Biomedical subjects

Karin S Dorman

Publications and source records attributed to Karin S Dorman.

8 recordsLinked to original sources

PubMed2006

Phylogenetic mapping of recombination hotspots in human immunodeficiency virus via spatially smoothed change-point processes.

We present a Bayesian framework for inferring spatial preferences of recombination from multiple putative recombinant nucleotide sequences. Phylogenetic recombination detection has been an active area of research for the last 15 years. However, only recently attempts to summarize information from several instances of recombination have been made. We propose a hierarchical model that allows for simultaneous inference of recombination breakpoint locations and spatial variation in recombination frequency. The dual multiple change-point model for phylogenetic recombination detection resides at the lowest level of our hierarchy under the umbrella of a common prior on breakpoint locations. The hierarchical prior allows for information about spatial preferences of recombination to be shared among individual data sets. To overcome the sparseness of breakpoint data, dictated by the modest number of available recombinant sequences, we a priori impose a biologically relevant correlation structure on recombination location log odds via a Gaussian Markov random field hyperprior. To examine the capabilities of our model to recover spatial variation in recombination frequency, we simulate recombination from a predefined distribution of breakpoint locations. We then proceed with the analysis of 42 human immunodeficiency virus (HIV) intersubtype gag recombinants and identify a putative recombination hotspot.

Animals↗

PubMed2006

cBrother: relaxing parental tree assumptions for Bayesian recombination detection.

UNLABELLED: Bayesian multiple change-point models accurately detect recombination in molecular sequence data. Previous Java-based implementations assume a fixed topology for the representative parental data. cBrother is a novel C language implementation that capitalizes on reduced computational time to relax the fixed tree assumption. We show that cBrother is 19 times faster than its predecessor and the fixed tree assumption can influence estimates of recombination in a medically-relevant dataset. AVAILABILITY: cBrother can be freely downloaded from http://www.biomath.org/dormanks/ and can be compiled on Linux, Macintosh and Windows operating systems. Online documentation and a tutorial are also available at the site.

Algorithms↗

PubMed2005

Dual multiple change-point model leads to more accurate recombination detection.

MOTIVATION: We introduce a dual multiple change-point (MCP) model for recombination detection among aligned nucleotide sequences. The dual MCP model is an extension of the model introduced previously by Suchard and co-workers. In the original single MCP model, one change-point process is used to model spatial phylogenetic variation. Here, we show that using two change-point processes, one for spatial variation of tree topologies and the other for spatial variation of substitution process parameters, increases recombination detection accuracy. Statistical analysis is done in a Bayesian framework using reversible jump Markov chain Monte Carlo sampling to approximate the joint posterior distribution of all model parameters. RESULTS: We use primate mitochondrial DNA data with simulated recombination break-points at specific locations to compare the two models. We also analyze two real HIV sequences to identify recombination break-points using the dual MCP model.

Algorithms↗

PubMed2003

Subpopulations of equine infectious anemia virus Rev coexist in vivo and differ in phenotype.

Lentiviruses exist in vivo as a population of related, nonidentical genotypes, commonly referred to as quasispecies. The quasispecies structure is characteristic of complex adaptive systems and contributes to the high rate of evolution in lentiviruses that confounds efforts to develop effective vaccines and antiviral therapies. Here, we describe analyses of genetic data from longitudinal studies of genetic variation in a lentivirus regulatory protein, Rev, over the course of disease in ponies experimentally infected with equine infectious anemia virus. As observed with other lentivirus data, the Rev variants exhibited a quasispecies character. Phylogenetic and partition analyses suggested that the Rev quasispecies comprised two distinct subpopulations that coexisted during infection. One subpopulation appeared to accumulate changes in a linear, time-dependent manner, while the other evolved radially from a common variant. Over time, the two subpopulations cycled in predominance coincident with changes in the disease state, suggesting that the two groups differed in selective advantage. Transient expression assays indicated the two populations differed significantly in Rev nuclear export activity. Chimeric proviral clones containing Rev genotypes representative of each population differed in rate and overall level of virus replication in vitro. The coexistence of genetically distinct viral subpopulations that differ in phenotype provides great adaptability to environmental changes within the infected host. A quasispecies model with multiple subpopulations may provide additional insight into the nature of lentivirus reservoirs and the evolution of antigenic and drug-resistant variants.

Amino Acid Sequence↗

PubMed2003

Are you my mother? Bayesian phylogenetic inference of recombination among putative parental strains.

