Haplotype Parsing

While the shared consensus genetic sequence of our species contains a great deal of information about our common biology, there is also much to be learned from the subtle genetic variations across our species. These variations are believed to be generally of little or no direct functional significance and predominantly reflect the chance accumulation of small genetic changes since our emergence as a species. Therefore, they carry little useful information when observed in a single individual. When tallied across a whole population though, these chance mutations can teach us a great deal about our evolutionary history and the patterns of inheritance in particular individuals. In particular, frequently observed patterns of single nucleotide polymorphisms (SNPs) in a population can identify segments of chromosome that have been passed down largely intact through long stretches of our evolution. Finding these frequently conserved chromosomal segments, or haplotypes, and developing methods to identify haplotype patterns in particular individuals, will in turn help us to identify those particular segments that carry genetic factors influencing risk for many common human diseases. To make the best use of this data, we will need to develop new models for the encoding of information in genome variations--the "language of genetic variation"--and new algorithms for fitting datasets to those models. This article surveys past work by the author and colleagues on this problem, utilising computational methods for locating frequent patterns in haploid sequence data, and "parsing" sequences so as to optimally explain them given the knowledge of the general population structure. The author's recent work in this area has been compiled into a set of computational tools available at http://www-2.cs.cmu.edu/~russells/software/hapmotif.html.     

Evolutionary conservation of metabolism explains howDrosophila nutrigenomics can help us understand human nutrigenomics

While large populations in the third world are enduring famine, much of the developed world is undergoing an obesity epidemic. In addition to reflecting an unbalanced distribution of food, the "epidemic of overabundance" is ironically leading to a decrease in the health and longevity of the obese and improperly nourished in the first world. International consortia, such as the European Nutrigenomics Organization (NuGO), are increasing our knowledge of nutrientgene interactions and the effects of diet and obesity on human health. In this review, we summarize both previous and ongoing nutrigenomics studies in Drosophila and we explain how these studies can be used to provide insights into molecular mechanisms underlying nutrigenomics in humans. We will discuss how quantitative trait locus (QTL) experiments have identified genes that affect triglyceride levels in Drosophila, and how microarray analyses show that hundreds of genes have altered gene expression under different dietary conditions. Finally, we will discuss ongoing combined microarray-QTL studies, termed "genetical genomics," that promise to identify "master modulatory loci" that regulate global responses of potentially hundreds of genes under different dietary conditions. When "master modulatory loci" are identified in Drosophila, then experiments in mammalian models can be used to determine the relevance of these genes to human nutrition and health.     

典型脆弱生态区生态技术评价方法及应用专题导读

全球经济发展和日益增强的人类活动给业已脆弱的生态系统带来了巨大挑战,寻求尊重自然规律、环境友好的生态治理与恢复技术成为实现联合国可持续发展目标的重要组成部分。近年来,国内外科学家和生态治理机构研发出了一系列技术体系和技术模式,对脆弱生态区退化生态系统展开了全面的治理和恢复。然而,缺乏对这些治理技术的评价和优选方法的研发和应用在很大程度上限制了优良技术的筛选和推广应用,造成了资金和人力的浪费和损失。针对这些问题,科技部在2016年启动了国家重点研发计划项目"生态技术评价方法、指标体系与全球生态治理技术评价",其中重要的任务之一是对生态技术进行梳理、评价和优选。本文旨在对已有的评价方法和指标体系的研究进展进行系统梳理,对生态技术的特征、生态技术评价的基本步骤和原则、生态技术的三阶段评估方法等进行了界定和深入分析,对本专题收录的14篇学术文章所涵盖的评价方法和模型研发、案例应用等进行了介绍,以期为筛选优良技术、提高生态技术应用效果、促进优良技术的输出和引进提供参考。     

"X-ray vision" and the evolution of forward-facing eyes

Why do our eyes face forward, and why do many mammals have eyes facing sideways? Here, we describe results suggesting that the degree of binocular convergence is selected to maximize how much the mammal can see in its environment. Mammals in non-cluttered environments can see the most around them with panoramic, laterally directed eyes. Mammals in cluttered environments, however, can see best when their eyes face forward, for binocularity has the power of "seeing through" clutter out in the world. Evidence across mammals closely fits the predictions of this "X-ray" hypothesis.     

