Bayesian Estimation of Positively Selected Sites

In protein-coding DNA sequences, historical patterns of selection can be inferred from amino acid substitution patterns. High relative rates of nonsynonymous to synonymous changes (=d _N /d _S ) are a clear indicator of positive, or directional, selection, and several recently developed methods attempt to distinguish these sites from those under neutral or purifying selection. One method uses an empirical Bayesian framework that accounts for varying selective pressures across sites while conditioning on the parameters of the model of DNA evolution and on the phylogenetic history. We describe a method that identifies sites under diversifying selection using a fully Bayesian framework. Similar to earlier work, the method presented here allows the rate of nonsynonymous to synonymous changes to vary among sites. The significant difference in using a fully Bayesian approach lies in our ability to account for uncertainty in parameters including the tree topology, branch lengths, and the codon model of DNA substitution. We demonstrate the utility of the fully Bayesian approach by applying our method to a data set of the vertebrate -globin gene. Compared to a previous analysis of this data set, the hierarchical model found most of the same sites to be in the positive selection class, but with a few striking exceptions.     

Spatiotemporal Mapping of Motility in Ex Vivo Preparations of the Intestines

Multiple approaches have been used to record and evaluate gastrointestinal motility including: recording changes in muscle tension, intraluminal pressure, and membrane potential. All of these approaches depend on measurement of activity at one or multiple locations along the gut simultaneously which are then interpreted to provide a sense of overall motility patterns. Recently, the development of video recording and spatiotemporal mapping (STmap) techniques have made it possible to observe and analyze complex patterns in ex vivo whole segments of colon and intestine. Once recorded and digitized, video records can be converted to STmaps in which the luminal diameter is converted to grayscale or color [called diameter maps (Dmaps)]. STmaps can provide data on motility direction (i.e., stationary, peristaltic, antiperistaltic), velocity, duration, frequency and strength of contractile motility patterns. Advantages of this approach include: analysis of interaction or simultaneous development of different motility patterns in different regions of the same segment, visualization of motility pattern changes over time, and analysis of how activity in one region influences activity in another region. Video recordings can be replayed with different timescales and analysis parameters so that separate STmaps and motility patterns can be analyzed in more detail. This protocol specifically details the effects of intraluminal fluid distension and intraluminal stimuli that affect motility generation. The use of luminal receptor agonists and antagonists provides mechanistic information on how specific patterns are initiated and how one pattern can be converted into another pattern. The technique is limited by the ability to only measure motility that causes changes in luminal diameter, without providing data on intraluminal pressure changes or muscle tension, and by the generation of artifacts based upon experimental setup; although, analysis methods can account for these issues. When compared to previous techniques the video recording and STmap approach provides a more comprehensive understanding of gastrointestinal motility.     

Proceedings of the SMBE Tri-National Young Investigators' Workshop 2005. Coalescent-based estimation of population parameters when the number of demes changes over time

We expand a coalescent-based method that uses serially sampled genetic data from a subdivided population to incorporate changes to the number of demes and patterns of colonization. Often, when estimating population parameters or other parameters of interest from genetic data, the demographic structure and parameters are not constant over evolutionary time. In this paper, we develop a Bayesian Markov chain Monte Carlo method that allows for step changes in mutation, migration, and population sizes, as well as changing numbers of demes, where the times of these changes are also estimated. We show that in parameter ranges of interest, reliable estimates can often be obtained, including the historical times of parameter changes. However, posterior densities of migration rates can be quite diffuse and estimators somewhat biased, as reported by other authors.     

Wavelet analysis for detecting anisotropy in point patterns

Although many methods have been proposed for analysing point locations for spatial pattern, previous methods have concentrated on clumping and spacing. The study of anisotropy (changes in spatial pattern with direction) in point patterns has been limited by lack of methods explicitly designed for these data and this purpose; researchers have been constrained to choosing arbitrary test directions or converting their data into quadrat counts and using methods designed for continuously distributed data. Wavelet analysis, a booming approach to studying spatial pattern, widely used in mathematics and physics for signal analysis, has started to make its way into the ecological literature. A simple adaptation of wavelet analysis is proposed for the detection of anisotropy in point patterns. The method is illustrated with both simulated and field data. This approach can easily be used for both global and local spatial analysis.     

