags on each molecule and the ability of the detector to resolve distances between tags of less than 300 base-pairs enables the construction of high-density genome maps.

genomics↗