Normalisation against circadian and age-related disturbances enables robust detection of gene expression changes in liver of aged mice

The expression of some genes is affected by age. To detect such age-related changes, their expression levels are related to constant marker genes. However, transcriptional noise increasing with advancing age renders difficult the identification of real age-related changes because it may affect the marker genes as well. Here, we report a selection procedure for genes appropriate to normalise the mouse liver transcriptome under various conditions including age. These genes were chosen from an initial set of 16 candidate genes defined based on a RNA-sequencing experiment and published literature. A subset of genes was selected based on rigorous statistical assessment of their variability using both RNA-sequencing and Nanostring hybridization experiments. The robustness of these marker genes was then verified by the analysis of 130 publicly available data sets using the mouse liver transcriptome. Altogether, a set of three genes, Atp5h, Gsk3β, and Sirt2 fulfilled our strict selection criteria in all assessments, while four more genes, Nono, Tprkb, Tspo, and Ttr passed all but one assessment and were included into the final set of marker genes to enhance robustness of normalisation against outliers. Using the geometric mean of expression of the genes to normalise Nanostring hybridization experiments we reliably identified age-related increases in the expression of Casein kinase 1δ and 1ϵ, and Sfpq, while the expression of the glucose transporter Glut2 decreased. The age- related changes were verified by real-time PCR and Western blot analysis. As conclusion, proper normalisation enhances the robustness of quantitative methods addressing age-related changes of a transcriptome

An approximate Markov model for the wright-fisher diffusion and its application to time series data

The joint and accurate inference of selection and demography from genetic data is considered a particularly challenging question in population genetics, since both process may lead to very similar patterns of genetic diversity. However, additional information for disentangling these effects may be obtained by observing changes in allele frequencies over multiple time points. Such data is common in experimental evolution studies, as well as in the comparison of ancient and contemporary samples. Leveraging this information, however, has been computationally challenging, particularly when considering multi-locus data sets. To overcome these issues, we introduce a novel, discrete approximation for diffusion processes, termed mean transition time approximation, which preserves the long-term behavior of the underlying continuous diffusion process. We then derive this approximation for the particular case of inferring selection and demography from time series data under the classic Wright- Fisher model and demonstrate that our approximation is well suited to describe allele trajectories through time, even when only a few states are used. We then develop a Bayesian inference approach to jointly infer the population size and locus-specific selection coefficients with high accuracy, and further extend this model to also infer the rates of sequencing errors and mutations. We finally apply our approach to recent experimental data on the evolution of drug resistance in Influenza virus, identifying likely targets of selection and finding evidence for much larger viral population sizes than previously reported

Atlas: analysis tools for low-depth and ancient samples

Summary: Post-mortem damage (PMD) obstructs the proper analysis of ancient DNA samples and can currently only be addressed by removing or down-weighting potentially damaged data. Here we present ATLAS, a suite of methods to accurately genotype and estimate genetic diversity from ancient samples, while accounting for PMD. It works directly from raw BAM files and enables the building of complete and customized pipelines for the analysis of ancient and other low-depth samples in a very user-friendly way. Based on simulations we show that, in the presence of PMD, a dedicated pipeline of ATLAS calls genotypes more accurately than the state-of-the-art pipeline of GATK combined with mapDamage 2.0. Availability: ATLAS is an open- source C++ program freely available at https://bitbucket.org/phaentu/atlas

Sino-Himalayan mountains act as cradles of diversity and immigration centres in the diversification of parrotbills (Paradoxornithidae)

Aim: Montane regions like the Sino-Himalayas constitute global diversity hotspots. Various mechanisms such as in situ adaptive divergence, speciation following immigration or allopatric diversification in complex landscapes have been proposed to account for the exceptional diversity found in a particular clade in a montane setting. We investigated macroevolutionary patterns to test these different hypotheses in the continental radiation of a Sino-Himalayan bird group, the parrotbills (Paradoxornithidae).Location: Sino-Himalayan region, Indo-Burma.Methods: We used phylogenetic comparative methods based on a multilocus, time-calibrated phylogeny to reconstruct patterns of lineage diversification, biogeographical history, morphological evolution as well as of climate niche history using ecological niche modelling.Results: The radiation of parrotbills started c. 12 Ma, diversifying at an apparent constant rate over time. The biogeographical history appears to be complex, within-region speciation in mountains was restricted to China. Size evolution was concentrated in the early phase of parrotbill radiation, whereas morphological shape evolution did not differ from Brownian motion. We found no indication for niche conservatism, with climate niche evolution occurring throughout the radiation of parrotbills.Conclusions: Parrotbills diversified within a time span of increased regional orogenesis and associated strong climate change. While the south-west and central Chinese mountains were revealed to be a species pump, with in situ allopatric diversification triggered by complex topography and high habitat turnover, the diversity in the Himalayas was chiefly the result of immigration. Evidence for continuous ecological specialization and for the absence of climate niche conservatism could be interpreted as the consequence of ongoing climate- and habitat-induced ecological opportunities. The radiation of parrotbills demonstrates the influence of multiple drivers of diversification in a single group due to the dynamic geological and palaeoclimatic history of the Sino-Himalayan region and illustrates the complex nature of continental radiations