Reading the landscape: temporal and spatial changes in a patterned peatland

The Everglades of south Florida is a patterned peatland that has undergone major hydrologic modification over the last century, including both drainage and impoundment. The Everglades ridge and slough patterns were originally characterized by regularly spaced elevated ridges and tree islands oriented parallel to water flow through interconnected sloughs. Many areas of the remaining Everglades have lost this patterning over time. Historical aerial photography for the years 1940, 1953, 1972, 1984, and 2004 provides source data to measure these changes over six decades. Maps were created by digitizing the ridges, tree islands, and sloughs in fifteen 24 km² study plots located in the remaining Everglades, and metrics were developed to quantify the extent and types of changes in the patterns. Pattern metrics of length/width ratios, number of ridges, and perimeter/area ratios were used to define the details and trajectories of pattern changes in the study plots from 1940 through 2004. These metrics characterized elongation, smoothness, and abundance of ridges and tree islands. Hierarchical agglomerative cluster analysis was used to categorize these 75 maps (15 plots by 5 years) into five categories based on a suite of metrics of pattern quality. Nonmetric multidimensional scaling, an ordination technique, confirmed that these categories were distinct with the primary axis distinguished primarily by the abundance of elongated ridges in each study plot. Strong patterns like those described historically were characterized by numerous, long ridges while degraded patterns contained few large, irregularly shaped patches. Pattern degradation usually occurred with ridges fusing into fewer, less linear patches of emergent vegetation. Patterning improved in some plots, probably through wetter conditions facilitating expression of the underlying microtopography. Trajectories showing responses of individual study plots over the six decades indicated that ridge and slough patterns can degrade or improve over time scales of a decade or less. Changes in ridge and slough patterns indicate that (1) patterns can be lost quickly following severe peat dryout, yet (2) patterns appear resilient at least over multi-decadal time periods; (3) patterns can be maintained and possibly strengthened with deeper water depths, and (4) the sub-decadal response time of pattern changes visible in aerial imagery is highly useful for change detection within the landscape. This analysis suggests that restoration of some aspects of these unique peatland patterns may be possible within relatively short planning time frames. Use of aerial photography in future Everglades restoration efforts can facilitate restoration and adaptive management by documenting sub-decadal pattern changes in response to altered hydrology and water management.     

Patterns of sexual dimorphism in the hominoid distal humerus

Basic biomechanical principles predict that body size differences and differences in the positional behavior of primates should impact on the design of the locomotor skeleton. Allometric distortions in joint shape might be expected between sexes if the degree of body size dimorphism is substantial and/or if sex-specific differences exist in behavior. Nevertheless, there are few documented cases of sexual dimorphism in the limb joints of hominoids, despite substantial body size dimorphism and some reports of intersexual differences in positional behavior. This study re-examines sexual dimorphism in the hominoid distal humerus using coordinate data, and distinguishes explicitly between degree of dimorphism (i.e., the magnitude of intersexual differences) and pattern of dimorphism (i.e. , the nature of these differences). Using a variety of multivariate morphometric methods (e.g., canonical variates analysis of Mosimann shape variables; Euclidean Distance Matrix Analysis of both form and pattern difference matrices), we address the following issues: (1) do males and females of different species and subspecies (or ethnic groups for humans) maintain similar joint shapes? (2) are multiple patterns of dimorphism evident in this region of hominoids? (3) are differences and similarities in degree and pattern predicted by phylogenetic propinquity and positional behavior? For the most part, our results support earlier findings that sexual dimorphism in the shape of the anthropoid elbow is slight. Of the eight taxa considered here, only the western lowland gorillas exhibited significant differences in the shape of the distal humerus. Gorilla gorilla gorilla also displays a significantly different pattern of dimorphism from the orang-utan. Pattern differences between Andaman Islanders and both mountain gorillas and the orang-utan also approach statistical significance (P<0.06 and P<0.08, respectively). Overall, and despite marked differences in the degree of dimorphism, the knuckle-walking African apes are more similar in patterns of dimorphism to each other than to other taxa (e.g., gorillas are more similar to orang-utans in degree, but more similar to chimpanzees and bonobos in pattern). We could find no definitive "human pattern" in our results and suspect that this is because human upper limbs face less stringent mechanical constraints since they are relieved of locomotor stresses (but we cannot rule out the possibility of undocumented differences among our human groups in sex-specific, work-related activities). We anticipate finding additional pattern differences among anthropoids in articular dimorphism as we add other taxa to our sample (including fossil hominids), and examine other joint systems.     

