Relationships between estimated autozygosity and complex traits in the UK Biobank

<div><p>Inbreeding increases the risk of certain Mendelian disorders in humans but may also reduce fitness through its effects on complex traits and diseases. Such inbreeding depression is thought to occur due to increased homozygosity at causal variants that are recessive with respect to fitness. Until recently it has been difficult to amass large enough sample sizes to investigate the effects of inbreeding depression on complex traits using genome-wide single nucleotide polymorphism (SNP) data in population-based samples. Further, it is difficult to infer causation in analyses that relate degree of inbreeding to complex traits because confounding variables (e.g., education) may influence both the likelihood for parents to outbreed and offspring trait values. The present study used runs of homozygosity in genome-wide SNP data in up to 400,000 individuals in the UK Biobank to estimate the proportion of the autosome that exists in autozygous tracts—stretches of the genome which are identical due to a shared common ancestor. After multiple testing corrections and controlling for possible sociodemographic confounders, we found significant relationships in the predicted direction between estimated autozygosity and three of the 26 traits we investigated: age at first sexual intercourse, fluid intelligence, and forced expiratory volume in 1 second. Our findings corroborate those of several published studies. These results may imply that these traits have been associated with Darwinian fitness over evolutionary time. However, some of the autozygosity-trait relationships were attenuated after controlling for background sociodemographic characteristics, suggesting that alternative explanations for these associations have not been eliminated. Care needs to be taken in the design and interpretation of ROH studies in order to glean reliable information about the genetic architecture and evolutionary history of complex traits.</p></div

The importance of including habitat-specific behaviour in models of butterfly movement

Dispersal is a key process affecting population persistence and major factors affecting dispersal rates are the amounts, connectedness and properties of habitats in landscapes. We present new data on the butterfly Maniola jurtina in flower-rich and flower-poor habitats that demonstrates how movement and behaviour differ between sexes and habitat types, and how this effects consequent dispersal rates. Females had higher flight speeds than males but their total time in flight was four times less. The effect of habitat type was strong for both sexes, flight speeds were ~2.5x and ~1.7x faster on resource-poor habitats for males and females respectively, and flights were approximately 50% longer. With few exceptions females oviposited in the mown grass habitat, likely because growing grass offers better food for emerging caterpillars, but they foraged in the resource-rich habitat. It seems that females faced a trade-off between ovipositing without foraging in the mown grass or foraging without ovipositing where flowers were abundant. We show that taking account of habitat-dependent differences in activity, here categorised as flight or non-flight, is crucial to obtaining good fits of an individual-based model to observed movement. An important implication of this finding is that incorporating habitat-specific activity budgets is likely necessary for predicting longer-term dispersal in heterogeneous habitats as habitat-specific behaviour substantially influences the mean (>30% difference) and kurtosis (1.4x difference) of dispersal kernels. The presented IBMs provide a simple method to explicitly incorporate known activity and movement rates when predicting dispersal in changing and heterogeneous landscapes

Dark Matter in Dwarf Spheroidals I: Models

This paper introduces a new two-parameter family of dwarf spheroidal (dSph) galaxy models. The density distribution has a Plummer profile and falls like the inverse fourth power of distance in projection, in agreement with the star-count data. The first free parameter controls the velocity anisotropy, the second controls the dark matter content. The dark matter distribution can be varied from one extreme of mass-follows-light through a near-isothermal halo with flat rotation curve to the other extreme of an extended dark halo with harmonic core. This family of models is explored analytically in some detail -- the distribution functions, the intrinsic moments and the projected moments are all calculated. For the nearby Galactic dSphs, samples of hundreds of discrete radial velocities are becoming available. A technique is developed to extract the anisotropy and dark matter content from such data sets by maximising the likelihood function of the sample of radial velocities. This is constructed from the distribution function and corrected for observational errors and the effects of binaries. Tests on simulated data sets show that samples of 1000 discrete radial velocities are ample to break the degeneracy between mass and anisotropy in the nearby dSphs. Interesting constraints can already be placed on the distribution of the dark matter with samples of 160 radial velocities (the size of the present-day data set for Draco).Comment: 16 pages, version in press at MNRA

