The Tidal Tails of 47 Tucanae

The Galactic globular cluster 47 Tucanae (47 Tuc) shows a rare increase in its velocity dispersion profile at large radii, indicative of energetic, yet bound, stars at large radii dominating the velocity dispersion and, potentially, of ongoing evaporation. Escaping stars will form tidal tails, as seen with several Galactic globular clusters, however, the tidal tails of 47 Tuc are yet to be uncovered. We model these tails of 47 Tuc using the most accurate input data available, with the specific aim of determining their locations, as well as the densities of the epicyclic overdensities within the tails. The overdensities from our models show an increase of 3-4% above the Galactic background and, therefore, should be easily detectable using matched filtering techniques. We find that the most influential parameter with regard to both the locations and densities of the epicyclic overdensities is the Heliocentric distance to the cluster. Hence, uncovering these tidal features observationally will contribute greatly to the ongoing problem of determining the distance to 47 Tuc, tightly constraining the distance of the cluster independent of other methods. Using our streakline method for determining the locations of the tidal tails and their overdensities, we show how, in principle, the shape and extent of the tidal tails of any Galactic globular cluster can be determined without resorting to computationally expensive N-body simulations.Comment: Original paper has 10 pages, 10 figures and 2 tables. Please note that this now includes an erratum. Erratum has 6 pages, 8 figures and 2 tables. Ignore the exclamation marks in Section 2 of the erratum, these are an artifact of the LaTeX class file used to produce the manuscrip

New methods for inferring the distribution of fitness effects for INDELs and SNPs

Small insertions and deletions (INDELs; ≤50bp) are the most common type of variability after SNPs. However, compared to SNPs, we know little about the distribution of fitness effects (DFE) of new INDEL mutations and how prevalent adaptive INDEL substitutions are. Studying INDELs has been difficult partly because identifying ancestral states at these sites is error-prone and misidentification can lead to severely biased estimates of the strength of selection. To solve these problems, we develop new maximum likelihood methods, which use polymorphism data to simultaneously estimate the DFE, the mutation rate, and the misidentification rate. These methods are applicable to both INDELs and SNPs. Simulations show that they can provide highly accurate results. We applied the methods to an INDEL polymorphism dataset in Drosophila melanogaster. We found that the DFE for polymorphic INDELs in protein-coding regions is bimodal, with the variants being either nearly neutral or strongly deleterious. Based on the DFE, we estimated that 71.5% - 83.7% of the INDEL substitutions that took place along the D. melanogaster lineage were fixed by positive selection, which is comparable to the prevalence of adaptive substitutions at non-synonymous sites. The new methods have been implemented in the software package anavar

Are sites with multiple single nucleotide variants in cancer genomes a consequence of drivers, hypermutable sites or sequencing errors?

Across independent cancer genomes it has been observed that some sites have been recurrently hit by single nucleotide variants (SNVs). Such recurrently hit sites might be either (i) drivers of cancer that are postively selected during oncogenesis, (ii) due to mutation rate variation, or (iii) due to sequencing and assembly errors. We have investigated the cause of recurrently hit sites in a dataset of >3 million SNVs from 507 complete cancer genome sequences. We find evidence that many sites have been hit significantly more often than one would expect by chance, even taking into account the effect of the adjacent nucleotides on the rate of mutation. We find that the density of these recurrently hit sites is higher in non-coding than coding DNA and hence conclude that most of them are unlikely to be drivers. We also find that most of them are found in parts of the genome that are not uniquely mappable and hence are likely to be due to mapping errors. In support of the error hypothesis, we find that recurently hit sites are not randomly distributed across sequences from different laboratories. We fit a model to the data in which the rate of mutation is constant across sites but the rate of error varies. This model suggests that ∼4% of all SNVs are errors in this dataset, but that the rate of error varies by thousands-of-fold between sites

Nonlinear bias correction for satellite data assimilation using Taylor series polynomials