Differences of behavioral rhythms observed by flat cage and running-wheel cage in female rat

The ambulatory, wheel-running, and drinking activities were measured in Wistar-Imamichi strain female rats under 12 L:12 D condition (6:00-18:00), using Gundai type ambulo-drinkometer (for simultaneous measurements of ambulation and drinking) and wheel-drinkometer (for simultaneous measurements of wheel-running and drinking) to compare the rhythmicities of each behavioral activity. These apparatuses are able to measure the behavioral activities over a long period, successively and automatically. The circadian patterns of ambulatory activity had two large peaks at 21 or 24:00 and at 6:00 (acrophase). Contrary to the above results, the wheel-running activity exhibited clear mono-peak at 21:00 (acrophase). Thus, apparent differences of the pattern were observed between the two activities. However, ambulatory and wheel-running activities fluctuated showing 4-days rhythmicity, and both activities increased in estrus and proestrus stages, respectively. The circadian rhythms of drinking activities measured by both apparatuses showed almost same patterns with acrophases at 6:00, and 4-days rhythmicities were also observed and were characterized by remarkable decrease of activity in every proestrus stages. From these results, it is concluded that circadian pattern of ambulatory activity is different from that of wheel-running activity, but circadian patterns of drinking activities are stable regardless of different methods of the measurement. The ambulatory, wheel-running and drinking activities reflect the behavioral changes in sexual cycles.     

Influence of a Dorsomedial Hypothalamus Lesion on the Circadian Changes in the Enzyme Development and Activity of Intestinal Brushborder Membranes in the Rat

Circadian changes in activities and electrophoretic pattern of the intestinal brushborder enzymes alkaline phosphatase (EC 3.1.3.1), isomaltase (EC 3.2.1.10) and sucrase (EC 3.2.1.26) of normal rats and of rats with a lesion of the dorsomedial hypothalamus (DMH-rats) were studied. In contrast to the rhythm found in normal rats, there are no significant differences between the average enzyme activities in the light or dark period for the DMH-rats. The peak ratio in the electrophoretic pattern for sucrase-isomaltase (SI) over pro-sucrase-isomaltase (pro-SI) changes over 24 hr with higher values during the active (dark) period of the normal rat. In DMH-rats this ratio is much higher, but no significant difference could be demonstrated between the values near the acrophase in these rats.     

Effect of walking speed on inter-joint coordination differs between young and elderly adults

Investigating inter-joint coordination at different walking speeds in young and elderly adults could provide insights to age-related changes in neuromuscular control of gait. We examined effects of walking speed and age on the pattern and variability of inter-joint coordination. Gait analyses of 10 young and 10 elderly adults were performed with different self-selected speeds, including a preferred, faster, and slower speed. Continuous relative phase (CRP), derived from phase planes of two adjacent joints, was used to assess the inter-joint coordination. CRP patterns were examined with cross-correlation measures and root-mean-square (RMS) differences when comparing ensemble mean curves of the faster or slower speed to preferred speed walking. Variability of coordination for each participant was assessed with the average value of all standard deviations calculated for each data point over a gait cycle from all CRP curves, namely the deviation phase (DP). For hip-knee CRP pattern, RMS differences were significantly greater between the slower and preferred walking speeds than between the faster and preferred walking speeds in young adults, but this was not found in elderly adults. Significant group differences in RMS differences and cross-correlation measures were detected in hip-knee CRP patterns between the slower and preferred walking speeds. No significant walking speed or age effects were detected for the knee-ankle CRP. Significant walking speed effects were also detected in hip-knee DP values. However, no significant group differences were detected for all three speeds. These findings suggested that young and elder adults compromise changes of walking speed with different neuromuscular control strategies.     