Data on the movement behaviour of four species of grassland butterfly

This Data in Brief article describes data on the movement behaviour of four species of grassland butterflies collected over three years and at four sites in southern England. The datasets consist of the movement tracks of and recorded using standard methods and presented as steps distances and turning angles. Sites consisted of nectar-rich field margins, meadows, and mown short turf grasslands with minimal flowers. In total, 783 unique movement tracks were collected. The data were used for analysing the movement behaviour of the species and for parameterising individual-based movement models

Integrating the influence of weather into mechanistic models of butterfly movement

Understanding the factors influencing movement is essential to forecasting species persistence in a changing environment. Movement is often studied using mechanistic models, extrapolating short-term observations of individuals to longer-term predictions, but the role of weather variables such as air temperature and solar radiation, key determinants of ectotherm activity, are generally neglected. We aim to show how the effects of weather can be incorporated into individual-based models of butterfly movement thus allowing analysis of their effects. Methods: We constructed a mechanistic movement model and calibrated it with high precision movement data on a widely studied species of butterfly, the meadow brown (Maniola jurtina), collected over a 21-week period at four sites in southern England. Day time temperatures during the study ranged from 14.5 to 31.5⁰C and solar radiation from heavy cloud to bright sunshine. The effects of weather are integrated into the individual-based model through weather-dependent scaling of parametric distributions representing key behaviours: the durations of flight and periods of inactivity. Results: Flight speed was unaffected by weather, time between successive flights increased as solar radiation decreased, and flight duration showed a unimodal response to air temperature that peaked between approximately 23⁰C and 26⁰C. After validation, the model demonstrated that weather alone can produce a more than two-fold difference in predicted weekly displacement. Conclusions: Individual Based models provide a useful framework for integrating the effect of weather into movement models. By including weather effects we are able to explain a two-fold difference in movement rate of M. jurtina consistent with inter-annual variation in dispersal measured in population studies. Climate change for the studied populations is expected to decrease activity and dispersal rates since these butterflies already operate close to their thermal optimum

Characterization of a large sex determination region in Salix purpurea L. (Salicaceae).

Dioecy has evolved numerous times in plants, but heteromorphic sex chromosomes are apparently rare. Sex determination has been studied in multiple Salix and Populus (Salicaceae) species, and P. trichocarpa has an XY sex determination system on chromosome 19, while S. suchowensis and S. viminalis have a ZW system on chromosome 15. Here we use whole genome sequencing coupled with quantitative trait locus mapping and a genome-wide association study to characterize the genomic composition of the non-recombining portion of the sex determination region. We demonstrate that Salix purpurea also has a ZW system on chromosome 15. The sex determination region has reduced recombination, high structural polymorphism, an abundance of transposable elements, and contains genes that are involved in sex expression in other plants. We also show that chromosome 19 contains sex-associated markers in this S. purpurea assembly, along with other autosomes. This raises the intriguing possibility of a translocation of the sex determination region within the Salicaceae lineage, suggesting a common evolutionary origin of the Populus and Salix sex determination loci

Landscape genetic connectivity in a riparian foundation tree is jointly driven by climatic gradients and river networks

Fremont cottonwood (Populus fremonti) is a foundation riparian tree species that drives community structure and ecosystem processes in southwestern U.S. ecosystems. Despite its ecological importance, little is known about the ecological and environmental processes that shape its genetic diversity, structure, and landscape connectivity. Here, we combined molecular analyses of 82 populations including 1312 individual trees dispersed over the species’ geographical distribution. We reduced the data set to 40 populations and 743 individuals to eliminate admixture with a sibling species, and used multivariate restricted optimization and reciprocal causal modeling to evaluate the effects of river network connectivity and climatic gradients on gene flow. Our results confirmed the following: First, gene flow of Fremont cottonwood is jointly controlled by the connectivity of the river network and gradients of seasonal precipitation. Second, gene flow is facilitated by mid-sized to large rivers, and is resisted by small streams and terrestrial uplands, with resistance to gene flow decreasing with river size. Third, genetic differentiation increases with cumulative differences in winter and spring precipitation. Our results suggest that ongoing fragmentation of riparian habitats will lead to a loss of landscape-level genetic connectivity, leading to increased inbreeding and the concomitant loss of genetic diversity in a foundation species. These genetic effects will cascade to a much larger community of organisms, some of which are threatened and endangered