Novel methods improve prediction of species' distributions from occurrence data

Prediction of species' distributions is central to diverse applications in ecology, evolution and conservation science. There is increasing electronic access to vast sets of occurrence records in museums and herbaria, yet little effective guidance on how best to use this information in the context of numerous approaches for modelling distributions. To meet this need, we compared 16 modelling methods over 226 species from 6 regions of the world, creating the most comprehensive set of model comparisons to date. We used presence-only data to fit models, and independent presence-absence data to evaluate the predictions. Along with well-established modelling methods such as generalised additive models and GARP and BIOCLIM, we explored methods that either have been developed recently or have rarely been applied to modelling species' distributions. These include machine-learning methods and community models, both of which have features that may make them particularly well suited to noisy or sparse information, as is typical of species' occurrence data. Presence-only data were effective for modelling species' distributions for many species and regions. The novel methods consistently outperformed more established methods. The results of our analysis are promising for the use of data from museums and herbaria, especially as methods suited to the noise inherent in such data improve.     

FaaPred: A SVM-Based Prediction Method for Fungal Adhesins and Adhesin-Like Proteins

Adhesion constitutes one of the initial stages of infection in microbial diseases and is mediated by adhesins. Hence, identification and comprehensive knowledge of adhesins and adhesin-like proteins is essential to understand adhesin mediated pathogenesis and how to exploit its therapeutic potential. However, the knowledge about fungal adhesins is rudimentary compared to that of bacterial adhesins. In addition to host cell attachment and mating, the fungal adhesins play a significant role in homotypic and xenotypic aggregation, foraging and biofilm formation. Experimental identification of fungal adhesins is labor- as well as time-intensive. In this work, we present a Support Vector Machine (SVM) based method for the prediction of fungal adhesins and adhesin-like proteins. The SVM models were trained with different compositional features, namely, amino acid, dipeptide, multiplet fractions, charge and hydrophobic compositions, as well as PSI-BLAST derived PSSM matrices. The best classifiers are based on compositional properties as well as PSSM and yield an overall accuracy of 86%. The prediction method based on best classifiers is freely accessible as a world wide web based server at http://bioinfo.icgeb.res.in/faap. This work will aid rapid and rational identification of fungal adhesins, expedite the pace of experimental characterization of novel fungal adhesins and enhance our knowledge about role of adhesins in fungal infections.     

Fusion Tensor Subspace Transformation Framework

Tensor subspace transformation, a commonly used subspace transformation technique, has gained more and more popularity over the past few years because many objects in the real world can be naturally represented as multidimensional arrays, i.e. tensors. For example, a RGB facial image can be represented as a three-dimensional array (or 3rd-order tensor). The first two dimensionalities (or modes) represent the facial spatial information and the third dimensionality (or mode) represents the color space information. Each mode of the tensor may express a different semantic meaning. Thus different transformation strategies should be applied to different modes of the tensor according to their semantic meanings to obtain the best performance. To the best of our knowledge, there are no existing tensor subspace transformation algorithm which implements different transformation strategies on different modes of a tensor accordingly. In this paper, we propose a fusion tensor subspace transformation framework, a novel idea where different transformation strategies are implemented on separate modes of a tensor. Under the framework, we propose the Fusion Tensor Color Space (FTCS) model for face recognition.     

Comparison of model selection technique performance in predicting the spread of newly invasive species: a case study with <Emphasis Type="Italic">Batrachochytrium salamandrivorans</Emphasis>

Species distribution models (SDMs) increasingly have been used to anticipate the spread of invasive species. However, these models are powerful conservation tools only if they are biologically relevant, and thus validation of these models is essential. Here, we evaluate four model selection frameworks for their ability to identify a best fit model of spread under low data conditions early in an invasion, specifically testing the efficacy of methods that utilize absence data in addition to presence data in evaluating models. We test this question using a simulation where we generated data with varying confidence in the accuracy of the absence data, as absences in early invasions may become presences in the future, and increasing quantity of observation data to test the models. We create these simulations based on a real-world example of a newly emergent, invasive fungal pathogen, Batrachochytrium salamandrivorans (Bsal). The simulation demonstrated that AIC and Likelihood consistently outperform both Kappa and AUC in selecting the true model as the best model when data are limited and absence data are low quality, with AIC providing the most conservative results due to penalties for overparameterization. With these results, we then used these techniques to compare five candidate models for predicting the spread of Bsal. Consistent with the simulation, the best fit model of the candidate models for Bsal was inconsistent across the four metrics. However, AIC, which performed best in the simulation study, suggested that the spread of Bsal into Western Europe was best predicted by a combination of bioclimatic suitability, salamander richness, and number of salamander imports. Our results highlight the difficulty in evaluating predictive models when data are limited and of low quality, as with a newly invasive species, but show that these challenges can be partially addressed with the appropriate model selection approach. Use of this approach is critical as SDMs of invasive species are often used to inform conservation policy and efforts before the invasion spreads, when limited data are available.     

