Splitting Events Research Articles

O-210 DNA methylation signature of monozygotic twinning: investigating the relationship with medically assisted reproduction, higher-order gestations, and common genetic variants

Abstract Study question To study a DNA methylation signature of monozygotic twins in relation to medically assisted reproduction (MAR), higher-order gestations, and genome-wide common genetic variants. Summary answer Monozygotic twinning and MAR show largely distinct DNA methylation signatures. Monozygotic triplets, like monozygotic twins, carry a comparable but stronger DNA methylation signature. What is known already Monozygotic twins arise when a zygote or embryo splits during pre-implantation stages of development. Higher-order monozygotic multiples including triplets have been hypothesized to arise from multiple consecutive splitting events. The underlying mechanisms are unknown. Some studies have reported a higher rate of monozygotic twins born after the use of medically-assisted reproductive technologies. We recently identified a DNA methylation signature in blood samples from adult monozygotic twins, which showed strong replication across cohorts and in buccal samples from children. This signature consists of 834 differentially methylated locations, enriched for loci with a role in embryonic processes, cell adhesion, and metastable epi-alleles. Study design, size, duration We compared buccal DNA methylation profiles of 934 naturally conceived monozygotic twins to 43 monozygotic twins conceived after IVF/ICSI (mean age=9). We generated monozygotic twinning DNA methylation scores in an independent buccal dataset (59 triplets, 198 twins, and 119 siblings of twins, mean age=15). A genome-wide association study (GWAS) on the DNA methylation score was performed in two datasets from the Netherlands Twin Register (NTR) (1: Blood, N = 2841, mean age=37, 2: Buccal, N = 1150, mean age=10). Participants/materials, setting, methods DNA methylation was assessed with Illumina arrays (450k/EPIC). To study the relationship between DNA methylation and MAR, we performed an epigenome-wide association study (EWAS) of MAR in monozygotic twins. We applied our previously developed DNA-methylation based predictor (trained on blood methylation data from twins using elastic net regression) to novel buccal methylation data from multiples including triplets. GWAS analysis was performed in gcta using --fastGWA-mlm correcting for 10 genetic ancestry PCs and genotype platform. Main results and the role of chance Through EWAS, we identified 29 differentially methylated CpGs in buccal cells from monozygotic twins conceived after MAR compared to naturally conceived monozygotic twins (after Bonferroni correction), of which 8 were previously identified in an EWAS meta-analysis of IVF on cord blood from singletons at birth. None of the 834 CpGs detected in our previous EWAS meta-analysis of monozygotic twinning were associated with MAR, suggesting that they are connected to natural monozygotic twinning. The monozygotic twinning epigenetic signature showed similar performance in buccal DNA methylation data from monozygotic twins as previously observed (81% of monozygotic twins correctly classified). Sensitivity was highest for monozygotic triplets (90% correctly classified), but specificity remains moderate (66% of DZ twins correctly predicted, 53% of non-twins correctly predicted). GWAS analysis of blood 450k array data identified three genome-wide significant loci. The top SNP (rs76157694, MAF=0.25) maps to TBX4; an embryonic transcription factor primarily known for its role in hindlimb development. This finding is consistent with our previous results of MZ-differentially methylated positions being enriched within TBX4 binding motifs. GWAS analysis of the buccal EPIC array data identified no genome-wide significant loci. We are planning a GWAS meta-analysis together with the Genetics of DNA methylation consortium. Limitations, reasons for caution Our research provides compelling hints towards an epigenomic event in monozygotic multiples, but whether the signature represents a cause, effect, or a byproduct of monozygotic twinning remains to be established. In ongoing research, we study the signature in pre- and perinatal tissues from twins (Dutch Fetal biobank and PANDA biobank). Wider implications of the findings The methylation signature may serve as a biomarker to retrospectively diagnose if a person was conceived as monozygotic twin, providing novel opportunities to examine links between vanishing monozygotic twin syndrome and certain congenital disorders. Examples include Beckwith-Wiedemann Syndrome and Amyoplasia (∼10-fold higher frequency of monozygotic twins among patients). Trial registration number not applicable

Machine Learning Assisted Experimental Characterization of Bubble Dynamics in Gas-Solid Fluidized Beds.

