Inference of Coalescence Times and Variant Ages Using Convolutional Neural Networks.

Accurate inference of the time to the most recent common ancestor (TMRCA) between pairs of individuals and of the age of genomic variants is key in several population genetic analyses. We developed a likelihood-free approach, called CoalNN, which uses a convolutional neural network to predict pairwise TMRCAs and allele ages from sequencing or SNP array data. CoalNN is trained through simulation and can be adapted to varying parameters, such as demographic history, using transfer learning. Across several simulated scenarios, CoalNN matched or outperformed the accuracy of model-based approaches for pairwise TMRCA and allele age prediction. We applied CoalNN to settings for which model-based approaches are under-developed and performed analyses to gain insights into the set of features it uses to perform TMRCA prediction. We next used CoalNN to analyze 2,504 samples from 26 populations in the 1,000 Genome Project data set, inferring the age of ∼80 million variants. We observed substantial variation across populations and for variants predicted to be pathogenic, reflecting heterogeneous demographic histories and the action of negative selection. We used CoalNN's predicted allele ages to construct genome-wide annotations capturing the signature of past negative selection. We performed LD-score regression analysis of heritability using summary association statistics from 63 independent complex traits and diseases (average N=314k), observing increased annotation-specific effects on heritability compared to a previous allele age annotation. These results highlight the effectiveness of using likelihood-free, simulation-trained models to infer properties of gene genealogies in large genomic data sets.

Genealogical histories in structured populations.

In genealogies of genes sampled from structured populations, lineages coalesce at rates dependent on the states of the lineages. For migration and coalescence events occurring on comparable time scales, for example, only lineages residing in the same deme of a geographically subdivided population can have descended from a common ancestor in the immediately preceding generation. Here, we explore aspects of genealogical structure in a population comprising two demes, between which migration may occur. We use generating functions to obtain exact densities and moments of coalescence time, number of mutations, total tree length, and age of the most recent common ancestor of the sample. We describe qualitative features of the distribution of gene genealogies, including factors that influence the geographical location of the most recent common ancestor and departures of the distribution of internode lengths from exponential.

Demographic inference using genetic data from a single individual: Separating population size variation from population structure.

The rapid development of sequencing technologies represents new opportunities for population genetics research. It is expected that genomic data will increase our ability to reconstruct the history of populations. While this increase in genetic information will likely help biologists and anthropologists to reconstruct the demographic history of populations, it also represents new challenges. Recent work has shown that structured populations generate signals of population size change. As a consequence it is often difficult to determine whether demographic events such as expansions or contractions (bottlenecks) inferred from genetic data are real or due to the fact that populations are structured in nature. Given that few inferential methods allow us to account for that structure, and that genomic data will necessarily increase the precision of parameter estimates, it is important to develop new approaches. In the present study we analyze two demographic models. The first is a model of instantaneous population size change whereas the second is the classical symmetric island model. We (i) re-derive the distribution of coalescence times under the two models for a sample of size two, (ii) use a maximum likelihood approach to estimate the parameters of these models (iii) validate this estimation procedure under a wide array of parameter combinations, (iv) implement and validate a model rejection procedure by using a Kolmogorov-Smirnov test, and a model choice procedure based on the AIC, and (v) derive the explicit distribution for the number of differences between two non-recombining sequences. Altogether we show that it is possible to estimate parameters under several models and perform efficient model choice using genetic data from a single diploid individual.

Post-glacial colonization of the Fennoscandian coast by a plant parasitic insect with an unusual life history.