Elastic Surface Model For Beta‐Barrels: Geometric,Computational, And Statistical Analysis

Over the past 2 decades, many different geometric models were created for beta barrels, including, but not limited to: cylinders, 1‐sheeted hyperboloids, twisted hyperboloids, catenoids, and so forth. We are proponents of an elastic surface model for beta‐barrels, which includes the minimal surface model as a particular case, but is a lot more comprehensive. Beta barrel models are obtained as numerical solutions of a boundary value problem, using the COMSOL Multiphysics Modeling Software. We have compared them against the best fitting statistical models, with positive results. The geometry of each individual beta barrel, as a rotational elastic surface, is determined by the ratio between the exterior diameter and the height. Through our COMSOL computational modeling, we created a rather large variety of generalized Willmore surfaces that may represent models for beta barrels. The catenoid is just a particular solution among all these shapes.     

Spatiotemporal modeling of first and second wave outbreak dynamics of COVID-19 in Germany

The COVID-19 pandemic has kept the world in suspense for the past year. In most federal countries such as Germany, locally varying conditions demand for state- or county-level decisions to adapt to the disease dynamics. However, this requires a deep understanding of the mesoscale outbreak dynamics between microscale agent models and macroscale global models. Here, we use a reparameterized SIQRD network model that accounts for local political decisions to predict the spatiotemporal evolution of the pandemic in Germany at county resolution. Our optimized model reproduces state-wise cumulative infections and deaths as reported by the Robert Koch Institute and predicts the development for individual counties at convincing accuracy during both waves in spring and fall of 2020. We demonstrate the dominating effect of local infection seeds and identify effective measures to attenuate the rapid spread. Our model has great potential to support decision makers on a state and community politics level to individually strategize their best way forward during the months to come.

     

Morphological Integration and the Interpretation of Fossil Hominin Diversity

The fossil record of primate and human evolution cannot provide accurate estimates of within species variation and integration. This means that we cannot directly observe how patterns of integration have evolved over time in this lineage. And yet, our interpretations of fossil diversity are awash with assumptions about variation patterning in precisely these fossil taxa. Most commonly, researchers rely on extant models of variation for interpreting past diversity, by assuming equality of variation (and occasionally covariation) among extant and fossil populations. Yet one of the things we know from studies of integration in primates is that patterns of morphological covariation can differ among even closely related taxa, indicating that they have diverged over evolutionary time, either in response to selection or as the result of neutral evolution. At the same time, overall patterns of integration remain remarkably similar, meaning that in many respects they are highly conserved evolutionarily. Taken together, these seemingly contradictory observations offer an important conceptual framework for interpreting patterns that we observe in the fossil past. This framework dictates that while we can use patterns of covariation in extant taxa as proxies for extinct diversity, and indeed their conserved nature makes them superior to approaches that rely on variation alone, we also need to account for the fact that such patterns change over time, and incorporate that into our models. Here I provide examples using covariation patterns estimated from modern humans and African great apes to demonstrate the extent to which divergence in covariance structure might affect our interpretations of hominin diversity.

Pushing Structural Information into the Yeast Interactome by High-Throughput Protein Docking Experiments

The last several years have seen the consolidation of high-throughput proteomics initiatives to identify and characterize protein interactions and macromolecular complexes in model organisms. In particular, more that 10,000 high-confidence protein-protein interactions have been described between the roughly 6,000 proteins encoded in the budding yeast genome (Saccharomyces cerevisiae). However, unfortunately, high-resolution three-dimensional structures are only available for less than one hundred of these interacting pairs. Here, we expand this structural information on yeast protein interactions by running the first-ever high-throughput docking experiment with some of the best state-of-the-art methodologies, according to our benchmarks. To increase the coverage of the interaction space, we also explore the possibility of using homology models of varying quality in the docking experiments, instead of experimental structures, and assess how it would affect the global performance of the methods. In total, we have applied the docking procedure to 217 experimental structures and 1,023 homology models, providing putative structural models for over 3,000 protein-protein interactions in the yeast interactome. Finally, we analyze in detail the structural models obtained for the interaction between SAM1-anthranilate synthase complex and the MET30-RNA polymerase III to illustrate how our predictions can be straightforwardly used by the scientific community. The results of our experiment will be integrated into the general 3D-Repertoire pipeline, a European initiative to solve the structures of as many as possible protein complexes in yeast at the best possible resolution. All docking results are available at http://gatealoy.pcb.ub.es/HT_docking/.     