This study introduces a machine learning (ML)-assisted image segmentation method for automatic bubble identification in gas-solid quasi-2D fluidized beds, offering enhanced accuracy in bubble recognition. Binary images are segmented by the ML method, and an in-house Lagrangian tracking technique is developed to track bubble evolution. The ML-assisted segmentation method requires few training data, achieves an accuracy of 98.75%, and allows for filtering out common sources of uncertainty in hydrodynamics, such as varying illumination conditions and out-of-focus regions, thus providing an efficient tool to study bubbling in a standard, consistent, and repeatable manner. In this work, the ML-assisted methodology is tested in a particularly challenging case: structured oscillating fluidized beds, where the spatial and time evolution of the bubble position, velocity, and shape are characteristics of the nucleation-propagation-rupture cycle. The new method is validated across various operational conditions and particle sizes, demonstrating versatility and effectiveness. It shows the ability to capture challenging bubbling dynamics and subtle changes in velocity and size distributions observed in beds of varying particle size. New characteristic features of oscillating beds are identified, including the effect of frequency and particle size on the bubble morphology, aspect, and shape factors and their relationship with the stability of the flow, quantified through the rate of coalescence and splitting events. This type of combination of classic analysis with the application of the ML assisted techniques provides a powerful tool to improve standardization and address the reproducibility of hydrodynamic studies, with the potential to be extended from gas-solid fluidization to other multiphase flow systems.

Vortex splitting in two-dimensional fluids and non-neutral electron plasmas with smooth vorticity profiles

Initially, elliptical, quasi-two-dimensional (2D) fluid vortices can split into multiple pieces if the aspect ratio is sufficiently large due to the growth and saturation of perturbations known as Love modes on the vortex edge. Presented here are experiments and numerical simulations, showing that the aspect ratio threshold for vortex splitting is significantly higher for vortices with realistic, smooth edges than that predicted by a simple “vortex patch” model, where the vorticity is treated as piecewise constant inside a deformable boundary. The experiments are conducted by exploiting the E × B drift dynamics of collisionless, pure electron plasmas in a Penning–Malmberg trap, which closely model 2D vortex dynamics due to an isomorphism between the Drift–Poisson equations describing the plasmas and the Euler equations describing ideal fluids. The simulations use a particle-in-cell method to model the evolution of a set of point vortices. The aspect ratio splitting threshold ranges up to about twice as large as the vortex patch prediction and depends on the edge vorticity gradient. This is thought to be due to spatial Landau damping, which decreases the vortex aspect ratio over time and, thus, stabilizes the Love modes. Near the threshold, asymmetric splitting events are observed in which one of the split products contains much less circulation than the other. These results are relevant to a wide range of quasi-2D fluid systems, including geophysical fluids, astrophysical disks, and drift-wave eddies in tokamak plasmas.

Neutral diversity in experimental metapopulations

New automated and high-throughput methods allow the manipulation and selection of numerous bacterial populations. In this manuscript we are interested in the neutral diversity patterns that emerge from such a setup in which many bacterial populations are grown in parallel serial transfers, in some cases with population-wide extinction and splitting events. We model bacterial growth by a birth–death process and use the theory of coalescent point processes. We show that there is a dilution factor that optimises the expected amount of neutral diversity for a given number of cycles, and study the power law behaviour of the mutation frequency spectrum for different experimental regimes. We also explore how neutral variation diverges between two recently split populations by establishing a new formula for the expected number of shared and private mutations. Finally, we show the interest of such a setup to select a phenotype of interest that requires multiple mutations.

Cristae dynamics is modulated in bioenergetically compromised mitochondria.