Species that exhibit very peculiar ecological traits combined with limited dispersal ability pose a challenge to our understanding of ecological and evolutionary mechanisms. This is especially true when they have managed to spread over long distances, overcome physical barriers, and colonize large areas. Climate and landscape changes, trophic web relations, as well as life history all interact to shape migration routes and present-day species distributions and their population genetic structures. Here we analyzed the post-glacial colonization of northern Europe by the gall midge Contarinia vincetoxici, which is a monophagous parasite on the perennial herb White swallowwort (Vincetoxicum hirundinaria). This insect not only has a narrow feeding niche but also limited dispersal ability and an exceptionally long dormancy. Gall midge larvae (n = 329) were collected from 16 sites along its distribution range in Denmark, Sweden, and Finland. Using microsatellite loci and knowledge of the species and the regions' history, we investigated the role of landscape change, host plant distribution, insect population dynamics, and life history in shaping the population genetic structure of the insect. We devoted particular interest to the role of the insect's presumed poor dispersal capacity in combination with its exceptionally extended diapause. We found significant levels of local inbreeding (95% highest posterior density interval = 0.42-0.47), low-level within-population heterozygosity (mean H E = 0.45, range 0.20-0.61) with private alleles in all populations except two. We also found significant (p < .001) regional isolation-by-distance patterns, suggesting regularly recurring mainly short-distance dispersal. According to approximate Bayesian computations, C. vincetoxici appears to have colonized the study area via wind-aided flights from remote areas approximately 4600-700 years before present when the land has gradually risen above the sea level. Extremely long dormancy periods have allowed the species to "disperse in time", thereby aiding population persistence despite generally low census population sizes.

Single bubble and drop techniques for characterizing foams and emulsions.

The physics of foams and emulsions has traditionally been studied using bulk foam/emulsion tests and single film platforms such as the Scheludko cell. Recently there has been a renewed interest in a third class of techniques that we term as single bubble/drop tests, which employ isolated whole bubbles and drops to probe the characteristics of foams and emulsions. Single bubble and drop techniques provide a convenient framework for investigating a number of important characteristics of foams and emulsions, including the rheology, stabilization mechanisms, and rupture dynamics. In this review we provide a comprehensive discussion of the various single bubble/drop platforms and the associated experimental measurement protocols including the construction of coalescence time distributions, visualization of the thin film profiles and characterization of the interfacial rheological properties. Subsequently, we summarize the recent developments in foam and emulsion science with a focus on the results obtained through single bubble/drop techniques. We conclude the review by presenting important venues for future research.

Analysis of node2vec random walks on networks.

Random walks have been proven to be useful for constructing various algorithms to gain information on networks. Algorithm node2vec employs biased random walks to realize embeddings of nodes into low-dimensional spaces, which can then be used for tasks such as multi-label classification and link prediction. The performance of the node2vec algorithm in these applications is considered to depend on properties of random walks that the algorithm uses. In the present study, we theoretically and numerically analyse random walks used by the node2vec. Those random walks are second-order Markov chains. We exploit the mapping of its transition rule to a transition probability matrix among directed edges to analyse the stationary probability, relaxation times in terms of the spectral gap of the transition probability matrix, and coalescence time. In particular, we show that node2vec random walk accelerates diffusion when walkers are designed to avoid both backtracking and visiting a neighbour of the previously visited node but do not avoid them completely.

An experimental study on the coalescence process of binary droplets in oil under ultrasonic standing waves.

The coalescence process of binary droplets in oil under ultrasonic standing waves was investigated with high-speed photography. Three motion models of binary droplets in coalescence process were illustrated: (1) slight translational oscillation; (2) sinusoidal translational oscillation; (3) migration along with acoustic streaming. To reveal the droplets coalescence mechanisms, the influence of main factors (such as acoustic intensity, droplet size, viscosity and interfacial tension, etc) on the motion and coalescence of binary droplets was studied under ultrasonic standing waves. Results indicate that the shortest coalescence time is achieved when binary droplets show sinusoidal translational oscillation. The corresponding acoustic intensity in this case is the optimum acoustic intensity. Under the optimum acoustic intensity, drop size decrease will bring about coalescence time decrease by enhancing the binary droplets oscillation. Moreover, there is an optimum interfacial tension to achieve the shortest coalescence time.

Tempo and mode of evolutionary radiation in Diabroticina beetles (genera Acalymma, Cerotoma, and Diabrotica).

