Bayesian inference of evolutionary histories under time-dependent substitution rates

Many factors complicate the estimation of time scales for phylogenetic histories, requiring increasingly complex evolutionary models and inference procedures. The widespread application of molecular clock dating has led to the insight that evolutionary rate estimates may vary with the time frame of measurement. This is particularly well established for rapidly evolving viruses that can accumulate sequence divergence over years or even months. However, this rapid evolution stands at odds with a relatively high degree of conservation of viruses or endogenous virus elements over much longer time scales. Building on recent insights into time-dependent evolutionary rates, we develop a formal and flexible Bayesian statistical inference approach that accommodates rate variation through time. We evaluate the novel molecular clock model on a foamy virus cospeciation history and a lentivirus evolutionary history and compare the performance to other molecular clock models. For both virus examples, we estimate a similarly strong time-dependent effect that implies rates varying over four orders of magnitude. The application of an analogous codon substitution model does not implicate long-term purifying selection as the cause of this effect. However, selection does appear to affect divergence time estimates for the less deep evolutionary history of the Ebolavirus genus. Finally, we explore the application of our approach on woolly mammoth ancient DNA data, which shows a much weaker, but still important, time-dependent rate effect that has a noticeable impact on node age estimates. Future developments aimed at incorporating more complex evolutionary processes will further add to the broad applicability of our approach.status: publishe

Development of a generic and open source Incidence-Prevalence-Mortality model for the assessment of chronic disease epidemiology

&lt;p&gt;It is often a problem for researchers when the epidemiology of a disease is unreliable or altogether lacking. This thesis was created in order to make an R package called DisModR that accounts for this problem. In particular, the package was made for applications on chronic diseases.&lt;/p&gt; &lt;p&gt;The compartmental model used was taken from previous iterations of a software called DisMod. This model gives the logical relationship between di erent epidemiological parameters of a disease. In particular, inputs on disease incidence, remission, and case fatality were needed to determine the disease-speci c mortality and prevalence. However, an iterative optimization procedure called the Nelder-Mead method was employed in order to accept more inputs. This was done through the fminsearch() function of the neldermead package. Likewise, in order to make the values of the input variables vary continuously as a function of age, cubic smoothing splines were incorporated in DisModR.&lt;/p&gt; &lt;p&gt;The DisMod() function in DisModR allows the user to compute the di erent epidemiological parameters of a disease. It accepts data on three of the following ve inputs: incidence, remission, case fatality, mortality, and prevalence. Likewise, it allows users to manipulate options on the cubic smoothing splines and the tolerance limits of the optimization procedure. Using the breast cancer data set of the Netherlands, the properties of the DisMod() function was shown. Additional outputs on case fatality, prevalence, and relative risk mortality were produced using only inputs on incidence, remission, and mortality. In addition, the function also produced various objects that contained lists of&lt;br&gt; input and output values, as well as their corresponding graphs.&lt;/p&gt; &lt;p&gt;There are several uses to DisModR. The first, which is perhaps the most obvious, is that it provides values for epidemiological parameters, which are otherwise unavailable such as mortality and prevalence of particular diseases. The second is that it allows users to compare its results with existing data. This is to check if the present data is consistent with the logical relationship of the other input variables. The third gives researchers the opportunity to work in the R environment, which is a unique feature of this package compared to other versions of DisMod. Furthermore, users are advised that they should not only rely on the R package alone, but they must combine the results with expert&lt;br&gt; knowledge of the epidemiology of the disease.&lt;/p&gt;</p

Quantifying the dynamics of evolutionary rates through time

The availability of evolutionary rate estimates in recent years led to the observation that they may depend on the time-scale on which they are measured. Specifically, RNA virus evolutionary rates are frequently estimated to be low towards the past and high towards the present. This time-dependent rate phenomenon (TDRP) has important implications for evolutionary studies as it could severely bias divergence time estimates. While recent studies are providing insights into the relationship between viral evolutionary rate and time, formal probabilistic models to draw inference under TDRP scenarios remain lacking. Here, we adopt epoch-modelling to develop a Bayesian model of discrete rate changes through time in an unknown evolutionary history and combine this with a log-linear parameterization of rates as a function of times in the past. We provide an implementation for nucleotide substitution rates as well as for nonsynonymous rates change in a codon substitution model. Using a foamy virus dataset for which internal node calibrations can be applied based on host-virus co-divergence, we estimate a significant decline in evolutionary rates as a function of time into the past for nucleotide substitutions as well as for non-synonymous substitutions in a codon model. We also estimate a deep evolutionary history for primate Lentiviruses by combining an HIV-1 group M node calibration and a biogeographic calibration for viruses in drill monkeys in the TDRP model. Our analyses lead to the conclusion that studies of evolutionary timescales require a reconsideration of substitution rates, in either codon and nucleotide substitution model, as a dynamic feature of molecular evolution.status: Published onlin