The control of copy number of IS6110 in Mycobacterium tuberculosis

Insertion sequence (IS) elements are bacterial genes that are able to transpose to different locations in the genome. These elements are often used in molecular epidemiology as genetic markers that track the spread of pathogens. Transposable elements have frequently been described as "selfish DNA" because they facilitate their own transposition, causing damage when they insert into coding regions, while contributing little if anything to the bacterial host. According to this hypothesis, the expansion of copy number of insertion sequences is opposed by negative selection against high copy numbers. From an alternative point of view, we might expect IS elements to intrinsically regulate transposition within cells, thereby limiting damage to their bacterial host. Here, we report evidence that the copy number of IS6110 in Mycobacterium tuberculosis is controlled by selection against the element. We first construct 12 different models of marker change resulting from a combination of possible transposition functions and selective regimes. We then compute the Akaike Information Criterion for each model to identify the models that best explain data consisting of serial isolates of M. tuberculosis genotyped with IS6110. We find that the best performing models all include selection against the accumulation of copies. Specifically, our analysis points to the interaction of separate copies of the element causing lethal effects. We discuss the implications of these findings for genome evolution and molecular epidemiology.     

Goodness of Fit of Probability Distributions for Sightings as Species Approach Extinction

Estimating the probability that a species is extinct and the timing of extinctions is useful in biological fields ranging from paleoecology to conservation biology. Various statistical methods have been introduced to infer the time of extinction and extinction probability from a series of individual sightings. There is little evidence, however, as to which of these models provide adequate fit to actual sighting records. We use L-moment diagrams and probability plot correlation coefficient (PPCC) hypothesis tests to evaluate the goodness of fit of various probabilistic models to sighting data collected for a set of North American and Hawaiian bird populations that have either gone extinct, or are suspected of having gone extinct, during the past 150 years. For our data, the uniform, truncated exponential, and generalized Pareto models performed moderately well, but the Weibull model performed poorly. Of the acceptable models, the uniform distribution performed best based on PPCC goodness of fit comparisons and sequential Bonferroni-type tests. Further analyses using field significance tests suggest that although the uniform distribution is the best of those considered, additional work remains to evaluate the truncated exponential model more fully. The methods we present here provide a framework for evaluating subsequent models.     

Ecology after 100 years: Progress and pseudo-progress

Has the science of ecology fulfilled the promises made by the originators of ecological science at the start of the last century? What should ecology achieve? Have good policies for environmental management flowed out of ecological science? These important questions are rarely discussed by ecologists working on detailed studies of individual systems. Until we decide what we wish to achieve as ecologists we cannot define progress toward those goals. Ecologists desire to achieve an understanding of how the natural world operates, how humans have modified the natural world, and how to alleviate problems arising from human actions. Ecologists have made impressive gains over the past century in achieving these goals, but this progress has been uneven. Some sub-disciplines of ecology are well developed empirically and theoretically, while others languish for reasons that are not always clear. Fundamental problems can be lost to view as ecologists fiddle with unimportant pseudo-problems. Bandwagons develop and disappear with limited success in addressing problems. The public demands progress from all the sciences, and as time moves along and problems get worse, more rapid progress is demanded. The result for ecology has too often been poor, short-term science and poor management decisions. But since the science is rarely repeated and the management results may be a generation or two down the line, it is difficult for the public or for scientists to decide how good or bad the scientific advice has been. In ecology over the past 100 years we have made solid achievements in behavioural ecology, population dynamics, and ecological methods, we have made some progress in understanding community and ecosystem dynamics, but we have made less useful progress in developing theoretical ecology, landscape ecology, and natural resource management. The key to increasing progress is to adopt a systems approach with explicit hypotheses, theoretical models, and field experiments on a scale defined by the problem. With continuous feedback between problems, possible solutions, relevant theory and experimental data we can achieve our scientific goals.     

