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Development of Bioinformatic Tools for Retroviral Analysis from High Throughput Sequence Data
No full textFor hundreds of millions of years, retroviruses have been integrating into genomes of vertebrates. This thesis contributes to the development of new methods for retrieval, characterization and the comparison of viruses that have integrated into the genome (endogenous retroviruses, or ERVs) and their integration sites in host genomes. The koala retrovirus is an outstanding study subject since it is currently in the transition from an exogenous to an endogenous retrovirus. In the past decades, high-throughput sequencing (HTS) has allowed scientists to investigate genomic data at high coverage and low costs. However, the development of new sequencing technologies facilitated the production of vast amounts of data. The analysis bottleneck has shifted from data production to the analysis of so-called “big data”. In consequence, new algorithms and pipelines need to be established to process biological data. Solutions for automated handling of short-read HTS data exist for many problems and can be improved and extended. Recent improvements in HTS resulting in longer sequence fragments have helped solve problems connected to short-read sequencing but produced new challenges for genomics data processing. In this thesis, I present pipelines to comprehensively profile endogenous retroviruses from short-read HTS data for museum koala samples (ancient DNA) and describe a new method to amplify retroviral integration sites facilitating long-read HTS. The thesis is divided into five sections. In the first part, I describe the biological problem, the evolution of sequencing technologies, resulting in information technology problems and proposed solutions (chapter 1). In the second chapter, I present a comparison of three different target enrichment techniques to retrieve retroviral integration sites from museum koala samples. The computational pipeline I developed for this purpose is presented. In chapter 3 I describe a method (sonication inverse polymerase chain reaction) for target enrich- ment of long sequence fragments to exploit the capacities of third-generation sequencing technologies. An analysis pipeline for the processing of sonication inverse PCR products was established. Moreover, the remaining problems resulting from artificial read structures are discussed. In chapter 4 the method described in chapter 3 was used to profile koala retrovirus integrations. The striking discovery of a new retroviral recombinant in koalas is reported. Finally, I discuss our findings and compare short- and long-read HTS technologies. An outlook for further applications and remaining computational problems is outlined. Overall, this thesis contributes to the automated computational processing of HTS data from target enrichment techniques to profile endogenous retroviruses in host genomes
Coupled, Physics-Based Modeling Reveals Earthquake Displacements are Critical to the 2018 Palu, Sulawesi Tsunami
No full textThe September 2018, Mw 7.5 Sulawesi earthquake occurring on the Palu-Koro strike-slip fault system was followed by an unexpected localized tsunami. We show that direct earthquake-induced uplift and subsidence could have sourced the observed tsunami within Palu Bay. To this end, we use a physics-based, coupled earthquake–tsunami modeling framework tightly constrained by observations. The model combines rupture dynamics, seismic wave propagation, tsunami propagation and inundation. The earthquake scenario, featuring sustained supershear rupture propagation, matches key observed earthquake characteristics, including the moment magnitude, rupture duration, fault plane solution, teleseismic waveforms and inferred horizontal ground displacements. The remote stress regime reflecting regional transtension applied in the model produces a combination of up to 6 m left-lateral slip and up to 2 m normal slip on the straight fault segment dipping 65∘ East beneath Palu Bay. The time-dependent, 3D seafloor displacements are translated into bathymetry perturbations with a mean vertical offset of 1.5 m across the submarine fault segment. This sources a tsunami with wave amplitudes and periods that match those measured at the Pantoloan wave gauge and inundation that reproduces observations from field surveys. We conclude that a source related to earthquake displacements is probable and that landsliding may not have been the primary source of the tsunami. These results have important implications for submarine strike-slip fault systems worldwide. Physics-based modeling offers rapid response specifically in tectonic settings that are currently underrepresented in operational tsunami hazard assessment
VARSCOT: variant-aware detection and scoring enables sensitive and personalized off-target detection for CRISPR-Cas9
No full textBackground
Natural variations in a genome can drastically alter the CRISPR-Cas9 off-target landscape by creating or removing sites. Despite the resulting potential side-effects from such unaccounted for sites, current off-target detection pipelines are not equipped to include variant information. To address this, we developed VARiant-aware detection and SCoring of Off-Targets (VARSCOT).