Cristae membranes have been recently shown to undergo intramitochondrial merging and splitting events. Yet, the metabolic and bioenergetic factors regulating them are unclear. Here, we investigated whether and how cristae morphology and dynamics are dependent on oxidative phosphorylation (OXPHOS) complexes, the mitochondrial membrane potential (ΔΨm), and the ADP/ATP nucleotide translocator. Advanced live-cell STED nanoscopy combined with in-depth quantification were employed to analyse cristae morphology and dynamics after treatment of mammalian cells with rotenone, antimycin A, oligomycin A, and CCCP. This led to formation of enlarged mitochondria along with reduced cristae density but did not impair cristae dynamics. CCCP treatment leading to ΔΨm abrogation even enhanced cristae dynamics showing its ΔΨm-independent nature. Inhibition of OXPHOS complexes was accompanied by reduced ATP levels but did not affect cristae dynamics. However, inhibition of ADP/ATP exchange led to aberrant cristae morphology and impaired cristae dynamics in a mitochondrial subset. In sum, we provide quantitative data of cristae membrane remodelling under different conditions supporting an important interplay between OXPHOS, metabolite exchange, and cristae membrane dynamics.

Forced vortex merging and splitting events in ferrofluidic Couette flow

Time-dependent boundary conditions are ubiquitous in numerous natural and industrial flows. However, to date, the influence of such temporal modulations has been given minor attention. This research addresses ferrofluidic Couette flow in between co-rotating cylinders in a spatially homogeneous magnetic field subject to time-periodic modulation. Using a modified Niklas approximation, we study the effect of amplitude and frequency modulation onto the transition scenarios between different toroidal flow structures, non-propagating vortex (nV) states, via vortex merging and splitting. Thereby, the system response appears to be quite sensitive/dependent on the driving frequency ΩH, which can cause a notable “delay” in the system response. Further, as a result of the inertia of the ferrofluid, resisting the fast-changing accelerating Kelvin force, new, temporal nV states appear within an alternating field. These states are unstable under static fields. Finally, we show that within the same nV state, while keeping similar flow dynamics, large discrepancies in angular momentum and torque can be observed.

Single synaptic vesicle tracking in TIRFM-amenable hippocampal synapses.

Single synaptic vesicle (SV) tracking is used to explore the dynamics of SV movement close to active zones (AZ) by total internal reflection fluorescence microscopy (TIRFM). To do so, we used cultured hippocampal ‘xenapses’, purely presynaptic boutons formed by neurons on micro-patterned coverslips, functionalized with synaptogenic cell adhesion proteins. For single SV labeling we developed surface-modified single-color quantum dots with improved photostability and pH-sensitivity for single SV tracking. Obtained single SV movies are analyzed with an improved single-particle tracking software, which combines Automatic Correction for sCMOS-related Noise algorithm (Nat. Commun., Mandracchia et al., 2020) for denoising, U-Track (Nat. Methods, Jaqaman et al., 2008) for frame-to-frame particle linking, and a newly developed single-particle localization algorithm. We yield a localization accuracy of 0.1229 ± 0.1004 pixels (110 nm pixel size) and are able to resolve merging and splitting events of two crossing particle trajectories even though they have low signal-to-noise ratio of ∼1.2. In hippocampal xenapses with active zones (AZ) facing the coverslip, SVs appear to jump between discrete levels of axial distance to AZs, and these discrete levels are remarkably stable over tens of seconds. As SVs in electron micrographs appear to be interconnected by short tethers, these discrete levels might arise from a layered structure of the SV cluster above the AZ.

Through history to growth dynamics: deciphering the evolution of spatial networks

Many ramified, network-like patterns in nature, such as river networks or blood vessels, form as a result of unstable growth of moving boundaries in an external diffusive field. Here, we pose the inverse problem for the network growth—can the growth dynamics be inferred from the analysis of the final pattern? We show that by evolving the network backward in time one can not only reconstruct the growth rules but also get an insight into the conditions under which branch splitting occurs. Determining the growth rules from a single snapshot in time is particularly important for growth processes so slow that they cannot be directly observed, such as growth of river networks and deltas or cave passages. We apply this approach to analyze the growth of a real river network in Vermont, USA. We determine its growth rule and argue that branch splitting events are triggered by an increase in the tip growth velocity.

Adaptive Subsystem Density Functional Theory.

