Search

This paper presents data on the geological position, geochemical features, main mineral composition (micas, feldspars), and melt and fluid inclusions in quartz from Aba high-silica leucocratic granitoids in the western part of the Talitsa batholith, Russian Altai. According to these new geochemical data, the granitoids are classified as S-type, meaning they are formed via the partial melting of metasedimentary source rocks. Geological data and oxygen isotope composition analysis indicate that major-phase granitoid magma evolution took place at the level of intrusion formation, whereas the parent melt of late-phase leucogranite evolved in a deeper chamber. The geochemical features (HFSE and REE, and REE spectra) of the granitoids indicate significantly higher differentiation in the late leucocratic phase. The presence of coexisting syngenetic melt and fluid inclusions shows that leucogranite magma was already saturated with volatiles in the early crystallization stages. Based on the new data presented in this work, the Aba rock formation is associated with the volatile saturation of magmatic melts, the exsolution of a fluid phase, and magma degassing.

—The Kalguty Mo–W ore-magmatic system (OMS) is a granite batholith (S = 70 km2, V = 12,800 km3 at the recent denudation level, according to geological and geophysical data). This batholith is cut by the East Kalguty belt of rare-metal ongonite–elvan dikes spatially and temporally associated with the East Kalguty quartz-vein–greisen Mo–W deposit. Geological and petrogenetic studies along with published and our new results of geochronological (U/Pb zircon, Re/Os molybdenite, and 40Ar/39Ar biotite and muscovite) dating made it possible to reconstruct the thermochronological history of the Kalguty OMS. Five stages have been recognized: I (215 ± 1 Ma)—formation of granites of major intrusive phase and of Mo-rich mineralization, which is an orebody called the Molybdenum stock; II (206 ± 1 Ma)—formation of leucogranite and intragranitic-pegmatite stocks in the granites of major intrusive phase; III (202 ± 1 Ma)—formation of most of ongonite–elvan dikes composing a dike belt; IV (195 ± 1 Ma)—formation of long ultrarare-metal ongonite–elvan dikes in the central part of the dike belt, which is spatially associated with the W-rich veins of the deposit; and V (181 ± 1 Ma)—formation of thin ongonite–elvan dikes on the periphery of the dike belt. The recognized age stages of the Kalguty Mo–W ore-magmatic system were mathematically tested based on the model of crystallization differentiation and the dynamics of heat and mass transfer in the magma chamber corresponding to the Kalguty granite batholith. The results obtained show that the formation of a granite batholith (215 ± 1 Ma) and a later ongonite–elvan dike complex with Mo–W-rich mineralization (195 ± 1 Ma) can be explained only by a two-level ore-magmatic system with the “upper” granite batholith at a depth of 5–15 km and the “lower” granite chamber at a depth of 20–31 km. The total duration of ore-magmatic processes is 20 Myr (ore production stage) or 30 Myr, if we take into account occasional elvan dikes with poor quartz–fluorite–barite–ferberite mineralization (181 ± 1 Ma) on the periphery of the Kalguty deposit.

Variants within the non-coding genome are frequently associated with phenotypes in genome-wide association studies. These non-coding regions may be involved in the regulation of gene expression, encode functional non-coding RNAs, or influence splicing and other cellular functions. We have curated a list of characterized non-coding human genome variants based on the published evidence that indicates phenotypic consequences of the variation. In order to minimize annotation errors, two curators have independently verified the supporting evidence for pathogenicity of each non-coding variant in the published literature. The database consists of 721 non-coding variants linked to the published literature describing the evidence of functional consequences. We have also sampled 7228 covariate-matched benign controls, that have a population frequency of over 5%, from the single nucleotide polymorphism database (dbSNP151) database. These were sampled controlling for potential confounding factors such as linkage with pathogenic variants, annotation type (untranslated region, intron, intergenic, etc.) and variant type (substitution or indel). The dataset presented here represents a curated repository, with a potential use for the training or evaluation of algorithms used in the prediction of non-coding variant functionality.Database URL: https://github.com/Gardner-BinfLab/ncVarDB.

