A MOSAIC of methods: Improving ortholog detection through integration of algorithmic diversity

Ortholog detection (OD) is a critical step for comparative genomic analysis of protein-coding sequences. In this paper, we begin with a comprehensive comparison of four popular, methodologically diverse OD methods: MultiParanoid, Blat, Multiz, and OMA. In head-to-head comparisons, these methods are shown to significantly outperform one another 12-30% of the time. This high complementarity motivates the presentation of the first tool for integrating methodologically diverse OD methods. We term this program MOSAIC, or Multiple Orthologous Sequence Analysis and Integration by Cluster optimization. Relative to component and competing methods, we demonstrate that MOSAIC more than quintuples the number of alignments for which all species are present, while simultaneously maintaining or improving functional-, phylogenetic-, and sequence identity-based measures of ortholog quality. Further, we demonstrate that this improvement in alignment quality yields 40-280% more confidently aligned sites. Combined, these factors translate to higher estimated levels of overall conservation, while at the same time allowing for the detection of up to 180% more positively selected sites. MOSAIC is available as python package. MOSAIC alignments, source code, and full documentation are available at http://pythonhosted.org/bio-MOSAIC

Robust forward simulations of recurrent hitchhiking

Evolutionary forces shape patterns of genetic diversity within populations and contribute to phenotypic variation. In particular, recurrent positive selection has attracted significant interest in both theoretical and empirical studies. However, most existing theoretical models of recurrent positive selection cannot easily incorporate realistic confounding effects such as interference between selected sites, arbitrary selection schemes, and complicated demographic processes. It is possible to quantify the effects of arbitrarily complex evolutionary models by performing forward population genetic simulations, but forward simulations can be computationally prohibitive for large population sizes ($> 10^5$). A common approach for overcoming these computational limitations is rescaling of the most computationally expensive parameters, especially population size. Here, we show that ad hoc approaches to parameter rescaling under the recurrent hitchhiking model do not always provide sufficiently accurate dynamics, potentially skewing patterns of diversity in simulated DNA sequences. We derive an extension of the recurrent hitchhiking model that is appropriate for strong selection in small population sizes, and use it to develop a method for parameter rescaling that provides the best possible computational performance for a given error tolerance. We perform a detailed theoretical analysis of the robustness of rescaling across the parameter space. Finally, we apply our rescaling algorithms to parameters that were previously inferred for Drosophila, and discuss practical considerations such as interference between selected sites

Diffusion Approximations for Demographic Inference: DaDi

Models of demographic history (population sizes, migration rates, and divergence times) inferred from genetic data complement archeology and serve as null models in genome scans for selection. Most current inference methods are computationally limited to considering simple models or non-recombining data. We introduce a method based on a diffusion approximation to the joint frequency spectrum of genetic variation between populations. Our implementation, DaDi, can model up to three interacting populations and scales well to genome-wide data. We have applied DaDi to human data from Africa, Europe, and East Asia, building the most complex statistically well-characterized model of human migration out of Africa to date

Continuous Theta Rhythm During Spatial Working Memory Task in Rodent Models of Streptozotocin-induced Type 2 Diabetes

Alzheimer’s disease is a neurodegenerative disorder altering memory loss thought to be due to neuropathological symptoms such as the buildup of beta amyloid plaques (Ab) and neurofibrillary tangles (NFT). The etiology of Alzheimer’s is still unknown; however, potential risk factors such as diabetes may lead to its development. The most common form of diabetes is type 2 diabetes known for persistent insulin resistance leading to a state of hyperglycemia. Insulin resistance has been shown to affect cognitive abilities such as learning, memory and also alters synaptic plasticity. Neural connections between the hippocampus (HC) and anterior cingulate cortex (ACC) are known to be very important for learning and memory and are highly plastic, making them an intriguing target that could be altered by hyperglycemia. We hypothesize that hyperglycemic rodents will exhibit spatial memory deficits that may be associated with cognitively linked interactions between the HC and ACC. Minimal doses of streptozotocin (STZ), which is toxic to insulin producing beta cells, were given for 9-10 weeks. Using a spatial working memory task known as delayed alternation we found significant differences between control and experimental rats in working memory accuracy. This task places strong working memory demands on subjects which may be compromised by a hyperglycemic state. We measured EEG recordings from the HC and ACC during task performance and found that hyperglycemic rats had nearly continuous theta rhythm during the 30-minute session. Control rats however, displayed normal transitions between theta and lower frequency delta. Neural connectivity may be altered due to a change in frequency activity between the HC and ACC due to diabetes which is a risk factor in the development of AD impairments. These results show that hyperglycemia leads to changes along the circuit critical for learning and memory