Results
VARSCOT identifies only 0.6% of off-targets to be common between 4 individual genomes and the reference, with an average of 82% of off-targets unique to an individual. VARSCOT is the most sensitive detection method for off-targets, finding 40 to 70% more experimentally verified off-targets compared to other popular software tools and its machine learning model allows for CRISPR-Cas9 concentration aware off-target activity scoring.
Conclusions
VARSCOT allows researchers to take genomic variation into account when designing individual or population-wide targeting strategies. VARSCOT is available from https://github.com/BauerLab/VARSCOT
Note on Interacting Langevin Diffusions: Gradient Structure and Ensemble Kalman Sampler by Garbuno-Inigo, Hoffmann, Li and Stuart
No full textAn interacting system of Langevin dynamics driven particles has been proposed forsampling from a given posterior density by Garbuno-Inigo, Hoffmann, Li and StuartinInteracting Langevin Diffusions: Gradient Structure and Ensemble Kalman Sampler(arXiv:1903:08866v2). The proposed formulation is primarily studiedfrom a formalmean-field limit perspective, while the theoretical behaviour under afinite particlesize is left as an open problem. In this note we demonstrate that theparticle-basedcovariance interaction term requires a non-trivial correction. Wealso show that thecorrected dynamics samples exactly from the desired posterior provided that the em-pirical covariance matrix of the particle system remains non-singular and the posteriorlog-density satisfies the standard Bakry– ́Emery criterion
Eigendecompositions of Transfer Operators in Reproducing Kernel Hilbert Spaces
Get PDFTransfer operators such as the Perron-Frobenius or Koopman operator play an important role in the global analysis of complex dynamical systems. The eigenfunctions of these operators can be used to detect metastable sets, to project the dynamics onto the dominant slow processes, or to separate superimposed signals. We extend transfer operator theory to reproducing kernel Hilbert spaces and show that these operators are related to Hilbert space representations of conditional distributions, known as conditional mean embeddings in the machine learning community. Moreover, numerical methods to compute empirical estimates of these embeddings are akin to data-driven methods for the approximation of transfer operators such as extended dynamic mode decomposition and its variants. In fact, most of the existing methods can be derived from our framework, providing a unifying view on the approximation of transfer operators. One main benefit of the presented kernel-based approaches is that these methods can be applied to any domain where a similarity measure given by a kernel is available. We illustrate the results with the aid of guiding examples and highlight potential applications in molecular dynamics as well as video and text data analysis
Stochastic homogenization of rate-dependent models of monotone type in plasticity
Get PDFIn this work we deal with the stochastic homogenization of the initial boundary value problems of monotone type. The models of monotone type under consideration describe the deformation behaviour of inelastic materials with a microstructure which can be characterised by random measures. Based on the Fitzpatrick function concept we reduce the study of the asymptotic behaviour of monotone operators associated with our models to the problem of the stochastic homogenization of convex functionals within an ergodic and stationary setting. The concept of Fitzpatrick's function helps us to introduce and show the existence of the weak solutions for rate-dependent systems. The derivations of the homogenization results presented in this work are based on the stochastic two-scale convergence in Sobolev spaces. For completeness, we also present some two-scale homogenization results for convex functionals, which are related to the classical Γ-convergence theory
State and parameter estimation from observed signal increments
Get PDFThe success of the ensemble Kalman filter has triggered a strong interest in expanding its scope beyond classical state estimation problems. In this paper, we focus on continuous-time data assimilation where the model and measurement errors are correlated and both states and parameters need to be identified. Such scenarios arise from noisy and partial observations of Lagrangian particles which move under a stochastic velocity field involving unknown parameters. We take an appropriate class of McKean-Vlasov equations as the starting point to derive ensemble Kalman-Bucy filter algorithms for combined state and parameter estimation. We demonstrate their performance through a series of increasingly complex multi-scale model systems
Memory-kernel extraction for different molecular solutes in solvents of varying viscosity in confinement