Evolution of behavior and neural control of the fast-start escape response

The fast-start startle behavior is the primary mechanism of rapid escape in fishes and is a model system for examining neural circuit design and musculoskeletal function. To develop a dataset for evolutionary analysis of the startle response, the kinematics and muscle activity patterns of the fast-start were analyzed for four fish species at key branches in the phylogeny of vertebrates. Three of these species (Polypterus palmas, Lepisosteus osseus, and Amia calva) represent the base of the actinopterygian radiation. A fourth species (Oncorhynchus mykiss) provided data for a species in the central region of the teleost phylogeny. Using these data, we explored the evolution of this behavior within the phylogeny of vertebrates. To test the hypothesis that startle features are evolutionarily conservative, the variability of motor patterns and kinematics in fast-starts was described. Results show that the evolution of the startle behavior in fishes, and more broadly among vertebrates, is not conservative. The fast-start has undergone substantial change in suites of kinematics and electromyogram features, including the presence of either a one- or a two-stage kinematic response and change in the extent of bilateral muscle activity. Comparative methods were used to test the evolutionary hypothesis that changes in motor control are correlated with key differences in the kinematics and behavior of the fast-start. Significant evolutionary correlations were found between several motor pattern and behavioral characters. These results suggest that the startle neural circuit itself is not conservative. By tracing the evolution of motor pattern and kinematics on a phylogeny, it is shown that major changes in the neural circuit of the startle behavior occur at several levels in the phylogeny of vertebrates.     

Dynamics of DNA Methylation in Recent Human and Great Ape Evolution

DNA methylation is an epigenetic modification involved in regulatory processes such as cell differentiation during development, X-chromosome inactivation, genomic imprinting and susceptibility to complex disease. However, the dynamics of DNA methylation changes between humans and their closest relatives are still poorly understood. We performed a comparative analysis of CpG methylation patterns between 9 humans and 23 primate samples including all species of great apes (chimpanzee, bonobo, gorilla and orangutan) using Illumina Methylation450 bead arrays. Our analysis identified ∼800 genes with significantly altered methylation patterns among the great apes, including ∼170 genes with a methylation pattern unique to human. Some of these are known to be involved in developmental and neurological features, suggesting that epigenetic changes have been frequent during recent human and primate evolution. We identified a significant positive relationship between the rate of coding variation and alterations of methylation at the promoter level, indicative of co-occurrence between evolution of protein sequence and gene regulation. In contrast, and supporting the idea that many phenotypic differences between humans and great apes are not due to amino acid differences, our analysis also identified 184 genes that are perfectly conserved at protein level between human and chimpanzee, yet show significant epigenetic differences between these two species. We conclude that epigenetic alterations are an important force during primate evolution and have been under-explored in evolutionary comparative genomics.     

DRUIDS--detection of regions with unexpected internal deviation from stationarity

Most methods for inferring phylogenies from sequence data assume that patterns of substitution have been stationary over time. Changes in evolutionary constraint can result in nonstationary substitution patterns that are phylogenetically misleading unless modeled appropriately. Here we present a multiple-alignment-based method to identify regions that are likely to contain misleading phylogenetic signals due to changes in evolutionary constraints. The method uses a moving window approach to identify regions with a statistically significant deviation from stationarity in the physicochemical properties of amino acids among taxa. The protocol has been implemented in the software package DRUIDS (Detecting Regions of Unexpected Internal Deviation from Stationarity), available from the first author upon request.     