Bayesian Inference of Evolutionary Histories under Time-Dependent Substitution Rates.

Many factors complicate the estimation of time scales for phylogenetic histories, requiring increasingly complex evolutionary models and inference procedures. The widespread application of molecular clock dating has led to the insight that evolutionary rate estimates may vary with the time frame of measurement. This is particularly well established for rapidly evolving viruses that can accumulate sequence divergence over years or even months. However, this rapid evolution stands at odds with a relatively high degree of conservation of viruses or endogenous virus elements over much longer time scales. Building on recent insights into time-dependent evolutionary rates, we develop a formal and flexible Bayesian statistical inference approach that accommodates rate variation through time. We evaluate the novel molecular clock model on a foamy virus cospeciation history and a lentivirus evolutionary history and compare the performance to other molecular clock models. For both virus examples, we estimate a similarly strong time-dependent effect that implies rates varying over four orders of magnitude. The application of an analogous codon substitution model does not implicate long-term purifying selection as the cause of this effect. However, selection does appear to affect divergence time estimates for the less deep evolutionary history of the Ebolavirus genus. Finally, we explore the application of our approach on woolly mammoth ancient DNA data, which shows a much weaker, but still important, time-dependent rate effect that has a noticeable impact on node age estimates. Future developments aimed at incorporating more complex evolutionary processes will further add to the broad applicability of our approach

Journeys through aroma space: a novel approach towards the selection of aroma-enriched strawberry cultivars in breeding programmes

Consumers often criticize the sensory quality of modern strawberry cultivars. Therefore, a new and fast workflow for cultivar selection was developed to aid in the development of cultivars with enhanced aroma. This workflow consists of Headspace (HS) solid-phase microextraction (SPME) fast GC-MS used for high-throughput aroma analysis of parents and hybrids. For data analysis, a chemometrical workflow was created. With a principal component analysis (PCA), the aroma similarity between the samples and a target aroma was evaluated. In order to know how the aroma profiles of the parents and hybrids are situated towards this target aroma, the Euclidean distances were calculated. These were then further used for a partial least-squares (PLS) regression analysis to determine which aroma compounds are responsible for the observed distance to the target. By using this new approach, hybrids showing aroma profiles similar to the target aroma can be identified as most suitable candidates for further breeding cycles. Besides being time-saving, the suggested workflow introduces aroma analysis as an integral part of breeding programmes. It prevents losing the coherence within the aroma profile and subsequently the loss of important information. © 2013 Blackwell Verlag GmbH.status: publishe

Safety Study on Ketoprofen in Pigs: Evaluating the Effects of Different Dosing and Treatment Scheme on Hematological, Hepatic, and Renal Parameters

A safety study on ketoprofen 10% was carried out on pigs using a different dosing and treatment scheme. Forty healthy crossbreed pigs with similar age, weight, and body condition score were distributed into five treatment groups. The pigs were intramuscularly injected once with different doses of ketoprofen: 3 mg/kg (group 1X), 6 mg/kg (group 2X), 9 mg/kg (group 3X). In addition, the 3 mg/kg dosis was administered on three consecutive days (group 1X ext.). Intramuscular injections of saline solution were used in control group (CTL). The pigs were clinically examined throughout the trial and blood samples were taken for hematological and biochemical evaluation on days −4 (before treatment), +3, +7, and +14 (the end of the trial). Any unusual behaviour or clinical signs were reported as potential toxic effects of ketoprofen. Serum measurements showed that none of the ketoprofen doses produced changes in renal or hepatic biochemical parameters, liver enzymes, or total bilirubin. Likewise, hematological assessment indicated no altered parameters or hematocrit percentage in the study groups. These results demonstrate that ketoprofen has no adverse effects in pigs when the doses and scheme evaluated in this study are applied