Reorganization of a government's engineering division to model civilian organization for success

textThe Directorate Public of Works Engineering Service Branch is responsible new designs, renovations of existing construction, and general supervision of new construction. Over the years (especially in the last two or three years), the Design Branch has been perceived as providing a low quality product. The quality can be directly related to personnel issues within the organization such as heavy workloads, low morale, lack of respect for management, and lack of leadership which is required to improve the quality of work. As a result of the evaluation of the current organizational structure and how it contributes to the personnel aspects of its staff I have recommended that the organization transitions from an operational structure to a matrix structure. I have furthermore, identifying the strengths of the recommended structure and how it will contribute to the improvement in the quality of the design. I have also identified weaknesses of the recommended structure and sought to identify solutions to minimize negative impacts on the organization. The roles and responsibilities are also identified in the recommended matrix organizational structure.Engineering Managemen

Population Genetics of Rare Variants and Complex Diseases

Identifying drivers of complex traits from the noisy signals of genetic variation obtained from high throughput genome sequencing technologies is a central challenge faced by human geneticists today. We hypothesize that the variants involved in complex diseases are likely to exhibit non-neutral evolutionary signatures. Uncovering the evolutionary history of all variants is therefore of intrinsic interest for complex disease research. However, doing so necessitates the simultaneous elucidation of the targets of natural selection and population-specific demographic history. Here we characterize the action of natural selection operating across complex disease categories, and use population genetic simulations to evaluate the expected patterns of genetic variation in large samples. We focus on populations that have experienced historical bottlenecks followed by explosive growth (consistent with most human populations), and describe the differences between evolutionarily deleterious mutations and those that are neutral. Genes associated with several complex disease categories exhibit stronger signatures of purifying selection than non-disease genes. In addition, loci identified through genome-wide association studies of complex traits also exhibit signatures consistent with being in regions recurrently targeted by purifying selection. Through simulations, we show that population bottlenecks and rapid growth enables deleterious rare variants to persist at low frequencies just as long as neutral variants, but low frequency and common variants tend to be much younger than neutral variants. This has resulted in a large proportion of modern-day rare alleles that have a deleterious effect on function, and that potentially contribute to disease susceptibility.Comment: 36 pages, 7 figure

Coping with climate change in the tourism industry: a review and agenda for future research

The two-way relationship between tourism and Climate Change has important economic and developmental implications for numerous regions worldwide. Purpose: The purpose of this paper is to present an overview of the existing literature on the relationship between tourism and climate change in order to establish the current state of corporate and institutional responses in the tourism industry and to set out an agenda for research. Methodology: As this is a literature review paper, a comprehensive review was undertaken of the management journals and related topics. Findings: The global or overall impact of tourism on climate has received little attention by researchers. In general, the majority of companies are still in a preliminary phase in terms of implementing adaptation and mitigation measures. There is a requirement to examine the determinants of these strategies in organisations, as well as their associated outcomes. There is a need to examine tourist preferences in terms of activities and destinations, the impacts of climate change, and whether and how this affects tourist-consumer decision making. Academic research has focused mostly on specific and individual solutions to address the impact of climate change on tourism. The analysis of the interplay of these measures and their possible synergies constitute an important topic for future research. Originality: The timeliness of the review is evident given the recent surge in popular debate on climate change, its effects on tourism and the appearance of a broad and disparate array of studies on this topic

Heavy and Light Quarks with Lattice Chiral Fermions

The feasibility of using lattice chiral fermions which are free of $O(a)$ errors for both the heavy and light quarks is examined. The fact that the effective quark propagators in these fermions have the same form as that in the continuum with the quark mass being only an additive parameter to a chirally symmetric antihermitian Dirac operator is highlighted. This implies that there is no distinction between the heavy and light quarks and no mass dependent tuning of the action or operators as long as the discretization error $O(m^2 a^2)$ is negligible. Using the overlap fermion, we find that the $O(m^2a^2)$ (and $O(ma^2)$) errors in the dispersion relations of the pseudoscalar and vector mesons and the renormalization of the axial-vector current and scalar density are small. This suggests that the applicable range of $ma$ may be extended to $\sim 0.56$ with only 5% error, which is a factor of $\sim 2.4$ larger than that of the improved Wilson action. We show that the generalized Gell-Mann-Oakes-Renner relation with unequal masses can be utilized to determine the finite $ma$ errors in the renormalization of the matrix elements for the heavy-light decay constants and semileptonic decay constants of the B/D meson.Comment: final version to appear in Int. Jou. Mod. Phys.