Output from a high-resolution ensemble data assimilation system is used to assess the ability of an innovative nonlinear bias correction (BC) method that uses a Taylor series polynomial expansion of the observation-minus background departures to remove linear and nonlinear conditional biases from all-sky satellite infrared brightness temperatures. Univariate and multivariate experiments were performed in which the satellite zenith angle and variables sensitive to clouds and water vapor were used as the BC predictors. The results showed that even though the bias of the entire observation departure distribution is equal to zero regardless of the order of the Taylor series expansion, there are often large conditional biases that vary as a nonlinear function of the BC predictor. The linear 1st order term had the largest impact on the entire distribution as measured by reductions in variance; however, large conditional biases often remained in the distribution when plotted as a function of the predictor. These conditional biases were typically reduced to near zero when the nonlinear 2nd and 3rd order terms were used. The univariate results showed that variables sensitive to the cloud top height are effective BC predictors especially when higher order Taylor series terms are used. Comparison of the statistics for clear-sky and cloudy-sky observations revealed that nonlinear departures are more important for cloudy-sky observations as signified by the much larger impact of the 2nd and 3rd order terms on the conditional biases. Together, these results indicate that the nonlinear BC method is able to effectively remove the bias from all-sky infrared observation departures

Zebrafish type I collagen mutants faithfully recapitulate human type I collagenopathies

The type I collagenopathies are a group of heterogeneous connective tissue disorders, that are caused by mutations in the genes encoding type I collagen and include specific forms of osteogenesis imperfecta (OI) and the Ehlers-Danlos syndrome (EDS). These disorders present with a broad disease spectrum and large clinical variability of which the underlying genetic basis is still poorly understood. In this study, we systematically analyzed skeletal phenotypes in a large set of zebrafish, with diverse mutations in the genes encoding type I collagen, representing different genetic forms of human OI, and a zebrafish model resembling human EDS, which harbors a number of soft connective tissues defects, typical of EDS. Furthermore, we provide insight into how zebrafish and human type I collagen are compositionally and functionally related, which is relevant in the interpretation of human type I collagen-related disease models. Our studies reveal a high degree of intergenotype variability in phenotypic expressivity that closely correlates with associated OI severity. Furthermore, we demonstrate the potential for select mutations to give rise to phenotypic variability, mirroring the clinical variability associated with human disease pathology. Therefore, our work suggests the future potential for zebrafish to aid in identifying unknown genetic modifiers and mechanisms underlying the phenotypic variability in OI and related disorders. This will improve diagnostic strategies and enable the discovery of new targetable pathways for pharmacological intervention

Virus Replication as a Phenotypic Version of Polynucleotide Evolution

In this paper we revisit and adapt to viral evolution an approach based on the theory of branching process advanced by Demetrius, Schuster and Sigmund ("Polynucleotide evolution and branching processes", Bull. Math. Biol. 46 (1985) 239-262), in their study of polynucleotide evolution. By taking into account beneficial effects we obtain a non-trivial multivariate generalization of their single-type branching process model. Perturbative techniques allows us to obtain analytical asymptotic expressions for the main global parameters of the model which lead to the following rigorous results: (i) a new criterion for "no sure extinction", (ii) a generalization and proof, for this particular class of models, of the lethal mutagenesis criterion proposed by Bull, Sanju\'an and Wilke ("Theory of lethal mutagenesis for viruses", J. Virology 18 (2007) 2930-2939), (iii) a new proposal for the notion of relaxation time with a quantitative prescription for its evaluation, (iv) the quantitative description of the evolution of the expected values in in four distinct "stages": extinction threshold, lethal mutagenesis, stationary "equilibrium" and transient. Finally, based on these quantitative results we are able to draw some qualitative conclusions.Comment: 23 pages, 1 figure, 2 tables. arXiv admin note: substantial text overlap with arXiv:1110.336

Soil organic carbon stocks in estuarine and marine mangrove ecosystems are driven by nutrient colimitation of P and N