Subsystem density functional theory (DFT) is emerging as a powerful electronic structure method for large-scale simulations of molecular condensed phases and interfaces. Key to its computational efficiency is the use of approximate nonadditive noninteracting kinetic energy functionals. Unfortunately, currently available nonadditive functionals lead to inaccurate results when the subsystems interact strongly such as when they engage in chemical reactions. This work disrupts the status quo by devising a workflow that extends subsystem DFT's applicability also to strongly interacting subsystems. This is achieved by implementing a fully automated adaptive definition of subsystems which is realized during geometry optimizations or ab initio molecular dynamics simulations. The new method prescribes subsystem merging and splitting events redistributing the resources (both for work and data) in an efficient way making use of modern parallelization strategies and object-oriented programming. We showcase the method with examples probing from moderate-to-strong inter-subsystem interactions, opening the door to using subsystem DFT for modeling chemical reactions in molecular condensed phases with a black box computational tool.

Vortex merging and splitting events in viscoelastic Taylor–Couette flow

Recent experiments have reported a novel transition to elasto-inertial turbulence in the Taylor–Couette flow of a dilute polymer solution. Unlike previously reported transitions, this newly discovered scenario, dubbed vortex merging and splitting (VMS) transition, occurs in the centrifugally unstable regime and the mechanisms underlying it are two-dimensional: the flow becomes chaotic due to the proliferation of events where axisymmetric vortex pairs may be either created (vortex splitting) or annihilated (vortex merging). In this paper, we present direct numerical simulations, using the finitely extensible nonlinear elastic-Peterlin (FENE-P) constitutive equation to model the polymer dynamics, which reproduce the experimental observations with great accuracy and elucidate the reasons for the onset of this surprising dynamics. Starting from the Newtonian limit and increasing progressively the fluid's elasticity, we demonstrate that the VMS dynamics is not associated with the well-known Taylor vortices, but with a steady pattern of elastically induced axisymmetric vortex pairs known as diwhirls. The amount of angular momentum carried by these elastic vortices becomes increasingly small as the fluid's elasticity increases and it eventually reaches a marginal level. When this occurs, the diwhirls become dynamically disconnected from the rest of the system and move independently from each other in the axial direction. It is shown that vortex merging and splitting events, along with local transient chaotic dynamics, result from the interactions among diwhirls, and that this complex spatio-temporal dynamics persists even at elasticity levels twice as large as those investigated experimentally.

Accounting for Errors in Data Improves Divergence Time Estimates in Single-cell Cancer Evolution.

Single-cell sequencing provides a new way to explore the evolutionary history of cells. Compared to traditional bulk sequencing, where a population of heterogeneous cells is pooled to form a single observation, single-cell sequencing isolates and amplifies genetic material from individual cells, thereby preserving the information about the origin of the sequences. However, single-cell data are more error-prone than bulk sequencing data due to the limited genomic material available per cell. Here, we present error and mutation models for evolutionary inference of single-cell data within a mature and extensible Bayesian framework, BEAST2. Our framework enables integration with biologically informative models such as relaxed molecular clocks and population dynamic models. Our simulations show that modeling errors increase the accuracy of relative divergence times and substitution parameters. We reconstruct the phylogenetic history of a colorectal cancer patient and a healthy patient from single-cell DNA sequencing data. We find that the estimated times of terminal splitting events are shifted forward in time compared to models which ignore errors. We observed that not accounting for errors can overestimate the phylogenetic diversity in single-cell DNA sequencing data. We estimate that 30–50% of the apparent diversity can be attributed to error. Our work enables a full Bayesian approach capable of accounting for errors in the data within the integrative Bayesian software framework BEAST2.

Characterizing Mesoscale Eddies of Eastern Upwelling Origins in the Atlantic Ocean and Their Role in Offshore Transport

Motivated by the recurrent formation of eddies in the eastern upwelling areas, we examine cross-basin connectivity that is promoted by coherent, long-lived and long-propagating mesoscale eddies in the Atlantic Ocean. By applying the TOEddies detection and tracking algorithm to daily satellite observations (AVISO/DUACS) of Absolute Dynamic Topography (ADT), we characterize mesoscale eddy activity and variability in the North and South Atlantic. This method provides a robust eddy-network reconstruction, enabling the tracking of eddies formed in the Atlantic eastern upwelling systems together with any merging and splitting events they undergo during their lifetime as long as they remain detectable in the altimetry field. We show that during the years of observations, mesoscale eddies are long-lived coherent structures that can ensure oceanic connectivity between the eastern and the western boundaries, as a result of complex inter-eddy interactions. Moreover, alignment of South Atlantic eddies of eastern boundary origins with available Argo floats achieves a mean cross-basin connectivity signal from both anticyclonic and cyc5lonic eddies which is particularly evident at depth, along thermocline isopycnal layers of γn = 26 - 27 kg m–3. We explore two individual cyclonic eddy trajectories from in-situ measurements gathered by different Argo profiling floats trapped inside the eddy cores. Our results support the hypothesis that mesoscale eddies sustain and transport water masses while subducting during their westward propagation.