Measuring the pace at which speciation and extinction occur is fundamental to understanding the origin and evolution of biodiversity. Both the fossil record and molecular phylogenies of living species can provide independent estimates of speciation and extinction rates, but often produce strikingly divergent results. Despite its implications, the theoretical reasons for this discrepancy remain unknown. Here, we reveal a conceptual and methodological basis able to reconcile palaeontological and molecular evidence: discrepancies are driven by different implicit assumptions about the processes of speciation and species evolution in palaeontological and neontological analyses. We present the “birth-death chronospecies” model that clarifies the definition of speciation and extinction processes allowing for a coherent joint analysis of fossil and phylogenetic data. Using simulations and empirical analyses we demonstrate not only that this model explains much of the apparent incongruence between fossils and phylogenies, but that differences in rate estimates are actually informative about the prevalence of different speciation modes., Nature Communications, 9, ISSN:2041-1723

Highlights • Formulation of stochastic model giving rise to phylogenetic trees with stratigraphic ranges. • Accounting for different speciation modes within a phylogeny. • Derivation of probability of phylogenetic tree with stratigraphic ranges given macroevolutionary parameters. • Outline of applications within a Bayesian setting to macroevolution and epidemiology., A birth-death-sampling model gives rise to phylogenetic trees with samples from the past and the present. Interpreting “birth” as branching speciation, “death” as extinction, and “sampling” as fossil preservation and recovery, this model – also referred to as the fossilized birth-death (FBD) model – gives rise to phylogenetic trees on extant and fossil samples. The model has been mathematically analyzed and successfully applied to a range of datasets on different taxonomic levels, such as penguins, plants, and insects. However, the current mathematical treatment of this model does not allow for a group of temporally distinct fossil specimens to be assigned to the same species. In this paper, we provide a general mathematical FBD modeling framework that explicitly takes “stratigraphic ranges” into account, with a stratigraphic range being defined as the lineage interval associated with a single species, ranging through time from the first to the last fossil appearance of the species. To assign a sequence of fossil samples in the phylogenetic tree to the same species, i.e., to specify a stratigraphic range, we need to define the mode of speciation. We provide expressions to account for three common speciation modes: budding (or asymmetric) speciation, bifurcating (or symmetric) speciation, and anagenetic speciation. Our equations allow for flexible joint Bayesian analysis of paleontological and neontological data. Furthermore, our framework is directly applicable to epidemiology, where a stratigraphic range is the observed duration of infection of a single patient, “birth” via budding is transmission, “death” is recovery, and “sampling” is sequencing the pathogen of a patient. Thus, we present a model that allows for incorporation of multiple observations through time from a single patient.

New HIV diagnoses among men having sex with men (MSM) have not decreased appreciably in most countries, even though care and prevention services have been scaled up substantially in the past 20 years. To maximize the impact of prevention strategies, it is crucial to quantify the sources of transmission at the population level. We used viral sequence and clinical patient data from one of Europe's nationwide cohort studies to estimate probable sources of transmission for 617 recently infected MSM. Seventy-one percent of transmissions were from undiagnosed men, 6% from men who had initiated antiretroviral therapy (ART), 1% from men with no contact to care for at least 18 months, and 43% from those in their first year of infection. The lack of substantial reductions in incidence among Dutch MSM is not a result of ineffective ART provision or inadequate retention in care. In counterfactual modeling scenarios, 19% of these past cases could have been averted with current annual testing coverage and immediate ART to those testing positive. Sixty-six percent of these cases could have been averted with available antiretrovirals (immediate ART provided to all MSM testing positive, and preexposure antiretroviral prophylaxis taken by half of all who test negative for HIV), but only if half of all men at risk of transmission had tested annually. With increasing sequence coverage, molecular epidemiological analyses can be a key tool to direct HIV prevention strategies to the predominant sources of infection, and help send HIV epidemics among MSM into a decisive decline.

Phylogenetic analyses which include fossils or molecular sequences that are sampled through time require models that allow one sample to be a direct ancestor of another sample. As previously available phylogenetic inference tools assume that all samples are tips, they do not allow for this possibility. We have developed and implemented a Bayesian Markov Chain Monte Carlo (MCMC) algorithm to infer what we call sampled ancestor trees, that is, trees in which sampled individuals can be direct ancestors of other sampled individuals. We use a family of birth-death models where individuals may remain in the tree process after sampling, in particular we extend the birth-death skyline model [Stadler et al., 2013] to sampled ancestor trees. This method allows the detection of sampled ancestors as well as estimation of the probability that an individual will be removed from the process when it is sampled. We show that even if sampled ancestors are not of specific interest in an analysis, failing to account for them leads to significant bias in parameter estimates. We also show that sampled ancestor birth-death models where every sample comes from a different time point are non-identifiable and thus require one parameter to be known in order to infer other parameters. We apply our phylogenetic inference accounting for sampled ancestors to epidemiological data, where the possibility of sampled ancestors enables us to identify individuals that infected other individuals after being sampled and to infer fundamental epidemiological parameters. We also apply the method to infer divergence times and diversification rates when fossils are included along with extant species samples, so that fossilisation events are modelled as a part of the tree branching process. Such modelling has many advantages as argued in the literature. The sampler is available as an open-source BEAST2 package (https://github.com/CompEvol/sampled-ancestors)., PLoS Computational Biology, 10 (12), ISSN:1553-734X, ISSN:1553-7358