Geographical Variation in Fundulus heteroclitus: Tests for Concordance Between Egg and Adult Morphologies

Recent studies have shown distinct patterns of variation inthe egg morphology (oil droplet number, diameter and densityof chorionic filaments) of Fundulus heteroclitus along the eastcoast (including Chesapeake and Delaware bays). We tested thehypothesis that variation in adult morphology and in electromorphsis concordant with that of egg morphology over the same rangeby subjecting data for these character sets to the Mantel test.This analysis was based on data for three egg characters, nineteenadult morphological (meristic and morphometric) characters andfive protein characters from locations along the Atlantic coast.If the geographical differences observed among locations reflectgenetic differences between two forms that have establishedsecondary contact after isolation, we would expect general concordancebetween the different character sets. We would expect littleconcordance between the sets if they are each affected by differentselectional and/or developmental responses to environmentalregimes. Our analyses indicate that patterns of variation amonglocalities for meristic, egg, and genetic character sets areall concordant, and thus the observed differences among locationsare likely the result of secondary intergradation between twopreviously isolated forms. These conclusions are supported bysimilar patterns of geographical variation in spawning sitepreference and body coloration. Thus, these results supportour earlier suggestion that these morphs should be treated asseparate taxa, with F. h. heteroclitus occurring along the eastcoast from New Jersey south to Florida including lower Chesapeakeand Delaware bays and F. h. macrolepidotus distributed fromConnecticut north to Newfoundland with disjunct populationsin upper Chesapeake and Delaware bays. Intergrade zones occurwhere the two morphs come together along the east coast in northernNew Jersey and on Long Island, as well as in Chesapeake andDelaware bays     

Hendra Virus Spillover is a Bimodal System Driven by Climatic Factors

Understanding environmental factors driving spatiotemporal patterns of disease can improve risk mitigation strategies. Hendra virus (HeV), discovered in Australia in 1994, spills over from bats (Pteropus sp.) to horses and thence to humans. Below latitude ? 22°, almost all spillover events to horses occur during winter, and above this latitude spillover is aseasonal. We generated a statistical model of environmental drivers of HeV spillover per month. The model reproduced the spatiotemporal pattern of spillover risk between 1994 and 2015. The model was generated with an ensemble of methods for presence–absence data (boosted regression trees, random forests and logistic regression). Presences were the locations of horse cases, and absences per spatial unit (2.7 × 2.7 km pixels without spillover) were sampled with the horse census of Queensland and New South Wales. The most influential factors indicate that spillover is associated with both cold-dry and wet conditions. Bimodal responses to several variables suggest spillover involves two systems: one above and one below a latitudinal area close to ? 22°. Northern spillovers are associated with cold-dry and wet conditions, and southern with cold-dry conditions. Biologically, these patterns could be driven by immune or behavioural changes in response to food shortage in bats and horse husbandry. Future research should look for differences in these traits between seasons in the two latitudinal regions. Based on the predicted risk patterns by latitude, we recommend enhanced preventive management for horses from March to November below latitude 22° south.     

Fast combinatorial methods to estimate the probability of complex temporal patterns of spikes

 This study presents two efficient algorithms – combinatorial and probabilistic combinatorial methods (CM and PCM) – for estimation of a number of precise patterns of discharges that occur by chance in records of multiple single-unit spike trains. The confidence limits estimated by these methods are in good agreement with different sets of simulated test data as well as with the ad-hoc method. Both combinatorial methods provided a better accuracy than the bootstrap algorithm and in most cases of nonstationary data PCM provided better estimations than the ad-hoc method. Introduction of a jitter for searching patterns with a precision of a few milliseconds and burst filtering may introduce biases in the estimations. Comparison of a new filtering procedure based upon a filtering frequency with previously described schemes of filtering indicates the possibility of using a simple setting which remains accurate over a wide range of parameters. We aim to implement a combination of PCM for estimations of the number of patterns formed by three to seven spikes and CM for higher-order complexities for estimations during experiments in progress. Received: 12 June 1995 / Accepted in revised form: 5 February 1997     