Reconstructing evolutionary relationships using Bayesian inference has become increasingly popular due to the ability of Bayesian inference to handle complex models of evolution. In this review we concentrate on inference of recombination events between strains of viruses when these events are sporadic, ie rare relative to point mutations. Bayesian inference is especially attractive in the detection of recombination events because it allows for simultaneous inferences about the presence, number and location of crossover points and the identification of parental sequences. Current frequentist recombination identification falls into a sequential testing trap. The most likely parental sequences and crossover points are identified using the data and then the certainty of recombination is assessed conditional on this identification. After briefly outlining basic phylogenetic models, Bayesian inference and Markov chain Monte Carlo (MCMC) computation, we summarise three different approaches to recombination detection and discuss current challenges in applying Bayesian phylogenetic inference of recombination.

Algorithms↗

PubMed2002

Bootstrap confidence levels for HIV-1 recombination.

Recombination has been invoked to explain the disparate evolutionary relationships observed for different genes or sequence segments of a single HIV-1 genome. We present a new method of assessing confidence in HIV-1 recombination as an alternative to the segment-by-segment nonparametric bootstrap commonly applied to confirm HIV-1 recombinant data. Our new method uses the bias-corrected accelerated percentile interval (BCa) bootstrap method as applied to the "problem of regions" (Efron and Tibshirani 1998). It is an extension of the BCa method used in the inference of evolutionary relationships (Efron et al. 1996). This method has two advantages over the traditional bootstrap procedure: (1) it gives a single overall confidence measure rather than segment-by-segment results, and (2) it is more accurate. We test our method on 61 sequences, including 16 with ambiguous recombinant status.

Base Sequence↗

PubMed2002

Oh brother, where art thou? A Bayes factor test for recombination with uncertain heritage.

Current methods to identify recombination between subtypes of human immunodeficiency virus 1 (HIV-1) fall into a sequential testing trap, in which significance is assessed conditional on parental representative sequences and crossover points (COPs) that maximize the same test statistic. We overcame this shortfall by testing for recombination while inferring parental heritage and COPs using an extended Bayesian multiple change-point model. The model assumes that aligned molecular sequence data consist of an unknown number of contiguous segments that may support alternative topologies or varying evolutionary pressures. We allowed for heterogeneity in the substitution process and specifically tested for intersubtype recombination using Bayes factors. We also developed a new class of priors to assess significance across a wide range of support for recombination in the data. We applied our method to three putative gag gene recombinants. HIV-1 isolate RW024 decisively supported recombination with an inferred parental heritage of AD and a COP 95% Bayesian credible interval of (1,152, 1,178) using the HXB2 numbering scheme. HIV-1 isolate VI557 barely supported recombination. HIV-1 isolate RF decisively rejected recombination as expected, given that the sequence is commonly used as a reference sequence for subtype B. We employed scaled regeneration quantile plots to assess convergence and found this approach convenient to use even for our variable dimensional model parameter space.

Algorithms↗

PubMedDate not supplied

Quantitative exposure assessment for confinement of maize biogenic systems.

The development of transgenic crops as production platforms for biogenic agents will largely depend on the success of efforts to confine the genes and their expressed proteins in field environments. We have used quantitative exposure assessment to evaluate how management practices affect materials escape due to outcrossing by pollen flow or grain loss during harvest operations. Specifically, we study the use of maize to produce biogenic agents within field-confined systems. Decision trees representing simplified schemes of fully conforming (designed to comply with current regulatory standards for field confined trials), partially conforming, and non-conforming management practices were developed. Exemplifying assumptions and published data for conformance and material fate probabilities were used in Monte Carlo simulations to forecast materials escape by pollen outcrossing and harvest operations from a 1 ha source field. Deterministic analyses showed fully conforming confinement management restricted materials loss to low levels (for this example, outcrossing produced <1 in 10(6) kernels in receptor fields). The corresponding high-end (90th percentile) probabilistic result was 16- and 4333-fold higher (relative to deterministic outcrossing = 1) for outcrossing and harvest loss, respectively. For partially conforming practice, high-end outcrossing ranged from 100- to >15000-fold over the base result in receptor fields, and harvest loss was >10000-fold over the base result. For non-conforming practice, high-end outcrossing produced >15000-fold greater kernels in receptor fields and high-end harvest loss was at least 19000-fold greater. Deterministic estimates of off-field loss by machine transfer are as much as 30000-fold higher for non-conforming operations relative to the base case of pollen outcrossing. Better knowledge of failure frequencies for confinement management practices, improved physical models of materials flows, refined analysis of confinement loss probabilities using quantitative tools, and decision analysis to improve and audit management system performance are all needed to extend understanding of confinement integrity beyond the exemplifying case used here.

Agriculture↗