Understanding human DNA sequence variation

Over the past century researchers have identified normal genetic variation and studied that variation in diverse human populations to determine the amounts and distributions of that variation. That information is being used to develop an understanding of the demographic histories of the different populations and the species as a whole, among other studies. With the advent of DNA-based markers in the last quarter century, these studies have accelerated. One of the challenges for the next century is to understand that variation. One component of that understanding will be population genetics. We present here examples of many of the ways these new data can be analyzed from a population perspective using results from our laboratory on multiple individual DNA-based polymorphisms, many clustered in haplotypes, studied in multiple populations representing all major geographic regions of the world. These data support an "out of Africa" hypothesis for human dispersal around the world and begin to refine the understanding of population structures and genetic relationships. We are also developing baseline information against which we can compare findings at different loci to aid in the identification of loci subject, now and in the past, to selection (directional or balancing). We do not yet have a comprehensive understanding of the extensive variation in the human genome, but some of that understanding is coming from population genetics.     

Directory of Soviet Scientists Engaged in Psychological and Psychophysiological Research

For purposes of space, and because the International Congress deals primarily with problems of psychology and psychophysiology, we have not included in this listing scientists engaged in purely psychiatric research. (Such a listing will appear in the next issue of this Journal.) The list includes all authors of relevant articles published in 1964 and 1965 in the journals Voprosy psikhologii (designated as V), Zhurnal vysshey nervnoy deyatel'nosti im. I. P. Pavlova (P), and Zhurnal nevropatologii i psikhiatrii im. S. S. Korsakova (K), and in all past issues of Soviet Psychology and Psychiatry (S) (1962-1965). Also included are authors of relevant books published in the period 1962-1965. The list has been augmented by information provided by members of the Advisory Board of this Journal, and by the trip reports listed in "Reviews in English of Recent Soviet Psychology: A Bibliography" (this issue). As we stated in regard to the Directory of Institutions, above, no doubt this compendium contains gaps and inaccuracies, for which we beg the indulgence of our readers and our Soviet colleagues. We have done the best we could with the material available to us.     

Human social organization during the Late Pleistocene: Beyond the nomadic-egalitarian model

Many researchers assume that until 10–12,000 years ago, humans lived in small, mobile, relatively egalitarian bands. This “nomadic-egalitarian model” suffuses the social sciences. It informs evolutionary explanations of behavior and our understanding of how contemporary societies differ from those of our evolutionary past. Here, we synthesize research challenging this model and articulate an alternative, the diverse histories model, to replace it. We review the limitations of using recent foragers as models of Late Pleistocene societies and the considerable social variation among foragers commonly considered small-scale, mobile, and egalitarian. We review ethnographic and archaeological findings covering 34 world regions showing that non-agricultural peoples often live in groups that are more sedentary, unequal, large, politically stratified, and capable of large-scale cooperation and resource management than is normally assumed. These characteristics are not restricted to extant Holocene hunter-gatherers but, as suggested by archaeological findings from 27 Middle Stone Age sites, likely characterized societies throughout the Late Pleistocene (until c. 130 ka), if not earlier. These findings have implications for how we understand human psychological adaptations and the broad trajectory of human history.     

Drug reps and the academic medical center: a case for management rather than prohibition

Abstract:Academic physicians and bioethicists are increasingly voicing objections to "drug rep" detailing. Leaders in academic medical centers are considering proposals to ban the small gifts of detailing within their walls. Such bans would be a mistake, as the small gifts are unlikely to act as bribes and do not create unacceptable conflicts of interest for physicians. Drug rep detailing does influence physician behavior, but this influence has not been shown to be harmful. Calls for a ban are premised on empirical evidence for harm that is inconclusive at best, and emerging literature in economics suggests that detailing may well be socially beneficial. A preponderance of harm over benefit is not, however, the primary source of the animus against detailing, which stems from moral considerations that are independent of its social consequences. However, pharmaceutical advertising, including detailing, is a morally legitimate aspect of the world of medical practice that we in academic medicine ought to be preparing our trainees to encounter and properly sift.     

Human cardiomyocyte progenitor cells: a short history of nearly everything

The high occurrence of cardiac disease in the Western world has driven clinicians and cardiovascular biologists to look for alternative strategies to treat patients. A challenging approach is the use of stem cells to repair the heart, in itself an inspiring thought. In the past 10 years, stem cells from different sources have been under intense investigation and, as a result, a multitude of studies have been published on the identification, isolation, and characterization, of cardiovascular progenitor cells and repair in different animal models. However, relatively few cardiovascular progenitor populations have been identified in human hearts, including, but not limited to, cardiosphere-derived cells, cKit+ human cardiac stem cells , Isl1+ cardiovascular progenitors, and, in our lab, cardiomyocyte progenitor cells (CMPCs). Here, we aim to provide a comprehensive summary of the past findings and present challenges for future therapeutic potential of CMPCs.