Evaluation of the spatiotemporal unsteady characteristics of the tip leakage vortex based on a direct numerical simulation database

The spatiotemporal evolution of the tip clearance vortical structures behind a flat hydrofoil immersed in a turbulent boundary layer over a flat plate was investigated by means of direct numerical simulation, with focus on the unsteady behaviors of the tip-leakage vortex (TLV) and their effects on the flow blockage. It is found that the TLV evolutionary processes can be characterized by three typical phases: the formation phase, the vortex wandering phase, and the vortex splitting and breakdown phase. In the second phase, the TLV is subject to the wall-normal low-frequency wandering motion, which is excited by the induced vortex. The abrupt increase in vortex wandering intensity near the trailing edge of the hydrofoil can be attributed to the frequent occurrence of vortex splitting and breakdown events in the third phase. The time-averaged vortex intensity of the TLV increases gradually in the first and second phases. On the other hand, instantaneous vortex intensity shows an initially decreasing and then increasing trend, as a result of the breakdown of the TLV and the formation of the secondary TLV, respectively. In addition, the investigation of flow blockage caused by the TLV indicates that along the streamwise direction, the time-averaged blockage area and blockage coefficient both follow an exponential distribution. The present results provide a qualitative and quantitative characterization for the spatiotemporal evolution of the TLV, which is critical for improving the efficiency loss and mechanical vibration caused by the unsteady behaviors of the TLV.

Age-based spatial distribution of workers is resilient to worker loss in a subterranean termite

Elaborate task allocation is key to the ecological success of eusocial insects. Termite colonies are known for exhibiting age polyethism, with older instars more likely to depart the reproductive center to access food. However, it remains unknown how termites retain this spatial structure against external disturbances. Here we show that a subterranean termite Coptotermes formosanus Shiraki combines age polyethism and behavioral flexibility to maintain a constant worker proportion at the food area. Since this termite inhabits multiple wood pieces by connecting them through underground tunnels, disastrous colony splitting events can result in the loss of colony members. We simulated this via weekly removal of all individuals at the food area. Our results showed that termites maintained a worker proportion of ~ 20% at the food area regardless of changes in total colony size and demographic composition, where younger workers replaced food acquisition functions to maintain a constant worker proportion at the food area. Food consumption analysis revealed that the per-capita food consumption rate decreased with younger workers, but the colony did not compensate for the deficiency by increasing the proportion of workers at the feeding site. These results suggest that termite colonies prioritize risk management of colony fragmentation while maintaining suitable food acquisition efficiency with the next available workers in the colony, highlighting the importance of task allocation for colony resiliency under fluctuating environments.

Extreme events in transitional turbulence.

Transitional localized turbulence in shear flows is known to either decay to an absorbing laminar state or to proliferate via splitting. The average passage times from one state to the other depend super-exponentially on the Reynolds number and lead to a crossing Reynolds number above which proliferation is more likely than decay. In this paper, we apply a rare-event algorithm, Adaptative Multilevel Splitting, to the deterministic Navier-Stokes equations to study transition paths and estimate large passage times in channel flow more efficiently than direct simulations. We establish a connection with extreme value distributions and show that transition between states is mediated by a regime that is self-similar with the Reynolds number. The super-exponential variation of the passage times is linked to the Reynolds number dependence of the parameters of the extreme value distribution. Finally, motivated by instantons from Large Deviation theory, we show that decay or splitting events approach a most-probable pathway. This article is part of the theme issue 'Mathematical problems in physical fluid dynamics (part 2)'.

Multiple species delimitation approaches with COI barcodes poorly fit each other and morphospecies - An integrative taxonomy case of Sri Lankan Sericini chafers (Coleoptera: Scarabaeidae).