Mangroves play an important role in carbon sequestration, but soil organic carbon (SOC) stocks differ between marine and estuarine mangroves, suggesting differing processes and drivers of SOC accumulation. Here, we compared undegraded and degraded marine and estuarine mangroves in a regional approach across the Indonesian archipelago for their SOC stocks and evaluated possible drivers imposed by nutrient limitations along the land-to-sea gradients. SOC stocks in natural marine mangroves (271–572 Mg ha-1 m-1 were much higher than under estuarine mangroves (100–315 Mg ha-1 m-1 with a further decrease caused by degradation to 80–132 Mg ha-1 m-1. Soils differed in C/N ratio (marine: 29–64; estuarine: 9–28), δ15N (marine: 0.6 to 0.7‰; estuarine: 2.5 to 7.2‰), and plant-available P (marine: 2.3–6.3 mg kg-1; estuarine: 0.16–1.8 mg kg-1). We found N and P supply of sea-oriented mangroves primarily met by dominating symbiotic N2 fixation from air and P import from sea, while mangroves on the landward gradient increasingly covered their demand in N and P from allochthonous sources and SOM recycling. Pioneer plants favored by degradation further increased nutrient recycling from soil resulting in smaller SOC stocks in the topsoil. These processes explained the differences in SOC stocks along the land-to-sea gradient in each mangrove type as well as the SOC stock differences observed between estuarine and marine mangrove ecosystems. This first large-scale evaluation of drivers of SOC stocks under mangroves thus suggests a continuum in mangrove functioning across scales and ecotypes and additionally provides viable proxies for carbon stock estimations in PES or REDD schemes.BMBF/03F064

Large scale variation in the rate of germ-line de novo mutation, base composition, divergence and diversity in humans

It has long been suspected that the rate of mutation varies across the human genome at a large scale based on the divergence between humans and other species. However, it is now possible to directly investigate this question using the large number of de novo mutations (DNMs) that have been discovered in humans through the sequencing of trios. We investi- gate a number of questions pertaining to the distribution of mutations using more than 130,000 DNMs from three large datasets. We demonstrate that the amount and pattern of variation differs between datasets at the 1MB and 100KB scales probably as a consequence of differences in sequencing technology and processing. In particular, datasets show differ- ent patterns of correlation to genomic variables such as replication time. Never-the-less there are many commonalities between datasets, which likely represent true patterns. We show that there is variation in the mutation rate at the 100KB, 1MB and 10MB scale that can- not be explained by variation at smaller scales, however the level of this variation is modest at large scales–at the 1MB scale we infer that ~90% of regions have a mutation rate within 50% of the mean. Different types of mutation show similar levels of variation and appear to vary in concert which suggests the pattern of mutation is relatively constant across the genome. We demonstrate that variation in the mutation rate does not generate large-scale variation in GC-content, and hence that mutation bias does not maintain the isochore struc- ture of the human genome. We find that genomic features explain less than 40% of the explainable variance in the rate of DNM. As expected the rate of divergence between spe- cies is correlated to the rate of DNM. However, the correlations are weaker than expected if all the variation in divergence was due to variation in the mutation rate. We provide evidence that this is due the effect of biased gene conversion on the probability that a mutation will become fixed. In contrast to divergence, we find that most of the variation in diversity can be explained by variation in the mutation rate. Finally, we show that the correlation between divergence and DNM density declines as increasingly divergent species are considered

Determinants of the efficacy of natural selection on coding and noncoding variability in two passerine species

Population genetic theory predicts that selection should be more effective when the effective population size (Ne) is larger, and that the efficacy of selection should correlate positively with recombination rate. Here, we analyzed the genomes of ten great tits and ten zebra finches. Nucleotide diversity at 4-fold degenerate sites indicates that zebra finches have a 2.83-fold larger Ne. We obtained clear evidence that purifying selection is more effective in zebra finches. The proportion of substitutions at 0-fold degenerate sites fixed by positive selection (α) is high in both species (great tit 48%; zebra finch 64%) and is significantly higher in zebra finches. When α was estimated on GC-conservative changes (i.e., between A and T and between G and C), the estimates reduced in both species (great tit 22%; zebra finch 53%). A theoretical model presented herein suggests that failing to control for the effects of GC-biased gene conversion (gBGC) is potentially a contributor to the overestimation of α, and that this effect cannot be alleviated by first fitting a demographic model to neutral variants. We present the first estimates in birds for α in the untranslated regions, and found evidence for substantial adaptive changes. Finally, although purifying selection is stronger in high-recombination regions, we obtained mixed evidence for α increasing with recombination rate, especially after accounting for gBGC. These results highlight that it is important to consider the potential confounding effects of gBGC when quantifying selection and that our understanding of what determines the efficacy of selection is incomplete