The Flexiscope a Low Cost, Flexible, Convertible, and Modular Microscope with Automated Scanning and Micromanipulation, bioRxiv, 2018-10-13

AbstractWith technologies rapidly evolving, many research institutions are now opting to invest in costly, high-quality, specialised microscopes which are shared by many researchers. As a consequence, the user does not have the ability to adapt a microscope to their specific needs and limitations in experimental design are introduced. A flexible work-horse microscopy system is a valuable tool in any laboratory to meet the diverse needs of a research team and promote innovation in experimental design. We have developed the Flexiscope; a multi-functional, adaptable, efficient and high performance microscopyelectrophysiology system for everyday applications in a neurobiology laboratory. The core optical components are relatively constant in the three configurations described here; an upright configuration, an inverted configuration and an uprightelectrophysiology configuration. We have provided a comprehensive description of the Flexiscope. We show that this method is capable of oblique infrared illumination imaging, multi-channel fluorescent imaging, and automated 3D scanning of larger specimens. Image quality is conserved across the three configurations of the microscope, and conversion between configurations is possible quickly and easily, while the motion control system can be repurposed to allow sub-micron computer-controlled micromanipulation. The Flexiscope provides similar performance and usability to commercially available systems. However, as it can be easily reconfigured for multiple roles, it can remove the need to purchase multiple microscopes, giving significant cost savings. The modular re-configurable nature allows the user to customise the system to their specific needs and adaptupgrade the system as challenges arise.

biorxiv neuroscience 0-100-users 2018

A Multi-State Birth-Death model for Bayesian inference of lineage-specific birth and death rates, bioRxiv, 2018-10-11

AbstractHeterogeneous populations can lead to important differences in birth and death rates across a phylogeny Taking this heterogeneity into account is thus critical to obtain accurate estimates of the underlying population dynamics. We present a new multi-state birth-death model (MSBD) that can estimate lineage-specific birth and death rates. For species phylogenies, this corresponds to estimating lineage-dependent speciation and extinction rates. Contrary to existing models, we do not require a prior hypothesis on a trait driving the rate differences and we allow the same rates to be present in different parts of the phylogeny. Using simulated datasets, we show that the MSBD model can reliably infer the presence of multiple evolutionary regimes, their positions in the tree, and the birth and death rates associated with each. We also present a re-analysis of two empirical datasets and compare the results obtained by MSBD and by the existing software BAMM. The MSBD model is implemented as a package in the Bayesian inference software BEAST2, which allows joint inference of the phylogeny and the model parameters.Significance statementPhylogenetic trees can inform about the underlying speciation and extinction processes within a species clade. Many different factors, for instance environmental changes or morphological changes, can lead to differences in macroevolutionary dynamics within a clade. We present here a new multi-state birth-death (MSBD) model that can detect these differences and estimate both the position of changes in the tree and the associated macroevolutionary parameters. The MSBD model does not require a prior hypothesis on which trait is driving the changes in dynamics and is thus applicable to a wide range of datasets. It is implemented as an extension to the existing framework BEAST2.

biorxiv evolutionary-biology 0-100-users 2018

Bayesian Estimation of Species Divergence Times Using Correlated Quantitative Characters, bioRxiv, 2018-10-11

Discrete morphological data have been widely used to study species evolution, but the use of quantitative (or continuous) morphological characters is less common. Here, we implement a Bayesian method to estimate species divergence times using quantitative characters. Quantitative character evolution is modelled using Brownian diffusion with character correlation and character variation within populations. Through simulations, we demonstrate that ignoring the population variation (or population noise) and the correlation among characters leads to biased estimates of divergence times and rate, especially if the correlation and population noise are high. We apply our new method to the analysis of quantitative characters (cranium landmarks) and molecular data from carnivoran mammals. Our results show that time estimates are affected by whether the correlations and population noise are accounted for or ignored in the analysis. The estimates are also affected by the type of data analysed, with analyses of morphological characters only, molecular data only, or a combination of both; showing noticeable differences among the time estimates. Rate variation of morphological characters among the carnivoran species appears to be very high, with Bayesian model selection indicating that the independent-rates model fits the morphological data better than the autocorrelated-rates model. We suggest that using morphological continuous characters, together with molecular data, can bring a new perspective to the study of species evolution. Our new model is implemented in the MCMCtree computer program for Bayesian inference of divergence times.

biorxiv evolutionary-biology 0-100-users 2018

 

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