DNA taxonomy including barcoding and metabarcoding is widely used to explore the diversity in biodiversity hotspots. In most of these hotspot areas, chafers are represented by a multitude of species, which are well defined by the complex shape of male genitalia. Here, we explore how well COI barcode data reflect morphological species entities and thus their usability for accelerated species inventorization. We conducted dedicated field surveys in Sri Lanka to collect the species‐rich and highly endemic Sericini chafers (Coleoptera: Scarabaeidae). Congruence among results of a series of protocols for de novo species delimitation and with morphology‐based species identifications was investigated. Different delimitation methods, such as the Poisson tree processes (PTP) model, Statistical Parsimony Analysis (TCS), Automatic Barcode Gap Discovery (ABGD), Assemble Species by Automatic Partitioning (ASAP), and Barcode Index Number (BIN) assignments, resulted in different numbers of molecular operational taxonomic units (MOTUs). All methods showed both over‐splitting and lumping of morphologically identified species. Only 18 of the observed 45 morphospecies perfectly matched MOTUs from all methods. The congruence of delimitation between MOTUs and morphospecies expressed by the match ratio was low, ranging from 0.57 to 0.67. TCS and multirate PTP (mPTP) showed the highest match ratio, while (BIN) assignment resulted in the lowest match ratio and most splitting events. mPTP lumped more species than any other method. Principal coordinate analysis (PCoA) on a match ratio‐based distance matrix revealed incongruent outcomes of multiple DNA delimitation methods, although applied to the same data. Our results confirm that COI barcode data alone are unlikely to correctly delimit all species, in particular, when using only a single delimitation approach. We encourage the integration of various approaches and data, particularly morphology, to validate species boundaries.

Differentiation patterns of emperor moths (Lepidoptera: Saturniidae: Saturniinae) of a continental island: divergent evolutionary history driven by Pleistocene glaciations.

BackgroundOn the basis of molecular dating, Pleistocene glaciations have been proposed as the major driving force of biota speciation in the Palearctic and the pre-Quaternary origin of Amazonian taxa. However, the major driving factors in East Asia remain unclear. All 16 saturniine species inhabiting Taiwan with congeners of populations, subspecies, or species in East Asia constitute research objects for addressing the mode of speciation because of the repeated formation and disappearance of a landbridge from the Asian mainland to Taiwan during glacial cycles.MethodsThe genetic divergences of mitochondrial cytochrome c oxidase subunit I (COI) and 16S rDNA and the nuclear 28S rDNA of the saturniine species from Taiwan and the Asian mainland were assessed to determine the monophyly of each genus and species of Saturniinae. Moreover, 519 saturniine COI sequences of 114 taxa from adjacent East and Southeast Asian populations and closely related species were retrieved from GenBank and analyzed. The differentiation timing and possible origination of the insular saturniines were elucidated based on phylogenetic relationships, haplotype networks, and lineage calibrations.ResultsApproximately 90% of intraspecific COI divergence was <2%; all divergences exceeding 2% originated from comparisons between allopatric populations or subspecies. Relationship analyses revealed that multiple introductions likely occurred in insular saturniines and that some East Asian saturniines were paraphyletic as deduced by analyzing endemic insular species. Calibration dating revealed that Taiwanese endemic saturniines split from sibling Asian species 0.2–2.7 million years ago (Mya), whereas subspecific-level and population-level splitting events occurred 0.1–1.7 Mya and 0.2–1.2 Mya, respectively. Moreover, phylogenetic patterns combined with geographical distributions revealed that hill-distributed Taiwanese saturniines are closely related to those from southern China and Southeast Asia, whereas saturniines inhabiting altitudes higher than 1,500 m in Taiwan have siblings distributed in temperate Northeast Asia.DiscussionThe Global DNA Barcoding Initiative was successfully applied to study the population genetic structure in species. Most Formosan saturniines are distinct and monophyletic, reflecting the vicariant barrier of the Taiwan Strait; Pleistocene glacial cycles provided opportunities for insular saturniines to experience repeated isolation from and secondary contact with the continental mainland. Each insular saturniine may have evolved with a unique differentiation timing pattern that possibly emerged in the Early, Middle, or Late Pleistocene with these patterns differing from the consistent pattern that occurred in the temperate Palearctic and tropical Amazonian regions. Moreover, multiple migrations or artificial genetic admixtures may have also occurred, as suggested by the coexistence of two divergent lineages in a few Taiwanese saturniines.