Mapping Change in Large Networks

Change is a fundamental ingredient of interaction patterns in biology, technology, the economy, and science itself: Interactions within and between organisms change; transportation patterns by air, land, and sea all change; the global financial flow changes; and the frontiers of scientific research change. Networks and clustering methods have become important tools to comprehend instances of these large-scale structures, but without methods to distinguish between real trends and noisy data, these approaches are not useful for studying how networks change. Only if we can assign significance to the partitioning of single networks can we distinguish meaningful structural changes from random fluctuations. Here we show that bootstrap resampling accompanied by significance clustering provides a solution to this problem. To connect changing structures with the changing function of networks, we highlight and summarize the significant structural changes with alluvial diagrams and realize de Solla Price''s vision of mapping change in science: studying the citation pattern between about 7000 scientific journals over the past decade, we find that neuroscience has transformed from an interdisciplinary specialty to a mature and stand-alone discipline.     

The application of rapid evaporative ionization mass spectrometry in the analysis of Drosophila species—a potential new tool in entomology

There is increasing emphasis on the use of new analytical approaches in subject analysis and classification, particularly in respect to minimal sample preparation. Here, we demonstrate that rapid evaporative ionization mass spectrometry (REIMS), a method that captures metabolite mass spectra after rapid combustive degradation of an intact biological specimen, generates informative mass spectra from several arthropods, and more specifically, is capable of discerning differences between species and sex of several adult Drosophila species. A model including five Drosophila species, built using pattern recognition, achieves high correct classification rates (over 90%) using test datasets and is able to resolve closely related species. The ease of discrimination of male and female specimens also demonstrates that sex-specific differences reside in the REIMS metabolite patterns, whether analysed across all five species or specifically for D. melanogaster. Further, the same approach can correctly discriminate and assign Drosophila species at the larval stage, where these are morphologically highly similar or identical. REIMS offers a novel approach to insect typing and analysis, requiring a few seconds of data acquisition per sample and has considerable potential as a new tool for the field biologist.     

Relating Phylogenetic Trees to Transmission Trees of Infectious Disease Outbreaks

Transmission events are the fundamental building blocks of the dynamics of any infectious disease. Much about the epidemiology of a disease can be learned when these individual transmission events are known or can be estimated. Such estimations are difficult and generally feasible only when detailed epidemiological data are available. The genealogy estimated from genetic sequences of sampled pathogens is another rich source of information on transmission history. Optimal inference of transmission events calls for the combination of genetic data and epidemiological data into one joint analysis. A key difficulty is that the transmission tree, which describes the transmission events between infected hosts, differs from the phylogenetic tree, which describes the ancestral relationships between pathogens sampled from these hosts. The trees differ both in timing of the internal nodes and in topology. These differences become more pronounced when a higher fraction of infected hosts is sampled. We show how the phylogenetic tree of sampled pathogens is related to the transmission tree of an outbreak of an infectious disease, by the within-host dynamics of pathogens. We provide a statistical framework to infer key epidemiological and mutational parameters by simultaneously estimating the phylogenetic tree and the transmission tree. We test the approach using simulations and illustrate its use on an outbreak of foot-and-mouth disease. The approach unifies existing methods in the emerging field of phylodynamics with transmission tree reconstruction methods that are used in infectious disease epidemiology.     

Molecular network strategy in multi-omics and mass spectrometry imaging

Human physiological activities and pathological changes arise from the coordinated interactions of multiple molecules. Mass spectrometry (MS)-based multi-omics and MS imaging (MSI)-based spatial omics are powerful methods used to investigate molecular information related to the phenotype of interest from homogenated or sliced samples, including the qualitative, relative quantitative and spatial distributions. Molecular network strategy provides efficient methods to help us understand and mine the biological patterns behind the phenotypic data. It illustrates and combines various relationships between molecules, and further performs the molecule identification and biological interpretation. Here, we describe the recent advances of network-based analysis and its applications for different biological processes, such as, obesity, central nervous system diseases, and environmental toxicology.