Fractal dimension and degree of order in sequential deposition of mixture

We present a number models describing the sequential deposition of a mixture of particles whose size distribution is determined by the power-law $p(x) \sim \alpha x^{\alpha-1}$, $x\leq l$ . We explicitly obtain the scaling function in the case of random sequential adsorption (RSA) and show that the pattern created in the long time limit becomes scale invariant. This pattern can be described by an unique exponent, the fractal dimension. In addition, we introduce an external tuning parameter beta to describe the correlated sequential deposition of a mixture of particles where the degree of correlation is determined by beta, while beta=0 corresponds to random sequential deposition of mixture. We show that the fractal dimension of the resulting pattern increases as beta increases and reaches a constant non-zero value in the limit $\beta \to \infty$ when the pattern becomes perfectly ordered or non-random fractals.Comment: 16 pages Latex, Submitted to Phys. Rev.

Management Effects on Greenhouse Gas Dynamics in Fen Ditches

Globally, large areas of peatland have been drained through the digging of ditches, generally to increase agricultural production. By lowering the water table it is often assumed that drainage reduces landscape-scale emissions of methane (CH4) into the atmosphere to negligible levels. However, drainage ditches themselves are known to be sources of CH4 and other greenhouse gases (GHGs), but emissions data are scarce, particularly for carbon dioxide (CO2) and nitrous oxide (N2O), and show high spatial and temporal variability. Here, we report dissolved GHGs and diffusive fluxes of CH4 and CO2 from ditches at three UK lowland fens under different management; semi-natural fen, cropland, and cropland restored to low-intensity grassland. Ditches at all three fens emitted GHGs to the atmosphere, but both fluxes and dissolved GHGs showed extensive variation both seasonally and within-site. CH4 fluxes were particularly large, with medians peaking at all three sites in August at 120-230 mg m-2 d-1. Significant between site differences were detected between the cropland and the other two sites for CO2 flux and all three dissolved GHGs, suggested that intensive agriculture has major effects on ditch biogeochemistry. Multiple regression models using environmental and water chemistry data were able to explain 29-59% of observed variation in dissolved GHGs. Annual CH4 fluxes from the ditches were 37.8, 18.3 and 27.2 g CH4 m-2 yr-1 for the semi-natural, grassland and cropland, and annual CO2 fluxes were similar (1100 to 1440 g CO2 m-2 yr-1) among sites. We suggest that fen ditches are important contributors to landscape-scale GHG emissions, particularly for CH4. Ditch emissions should be included in GHG budgets of human modified fens, particularly where drainage has removed the original terrestrial CH4 source, e.g. agricultural peatlands

The impact of premature extrauterine exposure on infants’ stimulus-evoked brain activity across multiple sensory systems

Prematurity can result in widespread neurodevelopmental impairment, with the impact of premature extrauterine exposure on brain function detectable in infancy. A range of neurodynamic and haemodynamic functional brain measures have previously been employed to study the neurodevelopmental impact of prematurity, with methodological and analytical heterogeneity across studies obscuring how multiple sensory systems are affected. Here, we outline a standardised template analysis approach to measure evoked response magnitudes for visual, tactile, and noxious stimulation in individual infants (n = 15) using EEG. By applying these templates longitudinally to an independent cohort of very preterm infants (n = 10), we observe that the evoked response template magnitudes are significantly associated with age-related maturation. Finally, in a cross-sectional study we show that the visual and tactile response template magnitudes differ between a cohort of infants who are age-matched at the time of study but who differ according to whether they are born during the very preterm or late preterm period (n = 10 and 8 respectively). These findings demonstrate the significant impact of premature extrauterine exposure on brain function and suggest that prematurity can accelerate maturation of the visual and tactile sensory system in infants born very prematurely. This study highlights the value of using a standardised multi-modal evoked-activity analysis approach to assess premature neurodevelopment, and will likely complement resting-state EEG and behavioural assessments in the study of the functional impact of developmental care interventions