Population divergence time estimation using individual lineage label switching.

Divergence time estimation from multilocus genetic data has become common in population genetics and phylogenetics. We present a new Bayesian inference method that treats the divergence time as a random variable. The divergence time is calculated from an assembly of splitting events on individual lineages in a genealogy. The time for such a splitting event is drawn from a hazard function of the truncated normal distribution. This allows easy integration into the standard coalescence framework used in programs such as Migrate. We explore the accuracy of the new inference method with simulated population splittings over a wide range of divergence time values and with a reanalysis of a dataset of 5 populations consisting of 3 present-day populations (Africans, Europeans, Asian) and 2 archaic samples (Altai and Ust’Isthim). Evaluations of simple divergence models without subsequent geneflow show high accuracy, whereas the accuracy of the results of isolation with migration models depends on the magnitude of the immigration rate. High immigration rates lead to a time of the most recent common ancestor of the sample that, looking backward in time, predates the divergence time. Even with many independent loci, accurate estimation of the divergence time with high immigration rates becomes problematic. Our comparison to other software tools reveals that our lineage-switching method, implemented in Migrate, is comparable to IMa2p. The software Migrate can run large numbers of sequence loci (>1,000) on computer clusters in parallel.

Comet fragmentation as a source of the zodiacal cloud

ABSTRACT Models of the zodiacal cloud’s thermal emission and sporadic meteoroids suggest Jupiter-family comets (JFCs) as the dominant source of interplanetary dust. However, comet sublimation is insufficient to sustain the quantity of dust presently in the inner Solar system, suggesting that spontaneous disruptions of JFCs may supply the zodiacal cloud. We present a model for the dust produced in comet fragmentations and its evolution. Using results from dynamical simulations, the model follows individual comets drawn from a size distribution as they evolve and undergo recurrent splitting events. The resulting dust is followed with a kinetic model which accounts for the effects of collisional evolution, Poynting–Robertson drag, and radiation pressure. This allows to model the evolution of both the size distribution and radial profile of dust, and we demonstrate the importance of including collisions (both as a source and sink of dust) in zodiacal cloud models. With physically motivated free parameters this model provides a good fit to zodiacal cloud observables, supporting comet fragmentation as the plausibly dominant dust source. The model implies that dust in the present zodiacal cloud likely originated primarily from disruptions of ∼50-km comets, since larger comets are ejected before losing all their mass. Thus much of the dust seen today was likely deposited as larger grains ∼0.1 Myr in the past. The model also finds the dust level to vary stochastically; e.g. every ∼50 Myr large (&amp;gt;100 km) comets with long dynamical lifetimes inside Jupiter cause dust spikes with order of magnitude increases in zodiacal light brightness lasting ∼1 Myr. If exozodiacal dust is cometary in origin, our model suggests it should be similarly variable.

Precursor types predict the stability of neuronal branches.

ABSTRACTBranches are critical for neuron function, generating the morphological complexity required for functional networks. They emerge from different, well-described, cytoskeletal precursor structures that elongate to branches. While branches are thought to be maintained by shared cytoskeletal regulators, our data from mouse hippocampal neurons indicate that the precursor structures trigger alternative branch maintenance mechanisms with differing stabilities. Whereas branches originating from lamellipodia or growth cone splitting events collapse soon after formation, branches emerging from filopodia persist. Furthermore, compared to other developing neurites, axons stabilise all branches and preferentially initiate branches from filopodia. These differences explain the altered stability of branches we observe in neurons lacking the plasma membrane protein phospholipid phosphatase-related protein 3 (PLPPR3, also known as PRG2) and in neurons treated with netrin-1. Rather than altering branch stability directly, PLPPR3 and netrin-1 boost a ‘filopodia branch programme’ on axons, thereby indirectly initiating more long-lived branches. In summary, we propose that studies on branching should distinguish overall stabilising effects from effects on precursor types, ideally using multifactorial statistical models, as exemplified in this study.