No full textThe friction coefficient of molecular solutes depends on the solute, on the solvent, and on the solute-solvent interactions, but is typically assumed to not depend on an externally applied force that acts on the solute. In this paper we compute the friction memory function from molecular dynamics simulations and show that the friction coefficients of harmonically confined methane, water, Na+, an artificial Na− ion, and glycerol in water in fact increase with confinement strength. The results show that the friction increase with confinement strength is a fundamental effect that occurs for hydrophobic, hydrophilic, as well as charged molecules. We demonstrate that a parameter-free extraction of the running integral over the memory function yields the most robust results when compared to methods based on parametrization or Fourier transforms. In all systems, this friction increase is accompanied by a slowdown of the solvent dynamics in the first hydration shell of the solutes. By simulations of a confined glycerol molecule in water-glycerol mixtures, we furthermore demonstrate that the friction dependence on the confining potential is magnified in more viscous solvents, which suggests that this effect plays an important role for larger molecules in highly viscous solutions like polymer melts, in line with dynamic scaling arguments
Where did you come from, where did you go: Refining metagenomic analysis tools for horizontal gene transfer characterisation
No full textHorizontal gene transfer (HGT) has changed the way we regard evolution. Instead of waiting for the next generation to establish new traits, especially bacteria are able to take a shortcut via HGT that enables them to pass on genes from one individual to another, even across species boundaries. The tool Daisy offers the first HGT detection approach based on read mapping that provides complementary evidence compared to existing methods. However, Daisy relies on the acceptor and donor organism involved in the HGT being known. We introduce DaisyGPS, a mapping-based pipeline that is able to identify acceptor and donor reference candidates of an HGT event based on sequencing reads. Acceptor and donor identification is akin to species identification in metagenomic samples based on sequencing reads, a problem addressed by metagenomic profiling tools. However, acceptor and donor references have certain properties such that these methods cannot be directly applied. DaisyGPS uses MicrobeGPS, a metagenomic profiling tool tailored towards estimating the genomic distance between organisms in the sample and the reference database. We enhance the underlying scoring system of MicrobeGPS to account for the sequence patterns in terms of mapping coverage of an acceptor and donor involved in an HGT event, and report a ranked list of reference candidates. These candidates can then be further evaluated by tools like Daisy to establish HGT regions. We successfully validated our approach on both simulated and real data, and show its benefits in an investigation of an outbreak involving Methicillin-resistant Staphylococcus aureus data.
Author summary
Evolution is traditionally viewed as a process where changes are only vertically inherited from parent to offspring across generations. Many principles such as phylogenetic trees and even the “tree of life” are based on that doctrine. The concept of horizontal gene transfer changed the way we regard evolution completely. Horizontal gene transfer is the movement of genetic information between distantly related organisms of the same generation. Genome sequencing not only provided further evidence complementing experimental evidence but also shed light onto the frequency and prominence of this concept. Especially the rapid spread of antimicrobial resistance genes is a prominent example for the impact that horizontal gene transfer can have for public health. Next generation sequencing brought means for quick and relatively cheap analysis of even complex metagenomic samples where horizontal gene transfer is bound to happen frequently. Methods to directly detect and characterise horizontal gene transfer from such sequencing data, however, are still lacking. We here provide a method to identify organisms potentially involved in horizontal gene transfer events to be used in downstream analysis that enables a characterisation of a horizontal gene transfer event in terms of impact and prevalence
Existence of long-time solutions to dynamic problems of viscoelasticity with rate-and-state friction
Get PDFWe establish existence of long-time solutions to a dynamic problem of bilateral contact between a rigid surface and a viscoelastic body, subject to rate-and-state friction. The term rate-and-state friction is used here to refer to a set of functions and equations satisfying conditions which rule out the slip law but do cover the ageing law, and thus at least one of the rate-and-state friction laws commonly used in the geosciences