Inference of evolutionary jumps in large phylogenies using Lévy processes

Although it is now widely accepted that the rate of phenotypic evolution may not necessarily be constant across large phylogenies, the frequency and phylogenetic position of periods of rapid evolution remain unclear. In his highly influential view of evolution, G. G. Simpson supposed that such evolutionary jumps occur when organisms transition into so-called new adaptive zones, for instance after dispersal into a new geographic area, after rapid climatic changes, or following the appearance of an evolutionary novelty. Only recently, large, accurate and well calibrated phylogenies have become available that allow testing this hypothesis directly, yet inferring evolutionary jumps remains computationally very challenging. Here, we develop a computationally highly efficient algorithm to accurately infer the rate and strength of evolutionary jumps as well as their phylogenetic location. Following previous work we model evolutionary jumps as a compound process, but introduce a novel approach to sample jump configurations that does not require matrix inversions and thus naturally scales to large trees. We then make use of this development to infer evolutionary jumps in Anolis lizards and Loriinii parrots where we find strong signal for such jumps at the basis of clades that transitioned into new adaptive zones, just as postulated by Simpson’s hypothesis

Trophic niche shifts and phenotypic trait evolution are largely decoupled in Australasian parrots

Background: Trophic shifts from one dietary niche to another have played major roles in reshaping the evolutionary trajectories of a wide range of vertebrate groups, yet their consequences for morphological disparity and species diversity differ among groups. Methods: Here, we use phylogenetic comparative methods to examine whether the evolution of nectarivory and other trophic shifts have driven predictable evolutionary pathways in Australasian psittaculid parrots in terms of ecological traits such as body size, beak shape, and dispersal capacity. Results: We found no evidence for an ‘early-burst’ scenario of lineage or morphological diversification. The bestfitting models indicate that trait evolution in this group is characterized by abrupt phenotypic shifts (evolutionary jumps), with no sign of multiple phenotypic optima correlating with different trophic strategies. Thus, our results point to the existence of weak directional selection and suggest that lineages may be evolving randomly or slowly toward adaptive peaks they have not yet reached. Conclusions: This study adds to a growing body of evidence indicating that the relationship between avian morphology and feeding ecology may be more complex than usually assumed and highlights the importance of adding more flexible models to the macroevolutionary toolbox.info:eu-repo/semantics/publishedVersio

Virtual reality-assisted cognitive behavioral therapy for patients with alcohol use disorder: a randomized feasibility study

IntroductionCognitive behavioral therapy (CBT) is an evidence-based treatment for alcohol use disorder (AUD). Exposure to high-risk situations in virtual reality (VR) has been suggested to have a potential therapeutical benefit, but no previous study has combined VR and CBT for AUD. We aimed to investigate the feasibility of using VR-simulated high-risk environments in CBT-based treatment of AUD.MethodsWe randomized ten treatment-seeking AUD-diagnosed individuals to three sessions of conventional CBT or VR-assisted CBT performed at two outpatient clinics in Denmark. In each session, patients randomized to VR-CBT were exposed to VR-simulations from a restaurant to induce authentic thoughts, emotions, physiological reactions, and craving for CBT purposes. The primary outcome measure was feasibility: Drop-out rate, psychological reactions, and simulator sickness. Secondary outcomes were assessment of preliminary short-term changes in alcohol consumption and craving from baseline to one-week and one-month follow-up. In addition, the study was conducted for training in operationalization of VR equipment, treatment manuals, and research questionnaires.ResultsThe majority of patients completed all study visits (90%). VR induced authentic high-risk related thoughts, emotions, and physiological reactions that were considered relevant for CBT by patients and therapists. Four of five patients randomized to VR-CBT experienced cravings during VR simulations, and most of these patients (3/5) experienced mild simulator sickness during VR exposure. The preliminary data showed that patients receiving VR-CBT had more reduction in alcohol consumption than patients receiving conventional CBT at one week- (median 94% vs. 72%) and one-month follow-up (median 98% vs. 55%). Similar results were found regarding changes in cravings.ConclusionWe demonstrated VR-CBT to be a feasible intervention for patients with AUD which supports continued investigations in a larger randomized clinical trial evaluating the efficacy of VR-CBT.Clinical trial registrationhttps://www.clinicaltrials.gov/study/NCT04990765?cond=addiction%20CRAVR&rank=2, identifier NCT05042180