Adaptive radiation is an aspect of evolutionary biology encompassing microevolution and macroevolution, for explaining the principles of lineage divergence. There are intrinsic as well as extrinsic factors that can be postulated to explain that adaptive radiation has taken place in specific lineages. The Diabroticina beetles are a prominent example of differential diversity that could be examined in detail to explain the diverse paradigms of adaptive radiation. Macroevolutionary analyses must present the differential diversity patterns in a chronological framework. The current study reviews the processes that shaped the differential diversity of some Diabroticina lineages (i.e. genera Acalymma, Cerotoma, and Diabrotica). These diversity patterns and the putative processes that produced them are discussed within a statistically reliable estimate of time. This was achieved by performing phylogenetic and coalescent analyses for 44 species of chrysomelid beetles. The data set encompassed a total of 2,718 nucleotide positions from three mitochondrial and two nuclear loci. Pharmacophagy, host plant coevolution, competitive exclusion, and geomorphological complexity are discussed as putative factors that might have influenced the observed diversity patterns. The coalescent analysis concluded that the main radiation within Diabroticina beetles occurred between middle Oligocene and middle Miocene. Therefore, the radiation observed in these beetles is not recent (i.e. post-Panamanian uplift, 4 Mya). Only a few speciation events in the genus Diabrotica might be the result of the Pleistocene climatic oscillations.

Asymptotic distributions of coalescence times and ancestral lineage numbers for populations with temporally varying size.

The distributions of coalescence times and ancestral lineage numbers play an essential role in coalescent modeling and ancestral inference. Both exact distributions of coalescence times and ancestral lineage numbers are expressed as the sum of alternating series, and the terms in the series become numerically intractable for large samples. More computationally attractive are their asymptotic distributions, which were derived in Griffiths (1984) for populations with constant size. In this article, we derive the asymptotic distributions of coalescence times and ancestral lineage numbers for populations with temporally varying size. For a sample of size n, denote by Tm the mth coalescent time, when m + 1 lineages coalesce into m lineages, and An(t) the number of ancestral lineages at time t back from the current generation. Similar to the results in Griffiths (1984), the number of ancestral lineages, An(t), and the coalescence times, Tm, are asymptotically normal, with the mean and variance of these distributions depending on the population size function, N(t). At the very early stage of the coalescent, when t → 0, the number of coalesced lineages n - An(t) follows a Poisson distribution, and as m → n, $$n\left(n-1\right){T}_{m}/2N\left(0\right)$$ follows a gamma distribution. We demonstrate the accuracy of the asymptotic approximations by comparing to both exact distributions and coalescent simulations. Several applications of the theoretical results are also shown: deriving statistics related to the properties of gene genealogies, such as the time to the most recent common ancestor (TMRCA) and the total branch length (TBL) of the genealogy, and deriving the allele frequency spectrum for large genealogies. With the advent of genomic-level sequencing data for large samples, the asymptotic distributions are expected to have wide applications in theoretical and methodological development for population genetic inference.

Phylogeography of Human T-lymphotropic Virus Type 1 (HTLV-1) Lineages Endemic to Japan.

We conducted phylogenetic analyses and an estimation of coalescence times for East Asian strains of HTLV-1. Phylogenetic analyses showed that the following three lineages exist in Japan: "JPN", primarily comprising Japanese isolates; "EAS", comprising Japanese and two Chinese isolates, of which one originated from Chengdu and the other from Fujian; and "GLB1", comprising isolates from various locations worldwide, including a few Japanese isolates. It was estimated that the JPN and EAS lineages originated as independent lineages approximately 3,900 and 6,000 years ago, respectively. Based on archaeological findings, the "Out of Sunda" hypothesis was recently proposed to clarify the source of the Jomon (early neolithic) cultures of Japan. According to this hypothesis, it is suggested that the arrival of neolithic people in Japan began approximately 10,000 years ago, with a second wave of immigrants arriving between 6,000 and 4,000 years ago, peaking at around 4,000 years ago. Estimated coalescence times of the EAS and JPN lineages place the origins of these lineages within this 6,000-4,000 year period, suggesting that HTLV-1 was introduced to Japan by neolithic immigrants, not Paleo-Mongoloids. Moreover, our data suggest that the other minor lineage, GLB1, may have been introduced to Japan by Africans accompanying European traders several centuries ago, during or after "The Age of Discovery." Thus, the results of this study greatly increase our understanding of the origins and current distribution of HTLV-1 lineages in Japan and provide further insights into the ethno-epidemiology of HTLV-1.